Differential improvement among countries in child stunting is associated with long-term development and specific interventions.
Stunting represents growth failure resulting from poor nutrition and health during the pre- and postnatal periods. Initiatives since 1980 have steadily reduced malnutrition and consequent retardation of child growth, but 1 of 3 preschool children worldwide remains stunted. Countries have varied substantially in progress achieved in reducing stunting. This study aimed to understand which underlying (i.e., proximal) and basic (i.e., distal) national factors have been most important in explaining this variation among countries, and the relation between the 2 sets of factors. Eighty-five developing countries with at least 2 surveys for stunting >4 y apart were included from the WHO Global Database on Child Growth. The analytic data set with independent variables from several sources was constructed to match closely by year for each country to initial and final stunting data. Full-information maximum likelihood estimated multiple linear regression models while accounting for missing data in independent variables. The final model explained 65.5% of the variance of change in stunting, and included both underlying and basic variables: initial and change in immunization rate, initial and change in safe water rate, initial female literacy rate, initial government consumption, initial income distribution, and the initial proportion of the economy devoted to agriculture. Although factors that were important for reducing stunting in the past may not necessarily be the ones that are important in the future, these results suggest that it possible for substantial progress to be made in reducing the current high prevalence of stunting by investing in both long-term development and in specific interventions.
Milman
Anna
A
Division of Nutritional Sciences, Cornell University, Ithaca, NY, USA.
Frongillo
Edward A
EA
de Onis
Mercedes
M
Hwang
Ji-Yun
JY
D000383:Agriculture / Q000191:economics; D002675:Child, Preschool; D003906:Developing Countries; D004467:Economics; D004522:Educational Status; D005260:Female; D006078:Government Programs; D006130:Growth Disorders / Q000517:prevention & control*; D006801:Humans; D007114:Immunization; D007182:Income; D016013:Likelihood Functions; D016014:Linear Models; D012044:Regression Analysis; D018508:Water Purification