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 Table of Contents  
ORIGINAL RESEARCH
Year : 2015  |  Volume : 4  |  Issue : 1  |  Page : 54-61

Inequality in maternal health-care services and safe delivery in eastern India


Food and Supplies Department, Government of West Bengal, West Bengal, India

Date of Web Publication19-May-2017

Correspondence Address:
Arabinda Ghosh
IAS, S-10/4, Srabani Abasan, FC Block, Sector III, Salt Lake, Kolkata 700106, West Bengal
India
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DOI: 10.4103/2224-3151.206621

PMID: 28607275

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  Abstract 


Background: The target for Millennium Development Goal 5 (MDG-5) is to reduce the maternal mortality ratio by three quarters between 1990 and 2015. The United Nations 2014 report on MDG-5 concluded that little progress had been made in the South Asian countries, including India, which accounts for 17% of all maternal deaths globally. In resource-poor economies with widespread disparities even within the same country, it is very important to explore inequalities in safe delivery during childbirth by key socioeconomic factors in order to provide insights for future programming and policy actions.
Methods: Data from the Indian District Level Household and Facility Survey 3 were analysed to examine inequalities in safe delivery in eastern India. Univariate and multivariate logistic regression models were used.
Results: There were substantial inequalities in safe delivery by asset quintile, education of the woman and her husband, area of residence (rural or urban), religion and age at marriage (<18 years or ≥18 years); however, not all inequalities were the same. After adjusting for education levels of both parents, area of residence, religion and mother’s age at marriage, the odds of having a safe delivery were almost eightfold higher for those in the highest asset quintiles compared with those in the lowest quintiles. The odds for a safe pregnancy were three times higher for educated women compared with a base case of no education. The chances of having a safe delivery were twofold higher for women living in urban areas compared with those in rural areas (odds ratio 2.04, 95% confidence interval 1.91-2.17).
Conclusion: Addressing inequalities in maternal health should be viewed as a central policy goal together with the achievement of MDG-5 targets. In addition to following the indirect route of improving maternal health via poverty alleviation, direct interventions are needed urgently. Women’s education has a strong potential to improve access for poor pregnant women to safe delivery services and to reduce disparities in maternal health outcomes in resource-poor economies.

Keywords: India, inequality, maternal mortality ratio, Millennium Development Goal 5, safe delivery


How to cite this article:
Ghosh A. Inequality in maternal health-care services and safe delivery in eastern India. WHO South-East Asia J Public Health 2015;4:54-61

How to cite this URL:
Ghosh A. Inequality in maternal health-care services and safe delivery in eastern India. WHO South-East Asia J Public Health [serial online] 2015 [cited 2019 Jul 24];4:54-61. Available from: http://www.who-seajph.org/text.asp?2015/4/1/54/206621




  Introduction Top


Over half a million women die each year due to complications during pregnancy and childbirth. The majority of these deaths are preventable.[1] Maternal mortality – the death of women during pregnancy or childbirth, or in the 42 days after delivery, from any cause related to or aggravated by the pregnancy or its management but not from accidental or incidental causes - remains a major challenge to health systems worldwide.[2] In 1987, the United Nations Population Fund (UNFPA), the World Bank and the World Health Organization launched the Safe Motherhood Initiative to raise awareness about the number of women dying each year from complications of pregnancy and childbirth, and to challenge the world to reduce this mortality burden.[3] The 1994 International Conference on Population and Development strengthened international commitment to reproductive health. The importance of maternal survival was reinforced in 2000, when it was included as one of the eight Millennium Development Goals (MDGs).[4] The target for MDG-5 is to reduce the maternal mortality ratio (MMR) by three quarters between 1990 and 2015.[5] For India, the target is to achieve an MMR of 109 per 100 000 live births by 2015[6] versus the MMR of 178 recorded for 2010-2012.[7]

Despite these efforts, maternal mortality remains unacceptably high across much of the developing world. Globally it decreased by less than 1% per year between 1990 and 2005 – far below the 5.5% annual improvement needed to reach the MDG targets. During the 2009 World Health Assembly, Mr Ban Ki-moon, Secretary-General of the United Nations (UN), stated that, “Today, maternal mortality is the slowest moving target of all the Millennium Development Goals – and that is an outrage. Together, let us make maternal health the priority it must be. In the twenty-first century, no woman should have to give her life to give life”.[8]

Though admittedly some progress has been made in reducing maternal mortality since 1990, the rate of decline is far from adequate for achieving the goal. An estimated 289 000 maternal deaths occurred in 2013, giving a global MMR of 210 maternal deaths per 100 000 live births.[9] Many of these deaths could have been prevented if the women had been attended by skilled health personnel during pregnancy and childbirth.[10]

Preventable maternal deaths indicate gross violation of the basic human right of survival and highlight the gross failure of the health services on almost all fronts, particularly in terms of choice of strategic interventions and their extent of coverage in the population.[11] The progress in maternal health has been uneven, inequitable and unsatisfactory.[12] The UN report card on MDG-5 concluded that little progress had been made in sub-Saharan Africa, where half of all maternal deaths take place. Sub-Saharan Africa had the highest MMR among developing regions, with 510 deaths per 100 000 live births, followed by South Asia. Almost one third of all global maternal deaths are concentrated in two populous countries: India, with an estimated 50 000 maternal deaths (17%), and Nigeria, with an estimated 40 000 maternal deaths (14%).[13]

Inequalities in the use and coverage of skilled maternity care persist within poor countries alongside maternal health outcomes. Overall, women from the wealthiest income or most educated groups are much more likely than the poorest or least educated women to use skilled care during pregnancy, delivery and the postpartum period.[14],[15],[16],[17],[18]

A reasonable number of inequalities in health determinants are due to the failure of publicly financed health care reaching the poor in almost all developing countries.[19] Disparity in income is perhaps the most important factor leading to inequality in health.[20] Education in general and female literacy in particular may play an important role in accessing maternal health-care services. Equality in maternal health outcomes and access to maternal health interventions have been on top of the equity agenda, as maternal health is an important component of the MDGs.[21]

In India, the MMR declined from 301 per 100 000 live births in 2001–2003, to 178 in 2010–2012.The MMR ranged from 328 in Assam to 66 in Kerala during 2010-2012.[7] Keeping in view the overall pace of decline in the MMR, it seems unlikely that India will achieve MDG-5 by reducing the MMR level to 109 by 2015. India is among the 51 nations with slow progress in maternal and child care.[11]

Safe delivery is defined as either institutional delivery or home delivery assisted by a skilled person, such as a doctor, nurse or a midwife with experience and proficiency in uncomplicated deliveries. The objective of this study is to explore inequalities in safe delivery by key socioeconomic factors in the eastern part of India to provide insights for future programming and policy actions.


  Methods Top


Indian District Level Household and Facility Survey 3

The current study uses data from Indian District Level Household and Facility Survey 3 (DLHS-3). The Ministry of Health and Family Welfare, Government of India, initiated District Level Household and Facility Surveys in 1997 to provide district-level estimates of health indicators to assist policy-makers and programme administrators in decentralized planning, monitoring and evaluation. The surveys were initiated in 1997 with a view to assessing the utilization of services provided by government health-care facilities and people’s perceptions of the quality of services. DLHS-3 is the third in the series of district surveys, preceded by DLHS-1 in 1998–1999 and DLHS-2 in 2002-2004. DLHS-3, like the two earlier rounds, is designed to provide estimates of important indicators of maternal and child health, family planning and other reproductive health services. This survey provides district-level estimates on maternal and child health, family planning and other reproductive health services to assist policy-makers and programme administrators in decentralized planning, monitoring and evaluation. DLHS-3 adopted a multistage stratified probability proportional to size sampling design. Fieldwork was conducted between December 2007 and December 2008, and information was gathered from 720 320 households from 34 states and union territories in India (excluding Nagaland). From these households, 643 944 ever-married women aged 15–49 years and 166 260 unmarried women aged 15–24 years were interviewed. Sampling weights for households, ever-married women and unmarried women were generated for each district. DLHS-3 combined household amenities, assets and durable goods to compute a wealth index at the national level and this was divided into five quintiles. Households were categorized from the poorest to the richest groups corresponding to the lowest to the highest quintiles at the national level.

Determinants of safe delivery in states of eastern India

The present study focuses on socioeconomic inequalities in safe delivery in eastern India, which comprises 11 states: Arunachal Pradesh, Assam, Bihar, Jharkhand, Manipur, Meghalaya, Mizoram, Orissa, Sikkim, Tripura and West Bengal; 25.9% of the Indian population live in these states. Information was gathered from 237 425 households in these states using DLHS-3, and 201 522 ever-married women aged 15–49 years were interviewed.

To look for determinants of safe delivery in these selected states of eastern India, a multivariate logistic regression model was used to calculate odds ratios (ORs), a measure of association between an outcome and an exposure variable. The independent variables in the regression models included asset quintile, education of the woman and her husband, area of residence (rural or urban), religion and age at marriage (<18 years or ≥18 years).

The household wealth status information provided by DLHS-3 was used as a socioeconomic indicator. Other variables used to measure inequality were area of residence (rural or urban), educational status of women and their husbands (none, 1–4 years, 5–9 years and ≥10 years of schooling), religion (Hindu, Muslim, Christian or other) and age at marriage (<18 years or ≥18 years).

The concentration index (Ci) is one of the commonly used measures of inequality in the field of economics. In recent years, it has become a fairly standard measurement tool in the health economics literature on equality and inequality in health and health care. It allows the measurement of health inequality while taking into consideration the distribution of the health variable across all categories of the health stratifier.[22]

Formally, the Ci in case of discrete social categories is defined as:

, where hi is the health sector variable, i\mZ_1 N r i=l μ is its mean, and ri = i/N is the fractional rank of individual i in the living standards distribution, with i = 1 for the poorest and i = N for the richest. For computation, a more convenient formula for the Ci defines it in terms of the covariance between the health variable and the fractional rank in the living standards distribution:

.

We used the concentration index, which varies between −1 and +1, to measure wealth-related and education-related inequality in safe delivery. A Ci of 0 indicates a lack of inequality while the more the index deviates from zero, the greater the magnitude of the inequality. A negative Ci indicates that a given favourable condition or practice (that is, safe delivery) is found more often among the economically poor or less educated, while a positive index suggests that a favourable condition or practice is found less often among the poorer than among the wealthier or educationally advanced social strata.[22],[23]


  Results Top


Sociodemographic characteristics

[Table 1] provides the descriptive statistics of sociodemographic characteristics of the respondents in percentages. Most of the households lived in rural areas (85.5%), and 64.8% of them were Hindu. Only about half of the households had electricity and/or sanitary latrines, while 57.9% of the households lived in a kachha house (short-lived structure made with inexpensive building materials), 24.5% had mobile phones and 46.6% of the respondents had never attended school, while the rate was 28.4% among their husbands.
Table 1: Sociodemographic characteristics of 201 522 ever-married women aged 15–49 years

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In our study area, only 39.6% of the respondents had a safe delivery against an all-India average of 52.7%. [Table 2] shows the inequalities in safe delivery in the eastern Indian states by area of residence, asset quintile, age at marriage, religion and education. The wealth inequality in safe delivery was widespread (Ci 0.28). Safe delivery was as low as 20.4% for the poorest respondents against 87.9% for the richest.
Table 2: Safe delivery in the states of eastern India by area of residence, asset quintile, age at marriage, religion and education in 2007–2008

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Regarding the relationship between safe delivery and level of education (Ci 0.25710), safe delivery was as low as 22.6% for women having no education, and as high as 76.9% for women who had had schooling for 10 years or more. With reference to the rural/urban inequality in safe delivery, safe delivery was 74.0% in urban areas and less than half of that in rural areas.

Religion was also a determining factor in these areas in ensuring safe delivery. The Hindu and Christian populations had a very similar level of safe delivery but the level for Muslim women was less than two thirds of this level.

Finally, age at marriage also played an important role in ensuring safe delivery in the states of eastern India. It was found that for mothers who were married when they were under 18 years, the safe delivery rate was as low as 30.2% compared with 49.1% for those married at 18 years and older.

Of women living in urban areas of eastern India who had had secondary education and were in the highest asset quintile, 94.6% had a safe delivery compared with 16.9% of rural, uneducated women in the lowest asset quintile.

Education and inequality in maternal health outcomes

Women in urban and rural areas who had attended school had greater access to safe delivery. For example, among urban women without any education and in the highest asset quintile, access to safe delivery was 63.1%. In contrast, for urban women with 10 years and more schooling, safe delivery was 94.6%. Similarly, among rural women without any education in the lowest asset quintile, access to safe delivery was 16.9%. On the other hand, for rural women with 10 years or more of schooling and in the lowest asset quintile, access to safe delivery was 39.8%.

Ci values presented in [Table 3] and [Figure 1] provide information on the degree of inequality. [Table 3] shows that Ci indicates significant inequality in favour of richer households for safe delivery. Mizoram had the lowest inequality (wealth) for safe delivery (Ci 0.18) and highest level of safe delivery (coverage 64.24%) among the states of eastern India. On the other hand, Jharkhand had highest level of inequality (Ci 0.36) and lowest level of safe delivery (coverage 24.93%). With respondents ranked by level of education, the inequality was relatively lower for safe delivery. Inequality in safe delivery was considerably lower by place of residence. It was found that higher coverage was associated with lower values of the Ci (r = -0.739; P <0.01).
Table 3: Equality results for safe delivery according to asset quintile, and respondent's education and place of residence

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Figure 1: Safe-delivery coverage and equality in states of eastern India

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[Table 4] provides the multivariate logistic regression results for the determinants of safe delivery in eastern India. The ORs in [Table 4] show the impact of an independent variable after adjusting for all other variables included in this model. It was found that wealth, education of mother, education of husband, area of residence, religion and age at marriage all played important roles in determining safe delivery in eastern India. Women belonging to the highest economic strata were more likely (OR 7.69, P <0.001) than those in the poorest category to deliver in an institution or at home assisted by a skilled person (assuming constant values for education, area of residence, religion and age at marriage). Women who had had an opportunity to attend primary education (1–4 years of schooling) were almost one and a half times more likely to have a safe delivery (OR 1.44, P <0.001) than those with no education. As compared with women with no education, those who had received a secondary education (5–9 years of schooling) were two times (OR 2.05, P <0.001) more likely to have a safe delivery. Finally, women who had had schooling for 10 years and more were three times (OR 3.24, P <0.001) more likely to have a safe delivery. It was further found that a woman’s own educational status was more important than that of her husband in ensuring a safe delivery. Although the father’s years of schooling also contributed to safe delivery, the ORs were lower than those for the mother at each level of schooling. Regarding religion, Muslim, Christian and women of other religions were less likely to have a safe delivery in comparison with Hindu women. The likelihood of a safe delivery for Muslim and Christian women was 48% (OR 0.52) and 43% (OR 0.57) less than for Hindu women, respectively. Age at marriage also played an important role in having a safe delivery. The likelihood of having a safe delivery increased by 27% (OR 1.27) among women who married at ≥18 years of age, compared with those who married at younger than 18 years of age.
Table 4: Determinants of safe delivery in eastern India

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  Discussion Top


In developing countries such as India, addressing inequalities in maternal health should be viewed as a central policy goal together with achievement of MDG-5 targets. The huge inequalities in maternity care underline the need for effective provision of services. Over the past decades, countries have introduced various strategies to increase the demand for and improve the availability, accessibility and affordability of professional delivery attendants.[24]

Although governments may claim that they provide services to ensure that the poor are reached, their health service subsidies tend to provide considerably greater benefits to the well-off. The situation in 21 countries (or areas within countries) was covered in a 2003 review (Argentina, Armenia, Bangladesh, Bulgaria, Colombia, Costa Rica, Côte d’Ivoire, Ecuador, Ghana, Guinea, Honduras, India, the state of Uttar Pradesh in India, Indonesia, rural Kenya, Madagascar, Nicaragua, South Africa, Sri Lanka, United Republic Tanzania and Viet Nam). The top 20% of the population obtained on average over 26% of the total financial subsidies provided through government health expenditure, compared with less than 16% in the lowest 20% of the population.[25] In India, the top 20% of the population obtained 32% of the financial subsidies against 10% for the lowest 20% of the population.[26]

There is a need to adopt strategies for economically underserved people to ensure equality in having a safe delivery. In the absence of a concerted effort to guarantee that health systems reach disadvantaged groups more effectively, such inequalities are likely to continue. Yet these inequalities need not be accepted as inevitable, for there are many promising measures that can be pursued, such as establishing goals for improved coverage among the poor, rather than in entire populations, and use of the goals to direct planning towards the needs of the disadvantaged.[25] There is a need to adopt strategies for poor people to establish equality in terms of access to, and use of, maternal health-care services. To safeguard the interest of poor people, direct interventions are needed. Many demand-side financing schemes have been proposed globally. Interventions recently tried include: improved means of identifying poor individuals (Colombia and Mexico), cash payments for use of services (Mexico), services provided by nongovernmental organizations working under contracts with carefully specified performance indicators (Cambodia), mass campaigns (Ghana and Zambia), and social marketing (United Republic of Tanzania). But the effectiveness of such interventions has not been adequately assessed in different contexts.[27]

Despite the increasing emphasis on institutional deliveries, the use of such services in general and among the poor in particular remains low. In addition to economic reasons, cultural and societal factors, and the availability of quality health services affect medical assistance at delivery in a country.[28] However, the Government of India has recently started an ambitious conditional cash transfer scheme: the Janani Suraksha Yojana (JSY), a 100% centrally sponsored scheme under the umbrella of the National Rural Health Mission, to promote institutional delivery, particularly among pregnant women above the age of 19 years belonging to below-poverty-line families, in both rural and urban areas.[29] A recent evaluation of the JSY suggests that the poorest and least educated women did not always have the highest odds of receiving JSY payments. However, findings emphasize the need for targeting poor women.[30]

Policy-makers in resource-poor economies prefer to give emphasis to poverty eradication rather than improving maternal health, and they follow the indirect route of improving maternal health via poverty alleviation. Although the findings of the present study show that asset quintiles exert a significant impact on safe delivery, changing the distribution of asset quintiles through poverty eradication methods would take time. In the present situation, emphasis on direct interventions is needed urgently.

It was found in this study that apart from wealth inequality, differences in the educational levels of parents, particularly those of the mothers, are crucial determinants for access to safe delivery. Though there is seemingly multicollinearity among some of the independent variables such as asset quintile and education, this study found that each individual variable affects safe delivery, even after adjusting for values of seemingly correlated exogenous variables.

Nothing can be changed about area of residence and religion. However, public interventions may target rural areas and religious minorities. Education has the advantage of improving the wealth/income position and warding off marriage at an early age, which are all factors that contribute to safe delivery and improved maternal health outcomes.

Empowering women through education should be one of the most fundamental strategies to promote health and reduce inequalities. The findings from this study indicate that education in general and women’s education in particular have a strong potential to improve access for poor pregnant women to safe delivery services that can reduce the disparities in maternal mortality outcomes in resource-poor economies.


  Acknowledgement Top


The author acknowledges the guidance provided by Dr Sajal Chattopadhyay, Economic Advisor, Centers for Disease Control and Prevention, Atlanta, Georgia, USA, in preparing this paper.

Source of Support: Nil.

Conflict of Interest: None declared.



 
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    Figures

  [Figure 1]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]


This article has been cited by
1 Inequalities in the utilization of maternal health care in the pre- and post-National Health Mission periods in India
Balhasan Ali,Preeti Dhillon,Sanjay K. Mohanty
Journal of Biosocial Science. 2019; : 1
[Pubmed] | [DOI]



 

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