Socioeconomic situation and growth in infants and juveniles

Anthropol Anz. 2017 Jul 1;74(2):101-107. doi: 10.1127/anthranz/2017/0706. Epub 2017 May 8.

Abstract

Background: Physical growth of children and adolescents depends on the interaction of genetic and environmental factors e.g. diet and living conditions. Aim: We aim to discuss the influence of socioeconomic situation, using income inequality and GDP per capita as indicators, on body height, body weight and the variability of height and weight in infants and juveniles. Material and methods: We re-analyzed data from 439 growth studies on height and weight published during the last 35 years. We added year- and country-matched GDP per capita (in current US$) and the Gini coefficient for each study. The data were divided into two age groups: infants (age 2) and juveniles (age 7). We used Pearson correlation and principal component analysis to investigate the data. Results: Gini coefficient negatively correlated with body height and body weight in infants and juveniles. GDP per capita showed a positive correlation with height and weight in both age groups. In infants the standard deviation of height increases with increasing Gini coefficient. The opposite is true for juveniles. A correlation of weight variability and socioeconomic indicators is absent in infants. In juveniles the variability of weight increases with declining Gini coefficient and increasing logGDP per capita. Discussion: Poverty and income inequality are generally associated with poor growth in height and weight. The analysis of the within-population height and weight variations however, shows that the associations between wealth, income, and anthropometric parameters are very complex and cannot be explained by common wisdom. They point towards an independent regulation of height and weight.

MeSH terms

  • Anthropology, Physical
  • Anthropometry
  • Body Height / physiology*
  • Body Weight / physiology*
  • Child
  • Child Development / physiology*
  • Child, Preschool
  • Humans
  • Infant
  • Models, Statistical*
  • Poverty
  • Socioeconomic Factors*