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This study examines how son preference affects short birth intervals among women in India, highlighting public health implications.

June 11, 2026Open Access

Gender bias in fertility choices: how son preference increases the risk of short birth intervals in India

Key Points

This study examines how son preference affects short birth intervals among women in India, highlighting public health implications.
Analyzed data from 117,135 married women aged 15-49 with at least two consecutive live births from NFHS-5.
Employed logistic regression models to estimate adjusted odds ratios for short birth intervals.
Applied the Fairlie decomposition technique to quantify contributions of various factors to birth interval disparities.
Women with son preference had 16% higher odds of short birth intervals (AOR = 1.16; 95% CI 1.12-1.20).
78.4% of disparity in short birth intervals explained by measurable factors, with household wealth being the largest contributor (64.7%).
21.6% of the disparity remains unexplained, suggesting unmeasured patriarchal norms and reproductive coercion.

Abstract

BACKGROUND: Short birth intervals are a persistent public health issue that elevate maternal and child health risks in India, where high patriarchy and son preference influence reproductive health outcomes among women. While prior research has not isolated or quantified the contribution of son preference to short birth interval (SBI). This study explores the impact of son preference on SBI in India. DATA AND METHODS: Using nationally representative data from India's National Family Health Survey (NFHS-5, 2019-21), we analyzed 117,135 married women aged 15-49 with at least two consecutive live births. We employed logistic regression models to estimate adjusted odds ratios (AORs) for SBI. Furthermore, the Fairlie decomposition technique was also applied to quantify the contribution of observed individual, household, and community-level characteristics in the differential length of birth interval among son preference and non-son preference women. RESULTS: Women who had son preference had 16% higher odds of SBI (AOR = 1.16; 95% CI 1.12-1.20). The Fairlie decomposition revealed that 78.4% of this disparity was explained by measurable factors. Household wealth was the dominant contributor (64.7%), followed by fertility desire (30.4%), maternal BMI (16.3%), and household size (15.9%). Notably, maternal education and regional context acting as equalizing forces, reducing the explained gap by 18.8% and 24.8%, functioning as protective suppressors, however, 21.6% of the disparity remained unexplained, suggesting unmeasured patriarchal norms and reproductive coercion mechanisms. CONCLUSION: Son preference's influence on SBI in India is not rooted solely in cultural tradition but is statistically explained by observed characteristics. Policies that enhance women's education, economic security, and access to family planning, especially in high-patriarchy regions, can disrupt the association between son preference and SBI. Integrating gender-transformative approaches into India's reproductive health programs is essential to advance both maternal health (SDG 3) and gender equality (SDG 5).

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