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Child stunting remains an important global health issue, with 157 million children under five years of age estimated to be stunted in 2014. Until recently, stunting was thought to occur in the first 1000 days of life (between conception and 2 years of life), and was thought to be largely irreversible thereafter. However, emerging research suggests that children can transition between stunted and non stunted status up to 15 years of age, with studies also suggesting potential implications in terms of cognitive status. Despite this, there is little research on stunting and its potential determinants among children of older ages, with most current studies confined to those under five. This study aims to assess the prevalence of stunting and examine potential sociodemographic determinants of stunting (including individual, maternal and household level indices) among older children (aged 6-19 years) in a Malaysian population.
Full description
This analysis is based on existing data collected by a health and demographic surveillance system operating in Segamat, Malaysia, and data for all individuals meeting the stated inclusion criteria are used in the study.
There is not a specific control treatment in this study. Rather, we calculate the risk of stunting associated with (1) a unit increase in each exposure, or (2) categories of exposure with respect to a referent category. Specifically, for the primary exposures as listed above:
Methods for crude analysis and gaining an introductory sense of the data include examination of variable distributions and clustering of the outcome variable of interest (stunting or height-for-age). Exposure variables are assessed by stunting status; differences between stunted and non-stunted groups are assessed using Student's t test for continuous variables, and Pearson's chi squared test (Fisher's exact test for variables with cell counts <5) for categorical variables. Additionally, the classification and prevalence of stunting is assessed using two different references: the World Health 2007 reference and Centers for Disease Control and Prevention 2000 reference; agreement in classification between the two is calculated using Cohen's kappa.
The primary method of analysis is mixed effects Poisson regression, with stunting as the outcome of interest. Final models include all exposure variables of interest, in order to assess any independent associations between each exposure and stunting risk. All models are adjusted for clustering at the household level.
A number of secondary analyses are used in order to check the robustness and specificity of associations. These include:
Both the primary and secondary analyses are run with stunting or height-for-age expressed according to (1) the Centers for Disease Control and Prevention 2000 reference and (2) the World Health Organization 2007 reference.
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Inclusion Criteria:
Exclusion Criteria None
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Data sourced from clinicaltrials.gov
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