Keywords: Inequality, Reproductive Maternal Neonatal and Child Health, Sustainable Development Goals, Delivery channel framework, Malnutrition, Stunting, Wasting, Underweight, National Family Health Survey, Anemia

Although India has achieved remarkable progress in health outcomes over recent decades, improvements in health outcomes have not kept pace with the economic growth that the country has experienced. Although women and child health indicators have improved significantly across the country, interstate disparities remain prevalent. Hence, it is vital to assess the coverage gap, which shall then aid in the precise distribution of resources and effective health programming. In our study, we compared and contrasted the trends in wealth-related inequalities in the coverage of Reproductive Maternal Neonatal and Child Health (RMNCH) services between a poor high-focus state (Chhattisgarh; CG) and a non-poor non-high-focus state (Tamil Nadu; TN) during the 2005–06 and 2019–21 periods by using the delivery channels framework. Also, we have analyzed the wealth-related inequalities in the nutrition status of women and children in both states. We also conducted a disaggregated analysis to examine whether the nutrition outcomes of the women and children in districts corroborate with their respective ranks (as per the TN Human Development Report, 2017).

We utilized unit-level data from three rounds of nationally representative surveys—i.e., the 3rd, 4th, and 5th National Family Health Survey (NFHS) conducted in 2005–06, 2015–16, and 2019–21, respectively)—for our analysis. For the first objective (i.e., to study the coverage of RMNCH services across various wealth quintiles), the interventions were classified into four groups (accounting for 16 indicators of RMNCH intervention coverage) according to their predominant delivery channels: community-based, health facility-based, environmental, and cultural. Also, to study the inequalities in nutrition status, we used the following standard indices of physical growth related to nutritional status: height for age (stunting); weight-for-height (wasting); weight for age (underweight). The height and weight measures of women were used to calculate body mass index (BMI) in kg/m2. The data for wealth quintiles were derived from information on household asset indices available in the unit-level data of the NFHS.

To study the trends and differentials of inequalities across wealth quintiles, we used two summary indices: absolute inequalities using the slope index of inequality (SII); relative inequalities using the concentration index (CIX). The values of SII and CIX lie between -1 and +1 and can be multiplied by 100. A positive value implies a pro-rich pattern and a negative value implies a pro-poor pattern, whereas a value of “0” implies no inequality. Estimates were performed at the 95% confidence interval (CI) and p