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Birth registration and child undernutrition in sub-Saharan Africa

Ornella Comandini1, Stefano Cabras2, Elisabetta Marini1

  • 11Department of Life and Environmental Sciences,University of Cagliari,Cittadella Universitaria,09042 Monserrato,Cagliari,Italy.

Public Health Nutrition
|December 17, 2015
PubMed

Insights

Millions of children lack birth registration, impacting nutritional status assessments. Inaccurate age data and selection bias can lead to underestimating childhood undernutrition prevalence in sub-Saharan Africa.

Area of Science:

  • Public Health
  • Nutrition Science
  • Demography

Background:

  • Millions of children globally lack birth registration, hindering accurate age determination.
  • Precise age data is crucial for assessing children's nutritional status and identifying undernutrition.
  • Sub-Saharan Africa faces significant challenges with birth registration and childhood undernutrition.

Purpose of the Study:

  • To investigate the impact of insufficient or imprecise age data on estimates of undernutrition prevalence.
  • To analyze the relationship between birth registration and childhood nutritional status in sub-Saharan Africa.
  • To quantify the effect of age bias and error on undernutrition prevalence estimates.

Main Methods:

  • Utilized data from Multiple Indicator Cluster Surveys and Demographic and Health Surveys in 37 sub-Saharan African countries.
  • Analyzed birth registration rates and nutritional status (stunting, underweight, wasting) across wealth quintiles.
  • Employed logistic regression, permutation tests, 95% probability intervals, and Student's t-test to assess relationships and biases.

Main Results:

  • Detected heterogeneous sampling designs, with registered children slightly overrepresented in nutritional analysis samples.
  • Found a negative relationship between birth registration and undernutrition; registered children had better nutritional status.
  • Quantified potential over- or underestimation of undernutrition up to 28% due to systematic age errors, with age imprecision slightly overestimating undernutrition.

Conclusions:

  • Selection bias favoring registered children can lead to underestimation of undernutrition.
  • Underestimation of children's age, a probable scenario, significantly impacts prevalence estimates.
  • Improving birth registration and age accuracy is vital for reliable child nutrition assessments.
Abstract

Keywords:
Demographic and Health SurveysMultiple Indicator Cluster SurveysStuntingUnderweightWasting

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