Why We Looked Beyond National Averages
India’s fertility decline is often cited as a demographic success. However, national and state averages can conceal deep local inequalities. We were concerned that high-risk fertility behaviours—such as early or late childbearing, short birth intervals, and high birth order—may still be concentrated in specific pockets of the country, continuing to expose women and children to avoidable health risks.
Seeing Fertility Through a Spatial Lens
Using over 1.2 million birth records from the National Family Health Survey (2019–21), we applied district-level spatial analysis to identify clusters of high-risk fertility behaviour (HRFB). Instead of viewing districts in isolation, spatial methods allowed us to see how neighbouring districts shared similar fertility risks, revealing clear hotspots and coldspots across India.
What the Maps Revealed
Nearly one-fourth of India’s districts emerged as HRFB hotspots, forming large contiguous belts across parts of Uttar Pradesh, Bihar, Jharkhand, Madhya Pradesh, Telangana, and West Bengal. In contrast, southern and hill states showed consistent coldspots. These patterns would remain invisible without district-level spatial analysis.
The Social Roots of Spatial Inequality
Hotspot districts were marked by significantly higher levels of child marriage, low female education, poverty, limited mass media exposure, and weaker engagement with family planning information. These disadvantages overlap spatially, reinforcing cycles of high-risk fertility across generations.
Why Child Marriage Matters Most
Decomposition analysis showed that child marriage alone explained nearly 70% of the gap in high-risk fertility between hotspot and coldspot districts. Early marriage extends women’s reproductive span while limiting autonomy over birth spacing and family size, making it a central driver of spatial inequality in fertility risk.
Implications for Policy and Practice
Many HRFB hotspots overlap with districts targeted under Mission Parivar Vikas, but our findings suggest the need to expand both coverage and scope. Beyond limiting births, district-specific strategies must address birth spacing, delayed childbearing, prevention of child marriage, and female education—especially in spatially clustered high-risk areas.
Reflections from the Research Journey
Working with spatial tools transformed how we interpreted familiar data. Seeing risk mapped across districts reinforced a key lesson: progress at the national level does not guarantee equity at the local level. Geography matters—and ignoring it risks leaving the most vulnerable behind.
Looking Ahead
Future research should combine spatial analysis with qualitative insights to understand how social norms and local contexts shape fertility behaviour. For policymakers, district-level evidence offers a powerful pathway to design targeted, equitable reproductive health interventions.
Further reading our paper: https://link.springer.com/article/10.1186/s12982-025-01263-5