Page 102 - GHES-3-1

Global Health Economics and
Sustainability
Maternal health-care service utilization

in the world to officially introduce the Family Planning rural areas, the survey employed a two-stage sample
Program (FPP) in 1951. After incorporating maternal design, whereas in most urban areas, a three-stage sample
and child health and recognizing the correlation between design was used. In rural regions, the first stage of village
increased newborn and child survival and declining birth selection was conducted using the probability proportional
rates, the FPP was eventually renamed the Family Welfare to size sampling scheme. In the second stage, the required
Program in 1977. In 1992, India restructured the Maternal number of households was selected through systematic
and Child Health program, in line with the 1987 Kenyan sampling. In urban areas, blocks were chosen in the first
International Safe Motherhood Conference – a global stage, followed by census enumeration blocks in the second
effort to reduce MMR, to become the Child Survival and stage, with approximately 150 – 200 families selected, and
Safe Motherhood (CSSM) program. Later, in 1997, the the required number of households was then chosen in the
CSSM program was merged into the Reproductive and third stage using systematic sampling. This study applied
Child Health program to address the needs of family sample weights [iw = wt] for the data analysis, and all
planning services, particularly for the impoverished and analyses were performed using STATA Version 17.
disadvantaged, and improve maternal and child health.
Similar in scope is the central Indian government’s recently 2.2. Methods
established National Rural Health Mission (NRHM, 2005), The maternal health outcome variables in this study are
a flagship initiative aimed at improving access to quality antenatal care (ANC), PNC, and SBA. A binary logistic
healthcare for rural residents across the nation, with a focus regression model was used to examine the demographic
on 18 states with inadequate public health infrastructure and socioeconomic determinants of MHCS utilization
(Pathak et al., 2010). in India. To analyze income inequalities in maternal
health outcomes, this study employs the decomposition
Economic status (Bhanderi & Srinivasan, 2015), caste
(Bhanderi & Srinivasan, 2015; Yadav & Jena, 2020), method developed by Blinder (1973) and Oaxaca (1973),
and generalized by Neumark (1988), in the subsequent
maternal education (Kumar & Paswan, 2021; Yadav et al., literature on health outcomes (Oaxaca & Ransom, 1988).
2021), partner’s education (Kumar & Paswan, 2021; Yadav
et al., 2021), religion (Chauhan et al., 2021; Jeffery & 2.3. Outcome variables
Jeffery, 2010), place of residence (Kumar & Paswan, 2021;
Yadav et al., 2021), women’s age (Yadav et al., 2022), mass Three outcome variables were included to evaluate the
media exposure (MME) (Yadav et al., 2022), and women’s sociodemographic and economic factors influencing
mothers’ use of healthcare: ANC coverage (at least four
autonomy (Yadav et al., 2022) are key factors associated visits [ANC4+]), SBA, and PNC.
with MHCS utilization.
This paper aims (i) to study the trends and patterns 2.4. Explanatory variables
of MHCS utilization between the poorest and richest The explanatory variables used in this study include age,
women in the EAG states of India over three decades, (ii) weight, place of residence, education level of the women,
to examine the determinants of MHCS utilization among partners’ education level, religion, caste, MME, wealth
women in EAG states, and (iii) to explore the disparities in index, women’s autonomy, and states.
MHCS utilization between the poorest and richest women
in the EAG states and identify factors responsible for these 3. Results
disparities. 3.1. Utilization of MHCS between poorest and
2. Data and methods richest women in India
Findings from Table 1 suggest that about 10.8% of the
2.1. Data
poorest women in 1998 in the EAG states had access to
The data used in this study were taken from the National ANC visits (ANC4+), compared to 67.26% of the richest
Family Health Survey (NFHS), conducted in four rounds women. From 1998 to 2021, this increased by an average
during 1998 – 1999, 2005 – 2006, 2015 – 2016, and 2019 of 31% with ANC4+ for the poorest rising to 41.8%,
– 2021. These surveys cover approximately 99% of the whereas access for the richest women increased by 4.56%
Indian population and are nationally representative. This to 71.82%. SBA also varied significantly. For the poorest
survey is equivalent to the demographic health survey women, SBA increased from 13.74% in 1998 to 77.6% in
and provides reliable and consistent estimates of many 2021, reflecting a rise of 63.86%. For the richest women,
health-related variables at both the national and state SBA access increased by 25.13% over the same period. PNC
levels, including family planning, mortality, fertility, and for the poorest women was unavailable in 1998. However,
use of maternal and child health-care services. In most by 2021, 82.13% of the poorest women had access to PNC,

Volume 3 Issue 1 (2025) 94 https://doi.org/10.36922/ghes.3324