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Child Poverty in Mozambique. A Situation and Trend ... - Unicef

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Figure 3.16: Underweight prevalence by age-group<br />

%<br />

40<br />

37<br />

35<br />

30<br />

29<br />

20<br />

20<br />

22<br />

18<br />

10<br />

5<br />

0<br />

Under 6<br />

months<br />

6 to 9<br />

months<br />

10 to 11<br />

months<br />

12 to 23<br />

months<br />

24 to 35<br />

months<br />

36 to 47<br />

months<br />

48 to 59<br />

months<br />

Source: DHS 2003<br />

Box 3.4: Compar<strong>in</strong>g children’s nutritional status over time<br />

In compar<strong>in</strong>g children’s nutritional status over space <strong>and</strong> time it is essential to<br />

compare like with like. In <strong>Mozambique</strong> this is complicated by subtle differences<br />

<strong>in</strong> demographics <strong>and</strong> survey implementation. Simler <strong>and</strong> Ibrahimo (2005) exam<strong>in</strong>e<br />

four different surveys (1996/97 IAF, 1997 DHS, 2000/01 CWIQ <strong>and</strong> 2003 DHS) <strong>and</strong><br />

f<strong>in</strong>d three key differences between the samples:<br />

1. The age distributions: The prevalence of stunt<strong>in</strong>g (low height-for-age) <strong>and</strong><br />

underweight (low weight-for-age) are highly correlated with age because they<br />

are cumulative processes. This means that if age distributions differ between<br />

surveys, they are no longer directly comparable. This is the case between the<br />

1997 DHS, which only collects data for children below 36 months, <strong>and</strong> the<br />

other three surveys, which collected data up to 60 months.<br />

2. The correlation of <strong>in</strong>complete data with household economic status: To<br />

produce accurate child nutrition data it is crucial to know the child’s age to at<br />

least the nearest month, usually us<strong>in</strong>g a health card or birth certificate. Without<br />

this <strong>in</strong>formation, stunt<strong>in</strong>g cannot be calculated <strong>and</strong> the child is left out of<br />

the analysis. S<strong>in</strong>ce poorer <strong>and</strong> older children are less likely to have adequate<br />

documentation of their date of birth, they are underrepresented <strong>in</strong> the analysis<br />

of stunt<strong>in</strong>g, thereby tend<strong>in</strong>g to underestimate the prevalence of stunt<strong>in</strong>g<br />

<strong>and</strong> underweight. If this bias changes over time it underm<strong>in</strong>es <strong>in</strong>ter-survey<br />

comparisons.<br />

3. Changes <strong>in</strong> child mortality: Obviously, measurements are only available for<br />

surviv<strong>in</strong>g children. Reductions <strong>in</strong> child mortality therefore make more children<br />

eligible for measurement <strong>and</strong> also probably change the characteristics of those<br />

survivors (i.e. there are more “survivors” <strong>in</strong> the more recent samples, who<br />

<strong>in</strong> the past would not have survived). This effect underm<strong>in</strong>es comparability<br />

between surveys.<br />

The authors, controll<strong>in</strong>g for these factors, show that there has been a more<br />

positive change <strong>in</strong> the nutritional status over time than the uncorrected data.<br />

Stunt<strong>in</strong>g amongst children of 0 – 59 months <strong>in</strong> particular is adjusted down from<br />

41% to 38% <strong>in</strong> the DHS 2003 (thereby br<strong>in</strong>g<strong>in</strong>g it <strong>in</strong>to l<strong>in</strong>e with the average for<br />

sub-Saharan Africa). The adjusted data are presented <strong>in</strong> Annex V. Overall, the<br />

authors still f<strong>in</strong>d that changes <strong>in</strong> child malnutrition are very small <strong>in</strong> comparison to<br />

recent ga<strong>in</strong>s <strong>in</strong> economic growth <strong>and</strong> poverty reduction.<br />

98 CHILDHOOD POVERTY IN MOZAMBIQUE: A SITUATION AND TRENDS ANALYSIS

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