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Article

Enablers and Barriers to the Utilization of Antenatal Care Services in India

by
Felix Akpojene Ogbo
1,2,*,
Mansi Vijaybhai Dhami
1,†,
Ebere Maureen Ude
1,†,
Praween Senanayake
1,†,
Uchechukwu L. Osuagwu
3,†,
Akorede O. Awosemo
2,
Pascal Ogeleka
4,
Blessing Jaka Akombi
5,
Osita Kingsley Ezeh
1,‡ and
Kingsley E. Agho
1,‡
1
Translational Health Research Institute (THRI), School of Medicine, Western Sydney University, Campbelltown Campus, Locked Bag 1797, Penrith 2571, Australia
2
General Practice Unit, Prescot Specialist Medical Centre, Welfare Quarters, Makurdi 972261, Nigeria
3
School of Medicine|Diabetes Obesity and Metabolism Translational Research Unit (DOMTRU), Macarthur Clinical School, Parkside Crescent, Campbelltown 2560, Australia
4
Obstetrics and Gynaecology Unit, City Hospital, Emmanuel Mande Close, Makurdi 972261, Nigeria
5
School of Public Health and Community Medicine, Faculty of Medicine, University of New South Wales, Sydney 2052, Australia
*
Author to whom correspondence should be addressed.
†
Joint second authors.
‡
Joint senior authors.
Int. J. Environ. Res. Public Health 2019, 16(17), 3152; https://doi.org/10.3390/ijerph16173152
Submission received: 6 August 2019 / Revised: 19 August 2019 / Accepted: 20 August 2019 / Published: 29 August 2019
(This article belongs to the Section Women's Health)
Browse Figure
Review Reports Versions Notes

Abstract

:
Antenatal care (ANC) reduces adverse health outcomes for both mother and baby during pregnancy and childbirth. The present study investigated the enablers and barriers to ANC service use among Indian women. The study used data on 183,091 women from the 2015–2016 India Demographic and Health Survey. Multivariate multinomial logistic regression models (using generalised linear latent and mixed models (GLLAMM) with the mlogit link and binomial family) that adjusted for clustering and sampling weights were used to investigate the association between the study factors and frequency of ANC service use. More than half (51.7%, 95% confidence interval (95% CI): 51.1–52.2%) of Indian women had four or more ANC visits, 31.7% (95% CI: 31.3–32.2%) had between one and three ANC visits, and 16.6% (95% CI: 16.3–17.0%) had no ANC visit. Higher household wealth status and parental education, belonging to other tribes or castes, a woman’s autonomy to visit the health facility, residence in Southern India, and exposure to the media were enablers of the recommended ANC (≥4) visits. In contrast, lower household wealth, a lack of a woman’s autonomy, and residence in East and Central India were barriers to appropriate ANC service use. Our study suggests that barriers to the recommended ANC service use in India can be amended by socioeconomic and health policy interventions, including improvements in education and social services, as well as community health education on the importance of ANC.

1. Introduction

Pregnancy and childbirth complications are the leading causes of maternal mortality worldwide, as an estimated 830 women lose their lives daily from preventable pregnancy- and/or childbirth-related causes. Over 99% of those maternal deaths occur in low- and middle-income countries (LMICs, including India) [1]. Antenatal care (ANC) provides a unique opportunity for screening and diagnosis, health promotion, and disease prevention among pregnant women, and their families and communities [2]. Appropriate utilisation of ANC services corresponds to improved maternal and newborn health, as well as a reduction in maternal deaths during pregnancy and childbirth [3,4,5]. Based on the benefits of ANC, the World Health Organisation (WHO) recommends that pregnant women should attend at least four ANC visits to increase opportunities for risk stratification and/or the identification, prevention, and management of pregnancy and/or comorbidities, as well as health promotion [2].
Worldwide, approximately 64% of women had attended four or more ANC visits in 2016. However, the attainment of the recommended ANC visits varied between and within countries, with LMICs reporting lower percentages [2]. In India, previous reports have indicated that the proportion of women who had four or more ANC visits has increased by approximately 38% over a 10-year period, from 37% in 2006 [6] to 51% in 2016 [7]. While this improvement in ANC service use may be commendable, it also suggests that many Indian women do not achieve the recommended four or more ANC visits, a proxy for comprehensive maternal care during pregnancy [2]. This lack of access to appropriate ANC may have potentially adverse short- and long-term impacts on Indian women and newborns. These adverse effects may include maternal death or health loss from haemorrhage, hypertensive disorders, sepsis, and abortion [4,8], as well as stillbirth and neonatal death [9].
Past nationally representative studies conducted based on the 2005–2006 India Demographic and Health Survey (DHS) data elucidated a number of factors associated with the underutilization of ANC services. These factors included low parental education, urban residence, a lack of mass-media exposure [10], lower household wealth, the region of residence, and belonging to Scheduled Castes, Scheduled Tribes, and the other backward class [11]. In addition, previous subnational studies suggested that financial and cultural issues, as well as a lack of awareness of the benefits of ANC among women and their partners, were also barriers to appropriate ANC service use [12,13]. Nevertheless, it is uncertain whether these factors have changed in the past 10 years in India, given the improvements in household economic and educational status [14], social mobility of women [15,16], and the implementation of the Government of India maternal and child health interventions. These programs included the National Rural Health Mission (2005), the National Urban Health Mission (2008), and the Reproductive, Maternal, Newborn, Child, and Adolescent Health (RMNCH+A) Strategy, introduced in 2013 to improve maternal and child health outcomes, including promotion of ANC service use [17]. Understanding the contextual factors that influence a mother’s decision to attend, or not to attend ANC is crucial to healthcare practitioners and policymakers, as it can offer relevant information and opportunities for targeted policy interventions.
Additionally, findings from the 2005–2006 India DHS may also differ from those obtained from the 2015–2016 DHS, the data source for the present study, due to variations in the sample size and methods used. The 2015–2016 India DHS collected data from 601,509 households, drawn from about 1.2 billion people [7], compared to 110,000 households in the 2005–2006 DHS, drawn from approximately 1 billion people [6]. Also, the 2015–2016 DHS methodology now forms the foundation for future national household surveys in India [7]. The availability of improved methodology for health information gathering and data also suggests the need for up-to-date evidence on the determining factors of ANC service use to guide national maternal health efforts. Therefore, the study aimed to investigate the enablers and barriers to ANC service use in India.

2. Methods

2.1. Data Sources

The broader methodological approach used in this study has been described in previously published studies [18,19,20]. In summary, the present study was based on the 2015–2016 India DHS, also known as the National Family Health Survey (NFHS-4). The data were collected by the International Institute for Population Sciences (IIPS), supervised by the Ministry of Health and Family Welfare (MoHFW), Government of India. A stratified two-stage sampling design for both rural and urban areas was used to obtain the total sample, based on the 2011 census frame, with villages serving as the primary sampling units (PSU) in rural areas and census enumeration blocks as the PSU in urban areas [7]. Using a standardised questionnaire, maternal and child health information (e.g., antenatal care, delivery care, postnatal care, and infant and young child feeding), as well as sociodemographic characteristics, were collected from eligible women aged 15–49 years in 601,509 households. Respondents were women who were residents in the household 24 h prior to the survey. In these households, 699,686 women were interviewed (204,735 in urban and 494,951 in rural areas), with an overall response rate of 96.7%. Detailed information on the survey methodology is provided in the final India DHS report [7].
In the present study, we used a total weighted sample of the 183,091 most recent live-birth infants of mothers, consistent with the India DHS report [7] and previously published studies [21,22], in an effort to minimise the potential effect of recall bias.

2.2. Outcome Variable

The outcome variable was the frequency of ANC service use, based on the WHO recommendation, where ANC service use was measured as at least a visit to the doctor, nurse, midwife, or lay health visitors [7]. In the present study, women were categorised according to their ANC service use into no ANC visits, one to three ANC visits, or four or more ANC visits, and these formed the outcome variables in the analyses. The no ANC visits group formed the reference category of the outcome variables in the analyses.

2.3. Study Factors

We adapted the Andersen behavioural conceptual framework [23] to group the study factors potentially related to ANC service use, based on evidence from past studies [18,24,25,26]. Twenty-three study factors were identified and categorised into four main groups: community, predisposing (socio-demographic and health knowledge), enabling, and need factors (Figure 1). Community-level factors included place of residence (urban and rural) and geopolitical region (North, South, East, West, Central, and Northeast), while predisposing factors included health knowledge (frequency of reading magazines or newspapers, frequency of listening to radio, and frequency of watching TV, knowledge of pregnancy complications, knowledge of delivery complications, and knowledge of post-birth complications), and socio-demographic factors (maternal age at delivery, household wealth index, maternal and paternal education, maternal marital status, maternal employment status, maternal body mass index, and types of castes/tribes). Enabling factors included permission to visit health services, distance to health facility, the presence of a companion, getting money to pay for health services, and household decision-making. Need factors included contraceptive use and desire for a pregnancy. In India, the Constitution recognises certain ethnic minority groups for special consideration as Scheduled Tribes, Scheduled Castes, or Other Backward Classes [27,28].

2.4. Statistical Analysis

The statistical approach was similar to previous studies [20,26,29]. In this study, preliminary analyses were conducted to describe the survey frequencies, as well as the prevalence of ANC service use and by the study factors in India using the Taylor series linearization to estimate confidence intervals (CIs) around the prevalence estimates. This was followed by the analysis to investigate potential factors related to the use of ANC services in univariate and multivariate multinomial logistic regression models. Generalised linear latent and mixed models (GLLAMM) with the mlogit link and binomial family that adjusted for clustering and sampling weights were used to assess the association between the independent variables and the outcome variables (no ANC visits, one to three ANC visits, or four or more ANC visits). A four-stage model was employed in the multivariate analyses, similar to the adopted conceptual model described by Anderson [23] and used in past studies [18,19]. In the first stage, community-level factors were entered into the model to assess their association with the outcome variables. In the second stage, the significant factors obtained from the stage one model were added to socio-demographic and health service factors to examine their relationship with the outcome variables. The same analytical approach was used for the enabling and need factors in the third and fourth stages, respectively. Any collinearity between the study factors was also investigated but none was evident in the analyses.
For the multivariate model, we calculated and reported statistically significant odds ratios (ORs) and their corresponding 95% CIs as the measure of association between the study factors and ANC service use in India. The analyses were conducted using the ‘svy’ command in Stata version 15.0 (Stata Corp, College Station, TX, USA) to adjust for clustering and sampling weights.

2.5. Ethics

The DHS project sought and obtained the required ethical approvals from Ethics Review Board of the International Institute for Population Sciences, Mumbai, India before the surveys were conducted, with informed consent obtained from participants during the surveys. Approval to use the data was sought from Measure DHS and permission was granted.

3. Results

3.1. Distribution of ANC Service Use by Study Factors

Of the total weighted sample of 183,091 reproductive age maternal responses, 16.6% (95% confidence intervals (95% CI): 16.3–17.0%) of women had no ANC visits, and 31.7% (95% CI: 31.3–32.2%) of women had between one and three ANC visits. A little above half (51.7%, 95% CI: 51.1–52.2%) of Indian women had four or more ANC visits (Table 1). A wide variation in the number of ANC visits was observed across Indian regions, as women who resided in the East reported the highest proportion of non-use of ANC services (39.3%, 95% CI: 38.2–40.6%), while those in the Northeast reported the lowest proportion of non-use of ANC services (2.9%, 95% CI: 2.7–3.2%). Women who resided in the South had the highest percentage of four or more ANC visits (28.4%, 95% CI: 27.7–29.2%), while those in the Northeast reported the lowest (3.7%, 95% CI: 3.5–3.8%) (Table 1).

3.2. Factors Associated with ANC Use (1–3 Visits)

Women from Southern, Eastern, Western, and Central India were less likely to make one to three ANC visits compared to those who resided in Northern India. Women from wealthier households were more likely to have between one and three ANC visits compared to those from poorer households. Women with higher education were more likely to make 1–3 ANC visits compared to those with no education (adjusted odds ratio column, Table 2). Exposure to the media (newspapers or magazines and television) was associated with Indian women attending between one and three ANC visits compared to non-media exposure. Women who reported difficulties in seeking permission to visit health services were less likely to attend one to three ANC visits compared to those who did not have problems in seeking permission (adjusted odds ratio column, Table 2).

3.3. Factors Associated with ANC Use (≥4 Visits)

Women from Southern India were more likely to attend four or more ANC visits compared to those from Northern India. In contrast, women from Eastern and Central India were less likely to attend four or more ANC visits compared to those from Northern India (adjusted odds ratio column, Table 2). Women from wealthier households were more likely to receive the four or more ANC visits compared to those from poorer households. In addition, higher parental education was associated with the attainment of four or more ANC visits compared to no maternal or partner education. Women from other tribes or castes were more likely to attend four or more ANC visits compared to those from Scheduled Caste. Women who engaged with the media (newspapers or magazines and television) were more likely to attend four or more ANC visits compared to those who did not engage with the media. Women who reported having problems seeking permission to attend health services and those who were not involved in household decision-making were less likely to attend four or more ANC visits compared to their counterparts. Women who reported visiting health facilities unaccompanied were less likely to attend four or more ANC visits compared to those who were accompanied by someone (adjusted odds ratio column, Table 2).

4. Discussion

The present study showed that 16.6% of Indian women had no ANC visits, 31.7% had between one and three ANC visits, and just over half received the recommended four or more ANC visits (51.7%). The study demonstrated that higher household wealth status and parental education, belonging to other tribes or castes, a woman’s autonomy to visit the health facility, residence in Southern India, as well as exposure to the media were enablers of the recommended ANC service use (≥4 visits). The recommended four or more ANC attendance was also associated with contraceptive use and a woman’s desire for pregnancy. In contrast, lower household wealth, a lack of woman’s autonomy, and residence in Eastern and Central India were barriers to appropriate ANC use.
The study indicated that mothers who resided in Southern India were more likely to attend at least four ANC visits, as recommended by the WHO compared to their counterparts in Northern India [2]. In contrast, mothers who resided in the East, Northeast, and Central India were less likely to attend at least four ANC visits compared to those who reside in Northern India. To the authors’ knowledge, region-specific determinants of ANC service use have not been elucidated in India; however, possible reasons for the regional variations in ANC use may be due to region-specific differences in economy, education, access and distance to health facilities, as well as the quality of service provision [30,31]. Studies that assess region-specific determining factors of ANC uptake may be needed to inform a more equitable distribution of maternal and child health (MCH) resources and policies at the sub-national level in India.
The association between household wealth status and ANC service utilisation has been documented in LMICs [32,33], and was a key factor in the present study. We found that mothers from wealthier households were more likely to attend ANC services compared to those from poorer households, and this association was stronger in those who attended at least four ANC visits. These findings are consistent with previous studies conducted in India [34,35], as well as other LMICs, including Nigeria [18], Pakistan [36], and Kenya [37]. Mothers who belonged to lower wealth quintiles may have greater financial challenges in accessing ANC services, as reported in studies from regional India [12,13]. Although ANC is almost free in most public hospitals in India, issues such as poor infrastructure, health professional absenteeism, and a shortage of medications in public hospitals, particularly in rural areas, may have pushed pregnant women to seek private ANC services [38]. Similarly, the costs associated with attending private maternity facilities [39] and the cost of transportation [40] have also been described as key barriers to accessible ANC in India.
In recent years, India has implemented a number of MCH interventions to tackle the expenses associated with maternity care services. Most notable of these is the Janani Suraksha Yojana (JSY) scheme, which was implemented by the National Rural Health Mission (NRHM) in 2005 to provide underprivileged pregnant women with cash assistance [41]. Nevertheless, the costs associated with accessing ANC remains significantly higher than the subsidies provided by programs such as the JSY program [42]. To improve ANC uptake among Indian women and other MCH outcomes, the Government of India has recently launched new MCH schemes, including the Pradhan Mantri Matru Vandana Yojana, Pradhan Mantri Surakshit Matritva Abhiyan, and LaQshya programmes [43,44]. While these initiatives are useful and required, the assessment of how successful and impactful these programs are may need to be documented in the scientific literature, consistent with a previous program [17], to guide future MCH programmes in India.
Higher maternal education level is an important enabler of ANC utilisation in the present study, as mothers with secondary or higher schooling were more likely to attend at least four ANC visits. The dose-response relationship between maternal education and ANC service use observed in this study is consistent with previous studies conducted in India [10], Indonesia [45], Bangladesh [46], and Turkey [47]. Higher maternal education may have a synergistic effect with other enablers of ANC utilisation, as women with higher education may be more likely to live in urban areas, gain employment, possess more wealth, and have a better understanding of the benefits of attending ANC [24]. This association was mirrored in the partner education levels, potentially due to similar reasons. Furthermore, higher education may empower parents to make informed decisions about their health and take action on health promotion initiatives. Our study highlights the importance of targeting low education mothers with health promotion messages, as the majority of mothers who did not attend ANC had no education. More broadly, the Government of India may need to ensure that young girls and boys have access to inclusive and quality education, and ensure a higher completion rates, as articulated in Sustainable Development Goal–4 [48], which may subsequently lead to greater utilisation of ANC service in the long-term.
Consistent with previous reports [18,49], the present study indicated that women who considered access to enabling factors (e.g., household decision-making power, autonomy to attend ANC, and requiring a companion to attend ANC) a big problem, had a corresponding underutilization of ANC services in India. In particular, women who were not involved in household decision-making were less likely to attend between one and three ANC visits, and even less likely to attend four or more ANC visits compared to their counterparts. Similarly, women who reported needing to seek permission from their partners to attend ANC and those who were not usually accompanied to health facilities were also less likely to attend the recommended number of ANC visits. These findings suggest that a woman’s autonomy and support from their partner play important roles in ANC service use.
Contrary to past studies [37,50,51], distance to health facilities was not associated with ANC service use in our study. The Government of India health initiative (the National Rural Health Mission) [17] that expanded MCH services to disadvantaged rural areas may have played a role in our finding. Women’s exposure to mass media (newspapers or magazines and television) was associated with ANC service use, and this is consistent with past studies [10,18]. A lack of exposure to these media outlets may have resulted in women missing out on health promotion messages relating to the benefits of ANC. Additionally, the ownership of media devices may be a direct result of higher household wealth, which was also related to ANC service use. Our research underpins the need to improve women’s autonomy in the household, as well as increase the reach and impact of health promotion campaigns and access to media sources for vulnerable women.
Past studies have suggested that the use of ANC services is influenced by a woman’s desire for pregnancy, as women who carry unplanned pregnancies were less likely to attend ANC [37,52]. This finding was demonstrated in our study, where women who had no desire for pregnancy were less likely to attend the recommended four or more ANC visits compared to those who had no desire for pregnancy. Similarly, women who did not use contraceptives were less likely to attend four or more ANC visits. These findings indicate the need for a scale-up of accessible family planning to women of reproductive age, as well as greater access to contraceptive methods and education in India.

Study Limitations and Strengths

This study had limitations. First, the study was based on cross-sectional data, which makes an assessment of a clear temporal relationship between the study factors and ANC attendance impossible. Second, the ANC data collected during the NFHS-4 would have been subjected to recall bias, as it relied on self-reporting. This may have resulted in misclassification measurement bias, and subsequently, led to either an over- or under-estimation of the effect size between the study factors and ANC service use. Third, there was a lack of assessment of other potential confounders (e.g., data on health care access or health status of pregnant women), which may have provided additional information with the enablers and barriers to ANC service use in India. The study also had strengths. First, the large representative sample, with a high response rate (approximately 98%). This implies that selection bias may be unlikely to affect the observed results. Second, trained personnel with validated questionnaires were used to collect data in the NFHS-4, which would have strengthened the internal validity of the study. Lastly, the study provides insight into key determinants of ANC visits in India, and thus, provides an opportunity for policymakers and public health practitioners to design and implement focused MCH interventions.

5. Conclusions

The present study indicated that higher household wealth status and parental education, belonging to other tribes or castes, a woman’s autonomy to visit the health facility, residence in Southern India, and desire for pregnancy, as well as exposure to the media, were enablers to frequent ANC service use. In contrast, residence in the East, Northeast, and Central regions of India were barriers to the utilisation of ANC services. Also, women from poorer households, those with no or primary education, and women who were not exposed to mass media were less likely to use ANC services compared to their counterparts. Our study elucidates key enablers and barriers to ANC attendance in India. It is vital that current and/or future MCH initiatives focus on women with socioeconomic vulnerabilities, while also designing and implementing multi-pronged MCH interventions that aimed to increase ANC uptake among underserved Indian women.

Author Contributions

Conceptualization, F.A.O. and E.M.U.; Data curation, F.A.O.; Formal analysis, F.A.O.; Funding acquisition, F.A.O.; Investigation, F.A.O., M.V.D., E.M.U., P.S., U.L.O., A.O.A., P.O., O.K.E. and K.E.A.; Methodology, F.A.O., O.K.E. and K.E.A.; Project administration, F.A.O.; Resources, F.A.O.; Software, F.A.O.; Supervision, F.A.O.; Validation, F.A.O., M.V.D., P.S., U.L.O., A.O.A., P.O., B.J.A., O.K.E. and K.E.A.; Visualization, F.A.O., M.V.D., E.M.U., P.S., U.L.O., A.O.A., P.O., B.J.A., O.K.E. and K.E.A.; Writing—original draft, F.A.O., M.V.D., E.M.U., P.S. and U.L.O.; Writing—review & editing, F.A.O., M.V.D., U.L.O., A.O.A., P.O., B.J.A., O.K.E. and K.E.A.

Funding

This research received no external funding. The APC was funded by the early career research funding grant from the Office of the Deputy Vice-Chancellor (Research and Innovation), Western Sydney University, obtained by Felix Akpojene Ogbo.

Acknowledgments

The authors are grateful to Measure DHS, ICF International, Rockville, Maryland, USA for providing the data for the analysis. The time and effort of Nilu Nagdev in reading the initial manuscript is also acknowledged.

Conflicts of Interest

The authors declare no conflict of interest. Felix Akpojene Ogbo is an Editorial Board Member for International Journal of Environmental Research and Public Health but did not play any role in the peer-review and decision-making process for this manuscript.

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Ijerph 16 03152 g001 550
Figure 1. Conceptual framework modified from the Andersen behavioural model [23].
Figure 1. Conceptual framework modified from the Andersen behavioural model [23].
Ijerph 16 03152 g001
Table
Table 1. Prevalence (PR) with corresponding 95% confidence interval (95% CI) of the frequency of antenatal care service use in India, 2015–2016 NFHS–4 (National Family Health Survey) (N = 183,091).
Table 1. Prevalence (PR) with corresponding 95% confidence interval (95% CI) of the frequency of antenatal care service use in India, 2015–2016 NFHS–4 (National Family Health Survey) (N = 183,091).
Antenatal Care (ANC) VisitsNo ANC VisitsANC (1–3) VisitsANC (≥4) Visits
Variablen *PR (95% CI)n *PR (95% CI)n *PR (95% CI)
Outcomes30,44916.6 (16.3–17.0)58,08231.7 (31.3–32.2)94,56051.7 (51.1–52.2)
Community-level factors
Residence type
Urban507416.6 (15.5–17.8)12,79922.0 (21.0–23.1)36,41038.5 (37.3–39.6)
Rural25,37583.3 (82.1–84.4)45,28377.9 (76.9–78.9)58,15061.5 (60.3–62.6)
Geopolitical region
North27058.9 (8.2–9.5)825414.2 (13.7–14.7)11,76512.4 (12.0–12.9)
South19776.5 (5.7–7.3)52559.0 (8.4–9.7)26,88628.4 (27.7–29.1)
East11,99439.3 (38.1–40.6)15,10226.0 (25.3–26.6)19,51820.6 (19.9–21.3)
West23377.7 (6.9–8.4)43347.4 (6.7–8.2)17,39018.3 (17.6–19.1)
Central10,53234.6 (33.4–35.7)22,47538.7 (37.9–39.4)15,54016.4 (15.9–16.8)
Northeast9042.9 (2.7–3.2)26614.5 (4.3–4.8)34613.6 (3.5–3.8)
Socio-demographic factors
Household wealth index
Poor22,02972.3 (71.3–73.3)31,51754.2 (53.4–55.0)28,10729.7 (29.0–30.4)
Middle413613.5 (13.0–14.1)11,29519.4 (18.9–19.9)21,00422.2 (21.7–22.7)
Rich428414.0 (13.2–14.9)15,27026.2 (25.5–27.0)45,44948.0 (47.2–48.8)
Mother’s education
No education16,48154.1 (53.1–55.0)19,91434.2 (33.6–34.9)14,27615.1 (14.6–15.5)
Primary429914.1 (13.6–14.6)908115.6 (15.2–16.0)11,27111.9 (11.5–12.2)
Secondary or higher966931.7 (30.8–32.7)29,08750.0 (49.3–50.7)69,01472.9 (72.4–73.5)
Mother’s working status
Did not work397113.0 (12.3–13.7)792013.6 (13.1–14.1)14,75615.6 (15.0–16.1)
Worked9132.9 (2.7–3.2)15692.7 (2.5–2.9)27282.8 (2.6–3.0)
Mother’s age
15–19 years9273.0 (2.7–3.3)19103.2 (3.1–3.4)34023.5 (3.3–3.8)
20–34 years24,67781.0 (80.4–81.6)50,64687.2 (86.8–87.5)84,38989.2 (88.9–89.5)
35–49 years484515.9 (15.3–16.4)55269.5 (9.2–9.8)67697.1 (6.8–7.4)
Maternal BMI kg/m2
≤18661621.7 (21.1–22.3)11,79320.3 (19.8–20.7)14,94815.8 (15.4–16.2)
19–2420,54367.4 (66.7–68.1)38,71966.6 (66.1–67.1)58,41661.7 (61.2–62.3)
≥2527459.0 (8.5–9.5)675811.6 (11.2–12.0)19,09320.1 (19.7–20.6)
Type of caste or tribe
Scheduled caste698822.9 (22.1–23.8)12,82022.0 (21.4–22.6)19,03020.1 (19.5–20.7)
Scheduled tribe375012.3 (11.6–12.9)634210.9 (10.4–11.4)86699.1 (8.7–9.5)
Other backward class14,24346.7 (45.7–47.8)26,78846.1 (45.3–46.9)38,83141.0 (40.3–41.7)
Others #546817.9 (17.1–18.8)12,13220.8 (20.2–21.6)28,03029.6 (28.9–30.3)
Marital status
Currently married29,92698.2 (98.0–98.4)57,36598.7 (98.6–98.8)93,28998.6 (98.5–98.7)
Formerly married (divorced/separated/widowed)4651.5 (1.3–1.7)6701.1 (1.0–1.2)11941.2 (1.1–1.3)
Partner education
No education16145.3 (4.9–5.7)18523.1 (2.9–3.4)17761.8 (1.7–2.0)
Primary29509.6 (9.1–10.2)651511.2 (10.7–11.6)12,19212.8 (12.4–13.3)
Secondary or higher2990.9 (0.8–1.1)10891.8 (1.7–2.0)34713.6 (3.4–3.9)
Religion
Hindu23,82578.2 (77.1–79.2)46,59880.2 (79.4–80.9)74,02978.2 (77.5–79.0)
Muslim567918.6 (17.6–19.6)923315.9 (15.1–16.6)14,51115.3 (14.6–16.0)
Christian and others9453.1 (2.7–3.5)22503.8 (3.6–4.1)60206.3 (5.9–6.7)
Health knowledge factors
Reads newspaper or magazine
Not all25,65784.2 (83.5–84.9)41,83572.0 (71.2–72.7)51,81254.7 (54.1–55.4)
Yes479215.7 (15.0–16.4)16,24627.9 (27.2–28.7)42,74945.2 (44.5–45.8)
Listens to radio
Not all26,36586.5 (85.9–87.2)50,71687.3 (86.7–87.8)80,81885.4 (85.0–85.9)
Yes408413.4 (12.7–14.0)736612.6 (12.1–13.2)13,74214.5 (14.0–14.9)
Watches television
Not all17,49657.4 (56.4–58.4)21,16836.4 (35.7–37.1)13,84114.6 (14.2–15.0)
Yes12,95342.5 (41.5–43.5)36,91463.5 (62.8–64.2)80,71985.3 (84.9–85.7)
Told about delivery complications
Any complications0030,72652.9 (52.1–53.6)66,91870.7 (70.1–71.3)
None30,44910027,35647.1 (46.3–47.8)27,64229.2 (28.6–29.8)
Knowledge of post-delivery complications
Yes491116.1 (15.4–16.8)20,23534.8 (34.1–35.5)42,50644.9 (44.2–45.6)
None25,53783.8 (83.1–84.5)37,84765.1 (64.4–65.8)52,05455.0 (54.3–55.7)
Enabling factors
Household decision making
Mother involved362111.8 (11.2–12.5)756613.0 (12.5–13.5)14,72115.5 (15.0–16.1)
Mother not involved26,82888.1 (87.4–88.7)50,51686.9 (86.4–87.4)79,83984.4 (83.8–84.9)
Seek permission to visit health services
No problem13,53344.4 (43.4–45.4)31,65854.5 (53.7–55.2)58,78562.1 (61.4–62.8)
Big problem920730.2 (29.3–31.2)12,44721.4 (20.8–22.0)14,46815.3 (14.8–15.8)
Not a big problem770925.3 (24.5–26.1)13,97724.0 (23.4–24.7)21,30722.5 (21.9–23.1)
Getting money to pay health services
No problem918630.1 (29.2–31.0)23,05339.6 (38.9–40.4)45,30947.9 (47.1–48.6)
Big problem11,84238.8 (37.9–39.8)16,74228.8 (28.1–29.4)21,00222.2 (21.6–22.8)
Not a big problem942130.9 (30.1–31.7)18,28731.4 (30.8–32.1)28,24929.8 (29.2–30.4)
Distance to health facility
No problem648521.3 (20.4–22.1)16,54628.4 (27.8–29.1)38,33240.5 (39.8–41.2)
Big problem13,82345.4 (44.3–46.4)20,90635.9 (35.2–36.7)24,23225.6 (25.0–26.2)
Not a big problem10,14133.3 (32.4–34.1)20,62935.5 (34.9–36.1)31,99633.8 (33.2–34.4)
Accompany to health facility
No problem979632.1 (31.2–33.1)23,33940.1 (39.5–40.8)49,19552.0 (51.3–52.7)
Big problem10,16333.3 (32.4–34.3)14,28524.5 (23.9–25.2)15,51116.4 (15.9–16.8)
Not a big problem10,49034.4 (33.6–35.3)20,45835.2 (34.5–35.8)29,85431.5 (30.9–32.1)
Need factors
Contraceptive use
Yes826427.1 (26.3–27.9)23,14739.8 (39.2–40.4)46,59949.2 (48.6–49.8)
No22,17972.8 (72.0–73.6)34,92660.1 (59.5–60.7)47,94250.7 (50.1–51.3)
Wanted pregnancy at the time
Then25,84484.8 (84.2–85.5)52,18989.8 (89.5–90.2)88,13993.2 (92.9–93.4)
Later12804.2 (3.8–4.5)26314.5 (4.3–4.7)35823.7 (3.5–3.9)
No more322310.5 (10.0–11.1)32615.6 (5.3–5.8)28393.0 (2.8–3.1)
n * = the weighted total number varies between categories due to missing data; PR = prevalence of pregnant women who attended ANC across the study variables; CI: confidence interval; others # includes Jews, Parsis/Zoroastrians, those following “other” religions, and those with no religion.
Table
Table 2. Factors associated with antenatal care service use in India, 2015–2016 NFHS (N = 183,091).
Table 2. Factors associated with antenatal care service use in India, 2015–2016 NFHS (N = 183,091).
Study FactorsAntenatal Care (1–3) VisitsAntenatal Care (≥4) Visits
COR(95% CI)p ValueaOR(95% CI)p ValueCOR(95% CI)p ValueaOR(95% CI)p Value
Community-level factors
Geopolitical region
North1.00 1.00 1.00 1.00
South0.800.74–1.020.0970.720.54–0.970.0353.122.68–3.65p < 0.0012.411.83–3.16p < 0.001
East0.410.37–0.45p < 0.0010.470.39–0.56p < 0.0010.370.33–0.41p < 0.0010.400.33–0.48p < 0.001
West0.600.51–0.71p < 0.0010.490.37–0.65p < 0.0011.711.49–1.95p < 0.0011.130.87–1.470.324
Central0.690.63–0.76p < 0.0010.760.64–0.910.0030.340.30–0.37p < 0.0010.360.30–0.44p < 0.001
North East0.960.85–1.090.5681.080.84–1.390.5060.880.77–1.000.0570.780.60–1.010.068
Socio-demographic factors
Household wealth index
Poor1.00 1.00 1.00 1.00
Middle1.901.80–2.02p < 0.0011.281.11–1.480.0013.983.74–4.22p < 0.0011.861.61–2.15p < 0.001
Rich2.492.30–2.68P < 0.0011.561.29–1.88p < 0.0018.317.71–8.96p < 0.0012.992.47–3.62p < 0.001
Mother education
No education1.00 1.00 1.00 1.00
Primary1.741.65–1.84p < 0.0011.481.29–1.70p < 0.0013.022.85–3.21p < 0.0012.031.75–2.36p < 0.001
Secondary and higher2.492.36–2.61p < 0.0011.771.57–2.00p < 0.0018.247.81–8.69p < 0.0013.423.01–3.87p < 0.001
Type of caste or tribe
Scheduled caste1.00 1.00 1.00 1.00
Scheduled tribe0.920.85–0.990.0391.160.98–1.380.0710.840.78–0.92p < 0.0011.281.05–1.540.110
Other backward class1.020.96–1.080.3811.030.91–1.170.5561.000.94–1.060.9700.880.77–1.000.058
Others1.201.12–1.30p < 0.0011.180.99–1.400.0551.881.74–2.03p < 0.0011.601.34–1.91p < 0.001
Partner education
No education1.00 1.00 1.00 1.00
Primary1.921.73–2.14p < 0.0011.321.19–1.48p < 0.0013.753.35–4.20p < 0.0011.551.37–1.75p < 0.001
Secondary and higher3.172.55–3.95p < 0.0011.621.28–2.04p < 0.00110.558.47–13.13p < 0.0012.511.98–3.18p < 0.001
Health knowledge factors
Reads newspaper or magazine
Not all1.00 1.00 1.00 1.00
Yes2.071.95–2.21p < 0.0011.181.00–1.380.0424.414.17–4.67p < 0.0011.271.08–1.500.003
Listens to radio
Not all1.00 1.00 1.00 1.00
Yes0.930.87–1.000.0800.670.57–0.78p < 0.0011.091.02–1.170.0050.650.55–0.77p < 0.001
Watches television
Not all1.00 1.00 1.00 1.00
Yes2.352.24–2.46p < 0.0011.421.27–1.59p < 0.0017.877.47–8.30p < 0.0012.562.26–2.89p < 0.001
Enabling factors
Household decision making
Mother involved1.00 1.00 1.00 1.00
Mother not involved0.900.84–0.960.0020.840.74–0.950.0070.730.68–0.78p < 0.0010.680.59–0.78p < 0.001
Seeking permission to visit health services
No problem1.00 1.00 1.00 1.00
Big problem0.570.54–0.61p < 0.0010.740.64–0.86p < 0.0013.620.34–0.38p < 0.0010.530.45–0.63p < 0.001
Not a big problem0.770.73–0.82p < 0.0010.790.69–0.900.0010.630.60–0.67p < 0.0010.650.56–0.76p < 0.001
Getting money to pay health services
No problem1.00 1.00 1.00 1.00
Big problem0.560.53–0.59p < 0.0010.990.84–1.170.9960.360.33–0.38p < 0.0011.080.89–1.290.406
Not a big problem0.770.73–0.81p < 0.0010.910.79–1.050.2230.600.57–0.64p < 0.0010.900.78–1.050.215
Distance to health facility
No problem1.00 1.00 1.00 1.00
Big problem0.590.55–0.63p < 0.0010.990.85–1.160.9340.290.27–0.31p < 0.0010.850.71–1.010.068
Not a big problem0.790.75–0.84p < 0.0010.970.83–1.140.7790.530.50–0.56p < 0.0010.910.76–1.080.284
Accompanied to health facility
No problem1.00 1.00 1.00 1.00
Big problem0.590.55–0.62p < 0.0010.900.77–1.060.2220.300.28–0.32p < 0.0010.780.65–0.940.011
Not a big problem0.810.77–0.86p < 0.0011.060.92–1.210.3850.560.53–0.59p < 0.0010.920.79–1.060.279
Need factors
Contraceptive use
Yes1.00 1.00 1.00 1.00
No0.560.53–0.58p < 0.0010.700.63–0.78p < 0.0010.380.36–0.40p < 0.0010.510.45–0.57p < 0.001
Wanted pregnancy at the time
Then1.00 1.00 1.00 1.00
Later1.010.92–1.120.7121.020.80–1.310.8220.820.74–0.90p < 0.0010.940.73–1.210.655
No more0.500.46–0.53p < 0.0010.720.61–0.870.0010.250.23–0.28p < 0.0010.510.41–0.64p < 0.001
Statistically significant (using p value < 0.05 and confidence intervals) study factors from multivariable models are shown. COR: crude odds ratio; aOR: adjusted odds ratio. In the model of community-level factors, adjustments were conducted for predisposing (sociodemographic and health), enabling, and need factors. Similar approaches were used for the predisposing, enabling, and need factors, with adjustments for respective factors in multivariable models.

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MDPI and ACS Style

Ogbo, F.A.; Dhami, M.V.; Ude, E.M.; Senanayake, P.; Osuagwu, U.L.; Awosemo, A.O.; Ogeleka, P.; Akombi, B.J.; Ezeh, O.K.; Agho, K.E. Enablers and Barriers to the Utilization of Antenatal Care Services in India. Int. J. Environ. Res. Public Health 2019, 16, 3152. https://doi.org/10.3390/ijerph16173152

AMA Style

Ogbo FA, Dhami MV, Ude EM, Senanayake P, Osuagwu UL, Awosemo AO, Ogeleka P, Akombi BJ, Ezeh OK, Agho KE. Enablers and Barriers to the Utilization of Antenatal Care Services in India. International Journal of Environmental Research and Public Health. 2019; 16(17):3152. https://doi.org/10.3390/ijerph16173152

Chicago/Turabian Style

Ogbo, Felix Akpojene, Mansi Vijaybhai Dhami, Ebere Maureen Ude, Praween Senanayake, Uchechukwu L. Osuagwu, Akorede O. Awosemo, Pascal Ogeleka, Blessing Jaka Akombi, Osita Kingsley Ezeh, and Kingsley E. Agho. 2019. "Enablers and Barriers to the Utilization of Antenatal Care Services in India" International Journal of Environmental Research and Public Health 16, no. 17: 3152. https://doi.org/10.3390/ijerph16173152

APA Style

Ogbo, F. A., Dhami, M. V., Ude, E. M., Senanayake, P., Osuagwu, U. L., Awosemo, A. O., Ogeleka, P., Akombi, B. J., Ezeh, O. K., & Agho, K. E. (2019). Enablers and Barriers to the Utilization of Antenatal Care Services in India. International Journal of Environmental Research and Public Health, 16(17), 3152. https://doi.org/10.3390/ijerph16173152

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