Report from the Sub-comittee on the environment and health

Measurement of <strong>the</strong>
potential exposure
The indicators can be too
rough
Epidemiological studies
Cross-sectional studies
(descriptive studies)
The potential human exposure to pesticides can be investigated by direct
measurements in food products, drinking water or <strong>the</strong> environment. The
most accurate data for exposure are presented in case reports, but only a
group designation is usually used (e.g. insecticide, fungicide or
herbicide) when describing <strong>the</strong> exposure, and <strong>the</strong> amount used is selfreported.
In several studies of children and pesticides, <strong>the</strong> length of time
<strong>the</strong> parents have been engaged in an occupation with potential pesticide
exposure, for example, and <strong>the</strong> frequency and use of pesticides are used
as indirect measures of <strong>the</strong> degree of exposure. O<strong>the</strong>r studies have
estimated <strong>the</strong> magnitude of <strong>the</strong> exposure by combining types of crops in
an area with information about <strong>the</strong> use of pesticides that are specific to
<strong>the</strong> crops in question. The rougher <strong>the</strong> measure used for classification of
<strong>the</strong> type and extent of <strong>the</strong> exposure, <strong>the</strong> more likely it is that any real
increased risk of health effects <strong>from</strong> specific pesticides will not be
discovered.
In many of <strong>the</strong> studies, an assessment of effects is also often based on
rough indicators. An exact description of <strong>the</strong> effects is extremely
important but is often problematical – as in <strong>the</strong> case, for instance, of
neurotoxic effects of pesticides, which can be very difficult to reveal and
quantify. Assessments are frequently based on comparisons of mean
values, whereby particularly deviant small groups can be overlooked. For
cancer, tissue tests may be necessary in order to make specific cancer
diagnoses. <strong>Sub</strong>-types of some diseases, e.g. leukaemia, can have different
causes, and mixing <strong>the</strong>se sub-types can blur a possible relationship with a
given exposure. Owing to poor precision in assessment of both exposure
and effect in <strong>the</strong> traditional epidemiology, incorrect classification is
likely, which results in <strong>the</strong>se methods having a low sensitivity, see
below.
Information on relationships between exposure to pesticides or o<strong>the</strong>r
environmental factors and <strong>the</strong> occurrence of disease in humans is often
obtained by means of epidemiological studies (also called population
studies). Great caution must be exercised in interpreting <strong>the</strong> results of
epidemiological studies because of a number of sources of error and
inherent weaknesses in <strong>the</strong> different epidemiological models. It must be
firmly stated <strong>from</strong> <strong>the</strong> start that epidemiological studies - in <strong>the</strong> classic
sense – are not enough on <strong>the</strong>ir own to establish causal relationships.
The models comprise: 1) descriptive epidemiological studies
(population-based) and 2) analytical epidemiological studies (individualbased).
In descriptive epidemiological studies, <strong>the</strong> lifestyle or conditions of life
of groups (e.g. whole countries’ populations) are typically registered as
causal factors. For example, <strong>the</strong> consumption of a given pesticide in
different population groups can be compared with statistical data on
morbidity and mortality in <strong>the</strong>se population groups, or changes in <strong>the</strong>
consumption of pesticides and morbidity or mortality over time in <strong>the</strong>
same population group. An obvious drawback with descriptive studies is
that it is not possible to make adjustment for known risk factors at
individual level (e.g. smoking, obesity or alcohol consumption). In
descriptive studies one can find certain patterns between exposure and
disease. For example, a high consumption of pesticides and thus probably
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