Multiple Vulnerabilities in Access to and Utilising of Maternal and Child Health Services in India: A Spatial

Abstract

Introduction

Although there are multiple vulnerabilities in the utilisation of maternal and child health (MCH) services in India, research has always been focused on single-dimension vulnerabilities like economic or social vulnerabilities. Individuals who are poor may also face other types of vulnerabilities that together affect access to health services. This article, therefore, investigates the linkages between multiple vulnerabilities and the utilisation of MCH care services.

Materials and Methods

Data from National Family Health Survey (2015–2016) for India and states were used for analysing the key outcome variables namely women received four or more antenatal care (ANC), institutional delivery, postnatal care (PNC) and full immunisation for children in the age group of 12–23 months. Bivariate analysis and binomial-logistic regression analysis were employed to examine the multiple vulnerabilities on utilising MCH services across three dimensions of vulnerabilities, such as education, wealth and caste.

Results

Women with multiple vulnerabilities were less likely to utilise essential MCH services. Women who faced vulnerabilities in all three dimensions were less likely to have received four or more ANC and postnatal care than those who were not deprived of any vulnerabilities (0.3 vs. 0.9 and 0.4 vs. 0.8, respectively). They were also less likely to deliver in health facilities and avail child immunisation (0.5 vs. 0.8 and 0.3 vs. 0.7, respectively).

Conclusion

A multi-sectoral approach is therefore required to deal with the issues of low access and underutilisation of MCH services.

Keywords

Caste and class multiple vulnerabilities MCH India

Introduction

Although India has made considerable progress in achieving the Millennium Development Goals (MDGs), the progress on several maternal and child health (MCH) indicators is still below the expected levels. With huge socio-cultural and economic differentials in nature, India faces unprecedented inequality in health and health care practices across geographic regions (urban–rural), socioeconomic groups, age–sex groups and migrant status (Patel et al., 2015; Paul et al., 2019). Higher maternal and child deaths are caused by low access and underutilisation of essential health services. Several studies in India have reported that inequities exist in access to maternal healthcare between states and within states and across regions (Deaton & Dreze, 2009; Navaneetham & Dharmalingam, 2002; Subramanian et al., 2006). Further, the variations in access to MCH services can also be seen across different segments of the population. Low education, poverty and social class have been shown to be significantly associated with lower utilisation of MCH services. The studies have also shown that variation across income groups in access to maternal care is widening, with poor women receiving fewer services than those who are better off (Pandey et al., 2004; Pathak et al., 2010).

Further, north Indian states such as Uttar Pradesh, Bihar and Jharkhand also have lower levels of utilisation of MCH services as compared to most of the south Indian states (Dehury & Samal, 2016). The MCH care services in the northern states are particularly poor, and this has been seen as highly inequitable across socio-economic groups. Empirical evidence suggests that although maternal care has improved in the states over the last few decades, progress has been slow and uneven within and between the states. For example, the proportions of women in Uttar Pradesh (a northern state) who received antenatal care for their last pregnancy and institutional delivery have increased between 1992 and 2015, from 44.7% to 72% and from 11.2% to 67.8%, respectively; however there is also the rich-poor gap (i.e. the ratio of the richest to the poorest wealth quintile) for the use of antenatal care, which remained high over the period while the proportion for institutional delivery declined (IIPS & ICF, 2017; IIPS & Macro International, 1995). Similarly, the illiterate–literate ratio and Schedule Caste/Schedule Tribes to others ratio for the use of antenatal care has widened over the same time period.

Although the proportion of women receiving medical assistance at delivery increased between 1992 and 2015, there is a huge gap in receiving medical assistance between poor and non-poor women. Similarly, the educational differential in institutional delivery in 1992 was 11.8% for women with no education and 75% for those with 10 or more years of schooling. The same figure in 2015 was 56% for women with no education and 85.8% for women with 10 or more years of schooling, indicating a faster improvement among women with no education (IIPS & ICF, 2017; IIPS & Macro International, 1995). Further, a study conducted in 2005–2006 also showed that the proportion of births between 2005 and 2006 that were delivered in a health institution varied from 31% for women with no education to 68.8% for women with 12 or more years of schooling (Mohanty, 2012). Likewise, the proportion of full ANC coverage and institutional delivery variations across social groups show slower progress among socially disadvantaged groups like SC/STs (Scheduled Caste/Schedule Tribe) than the other groups. In postnatal check-up within 2 days, women who have 12 or more years of schooling had gone for postnatal-care check-up nearly 78% than women with no schooling 51%. Similarly, those women who are from the wealthiest quintile received 80% postnatal check-up within 2 days than those women who are from the lowest wealth quintile (48%). Further, Scheduled Tribe women received 59% postnatal check-up within 2 days after delivery than those women who belong to the Forward-caste group (69%) (IIPS & ICF, 2017).

Several studies have contributed to understanding the income disparities in maternal health care utilisation (Houweling et al., 2007; Mohanty, 2012; Mohanty & Pathak, 2009). Several studies analysed various rounds of DHS (demographic and health survey) data to understand the inequalities in maternal and child health across household wealth quintiles after controlling for other social and demographic variables (Hong et al., 2006; Ladusingh & Singh, 2007; Mohanty, 2011; Mohanty & Pathak, 2009). In addition, some outlined the contextual determinants of maternal and childcare in different Indian states (Ladusingh & Singh, 2007). Apart from economic status, there are several other factors that determine vulnerability, that is, social determinants (Balarajan et al., 2011; Borooah et al., 2012; Mechanic, 2002; Phelan et al., 2010; Raghupathy, 1996). Two important factors such as poor education and lower caste are typical in Indian conditions, which add to vulnerability too when seeking maternal and childcare services (Gupta et al., 2016; Saroha et al., 2008). Many studies have independently demonstrated the effect of each of these factors on maternal and child health (Borooah et al., 2012; Goli et al., 2013; Mohanty, 2012; Raghupathy, 1996). However, very few studies have looked at the effects of multiple vulnerabilities and their linkages on the utilisation of health services. For example, a poor woman may also be poor educationally or she may also belong to a disadvantaged caste group.

The concept of multiple vulnerabilities has received recent attention from both researchers and policymakers because the use of individual-level socioeconomic indicators alone may fail to capture the health impacts of contextual factors. Approaches covering multiple vulnerabilities can take into account the effects of the individual as well as the household and contextual disadvantages that impact health. Similarly, the existing phenomena related to multiple intersecting identities, which are historically oppressed groups within the population, have become complexities in health disparities (Bowleg, 2012). The other critical step is recognising how systems of privilege and oppression result in multiple social inequalities (Bowleg, 2012).

Further, equity in health is the absence of systematic disparities in health (or in the major social determinants of health) between groups. Knowledge of the aggregate effects of multiple vulnerabilities is needed to shed light on the determinants of growing health inequities. The objective of this article is to understand the linkages between multiple vulnerabilities and maternal and child healthcare utilisation in India and across regions.

Multiple Vulnerabilities: Issues and Concerns

The association between vulnerabilities and health outcomes has always focused on single vulnerability like income or education and its linkage with health outcomes. However, in any society, poor people may also have lesser education or poorer health or they may be from socially disadvantaged groups. Those individuals who face more than one vulnerability may have a greater burden than those who face a single vulnerability. For example, women who belong to poorer households are more likely to have adverse health outcomes than those who are from wealthier households. If those poor women also lack education or if they are from socially disadvantaged groups, their burden increases, and they may have lower utilisation of health services than those who face only single vulnerability (Mohanty, 2011, 2012). Therefore, to address the health inequality in health care access and service utilisation, there is a greater need to understand this through the lens of multiple deprivations of wealth, education, class, caste and regional status. Studies have demonstrated that women who belong to the disadvantaged groups remained disadvantaged in health care access and utilisation of health services (Anand & Yusuf, 2011; Mohanty, 2012; Prusty et al., 2015; Saroha et al., 2008).

The disadvantaged groups of people can be identified in relative terms, such as socially disadvantaged, economically disadvantaged, disadvantaged concerning gender and geographically disadvantaged. The disadvantaged groups of people can also be recognised in three ways; first, at the individual level; second, at the family or household characteristics level and third the social-economic groups’ characteristics level (Brook & Williams, 1975).

The structural and social hierarchy is a highly significant attribute in health and healthcare practices in India (Acharya, 2010; Borooah et al., 2012). India is a caste-driven society, and caste plays an important role in defining the socio-political and economic structure of a particular society. In the hierarchy of social status, Scheduled Caste (SCs) or Dalits and Adivasis or Scheduled Tribes (STs) are the most disadvantaged groups. There is literature to support the view that probably social deprivation may affect more than wealth and health (Baru et al., 2010; Mosse, 2018; Saroha et al., 2008). In the economic class, there is a hierarchy in which poorest and poorer are more deprived of accessing public resources than richer and richest class. In India, socio-economic status determines health status of aparticular individual or community (Bhatia et al., 2006; Montagu et al., 2011).

A multi-dimensional vulnerability identifies clusters of vulnerability. While measuring multiple vulnerabilities, there are theoretical and methodological challenges, which include contextualising the dimensions and indicators in order to fix the cut-off point for ‘poor’ and ‘non-poor’, aggregation of multiple dimensions into a single index, weighting the dimensions and choosing the unit of analysis (Alkire, 2007; Alkire & Foster, 2009; Mohanty, 2012; Sen, 1992). This article, therefore, understands the three-dimensional vulnerability of wealth, education and caste and their linkages with the utilisation of maternal and child health services in the country.

Materials and Methods

The data were used from the National Family Health Survey, fourth round of 2015–2016. In India, NFHS-4 (DHS-2015–2016) has provided information on reproductive and child health care practices for all states. The survey covered 699,669 households and collected information from 259,627 women in the age group of 15–49. In the case of ever-married women, the sample size is 259,627 in the country who were interviewed in the age group of 15–49. The survey provides information on women’s characteristics, marriages, fertility, contraception, reproductive health, children’s immunisations and treatment of childhood illnesses. In the previous round of the survey, all this information was available at the state and national levels. The study uses NFHS-4 data to understand the current status of service utilisation among the disadvantaged groups of people with multiple dimensions of deprivation in India and its major states. Only ever-married women who have given birth in the last 5 years have been considered for the analysis.

The level and the utilisation pattern of MCH services across the region in India have been analysed using a multiple vulnerability approach. The outcome variables used here are four or more antenatal care (ANC), institutional delivery and postnatal care (PNC) as indicators of the utilisation of maternal healthcare services and coverage of full immunisation as child health care variable. Descriptive statistics, bivariate and logistic regression analyses are carried out to estimate the level and pattern of multiple vulnerabilities and their linkages to the utilisation of maternal and child healthcare services. Results are shown as predicted probabilities derived from logistic regression, and predicted probabilities adjust at the mean of all other independent variables.

Vulnerability Measures

To understand multiple vulnerabilities/deprivations, a variable integrating the three dimensions of deprivation based on education, wealth and caste was constructed, as they were used in the two Human Poverty Indexes and the Multidimensional Poverty Index (instead of the caste they used health). The low education is classified as those women who did not complete 5 years of schooling. For education, a woman is considered deprived or vulnerable if she reports in her individual survey that she has not completed 5 years of schooling. This cut-off is chosen because people with only a few years of education have been found to have health-seeking behaviour similar to those with no education. As the NFHS does not collect information on household consumption or income, household economic proxies such as housing quality, household amenities and consumer durables were used to construct the composite wealth quintile. Those who are poorest or poorer from the wealth quintile per se have been considered as economically ‘poor’ and middle, richer and richest are ‘non-poor.’

For caste, a woman is considered vulnerable if she belongs to a Schedule Caste or Schedule Tribe. Using the three dimensions of vulnerability based on education, wealth and caste, eight categories of vulnerability are possible: education, wealth and caste, education and wealth, education and caste, wealth and caste, education only, wealth only, caste only and none. The first four categories classify vulnerability in multiple dimensions, the next three in one dimension and the last category in none. The country-level data are sufficient to show differentials in MCH care for all eight categories of vulnerability/deprivation. However, the regional- and state-level data are issued for only four groups—vulnerable in none, in one dimension, in two dimensions and vulnerable in three dimensions.

Dependent variables

Antenatal care (ANC): In the NFHS-4, the question that was asked to women was whether they ‘had at least four visits for ANC check-up for recent birth during the 5 years preceding the survey’. In this analysis, those pregnant women who have gone for four or more rounds of antenatal care have been included in the analysis.

Institutional delivery: Institutional delivery is defined as deliveries that happen in hospitals/health facilities, either public or private.

Postnatal care (PNC): In the survey, women who had their last birth in the 5 years preceding the survey were asked, ‘Did you have any check-up within 42 hours after delivery?’ and ‘How many days after delivery did the first check-up take place?’ In this study, women who went for a check-up at any health facility/doctor within 2 weeks of delivery are considered to have used postnatal care services.

Full immunisation: A child in the age group of 12–23 months is fully immunised if she or he has received BCG, measles and three doses each of DPT and Polio vaccine.

Results

Dimensions of Vulnerabilities in India and Its Regions

The result (Table 1) shows the proportion of women with different types of vulnerabilities/deprivations in India and its regions. In India, 47% of women are in the poor category, 36% have low education and 33% belong to the Scheduled Caste and Scheduled Tribe category.

Table 1.

Proportion of Ever-married Women (age group of 15–49) with Different Types of Vulnerabilities in India and Its Regions, 2015–2016.

Categories of Vulnerabilities	India	Its Region
Categories of Vulnerabilities	Total	North	Central	East	West	South
Poor	47.32	29.86	57.74	72.3	29.18	20.15
Low education	36.24	35.68	44.23	48.91	21.7	16.53
SCs/STs	33.23	35.59	32.66	34.6	31.82	29.42

Source: IIPS and ICF (2017).

The regional variations in different types of vulnerabilities indicate that income vulnerability is the highest in the east region with 72.3%, followed by the central region with 57.7%, whereas the poverty level is least in the southern region with 20% of women belonging to the poor category. Educational vulnerability is lower in the southern region followed by the western region, and socially disadvantaged groups are higher in the northern region followed by the east region as compared to the other three regions (Table 1). The state-wise variations in all three types of vulnerability can be seen in Table 2. For example, in the low-education category, the value ranges from 0.8% in Kerala (south) to 63.8% in Bihar (north), and similarly, in the poor category, it ranges from 1.9% in Kerala to 81% in Bihar. The percentage share of SC/STs women is high in Orissa (50.7%). This shows the highest and lowest values in all the three major categories of vulnerability. Women belonged to these regions or states have different set of vulnerabilities, this can be seen in the Table 2.

Table 2.

Proportion of Ever-married Women (age group of 15–49) with Different Types of Vulnerabilities in India and Major States, 2015–2016.

India and Its States	Category of Vulnerabilities
India and Its States	Education	SCs/STs	Poor
Haryana	27.04	30.53	11.64
HP	6.15	31.37	11.67
J&K	35.9	45.18	34.36
Punjab	17.68	42.91	4.89
Rajasthan	47.73	36.48	45.59
Uttarakhand	26.25	28.39	24.99
Chhattisgarh	32.3	48.05	58.42
MP	40.66	42.31	59.2
UP	47.24	26.9	57.09
Assam	36.77	29.36	70.16
Bihar	63.8	26.07	81.03
Jharkhand	46.31	41.51	73.27
Orissa	37.44	50.77	65.82
WB	32.12	41.86	59.62
Gujarat	31.6	29.38	30.88
Maharashtra	16.6	33.09	28.3
AP	26.12	28.13	21.87
Karnataka	21.7	35.51	26.86
Kerala	0.8	11.64	1.94
TN	7.57	32.59	18.03
Telangana	24.1	26.85	23.37
Total	36.24	33.23	47.32

Source: NFHS-4 (The authors).

Note: HP (Himachal Pradesh), J&K (Jammu and Kashmir), MP (Madhya Pradesh), UP (Uttar Pradesh), WB (West Bengal), AP (Andhra Pradesh), TN (Tamil Nadu). Bold values shows the highest and lowest values in all the three major categories of vulnerability.

The study finds state-wise variations in different dimensions of vulnerabilities, which are none, one, two and three (Table 3). Overall, 34% of women in India do not face any type of vulnerability while seeking maternal and child health care services, whereas 12.4% of women face all three categories of vulnerabilities. The proportions of women with any one or two vulnerabilities are 27.5% and 26%, respectively.

Similarly, regional variations in levels of vulnerability show that multiple vulnerabilities are higher in the eastern region and central region, followed by the northern region than in the southern and western regions (Table 3). State-wise variations also show that states such as Orissa, Jharkhand, MP, Bihar, Chhattisgarh, Rajasthan and UP are the highest in all three dimensions of vulnerabilities, which is much more than the national average (12.4), whereas states such as Kerala, Punjab, HP, TN, AP, Haryana and Uttarakhand are the lowest in that category of vulnerability. However, inter-state variations can be seen at all levels of vulnerability. The proportion of women who are not deprived in any category ranges from 13% in Bihar to 87% in Kerala (Table 3). Huge variations can be seen across states in India in other dimensions of vulnerabilities.

Table 3.

Percentage Distribution of Ever-married Women by Dimension of Vulnerabilities in India’ Regions and its Major States, NFHS-4, 2015–2016.

India’ Regions	India and Major States	Dimensions of Vulnerability
India’ Regions	India and Major States	None	One	Two	Three
North region	Haryana	51.54	30.29	15.55	2.63
	HP	60.57	30.88	7.24	1.31
	J&K	31.44	31.23	22.97	14.37
	Punjab	50.53	36	10.9	2.57
	Rajasthan	31.02	25.41	26.24	17.33
	Uttarakhand	45.73	33.31	16.51	4.46
	North total	40.22	28.84	20.32	10.62
Central region	Chhattisgarh	26.76	25.76	29.37	18.11
	MP	25.89	26.38	26.93	20.8
	UP	26.57	28.07	32.97	12.39
	Central total	26.42	27.44	31.14	15
Eastern region	Assam	22.28	33.54	36.05	8.14
	Bihar	13.25	21.28	46.75	18.72
	Jharkhand	18.13	26.23	31.99	23.65
	Orissa	23.13	25.29	25.53	26.05
	WB	24.93	31.17	28.67	15.23
	East total	18.1	25.35	37.85	18.71
Western region	Gujarat	44.23	28.45	18.22	9.11
	Maharashtra	48.58	30.86	14.26	6.3
	West total	47.09	30.04	15.61	7.26
Southern region	AP	50.97	26.87	17.24	4.92
	Karnataka	45.31	30.12	17.55	7.02
	Kerala	87.4	10.92	1.41	0.27
	TN	56.02	31.3	11.06	1.62
	Telangana	53.14	25.42	15.09	6.36
	South total	55.12	27.29	13.49	4.1
	India/All total	34.0	27.54	26.17	12.39

Source: NFHS-4, 2015–2016 (The authors).

Table 3 presents the different dimensions of vulnerabilities in India and its regions. Overall, 65.6% of ever-married women reported being deprived in any of them (either education or wealth or caste), 15% of women deprived of education and wealth, 23% wealth and caste, 25.3% education and caste and 12.4% in all three dimensions; 34% of women are not deprived in any dimensions at the country level. Regional level variations show that women with any of (them) vulnerability are found higher to be in the eastern region with 81%, followed by the central region 73.5% and the least in the southern region with 44%. Similarly, the vulnerabilities that are concerned as education and wealth, wealth and caste and education and caste were also least in the southern region. Overall, the data show that there are huge variations in vulnerability levels across different regions in India (Table 4).

Table 4.

Percentage of Ever-married Women by Dimensions of Vulnerability in India and Its Regions, 2015–2016.

Categories of Vulnerability	India	Its Region
	Total	North	Central	East	West	South
	n = 259627	n = 30959	n = 70378	n = 72707	n = 32722	n = 46514
Any of them	65.64	59.22	73.49	81.02	52.36	43.97
Education and wealth	14.94	9.57	19.33	25.21	5.62	4.11
Wealth and caste	22.93	14.15	29.18	34.27	13.1	10.17
Education and caste	25.27	19.63	30.95	35.27	15.28	13.02
All three	12.39	10.62	15	18.71	7.26	4.1
None	34.3	40.78	26.51	18.98	47.64	56.03

Source: NFHS-4, 2015–2016 (The authors).

The correlation coefficients of dimensional deprivations were weak and found to be 0.11 for education and wealth, 0.34 for education and caste and 0.17 for wealth and caste, which indicates that these dimensions are unlikely to overlap.

Table 5.

Utilisation of Maternal and Childcare Services Among Ever-married Women Who Had at Least One Live Birth in the 5 Years Preceding the Survey by Dimensions of Vulnerability.

Type of Maternal Care	Dimensions of Deprivation
	None	One			Two			Three
		Education	Caste	Wealth	Education Wealth	Education Caste	Wealth Caste	Education Wealth, Caste
ANC visits	n = 70,617	n = 64,134	n = 59,816	n = 84,986	n = 25,774	n = 45,045	n = 40,650	n = 21,029
No ANC	7.96	30.48	19.27	27.46	37.23	28.24	29.66	32.81
One visit	3.95	7.44	5.79	7.34	8.63	7.51	7.76	7.09
2–3 visits	19.99	30.69	27.22	31	31.23	30.54	30.94	30.92
4 or more visits	68.09	31.4	47.72	34.2	22.91	33.72	31.64	29.19
Place of delivery	n = 89,189	n = 93,974	n = 82,935	n = 122,765	n = 38,749	n = 65,545	n = 59,501	n = 30,886
At home	6.93	36.69	24.73	32.85	40.66	32.97	34.12	40.14
At public	45.1	50.41	58.63	55.77	48.47	55.1	54.83	52.54
At private	47.78	12.63	16.37	11.08	10.58	11.64	10.75	7.03
Postnatal care	n = 70,602	n = 64,055	n = 59,766	n = 84,925	n = 25,756	n = 45,019	n = 40,632	n = 20,994
Yes	80.47	57.45	68.09	59.14	52.16	59.14	57.83	55.82
No	19.53	42.55	31.91	40.86	47.84	40.86	42.17	44.18
Full immunisation	n = 86,559	n = 88,363	n = 78,787	n = 115,639	n = 36,326	n = 61,731	n = 55,939	29,044.00
Full immunisation	56.7	44.36	50.3	46.33	42.4	45.9	45.3	43.8
Institutional delivery	n = 86,559	n = 88,363	n = 78,787	n = 115,639	n = 36,326	n = 61,731	n = 55,939	29,044.00
Institutional delivery	93	63.4	75.4	67.2	59.2	67	65.8	59.9

Source: NFHS-4, 2015–2016 (The authors).

Results represent the utilisation of maternal and childcare services among all ever-married women who gave at least one live birth in the 5 years preceding the survey across multiple dimensions of vulnerability. The table clearly shows that women who had multiple vulnerabilities were less likely to receive various MCH services. Overall, data show that four and more ANC coverage in India is very low and as low as 68% for those women with no deprivation, as compared to 31%–47% of those deprived of any one dimension, 22%–31% of those deprived in two dimensions and 29% of those deprived in all three dimensions. Similarly, the proportion of women with no antenatal care was also seen across all dimensions (Table 5).

The level of receiving institutional delivery is similar to that of four or more ANC service utilisation. Of live births that occurred to ever-married women in the previous 5 years, the proportion of deliveries that happened in the health facilities is 92% among those women who do not face vulnerability in any of the three dimensions, compared with 59% among those women who are vulnerable in all three dimensions. Further, with an increase in dimensions of vulnerability, the institutional delivery proportion decreases. Among women deprived in one dimension, the proportion of births taking place in health facilities is lowest for those deprived in education (62.5%), followed by those deprived in wealth (66.4%) and those deprived in caste (74.4%). Among women deprived in two dimensions, the proportion of births taking place in health facilities is lowest among those deprived in education and wealth (59%), followed by those deprived in education and caste (66.2%) and those deprived in wealth and caste (64.7%), and further, similar patterns can be seen in the public and private institutional delivery separately.

The pattern of utilisation for postnatal care (PNC) is similar to that of the other two indicators. The proportion of women who had received PNC is higher among those with no deprivations or vulnerabilities than among those with deprivation in all three dimensions (80.4% vs. 55.8%). Among those deprived in one dimension, the proportion receiving PNC is lower for those deprived in wealth than for those deprived in education or caste. Among those deprived in two dimensions, the proportion receiving PNC varied from 52% for those deprived in education and wealth, 59% for those deprived in education and caste and 53% for those deprived in wealth and caste (Table 5). In case of child immunisation aged 12–23 months, the proportion of children who got fully immunised is higher among those with no vulnerabilities than among those with all three vulnerabilities (56.7% vs. 43.8%).

Predicted probabilities for each of the four maternal and child health outcomes indicators have been estimated, adjusting for other social and demographic factors such as the age of the mother, place of residence, regions, religion, birth order and sex of the child. The predicted probability of full antenatal care for each level of vulnerability is lower than that of full immunisation, postnatal care (PNC) and institutional delivery. Women who have been deprived in all three dimensions are less likely than those who have not been deprived in any to have received four antenatal cares (predicted probability, 0.3 vs. 0.9), full immunisation (0.5 vs. 0.8), postnatal care (0.4 vs. 0.8) and institutional delivery (0.5 vs. 0.8). In addition, the probability of each outcome is lowest among those deprived in all three dimensions, followed by those deprived in education and wealth, education and caste, education only, caste and wealth, wealth only, caste only and in none. Overall, a single level of deprivation, like education, only appears to be stronger than the others, that is, caste only and wealth only. After adjusting for confounders, women deprived in education alone were less likely to use maternal and child health services such as four or more ANC, PNC, institutional delivery and full immunisation than those deprived of both wealth and caste (Figure 1).

Table 6.

Percentage of Ever married Women Who Received Four or More Antenatal Care Visits for Their Last Live Birth in the Previous 5 Years, Preceding the Survey, by Dimensions of Deprivation and the Ratio of Percentages, by Dimensions of Deprivation, According to Major States.

India and Its Major States	Dimensions of Vulnerability				Ratio of None to
India and Its Major States	None	One	Two	Three	One	Two	Three
Haryana	52.26	43.05	27.34	27.63	1.2	1.9	1.9
HP	74.14	65.31	43.26	19.34	1.1	1.7	3.8
J&K	85.46	69.96	54.86	46.63	1.2	1.6	1.8
Punjab	72.31	66.78	56.23	53.81	1.1	1.3	1.3
Rajasthan	51.48	40.99	27.26	24.52	1.3	1.9	2.1
Uttarakhand	39.89	26.56	14.37	7.25	1.5	2.8	5.5
Chhattisgarh	70.09	62.77	52.91	45.32	1.1	1.3	1.5
MP	53.44	36.24	26.41	20.35	1.5	2.0	2.6
UP	45.94	26.1	14.58	11.54	1.8	3.2	4.0
Assam	66.25	50.25	40.27	33.6	1.3	1.6	2.0
Bihar	34.94	18.46	8.94	6.44	1.9	3.9	5.4
Jharkhand	55	34.77	22.07	15.43	1.6	2.5	3.6
Orissa	69.14	64.18	59.47	53.44	1.1	1.2	1.3
WB	86.75	77.78	74.94	71	1.1	1.2	1.2
Gujarat	80.22	71.04	56.28	35.85	1.1	1.4	2.2
Maharashtra	76.82	70.54	66.75	50.81	1.1	1.2	1.5
AP	81.04	73.13	69.8	66.29	1.1	1.2	1.2
Karnataka	73.97	70.99	67.81	62.91	1.0	1.1	1.2
Kerala	90.17	92.31	79.49	79.82	1.0	1.1	1.1
TN	82.18	80.4	77.8	79.04	1.0	1.1	1.0
Telangana	78.65	77.31	61.33	65.15	1.0	1.3	1.2
Total	67.78	52.53	33.72	29.19	1.3	2.0	2.3

Source: NFHS-4, 2015–2016 (The authors).

Understating differences in women’s utilisation of four or more ANC services are explored across the states in India. The utilisation level and service coverage of ANC services vary among women across regions and states. Utilisation of maternal and child health care services also varied considerably by dimensions of vulnerabilities across regions and states, decreasing with increasing levels of deprivation/vulnerability.

To understand the inequality in a better way, the status of MCH care utilisation across different vulnerable groups, ratios have been calculated to compare the access and use of services among women who are not deprived in any dimension with those who are deprived in one, two and three dimensions; the closer the ratio is to 1.0, the lower the inequality is between the groups. For ANC, the ratio of women deprived in ‘none’ dimension to those deprived in one dimension was highest in Bihar (1.9), UP (1.8), Jharkhand (1.6) and MP (1.5); the lowest ratios were in Kerala, TN, Karnataka, Telangana and AP, WB, Gujarat and Maharashtra (1.0–1.1). And moreover, for two or three dimensions of vulnerabilities, the ratios were considerably higher in all states, ranging from 1.1 to 3.9 for two dimensions and 1.0–5.4 for three dimensions (Table 6). Similarly, the pattern was also observed for institutional delivery and postnatal care.

Table 7.

Institutional Delivery Received by Ever married Women in Recent Birth, Preceding the 5 Years, by Dimensions of Vulnerability and Ratio of Percentage, by the Percentage of Vulnerability in India and Its Major States.

India and Its Major States	Dimensions of Vulnerability				Ratio of None to
India and Its Major States	None	One	Two	Three	One	Two	Three
Haryana	89.18	77.22	61.43	63.65	1.2	1.5	1.4
HP	82.52	72.69	49.26	25.13	1.1	1.7	3.3
J&K	91.17	82.53	64.52	52.24	1.1	1.4	1.7
Punjab	94.57	88.97	80.44	73.58	1.1	1.2	1.3
Rajasthan	92.92	86.03	77.58	74.48	1.1	1.2	1.2
Uttarakhand	79.81	66.32	47.55	44.58	1.2	1.7	1.8
Chhattisgarh	84.81	74.25	64.78	51.73	1.1	1.3	1.6
MP	95.19	87.97	75.99	59.7	1.1	1.3	1.6
UP	82.86	69.87	58.71	55.48	1.2	1.4	1.5
Assam	91.68	79.05	62.69	63.07	1.2	1.5	1.5
Bihar	86.04	72.69	57.49	53.88	1.2	1.5	1.6
Jharkhand	87.04	71.95	55.39	40.35	1.2	1.6	2.2
Orissa	98.05	92.73	85.05	66.98	1.1	1.2	1.5
WB	91.29	78.15	65.17	69.6	1.2	1.4	1.3
Gujarat	96.38	89.21	79.41	66.87	1.1	1.2	1.4
Maharashtra	96.1	91.95	80.07	57.63	1.0	1.2	1.7
AP	96.43	90.72	84.79	68.94	1.1	1.1	1.4
Karnataka	97.46	95.28	87.47	84.01	1.0	1.1	1.2
Kerala	99.92	100	99.45	100	1.0	1.0	1.0
TN	99.27	98.82	98.61	92.33	1.0	1.0	1.1
Telangana	96.92	93.29	79.07	69.65	1.0	1.2	1.4
Total	92.78	82.36	66.74	59.57	1.1	1.4	1.6

Source: NFHS-4, 2015–2016 (The authors).

For institutional delivery (Table 7), the differences were observed across vulnerable groups that were similar to those in ANC. For postnatal care (Table 8), the state with low usage of ANC and institutional delivery also had low usage of PNC. Further, the differences between those deprived in multiple dimensions and those deprived in none are similar for ANC, institutional and PNC across states in India. And, when we grouped these states into a particular region, likewise, the eastern region falls into the highly deprived region with multiple dimensions, followed by the central and northern regions in India. The southern region faces less inequality in MCH services. Linking multiple deprivations/vulnerabilities, southern region suffers less compared to the other four regions.

Table 8.

Percentage of Postnatal Care Received by Ever married Women in the Recent Birth, Preceding the 5 Years, by Dimensions of Vulnerability and Ratio of Percentage, by the Percentage of Vulnerability in India and Its Major States.

India and Its Major States	Dimensions of Vulnerability				Ratio of None to
India and Its Major States	None	One	Two	Three	One	Two	Three
Haryana	78.01	73.02	61.08	65.08	1.1	1.3	1.2
HP	86.37	79.07	60.83	31.67	1.1	1.4	2.7
J&K	85.84	74.77	60.22	48.1	1.1	1.4	1.8
Punjab	93.03	89.97	84.52	85.93	1.0	1.1	1.1
Rajasthan	74.82	69.35	59.31	58.28	1.1	1.3	1.3
Uttarakhand	71.53	59.69	45.09	39.63	1.2	1.6	1.8
Chhattisgarh	81.66	76.79	73.36	62.01	1.1	1.1	1.3
MP	72.49	62.79	54.32	46.93	1.2	1.3	1.5
UP	75.1	64.12	53.26	49.71	1.2	1.4	1.5
Assam	81.39	73.54	63.8	63.81	1.1	1.3	1.3
Bihar	65.89	53.96	44.9	43.24	1.2	1.5	1.5
Jharkhand	70.13	58.39	48.19	39.22	1.2	1.5	1.8
Orissa	87.81	85.63	84.15	81.32	1.0	1.0	1.1
WB	80.7	71.93	66.95	72.19	1.1	1.2	1.1
Gujarat	72.74	73.55	69.1	61.91	1.0	1.1	1.2
Maharashtra	86.46	82.2	75.86	66.93	1.1	1.1	1.3
AP	87.01	88.02	83	80.41	1.0	1.0	1.1
Karnataka	72.69	70.36	59.81	57.3	1.0	1.2	1.3
Kerala	92.81	94.4	97.17	93.38	1.0	1.0	1.0
TN	89.92	89.65	86.67	84.9	1.0	1.0	1.1
Telangana	89.85	87.96	81.59	80.65	1.0	1.1	1.1
Total	80.6	72.22	59.14	55.82	1.1	1.4	1.4

Source: NFHS-4, 2015–2016 (The authors).

Table 9.

Percentage of Children Aged 12–23 Months Fully Immunised Before the Survey, Preceding the 5 Years, by Dimensions of Vulnerability and Ratio of Percentage, by the Percentage of Vulnerability in India and Its Major States.

India and Its Major States	Dimensions of Vulnerabilities				Ratio of None to
India and Its Major States	None	One	Two	Three	One	Two	Three
Haryana	71.37	56.2	48.25	59.47	1.3	1.5	1.2
HP	68.97	73.22	77.73	80.26	0.9	0.9	0.9
J&K	78.29	70.08	61.85	52.55	1.1	1.3	1.5
Punjab	92.71	85.91	86.51	84.78	1.1	1.1	1.1
Rajasthan	66.23	55.59	47.79	44.42	1.2	1.4	1.5
Uttarakhand	63.19	55.54	51.3	43.09	1.1	1.2	1.5
Chhattisgarh	87.03	80.28	69.87	65.13	1.1	1.2	1.3
MP	68.01	55.07	49.11	37.68	1.2	1.4	1.8
UP	60.75	54.39	44.47	40.81	1.1	1.4	1.5
Assam	63.12	51.69	43.27	41.85	1.2	1.5	1.5
Bihar	71.72	67.6	58.16	57.8	1.1	1.2	1.2
Jharkhand	68.92	66.57	60.65	54.38	1.0	1.1	1.3
Orissa	82.51	84	77.11	71.91	1.0	1.1	1.1
WB	86.61	80.33	87.54	86.48	1.1	1.0	1.0
Gujarat	54.18	53.98	41.81	37.9	1.0	1.3	1.4
Maharashtra	60.3	56.55	54.65	38.74	1.1	1.1	1.6
AP	69.01	65.48	59.7	64.07	1.1	1.2	1.1
Karnataka	63.16	62.38	56.53	58.54	1.0	1.1	1.1
Kerala	82.69	85.66	71.35	53.06	1.0	1.2	1.6
TN	70.61	70.88	68.19	58.67	1.0	1.0	1.2
Telangana	69.61	72.31	65.79	59.84	1.0	1.1	1.2
India	68.45	63.53	56.34	53.17	1.1	1.2	1.3

Source: NFHS-4, 2015–2016 (The authors).

Likewise, in case of child full immunisation, the ratios of children aged 12–23 months who were deprived in no dimension to those deprived in one are the highest, and they substantially increased at higher levels of dimensions like two and three dimensions (Table 9). State-wise variations are highly prevalent in child immunisation. It follows a similar pattern to institutional delivery in PNC and ANC, and also, the ratios of no deprivation to one, two and three dimensions of deprivation are similar.

Table 10.

Among Ever-married Women Who Had at Least One Live Birth in the Previous 5 Years, Predicted Probability of Having Received Four Antenatal Care Visits, Postnatal Care and Institutional Delivery and Among Children Aged 12–23 Months Who Received Full Immunisation Before the Survey, Predicted Probability by Dimensions of Deprivation (state).

India and Major States	Antenatal Care				Institutional Delivery
India and Major States	None	One	Two	Three	None	One	Two	Three
India	0.68	0.53	0.34	0.30	0.93	0.82	0.67	0.60
Haryana	0.48	0.39	0.27	0.18	0.90	0.79	0.63	0.52
HP	0.48	0.42	0.25	0.19	0.89	0.83	0.66	0.54
J&K	0.49	0.42	0.27	0.21	0.90	0.80	0.63	0.54
Punjab	0.51	0.45	0.35	0.20	0.90	0.84	0.71	0.54
Rajasthan	0.48	0.34	0.22	0.18	0.89	0.76	0.60	0.52
Uttarakhand	0.49	0.36	0.23	0.17	0.90	0.77	0.61	0.51
Chhattisgarh	0.58	0.44	0.33	0.25	0.91	0.81	0.70	0.58
MP	0.58	0.42	0.30	0.24	0.91	0.79	0.67	0.57
UP	0.56	0.39	0.23	0.22	0.91	0.76	0.60	0.54
Assam	0.67	0.50	0.34	0.33	0.93	0.82	0.68	0.63
Bihar	0.64	0.45	0.28	0.31	0.92	0.79	0.63	0.61
Jharkhand	0.66	0.48	0.36	0.35	0.92	0.81	0.66	0.55
Orissa	0.67	0.52	0.42	0.33	0.93	0.84	0.75	0.63
WB	0.68	0.53	0.41	0.35	0.92	0.82	0.71	0.66
Gujarat	0.75	0.62	0.47	0.40	0.94	0.85	0.75	0.66
Maharashtra	0.74	0.65	0.51	0.42	0.94	0.88	0.78	0.67
AP	0.80	0.72	0.59	0.52	0.95	0.89	0.80	0.73
Karnataka	0.81	0.73	0.61	0.52	0.95	0.89	0.81	0.72
Kerala	0.81	0.80	0.67	0.54	0.95	0.93	0.85	0.74
TN	0.82	0.75	0.65	0.54	0.95	0.91	0.84	0.74
Telangana	0.81	0.72	0.58	0.52	0.95	0.89	0.79	0.73
India	0.81	0.72	0.59	0.56	0.56	0.51	0.45	0.43
Haryana	0.76	0.70	0.58	0.50	0.54	0.50	0.45	0.41
HP	0.76	0.73	0.58	0.52	0.57	0.55	0.46	0.41
J&K	0.76	0.71	0.58	0.53	0.57	0.53	0.46	0.43
Punjab	0.77	0.74	0.65	0.52	0.57	0.55	0.50	0.42
Rajasthan	0.75	0.67	0.54	0.50	0.54	0.48	0.43	0.41
Uttarakhand	0.76	0.67	0.55	0.50	0.55	0.49	0.44	0.40
Chhattisgarh	0.78	0.70	0.61	0.55	0.55	0.51	0.47	0.43
MP	0.78	0.68	0.59	0.54	0.55	0.50	0.45	0.41
UP	0.78	0.67	0.54	0.52	0.55	0.48	0.43	0.41
Assam	0.81	0.71	0.60	0.59	0.58	0.53	0.45	0.45
Bihar	0.80	0.68	0.56	0.57	0.54	0.49	0.42	0.43
Jharkhand	0.80	0.69	0.60	0.58	0.54	0.50	0.46	0.45
Orissa	0.81	0.72	0.65	0.58	0.57	0.54	0.49	0.44
WB	0.81	0.72	0.63	0.60	0.56	0.52	0.46	0.43
Gujarat	0.82	0.76	0.66	0.61	0.57	0.52	0.47	0.44
Maharashtra	0.82	0.77	0.68	0.62	0.56	0.53	0.48	0.43
AP	0.84	0.79	0.71	0.66	0.56	0.53	0.49	0.45
Karnataka	0.84	0.80	0.71	0.65	0.57	0.54	0.49	0.46
Kerala	0.85	0.84	0.75	0.67	0.59	0.61	0.55	0.47
TN	0.84	0.81	0.73	0.66	0.58	0.56	0.52	0.47
Telangana	0.84	0.79	0.70	0.66	0.56	0.53	0.49	0.45

Source: NFHS-4, 2015–2016 (The authors).

Notes: Adjusted for the age of mother, place of residence, India regions, religion and birth order, parity, sex of child.

A set of binary logistic regressions examining the association between the level of vulnerability and utilisation of maternal and child health care services while controlling for social-economic and demographic covariates are conducted for India and its major states. Results are shown as adjusted predicted probabilities at the mean of all other independent variables. In general, the multivariate analysis supports the bivariate analysis. It showed that the probability of using each of the maternal and child health care services decreased with an increasing level of vulnerability. For example, the states come under the northern, central and eastern regions; the probability of receiving four ANC is lesser than the southern and western regions. States such as UP, Bihar, MP, Jharkhand, Rajasthan, J&K and Uttarakhand, the difference between dimensions are huge, when the probability of receiving ANC, institutional delivery, PNC and child immunisation among those who have not been deprived in any dimension and those who have been deprived in all three dimensions are huge (Table 10).

Discussion

Overall, the study brings out an interesting dimension to understanding the linkages between multiple vulnerabilities and utilisation of MCH services in India and its regions and moreover across major states. Although there have been improvements in the utilisation of different MCH services (Paul et al., 2019), there are inequalities in several of those utilisation indicators while accessing the services within and across regions and states. The study found huge disparities across regions and states in terms of MCH service coverage and supported earlier studies that raised the question of multiple deprivations, which made them more vulnerable to healthcare access (Balarajan et al., 2011; Mohanti, 2012; Pathak et al., 2010). Further, women with multiple vulnerabilities were less likely to have access to essential maternal and child healthcare than those women who were not vulnerable in any of them (none).

The use of maternal and childcare services—at least four ANC, institutional delivery, PNC and full immunisation—varies significantly among women by the level of deprivation/vulnerability in India and across states. While comparing India’s regions, which showed that women belonging to the eastern region followed by the central region face multiple vulnerabilities in utilising MCH services than the southern, western and northern regions. In fact, in all the regions, women who fall into multiple vulnerabilities/deprivations receive very few services irrespective of regions or states that is developed or underdeveloped.

The major determinants, that are, education, income and social identity that have a significant influence in the use of MCH services. However, in the earlier studies that have looked into the matter separately, and it is analysed with MCH outcome indicators (Acharya, 2010; Mohanty & Pathak, 2009; Raghupathy, 1996; Renkert & Nutbeam, 2001; Saroha et al., 2008). This is a unique study that analysed all three major women’s social determinants of health together and saw their combined effects on utilising MCH services.

Overall, the utilisation of MCH services declines with increasing levels of deprivation. The educational vulnerability appears to be stronger than other types of vulnerabilities like caste and wealth in utilisation of MCH services. An economic factor that influences women in accessing and utilising health care services stands at the second position after the education factor. As caste identity in India plays a significant role in defining the health status of women, it affects them less than the other two strong factors. The utilisation of maternal and child services also varies across regions, states and among socioeconomic groups in the country. Women from the eastern region (Assam, Bihar, Jharkhand, Orissa and West Bengal) appear to have a low level of MCH service utilisation followed, by the central region (Uttar Pradesh, Madhya Pradesh and Chhattisgarh), and in all the regions there exist inequality in service utilisation.

After the launch of NRHM (National Rural Health Mission) in 2005, the low-performing states, especially central and eastern region states, have improved substantially in the coverage of MCH services (Paul et al., 2019). However, the inequality remained the same across different vulnerability groups and regions. This study has proven that, still, socio-economic and demographic factors play a significant role in people not accessing universal MCH services. Due to it, many policies and programmes set out by the government are unable to reach their targets (Paul et al., 2019; Sahoo et al., 2015). Therefore, governments must improve both demand- and supply-side determinants rather than only strengthening the supply side. Even though, the supply-side determinants still, in India, have strongly become the barriers and constrained the utilisation of services across states (Anand & Yusuf, 2011). Knowledge, awareness and behavioural practices among women are therefore needed to improve to overcome the demand-side constraint, which still prevails in rural and remote areas in India and its states (Unnikrishnan et al., 2020).

Conclusion

In general, the differences between those with multiple deprivations and those with none appear to be high in the regions where service coverage is already low and low in the regions where service coverage is high. Such differences may arise from differences in availability, accessibility and quality of care in public health centres. Urgent actions are required to address inequities in MCH services as well as access to general healthcare, which should be comprehensive and based on multi-sectoral approaches. Women’s education may lead to better knowledge, awareness and health practices in the community, which need to be universal. For those women who face multiple vulnerabilities, the government must develop a targeted approach to protect them from health vulnerabilities and enhance their well-being.

Footnotes

Acknowledgements

The authors would like to acknowledge to Prof P. M. Kulkarni and Ms. B. P. Vani for their valuable comments to improve the manuscript.

Author’s Contribution

The concept was drafted by PSM and TSS; PSM and TSS contributed to the analysis design; solely PSM has done the data analysis. PSM and TSS advised on the article and assisted in its conceptualisation; PSM and TSS contributed to the comprehensive writing of the article. All authors read and approved the final manuscript.

Availability of Data and Materials

The study utilises secondary sources of data that is freely available in the public domain through http://iipsindia.org

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Ethical Approval and Consent to Participate

The data used in the study is in the public domain, and it has gone through the scientific and administrative supervision of the International Institute for Population Sciences (IIPS), Mumbai, India. The IIPS is the nodal agency that conducted the NFHS survey, and it is gone an independent ethical review of the NFHS protocols. The IIPS is under the supervision of the Ministry of Health and Family Welfare (MoHFW), Government of India.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

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Multiple Vulnerabilities in Access to and Utilising of Maternal and Child Health Services in India: A Spatial–Regional Analysis

Abstract

Introduction

Materials and Methods

Results

Conclusion

Keywords

Introduction

Multiple Vulnerabilities: Issues and Concerns

Materials and Methods

Vulnerability Measures

Dependent variables

Results

Dimensions of Vulnerabilities in India and Its Regions

Proportion of Ever-married Women (age group of 15–49) with Different Types of Vulnerabilities in India and Its Regions, 2015–2016.

Proportion of Ever-married Women (age group of 15–49) with Different Types of Vulnerabilities in India and Major States, 2015–2016.

Percentage Distribution of Ever-married Women by Dimension of Vulnerabilities in India’ Regions and its Major States, NFHS-4, 2015–2016.

Percentage of Ever-married Women by Dimensions of Vulnerability in India and Its Regions, 2015–2016.

Utilisation of Maternal and Childcare Services Among Ever-married Women Who Had at Least One Live Birth in the 5 Years Preceding the Survey by Dimensions of Vulnerability.

Percentage of Ever married Women Who Received Four or More Antenatal Care Visits for Their Last Live Birth in the Previous 5 Years, Preceding the Survey, by Dimensions of Deprivation and the Ratio of Percentages, by Dimensions of Deprivation, According to Major States.

Institutional Delivery Received by Ever married Women in Recent Birth, Preceding the 5 Years, by Dimensions of Vulnerability and Ratio of Percentage, by the Percentage of Vulnerability in India and Its Major States.

Percentage of Postnatal Care Received by Ever married Women in the Recent Birth, Preceding the 5 Years, by Dimensions of Vulnerability and Ratio of Percentage, by the Percentage of Vulnerability in India and Its Major States.

Percentage of Children Aged 12–23 Months Fully Immunised Before the Survey, Preceding the 5 Years, by Dimensions of Vulnerability and Ratio of Percentage, by the Percentage of Vulnerability in India and Its Major States.

Discussion

Conclusion

Footnotes

Acknowledgements

Author’s Contribution

Availability of Data and Materials

Declaration of Conflicting Interests

Ethical Approval and Consent to Participate

Funding

References