Individual and contextual factors associated with maternal healthcare utilisation in Mali: A cross-sectional study using Demographic and Health Survey data

BMJ Open, Volume 12, No. 2, Year 2022

Interpretation

Objective We examined the national prevalence as well as the individual and contextual factors associated with maternal healthcare utilisation in Mali. Setting The study was conducted in Mali. Participants We analysed data on 6335 women aged 15-49 years from Mali’s 2018 Demographic and Health Survey. Outcome variable Maternal healthcare utilisation comprising antenatal care (ANC) attendant, skilled birth attendant (SBA), and postnatal care (PNC) attendant, was our outcome variable. Results Prevalence of maternal healthcare utilisation was 45.6% for ANC4+, 74.7% for SBA and 25.5% for PNC. At the individual level, ANC4 + and SBA utilisation increased with increasing maternal age, level of formal education and wealth status. Higher odds of ANC4 + was found among women who are cohabiting (adjusted OR (aOR)=2.25, 95% CI 1.16 to 4.37) and delivered by caesarean section (aOR=2.53, 95% CI 1.72 to 3.73), while women who considered getting money for treatment (aOR=0.72, 95% CI 0.60 to 0.88) and distance to health facility (aOR=0.73, 95% CI 0.59 to 0.90) as a big problem had lower odds. Odds to use PNC was higher for those who were working (aOR=1.22, 95% CI 1.01 to 1.48) and those covered by health insurance (aOR=1.87, 95% CI 1.36 to 2.57). Lower odds of SBA use were associated with having two (aOR=0.48, 95% CI 0.33 to 0.71), three (aOR=0.37, 95% CI 0.24 to 0.58), and four or more (aOR=0.38, 95% CI 0.24 to 0.59) children, and residing in a rural area (aOR=0.35, 95% CI 0.17 to 1.69). Listening to the radio and watching TV were associated with increased maternal healthcare utilisation. Conclusion The government should increase availability, affordability and accessibility to healthcare facilities by investing in health infrastructure and workforce to achieve Sustainable Development Goal 3.4 of reducing maternal morality to less than 70 deaths per 100 000 live births by 2030. It is important to ascertain empirically why PNC levels are astonishingly lower relative to ANC and SBA. We analysed a cross-sectional data from the 2018 DHS of Mali. The DHS is a nationally representative and comparative survey conducted in over 85 LMICs worldwide.27 A structured questionnaire was used to collect data from the respondents on health indicators such as maternal healthcare utilisation.27 The respondents were sampled using a two-stage cluster sampling technique. Detailed sampling technique has been highlighted in a study by Aliaga and Ruilin.28 In the present study, a total of 6335 women of reproductive age (15–49 years) were included in the analysis. The data set is freely available for download on the DHS platform.29 In drafting this manuscript, we relied on the Strengthening the Reporting of Observational Studies in Epidemiology statement guidelines.30 Mali is a West-African country with a population of 20 548 743.31 It has a pyramidal healthcare system, the community health system, requiring entry into the health system from community health centres.32 This decentralised system operates at five levels, namely national, regional, district, health area and community.32 The major healthcare financing mechanism is out-of-pocket payments for services including maternal healthcare services. Existing insecurities and internal displacement of people have also exacerbated inequalities in health infrastructure and access.33 No patients were involved in this study as we used secondary data. ANC, SBA and PNC were the outcome variables in this study. To assess ANC, the respondents were asked about the number of antenatal visits they made during their recent pregnancy. The response options recoded into 0–3=0 (<4 ANC attendance) and ≥4=1 (≥4 ANC attendance). With SBA, the respondents were asked ‘Who assisted (NAME) during delivery?’. Those whose response options included any category of health professionals were classified as ‘having SBA’ while those who were assisted by traditional birth attendants and others were grouped as ‘not having SBA’. PNC on the other hand was assessed using the question, ‘Did (NAME) go for postnatal checks within 2 months?’. The response options were 0=no; 1=yes; and 8=don’t know. Those whose response option was ‘don’t know’ were dropped. We, therefore, used the dichotomised responses in the final analysis. The coding and classification were informed by literature that used the DHS data sets.34–37 We considered 17 explanatory variables in this study. These variables were selected based on their availability in the DHS data sets as well as their significant association with the outcome variables in the study.34 38 39 The variables were ground into individual level (age of the respondent, educational level, marital status, religion, current working status, parity, national health insurance coverage, delivery by caesarean section, frequency of listening to radio, frequency of watching television, frequency of reading newspaper or magazine, getting medical help for self: permission to go; getting medical help for self: distance to health facility, and getting medical help for self: getting money for treatment) and contextual level (wealth index, place of residence and region). We maintained the existing coding in the DHS data set for current working status, national health insurance, delivery by caesarean section, frequency of listening to radio, frequency of watching television, frequency of reading newspaper/magazine, getting medical help for self: permission to go; getting medical help for self: distance to health facility, and getting medical help for self: getting money for treatment, wealth index, place of residence and region. The age of the respondent was recoded into ‘15–19’, ‘20–24’, ’25–29’, ’30–34’ and ‘35 and above’. The level of education of the respondent was recoded into ‘no education’, ‘primary’ and ‘secondary or higher’. Marital status was coded as ‘never married’, ‘married’, ‘cohabiting’ and ‘widowed or divorced or separated’. Religious affiliation was coded as ‘Christianity’, ‘Islamic’, ‘African Traditional or no religion or others’. Parity was coded as ‘one birth’, ‘two births’, ‘three births’ and ‘four or more births’. Stata software V.16.0 was used to perform the statistical analysis. All the analyses were weighted. We used percentages to summarise the prevalence of ANC, SBA and PNC as shown in figure 1. Later, cross-tabulation and χ2 tests were performed to examine the distribution of the outcome variables across the explanatory variables. Corresponding p values from the χ2 test were used to determine the statistically significant association between the outcome variables and the explanatory variables. All the variables that showed significance were placed in the regression model. We built four models under multilevel regression analysis to examine the association between each of the outcome variables and the explanatory variables. The first model (Model O) was fitted to show the variance in the outcome variables attributed to the clustering of the primary sampling units and the explanatory variables. Model I was fitted to include the individual-level variables against each of the outcome variables. Model II contained the contextual-level variables. Model III was fitted to include all the explanatory variables against each of the outcome variables. We used Akaike’s Information Criterion to test for model fitness and model comparison. The result of the regression analysis was presented using adjusted ORs (aORs) with their 95% CIs. We applied the women’s sample weights (v005/1000 000) to obtain unbiased estimates, according to the DHS guidelines and the Stata survey command ‘svy’ was used to adjust for the complex sampling structure of the data in all the analyses. Prevalence of maternal healthcare utilisation among women in Mali. ANC, antenatal care; PNC, postnatal care; SBA, skilled birth attendant. Since our analysis was based on publicly available data, no further ethical permission was necessary. Ethical guidelines regarding the usage of secondary data for publication were adhered to. Further information about DHS data usage and ethical standards are available at http://googl/ny8T6X.

AI Digest

Study Justification:

This study aimed to examine the prevalence of maternal healthcare utilization in Mali and identify individual and contextual factors associated with it. The justification for this study is to provide insights into the current state of maternal healthcare utilization in Mali and understand the factors that influence it. This information is crucial for policymakers and healthcare providers to develop targeted interventions and improve maternal healthcare services in the country.

Highlights:

– The prevalence of maternal healthcare utilization in Mali was found to be 45.6% for antenatal care (ANC4+), 74.7% for skilled birth attendant (SBA), and 25.5% for postnatal care (PNC).
– Individual factors such as maternal age, level of formal education, wealth status, cohabitation, and delivery by caesarean section were associated with higher utilization of ANC4+ and SBA.
– Factors such as considering getting money for treatment and distance to health facility as a big problem were associated with lower odds of ANC4+ utilization.
– Working status and health insurance coverage were associated with higher odds of PNC utilization.
– Having multiple children and residing in a rural area were associated with lower odds of SBA utilization.
– Listening to the radio and watching TV were associated with increased maternal healthcare utilization.

Recommendations:

Based on the findings of this study, the following recommendations can be made:

1. The government should invest in health infrastructure and workforce to increase the availability, affordability, and accessibility of healthcare facilities.
2. Efforts should be made to reduce financial barriers to maternal healthcare by improving health insurance coverage and addressing the issue of getting money for treatment.
3. Interventions should be targeted towards women in rural areas and those with multiple children to improve their access to skilled birth attendants.
4. Health promotion campaigns through radio and television should be encouraged to increase awareness and utilization of maternal healthcare services.

Key Role Players:

– Government health departments and ministries
– Healthcare providers and facilities
– Health insurance agencies
– Non-governmental organizations (NGOs) working in maternal healthcare
– Community leaders and organizations
– Media organizations for health promotion campaigns

Cost Items for Planning Recommendations:

1. Investment in health infrastructure: Construction and renovation of healthcare facilities, equipment, and supplies.
2. Workforce development: Training and recruitment of healthcare professionals, including doctors, nurses, midwives, and community health workers.
3. Health insurance coverage: Subsidies and financial support for expanding health insurance coverage for maternal healthcare services.
4. Health promotion campaigns: Production and dissemination of educational materials, radio and television advertisements, and community outreach programs.
5. Monitoring and evaluation: Data collection and analysis to assess the impact of interventions and make informed decisions for future planning.
Please note that the cost items provided are general categories and not actual cost estimates. Actual costs will vary based on the specific context and implementation strategies.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a cross-sectional study using nationally representative data, which provides a solid foundation. The study includes a large sample size and analyzes multiple individual and contextual factors associated with maternal healthcare utilization. However, the evidence is limited to associations and does not establish causality. To improve the strength of the evidence, future research could consider longitudinal designs to establish temporal relationships and conduct qualitative studies to gain a deeper understanding of the reasons behind the low postnatal care utilization relative to antenatal care and skilled birth attendance.

Abstract

We analysed a cross-sectional data from the 2018 DHS of Mali. The DHS is a nationally representative and comparative survey conducted in over 85 LMICs worldwide.27 A structured questionnaire was used to collect data from the respondents on health indicators such as maternal healthcare utilisation.27 The respondents were sampled using a two-stage cluster sampling technique. Detailed sampling technique has been highlighted in a study by Aliaga and Ruilin.28 In the present study, a total of 6335 women of reproductive age (15–49 years) were included in the analysis. The data set is freely available for download on the DHS platform.29 In drafting this manuscript, we relied on the Strengthening the Reporting of Observational Studies in Epidemiology statement guidelines.30 Mali is a West-African country with a population of 20 548 743.31 It has a pyramidal healthcare system, the community health system, requiring entry into the health system from community health centres.32 This decentralised system operates at five levels, namely national, regional, district, health area and community.32 The major healthcare financing mechanism is out-of-pocket payments for services including maternal healthcare services. Existing insecurities and internal displacement of people have also exacerbated inequalities in health infrastructure and access.33 No patients were involved in this study as we used secondary data. ANC, SBA and PNC were the outcome variables in this study. To assess ANC, the respondents were asked about the number of antenatal visits they made during their recent pregnancy. The response options recoded into 0–3=0 (<4 ANC attendance) and ≥4=1 (≥4 ANC attendance). With SBA, the respondents were asked ‘Who assisted (NAME) during delivery?’. Those whose response options included any category of health professionals were classified as ‘having SBA’ while those who were assisted by traditional birth attendants and others were grouped as ‘not having SBA’. PNC on the other hand was assessed using the question, ‘Did (NAME) go for postnatal checks within 2 months?’. The response options were 0=no; 1=yes; and 8=don’t know. Those whose response option was ‘don’t know’ were dropped. We, therefore, used the dichotomised responses in the final analysis. The coding and classification were informed by literature that used the DHS data sets.34–37 We considered 17 explanatory variables in this study. These variables were selected based on their availability in the DHS data sets as well as their significant association with the outcome variables in the study.34 38 39 The variables were ground into individual level (age of the respondent, educational level, marital status, religion, current working status, parity, national health insurance coverage, delivery by caesarean section, frequency of listening to radio, frequency of watching television, frequency of reading newspaper or magazine, getting medical help for self: permission to go; getting medical help for self: distance to health facility, and getting medical help for self: getting money for treatment) and contextual level (wealth index, place of residence and region). We maintained the existing coding in the DHS data set for current working status, national health insurance, delivery by caesarean section, frequency of listening to radio, frequency of watching television, frequency of reading newspaper/magazine, getting medical help for self: permission to go; getting medical help for self: distance to health facility, and getting medical help for self: getting money for treatment, wealth index, place of residence and region. The age of the respondent was recoded into ‘15–19’, ‘20–24’, ’25–29’, ’30–34’ and ‘35 and above’. The level of education of the respondent was recoded into ‘no education’, ‘primary’ and ‘secondary or higher’. Marital status was coded as ‘never married’, ‘married’, ‘cohabiting’ and ‘widowed or divorced or separated’. Religious affiliation was coded as ‘Christianity’, ‘Islamic’, ‘African Traditional or no religion or others’. Parity was coded as ‘one birth’, ‘two births’, ‘three births’ and ‘four or more births’. Stata software V.16.0 was used to perform the statistical analysis. All the analyses were weighted. We used percentages to summarise the prevalence of ANC, SBA and PNC as shown in figure 1. Later, cross-tabulation and χ2 tests were performed to examine the distribution of the outcome variables across the explanatory variables. Corresponding p values from the χ2 test were used to determine the statistically significant association between the outcome variables and the explanatory variables. All the variables that showed significance were placed in the regression model. We built four models under multilevel regression analysis to examine the association between each of the outcome variables and the explanatory variables. The first model (Model O) was fitted to show the variance in the outcome variables attributed to the clustering of the primary sampling units and the explanatory variables. Model I was fitted to include the individual-level variables against each of the outcome variables. Model II contained the contextual-level variables. Model III was fitted to include all the explanatory variables against each of the outcome variables. We used Akaike’s Information Criterion to test for model fitness and model comparison. The result of the regression analysis was presented using adjusted ORs (aORs) with their 95% CIs. We applied the women’s sample weights (v005/1000 000) to obtain unbiased estimates, according to the DHS guidelines and the Stata survey command ‘svy’ was used to adjust for the complex sampling structure of the data in all the analyses. Prevalence of maternal healthcare utilisation among women in Mali. ANC, antenatal care; PNC, postnatal care; SBA, skilled birth attendant. Since our analysis was based on publicly available data, no further ethical permission was necessary. Ethical guidelines regarding the usage of secondary data for publication were adhered to. Further information about DHS data usage and ethical standards are available at http://googl/ny8T6X.

Materials

Innovations

Based on the information provided, here are some potential innovations that could improve access to maternal health in Mali:

1. Mobile Health (mHealth) Solutions: Implementing mobile health technologies, such as text messaging and mobile apps, to provide pregnant women with important information about antenatal care, skilled birth attendance, and postnatal care. These technologies can also be used to send reminders and appointment notifications.

2. Community Health Workers: Training and deploying community health workers to provide maternal health services in rural areas where access to healthcare facilities is limited. These workers can provide antenatal care, assist with deliveries, and offer postnatal care services.

3. Telemedicine: Establishing telemedicine services to connect pregnant women in remote areas with healthcare professionals who can provide virtual consultations and guidance. This can help address the issue of distance to health facilities and improve access to skilled birth attendants.

4. Financial Support: Introducing financial support programs, such as conditional cash transfers or health insurance schemes, to alleviate the financial barriers that prevent women from seeking maternal healthcare services. This can help improve affordability and increase utilization rates.

5. Infrastructure Development: Investing in the development and improvement of healthcare infrastructure, including the construction of more health facilities and the provision of necessary medical equipment and supplies. This can help increase the availability and accessibility of maternal healthcare services.

6. Health Education and Awareness: Implementing comprehensive health education programs to raise awareness about the importance of maternal healthcare and address cultural and social barriers that may prevent women from seeking care. This can be done through community outreach programs, media campaigns, and educational materials.

It is important to note that the specific implementation and effectiveness of these innovations would require further research and evaluation.

AI Innovations Description

Based on the information provided, the following recommendation can be developed into an innovation to improve access to maternal health:

1. Increase availability, affordability, and accessibility to healthcare facilities: The government should invest in health infrastructure and workforce to ensure that healthcare facilities are readily available and easily accessible to pregnant women. This can include building more health centers, improving existing facilities, and ensuring that healthcare services are affordable for all women, especially those from low-income backgrounds.

2. Improve education and awareness: Implement educational programs and campaigns to raise awareness about the importance of maternal healthcare and the available services. This can include educating women and their families about the benefits of antenatal care, skilled birth attendance, and postnatal care. It is important to address any misconceptions or cultural barriers that may prevent women from seeking these services.

3. Address financial barriers: Develop innovative financing mechanisms, such as health insurance schemes or subsidies, to reduce the financial burden on women seeking maternal healthcare services. This can help to ensure that cost does not become a barrier to accessing necessary care.

4. Strengthen community-based healthcare: Enhance the community health system by training and empowering community health workers to provide basic maternal healthcare services. This can help to bridge the gap between healthcare facilities and remote or underserved areas, ensuring that women in these areas have access to essential care.

5. Utilize technology: Explore the use of technology, such as telemedicine or mobile health applications, to improve access to maternal healthcare services. This can include providing remote consultations, delivering health information through mobile apps, or using SMS reminders for antenatal and postnatal appointments.

6. Address cultural and social barriers: Work with community leaders, religious institutions, and local organizations to address cultural and social barriers that may prevent women from seeking maternal healthcare. This can involve sensitization programs, community dialogues, and engaging influential community members to promote the importance of maternal health.

By implementing these recommendations, it is possible to improve access to maternal healthcare services in Mali and reduce maternal mortality rates, ultimately contributing to the achievement of Sustainable Development Goal 3.4 of reducing maternal mortality to less than 70 deaths per 100,000 live births by 2030.

AI Innovations Methodology

Based on the information provided, here are some potential recommendations to improve access to maternal health in Mali:

1. Increase availability of healthcare facilities: The government should invest in improving health infrastructure by building more healthcare facilities, especially in rural areas where access is limited. This would ensure that pregnant women have nearby facilities to seek maternal healthcare services.

2. Improve affordability of healthcare services: Implement policies to make maternal healthcare services more affordable, such as providing subsidies or insurance coverage for pregnant women. This would help reduce financial barriers and encourage more women to seek antenatal, skilled birth, and postnatal care.

3. Enhance accessibility to healthcare facilities: Address the issue of distance to health facilities by establishing mobile clinics or outreach programs that bring maternal healthcare services closer to remote communities. This would make it easier for women living in rural areas to access the care they need.

4. Strengthen the healthcare workforce: Invest in training and deploying more skilled healthcare professionals, particularly midwives and obstetricians, to ensure that there are enough skilled birth attendants available to assist women during delivery. This would help improve the quality of care and reduce maternal mortality rates.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Define the indicators: Identify specific indicators that measure access to maternal health, such as the percentage of women receiving antenatal care, skilled birth attendance, and postnatal care.

2. Collect baseline data: Gather data on the current levels of access to maternal health services in Mali, using sources such as national surveys or health facility records.

3. Develop a simulation model: Create a mathematical or statistical model that incorporates the various factors influencing access to maternal health, including the individual and contextual factors identified in the study. This model should be able to simulate the impact of different interventions or recommendations on the indicators of access.

4. Input intervention scenarios: Input the recommended interventions into the simulation model, adjusting relevant parameters such as the number of healthcare facilities, affordability measures, accessibility initiatives, and healthcare workforce capacity.

5. Run simulations: Run the simulation model with different intervention scenarios to estimate the potential impact on access to maternal health. This could involve comparing the indicators of access between the baseline scenario and the intervention scenarios.

6. Analyze results: Analyze the simulation results to determine the potential effectiveness of the recommended interventions in improving access to maternal health. This could include assessing changes in the indicators of access, identifying key drivers of change, and evaluating the cost-effectiveness of the interventions.

7. Refine and iterate: Based on the simulation results, refine the interventions and model parameters as needed, and repeat the simulation process to further optimize the recommendations for improving access to maternal health.

It is important to note that the methodology for simulating the impact of recommendations may vary depending on the specific context and available data. The steps outlined above provide a general framework for conducting such simulations.

Author

Dima Health

Statistics:

Citations: 1

Identifiers:

DOI: 10.1136/bmjopen-2021-057681

Research Areas:

Community Interventions, Disparities, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants

Study Countries:

Mali

Study Design:

Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Female