Four out of ten married women utilized modern contraceptive method in Ethiopia: A Multilevel analysis of the 2019 Ethiopia mini demographic and health survey

PLoS ONE, Volume 17, No. 1 January 2022, Year 2022

Interpretation

Background Modern contraceptive method is a product or medical procedure that interferes with reproduction from acts of sexual intercourse. Globally in 2019, 44% of women of reproductive age were using a modern method of contraception but it was 29% in sub-Saharan Africa. Therefore, the main aim of this analysis was to assess the prevalence of modern contraceptive utilization and associated factors among married women in Ethiopia. Method The current study used the 2019 Ethiopia mini demographic and health survey dataset. Both descriptive and multilevel mixed-effect logistic regression analysis were done using STATA version 14. A p-value of less than 0.05 and an adjusted odds ratio with a 95% confidence interval were used to report statistically significant factors with modern contraceptive utilization. Result The overall modern contraceptive utilization among married women in Ethiopia was 38.7% (95% CI: 37.3% to 40.0%). Among the modern contraceptive methods, injectables were the most widely utilized modern contraceptive method (22.82%) followed by implants (9.65%) and pills (2.71%). Maternal age, educational level, wealth index, number of living children, number of births in the last three years, number of under 5 children in the household, religion, and geographic region were independent predictors of modern contraceptive utilization. Conclusion In the current study only four out of ten married non-pregnant women of reproductive age utilized modern contraceptive methods. Furthermore, the study has identified both individual and community-level factors that can affect the utilization of modern contraceptive methods by married women in the country. Therefore, concerned bodies need to improve access to reproductive health services, empower women through community-based approaches, and minimize region wise discrepancy to optimize the utilization. The study used the 2019 Ethiopia mini demographic and health survey (EMDHS) dataset. It is the second mini demographic and health survey which was conducted in March, 2019, to June, 2019 in Ethiopia. Ethiopia is divided into two administrative cities and nine regions. All married women in the reproductive age living in nine regions and two administrative cities of Ethiopia were included in the study. The EMDHS used a complete list of 149,093 enumeration areas (EAs) created for the upcoming Ethiopia population and housing census as a sampling frame. The frame comprises information about the EA location, type of residence (urban or rural), and estimated number of residential households. Accordingly, the sample was stratified and selected in two-stages [28]. Out of the total EAs, a total of 305 EAs (93 in urban areas and 212 in rural areas) were selected with probability proportional to EA size and with independent selection in each sampling stratum for the survey. Secondly, a fixed number of 30 households per cluster were selected with an equal probability systematic selection from the newly created household listing. Finally, the 2019 EMDHS survey covered 8,663 households out of the selected 8,794 households providing a response rate of 99%. About 8,885 women completed the interview from 16,583 women identified for the interview, yielding a response rate of 99%. According to the EMDHS report response rates were higher in rural than in urban areas [28]. The source population of this study was all married non-pregnant women who were in the reproductive age group and living in Ethiopia. Pregnant mothers and those who were not in union at the time of survey were excluded from the study. Hence, 4,983 married women data were extracted from the 2019 EMDHS datasets. Modern contraceptive utilization was the outcome variable of the study. Woman was considered as a “utilizer” if she had been utilizing any modern contraceptive methods such as oral contraceptives, male and female sterilization, intrauterine contraceptive device, injectables, implants, male and female condoms, lactational amenorrhea method, standard days method, and emergency contraception [4, 30] during the 2019 EMDHS survey period while woman who had been utilizing traditional, folkloric or no method was considered as a “non-utilizer”. Both the individual and community level explanatory variables were used to assess modern contraceptives utilized among women in childbearing age in the country. Maternal age, educational level of mother, wealth index, total children ever born, number of living children, births in the last three years, age of respondent at first birth, family size, number of under five children in household, and knowledge on modern contraceptive method. Community level explanatory variables include religion, region, and place of residence (Table 1). PCA: principal components analysis. The data were extracted, cleaned, re-coded, and analyzed using STATA version 14. Descriptive statistics were presented using graphs, tables and narrations. A multilevel mixed-effect logistic regression analysis, an advanced model, was used to overcome the violation of independence of observations and equal variance assumption of the traditional logistic regression model due to a hierarchical nature of DHS data. We first estimated an intercept-only model or the null model (with only the outcome variable). Secondly, we included all individual level factors in the model (model I). In the third stage, we constructed model II (fitted with community-level factors only) and finally model III was fitted with both individual and community-level factors. To examine clustering and the extent to which community-level factors explain the unexplained variance of the null model, the intraclass correlation coefficient (ICC) and a proportional change in variance (PCV) were checked. The model with the lowest deviance, model III, was selected as the best-fitted model for the analysis. Variance inflation factor (VIF) was done to test the existence of multicollinearity among the independent variables. Variables having a p-value of less than 0.2 in the bivariable analysis were selected as candidate variables for the multivariable mixed-effect logistic regression analysis. In the final model, a p-value of less than 0.05 and an adjusted odds ratio (AOR) with a 95% confidence interval (CI) were used to report statistically significant factors with modern contraceptive utilization among childbearing age women. This study used secondary data from demographic and health survey repositories. The survey data do not contain all identifying information. The MEASURE Demographic and Health Survey Program team allowed us to access the data upon sending an abstract of our study to an online request form http://www.measuredhsprogram.com.

AI Digest

Study Justification:

The study aimed to assess the prevalence of modern contraceptive utilization and associated factors among married women in Ethiopia. This is important because globally, only 44% of women of reproductive age were using a modern method of contraception in 2019, and in sub-Saharan Africa, the rate was even lower at 29%. Understanding the factors influencing contraceptive utilization in Ethiopia can help inform policies and interventions to improve access to reproductive health services and empower women.

Highlights:

– The overall modern contraceptive utilization among married women in Ethiopia was 38.7%.
– The most widely utilized modern contraceptive method was injectables (22.82%), followed by implants (9.65%) and pills (2.71%).
– Maternal age, educational level, wealth index, number of living children, number of births in the last three years, number of under 5 children in the household, religion, and geographic region were independent predictors of modern contraceptive utilization.

Recommendations:

– Improve access to reproductive health services: Policies and interventions should focus on increasing availability and affordability of modern contraceptive methods, particularly in rural areas.
– Empower women through community-based approaches: Efforts should be made to educate and empower women about their reproductive health rights and choices, including family planning.
– Minimize regional disparities: Addressing regional differences in contraceptive utilization can help ensure equitable access to reproductive health services across the country.

Key Role Players:

– Ministry of Health: Responsible for developing and implementing policies and programs related to reproductive health and family planning.
– Non-governmental organizations (NGOs): Involved in providing reproductive health services, education, and advocacy.
– Community health workers: Play a crucial role in delivering reproductive health services and educating women about contraceptive options.
– Health facilities: Provide access to modern contraceptive methods and counseling services.

Cost Items for Planning Recommendations:

– Training and capacity building for healthcare providers and community health workers.
– Procurement and distribution of modern contraceptive methods.
– Awareness campaigns and educational materials.
– Infrastructure development to improve access to reproductive health services.
– Monitoring and evaluation of program implementation.
Please note that the cost items provided are general categories and not actual cost estimates. The actual budget for implementing the recommendations would depend on various factors such as the scale of intervention, target population, and specific strategies employed.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong. The study used a large sample size and a nationally representative dataset, which enhances the generalizability of the findings. The study also employed multilevel mixed-effect logistic regression analysis to account for the hierarchical nature of the data. However, the abstract lacks information on the specific methodology used for data collection and sampling, which could affect the validity of the results. To improve the strength of the evidence, the abstract should provide more details on the sampling strategy, data collection methods, and measures taken to ensure data quality. Additionally, it would be helpful to include information on the limitations of the study and potential sources of bias.

Abstract

The study used the 2019 Ethiopia mini demographic and health survey (EMDHS) dataset. It is the second mini demographic and health survey which was conducted in March, 2019, to June, 2019 in Ethiopia. Ethiopia is divided into two administrative cities and nine regions. All married women in the reproductive age living in nine regions and two administrative cities of Ethiopia were included in the study. The EMDHS used a complete list of 149,093 enumeration areas (EAs) created for the upcoming Ethiopia population and housing census as a sampling frame. The frame comprises information about the EA location, type of residence (urban or rural), and estimated number of residential households. Accordingly, the sample was stratified and selected in two-stages [28]. Out of the total EAs, a total of 305 EAs (93 in urban areas and 212 in rural areas) were selected with probability proportional to EA size and with independent selection in each sampling stratum for the survey. Secondly, a fixed number of 30 households per cluster were selected with an equal probability systematic selection from the newly created household listing. Finally, the 2019 EMDHS survey covered 8,663 households out of the selected 8,794 households providing a response rate of 99%. About 8,885 women completed the interview from 16,583 women identified for the interview, yielding a response rate of 99%. According to the EMDHS report response rates were higher in rural than in urban areas [28]. The source population of this study was all married non-pregnant women who were in the reproductive age group and living in Ethiopia. Pregnant mothers and those who were not in union at the time of survey were excluded from the study. Hence, 4,983 married women data were extracted from the 2019 EMDHS datasets. Modern contraceptive utilization was the outcome variable of the study. Woman was considered as a “utilizer” if she had been utilizing any modern contraceptive methods such as oral contraceptives, male and female sterilization, intrauterine contraceptive device, injectables, implants, male and female condoms, lactational amenorrhea method, standard days method, and emergency contraception [4, 30] during the 2019 EMDHS survey period while woman who had been utilizing traditional, folkloric or no method was considered as a “non-utilizer”. Both the individual and community level explanatory variables were used to assess modern contraceptives utilized among women in childbearing age in the country. Maternal age, educational level of mother, wealth index, total children ever born, number of living children, births in the last three years, age of respondent at first birth, family size, number of under five children in household, and knowledge on modern contraceptive method. Community level explanatory variables include religion, region, and place of residence (Table 1). PCA: principal components analysis. The data were extracted, cleaned, re-coded, and analyzed using STATA version 14. Descriptive statistics were presented using graphs, tables and narrations. A multilevel mixed-effect logistic regression analysis, an advanced model, was used to overcome the violation of independence of observations and equal variance assumption of the traditional logistic regression model due to a hierarchical nature of DHS data. We first estimated an intercept-only model or the null model (with only the outcome variable). Secondly, we included all individual level factors in the model (model I). In the third stage, we constructed model II (fitted with community-level factors only) and finally model III was fitted with both individual and community-level factors. To examine clustering and the extent to which community-level factors explain the unexplained variance of the null model, the intraclass correlation coefficient (ICC) and a proportional change in variance (PCV) were checked. The model with the lowest deviance, model III, was selected as the best-fitted model for the analysis. Variance inflation factor (VIF) was done to test the existence of multicollinearity among the independent variables. Variables having a p-value of less than 0.2 in the bivariable analysis were selected as candidate variables for the multivariable mixed-effect logistic regression analysis. In the final model, a p-value of less than 0.05 and an adjusted odds ratio (AOR) with a 95% confidence interval (CI) were used to report statistically significant factors with modern contraceptive utilization among childbearing age women. This study used secondary data from demographic and health survey repositories. The survey data do not contain all identifying information. The MEASURE Demographic and Health Survey Program team allowed us to access the data upon sending an abstract of our study to an online request form http://www.measuredhsprogram.com.

Materials

https://efashare.b-cdn.net/materials/92327b85930ac6a2a48914be45fb98728cd2544e602d5d34ac55aa90f792f2a5/pone.0262431.s001.docx

Innovations

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

1. Mobile Health (mHealth) Solutions: Develop mobile applications or SMS-based platforms that provide information and reminders about modern contraceptive methods, prenatal care, and postnatal care. These platforms can also connect women to healthcare providers and enable them to schedule appointments or receive virtual consultations.

2. Community Health Workers (CHWs): Train and deploy CHWs to provide education and counseling on modern contraceptive methods and maternal health. CHWs can reach remote or underserved areas, conduct home visits, and provide personalized support and guidance to women and their families.

3. Telemedicine Services: Establish telemedicine services that allow pregnant women and new mothers to consult with healthcare professionals remotely. This can help address barriers to accessing healthcare, especially in rural or isolated areas where healthcare facilities are limited.

4. Task-Shifting and Training: Expand the roles and responsibilities of midwives, nurses, and other healthcare providers to include the provision of modern contraceptive methods. This can help alleviate the burden on doctors and increase the availability of contraceptive services.

5. Public-Private Partnerships: Foster collaborations between the government, private sector, and non-profit organizations to improve access to maternal health services. This can involve leveraging private sector resources and expertise to enhance service delivery, supply chain management, and infrastructure development.

6. Quality Improvement Initiatives: Implement quality improvement programs in healthcare facilities to ensure that maternal health services are delivered in a safe, effective, and patient-centered manner. This can involve training healthcare providers, improving infection control practices, and enhancing the overall quality of care.

7. Financial Incentives: Introduce financial incentives or subsidies to encourage women to utilize modern contraceptive methods and seek timely prenatal and postnatal care. This can help reduce financial barriers and increase the affordability of maternal health services.

8. Community-Based Approaches: Engage local communities and traditional leaders in promoting maternal health and family planning. This can involve community awareness campaigns, peer education programs, and the establishment of support groups for women and their partners.

9. Integration of Services: Integrate maternal health services with other healthcare programs, such as HIV/AIDS prevention and treatment, nutrition support, and immunization. This can improve the efficiency and effectiveness of service delivery and ensure comprehensive care for women and their children.

10. Research and Data Collection: Invest in research and data collection to better understand the barriers and challenges to accessing maternal health services. This can inform evidence-based interventions and policies to improve access and utilization.

AI Innovations Description

Based on the study findings, here is a recommendation that can be developed into an innovation to improve access to maternal health:

1. Improve access to reproductive health services: Develop and implement programs that focus on increasing access to modern contraceptive methods for married women in Ethiopia. This can include establishing more reproductive health clinics and facilities in rural areas, where access is limited. Additionally, mobile health clinics or telemedicine services can be utilized to reach women in remote areas.

2. Empower women through community-based approaches: Implement community-based education and awareness programs to empower women and increase their knowledge about modern contraceptive methods. This can involve training community health workers or volunteers to provide information and counseling on family planning options. Peer support groups can also be established to create a supportive environment for women to discuss and make informed decisions about their reproductive health.

3. Address regional disparities: Identify and address regional disparities in modern contraceptive utilization by implementing targeted interventions in regions with lower utilization rates. This can involve collaborating with local authorities and community leaders to understand the specific barriers and challenges faced by women in these regions and develop tailored strategies to overcome them.

4. Strengthen health systems: Invest in strengthening the overall health system in Ethiopia, including improving infrastructure, ensuring the availability of essential medicines and supplies, and enhancing the capacity of healthcare providers to deliver quality reproductive health services. This can be achieved through training programs, supportive supervision, and regular monitoring and evaluation of service delivery.

By implementing these recommendations, it is expected that access to maternal health will be improved, leading to better reproductive health outcomes for women in Ethiopia.

AI Innovations Methodology

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

1. Strengthening Reproductive Health Services: Increase the availability and accessibility of reproductive health services, including modern contraceptive methods, through the establishment and improvement of healthcare facilities, particularly in rural areas. This can be achieved by increasing the number of trained healthcare providers, ensuring the availability of necessary equipment and supplies, and implementing outreach programs to reach underserved populations.

2. Community-Based Approaches: Implement community-based interventions to empower women and increase awareness about maternal health and family planning. This can include education programs, peer support groups, and community health workers who can provide information, counseling, and referrals for reproductive health services.

3. Addressing Socioeconomic Factors: Address socioeconomic factors that hinder access to maternal health services, such as poverty, low educational attainment, and limited access to transportation. This can be done through targeted interventions that provide financial support, scholarships, and transportation assistance to women in need.

4. Regional Disparity Reduction: Reduce regional disparities in access to maternal health services by allocating resources and implementing targeted interventions in regions with lower utilization rates. This can involve working closely with local governments, community leaders, and stakeholders to identify and address specific barriers in each region.

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

1. Data Collection: Collect baseline data on the current utilization rates of maternal health services, including modern contraceptive methods, in different regions or communities. This can be done through surveys, interviews, or analysis of existing data sources.

2. Intervention Design: Develop a simulation model that incorporates the recommended interventions and their potential impact on improving access to maternal health services. This model should consider factors such as population size, demographic characteristics, healthcare infrastructure, and resource allocation.

3. Parameter Estimation: Estimate the parameters of the simulation model based on available data and expert knowledge. This may involve conducting statistical analyses, literature reviews, or expert consultations to determine the potential effectiveness of each intervention.

4. Simulation Execution: Run the simulation model using the estimated parameters to project the potential impact of the recommended interventions on access to maternal health services. This can be done by simulating different scenarios, such as implementing one or multiple interventions simultaneously, and comparing the outcomes.

5. Evaluation and Analysis: Evaluate the results of the simulation to assess the effectiveness of the recommended interventions in improving access to maternal health services. Analyze the data to identify key factors or combinations of interventions that have the greatest impact on utilization rates.

6. Policy Recommendations: Based on the simulation results, provide policy recommendations and guidelines for implementing the most effective interventions to improve access to maternal health services. These recommendations should consider the feasibility, cost-effectiveness, and sustainability of the interventions.

It is important to note that the methodology described above is a general framework and may need to be adapted based on the specific context and available data.

Author

Dima Health

Statistics:

Citations: 4

Identifiers:

DOI: 10.1371/journal.pone.0262431

Research Areas:

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

Study Countries:

Ethiopia

Study Design:

Case-Control Study, Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Male & Female