Heterogeneous effects of factors on child nutritional status in Bangladesh using linear quantile mixed model

Earlier studies to assess the effects of risk factors on child nutritional status in Bangladesh have used conventional regression models that are inadequate to capture a complete scenario of effects. Therefore, this study aimed to evaluate the heterogeneous effects of factors at different points of conditional height-for-age Z-score (HAZ) distribution accounting for cluster-level variation using linear quantile mixed model (LQMM) and to compare them with a linear mixed model (LMM). In addition, an unconditional quantile model (UQM) was used to measure the effect of factors on the unconditional (marginal) HAZ distribution. A total of 6340 children aged 0–59 months extracted from the 2014 Bangladesh Demographic and Health Survey. Different factors – maternal characteristics (age, occupation, nutritional status, parity, birth interval), parental education, child age, breastfeeding status, and morbidity had significant heterogeneous effects on HAZ distribution. For example, secondary or higher educated parents had substantial differential impacts on the lower tail and upper tail of the child HAZ distribution, which was masked by LMM estimate. Moreover, significant cluster-level variations found across all quantiles of child HAZ. During intervention design, heterogeneous effects of factors and cluster variation ought to consider addressing the undernutrition problem in Bangladesh.