Abstract
BACKGROUND: Non-institutional deliveries, defined as childbirth outside healthcare facilities, remain a significant global concern. It poses serious maternal and child health problems and significantly contributes to maternal and infant mortality. India witnessed a sustained decrease in non-institutional deliveries in thepast 20 years. However, the rate of decline has tapered recently while the country still has a sizeable number of women delivering out of the facility. To better understand the enduring proportions of non-institutional deliveries, this study preliminarily analyses its predictors. The prime objective of the study is to unravel the inequality in the prevalence of non-institutional deliveries and understand if they are unfairly concentrated among certain households in India. It also aims to provide policy-relevant insights into the socioeconomic factors contributing to its concentration among specific households and their implications for maternal and child health. METHODOLOGY: Using the National Family Health Survey-5 (NFHS-5) data (N = 1,75,569 deliveries), we developed a regression model to understand the existing non-institutional deliveries and their predictors. We employed the Erreygers’ Concentration Index (ECI) to quantify the degree of concentration (inequality) of non-institutional deliveries among households. Furthermore, a decomposition analysis was run to analyse the factors contributing to the concentration of non-institutional deliveries in a particular groups of households. It breaks down the overall inequality at population level into its constituent parts to identify the sources of inequality. This approach helps discover prime causes of inequality, such as differences in income, education, or other relevant factors. FINDINGS: Out of the total sampled deliveries in the reference period, around 14% were non-institutional. Inequality analysis (ECI=-0.2174; p-value < 0.0001) suggests that non-institutional deliveries were unequally and unfairly concentrated in low-income households. The concentration of non-institutional deliveries in poor households was majorly contributed by factors like education (13.85%), wealth (13.91%), mass media exposure (12.27%) region (9.76%), birth order (3.17%), distance to health facilities (2.77%), caste (2.82%), timing of first ANC visit (1.07%), and women considering having to take transport as a problem (1.60%). CONCLUSIONS: This research employs inequality analyses of non-institutional deliveries and contributes to the existing literature by establishing its unfair concentration among poor households in India. It expands our understanding of the factors driving non-institutional deliveries among the disadvantaged. The findings highlight the importance of targeted interventions and policies to reduce the concentration of last-mile non-institutional deliveries among vulnerable women living in marginalized households. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12905-025-03819-8.