Addressing Disparities in Maternal and Child Health Services:

A Focus on Uttar Pradesh, India

Parihar Anand Kumar Singh¹, Singh Moksha²

¹PhD Scholar, Humanities of Social Sciencce, National Institute of Technology, Raipur, India.

²Faculty, Humanities of Social Sciencce, National Institute of Technology, Raipur, India.

*Corresponding Author E-mail: msingh.eng@nitrr.ac.in

ABSTRACT:

Background: India faces a critical challenge in maternal and child health, having reported the highest maternal and child deaths globally in 2010 and 2009, respectively. Despite a 70% decline in maternal mortality from 1990 to 2015, India still accounts for 15% of global maternal deaths. This study focuses on Uttar Pradesh, India's most populous state, where under-five child mortality rates are alarming, particularly in rural areas. Despite governmental efforts, accessibility, availability, and affordability of maternal and child health services remain problematic. Data and Methods: This study utilizes publicly available multi-level data from the HMIS portal of the Ministry of Health and Family Welfare, focusing on Uttar Pradesh. The HMIS is a crucial tool for monitoring and implementing national health programs. Examining data from 2018 to 2020, the study assesses the spatial distribution of Maternal and Child Health (MCH) coverage at the district level using descriptive statistics. The findings contribute to understanding MCH service utilization in Uttar Pradesh. Result and Discussion: This research investigates maternal health service utilization across districts in Uttar Pradesh, India, analyzing key indicators from 2018 to 2020. The study reveals significant variations in early registration, antenatal care, vaccination, and delivery preferences. Positive changes, notably in Basti and Kanpur Dehat, contrast with negative trends in Meerut and Varanasi. The findings underscore the need for targeted interventions to address disparities and enhance maternal health outcomes in Uttar Pradesh. Conclusion: Maternal health service utilization is vital for community well-being. Despite increased awareness, persistent gaps exist due to barriers like inadequate infrastructure and cultural norms. Addressing these demands a multi-faceted approach, including policy reforms, education, and innovative technologies. Optimizing maternal health requires holistic efforts to bridge socio-economic gaps and build resilient communities.

KEYWORDS: Early registration, Delivery, District, MCH.

INTRODUCTION:

India reported the highest number of maternal (2010) and child (2009) deaths in the world suggesting a poor coverage in Maternal and Child Health care services (MCHS). Maternal and child mortality, a crisis essentially of the poor in the 21st century, and a neglected tragedy of developing countries reflects one of the shameful failures of human development. The gap in the risk of maternal deaths between developed and developing countries is considered the ‘‘greatest health divide in the world’. Notably, India showed an even greater decline, of 70% in maternal mortality, from 152,000 in 1990 to 45,000 in 2015. Regrettably, despite this significant decline, India still accounts for 15% of global maternal mortality and ranks second after Nigeria for the absolute number of maternal deaths¹. The persistence of preventable maternal and child deaths calls for better measures beyond the conventional coverage. 

Maternal and child health care (MCH) care is the health service provided to mothers (women in their childbearing age) and children. The targets for MCH are all women in their reproductive age groups, i.e., 15-49 years of age, children, school age population, and adolescents. Throughout the world, especially in the developing countries, there is an increasing concern and interest in maternal and child health care. This commitment towards MCH care gains further strength after the world summit for children, 1991, which gave serious be addressed in the provision of maternal and child health care services². Even after controlling the possible biophysical and geographical variables, the study reveals that the health program initiatives have a major role to play in reducing under-five mortality rate in the high focus states in India³.

Maternal and child health care refers to those activities whose primary purpose is to restore, improve and maintain the health of women and their newborn during pregnancy, childbirth, and the 7-day post-natal period. WHO guidance on the activities that should be included in MCH care includes the essential packages of intervention that address pregnancy, childbirth, postpartum care to mothers and care subject to wide geographic inequities, both at regional, national, and sub-national level⁴. Despite the national programs for improving maternal and child health in India, maternal mortality and morbidity continue to be high. One of the important reasons for this is under–utilization or non–utilization of the maternal health care services due to lack of awareness in the rural and slum population in India. The effects of bio-demographic and socioeconomic variables (maternal education, maternal age, birth order and place of residence) on infant and child mortality, district specific variation of infant and child mortality show a rural-urban distinction with the relatively lower risk of mortality in main urban areas⁵.

To reduce child mortality, the Government of India launched an ambitious National Rural Health Mission in April 2005, where the child health program comprehensively integrated interventions that improve child health and addresses factors contributing to infant and under-five mortality. The major component of child health program are establishment of new-born care facilities and facility-based integrated management of neonatal and childhood illnesses (F-IMNCI); Navjaat Shishu Shurakhsha Karyakaram; integrated management of neonatal and childhood illness (IMNCI) pre-service (IMNCI): home based care of new-born , universal immunization early detection and appropriate management of Acute Respiratory Infection (ARI), diarrhoea and other infection coupled with other supplementation and school health program. The South and north-eastern regions of India reported a higher coverage gap in maternal and child health care services. Also, a significant positive relationship between the coverage gap index and under-five mortality rate across states⁶. Additionally, north-south variation in child mortality in India has been reflected in literature where some of the north Indian states such as Rajasthan, Uttar-Pradesh, Bihar, Orissa, Chhattisgarh, and Madhya Pradesh persistently performed poorly in health care. On account of the unacceptability high fertility and mortality indicators, the eight Empowered Action Group (EAG) states (Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Orissa, Rajasthan, Uttarakhand, Uttar Pradesh and Assam) which account for about 48% of India’s population are designated as “High focus states” by the Government of India.

Uttar Pradesh (UP) is the most populous state in India, reporting the highest number of under-five (U5) child mortality rate i.e., 78 per 1000 live births. One factor contributing to the high U5MR is the high proportion of the population living in rural areas (77.7 %) which may limit access to child health services. In UP, the mortality rate among U5 children living rurally (82 per 1000 live births) is more than 30 % higher than those living in urban areas (62 per 1000 live births). According to the National Sample Survey 2014, the proportion of U5 children with a reported illness requiring treatment in the 15 days prior to the survey was 103 per 1000 U5 population in rural settings and 114 in urban settings⁷. Rural Uttar Pradesh reported higher mortality rates and lower identification of illnesses requiring treatment and lower hospitalization rates. This suggests different illness recognition and care-seeking patterns in rural areas that likely adversely affect the survival of young children⁸. Despite several policies and program provisioning, the accessibility, availability, and affordability of maternal and child health care services remain a challenge to the health care system of Uttar Pradesh.

Our country showed a positive steady decline in Maternal and Child mortality rates between 1990 and 2015 as stated by Millennium Development Goal (MDG)- IV and V. But it has not been achieved to an optimum level which is required for betterment for the country. So, the new agenda till 2030 is reduced maternal mortality by 70 per 100,000 live births, and end preventable deaths of newborns and children under 5 years of age, with all countries aiming to reduce neonatal mortality to at least as low as 12 per 1,000 live births and under-5 mortality to at least as low as 25 per 1,000 live births as maintained by Sustainable Development Goal (SDG-3). This calls for the need to conduct a study of the Health facility for Maternal and Child health care at district level for India. Novelty of this study is that the unit of analysis is districts which is a lower-level unit compared to the state/province. By doing so, we go below the state level averages that often mask the crux of the problem and thus we highlight the inter-district disparities in maternal and child health in India. However, enormous geographical differentials are present in maternal and child health care within state.

This study attempts at understanding the coverage of utilization of maternal health services at district level in Uttar Pradesh, India. Against this backdrop, this paper reviews the status of maternal and child health services coverage for different beneficiary groups of NRHM and NHM program. Based on Health Management Information System (HMIS) data, we examine the coverage across Uttar Pradesh during FY 2018-19 and 2019-20. It may be noted that no commonly available large-scale data provides information about the coverage of maternal health services across states and districts in India and across the beneficiary groups. The HMIS has successfully captured the data which is made available in the public domain.

DATA AND METHODS:

The study utilizes multi-level data publicly available at the HMIS portal (https://hmis.mohfw.gov.in/) of the Ministry of Health and Family Welfare for number of total target beneficiaries for different age groups. This portal is identified as a one-stop shop for program implementation, review and coverage statistics.

HMIS is a web-based Monitoring Information System of Ministry of Health & Family Welfare to monitor the National Health Mission and other National Health Programme and provide key inputs for policy formulation and appropriate programme interventions. HMIS is specially designed to assist health departments, at all levels, in managing and planning of health programmes. Five type of health facilities viz. Sub Centres (SCs), Primary Health Centres (PHCs), Community Health Centres (CHCs), Sub-District Hospitals (SDHs) and District Hospitals (DHs) report on HMIS. Medical Colleges are mapped at SDH and DH level in respective States/UTs. As of 2019-20, there were around 705 districts and around 2.08 lakh health facilities mapped and reporting on HMIS Portal.

This study extracted district level data of Uttar Pradesh on coverage of utilization of maternal health services. Based on the HMIS data of the study area from 2018 to 2020, the spatial distribution of the average MNC coverage change in the study area was obtained by using the difference method. Descriptive statistics were reported as numbers and percentage for district level coverage of utilization maternal and child health services.

RESULT AND DISCUSSION:

Maternal health remains a critical dimension of public health, serving as an essential indicator of the overall well-being of societies. In the diverse landscape of India, the state of Uttar Pradesh stands as a microcosm, encapsulating the complexities and challenges associated with maternal health services. The effective utilization of maternal health services is paramount for ensuring the well-being of both mothers and newborns, contributing to the reduction of maternal and neonatal mortality rates. However, significant variations in the utilization of these services across districts in Uttar Pradesh present a formidable challenge to achieving equitable healthcare outcomes.

Uttar Pradesh, with its vast and diverse population, is confronted with multifaceted health disparities, including variations in healthcare infrastructure, socio-economic conditions, and cultural practices. These variations have been shown to influence the utilization of maternal health services, thereby affecting the overall maternal health landscape of the state. Recognizing the significance of understanding these variations is imperative for designing targeted interventions, shaping effective policies, and ultimately improving maternal health outcomes.

This research seeks to delve into the intricacies of maternal health service utilization across districts in Uttar Pradesh. By examining key indicators such as early registration during the first trimester, receipt of antenatal care check-ups, tetanus toxoid vaccination coverage, iron and folic acid supplementation, and preferences for institutional delivery, we aim to uncover the extent of variations, identify contributing factors, and provide insights that can inform evidence-based strategies.

As we embark on this study, it is essential to underscore the potential impact of our findings. The implications extend beyond academic discourse, reaching into the realms of public health policy and the delivery of healthcare services. By elucidating the nuances of maternal health service utilization in Uttar Pradesh, this research aspires to contribute to the ongoing dialogue surrounding maternal health, fostering an environment where every woman, regardless of geographical location, can access and benefit from essential maternal health services.

In the subsequent sections, we will delve into the existing literature, outline the methodology employed in this study, and present our findings, with the ultimate goal of providing actionable insights that can inform interventions aimed at improving maternal health outcomes across districts in Uttar Pradesh.

The Table depicts the variation in change in coverage utilization of maternal services in districts of Uttar Pradesh between 2018-19 and 2019-20. The key indicators utilized in the study were early registration during the first trimester, receipt of antenatal care check-ups, tetanus toxoid vaccination coverage, iron and folic acid supplementation, and preferences for institutional delivery. The data shows the change in the prevalence of the number of women registered during the first trimester of pregnancy in different districts of Uttar Pradesh.

Table: Change in prevalence of utilization of maternal services in districts of Uttar Pradesh in between 2018-19 and 2019-20

SL. No	District	Change in prevalence of number of women registered during first trimester	Change in prevalence of number of women received all 4 ANC Check-up	Change in prevalence of number of Pregnant women received TT2+ TT Booster	Change in prevalence of number of Pregnant women given 180 IFA	Change in prevalence of number of Pregnant women went for institutional delivery
	_Uttar Pradesh	17.55	33.98	-1.62	-1.24	2.80
1	Agra	12.58	32.96	11.00	86.10	0.21
2	Aligarh	5.61	13.67	-3.11	-9.56	-0.89
3	Allahabad	4.20	42.07	-3.61	-3.27	5.02
4	Ambedkar Nagar	8.85	0.29	2.13	0.21	1.42
5	Auraiya	7.92	25.53	-8.24	-1.79	2.14
6	Azamgarh	29.49	47.44	-6.63	-26.49	1.22
7	Bagpat	6.87	50.58	-1.94	9.63	4.37
8	Bahraich	30.15	20.81	1.03	-8.58	7.91
9	Ballia	21.70	3.28	2.74	92.06	-0.84
10	Balrampur	35.14	29.14	3.54	17.70	15.28
11	Banda	-9.56	64.94	-2.94	-0.90	0.10
12	Barabanki	19.20	33.83	-0.12	-13.35	1.73
13	Bareilly	7.68	17.16	4.63	4.64	-6.14
14	Basti	63.59	114.57	24.39	163.74	1.38
15	Bijnor	11.61	21.19	4.33	18.52	-1.51
16	Budaun	22.96	65.04	0.42	79.36	0.26
17	Bulandshahar	-12.20	72.12	-26.73	-20.16	3.44
18	C S M Nagar	1.56	18.06	-3.22	0.42	0.41
19	Chandauli	3.58	19.51	-7.87	-16.97	8.11
20	Chitrakoot	28.35	39.88	-2.88	1.85	0.53
21	Deoria	-1.91	102.84	-5.17	38.84	-0.41
22	Etah	6.81	47.18	1.06	-41.09	11.93
23	Etawah	-15.45	-1.24	-5.18	-20.60	0.40
24	Faizabad	35.28	11.39	-10.61	-0.72	0.85
25	Farrukhabad	44.26	81.79	23.75	26.96	5.91
26	Fatehpur	40.45	30.90	6.52	7.74	0.00
27	Firozabad	26.82	9.07	12.09	16.31	2.94
28	Gautam Buddha Nagar	-2.94	13.76	0.24	0.00	0.94
29	Ghaziabad	13.83	78.92	-13.84	6.06	9.75
30	Ghazipur	16.20	24.56	2.96	3.59	6.34
31	Gonda	42.86	48.83	2.88	7.07	-1.32
32	Gorakhpur	-1.54	90.34	-6.09	-27.11	0.20
33	Hamirpur	-4.01	25.33	-4.38	-5.64	0.61
34	Hapur	23.23	29.10	2.50	37.77	8.04
35	Hardoi	11.80	37.08	-7.92	-2.34	1.27
36	Hathras	19.81	56.25	-0.21	-4.68	60.82
37	Jalaun	38.97	44.23	19.57	42.20	1.11
38	Jaunpur	29.49	30.46	-0.11	-2.77	9.83
39	Jhansi	7.01	26.42	-3.91	7.68	0.00
40	Jyotiba Phule Nagar	10.12	8.09	-11.56	-26.63	4.96
41	Kannauj	18.16	67.76	9.45	-11.11	-0.22
42	Kanpur Dehat	46.34	135.58	54.13	30.55	-0.96
43	Kanpur Nagar	8.86	30.24	4.73	-30.03	-1.24
44	Kashi Ram Nagar	61.44	59.03	17.79	72.90	4.53
45	Kaushambi	13.32	32.83	-5.37	12.48	1.38
46	Kushinagar	8.31	2.19	-17.40	-3.67	9.50
47	Lakhimpur Kheri	21.75	103.57	-0.98	18.77	-3.98
48	Lalitpur	16.92	7.16	-6.74	-5.05	1.14
49	Lucknow	7.17	23.90	-5.18	105.58	-0.20
50	Maharajganj	49.52	49.53	4.95	8.27	-2.80
51	Mahoba	25.85	14.30	27.70	-14.38	0.10
52	Mainpuri	9.18	40.73	-5.31	58.79	26.27
53	Mathura	19.44	29.28	-1.80	-71.10	11.50
54	Maunathbhanjan	-2.49	14.77	-6.80	48.52	2.27
55	Meerut	-43.82	-37.78	-36.16	-18.13	11.00
56	Mirzapur	45.09	46.26	-4.95	-19.33	0.89
57	Moradabad	6.61	33.76	-1.37	3.62	27.24
58	Muzaffarnagar	17.76	85.71	7.27	14.02	2.63
59	Pilibhit	20.16	25.79	12.09	2.36	1.41
60	Pratapgarh	124.93	62.11	5.76	7.69	2.60
61	Rae Bareli	9.06	16.73	-9.04	-7.49	0.73
62	Rampur	31.10	63.08	-2.48	31.48	20.62
63	Saharanpur	6.33	14.29	11.03	7.68	3.93
64	Sambhal	26.56	50.70	-0.15	11.98	3.37
65	Sant Kabir Nagar	22.54	44.77	-1.06	0.22	0.46
66	Sant Ravidas Nagar	20.04	32.72	-19.11	38.30	0.41
67	Shahjahanpur	11.13	17.20	-5.68	-22.48	-5.23
68	Shamli	6.75	29.43	0.91	-5.92	3.32
69	Shrawasti	31.35	30.40	4.14	-4.37	1.39
70	Siddharth Nagar	31.21	34.84	-4.10	-4.14	0.00
71	Sitapur	26.67	24.61	-9.95	-3.52	5.34
72	Sonbhadra	7.30	11.75	6.39	17.95	0.00
73	Sultanpur	16.45	57.78	31.02	147.70	0.41
74	Unnav	90.27	73.47	-2.28	-6.36	1.00
75	Varanasi	47.41	0.00	-1.39	-67.75	-0.51

Overall, there's a positive change of 17.55%, indicating an increase in the prevalence of women registered during the first trimester across the state. Some districts, such as Pratapgarh, Basti, and Unnav, show substantial positive changes, suggesting a significant increase in the number of women registered during the first trimester. In contrary, districts like Meerut and Gorakhpur show negative changes, indicating a decrease in the prevalence of women registered during the first trimester. The district of Banda has a notable negative change of -9.56%, suggesting a decrease in the number of women registered during the first trimester in that area.

The data further shows the change in the prevalence of the number of women who received all four ANC (Antenatal Care) check-ups in different districts of Uttar Pradesh between 2018-19 and 2019-20. The state as a whole shows a positive change of 33.98%, indicating an increase in the prevalence of women who received all four ANC check-ups. Among the districts Basti, Kanpur Dehat, and Ghaziabad show substantial positive changes, suggesting a significant increase in the prevalence of women receiving all four ANC check-ups. Other districts with positive changes include Pratapgarh, Meerut, and Unnav. On the other hand, districts, such as Varanasi, Etawah, and Kaushambi, show either no change or a decline in the prevalence of women receiving all four ANC check-ups. There is considerable variability across districts, with some showing significant improvements, while others exhibit declines or minimal changes. Within the districts, Basti stands out with a remarkable increase of 114.57%. Kanpur Dehat and Ghaziabad also show substantial positive changes, with 135.58% and 78.92%, respectively. Meerut has a notable negative change of -37.78%, indicating a significant decrease. Varanasi shows no change (0.00%), suggesting stagnation in the prevalence of women receiving all four ANC check-ups.

The data on change in the prevalence of pregnant women who received TT2+ TT Booster (Tetanus Toxoid vaccinations) in different districts of Uttar Pradesh shows a negative change of -1.62%, indicating a decrease in the prevalence of pregnant women who received TT2+ TT Booster between 2018-19 and 2019-20. Positive change was noted in districts like Basti, Kanpur Dehat, and Mainpuri, suggesting an increase in the prevalence of pregnant women receiving TT2+ TT Booster. Several districts show negative changes, indicating a decrease in the prevalence of pregnant women receiving TT2+ TT Booster. There is considerable variability across districts, with some showing improvements and others exhibiting declines in the prevalence of pregnant women receiving TT2+ TT Booster. Within the districts, Basti stands out with a significant increase of 24.39%. Kanpur Dehat and Mainpuri also show substantial positive changes, with 54.13% and -5.31%, respectively. In contrary, Meerut has a notable negative change of -36.16%, indicating a significant decrease. Ghaziabad and Bulandshahar also show substantial negative changes.

The data also shows the change in the prevalence of pregnant women who were given 180 IFA (Iron and Folic Acid supplementation) in different districts of Uttar Pradesh between 2018-19 and 2019-20. The state as a whole shows a negative change of -1.24%, indicating a decrease in the prevalence of pregnant women who were given 180 IFA. Few districts like Basti, Lucknow, and Sultanpur show substantial positive changes, suggesting an increase in the prevalence of pregnant women given 180 IFA. Other districts with positive changes include Gonda, Hapur, and Jalaun. Several districts show negative changes, indicating a decrease in the prevalence of pregnant women given 180 IFA. Notable negative changes are observed in districts like Varanasi, Mathura, and Meerut. There is considerable variability across districts, with some showing improvements and others exhibiting declines in the prevalence of pregnant women given 180 IFA. Across the districts, Basti stands out with a significant increase of 163.74%. Lucknow and Sultanpur also show substantial positive changes, with 105.58% and 147.70%, respectively. Whereas, Varanasi has a notable negative change of -67.75%, indicating a significant decrease followed by Mathura and Meerut.

The table further shows the change in the prevalence of pregnant women who went for institutional delivery in different districts of Uttar Pradesh. In Uttar Pradesh, a positive change of 2.80 increase was noted in the prevalence of pregnant women who opted for institutional delivery between 2018-19 and 2019-20. Districts like Hathras, Moradabad, and Mainpuri show substantial positive changes, suggesting an increase in the prevalence of pregnant women choosing institutional delivery. Some districts like like Shahjahanpur, Kanpur Nagar, and Varanasi shows negative changes, indicating a decrease in the prevalence of pregnant women opting for institutional delivery. There is considerable variability across districts, with some showing improvements and others exhibiting declines in the prevalence of pregnant women opting for institutional delivery. Among the districts, Hathras reported highest increase of 60.82% followed by Moradabad and Mainpuri also show substantial positive changes, with 27.24% and 26.27%, respectively. In contrary, Shahjahanpur has a notable negative change of -5.23%, indicating a significant decrease. Kanpur Nagar and Varanasi also show substantial negative changes.

CONCLUSION:

In conclusion, the utilization of maternal health services plays a pivotal role in ensuring the well-being of mothers and infants, contributing significantly to the overall health of communities. Through a comprehensive review of available data and research, several key observations have emerged.

Firstly, previous studies have proven that access to maternal health services is influenced by a complex interplay of factors, including socio-economic status, geographic location, education, and cultural beliefs. Understanding and addressing these determinants are crucial for designing targeted interventions that promote inclusivity and equitable access.

Increasing awareness and availability of maternal health services, there remain persistent gaps in utilization rates. Barriers such as inadequate infrastructure, limited healthcare workforce, and socio-cultural norms continue to impede optimal service uptake. Addressing these challenges requires a multi-faceted approach, involving policy reforms, community engagement, and infrastructure development.

Furthermore, the role of education and awareness campaigns cannot be overstated. Efforts to empower women with knowledge about the importance of antenatal care, skilled birth attendance, and postnatal services can contribute significantly to increased utilization. Collaborative initiatives involving healthcare providers, community leaders, and non-governmental organizations can amplify the impact of such awareness programs.

Innovative approaches, such as mobile health technologies and community-based health promotion, should be explored to reach remote and underserved populations. Additionally, integrating maternal health services into existing healthcare frameworks and ensuring continuity of care across the maternal health continuum are critical for sustained improvements.

In conclusion, optimizing maternal health service utilization demands a holistic and collaborative effort. By addressing socio-economic disparities, cultural nuances, and healthcare system challenges, societies can make significant strides toward achieving improved maternal and child health outcomes. As we move forward, it is imperative to prioritize maternal health within the broader context of public health, recognizing its foundational role in building healthier and more resilient communities.

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4. Ebener, S., et al., The geography of maternal and newborn health: the state of the art. International Journal of Health Geographics, 2015. 14(1): p. 19.

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Received on 03.10.2023        Modified on 30.10.2023

Accepted on 25.11.2023 © A&V Publication all right reserved

Int. J. Rev. and Res. Social Sci. 2023; 11(4):270-276.

DOI: 10.52711/2454-2687.2023.00046