You are here

  • Home
  • Archive
  • Volume 13, Issue 10
  • Inequalities in adequate maternal healthcare opportunities: evidence from Bangladesh Demographic and Health Survey 2017–2018

Article Text

Article menu

Download PDFPDF

Health policy
Original research
Inequalities in adequate maternal healthcare opportunities: evidence from Bangladesh Demographic and Health Survey 2017–2018
  1. Md Injamul Haq Methun1,
  2. Bright Opoku Ahinkorah2,
  3. Sutopa Roy3,
  4. Joshua Okyere4,
  5. Md Ismail Hossain3,
  6. Iqramul Haq5,
  7. Shatabdi Shamrita Ume3,
  8. Md Kamrul Hasan6
  1. 1Department of Statistics, Tejgaon College, National University Bangladesh, Dhaka, Bangladesh
  2. 2Faculty of Health, The Australian Centre for Public and Population Health Research, University of Technology Sydney, Liverpool, New South Wales, Australia
  3. 3Department of Statistics, Jagannath University, Dhaka, Bangladesh
  4. 4Department of Population and Health, University of Cape Coast, Cape Coast, Ghana
  5. 5Department of Agricultural Statistics, Faculty of Agribusiness Management, Sher-e-Bangla Agricultural University, Dhaka, Bangladesh
  6. 6Department of Public Health, North South University, Dhaka, Bangladesh
  1. Correspondence to Dr Md Kamrul Hasan; kamrul.hasan11{at}northsouth.edu

Abstract

Objectives This study investigated the inequalities in access to maternal healthcare services in Bangladesh.

Design and setting This study used cross-sectional data from the nationally representative Bangladesh Demographic and Health Survey conducted in 2017–2018. The survey encompassed diverse regions and households across Bangladesh. The study used the Human Opportunity Index (HOI) and Shapley’s decomposition technique to measure the inequality in access to maternal healthcare opportunities.

Participants This study included 20 127 women aged 15–49 years. Among them, 5012 women had live births in the preceding 3 years of the survey, forming the study sample.

Primary and secondary outcome measures This study has no secondary outcome variable. The primary dependent variable is ‘adequate maternal healthcare’, a dichotomous variable.

Results Household wealth status contributed the highest to inequality in accessing adequate maternal healthcare services (41.4%) such as receiving at least four antenatal care (ANC) visits (39.7%), access to proper ANC (50.7% and 44.0%) and health facility birth (43.4%). Maternal educational status contributes the second highest inequality among all factors in accessing adequate maternal healthcare (29.5%). Adequate maternal healthcare presented the lowest coverage rate and opportunity index among all (approximately 24% with HOI=17.2).

Conclusions We found that attained adequate maternal healthcare had the lowest coverage and widest dissimilarity, while wealth index, education and place of residence are the major factors that contribute to inequalities in accessibility to maternal healthcare services in Bangladesh. These findings underscore a need for pro-poor interventions to narrow the economic inequalities between the poor and rich in terms of accessibility to maternal healthcare services. The results indicate the need for the Bangladeshi government and its health department to strengthen their commitment to improving female education. Investments should be made in initiatives that facilitate the proximity of maternal healthcare services to women in rural areas.

  • Health policy
  • Health Equity
  • OBSTETRICS
  • PUBLIC HEALTH

Data availability statement

Data are available upon reasonable request. Data are available in a public, open-access repository. Data are available upon reasonable request at https://dhsprogram.com/data/available-datasets.cfm.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi-org.ezproxy.u-pec.fr/10.1136/bmjopen-2022-070111

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    STRENGTHS AND LIMITATIONS OF THIS STUDY

    • The use of Bangladesh Demographic and Health Survey (BDHS) provided a large nationally representative dataset that can be based on to generalise the findings to the Bangladeshi women population and other resource-constrained settings with similar contextual characteristics as Bangladesh.

    • Also, the use of Human Opportunity Index, D-index and decomposing technique was appropriate for understanding the inequalities in accessibility to maternal healthcare services.

    • Given that the study relied on data from the BDHS that uses cross-sectional design, the inequalities observed cannot be interpreted as causal inferences.

    • Also, the questions on adequate maternal healthcare, antenatal care (ANC), ANC from skilled personnel and delivery at the health facility were self-reported. Hence, there is the possibility of recall and social desirability bias.

    • Moreover, residual factors such as community norms and cultural beliefs were not available in the BDHS; hence, we are unable to test how that contributes to the observed inequalities.

    Background

    Globally, there is unequivocal consensus from literature that access and utilisation of maternal healthcare services is a critical strategy that contributes substantially to reducing maternal deaths.1 This is because access and utilisation of maternal healthcare services provides women with timely interventions such as services from skilled health professionals during childbirth, emergency obstetric care and the opportunity to have pregnancy-related complications detected and treated on time.2–4 Nevertheless, maternal mortality rate remains unacceptably high particularly in low-income and middle-income countries such as Bangladesh.5 For instance, the WHO reports that in 2017, nearly 810 women died each day as a result of preventable pregnancy and childbirth-related complications.6 In the case of Bangladesh, the rate of maternal deaths had declined by 40% between 2001 and 2010, from 574 to 200 deaths per 100 000 live births, with an annual diminishing rate of 5.9%.7 If this trajectory of decline continues, then Bangladesh may not be able to achieve the 3.1 of the Sustainable Development Goals (SDGs) which envision to reduce maternal deaths to 70 per 100 000 live births. However, the country may be closer to achieving the SDGs if there is equity in the accessibility and utilisation of maternal healthcare services.8

    In the context of this study, maternal healthcare encapsulates access and use of antenatal care (ANC), delivery at the health facility, childbirth by skilled care provider and receiving adequate care. Previous studies show inequalities in the utilisation of maternal healthcare services.9–11 For example, a study conducted in Malawi found inequalities in the utilisation of maternal healthcare services across the dimensions of wealth, education and place of residence.9 Similarly, a related study from India reported geographical inequalities in using maternal healthcare services.11 In Bangladesh, Pulok et al12 have revealed the existence of socioeconomic inequalities in the usage of maternal healthcare services. These inequalities are a threat to the attainment of the SDGs, particularly target 3.1, thus emphasising a need for more evidence-based research to understand the dynamics and nuances of the existing inequalities in access and utilisation of maternal healthcare services.

    Despite the importance of unearthing and understanding the inequalities in both access to and utilisation of maternal healthcare services, a preponderance of empirical literature has been one sided, focusing only on inequalities in the utilisation of maternal healthcare services.9–11 Bangladesh’s situation is not different as studies have only investigated the inequalities in using maternal healthcare services.12–14 However, there are few studies that have explored the accessibility dimension. For example, Ahmed et al,5 and Di Novi and Thakare15 investigated inequalities regarding accessibility to maternal healthcare services in Bangladesh. However, in Ahmed et al’s study, only gender inequality in accessibility to maternal healthcare services was investigated.5 To the best of our knowledge, no study in Bangladesh has simultaneously investigated inequalities in access to adequate maternal healthcare services, ANC from skilled health personnel, receiving at least four ANC visits and delivery at a health facility. Therefore, there is a a significant limitation in the current understanding of the inequality dynamics regarding access to maternal healthcare services in Bangladesh. We, therefore, aimed to narrow this gap by investigating the inequalities in access to maternal healthcare services in Bangladesh. The study expands on the Human Opportunity Index (HOI), created by the World Bank in 2006, and measures how socioeconomic and demographic factors predict inequalities in access to maternal healthcare services. We also categorise inequality according to the circumstances using Shapley’s decomposition technique. This approach shows how much each scenario element contributes to overall inequalities in access to maternal healthcare services.

    Methods

    Data source

    Nationally representative 2017–2018 Bangladesh Demographic and Health Survey (2017–2018 BDHS) data had been used in this study. The data provide several nationally representative maternal and child health indicators along with socioeconomic status. The BDHS was first carried out in 1993 and since then it was carried out every 3–4 years.

    Data collection

    The data of the 2017–2018 BDHS were collected under the authority of the National Institute of Population Research and Training. The 2017–2018 BDHS uses a two-stage stratified sampling technique to select study participants. Clusters usually known as enumeration areas (EAs) were selected in the first stage using probability proportional to EA size. In the second stage, using systematic sampling, households were selected from the EAs. From the selected households, a total of 20 127 women aged 15–49 years were interviewed. Details of the sampling procedure were described elsewhere.16 Among the interviewed women, only 5012 gave live births in the previous 3 years of the survey. Thus, the study population was formed through these 5012 women. Moreover, there was no missing value; hence, we used information of 5012 women for the final analysis. Data screening for women who had last birth in the last 3 years preceding the survey is presented in figure 1.

    Figure 1
    Figure 1

    Data screening for women who had their last birth in the last 3 years preceding the Bangladesh Demographic and Health Survey 2017–2018.

    Maternal healthcare opportunities

    Opportunities are recognised as the essential set of goods and services that enable individuals to fulfil their potentials.17 The opportunity to access the maternal healthcare services throughout pregnancy has an indispensable role in fostering positive health outcomes for both the mother and child through the mitigation of potential risks and complications associated with pregnancy. As for the opportunity to access maternal healthcare, we use the following indicators: access to ANC care, access to minimum required ANC visits, access to medically trained persons who provided ANC, access to institutional delivery and access to adequate maternal healthcare. Here, access to adequate maternal healthcare services is a composite indicator, and the descriptions of this indicator along with other indicators are given in table 1.

    View this table:
    Table 1

    List of opportunities and their descriptions

    Circumstances

    According to the principle of equal opportunities, everyone deserves equal chance of accessing the opportunities, irrespective of their circumstances. Personal, family or community characteristics that one cannot directly influence are acknowledged as circumstances.18 Studies have demonstrated that utilisation of maternal healthcare opportunities is affected by different factors such as wealth status, living area and educational levels.19–21 Mothers can have considerably limited influences on these distinctive grouping factors. Therefore, in the context of this study, these stratified characteristics can be classified as circumstances. Based on the existing literature, eight circumstances were selected for this study. Descriptions of the selected circumstances are given in table 2.

    View this table:
    Table 2

    Categorisation of the circumstances

    Statistical analyses

    For this study, we have used weighted data. Descriptive analysis was performed at first, and then, the association between the circumstances and maternal healthcare opportunities was assessed using the Χ2 test. We calculate the HOI and the dissimilarity index (D-index) for each maternal health opportunity to measure inequality of maternal health opportunity. The methodological framework of this study was developed based on measures of inequality of opportunity used in previous studies.22 23 The D-index measures relative inequality in allocating maternal health opportunities over various groups defined by different circumstances. The index quantifies the ratio of mothers who need access to maternal healthcare services, relative to those who enjoy access to the corresponding services. We estimated the D-index using the following three steps:

    First step: we computed the conditional likelihood by fixing a binary function between maternal healthcare opportunities and circumstances (X1, X2, X3,…, X8) using logistic regression where X1=age at delivery, X2=educational status, X3=employment status, X4=healthcare decision, X5=wealth status, X6=religion, X7=residence, X8=division.

    Second step: we estimated predicted probability for access to maternal healthcare services considering the chosen circumstances.

    Third step: we estimated the D-index and the probability of access to care (p) using the following equations:

    Embedded Image

    Where Embedded Image and n denotes number of disjoint groups defined by the circumstances.

    Embedded Image

    The values of D range from 0 to 1 in general and 0–100 in percentage. D takes the value 0 for perfect equality in the access to maternal healthcare opportunities.

    Human Opportunity Index

    Penalising the degree of inequality in the distribution of essential maternal health services among different groups based on the circumstances, the HOI assesses the availability of essential maternal health services that are fundamental to positive motherhood.22 This index was developed by the World Bank with exterior researchers and represented in 2009.24 HOI was computed as:

    HOI = Embedded Image

    Where D is the D-index of inequality of opportunities in accessing basic services for circumstance groups. (1–D) will be equal to 1 when the inequality of opportunity (D) is 0. It means that the coverage rate or average access (Embedded Image) will become equal to that much of access to the opportunity and HOI is independent of circumstances. The HOI is graded on a scale ranging 0–100, where the score 100 means the society received universal coverage of the health services.

    Shapley’s decomposition method

    Shapley’s decomposition25 method was used to find out the relative contribution of each circumstance to the inequality. The contribution of each circumstance (Cj) to the inequality of maternal healthcare opportunities is estimated by the following equation:

    Embedded Image

    where:

    N=denotes total number of the circumstances.

    n=denotes the number of selected circumstances in N.

    s=denotes a subset of N circumstances without Cj.

    D(S)=denotes estimated D-index using a set of circumstances (S).

    D(S∪{Cj})=D-index calculated with the circumstance Cj and the subset of circumstances S.

    Then, the contribution of Cj circumstance to the D-index is examined by the following formula:

    Embedded Image = Embedded Image, where Embedded Image

    We use the inequality of opportunity module in Stata V.17.

    Statistical software

    The most popular instruments for statistical computation, R (V.4.0.3) and Stata (V.17), were used to conduct our analysis.

    Patient and public involvement

    This study was based on secondary data analysis, so there was no direct patient and public involvement.

    Results

    Table 3 provides an overview of the demographic characteristics of the mothers. Most mothers reside in rural areas, accounting for 65.6% of the sample. The highest percentage of mothers falls within the age group of 20–24 years, constituting 35.4%. In terms of education, 53.1% of mothers have completed secondary education. The majority of households (87.9%) have a male household head.

    View this table:
    Table 3

    Frequency distribution of selected socioeconomic and maternal healthcare characteristics

    Regarding employment status, 62.5% of mothers do not have work. Approximately half of the mothers (50.3%) opted for institutional delivery. A significant proportion of mothers (91.9%) had access to ANC care, and 83.2% received care from qualified providers. However, 64% of mothers did not receive the required ANC.

    Furthermore, 75.6% of mothers did not receive adequate care. The healthcare decisions for 64.6% of mothers were made by their husbands. Lastly, 70.8% of mothers had their first birth between the age of 20 and 34 years.

    Table 4 shows the association between the percentage distribution and adequate care of mothers, which was related to Bangladesh’s sociodemographic characteristics. It presented the factors significantly associated (p<0.001, or p<0.01, or p<0.05) with adequate care, which were residence, division, education, wealth status, religion, working status, healthcare decision and age at birth.

    View this table:
    Table 4

    Association between adequate maternal healthcare with selected socioeconomic healthcare

    Access to adequate maternal healthcare significantly differs by the mothers’ residence.

    Almost 36.5% of mothers from urban areas got adequate maternal healthcare and only half (18.1%) in rural areas.

    Moreover, a significant relationship was found between division and adequate maternal healthcare in Bangladesh. Mothers from Dhaka (31.7%) and Khulna (31.1%) got the highest maternal care among all divisions. Approximately 20% of mothers from Barisal got adequate maternal healthcare. However, in Mymensingh, 18.7% and in Sylhet, 18.3% of mothers got adequate care.

    Table 4 shows the positively significant association between adequate maternal healthcare and respondents’ education. It was prominent that mothers with higher education (47.3%) got adequate maternal healthcare. Moreover, 21.1% of mothers with secondary and 10.1% of mothers with primary education got adequate maternal healthcare, respectively. Among the mothers with no education, only 6.7% got adequate maternal healthcare.

    Again, wealth status affected adequate maternal healthcare in Bangladesh, where almost 51.1% of mothers from the richest family, 28.6% from richer family and 22.5% from middle-income family got adequate maternal healthcare. Among the poorer and poorest mothers, 12.1% and 8.5% got adequate maternal healthcare, respectively. On top of that, the percentage of adequate care received by working mothers (20.1%) is lower than that received by non-working mothers (27.0%). Mothers who gave birth in middle age got the highest maternal healthcare (25.6%), and this was found to have significant relation.

    In terms of healthcare decisions, it was observed that there was a significant association between adequate maternal healthcare with respondents’ healthcare decisions. Adequate maternal healthcare was observed when the decision was taken by only the respondent (25.1%), but if this decision was made jointly (respondent as well as the husband), then the percentage of adequate maternal healthcare increased (approximately 26%).

    HOI, D-index and coverage (C) of maternal healthcare in Bangladesh are presented in table 5. The highest coverage rate and HOI were found for the third indicator of access to ANC care. The highest access to ANC means most of the mothers can access ANC. The same indicator’s dissimilarity (D) value is lower among all five indicators (3.3). Among the maternal healthcare opportunities, access to medically trained persons who provided ANC also has a high coverage rate (C=83.2) and HOI (77.5). Similarly, there was less inequality in the access to this opportunity (D=6.8).

    View this table:
    Table 5

    Opportunity and inequality in maternal healthcare

    Both ‘access to minimum required ANC visits’ (C=36.0; HOI=29.7) and ‘access to institutional delivery’ (C=50.3; HOI=40.9) exhibited significantly lower coverage rates than the preceding two opportunities. The D-indices for ‘access to minimum required ANC visits’ and ‘access to institutional delivery’ were 17.3 and 18.6, respectively. The composite indicator, that is, adequate maternal healthcare, presented the lowest coverage rate as well as opportunity index (approximately 24% with HOI=17.2). Naturally, the dissimilarity rate was highest (29.6%).

    The decomposition of inequality of maternal healthcare (table 6) reveals that it is the household wealth status that contributes much more inequality to accessing the adequate maternal healthcare services (41.4%), such as receiving at least four ANC visits (39.7%), access to proper ANC (50.7% and 44.0%) and health facility birth (43.4%). Maternal educational status contributes as the second highest inequality in accessing adequate maternal healthcare (29.5%). For access to at least four ANC visits, maternal education contributes 31.4% of the total inequality; for access to ANC from qualified staff, maternal education contributes 27.2% of the total inequality; for access to ANC, maternal education contributes 34.8% of the total inequality; and for access to healthcare delivery, maternal education contributes 27.4% of the total inequality. Division contributes the lowest inequality among factors included in this study.

    View this table:
    Table 6

    Decomposition of inequality of maternal healthcare

    Discussion

    The present study was conducted to investigate the inequalities in access to maternal healthcare services in Bangladesh using a large nationally representative dataset while expanding on HOI and using Shapley’s decomposition technique. From the opportunity index analysis, it is indicative that the coverage of ANC and ANC from skilled health personnel was high, whereas adequate maternal healthcare and having attended at least four ANC visits had the lowest coverage. Nonetheless, the highest dissimilarity was reported in the dimension of adequate maternal care, indicating that there is wide inequality in receiving adequate maternal care in Bangladesh.

    It is evident from the decomposition analysis that the factors that contributed the most to inequalities across all the five maternal healthcare opportunities were wealth index, education and place of residence. The findings correlate with evidence from previous studies conducted in Bangladesh,15 Sierra Leone,26 Indonesia27 and Togo.28 A plausible explanation for the contribution of wealth status to inequalities in access to maternal healthcare services could be explained from the perspective that women of higher wealth status often have a higher likelihood of visiting a hospital and, when necessary, pay for both the transport cost and the actual healthcare services compared with those from poorer wealth index.28 29 This implies that for Bangladesh to be able to improve women’s accessibility to maternal healthcare services, pro-poor policies and interventions would have to be instituted to bridge the existing economic inequality gap.

    The findings that education is a major contributor to inequality in terms of accessibility to maternal healthcare services could be explained from different perspectives. First, education has been found to be significantly correlated with higher likelihood of women’s autonomy and empowerment.30 31 This empowerment allows women to take critical healthcare decisions such as decisions to deliver at the health facility, receive ANC and receive the recommended number of ANC visits. Another perspective to this observation could be that educated women tend to be more self-sufficient in their finances and may have the economic resources to pay for maternal healthcare when necessary.30 32 We also postulate that women who have received formal education may have access to varied sources of health information and better understand the need to seek maternal healthcare services and even request services when healthcare providers do not offer that to them.

    The third major contributor to inequalities in accessibility to maternal healthcare in Bangladesh was the place of residence. Similarly, Atake28 and Zere et al29 have also reported that there are significant rural–urban inequalities in the accessibility to maternal healthcare services, with those residing in rural areas being the most disadvantaged. This observation could be due to the better transportation infrastructure and adequately staffed and well-equipped health facilities in urban areas compared with rural areas.28 Another possible explanation could be that the nearest health facility to women in rural areas may be distant from residents.33 Hence, making maternal healthcare services accessible to rural-dwelling women is challenging. This result is a call for aggressive policies and interventions to target rural-dwelling women for maternal healthcare services. Practically, the findings could inform the implementation of interventions to increase the availability and proximity of primary healthcare facilities to women in rural areas.

    Strengths and limitations

    The present study has several limitations that must be considered in the interpretation of the findings. Given that the study relied on data from the BDHS that uses cross-sectional design, the inequalities observed cannot be interpreted as causal inferences. Longitudinal studies would be needed to establish causality in the factors that contribute to inequalities in accessibility to maternal healthcare services. Also, the questions on adequate maternal healthcare, ANC, ANC from skilled personnel and delivery at the health facility were self-reported. Hence, there is the possibility of recall and social desirability bias. Moreover, residual factors such as community norms and cultural beliefs were not available in the BDHS; hence, we are unable to test how those contribute to the observed inequalities. Notwithstanding the limitations, there are some strengths that are noteworthy. The use of BDHS provided a large nationally representative dataset that can be based on to generalise the findings to the Bangladeshi women population and other resource-constrained settings with similar contextual characteristics such as Bangladesh. Also, the use of HOI, D-index and decomposing technique was appropriate for understanding the inequalities in accessibility to maternal healthcare services.

    Conclusion

    The study concludes that attaining adequate maternal healthcare had the lowest coverage and widest dissimilarity. We also conclude that wealth index, education and place of residence are the major factors that contribute to inequalities in accessibility to maternal healthcare services in Bangladesh. These findings underscore a need for pro-poor interventions to narrow the economic inequalities between the poor and rich in terms of accessibility to maternal healthcare services. Also, the results point to the need for the Bangladeshi government and its health department to strengthen their commitment to improving female education. Additionally, there is a need to invest in initiatives that would bring maternal healthcare services closer to women residing in rural areas.

    Data availability statement

    Data are available upon reasonable request. Data are available in a public, open-access repository. Data are available upon reasonable request at https://dhsprogram.com/data/available-datasets.cfm.

    Ethics statements

    Patient consent for publication

    Ethics approval

    The ethical approval, participant consent and permission for the primary survey were obtained by the National Institute of Population Research and Training (NIPORT) and ICF. MEASURE DHS authorised and granted secondary use of the survey data for the present analysis. Since the data were publicly available without any personal identifier, ethical approval was not required for the current study.

    Acknowledgments

    The authors are grateful to MEASURE DHS (Demographic and Health Surveys) for making data available for this study.

    References

    1. ↵
      1. WHO
      . Trends in maternal mortality: 1990-2015: estimates from WHO, UNICEF, UNFPA, world bank group and the United Nations population division. 2015.
    2. ↵
      1. Dzomeku VM,
      2. Duodu PA,
      3. Okyere J, et al
      . Prevalence, progress, and social inequalities of home deliveries in Ghana from 2006 to 2018: insights from the multiple indicator cluster surveys. BMC Pregnancy Childbirth 2021;21:518. doi:10.1186/s12884-021-03989-x
    3. ↵
      1. Kyei-Nimakoh M,
      2. Carolan-Olah M,
      3. McCann TV
      . Access barriers to obstetric care at health facilities in sub-Saharan Africa-a systematic review. Syst Rev 2017;6:110. doi:10.1186/s13643-017-0503-x
    4. ↵
      1. Nuamah GB,
      2. Agyei-Baffour P,
      3. Mensah KA, et al
      . Access and utilization of maternal Healthcare in a rural district in the forest belt of Ghana. BMC Pregnancy Childbirth 2019;19:6. doi:10.1186/s12884-018-2159-5
    5. ↵
      1. Ahmed F,
      2. Oni FA,
      3. Hossen SS
      . Does gender inequality matter for access to and utilization of maternal Healthcare services in Bangladesh PLoS One 2021;16:e0257388. doi:10.1371/journal.pone.0257388
    6. ↵
      1. WHO
      . Maternal mortality. 2019. Available: https://www.who.int/news-room/fact-sheets/detail/maternal-mortality [Accessed 20 Jun 2022].
    7. ↵
      1. Patrick M,
      2. Zaman MSU,
      3. Afzal G, et al
      . Factors that affect maternal mortality in Rwanda: A comparative study with India and Bangladesh. Comput Math Methods Med 2022;2022:1940188. doi:10.1155/2022/1940188
    8. ↵
      1. Kruk ME,
      2. Gage AD,
      3. Arsenault C, et al
      . High-quality health systems in the sustainable development goals era: time for a revolution. The Lancet Global Health 2018;6:e1196–252. doi:10.1016/S2214-109X(18)30386-3
      OpenUrl
    9. ↵
      1. Yaya S,
      2. Bishwajit G,
      3. Shah V
      . Wealth, education and urban–rural inequality and maternal Healthcare service usage in Malawi. BMJ Glob Health 2016;1:e000085. doi:10.1136/bmjgh-2016-000085
    10. ↵
      1. Okoli C,
      2. Hajizadeh M,
      3. Rahman MM, et al
      . Geographical and socioeconomic inequalities in the utilization of maternal Healthcare services in Nigeria: 2003-2017. BMC Health Serv Res 2020;20:849. doi:10.1186/s12913-020-05700-w
    11. ↵
      1. Mishra PS,
      2. Pautunthang N,
      3. Marbaniang SP, et al
      . Geographical divide led inequality in Accessing maternal Healthcare services between hills and valley regions of Manipur state, India. Clinical Epidemiology and Global Health 2021;11:100744. doi:10.1016/j.cegh.2021.100744
      OpenUrl
    12. ↵
      1. Pulok MH,
      2. Uddin J,
      3. Enemark U, et al
      . Socioeconomic inequality in maternal Healthcare: an analysis of regional variation in Bangladesh. Health Place 2018;52:205–14. doi:10.1016/j.healthplace.2018.06.004
      OpenUrlPubMed
    13. ↵
      1. Anwar I,
      2. Nababan HY,
      3. Mostari S, et al
      . Trends and inequities in use of maternal health care services in Bangladesh, 1991-2011. PLoS One 2015;10:e0120309. doi:10.1371/journal.pone.0120309
    14. ↵
      1. Kabir MR
      . Adopting Andersen’s behavior model to identify factors influencing maternal Healthcare service utilization in Bangladesh. PLoS One 2021;16:e0260502. doi:10.1371/journal.pone.0260502
    15. ↵
      1. Di Novi C,
      2. Thakare H
      . Inequality of opportunity in Accessing maternal and newborn Healthcare services: evidence from the Bangladesh demographic and health survey. Soc Indic Res 2022:1–25. doi:10.1007/S11205-022-03004-6/TABLES/7
    16. ↵
      1. NIPORT ICF
      . Bangladesh demographic and health survey 2017-18. Natl Inst Popul Res Train 2020:1–511.
    17. ↵
      1. Pons-Duran C,
      2. Lucas A,
      3. Narayan A, et al
      . Inequalities in sub-Saharan African women’s and girls’ health opportunities and outcomes: evidence from the demographic and health surveys. J Glob Health 2019;9:010410. doi:10.7189/jogh.09.010410
    18. ↵
      1. Molinas Vega JR,
      2. Paes de Barros R,
      3. Chanduvi JS, et al
      . Do our children have a chance? 2011. doi:10.1596/978-0-8213-8699-6
    19. ↵
      1. Khan MdN,
      2. Kumar P,
      3. Rahman MdM, et al
      . Inequalities in utilization of maternal reproductive health care services in urban Bangladesh: A population-based study. SAGE Open 2020;10:215824402091439. doi:10.1177/2158244020914394
      OpenUrl
    20. ↵
      1. Saha S,
      2. Mubarak M,
      3. Jarl J
      . What socioeconomic factors are associated with different levels of Antenatal care visits in Bangladesh? A behavioral model. Health Care Women Int 2017;38:2–16. doi:10.1080/07399332.2016.1217864
      OpenUrl
    21. ↵
      1. Methun MIH,
      2. Haq I,
      3. Uddin MSG, et al
      . Socioeconomic correlates of adequate maternal care in Bangladesh: analysis of the Bangladesh demographic and health survey 2017-18. Biomed Res Int 2022;2022:8027712. doi:10.1155/2022/8027712
    22. ↵
      1. Sanoussi Y
      . Measurement and analysis of inequality of opportunity in access of maternal and child health care in Togo. BMC Health Serv Res 2017;17(Suppl 2):699. doi:10.1186/s12913-017-2647-8
    23. ↵
      1. Ferreira FHG,
      2. Molinas Vega JR,
      3. Paes de Barros R, et al
      . Measuring inequality of opportunities in Latin America and the Caribbean. In: Measuring inequality of opportunities in latin america and the caribbean. Washingt. New York: World Bank Palgrave Macmillan, 2008. doi:10.1596/978-0-8213-7745-1
    24. ↵
      1. Roser M,
      2. Ritchie H
      . Maternal mortality. In: Our World Data. 2013.
    25. ↵
      1. Aran MA,
      2. Ersado L
      . Inequality of opportunity in access to basic services among Egyptian children. SSRN Journal July 8, 2013. doi:10.2139/ssrn.2292461
    26. ↵
      1. Tsawe M,
      2. Susuman AS
      . Examining inequality of opportunity in the use of maternal and reproductive health interventions in Sierra Leone. J Public Health (Oxf) 2020;42:254–61. doi:10.1093/pubmed/fdz023
      OpenUrl
    27. ↵
      1. Nababan HY,
      2. Hasan M,
      3. Marthias T, et al
      . Trends and inequities in use of maternal health care services in Indonesia, 1986–2012. Int J Womens Health 2018;10:11–24. doi:10.2147/IJWH.S144828
      OpenUrlPubMed
    28. ↵
      1. Atake E-H
      . Socio-economic inequality in maternal health care utilization in sub-Saharan Africa: evidence from Togo. Int J Health Plann Manage 2021;36:288–301. doi:10.1002/hpm.3083
      OpenUrlPubMed
    29. ↵
      1. Zere E,
      2. Oluwole D,
      3. Kirigia JM, et al
      . Inequities in skilled attendance at birth in Namibia: A decomposition analysis. BMC Pregnancy Childbirth 2011;11:1–10.:34. doi:10.1186/1471-2393-11-34
      OpenUrlCrossRefPubMed
    30. ↵
      1. Seidu A-A,
      2. Aboagye RG,
      3. Okyere J, et al
      . Women’s autonomy in household decision-making and safer sex negotiation in sub-Saharan Africa: an analysis of data from 27 demographic and health surveys. SSM - Population Health 2021;14:100773. doi:10.1016/j.ssmph.2021.100773
      OpenUrl
    31. ↵
      1. Acharya DR,
      2. Bell JS,
      3. Simkhada P, et al
      . Women’s autonomy in household decision-making: A demographic study in Nepal. Reprod Health 2010;7:1–12.:15. doi:10.1186/1742-4755-7-15
      OpenUrlCrossRefPubMed
    32. ↵
      1. Grown C,
      2. Gupta GR,
      3. Pande R
      . Taking action to improve women’s health through gender equality and women’s empowerment. Lancet 2005;365:541–3. doi:10.1016/S0140-6736(05)17872-6
      OpenUrlCrossRefPubMedWeb of Science
    33. ↵
      1. Chowdhury ME,
      2. Biswas TK,
      3. Rahman M, et al
      . Use of a geographic information system to assess accessibility to health facilities providing emergency obstetric and newborn care in Bangladesh. Int J Gynecol Obstet 2017;138:164–70. doi:10.1002/ijgo.12196
      OpenUrlPubMed
      1. National Institute of Population Research and Training, ICF
      . Bangladesh demographic and health survey 2017-18. 2020. Available: https://dhsprogram.com/publications/publication-FR344-DHS-Final-Reports.cfm

    Footnotes

    • Contributors MIHM and SR had the original idea for this study. MIHM, IH and MIH made the statistical analysis. MIHM, BOA, JO, SSU and MKH contributed to the writing, editing and finalising the manuscript. All authors read and approved the final manuscript.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests None declared.

    • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

    • Provenance and peer review Not commissioned; externally peer reviewed.