Family background and child development up to age 7

RESEARCH
Up to Age 7:
Family Background and Child Development
Up to Age 7 in the Avon Longitudinal Survey
of Parents and Children (ALSPAC)
CPMO Research Team
University of Bristol
Research Report RR808A

Research Report
No 808A
Up to Age 7:
Family Background and Child Development
Up to Age 7 in the Avon Longitudinal Survey
of Parents and Children (ALSPAC)
CPMO Research Team
University of Bristol
The views expressed in this report are the authors’ and do not necessarily reflect those of the Department for Education
and Skills.
© University of Bristol 2006
ISBN 978 1 84478 840 8

Up To 7:
Family Background and Child Development Up to
Age 7 in the Avon Longitudinal Survey of Parents
and Children (ALSPAC).
Prepared by CMPO Research Team, University of Bristol
We would like to thank the Department for Education and Skills for financial support on this project.
We are extremely grateful to all the mothers who took part and to the midwives for their cooperation
and help in recruitment. The whole ALSPAC Study Team comprises interviewers, computer
technicians, laboratory technicians, clerical workers, research scientists, volunteers and managers who
continue to make the study possible. The ALSPAC could not have been undertaken without the
financial support of the Medical Research Council, the Welcome Trust, UK government departments,
medical charities and others. The ALSPAC study is part of the WHO initiated European Longitudinal
Study of Pregnancy & Childhood. The CMPO research team on this project includes Simon Burgess,
Paul Gregg, Emma Hall, Sara Meadows, Stephen Proud, Carol Propper and Liz Washbrook. Usual
disclaimers apply.
Leverhulme Centre for Market and Public Organisation
University of Bristol
8 Woodland Rd.
Bristol BS8 1TN
e-mail – P.Gregg@bristol.ac.uk
Tel: 0117 928 9061
2

Executive Summary and Conclusions
The Research Methodology
We use the rich information in the ALSPAC data set to identify child outcomes at age 5 and
age 7, and to explore how these are influenced by measures of family background and
proximal, mediating, factors such as parenting behaviours and childcare arrangements. Details
of our precise methodology are given in section 3.2 Part 1 of this report. In summary, we begin
by examining the relationship between each of the groups of mediating variables and the two
child outcomes (cognitive and behavioural) at age 5. This allows us to exploit the rich data to
examine the effect of measures of each set of proximal factors in some depth, and to determine
which factors are significantly associated with outcomes. We then examine the
interrelationship between all seven sets of proximal variables and child outcomes, using the
measures of each set of proximal factors that have been shown to be significantly associated
with the outcomes of interest. In this examination, our focus is on the pathways by which
parental education and income affect child outcomes at school entry. Causality in this area is
obviously difficult to infer with complete confidence owing to the complexities of such
interrelationships. Nevertheless, we explore plausible routes (the proximal factors) through
which the distal factors (family background measures) might affect children’s development.
We focus on income and parental education but also explore other family characteristics and
their relationship with our proximal factors. These are age of mother at birth, numbers of
siblings, ethnicity and lone parenthood.
Having established the patterns of association at age 5 for cognitive and behavioural outcomes,
we then examine (in Part 2 of the report) the persistence of the picture through the first two
years of schooling. In this part, we examine only cognitive outcomes. We aim to assess
whether the first two years of education in school changes the picture of which are the key
influences on child development prior to school entry. In particular, we assess whether the
early learning deficits based on family background persist and the role played in these deficits
by the factors identified in Part 1 in this persistence. In addition to these factors, we also
examine the effect of the school attended by the child.
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The Outcome Measures Used
The data contains two school-based measures of cognitive development. These are the Entry
Assessment (EA) test taken at age 4 or 5 and the Key Stage 1 (KS1) assessment, administered
in Year 2 at age 6 or 7. Each test is composed of four sub-scores that capture ability in reading,
writing, mathematics and language skills (EA only) or spelling (KS1 only). The data also
contains an assessment of cognitive ability administered by the ALSPAC team to children at
the age of 7. Factor analysis was used to combine the sub-scores for each measure into one
overall score. Attrition and the fact that not all permissions to use tests taken in school have
been given to ALSPAC mean the sample size for the EA test score is around 5000. At age 7
the availability of the two available scores allows us to construct a composite score, which will
be more accurate than a single measure alone. This composite score covers some 7,500
children.
The measure of behavioural problems is derived from mother-reported data at age 4. As the
results are mother reported there is some question over the accuracy of reporting and whether it
may be influenced by the mothers mental (e.g. stress) and physical health. The measure
contains five components – scores relating to hyperactivity, emotional symptoms, conduct
problems, peer problems and a pro-social score (which is reversed as unlike for the other
measures a higher score is a positive outcome). The sample size for this measure is around
9500.
Each measure is standardised to have mean 100 and standard deviation 10. This enables easy
comparisons across the measures used. A score of plus or minus 1 on each measure therefore
represents a move of plus or minus one tenth of a standard deviation. This equates to roughly
moving plus or minus four percentage points from the median. On the EA test score we can
also translate this into months of development within a school year. Here then plus or minus
one point of the score equates to plus or minus 1 ½ months of child development. On the
behaviour score there is little age variation and so such a comparison between age and
behavioural development makes little sense. Full details of the ALSPAC cohort and the
information in the data set are given in Part 1 of this report. Part 2 gives further information on
the measures of child attainment at age 7.
5

Understanding the Findings
The approach of this research is to explore how the association between distal factors such as
family income and parental education impact on children’s early development. This is
undertaken in two steps, first we condition on other distal factors such as mothers age, family
structure. This enables us to suggest that the association of child outcomes and family income
does not stem from income per se but because it is also associated with teen pregnancy, larger
families etc. In the second step we introduce groupings of proximal influences; Parenting
Behaviour and the Home Environment, Maternal Employment, Childcare, Maternal
Health, Social Support and Background, Neighbourhood and Peer Groups. It is possible
through this approach to also look at other background factors, other than income or parental
educations and to explore how important the proximal influences are to child development (not
just to the achievement gaps across income or parental education groups). In the summary that
follows we define a modest effect equates to a n effect of up to 1/10 of a standard deviation, a
moderate effect to between 1/10 and 2/10 of a standard deviation and a Large effect to above
2/10 of a standard deviation. 1/10 of a standard deviation would move a child from the middle
of the distribution of attainment (the median) by just under 4 percentage points.
Summary of Findings up to age 5
Educational Development Up to Age 5
• Even by age 5 substantial variations in educational attainment are apparent across
children from different family backgrounds. Large early learning variations are
associated with parental education, family income, age of mother and numbers of
siblings and gender of the child. Children from the poorest fifth of families have
lower cognitive attainment than children from richer by nearly 7 percentage points
in the raw data (around 10 months behind) and less educated (no A-C grades
GCSEs or higher level qualifications) are 9 points or a year behind those from more
educated families. However, these raw results role many aspects of family
background together, for instance the lower income families tend also to be less
educated. Once we draw out the separate effects of education and income, those
from less educated families (no A-C grades or higher level qualifications) are 5
points behind those with degree educated mothers and those from the poorest fifth
of homes are just over 3 points behind those from the most affluent fifth. Boys also
6

have lower attainment than girls, those with younger mothers are behind those with
older mothers and those with more older siblings are also behind the first born
children compared to when they were aged 5.
• Parents’ teaching (e.g. teaching children a number of items such as shapes, colours
and numbers) and reading to children during the pre-school period are the largest
single influence on children’s early learning. After controlling for other influences
children who are rarely read to before school entry are 1.6 points behind and those
where the mothers rarely actively teach their children are 3.6 points behind.
However, differences in teaching and reading do not explain very much of the early
learning deficits of children from poorer and less educated families. For instance,
the gap between children with the highest and lowest educated groups of mothers
falls from 4.9 points to 4.4 points once parenting behaviour is included. That is,
parenting behaviours are the mediating influence for just 10% of the gap between
children with the highest and lowest educated groups of mothers. There is also no
evidence that better educated parents teach and read to young children more
effectively; they just do these things somewhat more often. There is evidence,
however, that teenage mothers engage in reading to and teaching their children less
often and these are key reasons why children of teenage mothers are underachieving
at age 5.
• Exposure to pre-school childcare is modestly beneficial to early learning but it is a
minor factor in explaining the early learning deficits observed. Full-time childcare
prior to school entry is no more beneficial than part-time but attending a pre-school
containing high achieving children is beneficial.
• Centre based care at or before age 2 is as beneficial to children’s learning as is other
paid care (e.g. child minders). Long hours of care (20 or more hours a week) up to
the age of 2 by unpaid carers, such as friends and relatives, is associated with lower
attainment, whilst father’s involvement in child care before age 2 is modestly
beneficial.
• The home environment - in terms of books and toys and the attainment of the peer
group attending the same pre-school setting – make a substantial contribution to the
early learning deficits of children from poorer and less educated families. These
proximal factors are strongly related to family income levels.
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• Mother’s mental and physical health and her own childhood experiences are not
major influences on children’s early leaning. Despite this, they explain around 10%
of the lower test scores of children from poorer and less well educated households.
This is because they are strongly related to income and parental education levels.
Behaviour at age 5
• Differences in raw behaviour scores across children from families with different
levels of income and education are relatively small compared to those observed in
cognitive development.
• Mother’s mental and physical health, especially stress, anxiety and self-esteem, and
low quality relationships between parents are strongly related to poor behavioural
outcomes. In turn these indicators of poor mental health and lack of belief that there
own actions make a difference, are strongly correlated with low income and low
educational attainment.
• Parental teaching and reading also have marked influences on later behavioural
outcomes (as for learning outcomes). But, in addition, parental behaviours
including weak early maternal bonding, smoking in pregnancy, talking to children
whilst engaged in other activities and the child watching 6+ hours of TV a week at
18 months are also associated with worse behaviour.
• Centre based care at or before age 2 is associated with worse behaviours relative to
parental carers or child minders. Long hours of care (20 or more hours a week) by
unpaid carers, such as friends and relatives are also associated with worse
behaviour.
• The differences in raw behaviour scores between the highest and lowest education
and income groups are modest in size and explained mainly by the correlations
between parenting and mother’s mental and physical health and income or
education. Parenting patterns are more important in driving the differences in
behavioural outcomes, between the most and least affluent children, than they are
for early educational attainment
8

Summary of findings age 5 to age 7
Persistence of Early Learning from Age 5 to 7
• Family Background. In general most dimensions of family background have slightly
weaker influences at age 7, after two years of schooling, than at age 5. This is most
marked for age of mother, low birth weight children and boys (as the gender gap
diminishes but far from disappears). It is fairly marginal, however, for income, parental
education and sibling numbers. This pattern of effects is not influenced by the
inclusion or exclusion of our mediating influences.
• Parenting patterns. Most effects (reading, activities, teaching and breast feeding)
remain highly persistent, that is they are still important at age 7. There is a weakening
of the impact early TV watching on a child’s cognitive development.
• The home learning environment and outings. There is evidence of a minor reduction
in the impact of the home learning environment on children’s attainment between ages
5 and 7. The toy score, having few toys in the home, becomes indistinguishable from
having no effect by age 7, whereas there was a significant relationship at age 5.
• Child care. The report covers usage, types and extent of care up to age 24 months plus
a more detailed study of child care exposure and limited measures of quality prior to
school entry at age 4. The reliance on friends and relatives for early care has
persistently adverse effects on attainment. All other early care arrangements appear
broadly indistinguishable from each other and have no significant impact at age 7.
Variations in the impact of exposure to different early learning environments
immediately prior to school entry at age 4, all disappear after two years of schooling.
Children who had attended only parent-organised play groups were behind children
who had attended nursery schools at age 5, but show no substantive difference in
attainment by age 7.
• Maternal physical and mental health and social support networks. These factors
had little impact on children’s cognitive development at age 5, but the importance of
the mother’s locus of control score, the extent to which the mother feels her choices and
actions can affect the family’s circumstances, remains persistent through the early
school years.
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Implications for future research
This research makes a substantive contribution to the understanding of the origins of early
learning differences in children and their persistence on entry into school. As these children
age, ALSPAC will continue to offer a unique method of tracking how early learning and
behaviour are transmitted through childhood and into adulthood and to assess how other
influences come forward to mitigate or accentuate early differences. The data will also be able
to track whether recent government initiatives can alter this process, for instance, the Literacy
Hour programme which these children will have experienced after age 7 or programmes such
as the Community Trust Fund of anti-social behaviour.
Family background is observed to be associated with major differences in attainment and
behaviour on school entry. These family background influences cross the dimensions of
parental education, family income, age of mother at birth and numbers of siblings within the
family. The early learning deficits of those from poorer and less educated families remain
largely intact through the first two years of schooling but they are not continuing to worsen.
These early learning deficits substantially stem from the association between the measures of
family background and a set of proximal influences drawn from the data. The key proximal
influences differ between behaviour and early learning outcomes. For both income and parental
education, the mediating influence which is most important for early behaviour outcomes is the
mother’s mental and physical health. This includes anxiety, stress and a weak locus of control.
Disciplining behaviour is also important. For early learning, the physical home leaning
environment (books and toys), parental teaching and reading to children and the make up of
peer groups in pre-school settings are key proximal influences.
Through the first two years of schooling, the pattern of early learning across children remains
broadly intact, in that most of the drivers of early learning differences before entry to school
remain undiminished after two years of school. The deficits associated with having a teenage
mother weaken and those from ethnic minorities are doing better than Whites on average by
age 7 (we do not have large enough samples to examine specific ethnic groups). The evidence
that pre-school setting influences child development on school entry, including evidence that
the pre-school peer group matters (which other children attend the same pre-school) show clear
10

signs of diminishing through the first two years of schooling. A caveat is that this study does
not have the evidence of quality in the pre-school setting available in other studies.
11

Part 1
Early Development Variations upon entry into school
1. Introduction 13
2. Measures of Child Attainment and Correlations with
Background Characteristics 15
3. Parenting Behaviour and the Home Environment 23
4. Maternal Employment 51
5. Childcare 63
6. Maternal Health, Social Support and Background 73
7. Neighbourhood and Peer Groups 89
8. Combined Analysis 97
9. Conclusions 129
Part 2
The Persistence of Early Learning Variations Through the
First Two Years of Schooling
10. Introduction 135
11. Data & Measures of Child Outcomes 137
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12. Background Characteristics 145
13. Parenting Behaviours & Attainment Up to 7 149
14. Outings & the Home Learning Environment &
Attainment Up to 7 151
15. Pre-school Childcare & Attainment Up to 7 153
16. Mother’s Childhood & Family Background &
Attainment Up to 7 155
17. Mothers Health, Social Networks and Family Conflicts
& Attainment Up to 7 157
18. Neighbourhood and Peer Groups & Attainment Up to
7 158
19. Overview of Family Background & Child
Development on Entry to School 161
20. Conclusions 169
References 177
Appendix 1. Variable Definitions 183
Appendix 2. Parenting Figures 219
Appendix 3. Parenting Interaction Tables 223
Appendix 4. Detailed tables of Results for Part II
including School Fixed Effects 232
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1. Introduction
This report draws together the research undertaken at the Leverhulme Centre for Market and
Public Organisation at the University of Bristol for the Department for Education and Skills on
children’s cognitive development and behaviour up to entry into school. This report has two
parts – Part 1 examines two measures of attainment up to school entry at age 4 to 5, one
cognitive and one behavioural. Part 2 presents a complementary analysis of the persistence of
variations in early learning during the first two years of school. The study uses the rich data
from the Avon Longitudinal Study of Parents and Children (ALSPAC).
Part 1 examines two measures of attainment, one cognitive and one behavioural. It focuses on
seven main sets of proximal factors, which may mediate between family background and these
outcomes. These are:
• Parenting patterns - covering reading, activities, teaching, etc.;
• The home learning environment and outings;
• Maternal employment from the birth to when the child is aged 47 months;
• Child Care usage covering types and extent of care up to 30 months and more detailed
study of child care exposure and limited measures of quality prior to school entry at age 4;
• Maternal physical and mental health, especially depression, domestic violence and intrafamily
conflict;
• Mother’s childhood experiences; and
• The neighbourhood of residence and peer groups.
We also focus on the role of family income and the relationship between income and
expenditure on children’s activities, childcare etc. in the transmission of family background
into child attainment. We allow this, in turn, to operate through the mechanisms described
above. Likewise we explore the role of parental education on children’s outcomes and the roles
of the factors above as mediating influences.
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2. Measures of Child Attainment and Correlations with
Background Characteristics.
The Avon Longitudinal Study of Parents and Children (ALSPAC) is a cohort study of around
13 000 children born in the Avon area of the UK in 1991 and 1992. Hence the survey is after
the bulk of the major expansion of early return to work by mothers that occurred in the midlate
1980s (see Gregg et al. 2003) but before the guaranteed half day places at pre-school for
four and most recently 3 year olds. Mothers complete up to three surveys a year, one relating to
the characteristics of herself and the household in general and two relating to the child 1 . In
addition, mothers answered four questionnaires during their pregnancies. The ALSPAC survey
also contains data from sources other than self-completion questionnaires. The ALSPAC team
have run a number of clinics for children from the age of seven. Here the child attends an
assessment centre (with a parent or guardian) run by ALSPAC at which tests are undertaken to
assess various aspects of the children’s development. Records from schools can also be
matched, with a parent’s permission, to the individual children, so data is available on schoolbased
assessments at ages 4 to 5 and again for ages 6 to 7.
2.1 Cognitive attainment
The two school-based measures of cognitive development available in ALSPAC are the Entry
Assessment (EA) test taken at age 4 or 5 and the Key Stage 1 (KS1) assessment, which is
administered in Year 2 at age 6 or 7. Each test is composed of four subscores that capture
ability in reading, writing, mathematics and language skills (EA only) or spelling (KS1 only).
Our third assessment of cognitive ability was administered, by the ALSPAC team, to children
at the age of 7. This ALSPAC literacy score is again composed of a number of subscores, in
this case capturing skills in reading, spelling and the manipulation of words. This ALSPAC test
was administered with other child assessment under a heading of Focus at 7. From here on we
describe the ALSPAC test as the Focus at 7 test.
To combine the subscores for each measure into one overall score we used factor analysis. This
method allows the data to dictate the relative weights attached to each component and so to
distil the maximum possible information into a single measure. Each of the three resulting
1 The mother’s partner also received annual questionnaires but the response here is patchy.
16

scores were then normalised to have a mean of 100 and a standard deviation of 10. As is
inevitable in a survey of the scale of ALSPAC, attrition results in smaller sample sizes for the
later assessments of child development. So by age 5 there were around 9500 usable cases. In
addition to this problem, parents were required to give written permission for the release of the
school-based test results. The sample sizes for the Entry Assessment and Key Stage 1 scores
are therefore substantially smaller than for the other measures. Some 6030 children (just under
two thirds) have permissions for matching of school results. Here we focus on the attainment
measures at 4 or 5. The EA score was not then a national test and so those schools not
operating this test, mainly outside the Avon area, do not have these scores. These restrictions
on data mean that our working sample on the EA test scores is just 4,607. The data available at
age 7 is far less restrictive.
The small sample sizes raise the question of whether there is major variation in the
characteristics of the population reporting an EA score and those that don’t as a result of
attrition and giving of permission to match to the ALSPAC data. We investigated this issue for
a range of observable characteristics such as household income, mother’s age and educational
attainment, etc and concluded that there is little variation in the composition of each sample.
The only clear sample composition difference is an under-representation of lone parents in the
ALSPAC sample. This is substantive among never partnered lone parents and those becoming
lone parents within the first year of so of the child’s life. Hence there appears to be no
substantive attrition bias in the sample composition as measured on observable characteristics
for couple families but there may well be unobservable differences. However, there are clearly
too few lone parents and especially never married lone parents and so our results for lone
parents need to interpreted with caution. We have chosen not to re-weight the data to raise the
size of lone parent population, as those remaining may be unrepresentative.
As a guide to interpreting the size of our estimates, assuming a normal distribution an
increment of 1 point (i.e. a tenth of a standard deviation) results in a shift from the median to
the 54 th percentile, while an increment of 5 points (or half a standard deviation) results in a
shift from the median to the 69 th percentile. Table 2.1 shows the pairwise correlations between
the EA score, and two other measures of cognitive attainment – the KS1 score, and the Focus
at 7 test, an ALSPAC administered literacy score taken at 7 years.
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Table 2.1: Sample sizes and correlations between child outcome scores
Entry
Assessment
Key Stage
One
Focus at 7
Behaviour at
age 4
Behaviour at
age 7
Entry
Assessment
1.0000
Key Stage
One
0.5515 1.0000
Focus at 7
0.4395 0.8381 1.0000
Behaviour at
age 4
-0.1906 -0.1906 -0.1323 1.0000
Behaviour at age
7
-0.2805 -0.3510 -0.2674 0.2535 1.0000
The EA test is moderately strongly correlated with test scores at age 6 or 7. In particular there
is a very high correlation with the KS1 score, which is also a school-based assessment. The
school based KS1 and the Focus at 7 literacy test have a very high correlation of 0.84, which
suggests these can be considered as two alternative estimates of cognitive attainment with
some measurement error. Hence the EA test is a reasonably strong predictor of later attainment
but there are clearly substantial differences between EA and the ALSPAC literacy and KS1
tests unlikely to be accounted for by the time gap of the tests, which is only around two years.
This suggests that the EA test seems to contain far more measurement error than the later tests.
This may reflect far greater teacher discretion in scoring children than in the national KS1 tests
and the clinic based assessment, Focus at 7. There is evidence in the data of schools scoring
pupils consistently higher or lower in the EA tests than in the KS1 tests. As the KS1 and Focus
at 7 scores match well, this suggests strongly that there are systematic reporting differences at
school level in the EA scores. Such reporting errors will not bias the results presented unless
they are systematically related to pupil characteristics. This is explored more in the second
companion report that compares results from the age 5 and age 7 tests.
2.2 Behavioural attainment at 5
Our measure of behavioural problems is derived from mother-reported data at age 4. This
behaviour measure was undertaken through postal questionnaire sent to the mother and has a
much larger sample size of 9416. As the reports are mother reported there is some question
over the accuracy of reporting and whether it may be influenced by the mothers mental (e.g.
stress) and physical health. The measure contains five components – scores relating to
hyperactivity, emotional symptoms, conduct problems, peer problems and a pro-social score
(which is reversed as a score is positive unlike for the other behavioural measures). The
behavioural problems measure is the opposite sign to the cognitive measures as higher scores
18

indicate more behavioural problems. That this early measure of behaviour is mother reported
might lead to biases or inaccuracies in the information reported. There is also a later measure
of behaviour reported by teachers at age 7. This is available for a much restricted sub-sample
of around 3,300 cases. As shown in Table 2.1 the correlation between these two measures is
quite low and also it is less well correlated with the attainment measures. So it would appear
that there is probably a lot of reporting error. We explore whether this leads to systematic
biases by exploring the relationships between the age 5 measure and behaviour measured at 7
by teachers, on a common sample. The results are fairly similar for most of the variables
considered in our analysis (although the smaller sample often leads to statistically insignificant
estimates). However, the results for the mother’s self-esteem score differ significantly and so
some caution about this particular measure needs to be exercised.
2.3 The effect of background controls
Table 2.2 reports a basic regression showing the partially conditional relationship between a set
of background factors and the EA test scores. These background controls are our base equation
to which the other sets of factors examined in this report are added sequentially. The
background controls are parental education, lone parent status, mother’s age, ethnicity and
gender of the child, birth weight and numbers of siblings, month and year of the birth (the
coefficients on the last 2 are not reported in the table). In this Table and through out the report
we will use ***, **, and * to indicate significance at the 1%, 5% and 10% levels respectively.
Table 2.2: Estimates of the effect of household demographic characteristics on Entry
Assessment scores
Without Income
With Income
Log of household income - 2.149***
Financial difficulties before birth (base = no)
Yes
Mother’s highest qualification (base = vocational/O-level)
CSE/none
A-level
Degree
Partner’s highest qualification (base = vocational/O-level)
CSE/none
A-level
Degree
(0.376)
- -0.247
(0.418)
-2.150*** -1.966***
(0.398) (0.398)
1.278*** 1.057***
(0.320) (0.321)
3.314*** 2.928***
(0.484) (0.487)
-1.657*** -1.460***
(0.373) (0.374)
0.560* 0.459
(0.331) (0.331)
2.546*** 2.176***
(0.449) (0.452)
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Table 2.2: Estimates of the effect of household demographic characteristics on Entry
Assessment scores (continued)
Lone parent status (base = never lone parent)
Intermittently, with partner at 47 months
Intermittently, no partner at 47 months
Since birth
Mother’s age at birth (base = 25-29)
1
Older siblings (base = none)
1
2
-0.021 0.740
(0.829) (0.837)
-1.003 0.425
(0.637) (0.681)
-1.507 0.111
(1.273) (1.299)
-4.071*** -3.536***
(0.978) (0.979)
-0.989** -0.761*
(1) (2)
(0.388) (0.389)
0.638** 0.548*
(0.304) (0.304)
1.083** 0.994**
(0.441) (0.440)
-2.085*** -1.966***
(0.684) (0.683)
3.523*** 3.488***
(0.249) (0.249)
-2.749*** -2.610***
(0.669) (0.667)
-0.826*** -0.771***
(0.261) (0.260)
-0.373 -0.369
(0.552) (0.551)
-0.181 -0.119
(0.313) (0.313)
-2.153*** -2.045***
(0.759) (0.756)
-1.477*** -1.396***
(0.328) (0.328)
-3.063*** -2.974***
(0.438) (0.437)
3+
-4.827*** -4.660***
(0.648) (0.648)
Partner’s employment status at 47 months (base = in work)
Not in work -1.132** -0.385
(0.533) (0.546)
Adj R2 0.2381 0.2429
1. The regression also includes controls for the age of the child in months at assessment and cohort year.
2. Each measure of cognitive development is normalised to mean 100, standard deviation 10.
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The impact of teen mothers is perhaps the most striking result in this table, along with the
impact of large numbers of siblings. To assess the magnitude of the coefficients, the dependent
variable has mean 100 and standard deviation 10. So the coefficient on teen motherhood in
Table 2.2 is –4.07, so this represents 0.41 of a standard deviation. The average position of
those children with teen mothers, conditional on other factors, is the approximately the 34 th
percentile (16 percentile points below the sample mean). This is comparing a teen mother to
one aged 25-29 at birth. Compared with an older mother, 35+, the gap is larger at 5.2 points or
over half a standard deviation. As well as teen mothers, there are large differences in
attainment associated with mother’s education and having a large number (3+) of older
siblings. Very low birth weight (in lowest 5% of the weight distribution), being a boy and
having a less well educated father (relative to degree educated) are all associated with
substantial attainment deficits. Lone parenthood is not associated with negative outcomes at
age 4/5 once other background characteristics are conditioned on.
The second column introduces family income as an additional regressor. Despite the richness
of the ALSPAC data in some areas, information on the finances of the household is quite
limited. We have no measure of household income prior to 33 months and no data on
individual earnings whatsoever. We cannot, therefore, directly assess the contribution of the
mother’s earnings to the household on child outcomes. Our best available measure for
capturing the financial circumstances of the household is the average of net household income
at 33 and 47 months, expressed in June 1995 prices 2 . Adding in income already gives some
sense of how the other background factors are jointly correlated with attainment and family
income. Most of the other background factors are less powerful predictors of attainment once
family income is conditioned on but the largest shifts are for lone parents, father not working
and teen motherhood, although the latter is still a very strong predictor.
This process is now repeated for the behaviour measure. We predict the behaviour variation
less well (the R 2 are lower), in part because there is no age-related variation in the behavioural
measure. Note that the scale of the behaviour score is in the reverse direction to the EA score
so that a higher score represents more behavioural problems. Hence we would expect most
coefficients to have the opposite sign than for the cognitive measure.
2 Income data from the ALSPAC data is banded. We imputed a median value for each band using data from the
Family Expenditure Survey. These values were then expressed in real terms and averaged to give a total income
figure.
21

Table 2.3 then examines the impact of these background controls on behaviour. Parental
education and large families are much less strongly correlated with behavioural outcomes but
teen mothers and boys are still associated with substantial deficits. Children of lone parents are
portraying behaviour consistent with higher scores. Overall the behaviour data is much less
predicted by these background demographic characteristics. The adjusted R 2 is just 5%
whereas that for educational attainment, excluding for the contribution from age adjustment, is
around 14%.
Table 2.3: Estimates of the effect of household demographic characteristics on
Behavioural scores
(1) (2)
Log of household income - -1.447***
Financial difficulties pre birth (base = no)
Yes
Mother’s highest qualification (base = vocational/O-level)
CSE/none
A-level
Degree
Partner’s highest qualification (base = vocational/O-level)
CSE/none
A-level
Degree
Lone parent status (base = never lone parent)
Intermittently, with partner at 47 months
Intermittently, no partner at 47 months
Since birth
Mother’s age at birth (base = 25-29)

Table 2.3: Estimates of the effect of household demographic characteristics on
Behavioural scores (continued)
Ethnicity (base = white)
Non-white
0.694 0.454
Gender (base = male)
Female
Birth weight (base = above median)
Very low
Low
Special care unit at birth (base = no)
Yes
Younger siblings by 47 months (base = none)
1
> 1
Older siblings (base = none)
1
2
(0.542) (0.540)
-2.510*** -2.498***
(0.202) (0.201)
0.870 0.733
(0.571) (0.569)
0.534** 0.510**
(1) (2)
(0.212) (0.211)
0.533 0.537
(0.473) (0.471)
0.672*** 0.661***
(0.240) (0.238)
0.798 0.635
(0.563) (0.561)
1.275*** 1.111***
(0.253) (0.252)
0.795** 0.618*
(0.333) (0.332)
3+
1.065** 0.763
(0.490) (0.488)
Partner’s employment status at 47 months (base = in work)
Not in work 1.904*** 1.151***
(0.377) (0.392)
Adj R2 0.0525 0.0618
Notes
1. Each measure of cognitive development is normalised to mean 100, standard deviation 10.
2. ***, **, and * indicate significance at the 1%, 5% and 10% levels respectively.
The strongest effects observed are associated with teen mothers and gender of the child.
Mother’s education and lone parenthood are also reasonably strongly correlated with mother
reported behavioural problems of the child. Family income, introduced in column 2, and
whether the mother reported financial difficulties pre-birth are both strongly related to
children’s reported behavioural problems. Again the estimated relationship between teen
motherhood and lone parenthood and the child outcome is substantially reduced once family
income is conditioned on, although teen motherhood retains a strong conditional correlation.
23

3. Parenting Behaviour and Home Environment
This first substantive section looks at the first two groupings of proximal factors under
consideration. We start with differences in parenting behaviour across families and variations
in the home environment as these are closely related. We correlate available measures with
child outcomes at age 5, conditioning on the background factors presented above. The
variables cover two of our seven groupings; those variables which represent a direct parenting
behaviour, such as teaching, reading or how often the mother talks to the child whilst occupied
with other things, and those characteristics of the child’s home learning environment which
reflect more than just parental time or attention. In this latter group we include toys and book
acquisition, trips out and housing conditions.
3.1 Relevant Literature
From very early in their lives, children differ in their cognitive development and their
behaviour. These differences may be highly stable throughout their childhoods and contribute
to the different outcomes of their formal education and to their risk of social exclusion (e.g.
Jencks et al 1972, Hills, Le Grand and Piachaud 2002). Psychological and social theories
about the sources of these differences appeal to multiple different influences, some located in
the child, some in the immediate physical environment, some in the immediate social
experience, some in the social and cultural institutions of children's wider worlds
(Bronfenbrenner 1979, Bronfenbrenner and Morris 1998). The possible distal factors that have
been suggested range from genes to environmental pollution to public policy; the suggested
proximal factors for preschool development centre on children's experiences in their families
and in family-like settings. There is extensive evidence (Bloom 1998, Campbell 1995, David
et al 2003, Luthar 1999, Meadows 1993, 1996) from observation-based studies of small
samples (e.g. Dunn, Gallaway and Richards 1994, Wells 1985), from larger samples in the US
(e.g. Bradley et al 1989, NICHD 2000, 2002) and from both large and small intervention
studies (e.g. Ramey and Ramey 1998) of correlations between parent behaviour and child
characteristics which suggest that proximal variables such as quantity and quality of parentchild
interaction in the preschool years may be causally associated with better cognitive
development and fewer behaviour problems at entry to school. Furthermore they suggest that
this causal link may be one of the mechanisms for the differences in children's attainment and
24

adjustment associated with distal variables such as social class, family structure, and parental
employment, or with genetic/biological influences.
However, the evidence is not sufficient to confirm this inference. Many of the studies that
make up the evidence base have mostly focused on simple analyses of one input variable and
one output measure, consigning other variables to error. Other studies have used composite
independent variables such as attendance at a Head Start programme and have not been able to
provide information on which parts of the experience have been crucial. Additionally, some
studies have used small and possibly unrepresentative samples. Furthermore, it is not
unproblematic to extrapolate sensibly from one society to another (Rogoff et al 2003).
Correlations and effect sizes are typically of only moderate size, thus although it was
appropriate initially to use such strategies to simplify otherwise intractable problems, and they
have led to interesting results, the studies have been open to criticism (e.g. Scarr 1992) for
failure to separate confounded genetic, environmental and interaction-based effects; failure to
compare the influence of parents and of other carers, including out-of-home care, or to
acknowledge the effect of children on parents; failure to identify exactly which parenting
behaviours are affecting which child behaviours; and failure to compare different causes within
the same sample.
The literature on the role of children’s experience in their families on their cognitive
development and their behaviour involves two main conceptual levels. The first involves more
or less permanent characteristics of family background, such as adults’ social class, education
level or intelligence, or family structure, which are associated with different outcomes for the
child. The second looks at activities (and attitudes) of parents (and children’s other carers),
which make them, moment by moment, more or less effective supporters or inducers of their
children’s learning.
Family background and children’s cognitive development
There has been evidence for at least the last century that cognition or, more specifically,
educational achievement, is associated with family background. From at least Galton’s
‘hereditary genius’ onwards, children with more middle-class backgrounds or more educated
parents do better throughout their educational careers, staying in education longer and having
higher achievement at most stages. They also tend to do somewhat better on IQ tests (though
not during infancy (Slater 1995)), in particular contributing relatively few cases to the
25

population of marginally subnormal scorers, and to a lesser degree they also tend to do better
on Piagetian tests. The socio-economic status (SES) of the family is still a fairly good predictor
of children’s academic achievement (Blake 1989, Bornstein and Bradley 2003, Bradley and
Corwyn 2002, Duncan, Brooks-Gunn and Klebanov 1994, Duyme, Dumaret and Tomkiewicz
1999, Hart and Risley 1995, Hoff 2003). Social class differences like these have persisted
despite the existence of a general rise in achievement and intelligence and of mobility between
social classes between generations, and despite the belief in meritocracy and egalitarianism
which characterizes countries like Britain and the United States.
But social class, or socioeconomic status (SES), is not of itself a causal variable. It is an index
based on the occupation of the head of the family, and thus a guide to the family’s income, the
parents’ education, and, less directly, to a wider set of social circumstances. The same point
applies to research on family structure. Social class or family structure research sometimes
focuses on comparing people from different categories (with different ‘social addresses’
(Bronfenbrenner 1979, 1986, Bronfenbrenner et al 1996, 1998, 2000) rather than on the
intervening processes which might explain how the address label comes to be associated with
different developmental outcomes. The results of such research are often open to several
interpretations as they do little to clarify causal pathways. It is not entirely clear how a variable
like socio-economic status affects children’s cognitive achievement, what sort of explanatory
model is appropriate. The correlation between SES and intelligence or educational
achievement might reflect differences in innate ‘intelligence’ (Eysenck 1971): however
adoption studies show that the average level of attainment of adopted children resembles that
of their adoptive family rather than that of their biological parents (Meadows 2005), studies of
the different SES risk of severe and mild mental retardation (e.g. Broman et al 1987) show
different causes and different involvement of family backgrounds, and what promotes high
cognitive attainment in children from low SES backgrounds appears to be family interaction
not genes (Kim-Cohen, Moffitt, Caspi and Taylor 2004). There might be SES differences in
children’s behaviour which differentially facilitates good performance on IQ tests and in
school; there might be different reactions by schools and other tests to children differing in
SES. There might be different opportunities available to the different social classes (for
example better-funded schools in wealthier areas), even in a social system which believes it is
meritocratic and open to all those who are talented. There might be differences in health and
nutrition. These possibilities are by no means mutually exclusive: indeed the different
disadvantages of poverty tend to co-occur (Evans 2004.) Whichever cause may apply, we
26

surely need to look closely at the moment by moment way the effect is brought about. Work
which looks at more specific variables than family background is needed if we are to address
the question of why there is variation within classes and other overtly similar backgrounds, and
to elucidate causal chains.
If we are to look for explanations of differences in children’s cognitive development and
behaviour in their family interaction rather than their family background, the key variables will
include behaviour that is formally or informally educational and also behaviour which supports
positive emotional and social development (Meadows 1996, 2005). Among the important
variables will be
• the family’s parent-child language use and parents’ efforts to support their children’s
cognition (e.g. Tizard and Hughes 1984, Wells 1985, Rice 1989, Snow et al. 1991,
Crain-Thoreson and Dale 1992, Lieven, Pine and Dresner Barnes 1992, Bates, Dale and
Thal 1995, Hart and Risley 1995, Ochs and Schieffelin 1995, Snow 1995, Meadows
1996 and 2005, Bloom 1998, Huttenlocher 1998, Evans, Maxwell & Hart 1999, Hoff
and Naigles 2002, Senechal and LeFevre 2002, Williams and Rask 2003, Haney and
Hill 2004, Johnson-Glenberg and Chapman 2004).
• family cohesiveness, communication and shared meaning, which may be making
important contributions to children doing better than expected cognitively (e.g.
Eisenberg and Mussen 1989, Heath 1983, Kaye 1984, Meins 1997, 1998, Hubbs-Tait et
al 2002, Howe and Rinaldi 2004, Petrill and Deater-Deckard 2004,Thompson 2004)
• emotional risk and malaise, especially in so far as it impedes facilitative parent-child
interaction (Cicchetti 2002, Hammen 2003, Ackerman, Brown and Izard (2004a,
2004b, Cummings, Keller and Davies 2005)
After decades of controversy, there is now strong evidence of the effectiveness of special
educational programmes for children from disadvantaged families (e.g. Barnett 1995,
Burchinal et al 1997, Campbell et al 2001, Campbell and Ramey 1995, Campbell et al 2002,
Fan and Chen 2001, Mosteller 1995, Ramey and Ramey 1998, Reynolds 1994, Reynolds et al
1996, Reynolds and Temple 1998, Yoshikawa 1995, Reynolds, Ou and Topitzee 2004). Two
particularly well-documented projects, the Abecedarian project (Ramey and Ramey 1998) and
the Chicago Child-Parent Centers (Reynolds, Ou and Topitzes 2004) show what the causal
path between intervention and outcome may be. There are three main possibilities: that the
27

intervention improves children’s cognitive abilities as measured in standardised tests and these
improvements initiate a sequence of improved performance on school tasks and tests which
culminate in better school achievement; that the intervention makes families more likely to
support the child’s cognitive development more effectively; that participation in the
programme makes the families seek out better schools for their children and use the schools
more effectively. The evidence from the major studies is that all these things happen.
Children’s cognition was boosted by their preschool experience and this plus continuing family
support and school support through the later part of their education lead to higher rates of
school completion. Program participation enhanced these little children’s cognition and
language and their readiness to cope with the demands of formal schooling; this led to higher
ratings from teachers, less likelihood of being retained in grade to repeat a year, and more
completion of high school. Programme involvement of mothers had a positive effect on both
child outcomes and mothers’ well-being. School support and family support as they grew older
were the major predictors of children avoiding involvement in crime and delinquency. The
quality of schooling after the intervention was crucial for the eventual outcome; the early
intervention is not so much an ‘inoculation’ that can prevent failure all by itself so much as an
early advantage which can be built on to lead, eventually, to success, if school and family
continue to support the child.
Parent activities which ‘encourage development’, in joint play or through providing
appropriate and varied materials and experiences, are relevant to cognitive achievement. The
core is warm participation in socially and intellectually stimulating interactions, with adults
showing reciprocity with children, being responsive to them, and providing emotional support
but also providing some structured, directed experiences with encouragement and praise
(Meins 1997, 1998, Hubbs-Tait et al 2002, Petrill and Deater-Deckard 2004, Meadows 2005).
Possibly the child participant in such interaction derives an enhanced sense of being competent
and effective as well as receiving good cognitive opportunities and helpful interpretations and
support from the adult; it is worth noting that maternal intrusiveness, being very directive and
controlling, is associated with the child doing less well. There are quite consistent positive
correlations between the amount of adult–child interaction of this sort and the child’s cognitive
development, which remain even when maternal IQ and educational level are partialled out in
an attempt to control for passive genotype–environment interaction effects (Gottfried 1984,
Luster and Dubow 1992) and when other demographic variables are controlled (Gregg,
Washbrook and Meadows 2004). It is not entirely clear which components of the parent’s
28

ehaviour have direct effects, and which are mediated by other factors, and the best balance of
behaviour may very from task to task and age to age (Hubbs-Tait et al 2002), but it does seem
to be the case that if the parent-child interaction is characterized by positive emotional support,
high cognitive stimulation and low parental intrusiveness the child is likely to do well in terms
of both cognition and confidence, while the reverse of this pattern is associated with the child
doing badly. Thompson (2004) sees parenting and the environment of the home as the basis of
individuals’ approaches to learning challenges and achievement. The relevant literature for key
proximal influences is discussed in more detail in their relevant sections.
The ALSPAC database offers an opportunity to look at the relationship between parenting
behaviours and child outcomes beyond the parent input-child output model. Its extensive data
on household demographic characteristics and parent characteristics allow us to examine the
effect of parenting behaviour in the context of other more distal variables that would be
expected to affect the child's development. For example, parents' educational level has long
been known to be a predictor of children's educational outcomes but, if the former is causing
the latter, the mechanism could be through genetic transmission of aptitudes essential for
educational achievement, or through the provision of better or worse educational opportunities
in the school years, or through differences in parents' behaviour with children in the home.
The ALSPAC data offers a similar advantage relating to child characteristics, which may have
a direct effect on development or an indirect one through their evoking of different behaviour
from the parent. For example, the gender difference in educational achievement in the early
stages of schooling could reflect some inherent earlier maturity of girls or differences in their
earlier interaction with significant adults. The presence in the database of multiple measures of
child development allows for examination of simultaneous effects; for example whether the
effects of a particular parenting behaviour are as positive for behaviour as for cognition, and
whether the timing of an experience is important. These issues are theoretically important, but
also are especially important for policy and interventions as effects may be bigger for some
subgroups of children than for others, or may have costs as well as benefits, or may need to be
carefully timed.
3.2 Methodology
Our aim in this section is to explore the relationship between inherent parenting behaviours and
the home environment and child outcomes, both cognitive and behavioural, at age 4 to 5. Our
primary focus here is to ask the questions:
29

• What are the observed relationships between different types of parenting behaviours
and child outcomes, conditional on just the limited range of background controls
introduced above?
• Which parenting behaviours matter most for which child outcomes?
• Are certain sub-populations more effective when employing specific types of
parenting behaviours?
The aim is to identify a parsimonious number of parenting variables, all of which have
independent and significant effects on children’s development. This group of variables can
then be used in the analysis of the effects of other factors as an effective control for the child’s
‘home environment’. For example, we can then explore the relationships between family
income, childcare arrangements and parenting and the relative importance of each.
Our empirical strategy is to first estimate K regressions of the form:
C = β +
i
k
α1 + α
2
X
i
+
k
Pi
ui
k = 1,…, K (1)
where C i is the outcome measure for child i, X i is a vector of controls capturing the basic
k
demographics of the household, and P i is a measure of the kth parenting behaviour
experienced by child i. Hence our first step is to explore the conditional correlations of each
parenting measure with the child outcome separately. Although not raw correlations, the β
coefficients show the relationships between parenting and outcomes without taking account of
many other factors that may have a causal influence on both – for example the mother’s mental
health and household income. The main purpose of this is to explore whether there is any
evidence at all that the behaviour captured by P k has any impact on child outcomes. If not, then
that measure can be dropped from all further analyses.
Rather than using continuous measures of parenting in our estimation, we divide each measure
into discrete categories and create dummy variables to indicate into which category the parent
falls. This is because
• It allows us to create a separate category for missing observations, rather than imputing
values
30

• It allows for non-linearities in the relationship between parenting behaviours and child
outcomes. For instance, not reading to a child at all may be far more important than the
difference between reading 4 and 5 times a week.
• The raw values of the parenting scores vary across measures and are difficult to interpret.
The use of discrete categories allows comparisons based only on the relative positions of
households in the distribution (for example, we can examine the effect of a move from the
lowest to the highest quartile).
In determining the category boundaries, the aim is to minimise the number of categories
without losing explanatory power, and also to maintain the same boundaries for use in both the
EA and Behavioural regressions. To do this, we first introduce the variable into the regressions
in a highly disaggregated form (for example in deciles). We then observe the coefficients and
test which categories can be combined using joint F-tests. This method allows us to overcome
the fact that the distribution of some parenting measures is highly skewed and so do not lend
themselves to division into equal quantiles. (For example, the observed range of the maternal
teaching score is from 10 to 30 points. However, 22% of observations score the maximum of
30 points and 40% score 29 or above).
The next step is to introduce all K parenting measures into the regression simultaneously:
n
1
+ α
2
X
i
+ β
k
k=1
k
C
i
= α ∑ Pi
+ ei
(2)
As many of the measures are likely to be highly correlated, this step allows us to observe how
the estimated effect of each behaviour changes when all the other behaviours are controlled for.
Measures that give no additional explanatory power (i.e. that are insignificant) can be tested
jointly and dropped from the model. The results of the final specification then show us the
magnitude and relative importance of different types of parenting activity on child outcomes
and, when taken together, provide a concise measure of parental behaviour that can be used as
a control in further analyses. The addition of such household characteristics as the ownership
of a car and the prevalence of damp in the home allows the analysis of parenting behaviour to
be expanded to parenting and home environment.
3.2.1 General notes on the construction of the parenting measures
As our child outcomes are measured at age 4 or 5, in general we have attempted to construct
variables that capture the child’s experience of a particular behaviour throughout the entire
31

preschool period. To test robustness we do explore a number of alternative specifications that
distinguish between behaviours at different points in time (at 1 ½ and 3 ½ years, for example).
Thus we do allow to some extent for the fact that parental behaviours might have different
effects at different ages of the child. However, given the almost over-rich nature of the
ALSPAC data, it is necessary to largely abstract from the issue of exact timing in favour of
tractability.
When constructing composite parenting measures that aggregate a large number of individual
questions, it is inevitable that many observations will have a certain number of missing
responses. Rather than imputing many of these missing values, in general we choose to focus
only on complete observations. Incomplete observations are thus coded as ‘missing’ and
comprise a separate category within a given discrete variable, denoted by a specific dummy
variable. This ensures that we can be certain of the composition of the groups used in intergroup
comparisons and our estimates will not be biased by inappropriate assumptions on the
way that missing values are imputed. The large sample size of the ALSPAC dataset means that,
even using this method, ample observations remain for estimation.
3.2.2 The measures
The following gives a brief description of each of the parenting measures used in our analysis.
The measures used are grouped into those directly involving parental choices and those where
other dimensions of the family background may constrain the choices available. These
constraints may reflect lack of income or housing quality. The divide is not always clear-cut
and this is, in part, why we discuss and analyse these parts simultaneously. Further details are
given in Appendices on the scoring system used to construct each variable (Appendix A1), the
distribution of the measures and the ways the scores were grouped to construct discrete
variables (Appendix A2).
Parenting Behaviour
Parental reading scores
The aim was to create some measure of how frequently the child was read to by a parent during
the pre-school period as a whole. The mother was asked at regular intervals how frequently
she, and also her partner, read to the child or showed him/her pictures in books. Table A1 3.1a
gives details of the scoring for each of the mother’s questions and of our derived maternal
reading variable. At each age observed an intensity of reading score is created ranging from
32

zero to four. Then a total maternal reading score is derived by summing the points for each
response across the four questionnaires. This total score ranges from zero to fifteen. If any
elements are missing then the total maternal reading score is missing. Then we explored which
parts of the distribution of this score were associated with clear differences in attainment and
chose four categories that gave the best fit. The very low and low intensity of reading scores
each cover a little under a tenth of the observed population, the medium category around a
quarter, leaving the high covering over half of the population. This was because of large
bunching of results with scores at 13 or above where no material difference in the correlation
with outcomes could be distinguished.
A problem arises in deriving the paternal reading score as, in this case, we do not want the
effects of differential reading behaviours to be confounded with family structure. Low paternal
reading scores will capture paternal absence as well as low reading involvement. To overcome
this problem, the paternal reading score is only defined for households in which a partner was
continuously present throughout the pre-school period (i.e. the mother responded that she had a
current partner in all of the 8, 21, 33 and 47 month questionnaires). Households with any
record of lone parenthood (or missing information) are placed in a category captured by a
separate dummy. Hence our results relate to the effect of differences in partners’ reading
behaviour within intact families only and do not reflect the effects of paternal absence (which
are captured elsewhere). Given this different interpretation of paternal reading behaviour
relative to maternal reading behaviour, we adopt a simplified measure of paternal reading
involvement based on the number of times the partner is observed as being highly involved in
reading to the child. Details are given in Table A1 3.2a. Table A1 3.1b shows how the raw
maternal reading score variable was grouped first into disaggregated categories and then, after
a series of specification tests, into final categories. For the paternal measure each score from 0
to 4 represents a different discrete category (Table A1 3.2b). The distributions of the two
reading score variables are shown in Figures A2.1 and A2.2.
Maternal teaching score
Mothers were asked on three separate occasions whether they tried to teach their children a
number of items (such as colours, numbers, etc). Our derived measure is designed to capture
something about both the range of items taught and the timing of the teaching activities. Table
A1 3.3a gives details of the points allocated to each response. Item scores are coded as missing
if it is not possible to identify the age at which the mother started teaching the child a
33

particular item (for example if there is a missing response to the teaching of colours at 18
months and a response of yes at 30 months). The total teaching score is the sum of the
individual item scores and if any item score is missing, the total teaching score is set to
missing.
The grouping of the teaching score into discrete categories is shown in Table A1 3.3b and
graphically in Figure A2.3.
Talking whilst occupied score
This score is designed to capture the degree of stimulation that the child receives when the
mother is primarily engaged in activities other than direct childcare. Mothers were asked at
regular intervals (6, 18, 30 and 42 months) ‘How often do you talk to your child while you do
housework or are occupied in some other way?’ Responses were scored as shown in Table A1
3.4a and then summed to create an overall talking whilst occupied score. If any of the four
responses were missing then the talking score was coded as missing.
Table A1 3.4b and Figure A2.4 show the distribution and category boundaries of the talking
whilst occupied score.
Television scores
There are questions regarding the child’s television watching habits at regular intervals in
ALSPAC but the questions asked are not consistent across questionnaires. For this reason we
are not able to construct a composite television score for the whole preschool period. Rather,
we look at two different measures, one early (18 months) and one later (38 months). The early
measure relates to how often the mother has the television on at different times of the day. The
later measure relates to how many hours a day the child typically watches television on
weekdays and at weekends.
Details of the scoring of the two measures are given in Tables A1 3.5a and A1 3.6a. Tables A1
3.5b and A1 3.6b and Figures A2.5a and A2.5b show the distributions and category boundaries
for the two television scores.
Breastfed baby
Mother’s were asked both when the child was 6 months and again when they were 15 months
about the duration of the mother’s breastfeeding. The results have been grouped into never,
34

less than 6 months and more than 6 months. This variable is specified in this way as the mere
act of initiating breastfeeding could have a positive effect on child’s development, whereas 6
months could be seen as a threshold signifying a lengthy period of breastfeeding.
Smoked in pregnancy
Questions were asked about the mother smoking during her pregnancy at various points of the
pregnancy and soon afterwards. This information was used to derive a simple dummy variable
of whether the mother did smoke or not.
Maternal bonding score
A number of questions were asked to the mother when the child was 8 months old, such as ‘I
really enjoy my baby’ and ‘it is a great pleasure to watch my baby develop’. A scale was
derived from the answers to these questions to reflect how much the mother feels she has
bonded with her baby, and divided into quintiles. As the mother had a choice of four answers
(feel exactly, feel often, feel sometimes, feel never), and these answers were recoded from
nought to three and then all the answers summed, dividing the scale into quintiles seems more
appropriate than using the continuous measure as the quintiles reflect the relative position of
the mother.
Details of the distribution and grouping of the results are found in Table A1 3.9a and A1 3.9b
Types of discipline
When the child was 42 months old, ALSPAC asked the mother questions on various forms of
discipline. In order to use the answers to these questions for our analysis, the forms of
discipline are divided into whether they were used at least once a week or less than once a
week. By keeping the forms of discipline separate rather than trying to aggregate them in some
way, it is then possible to observe whether some forms of discipline are more detrimental than
others. For instance, whether smacking a naughty child is more harmful in respect to their
development than simply ignoring them.
Home Environment and Outings
Outings scores
ALSPAC contains data at various intervals (18, 30 and 42 months) on the frequency with
which the child is taken to visit a range of eight different places (for example, to the local
35

shops, the park and to visit friends or family). We experimented with two alternative methods
of specifying the relationship between outings and child outcomes. Firstly, we adopt a method
that allows the effect on children’s development of outings to different places to vary. Hence
we can investigate whether trips to certain places are more beneficial to children’s
development than others. Table A1 4.1a gives details of how a score was constructed for visits
to each of the eight places over the period from 18 months to 42 months. If any of the elements
of a place-specific outings score are missing then that score is coded as missing.
Our second method is to construct a composite score of total outings over the two-year period.
This method treats all type of outings identically and makes no distinction between the
different places the child might visit. This composite score is simply the sum of the eight
individual place-specific scores. If any of the place-specific outings scores are missing then the
total outings score is coded as missing.
In order to incorporate the place-specific outings scores into our analysis, each one was split
into two categories – high (above the mean) and low (below the mean). Table A1 4.1b and
Figures A2.6a to A2.6h show the distributions of each of the scores and their category
boundaries. The total outings score was treated in a similar way to the other parenting
variables, entering the regressions first in a disaggregated form and then in a more concise
form. Table A1 4.1c and Figure A2.7 show the distribution.
Grouped together with the place-specific outings scores, due to its obvious association with
outings, is whether the household owns a car. This was asked when the child was 33 months
and is included in the analysis as a dummy variable. Missing results are recorded separately as
missing.
Book score
This score is designed to capture how many books the child has throughout the preschool
period. Questions on the number of books the child owns are asked at 6, 18, 24, 30 and 42
months. Table A1 4.2a gives details of how points are allocated to each response. The total
book score is simply the sum of these point scores. If any individual point score is missing the
total book score is coded as missing.
36

Table A1 4.2b and Figure A2.8 show the distribution and category boundaries of the book
score.
Toy score (24 months)
This score is designed to capture the number and range of toys available to the child at 2 years
of age. Table A1 4.3a shows the scoring for questions on the number of each of eleven types of
toys to which the child has access. The total toy score is the sum of these scored responses and
is missing if any of the responses are missing.
Table A1 4.3b and Figure A2.9 show the distribution and category boundaries of the toy score.
Crowding index
This index is created by dividing the number of people in the home by the number of rooms in
the house. Questions regarding the number of people and the number of rooms were asked in
the same questionnaire, given when the child was 42 months old.
Damp/condensation/mould
Mothers were asked during the 33 month questionnaire how much a problem damp,
condensation and mould was in the house.
3.2.3 Simple Correlation analysis
Table 3.1 gives the pairwise (unconditional) correlations between all our parenting measures
(represented continuously where possible), plus the correlations with a number of broad
demographic measures. We can see that most parenting behaviours are positively correlated,
even for those done separately by the mother and her partner. For example, the correlation
between the mothers and partners’ reading scores is 0.43. There is little evidence on the basis
of the raw data, then, that households substitute learning activities by one parent with the other.
Children in households with relatively high measures of cognitive stimulation tend to
experience a number of parenting behaviours simultaneously. So, mothers who read to their
children frequently also teach them a wider range of material and talk to them more frequently
when occupied with another task. Likewise the children of mothers with a high teaching score
also have more trips to the park and places of interest and a higher book score but watch less
TV.
37

Turning to the correlations with other household characteristics, we see that there are differing
relationships between types of parenting and the resources of the household. Outings to places
of interest and the book score are relatively strongly correlated with household income, while
outings to the local shops and watching television are negatively correlated. Other measures,
most notably the teaching and talking whilst occupied scores, reveal no relationship with
household income and very little relationship with parental education. Table 3.1 also shows
that lone parents do not differ greatly in the parenting behaviours from mothers in couples. The
greatest differences are along dimensions like outings to the local shops and department stores,
outings to places of interest and the number of books and toys, all of which are relatively
strongly associated with household income. There may be time constraints on mothers which
mean trips to shops are more common but trips to the zoo or similar are less commonly
undertaken by lone parents. Many of these activities are also correlated with being a first child
suggesting parents with more children find it harder to find time for reading and teaching to a
specific child. We will explore these relationships more closely later in the report.
3.3 The impact of the parenting variables on outcomes at 5
The first step in our estimation process was to estimate equation (1), including each of the K
parenting measures separately in a highly disaggregated form. These narrowly defined
categories were then combined as far as allowed by a test of restrictions. The results presented
here relate only to the more parsimonious, second-stage specifications.
3.3.1 Single Measure Estimates for Cognitive Development
Table 3.2 gives the conditional ( β ) coefficients from equation (1) with EA as the dependent
k
variable. These are the coefficients on each of the parenting measures when they are added to
the basic specification in separate groups. So these estimates take no account of the
correlations between the parenting measures, which are strongly correlated. The aim here is to
move from observing basic correlations to showing which parenting measures are the core
drivers of attainment and which are probably just correlated with more important behaviours. It
is clear from Table 3.3 that many of our parenting measures are significantly associated with
the EA scores. The largest coefficients effects are found for those with the lowest scores for the
maternal reading, maternal teaching and book scores, all large and negative. To give an idea of
the magnitude of these effects, a maternal qualification of CSE/none is associated with a score
of between 2 and 3 points lower, on average, than a qualification of an A-level or higher (the
38

coefficients on education are discussed further below). A move from the top 40 percent band to
the lowest 8 per cent band of the teaching score, however, is associated with a drop of 4.6
points, or nearly half a standard deviation. Aspects of the home environment are also strongly
correlated with attainment such as the book score (there is over 4 points gap between the top
and bottom categories).
The effects of different parenting behaviours are not solely concentrated in the extremes of the
distributions. Many of the scores (e.g. the maternal reading, teaching, breastfeeding scores)
show a clear gradient in the effect as the score decreases. Smoking in pregnancy, positive
feelings towards motherhood and types of discipline do not appear significant for the EA test,
whereas attending an antenatal class and breastfeeding are. It is perhaps also worth pointing out
that all the outing destinations do not have the same sign. Whilst trips to the library and places
of interest are positively associated with child outcomes, trips to department stores are negative
and significant.
A number of measures were found to have no correlation even at this early stage of
investigation. For instance, car ownership, maternal bonding and indicators of housing
conditions (crowding and damp) are not correlated with attainment when only background
family characteristics are conditioned on.
39

Table 3.1: Pairwise correlations between parenting measures and selected household characteristics
Mother's
reading
CORRELATIONS
score
Mother's reading score 1.00
Partner’s
reading
score 1
Partner’s reading score 1 0.43 1.00
Teaching
score
Teaching score 0.40 0.25 1.00
Talking
score
Talking score 0.30 0.19 0.25 1.00
TV at 18
months
TV at 18 months -0.16 -0.15 -0.05 -0.03 1.00
TV at 38
months
TV at 38 months -0.13 -0.10 -0.02 -0.05 0.38 1.00
Never
breastfed
baby
Never breastfed baby 3 -0.13 -0.10 -0.06 0.01 0.19 0.12 1.00
Smoked in
pregnancy
Smoked in pregnancy 1 -0.10 -0.08 0.01 0.02 0.12 0.10 0.14 1.00
Maternal bonding score 0.10 0.05 0.06 0.21 0.01 -0.00 0.03 -0.00 1.00
Maternal
bonding
score
Household owns a car 2 -0.04 -0.05 -0.01 0.00 0.11 0.10 0.12 0.20 0.01 1.00
Household
owns a car 2 Book score Toy score
Book score 0.45 0.31 0.32 0.14 -0.21 -0.13 -0.20 -0.14 0.03 -0.12 1.00
Toy score 0.18 0.13 0.13 0.12 -0.12 -0.10 -0.08 -0.10 0.09 -0.12 0.27 1.00
Crowding index -0.15 -0.14 -0.09 -0.03 0.16 0.11 0.12 0.12 0.05 0.10 -0.22 -0.08 1.00
No damp/condensation/mould problem 0.03 0.02 0.02 0.08 0.01 0.02 0.06 -0.01 0.07 -0.05 0.01 0.03 -0.12 1.00
Ignores child when naughty -0.01 -0.00 -0.01 -0.07 0.03 0.03 -0.00 0.04 -0.11 0.02 -0.01 -0.03 0.00 -0.02
Smacks child when naughty -0.10 -0.08 -0.04 -0.07 0.15 0.12 0.04 0.03 -0.04 0.02 -0.07 -0.08 0.05 -0.03
Shouts at child when naughty -0.10 -0.05 -0.05 -0.09 0.13 0.12 0.00 0.03 -0.13 0.00 -0.04 -0.06 0.04 -0.07
Sends child to room when naughty 0.01 0.03 0.05 -0.04 0.00 -0.01 -0.02 0.01 -0.06 0.04 0.06 -0.01 -0.00 -0.04
Takes away treats when child naughty 0.01 0.02 0.08 0.00 0.07 0.04 0.02 0.06 -0.02 0.04 0.02 -0.02 0.01 -0.01
Tells off child when naughty -0.02 -0.00 -0.02 -0.07 0.04 0.04 -0.03 0.01 -0.10 -0.01 0.02 -0.04 0.02 -0.08
Bribes child when naughty -0.07 -0.05 -0.03 -0.12 0.07 0.09 -0.01 0.01 -0.11 -0.01 -0.04 -0.02 -0.02 -0.03
Local shops 0.06 0.03 0.03 0.15 0.10 0.08 0.12 0.16 0.07 0.16 -0.09 -0.00 0.12 0.00
Dpt store 0.07 0.05 0.10 0.08 0.06 0.02 0.08 0.00 0.01 0.08 0.03 0.03 -0.05 0.08
Supermarket 0.03 -0.01 0.04 0.08 0.11 0.09 0.07 0.03 0.05 0.06 -0.04 -0.01 0.06 0.02
Park 0.25 0.21 0.16 0.12 -0.17 -0.11 -0.07 0.01 0.02 0.03 0.16 0.10 -0.07 0.04
Friends 0.10 0.08 0.09 0.12 0.01 -0.01 0.05 0.03 0.09 -0.02 0.11 0.09 -0.04 0.04
Library 0.24 0.15 0.07 0.04 -0.24 -0.17 -0.15 -0.09 -0.03 -0.01 0.21 0.19 -0.05 -0.05
Places interest 0.27 0.23 0.15 0.08 -0.28 -0.22 -0.15 -0.12 -0.01 -0.12 0.29 0.22 -0.20 0.02
Places entertainment 0.12 0.08 0.12 0.06 -0.06 -0.07 -0.02 -0.02 -0.00 -0.06 0.12 0.15 -0.09 0.05
Household income 0.13 0.14 0.04 -0.00 -0.24 -0.16 -0.21 -0.27 -0.03 -0.36 0.24 0.19 -0.28 -0.06
Ever lone parent 2 -0.04 - -0.00 -0.02 0.07 0.05 0.09 0.24 -0.03 0.40 -0.07 -0.09 -0.03 -0.01
Maternal education 3 0.21 0.21 0.06 -0.04 -0.33 -0.23 -0.30 -0.22 -0.08 -0.18 0.26 0.14 -0.23 -0.08
Firstborn child 2 0.23 0.26 0.26 0.10 -0.04 -0.01 -0.07 -0.02 -0.04 0.03 -0.28 -0.22 -0.21 0.02
Crowding
index
No damp/
mould
40

Table 3.2: Entry Assessment – coefficients on parenting and home environment variables
when included individually in basic specification (N = 5010)
Adj R squared 0.2429 0.2527 0.2579 0.2467 0.2453 0.2510 0.2540 0.2429
Maternal reading score: base = high
Very low - -3.18 *** - - - - - -
Low - -1.99 *** - - - - - -
Medium - -0.95 *** - - - - - -
Number of times partner highly involved in reading (intact families only): base = 2
0 - -1.02 ** - - - - - -
1 - -0.51 - - - - - -
3 - 0.17 - - - - - -
4 - 0.31 - - - - - -
Maternal teaching score: base = high
Very low - - -4.58 *** - - - - -
Low - - -2.61 *** - - - - -
Medium - - -1.30 *** - - - - -
Talking score: base = high
18 month TV score: base = 0-2
Insig
3-5 - - - -0.93 *** - - - -
6 - - - -1.95 *** - - - -
38 month TV score: base = < 10 hrs pwk
10+ hrs pwk - - - -0.77 ** - - - -
Breastfed baby: base = never
0- 6 months - - - - 0.66 ** - -
6 months + - - - - 1.45 *** - -
Smoked in pregnancy
Maternal bonding score
Types of discipline (used at least once a week)
Place –specific outings scores: base = low (for each score)
Local shops - - - - - Insig - -
Dpt store - - - - - -0.65 ** - -
Supermarket - - - - - Insig - -
Park - - - - - Insig - -
Friends - - - - - Insig - -
Library - - - - - 1.33 *** - -
Places interest - - - - - 1.05 *** - -
Places entertainment - - - - - Insig - -
Household owns a car: base = yes
Book score: base = high
Very low - - - - - - -3.54 *** -
Low - - - - - - -1.58 *** -
Medium - - - - - - -0.90 ** -
Toy score: base = high
Very low - - - - - - -1.88 *** -
Low - - - - - - -0.98 ** -
Medium - - - - - - 0.05 -
Crowding index (people per room): base = < 0.5
Damp/condensation/mould: base = none
Notes
1. All regressions include controls for the age of the child in months at assessment, cohort year, number of older siblings, number of
younger siblings by 42 months, gender, birth weight, special care unit at birth, ethnicity, mother’s age at birth and highest
educational attainment, lone parent status at 47 months, the partner’s highest educational attainment and employment status at 47
months.
2. Each measure of cognitive development is normalised to mean 100, standard deviation 10. 3. ***, **, and * indicate significance at
the 1%, 5% and 10% levels respectively.
Insig
Insig
Insig
Insig
Insig
Insig
41

3.3.2 Estimation Conditional on All Other Parenting Measures
Here we explore which measures still matter when they are all included together and assess the
explanatory power of the parenting variables. Column 1 of Table 3.3 includes all parenting and
home environment measures simultaneously and as before includes a set of basic background
controls for the demographics of the household. A number of features stand out in particular.
Mother’s reading score becomes only half the size of that when other parenting influences are
excluded. Book and toy scores are also substantially smaller. Some variables are not significant
once other measures are included, trips to places of interest and crowding, for example.
Column 2 repeats this exercise but gives a more parsimonious representation with insignificant
terms being dropped. The pattern of results is largely unaffected by this process. But partner’s
reading, which was very marginal in column 1, becomes insignificant once other insignificant
terms are excluded and it is excluded from further analysis. These results suggest that a
surprisingly large set of parental influences is found to have independent effects. Mother’s
teaching score remains the single most powerful predictor of child development at school entry
but the number of books and toys in the house, the amount of TV watched, especially at 18
months, and trips to the department stores and library have independent identifiable effects on
children. Breastfeeding for 6 months or more also remains significant.
42

Table 3.3: Entry Assessment – coefficients on parenting variables when included
simultaneously in basic specification (N = 5010)
Adj R2 0.2714 0.2709
Coef
Coef
Maternal reading score: base = high
Very low -1.34** -1.69***
Low -0.87* -1.05**
Medium -0.32 -0.44
Number of times partner highly involved in reading (intact families only): base = 2
0 -0.89** -
1 -0.28 -
3 -0.03 -
4 -0.02 -
Maternal teaching score: base = high
Very low -3.47*** -3.55***
Low -1.94*** -1.98***
Medium -1.03*** -1.03***
18 month TV score: base = 0-2
3-5 -0.58* -0.69**
6 -1.30*** -1.53***
38 month TV score: base = < 10 hrs pwk
10+ hrs pwk -0.55* -
Breastfed baby: base = never
0- 6 months 0.47 0.45
6 months + 0.91** 0.89**
Place –specific outings scores: base = low (for each score)
Dpt store -0.71*** -0.65**
Library 0.83*** 0.91***
Places interest 0.35 -
Book score: base = high
Very low -1.99*** -2.07***
Low -0.58 -0.67*
Medium -0.48 -0.51
Toy score: base = high
Very low -1.06* -1.18*
Low -0.37 -0.45
Medium 0.41 0.37
Notes
1. All regressions include controls for the age of the child in months at assessment, cohort year, number of older siblings, number of
younger siblings by 42 months, gender, birth weight, special care unit at birth, ethnicity, mother’s age at birth and highest educational
attainment, lone parent status at 47 months, the partner’s highest educational attainment and employment status at 47 months.
2. Each measure of cognitive development is normalised to mean 100, standard deviation 10.
3. ***, **, and * indicate significance at the 1%, 5% and 10% levels respectively.
43

3.3.3 Behaviour
Tables 3.4 and 3.5 repeat the above analysis for our behaviour measure and shows regressions
for a basic set of controls plus each set of parenting and home environment measure in turn.
Again these parenting measures are extremely strong predictors of behavioural problems,
although the magnitudes differ in their relative importance. Reading, teaching and the book
score are still strong influences on behaviour but the toy score is more important, as is talking
whilst engaged in housework.
There are a wider set of parenting behaviours and home environment indicators that are
individually significant for behavioural outcomes (smoking during pregnancy, positive feelings
towards motherhood and types of discipline used) whereas they were insignificant for the
cognitive measure. Feelings about motherhood are extremely strongly correlated with child
behaviour. Even though the measure of mother’s feelings is assessed at just 8 months and the
behaviour measured at around 50-60 months, it is still possible there is some reverse causality
here. Children with persistent behaviour problems may affect mothers’ attitudes at 8 months
and still be reflected in behaviour at 60 months and as both are mother reported they could both
reflect a mother’s specific feelings toward their children. Even so the lagging of mother’s
feelings may reflect a vicious cycle of poor child behaviour and negative feelings by the
mother. The same is perhaps true of forms of discipline used. No one disciplining device stands
out as having adverse effects but rather the use of a lot of different techniques would appear to
be damaging. This could simply reflect poor behaviour leading to more techniques being used
but diverse or inconsistent disciplining may be less effective. More place-specific outings
scores are significant for behaviour and housing conditions also.
44

Table 3.4: Behaviour – coefficients on parenting variables when included individually in
basic specification (N = 9416)
Adj R squared 0.0872 0.0922 0.0688 0.1678
Maternal reading score: base = high
Very low 4.26 *** - - -
Low 3.15 *** - - -
Medium 1.22 *** - - -
Number of times partner highly involved in reading (intact families only): base = 2
0 1.15 *** - - -
1 0.51 - - -
3 -0.76 ** - - -
4 -1.75 *** - - -
Maternal teaching score: base = high
Very low - 2.64 *** - -
Low - 2.02 *** - -
Medium - 0.99 *** - -
Talking score: base = high
Low - 4.81 *** - -
Medium - 2.25 *** - -
18 month TV score: base = 0-2
3-5 - - 0.95 *** -
6 - - 1.90 *** -
38 month TV score: base = < 10 hrs pwk
10+ hrs pwk - - 1.45 *** -
Breastfed baby: base = never
0-6 months -0.46 *
6 months + -0.58 **
Smoked in pregnancy: base = no
Yes - - - 1.01 ***
Maternal bonding score: base = highest quintile
Lowest quintile - - - 6.41 ***
2 nd quintile - - - 3.99 ***
3 rd quintile - - - 3.01 ***
4 th quintile - - - 2.01 ***
Types of discipline (used at least once a week)
Ignores child when naughty - - - 1.73 ***
Smacks child when naughty - - - 1.64 ***
Shouts at child when naughty - - - 1.87 ***
Sends child to room when naughty - - - 1.37 ***
Takes away treats when child naughty - - - 0.54 **
Tells off child when naughty - - - 1.52 ***
Bribes child when naughty - - - 1.81 ***
45

Table 3.5: Behaviour – coefficients on parenting variables when included individually in
basic specification (N = 9416)
Adj R Squared 0.0769 0.0776 0.0671
Place –specific outings scores: base = low (for each score)
Local shops
Insig
Dpt store -0.46 ** - -
Supermarket -0.46 * - -
Park -0.97 *** - -
Friends -0.88 *** - -
Library -0.79 *** - -
Places interest -1.29 *** - -
Places entertainment -0.44 * - -
Household owns a car:
base = yes
Insig
Book score: base = high
Very low - 2.46 *** -
Low - 1.91 *** -
Medium - 0.80 *** -
Toy score: base = high
Very low - 3.73 *** -
Low - 2.44 *** -
Medium - 1.41 *** -
Crowding index (people per room): base = < 0.5
0.5 to < 0.75 - - -0.21
0.75 to < 1.00 - - 0.08
1.00+ - - 0.55
Damp/condensation/mould: base = none
Minor problem - - 1.23 ***
Serious Problem - - 2.25 ***
Notes
1. All regressions include controls for the number of older siblings, number of younger siblings by 42 months, gender, birth weight, special
care unit at birth, ethnicity, mother’s age at birth and highest educational attainment, lone parent status at 47 months, the partner’s highest
educational attainment and employment status at 47 months.
2. Each measure of cognitive development is normalised to mean 100, standard deviation 10.
Table 3.6 controls for all the measures simultaneously. The impact of the teaching and reading
scores and even TV watching are rather modest for behavioural measures of parenting
behaviours. But the maternal bonding score and the large range of discipline measures are
extremely powerful indicators of behaviour problems. Mother’s talking to children during
housework is also a robust predictor. Among the indicators of outings and the home
environment the toy score is most important but also outings and book scores and damp,
condensation or mould also seems to have an influence on child’s behaviour scores.
46

Table 3.6: Behaviour – coefficients on parenting variables when included simultaneously
in basic specification (N = 9416)
Adj R2 0.1995 0.1992
Maternal reading score: base = high
Very low
Low
Medium
1.47
1.24
0.08
***
***
1.56
1.29
0.11
***
***
Number of times partner highly involved in reading (intact families only): base = 2
0
1
3
4
0.80
0.30
-0.40
-0.60
** 0.82
0.30
-0.41
-0.63
Maternal teaching score: base = high
Very low
Low
Medium
Talking score: base = high
Low
Medium
18 month TV score: base = 0-2
3-5
6
1.03
0.80
0.32
2.24
0.92
**
**
***
***
0.31
0.71 **
1.03
0.80
0.32
2.26
0.91
**
**
**
***
***
38 month TV score: base = < 10 hrs pwk
10+ hrs pwk 0.73 *** 0.83 ***
Breastfed baby: base = never
0- 6 months
6 months +
-0.35
-0.26
Smoked in pregnancy: base = no
Yes 0.94 *** 0.97 ***
Maternal bonding score: base = highest quintile
Lowest quintile
2 nd quintile
3 rd quintile
4 th quintile
Types of discipline (used at least once a week)
Ignores child when naughty
Smacks child when naughty
Shouts at child when naughty
Sends child to room when naughty
Takes away treats when child naughty
Tells off child when naughty
Bribes child when naughty
5.40
3.38
2.48
1.68
1.75
1.31
1.54
1.46
0.80
1.45
1.54
***
***
***
***
***
***
***
***
***
***
***
Place –specific outings scores: base = low (for each score)
Dpt store
Supermarket
Park
Friends
Library
Places interest
Places entertainment
-0.30
-0.26
-0.48
-0.53
-0.21
-0.71
-0.46
**
**
***
*
Book score: base = high
Very low
Low
Medium
Toy score: base = high
Very low
Low
Medium
Crowding index (people per room): base = < 0.5
0.5 to < 0.75
0.75 to < 1.00
1.00+
Damp/condensation/mould: base =
none
Minor problem
Serious Problem
0.34
0.79
0.27
1.65
1.00
0.60
-0.36
-0.26
0.04
0.63
1.21
***
***
***
**
***
***
5.40
3.39
2.48
1.69
1.75
1.34
1.55
1.46
0.79
1.46
1.55
-
-
-0.55
-0.52
-
-0.80
-0.49
-
-
-
0.44
0.84
0.29
1.69
1.01
0.60
0.65
1.27
***
***
***
***
***
***
***
***
***
***
***
**
**
***
**
***
***
***
**
***
***
Notes
1. All regressions include controls for the number of older siblings, number of younger siblings by 42 months, gender, birth
weight, special care unit at birth, ethnicity, mother’s age at birth and highest educational attainment, lone parent status at 47
months, the partner’s highest educational attainment and employment status at 47 months.
2. Each measure of cognitive development is normalised to mean 100, standard deviation 10.
47

Among the outing types, trips to places of interest, places of entertainment, friends and the
park are all associated with better behaviour but the library or shops are uncorrelated. Causal
interpretation remains problematic, especially for the discipline measure, as these effects could
reflect family traits rather than the activity per se. However, these parenting and home
environment measures are making a huge difference to the amount of the variation in
behaviour explained by the model.
3.3.4 Are Better Educated Parents More Effective?
So far we have examined what are the more beneficial parenting activities, in terms of whether
these different behaviours influence a children’s development. It is our intention to explore
whether these measures of parenting behaviour substantially explain the implied role of
parental education or family income. However, it may also be the case that better educated
parents are doing not just more in terms of outings, books, etc., but also that they are doing it
better by using more educationally orientated activities or because they are more skilled at
parenting. To test this important hypothesis we explore interactions between the key parenting
behaviours and parental education. To simplify the number of potential interactions we use a
single parental education interaction term, where the categories are mother’s education if the
question relates to the mother only, and likewise father only, but a combined parental
education grouping if the question refers to the family more generally. The detailed results of
these interactions are explored in Appendix Tables A3.1 to A3.12 but the summary of these
tests is presented in Table 3.7. Each coefficient reported is that for a (F-) test that the
interaction terms between the variable of focus (mothers reading etc.) and each of parental
education categories can be accepted as jointly significant. A value of less than 0.1 would
suggest that there is significant variation in the impact of the parenting behaviour variable
across parental education categories. The table suggests that in general there is a high
probability that these interactions are insignificant and that the impact of greater pro-learning
behaviour is the same across all parental education groups.
48

Table 3.7: Summary of F-test for significance of interaction terms (parenting variables *
parental education)
Parenting measure Prob effect of parenting does not vary with
educational group – joint test of no
variation within all parenting categories 1
Entry Assessment Behaviour
Mother’s reading score 0.5625 0.6341
Partner’s reading score 0.6554 0.5276
Teaching score 0.9124 0.2824
Talking whilst occupied score 0.5337 0.9422
18 month TV score 0.8567 0.2158
38 month TV score 0.4961 0.5203
Breastfeeding score 0.0295 0.2553
Maternal bonding score 0.8238 0.6620
Mother ignores child when naughty 0.6707 0.3192
Mother smacks child when naughty 0.5441 0.3194
Mother shouts at child when
naughty
0.3705 0.0398
Mother sends child to room when
naughty
0.4928 0.3209
Mother takes away treats when
child is naughty
0.0782 0.5322
Mother tells off child when naughty 0.4978 0.0870
Mother bribes child when naughty 0.6848 0.0731
Department stores outings score 0.7365 0.4622
Park/playground outings score 0.4592 0.2441
Visits to friends/relatives outings
score
0.0745 0.4605
Library outings score 0.0249 0.0228
Places of interest outings score 0.0458 0.4553
Places of entertainment outings
score
0.2594 0.1456
Book score 0.3579 0.6631
Toy score 0.8504 0.9095
Damp/mould/condensation score 0.0802 0.6707
Notes
1. i.e. the probability that the interaction terms can be dropped and the original specification of levels only
retained.
2. Each regression includes basic demographic controls.
This needs clear interpretation; parental education remains an important influence after
conditioning on parental behaviours. This residual component may reflect the, as yet, omitted
transmission mechanisms in our study, others not available to us to explore (e.g. genetic
influences) or a generic capability for the better educated to undertake all the discussed
activities more effectively. However, the result is important because it suggests that better
educated parents may read and teach their children more intensively but they do not do it more
49

effectively for any specific elements among our measured parental inputs. The exceptions to
this general rule occur mainly for outings for the cognitive measures and the disciplining
variables for behaviour. These do appear to have a variable impact across education groups and
closer investigation suggests that low education parents that undertake more outings have a
beneficial effect on their child’s development.
In summary, reading to and teaching children are very important to children’s cognitive
outcomes at age 4/5. The home environment (toys and books) and outings are also substantial
predictors of attainment. For behaviour mothers bonding with the child and discipline
strategies are also important, as are toy scores and outings. Further there is no evidence that
more highly educated parents teach and read to their children more effectively than the less
well educated. Teaching and reading to children, trips out and books in the home appear to be
equally important to a child’s pre-school development, irrespective of the educational
attainment of the family. This supports the notion that it is the behaviours captured by these
variables that stimulate children’s development, and not that the variables simply act as proxies
for other parental characteristics. The implication is that if a family’s reading could be raised
then it would make a direct, positive contribution to children’s cognitive development
regardless of parental background. Note though that parental education is still an important
direct predictor of child attainment suggesting there are still important unexplained routes by
which attainment is raised by better-educated parents.
50

4. Maternal Employment
This section looks at whether mother’s return to work timing decision makes any difference to
children’s cognitive and behavioural development. This topic has been the subject of more
substantive analysis (Gregg et al. 2005). Here we aim to broadly replicate this research within
the structure of the present report.
4.1 Existing Evidence
The motivation for looking at maternal employment stems from an awareness that patterns of
maternal employment have changed dramatically over the last twenty years or so (see Gregg et
al. 2003) and the mainly US evidence suggesting that early maternal employment can hinder
children’s development. Virtually all of the recent evidence on the effects of early maternal
employment on child outcomes is US-based and most studies use data from a single source –
the National Longitudinal Survey of Youth (NLSY). Despite the use of this common dataset,
these studies frequently provide conflicting results as to the nature of the impact of mothers’
employment. It is clear that their conclusions are sensitive to methodological differences with
regard to sample selection, the measures of maternal employment and child development used
and the choice of control variables. Comprehensive surveys of this literature exist elsewhere
(see, for example, Waldfogel et. al., 2002, and Ruhm, in press). However, because this paper
explores a number of different hypotheses surrounding maternal employment and child
development, it is instructive to review the evidence on each issue separately. Although much
work was carried out on this topic in the early 1990s, we concentrate here on more recent
studies 3 . These tend to address at least partially some of the methodological deficiencies that
have been highlighted in the earlier papers (see Harvey, 1999, and Ruhm, 2004, on this issue).
4.1. Is early maternal employment harmful to children’s development and does its effect vary
with the timing and intensity of work?
Although it is by no means universal, a substantial number of the recent US studies report the
result that maternal employment in the first year after the birth has small negative effects on
children’s cognitive outcomes (relative to not working at all in the first three years).
3 For examples of this first wave of studies, see Desai et. al. (1989), Bayder and Brooks-Gunn (1991), Belsky and
Eggebeen (1991), Vandell and Ramanan (1992), Parcel and Meneghan (1994), and Greenstein (1995).
52

However, this may be at least partially offset by positive effects of working in the second and
third years of the child’s life 4 . Many studies suggest that these effects are larger for full time
working than part-time or that higher intensity of working in the first year is more damaging.
In general, behavioural problems in children seem to respond to maternal employment in the
same directions as cognitive outcomes although here the relation is weak and estimates tend to
be insignificant.
Using five measures of cognitive development 5 as the dependent variables in OLS regressions,
Waldfogel et. al. (2002) find significantly poorer outcomes on all five measures for the
children of mothers who worked at all in the first year of life. The effects of employment in
years 2 and 3 are positive when compared to not returning to work by year 3, although
generally smaller in absolute magnitude and less well determined than the early negative
effects. They test whether working in all three years has more harmful effects than employment
in years 2 and 3 alone and find that delaying employment until after the first year is associated
with significant improvements in the child’s performance over working all 3 years. The net
effect of working in all three years compared to not returning by age 3 was insignificantly
negative. With regard to intensity of employment, they find that the negative effects of first
year employment are driven by the effect of full time working (more than 20 hours per week).
The coefficients on first year part time work, whilst generally negative, are small and
insignificant.
Using a smaller sample but a very similar methodology, Han et. al. (2001) again find negative
effects of first year employment and weaker positive effects of later work for white children
only. In this case, they find no significant differences between part time and full time working
in the first year. They also test whether the negative impact of work in the first year is greater
for mothers who returned to work more quickly after the birth. They find that the negative
effects of return before the child is 10 months old are stronger than for return in the last quarter
of the first year.
Rather than using regression analysis like the other work on the NLSY, Hill et. al. (2001) use
the technique of propensity matching in order to identify the effects of early maternal
4 See Section 5.1 for a discussion of the magnitudes of these estimates.
5 The measures of cognitive development available in the NLSY are the Peabody Picture Vocabulary Test-R
(PPVT-R) at age 3 or 4 and the Peabody Individual Achievement Tests on maths and reading recognition (PIAT-
M and PIAT-R respectively) at age 5 or 6. Some studies also analyse the PIAT scores for children at later ages,
most commonly for 7 or 8 year olds.
53

employment. This technique is discussed further below but we note here that Hill et. al. find
that children of mothers who worked part-time in the first year would have experienced
adverse effects if their mothers had instead worked full time. They also find that children of
mothers who worked full time apparently could have benefited if their mothers had not worked
in the first year. The effects of second and third year employment on performance tend to be
positive but insignificant.
Ruhm (in press) again analyses NLSY data for children aged 3 or 4 and 5 or 6. His inclusion in
the regressions of a far more extensive set of background controls, however, leads to somewhat
different results. He again finds a negative effect of the amount of employment in the first year
but it is only significant for 3 to 4 year olds. In contrast with other work, he also finds
significantly negative effects for second and third year employment. Ruhm also investigates
whether the timing of return to work matters. He finds no significant difference between return
prior to 6 months and return between 7 and 12 months, although his results suggest that
children gain if mothers delay their return until after the first year. In general, Ruhm’s
specifications impose a linear relationship on the number of hours worked and child outcomes.
He notes, however, that when he explored potential non-linearities he found some evidence the
employment exceeding 20 hours per week had particularly negative effects.
Harvey (1999) provides a further challenge to the finding of damaging effects of early
employment offset by later positive effects in the NLSY. Harvey explores the effects of a
variety of measures of maternal employment such as age of the child in weeks at return and
dummies for any employment in the first year or in the first three years. Relative to not
working in the first three years, she finds no evidence of any adverse of effects of early
employment. However, amongst women who do work in the first three years, Harvey finds that
working more hours is associated with a small but significant decrease in test scores.
Turning to studies based on data other than the NLSY, Brooks-Gunn et. al. (2002) analyse data
from the richly detailed NICHD Study of Early Childcare. Unlike the NLSY, data are only
available on the cognitive outcomes of infants (aged 15, 24 and 36 months). Brooks-Gunn et.
al. find that the children of mothers who are employed by the ninth month score significantly
lower on the assessment at age 3, compared to the children of mothers who do not return
before that date. When they explore whether this effect varies with the intensity of
employment, they find that the adverse effect of full time work in the first nine months is
54

double the effect of part time work. However, they find no evidence of negative effects on
children’s scores at younger ages.
Gregg et al. (2003) use the ALSPAC data being used here and suggest that full-time
employment in the first 18 months after birth has small adverse effects on attainment measured
by tests at age 7 but were unable to detect these effects in the EA data being used in this study
or in the behaviour measure. The authors suggest that these adverse effects are restricted to
where informal care by friends and relatives is used rather than childminders or nursery
centres. Part-time working is never found to have adverse consequences. Such modest effects
restricted to a small minority of mothers are also found by Joshi and Verropoulu (2000). They
analysed data from the British NCDS and BCS70 they suggest that first year maternal
employment may lead to slightly poorer achievement in reading, but not maths, amongst
school age children and that employment between years 1 and 4 is associated with a small
improvement in emotional well being. Ermisch and Francesconi (2000) use retrospective
information from the British Household Panel Survey and, as a result, the measures of
employment and child development are a good deal cruder than those employed in the other
studies. Ermisch and Francesconi analyse the effect of maternal employment in the first five
years of life on the probability of achieving at least an A-level as a young adult. They find that
increasing the amount of full time maternal employment before age 5 by one year reduces the
probability of achieving at least an A-level by 7 to 9 percentage points. A similar increase in
part time work lowers the probability but by a smaller amount – 3 to 6 percentage points.
These results rely on their use of a sibling difference estimator, as their cross-sectional logit
estimates do not identify any significant effects of early maternal employment on later
achievement.
4.2 Measures of maternal employment
Our measure of early maternal employment is based on the age of the child in months when the
mother returned to work. Our analysis focuses on maternal employment prior to 34 months
because our data on return times is censored at this point and also because this cut-off
corresponds well to the three-year break used in many previous studies. However, we also have
an observation of whether the mother is working or not at 47 months and hence can construct a
group for those reported as not returning before 34 months but observed in work at 47 months.
We divide the 0 to 34 month period into sub-periods and create dummies to indicate whether
the mother returned to work in each one. Throughout most of our analysis we distinguish
between return prior to 18 months and return in the 19 to 34 month period. Ideally, we would
55

like to allow our results to vary with the number of hours that the mother worked in a typical
week in the first three years if the child’s life. Unfortunately, data on the mother’s hours of
work are only available at the discrete points of 21 and 33 months. We therefore use this
information to assign mothers to either a part time category (less than 30 hours per week) of a
full time category (30 or more hours per week), giving priority to the 21-month data.
The proportions of mothers falling into each employment category are shown in Table 4.1.
Some 73 percent of mothers have returned to work by 47 months, approximately just prior to
school entry. The bulk of returns (55% of all mothers) are in the first 18 months with a small
dribble of returners after this date, when virtually all returns are part-time. In the first 18
months return is concentrated between 4 and 7 months when paid and then unpaid maternity
leave periods, which applied at the time of the ALSPAC cohort, expire (see Burgess et al. 2002
for a detailed analysis of mothers return dates). Virtually all full-time returns are in this
window. However, there are substantial numbers of part-time returners between 7 and 18
months. Very few mothers who had not returned to work by 34 months were observed in work
at 47 months, just before school entry. The data therefore refers to the earliest return date and
doesn’t imply continuous working thereafter.
Table 4.1 The distribution of return times
Maternal employment % of total sample 1
0 – 18 months PT 42.4
Of which:
0 – 6 months PT 24.2
7 – 12 months PT 11.3
13 – 18 months PT 6.9
0 – 18 months FT 13.8
Of which:
0 – 6 months FT 10.5
7 – 12 months FT 2.4
13 – 18 months FT 0.9
19 – 34 months 10.5
Of which:
19 – 34 months PT 9.5
19 – 34 months FT 1.0
35 – 47 months 5.9
Not by 47 months 27.5
Total 100.0
Notes:
1.Sample with at least one outcome measure (Entry Assessment or Behaviour), excluding observations where maternal employment data is
missing: N = 7881.
In what follows we distinguish returners pre-18 months according to full and part-time status,
and returned 19-34 months and 35-47. We do not distinguish between part and full time work
56

for mothers who returned between 19 months or later because so few of these mothers fall into
the full time category (only 1.9 per cent of the total sample). For some regressions this leads to
cell sizes that are simply too small to be of analytical value.
4.3 Results
4.3.1 Children’s cognitive development
Column 1, Table 4.2 shows that, without conditioning on mother’s education, age etc, children
of mothers who return full-time before 18 months are doing better on average than other
children. However, in column 2 we condition on mothers age, mothers and partners education
and other basic controls and this result disappears. There is no evidence that children of women
who return to work in the first 18 months are doing less well than others on the EA measure.
Column 3 confirms that there are no sub-periods, especially early return periods, which are
associated with negative effects in our age 4/5 measure of educational development. Note
Gregg et al. (2003) find later measures of cognitive ability also tend to be significantly
negative with a specification similar to that reported in column 2, but they find that this adverse
outcome is limited to those working full-time and use unpaid informal care by friends or
relatives but this was not also true for the EA measure at 4/5. We explore childcare later.
We next move to looking at whether there is any variation in the size of the coefficients on
mothers return date across mothers’ education and lone parent status. These interactions are
reported in Table 4.3. The coefficients reported are then the impact of returning by the date
indicated for each panel broken out by each education group. The comparison is then between
returning by that date relative to not working before 47 months for each education group. The
results suggest that the lone parent interaction terms are never individually statistically
important nor do F-tests suggests any variations across education groups for each return date.
In other words, there are no differences between lone parents and mothers in couples on how
their employment is related the child’s cognitive development.
Table 4.2: The effects of early maternal employment on Entry Assessment scores
57

(N = 5010)
(1) (2) (3)
Return date Coef. (s.e.) Coef. (s.e.) Coef. (s.e.)
0 –18 months PT 0.558 -0.444 -
(0.385) (0.367)
0 – 6 months PT - - -0.568
(0.409)
7 – 12 months PT - - -0.252
(0.502)
13 – 18 months PT - - -0.323
(0.598)
0 –18 months FT 1.593*** -0.493 -
(0.511) (0.499)
0 – 6 months FT - - -0.367
(0.542)
7 – 12 months FT - - -0.329
(0.951)
13 – 18 months FT - - -2.458
(1.540)
19 – 34 months -0.091 0.081 0.078
(0.556) (0.520) (0.520)
After 34 but in work at 47
months -0.598 -0.394 -0.398
(0.729) (0.676) (0.676)
Test of restrictions 5 : 0.6795
Adj R2 0.0970 0.2363 0.2361
Notes
1. Regression (1) includes controls for the age of the child at assessment only.
2. Regressions (2) and (3) include controls for the age of the child in months at assessment, cohort year, number of older siblings, number
of younger siblings by 47 months, gender, birth weight, special care unit at birth, ethnicity, mother’s age at birth and highest educational
attainment, lone parent status at 47 months, the partner’s highest educational attainment and employment status at 47 months, log of
weekly household income and an indicator of pre-birth financial deprivation.
3. Each measure of cognitive development is normalised to mean 100, standard deviation 10.
4. ***, **, and * indicate significance at the 1%, 5% and 10% levels respectively.
5. The F-test of restrictions tests the hypothesis that the effects of part time work before 18 months do not vary with the date of return and
that simultaneously the effects of full time work do not vary with return date.
For mother’s education there is some evidence the impact on children of the mother working
before 34 months is more negative where the mother is better educated, with part-time working
before 18 months for degree holders and again for 19-34 months showing individual
coefficients that are statistically significant. This suggests that the mother’s foregone parenting
input maybe of greater value for better educated mothers. However, the F-tests suggest that
only for the part-time before 18 months are there significant variations in coefficients across
education groups. Together with the parenting results, where we found better educated mothers
were engaged in more reading and teaching but where there was no evidence this was done
more effectively, this might suggest reduced levels of parenting input where mothers are
working before 18 months. There seems to be the reverse relationship for those returning
between 34 and 47 months where lesser educated mothers have a large negative coefficient but
the sample sizes here are very small and perhaps not too much emphasis should be placed on
this result.
58

Table 4.3: Differential effects of early maternal employment by maternal education and
lone parent status: Entry Assessment (N = 5010)
Maternal F- test 1 F- test 1
Return Date Coef. (s.e.) P > F = Coef. (s.e.) P > F =
0 – 18 months PT
* CSE/none -0.711
(0.813)
* Vocational/ O-level -0.118 * Never lone parent -0.534
(0.473) (0.391)
0.0302
* A-level 0.180 * Ever lone parent -0.658 0.9089
(0.624) (1.055)
* Degree -2.753***
(0.889)
0 – 18 months FT
* CSE/none 0.961
(1.618)
* Vocational/ O-level -1.360* * Never lone parent -0.810
(0.726) (0.543)
0.2775
* A-level 0.288 * Ever lone parent -0.032 0.6166
(0.833) (1.502)
* Degree -1.226
(1.014)
19 – 34 months
* CSE/none 1.212
(1.210)
* Vocational/ O-level -0.121 * Never lone parent -0.059
(0.676) (0.575)
0.1099
* A-level 1.521 * Ever lone parent 1.707 0.2670
(1.106) (1.510)
* Degree -2.650*
(1.519)
After 34 months but in
work at 47 months
* CSE/none -4.526***
(1.534)
* Vocational/ O-level 0.610 * Never lone parent -0.185
(0.942) (0.725)
0.0095
* A-level 1.572 * Ever lone parent -2.175 0.3651
(1.332) (2.089)
* Degree -2.149
(2.230)
Simultaneous test of
equality of 0.0075 0.6138
interacted terms:
Adj R2 0.2385 0.2361
Notes
1. The F-test of restrictions tests the hypothesis that the interaction terms for each employment group are equal, i.e. that there is no variation
in the effect of each type of employment with the mothers’ characteristics.
All regressions include controls for the age of the child in months at assessment, cohort year, number of older siblings, number of younger
siblings by 47 months, gender, birth weight, special care unit at birth, ethnicity, mother’s age at birth and highest educational attainment, lone
parent status at 47 months, the partner’s highest educational attainment and employment status at 47 months, log of weekly household income
and an indicator of pre-birth financial deprivation
59

Table 4.4: The effects of early maternal employment on Behaviour scores (N = 9416)
(1) (2) (3)
Return date Coef. (s.e.) Coef. (s.e.) Coef. (s.e.)
0 –18 months PT -1.194*** -0.261 -
(0.278) (0.279)
0 – 6 months PT - - -0.302
(0.316)
7 – 12 months PT - - 0.008
(0.400)
13 – 18 months PT - - -0.545
(0.479)
0 –18 months FT -1.321*** 0.353 -
(0.377) (0.390)
0 – 6 months FT - - 0.300
(0.425)
7 – 12 months FT - - 0.390
(0.769)
13 – 18 months FT - - 0.994
(1.244)
19 – 34 months -0.569 -0.257 -0.258
(0.415) (0.406) (0.406)
34 – 47 months -0.134 -0.101 -0.101
(0.513) (0.501) (0.501)
Test of restrictions 4 : 0.8394
Adj R2 0.0023 0.0617 0.0614
Notes:
1. Higher behavioural scores indicate more adverse outcomes.
2. Regression (1) includes no additional controls.
3. Regressions (2) and (3) include controls for number of older siblings, number of younger siblings by 47 months, gender, birth
weight, special care unit at birth, ethnicity, mother’s age at birth and highest educational attainment, lone parent status at 47
months, the partner’s highest educational attainment and employment status at 47 months, log of weekly household income and an
indicator of pre-birth financial deprivation.
4. The F-test of restrictions tests the hypothesis that the effects of part time work before 18 months do not vary with the date of return
and that simultaneously the effects of full time work do not vary with return date.
60

Table 4.5: Differential effects of early maternal employment by maternal education and
lone parent status: Behaviour (N = 9416)
Maternal F- test 1 F- test 1
Employment Coef. (s.e.) P > F = Coef. (s.e.) P > F =
0 – 18 months PT
* CSE/none -0.326
(0.634)
* Vocational/ O-level -0.265 * Never lone parent -0.317
(0.380) (0.298)
0.4295
* A-level -0.697 * Ever lone parent -0.723 0.6192
(0.500) (0.786)
* Degree 0.626
(0.655)
0 – 18 months FT
* CSE/none 0.513
(1.243)
* Vocational/ O-level 0.117 * Never lone parent 0.328
(0.607) (0.421)
0.8125
* A-level 0.175 * Ever lone parent 0.353 0.9830
(0.665) (1.111)
* Degree 0.964
(0.751)
19 – 34 months
* CSE/none -0.407
(0.934)
* Vocational/ O-level -0.131 * Never lone parent 0.264
(0.558) (0.447)
0.4365
* A-level 0.341 * Ever lone parent -2.881** 0.0093
(0.861) (1.139)
* Degree -1.959
(1.170)
34 – 47 months
* CSE/none 0.565
(1.108)
* Vocational/ O-level -0.109 * Never lone parent -0.216
(0.711) (0.543)
0.4997
* A-level -0.926 * Ever lone parent -2.097 0.2328
(1.006) (1.491)
* Degree 1.903
(1.736)
Simultaneous test of
equality of 0.6211 0.0968
interacted terms:
Adj R2 0.0613 0.0630
Notes
1. Higher behavioural scores indicate more adverse outcomes.
2. All regressions include controls for the age of the child in months at assessment, cohort year, number of older siblings, number of
younger siblings by 47 months, gender, birth weight, special care unit at birth, ethnicity, mother’s age at birth and highest educational
attainment, lone parent status at 47 months, the partner’s highest educational attainment and employment status at 47 months, log of
weekly household income and an indicator of pre-birth financial difficulties.
61

4.3.2 Behavioural Outcomes
Tables 4.4-4.5 repeat this analysis for behavioural outcomes. As for cognitive development
children whose mothers return to work full-time have better than average scores (the measure
is inverted relative to cognitive development) when no other information is conditioned on.
However, this result disappears once parental education and other basic background controls
are introduced in column 1, as mothers working full-time are better educated and older. Unlike
for cognitive development, further conditioning on the mothers’ pre-birth employment and
financial situation and occupation make little further difference. Hence there is no evidence of
any difference in behavioural outcomes according to the mothers return to work decision. This
is also true across all mother’s education groups, as none of the interaction terms show any
significant or consistent pattern.
Summary
Maternal employment in the early months and years after a birth is not found to be a predictor
of the EA test scores on arriving at school at age 4 to 5 once other background characteristics
are conditioned. Nor is there any effect on behaviour scores. We thus do not pursue this line of
study further. Early work contained in Gregg et al. (2003) suggests that there is evidence of
adverse effects observable at age 7 in the KS1 and the Focus at 7 ALSPAC administered tests
and this will be investigated in follow up research looking at later attainment.
62

5. Childcare
This section describes the pattern of childcare usage amongst the ALSPAC sample, and
examines the impact of childcare, controlling only for our standard set of controls, on cognitive
and behavioural outcomes at ages 4 to 5. There are two sources of childcare information
available, the first is taken from mothers’ questionnaires at 8 weeks, 8 months, 15 months and
24 months. This asked the mother if a particular type of childcare was used and for the number
of hours it was used for. From this we construct measures of whether each type of care was
used more that 20 hours a week at any date up to and just beyond the child’s second birthday
(see Appendix 1 childcare section for more details). The survey at 24 months falls just after
the second birthday, and as mothers will answer the questions with a delay of 1 to 2 months,
the data covers the two to three month period after the second birthday.
As part of the Focus at 7 interviews the mother reported retrospectively the names and broad
type of all centre based pre-school providers used. This is the second source of information on
pre-school childcare. Periods of use and number of ½ day sessions attended were also detailed.
From this we can identify the type of the last pre-school attended prior to school entry and how
many sessions attended. In some cases more than one was attended simultaneously in which
case both are recorded. Hence the groups are not mutually exclusive. As the individual
provider is identified and we have a large proportion of children within this age range in the
Avon study, many children will attend the same provider. This allows us to observe members
of the child’s peer group at the provider and this is explored in Section 7 on neighbourhoods
and peer groups later.
5.1 Patterns in the use of childcare
Table 5.1 presents childcare use up to and just beyond the ALSPAC child’s second birthday.
The categories are not mutually exclusive, as a mother may use several sources of childcare.
The question refers to any care, which replaces that of the mother, not just care for when the
mother is at work.
64

Table 5.1: Childcare usage up to age 2
Type
Ages 8 weeks, 8,
15 and 24 months
All Mothers
At 24 Months
Mother
working
Mother
working
Full-Time
All Mothers
Partner
5-19 hours per week 35.5 29.1 37.8 26.2 41.7
20+ hours per week 40.4 13.5 18.2 25.7 15.5
Total 75.9 42.6 56.0 51.9 57.3
Friend/relative
5-19 hours per week 26.2 17.3 23.1 14.4 26.1
20+ hours per week 22.0 8.7 12.5 17.9 10.6
Total 48.2 26.1 35.6 32.2 36.7
Paid person
5-19 hours per week 8.4 6.9 10.6 7.3 11.6
20+ hours per week 13.5 9.0 16.1 35.3 9.4
Total 21.9 15.9 26.7 42.6 21.0
Centre care
5-19 hours per week 5.3 4.6 5.6 5.6 5.6
20+ hours per week 3.2 2.3 4.0 9.0 2.3
Total 8.5 6.8 9.7 14.6 7.9
Mother
working
Part-time
Figures given are the percentage of the total working sample in each cell (i.e., the sample with at least one outcome measure – Entry
Assessment or Behaviour – excluding observations where data on usage of that type of care is missing).
The most common source of childcare is the partner (around ¾ of the sample have partner’s
supplying care), followed by friends and relatives (around half the sample). Apart from very
short hours around three quarters of this care is provided by grandparents. Paid care is used by
around 30% of the sample, either in the form of a person (child minder or nanny – 80% of this
group have child minders for above 5 hours of care) or, less commonly, centre based (only
8.5% of the sample). Note that this reflects answers at four ages up to around 26 months and so
the use of centre based care at any point in time is very low, especially for more than 20 hours
per week. So pre-2, centre based care is very rarely used for long hours, probably because the
cost is very high. The table also reports childcare use from the 24 month survey broken down
by employment status of the mother at 21 months. This gives a clearer picture of variations in
usage for working mothers and across hours of work. It shows that partners do more when the
mother works with higher involvement of at least 5 hours but where the mother works full-time
partner’s involvement for over 20 hours is far more extensive. Increased use of
childminders/nannies for 20+ hours (35% as opposed to just 9% on average) is also much more
marked where the mother works full-time. Whilst long hours of care in centres or by friends
and relatives also rise with full-time working the steps are much less marked.
65

Post age-3 the use of centre-based care rises considerably with virtually all parents using some
form of centre based care between the ages of 3 and 5. Table 5.2 shows the types of pre-school
providers used most recently prior to entry in school. The categories used are reported by the
mothers and are thus subject to some interpretation, but Nursery class is thought to refer to a
class attached to a school, whilst the LEA nursery probably covers both day nurseries
historically provided by social services and LEA provided nursery schools. We are unable to
distinguish between these two very different alternatives with any certainty. As well as private
day nurseries there is an unspecified residual nursery category where the parent could not be
more specific. The small “other” group covers, we think, special needs centres and any other
circumstance where mother was unable to match the available categories.
Nurseries are widely used but a sizeable proportion of mothers were unable to describe the type
of nursery used (whether it was a dedicated public or private nursery). Over 45% of children
were using a dedicated Nursery (including the unspecified group) and this rises to around 60%
if Nursery classes within schools are added 6 . Playgroups were also widely used with 63% using
Playgroups at all but only 39% used Playgroups without also using Nursery care as well (see
Table 5.3).
Nursery classes are mainly used for 3-5 sessions per week, especially school-based nurseries.
The use made of playgroups is more limited than that of nurseries. Very few families use more
than 3-5 sessions per week at a playgroup, but of the mothers who use the alternative types of
nurseries around 20% use over 5 sessions per week. Mothers also combine the use of different
centre based care.
6 This will have increased markedly more recently as the government now offers a free ½ day place for all three
and four year olds.
66

Table 5.2: Centre-based care prior to school entry
% of sample using Number of sessions used per week, % of those using
type (after type
36 months) 1-2 sessions 3-5 sessions 6-10 sessions
Nursery class 15.5 1.7 85.5 12.8
LEA nursery 9.3 0.6 74.0 25.3
Private day nursery 13.6 35.4 40.2 24.4
Nursery (undefined) 25.1 20.6 62.9 16.5
Playgroup 63.5 38.8 59.9 1.3
Other 1.7 6.2 29.9 63.9
Figures given are the percentage of the total working sample in each cell (i.e., the sample with at least one outcome measure – Entry
Assessment or Behaviour – excluding observations where data on usage of that type of care is missing).
Table 5.3: Combinations of nursery and playgroup care prior to school entry
Type of nursery
used
Used alone
Used in
conjunction with
playgroup only
Total
None 0.6 38.6 39.2
Nursery class 8.8 5.2 14.0
LEA nursery school 5.6 2.8 8.4
Private day nursery 6.3 5.0 11.3
Nursery (undefined) 12.1 10.6 22.7
Other 0.8 0.4 1.2
Total 34.3 62.6 96.9*
Table sample is households that used a maximum of one type of nursery (excluding playgroups) post-age 3. The
remaining 3.1% of the sample used combinations of two or more types of nursery.
5.2 Patterns of association of childcare and cognitive and behavioural outcomes
Column 1 of Table 5.4 examines the relationship between type of childcare up to age 2 and
outcomes at age 5 with no controls for later childcare use. Each type of care is split into 2
mutually exclusive categories and a test made of the equality of impact of less compared to
more use of each type of care. The regression analysis controls for our standard set of controls
(see Table 2.2) and the magnitude of the coefficients are comparable within column (and with
other sections) as the outcome measures are standardised to mean 100 and s.d. 10. Since we do
not control for the correlates of the care patterns, in this preliminary analysis, we are essentially
examining whether any direct or indirect relationship exists between the outcomes and the type
of care.
Column 1 indicates that EA scores are positively associated with care from a partner (provided
it is for less than 20 hours a week) and use of centre care, particularly of a duration of more
67

than 20 hours per week. Children attending centre care for over 20 hours per week before the
age of 2 score, on average, 1.7 points better than their peers. However, the proportion of
children in this group is very small, being just 3 percent of the sample. In contrast, having care
from a friend or relative for over 20 hours per week has a significant negative impact on
outcome. As we are not yet conditioning on other childcare usage and other related factors
these are not necessarily causal relationships.
Column 2 of Table 5.4 examines the impact of the last used pre-school provider on EA test
scores, on top of care pre age 2, allowing for a differential impact of the type of centre-based
care. Additionally, column 3 differentiates between the number of sessions of each type of
centre based care used each week. Note the use of partner care up to 2 and the negative effect
of unpaid friends or relatives remain but the centre based care result diminishes. Already there
is no strong evidence that early use of centre based care is beneficial to children’s cognitive
development.
Columns 2 and 3 indicate that not all types of centre care are associated with positive
outcomes. Column 2 shows attendance at what mothers report as LEA nurseries has a negative
effect on outcomes as does attendance (particularly long attendance) at the undefined other
category of centre care. The LEA nursery effect may reflect that many children in these
nurseries will be there at the recommendation of social services. The other category includes
special referral units and the coefficients will reflect that. When we also explore the
information contained in peer groups attending the same providers these possible explanations
will be more clearly addressed. Attendance at nurseries (private or other), in contrast, is
associated with positive outcomes. Column 3 shows that the negative impact of LEA nursery
school attendance is greatest for those who attend only a few times, but the sample size here is
small. Of the more commonly used forms of care there is little evidence that longer exposure
within the week is better in terms of development. Only for private nurseries do outcomes rise
monotonically with number of sessions and even here a restriction to just a single term, used or
not used, is not rejected by the data. This suggests that for nursery settings positive attainment
outcomes are as pronounced for part-time as full-time attendance.
68

Table 5.4: Controlling for centre-based child care usage post-age 3 (Entry Assessment)
(1) (2) (3)
Coef S.E. Coef S.E. Coef S.E. F-test 1
Pre-age 2 childcare usage
P>F =
Partner
5-19 hours per week 0.581* (0.346) 0.624* (0.345) 0.581* (0.346) -
20+ hours per week -0.079 (0.345) 0.005 (0.344) -0.022 (0.345)
Friend/relative
5-19 hours per week -0.269 (0.317) -0.255 (0.316) -0.263 (0.316) -
20+ hours per week -0.906*** (0.342) -0.897*** (0.340) -0.911*** (0.341)
Paid person
5-19 hours per week -0.244 (0.474) -0.297 (0.474) -0.225 (0.474) -
20+ hours per week 0.320 (0.405) 0.258 (0.404) 0.287 (0.406)
Centre care
5-19 hours per week 0.380 (0.604) 0.100 (0.608) 0.122 (0.611) -
20+ hours per week 1.655** (0.830) 1.320 (0.836) 1.425* (0.848)
Post-age 3 centre-based care
Nursery class - 0.775* (0.399) -
1-2 sessions per week - 0.671 (3.306)
3-5 sessions per week - 0.795* (0.420) 0.8600
6-10 sessions per week - 0.224 (1.049)
LEA nursery - -1.106** (0.485) -
1-2 sessions per week - -11.709* (6.132)
3-5 sessions per week - -0.952* (0.543) 0.1845
6-10 sessions per week - -1.553* (0.906)
Private day nursery - 1.400*** (0.430) -
1-2 sessions per week - 0.837 (0.597)
3-5 sessions per week - 1.482** (0.616) 0.3791
6-10 sessions per week - 2.140*** (0.826)
Nursery (type undefined) - 1.130*** (0.358) -
1-2 sessions per week - 1.557*** (0.604)
3-5 sessions per week - 1.350*** (0.428) 0.0188
6-10 sessions per week - -0.891 (0.824)
Playgroup - 0.377 (0.340) -
1-2 sessions per week - 0.221 (0.381)
3-5 sessions per week - 0.430 (0.399) 0.6382
6-10 sessions per week - 1.459 (1.604)
Other - -3.529*** (1.109) -
1-2 sessions per week - -4.429 (6.135)
3-5 sessions per week - -2.372 (2.080) 0.3903
6-10 sessions per week - -5.897*** (1.576)
Joint test of restrictions - - - 0.1586
Adj R2 0.2445 0.2519 0.2531
Notes
1. The F-test of restrictions tests the null hypothesis that the coefficients on the number of sessions per week
categories are equal, i.e. that the effect of a particular type of centre-based care does not depend on the
intensity of its use.
2. ***, **, and * indicate significance at the 1%, 5% and 10% levels respectively.
69

Table 5.5: Controlling for centre-based child care usage prior to school entry (Behaviour)
(1) (2) (3)
Pre-age 2 childcare usage Coef S.E. Coef S.E. Coef S.E.
Partner
5-19 hours per week -0.238 (0.277) -0.236 (0.277) -0.211 (0.278) -
20+ hours per week -0.495* (0.275) -0.504* (0.275) -0.495* (0.275)
Friend/relative
5-19 hours per week 0.555** (0.257) 0.573** (0.257) 0.571** (0.257) -
20+ hours per week 0.855*** (0.277) 0.881*** (0.277) 0.855*** (0.277)
Paid person
5-19 hours per week 0.339 (0.384) 0.331 (0.385) 0.334 (0.386) -
20+ hours per week 0.243 (0.325) 0.276 (0.326) 0.343 (0.328)
Centre care
5-19 hours per week 1.669*** (0.470) 1.638*** (0.474) 1.715*** (0.475) -
20+ hours per week 0.103 (0.601) 0.114 (0.606) 0.276 (0.614)
Post-age 3 centre-based care
F-test 1
P>F =
Nursery class - -0.020 (0.389) -
1-2 sessions per week - 3.559 (2.297)
3-5 sessions per week - 0.026 (0.417) 0.1201
6-10 sessions per week - -1.204 (0.931)
LEA nursery - 1.062** (0.466) -
1-2 sessions per week - -7.531 (4.850)
3-5 sessions per week - 0.707 (0.529) 0.0653
6-10 sessions per week - 2.101** (0.840)
Private day nursery - 0.171 (0.397) -
1-2 sessions per week - 1.181** (0.576)
3-5 sessions per week - -0.163 (0.576) 0.0257
6-10 sessions per week - -1.137 (0.737)
Nursery (type undefined) - 0.335 (0.330) -
1-2 sessions per week - 0.054 (0.559)
3-5 sessions per week - 0.283 (0.396) 0.7595
6-10 sessions per week - 0.663 (0.682)
Playgroup - 0.295 (0.308) -
1-2 sessions per week - 0.051 (0.354)
3-5 sessions per week - 0.282 (0.365) 0.4377
6-10 sessions per week - -1.146 (1.297)
Other - 2.044** (0.988) -
1-2 sessions per week - 15.045*** (5.594)
3-5 sessions per week - 1.650 (2.041) 0.0771
6-10 sessions per week - 2.645* (1.389)
Joint test of restrictions - - - 0.0166
Adj R2 0.0634 0.0634 0.0657
Notes
1. The F-test of restrictions tests the null hypothesis that the coefficients on the number of sessions per week categories are equal, i.e. that
the effect of a particular type of centre-based care does not depend on the intensity of its use.
2. All regressions include controls for the age of the child in months at assessment, cohort year, number of older siblings, number of
younger siblings by 42 months, gender, birth weight, special care unit at birth, ethnicity, mother’s age at birth and highest educational
attainment, lone parent status at 47 months, the partner’s highest educational attainment and employment status at 47 months.
3. Each measure of cognitive development is normalised to mean 100, standard deviation 10.
4. ***, **, and * indicate significance at the 1%, 5% and 10% levels respectively.
Table 5.5 repeats the same analysis for behavioural outcomes. Column 1 suggests that the
association of care pre-age 2 with behavioural outcomes is somewhat different (note a negative
score indicates a better outcome). The impact of care by partners is still beneficial and the
effect of care by a friend or relative still on balance adverse. The effect of centre care is now
70

that short hours of centre care are associated with worse outcomes. This is not the case for long
hours but note the small sample that has long hours of centre based care. The explanatory
power of the behavioural regression is very low (in contrast to the regression for EA). All these
results remain when later care arrangements are conditioned on. So there is a case that early
centre based care is associated to poorer later behaviour outcomes.
Column 2 shows that the negative effects of LEA nursery and other care on cognitive outcomes
are also present for behavioural outcomes, and for LEA nurseries the negative effect is
increasing in usage. On average, other forms of centre-based care have no effect on behaviour
(column 2). In contrast with care at pre-2, it appears that private nurseries are associated with
no harmful effects on behavioural outcomes and preliminary evidence of beneficial cognitive
effects, whilst LEA nursery attendance is associated with negative outcomes on both measures.
We will explore to what extent these reflect selection of client groups later.
5.3 Do Patterns of association of childcare and cognitive and behavioural outcomes vary
by parental characteristics?
We now examine whether parental education interacts with the type of childcare used: in other
words, do better-educated parents translate a given type of care into better outcomes?
There are a number of studies suggesting that high quality childcare is especially beneficial to
those from deprived backgrounds (see Ramey and Ramey, 1998, for example). Table 5.6
examines this for cognitive outcomes and Table 5.7 for behavioural outcomes. Reading across
rows in Table 5.6 shows no clear pattern as the educational group of the parent increases. This
is confirmed from the F-tests: the impact of type of care on EA scores is the same across all
categories of parental educational attainment. Table 5.7 shows a very similar pattern for
behaviour. So parental education determines which kind of childcare is chosen and this has an
impact on child outcomes. But, conditional on a particular type of care being used and a
general term reflecting parental education, better-educated parents do not get better outcomes
through childcare for their children.
71

Table 5.6: Interactions of parental education with childcare usage (Entry Assessment)
Parental education 1
CSE/none
Vocational/
O-level
A-level Degree
Partner
5-19 hours per week 0.887 0.975* -0.254 0.188
(0.752) (0.587) (0.629) (0.805)
20+ hours per week -0.689 0.029 0.432 -0.249
(0.713) (0.579) (0.629) (0.817)
Friend/relative
5-19 hours per week 0.381 -0.492 -0.450 1.287
(0.802) (0.440) (0.594) (1.031)
20+ hours per week -0.782 -1.172** -0.598 -0.815
(0.839) (0.474) (0.632) (1.155)
Paid person
5-19 hours per week -3.306** 0.694 -0.623 -0.110
(1.465) (0.791) (0.784) (1.088)
20+ hours per week -1.514 1.136* 0.219 -0.723
(1.691) (0.676) (0.668) (0.791)
Centre care
5-19 hours per week 2.311 -0.328 1.021 -1.894
(2.212) (0.963) (1.058) (1.299)
20+ hours per week 6.739 1.309 1.144 0.898
(5.038) (1.371) (1.447) (1.526)
Prob
(row coefs equal)
P > F =
0.4615
0.6710
0.3503
0.8951
0.1088
0.2205
0.2313
0.7417
Joint test of
restrictions
P > F =
0.1917
0.6891
0.1127
0.4848
Nursery class
1.408* 1.141** 0.236 0.584
(0.821) (0.538) (0.744) (1.044)
0.6584
-
LEA nursery school
-1.495 -1.650** -0.049 -1.306
(1.205) (0.671) (0.845) (1.242)
0.4627
-
Private day nursery
1.052 2.091*** 0.412 0.862
(1.402) (0.637) (0.712) (0.842)
0.2895
-
Nursery (type
undefined) 1.183 0.687 1.615*** 1.495*
(0.843) (0.497) (0.610) (0.853)
0.6146
-
Playgroup
0.306 0.478 0.203 0.106
(0.711) (0.451) (0.567) (0.757)
0.9607
-
Other
-5.117*** -4.455** -0.747 -5.745
(1.949) (1.798) (2.638) (3.584)
0.5432
-
Notes
1. All types of childcare are interacted with maternal educational attainment, with the exception of care by the partner pre-age 2 which is
interacted with paternal education.
2. The interaction terms for each type of care relate to separate regressions in which all other types of care (both pre-age 2 and post-age 3)
are included as level controls, i.e. only one set of interaction terms is included per regression.
3. The F-test of restrictions tests the null hypothesis that the coefficients on each of the educational categories are equal, i.e. that the effect
of a particular type of centre-based care does not vary with parental education.
72

Table 5.7: Interactions of parental education with childcare usage (Behaviour)
Parental education 1
CSE/none
Vocational/
O-level
A-level Degree
Partner
5-19 hours per week 0.321 -0.236 -0.636 -0.263
(0.587) (0.502) (0.526) (0.603)
20+ hours per week 0.334 -1.215** -0.418 -0.458
(0.561) (0.489) (0.522) (0.598)
Friend/relative
5-19 hours per week 1.571** 0.671* 0.119 -0.485
(0.635) (0.369) (0.495) (0.772)
20+ hours per week 1.246* 0.896** 0.706 0.395
(0.641) (0.398) (0.541) (0.850)
Paid person
5-19 hours per week -0.633 1.037 0.177 0.203
(1.259) (0.666) (0.640) (0.812)
20+ hours per week 1.216 -0.356 0.833 0.274
(1.364) (0.593) (0.547) (0.588)
Centre care
5-19 hours per week 0.972 1.881** 1.659** 1.336
(1.715) (0.779) (0.822) (0.995)
20+ hours per week -1.993 -1.085 -0.253 1.598
(2.526) (1.180) (1.082) (0.978)
Prob
(row coefs equal)
P > F =
0.6760
0.2029
0.1523
0.8593
0.6178
0.4411
0.9520
0.2418
Joint test of
restrictions
P > F =
0.3155
0.4938
0.5659
0.5905
Nursery class
0.222 -0.348 0.658 -0.559
(0.842) (0.535) (0.709) (0.889)
0.5912
-
LEA nursery school
1.333 0.755 1.142 1.160
(1.139) (0.650) (0.817) (1.201)
0.9597
-
Private day nursery
-1.132 0.187 0.255 0.459
(1.442) (0.630) (0.642) (0.689)
0.7938
-
Nursery (type
undefined) -0.099 0.030 0.437 0.788
(0.830) (0.471) (0.534) (0.635)
0.7182
-
Playgroup
0.151 0.559 -0.216 0.574
(0.618) (0.395) (0.461) (0.561)
0.4485
-
Other
1.503 2.293 4.063* -2.240
(1.871) (1.550) (2.184) (2.825)
0.3534
-
Notes
1. All types of childcare are interacted with maternal educational attainment, with the exception of care by the partner pre-age 2 which is
interacted with paternal education.
2. The interaction terms for each type of care relate to separate regressions in which all other types of care (both pre-age 2 and post-age 3)
are included as level controls, i.e. only one set of interaction terms is included per regression.
3. The F-test of restrictions tests the null hypothesis that the coefficients on each of the educational categories are equal, i.e. that the effect
of a particular type of centre-based care does not vary with parental education.
73

6. Maternal Health, Social Support and Background.
6.1 The measures
The ALSPAC data contain information on the financial resources of the mother when a child, a
(negative) life events score for occurrences that happened to her before adulthood, measures of
her mental and physical health from pregnancy onwards, measures of her social networks, and
family conflict. Together, they provide a rich picture of the mother’s health resources,
particularly mental and emotional. We group these into 2 groups.
1) Mothers childhood and family background: measures of education, financial resources, and
life events
These measures are:
• The tenure of mother’s childhood home
• The mother’s mother and father’s highest educational qualification
• Whether the father was present (or not) in the mother’s childhood home
• Whether the mother was frequently away from school before or after age 11
• Whether the mother feels school was valuable for her (not at all versus all others)
• The mother’s relationship with her own mother
• Home stability
• The weighted life events score.
The last three of these are described in a little more detail here.
Mother’s relationship with her own mother
Mothers were given 12 statements regarding their feelings towards their own mother (or
mother figure) in the first 16 years of their life. Examples are:
• My mother was affectionate to me
• My mother appeared to understand my problems and worries
Responses were coded 0,1 or 2 with higher scores indicating more positive memories. These
were summed to give an overall score with a range of 0 to 24. This score was divided into
quartiles for use in the regressions.
Home stability during childhood
Mothers were asked if the behaviour of their mother (figure) and father (figure) to them as a
child was stable and predictable. The home stability variable was coded depending on the most
74

negative response given to either of the questions. If both responses were ‘Always stable and
predictable’ the home stability code is ‘Very stable’. If either parent were at worst ‘Mostly
stable and predictable’ then the code ‘Fairly stable’ was assigned. If either parent were at worst
‘Rarely stable and predictable’ then the code ‘Unstable’ was assigned. And if either parent
were at worst ‘Never stable and predictable’ then the code ‘Very unstable’ was assigned. In our
analysis we distinguished only between a very stable childhood home and not.
Childhood weighted life events score
Mothers were asked whether a list of 31 events had happened to them before the age of 17.
Examples of events are experience of sexual abuse, a parent being mentally ill, separation of
parents, illness of siblings. If the event occurred they were asked how much it affected them,
with responses ranging from ‘A lot’ (scored as 4) to ‘It did not affect me’ (scored as 1). If the
event did not happen it was scored as zero. These weighted responses were then summed to
give a total score. The continuous score was divided into quintiles but, after testing, only the 20
percent with the lowest score (i.e. experiencing the least events) were distinguished from the
rest.
2) Mothers Physical and mental health, family conflict and social support
Mother’s physical health
Mothers were asked for a general assessment of their fitness in the 8 week, 8 months, 21
months, 33 months and 47 months questionnaires. The responses were scored from 0 to 3 with
higher scores indicating better physical health. A continuous total physical health score was
generated by summing these scores across the five questionnaires, giving a variable with a
range of 0 to 15. This continuous score was divided into four categories based roughly on
quartiles.
Mother’s social networks
There are two measures; the social networks score and a social support score. The social
networks score measures the extent of the mother’s social network of friends and family. It was
administered in pregnancy and is composed of the responses to 10 items. Mothers were asked
to what extent they agreed with statements such as
• How many people are there that you can talk to about personal problems?
• During the last month, how many times did you get together with one or more of your
relatives or your partner's relatives?
75

Possible responses ranged from ‘This is exactly how I feel’ to ‘I never feel this way’. They
were scored from 0 to 3 with higher scores indicating wider social networks. The total score is
the sum of the 10 item scores, which is then divided into 3 quantiles for use in the regressions.
The social support score measures the perceived level of social support from family, friends
and official agencies. It was administered in pregnancy and is composed of the responses to 10
items. Mothers were asked to what extent they agreed with statements such as
• There is always someone with whom I can share my happiness and excitement about
my pregnancy.
• If I feel tired I can rely on my partner to take over.
Possible responses ranged from ‘This is exactly how I feel’ to ‘I never feel this way’. They
were scored from 0 to 3 with higher scores indicating a greater degree of perceived support.
The total score is the sum of the 10 item scores, which is then divided into 3 quantiles for use
in the regressions.
Mother’s mental health
The Crown-Crisp Experimental Index (CCEI)
The CCEI is a measure of psycho-neurotic pathology. It is comprised of 23 questions that go to
make up 3 subscores. Each question has the possible responses: Very often, Often, Not very
often, Never. These are coded as 0, 1 or 2 depending on the sense of the question and summed.
The CCEI score is the sum of all 23 responses and has a range of 0 to 46. Higher scores
indicate greater mental distress. Within this there is an anxiety subscore (comprised of 8
questions), a somatic subscore (comprised of 7 questions) and a depression subscore
(comprised of 8 questions). The CCEI is measured at 18 weeks gestation, 32 weeks gestation, 8
weeks post-natal, and at 8 months. It is also available at 21 months and 33 months but these are
not used because they may be subject to influence by the child’s behaviour. The measure used
in most of our analysis is the mean of the 4 early scores. 7 To allow for non-linearities all the
CCEI measures enter the regressions as discrete variables relating to quintiles.
7.
We also explore specifications that relate to the CCEI in pregnancy (the average of the 18 and 32 week gestation
scores), in the first year of the child’s life (the average of the 8 week and 8 month scores) and in years 2 and 3 (the
average of the 21 and 33 month scores). Another specification we explore takes the mean of each of the subscores
across all 6 questionnaires.
76

Self-esteem measure
The self-esteem score is derived from 11 questions asked at 33 months. Mothers were asked to
rate whether 11 statements were true: ‘Almost always’,’ Often’,’ Sometimes’, ‘Seldom’ or
‘Never’. Examples are:
• I feel I am able to do things as well as most other people
• I feel I do not have much to be proud of
Responses were scored from 0 to 4 depending on the sense of the question and then summed to
give an overall score with a range of 0 to 44. Higher scores indicate greater self-esteem. Again,
the self-esteem score enters the regressions in quintiles.
Locus of control
The locus of control score is derived from responses to a questionnaire administered during
pregnancy. Locus of control of reinforcement has been defined as the perception of a
connection between one’s actions and their consequences. People who believe that an outcome
is largely contingent upon their own behaviour are seen as having a more internal locus of
control, whereas those who believe that luck, fate, chance or powerful others largely determine
an outcome are considered to be more external 8 . The score is based on the responses to 12
questions scored as 0 or 1 then summed, leading to an overall score with a range of 0 to 12.
Higher scores indicate a more external locus of control, i.e. a greater belief in the importance of
luck, fate or chance. Hence we label higher scores as reflecting an “external” sense of where
the locus of control lies. Given the small range of this variable, it was split into low-mediumhigh
categories (in the proportions 35 – 50 – 15) on the basis of observation of the distribution.
Family conflict
There are two measures of family conflict:
Cruelty from partner
Mothers were asked whether they had experienced physical or emotional cruelty from their
partner at 8, 21, 33 and 47 months. If a mother answered yes to either of these items on any of
the four questionnaires, she is classed as having experienced cruelty from her partner.
8 Measures of internality and externality have been shown to be associated with a number of different factors,
including academic achievement, psychological well-being and beliefs.
77

Mother’s satisfaction with relationship
The mother’s satisfaction with relationship score is derived from 7 questions in the 33-month
questionnaire. Mothers were asked how satisfied they were with aspects of their relationship,
for example
• Demonstrations of affection
• Amount of time spent together
• Handling family finances
There are four possible responses ranging from ‘Very satisfied’ to ‘Very dissatisfied’ and these
are scored from 0 to 3 with higher scores indicating greater satisfaction. The total score is the
sum of the 7 item scores. The continuous score is divided into quintiles for use in the
regressions.
6.2 The correlations between the measures
Table 6.1 presents the correlations between these measures. The correlations indicate that these
measures fall into groups. Higher risks of childhood deprivation (a LA home during childhood
and low education of parents) are associated with each other (and with mother’s own
education) but are not particularly closely associated with the measures of mother’s health. The
various dimensions of the mother’s health are associated, both during the post pregnancy
period and from the mother’s childhood to her adulthood. The experience of adverse events
during childhood and finding them difficult to cope with (the weighted life events score) is
linked to later experience of poor mental health (the CCEI score). Post pregnancy poor mental
health, feelings of lack of control and low self-esteem are closely associated with each other,
and in turn, this set of variables are closely associated with poor social networks. Whilst poor
physical health is not closely associated with low financial resources during childhood, it is
reasonably closely associated with having poorer social support and is strongly associated with
poorer mental health. Experiencing cruelty from a partner is associated with experiencing
adverse events during childhood, having poorer physical health, lower social support and
poorer mental health.
78

Table 6.1: Correlations between selected maternal background characteristics
Childhood
home council
rented 1
Mother’s childhood and family background Physical health Mother’s social networks
Mother’s father
Mother’s
absent from Mother’s Weighted life relationship
Social
child-hood mother had no events in with own Mother’s networks Social
home 1 qual-ifications 1 childhood score mother score physical health score support score
Childhood home council rented 1 1.00
Mother’s father absent from
1
childhood home
0.10 1.00
Mother’s mother had no
1
qualifications
0.32 0.06 1.00
Weighted life events in
childhood score
0.06 0.07 -0.06 1.00
Mother’s relationship with own
mother score
-0.10 -0.07 -0.09 -0.25 1.00
Mother’s physical health -0.06 -0.01 -0.04 -0.19 0.19 1.00
Social networks score -0.15 -0.09 -0.17 -0.08 0.26 0.12 1.00
Social support score -0.09 -0.07 -0.09 -0.14 0.28 0.22 0.49 1.00
Total CCEI score 0.07 0.06 0.05 0.29 -0.27 -0.55 -0.23 -0.36 1.00
Mental health and psychological
measures
Total CCEI
score
Locus of
control score
Locus of control score 0.19 0.12 0.22 0.07 -0.17 -0.12 -0.26 -0.25 0.22 1.00
Self-esteem
score
Experienced
cruelty from
partner 1
Family conflict
Self-esteem score -0.08 -0.05 -0.07 -0.13 0.22 0.37 0.23 0.34 -0.54 -0.23 1.00
Experienced cruelty from
1
partner
0.03 0.02 0.00 0.19 -0.17 -0.19 -0.13 -0.24 0.31 0.10 -0.19 1.00
Mother’s satisfaction with
relationship
0.00 0.01 0.02 -0.13 0.19 0.27 0.14 0.33 -0.36 -0.07 0.35 -0.33 1.00
Log household income -0.21 -0.10 -0.20 -0.11 0.08 0.12 0.23 0.22 -0.21 -0.38 0.19 -0.21 0.09
prebirth financial difficulties 1 0.07 0.03 0.05 0.12 -0.14 -0.14 -0.18 -0.20 0.26 0.17 -0.17 0.15 -0.15
Ever lone parent 1 0.09 0.11 0.10 0.13 -0.07 -0.07 -0.15 -0.22 0.20 0.21 -0.13 0.33 -0.08
Maternal education -0.28 -0.10 -0.37 0.01 0.03 0.04 0.21 0.11 -0.09 -0.44 0.11 -0.03 -0.03
Paternal education -0.22 -0.09 -0.32 0.00 0.02 0.03 0.17 0.13 -0.08 -0.34 0.08 -0.07 0.02
Firstborn child 1 -0.07 0.01 -0.08 -0.01 0.08 0.06 0.08 0.06 -0.04 -0.06 0.06 -0.04 0.03
Notes
1. Dummy variables
2. Bold indicates significance at 1% level, Underlining significance at the 5% level
Mother’s
satisfaction
with the
relationship
79

In sum, the data shows a picture in which individuals who experience poor post pregnancy
mental health are more likely to have experienced adverse events during their childhood, have
poorer social networks, have poorer physical health and are more likely to experience cruelty
from their partners. These events are also, as the last part of table 6.1 shows, associated with
both a lower household income and single parenthood during the study child’s life.
6.3 The effect of maternal health and background on EA score
Table 6.2 presents the results of equation (1), which estimates the independent impact of each
of the maternal health and background measures on the EA scores. The results show that
individually most of these measures are correlated with EA and that the direction of
correlations is in the expected direction. Those mothers from poorer financial backgrounds,
who experience poorer health and less social support whilst their child is under 5 have children
with lower EA scores. However, there appears to be little enduring impact of the mental health
related events experienced by the mother during her own childhood. In addition, the
magnitudes reported in this table are modest in comparison with those seen in the parenting
and childcare sections. This suggests that facets of the mother’s physical and mental health, the
mother’s background and family conflict are not substantive drivers of early child
development.
Table 6.3 explores the joint association between these factors and the EA score. The first
column of coefficients presents a full specification, while the second column drops those
variables that are not significantly different from zero. The results show that a low EA score is
associated with the mother coming from a poorer background (having low financial resources
during childhood and low educational attainment of the maternal grandmother), with the
mother having poor social networks and with the mother feeling she has little control over her
life. However, there is no association of either physical or mental health (as measured by the
CCEI score) with EA test scores once we have allowed for the joint correlations between these
maternal health measures and other measures of the mother’s health. Again, the correlations of
these measures with EA are lower than those in the parenting and childcare sections above.
80

Table 6.2: Entry Assessment – coefficients on maternal background variables when
included individually in basic specification (N = 5010)
Adj R2 0.2473 0.2429 0.2450 0.2458 0.2429
Mother's childhood and family background
Tenure of mother's childhood home (base = mortgage/owned))
Council housing -0.89 *** - - - -
Other rented -0.30 - - - -
Other 0.80 - - - -
Mother's father present in childhood home (base = not at all)
Throughout 1.73 ** - - - -
Partly 1.54 ** - - - -
Mother's mother's educational attainment (base = CSE/none)
Vocational/O-level 0.721 ** - - - -
A-level 1.30 *** - - - -
Degree 0.18 - - - -
Mother's father's educational attainment Insig - - - -
Childhood events score Insig - - - -
Mother's relationship with mother Insig - - - -
Home stability during childhood Insig - - - -
Mother has history of truancy (base = yes)
No 1.32 ** - - - -
Mother feels school was a valuable experience (base = not sure/generally not/no)
Yes very 0.37 - - - -
Yes generally -0.40 - - - -
Mother's physical health
Mother's physical health score
Insig
Mother's social networks
Social networks score (base = highest third)
Middle third - - 0.64 ** - -
Highest third - - 0.69 ** - -
Social support score (base = highest third)
Middle third - - 0.44 - -
Highest third - - 1.00 *** - -
Mental health & psychological measures
Total CCEI score (base = lowest quintile)
2nd quintile - - - -0.56 -
3rd quintile - - - -0.63 -
4th quintile - - - -0.51 -
Highest quintile - - - -1.20 *** -
Locus of control score (base = Internal) -
Medium - - - -0.82 *** -
External - - - -1.47 *** -
Self-esteem score - - - Insig -
Interpersonal sensitivity measure subscore - - - Insig -
Family conflict
Experience of cruelty from partner - - - - Insig
Mother’s satisfaction with relationship
Insig
81

Table 6.3: Entry Assessment – coefficients on maternal background variables when
included simultaneously in basic specification, full and parsimonious specifications
(N = 5010)
Adj R2 0.2502 0.2498
Mother's childhood and family background
Tenure of mother's childhood home (base = mortgage/owned)
Council housing -0.81 ** -0.84 **
Other rented -0.24 -0.25
Other 0.81 0.75
Mother's father present in childhood home (base = not at all)
Throughout 1.56 ** 1.66 **
Partly 1.44 * 1.54 **
Mother's mother's educational attainment (base = CSE/none)
Vocational/O-level 0.66 * 0.68 **
A-level 1.24 *** 1.27 ***
Degree 0.05 0.10
Mother has history of truancy (base = yes)
No 1.12 ** 1.12**
Mother feels school was a valuable experience (base = not sure/generally not/no)
Yes very -0.00 0.11
Yes generally -0.61 * -0.54
Mother's physical health
Mother's social networks
Social networks score (base = lowest third)
Middle third 0.52 * Dropped
Highest third 0.52 -
Social support score (base = lowest third)
Middle third 0.21 0.43
Highest third 0.72 * 1.06 ***
Mental health & psychological measures
Total CCEI score (base = lowest quintile)
2nd quintile -0.45 Dropped
3rd quintile -0.52 -
4th quintile -0.28 -
Highest quintile -0.93 ** -
Locus of control score (base = Internal)
Medium -0.70 ** -0.72 **
External -1.13 ** -1.23 **
6.4 The effect of maternal health measures on child behaviour
Table 6.4 investigates the relationship between individual maternal health and her child’s
behaviour. The lower the score the fewer the behavioural problems. The table shows strong
association between mothers health and child behaviour. Mothers with more settled childhoods
– with fewer adverse events in their own childhood, with better relationships with their
mothers, from more stable household, with little experience of truancy and who felt school was
valuable are more likely to have children with fewer behavioural problems. Similarly, mothers
in better mental and physical health have children with fewer behavioural problems. These
correlations are very substantial. Mothers who have better social networks have children with
82

fewer behavioural problems. Finally, mothers who do not experience cruelty from their
partners and who are more satisfied with their relationship have children with fewer
behavioural problems.
Table 6.5 examines whether these strong patterns are robust to the addition of the basic
controls and allowing for the correlation between the maternal health, background and support
measures. The second column shows that this is predominantly the case. With the exception of
adverse events in childhood and the experience of cruelty from a partner, all other measures of
maternal health remain associated with child behaviour. Within each measure the relationship
is monotonic, so that within and across measures, poorer behaviour is associated with poorer
maternal health. The size of the association between poor behaviour and mental health, very
poor physical health, and very low self-esteem are large. A child with a mother in very poor
health, in the highest quintile of the CCEI score or in the highest quintile of low self esteem is
on average likely to have a behavioural score around 3 points higher than a child whose mother
is in very good health, has the lowest CCEI score and with the highest self esteem. A
combination of all three would move the child almost a whole standard deviation. These are
very substantial effects. However, as noted when discussing the measures this is mother
reported data and whilst we looked at teacher reported data for a sub-sample at age 7 and found
similar patterns there is evidence of a lot of measurement error in these reports. In addition the
mothers self-esteem score did not appear as an important predictor of age 7 teacher reported
scores, this raises the prospect that the mother is reporting with bias where she has low selfesteem.
83

Table 6.4: Behaviour – coefficients on background variables when included individually
in basic specification (N = 9416)
1 2 3 4 5
Adj R2 0.0914 0.1026 0.0898 0.1439 0.0948
Mother's childhood and family background
Tenure of mother's childhood home
Insig
Mother's father present in childhood home Insig - - - -
Mother's mother's educational attainment Insig - - - -
Mother's father's educational attainment Insig - - - -
Childhood events score (base = 20 th to 100 th percentiles - - - -
Lowest quintile -0.82 ***
Mother's relationship with mother (base = lowest quartile) - - - -
Second quartile -0.43
Third quartile -1.74 *** - - - -
Highest quartile -2.86 *** - - - -
Home stability during childhood (base = fairly stable/unstable/very unstable) - - -
Very -0.80 *** - - -
Mother has history of truancy (base = yes) - - -
No -1.30*** - - -
Mother feels school was a valuable experience (base = not sure/generally not/no) - -
Yes very -2.55***
Yes generally -1.46 *** - - - -
Mother's physical health
Mother's physical health score (base = v high)
V low - 6.27 *** - - -
Low - 3.46 *** - - -
High - 1.72 *** - - -
Mother's social networks
Social networks score (base = highest third)
Middle third - - -0.94 *** - -
Highest third - - -1.66 *** - -
Social support score (base = highest third)
Middle third - - -1.86 *** - -
Highest third - - -3.68 *** - -
Mental health & psychological measures
Total CCEI score (base = lowest quintile)
2nd quintile - - - 1.94 *** -
3rd quintile - - - 3.00 *** -
4th quintile - - - 3.53 *** -
Highest quintile - - - 5.73 *** -
Locus of control score (base = Internal -
Medium - - - 0.71 *** -
External - - - 2.05 *** -
Self-esteem score (base=highest quintile)
Lowest quintile - - - 4.76 ***
2 nd quintile - - - 2.96 ***
3 rd quintile - - - 2.26 ***
4 th quintile - - - 1.37 ***
Interpersonal sensitivity measure subscore - - - Insig -
Family conflict
Experience of cruelty from partner - - - - 1.56 ***
Mother’s satisfaction with relationship (base = highest quintile)
Lowest quintile - - - - 5.19***
2 nd quintile - - - - 3.42***
3 rd quintile - - - - 3.10***
4 th quintile - - - - 1.59***
84

Table 6.5: Behaviour – coefficients on maternal background variables when included
simultaneously in basic specification, full and parsimonious specifications (N = 9416)
1 2
Adj R2 0.1654 0.1653
Mother's childhood and family background
Childhood events score (base = 20 th to 100 th percentiles
Lowest quintile -0.25 Dropped
Mother's relationship with mother (base = lowest quartile)
Second quartile 0.24 0.24
Third quartile -0.70 ** -0.69**
Highest quartile -1.16 *** -1.15***
Home stability during childhood (base = fairly stable/unstable/very unstable)
Very 0.15 Dropped
Mother has history of truancy (base = yes)
No -0.88 ** -0.90**
Mother feels school was a valuable experience (base = not sure/generally not/no)
Yes very -0.82 *** -0.79 **
Yes generally -0.52 ** -0.51 **
Mother's physical health
Mother's physical health score (base = v high)
V low 2.68 *** 2.68 ***
Low 1.16 *** 1.17 ***
High 0.67 ** 0.67 **
Mother's social networks
Social networks score (base = highest third)
Middle third -0.73 *** -0.73 ***
Highest third -1.16 *** -1.17 ***
Social support score (base = highest third)
Middle third -0.39 -0.40
Highest third -1.11 *** -1.12 ***
Mental health & psychological measures
Total CCEI score (base = lowest quintile)
2nd quintile 1.29 *** 1.30 ***
3rd quintile 1.97 *** 1.99 ***
4th quintile 2.01 *** 2.05 ***
Highest quintile 3.48 *** 3.58 ***
Locus of control score (base = Internal)
Medium 0.52 ** 0.51 **
External 1.36 *** 1.35 ***
Self-esteem score (base = highest quintile)
Lowest quintile 3.45 *** 3.43 ***
2 nd quintile 2.04 *** 2.02 ***
3 rd quintile 1.58 *** 1.57 ***
4 th quintile 0.99 *** 0.98 ***
Family conflict
Experienced cruelty from partner 0.30 Dropped
Mother’s satisfaction with relationship (base = highest quintile)
Lowest quintile 2.10 *** 2.17 ***
2 nd quintile 1.27 *** 1.29 ***
3 rd quintile 1.53 *** 1.55 ***
4 th quintile 0.75 ** 0.76 **
85

6.5 Robustness of Mental Health Measures
Tables 6.6 and 6.7 examine the robustness of the CCEI measure, which has been shown to be
an important determinant of both cognitive and behavioural outcomes. The behavioural score,
in particular, is strongly related to the CCEI score of the mother.
Table 6.6 shows that the association with the variable measured at any one period, is only well
defined if we slice the distribution into two – those in the top quintile and those not. But when
the whole period experience of low mental health is assessed, there is a clearer gradient: the
better health, on average, the higher the cognitive development of the child.
Table 6.7, on the other hand, shows that no matter when mental health is measured, there is a
very strong association between poorer mental health and poorer child behaviour. There is also
indication that the closer in time the mother experiences mental health to her child being age 5,
the stronger the association with poor behaviour. This is not true however of each of the
separate subscales. In summary, it appears that there is a very strong association between poor
mental health of the mother – whenever experienced during the first three years of the child’s
life - and behaviour.
6.6 Interactions with Mother’s Education
As in previous sections we explore whether there are interactions between mother’s childhood,
mental and physical health and relationship measures and her education. These F-test results
are reported in Table 6.8 and they test whether the additive representation of these measures
with mother’s education is valid or whether children of better educated mothers suffer more or
less when their mother’s health etc. is below the norm. The results, as before, tend to suggest
that the additive representation is broadly accepted. This suggests that there are no major
variations in how mother’s poor mental health, for example, impacts on children across
parental education groups. This, however, is not found for mothers’ physical health in the
behaviour equation. Here the test strongly rejects that the impact of poor maternal physical
health on children is the same for all education groups. Closer examination of the interaction
terms shows that lower educated mothers have substantially better (more negative scores) for a
given health level. So poor maternal physical health has a much larger adverse effect on
children’s behaviour scores among better educated mothers.
86

Table 6.6: Entry Assessment – Tests of robustness for CCEI measure, timing and composition of measure
Average
CCEI
Pregnancy
period First year
Second and
third year
Anxiety
subscore
Depression
subscore
Somatic
subscore
Adj R2 0.2442 0.2443 0.2432 0.2434 0.2444 0.2441 0.2456
Score (base = lowest quintile)
2nd quintile -0.56 -0.46 0.51 -0.36 -0.02 -0.18 0.65*
3rd quintile -0.69* -0.26 -0.09 -0.33 -0.38 -0.20 -0.19
4th quintile -0.61 -0.92** -0.28 -0.50 -0.26 -0.78** -0.31
Highest quintile -1.38*** -1.40*** -0.42 -0.95** -0.63 -1.09*** -1.08***
Table 6.7: Behaviour – Tests of robustness for CCEI measure, timing and composition of measure
Average
CCEI
Pregnancy
period First year
Second and
third year
Anxiety
subscore
Depression
subscore
Somatic
subscore
Adj R2 0.1232 0.0914 0.1125 0.1250 0.1099 0.1213 0.0982
Score (base = lowest quintile)
2nd quintile 2.47*** 1.94*** 1.94*** 2.58 *** 2.11*** 2.66*** 1.71***
3rd quintile 4.00*** 2.81*** 3.62*** 4.12 *** 3.01*** 3.78*** 2.93***
4th quintile 5.02*** 3.61*** 4.71*** 5.29 *** 4.47*** 4.95*** 4.12***
Highest quintile 7.89*** 5.51*** 6.86*** 7.77 *** 6.81*** 7.76*** 5.96***
87

Table 6.8: Summary of significance of interaction terms (family background variables *
maternal education)
Prob effect of family background measures
Family background measure
does not vary with educational group –
joint test of no variation within all family
background categories 1
Entry Assessment Behaviour
Tenure of mother’s childhood home 0.8516 -
Mother’s father present in childhood home 0.5185 -
Mother’s mother’s educational attainment 0.3586 -
Mother’s relationship with mother - 0.3135
Mother feels school was a valuable
0.5125 0.8089
experience
Mother’s physical health score - 0.0004
Social networks score - 0.3655
Social support score 0.8652 0.8198
Total CCEI score - 0.3533
Locus of control score 0.9656 0.4918
Self esteem score - 0.5832
Mother’s satisfaction with relationship with
partner
- 0.9138
88

7. Neighbourhood and Peer Groups
In this brief section we explore how to best represent information on the neighbourhood and
peer group of the child. In the next section we bring together the groups of indicators and
explore how they correlate with each other and with measures of family income and
background.
Children do not grow up in isolation within the home or school but interact with other people
and especially with the children they share facilities with. This is particularly likely to be
important when the child is in extended contact with children whilst at a pre-school. The other
children a child interacts with are often described as their peer group. It is hard to distinguish the
extent to which a child is influenced by their neighbourhood or peer group from whether it
reflects some (unobserved) aspect of the parents who have been sorted into neighbourhoods or
chosen a particular pre-school provider. However, important information has come to light from
the Moving to Opportunity experiments in the US (see Katz, Kling and Leibman 2001, Ludwig,
Duncan and Hirschfield, 2001 and Ludwig, Ladd and Duncan, 2001). Here families from poor
neighbourhoods are randomly selected into one of three populations. First, there are those given
financial assistance with rents to move to a rental unit in a more affluent neighbourhood. 9 If
they did not move they received nothing. A second group got rent support but could move to
any neighbourhood. The third group received no help in moving from the deprived
neighbourhood. So the treatment is that families receive financial support to meet higher
housing costs associated with moving to more affluent (and high rent) areas, provided they
make the move.
These studies provide crucial evidence of how neighbourhoods and peer groups might influence
children’s educational outcomes as moving to a better neighbourhood occurs for reasons that are
unrelated to the characteristics of the family. Importantly, these moves were not associated with
increases in employment or earnings among adults, so the effects observed are operating purely
through neighbourhood change. The results suggest that moving neighbourhood (which goes
hand-in-hand with changing school and peer group for most children) are associated with
marked improvements in behavioural problems and school test scores and, for school age
children, a reduction in the number of arrests for violent crime. The children being assessed
under these experiments are aged from 5 to 15 and hence may not reflect the effects of
9 The rent assistance was in the form of Section 8 housing vouchers which is rent assistance programme in the US
which has some parallels with Housing Benefit in the UK but is more restricted in its availability.
90

neighbourhood on pre-school children but they do provide powerful evidence of such effects for
older children.
As ALSPAC is drawn from the former area of Avon, most children are growing up in the same
neighbourhoods within that area and indeed are attending the same schools and pre-schools. We
can thus merge information on the neighbourhoods the children live in and look at the
characteristics of many of the children the child shares facilities with.
7.1 Neighbourhood and Peer Group Measures
First, we have matched into ALSPAC information at ward level from the Index of Multiple
Deprivation IMD (administered by the Office of the Deputy Prime Minister). The overall index
is constructed from six component measures covering employment, health, education, income,
housing and access to services. There is also a measure of child poverty at the ward level that is
not incorporated into the index itself. We explore which of these dimensions is associated with
early childhood learning deficits. The measures are very strongly related, as shown in Table 7.1.
Hence they may be best represented as a single composite index or one measure may clearly
dominate in its predictive power. We will therefore explore which dimensions of deprivation are
most strongly correlated with pre-school age child attainment. It is hard to say more about
exactly what drives any observed relationship.
Table 7.1 Correlations between Domains of the Index of Multiple Deprivation in Avon
area
Total index of
multiple deprivation
Education domain
score
Access domain
score
Income domain
score
Employment
domain score
Health domain
score
Housing domain
score
Poverty domain
score
Total index
of multiple
deprivation
1.0000
Education
domain
score
0.8327 1.0000
Access
domain
score
-0.4234 -0.3655 1.0000
Income
domain
score
0.9784 0.7761 -0.4663 1.0000
Employment
domain score
0.9510 0.6762 -0.4985 0.9508 1.0000
Health
domain
score
0.8744 0.7012 -0.4866 0.8705 0.8905 1.0000
Housing
domain
score
0.8030 0.7131 -0.4884 0.7750 0.7277 0.6697 1.0000
Poverty
domain
score
0.9600 0.8070 -0.4408 0.9768 0.9202 0.8452 0.7735 1.0000
Second, as part of the ‘Focus at 7’ face to face interviews with mother and child, the mother was
asked to document childcare providers used from the age of 3. Importantly this included the
91

name of the provider as well as the broad type of care and number of sessions attended. In many
cases therefore we can observe many children attending the same pre-school provider
immediately prior to school entry. From this then we can get a measure of attainment among the
child’s pre-school peer group. We were concerned that many children would go on to be
assessed by the same teacher for the EA score and that any idiosyncratic teacher effects in
scoring would muddy this measure of the pre-school peer group. Such teacher effects should be
just random measurement error over the whole population. But within the same school this
practice would give the impression that the peer group was very influential whereas in reality it
was just teacher bias (a teacher scoring the children higher or lower than average). So we
construct our measure of the peer group from those who attended the same pre-school but did
not attend the same school. These observations are thus independent of the child. Using these
observations we, in the first instance, simply average the EA score. Where a child attends more
than one provider we average across the different providers weighting by the number of sessions
attended. This peer group measure will capture a range of influences from the natural attainment
of the other children, their family background etc. and any common influence of the pre-school.
It thus includes any effects of the quality of the pre-school provider.
We can go further, though, in separating influences. We predict the other children’s attainment
using the general model containing all family background and mediating influences provided in
the data, except the nature of the pre-school provider. This is then a measure of the extent to
which the children forming the peer group are from more affluent, better educated families
which read to their children etc., reflecting how these factors influence attainment in our model.
This measure therefore does not contain any element of the quality of pre-school provider as it
is based only on family characteristics of the children attending it. The unexplained residual
from our estimates then reflects the average of the variation in attainment across children in the
peer group that is not explained by the child’s background. This will cover the idiosyncratic
component for each individual child averaged across the peer group, which will be influenced
by the quality of the common attendance of the same pre-school provider. It will also reflect
any measurement error in the data. Large amounts of measurement error will make it hard to
observe childcare quality for small samples attending each provider.
Table 7.2 gives a flavour of the information this provides showing how the average EA scores
vary across types of pre-school provider. So, for example, children attending private nurseries
score well above the mean of 100 on average (102.77) but this is fully predicted by the
background and mediating behaviours of the families and the residual term is close to 0. This
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suggests that children leaving these nurseries may be performing well (as shown in the section
on childcare types) due to the common high quality of their family background, not because of
the type of nursery attended. The reverse story applies to LEA nurseries. In addition, though, the
table shows that there is considerable variation across providers in this residual unexplained
component which may suggest that there are good and bad providers within each sector.
Table 7.2 Peer Group EA Scores by Pre-school Provider Type
Variable
No. of
observations
Mean
Standard
Deviation
10 th
percentile
90 th percentile
Nursery Class
Average EA score of peers 567 100.44 4.32 94.51 105.88
Predicted part 567 100.73 2.59 97.37 103.75
Residual part 567 -0.21 4.00 -4.31 5.54
LEA nursery
Average EA score of peers 391 99.16 3.60 94.64 103.52
Predicted part 391 98.96 1.89 96.50 101.35
Residual part 391 0.26 3.06 -3.23 3.55
Private nursery
Average EA score of peers 516 102.77 3.69 97.92 105.35
Predicted part 516 102.67 2.55 99.22 105.89
Residual part 516 -0.07 2.75 -3.50 2.95
Playgroup
Average EA score of peers 1935 100.68 4.44 94.80 106.06
Predicted part 1935 100.73 2.58 97.47 104.15
Residual part 1935 -0.24 3.65 -4.84 3.58
Nursery (type undefined)
Average EA score of peers 667 101.54 4.91 93.57 107.22
Predicted part 667 101.66 2.87 97.57 106.06
Residual part 667 -0.46 3.90 -5.84 4.30
Other
Average EA score of peers 38 97.50 4.29 90.52 101.18
Predicted part 38 97.25 2.46 92.62 98.74
Residual part 38 0.32 2.75 -4.14 2.15
When looking at behavioural outcomes we employ the same technique but use the behaviour
scores of the peer group rather than their EA test results.
7.2 Correlations Between Neighbourhood and Peer Group Variables and Child Outcomes
Table 7.3 shows how these peer group measures correlate with cognitive attainment and Table
7.4 shows how they correlate with behaviour. Column 1 of Table 7.3 shows the effect of the raw
peer group measure of average EA attainment of other children at the same provider. The results
suggest that the child is doing slightly better, given their background family factors, if attending
a provider with a very high attaining peer group. But among lower attaining groups there is no
variation.
93

Column 2 introduces the IMD as a single combined index. This shows a strong correlation with
attainment, such that a higher multiple deprivation score is associated with somewhat lower
attainment. Columns 3 and 4 show the elements of the index separately and also include the
additional ward level measure of child poverty (Column 3 includes the total index as well).
What is striking is that the ward level indicator with the strongest correlation with attainment is
the Education Domain. This domain consists of 6 indicators:
• Proportion of Working Age adults with no qualifications (LFS)
• Children aged 16+ not in full-time education
• Proportion of 17-19 year olds not applying to HE
• KS2 primary school performance
• Primary School Children with English as an additional language
• Primary School Absenteeism
Hence the indicator is derived from current school age performance, post-school staying on in
education and adult education levels. Whilst primary school age children could be older siblings
of ALSPAC children, the rest of the measure reflects the wider educational attainment in the
population in the ward. This appears strongly correlated with pre-school attainment of children.
If Educational Domain is excluded the Employment Domain becomes marginally significant.
Column 5 of Table 7.1 reports the parsimonious specification using only the education domain.
Moving from the 10 th percentile of education deprivation domain to the 90 th results in a
predicted decrease in attainment of 2.49 points. This is a reasonably large effect compared to
others we have seen in this study.
Columns 6 to 8 of Table 7.3 explore the implications of decomposing the peer group effect into
that part which reflects the family background and mediating influences of the peers, predicted
by our model, and the unexplained component, which will include any influence of the preschool.
Note that the predicted element is large and positive. Attending a pre-school that
contains pupils from family backgrounds that produces high attainment (as defined by our
model) is highly beneficial to a child’s outcomes. However, the unexplained part - the random
variation in children or characteristics of the provider - is not strongly correlated with the child’s
attainment. Indeed, the point estimates are negative. Hence we find strong evidence for the
importance of attending pre-schools that are attended by children from family backgrounds
associated with high attainment. We cannot find any clear evidence of a pre-school performance
factor that is common to all children attending. Note the peer group effects reduce the size of the
94

neighbourhood effect somewhat, suggesting that peer group influences drive part of the
observed neighbourhood effects.
Table 7.3: The effects of neighbourhood on Entry Assessment
(1) (2) (3) (4) (5) (6) (7) (8)
Total index of - -0.054*** 0.101 - - - - -
multiple deprivation (0.010) (0.096)
Education domain - - -1.482*** -1.098*** -1.006*** -0.865*** -1.043*** -0.859***
score (0.446) (0.253) (0.145) (0.147) (0.143) (0.147)
Access domain - - -0.534 -0.319 - - - -
score (0.347) (0.280)
Income domain - - -0.129 -0.056 - - - -
score (0.111) (0.085)
Employment
- - -0.073 0.066 - - - -
domain score (0.172) (0.108)
Health domain - - 0.125 0.043 - - - -
score (0.413) (0.405)
Housing domain - - 0.005 0.122 - - - -
score (0.307) (0.286)
Child poverty index - - 0.022 0.009 - - - -
score (0.048) (0.047)
Average EA score of peers (base = lowest quintile)
2 nd quintile -0.323 -0.384 -0.355 -0.359 -0.349 - - -
(0.500) (0.499) (0.499) (0.499) (0.498)
3 rd quintile -0.091 -0.313 -0.310 -0.326 -0.324 - - -
(0.497) (0.497) (0.497) (0.497) (0.496)
4 th quintile 0.034 -0.275 -0.410 -0.396 -0.419 - - -
(0.507) (0.509) (0.512) (0.512) (0.509)
Highest quintile 1.831*** 1.582*** 1.342*** 1.359*** 1.402*** - - -
(0.511) (0.512) (0.515) (0.515) (0.513)
Average EA score of peers – predicted value (base = lowest quintile)
2 nd quintile - - - - - 0.146 - 0.347
(0.499) (0.509)
3 rd quintile - - - - - 1.178** - 1.329***
(0.504) (0.509)
4 th quintile - - - - - 2.166*** - 2.333***
(0.509) (0.516)
Highest quintile - - - - - 2.283*** - 2.377***
(0.532) (0.535)
Average EA score of peers – residual part (base = lowest quintile)
2 nd quintile - - - - - - -1.053** -1.118**
(0.498) (0.503)
3 rd quintile - - - - - - -0.542 -0.693
(0.498) (0.505)
4 th quintile - - - - - - -0.757 -0.972*
(0.497) (0.503)
Highest quintile - - - - - - -0.595 -0.757
(0.496) (0.497)
Adj R2 0.2476 0.2518 0.2543 0.2542 0.2547 0.2569 0.2527 0.2572
All regressions include basic demographic controls.
95

Table 7.4: The effects of neighbourhood on Behaviour
(1) (2) (3) (4) (5) (6) (7) (8)
Total index of multiple - -0.012 -0.051 - - - - -
deprivation (0.008) (0.075)
Education domain score - - 0.185 0.004 - - - -
(0.336) (0.204)
Access domain score - - -0.168 -0.278 - - - -
(0.268) (0.214)
Income domain score - - 0.037 -0.000 - - - -
(0.084) (0.064)
Employment domain - - -0.045 -0.111 - - - -
score (0.128) (0.085)
Health domain score - - -0.091 -0.073 - - - -
(0.316) (0.315)
Housing domain score - - -0.081 -0.156 - - - -
(0.251) (0.225)
Child poverty index - - 0.024 0.031 - - - -
score (0.037) (0.035)
Average behaviour score of peers (base = lowest quintile)
2 nd quintile 0.195 0.210 0.182 0.187 0.195 - - -
(0.458) (0.459) (0.459) (0.459) (0.458)
3 rd quintile 0.011 0.033 -0.036 -0.025 0.011 - - -
(0.459) (0.459) (0.463) (0.462) (0.459)
4 th quintile 0.672 0.706 0.646 0.654 0.672 - - -
(0.460) (0.461) (0.463) (0.463) (0.460)
Highest quintile 0.770* 0.828* 0.746 0.756 0.770* - - -
(0.463) (0.464) (0.469) (0.469) (0.463)
Average behaviour score of peers – predicted value (base = lowest quintile)
2 nd quintile - - - - - -0.806* -0.832*
(0.460) (0.460)
3 rd quintile - - - - - -1.088** -0.995**
(0.464) (0.465)
4 th quintile - - - - - -0.171 0.005
(0.469) (0.470)
Highest quintile - - - - - -0.308 -0.249
Average behaviour score of peers – residual part (base = lowest quintile)
(0.471) (0.475)
2 nd quintile - - - - - - -0.919** -0.965**
(0.458) (0.459)
3 rd quintile - - - - - - 1.119** 1.164**
(0.458) (0.462)
4 th quintile - - - - - - -0.410 -0.350
(0.458) (0.463)
Highest quintile - - - - - - 0.716 0.665
(0.458) (0.460)
Adj R2 0.0641 0.0642 0.0639 0.0640 0.0641 0.0644 0.0662 0.0666
All regressions include basic demographic controls.
Table 7.4 repeats this analysis for behaviour. The measures of local ward level deprivation are
all individually and collectively insignificant, suggesting no neighbourhood influences on early
96

child behaviour. But the peer group behaviour score is very weakly associated with outcomes
such that a very high behaviour score is correlated weakly with that for the child. Decomposing
this into the predicted and residual components leads to no clear patterns. Hence there is little
evidence here that neighbourhood and peer group influences the behaviour of young children.
97

8. Combined Analysis
The approach in this last section is to examine how the introduction of the alternative groups of
proximal variables studied in the previous sections acts as transmission routes for the more
distal indicators - income, parental education, lone parent status etc - on the attainment and
behaviour outcomes. The intention is to see whether these behaviours are the route by which
background family circumstances affect outcomes. Causality cannot be proven, but if, for
example, we observe that well educated parents appear to be raising child educational
attainment through engaging in more reading and teaching activity then this appears to be a
plausible causal chain. Likewise if the income effect is coming from reduced books or toys in
the home or less childcare, outings and the like, then it seems reasonable to view these as the
impact of reduced financial circumstances. However, there will be a lot of grey areas where
causality is at best tentative. We then are assessing which of the proximal influences measured
in ALSPAC are associated with educational attainment and behaviour outcomes directly and to
what extent they appear to be the routes through which dimensions of family background are
operating.
8.1 Summary of Influences
Table 8.1 lists the variable groupings that we are going to explore as potential routes by which
distal factors are working. These groupings cover pre-school childcare, parenting behaviour,
aspects of the home environment and out-of-home activities, mother’s family background,
mother’s health and social networks and neighbourhood and peer group. Income has a dual role
here in that we explore how the proximal variables might be routes by which income works but
also we assess whether income is a route through which lone parenthood or parental education
operate.
98

Table 8.1: Groups of variables used as controls in Entry Assessment regressions
Basic
demographics
Mother’s highest
qualification
Partner’s highest
qualification
Lone parent
status
Income Childcare Parenting
Log average
weekly net
income
Financial
difficulties
pre-birth
Care by partner
pre-age 2
Care by
friend/relative
pre-age 2
Care by paid
person pre-age
2
Maternal
reading score
Teaching score
18 month TV
score
Outings Scores &
Home
Environment
Department store
outings score
Library outings
score
Book score
Mother’s childhood
and family
background
Tenure of mother’s
childhood home
Mother’s father
absent from
childhood home
Mother’s mother’s
highest qualification
Maternal health,
attitudes and
social networks
Social support
score
Locus of control
score
Neighbourhood
Education
domain
deprivation score
Average EA
score of peers –
predicted
component
Average EA
score of peers –
residual
component
Mother’s age at
birth
Centre-based
care pre-age 2
Breastfeeding
Toy score
Mother has a history
of truancy
Ethnicity
Nursery class
age 3/ 4
Mother feels school
was a valuable
experience
Gender
LEA nursery
school age 3/ 4
Birth weight
Private day
nursery age 3/ 4
Special care unit
at birth
Nursery (type
undefined) age
3/ 4
Younger siblings
by 47 months
Playgroup age
3/ 4
Older siblings
Other centrebased
care age
3/ 4
Cohort year
Partner’s
employment at
47 months
8.2 How do Parental Education, Lone Parenthood, mother’s age, ethnicity and siblings
impact on child development?
This section begins the substantive discussion of how these proximal factors suggest family
background influences child development. So, for example, one question of particular interest is
whether more educated parents tend to provide more cognitive stimulation for their children. It
also assesses how the proximal factors we study here are working independently of others or
how they are correlated.
Table 8.2 shows how these groups of proximal variables reduce the observed correlation of
basic demographics (family background characteristics) with attainment. Each group is entered
separately and then they are all combined. This gives a sense of the impact of each variable
99

grouping. Column 1 thus shows a basic regression without these proximal controls, column 2
introduces family income and columns 3-8 then introduce the groups of controls considered
above, whilst column 9 includes all the measures together. Our focus is to examine whether
family characteristics become less important as other proximal factors are added and to get a
sense of the routes by which family background operates to influence attainment. So Column 1
of Table 8.2 has the set of background factors described in section 2 whilst Column 9 has
introduced the full set of routes of influence we explore. A comparison between these two
columns suggests the extent to which each background factor is related to the EA score through
these mechanisms. At the end of this section we show more formal decompositions of the
contributions the observed mediating factors play in acting as routes by which parental
education (and income) influence outcomes.
8.2.1 Parental Education
This comparison for parental education shows the coefficients are reduced substantially. The
raw gap between attainment of children with the least and most educated mothers was 5.5 points
or ½ a standard deviation. Conditioning on our mediating influences reduces this to 2.4 points
(44% of the original value). So our groups of mediating influences can explain a little over half
of the effect of parental education on attainment. We have already assessed whether better
education parents do these mechanisms more effectively and the evidence suggests not. So the
observed decline in the strength of the relationship between parental education and child
attainment as we add in proximal controls suggests the routes by which parental education
operate.
Looking at the impact of each group in turn suggests that parenting behaviour and the home
environment measures are the strongest mechanisms through which parental education operates.
However, family income is also a substantive route through which parental education
(especially partner’s education) impacts on attainment, as are the neighbourhood and peer
group. The simple correlations in Table 3.1 (also see Appendix A3) showed that better educated
parents engaged in reading to their children more and their children watched less TV especially
at age 3. They also provided a home with higher book and toy scores and engaged in more trips
to the library. These are aspects of behaviour and the home environment shown to influence
child attainment. Pre-school childcare is not a major route by which well-educated parents
increase their children’s attainment. Mother’s own childhood events and her locus of control
and social networks are more important in explaining the impact of low education relative to
middle education.
100

8.2.2 Lone Parenthood
Lone parenthood goes from being a marginally negative influence on child outcomes to a
marginally positive one when these routes of influence are included. However, lone parenthood
is not a statistically significant influence on early attainment in any specification. Low income
and low book and toy scores are the main factors which turn around the point estimates. One
other interesting feature of these results is that the lone parent coefficients are left broadly
unchanged once parenting behaviour controls are introduced. This would suggest that children
of lone parents are not doing less well because of parenting behaviours, where time constraints
might be expected to bite. The main conclusion is that children of lone mothers are not
performing worse than their peers, once other factors are conditioned on (especially their age
and income). But as noted in Section 2 our sample of lone parents is not representative and so
care needs to be exercised here.
8.2.3 Mother’s Age
Teen motherhood has an especially large negative association with the child’s cognitive
attainment. The proximal routes explored can explain around 40% of this attainment deficit,
with family income being the most substantive route. But all factors make some contribution.
The positive benefits of older motherhood are much better explained by the observed mediating
factors, with parenting behaviour and income being the major two influences.
8.2.4 Ethnic Minorities
Children from non-white families do slightly less well on entry to school than white children.
There are too few observations among these communities to allow for more detailed breakdown
by ethnicity. About a third of this can be explained by observed differences in the groups of
more proximal influences used here. The biggest influence is in the home environment (book
and toy scores) and outings measures. Income also plays a role. Parenting behaviour, maternal
employment and mental health and social support are unimportant as routes explaining the gap
between non-whites and whites.
101

Table 8.2: Estimated effects of basic demographics on Entry Assessment, various
specifications (N = 5010)
(1) (2) (3) (4) (5) (6) (7) (8) (9)
Mother’s highest qualification (base = vocational/O-level)
CSE/none -2.150*** -1.984*** -2.014*** -1.744*** -1.683*** -1.710*** -1.864*** -1.924*** -0.991**
(0.398) (0.398) (0.397) (0.396) (0.397) (0.406) (0.403) (0.395) (0.404)
A-level 1.278*** 1.057*** 1.177*** 0.771** 0.893*** 0.915*** 1.111*** 1.012*** 0.110
(0.320) (0.321) (0.322) (0.320) (0.320) (0.328) (0.322) (0.318) (0.329)
Degree 3.314*** 2.928*** 2.953*** 2.752*** 2.686*** 2.740*** 3.085*** 2.847*** 1.442***
(0.484) (0.487) (0.492) (0.486) (0.485) (0.507) (0.487) (0.481) (0.514)
Partner’s highest qualification (base = vocational/O-level)
CSE/none -1.657*** -1.460*** -1.618***
(0.373) (0.374) (0.372)
A-level 0.560* 0.459 0.461
(0.331) (0.331) (0.329)
Degree 2.546*** 2.176*** 2.197***
(0.449) (0.452) (0.451)
Lone parent status (base = never lone parent)
Intermittently, with
partner at 47 months
-0.021
(0.829)
Intermittently, no -1.003
partner at 47 months (0.637)
Since birth -1.507
(1.273)
Mother’s age at birth (base = 25-29)
1 -2.153*** -2.045***
(0.759) (0.756)
Older siblings (base = none)
1 -1.477***
(0.328)
2
-3.063***
(0.438)
3+ -4.827***
(0.648)
-1.396***
(0.328)
-2.974***
(0.437)
-4.660***
(0.648)
0.089
(0.830)
-0.873
(0.638)
-1.078
(1.282)
-3.617***
(0.975)
-0.861**
(0.387)
0.540*
(0.303)
1.003**
(0.441)
-1.829***
(0.686)
3.519***
(0.248)
-2.597***
(0.665)
-0.831***
(0.259)
-0.434
(0.550)
-0.153
(0.313)
-1.888**
(0.757)
-1.351***
(0.334)
-2.898***
(0.444)
-4.351***
(0.654)
Partner’s employment status at 47 months (base = in work)
Not in work -1.132** -0.385 -1.013*
(0.533) (0.546) (0.532)
-1.526***
(0.368)
0.447
(0.326)
2.235***
(0.445)
0.119
(0.818)
-0.885
(0.630)
-1.165
(1.255)
-3.756***
(0.968)
-0.892**
(0.384)
0.461
(0.301)
0.663
(0.438)
-2.090***
(0.676)
3.359***
(0.247)
-2.761***
(0.660)
-0.810***
(0.257)
-0.239
(0.545)
-0.263
(0.309)
-1.912**
(0.749)
-0.716**
(0.332)
-2.246***
(0.440)
-3.868***
(0.646)
-0.947*
(0.526)
-1.436***
(0.370)
0.407
(0.328)
2.301***
(0.446)
0.193
(0.822)
-0.761
(0.632)
-0.874
(1.263)
-3.856***
(0.971)
-0.908**
(0.385)
0.569*
(0.302)
0.910**
(0.437)
-1.633**
(0.680)
3.461***
(0.247)
-2.725***
(0.663)
-0.802***
(0.259)
-0.310
(0.547)
-0.178
(0.311)
-2.164***
(0.753)
-1.377***
(0.343)
-2.871***
(0.450)
-4.379***
(0.657)
-0.820
(0.530)
-1.485***
(0.375)
0.487
(0.330)
2.394***
(0.450)
0.202
(0.828)
-0.834
(0.640)
-1.114
(1.272)
-3.664***
(0.981)
-0.834**
(0.389)
0.693***
(0.305)
1.155***
(0.444)
-2.075***
(0.687)
3.544***
(0.249)
-2.795***
(0.667)
-0.761***
(0.261)
-0.326
(0.551)
-0.179
(0.313)
-2.077***
(0.759)
-1.398***
(0.328)
-2.966***
(0.438)
-4.555***
(0.649)
-1.034*
(0.533)
-1.573***
(0.373)
0.535
(0.330)
2.371***
(0.449)
0.238
(0.830)
-0.714
(0.639)
-0.836
(1.287)
-3.857***
(0.977)
-0.871**
(0.388)
0.626**
(0.304)
1.107**
(0.440)
-2.060***
(0.683)
3.535***
(0.249)
-2.680***
(0.667)
-0.840***
(0.260)
-0.375
(0.551)
-0.222
(0.313)
-2.177***
(0.757)
-1.410***
(0.328)
-2.953***
(0.438)
-4.648***
(0.647)
-0.934*
(0.533)
-1.481***
(0.370)
0.426
(0.328)
2.022***
(0.448)
0.115
(0.822)
-0.844
(0.632)
-1.064
(1.263)
-3.601***
(0.971)
-0.781**
(0.385)
0.383
(0.303)
0.785*
(0.438)
-1.683**
(0.679)
3.532***
(0.247)
-2.681***
(0.663)
-0.821***
(0.258)
-0.212
(0.547)
-0.226
(0.310)
-1.829**
(0.753)
-1.353***
(0.326)
-2.893***
(0.434)
-4.200***
(0.644)
-0.884*
(0.529)
-1.080***
(0.368)
0.095
(0.323)
1.183***
(0.449)
1.047
(0.830)
0.408
(0.679)
1.026
(1.299)
-2.412**
(0.967)
-0.430
(0.385)
0.221
(0.300)
0.411
(0.440)
-1.416**
(0.679)
3.343***
(0.244)
-2.510***
(0.652)
-0.736***
(0.254)
-0.169
(0.538)
-0.227
(0.307)
-1.640**
(0.744)
-0.675*
(0.349)
-2.049***
(0.455)
-3.125***
(0.661)
-0.071
(0.538)
Adjusted R-squared 0.2381 0.2429 0.2486 0.2609 0.2538 0.2433 0.2424 0.2550 0.2889
Notes
1. Controls for each specification are specified overleaf.
102

Table 8.2: (continued) Controls included in Estimated effects of basic demographics on
Entry Assessment, various specifications
Specification (1) (2) (3) (4) (5) (6) (7) (8) (9)
Controls included
X
Income X X
Childcare X X
Parenting X X
Outings & home
environment
Maternal background X X
Maternal health etc. X X
Neighbourhood X X
X
X
8.2.5 Gender, Birth Weight and Siblings
Coefficients on low birth weight, gender of the child and the presence of younger siblings are
not greatly affected by the introduction of the groups of proximal variables. The coefficients on
older siblings are substantially reduced by inclusion of parenting behaviours, suggesting that the
influence of siblings is to slow child development by reducing parental inputs to the child,
especially teaching and reading.
8.2.6 Partner’s Employment Status
The small negative effect from a non-working partner at 47 months is fully explained by the
mediating factors. The dominant route by which this is operating is family income. So the
modest negative effects of an absent (lone parenthood) and a workless father seem to operate
almost entirely through income.
8.3 Which Influences are Important?
We explore next which particular dimensions of the set of proximal influence variables remain
important once we condition on the full set of influences described in Table 8.1. We follow the
same logic as in section 8.2 where we add each set of influences in turn and assess which
influences remain important. For example, parenting and childcare may vary systematically
together. Once parenting behaviour is conditioned upon, childcare may become less relatively
important than when its impact is measured in isolation.
8.3.1 Childcare
Table 8.3 shows that the broad pattern of the results for care up to age 2 discussed above are not
greatly affected by other influences considered here. However, controlling family income does
reduce the positive effects of nursery centres. The most important change in estimated impact of
pre-school entry provider comes after controlling for the neighbourhood and peer group
103

(column 7). The peer group is defined on the basis of the pre-school attended. The results
suggest that much of the positive effects of private nurseries and all the adverse effects of LEA
nurseries are driven by peer group composition. This is also partly true for the other (probably
specialist) care. Private care up to age 2 and private care prior to school entry and LEA nursery
care become insignificant when all factors are conditioned upon (column 8). So the initially
apparent beneficial association of attending a private nursery prior to school entry comes from
the association with the child coming from a more affluent family with more home teaching,
books, toys, outings etc and from attending a pre-school with similar high attaining children. So
once we condition on the peer group there is no evidence that private nurseries are
outperforming Nursery classes. In addition, LEA nurseries are performing poorly solely because
of the concentration of children from deprived backgrounds in this pre-school setting.
The results suggest that conditional on all other mediating influences and background
characteristics:
• Limited hours of care by partner up to age 2 is modestly beneficial to child development
(this could well be outside the partners working hours)
• Extended care up to age 2 by friends, grandparents and other relatives is modestly
harmful.
• Nursery care (in school class or private setting) when aged 3-4 is modestly beneficial to
children’s attainment on entry to school.
• Following earlier analysis in Section 5, there is no evidence that full-time Nursery
exposure at 3 or 4 is more beneficial than part-time.
• There is no evidence that attending a Nursery is more beneficial for those with less
educated mothers. (Note that the lack of assessment of quality of childcare means these
results are less reliable than other studies of the influence of quality childcare on
development such as the EPPE project, see Sylva et al. 2004.)
104

• Table 8.3: Estimated effects of childcare arrangements on Entry Assessment,
various specifications (N = 5010)
(1) (2) (3) (4) (5) (6) (7) (8)
Childcare pre-age 2
Used partner 5-19 hours per 0.629* 0.624* 0.681** 0.628* 0.637* 0.565 0.623* 0.616*
week (0.346) (0.345) (0.341) (0.343) (0.345) (0.345) (0.344) (0.340)
Used partner 20+ hours per -0.008 0.005 0.030 -0.027 0.028 -0.063 0.092 0.024
week (0.345) (0.344) (0.341) (0.342) (0.345) (0.344) (0.343) (0.340)
Used friend/relative 5-19 -0.235 -0.255 -0.211 -0.200 -0.242 -0.253 -0.197 -0.135
hours per week (0.316) (0.316) (0.312) (0.313) (0.316) (0.315) (0.314) (0.311)
Used friend/relative 20+
-
hours per week
-0.818** -0.897*** -0.879*** -0.760** -0.868** 0.896*** -0.862** -0.769**
(0.341) (0.340) (0.337) (0.338) (0.341) (0.340) (0.339) (0.336)
Used paid person 5-19 hours -0.117 -0.297 -0.395 -0.270 -0.334 -0.241 -0.327 -0.389
per week (0.473) (0.474) (0.468) (0.470) (0.474) (0.473) (0.471) (0.466)
Used paid person 20+ hours 0.599 0.258 0.348 0.339 0.220 0.291 0.178 0.290
per week (0.399) (0.404) (0.400) (0.401) (0.404) (0.404) (0.402) (0.399)
Used centre-based care 5-19 0.234 0.100 0.079 0.206 0.085 0.146 0.073 0.084
hours per week (0.608) (0.608) (0.600) (0.603) (0.607) (0.606) (0.605) (0.597)
Used centre-based care 20+ 1.604* 1.320 1.216 1.405* 1.195 1.232 1.384* 1.135
hours per week (0.836) (0.836) (0.826) (0.829) (0.836) (0.835) (0.835) (0.825)
Childcare age 3 to 4
Nursery class 0.693* 0.775* 0.812** 0.746* 0.784** 0.762* 1.044** 0.982**
(0.399) (0.399) (0.394) (0.396) (0.399) (0.399) (0.408) (0.403)
LEA nursery -1.233** -1.106** -1.127** -1.159** -1.031** -1.066** -0.198 -0.271
(0.486) (0.485) (0.479) (0.481) (0.486) (0.485) (0.514) (0.508)
Private day nursery 1.544*** 1.400*** 1.281*** 1.288*** 1.287*** 1.393*** 0.817* 0.654
(0.429) (0.430) (0.424) (0.427) (0.430) (0.429) (0.445) (0.439)
Playgroup 0.421 0.377 0.374 0.258 0.307 0.326 0.135 0.044
(0.340) (0.340) (0.335) (0.337) (0.340) (0.339) (0.341) (0.337)
Nursery (type undefined) 1.150*** 1.130*** 1.186*** 1.148*** 1.103*** 1.131*** 1.089*** 1.122***
Other
(0.358) (0.358) (0.353) (0.355) (0.358) (0.358) (0.364) (0.359)
-
-3.674*** -3.529*** -2.996*** -3.636*** -3.501*** 3.569*** -2.610** -2.381**
(1.111) (1.109) (1.096) (1.099) (1.108) (1.108) (1.115) (1.101)
Adjusted R-squared 0.2486 0.2519 0.2735 0.2664 0.2552 0.2550 0.2611 0.2889
Controls included
Basic demographics X X X X X X X X
Income X X X X X X X
Parenting X X
Outings & home
environment
Maternal background X X
Maternal health etc. X X
Neighbourhood X X
X
X
8.3.2 Parenting Behaviour
Table 8.4 shows that the broad pattern of parenting behaviour results remain unchanged when
other influences are conditioned on. The impact of TV watching and breastfeeding are reduced
substantially in magnitude. Conditioning on family income is important in reducing the
importance of these behaviours and the home environment (books and toys) and outings are
105

important in reducing the impact of TV watching, suggesting these are partial substitutes. TV is
used more by low-income families perhaps because it is cheap entertainment. Teaching
behaviour is almost completely unaffected by this conditioning and remains the most important
influence of measured attainment at 5.
Table 8.4: Estimated effects of parenting behaviours on Entry Assessment, various
specifications (N = 5010)
(1) (2) (3) (4) (5) (6) (7) (8)
Maternal reading score (base = high)
Very low - - - - - -
2.427*** 2.367*** 2.353*** 1.691*** 2.291*** 2.237*** -2.281*** -1.584***
(0.541) (0.540) (0.538) (0.556) (0.540) (0.541) (0.535) (0.553)
Low - - -
- -
1.418*** 1.464*** 1.472*** -1.048** 1.445*** 1.389*** -1.393*** -0.999**
(0.486) (0.484) (0.483) (0.491) (0.486) (0.485) (0.480) (0.488)
Medium -0.627* -0.642** -0.630* -0.436 -0.651** -0.603* -0.576* -0.409
Teaching score (base =
high)
Very low -
3.846***
(0.326) (0.325) (0.324) (0.329) (0.326) (0.325) (0.323) (0.327)
-
3.793***
-
3.808***
-
3.550***
-
3.861***
-
3.749*** -3.812*** -3.654***
(0.576) (0.574) (0.573) (0.579) (0.574) (0.574) (0.570) (0.576)
Low - - - - - -
2.036*** 2.059*** 2.138*** 1.982*** 2.049*** 2.005*** -2.077*** -2.022***
(0.453) (0.452) (0.451) (0.457) (0.452) (0.452) (0.449) (0.453)
Medium - - - - - -
0.979*** 0.999*** 1.084*** 1.031*** 1.011*** 0.998*** -1.020*** -1.108***
(0.296) (0.295) (0.295) (0.296) (0.295) (0.296) (0.293) (0.295)
18 month TV score (base = 0-2 hours per week)
3 –5 - -
0.896*** 0.816*** -0.678** -0.690** -0.745** -0.775** -0.684** -0.376
(0.316) (0.316) (0.315) (0.316) (0.316) (0.315) (0.314) (0.316)
6 - - - - - -
1.877*** 1.761*** 1.562*** 1.530*** 1.587*** 1.675*** -1.574*** -1.057**
(0.458) (0.458) (0.458) (0.460) (0.459) (0.458) (0.455) (0.460)
Duration of breastfeeding (base = never)
Breastfed 6 1.099*** 1.106*** 1.115*** 0.891** 1.002*** 1.034*** 0.994*** 0.680*
months (0.357) (0.356) (0.357) (0.357) (0.357) (0.357) (0.354) (0.358)
Adjusted R-
squared 0.2609 0.2650 0.2735 0.2709 0.2680 0.2664 0.2780 0.2889
Controls
included
Basic
demographics
X X X X X X X X
Income X X X X X X X
Childcare X X
Outings &
home
environment
Maternal
background
Maternal
health etc.
Neighbourhood X X
X
X
X
X
X
X
So the key parenting influences are:
106

• Maternal teaching behaviour in the pre-school period has a large effect on school entry
attainment levels among children. The magnitude is such that children of mothers who are in
the lowest 8% in terms of age of starting and range of teaching are 3.5 points behind other
similar children (or 14 percentile points lower in the distribution). Those children in the next
11% of the distribution are 2 points (or 8 percentile points) behind in the distribution. These
are big effects. Note in passing they are larger than the conditional effects of mothers
education and there is no evidence that teaching by the better educated mothers are more
effective.
• Maternal reading is less important but less intensive reading does result in substantial
deficits.
• Other parenting behaviours such as 6+ hours of TV a week at 18 months and breast-feeding
beyond 6 months are of moderate importance.
8.3.3 Outings and the Home Environment
The outings and home environment measures are strongly correlated with parenting behaviours
around TV watching and reading. Low income also reduces the predicted effects of the poor
home environment measures. It is obvious that reading requires books but the results suggest
that the quality of the home environment - in terms of the variety of books and toys available - is
important in and of itself and that this is associated with low income.
Table 8.5 shows the key Outings and Home Environment influences are:
• A very low book score (which in turn is associated with low reading and low income) -
which affects the 6% of children (those in homes reporting no more than 9 children’s
books in the home on 5 occasions before school entry) - remains a substantive influence
on child attainment conditional on confounding influences.
• In the same vein, a very low toy score (measured at 24 months and covering 7% of
children with lowest cumulative score for a range of toys) is also found to be detrimental
to child cognitive development.
• There is no evidence that better educated parents are providing higher quality books or
toys, in terms of their impact on child development (see section 3).
• Trips to Libraries and not attending department stores remain weak influences on
development.
107

Table 8.5: Estimated effects of outings scores and home environment on Entry
Assessment, various specifications (N = 5010)
(1) (2) (3) (4) (5) (6) (7) (8)
Outings scores
Department stores -0.496* -0.559** -0.504* -0.655** -0.537** -0.558** -0.463* -0.511*
(0.271) (0.270) (0.270) (0.269) (0.270) (0.270) (0.268) (0.267)
Library 1.171*** 1.234*** 1.239*** 0.907*** 1.147*** 1.224*** 1.189*** 0.864***
(0.282) (0.281) (0.281) (0.284) (0.282) (0.281) (0.279) (0.283)
Book score (base = high)
Very low -3.525*** -3.325*** -3.321*** -2.067*** -3.131*** -3.129*** -3.112*** -1.741***
(0.613) (0.612) (0.611) (0.628) (0.614) (0.614) (0.609) (0.626)
Low -1.530*** -1.434*** -1.415*** -0.673* -1.371*** -1.341*** -1.309*** -0.490
(0.362) (0.361) (0.360) (0.372) (0.362) (0.362) (0.359) (0.370)
Medium -0.902** -0.869** -0.844** -0.510 -0.846** -0.792** -0.852** -0.421
(0.366) (0.365) (0.364) (0.365) (0.365) (0.366) (0.363) (0.363)
Toy score (base = high)
Very low -1.854*** -1.842*** -1.813*** -1.176* -1.951*** -1.726*** -1.775*** -1.199**
(0.606) (0.605) (0.602) (0.604) (0.606) (0.606) (0.600) (0.603)
Low -1.019** -0.893** -0.917** -0.447 -0.889** -0.845* -0.891** -0.460
(0.437) (0.436) (0.435) (0.436) (0.436) (0.436) (0.433) (0.434)
Medium 0.026 0.090 0.062 0.367 0.104 0.091 0.093 0.341
(0.351) (0.351) (0.349) (0.350) (0.351) (0.351) (0.348) (0.348)
Adjusted R-squared 0.2538 0.2579 0.2664 0.2709 0.2611 0.2596 0.2709 0.2889
Controls included
Basic demographics X X X X X X X X
Income X X X X X X X
Childcare X X
Parenting X X
Maternal background X X
Maternal health etc. X X
Neighbourhood X X
8.3.4 Mother’s Childhood and Family Background
Table 8.6 shows the mother’s childhood and family background influences are sharply reduced
in importance once other influences are included. Mother’s mother’s education becomes
insignificant and housing tenure of childhood home is very marginal. Current low income, a
poor home environment and parenting behaviours are the influences driving these terms to
insignificance. The mother having grown up in an intact family throughout her childhood has a
modest positive influence as does not having a history of truancy and having a positive attitude
towards her own education experience. These factors describing the mother’s own childhood are
generally not a major source of influence on the child once current circumstances are
conditioned on. This suggests that there is a degree of intergenerational persistence in low
income or deprivation that the contemporaneous elements are picking up, rather than these
108

eing alternative routes of influence. However, there is evidence that the mother’s education
experience has a modest lasting effect on her children’s development.
Table 8.6: Estimated effects of mother’s childhood and family background controls on
Entry Assessment, various specifications (N = 5010)
(1) (2) (3) (4) (5) (6) (7) (8)
Tenure of mother’s childhood home (base = mortgage/owned
Council rented -1.000*** -0.893*** -0.807** -0.779** -0.824** -0.830** -0.707** -0.569*
(0.344) (0.343) (0.343) (0.340) (0.342) (0.343) (0.341) (0.338)
Other rented -0.374 -0.299 -0.410 -0.416 -0.285 -0.227 -0.282 -0.494
(0.779) (0.777) (0.775) (0.767) (0.771) (0.777) (0.771) (0.760)
Other 0.720 0.796 0.779 0.873 0.743 0.794 0.823 0.789
(0.691) (0.690) (0.687) (0.681) (0.684) (0.690) (0.684) (0.674)
Mother’s father present in childhood home (base = not at all)
Throughout 1.699** 1.731** 1.495** 1.725** 1.581** 1.594** 1.455** 1.226*
(0.699) (0.697) (0.696) (0.688) (0.691) (0.698) (0.692) (0.684)
Partly 1.427* 1.542** 1.297* 1.530** 1.437* 1.477* 1.296* 1.101
(0.760) (0.758) (0.757) (0.748) (0.752) (0.759) (0.752) (0.743)
Mother’s mother’s highest qualification (base = CSE/none)
Vocational/Olevel
0.738** 0.717** 0.548 0.626* 0.546 0.650* 0.543 0.247
(0.346) (0.345) (0.345) (0.341) (0.343) (0.345) (0.343) (0.340)
A-level 1.328*** 1.299*** 1.193*** 0.962** 1.067** 1.232*** 1.117** 0.643
(0.454) (0.453) (0.452) (0.449) (0.450) (0.453) (0.450) (0.445)
Degree 0.083 0.180 0.231 0.279 0.084 0.061 0.111 0.141
(0.782) (0.780) (0.780) (0.771) (0.774) (0.780) (0.775) (0.767)
Mother has a history of truancy (base = yes)
No 1.387** 1.315** 1.221** 1.265** 1.442*** 1.124** 1.264** 1.172**
(0.544) (0.543) (0.541) (0.536) (0.540) (0.545) (0.539) (0.534)
Mother feels school was a valuable experience (base = not sure/generally not/no)
Yes very 0.487 0.367 0.332 -0.089 0.048 0.090 0.437 -0.287
(0.399) (0.398) (0.397) (0.396) (0.397) (0.403) (0.395) (0.397)
Yes generally -0.321 -0.397 -0.433 -0.670** -0.646* -0.557 -0.379 -0.854**
(0.338) (0.337) (0.336) (0.334) (0.336) (0.339) (0.335) (0.334)
Adjusted R-
squared 0.2433 0.2473 0.2552 0.2680 0.2611 0.2499 0.2604 0.2889
Controls
included
Basic
demographics
X X X X X X X X
Income X X X X X X X
Childcare X X
Parenting X X
Outings & home
environment
Maternal health
etc.
Neighbourhood X X
X
X
X
X
109

8.3.5 Mother’s Health, social networks and Family Conflict
This group of potential influences were not found to have a large impact of children’s
educational development. The influences remaining significant in this group of variables were
only the mother’s locus of control measure and the indicators of social networks and support.
This, in itself, suggested that mother’s mental and physical health and within family conflict had
little influence on a child’s educational development pre-school. Table 8.7 indicates that, after
conditioning on other influences, the social networks score becomes insignificant and the locus
of control term is reduced in importance, largely through its correlation with poorer parenting
scores and a worse home environment. Mothers who feel their actions have little impact engage
in less teaching and reading to their children. However, there remains a modest independent
effect of this factor over and above this.
Table 8.7: Estimated effects of maternal health, attitudes and social networks on Entry
Assessment, various specifications (N = 5010)
(1) (2) (3) (4) (5) (6) (7) (8)
Social support score (base = low)
Medium 0.580* 0.500 0.503 0.226 0.244 0.433 0.487 0.077
(0.325) (0.325) (0.324) (0.322) (0.324) (0.326) (0.323) (0.321)
High 1.203*** 1.130*** 1.070*** 0.725** 0.793** 1.064*** 1.068*** 0.495
(0.338) (0.338) (0.338) (0.336) (0.338) (0.340) (0.336) (0.336)
Locus of control score (base = Internal)
Medium -0.906*** -0.808*** -0.795*** -0.654** -0.712** -0.717** -0.732** -0.543*
(0.303) (0.303) (0.301) (0.299) (0.300) (0.304) (0.300) (0.298)
External -1.698*** -1.434*** -1.471*** -1.136** -1.183** -1.234** -1.319*** -0.916*
(0.471) (0.473) (0.471) (0.469) (0.470) (0.479) (0.470) (0.470)
Adjusted R-
squared 0.2424 0.2462 0.2550 0.2664 0.2596 0.2498 0.2601 0.2889
Controls
included
Basic
demographics
X X X X X X X X
Income X X X X X X X
Childcare X X
Parenting X X
Outings score X X
Maternal
background.
Neighbourhood X X
X
X
110

8.3.6 Neighbourhood and Peer Group
Table 8.8 completes this exercise by looking at how the relationships between neighbourhood
and peer group and child attainment are related to other mediating influences. We have already
seen in section 7 that the peer group within the pre-school provider plays a substantial role in
how the neighbourhood impacts on children. However, apart from that impact, there is little
further overlap with the other mediating influences: the point estimates on the educational
domain score barely move as other factors are added in. This leaves what drives the
neighbourhood influences unclear.
Table 8.8: Estimated peer and neighbourhood effects on Entry Assessment, various
specifications (N = 5010)
(1) (2) (3) (4) (5) (6) (7) (8)
Education domain
score
-0.919*** -0.853*** -0.924*** -0.841*** -0.740*** -0.812*** -0.836*** -0.787***
(0.146) (0.147) (0.157) (0.144) (0.146) (0.147) (0.146) (0.156)
Average EA score of peers – predicted component (base = lowest quintile)
2 nd quintile 0.374 0.416 0.263 0.321 0.436 0.455 0.426 0.265
(0.475) (0.474) (0.480) (0.469) (0.470) (0.474) (0.474) (0.473)
3 rd quintile 1.436*** 1.403*** 0.965** 1.368*** 1.497*** 1.376*** 1.379*** 0.943**
(0.469) (0.469) (0.477) (0.463) (0.465) (0.468) (0.468) (0.469)
4 th quintile 2.481*** 2.406*** 1.919*** 2.444*** 2.455*** 2.335*** 2.338*** 1.857***
(0.479) (0.478) (0.488) (0.472) (0.474) (0.478) (0.478) (0.481)
Highest quintile 2.642*** 2.462*** 1.775*** 2.514*** 2.621*** 2.421*** 2.443*** 1.741***
(0.484) (0.485) (0.509) (0.478) (0.482) (0.485) (0.485) (0.503)
Average EA score of peers – residual component (base = lowest quintile)
2 nd quintile -1.014** -1.046** -0.858* -1.032** -1.115** -1.037** -1.039** -0.894*
(0.466) (0.465) (0.469) (0.460) (0.461) (0.465) (0.464) (0.463)
3 rd quintile -0.647 -0.625 -0.475 -0.697 -0.731 -0.593 -0.583 -0.537
(0.472) (0.471) (0.476) (0.466) (0.467) (0.471) (0.471) (0.470)
4 th quintile -0.914* -0.906* -0.652 -0.942** -0.974** -0.885* -0.892* -0.677
(0.472) (0.472) (0.478) (0.466) (0.468) (0.472) (0.471) (0.471)
Highest quintile -0.702 -0.684 -0.555 -0.653 -0.775* -0.727 -0.643 -0.635
(0.457) (0.457) (0.458) (0.452) (0.453) (0.457) (0.456) (0.452)
Adjusted R-squared 0.2550 0.2573 0.2611 0.2758 0.2709 0.2604 0.2601 0.2889
Controls included
Basic demographics X X X X X X X X
Income X X X X X X X
Childcare X X
Parenting X X
Outings & home
environment
Maternal
background
Maternal health etc. X X
X
X
X
X
The peer group influences are moderately affected by the inclusion of other mediating
influences. The already weak relationship of the child cognitive outcome with the residual
111

component of the peer group (that part not explained by parental background) is further reduced
and its statistical significance becomes very borderline. The positive relationship of child
attainment with higher attaining peer groups is modestly reduced by the inclusion of the
childcare measures that include the type of provider that the peer group and the child attends.
This is probably because attending a provider which has children drawn from families with
characteristics that encourage attainment (high incomes, parental teaching, reading etc) has a
strong influence on a child’s attainment.
8.4 How do Parental Education and Income Influence a Child’s Early Development?
Here we explore fully how income and parental education work through the proximal factors
that we have studied here to produce variations in child development. We start by drawing
together what all the factors addressed here can say about early child development. Table 8.9
decomposes the variation in Entry Assessment tests at age 4 to 5 into that which all the data
used here can explain and the remaining unexplained variation. This unexplained element will
include the (no doubt) substantial measurement error (suggested by the only moderate
correlation of EA with measured attainment two years later). Then we further decompose the
explained variation into the factors underlying it. Throughout we focus on parental education
and family income.
The first block of results (columns 1 to 6) looks at the total variation in child development and
starts by showing that the attainment gap between the average scores in top and bottom quintiles
is some 25 points (or 2.5 standard deviations). The child’s age when tested explains around 2.6
points (or 10%) of this variation. The first three columns show that if only family income and
parental education are considered (only conditioning on age of child at assessment) then only
11% of the gap between the best and worst performers is explained by parental education and
family income (2.6 points out of the 22.8 points gap after the age variation of children is
factored out). The inclusion of all other demographic and proximal influences observed in the
ALSPAC data raises the percentage variation explained (other than by age at assessment) to
23% (the sum of the values in column 5 excluding that for one of child at assessment). So just
over three quarters of the total gap is unexplained. This unexplained variation will include
measurement errors, genetic factors, unmeasured factors and child specific variation.
Nevertheless, explaining a quarter of the total difference between the best and poorest
performing children is substantial.
112

The largest contribution to this explained variation is made by the basic demographic factors, in
particular gender, age of mother, numbers of siblings and low birth weight. These factors
explain 5% of the total attainment gap (6% once age variation is netted out) and around 25% of
the total contribution made by all observed characteristics within the data (other than age of
child). These factors are largely unalterable, except perhaps teenage births or large families.
After this, three groups of influences are of broadly similar magnitude, these being parental
education, parenting behaviours and the neighbourhood and peer group (neighbourhood and
peer group in turn contribute roughly equally to this effect). The home environment, childcare
and residual family income experienced make modest contributions to the attainment gap with
mother’s mental and physical health proving the least important. Note that in this context the
discussion of income and parental education are the residual contributions uncorrelated with the
other proximal influences. Our set of proximal influences (neighbourhood, childcare, parenting
behaviours, the home environment, mothers upbringing and her mental and physical health) can
explain around 13% of the attainment gap between the top and bottom fifths of child by
attainment (after netting out age at time test taken).
So parental teaching and reading to children are the strongest routes of influence observable of
children doing well, in terms of educational attainment, on school entry. The peer group which
the child attends pre-school with and neighbourhood of residence are also very strong
influences. The home environment (books, toys and trips to the library) is the next most
important group of influences (note these are strongly related to family income). The childcare
experienced (other than through its association with peer group) prior to school entry is of
modest importance. The mother’s childhood and her mental and physical health are minor
influences. Family income and parental education continue to have influences on attainment
over and above through the mediating factors but the role of income is modest. The residual
effect of parental education could reflect that that better educated parents undertake the same
mediating factors more effectively or there are other influences not captured in our model (an
obvious candidate is genetic influences). We explored whether there was clear evidence of
whether better educated parents undertake some activities more effectively through interactions
and this hypothesis was generally rejected. So whilst it could be the case that better educated
parents are doing everything better to same degree, the lack of variations across different routes
makes it more probable that the remaining influence of parental education reflects unmeasured
factors.
113

Table 8.9: Decomposition of range of mean scores for various groups (Entry Assessment)
Difference in mean
scores
Explained variation –
contribution of:
Age of child at
assessment
Income
Points
Top and bottom quartiles of attainment
%
% total
explained
variation
variation
accounted
accounted
for by:
for by:
Points
%
% total
explained
variation
variation
accounted
accounted
for by:
for by:
Top and bottom quartiles of
household income
Points
%
% total
explained
variation
variation
accounted
accounted
for by:
for by:
Children of mothers with
CSE/no qualifications vs. a
degree
%
% total
explained
variation
Points
variation
accounted
accounted
for by:
for by:
25.4 100 100 25.4 100 100 6.6 100 100 9.5 100 100
2.6 10.2 50.4 2.6 10.1 32.2 -0.1 -1.9 -2.0 -0.1 -0.7 -0.7
0.7 2.7 13.6 0.3 1.3 4.1 1.6 24.7 25.2 0.7 7.4 7.4
Parental Education 1.9 7.3 36.0 0.9 3.4 10.8 1.5 22.2 22.7 3.8 40.4 40.4
Other Demographic
Variables
- - - 1.3 5.0 15.8 0.7 10.0 10.2 0.6 6.7 6.7
Childcare - - - 0.3 1.3 4.3 0.3 4.6 4.7 0.4 4.2 4.2
Parenting - - - 0.8 3.2 10.1 0.4 5.9 6.0 0.9 9.1 9.1
Outings & Home
Environment
Mother’s childhood
and family
background
Maternal health,
attitudes and social
networks
Neighbourhood and
peer group
Unexplained
variation
- - - 0.6 2.3 7.4 0.5 8.1 8.2 1.1 11.1 11.1
- - - 0.3 1.1 3.4 0.3 4.9 5.0 0.6 6.3 6.3
- - - 0.2 0.7 2.2 0.3 4.5 4.6 0.4 4.3 4.3
- - - 0.8 3.0 9.6 1.0 14.9 15.2 1.1 11.3 11.3
20.3 79.7 - 17.5 68.7 - 0.1 2.1 - 0.0 0.0 -
Focusing on parental education and family income, we can explore how the observed mediating
routes transmit education and income into the child’s attainment. The second block of Table 8.9
does this for family income. It shows that the highest and lowest quartiles of the income
distribution have average attainment gap of 6.6 points. So those from deprived and affluent
families are about two thirds of a standard deviation apart on school entry. Parental education
and demographic characteristics of the family, especially numbers of siblings and mother’s age,
are important determinants of this gap. These reflect influences on attainment, which although
correlated with income, are probably causal in themselves rather than being a reflection of how
income impacts on children’s development. The number of siblings could be an exception to
this general rule as more children mean available income is being spread more thinly. The
mother’s upbringing, which reflects the impact of her pre-birth deprivation on the attainment of
the child, is also unlikely to be influenced by current income changes. Rather it reflects
intergenerational effects of deprivation (though note it only makes a small residual
114

contribution). Of the proximal influences where income may well make a difference, the
strongest are the neighbourhood and peer group, the home environment (books, toys and
outings) and childcare. These are plausible routes by which income impacts on child
development irrespective of other family circumstances. Parenting, and mother’s mental and
physical health play supporting roles. So whilst it is possible that parenting styles and the mental
health of the mother improve with higher incomes, it is less obvious that these factors link
income and attainment. Perhaps the most important result here is that although parenting
behaviour is very important in driving a child’s pre-school attainment, it is not strongly related
to family income. Nor, as noted above, is there any evidence that better educated families teach
pre-school children more effectively than those with lesser educational qualifications. The
identified family income effects are operating more substantially through the neighbourhood
and peer group, the home environment and pre-school childcare. What is striking about the
neighbourhood effects is that once we have conditioned on family income and the basic
demographics all the other proximal influences considered have little or no conditional
correlation with neighbourhood. This suggests that measures of family functioning and home
circumstances are not correlated with the neighbourhood effects observed.
Of the total 6.6 point attainment gap between rich and poor some 1.6 points, or a quarter, is
unrelated to the other influences considered. This residual component can represent three
possible factors. First, there are missing elements or mechanisms driven by income; second,
high income families do the mechanisms reported here more effectively in an additive way or
third, there are unmeasured background factors correlated with income which mean that the
residual income effects are not causal. Neighbourhood and peer group, the home environment
and childcare are mediating influences with strong monetary components. These factors account
for 26% of the raw correlation between income and attainment. Including mother’s mental
health and parenting behaviours would raise this to around 35% but perhaps the lower value is
closer to the truth. Note that another 25% of the original variation in attainment correlated with
income remains attributed to family income. This residual correlation then reflects neither
parental education, parenting styles nor other influences studied here. This too could be a causal
influence of income but its status is uncertain. So, at most, around half of the raw difference in
attainment between the richest and poorest pre-school children can be thought of as genuinely
driven by income, with a lower bound of around a quarter 10 .
10 US welfare experimental studies suggest that raising income as a result of in-work welfare supplements raising
child attainment measures among pre-school children (see Clark-Kauffman et al. (2003). This research suggests
that around a 20% increase in income results in improved attainment of the order of 5 to 7 per cent of a standard
deviation. The results here suggest that increased income from the top to bottom quintiles, approximately a tripling
115

Moving on to parental education, the gap in attainment between children of mothers with CSE
level qualifications or lower (i.e. below GCSE level A-C) and degree holding mothers is much
larger than the gap between the poorest and richest families at 9.5 points. Around 40% of this
raw unconditional gap is not explained by other factors observed in the data. So the proximal
influences considered do more work in explaining how parental education is transmitted to
children than they do for income. If we include residual income as another mechanism this rises
to nearly half. Of the proximal influences the most important contribution comes from the home
environment, parenting behaviours (especially teaching and reading), and the
neighbourhood/peer group. The residual correlation with parental education could reflect
omitted factors such as genetic inheritance, other transmission mechanisms not covered here, or
that the better educated impart learning in general way unrelated to the mechanisms considered
here. Nevertheless, 60% of the early learning deficit associated with less educated parents is
explained and the results suggest that the home environment (which is strongly related to
income), parenting behaviours, family income, neighbourhood and the peer group the child is
attending pre-school with are the main drivers. Early differences in pre-school childcare
arrangements are only a minor factor.
8.5 Behaviour
We repeat this analysis for the behaviour scores. The range of factors found to have an influence
on behaviour (conditional only on basic demographics) is substantially different than for
educational attainment and these are shown in Table 8.10. In particular, mother’s physical and
mental health and within family conflict issues are far more important for behaviour than for
attainment, as are mother’s attitude to, or bonding with, the child and discipline strategies.
Basic Demographics and Behaviour Outcomes
Table 8.11 reports the coefficients on the basic demographic variables as each group of
proximal variables is introduced into the model separately and then combined in the final
of income, would raise attainment by 34% of a standard deviation (the unexplained component plus the correlations
with childcare and home environment which are plausibly driven by income). Whilst not strictly comparable, the
order of magnitude is not way out of line. Interestingly this literature also highlights the roles of childcare and
outings as routes by which income changes influence attainment. The Moving To Opportunity experiments in the
US where some families are moved out of ghetto areas into more affluent ones on a random basis has also been
shown to improve education outcomes but results are for primary school age children (see Goering and Feins, 2003,
for a discussion of MTO results).
116

column. The aim is to show how the influence of background factors is mediated by the
proximal variables.
8.5.1 Parental Education
Parental education was not strongly related to behavioural outcomes of the children in our
earlier analyses. The role of parental education is further diminished when the groups of
proximal factors are introduced. Perhaps surprisingly, parenting behaviours - which include
discipline mechanisms and mothers bonding with the child - are not important in this process.
Rather it is the home environment (toys, books etc) and mothers mental health and selfconfidence
that are important for behaviour. So the influence of parental education on behaviour
appears to work mainly through the home environment, mother’s locus of control, self-esteem
and reduced depression/anxiety. When all other factors are included parental education has a
very modest residual effect.
Table 8.10: Groups of variables used as controls in Behaviour regressions
Basic
demographics
Mother’s
highest
qualification
Partner’s
highest
qualification
Lone parent
status
Mother’s age
at birth
Ethnicity
Gender
Birth weight
Special care
unit at birth
Younger
siblings by 47
months
Older siblings
Income Childcare Parenting
Log average
weekly net
income
Financial
difficulties prebirth
Care by partner
pre-age 2
Care by
friend/relative preage
2
Care by paid
person pre-age 2
Centre-based care
pre-age 2
Nursery class age
3/ 4
LEA nursery
school age 3/ 4
Private day
nursery age 3/ 4
Nursery (type
undefined) age 3/
4
Playgroup age 3/ 4
Other centre-based
care age 3/ 4
Maternal
reading score
Paternal
reading score
Teaching score
Talking whilst
occupied score
18 month TV
score
38 month TV
score
Smoked in
pregnancy
Maternal
bonding score
Types of
discipline
117
Outings Scores
& Home
Environment
Park/playground
outings score
Visits to
friends/relatives
outings score
Places of interest
outings score
Places of
entertainment
outings score
Book score
Toy score
Damp/
condensation/
mould
Mother’s
childhood and
family
background
Mother’s
relationship with
mother score
Mother has a
history of
truancy
Mother feels
school was a
valuable
experience
Maternal
health,
attitudes
and social
networks
Mother’s
physical
health
Social
networks
score
Social
support score
Total CCEI
score
Self-esteem
score
Locus of
control score
Mother’s
satisfaction
with
relationship
Partner’s
employment at
47 months
8.5.2 Lone Parenthood
Children in lone parent families exhibit substantially worse behaviour scores but these appear to
mainly to be working through parenting differences and family income. Lone parents with a
Neighbourhood
Average behaviour
score of peers –
predicted component
Average behaviour
score of peers –
residual component

new partner at 47 months are still observed as having moderately worse behaviour scores, which
may reflect tensions brought on by re-partnering. Mother’s mental health and self-esteem/locus
of control scores also appears to be an important mediating influence for the impact of lone
parent status on child behaviour.
8.5.3 Mother’s Age
Teen mothers and, to a slightly lesser degree, mothers in their early 20s have children with
substantially worse behaviour scores. This is transmitted through differences in parenting
behaviour, especially discipline and maternal bonding and in mother’s mental health and selfesteem.
So, conditional on these proximal routes, teen motherhood has only a modest
independent effect on behaviour and motherhood in the early 20s have no adverse effects. Note
these mothers have very low scores on maternal bonding self-esteem and locus of control.
Hence the bulk of the relationship between teen motherhood and children’s behaviour is
explained by our mediating influences.
8.5.4 Ethnicity, Gender and Siblings and a Non-Working partner
Ethnicity is not a predictor of behaviour problems at age 4 and the impact of low birth weight
and gender are again largely unaffected by these proximal controls. Numbers of siblings are not
strongly associated with behaviour variation, but the extent to which they are associated reflects
poor mother mental health and family conflict scores. A non-working partner is also associated
with poorer behaviour scores. Again this is substantially operating through mother’s mental
health and family conflict. Income also plays a role here.
118

Table 8.11: Estimated effects of basic demographics on Behaviour, various specifications
(N = 9416)
(1) (2) (3) (4) (5) (6) (7) (8) (9)
Mother’s highest qualification (base = vocational/O-level)
CSE/none 1.071*** 0.908*** 1.034***
(0.317) (0.316) (0.318)
A-level -1.253*** -1.069*** -1.262***
(0.268) (0.269) (0.271)
Degree -1.841*** -1.570*** -1.763***
(0.378) (0.380) (0.388)
Partner’s highest qualification (base = vocational/O-level)
CSE/none 0.249 0.041 0.234
(0.311) (0.310) (0.311)
A-level -0.608** -0.439 -0.607**
(0.279) (0.278) (0.279)
Degree -0.751** -0.329 -0.667*
(0.356) (0.360) (0.360)
Lone parent status (base = never lone parent)
Intermittently, with
partner at 47 months
2.209***
(0.585)
Intermittently, no 1.544***
partner at 47 months (0.455)
Since birth 2.511***
(0.955)
Mother’s age at birth (base = 25-29)
1 0.798 0.635
(0.563) (0.561)
Older siblings (base = none)
1 1.275***
(0.253)
2 0.795**
(0.333)
3+ 1.065**
(0.490)
1.111***
(0.252)
0.618*
(0.332)
0.763
(0.488)
1.954***
(0.590)
1.358***
(0.461)
2.224**
(0.969)
2.982***
(0.653)
1.263***
(0.312)
-0.049
(0.251)
0.070
(0.362)
0.523
(0.544)
-2.501***
(0.202)
0.848
(0.571)
0.536**
(0.212)
0.560
(0.473)
0.692***
(0.240)
0.860
(0.564)
1.373***
(0.258)
0.930***
(0.339)
1.157**
(0.496)
Partner’s employment status at 47 months (base = in work)
Not in work 1.904*** 1.151*** 1.848***
(0.377) (0.392) (0.379)
1.074***
(0.296)
-0.950***
(0.251)
-1.695***
(0.356)
0.260
(0.289)
-0.334
(0.259)
-0.637*
(0.333)
1.370**
(0.599)
0.660
(0.513)
1.212
(0.916)
2.092***
(0.606)
0.807***
(0.291)
0.126
(0.233)
0.680**
(0.335)
0.205
(0.503)
-1.785***
(0.189)
0.407
(0.532)
0.418**
(0.198)
0.593
(0.440)
0.607***
(0.224)
0.781
(0.524)
0.620**
(0.243)
0.622*
(0.321)
0.977**
(0.465)
1.630***
(0.351)
0.687**
(0.314)
-0.805***
(0.267)
-1.389***
(0.377)
0.033
(0.306)
-0.391
(0.275)
-0.311
(0.353)
2.334***
(0.577)
1.487***
(0.455)
1.875**
(0.942)
2.830***
(0.641)
1.211***
(0.307)
-0.048
(0.248)
0.022
(0.357)
0.216
(0.536)
-2.367***
(0.200)
0.714
(0.562)
0.458**
(0.209)
0.533
(0.466)
0.661***
(0.236)
0.715
(0.555)
1.021***
(0.261)
0.353
(0.342)
0.245
(0.495)
1.495***
(0.373)
0.535*
(0.316)
-0.936***
(0.266)
-1.336***
(0.379)
0.248
(0.306)
-0.664**
(0.274)
-0.756**
(0.351)
1.954***
(0.577)
1.308***
(0.456)
1.926**
(0.941)
2.529***
(0.642)
1.020***
(0.307)
-0.230
(0.246)
-0.291
(0.354)
0.383
(0.534)
-2.506***
(0.199)
0.862
(0.562)
0.556***
(0.209)
0.423
(0.466)
0.680***
(0.236)
0.602
(0.555)
1.141***
(0.249)
0.462
(0.329)
0.468
(0.484)
1.658***
(0.372)
0.518*
(0.303)
-0.893***
(0.256)
-1.441***
(0.362)
0.151
(0.293)
-0.522**
(0.263)
-0.454
(0.337)
1.833***
(0.597)
0.266
(0.480)
1.428
(0.989)
2.347***
(0.613)
0.763***
(0.294)
-0.111
(0.236)
-0.336
(0.339)
0.130
(0.513)
-2.474***
(0.191)
0.761
(0.538)
0.548***
(0.200)
0.264
(0.446)
0.883***
(0.226)
1.005*
(0.531)
0.886***
(0.239)
0.292
(0.315)
0.272
(0.462)
1.167***
(0.357)
1.011***
(0.317)
-1.226***
(0.269)
-1.815***
(0.379)
0.228
(0.311)
-0.621**
(0.279)
-0.798**
(0.358)
2.125***
(0.585)
1.450***
(0.456)
2.391**
(0.955)
2.992***
(0.650)
1.242***
(0.311)
-0.063
(0.251)
-0.056
(0.360)
0.666
(0.542)
-2.512***
(0.202)
0.834
(0.571)
0.528**
(0.212)
0.513
(0.473)
0.692***
(0.239)
0.748
(0.563)
1.280***
(0.252)
0.781**
(0.333)
0.998**
(0.490)
1.831***
(0.378)
0.410
(0.296)
-0.465*
(0.251)
-0.891**
(0.365)
0.129
(0.282)
-0.264
(0.252)
-0.209
(0.331)
1.110*
(0.638)
-0.206
(0.563)
0.340
(1.012)
1.450**
(0.600)
0.421
(0.286)
0.142
(0.228)
0.409
(0.332)
-0.273
(0.494)
-1.858***
(0.184)
0.330
(0.516)
0.448**
(0.192)
0.391
(0.427)
0.606***
(0.218)
0.654
(0.510)
0.541**
(0.250)
0.270
(0.327)
0.223
(0.466)
0.985***
(0.357)
Adjusted R2 0.0525 0.0618 0.0546 0.1861 0.0838 0.0828 0.1612 0.0554 0.2416
Controls included
Income
Childcare
Parenting
Outings & home env
Maternal background
Maternal health etc.
Neighbourhood
X
X
X
X
X
X
X
X
X
X
X
X
X
X
119

8.5.5 Childcare and Behaviour
The use of friends and relative carers up to age 2 and also centre based care are weakly
associated with adverse behavioural outcomes before other proximal influences are controlled
for. There is little evidence of behaviour variations associated with care immediately prior to
school entry (outside specialist or social service run care). Table 8.12 introduces the other
proximal factors and the weak negative results up to age 2 are largely unaffected suggesting no
correlation with other proximal influences and that it is early childcare of these forms which is
slightly damaging. The results for pre-school childcare disappear once parenting is controlled
for. Poor mother’s mental health has the same effect. This suggests that LEA nursery and other
care types are not the driver of these adverse correlations but parenting behaviours and mothers
poor mental health, locus of control etc., which is consistent with those using these types of care
having special needs identified by social services.
8.5.6 Parenting and Behaviour
Table 8.13 repeats this process focusing on the parenting measures. These are very strong
drivers of behaviour scores, especially maternal bonding at 8 months. The introduction of other
proximal factors tends to reduce this a little. Mother’s mental health, self-esteem, locus of
control and family conflict are the key correlated influences. The results suggest that poor
physical health, maternal depression and low self-esteem intertwine with weaker parenting
behaviours to produce adverse behavioural scores.
120

Table 8.12: Estimated effects of childcare arrangements on Behaviour, various
specifications (N = 9416)
(1) (2) (3) (4) (5) (6) (7) (8)
Childcare pre-age 2
Used partner 5-19 hours
per week
Used partner 20+ hours per
week
Used friend/relative 5-19
hours per week
Used friend/relative 20+
hours per week
Used paid person 5-19
hours per week
Used paid person 20+
hours per week
Used centre-based care 5-
19 hours per week
Used centre-based care 20+
hours per week
Childcare age 3 to 4
-0.212 -0.236 -0.148 -0.185 -0.221 -0.189 -0.239 -0.151
(0.279) (0.277) (0.260) (0.274) (0.274) (0.263) (0.277) (0.254)
-0.473* -0.504* -0.205 -0.458* -0.562** -0.371 -0.501* -0.267
(0.277) (0.275) (0.261) (0.272) (0.272) (0.261) (0.275) (0.254)
0.550** 0.573** 0.392 0.754*** 0.639** 0.727*** 0.579** 0.651***
(0.258) (0.257) (0.240) (0.255) (0.254) (0.244) (0.257) (0.235)
0.785*** 0.881*** 0.776*** 0.922*** 0.970*** 0.919*** 0.876*** 0.893***
(0.278) (0.277) (0.259) (0.275) (0.274) (0.263) (0.277) (0.253)
0.167 0.331 -0.145 0.293 0.136 0.293 0.297 -0.111
(0.386) (0.385) (0.359) (0.380) (0.380) (0.365) (0.385) (0.349)
-0.058 0.276 -0.093 0.203 0.151 0.180 0.236 -0.081
(0.324) (0.326) (0.305) (0.323) (0.322) (0.310) (0.326) (0.299)
1.500*** 1.638*** 1.065** 1.735*** 1.463*** 1.305*** 1.651*** 1.050**
(0.476) (0.474) (0.442) (0.468) (0.468) (0.449) (0.474) (0.430)
-0.157 0.114 -0.139 -0.055 0.066 -0.153 0.119 -0.289
(0.607) (0.606) (0.565) (0.599) (0.597) (0.574) (0.605) (0.551)
Nursery class 0.046 -0.020 -0.157 0.127 -0.046 -0.093 0.029 -0.069
(0.391) (0.389) (0.362) (0.384) (0.384) (0.368) (0.399) (0.361)
LEA nursery school 1.239*** 1.062** 0.491 1.087** 0.887* 0.496 1.219** 0.419
(0.468) (0.466) (0.435) (0.461) (0.460) (0.442) (0.494) (0.450)
Private day nursery 0.106 0.171 0.039 0.516 0.199 0.053 0.250 0.111
(0.398) (0.397) (0.369) (0.392) (0.391) (0.376) (0.406) (0.369)
Playgroup 0.244 0.295 -0.049 0.516* 0.428 0.589** 0.380 0.373
(0.309) (0.308) (0.287) (0.304) (0.304) (0.292) (0.310) (0.281)
Nursery (type undefined) 0.311 0.335 0.026 0.433 0.319 0.147 0.221 -0.049
(0.331) (0.330) (0.307) (0.325) (0.325) (0.312) (0.331) (0.300)
Other 2.196** 2.044*** 0.993 1.965** 1.624* 1.193 2.387** 1.116
(0.992) (0.988) (0.920) (0.974) (0.974) (0.936) (0.998) (0.905)
Adjusted R-squared 0.0546 0.0641 0.1916 0.0919 0.0909 0.1635 0.0670 0.2416
Controls included
Basic demographics X X X X X X X X
Income X X X X X X X
Parenting X X
Outings & home
environment
Maternal background X X
Maternal health etc. X X
Neighbourhood X X
X
X
121

Table 8.13: Estimated effects of parenting behaviours on Behaviour, various specifications
(N = 9416)
(1) (2) (3) (4) (5) (6) (7) (8)
Maternal reading score (base = high)
Very low
2.118*** 2.083*** 2.052*** 1.565*** 1.852*** 1.766*** 2.038*** 1.357***
(0.415) (0.414) (0.416) (0.425) (0.412) (0.405) (0.414) (0.417)
Low
1.639*** 1.656*** 1.620*** 1.286*** 1.446*** 1.390*** 1.632*** 1.029***
(0.377) (0.376) (0.377) (0.378) (0.375) (0.368) (0.376) (0.370)
Medium
0.369 0.397 0.383 0.110 0.325 0.349 0.358 0.090
(0.255) (0.255) (0.255) (0.257) (0.253) (0.248) (0.254) (0.252)
Paternal reading score (base = 2)
0.985*** 0.947*** 0.918*** 0.818** 0.936*** 0.625* 0.954*** 0.530
0 (0.345) (0.344) (0.346) (0.343) (0.342) (0.337) (0.344) (0.338)
0.287 0.340 0.346 0.295 0.366 0.155 0.355 0.171
1 (0.334) (0.333) (0.334) (0.332) (0.332) (0.326) (0.333) (0.325)
-0.575* -0.521* -0.505* -0.411 -0.414 -0.265 -0.523* -0.145
3 (0.302) (0.301) (0.301) (0.300) (0.299) (0.295) (0.301) (0.294)
-0.942** -0.915** -0.927** -0.629 -0.839** -0.504 -0.927** -0.281
4 (0.403) (0.401) (0.403) (0.401) (0.399) (0.393) (0.401) (0.395)
Teaching score (base = high)
Very low
1.567*** 1.536*** 1.515*** 1.027** 1.422*** 1.556*** 1.498*** 1.119***
(0.418) (0.417) (0.418) (0.420) (0.415) (0.408) (0.417) (0.411)
Low
1.135*** 1.155*** 1.206*** 0.799** 1.068*** 1.072*** 1.174*** 0.843**
(0.353) (0.352) (0.352) (0.354) (0.350) (0.344) (0.351) (0.346)
Medium
0.478** 0.503** 0.522** 0.318 0.431* 0.546** 0.497** 0.369*
(0.229) (0.228) (0.228) (0.228) (0.227) (0.223) (0.228) (0.223)
Talking whilst occupied score (base = high)
Low
2.579*** 2.526*** 2.561*** 2.264*** 2.261*** 2.193*** 2.523*** 1.936***
(0.365) (0.364) (0.365) (0.364) (0.363) (0.356) (0.364) (0.357)
Medium
1.057*** 1.042*** 1.051*** 0.911*** 0.954*** 0.898*** 1.038*** 0.801***
(0.223) (0.223) (0.223) (0.222) (0.221) (0.218) (0.222) (0.218)
38 month TV score (base =

Table 8.14: Estimated effects of Home Environment and Outings scores on Behaviour,
various specifications (N = 9416)
(1) (2) (3) (4) (5) (6) (7) (8)
Outings scores
Park/playground -0.978*** -0.964*** -0.982*** -0.548** -0.924*** -0.736*** -0.938*** -0.453**
(0.230) (0.229) (0.230) (0.219) (0.227) (0.219) (0.230) (0.214)
Visits to
-0.692*** -0.680*** -0.744*** -0.523** -0.479** -0.214 -0.672*** -0.304
friends/relatives (0.221) (0.220) (0.223) (0.207) (0.218) (0.212) (0.220) (0.207)
Places of interest -1.141*** -1.082*** -1.096*** -0.796*** -1.039*** -0.803*** -1.076*** -0.624***
(0.258) (0.258) (0.258) (0.243) (0.255) (0.246) (0.258) (0.239)
Places of entertainment -0.389 -0.357 -0.436* -0.489** -0.406* -0.452* -0.357 -0.572**
(0.249) (0.249) (0.249) (0.234) (0.246) (0.237) (0.249) (0.229)
Book score (base = high)
Very low 2.112*** 2.000*** 1.970*** 0.436 1.763*** 1.235*** 1.951*** 0.064
(0.468) (0.467) (0.467) (0.456) (0.462) (0.447) (0.467) (0.447)
Low 1.736*** 1.689*** 1.652*** 0.839*** 1.511*** 1.254*** 1.655*** 0.610**
(0.291) (0.291) (0.291) (0.281) (0.288) (0.278) (0.291) (0.276)
Medium 0.711** 0.689** 0.697** 0.293 0.606** 0.279 0.641** 0.029
(0.297) (0.296) (0.296) (0.280) (0.293) (0.283) (0.296) (0.274)
Toy score (base = high)
Very low 3.147*** 3.088*** 3.028*** 1.694*** 2.727*** 2.291*** 3.096*** 1.309***
(0.480) (0.479) (0.479) (0.455) (0.474) (0.459) (0.479) (0.446)
Low 2.096*** 1.997*** 1.982*** 1.006*** 1.765*** 1.537*** 1.989*** 0.846**
(0.355) (0.354) (0.355) (0.336) (0.351) (0.339) (0.354) (0.330)
Medium 1.179*** 1.141*** 1.152*** 0.600** 1.005*** 0.901*** 1.129*** 0.515*
(0.290) (0.289) (0.289) (0.272) (0.286) (0.276) (0.289) (0.267)
Damp/condensation/mould (base = none)
Minor problem 1.226*** 1.132*** 1.143*** 0.647*** 0.994*** 0.614*** 1.143*** 0.423**
(0.220) (0.220) (0.220) (0.207) (0.218) (0.211) (0.220) (0.203)
Serious problem 2.559*** 2.118*** 2.112*** 1.270*** 1.751*** 0.823* 2.119*** 0.547
(0.440) (0.444) (0.444) (0.417) (0.439) (0.425) (0.443) (0.410)
Adjusted R-squared 0.0838 0.0893 0.0919 0.1992 0.1108 0.1740 0.0916 0.2416
Controls included
Basic demographics X X X X X X X X
Income X X X X X X X
Childcare X X
Parenting X X
Maternal background X X
Maternal health etc. X X
Neighbourhood X X
8.5.7 Home Environment and Behaviour
The reported evidence of outings and the home based book and toy score are correlated with
behavioural scores before other proximal factors are considered (table 8.14). There is a strong
overlap between these factors and parenting behaviours which causes large declines in the their
importance when parenting is also included (column 4) or in the final column with all factors
considered. Yet apart from the overlap with parenting behaviours these relationships are not
123

greatly affected by the other proximal factors. Damp housing was also strongly correlated with
adverse behaviour. Here mother’s mental and physical health reflects part of this correlation.
Outings to the park, places of interest such as the Zoo, and to places of entertainment, and high
toy scores are associated with minor improvements in behaviour scores. Low book scores and
damp housing conditions are very minor influences on behaviour. All these factors, in turn, are
strongly related to family income.
8.5.8 Mother’s Childhood and Behaviour
The reported evidence of the mother’s relationship with her mother and how positive the mother
feels about her own schooling are strongly correlated with behavioural outcomes of the child
when other influences are not considered (table 8.15). These attitudes are strongly correlated in
turn with reports of physical and mental health (depression and self-esteem) and to a lesser
degree with parenting behaviour. So once these proximal influences are conditioned on the
mother’s own childhood experiences of school and relationship with her mother have only a
modest effect
Table 8.15: Estimated effects of mother’s childhood and family background controls on
Behaviour, various specifications (N = 9416)
(1) (2) (3) (4) (5) (6) (7) (8)
Mother’s relationship with own mother score (base = lowest quartile)
2 nd quartile -0.798**
(0.317)
3 rd quartile -2.250***
(0.305)
Highest quartile -3.522***
(0.304)
-0.649**
(0.317)
-2.085***
(0.305)
-3.342***
(0.304)
-0.690**
(0.317)
-2.115***
(0.305)
-3.359***
(0.304)
-0.453
(0.297)
-1.394***
(0.287)
-1.988***
(0.289)
-0.567*
(0.313)
-1.860***
(0.302)
-2.966***
(0.302)
0.241
(0.306)
-0.690**
(0.298)
-1.148***
(0.303)
-0.643**
(0.316)
-2.076***
(0.304)
-3.355***
(0.303)
0.045
(0.293)
-0.627**
(0.285)
-0.841***
(0.292)
Mother has history of truancy (base = yes)
No 1.610***
(0.403)
1.434***
(0.402)
1.388***
(0.402)
0.861**
(0.381)
1.516***
(0.398)
0.900**
(0.387)
1.377***
(0.402)
0.593
(0.374)
Mother feels school was a valuable experience (base = not sure/generally not/no)
Yes very
Yes generally
-2.695***
(0.317)
-1.530***
(0.267)
-2.591***
(0.316)
-1.472***
(0.266)
-2.559***
(0.316)
-1.463***
(0.267)
-1.837***
(0.298)
-1.018***
(0.251)
-2.302***
(0.314)
-1.226***
(0.264)
-0.795**
(0.312)
-0.512**
(0.259)
-2.537***
(0.316)
-1.456***
(0.266)
-0.614**
(0.300)
-0.321
(0.248)
Adjusted R-squared 0.0828 0.0890 0.0909 0.2010 0.1108 0.1653 0.0916 0.2416
Controls included
Basic demographics
Income
Childcare
Parenting
Outings & home env.
Maternal health etc.
Neighbourhood
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
124

Table 8.16: Estimated effects of maternal health, attitudes and social networks controls on
Behaviour, various specifications (N = 9416) (continued)
(1) (2) (3) (4) (5) (6) (7) (8)
Mother's physical health score (base = v high)
Very low
2.779*** 2.754*** 2.776*** 1.961*** 2.676*** 2.680*** 2.785*** 1.912***
(0.373) (0.373) (0.374) (0.360) (0.371) (0.373) (0.373) (0.359)
Low
1.286*** 1.276*** 1.293*** 0.801** 1.221*** 1.171*** 1.317*** 0.749**
(0.340) (0.340) (0.341) (0.327) (0.338) (0.340) (0.340) (0.327)
High
0.711** 0.711** 0.730** 0.374 0.699** 0.670** 0.747** 0.369
(0.329) (0.329) (0.329) (0.316) (0.327) (0.329) (0.329) (0.315)
Social networks score (base = low)
Medium
-0.803*** -0.783*** -0.806*** -0.757*** -0.520** -0.734*** -0.779*** -0.603**
(0.246) (0.246) (0.246) (0.236) (0.246) (0.246) (0.246) (0.237)
-1.337***
High
(0.262)
Social support score (base = low)
-0.536**
Medium
(0.259)
-1.324***
High
(0.292)
Total CCEI score (base = lowest quintile)
2nd quintile
3rd quintile
4th quintile
1.353***
(0.301)
2.083***
(0.320)
2.230***
(0.336)
Highest quintile
3.826***
(0.381)
Self-esteem score (base = highest quintile)
Lowest quintile
3.705***
(0.364)
2 nd quintile
2.208***
(0.353)
3 rd quintile
1.691***
(0.323)
4 th quintile
1.063***
(0.321)
Locus of control score (base = Internal)
Medium
0.637***
(0.236)
External
1.743***
(0.359)
-1.297***
(0.263)
-0.511**
(0.259)
-1.305***
(0.292)
1.343***
(0.301)
2.069***
(0.320)
2.170***
(0.337)
3.723***
(0.383)
3.680***
(0.365)
2.185***
(0.354)
1.682***
(0.323)
1.055***
(0.321)
-1.367***
(0.264)
-0.514**
(0.259)
-1.276***
(0.292)
1.338***
(0.301)
2.065***
(0.320)
2.156***
(0.338)
3.677***
(0.383)
3.724***
(0.365)
2.216***
(0.354)
1.687***
(0.323)
1.066***
(0.321)
0.620***
(0.237)
0.623***
(0.237)
1.667*** 1.627***
(0.361) (0.361)
Mother’s satisfaction with relationship (base = highest quintile)
Lowest quintile
2.350*** 2.311*** 2.300***
(0.353) (0.353) (0.353)
2 nd quintile
1.428*** 1.412*** 1.384***
(0.337) (0.337) (0.337)
3 rd quintile
1.663*** 1.658*** 1.650***
(0.329) (0.329) (0.330)
4 th quintile
0.791** 0.789** 0.795**
(0.331) (0.331) (0.331)
-1.088***
(0.253)
-0.305
(0.249)
-0.790***
(0.282)
0.998***
(0.290)
1.493***
(0.310)
1.309***
(0.328)
2.252***
(0.378)
2.743***
(0.353)
1.348***
(0.341)
0.928***
(0.312)
0.529*
(0.309)
0.765***
(0.227)
1.559***
(0.348)
1.685***
(0.342)
0.873***
(0.325)
1.045***
(0.318)
0.491
(0.319)
-0.810***
(0.266)
-0.458*
(0.258)
-1.151***
(0.291)
1.306***
(0.299)
2.073***
(0.318)
2.160***
(0.335)
3.744***
(0.381)
3.403***
(0.363)
1.996***
(0.352)
1.597***
(0.321)
0.979***
(0.319)
0.559**
(0.235)
1.520***
(0.359)
2.194***
(0.351)
1.366***
(0.335)
1.581***
(0.328)
0.743**
(0.330)
-1.168***
(0.263)
-0.397
(0.260)
-1.116***
(0.293)
1.301***
(0.301)
1.994***
(0.320)
2.054***
(0.337)
3.585***
(0.384)
3.426***
(0.369)
2.015***
(0.355)
1.566***
(0.324)
0.983***
(0.321)
0.514**
(0.237)
1.346***
(0.365)
2.166***
(0.353)
1.292***
(0.337)
1.553***
(0.330)
0.756**
(0.331)
-1.301***
(0.263)
-0.504*
(0.259)
-1.289***
(0.291)
1.347***
(0.301)
2.057***
(0.320)
2.179***
(0.337)
3.699***
(0.383)
3.669***
(0.364)
2.176***
(0.353)
1.686***
(0.323)
1.073***
(0.320)
0.617***
(0.236)
1.644***
(0.361)
2.336***
(0.353)
1.422***
(0.336)
1.670***
(0.329)
0.784**
(0.331)
-0.798***
(0.258)
-0.246
(0.249)
-0.622**
(0.283)
0.937***
(0.290)
1.451***
(0.309)
1.240***
(0.328)
2.170***
(0.380)
2.458***
(0.357)
1.203***
(0.343)
0.831***
(0.312)
0.476
(0.308)
0.643***
(0.228)
1.261***
(0.351)
1.598***
(0.343)
0.808**
(0.325)
1.006***
(0.318)
0.473
(0.318)
Adjusted R-squared 0.1612 0.1617 0.1635 0.2318 0.1740 0.1653 0.1641 0.2416
Controls included
Basic demographics X X X X X X X X
Income X X X X X X X
Childcare X X
Parenting X X
Outings & home
environment
X
X
Maternal background X X
Neighbourhood X X
125

8.5.9 Mother’s Mental and Physical Health, Family Conflict and Behaviour
Mother’s mental and physical health and family conflict are strongly related to behavioural
outcomes of children (table 8.16). There could be some reverse causality, in that the children’s
behaviour is affecting the mother, although this seems unlikely for physical health and measures
of conflict. The main cross-correlation between these indicators and other proximal influences is
through parenting behaviours (which include maternal bonding and discipline behaviours).
There is a strong interrelationship between maternal bonding, mental health (self-esteem, locus
of control and depression). All the measures retain a substantive independent effect on
behaviour outcomes. The social support scores become modest in their effects once other factors
are conditioned on.
Table 8.17: Estimated neighbourhood effects on Behaviour, various specifications (N =
9416)
(1) (2) (3) (4) (5) (6) (7) (8)
Average behaviour score of peers – predicted component (base = lowest quintile)
2 nd quintile -0.756 -0.837* -0.845* -0.627 -0.891** -0.833* -0.580 -0.585
(0.462) (0.460) (0.464) (0.429) (0.454) (0.454) (0.436) (0.420)
3 rd quintile -0.790* -0.937** -0.888* -0.948** -1.113** -0.911** -0.657 -0.902**
(0.467) (0.465) (0.466) (0.432) (0.458) (0.458) (0.440) (0.423)
4 th quintile 0.264 0.028 -0.063 -0.344 -0.303 -0.148 -0.096 -0.625
(0.472) (0.470) (0.484) (0.438) (0.465) (0.464) (0.445) (0.439)
Highest quintile -0.004 -0.261 -0.571 -0.403 -0.515 -0.385 -0.457 -0.780*
(0.475) (0.475) (0.502) (0.442) (0.469) (0.468) (0.449) (0.455)
Average behaviour score of peers – residual component (base = lowest quintile)
2 nd quintile -0.955** -0.971** -1.030** -1.308*** -1.058** -0.937** -0.975** -1.293***
(0.462) (0.459) (0.460) (0.427) (0.453) (0.453) (0.435) (0.417)
3 rd quintile 1.121** 1.165** 1.123** 1.015** 0.998** 1.132** 1.154*** 0.960**
(0.464) (0.462) (0.463) (0.429) (0.456) (0.455) (0.437) (0.419)
4 th quintile -0.380 -0.371 -0.501 -0.251 -0.319 -0.307 -0.000 -0.118
(0.466) (0.464) (0.466) (0.431) (0.457) (0.457) (0.439) (0.422)
Highest quintile 0.617 0.658 0.675 0.520 0.495 0.713 0.703 0.484
(0.462) (0.460) (0.460) (0.428) (0.454) (0.454) (0.436) (0.417)
Adjusted R-squared 0.0554 0.0647 0.0670 0.1937 0.0916 0.0916 0.1641 0.2416
Controls included
Basic demographics X X X X X X X X
Income X X X X X X X
Childcare X X
Parenting X X
Outings & home
environment
Maternal
background
Maternal health etc. X X
X
X
X
X
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8.5.10 Neighbourhood and Peer Group
No neighbourhood influences were apparent for behaviour in our preliminary investigation but
there were very modest peer group effects. These, however, were only significant for the third
quintile and that made the pattern look rather inconclusive. Conditioning on other mediating
influences tends to produce a more consistent picture (table 8.17). Those children attending preschools
with other children with poorly reported behaviour have slightly better scores. This
probably reflects that the mother (who gives the report) is witnessing the behaviour of other
children at the pre-school and this is influencing their assessment of their own child. These
minor effects are thus not probably genuine but reflect reporting bias.
8.6 How do Parental Education and Income Influence a Child’s Early Behaviour?
Here we explore fully how income and parental education work through the proximal factors to
influence children’s behaviour. First we show the unconditional relationships between parental
education, family income and the child’s behaviour (table 8.18). The behavioural measure is
standardised such that the mean gap between the highest quartile of scores and the lowest is 25
points (2.5 standard deviations). Family income and parental education can explain less than 5%
of this even when no other factors are considered. Once other factors are introduced family
income and parental education are almost trivial in their conditional correlation with behaviour
scores. However, parenting behaviours including maternal bonding, teaching, reading etc. and
mother mental and physical health, especially self-esteem CCEI and locus of control scores, are
important predictors of the gap. All told the model can explain around 25% of this gap and of
the 6.5 points explained, 4.9 are attributable to these two groups of influences. Of the remaining
factors the home environment offers a modest contribution. Childcare, like parental education,
income, neighbourhood and maternal employment, has no substantive part to play in our data.
The differences in raw behaviour scores between the highest and lowest education and income
groups are thus modest in size and explained mainly by the cross-correlation with parenting and
mother mental and physical health. It should be noted again that our behavioural measure is
solely mother reported and does not correlate strongly with teacher based assessments for the
sub-sample where this is available and so these results need to be treated with some caution.
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Table 8.18: Decomposition of range of mean scores for various groups (Behaviour)
Difference in mean
scores
Explained variation –
contribution of:
Income
Points
Top and bottom quartiles of attainment
%
% total
explained
variation
variation
accounted
accounted
for by:
for by:
Points
%
% total
explained
variation
variation
accounted
accounted
for by:
for by:
Top and bottom quartiles of
household income
Points
%
% total
explained
variation
variation
accounted
accounted
for by:
for by:
Children of mothers with
CSE/no qualifications vs. a
degree
%
% total
explained
variation
Points
variation
accounted
accounted
for by:
for by:
25.2 100 100 25.2 100 100 4.6 100 100 4.6 100 100
0.7 2.8 62.3 0.1 0.6 2.1 0.6 13.0 13.1 0.3 6.8 6.8
Parental Education 0.4 1.7 37.7 0.2 0.8 3.2 0.6 14.2 14.2 1.5 33.4 33.4
Other Demographic
Variables
- - - 0.4 1.8 6.8 0.3 7.5 7.5 0.1 3.2 3.2
Childcare - - - 0.1 0.3 1.0 0.0 0.9 0.9 0.1 2.2 2.2
Parenting - - - 2.9 11.5 44.1 0.9 20.6 20.7 0.6 13.5 13.5
Outings & Home
Environment
Mother’s childhood
and family
background
Maternal health,
attitudes and social
networks
Neighbourhood and
peer group
Unexplained
variation
- - - 0.4 1.8 6.5 0.4 8.4 8.5 0.4 9.4 9.4
- - - 0.3 1.1 4.0 0.2 4.5 4.5 0.3 6.3 6.3
- - - 2.0 7.9 30.4 1.4 30.2 30.4 1.1 24.0 24.0
- - - 0.1 0.5 1.8 0.1 1.2 1.2 0.1 1.2 1.2
24.1 95.5 - 18.6 73.9 - -0.0 -0.4 - 0.0 0.0 -
128

129

9. Conclusions
This research has used the highly detailed Avon Longitudinal Survey of Parents and Children
(ALSPAC), a birth cohort of 12,000 children born in the Avon area in 1991-2, to explore the
origins of variation in pre-school behaviour and educational attainment scores at school entry.
The intention has been to explore what factors are correlated with early learning deficits and
behavioural problems and, in particular, to assess how raw correlations between parental
education and family income are transmitted into the observed outcomes through mediating
factors.
Under this approach we explore seven groupings of factors which are very detailed in the
ALSPAC study and which may act as mediating influences between family background (income
and education) and children’s outcomes. These are parenting behaviour, the neighbourhood and
peer group, maternal employment, maternal mental and physical health, mother’s childhood
experiences, the home environment and pre-school childcare. We refer to these as proximal
factors.
Educational Attainment
Our measure of educational attainment on school entry is based on teacher delivered tests
undertaken in the Avon area at this time. This test score is fairly strongly correlated with later
test scores at age 7 measured by the ALSPAC team and with the national KS1 tests. Our
available information can explain around a quarter of the gap between the highest and lowest
achieving quarters of the distribution (once age related variation, which explains 10% of the
overall variation, is excluded).
We find the following results for proximal or mediating influences in explaining the variation
between the highest and least achieving children:
• Maternal employment patterns have no significant influence.
o Parenting behaviours, especially teaching and reading activities by parents are very
important.
• The key parenting influences is maternal teaching behaviour in the pre-school period.
The magnitude is such that children of mothers who are in the lowest 8% in terms of age
of starting and range of maternal teaching are 3.5 points behind other similar children (or
14 percentile points lower in the distribution). Those children in the next 11% of the
distribution are 2 points (or 8 percentile points lower in the distribution) behind in the
130

distribution. These are large effects.
o Maternal reading is less important but less intensive reading does result in substantial
deficits.
o Other parenting behaviours (6+ hours of TV a week at 18 months and breast-feeding
beyond 6 months) are of moderate importance.
• Neighbourhoods and peer groups are almost as important as parenting behaviours.
o For neighbourhood, the key indicator is not financially based but is a measure of the
educational attainment of the wider population including adults and older children in
the neighbourhood (note there is a strong correlation between educational attainment
and income/employment at this area level)
o In addition the attainment of peer children attending the same pre-school is a
substantial influence on a child’s attainment. The analysis suggests that if a child is
attending a pre-school where the other children have well educated parents who are
heavily engaged in teaching and providing a high quality home learning environment
this benefits the focus child over and above their own family learning environment.
• Outings and Home Environment are the next most substantive in their impact on
children’s attainment.
o A very low book score (which in turn is associated with low reading and low
income) which affects the 6% of children has a substantive influence on child
attainment conditional on confounding influences.
o A very low toy score is also detrimental to child cognitive development.
o There is no evidence that better educated parents are providing higher quality books
or toys, in terms of their impact on child development.
o Trips to Libraries and not attending department stores have weak (positive)
influences on development.
• Childcare is a much more modest influence on children’s attainment (other than through
the peer group noted above) and the results suggest that:
o Limited hours of care by partner up to age 2 is modestly beneficial to child
development
o Extended care by friends, grandparents and other relatives up to age 2 is modestly
harmful.
o Nursery care (in school class or private setting) prior to entry into school is modestly
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eneficial to children’s attainment on entry.
o There is no evidence that full-time Nursery exposure at 3 or 4 is more beneficial than
part-time. Nor is there evidence that attending a Nursery is more beneficial for those
with less educated mothers.
• Mother’s mental and physical health, family conflict and mother’s childhood are not
major influences on children’s educational attainment at age 4.
We then focus on the routes by which family income and parental education transmit to child
educational outcomes.
• There is a total 6.6 point attainment gap between rich and poor children. Around a
quarter of this raw correlation between income and attainment can be explained by
observable proximal influences that have a plausible causal link. The main influences are
the home environment, the neighbourhood and peer group, and childcare. Another
quarter of the original variation in attainment correlated with income remains attributed
to family income. This residual correlation reflects neither parental education, parenting
styles nor other influences studied here. This too could be a causal influence of income
but its status is uncertain. So at most around half of the raw difference in attainments
between the richest and poorest pre-school children can be thought of as genuinely
driven by income and probably more like a third.
• The gap in attainment between children of mothers with CSE level qualifications or
lower and degree holding mothers is much larger than between the poorest and richest
families. The proximal influences considered here do more work in explaining how
parental education is transmitted through to children than they do for income. Together
the major proximal influences account for some 40% of raw gap in attainment between
the children of well and less educated mothers. If we include residual income as another
mechanism this rises to nearly a half. Of the proximal influences the most important
contribution comes from the home environment, the neighbourhood/peer group and to a
lesser degree parenting behaviours (through teaching and reading). Whilst parenting
behaviours are the strongest predictors of overall child attainment they differ only
moderately between well and poorly educated mothers and hence they do not dominate
the relationship between parental education and child outcomes. Around 40% of this raw
unconditional gap remains unexplained by other factors observed in the data. This
residual correlation with parental education could also reflect omitted factors such as the
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genetic inheritance or other transmission mechanisms not measured in ALSPAC.
Children’s Behaviour
The results for behaviour show less effect of income and education. Once other factors are
introduced family income and parental education have almost trivial conditional correlation with
measured behaviour.
• Parenting behaviours (including maternal bonding, teaching, reading etc.) are extremely
important predictors of behaviour. The most important parental behaviours are parental
bonding at 8 months, discipline strategies and talking whilst engaging in other activities
such as housework. Low teaching and reading scores are weakly associated with adverse
behaviour (though causality could run the other way).
• There is a strong inter-relationship between maternal bonding and mental health
(measured as self-esteem, locus of control and depression).
• The results suggest that poor physical health, maternal depression/anxiety and low selfesteem
are intertwined with weaker parenting behaviours to produce adverse behavioural
scores. There could be some reverse causality here, in that the child’s behaviour is
affecting the mother, although we use measures of these factors taken at least 2 years
before the child’s behavioural outcomes are observed to minimise this.
• Of the remaining factors the home environment has a modest association.
• Childcare, like parental education, income and maternal employment, has no substantive
part to play.
• The differences in raw behaviour scores between the highest and lowest education and
income groups are modest in size and explained mainly by the correlation of parenting
and mother’s mental and physical health.
In Summary, the key findings are:
• Parents teaching (e.g. teaching children a number of items such as shapes, colours and
numbers) and reading to children during the pre-school period is extremely important for
children’s early learning. However, differences in teaching and reading do not explain
very much of the early learning deficits of those from poorer or less educated families.
There is no evidence that better educated parents teach and read to young children more
effectively; they just do it somewhat more often.
• Exposure to pre-school childcare is modestly beneficial to early learning but it is a minor
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factor in explaining early learning deficits observed. Full-time childcare prior to school
entry is no more beneficial than part-time but .attending a pre-school containing high
achieving children is beneficial..
• Centre based care at or before age 2 is as beneficial to children’s learning as other paid
care (e.g. child minders) but is associated with worse behaviours. Long hours of care (20
or more hours a week) up to the age of 2 by unpaid carers, such as friends and relatives,
is associated with both lower attainment and worse behaviour, whilst fathers
involvement before age 2 is modestly beneficial.
• The home environment in terms of books and toys and the attainment of the peer group
attending the same pre-school are substantial factors behind the early learning deficits of
children from poorer and less educated families. These proximal are strongly related to
family income levels.
• Mother’s mental and physical health, especially stress, anxiety and self-esteem, and low
quality relationships between parents are strongly related to poor behavioural outcomes.
134

135

Up To 7
Part 2
The Persistence of Early Learning Variations
Through the First Two Years of Schooling
10. Introduction
Part 1 covered development in the pre-school period, and looked at what insights the Children
of the 90s database could provide about how dimensions of family background transmit into
children’s educational and behavioural development on entry into primary school. Part 2 looks
at the persistence of the picture up to age 7 through the first two years of schooling. It aims to
assess how the first two years of education in school changes the picture of the key influential
factors on child development prior to school entry. In particular, the aim is to assess how aspects
of early learning deficits based on family background and the role of pre-school childcare
experiences persist or decay on school entry. In addition, we explore the importance of the
particular school attended for the degree of persistence of early educational (dis-)advantages.
Both studies use the same rich ALSPAC Children of the 90s database developed at the
University of Bristol.
At age 7, attainment is measured by Key Stage 1 tests (see section on Data and Measures used
for details) and an independent assessment of literacy and language development. The two age 7
measures record very similar subject matter and are very highly correlated. They are in effect
two replications of measuring child attainment. So we combine these two age 7 measures so as
to improve the accuracy of the measure used.
Drawn from the first part of this study, we look at a range of family background factors often
associated with variance in educational achievement, such as teen motherhood, family size,
parental education and income. We look at how child outcomes relate to family functioning and
early education experiences. We focus on six main groups of factors, which were found in the
previous pre-school study to mediate between dimensions of family background and attainment.
These are
• Parenting patterns - covering reading, activities (e.g. singing, bathing, playing),
136

teaching, etc.
• The home learning environment and outings
• Child care usage covering types and extent of care up to age 2 1/2 and more detailed
study of child care exposure and limited measures of quality prior to school entry at age
4
• Maternal physical and mental health, especially depression
• Mother’s childhood experiences
• The neighbourhood of residence and peer groups in pre-school providers
The details of how the components which make up each grouping were identified are shown in
Part 1.
The approach of the report
In our examination of these interrelationships in Part 1, we focused particularly on the impact of
parental education and income on outcomes, examining the pathways (the factors listed above)
through which income and parental education operate to affect child outcomes at age 5.
Causality in this area is obviously difficult to infer with complete confidence owing to the
complexities of such interrelationships. Nevertheless we explored plausible pathways (or
proximal factors) through which the distal factors (income and parental education) might affect
children’s development. As well as parental education and income, we also explored other
family characteristics and their relationship with our mediating factors. These are age of mother
at birth of child, numbers of siblings and lone parenthood. Here we examine whether these early
childhood influences persist on entry to school. The expectation is that the entry into formal
schooling may mitigate some dimensions of disadvantage from the pre-school period.
The modelling approach adopted for the data observed at age 7 replicates the results reported in
the first part of the analysis for age 5. Then we formally test a value-added model for
differences in child trajectories to see if value-added is associated with these factors. Since
children are at school and subject to school influences, we test the value-added models for
robustness to inclusion of school effects (dummies for each school in the Avon district). Where
we observe substantive changes in the relationship between a factor and educational attainment
at ages 5 and 7, an assessment needs to be made as to whether this is a genuine change or
reflects systematic reporting errors. This is discussed further below when we discuss the data
and measures used.
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11. Data and Measures of Child Outcomes
The Avon Longitudinal Study of Parents and Children (ALSPAC) is a cohort study of around
14,000 children born in the Avon area of the UK in 1991 and 1992. Hence the pre-school period
we consider was after the bulk of the major expansion of early return to work by mothers that
occurred in the mid-late 1980s, (see Gregg et al. 2003) but before the guaranteed half day places
at pre-school for four and most recently 3 year olds. The early school period (often described as
Infants in the school system) is for the three school years starting 1995-1997 and is completed
by 1999. This period pre-dates the bulk of the moves to reductions in class sizes in primary
schools, but does partially cover the introduction of the literacy hour in September 1998. Hence
the last two of our three-school-year cohort experienced some literacy exposure, but it should be
noted that on its introduction the focus of the literacy hour was mainly on slightly older
children.
Mothers in the ALSPAC Survey complete up to three surveys a year, one relating to the
characteristics of herself and the household in general and two relating to the child 11 . In
addition, mothers answered four questionnaires during their pregnancies. The ALSPAC survey
also contains data from sources other than self-completion questionnaires. The ALSPAC team
have run a number of clinics for children from the age of seven onwards in which they are able
to directly assess various aspects of the children’s development. Records from schools, referred
to below, can also be matched to the individual children so data is available on school-based
assessments at ages 4 to 5 and again for ages 6 to 7.
11.1 Measures of Cognitive attainment
The two school-based measures of cognitive development available in ALSPAC are the Entry
Assessment (EA) test taken at age 4 or 5 and the Key Stage 1 assessment, which is administered
in Year 2 at age 6 or 7. Each test is composed of four sub-scores that capture ability in reading,
writing, mathematics and language skills (EA only) or spelling (KS1 only). Our third
assessment of cognitive ability was administered, by the ALSPAC team, to children at the age
of 7. This ALSPAC test was labelled Focus @ 7 and is a literacy score. This score is composed
of a number of sub-scores, capturing skills in reading, spelling and the manipulation of words.
To combine the sub-scores for each measure into one overall score we used the technique of
factor analysis. This method allows the data to dictate the relative weights attached to each
11 The mother’s partner also received annual questionnaires but the response is patchy.
138

component and so to distil the maximum possible information into a single measure. Each of the
three resulting scores were then normalised to have a mean of 100 and a standard deviation of
10.
As is inevitable in a survey of the scale of ALSPAC, attrition results in smaller sample sizes for
the later assessments of child development. So by age 7 there were 9,500 children in the full
study. In addition to this problem, parents were required to give written permission for the
release of the school-based test results. The sample sizes for the Entry Assessment and Key
Stage 1 scores are therefore substantially smaller than the full sample. The EA test had an
additional sample loss because this was not a national test at that time and hence children who
had left the Avon area or entered into some independent schools were not tested. Likewise the
Focus @ 7 test required parents to bring the child to an ALSPAC clinic and this too results in a
reduced sample. Part 1 of this analysis used the attainment measures at 4 or 5. At age 7 we have
two alternative measures of cognitive development, one based on a school based participation in
the national Key Stage 1 test for which we only have children whose parents provided
permissions for this matching, and an ALSPAC assessment centre based test which is available
for those who attended the clinics held by the ALSPAC team. As most permissions came at
these clinics the two samples strongly overlap. The ALSPAC Focus @ 7 test has 7357
observations and the KS1 tests 6030 and 5852 provide information on both scales. The EA test
has just under 5,000 cases all drawn from the KS1 sample.
The reduced sample sizes raise the question of whether there is major variation in the
characteristics of the population reporting a test score and those that don’t as a result of attrition
and giving of permission to match to the ALSPAC data/attending a clinic. We investigated this
issue for a range of observable characteristics such as household income, mother’s age and
educational attainment, etc and concluded that there is little variation in the composition of each
sample. The only clear sample composition difference is an under-representation of lone parents
in the ALSPAC sample. This is substantive among never partnered lone parents and those
becoming lone parents within the first year or so of the child’s life. Hence there appears to be no
substantive attrition bias in the sample composition as measured on observable characteristics
other than too few lone parents but there may well be unobservable differences. We have chosen
not to re-weight the data to raise the size of lone parent population, as those remaining may be
unrepresentative of those not reporting. However, the analysis needs to have a specific caveat
about the representativeness of the lone parent sample.
139

As a guide to interpreting the size of our estimates, assuming a normal distribution an increment
of 1 point (i.e. a tenth of a standard deviation) results in a shift from the median to the 54 th
percentile, while an increment of 5 points (or half a standard deviation) results in a shift from
the median to the 69 th percentile. Table 11.1 shows the pairwise correlations between the EA
score, and two other measures of cognitive attainment – the Key Stage 1 score, and an ALSPAC
administered literacy score taken at 7 years.
Table 11.1: Pairwise correlations between entry assessment, KS1 and Focus at 7, all age
adjusted.
Entry
Assessment
KS1 Focus @ 7
Average
KS1 – F @
7 score
Entry
Assessment
1.0000
KS1 0.5523 1.0000
F @ 7 0.4389 0.8366 1.0000
Average KS1- F
@ 7 score
0.5105 0.9482 0.9430 1.0000
Max. sample
size
4, 996 6,030 7, 329 7, 537
Here KS1 and Focus @ 7 scores were adjusted to allow for variation in age. KS1 is undertaken
at a point in time when children’s ages will vary within the year. The ALSPAC clinics
approached children when they reached a specific age (so as to smooth the flow of children
attending through out a year) and so there is little age variation among the children in the Focus
@ 7 data. To adjust for these differences, KS1 scores were regressed against month of birth and
year of taking the exam, and then standardised to again give a mean of 100 and standard
deviation of 10. Focus @ 7 scores were regressed against the age of the child when taking the
test and also standardised. The school based Key Stage 1 and the ALSPAC literacy test have a
very high correlation of 0.84, which suggests these can be considered as two alternative
estimates of cognitive attainment with some measurement error.
As the two measures are coincident in timing and very similar in content and extremely strongly
correlated, taking an average of the two will reduce measurement errors in the data for those
where we have both observations. So with both the scores now cleaned for differential age when
the test was sat, an average score was calculated by simply summing the two scores and
dividing them by two. In order to maximise the sample where only one of the test score
observations is available we use data where just one of the two measures is observed, but
140

included dummies for which source is used for this single observation. This is more of an issue
for the maximum age 7 sample than for the case where we restrict ourselves to the presence of a
valid Entry Assessment score at age 4/5 as well. This is because the EA sample is the most
restrictive and relies on permissions, which overlap almost perfectly with KS1 and strongly with
attending a clinic. EA scores were also adjusted for age, so that when determining the value
added both scores would be clean. The EA test is moderately strongly correlated with test scores
at age 7. For this test there is a higher correlation with the KS1 score, which is also a schoolbased
assessment. The correlation with the averaged age 7 measure is 0.5. Hence the EA test is
a reasonably strong predictor of later attainment but there is clearly substantial error, as the age
difference between EA and the Focus @ 7 and Key Stage 1 tests is around two years. As the
averaged measure at 7 comes from two independent assessments of the child at the same date,
the bulk of any measurement error will be in the EA test. As this test was undertaken by
teachers and has room for more individual discretion than the national KS1 test, there is a
danger of teacher specific reporting effects in the EA scores. In comparing the results for the EA
test scores and later measures we need to be conscious of the potential teacher specific bias and
of the potential for teachers to have subjective judgements more generally.
11.2 Predictors of attainment by Age 5 and the Role of Mediating Influences
In Part 1 of the study, the rich ALSPAC data was explored to identify the major predictors of
cognitive attainment on entry into school. The basic demographic characteristics of families are
strongly correlated with child attainment on school entry and Part 1 attempted to suggest what
aspects of family functioning and decision making act as the routes by which these background
characteristics impact on child outcomes.
Table 11.2 provides a listing of the variables included in the final analysis, which formed a
substantive contribution to attainment. They are grouped under headings that will form the basis
of our discussions here about which factors decay in their impact and which persist in the early
school years. The main groupings that predicted attainment at age 5 were demographic factors
including parental education, age of mother, gender and numbers of siblings. In addition, key
proximal factors covered parenting behaviours, which included teaching and reading to the
child, neighbourhood and peer groups who attended the same pre-school and the home leaning
environment which covered books and toys. Mothers’ mental and physical health and childhood
experiences were not major influences on educational outcomes.
The raw gap between attainment of children with the least and most educated mothers was 9.5
141

points at age 5 or a standard deviation. Other background characteristics and our mediating
influences can explain around 60% of the effect of parental education on attainment. The results
suggested that parenting behaviour and the home environment measures are the strongest
mechanisms through which parental education operates. However, family income is also a
substantive route through which parental education (especially partner’s education) impacts on
attainment, as are the neighbourhood and peer group. Pre-school childcare is not a major route
by which well-educated parents increase their children’s attainment, nor do we find that
children from disadvantaged families or with less well educated parents benefit especially from
attending pre-school nurseries or similar provision. The study also assessed whether bettereducated
parents undertake the mediating activities (e.g. reading to and teaching the child) more
effectively; the evidence suggests not.
Table 11.2: Groups of variables used as controls in Entry Assessment regressions
Basic
demographics
Mother’s highest
qualification
Partner’s highest
qualification
Lone parent
status
Income Childcare Parenting
Log average
weekly net
income
Care by partner
pre-age 2
Care by
friend/relative
pre-age 2
Care by paid
person pre-age
2
Maternal
reading score
Teaching score
18 month TV
score
Outings Scores &
Home
Environment
Department store
outings score
Library outings
score
Book score
Mother’s childhood
and family
background
Tenure of mother’s
childhood home
Mother’s father
absent from
childhood home
Mother’s mothers
highest qualification
Maternal health,
attitudes and
social networks
Social support
score
Locus of control
score
Neighbourhood
Education domain
deprivation score
Average EA score of
peers – predicted
component
Average EA score of
peers – residual
component
Mother’s age at
birth
Centre-based
care pre-age 2
Breastfeeding
Toy score
Mother has a history
of truancy
Ethnicity
Nursery class
age 3/ 4
Mother feels school
was a valuable
experience
Gender
LEA nursery
school age 3/ 4
Birth weight
Private day
nursery age 3/ 4
Special care unit
at birth
Nursery (type
undefined) age
3/ 4
Younger siblings
by 47 months
Playgroup age
3/ 4
Older siblings
Other centrebased
care age
3/ 4
Cohort year
Partner’s
employment at
47 months
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Lone parenthood was not a statistically significant influence on early attainment in any
specification. The main conclusion was that children of lone mothers are not performing worse
than their peers, once other factors are conditioned on (especially mothers age and income). But,
as already noted, our sample of lone parents is not representative and so care needs to be
exercised here.
Teen motherhood has an especially large negative association with the child’s cognitive
attainment at age 5. The proximal routes explored can explain around 40% of this attainment
deficit, with family income being the most substantive route. But all factors make some
contribution. The positive benefits of older motherhood are much better explained by the
observed mediating factors, with parenting behaviour and income being the major two
influences.
Children from non-white families appear to do slightly less well on entry to school than white
children. About a third of this can be explained by observed differences in the groups of more
proximal influences used here. The biggest influence is in the home environment (book and toy
scores) and outings measures. Income also plays a role. Parenting behaviour, maternal
employment and mental health and social support are unimportant as routes explaining the gap
between non-whites and whites.
Coefficients on low birth weight, gender of the child and the presence of younger siblings are
not greatly affected by the introduction of the groups of proximal variables. The coefficients on
older siblings are substantially reduced by inclusion of parenting behaviours, suggesting that the
influence of siblings is to slow child development by reducing parental inputs to the child,
especially teaching and reading.
The raw difference in attainment at age 5 between children from the highest and lowest quintiles
of family income was 6.6 points or two thirds of a standard deviation. Around three quarters of
this correlation is explained by other background demographics (mainly parental education) and
our mediating influences. The main routes through which income impacts on children by age 5
are through the home learning environment (books and toys) and the neighbourhood and preschool
peer group.
143

11.3 Strategy for Comparing Findings at Ages 5 and 7
In what follows we present results in four columns, all of which contain the same set of
variables from Part 1 of the study, representing the key drivers of early learning in children prior
to entry into school. We report the results of a single large regression in sections. We examine
how the situations at age 5 and 7 compare on a common sample (4996 observations), whether
the age 7 results are robust to including a larger maximum possible sample (7537 observations),
and whether there are significant changes in the effect of behaviors and parental attributes on a
value added measure between ages 5 and 7. In the first column we show results for the
maximum sample size we can observe at age 7, this is followed by the common sample that has
both age 7 and age 8 EA test results and this is followed in turn by the EA results for this same
sample. The final column is a simple value added (or change) measure that is just the age 7
score minus the age 5 score.
144

145

12. Background Characteristics
We start by looking at the impact on attainment at age 7 of the basic demographic
characteristics that are strong predictors of age 5 assessment. We first present results without the
mediating factors included so that broader relationships between family background and child
attainment can be observed (Table 12.1). The results comparing the larger and restrictive
samples (columns 1 and 2) for the average attainment score at age 7 are very similar. In no case
are the estimated coefficients significantly different from each other. In addition, the
comparison between the age 7 score results and the EA test results show very similar patterns in
most cases.
There are a number of results where the general pattern of stability does not hold. Firstly, we
see that children of lone parents are performing less well in the age 7 data than the age 5 data,
especially in the expanded sample. However, for sampling reasons already discussed, the lone
parent results need to be treated with caution. Next we come to mother’s age, where although
the signs are similar the magnitudes of the adverse effects are substantially lower. This shift
may reflect a reduction in the power of the mediating influences associated with teen
motherhood or a general catch up by these children. Alternatively it could reflect bias in the EA
results if teachers are systematically under-scoring children with young mothers. The same story
applies to children from ethnic minorities. In the EA tests these pupils were scored as under
performing compared to those from the white population. However, in the average test results at
age 7 this has completely turned around. Again this could reflect rapidly improving child
development or that teachers were systematically under-scoring these children on school entry.
The gender of the child makes less of a difference at age 7 than at age 5, although girls are still
significantly ahead of boys in educational development. This may well be a genuine
developmental catch up. Likewise very low birth weight is associated with significantly less of a
deficit in the age 7 data.
Table 12.2 reports results with the mediating influences included. These differ from the results
reported in table 12.1 to the extent that the mediating factors transmit family background
through to attainment. If some dimensions of these pre-school entry mediating factors are
becoming less important as the child grows we would see that they would explain less of the
family background effects. This will be explored in more detail in the final section of the report.
Broadly the patterns of results are very similar after this conditioning. This is easiest to see in
the value added measures in Tables 12.1 and 12.2. The introduction of the mediating variables
146

leaves the value added regressions almost identical. It follows that the influence of the
mediating factors in transmitting the relationship between family background and educational
attainment has remained very much the same as the children have aged. So any differences
between the two ages in the effect of family background impact on child outcomes is driven by
the unexplained component of each family background measure. With regard to the age of
motherhood, it is now the case that almost all the attainment gap, at age 7, can be explained by
the mediating influences. The attainment gap between children of teen mothers and for those
aged over 35 of 1.5 points at age 5 (Table 12.1) has fallen to just 0.33 points after conditioning
on the mediating routes through which such a distal factor impacts on children. For numbers of
siblings, parental education and family income the mediating factors make substantial
contributions to explaining how family background impacts on child attainment at 7. However,
for gender, low birth weight and ethnicity explain virtually nothing. So at this age the fact that
girls are ahead of boys does not reflect increased parental teaching or reading to girls or
exposure to different peer groups.
147

Table 12.1 Basic Demographics without mediating factors included – Average Score at 7
and Entry Assessment at 5
Full Sample Average
Score
Restricted Sample
Average Score
148
Entry Assessment
No. of observations 7537 4996 4996 4996
Log of household income
Early Measure
1.452***
(0.280)
Mother’s highest qualification (base = vocational/O-level)
CSE/none
-2.146***
(0.315)
A-level
0.953***
(0.243)
Degree
1.948***
(0.340)
Partner’s highest qualification (base = vocational/O-level)
CSE/none
-1.476***
(0.296)
A-level
0.408
(0.256)
Degree
1.994***
(0.325)
Lone parent status (base = never lone parent)
Intermittently, with partner at 47
months
Intermittently, no partner at 47
months
Since birth
Mother’s age at birth (base = 25-29)
1
(0.573)
Older siblings (base = none)
1
2
3+
-1.406***
(0.247)
-2.520***
(0.327)
-3.732***
(0.494)
Partner’s employment status at 47 months (base = in work)
-0.776*
Not in work
(0.418)
1.810***
(0.367)
-1.935***
(0.393)
1.064***
(0.318)
2.184***
(0.483)
-1.579***
(0.369)
0.446
(0.327)
2.369***
(0.449)
-0.947
(0.827)
-0.174
(0.673)
0.041
(1.281)
-1.142
(0.971)
-0.606
(0.384)
0.297
(0.300)
0.477
(0.434)
1.326**
(0.676)
2.840***
(0.246)
-1.033
(0.660)
-0.605**
(0.257)
-1.177**
(0.545)
-0.138
(0.309)
-1.690**
(0.746)
-1.603***
(0.324)
-2.928***
(0.432)
-3.854***
(0.639)
-0.752
(0.540)
2.189***
(0.387)
-2.205***
(0.414)
1.031***
(0.335)
3.040***
(0.510)
-1.540***
(0.389)
0.417
(0.345)
2.280***
(0.473)
0.706
(0.872)
0.264
(0.710)
0.067
(1.352)
-3.329***
(1.025)
-0.755*
(0.405)
0.578*
(0.317)
0.982**
(0.458)
-2.080***
(0.713)
3.642***
(0.260)
-2.760***
(0.696)
-0.787***
(0.271)
-0.270
(0.575)
-0.217
(0.326)
-2.351***
(0.787)
-1.371***
(0.342)
-3.167***
(0.456)
-4.890***
(0.675)
-0.448
(0.570)
Simple Value Added
-0.379
(0.404)
0.270
(0.432)
0.033
(0.350)
-0.856
(0.532)
-0.040
(0.406)
0.029
(0.360)
0.089
(0.494)
-1.653*
(0.910)
-0.438
(0.741)
-0.026
(1.410)
2.188**
(1.069)
0.149
(0.422)
-0.281
(0.331)
-0.505
(0.478)
3.406***
(0.744)
-0.801***
(0.271)
1.727**
(0.726)
0.182
(0.283)
-0.907
(0.600)
0.079
(0.340)
0.661
(0.822)
-0.232
(0.357)
0.239
(0.475)
1.036
(0.704)
-0.304
(0.595)
Adjusted R-squared 0.1361 0.1378 0.1678 0.0116

Table 12.2 Basic Demographics – Average Score at 7 and Entry Assessment at 5
Full Sample Average
Score
Restricted Sample
Average Score
149
Entry Assessment
No. of observations 7537 4996 4996 4996
Log of household income
Early Measure
0.986***
(0.292)
Mother’s highest qualification (base = vocational/O-level)
CSE/none
-1.294***
(0.324)
A-level
0.415*
(0.252)
Degree
1.146***
(0.365)
Partner’s highest qualification (base = vocational/O-level)
CSE/none
-1.137***
(0.296)
A-level
0.316
(0.253)
Degree
1.579***
(0.328)
Lone parent status (base = never lone parent)
Intermittently, with partner at 47
months
Intermittently, no partner at 47
months
Since birth
Mother’s age at birth (base = 25-29)
1
(0.571)
Older siblings (base = none)
1
2
3+
(0.429) (0.541) (0.562) (0.601)
-0.905***
(0.267)
-1.897***
(0.346)
-2.760***
(0.511)
-0.318
(0.308)
-1.472**
(0.747)
-1.136***
(0.351)
-2.394***
(0.456)
-2.946***
(0.663)
-0.314
(0.320)
-1.934**
(0.776)
-0.673*
(0.364)
-2.276***
(0.474)
-3.335***
(0.688)
-0.004
(0.342)
0.461
(0.829)
-0.463
(0.389)
-0.117
(0.506)
0.389
(0.735)
Partner’s employment status at 47 months (base = in work)
-0.455
-0.224
-0.086
-0.139
Not in work
(0.417)
(0.541)
(0.562)
(0.600)
Adjusted R-squared 0.1613 0.1639 0.2174 0.0257

13. Parenting Behaviours and Attainment Up to 7
This section and the following ones explore whether the mediating influences appear to have
different effects at ages 5 and 7. The mediating influences we consider all pre-date age 5 and so
we might expect that some aspects of what effects early child learning will dissipate as children
age. We start with parental interactions with their children between ages 8 months and 4 years.
Our first report showed that the parenting behaviours in the pre-school period were a strong
influence on EA scores. The largest impact came from maternal teaching behaviour in the preschool
period. The effect of maternal teaching was large, and greater than effects of mother’s
education. There was no evidence that the teaching of better educated mothers was more
effective than that of the less educated. Maternal reading behaviour was quantitatively less
important but less intensive reading resulted in substantial deficits. Other parenting behaviours
such as the child watching 6+ hours of TV a week at 18 months and breast-feeding beyond 6
months were of moderate importance.
Table 13.1 Parenting – Average Score at 7 and Entry Assessment at 5
Full Sample
Average Score
Restricted Sample
Average Score
Entry Assessment
No. of observations 7537 4996 4996 4996
Simple Value
Added
Maternal reading score (base = high)
Very low -1.292*** -1.521*** -1.657*** 0.137
(0.428) (0.554) (0.576) (0.615)
Low -0.738** -0.966** -1.015** 0.049
(0.375) (0.490) (0.509) (0.544)
Medium -0.381 -0.346 -0.328 -0.018
(0.253) (0.329) (0.342) (0.365)
Teaching score (base = high)
Very low -2.386*** -3.087*** -3.661*** 0.574
(0.443) (0.578) (0.601) (0.642)
Low -1.721*** -1.865*** -2.055*** 0.190
(0.354) (0.455) (0.473) (0.505)
Medium -0.694*** -0.905*** -1.110*** 0.205
(0.229) (0.296) (0.308) (0.329)
18 month TV score (base = 0-2 hours per week)
3 –5 0.118 0.129 -0.339 0.468
150

Table 13.1 Parenting – Average Score at 7 and Entry Assessment at 5 (continued)
(0.236) (0.317) (0.330) (0.352)
6 0.110 -0.108 -1.085** 0.977*
(0.357) (0.460) (0.478) (0.511)
Duration of breastfeeding (base = never)
Breastfed 6 months
0.784*** 0.968*** 0.763** 0.205
(0.282) (0.359) (0.373) (0.399)
Adjusted R-squared 0.1613 0.1639 0.2174 0.0257
Our analysis of age 7 attainment scores (Table 13.1) shows that maternal teaching and maternal
reading during pre-school remain significant determinants of cognitive outcomes. The relative
impact of the two behaviours is the same: teaching has a larger impact than reading. Again, the
impact of maternal teaching is greater than the effect of maternal education (shown in Table
13.1). Breastfeeding is also a significant determinant of age 7 attainment outcomes, but long
hours of TV watching when young appears no longer to affect outcomes.
A comparison of the impact of parental behaviours at age 5 and age 7 (comparison of columns 2
and 3) indicates that, with the sole exception of TV watching, the impact of the parental
behaviours on child outcomes is very similar at the two ages. There is some indication that the
impact of early teaching behaviour is slightly weaker for age 7 than age 5 outcomes, but these
changes are not statistically significant in the value added equation.
Given these similarities, it is not surprising that when we examine the effect of these behaviours
on value added – the change in test scores – they have no impact. Put another way, once we
condition on the effect these behaviours have on age 5 test scores, there is no diminution after
that age. There is one exception: high levels of TV watching when young appears to be
associated with high value added between age 5 and 7, so the early adverse effect diminishes.
So early TV watching has no lasting effect as children from households in which the TV is on a
lot when they are young catch up relative to their peers once at school.
151

14. Outings and the Home Learning Environment and
Attainment Up to 7
The outings and home environment measures are strongly correlated with parenting behaviours
around TV watching and reading and with having a low income. Entry assessment scores at age
5 were significantly associated with several aspects of the home environment. A very low book
score (which in turn is associated with low reading and low income), which affects the 6% of
children, was a substantive negative influence on child attainment. Similarly, a very low toy
score (measured at 24 months and covering 7% of children with lowest cumulative score for a
range of toys) was also found to be detrimental to child cognitive development. The pattern of
outings also affected attainment, where trips to libraries had a positive impact and attending
department stores a negative impact on development at age 5.
The results for attainment at age 7 indicate that these behaviours have a weaker link with
attainment. The effect of being in a home with a low book score is negatively and significantly
associated with the age 7 attainment score. The effect is somewhat smaller than at age 5
although the change is not statistically significant. The number of toys is no longer significantly
associated with attainment. The library as the destination of outings retains a significant impact
but one that is around half the size of its impact on age 5 outcomes. Trips to department stores
when young have no effect on attainment at age 7.
Conditioning on the link between these behaviours and outcomes at age 5, none of these
behaviours have a significant effect by age 7. In other words, once we have taken into account
their effect on entry assessment scores, they do not explain any of the variance in age 7 scores.
However, there is a pattern across all these variables that their impact has declined somewhat.
So these results suggest that the effects of the early home learning environment, which are
strongly linked to income, have modestly weakened by age 7.
152

Table 14.1 Outings and Home Environment – Average Score at 7 and Entry Assessment at
5
Full Sample
Average Score
Restricted Sample
Average Score
Entry Assessment
Simple Value
Added
No. of observations 7537 4996 4996 4996
Outings scores
Department stores -0.075 -0.249 -0.536* 0.287
(0.207) (0.268) (0.279) (0.298)
Library 0.402* 0.412 0.909*** -0.496
(0.217) (0.284) (0.296) (0.316)
Book score (base = high)
Very low -1.391*** -1.059* -1.833*** 0.773
(0.488) (0.628) (0.652) (0.696)
Low -0.303 -0.274 -0.505 0.231
(0.285) (0.371) (0.385) (0.411)
Medium -0.036 -0.043 -0.473 0.429
(0.277) (0.364) (0.378) (0.404)
Toy score (base = high)
Very low 0.101 -0.715 -1.364** 0.649
(0.474) (0.604) (0.628) (0.671)
Low 0.108 -0.196 -0.478 0.282
(0.333) (0.435) (0.452) (0.483)
Medium 0.237 0.038 0.389 -0.351
(0.265) (0.350) (0.364) (0.388)
Adjusted R-squared 0.1613 0.1639 0.2174 0.0257
153

15. Pre-School Childcare and Attainment Up to 7
The study of exposure to early childcare is discussed in three sections here, as well as in Part 1
of the report. Firstly, exposure to childcare up to the age of 24 months is considered, measured
by the types of care used and whether this was for 5-19 or over 20 hours per week. Then the
type of childcare or early education setting immediately prior to entry into school, normally at
age 4 is considered. Finally we measure who the child went to pre-school with – the peer group.
The last measure is considered later in the study whilst here we deal with the type of provision.
Table 15.1 Childcare Utilisation – Average Score at 7 and Entry Assessment at 5
Full Sample Average
Score
Restricted Sample
Average Score
Entry Assessment
No. of observations 7537 4996 4996 4996
Childcare pre-age 3
Used partner 5-19 hours per 0.001 0.109 0.584 -0.475
week (0.259) (0.342) (0.355) (0.380)
Used partner 20+ hours per 0.086 0.137 0.031 0.106
week (0.259) (0.342) (0.355) (0.379)
Used friend/relative 5-19 -0.494** -0.555* -0.234 -0.321
hours per week (0.240) (0.312) (0.324) (0.346)
Used friend/relative 20+ hours -0.567** -0.683** -0.907*** 0.225
per week (0.260) (0.338) (0.351) (0.375)
Used paid person 5-19 hours -0.415 -0.323 -0.501 0.178
per week (0.343) (0.467) (0.486) (0.519)
Used paid person 20+ hours -0.374 -0.042 0.117 -0.159
per week (0.293) (0.401) (0.416) (0.445)
Used centre-based care 5-19 -0.303 -0.645 -0.085 -0.560
hours per week (0.430) (0.599) (0.622) (0.664)
Used centre-based care 20+ 0.841 0.396 0.903 -0.507
hours per week (0.562) (0.827) (0.859) (0.918)
Childcare age 3 to 4
Nursery class -0.568* -0.344 1.047** -1.391***
(0.314) (0.403) (0.418) (0.447)
LEA nursery school 0.281 0.267 -0.192 0.459
(0.391) (0.513) (0.533) (0.569)
Private day nursery -0.115 -0.126 0.707 -0.832*
(0.330) (0.439) (0.456) (0.487)
Playgroup 0.401 0.060 -0.081 0.141
(0.247) (0.331) (0.344) (0.367)
Nursery (type undefined) -0.022 -0.067 1.157*** -1.224***
(0.263) (0.357) (0.371) (0.396)
Other -0.745 -0.787 -1.859 1.072
(0.767) (1.119) (1.162) (1.242)
Simple Value Added
Adjusted R-squared 0.1613 0.1639 0.2174 0.0257
The key findings in our assessment of the relationship between pre-school childcare and
attainment at school entry were:
• Limited hours of care by a partner (normally the father of the child) up to age 2 is
154

modestly beneficial to child development (this could well be outside the other partner’s,
usually the mother’s working hours)
• Extended care up to age 2 by friends, grandparents and other relatives is modestly
harmful.
• Nursery care (in school class or private setting) when aged 3-4 is modestly beneficial to
children’s attainment on entry to school.
• There is no evidence that full-time Nursery exposure at 3 or 4 is more beneficial than
part-time.
• There is no evidence that attending a Nursery is more beneficial for those with less
educated mothers.
Table 15.1 shows these patterns have substantially changed by the time children have
experienced the first two years of full-time schooling. The impact of nursery attendance in the
immediate pre-school period has vanished for all three groups of nursery care, school based,
private and unknown. The robustness of this result across all three types of nursery care makes it
clear this is a general phenomenon. Hence exposure to pre-school learning in a nursery setting
has no greater effect on attainment at 7 than just attending a parent run playgroup or indeed
nothing at all (although few children had no pre-school exposure). Note that the lack of
assessment of quality of childcare means these results are less reliable than other studies of the
influence of quality childcare on development such as the EPPE project (Sylva et al. 2004).
The one persistent finding is that childcare by friends or relatives is associated with modestly
adverse educational outcomes at age 7 and that this is now true for 5-19 hours as well as over 20
hours a week.
155

16. Mother’s Childhood and Family Background and
Attainment Up to 7
The influence of the mother’s childhood and family background on children’s attainment at age
5 was modest. The mother having grown up in an intact family throughout her childhood had a
modest positive influence as did not having a history of truancy and having a positive attitude
towards her own education experience. So these factors describing the mother’s own childhood
are generally not a major source of influence on the child once current circumstances are
conditioned on. By age 7 even these modest effects had further diminished and the only
sustained influence is the mother not having a history of truancy in her own childhood.
Table 16.1 Mother’s Childhood and Family Background – Average Score at 7 and Entry
Assessment at 5
Full Sample
Average Score
Restricted Sample
Average Score
Entry Assessment
No. of observations 7537 4996 4996 4996
Simple Value
Added
Tenure of mother’s childhood home (base = mortgage/owned
Council rented -0.605** -0.248 -0.499 0.252
(0.269) (0.340) (0.353) (0.377)
Other rented 0.695 1.042 -0.571 1.613*
(0.564) (0.762) (0.791) (0.845)
Other 0.106 -0.001 0.800 -0.802
(0.513) (0.676) (0.702) (0.750)
Mother’s father present in childhood home (base = not at all)
Throughout 0.680 0.593 1.267* -0.674
(0.527) (0.691) (0.718) (0.766)
Partly 0.451 0.305 1.137 -0.831
(0.571) (0.749) (0.778) (0.831)
Mother’s mother’s highest qualification (base = CSE/none)
0.225 0.269 0.354 -0.085
Vocational/O-level
(0.260) (0.341) (0.354) (0.378)
A-level 0.014 -0.035 0.730 -0.764
156

Table 16.1 Mother’s Childhood and Family Background – Average Score at 7 and Entry
Assessment at 5 (continued)
Full Sample Restricted Sample
Simple Value
Entry Assessment
Average Score Average Score
Added
(0.326) (0.447) (0.464) (0.496)
Degree 0.308 0.295 0.141 0.154
(0.528) (0.769) (0.799) (0.853)
Mother has a history of truancy (base = yes)
No 1.246*** 1.436*** 1.281** 0.155
(0.423) (0.535) (0.556) (0.594)
Mother feels school was a valuable experience (base = not sure/generally not/no)
Yes very 0.322 0.309 -0.321 0.631
(0.302) (0.399) (0.414) (0.442)
Yes generally -0.068 -0.285 -0.952*** 0.666*
(0.258) (0.335) (0.348) (0.372)
Adjusted R-squared 0.1613 0.1639 0.2174 0.0257
157

17. Mother’s Health, social networks, Family Conflict and
Attainment Up to 7
This group of potential influences were not found to have a large impact on children’s
educational development. The variable from this group retaining a significant effect was only
the mother’s locus of control measure. This, in itself, suggested that mother’s mental and
physical health and within family conflict had little influence on a child’s educational
development pre-school. As Table 17.1 indicates, the role of the mother’s locus of control
persists and may have increased marginally in strength. Mothers who feel their actions have
little impact also engage in less teaching and reading of their children than do other parents. So
this influence is quite substantial in that it may causally reduce parental teaching as well as
having a modest independent effect over and above this.
Table 17.1 Maternal Health, Attitudes and Social Networks – Average Score at 7 and Entry
Assessment at 5
No. of
observations
Full Sample Average
Score
7537
Restricted Sample
Average Score
4996
Entry
Assessment
4996 4996
Simple Value
Added
Social support score (base = low)
Medium 0.317 0.102 0.038 0.065
(0.244) (0.322) (0.335) (0.357)
High 0.177 0.074 0.463 -0.389
(0.259) (0.337) (0.351) (0.375)
Locus of control score (base = Internal)
Medium -0.370 -0.386 -0.591* 0.205
(0.228) (0.299) (0.311) (0.332)
External -1.423*** -1.646*** -1.046** -0.600
(0.372) (0.472) (0.490) (0.524)
Adjusted R-
squared 0.1613 0.1639 0.2174 0.0257
158

18. Neighbourhood and Peer Groups and Attainment Up to
7
This section looks at how the relationships between neighbourhood and peer group and child
attainment are related to other mediating influences. As part of the Focus @ 7 face-to-face
interviews with mother and child, the mother was asked to document childcare providers used
from the age of 3. Importantly this included the name of the provider as well as the broad type
of care and number of sessions attended. In many cases therefore we can observe many children
attending the same pre-school provider immediately prior to school entry. From this then we can
get a measure of attainment among the child’s pre-school peer group.
We were concerned that many children from one provider would be assessed by the same
teacher for their EA score so that any idiosyncratic teacher effects in scoring would muddy this
measure of the pre-school peer group. Such teacher effects should be just random measurement
error over the whole population. But for children within the same school this practice would
give the impression that the peer group was very influential whereas in reality it was just teacher
bias (a teacher scoring the children higher or lower than average). So we construct our measure
of the peer group from those who attended the same pre-school but did not attend the same
school (and so were scored for EA by a different teacher). These observations are thus
independent of the child. Where a child attends more than one provider we average across the
different providers, weighting by the number of sessions attended. This peer group measure will
capture a range of influences from the natural attainment of the other children, their family
background etc. and any common influence of the pre-school. It thus includes any effects of the
quality of the pre-school provider.
We can go further in separating influences. To get at childcare quality we do the following. We
predict the other children’s attainment using the general model containing all family background
and mediating influences provided in the data, but excluding the pre-school provider. This is
then a measure of the extent to which the children forming the peer group are from more
affluent, better educated families etc. This measure therefore does not contain any element of
the quality of pre-school provider as it is based only on the family characteristics of the children
attending it. The unexplained residual from these estimates (the difference between the actual
EA score and the predicted score of the peer group) then reflects the variation in attainment
across children in the peer group that is not explained by the child’s background. This will
contain the idiosyncratic component for each individual child averaged across the peer group,
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which will be influenced by the quality of the common attendance of the same pre-school
provider. It will also reflect any measurement error in the data. Large amounts of measurement
error will make it hard to observe childcare quality for the small samples which attend each
provider.
Table 18.1 shows, for the EA test, having attended a pre-school provider whose intake is from
families who have characteristics associated with high attaining children results in gains for a
child. This is probably because attending a provider that has children drawn from families with
high incomes, positive parenting behaviours, etc, has a strong peer group influence on a child.
The residual component of attainment among peer group children, the part not predicted by each
child’s background characteristics, is negatively associated with attainment. If this reflected
attainment amongst a common population attending the same pre-school then this relationship
should be positive. So we can find no evidence of a pre-school quality effect, this is probably
because this residual is being swamped by measurement error in the data. Finally, coming from
a ward where education levels in the population are low is associated with less child attainment.
By age 7 the main peer group effect disappears. Those who attended a pre-school with children
whose family backgrounds are associated with high achieving event (and who went on to
different primary schools) are no longer out performing other children. So early peer group
influences appear very short lived. Put together with the evidence on the lack of effects from the
types of pre-school providers used, this suggests that the form of pre-school education has no
lasting impact on children.
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Table 18.1 Neighbourhood – Average Score at 7 and Entry Assessment at 5
Full Sample Average
Score
Restricted Sample
Average Score
Entry Assessment
No. of observations 7537 4996 4996 4996
Simple Value
Added
Ward education -0.501*** -0.789*** -0.827*** 0.039
domain score (0.116) (0.157) (0.163) (0.174)
Average EA score of peers – predicted component (base = lowest quintile)
2 nd quintile
3 rd quintile
4 th quintile
Highest quintile
0.094 -0.053 0.164 -0.217
(0.472) (0.507) (0.527) (0.563)
0.454 0.168 0.939* -0.771
(0.473) (0.513) (0.533) (0.569)
0.730 0.384 1.864*** -1.480**
(0.479) (0.523) (0.543) (0.580)
0.106 -0.590 1.688*** -2.278***
(0.496) (0.558) (0.579) (0.619)
Average EA score of peers – residual component (base = lowest quintile)
2 nd quintile -1.040** -1.058** -0.989* -0.070
3 rd quintile
4 th quintile
Highest quintile
Full Sample Average
Score
Restricted Sample
Average Score
Entry Assessment
Simple Value
Added
(0.467) (0.499) (0.518) (0.554)
-1.356*** -1.356*** -0.683 -0.673
(0.468) (0.502) (0.521) (0.557)
-0.995** -1.034** -0.966* -0.068
(0.468) (0.501) (0.520) (0.555)
-1.719*** -1.635*** -0.802 -0.833
(0.460) (0.491) (0.511) (0.545)
Adjusted R-squared 0.1613 0.1639 0.2174 0.0257
The measured impact of the neighbourhood, captured by the extent of low educational
attainment in different parts of the population remains as strong at age 7 as at age 5. So whilst
the neighbourhood effect remains persistent, the influence of the peer group at a pre-school
provider is temporary.
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19. Overview of Family Background and Child
Development on Entry to School
The final substantive section brings together the major background and mediating influences
and provides an overview of the key drivers in child attainment by age 7. We start to do this by
partitioning out the amount of the total gap in attainment between the top and bottom quarters of
the attainment distribution at age 7 that can be explained by each grouping of influences.
Table 19.1 decomposes the variation in Average Attainment Score from tests at age 7 into that
which all the data used here can explain and the remaining unexplained variation. This
unexplained element will include any measurement error and unmeasured influences. Then we
further decompose the explained variation into the factors underlying it. As well as the total
attainment picture we also focus on attainment gaps across parental education and family
income.
The gap in average attainment between those in the top and bottom quarters of the population of
children is just under 24 points or two standard deviations. In Columns 1-3 we only decompose
the amount of this gap that is associated with family income at age 3-4 and parental education
(unconditional of other factors). Together these explain around 10% of the overall attainment
gap at age 7 with parental education being around three times as powerful as income.
Introducing all other background controls and all the mediating factors raises the amount of the
attainment gap explained to nearly 20%. The strong influences other than income and parental
education are other background measures (gender, ethnicity, numbers of siblings etc.), parenting
activity, the home learning environment, neighbourhood and mothers’ childhood experiences.
Childcare and mothers’ mental and physical health are of negligible associated with the
attainment gap.
162

Table 19.1: Decomposition of range of mean scores for various groups (Average score of
Key Stage One and Focus at 7) – Restricted sample
Difference in mean
scores
Top and bottom quartiles of attainment
Points
Explained variation – contribution of:
%
%total
explained
variation
variation Points
accounted
accounted
for by:
for by:
%
% total
explained
variation
variation Points
accounted
accounted
for by:
for by:
Top and bottom quartiles of
household income
%
% total
explained
variation
variation Points
accounted
accounted
for by:
for by:
Children of mothers with
CSE/no qualifications vs. a
degree
%
% total
explained
variation
variation
accounted
accounted
for by:
for by:
23.8 100 100 23.8 100 100 5.9 100 100 8.4 100 100
Income
0.6 2.7 27.6 0.3 1.3 6.9 1.7 28.3 29.2 0.7 8.0 8.0
Parental Education 1.7 7.3 72.7 1.0 4.2 22.7 1.7 28.6 29.5 4.0 47.4 47.4
Other Demographic
Variables
- - - 1.1 4.6 25.4 0.4 6.0 6.2 0.6 6.8 6.8
Childcare - - - 0.1 0.6 3.1 0.1 1.8 1.8 0.2 2.7 2.7
Parenting - - - 0.5 2.3 12.6 0.2 3.4 3.5 0.6 6.5 6.5
Outings & Home
Environment
Mother’s childhood
and family
background
Maternal health,
attitudes and social
networks
- - - 0.3 1.5 8.0 0.3 5.9 6.0 0.6 7.1 7.1
- - - 0.3 1.2 6.6 0.4 7.0 7.2 0.7 7.9 7.9
- - - 0.2 1.0 5.3 0.4 7.3 7.6 0.6 6.8 6.8
Neighbourhood - - - 0.4 1.7 9.3 0.5 8.7 9.0 0.6 6.7 6.7
Unexplained
variation
21.5 90.3 - 19.4 81.7 - 0.2 2.9 - 0.0 0.0 -
The attainment gap between the richest and poorest quarters of the children is 5.9 points (or just
under 0.6 of a standard deviation). This is a substantial attainment gap. Once we condition on all
other measures of family background and the mediating influences around 28% of this gap
remains unexplained (and is thus just correlated with income). Parental education and other
background influences are associated with around 35% of the attainment gap between rich and
poor. The remaining influences are our proximal factors, the routes through which income could
be having a direct influence. Childcare and parenting are relatively minor routes through which
income influences the attainment differences between rich and poor children. The more
substantial influences are neighbourhood (including the pre-school peer group), maternal mental
and physical health, mother’s childhood and the home learning environment.
The attainment gap between those with degree educated mothers and those with mothers with
163

very low or no qualifications, is 8.4 points (or 0.8 of a standard deviation). Around half of this
gap is unexplained by the model and could reflect genetic and other influences. Family income
and other family background factors are associated with around 15% of this gap but all the other
proximal influences are powerful transmitters of parental education with the exception of
childcare choices. So our mediating or proximal influences explain more of how parental
education is transmitted to children than of how family income is transmitted, although our
measure of family income is somewhat dated by age 7, being an average of income at ages 3
and 4.
When compared with the results for Entry Assessment at age 5, (Table 19.2) the raw
relationships between attainment and family income and parental education at age 7 are very
similar. However, once we introduce all background and mediating influences it is clear that the
model explains less of the overall variation in attainment at age 7 than at age 5. There is a
general decline in the predictive power of pre-school experiences on child development as the
children age (from 25% of the attainment gap between the highest and least able quarters of the
population, to around 20%). This could reflect a simple ageing process or other influences
coming to bear, the most obvious being schooling. Looking at the influences in detail, by
comparing Tables 19.1 and 19.2, suggests widespread small declines in the influences of
parenting behaviours, neighbourhood and peer groups, the home learning environment and other
background factors. The influence of parental education and income is more stable.
When we focus on the attainment gap between the richest and poorest quarters of children we
see a small convergence in attainment as the gap reduces from 6.9 points at age 5 to 5.9 at age 7.
This convergence is especially apparent in the decline in the impact of neighbourhood and peer
group in explaining the attainment gap between rich and poor. There are also declines in many
other influences.
164

Table 19.2: Decomposition of range of mean scores for various groups (Entry Assessment)
– Restricted sample
Top and bottom quartiles of attainment
Points
%
% total
explained
variation
variation Points
accounted
accounted
for by:
for by:
%
% total
explained
variation
variation Points
accounted
accounted
for by:
for by:
Top and bottom quartiles of
household income
%
% total
explained
variation
variation Points
accounted
accounted
for by:
for by:
Children of mothers with
CSE/no qualifications vs. a
degree
%
% total
explained
variation
variation
accounted
accounted
for by:
for by:
Difference in mean
scores
25.3 100 100 25.3 100 100 6.9 100 100 9.9 100 100
Explained variation –
contribution of:
Income
0.7 2.9 26.2 0.4 1.5 6.3 1.8 25.6 26.2 0.8 7.7 7.7
Parental Education 2.1 8.3 73.8 1.0 3.9 16.8 1.5 22.3 22.9 4.1 41.6 41.6
Other Demographic
Variables
- - - 1.4 5.5 23.6 0.5 7.3 7.5 0.5 4.6 4.6
Childcare - - - 0.3 1.1 4.9 0.2 3.4 3.4 0.4 3.7 3.7
Parenting - - - 0.9 3.4 14.5 0.4 5.7 5.8 0.9 8.8 8.8
Outings & Home
Environment
Mother’s childhood
and family
background
Maternal health,
attitudes and social
networks
- - - 0.7 2.7 11.8 0.6 8.5 8.7 1.1 11.6 11.6
- - - 0.3 1.2 5.0 0.3 4.7 4.8 0.6 6.0 6.0
- - - 0.2 0.9 3.7 0.4 5.1 5.2 0.5 4.8 4.8
Neighbourhood - - - 0.8 3.1 13.2 1.0 15.1 15.5 1.1 11.2 11.2
Unexplained
variation
22.4 88.8 - 19.4 76.8 - 0.2 2.4 - 0.0 0.0 -
As noted above, one of the reasons the model is explaining less of the patterns of attainment at
age 7 may be that children are now attending school. To explore this in part, we repeat Table
19.1 in Table 19.3, but now also include dummy variables for each school in the sample where
more than four children attend (the average is 20). These school fixed effects will capture
variation in a school’s contribution to its children’s attainment from the typical (mean) school.
This school effect may vary systematically with aspects of children’s pre-school background,
perhaps because more affluent or educated parents seek out better schools (see Gibbons and
Machin, 2003) or perhaps because schools are more effective in raising attainment for certain
groups of children than for others and these kinds of children are concentrated in some schools.
The detailed regression information is contained in Appendix A4.
165

Table 19.3: Decomposition of range of mean scores for various groups (Average score of
Key Stage One and Focus at 7) – Restricted sample
Including School Dummies
Top and bottom quartiles of attainment
Points
%
% total
explained
variation
variation Points
accounted
accounted
for by:
for by:
%
% total
explained
variation
variation Points
accounted
accounted
for by:
for by:
Top and bottom quartiles of
household income
%
% total
explained
variation
variation Points
accounted
accounted
for by:
for by:
Children of mothers with
CSE/no qualifications vs. a
degree
%
% total
explained
variation
variation
accounted
accounted
for by:
for by:
Difference in mean
scores
23.8 100 100 23.8 100 100 5.9 100 100 8.4 100 100
Explained variation –
contribution of:
Income
0.6 2.7 27.3 0.4 1.7 6.8 2.0 33.9 34.2 0.9 10.6 10.6
Parental Education 1.7 7.1 72.7 1.0 4.0 16.2 1.6 27.9 28.2 3.9 46.5 46.5
Other Demographic
Variables
- - - 1.1 4.5 18.0 0.2 4.0 4.0 0.5 6.3 6.3
Childcare - - - 0.2 0.7 2.7 0.2 2.9 2.9 0.3 3.4 3.4
Parenting - - - 0.6 2.6 10.6 0.3 5.3 5.3 0.7 8.8 8.8
Outings & Home
Environment
Mother’s childhood
and family
background
Maternal health,
attitudes and social
networks
- - - 0.3 1.4 5.8 0.4 6.0 6.0 0.6 7.3 7.3
- - - 0.3 1.2 4.7 0.4 7.0 7.1 0.7 8.2 8.2
- - - 0.2 0.7 2.9 0.3 5.6 5.7 0.4 5.1 5.1
Neighbourhood - - - 0.4 1.7 7.0 0.6 9.9 10.0 0.6 7.2 7.2
School Effects - - - 1.5 6.3 25.4 -0.2 -3.3 -3.4 -0.3 -3.3 -3.3
Unexplained
variation
21.5 90.3 - 17.8 75.1 - 0.1 1.0 - 0.0 0.0 -
When we introduce school fixed effects the explanatory power of the model at age 7 rises to
25% (similar to that explained at age 5). The variation in school performance is now the most
powerful group of predictors within the model, explaining around 6% of the overall variation.
Including school fixed effects has little impact on the other factors included, but the
contributions of income, parenting behaviours and childcare rise slightly. So the variation in the
impact of a specific school on children is weakly negatively correlated with income, involved
parents and attending nurseries prior to school entry. This is clearer (for income) when we
explore the attainment gap between the richest and poorest quarters of children (income
measured at ages 3-4). At age 5 this gap was predicted to be 6.9 points but at 7 it has fallen
slightly to 5.9 points, which may reflect that the income measure is more dated but also the
166

school fixed effects (bottom row), which are weakly negatively correlated with this gap. In their
absence the gap between rich and poor would be wider at 6.1 points. So variations in school
effectiveness have slightly narrowed the attainment gap between rich and poor children. We see
similar results when considering parental education. The importance of parental education in
predicting attainment has narrowed a little from age 5 to age 7 (a 9.9 point gap in attainment
between those with most and least educated mothers at age 5 has fallen to 8.4 by age 7).
However, in the absence of variations in school effectiveness this would be 0.3 points higher at
8.7 points. So school effectiveness is helping very slightly to mitigate early (dis-)advantages.
The unexplained income effect and the mediating effects associated with parenting, the home
learning environment and childcare all rise in importance (comparing columns 7-9 in Tables
19.1 and 19.3).
Table 19.4 reports the retrieved school fixed effects. These measure the mean deviation for all
pupils in a school from the others in the model conditional on all other systematic influences.
The range of these school effects between the 10 th and 90 th percentiles is from approximately –4
to +4 points. So predicted school effectiveness is a very large influence on child attainment.
There is normally thought to be residual unobserved heterogeneity in cross-sectional data such
as this, whereby pupils with low predicted attainment may have other adverse unobserved
characteristics. The model would then be expected to find that schools serving poor and low
achieving children would look worse than other schools because of the unmeasured
characteristics of the pupils, rather than reflecting true school effectiveness. We actually find
that the schools serving poorer children are predicted to have very marginally higher
effectiveness. So the school effect very slightly reduces attainment gaps between the affluent
and the poor for the common EA (age 5) and average age 7 samples. The correlation between
log of household income and the school fixed effects is -0.0127 but is not significant. The
correlation between mother's qualification and school is also negative, -0.0607, and is
significant at 1%. However, on the larger sample at age 7 these effects diminish to be close to
zero. So variations in school effectiveness are not making a substantive contribution to the
narrowing the attainment gap. But it is still possible that the modest general improvement might
reflect schooling in general rather than specific school effectiveness. Alternatively the
narrowing of attainment gaps between the deprived and affluent may merely reflect the ageing
process whereby measures of family background before 5 have a diminished impact.
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Table 19.4 Retrieved School Fixed Effects Coefficients- Restricted sample, average scores
10% 25% Median 75% 90%
-3.93 -1.62 0.35 2.87 3.59
168

169

20. Conclusions
This report draws together the research undertaken at the Centre for Market and Public
Organisation at the University of Bristol for the Department for Education and Skills on
children’s cognitive development and behaviour up to age 7. Part 1 covered development in the
pre-school period, and looks at what insights the Children of the 90s database can provide about
how dimensions of family background transmit into children’s educational and behavioural
development on entry into primary school. The aim here is to look at the persistence of the
picture up to age 5 through the first two years of schooling. In particular the aim is to assess
how aspects of early learning (dis-)advantages based on family background and the role of preschool
childcare experiences persist or decay on school entry. Part 2 of the report is not seeking
to identify what are key aspects of the family’s circumstances between ages 5 and 7 that
influence development through that period but to see whether family circumstances prior to age
5 persist. One exception to this is we do explore the importance of the particular school attended
to the degree of persistence of early educational (dis-)advantages.
Part 2 examines cognitive attainment at age 7. Drawn from Part 1, we look at a range of family
background factors often associated with variance in educational achievement, such as teen
motherhood, family size, parental education and income, and investigate by what routes effects
are transmitted to children by measures family functioning and early education experiences. We
focus on six main groups of factors, which were found in the previous pre-school study to
mediate between dimensions of family background and attainment.
The main findings are:
• Family Background: In general most dimensions of family background have slightly
weaker influence at age 7, after two years of schooling, than at age 5. This is most
marked for age of mother, for low birth weight children and for boys (as the gender gap
diminishes but far from disappears). The fall in influence is less, however, for income,
parental education and sibling numbers. This pattern of effects is not influenced by the
inclusion or exclusion of our mediating influences.
• Parenting patterns: Most effects, covering reading, activities, teaching and breast
feeding, remain highly persistent, that is they are still important at age 7. There is a
weakening of the impact early TV watching on children’s cognitive development.
• The home learning environment and outings: Again there is evidence of a minor
reduction in the impact of the home learning environment on children’s attainment at 7
170

compared to 5. The toy score, having few toys in the home, becomes indistinguishable
from having no effect at age 7. Whereas there was a significant relationship at age 5.
• Child care: We look at usage, covering types and extent of care up to age 2 1/2 and
more detailed study of child care exposure and limited measures of quality prior to
school entry at age 4. The reliance on friends and relatives for early care has persistently
adverse effects on attainment, but all other early care arrangements appear broadly
indistinguishable from each other and have no significant impact on outcomes at age 7.
Variations in the impact of exposure to different early learning environments
immediately prior to school entry at age 4, all disappear after two years of schooling. So
that while children who have just attended parent organised play groups were behind
children who had attended nursery schools at age 5, there is no substantive difference in
attainment by age 7.
• Maternal physical and mental health and social support networks: These factors
had little impact on children’s cognitive development but the importance of mothers’
lack of locus of control score, the extent to which the mother feels her choices and
actions can affect the family’s circumstances, remains persistent through the early school
years.
• Mother’s childhood experiences: The only persistent effect here is the association of
poorer cognitive outcomes where the mother has a history of truanting from school.
• The neighbourhood of residence and peer groups in pre-school providers: By age 7
the peer group effect at pre-school disappears. Those who attended a pre-school with
children from family backgrounds associated with high achievement (and who went on
to different primary schools) are no longer out performing other children. So early peer
group influences appear very short lived. Put together with the evidence on the lack of
effects from the types of pre-school providers used, this suggests that the form of preschool
education has no lasting impact on children. Ward characteristics still have an
effect on outcomes at 7 as at 5, but impact is smaller at age 7.
• Overall Patterns of Attainment and Role of Family Background: The overall gap
between the lowest achieving and highest achieving children become less predicted by
measures of family background and the mediating influences studied in this research.
The amount of the gap explained falls from 25% at age 5 to 20% at age 7. The variation
in school effectiveness measured by individual school dummies captures almost exactly
5% of this variation. So family background remains very powerful in predicting
attainment but variation in schools attended appears to have a substantive effect by age
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7. The elements of the model which are showing a lesser impact at age 7 than age 5 are
aspects of family background other than family income and parental education, these
being parenting and home learning environment, peer group influences and child care
type. So the modest weakening of the relationship of parental education and family
income on attainment stems almost entirely from the weakening of the mediating
influences, especially peer group, the home learning environment and parenting.
The general picture is of a large degree of persistence in family background and proximal
influences on children between the ages of 5 and 7, but there is a slight weakening of the
importance of family circumstances. In particular, the child care provider attended and the
peer group attending this provider have declining influence. This possibly suggests that the
school peer group replaces the pre-school one for outcomes at age 7.
Implications for future research
This research makes a substantive contribution to the understanding of the origins of early
learning differences in children and their persistence on entry into school. As these children age
ALSPAC will continue to offer a unique method of tracking how early learning and behaviour
are transmitted through childhood and into adulthood and to assess how other influences come
forward to mitigate or accentuate early differences. The data will also be able to track whether
recent government initiatives can alter this process, for instance, the Literacy Hour programme
which these children will have experienced after age 7 or programmes such as the Community
Trust Fund of anti-social behaviour.
Family background is observed to be associated with major differences in attainment and
behaviour on school entry. These family background influences cross the dimensions of parental
education, family income, age of mother at birth and numbers of siblings within the family. The
early learning deficits of those from poorer and less educated families remain largely intact
through the first two years of schooling but they are not continuing to worsen. These early
learning deficits substantially stem from the association between the measures of family
background and a set of proximal influences drawn from the data. The key proximal influences
differ between behaviour and early learning outcomes. For both income and parental education,
the mediating influence which is most important for early behaviour outcomes is the mother’s
mental and physical health. This includes anxiety, stress and a weak locus of control.
Disciplining behaviour is also important. For early learning, the physical home leaning
172

environment (books and toys), parental teaching and reading to children and the make up of
peer groups in pre-school settings are key proximal influences.
Through the first two years of schooling, the pattern of early learning across children remains
broadly intact, in that most of the drivers of early learning differences before entry to school
remain undiminished after two years of school. The deficits associated with having a teenage
mother weaken and those from ethnic minorities are doing better than Whites on average by age
7 (we do not have large enough samples to examine specific ethnic groups). The evidence that
pre-school setting influences child development on school entry, including evidence that the
pre-school peer group matters (which other children attend the same pre-school) show clear
signs of diminishing through the first two years of schooling. A caveat is that this study does
not have the evidence of quality in the pre-school setting available in other studies.
Policy Implications
Emerging evidence for the UK suggests that the extent of social (or intergeneration income)
mobility lessens between cohorts of children born in 1958 (NCDS) and in 1970 (BCS) – see
Blanden Gregg and Machin, 2005. Additionally, Feinstein (2003) has identified that much, but
far from all, of the educational deficit of more deprived children emerges prior to age 7. This
research and other related pieces has stimulated a governmental interest in social mobility and
the role of early years experiences in shaping children’s opportunities. This piece of research
looks at the evidence from a recent birth cohort (from 1991 to 1992) to assess the extent of early
learning deficits associated with a number of dimensions of family background. The research
goes on to assess the role of a range of measurable proximal influences (e.g. parental
behaviours, choices and circumstances), and assess how important these are in the emerging
evidence of early development and in particular in transmitting dimensions of family
background into development outcomes. When discussing the policy implications there are
instantly issues around causality. At its heart the question is whether the activity observed as
being associated with different outcomes, for example parents reading to children, is in it self
the factor that makes the difference or does it reflect broader underlying differences between
parents. So, if a policy was launched that successfully got parents who currently do not read to
their children to do so, but changed no other behaviours or attitudes, would we observe effects
on children’s attainment on the scale suggested by this study? Alternatively, is reading to your
child symptomatic of underlying differences between parents that do not change. The simple
answer is that a study such as this can not answer these questions and what is required is
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experimental or pathfinder trials of initiatives (some of which may well already exist) to assess
the potential for policy to make a difference.
There are four broad areas of potential intervention, in the light of this study, that are worthy of
policy discussion or experimentation.
Parental Teaching and Reading
First, is parental teaching, reading and activity with children. This is the single most powerful
grouping of proximal influences on children’s early cognitive development. The extent to which
different teaching behaviours lie behind deficits associated with low parental education or
family income is worth reviewing. Such activity by parents is widespread but far from universal.
The extent to which poorer or less well educated parents do less of these activities is quite
modest. Nor is there any evidence that better educated parents do these activities more
effectively. However, as these activities are so important the deficits observed among poorer
children or those with less well educated parents are still important components of early
disadvantage. To address this issue there are two, potentially complimentary approaches, the
first is to promote teaching and reading among parents and the second is to expand early years
education in order to provide effective stimulation away from the home. Both these strategies
are being tried, under Sure Start in the first instance and expanded pre-school education (free
half day places from age 3) for the later (discussed below). The effectiveness of these
programmes is not yet clear. There have been a range of parenting support programmes tried
around the world with very mixed results. This literature needs study and best practice
strategies tried under the auspices of Sure Start. The evidence suggests this is a hard thing to get
right, certainly first time round, and so a range of trials and promulgating best practice across
the country is probably required.
Physical Home Learning Environment
The second key area for potential intervention is one that is closely related to parental teaching
activities, and that is the physical home leaning environment. For language, literacy and maths
development this is mainly facilitated within the home through books and toys (although outings
are of minor importance). For behavioural development damp and overcrowding also play a
role. These aspects of home environment are strongly influenced by income levels. Again there
are two possible routes for influencing this. First, an indirect route is to give poorer to middle
income families more financial resources and hope that they will increase spending on such
items. Evidence from Gregg, Waldfogel and Washbrook (2004) suggests that the recent
174

increases in tax credits etc. have resulted in increased spending on these items and a closing of
the gap for poorer families with the more affluent. However, parents are balancing a whole set
of needs for their children and only a small share of the total increases in income goes on such
items. Indeed, spending on cars and travel, clothing (including children’s clothing) and food are
clearly high priorities for poor families, although spending on cigarettes and alcohol actually
falls. A direct route could be to provide free books and toy clubs, perhaps through Sure Start.
These are targeted but fail to allow parents to prioritise spending. Such book schemes are being
tried in the UK e.g., Bookstart operated by the Book Trust, but it is crucial that they are
evaluated effectively to assess whether they can make a difference.
Pre-school Education and Childcare
The third major element, which the government is also investing heavily in, is pre-school
education. Free half-day places for all and 3 and 4 year olds are now in place. The government
also subsidises wrap around care heavily for low to middle income parents and is piloting
extending care to younger children in poorer areas and also seeking to place an emphasis on
high quality. The evidence presented here is that the majority of 4 year olds already receive
some form of pre-school care, as under 40% of these children were not in a Nursery setting prior
to school entry. The evidence presented in this report indicates that exposure to average quality
nursery care (we cannot measure quality in each pre-school so we can only group all providers
of a particular type, which will represent the average quality of that type of care) produces
modest improvements in learning outcomes, most of which disappear after two years of
schooling. The peer group mix at the pre-school provider matters a lot for early learning and
behaviour outcomes, suggesting that services provided exclusively for the poor or troubled
children is not desirable. Again though the bulk of these benefits are lost after two years in
school. This suggests that exposure to typical pre-school childcare is not a major reason for
variations in early learning attainment. However, the importance of high quality care and its
potential benefits to deprived children cannot be studied here and better evidence should be used
(such as the EPPE study).
Mothers Mental Health
For measured behaviour the key influence is the mothers mental and physical health, especially
depression, stress, low self-esteem and an external locus of control. These measures also
correlate strongly with discipline strategies employed by parents. As with other intervention
there is potential for general and targeted action. Mental health treatment, especially in nonacute
forms such as depression is often described as the Cinderella service. However, new
175

treatments such as Cognitive Behaviour Therapy and new drugs mean that the potential to
address depression nationally appears to more possible than ever before. The benefits of
treatment for both parents and children, in terms of behavioural outcomes, could be substantial.
Targeted initiatives for parents around disciplining responses may be deliverable alongside
parenting support for teaching and reading. An external sense of locus of control naturally fits
within this, to convince parents that their actions can make a difference.
176

177

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Appendix 1
BASIC DEMOGRAPHICS
A1 1.1 Mother’s Highest Qualification
Mother’s were asked during the questionnaire at 32 weeks gestation about their highest
educational qualification. There were 940 missing observation, but as it was felt that many
mother’s with no educational qualification merely left the whole question blank, these mother’s
were grouped into the ‘CSE/none’ category and only those mother’s who ticked ‘not known’
remained coded as ‘missing’.
Mother’s highest qualification Frequency Percentage
CSE/none 2133 17.60
Vocational/O-level 5174 42.70
A-level 2670 22.03
Degree 1553 12.82
Missing 588 4.85
Total 12118 100.00
A1 1.2 Partner’s Highest Qualification
The mother also answered this question at 32 weeks gestation. When the question was left
blank, it was assumed the partner had no educational qualification. Only when the mother ticked
‘not known’ or ‘no partner’ was the qualification coded as ‘missing’ or ‘no partner’
respectively.
Partner’s highest qualification Frequency Percentage
CSE/none 2678 22.10
Vocational/O-level 3309 27.31
A-level 2940 24.26
Degree 2094 17.28
No partner 125 1.03
Missing 972 8.02
Total 12118 100.00
184

A1 1.3 Lone Parent Status
Mother’s were asked about single parent status at 8, 21, 33 and 47 months. The lone parent
status variable was derived from these responses.
Lone parent status Frequency Percentage
Always had a partner 7230 59.66
No partner at some point but had by 47 months 322 2.66
No partner at some point and none by 47 months 546 4.51
No partner at some point, don’t know at 47
months
269 2.22
Never had a partner 125 1.03
Info missing but had partner at 47 months 1301 10.74
Info missing and don’t know if had partner at 47
months
2325 19.19
Total 12118 100.00
A1 1.4 Mother’s Age At Birth
Mother’s age at birth Frequency Percentage
< 20 434 3.58
20 – 24 2112 17.43
25 – 29 4771 39.37
30 – 34 3548 29.28
35 + 1253 10.34
Total 12118 100.00
A1 1.5 Ethnicity
The mother was asked at 32 weeks gestation in which ethnic group she would place herself and
her partner. The options were white, black/Caribbean, black/African, black/other, Indian,
Pakistani, Bangladeshi, Chinese or other. If any answer other than white was recorded for either
the mother or the partner, the child was classified as non-white.
Child’s ethnicity Frequency Percentage
White 10747 88.69
Non-white 512 4.23
Missing 859 7.09
Total 12118 100.00
A1 1.6 Gender
Child’s sex Frequency Percentage
Male 6258 51.64
Female 5860 48.36
Total 12118 100.00
A1 1.7 Birth weight
This data came from a mixture of sources: obstetric data, ALSPAC measurers and birth
185

notification. If there was more than one weight recorded for a particular child, the lower figure
was taken. If the figures disagreed by more that 100g the data was coded as being missing. The
lowest recorded birth weight was 200g and the highest was 5640g. The median birth weight was
3410g. Here, low is taken as being less than 2500g.
Child’s birth weight Frequency Percentage
Low 608 5.02
Below Median 4949 40.84
Above Median 6412 52.91
Missing 149 1.23
Total 12118 100.00
A1 1.8 Special Care Unit At Birth
When the child was 4 weeks old the mother was asked if the baby had been admitted to a special
care unit or a neonatal intensive care unit or other hospital ward. The mother could either
respond with ‘yes’, ‘no’ or ‘unsure’. Unsure was coded as missing.
SCBU Frequency Percentage
No 10679 88.13
Yes 791 6.53
Missing 648 5.35
Total 12118 100.00
A1 1.9 Younger Siblings By 47 Months
At 47 months the mother was asked how many younger siblings the study child had living with
them or visiting at least once a week. They were told to include any half-brothers or sisters,
step-brothers or sisters and fostered or adopted children.
Younger Siblings Frequency Percentage
0 5693 46.98
1 3593 29.65
More than 1 335 2.76
Missing 2497 20.61
Total 12118 100.00
186

A1 1.10 Older Siblings
At 47 months the mother was asked how many older siblings the study child had living with
them or visiting at least once a week. They were told to include any half-brothers or sisters,
step-brothers or sisters and fostered or adopted children.
Older Siblings Frequency Percentage
0 4281 35.33
1 3408 28.12
2 1389 11.46
3 or more 543 4.48
Missing 2497 20.61
Total 12118 100.00
A1 1.11 Cohort Year
This is simply a variable recording in which year the Entry Assessment examination took place.
Cohort Year Frequency Percentage
1995 1088 8.98
1996 2970 24.51
1997 955 7.88
Missing 7105 58.63
Total 12118 100.00
A1 1.12 Partner’s Employment Status At 47 Months
At 47 months the mother was asked if she had a partner and also if this partner was currently
employed.
Partner in Employment Frequency Percentage
Yes 7839 64.69
No 800 6.60
No Partner 671 5.54
Missing 2808 23.17
Total 12118 100.00
CHILDCARE
When the child was 8 weeks old the mother was asked
“Who regularly looks after your baby when you’re not there?”
partner
baby’s grandparent
other relative
friend/neighbour
187

paid person outside your home (e.g. childminder)
paid person in your home (e.g. nanny, babysitter)
day nursery (crèche)
other (please describe)
If the mother’s answered yes to any of these options they were then asked to give the number of
hours per week the baby was cared for in this way and the age of the baby when this began. A
similar question was again asked at 8 months, 15 months and 24 months, with the same options
for answers and the same request for information on the number of hours each method of care
was used for per week.
If a mother used any type of childcare for over 5 hours when the child was 8 weeks, 8 months,
15 months OR 24 months, they were added to that category. The same applies if the type of
childcare was used for over 20 hours.
A1 2.1 Care by partner pre-age 2
Overall use of partner by 24 Frequency
Percentage
months
< 5 hrs pwk before 24 months 2545 21.00
5-19 hrs pwk before 24
months
3947 32.57
20+ hrs pwk before 24
months
4588 37.86
Missing 1038 8.57
Total 12118 100.00
A1 2.2 Care by friend/relative pre-age 2
Overall use of friend/relative Frequency
Percentage
by 24 months
< 5 hrs pwk before 24 months 5312 43.84
5-19 hrs pwk before 24
months
2892 23.87
20+ hrs pwk before 24 months 2506 20.68
Missing 1408 11.62
Total 12118 100.00
188

A1 2.3 Care by paid person pre-age 2
Overall use of paid person by Frequency
Percentage
24 months
< 5 hrs pwk before 24 months 7871 64.95
5-19 hrs pwk before 24
months
939 7.75
20+ hrs pwk before 24
months
1511 12.47
Missing 1797 14.83
Total 12118 100.00
A1 2.4 Centre-based care pre-age 2
Overall use of centre-based Frequency
Percentage
care by 24 months
< 5 hrs pwk before 24 months 9191 75.85
5-19 hrs pwk before 24
months
560 4.62
20+ hrs pwk before 24
months
334 2.76
Missing 2033 16.78
Total 12118 100.00
During the Focus at 7 clinics, mothers took part in an interview about day-care. Therefore,
information used to produce the variables for types of childcare used post age 3 is motherreported
retrospective data.
A1 2.5 Nursery Class age3/4
Used nursery class 36 months Frequency
Percentage
+
No 10981 90.62
Yes 1137 9.38
Total 12118 100.00
A1 2.6 LEA Nursery Class age 3/4
Used LEA nursery school 36 Frequency
Percentage
months +
No 11436 94.37
Yes 682 5.63
Total 12118 100.00
189

A1 2.7 Private Day Nursery age 3/4
Used private day nursery 36 Frequency
Percentage
months +
No 11124 91.80
Yes 994 8.20
Total 12118 100.00
A1 2.8 Nursery (type undefined) age 3/4
Used nursery (type undefined) Frequency
Percentage
36 months +
No 10279 84.82
Yes 1839 15.18
Total 12118 100.00
A1 2.9 Playgroup age 3/4
Used Playgroup 36 months + Frequency Percentage
No 7462 61.58
Yes 4656 38.42
Total 12118 100.00
A1 2.10 Other centre-based care age 3/4
Used other centre-based care Frequency
Percentage
36 months +
No 11995 98.98
Yes 123 1.02
Total 12118 100.00
PARENTING
A1 3.1a Maternal Reading Score
Question: How often do you (the mother) read your child stories or show him/her pictures in books? (N=8177)
Questionnaire Highest score Intermediate scores Lowest score
response points response points response points response points response points
6 months often 3.5 - - occasionally 1.5 - - hardly ever 0.5
18 months nearly every 3-5 times 1-2 times a less than
never
day 4 a week 3 week 2 once a week 1
0
38 months often 3.5 - - sometimes 2 rarely 1 never 0
42 months
nearly every 3-5 times 1-2 times a less than
never
day 4 a week 3 week 2 once a week 1
0
Max
possible 15 Min possible 0.5
190

A1 3.1b Categories of maternal reading score
Disaggregated Final
categories categories
Points Freq % % %
2.5 1 0.0
3.5 13 0.2
4.5 23 0.3
5.5 48 0.6
6 3 0.0
6.5 92 1.1 8.7 - 8.7
7 21 0.3 (very
7.5 135 1.7 low)
8 41 0.5
8.5 199 2.4
9 133 1.6
9.5 222 2.7
10 335 4.1 9.5 - 9.5
10.5 220 2.7 (low)
11 687 8.4
10.2
11.5 148 1.8
25.8
12 1202 14.
7 15.6
(medium)
12.5 75 0.9
13 1772 21.
7
13.5 60 0.7 29.1
14 550 6.7 56.0
15 2197 26. -
9
26.9 (high)
Total 8177
A1 3.2a Paternal Reading Score
Question: How often does your partner read your child stories or show him/her pictures in books? (N=7443)
Questionnaire Highest score Intermediate scores Lowest score
response points response points response points response points response points
6 months often 1 - - occasionally 0 - - hardly ever 0
18 months
nearly
3-5 times a 1-2 times a less than
never
every day 1 week 1 week 0 once a week 0
0
38 months often 1 - - sometimes 0 rarely 0 never 0
42 months
nearly
3-5 times a 1-2 times a less than
never
every day 1 week 1 week 0 once a week 0
0
Max
possible 4
Min
possible 0
191

A1 3.2b Categories of paternal reading score (intact families only)
Points Freq %
0 1402 18.8
1 1403 18.8
2 1673 22.5
3 2143 28.8
4 822 11.0
Total 7443
A1 3.3a Maternal Teaching Score
Question: Earliest age at which mother tries to teach child… (N=8775)
Item Highest score Intermediate scores Lowest score
Age of child points Age of child points Age of child points Age of child points
clapping games
(ie pat-a-cake)
18 months 3 - - - - not at all 0
parts of the body 18 months 3 - - - - not at all 0
to wave bye-bye 18 months 3 - - - - not at all 0
Colours 18 months 3 30 months 2 42 months 1 not at all 0
Alphabet 18 months 3 30 months 2 42 months 1 not at all 0
Numbers 18 months 3 30 months 2 42 months 1 not at all 0
nursery rhymes 18 months 3 30 months 2 42 months 1 not at all 0
Songs 18 months 3 30 months 2 42 months 1 not at all 0
shapes and sizes 18 months 3 30 months 2 42 months 1 not at all 0
politeness (ie
please and thank 18 months 3 30 months 2 42 months 1 not at all 0
you)
Max possible 30 Min possible 0
192

A1 3.3b Categories of maternal teaching score
Disaggregated
categories Final categories
Points Freq % % %
10 1 0.0
11 2 0.0
12 2 0.0
13 5 0.1
14 15 0.2
15 5 0.1
16 6 0.1 7.5 - 7.5
17 10 0.1 (very
18 24 0.3 low)
19 35 0.4
20 74 0.8
21 105 1.2
22 142 1.6
23 234 2.7
24 387 4.4 - 4.4 11.0
25 579 6.6 - 6.6 (low)
26 925 10.5 - 10.5
27 1212 13.8 - 13.8 42.1
28 1561 17.8 - 17.8 (medium)
29 1498 17.1 - 17.1 39.3
30 1953 22.3 - 22.3 (high)
Total 8775
A1 3.4a Talking Whilst Occupied Score
Question: How often do you talk to your child while you do housework or are occupied in some other way ?
(N=8088)
Questionnaire Highest score Intermediate scores Lowest score
response points response points response points response points response points
6 months always 4 Often 3 sometimes 2 rarely 1 never 0
18 months always 4 Often 3 sometimes 2 rarely 1 never 0
30 months always 4 Often 3 sometimes 2 rarely 1 never 0
42 months always 4 Often 3 sometimes 2 rarely 1 never 0
Max
possible 16
Min
possible 0
193

A1 3.4b Categories of talking whilst occupied score
Disaggregated Final
categories categories
Points Freq % %
1 1 0.0 %
4 3 0.0
5 4 0.0
6 10 0.1
7 17 0.2 10.8
8 65 0.8 - 10.8
9 135 1.7 (low)
10 207 2.6
11 430 5.3
12 827 10.2 - 10.2
13 1088 13.5 - 13.5
14 1401 17.3 - 17.3 41.0
15 1708 21.1 - 21.1 (medium)
16 2192 27.1 - 27.1 48.2
Total 8088 100.0
(high)
A1 3.5a 18 Month TV Score
Question: (At 18 months) Do you usually have the television on in the …? (N = 9026)
Item Highest score Intermediate scores Lowest score
response points response points response points
Mornings Yes, every day 2 Yes, some days 1 No, hardly ever 0
Afternoons Yes, every day 2 Yes, some days 1 No, hardly ever 0
Evenings Yes, every day 2 Yes, some days 1 No, hardly ever 0
Max possible 6 Min possible 0
A1 3.5b Categories of 18 month TV score
Disaggregated
categories
Final
categories
Points Freq % %
0 185 2.0
1 636 7.0 25.4
2 1469 16.3 (low)
3 2288 25.3
4 2183 24.2 60.8
5 1018 11.3 (medium)
6 1247 13.8 -
13.8
(high)
Total 9026 100.0
194

A1 3.6a 38 Month TV Score
Question: (At 38 months) How much time does your child spend watching television…?
(N = 9014)
Highest score Intermediate scores Lowest score
response points response pointsresponse points response points
Most weekday more than 2 1 to 2 hours less than
days
hours a day 10 a day 5 1 hour 2.5 not at all 0
Most weekend
days
more than 2
hours a day 4
1 to 2 hours
a day 2
less than
1 hour 1 not at all 0
Max possible 14 Min possible 0
A1 3.6b Categories of 38 month TV score
Disaggregated
categories
Final
categories
Points Freq % % %
0 151 1.7
1 33 0.4 2.1
2 4 0.0
2.5 126 1.4
3.5 1631 18.1 19.5
4 2 0.0
4.5 640 7.1 75.4
5 17 0.2 (low)
5.5 608 6.7 14.3
6 25 0.3
6.5 2867 31.8 - 31.8
9 686 7.6
10 5 0.1 7.7
11 44 0.5
12 437 4.8 5.3 24.6
14 1738 19.3 - 19.3 (high)
Total 9014 100.0
A1 3.7 Breast-feeding
Duration of breastfeeding Frequency Percentage
Never 3142 25.93
0 – 6 months 4710 38.87
6 + months 3847 31.75
Missing 419 3.46
Total 12118 100.00
195

A1 3.8 Smoking during pregnancy
Smoked in pregnancy Frequency Percentage
No 8977 74.08
Yes 3066 25.30
Missing 75 0.62
Total 12118 100.00
A1 3.9a Maternal Bonding Score
Question: (At 8months) Please indicate what your feelings are…?
(N = 9014)
Highest score Intermediate scores Lowest score
response points response points response points response points
I really enjoy my baby Feel exactly 3 Feel often 2
Feel
sometimes 1 Feel never 0
I would have preferred that we had not
had this baby when we did Feel never 3
Feel
sometimes 2 Feel often 1 Feel exactly 0
I feel confident with my baby Feel exactly 3 Feel often 2
Feel
sometimes 1 Feel never 0
I dislike the mess that surrounds a baby Feel never 3
Feel
sometimes 2 Feel often 1 Feel exactly 0
It is a great pleasure to watch my baby
develop Feel exactly 3 Feel often 2
Feel
sometimes 1 Feel never 0
I really can not bear it when the baby
cries Feel never 3
Feel
sometimes 2 Feel often 1 Feel exactly 0
I feel constantly unsure if I’m doing the
right thing for my baby Feel never 3
Feel
sometimes 2 Feel often 1 Feel exactly 0
I feel I should be enjoying my baby but
I’m not Feel never 3
Feel
sometimes 2 Feel often 1 Feel exactly 0
Babies are fun Feel exactly 3 Feel often 2
Feel
sometimes 1 Feel never 0
Max possible 27
Min
possible 0
196

A1 3.9b Categories of mother’s maternal bonding score
Categories
Points Freq % %
4 1 0.01
5 1 0.01
6 1 0.01
7 1 0.01
8 4 0.04
9 4 0.04
10 7 0.06
11 5 0.05
12 24 0.22
13 21 0.19 21.82
14 31 0.28
15 48 0.44
16 54 0.49
17 108 0.98
18 167 1.52
19 202 1.84
20 379 3.44
21 548 4.98
22 795 7.22
23 1100 10.00 23.83
24 1523 13.84
25 1850 16.81 - 16.81
26 2171 19.73 - 19.73
27 1960 17.81 - 17.81
Total 11005 100.0 100.0
A1 3.10a Types of discipline
Question: About how often do you do the following when your study child is naughty …?
Never Rarely Once a month Once a week Daily Total
Freq % Freq % Freq % Freq % Freq % Freq %
Ignore him 2082 22.16 3573 38.03 726 7.73 2201 23.43 813 8.65 9395 100.00
Smack him 1037 11.04 3789 40.33 1289 13.72 2815 29.96 465 4.95 9395 100.00
Shout at him 68 0.72 980 10.43 647 6.89 3902 41.53 3798 40.43 9395 100.00
Send him to is
bedroom/ naughty 1744 18.56 2085 22.19 1613 17.17 3408 36.27 545 5.80 9395 100.00
chair/ step etc
Take away treats 1272 13.54 2940 31.29 1487 15.83 3229 34.37 467 4.97 9395 100.00
Tell him off 12 0.13 276 2.94 272 2.90 2927 31.15 5908 62.88 9395 100.00
Bribe him 2850 30.34 3191 33.96 845 8.99 2130 22.67 379 4.03 9395 100.00
197

These results were condensed to create variables for the type of discipline being administered
either more or less than once a week.
Rarely Frequently Missing Total
Freq % Freq % Freq % Freq %
Ignore him 6381 52.66 3014 24.87 2723 22.47 12118 100.00
Smack him 6115 50.46 3280 27.07 2723 22.47 12118 100.00
Shout at him 1695 13.99 7700 63.54 2723 22.47 12118 100.00
Send him to is
bedroom/ naughty 5442 44.91 3953 32.62 2723 22.47 12118 100.00
chair/ step etc
Take away treats 5699 47.03 3696 30.50 2723 22.47 12118 100.00
Tell him off 560 4.62 8835 72.91 2723 22.47 12118 100.00
Bribe him 6886 56.82 2509 20.70 2723 22.47 12118 100.00
OUTINGS SCORES AND HOME ENVIRONMENT
A1 4.1a Outings scores
Question: About how often do you take your child to…?
a) local shops e) park or playground
b) department store f) library
c) supermarket g) places on interest (eg zoo)
d) visits to friends or family h) places of entertainment (eg funfair)
Questionnaire Highest score Intermediate scores Lowest score
18 months nearly every day 4
once a
week 3
once a
month 2
a few times
per year 1 never 0
30 months nearly every day 4
once a
week 3
once a
month 2
a few times
per year 1 never 0
once a once a a few times
week 3 month 2 per year 1 never 0
42 months nearly every day 4
Max possible
Each of 8
individual scores 12
Min possible
Each of 8
individual scores 0
198

A1 4.1b Categories of place-specific outings scores
Local shops Department stores Supermarket Park or playground Visits to friends or family Library Places of interest Places of entertainment
categories categories categories categories categories categories categories categories
Score Freq % % Freq % % Freq % % Freq % % Freq % % Freq % % Freq % % Freq % %
0 1 0.0 77 0.9 0 0.0 7 0.1 1 0.0 2090 25.3 38 0.5 344 4.2
1 1 0.0 134 1.6 4 0.0 16 0.2 3 0.0 736 8.9 56.6 78 0.9 600 7.3 60.1
2 1 0.0 269 3.3 47.5 8 0.1 33 0.4 5 0.1 973 11.8 (low) 338 4.1 47.8 1197 14.5 (low)
3 3 0.0 1105 13.4 (low) 20 0.2 131 1.6 12 0.1 880 10.6 2143 25.8 (low) 2816 34.2
4 8 0.1 1098 13.4 40 0.5 23.0 225 2.7 42.3 26 0.3 863 10.4 1381 16.6 1351 16.4
5 13 0.2 35.3 1218 14.8 102 1.2 (low) 385 4.7 (low) 40 0.5 50.4 740 9.0 1219 14.7 906 11.0
6 44 0.5 (low) 1745 21.2 270 3.2 651 7.9 117 1.4 (low) 1058 12.8 1240 14.9 566 6.9
7 84 1.0 1001 12.2 446 5.3 877 10.6 155 1.9 476 5.8 798 9.6 275 3.3
8 240 2.9 710 8.6 1037 12.4 1170 14.2 384 4.6 257 3.1 43.4 552 6.6 52.2 120 1.5 39.9
9 1272 15.2 759 9.2 52.5 4832 57.7 2540 30.8 1883 22.6 186 2.3 (high) 472 5.7 (high) 53 0.6 (high)
10 1284 15.4 77 0.9 (high) 889 10.6 77.0 1114 13.5 57.7 1578 18.9 4 0.0 47 0.6 11 0.1
11 1611 19.3 64.7 14 0.2 433 5.2 (high) 648 7.8 (high) 1741 20.9 49.6 2 0.0 9 0.1 3 0.0
12 3788 45.4 (high) 13 0.2 295 3.5 462 5.6 2393 28.7 (high) 0 0.0 2 0.0 0 0.0
Total 8350 100 8220 100 8376 8259 100 8338 100 8265 100 8317 100 8242 100
199

A1 4.1c Categories of total outings score
Disaggregated
categories
Final
categories
Disaggregated
categories
Final
categories
Points Freq % % % Points Freq % % %
18 1 0.0 56 396 5.1
24 1 0.0 57 365 4.7
9.8
25 1 0.0 58 377 4.8
9.3
26 2 0.0 59 349 4.5
37.4
28 1 0.0 60 361 4.6 (high)
8.3
29 4 0.1 61 287 3.7
30 1 0.0 62 321 4.1
31 4 0.1 63 243 3.1 10.0
32 6 0.1 64 214 2.7
33 10 0.1 65 210 2.7
34 8 0.1 9.7 66 165 2.1
9.7 -
35 14 0.2
(very 67 136 1.7
36 20 0.3 low) 68 99 1.3
37 21 0.3 69 83 1.1
38 26 0.3 70 64 0.8
39 36 0.5 71 52 0.7
40 51 0.7 72 43 0.6
41 73 0.9 73 28 0.4
42 87 1.1 74 22 0.3 12.1 - 12.1
43 100 1.3 75 11 0.1 (very
44 124 1.6 76 7 0.1 high)
45 162 2.1 77 7 0.1
46 174 2.2 78 6 0.1
47 205 2.6 79 2 0.0
11.4
48 228 2.9
80 3 0.0
49 283 3.6 19.9 81 1 0.0
50 314 4.0 (low) 82 1 0.0
8.5
51 348 4.5
86 1 0.0
52 350 4.5
9.8
Total 7793 100.0
53 415 5.3
21.0
54 438 5.6 (medium)
11.2
55 431 5.5
200

A1 4.2a Book score
Question: About how many books does the child have of his/her own? (N=7924)
Questionnaire Highest score Intermediate scores Lowest score
response points response points response points response points
6 months 10 or more 3 3 to 9 2 1 to 2 1 none 0
18 months 10 or more 3 3 to 9 2 1 to 2 1 none 0
24 months 4 or more 2.5 2 to 3 1.5 1 0.5 none 0
30 months 10 or more 3 3 to 9 2 1 to 2 1 none 0
42 months 10 or more 3 3 to 9 2 1 to 2 1 none 0
Max
possible 14.5
A1 4.2b Categories of book score
Disaggregated
categories Final categories
Points Freq % % %
0 1 0.0
3 2 0.0
3.5 2 0.0
4.5 11 0.1
5.5 19 0.2
6 1 0.0
6.5 48 0.6 7.7 - 7.7
7 1 0.0 (very
7.5 78 1.0 low)
8.5 152 1.9
9 1 0.0
9.5 291 3.7
10 1 0.0
10.5 690 8.7 - 8.7 23.6
11 2 0.0 (low)
14.9
11.5 1177 14.9
12.5 1525 19.2 - 19.2 -
19.2
(medium)
13.5 2391 30.2 - 30.2 49.5
14.5 1531 19.3 - 19.3 (high)
Total 7924 100.0
Min
possible 0
201

A1 4.3a Toy score
Question: How many of the following does you child have at home that he can look at or play with? (N=8911)
Component Toy Highest score Intermediate scores Lowest score
response points response points response points response points
1 Cuddly animals 4 or more 3 2 or 3 2 one 1 none 0
2 Dolls 4 or more 3 2 or 3 2 one 1 none 0
3 A swing 4 or more 3 2 or 3 2 one 1 none 0
4 toy cars or lorries 4 or more 3 2 or 3 2 one 1 none 0
5 Jigsaw puzzles 4 or more 3 2 or 3 2 one 1 none 0
6 Mobiles 4 or more 3 2 or 3 2 one 1 none 0
7 Building bricks or blocks 4 or more 3 2 or 3 2 one 1 none 0
8 Balls 4 or more 3 2 or 3 2 one 1 none 0
9 A walker (that he puts things in and pushes) 4 or more 3 2 or 3 2 one 1 none 0
10 A walker (that he sits in and walks) 4 or more 3 2 or 3 2 one 1 none 0
11 toys where he has to fit things together 4 or more 3 2 or 3 2 one 1 none 0
Max possible 33 Min possible 0
202

A1 4.3b Categories of toy score
Disaggregated
categories
Final
categories
Points Freq % % %
1 2 0.0
3 1 0.0
5 1 0.0
6 1 0.0
7 2 0.0
8 4 0.0
9 4 0.0 7.6 - 7.6
10 18 0.2 (very
11 23 0.3 low)
12 61 0.7
13 110 1.2
14 175 2.0
15 275 3.1
16 436 4.9
17 568 6.4 11.3 20.3
18 801 9.0 - 9.0 (low)
19 926 10.4 - 10.4
20 1041 11.7 - 11.7
21 1068 12.0 - 12.0 54.2
22 999 11.2 - 11.2 (medium)
23 795 8.9 - 8.9
24 649 7.3 - 7.3
25 450 5.0
26 247 2.8
27 134 1.5
28 64 0.7
29 29 0.3 10.7 18.0
30 19 0.2 (high)
31 3 0.0
32 1 0.0
33 5 0.1
Total 8911 100.0
A1 4.4 Damp/ condensation/ mould score
Damp/ condensation/ mould at Frequency
Percentage
33 months
None 4474 39.92
Yes, but not serious problem 4233 34.93
Fairly/very serious 650 5.36
Missing 2761 22.78
Total 12118 100.00
203

MOTHER’S CHILDHOOD AND FAMILY BACKGROUND
A1 5.1 Tenure of mother’s childhood home
Tenure of mother’s childhood Frequency
Percentage
home
Council housing 2141 17.67
Being bought/ owned 6698 55.27
Other rented 295 2.43
Other 367 3.03
Missing 2617 21.60
Total 12118 100.00
A1 5.2 Mother’s father present in childhood home
Mother’s father present in Frequency
Percentage
childhood home
Throughout 4474 39.92
Partly 4233 34.93
Not at all 650 5.36
Missing 2761 22.78
Total 12118 100.00
A1 5.3 Mother’s mothers educational attainment
Mother’s highest qualification Frequency Percentage
CSE/none 4046 33.39
Vocational/O-level 2767 22.83
A-level 1369 11.30
Degree 403 3.33
Missing 3533 29.15
Total 12118 100.00
204

A1 5.4a Mother’s relationship with her mother
At 12 weeks gestation the mother was asked a series of questions relating to her relationship
with her own mother. A ‘mothers relationship with her mother’ variable was derived from these
answers by simply summing all the responses and then subtracting 12.
Question: Please tick the box to indicate how you mostly remember your mother in your first 16 years.
My mother …
Lowest score Intermediate scores Highest score
response points response points response points
Spoke to me with a warm and friendly voice Never 1 Sometimes 2 Usually 3
Helped me as much as I needed Never 1 Sometimes 2 Usually 3
Seemed emotionally cold to me Usually 1 Sometimes 2 Never 3
Appeared to understand my problems and
worries Never 1 Sometimes 2 Usually 3
Was affectionate to me Never 1 Sometimes 2 Usually 3
Made me feel I wasn’t wanted Usually 1 Sometimes 2 Never 3
Talked things over with me Never 1 Sometimes 2 Usually 3
Praised me Never 1 Sometimes 2 Usually 3
Enjoyed talking things over with me No 1 - - Yes 3
Frequently smiled at me No 1 - - Yes 3
Seemed to understand what I needed or
wanted No 1 - - Yes 3
Could make me feel better when I was upset No 1 - - Yes 3
Min
possible 0 Max possible 24
205

A1 5.4b Categories of mother’s relationship with her mother score
Categories
Points Freq % %
0 52 0.49
1 44 0.41
2 60 0.56
3 62 0.58
4 97 0.91
5 76 0.71
6 109 1.02
7 101 0.95
8 142 1.33 22.17
9 127 1.19
10 127 1.19
11 136 1.28
12 138 1.30
13 153 1.44
14 193 1.81
15 220 2.07
16 238 2.24
17 284 2.67
18 370 3.48
19 436 4.10 22.43
20 657 6.17
21 924 8.68
22 1324 12.44
23 1549 14.56 27.00
24 3022 28.40 - 28.40
Total 10641 100.0
A1 5.5 Mother has a history of truancy
Mother has a history of Frequency
Percentage
truancy
No 8746 72.17
Yes 864 7.13
Missing 2508 20.70
Total 12118 100.00
206

A1 5.6 Mother feels school was a valuable experience
Mother feels school was a Frequency
Percentage
valuable experience
Very 2412 19.90
Generally 4826 39.83
Not sure 1646 13.58
Generally not/ no 833 6.87
Missing 2401 19.81
Total 12118 100.00
MATERNAL HEALTH, ATTITUDES AND SOCIAL NETWORKS
A1 6.1a Mother’s physical health
At various times the mother was asked to describe her physical health. These results were
summed to produce an aggregate score. If one observation was missing, the mean of the other
observations was added to make up the fifth observation. If two observations were missing then
the mean of the other observations was added twice. This is why some results are not integers.
Question: How would you describe your health now? (N=7924)
Questionnaire Highest score Intermediate scores Lowest score
response points response points response points response points
Always fit Mostly fit and
Hardly ever
8 weeks and well 3 well 2 Often unwell 1 well 0
8 months
Always fit Mostly fit and
Hardly ever
and well 3 well 2 Often unwell 1 well 0
21 months
Always fit Mostly fit and
Hardly ever
and well 3 well 2 Often unwell 1 well 0
Always fit Mostly fit and
Hardly ever
33 months
47 months
and well 3
Always fit
and well 3
well 2 Often unwell 1
Mostly fit and
well 2 Often unwell 1
well 0
Hardly ever
well 0
Max
possible 15 Min possible 0
207

A1 6.1b Categories of mother’s health score
Categories
Points Freq % %
0 4 0.04
1 1 0.01
1.667 1 0.01
2 2 0.02
3 1 0.01
3.333 1 0.01
3.75 2 0.02
4 5 0.05
5 33 0.31 9.25
6 35 0.33
6.25 17 0.16
6.667 29 0.27
7 88 0.82
7.5 47 0.44
8 173 1.61
8.333 63 0.59
8.75 118 1.10
9 371 3.45
10 1869 17.39 - 17.39
11 1167 10.86
11.25 411 3.82 14.68
11.667 302 2.81
12 1194 11.11 17.36
12.5 370 3.44
13 1323 12.31
13.333 271 2.52 17.80
13.75 319 2.97
14 1182 11.00 - 11.00
15 1348 12.54 - 12.54
Total 10747 100.0 100.0
208

A1 6.2a Social networks score
At 12 weeks gestation, the mother had to answer questions about family and friends. A ‘social networks’ variable was derived from these
answers by simply summing all the responses.
Lowest score Intermediate scores Highest score
response points response points response points response points
How many of your relatives and your
partner’s relatives do you see at least twice a
year? None 0 1 1 2 - 4 2 > 4 3
About how many friends do you have? None 0 1 1 2 - 4 2 > 4 3
Overall, would you say that you belong to a
close circle of friends? No 1 - - - - Yes 2
How many people are there that you can talk
to about personal problems? None 0 1 1 2 - 4 2 > 4 3
How many people talk to you about their
personal problems or their private feelings? None 0 1 1 2 - 4 2 > 4 3
If you have to make an important decision,
how many people are there with whom you
can discuss it? None 0 1 1 2 - 4 2 > 4 3
How many people are there among your
family and friends from whom you could
borrow £100 if you needed to? None 0 1 1 2 - 4 2 > 4 3
How many of your family and friends would
help you in times of trouble? None 0 1 1 2 - 4 2 > 4 3
During the last month, how many times did
you get together with one or more friends? None 0 1 1 2 - 4 2 > 4 3
During the last month, how many times did
you get together with one of your relatives or
your partner’s relatives? None 0 1 1 2 - 4 2 > 4 3
Min
possible 1
Max
possible 29
209

A1 6.2b Categories of mother’s social networks score
Categories
Points Freq % %
3 2 0.02
4 1 0.01
5 5 0.04
6 3 0.03
7 7 0.06
8 14 0.12
9 16 0.14
10 28 0.25
11 29 0.26
12 43 0.38 36.14
13 74 0.66
14 86 0.77
15 118 1.05
16 174 1.55
17 232 2.07
18 318 2.83
19 489 4.36
20 594 5.29
21 764 6.81
22 1059 9.44
23 1183 10.54
24 1258 11.21 32.55
25 1212 10.80
26 1023 9.12
27 922 8.22 31.30
28 837 7.46
29 729 6.50
Total 11220 100.0 100.0
210

A1 6.3a Social support score
At 12 weeks gestation, mothers were asked to answer questions concerning how much support they felt they had. Their responses to these
questions were summed to produce a ‘social support’ score.
Highest score Intermediate scores Lowest score
response points response points response points response points
Sometimes
I have no one to share my feelings with Never feel 3 feel 2 Often feel 1 Exactly feel 0
My partner provides the emotional support I Exactly
Sometimes
need
feel 3 Often feel 2 feel 1 Never feel 0
There are other pregnant women with whom Exactly
Sometimes
I can share my experiences
feel 3 Often feel 2 feel 1 Never feel 0
I believe in moments of difficulty my
neighbours would help me
Exactly
feel 3 Often feel 2
Sometimes
feel 1 Never feel 0
Sometimes
I’m worried that my partner might leave me Never feel 3 feel 2 Often feel 1 Exactly feel 0
There is always someone with whom I can
share my happiness and excitement about
my pregnancy
Exactly
feel 3 Often feel 2
Sometimes
feel 1 Never feel 0
If I feel tired I can rely on my partner to
take over
Exactly
feel 3 Often feel 2
Sometimes
feel 1 Never feel 0
If I was in financial difficulty I know my
family would help if they could
Exactly
feel 3 Often feel 2
Sometimes
feel 1 Never feel 0
If I was in financial I know my friends
would help if they could
Exactly
feel 3 Often feel 2
Sometimes
feel 1 Never feel 0
If all fails I know the state will support and
assist me
Exactly
feel 3 Often feel 2
Sometimes
feel 1 Never feel 0
Max
possible 30
Min
possible 0
211

A1 6.3b Categories of mother’s social supports score
Categories
Points Freq % %
0 1 0.01
1 2 0.02
2 3 0.03
3 8 0.07
4 8 0.07
5 21 0.20
6 59 0.55
7 46 0.43
8 80 0.75 31.22
9 124 1.16
10 156 1.46
11 206 1.93
12 259 2.43
13 313 2.93
14 395 3.70
15 451 4.23
16 583 5.46
17 618 5.79
18 721 6.76
19 765 7.17
20 805 7.54 37.27
21 861 8.07
22 825 7.73
23 758 7.10
24 789 7.39
25 606 5.68
26 409 3.83 31.49
27 394 3.69
28 178 1.67
29 96 0.90
30 131 1.23
Total 10671 100.0 100.0
A1 6.4a Total CCEI score
The CCEI score is actually the sum of three separate scores, all of which are derived by
summing the responses to various different questions. The same questions were asked at 8
weeks gestation, 32 weeks gestation, 8 weeks, 8 months, 21 months and 33 months. The
variable used in the analysis is a mean score for the entire preschool period.
212

Question: Please indicate the way you feel at this stage…
Lowest score Intermediate scores Highest score
response points response points response points response points
ANXIETY SUBSCORE
Do you feel upset for no obvious reason? Never 0
Not very
often 0 Often 2 Very often 2
Have you felt as though you might faint? Never 0
Not very
often 1 Often 2 Very often 2
Not very
Do you feel uneasy and restless? Never 0 often 1 Often 2 Very often 2
Do you sometimes feel panicky? Never 0
Not very
often 2 Often 2 Very often 2
Do you worry a lot? Never 0
Not very
often 1 Often 2 Very often 2
Do you feel strung-up inside? Never 0
Not very
often 0 Often 2 Very often 2
Do you ever have the feeling you are
going to pieces? Never 0
Not very
often 0 Often 2 Very often 2
Do you have bad dreams which upset you
when you wake up? Never 0
Not very
often 1 Often 2 Very often 2
DEPRESSION SUBSCORE
Do you feel that life is too much effort? Never 0
Not very
often 1 Often 2 Very often 2
Do you regret much of your past
behaviour? Never 0
Not very
often 0 Often 2 Very often 2
Do you wake unusually early in the
morning? Never 0
Not very
often 0 Often 2 Very often 2
Do you experience long periods of
sadness? Never 0
Not very
often 1 Often 2 Very often 2
Do you find yourself needing to cry? Never 0
Not very
often 1 Often 2 Very often 2
Do you lose the ability to feel sympathy
for others? Never 0
Not very
often 0 Often 2 Very often 2
Not very
Can you think quickly? Very often 0 Often 0 often 2 Never 2
Do you have to make a special effort to
Not very
face up to a crisis or difficulty? Never 0 often 1 Often 2 Very often 2
SOMATIC SUBSCORE
Do you get troubled by dizziness or
shortness of breath? Never 0
Not very
often 1 Often 2 Very often 2
Do you feel sick or have indigestion? Never 0
Not very
often 0 Often 2 Very often 2
Do you feel tingling or prickling
sensations in your body, arms or legs? Never 0
Not very
often 1 Often 2 Very often 2
Do you find that you have little or no
appetite? Never 0
Not very
often 0 Often 2 Very often 2
Do you feel tired or exhausted? Never 0
Not very
often 1 Often 2 Very often 2
Not very
Can you get off to sleep alright? Very often 0 Often 0 often 2 Never 2
Do you often have excessive sweating or
Not very
fluttering of the heart? Never 0 often 0 Often 2 Very often 2
Min
Max
possible 0
possible 46
213

A1 6.4b Categories of mother’s CCEI score
Categories
Points Freq % %
0 – 1.833 104 0.86
2 – 3.833 637 5.28 20.08
4 – 5.833 1401 11.60
6 – 6.25 283 2.34
6.333 – 7.833 1483 12.28 21.00
8 – 9 1053 8.72
9.166 – 9.833 684 5.66
10 – 11.833 1490 12.34 19.22
12 148 1.23
12.166 – 13.833 1116 9.24
14 – 15.833 956 7.91 19.91
16 – 16.666 333 2.76
16.75 – 17.833 414 3.43
18 – 19.833 570 4.72
20 – 21.833 423 3.50
22 – 23.833 292 2.42
24 – 25.833 236 1.95
26 – 27.833 172 1.42
28 – 29.833 121 1.00
30 – 31.833 68 0.56 19.79
32 – 33.833 45 0.37
34 – 35.833 22 0.18
36 – 37.833 13 0.11
38 – 39.833 10 0.08
40 – 41.833 4 0.03
42 – 43.833 0 0
44 – 45.833 1 0.01
Total 12079 100.0 100.0
214

A1 6.5a Self-esteem score
At 33 months, mothers were asked to answer questions to try to measure how much self esteem
the mother has. Their responses to these questions were summed to produce a ‘self esteem’
score.
Question: Below are some statements. Please say how true they are to you.
Highest score Intermediate scores Lowest score
response point response point response point response point response point
I feel that I am a person of Almost
Sometimes Seldom
Often true
worth, at least equal to others always true 4
3 true 2 true 1
Never true 0
I feel I have a number of good Almost
Sometimes Seldom
Often true
qualities
always true 4
3 true 2 true 1
Never true 0
I am able to do things as well as Almost
Sometimes Seldom
Often true
most other people
always true 4
3 true 2 true 1
Never true 0
I feel I do not have much to be
Sometimes
Almost
Never true Seldom true Often true
proud of
4 3 true 2
1 always true 0
I take a positive attitude Almost
Sometimes Seldom
Often true
towards myself
always true 4
3 true 2 true 1
Never true 0
Sometimes I think I am no good
Sometimes
Almost
Never true Seldom true Often true
at all
4 3 true 2
1 always true 0
I am a useful person to have Almost
Sometimes Seldom
Often true
around
always true 4
3 true 2 true 1
Never true 0
I feel I cannot do anything right Never true 4
Seldom true 3
Sometimes
Almost
Often true
true 2
1 always true 0
Almost
Sometimes Seldom
Often true
always true 4
3 true 2 true 1
Never true 0
When I do a job I do it well
I feel that my life is not very
useful
I am unlucky
Sometimes
Never true Seldom true 4 3 true 2
Sometimes
Never true Seldom true 4 3 true 2
Max
possible 44
Often true
Often true
1
1
Almost
always true 0
Almost
always true 0
Min
possible 0
215

A1 6.5b Categories of mother’s self esteem score
Categories
Points Freq % %
0,1 1 4.53
2,3 0 6.66
4,5 1 8.46
6,7 5 10.34
8,9 6 10.05
10,11 10 10.94
12,13 21 10.83 20.91
14,15 36 9.27
16,17 77 8.01
18,19 131 6.64
20,21 195 5.46
22,23 349 3.70
24,25 515 2.06
26,27 627 1.39
28,29 756 0.82 17.27
30,31 875 0.38
32,33 1023 0.22 21.78
34,35 1033 0.10
36,37 949 0.06 20.39
38,39 976 0.05
40,41 799 0.01
42,43 629 0.00 19.66
44 428 0.01
Total 9442 100.0 100.0
216

A1 6.6a Locus of control score
At 12 weeks gestation mothers were asked to complete some questions regarding their outlook
on life. The results were summed to produce a ‘locus of control’ score. Low scores therefore
represent somebody who does feel they have control and hence we have labelled those with a
low score as having a high locus of control ranking.
Highest score Lowest score
response points response points
Did getting good marks at school mean a
great deal to you? No 1 Yes 0
Are you often blamed for things that just
aren’t your fault? Yes 1 No 0
Do you feel that most of the time it doesn’t
pay to try hard because things never turn out
right anyway? Yes 1 No 0
Do you feel that if things start out well in
the morning that it’s going to be a good day
no matter what you do? Yes 1 No 0
Do you believe that whether or not people
like you depends on how you act? No 1 Yes 0
Do you believe that when bad things are
going to happen they are just going to
happen no matter what you try to do to stop
them? Yes 1 No 0
Do you feel when good things happen they
happen because of hard work? No 1 Yes 0
Do you feel that when someone doesn’t like
you there’s little you can do about it? Yes 1 No 0
Did you usually feel that it was almost
useless to try in school because most other
children were cleverer than you? Yes 1 No 0
Are you the kind of person who believes
that planning ahead makes things turn out
better? No 1 Yes 0
Most of the time, do you feel that you have
little to say about what you family decides
to do? Yes 1 No 0
Do you think it’s better to be clever than to
be lucky? No 1 Yes 0
Max
possible 12
Min possible 0
217

A1 6.6b Categories of mother’s locus of control score
Categories
Points Freq % %
0 215 2.19
1 665 6.78 37.75
2 1250 12.74 (internal)
3 1574 16.04
4 1724 17.57
5 1626 16.57 46.75
6 1237 12.61 (medium)
7 770 7.85
8 430 4.38
9 194 1.98 15.50
10 96 0.98 (external)
11 28 0.29
12 3 0.03
Total 9812 100.0 100.0
A1 6.7a Mother’s satisfaction with relationship
At 33 months the mother was asked to complete some questions concerning her satisfaction
with her relationship with her partner. These results were summed to produce a composite score.
Question: People vary greatly in the amount they are satisfied or dissatisfied with their relationship. How do you feel
about the following aspects of your life together?
Highest score Intermediate scores Lowest score
response points response points response points response point
Very
Moderately Somewhat Very
Handling family finances
satisfied 3 satisfied 2 dissatisfied 1 dissatisfied 0
Demonstrations of affection
Very
satisfied 3
Moderately
satisfied 2
Somewhat
dissatisfied 1
Very
dissatisfied 0
Sex
Very
satisfied 3
Moderately
satisfied 2
Somewhat
dissatisfied 1
Very
dissatisfied 0
Amount of time spent together
Very
satisfied 3
Moderately
satisfied 2
Somewhat
dissatisfied 1
Very
dissatisfied 0
Making major decisions
Very
satisfied 3
Moderately
satisfied 2
Somewhat
dissatisfied 1
Very
dissatisfied 0
Household tasks
Very
satisfied 3
Moderately
satisfied 2
Somewhat
dissatisfied 1
Very
dissatisfied 0
Leisure time interests and activities
Very
satisfied 3
Max
possible 21
Moderately
satisfied 2
Somewhat
dissatisfied 1
Very
dissatisfied 0
Min
possible 0
218

A1 6.7b Categories of mother’s satisfaction with partner score
Categories
Points Freq % %
0 17 0.19
1 9 0.10
2 18 0.20
3 18 0.20
4 14 0.16
5 46 0.52
6 62 0.71 19.69
7 94 1.07
8 121 1.38
9 170 1.94
10 244 2.78
11 404 4.60
12 512 5.83
13 684 7.79 20.10
14 1081 12.31
15 888 10.11 20.49
16 911 10.37
17 863 9.83
18 785 8.94 18.77
19 689 7.85
20 510 5.81 20.96
21 642 7.31
Total 8782 100.0 100.0
INCOME
A1 7.1 Education, Skills and Training
E
This domain measures education deprivation in as direct a way as possible. This is
predominantly measured by lack of qualifications amongst adults and children of different ages
in a local area. Indicators of children aged 16 and over who are not in full time education and
the proportion of 17 year olds who have not successfully applied for higher education have also
been included. Both of these participation measures are important aspects of area deprivation.
n, Skills and Training Deprivation: Summary of Indicators
• Working age adults with no qualifications (3 years aggregated LFS data at district level,
modelled
to ward level) for 1995-1998
• Children aged 16 and over who are not in full-time education (Child Benefit data – DSS) for
1999
• Proportions of 17-19 year old population who have not successfully applied for HE (UCAS
219

data)
for 1997 and 1998
• KS2 primary school performance data (DfEE, converted to ward level estimates) for 1998
• Primary school children with English as an additional language (DfEE) for 1998
• Absenteeism at primary level (all absences, not just unauthorised) (DfEE) for 1998
A1 7.2 Geographical Access to Services
Access to essential services is an important aspect of people’s everyday lives. While this is true
for all people, we have focused solely on people with low incomes (on benefits) for the first
three indicators as they are more likely to be experiencing the disadvantage of lack of access to
services more acutely than those on higher incomes, who are in principle more able to afford
public or private transport. Access to primary schools was measured for all 5-8 year olds.
Geographical Access to Services: Summary of Indicators
• Access to a post office (General Post Office Counters) for April 1998
• Access to food shops (Data Consultancy) 1998
• Access to a GP (NHS, BMA, Scottish Health Service) for October 1997
• Access to a primary school (DfEE) for 1999
220

Appendix A2
Figure A2.1
Distribution of maternal reading score (with final categories)
%
of
sa
m
pl
e
30
25
20
15
10
5
0
2 3 4 5 6 7 8 9 10 11 12 13 14 15
Maternal reading score
Figure A2.2
Distribution of paternal reading score (intact families only)
30
25
% of sample
20
15
10
5
0
0 1 2 3 4
# times partner recorded as frequent reader
Figure A2.3
Distribution of talking whilst occupied score (with final
categories)
30
25
% of sample
20
15
10
5
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Talking score
221

Figure A2.4
Distribution of 18 month TV score (with final categories)
30
25
% of sample
20
15
10
5
0
0
1
2
3
4
18 month TV score
5
6
Figure A2.5a
Distribution of maternal teaching score (with final
categories)
% of sample
25
20
15
10
5
0
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Maternal teaching score
Figure A2.5b
Distribution of 38 month TV score (with final categories)
35
30
% of sample
25
20
15
10
5
0
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
38 month TV score
222

Figure A2.6a
Figure A2.6b
50
50
% of sample
40
30
20
10
% of sample
40
30
20
10
0
0
0 1 2 3 4 5 6 7 8 9 10 11 12
0 1 2 3 4 5 6 7 8 9 10 11 12
Local shops
Department stores
Figure A2.6c
Figure A2.6d
% of sample
60
50
40
30
20
10
% of sample
40
30
20
10
0
0 1 2 3 4 5 6 7 8 9 10 11 12
0
0 1 2 3 4 5 6 7 8 9 10 11 12
Supermarket
Park or playground
Figure A2.6e
Figure A2.6f
40
40
% of sample
30
20
10
% of sample
30
20
10
0
0 1 2 3 4 5 6 7 8 9 10 11 12
0
0 1 2 3 4 5 6 7 8 9 10 11 12
Visits to friends or family
Library
Figure A2.6g
Figure A2.6h
40
40
% of sample
30
20
10
% of sample
30
20
10
0
0 1 2 3 4 5 6 7 8 9 10 11 12
0
0 1 2 3 4 5 6 7 8 9 10 11 12
Places of interest
Places of entertainment
223

Figure A2.7
Distribution of total outings score (with final categories)
6
5
% of sample
4
3
2
1
0
18
20
22
24
26
28
30
32
34
36
38
40
42
44
46
48
50
52
54
56
58
60
62
64
66
68
70
72
74
76
78
80
82
84
86
Total outings score
Figure A2.8
Distribution of book score (with final categories)
40
35
30
25
20
15
10
5
0
0
1
2
3
4
5
6
% of sample
7
8
9
10
11
12
13
14
Book score
Figure A2.9
Distribution of 24 month toy score (with final categories)
% of sample
14
12
10
8
6
4
2
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Toy score
224

Appendix A3
Appendix Tables A3.1 to A3.12 show the interaction of each of the parenting measures
with a measure of parental education. (All regressions include the basic set of controls in
addition.) Each cell contains the coefficient (and standard error) corresponding to that
combination of education and parenting score. All coefficients are relative to a base combining
the most highly educated and the highest parenting score. Hence, we would expect all the
estimates to be negative for the EA scores and positive for the Behaviour scores. Moving
upwards and leftwards from the base in the bottom right corner of each table, we might expect
the estimates to become more negative (positive for Behaviour) in both directions. Moving
upwards, the effects will be more negative if, for a given amount of parenting, less educated
parents are less effective or productive than more educated parents. The figures given in the
bottom row of each table are F-tests of the null hypothesis that there is no difference in the
effect of being in a particular parenting category according to education. So high values here,
say greater than 0.1000, imply that there are no ‘efficiency’ effects for that parenting group –
less educated parents are no better or worse than more educated parents for a given level of
involvement. The figure on the far right of the bottom row, in the bottom left triangle, is a test of
the hypothesis that there are jointly no efficiency effects for any level of the parenting variable.
This is a key summary statistic – high values tell us that we can drop the interaction terms and
retain our original specification.
Moving from right to left, the estimates will become more negative if, for a given educational
group, lower parenting scores result in worse outcomes. It may be, for example, that certain
types of parenting behaviour only matter in certain households, i.e. those in which the parents
are highly educated. The figures in the last column of the tables are F-tests of the null
hypothesis that for the given education group, the parenting behaviour has no effect. So values
close to zero here imply that the parenting measure has an impact on children in that particular
parental education group. The figure in the bottom right corner, in the top left triangle, is a test
that outcomes do not vary with parenting jointly for every educational group.
225

Guide to interpretation:
Bottom left triangle Top right triangle
High Low The parenting variable matters for outcomes
but the effectiveness of the parenting
doesn’t vary with education
High High The parenting variable doesn’t matter for
outcomes
Low High The parenting variable doesn’t matter for
outcomes but education does (shouldn’t
observe this because all regressions control
for education level separately)
Low Low The parenting variable matters for outcomes
and its effectiveness varies with education
Table A3.1: Interactions between mothers’ reading scores and maternal education
Entry Assessment (adj R2 = 0.2516) Behaviour (adj R2 = 0.0869)
Mother's education Mother’s reading score Mother’s reading score
Very low Low Medium High Prob equal Very low Low Medium High
Prob equal
CSE/none -3.253 -1.020 -1.584 0.745 0.0021 3.807*** 3.795*** 0.514 -0.086 0.0000
(1.709) (1.821) (1.561) (1.520) (1.356) (1.438) (1.255) (1.222)
vocational/O-level -4.898*** -3.216** -1.772 -1.329 0.0000 5.242*** 3.612*** 2.018 1.072 0.0000
(1.465) (1.451) (1.372) (1.348) (1.206) (1.193) (1.130) (1.107)
A-level -3.496 -2.913 -1.346 -0.091 0.0034 5.840*** 4.152*** 2.637** 0.966 0.0000
(2.073) (1.703) (1.520) (1.451) (1.575) (1.411) (1.268) (1.212)
Degree/higher -3.853 -3.267** -2.560*** 0.000 0.0046 4.751*** 4.682*** 1.612** 0.000 0.0000
(2.098) (1.463) (0.933) (base) (1.456) (1.162) (0.685) (base)
0.0000 0.0000
Prob equal 0.6480 0.5405 0.9053 0.1843 0.5625 0.4916 0.9050 0.2170 0.4494 0.6341
Table A3.2: Interactions between partners’ reading scores and paternal education (intact
families only)
Entry Assessment (adj R2 = 0.2527) Behaviour (adj R2 = 0.0870)
Partner's education
# times partner observed as highly involved in
reading to child
# times partner observed as highly involved in
reading to child
0 1 2 3 4 0 1 2 3 4
Prob
equal
CSE/none -3.026** -3.044** -2.709* -1.646 -2.227 0.6241 1.167 -0.561 -0.256 -0.307 -2.999** 0.0047
(1.447) (1.499) (1.478) (1.489) (1.794) (1.113) (1.151) (1.150) (1.152) (1.430)
vocational/O-level -2.054 -0.905 -0.882 -1.015 -1.197 0.5560 0.730 0.518 -0.159 -0.890 -1.606 0.0117
(1.414) (1.392) (1.384) (1.366) (1.519) (1.113) (1.105) (1.087) (1.081) (1.199)
A-level -3.490** -2.171 -1.066 -0.951 -1.044 0.0174 1.842 0.908 0.549 -0.426 -1.879 0.0000
(1.492) (1.471) (1.437) (1.406) (1.502) (1.166) (1.144) (1.127) (1.100) (1.193)
Degree/higher -0.146 -1.769 -0.516 -0.576 0.000 0.6635 1.992 2.512*** 0.883 -0.012 0.000 0.0043
(1.408) (1.299) (1.083) (0.985) (base) (1.025) (0.898) (0.814) (0.734) (base)
0.2701 0.0000
Prob equal 0.1831 0.2935 0.3118 0.8766 0.6665 0.6554 0.6001 0.0627 0.6353 0.8188 0.1846 0.5276
226

Table A3.3: Interactions between mothers’ teaching scores and maternal education
Entry Assessment (adj R2 = 0.2567) Behaviour (adj R2 = 0.0729)
Mother's education Mother’s teaching score Mother’s teaching score
Very low Low Medium High Prob equal Very low Low Medium High
Prob equal
CSE/none -4.919** -3.203 -2.147 -1.427 0.0407 1.888 -0.656 -0.354 -2.161 0.0002
(2.139) (2.033) (1.888) (1.894) (1.587) (1.545) (1.435) (1.443)
vocational/O-level -6.149*** -3.918** -2.483 -1.482 0.0000 1.575 1.693 -0.156 -1.708 0.0000
(1.858) (1.786) (1.720) (1.725) (1.433) (1.393) (1.331) (1.334)
A-level -4.497** -3.243 -1.932 0.166 0.0000 2.534 0.517 -1.085 -2.496 0.0000
(2.139) (2.030) (1.894) (1.888) (1.670) (1.587) (1.479) (1.477)
Degree/higher -5.527*** -2.299 -1.138 0.000 0.0053 2.489** 1.386 0.409 0.000 0.1194
(1.665) (1.240) (0.804) (base) (1.145) (0.995) (0.599) (base)
0.0000 0.0000
Prob equal 0.7649 0.8486 0.8676 0.4752 0.9124 0.8899 0.2353 0.7339 0.3729 0.2824
Table A3.4: Interactions between talking whilst occupied scores and maternal education
Entry Assessment (adj R2 = 0.2443) Behaviour (adj R2 = 0.0858)
Mother's education Talking whilst occupied score Talking whilst occupied score
Low Medium High Prob equal
CSE/none -4.561** -0.875 -0.902 0.0071 6.270*** 3.286*** 0.495 0.0000
(1.811) (1.566) (1.542) (1.431) (1.203) (1.183)
vocational/O-level -2.098 -1.685 -1.000 0.1252 6.816*** 3.670*** 1.382 0.0000
(1.484) (1.391) (1.384) (1.168) (1.083) (1.079)
A-level -1.103 -0.546 -0.302 0.6934 6.351*** 3.655*** 1.083 0.0000
(1.705) (1.507) (1.494) (1.333) (1.191) (1.182)
degree/higher -2.155* -1.256 0.000 0.1122 4.971*** 2.265*** 0.000 0.0000
(1.127) (0.822) (base) (0.875) (0.591) (base)
0.0146 0.0000
Prob equal 0.2300 0.6663 0.8191 0.5337 0.5848 0.6028 0.4970 0.9422
Table A3.5a: Interactions between 18 month TV scores and combined parental education
Entry Assessment (adj R2 = 0.2465) Behaviour (adj R2 = 0.0633
Parents' education 18 month TV score 18 month TV score
6 3-5 0-2 P equal 6 3-5 0-2 P equal
Neither A-level + -3.143*** -1.864 -0.285 0.0004 1.626** 0.708 -0.110 0.0108
(1.065) (0.960) (1.050) (0.828) (0.750) (0.828)
one A-level + -2.086 -1.415 -0.412 0.1518 2.955*** 0.598 -0.078 0.0022
(1.191) (0.842) (0.907) (0.958) (0.640) (0.694
both A-level + -3.668 -0.780 0.000 0.1790 0.851 1.962** 0.000 0.0027
(2.128) (0.789) (base) (1.465) (0.570) (base)
0.0008 0.0000
P equal 0.5916 0.5212 0.9009 0.8567 0.2598 0.1105 0.9906 0.2158
227

Table A3.5b: Interactions between 38 month TV scores and combined parental education
Entry Assessment (adj R2 = 0.2438) Behaviour (adj R2 = 0.0659)
Parents' education 38 month TV score 38 month TV score
10 + hrs pwk < 10 hrs pwk P equal 10 + hrs pwk < 10 hrs pwk P equal
Neither A-level + -2.202** -1.252 0.0335 0.514 -1.198 0.0000
(0.963) (0.923) (0.767) (0.734)
one A-level + -1.948** -0.668 0.0626 0.731 -0.999 0.0023
(0.914) (0.748) (0.727) (0.576)
both A-level + 0.111 0.000 0.9252 1.412 0.000 0.1141
(1.183) (base) (0.894) (base)
0.0473 0.0000
P equal 0.2414 0.3829 0.4961 0.7178 0.2002 0.5203
Table A3.6: Interactions between breast feeding duration and maternal education
Entry Assessment (adj R2 = 0.2468) Behaviour (adj R2 = 0.0634)
Mother's education Duration of Breastfeeding Duration of Breastfeeding
Never
0 – 3
Months
3 – 6
Months
6 – 12
Months
12 +
Months
Prob
equal Never
0 – 3
Months
3 – 6
Months
6 – 12
Months
12 +
Months Prob equal
CSE/none -3.824 -4.253 -0.931 -4.620 -1.170 0.0073 -0.967 -0.557 -1.068 -1.801 -4.545 0.0141
(4.868) (4.882) (4.922) (4.933) (5.050) (3.353) (3.370) (3.408) (3.415) (0.397)
vocational/O-level -3.780 -3.422 -3.992 -2.784 -2.395 0.1149 0.472 0.209 -0.840 -0.253 -0.644 0.0457
(4.701) (4.700) (4.710) (4.705) (4.737) (3.282) (3.282) (3.292) (3.288) (3.320)
A-level -2.579 -0.657 0.055 0.489 -0.880 0.0024 4.376 4.703 3.878 4.705 3.555 0.3312
(5.040) (5.028) (5.030) (5.021) (5.049) (3.839) (3.823) (3.825) (3.815) (3.841)
degree/higher -1.603 -1.592 -1.578 -0.442 0.000 0.5087 -1.183 1.346 -0.269 -0.009 0.000 0.3882
(1.786) (1.239) (1.113) (0.939) (base) (1.401) (0.957) (0.872) (0.705) (base)
0.0004 0.0101
Prob equal 0.9476 0.6827 0.4776 0.4282 0.9254 0.0295 0.2902 0.3068 0.3370 0.1643 0.0581 0.2533
Table A3.7: Interactions between maternal bonding score and maternal education
Entry Assessment (adj R2 = 0.2419) Behaviour (adj R2 = 0.1144)
Mother's education Maternal Bonding Score Maternal Bonding Score
Lowest
Quintile
2 nd
Quintile
3 rd
Quintile
4 th
Quintile
Highest
Quintile
Prob
equal
Lowest
Quintile
2 nd
Quintile
3 rd
Quintile
4 th
Quintile
Highest
Quintile
Prob equal
CSE/none 1.990 2.477 2.984 2.181 1.212 0.6001 7.221*** 4.665** 3.340 2.538 -0.472 0.0000
(2.630) (2.614) (2.682) (2.630) (2.604) (1.884) (1.870) (1.900) (1.879) (1.852)
vocational/O-level 0.021 -0.069 0.519 -0.585 -0.110 0.4877 8.390*** 5.710*** 4.405** 3.446** 0.745 0.0000
(2.446) (2.441) (2.449) (2.445) (2.450) (1.753) (1.749) (1.758) (1.753) (1.756)
A-level 2.492 1.941 1.877 1.720 1.810 0.8784 10.243*** 7.513*** 6.011*** 4.852** 2.995 0.0000
(2.607) (2.598) (2.618) (2.610) (2.641) (1.897) (1.891) (1.909) (1.903) (1.928)
degree/higher 1.031 1.852 0.361 1.116 0.000 0.6543 6.264*** 4.049*** 3.778*** 2.040 0.000 0.0000
(1.561) (1.586) (1.668) (1.660) (base) (1.083) (1.090) (1.155) (1.146) (base)
0.8302 0.0000
Prob equal 0.3620 0.3086 0.4534 0.2483 0.6206 0.8238 0.0638 0.1096 0.2804 0.2830 0.0854 0.6620
228

Table A3.8: Interactions types of discipline and maternal education
Entry Assessment (N = 5010) Behaviour (N = 9416)
Mother’s education Ignores child Ignores child
Rarely Frequently P equal Rarely Frequently P equal
CSE/ none -0.245 -0.603 0.7973 2.603*** 2.292** 0.7795
(0.805) (1.303) (0.582) (1.052)
vocational/ O-level -0.052 1.052 0.3449 1.905*** 2.070** 0.8657
(0.421) (1.139) (0.338) (0.950)
A-level -0.708 -0.161 0.6776 1.941*** 2.070 0.9069
(0.581) (1.261) (0.451) (1.070)
degree/higher 0.079 0.000 0.9176 1.976*** 0.000 0.0004
(0.765) (base) (0.559) (base)
0.7435 0.0112
P equal 0.7909 0.3623 0.6707 0.7592 0.1129 0.3192
Smacks child
Smacks child
Rarely Frequently P equal Rarely Frequently P equal
CSE/ none -0.737 -0.747 0.9939 2.128*** 2.252** 0.9099
(0.776) (1.306) (0.570) (1.054)
Vocational/ O-level -0.739* 0.838 0.1711 1.747*** 2.116** 0.7015
(0.409) (1.137) (0.328) (0.950)
A-level -1.130** -0.299 0.5241 1.388*** 1.980 0.5914
(0.576) (1.258) (0.452) (1.069)
degree/higher 0.351 0.000 0.6893 1.251** 0.000 0.0497
(0.879) (base) (0.637) (base)
0.5142 0.3513
P equal 0.5617 0.4311 0.5441 0.6656 0.1149 0.3194
Shouts at child
Shouts at child
Rarely Frequently P equal Rarely Frequently P equal
CSE/ none 1.179 0.528 0.6255 3.213*** 3.727*** 0.6318
(1.066) (1.552) (0.714) (1.205)
Vocational/ O-level -0.877 0.401 0.2805 2.561*** 3.210*** 0.5072
(0.607) (1.281) (0.469) (1.046)
A-level -0.017 0.121 0.9155 2.127*** 2.836** 0.5173
(0.722) (1.417) (0.557) (1.176)
degree/higher -0.107 0.000 0.9013 1.361** 0.000 0.0255
(0.859) (base) (0.609) (base)
0.3851 0.1349
P equal 0.3178 0.9822 0.3705 0.2064 0.0065 0.0398
Sends child to room
Sends child to room
Rarely Frequently P equal Rarely Frequently P equal
CSE/ none -0.532 -0.644 0.9352 1.023* 1.949* 0.3988
(0.778) (1.312) (0.569) (1.059)
Vocational/ O-level 0.527 1.371 0.4673 1.637*** 2.191** 0.5668
(0.409) (1.144) (0.327) (0.955)
A-level -0.194 0.033 0.8604 1.362*** 2.060* 0.5223
(0.544) (1.273) (0.429) (1.078)
degree/higher -0.209 0.000 0.7833 1.516*** 0.000 0.0054
(0.760) (base) (0.545) (base)
0.8995 0.0537
P equal 0.5013 0.2156 0.4928 0.8000 0.1253 0.3209
229

Table A3.8: Interactions types of discipline and maternal education (Continued)
Entry Assessment (N = 5010) Behaviour (N = 9416)
Mother’s education Takes away treats Takes away treats
Rarely Frequently P equal Rarely Frequently P equal
CSE/ none -0.739 -1.035 0.8275 0.451 1.928* 0.1763
(0.770) (1.311) (0.564) (1.058)
Vocational/ O-level 0.390 1.018 0.5864 0.612* 1.994** 0.1520
(0.409) (1.141) (0.328) (0.953)
A-level -1.048* -0.557 0.7044 0.499 1.934* 0.1904
(0.557) (1.264) (0.435) (1.073)
degree/higher 1.284 0.000 0.1060 0.364 0.000 0.5253
(0.794) (base) (0.573) (base)
0.4499 0.5130
P equal 0.0396 0.1896 0.0782 0.9808 0.1724 0.5322
Tells off child
Tells off child
Rarely Frequently P equal Rarely Frequently P equal
CSE/ none 2.054 1.294 0.6085 0.837 2.044 0.3071
(1.447) (1.981) (0.969) (1.462)
Vocational/ O-level -0.198 0.796 0.4635 2.556*** 3.641*** 0.3240
(0.930) (1.600) (0.729) (1.283)
A-level -0.560 -0.567 0.9963 0.784 1.947 0.3329
(1.231) (1.854) (0.963) (1.500)
degree/higher 0.192 0.000 0.8925 1.083 0.000 0.3052
(1.418) (base) (1.056) (base)
0.4859 0.2857
P equal 0.5120 0.7827 0.4978 0.3168 0.0445 0.0870
Bribes child
Bribes child
Rarely Frequently P equal Rarely Frequently P equal
CSE/ none 0.023 -0.434 0.7453 2.749*** 2.416** 0.7697
(0.825) (1.296) (0.621) (1.047)
Vocational/ O-level -0.557 0.992 0.1881 2.006*** 2.226** 0.8228
(0.446) (1.133) (0.354) (0.948)
A-level -0.960 -0.119 0.5285 2.637*** 2.372** 0.8136
(0.624) (1.255) (0.480) (1.067)
degree/higher -0.389 0.000 0.6348 1.033* 0.000 0.0760
(0.819) (base) (0.582) (base)
0.4539 0.4613
P equal 0.8096 0.4690 0.6848 0.1205 0.0702 0.0731
230

Table A3.9: Interactions between place-specific outings scores and maternal education
Entry Assessment (N = 5010) Behaviour (N = 9416)
Department store
Department store
Low High P equal Low High P equal
CSE/ none -2.835 -3.594 0.3295 0.175 -1.300 0.0157
(4.225) (4.215) (2.553) (2.545)
Vocational/ O-level 0.790 0.152 0.1141 1.246 0.785 0.1698
(3.984) (3.986) (2.467) (2.466)
A-level 1.339 0.699 0.2423 2.006 1.688 0.4717
(4.234) (4.234) (2.748) (2.749)
degree/higher -0.054 0.000 0.9435 -0.172 0.000 0.7604
(0.768) (base) (0.565) (base)
0.3082 0.0813
P equal 0.4619 0.4221 0.7365 0.7999 0.5439 0.4622
Park
Park
Low High P equal Low High P equal
CSE/ none -1.082 -1.535 0.5726 2.800 2.128 0.2714
(4.370) (4.372) (3.070) (3.065)
Vocational/ O-level -1.391 -0.842 0.1893 0.447 -1.019 0.0000
(3.796) (3.795) (2.756) (2.755)
A-level -3.911 -4.476 0.3251 0.898 0.096 0.0860
(3.913) (3.904) (2.888) (2.880)
degree/higher 0.528 0.000 0.5226 -0.263 0.000 0.6688
(0.825) (base) (0.614) (base)
0.4851 0.0002
P equal 0.6147 0.4556 0.4592 0.7233 0.6117 0.2441
Entry Assessment (N = 5010) Behaviour (N = 9416)
Mother’s education Friends/relatives Friends/relatives
Low High P equal Low High P equal
CSE/ none 0.717 0.954 0.7531 -1.827 -2.394 0.3237
(3.169) (3.183) (2.140) (2.153)
Vocational/ O-level -4.556** -4.721** 0.6825 2.441 1.551 0.0074
(2.118) (2.120) (1.867) (1.865)
A-level -4.249* -3.239 0.0601 4.355* 3.472 0.0440
(2.490) (2.497) (2.295) (2.304)
degree/higher 0.725 0.000 0.3459 1.434** 0.000 0.0116
(0.769) (base) (0.568) (base)
0.3162 0.0011
P equal 0.0380 0.0805 0.0745 0.2369 0.2402 0.4605
Library
Library
Low High P equal Low High P equal
CSE/ none 10.087** 11.222*** 0.1876 2.245 1.702 0.4112
(4.194) (4.233) (2.826) (2.862)
Vocational/ O-level 13.419*** 14.937*** 0.0002 1.456 0.593 0.0119
(3.992) (3.993) (2.672) (2.675)
A-level 8.929* 10.150** 0.0224 -4.845 -6.338** 0.0006
(4.574) (4.574) (3.180) (3.180)
degree/higher -0.958 0.000 0.2351 -0.334 0.000 0.5730
(0.807) (base) (0.593) (base)
0.0002 0.0008
P equal 0.0045 0.0025 0.0249 0.0586 0.0275 0.0228
231

Table A3.9: Interactions between place-specific outings scores and maternal education
(continued)
Places of interest
Places of interest
Low High P equal Low High P equal
CSE/ none -3.670 0.111 0.0000 -1.100 -1.398 0.6654
(5.816) (5.826) (4.234) (4.244)
Vocational/ O-level -1.960 -1.392 0.2202 -4.362 -5.635 0.0011
(5.596) (5.595) (4.068) (4.062)
A-level 2.884 3.507 0.3211 -0.414 -2.107 0.0009
(5.842) (5.825) (4.357) (4.341)
degree/higher -1.654* 0.000 0.0864 0.980 0.000 0.1691
(0.964) (base) (0.713) (base)
0.0002 0.0001
P equal 0.4543 0.6596 0.0458 0.4258 0.3541 0.4553
Places of entertainment Places of entertainment
Low High P equal Low High P equal
CSE/ none -3.504 -4.790 0.1691 1.120 -0.572 0.0153
(4.629) (4.653) (2.993) (3.013)
Vocational/ O-level -7.073 -6.991 0.8578 3.085 2.261 0.0329
(4.361) (4.363) (2.802) (2.804)
A-level -5.071 -5.121 0.9356 1.941 2.490 0.2661
(4.511) (4.518) (2.998) (2.999)
degree/higher 1.529* 0.000 0.0681 0.546 0.000 0.3705
(0.838) (base) (0.610) (base)
0.2619 0.0141
P equal 0.2184 0.4391 0.3594 0.7681 0.5423 0.1456
Table A3.10: Interactions between book scores and combined parental education
Entry Assessment (adj R2 = 0.2514) Behaviour (adj R2 = 0.0704)
Parents' education Book score Book score
Very low Low Medium High P equal Very low Low Medium High P equal
neither A-level + -4.013*** -2.232** -1.652* -0.875 0.0004 1.596* 1.187 -0.197 -1.008 0.0000
(1.135) (0.975) (0.994) (0.942) (0.864) (0.751) (0.774) (0.733)
One A-level + -5.415*** -3.277*** -1.603* -0.045 0.0000 3.586** 1.769** 0.117 -1.178* 0.0000
(1.895) (0.953) (0.972) (0.790) (1.453) (0.745) (0.757) (0.605)
both A-level + -5.384* -0.787 0.115 0.000 0.2458 2.275 1.985** 0.485 0.000 0.1029
(2.786) (1.183) (1.006) (base) (2.045) (0.868) (0.734) (base)
0.0000 0.0000
P equal 0.7168 0.1481 0.3258 0.3947 0.3579 0.4034 0.6173 0.7659 0.1500 0.6631
232

Table A3.11: Interactions between toy scores and combined parental education
Entry Assessment (adj R2 = 0.2483) Behaviour (adj R2 = 0.0717)
Parents' education Toy score Toy score
Very low Low Medium High P equal Very low Low Medium High P equal
neither A-level + -2.804** -2.393** -1.531 -0.699 0.0379 3.910*** 2.469*** 1.192 -0.536 0.0000
(1.347) (1.195) (1.140) (1.223) (1.015) (0.909) (0.867) (0.937)
one A-level + -4.587*** -2.031* -1.185 -0.671 0.0501 2.385* 2.386*** 1.114 -0.297 0.0019
(1.700) (1.147) (1.011) (1.115) (1.339) (0.873) (0.752) (0.856)
Both A-level + -0.246 -1.361 -0.508 0.000 0.7733 4.916*** 2.052** 1.566** 0.000 0.0036
(2.142) (1.298) (0.904) (base) (1.526) (0.916) (0.652) (base)
0.0490 0.0000
P equal 0.2113 0.7494 0.5734 0.8172 0.8504 0.3461 0.9201 0.7695 0.8482 0.9095
Table A3.12: Interactions between damp/mould/condensation scores and combined parental
education
Entry Assessment (adj R2 = 0.2434) Behaviour (adj R2 = 0.0664)
Parents' education Damp score Damp score
None
Minor
Problem
Serious
Problem
P equal
None
Minor
Problem
Serious
Problem
P equal
Neither A-level + 0.120 0.463 -0.916 0.3004 -2.441* -1.148 -0.361 0.0001
(1.853) (1.855) (2.024) (1.400) (1.402) (1.535)
one A-level + 0.581 0.882 3.703* 0.0468 -2.671** -1.298 0.054 0.0015
(1.785) (1.783) (2.115) (1.338) (1.333) (1.614)
both A-level + 1.591 1.796 0.000 0.5805 -1.686 -0.183 0.000 0.0219
(1.761) (1.726) (base) (1.291) (1.275) (base)
0.1399 0.0000
P equal 0.3622 0.3977 0.6509 0.0802 0.3467 0.2318 0.8140 0.6707
233

Appendix A4
Tables of Regression including School Dummies
Table A.4.1 Basic Demographics – Average Score with school dummies
Full Sample
Average Score
Restricted Sample Average
Score
234
Entry Assessment
No. of observations 7537 4996 4996 4996
Log of household income
Early Measure
1.394***
(0.322)
Mother’s highest qualification (base = vocational/O-level)
CSE/none
-1.155***
(0.326)
A-level
0.483*
(0.254)
Degree
1.253***
(0.367)
Partner’s highest qualification (base = vocational/O-level)
CSE/none
A-level
Degree
-1.056***
(0.298)
0.233
(0.255)
1.475***
(0.331)
Lone parent status (base = never lone parent)
Intermittently, with partner at 47 months
-0.530
(0.650)
Intermittently, no partner at 47 months
-0.120
(0.531)
Since birth
-0.068
(0.979)
Mother’s age at birth (base = 25-29)
1
(0.575)
Older siblings (base = none)
1
2
3+
-0.846***
(0.268)
-1.845***
(0.349)
-2.818***
(0.515)
Partner’s employment status at 47 months (base = in work)
-0.431
Not in work
(0.417)
1.809***
(0.425)
-0.753*
(0.410)
0.566*
(0.336)
1.476***
(0.529)
-1.217***
(0.374)
0.162
(0.328)
1.735***
(0.462)
-0.775
(0.842)
0.042
(0.682)
1.518
(1.332)
-0.288
(1.004)
-0.012
(0.392)
0.011
(0.307)
-0.138
(0.447)
1.736**
(0.712)
2.538***
(0.247)
-0.893
(0.662)
-0.667***
(0.258)
-0.952*
(0.544)
-0.335
(0.313)
-1.237
(0.760)
-1.073***
(0.356)
-2.371***
(0.466)
-3.050***
(0.674)
-0.227
(0.547)
1.639***
(0.408)
-0.745*
(0.394)
-0.048
(0.323)
1.402***
(0.508)
-1.127***
(0.359)
0.124
(0.315)
1.178***
(0.444)
0.676
(0.809)
0.008
(0.656)
0.726
(1.280)
-2.516***
(0.965)
-0.531
(0.376)
0.201
(0.295)
0.359
(0.430)
-0.431
(0.684)
3.511***
(0.237)
-2.596***
(0.636)
-0.798***
(0.248)
-0.371
(0.523)
-0.145
(0.300)
-1.240*
(0.730)
-0.683**
(0.343)
-2.195***
(0.448)
-3.108***
(0.647)
-0.187
(0.525)
Simple Value Added
0.170
(0.439)
-0.007
(0.423)
0.614*
(0.347)
0.074
(0.546)
-0.089
(0.386)
0.038
(0.339)
0.557
(0.478)
-1.451*
(0.870)
0.034
(0.705)
0.792
(1.377)
2.227**
(1.038)
0.519
(0.405)
-0.191
(0.317)
-0.497
(0.462)
2.168***
(0.735)
-0.973***
(0.255)
1.703**
(0.684)
0.131
(0.267)
-0.581
(0.563)
-0.190
(0.323)
0.004
(0.785)
-0.390
(0.368)
-0.177
(0.482)
0.058
(0.696)
-0.039
(0.565)
Adjusted R-squared 0.1845 0.1902 0.3513 0.1813

Table A4.2 Childcare – Average Score with school dummies
Full Sample Restricted Sample Entry Simple Value
Average Score Average Score Assessment Added
No. of observations 7537 4996 4996 4996
Childcare pre-age 3
Used partner 5-19 hours per -0.036 0.064 0.489 -0.425
week (0.260) (0.345) (0.332) (0.357)
Used partner 20+ hours per 0.000 -0.000 0.020 -0.021
week (0.260) (0.346) (0.332) (0.357)
Used friend/relative 5-19 -0.535** -0.643** -0.287 -0.356
hours per week (0.241) (0.315) (0.303) (0.326)
Used friend/relative 20+ -0.546** -0.667* -0.822** 0.155
hours per week (0.261) (0.343) (0.330) (0.354)
Used paid person 5-19 hours -0.402 -0.299 -0.544 0.244
per week (0.344) (0.473) (0.455) (0.489)
Used paid person 20+ hours -0.420 -0.059 0.145 -0.204
per week (0.293) (0.404) (0.388) (0.417)
Used centre-based care 5-19 -0.310 -0.678 -0.100 -0.578
hours per week (0.432) (0.608) (0.585) (0.629)
Used centre-based care 20+ 1.075* 0.945 1.752** -0.808
hours per week (0.564) (0.843) (0.810) (0.871)
Childcare age 3 to 4
Nursery class -0.512 -0.222 1.053** -1.276**
(0.369) (0.517) (0.497) (0.534)
LEA nursery school -0.076 -0.334 0.402 -0.737
(0.431) (0.603) (0.580) (0.623)
Private day nursery -0.032 0.028 0.600 -0.571
(0.337) (0.457) (0.439) (0.472)
Playgroup 0.398 -0.001 -0.191 0.190
(0.254) (0.348) (0.334) (0.359)
Nursery (type undefined) 0.081 0.070 0.919** -0.849**
(0.278) (0.394) (0.379) (0.408)
Other -0.768 -0.909 -0.969 0.060
(0.791) (1.203) (1.156) (1.243)
Adjusted R-squared 0.1845 0.1902 0.3513 0.1813
235

Table A4.3 Parenting – Average Score with school dummies
Full Sample
Average Score
Restricted Sample
Average Score
Entry
Assessment
No. of observations 7537 4996 4996 4996
Simple Value
Added
Maternal reading score (base = high)
Very low -1.358*** -1.664*** -1.598*** -0.066
(0.431) (0.562) (0.540) (0.581)
Low -0.752** -1.014** -0.745 -0.268
(0.377) (0.497) (0.477) (0.513)
Medium -0.452* -0.442 -0.298 -0.145
(0.254) (0.332) (0.319) (0.344)
Teaching score (base = high)
Very low -2.476*** -3.257*** -4.063*** 0.807
(0.445) (0.586) (0.563) (0.606)
Low -1.734*** -1.862*** -2.290*** 0.428
(0.357) (0.464) (0.446) (0.479)
Medium -0.661*** -0.863*** -1.312*** 0.449
(0.231) (0.301) (0.289) (0.311)
18 month TV score (base = 0-2 hours per week)
3 –5 0.009 -0.050 -0.191 0.141
(0.237) (0.323) (0.310) (0.334)
6 0.056 -0.283 -0.747* 0.464
(0.360) (0.469) (0.450) (0.484)
Duration of breastfeeding (base = never)
Breastfed 6 months
0.902*** 1.202*** 0.914*** 0.288
(0.284) (0.365) (0.351) (0.377)
Adjusted R-squared 0.1845 0.1902 0.3513 0.1813
236

Table A4.4 Outings and Home Environment – Average Score with school dummies
Full Sample
Average Score
Restricted Sample
Average Score
Entry
Assessment
No. of observations 7537 4996 4996 4996
Simple Value
Added
Outings scores
Department stores -0.076 -0.289 -0.351 0.062
(0.211) (0.278) (0.267) (0.287)
Library 0.436** 0.449 0.975*** -0.527*
(0.219) (0.290) (0.278) (0.299)
Book score (base = high)
Very low -1.322*** -0.921 -2.208*** 1.287**
(0.490) (0.634) (0.610) (0.656)
Low -0.307 -0.283 -0.689* 0.406
(0.286) (0.375) (0.361) (0.388)
Medium -0.007 0.021 -0.314 0.334
(0.278) (0.368) (0.354) (0.381)
Toy score (base = high)
Very low 0.041 -0.904 -1.296** 0.392
(0.478) (0.614) (0.590) (0.634)
Low 0.058 -0.265 -0.352 0.087
(0.334) (0.440) (0.423) (0.455)
Medium 0.196 -0.001 0.482 -0.482
(0.266) (0.354) (0.340) (0.366)
Adjusted R-squared 0.1845 0.1902 0.3513 0.1813
237

Table A4.5 Mother’s childhood and family background – Average Score with school
dummies
Full Sample
Average Score
Restricted Sample
Average Score
Entry
Assessment
No. of observations 7537 4996 4996 4996
Simple Value
Added
Tenure of mother’s childhood home (base = mortgage/owned
Council rented -0.491* -0.107 -0.416 0.308
(0.271) (0.346) (0.332) (0.357)
Other rented 0.757 1.115 0.580 0.534
(0.564) (0.768) (0.738) (0.793)
Other 0.380 0.418 1.179* -0.761
(0.514) (0.683) (0.656) (0.706)
Mother’s father present in childhood home (base = not at all)
Throughout 0.696 0.555 0.624 -0.069
(0.528) (0.696) (0.669) (0.719)
Partly 0.439 0.211 0.337 -0.126
(0.573) (0.756) (0.727) (0.782)
Mother’s mother’s highest qualification (base = CSE/none)
Vocational/O-level
0.316 0.416 0.190 0.226
(0.261) (0.344) (0.331) (0.356)
A-level 0.192 0.325 0.661 -0.337
(0.327) (0.454) (0.436) (0.469)
Degree 0.436 0.538 0.402 0.136
(0.530) (0.785) (0.755) (0.812)
Mother has a history of truancy (base = yes)
No 1.140*** 1.266** 1.231** 0.035
(0.426) (0.544) (0.522) (0.562)
Mother feels school was a valuable experience (base = not sure/generally not/no)
Yes very 0.371 0.368 -0.016 0.383
(0.304) (0.406) (0.390) (0.419)
Yes generally 0.017 -0.181 -0.471 0.290
(0.260) (0.340) (0.326) (0.351)
Adjusted R-squared 0.1845 0.1902 0.3513 0.1813
238

Table A4.6 Maternal health, attitudes and social networks – Average Score with
school dummies
Full Sample
Average Score
Restricted Sample Average
Score
Entry Assessment
No. of observations 7537 4996 4996 4996
Simple Value Added
Social support score (base = low)
Medium 0.388 0.175 -0.109 0.284
(0.246) (0.327) (0.314) (0.338)
High 0.198 0.085 0.020 0.065
(0.261) (0.342) (0.329) (0.354)
Locus of control score (base = low)
Medium -0.261 -0.206 -0.651** 0.445
(0.228) (0.302) (0.290) (0.312)
High -1.041*** -1.137** -0.680 -0.457
(0.376) (0.480) (0.461) (0.496)
Adjusted R-squared 0.1845 0.1902 0.3513 0.1813
Table A4.7 Neighbourhood – Average Score with school dummies
Full Sample
Average Score
Restricted Sample Average
Score
Entry Assessment
No. of observations 7537 4996 4996 4996
Simple Value Added
Education domain score
-0.220 -0.818*** -0.486* -0.331
(0.145) (0.260) (0.250) (0.269)
Average EA score of peers – predicted component (base = lowest quintile)
2 nd quintile -0.315 -0.343 0.887 -1.230**
(0.541) (0.579) (0.556) (0.598)
3 rd quintile 0.587 0.428 1.302** -0.874
(0.554) (0.595) (0.572) (0.615)
4 th quintile 0.933* 0.759 1.525*** -0.766
(0.565) (0.609) (0.585) (0.629)
Highest quintile -0.027 -0.427 1.513** -1.939***
(0.583) (0.636) (0.612) (0.658)
Average EA score of peers – residual component (base = lowest quintile)
2 nd quintile -0.675 -0.701 -0.357 -0.344
(0.531) (0.567) (0.545) (0.586)
3 rd quintile -0.828 -0.842 0.132 -0.975*
(0.533) (0.571) (0.548) (0.590)
4 th quintile -0.543 -0.486 0.295 -0.781
(0.548) (0.586) (0.563) (0.606)
Highest quintile -0.961* -0.880 0.154 -1.034*
(0.542) (0.579) (0.557) (0.599)
Adjusted R-squared 0.1845 0.1902 0.3513 0.1813
239

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