Community-based clustering of height in Ethiopia, India, Peru, and Vietnam

Human growth and final height are influenced by many factors such as genetics, nutrition, living conditions, socioeconomic background and, as recently proposed, by social peer groups and the community. In this paper, we aim to evaluate the extent to which spatial proximity, acting as a proxy for the social community, causes height clustering in low and middle income countries.

We analyzed data from the study "Young Lives-Measuring Child Poverty and Health", a study performed in four low and middle income countries (Ethiopia, India, Peru and Vietnam) to describe the health situation of children. We used linear mixed effects models with different random effect structures to analyze the influence of the community on clustering of height in boys and girls.

In all analyzed low and middle income countries, linear mixed effects with hierarchical structures with communities nested within regions provide a better fit than the basic models neglecting community-based clustering (p < .001).

Although the underlying mechanisms require future research, spatial proximity arising from clustering needs to be integrated into explorative modelling of height variability in humans.