Caesarean section epidemic in India: Is private sector to blame? A multivariate logistic regression analysis of the National Family Health Survey - Manoj Kumar; Akshat Kumar Singh (PLoS ONE, 2026)
Background C-sections (CS) can be lifesaving in certain medical situations, but their prevalence has surged beyond recommended levels globally, raising concerns about inappropriate medical interventions and healthcare delivery quality. Objectives The study explores whether medical conditions alone determine C-sections or if socio-economic and institutional factors (i.e., Private/Public) also play a significant role. Method Using WHO and World Bank data, the relationship between C-section rates and income was analysed at the global level. Furthermore, at the national and state levels in India, the same analysis was conducted using data from the Ministry of Statistics and Programme Implementation and NFHS-5. Additionally, utilising the Birth recode datasets of NFHS-4 and 5, multivariate logistic regression was performed with C-section as the outcome variable and socio-economic and institutional variables, such as place of residence, levels of education, wealth index, and place of delivery, as predictor variables. Results Throughout the analysis, we found the institutional setting as the most significant influencing factor of CS rates, at both the national (OR: 4.11, 95% CI 3.98–4.24; NFHS-5) and state level for Bihar (OR: 16.19, 95% CI 13.76–19.05; NFHS-5), Uttar Pradesh (OR: 8.62, 95% CI 7.84–9.47; NFHS-5), Tamil Nadu (OR: 3.08, 95% CI 2.70–3.52; NFHS-5) and Andhra Pradesh (OR: 4.16, 95% CI 3.40–5.09, NFHS-5). On the contrary, we found that socioeconomic factors influenced the likelihood of CS only in states where medical infrastructure was lacking, indicating that socioeconomic factors are not directly responsible for CS rates; they are complicit only in determining institutional access. Additionally, an inverted U-shaped relationship was found between national per capita income and CS rates, indicating global inequality in the quality of healthcare. Within India, this relationship increasingly mirrors the global trend, possibly due to disparities in healthcare access and quality. Conclusion Our analysis confirms that the increase in CS rates is not solely caused by medical conditions, but is also significantly influenced by non-medical factors, particularly institutional factors. Economic incentives strongly drive private healthcare providers to prefer CS deliveries. The results suggest the need for targeted policy interventions to mitigate perverse incentives for private facilities and enhance public medical infrastructure, particularly in underserved regions.