Birth registration and child undernutrition in sub-Saharan Africa

Abstract

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.

Nutritional status of Ugandan school‐children: The effect of age imprecision

“…In fact, we excluded 225 children (21.3%) from the total sample, due to their lack or incorrect dates of birth. Such exclusion represents an unintentional selection bias that likely caused the underestimation of undernutrition, according to the results of Comandini et al () and Jeong et al (). Indeed, children whose births are more accurate generally belong to the better‐educated and also better‐nourished segments of the population (Comandini et al, ).…”

“…One of the methodological challenges faced during nutritional assessment in sub‐Saharan Africa is the insufficient and imprecise information on child age (Comandini, Cabras, & Marini, ; Comandini, Cabras, & Marini, ; Finaret & Hutchinson, ; Jeong, Bhatia, & Fink, ; Larsen, Headey, & Masters, ). In fact, without reliable information about a child's age, the indicators stunting, underweight, and obesity (defined in relation to sex and age), according to standard criteria (WHO, ) cannot be accurately calculated.…”

“…Hence, in most cases, particularly in older children, nutritional analyses can be affected by coverage biases toward children with a valid date of birth, and information error in children whose knowledge of age is imprecise. Both selection bias and imprecision have an effect on malnutrition prevalence estimates (Comandini et al, , ; Grellety & Golden, ). Particularly, Grellety and Golden () estimated that even small errors in age can change the estimates of malnutrition prevalence substantially.…”

“…Further, the relationship between malnutrition and age imprecision has not been faced. Yet, the lack or uncertainness of birth data is common in Uganda (registration of children soon after their birth is 32.2%; UBOS & ICF, ), further reducing the possibility of evaluating and tracking childhood nutritional status (Comandini et al, ; Comandini et al, ).…”

Biometrics' new identity—measuring more physical and biological traits

“…"In these regions, children without a certain date of birth-month and year-have zero probability of selection in large epidemiological studies on nutritional status", said anthropologist Elisabetta Marini from the University of Cagliari, Italy. "We have shown that in sub-Saharan Africa a selection bias favouring registered children is present in demographic and health surveys, and can lead to underrate undernutrition prevalence" [9]. Guessing the age of unregistered children by asking parents is prone to inaccuracies, often ending up with an undervaluation of the age of these children, especially if they are stunted.…”