Inequalities in maternal health care utilization in Benin: A population based cross-sectional study

BMC Pregnancy and Childbirth, Volume 18, No. 1, Year 2018

Interpretation

Background: Ensuring equitable access to maternal health care including antenatal, delivery, postnatal services and fertility control methods, is one of the most critical challenges for public health sector. There are significant disparities in maternal health care indicators across many geographical locations, maternal, economic, socio-demographic factors in many countries in sub-Sahara Africa. In this study, we comparatively explored the utilization level of maternal health care, and examined disparities in the determinants of major maternal health outcomes. Methods: This paper used data from two rounds of Benin Demographic and Health Survey (BDHS) to examine the utilization and disparities in factors of maternal health care indicators using logistic regression models. Participants were 17,794 and 16,599 women aged between15-49years in 2006 and 2012 respectively. Women’s characteristics were reported in percentage, mean and standard deviation. Results: Mean (±SD) age of the participants was 29.0 (±9.0) in both surveys. The percentage of at least 4 ANC visits was approximately 61% without any change between the two rounds of surveys, facility based delivery was 93.5% in 2012, with 4.9% increase from 2006; postnatal care was currently 18.4% and contraceptive use was estimated below one-fifth. The results of multivariable logistic regression models showed disparities in maternal health care service utilization, including antenatal care, facility-based delivery, postnatal care and contraceptive use across selected maternal factors. The current BHDS showed age, region, religion were significantly associated with maternal health care services. Educated women, those from households of high wealth index and women currently working were more likely to utilize maternal health care services, compared to women with no formal education, from poorest households or not currently employed. Women who watch television (TV) were 1.31 (OR=1.31; 95% CI=1.13-1.52), 1.69 (OR=1.69; 95% CI=1.20-2.37) and 1.38 (OR=1.38; 95% CI=1.16-1.65) times as likely to utilize maternal health care services after adjusting for other covariates. Conclusion: The findings would guide stakeholders to address inequalities in maternal health care services. More so, health care programmes and policies should be strengthened to enhance accessibility as well as improve the utilization of maternal care services, especially for the disadvantaged, uneducated and those who live in hard-to-reach rural areas in Benin. The Benin government needs to create strategies that cover both the supply and demand side factors at attain the universal health coverage. Data for this study were derived from two rounds of Demographic and Health Survey in Benin that provided information on antenatal care, institutional delivery and contraceptive use. The datasets have one record for every eligible woman as defined by the household schedule. The questionnaire contains all the data collected from the individual woman for whom information on antenatal care, delivery and contraceptive usage and some variables from the household were elicited. The 2006 and 2012 Benin Demographic and Health Survey (BDHS) data contains 17,794 and 16,599 cases (units of analysis), which in this file is the woman. BDHS performed cross-sectional analyses using nationally representative data, to collect information on demographic, health, and nutrition indicators. The survey is majorly funded by the United States Agency for International Development (USAID). The two rounds of BDHS utilized a multi-stage, stratified sampling design, with households as the sampling unit. Within each sample household, all eligible women were interviewed [20]. In this study, we used four outcome measures of maternal health care utilization extracted from the BDHS. Firstly, we derived the; “number of antenatal care (ANC) visits during pregnancy”, this was grouped as 4 or more ANC visits vs below 4 ANC visits. ANC visits is a measure of skilled pregnancy care received by women during most recent pregnancy. Secondly, we extracted the “place of delivery (home vs health facility)”. This was measured as a binary outcome for 1, if a woman delivered in a health facility (where skilled delivery attention is available) and 0, if otherwise. In addition, postnatal care was measured by “respondents health’s checked after discharge/delivery at home” Lastly, women’s “contraceptive use”; was obtained as binary indicator taking 1 if the “woman ever used a contraceptive method” and 0, if otherwise. The utilization of ANC visits, facility-based delivery and contraceptive use are known to depend on a set of determinants, such as demographic, economic, other proximate and social factors. Empirical literature on the factors pertinent to maternal health care services basically helped to select the variables of study. These variables age of individual woman (15–19, 20–24, 25–29, 30–34, 35–39, 40–44 and 45–49 year), geographical region (Alibori, Atacora, Atlantique, Borgou, Collines, Couffo, Donga, Littoral, Mono, Queme, Plateau and Zou), type of residence (rural vs urban). Educational attainment was categorized as those having no formal education, primary, secondary and higher education. Religious beliefs included; Christianity, Islam, traditional and other religion, while access to health information was measured using frequency of reading newspaper or magazine, listening to radio and watching TV. The wealth scores is obtained by principal components analysis, based on a list of household assets as specified by DHS, which include, number of household members, wall and roof materials, floor types, access to potable water and sanitation, type of cooking fuel, ownership of television, radio, motorcycle, refrigerator amongst others. Based on the weighted wealth scores, households were grouped into five wealth quintiles; poorest, poorer, middle, richer and richest. Furthermore, parity was measured by the number of children ever born by each individual woman; categorized as 1–4 and > 4 children. We did the analyses using publicly available data from demographic health surveys. Ethical procedures were the responsibility of the institutions that commissioned, funded, or managed the surveys. All DHS surveys are approved by ICF international as well as an Institutional Review Board (IRB) in respective country to ensure that the protocols are in compliance with the U.S. Department of Health and Human Services regulations for the protection of human subjects. Summary statistics including percentage and means (±standard deviation) were used to examine the distribution of socio-demographic, economic distal and proximate maternal characteristics. To adjust for data representation, we used complex survey module (svyset) for all analyses to account for clustering, stratification and sample weight. In addition, the percentages of outcome variables were presented in bar chart. The factors associated with ANC visits, facility-based delivery, postnatal care and contraceptive use were examined using logistic regression models. The bivariate analysis conducted to examine the factors that were added in the multivariable regression models involved a simple regression with each explanatory variable. Therefore, factors, which were statistically significant in the crude regression models, were added in the multivariable regression models to adjust for possible confounders. An α level of 0.05 was considered statistically significant. All analyses were conducted using STATA 14.0.

AI Digest

Study Justification:

– Ensuring equitable access to maternal health care is a critical challenge for the public health sector.
– Significant disparities in maternal health care indicators exist across geographical locations, maternal, economic, and socio-demographic factors in many countries in sub-Saharan Africa.
– This study aims to explore the utilization level of maternal health care and examine disparities in the determinants of major maternal health outcomes in Benin.

Highlights:

– The study used data from two rounds of the Benin Demographic and Health Survey (BDHS) to examine maternal health care utilization and disparities.
– The percentage of at least 4 antenatal care (ANC) visits remained around 61% between 2006 and 2012.
– Facility-based delivery increased from 93.5% in 2006 to 98.4% in 2012.
– Postnatal care utilization was 18.4%.
– Contraceptive use was estimated to be below one-fifth.
– Disparities in maternal health care utilization were found across selected maternal factors, including age, region, religion, education, wealth index, employment status, and exposure to media.

Recommendations:

– Stakeholders should address inequalities in maternal health care services.
– Health care programs and policies should be strengthened to enhance accessibility and improve utilization, especially for disadvantaged, uneducated, and rural women.
– The Benin government needs to create strategies that cover both the supply and demand side factors to achieve universal health coverage.

Key Role Players:

– Ministry of Health: Responsible for implementing and coordinating maternal health care programs and policies.
– Non-governmental organizations (NGOs): Provide support and resources for improving maternal health care services.
– Health care providers: Deliver maternal health care services and ensure quality care.
– Community leaders and traditional birth attendants: Play a role in promoting awareness and utilization of maternal health care services.
– Media organizations: Contribute to disseminating information and raising awareness about maternal health care.

Cost Items for Planning Recommendations:

– Training and capacity building for health care providers.
– Infrastructure development and improvement of health facilities.
– Outreach programs and community mobilization.
– Information, education, and communication campaigns.
– Monitoring and evaluation systems.
– Research and data collection.
– Collaboration and coordination efforts between stakeholders.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is relatively strong, but there are a few areas for improvement. The study utilized data from two rounds of a nationally representative survey, which provides a robust sample size. The logistic regression models were used to examine the utilization and disparities in maternal health care indicators, which adds statistical rigor to the analysis. However, the abstract could be improved by providing more specific information about the methodology, such as the sampling design and the variables included in the regression models. Additionally, it would be helpful to include the key findings of the study, such as the magnitude of the disparities and the factors that were found to be significantly associated with maternal health care utilization. This would provide a clearer understanding of the study’s implications and potential actionable steps to address the identified inequalities.

Abstract

Data for this study were derived from two rounds of Demographic and Health Survey in Benin that provided information on antenatal care, institutional delivery and contraceptive use. The datasets have one record for every eligible woman as defined by the household schedule. The questionnaire contains all the data collected from the individual woman for whom information on antenatal care, delivery and contraceptive usage and some variables from the household were elicited. The 2006 and 2012 Benin Demographic and Health Survey (BDHS) data contains 17,794 and 16,599 cases (units of analysis), which in this file is the woman. BDHS performed cross-sectional analyses using nationally representative data, to collect information on demographic, health, and nutrition indicators. The survey is majorly funded by the United States Agency for International Development (USAID). The two rounds of BDHS utilized a multi-stage, stratified sampling design, with households as the sampling unit. Within each sample household, all eligible women were interviewed [20]. In this study, we used four outcome measures of maternal health care utilization extracted from the BDHS. Firstly, we derived the; “number of antenatal care (ANC) visits during pregnancy”, this was grouped as 4 or more ANC visits vs below 4 ANC visits. ANC visits is a measure of skilled pregnancy care received by women during most recent pregnancy. Secondly, we extracted the “place of delivery (home vs health facility)”. This was measured as a binary outcome for 1, if a woman delivered in a health facility (where skilled delivery attention is available) and 0, if otherwise. In addition, postnatal care was measured by “respondents health’s checked after discharge/delivery at home” Lastly, women’s “contraceptive use”; was obtained as binary indicator taking 1 if the “woman ever used a contraceptive method” and 0, if otherwise. The utilization of ANC visits, facility-based delivery and contraceptive use are known to depend on a set of determinants, such as demographic, economic, other proximate and social factors. Empirical literature on the factors pertinent to maternal health care services basically helped to select the variables of study. These variables age of individual woman (15–19, 20–24, 25–29, 30–34, 35–39, 40–44 and 45–49 year), geographical region (Alibori, Atacora, Atlantique, Borgou, Collines, Couffo, Donga, Littoral, Mono, Queme, Plateau and Zou), type of residence (rural vs urban). Educational attainment was categorized as those having no formal education, primary, secondary and higher education. Religious beliefs included; Christianity, Islam, traditional and other religion, while access to health information was measured using frequency of reading newspaper or magazine, listening to radio and watching TV. The wealth scores is obtained by principal components analysis, based on a list of household assets as specified by DHS, which include, number of household members, wall and roof materials, floor types, access to potable water and sanitation, type of cooking fuel, ownership of television, radio, motorcycle, refrigerator amongst others. Based on the weighted wealth scores, households were grouped into five wealth quintiles; poorest, poorer, middle, richer and richest. Furthermore, parity was measured by the number of children ever born by each individual woman; categorized as 1–4 and > 4 children. We did the analyses using publicly available data from demographic health surveys. Ethical procedures were the responsibility of the institutions that commissioned, funded, or managed the surveys. All DHS surveys are approved by ICF international as well as an Institutional Review Board (IRB) in respective country to ensure that the protocols are in compliance with the U.S. Department of Health and Human Services regulations for the protection of human subjects. Summary statistics including percentage and means (±standard deviation) were used to examine the distribution of socio-demographic, economic distal and proximate maternal characteristics. To adjust for data representation, we used complex survey module (svyset) for all analyses to account for clustering, stratification and sample weight. In addition, the percentages of outcome variables were presented in bar chart. The factors associated with ANC visits, facility-based delivery, postnatal care and contraceptive use were examined using logistic regression models. The bivariate analysis conducted to examine the factors that were added in the multivariable regression models involved a simple regression with each explanatory variable. Therefore, factors, which were statistically significant in the crude regression models, were added in the multivariable regression models to adjust for possible confounders. An α level of 0.05 was considered statistically significant. All analyses were conducted using STATA 14.0.

Materials

N/A

Innovations

The study “Inequalities in maternal health care utilization in Benin: A population based cross-sectional study” provides several recommendations to improve access to maternal health care. These recommendations can be developed into innovations to address the disparities in maternal health care utilization in Benin. Here are some possible innovations based on the study’s recommendations:

1. Mobile Health Clinics: Implementing mobile health clinics that travel to rural and hard-to-reach areas can improve access to maternal health care services. These clinics can provide antenatal care, facility-based delivery, postnatal care, and contraceptive services to women who may have limited access to health facilities.

2. Telemedicine: Using telemedicine technologies, such as video consultations and remote monitoring, can help overcome geographical barriers and improve access to maternal health care. Women in remote areas can consult with healthcare providers and receive guidance and support throughout their pregnancy and postpartum period.

3. Community Health Workers: Training and deploying community health workers can help bridge the gap between healthcare facilities and communities. These workers can provide education, counseling, and basic maternal health care services to women in their own communities, improving access and reducing barriers.

4. Health Education Apps: Developing mobile applications that provide information and education on maternal health care can empower women with knowledge and help them make informed decisions about their health. These apps can include information on antenatal care, facility-based delivery, postnatal care, and contraceptive use.

5. Public-Private Partnerships: Collaborating with private healthcare providers and organizations can help expand access to maternal health care services. Public-private partnerships can leverage the resources and expertise of both sectors to improve service delivery and reach underserved populations.

6. Transportation Support: Providing transportation support, such as subsidized or free transportation services, can help overcome transportation barriers faced by women in accessing maternal health care services. This can include arranging transportation to and from health facilities for antenatal visits, delivery, and postnatal care.

These innovations can help address the specific barriers identified in the study and improve access to maternal health care services in Benin. It is important to tailor these innovations to the local context and involve stakeholders, including government agencies, healthcare providers, and community members, in their development and implementation.

AI Innovations Description

Based on the study “Inequalities in maternal health care utilization in Benin: A population based cross-sectional study,” the following recommendation can be developed into an innovation to improve access to maternal health:

1. Strengthening Health Care Programs and Policies: The study highlights the need to strengthen health care programs and policies to enhance accessibility and improve the utilization of maternal care services. This can be achieved by implementing targeted interventions that address the specific barriers faced by disadvantaged, uneducated, and rural women in accessing maternal health care.

2. Universal Health Coverage: The Benin government should create strategies that aim to achieve universal health coverage. This involves ensuring that all individuals, regardless of their socio-economic status or geographical location, have access to essential maternal health care services. This can be achieved through the expansion of health insurance coverage and the establishment of health facilities in hard-to-reach rural areas.

3. Education and Awareness: Promoting education and awareness about maternal health care is crucial in improving access. Efforts should be made to educate women and communities about the importance of antenatal care, facility-based delivery, postnatal care, and contraceptive use. This can be done through community-based education programs, health campaigns, and the use of various media platforms such as television, radio, and newspapers.

4. Addressing Socio-Demographic Factors: The study identifies several socio-demographic factors that influence maternal health care utilization, such as age, region, religion, and educational attainment. To improve access, interventions should be tailored to address these specific factors. For example, targeted programs can be implemented to reach younger women, women in rural areas, and women with lower levels of education.

5. Collaboration and Partnerships: Collaboration between government agencies, non-governmental organizations, and international partners is essential in developing and implementing innovative solutions to improve access to maternal health care. By working together, resources can be pooled, expertise can be shared, and comprehensive strategies can be developed to address the complex challenges faced in improving maternal health care access.

By implementing these recommendations, it is possible to develop innovative solutions that can significantly improve access to maternal health care in Benin and other similar contexts.

AI Innovations Methodology

To simulate the impact of the main recommendations on improving access to maternal health, the following methodology can be used:

1. Data Collection: Collect data on maternal health care indicators, such as antenatal care visits, facility-based delivery, postnatal care, and contraceptive use, from a representative sample of women in Benin. This data can be obtained through surveys or by accessing existing datasets, such as the Benin Demographic and Health Survey (BDHS).

2. Identify Disparities: Analyze the collected data to identify disparities in maternal health care utilization based on factors such as age, region, religion, educational attainment, and socio-economic status. This will help understand the specific barriers faced by different groups of women in accessing maternal health care.

3. Model Development: Develop a simulation model that incorporates the main recommendations mentioned in the abstract. This model should consider the potential impact of strengthening health care programs and policies, achieving universal health coverage, promoting education and awareness, addressing socio-demographic factors, and fostering collaboration and partnerships.

4. Parameter Estimation: Estimate the parameters of the simulation model based on available data and evidence from the literature. This may involve conducting statistical analyses, such as logistic regression models, to determine the associations between the main recommendations and maternal health care utilization.

5. Scenario Analysis: Conduct scenario analyses to simulate the impact of different combinations of the main recommendations on improving access to maternal health care. This can involve adjusting the parameters of the simulation model to reflect different levels of implementation and evaluating the resulting changes in maternal health care utilization.

6. Sensitivity Analysis: Perform sensitivity analyses to assess the robustness of the simulation results. This can involve varying the input parameters within plausible ranges to determine the extent to which the results are sensitive to changes in these parameters.

7. Interpretation and Reporting: Interpret the simulation results and report the findings in a clear and concise manner. This should include a discussion of the potential implications of the main recommendations on improving access to maternal health care in Benin, as well as any limitations or uncertainties associated with the simulation model.

By following this methodology, policymakers and stakeholders can gain insights into the potential impact of implementing the main recommendations on improving access to maternal health care in Benin. This can inform decision-making and help prioritize interventions that are most likely to have a positive effect on maternal health outcomes.

Author

Dima Health

Statistics:

Citations: 51

Identifiers:

DOI: 10.1186/s12884-018-1846-6

Research Areas:

Disparities, Environmental, Food Security, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health

Study Countries:

Benin

Study Design:

Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Female