Methodology for estimating regional and global trends of child malnutrition

Int J Epidemiol. 2004 Dec;33(6):1260-70. doi: 10.1093/ije/dyh202. Epub 2004 Nov 12.

Abstract

Background: Child malnutrition is an important indicator for monitoring progress towards the Millennium Development Goals (MDG). This paper describes the methodology developed by the World Health Organization (WHO) to derive global and regional trends of child stunting and underweight, and reports trends in prevalence and numbers affected for 1990-2005.

Methods: National prevalence data from 139 countries were extracted from the WHO Global Database on Child Growth and Malnutrition. A total of 419 and 388 survey data points were available for underweight and stunting, respectively. To estimate trends we used linear mixed-effect models allowing for random effects at country level and for heterogeneous covariance structures. One model was fitted for each United Nation's region using the logit transform of the prevalence and results back-transformed to the original scale. Best models were selected based on explicit statistical and graphical criteria.

Results: During 1990-2000 global stunting and underweight prevalences declined from 34% to 27% and 27% to 22%, respectively. Large declines were achieved in Eastern and South-eastern Asia, while South-central Asia continued to suffer very high levels of malnutrition. Substantial improvements were also made in Latin America and the Caribbean, whereas in Africa numbers of stunted and underweight children increased from 40 to 45, and 25 to 31 million, respectively.

Conclusion: Linear mixed-effect models made best use of all available information. Trends are uneven across regions, with some showing a need for more concerted and efficient interventions to meet the MDG of reducing levels of child malnutrition by half between 1990 and 2015.

MeSH terms

  • Child
  • Child Nutrition Disorders / epidemiology*
  • Child Nutritional Physiological Phenomena*
  • Developing Countries*
  • Global Health*
  • Growth Disorders / epidemiology
  • Humans
  • Linear Models
  • Prevalence