The author investigates the extent and determinants of poor child health and nutrition in rural Guatemala, as reflected in attained height. Exploiting a rich data set on relevant social, economic, ethnic, and geographic characteristics, he estimates the role played by exogeneous individual, household, and community covariates in shaping differentials in children's height. Then he addresses empirical questions ignored in previous anthropometric research, such as the distribution of child stunting across communities and the magnitude of intra-family correlation of height-for-age outcomes, before and after controlling for observed covariates. The author estimates are guided by the economic model of the family and the proximate determinants framework. The author fits multilevel models to hierarchically clustered data to control for family and community heterogeneity. His results confirm findings from previous research, suggesting that poor child growth outcomes in Guatemala are the result of widespread poverty. He finds that height-for-age differentials between children of latino mothers and children of indigenous mothers who do not speak Spanish are larger among children living in communities with better health care facilities. Estimates derived from multilevel models reveal much clustering of child height-for-age outcomes within families and communities. The models account for most of the community-level variation in child growth patterns, but explain only half of the overall intra-family correlation.
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