District-Level Low Birth Weight Patterns Linked to Temperature in India

Researchers analysed NFHS-5 data from 2019–21 in a cross-sectional ecological spatial study of Indian districts. Temperature-related analyses covered 706 districts; Lakshadweep was excluded because temperature data were unavailable. The team mapped low-birth-weight (LBW) prevalence and assessed spatial clustering, then used regression models to examine district-level correlates while accounting for spatial dependence.

Mean district-level LBW prevalence was 17.15%. Punjab had the highest state-level prevalence (22.4%) and Mizoram the lowest (4.0%); district estimates ranged from 36.6% in Dantewada, Chhattisgarh, to 0.7% in Kohima, Nagaland. LBW showed strong spatial clustering (Moran’s I=0.572; p<0.001), including a high-prevalence belt across Rajasthan, Madhya Pradesh and Gujarat. In the preferred spatial error model, mean annual temperature was positively associated with LBW (β=0.181; p=0.023), as were maternal anaemia, maternal underweight and winter births. Adequate antenatal care coverage was negatively associated (β=-0.048; p<0.001).

The findings identify geographic patterns that may inform population-level maternal health planning. However, this ecological analysis reports district-level associations, not individual-level effects or evidence that temperature causes LBW; its results do not establish the impact of specific interventions.