BACKGROUND:
India has substantially reduced the burden of under-five child malnutrition over the last two decades. Despite this, it is still gigantic and differs remarkably across districts, while the demographic and socio-economic groups are most affected by it. This paper aimed to decrypt the place-specific spatial dependence and heterogeneity in associations between district-level nutritional status (stunting, wasting and under-weight) and its considered correlates using a geocoded database for all 640 Indian districts

METHODS:
Data were drawn from the latest fifth wave of the National Family Health Survey, 2019–21. Univariate Moran’s I and LISA statistics were used to confirm the spatial clustering and dependence in under-five nutritional status. The Ordinary Least Square (OLS), Geographically Weighted Regression (GWR), Spatial (lag/error) models were employed to examine the effects of correlates on the district-level nutritional status.

RESULTS:
The nationwide prevalence of under-five stunting, wasting, and underweight were 35.5%, 19.3% and 32.1%, respectively. The Moran’s I value for the district-level stunting, wasting and underweight were 0.634, 0.488 and 0.721, respectively. The GWR results disclosed that the spatial heterogeneity in relationships between district-level nutritional status and its driving forces were strongly location-based, altering their direction, magnitude and strength across districts. Overall, the localized model performed better, and best fit the data than the OLS and spatial (lag/error) models.

CONCLUSIONS:
This nationwide study confirmed that the spatial dependencies and heterogeneities in the district-level nutritional status indicators were strongly explained by a multitude of factors and thus can help policymakers in formulating effective nutrition-specific programmatic interventions to speed up the coverage of under-five malnutrition status in most priority districts and geographical hot spots across India.