Birth Interval and Nutritional Status (HAZ/WAZ) of Under-Five Children in North-East India: A Quantile Regression Analysis of NFHS-5 Data

Background: Chronic malnutrition harms children’s health. To achieve the SDGs, we still need to strengthen children’s nutritional outcomes in India. The objective was to investigate the association between birth interval and HAZ and WAZ across various quantiles; WHZ is not included. Methods: The present study used secondary data from DHS. Quantile regression is used to estimate covariate parameters at different percentiles. LMS method is then applied to draw the growth chart of children under five ages. Findings: Quantile regression indicates that longer birth intervals are associated with higher HAZ and WAZ (p-value <0.001). Low birth weight is negatively associated with HAZ and WAZ (ranging from -0.27 to -0.19, p <0.001), a significant association across quantiles. Maternal education is significantly associated with HAZ in the lower quantiles, whereas wealth index is also a significant factor for both HAZ and WAZ. Breastfeeding is not a significant factor for HAZ and WAZ across all quartiles. LMS analysis of HAZ over time shows a decreasing trend across all smoothed percentile curves. Conclusion: Quantile regression suggests that effects of different covariates vary across the HAZ and WAZ distributions. Among other predictors, birth interval is a key factor in identifying children with stunting and underweight.