Child mortality as predicted by nutritional status and recent weight velocity in children under two in rural Africa

J Nutr. 2012 Mar;142(3):520-5. doi: 10.3945/jn.111.151878. Epub 2012 Jan 18.

Abstract

WHO has released prescriptive child growth standards for, among others, BMI-for-age (BMI-FA), mid-upper arm circumference-for-age, and weight velocity. The ability of these indices to predict child mortality remains understudied, although growth velocity prognostic value underlies current growth monitoring programs. The study aims were first to assess, in children under 2, the independent and combined ability of these indices and of stunting to predict all-cause mortality within 3 mo, and second, the comparative abilities of weight-for-length (WFL) and BMI-FA to predict short-term (<3 mo) mortality. We used anthropometry and survival data from 2402 children aged between 0 and 24 mo in a rural area of the Democratic Republic of Congo with high malnutrition and mortality rates and limited nutritional rehabilitation. Analyses used Cox proportional hazard models and receiver operating characteristic curves. Univariate analysis and age-adjusted analysis showed predictive ability of all indices. Multivariate analysis without age adjustment showed that only very low weight velocity [HR = 3.82 (95%CI = 1.91, 7.63); P < 0.001] was independently predictive. With age adjustment, very low weight velocity [HR = 3.61 (95%CI = 1.80, 7.25); P < 0.001] was again solely retained as an independent predictor. There was no evidence for a difference in predictive ability between WFL and BMI-FA. This paper shows the value of attained BMI-FA, a marker of wasting status, and recent weight velocity, a marker of the wasting process, in predicting child death using the WHO child growth standards. WFL and BMI-FA appear equivalent as predictors.

MeSH terms

  • Body Height
  • Body Mass Index
  • Democratic Republic of the Congo / epidemiology
  • Female
  • Humans
  • Infant
  • Infant Mortality*
  • Infant, Newborn
  • Male
  • Multivariate Analysis
  • Nutritional Status*
  • Proportional Hazards Models
  • Rural Population
  • Wasting Syndrome / epidemiology
  • Wasting Syndrome / pathology
  • Weight Gain*