Objective: In many countries of the world millions of people are not registered at
birth. However, in order to assess children’s nutritional status it is necessary to
have an exact knowledge of their age. In the present paper we discuss the effects
of insufficient or imprecise age data on estimates of undernutrition prevalence.
Design: Birth registration rates and levels of stunting, underweight and wasting
were retrieved from Multiple Indicator Cluster Surveys and Demographic and
Health Surveys of thirty-seven sub-Saharan African countries, considering the
subdivision in wealth quintiles. The composition of the cross-sectional sample
used for nutritional evaluation was analysed using a permutation test. Logistic
regression was applied to analyse the relationship between birth registration and
undernutrition. The 95 % probability intervals and Student’s t test were used to
evaluate the effect of age bias and error.
Results: Heterogeneous sampling designs were detected among countries, with
different percentages of children selected for anthropometry. Further, registered
children were slightly more represented within samples used for nutritional
analysis than in the total sample. A negative relationship between birth registration
and undernutrition was recognized, with registered children showing a better
nutritional status than unregistered ones, even within each wealth quintile.
The over- or underestimation of undernutrition in the case of systematic over- or
underestimation of age, respectively, the latter being more probable, was
quantified up to 28 %. Age imprecision was shown to slightly overestimate
undernutrition.
Conclusions: Selection bias towards registered children and underestimation of
children’s age can lead to an underestimation of the prevalence of undernutrition