Evidence map›Paper›PMID 42676529›Full record

ArticleFrontiers in global women's health2026

Geographical clustering of delayed motherhood in India: an application of multilevel and geospatial analyses.

Mayank Singh, Chander Shekhar, Jagriti Gupta, Rajeev Kumar

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Article in Frontiers in global women's health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Mayank SinghDepartment of Epidemiology and Biostatistics, KLE Academy of Higher Education and Research, Belagavi, Karnataka, India.
Chander ShekharDepartment of Fertility & Social Demography, International Institute for Population Sciences (IIPS), Mumbai, India.
Jagriti GuptaBiostatistician, Bagchi School of Public Health, Ahmedabad University, Ahmedabad, Gujrat, India.
Rajeev KumarPG Department of Statistics, Patna University, Patna, Bihar, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Rapid sociodemographic changes in India, including rising female education, workforce participation, urbanization, and changing gender norms, have contributed to delayed childbearing. Despite declining fertility, limited evidence exists on the district-level geographic variations and determinants of delayed motherhood (childbirth at age ≥35) in India. This study applies multilevel and geospatial analyses to examine the distribution, determinants, and district-level spatial clustering of delayed motherhood using National Family Health Survey data. Methods: This study employed multilevel multivariable logistic regression to examine individual- and district-level determinants of delayed motherhood. Spatial clustering was assessed using Global Moran's Results: The prevalence of delayed motherhood varied widely, ranging from negligible levels in some districts to as high as 60.18% in South West Khasi Hills, with a national average of 8.7% [95% confidence interval (CI): 8.1-9.3]. Higher education [adjusted odds ratio (AOR): 2.00; 95% CI: 1.80-2.23] and age at marriage ≥21 years (AOR: 5.13; 95% CI: 4.65-5.67) were significant predictors. Additional factors such as higher parity, religious affiliation, and socioeconomic status also showed significant associations. A spatial analysis revealed strong clustering (Moran's Conclusion: Delayed motherhood in India exhibits substantial sociodemographic and spatial heterogeneity. Key determinants include education, marriage timing, and parity patterns. The presence of distinct geographic clusters highlights the importance of regional context. These findings underscore the need for region-specific and demographically targeted policy interventions, along with further research into behavioral and health system factors influencing delayed childbearing.

Indexed as

age at marriagedelayed motherhooddistrict-level disparitiesIndiamaternal and child healthmultilevel analysissocioeconomic determinantsspatial analysis

Identifiers

PMID42676529
PMCPMC13526969

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