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Distinct clusters of stunted children in India: An observational study.

Mark Alan GreenDaniel J CorsiIvan Mejía-GuevaraS V Subramanian
Published in: Maternal & child nutrition (2018)
Childhood stunting is often conceptualised as a singular concept (i.e., stunted or not), and such an approach implies similarity in the experiences of children who are stunted. Furthermore, risk factors for stunting are often treated in isolation, and limited research has examined how multiple risk factors interact together. Our aim was to examine whether there are subgroups among stunted children, and if parental characteristics influence the likelihood of these subgroups among children. Children who were stunted were identified from the 2005-2006 Indian National Family Health Survey (n = 12,417). Latent class analysis was used to explore the existence of subgroups among stunted children by their social, demographic, and health characteristics. We examined whether parental characteristics predicted the likelihood of a child belonging to each latent class using a multinomial logit regression model. We found there to be 5 distinct groups of stunted children; "poor, older, and poor health-related outcomes," "poor, young, and poorest health-related outcomes," "poor with mixed health-related outcomes," "wealthy and good health-related outcomes," and "typical traits." Both mother and father's educational attainment, body mass index, and height were important predictors of class membership. Our findings demonstrate evidence that there is heterogeneity of the risk factors and behaviours among children who are stunted. It suggests that stunting is not a singular concept; rather, there are multiple experiences represented by our "types" of stunting. Adopting a multidimensional approach to conceptualising stunting may be important for improving the design and targeting of interventions for managing stunting.
Keyphrases
  • young adults
  • risk factors
  • mental health
  • healthcare
  • physical activity
  • type diabetes
  • metabolic syndrome
  • climate change
  • skeletal muscle
  • risk assessment
  • middle aged
  • quality improvement
  • data analysis
  • human health