Data on birth weight in developing countries: can surveys help?

Bull World Health Organ. 1996;74(2):209-16.

Abstract

The main source of data on birth weight in developing countries is statistics from health facilities, although most developing countries do not produce annual estimates of the incidence of low birth weight from these data. Such estimates would be subject to selection bias as the data are usually limited to babies born within health facilities, and therefore are representative of a subgroup that is markedly different from the overall population of neonates. Since 1990 the Demographic and Health Surveys programme has included questions on recalled birth weight and relative size at birth in 15 national surveys. In this article, we show that these cross-sectional surveys can provide a useful data source for making national estimates of mean birth weight and the incidence of low birth weight. The extent of misclassification of birth weight is, however, too large to use the data on relative size at birth as an indicator of low birth weight at the individual level.

PIP: Data from 15 surveys conducted in developing countries that included questions on birth weight were analyzed to determine whether birth weight data from cross-sectional surveys can be used to improve national estimates of mean birth weight and the incidence of low birth weight (LBW). The proportion of children weighed at birth ranged from 9% in Pakistan and Yemen to 91% in the Dominican Republic. Most women could recall the birth weight. Units of measurement to record birth weight included grams in seven surveys, kilograms carried to one decimal place in five surveys, kilograms carried to two decimal places in one survey, pounds and ounces in one survey, and pounds or kilograms in one survey. Among all surveys reporting in kilograms or grams, 33-50% of birth weights were recorded in multiples of 500 g. The sensitivity of the relative-size-at-birth indicator to identify LBW babies was very low in all surveys (mean, 29%), even though the positive predictive value (PPV) was at least 70% in most surveys. Thus, most infants reported as very small were indeed LBW, but only 29% of all LBW infants were identified. When one used both very small and small as indicators of LBW, sensitivity improved greatly (mean, 66%). Yet 45% (mean PPV) of the very small and small infants were of LBW. The incidence of LBW, when considering both numerical weight and size, ranged from 8.7% (Colombia) to 18.8% (Tanzania). Poor data quality probably accounted for the fact that data from Yemen were very different than those from the other surveys. These findings suggest that these surveys can be a useful data source for estimating mean birth weight nationwide and the incidence of LBW. Misclassification of birth weight is too common to use the data on relative size at birth as an indicator of LBW at the individual level.

MeSH terms

  • Bias
  • Birth Weight*
  • Body Height
  • Cross-Sectional Studies
  • Developing Countries*
  • Humans
  • Infant, Low Birth Weight
  • Infant, Newborn
  • Population Surveillance*
  • Predictive Value of Tests
  • Retrospective Studies
  • Sensitivity and Specificity
  • Surveys and Questionnaires