Magnitude of antenatal care service uptake and associated factors among pregnant women: Analysis of the 2016 Ethiopia Demographic and Health Survey

BMJ Open, Volume 11, No. 4, Year 2021

Interpretation

Objective Antenatal and postnatal cares are crucial for the survival and well-being of both the mother and the child. WHO recommends a minimum of four antenatal care (ANC) visits during a pregnancy. In Ethiopia, only 38% of women in the reproductive age make a minimum of first ANC visits. This value is far below the typical rates of least developed countries. This study aimed to calculate the magnitude and identify associated factors of ANC service utilisation among pregnant women in Ethiopia. Design Cross-sectional study design. Setting Ethiopia. Participants A total of 7913 pregnant women participated in the study. Primary outcome measures Antenatal care service uptake among pregnant women. Result Only 35.5% of the pregnant mothers have used ANC services at least four times and 64.5% of the pregnant mothers have used less than three times during their periods of pregnancy. The study showed that rich women (PR=1.077, 95% CI: 1.029 to 1.127), having access to mass media (PR=1.086, 95% CI: 1.045 to 1.128), having pregnancy complications (PR=1.203, 95% CI: 1.165 to 1.242), secondary education and above (PR=1.112, 95% CI:1.052 to 1.176), husbands’ having secondary education and above (PR=1.085, 95% CI: 1.031 to 1.142) and married (PR=1.187; 95% CI: 1.087 to 1.296), rural women (PR=0.884, 95% CI: 0.846 to 0.924) and women>30 years of age (PR=1.067, 95% CI: 1.024 to 1.111) significantly associated with the ANC service uptake. Conclusion The magnitude of ANC service uptake was low. This low magnitude of ANC service utilisation calls for a need to improve community awareness about maternal health. More importantly, intensive health education is required for pregnant women to have better ANC service uptake and follow-up adherence. This study used a publicly available data set (2016 EDHS). Therefore, there were no patients or members of the public involved. The data used for this study were taken from the 2016 EDHS. This survey is the fourth comprehensive survey designed to provide estimates for the health and demographic variables of interest for the whole urban and rural areas of Ethiopia as a domain. Women who had 9 months of pregnancy during the survey interview were included in the analysis. The study includes 7193 cases of the reproductive age group within the country. The 2016 EDHS employed a stratified two-stage cluster sampling procedure designed to provide a representative sample for multiple health and population indicators at national and subnational levels (nine regions and two city administrations). Initially, 645 enumeration areas (EAs) (202 in urban areas and 443 in rural areas) were drawn using probability proportional to size sampling approach from a whole list of 84 915 EAs defined within the recent 2007 population census. Then, in every selected EA, an exhaustive listing of households was made and 28 households were selected using a systematic sampling approach. Within the chosen households, enumeration of the entire members was made and information about the ANC service utilisation among all household members was collected primarily from the women.19 The outcome variable of interest in this study was a count response of the number of ANC visits during their last pregnancy. The independent variables of this study were selected by reviewing related work of the literature.12–17 20–25 Women’s educational level (no education, primary, secondary and higher), husband’s occupation (not working, working), wealth index (poor, middle, rich), marital status (living alone, married, divorced/widowed), women occupation (housewife, employed), age of women (15–24, 25–29 and ≥30 years), husband’s educational level (no education, primary, secondary and higher), planned pregnancy (yes, no), access to mass media (yes, no), pregnancy complications (yes, no), the desire of pregnancy (yes, no), a history of terminated pregnancy ever in her life (yes, no) and residence (urban, rural) were considered to be independent variables within the study. The cleaned and recoded data were analysed using R software V.3.5.3. Frequencies and percentages were used to describe the categorical variables. Data were presented using tables. ZIPR model was conducted to identify factors associated with ANC service utilisation among the pregnant women. In recent years, the ZIPR model has gained popularity for modelling count data with excess zeroes.18 The ZIPR model can be viewed as a finite mixture model with a degenerative distribution where its mass is concentrated at zero. Excess zeroes arise when the event of interest is not experienced by many of the subjects.26 In this study, the ZIPR model was employed to identify the determinant factors of ANC service uptake among pregnant women. Suppose Yi is the number of ANC service uptake among the pregnant. Thus, the probability mass function of ZIPR is given by18 27 28 The parameters μi and πi depend on the covariates xi and zi, respectively. The mean and the variance of ZIPR model, respectively, are Eyi=1-πiμiand Varyi=μi1-πi1+πiμi. To apply the ZIPR model in practical modelling situations, Lambert, Afifi et al and Agarwal et al 18 27 28 suggested the following joint models for μ and π: lnμ=XTβand ln⁡π1-π=ZTγ where X and Z are covariate matrices and βandγ are p+1×1 and q+1×1 vectors of unknown parameters, respectively. The two sets of covariates may or may not coincide. Finally, the OR and prevalence ratios (PR) with a 95% CI were used to assess the strength of associations between the outcome and the independent variables using Poisson and Bernoulli regression models’ assumptions. P values of ≤0.05 were considered for statistically significant.

AI Digest

Study Justification:

– Antenatal and postnatal care are essential for the health and well-being of both mothers and children.
– The World Health Organization (WHO) recommends a minimum of four antenatal care (ANC) visits during pregnancy.
– In Ethiopia, only 38% of women in the reproductive age receive the recommended minimum ANC visits.
– This study aimed to determine the magnitude of ANC service utilization and identify factors associated with it among pregnant women in Ethiopia.

Study Highlights:

– The study included 7,913 pregnant women in Ethiopia.
– Only 35.5% of pregnant women had received ANC services at least four times, while 64.5% had received less than three times.
– Factors associated with ANC service uptake included wealth, access to mass media, pregnancy complications, education level of the woman and her husband, marital status, rural residence, and age over 30.
– The study highlights the need to improve community awareness about maternal health and provide intensive health education to pregnant women for better ANC service uptake and adherence.

Study Recommendations:

– Increase community awareness about the importance of antenatal care and its benefits for maternal and child health.
– Provide intensive health education programs targeting pregnant women to improve ANC service uptake and follow-up adherence.

Key Role Players:

– Ministry of Health: Responsible for implementing and coordinating interventions to improve ANC service utilization.
– Health Extension Workers: Provide community-level health education and promote ANC services.
– Non-Governmental Organizations (NGOs): Support awareness campaigns and provide resources for ANC services.
– Community Leaders: Engage in advocacy and mobilize community members to prioritize ANC services.

Cost Items for Planning Recommendations:

– Development and dissemination of educational materials: Printing and distribution costs.
– Training programs for health extension workers: Costs for trainers, materials, and logistics.
– Awareness campaigns: Costs for media advertisements, community events, and outreach activities.
– Monitoring and evaluation: Costs for data collection, analysis, and reporting.
Please note that the cost items provided are general categories and not actual cost estimates. The specific costs will depend on the scale and scope of the interventions implemented.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is rated 7 because it provides specific data from a cross-sectional study design and includes statistical analysis. However, the evidence could be strengthened by providing more details on the sampling procedure, data collection methods, and potential limitations of the study. Additionally, the abstract could benefit from a clearer statement of the study’s objectives and implications for future research.

Abstract

This study used a publicly available data set (2016 EDHS). Therefore, there were no patients or members of the public involved. The data used for this study were taken from the 2016 EDHS. This survey is the fourth comprehensive survey designed to provide estimates for the health and demographic variables of interest for the whole urban and rural areas of Ethiopia as a domain. Women who had 9 months of pregnancy during the survey interview were included in the analysis. The study includes 7193 cases of the reproductive age group within the country. The 2016 EDHS employed a stratified two-stage cluster sampling procedure designed to provide a representative sample for multiple health and population indicators at national and subnational levels (nine regions and two city administrations). Initially, 645 enumeration areas (EAs) (202 in urban areas and 443 in rural areas) were drawn using probability proportional to size sampling approach from a whole list of 84 915 EAs defined within the recent 2007 population census. Then, in every selected EA, an exhaustive listing of households was made and 28 households were selected using a systematic sampling approach. Within the chosen households, enumeration of the entire members was made and information about the ANC service utilisation among all household members was collected primarily from the women.19 The outcome variable of interest in this study was a count response of the number of ANC visits during their last pregnancy. The independent variables of this study were selected by reviewing related work of the literature.12–17 20–25 Women’s educational level (no education, primary, secondary and higher), husband’s occupation (not working, working), wealth index (poor, middle, rich), marital status (living alone, married, divorced/widowed), women occupation (housewife, employed), age of women (15–24, 25–29 and ≥30 years), husband’s educational level (no education, primary, secondary and higher), planned pregnancy (yes, no), access to mass media (yes, no), pregnancy complications (yes, no), the desire of pregnancy (yes, no), a history of terminated pregnancy ever in her life (yes, no) and residence (urban, rural) were considered to be independent variables within the study. The cleaned and recoded data were analysed using R software V.3.5.3. Frequencies and percentages were used to describe the categorical variables. Data were presented using tables. ZIPR model was conducted to identify factors associated with ANC service utilisation among the pregnant women. In recent years, the ZIPR model has gained popularity for modelling count data with excess zeroes.18 The ZIPR model can be viewed as a finite mixture model with a degenerative distribution where its mass is concentrated at zero. Excess zeroes arise when the event of interest is not experienced by many of the subjects.26 In this study, the ZIPR model was employed to identify the determinant factors of ANC service uptake among pregnant women. Suppose Yi is the number of ANC service uptake among the pregnant. Thus, the probability mass function of ZIPR is given by18 27 28 The parameters μi and πi depend on the covariates xi and zi, respectively. The mean and the variance of ZIPR model, respectively, are Eyi=1-πiμiand Varyi=μi1-πi1+πiμi. To apply the ZIPR model in practical modelling situations, Lambert, Afifi et al and Agarwal et al 18 27 28 suggested the following joint models for μ and π: lnμ=XTβand ln⁡π1-π=ZTγ where X and Z are covariate matrices and βandγ are p+1×1 and q+1×1 vectors of unknown parameters, respectively. The two sets of covariates may or may not coincide. Finally, the OR and prevalence ratios (PR) with a 95% CI were used to assess the strength of associations between the outcome and the independent variables using Poisson and Bernoulli regression models’ assumptions. P values of ≤0.05 were considered for statistically significant.

Materials

Innovations

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

1. Mobile Health (mHealth) Applications: Develop mobile applications that provide pregnant women with information and reminders about antenatal care visits, as well as access to teleconsultations with healthcare providers.

2. Community Health Workers: Train and deploy community health workers to educate pregnant women about the importance of antenatal care and provide support in accessing healthcare services.

3. Telemedicine: Implement telemedicine programs that allow pregnant women in remote areas to consult with healthcare providers through video calls, reducing the need for travel and improving access to antenatal care.

4. Health Education Campaigns: Conduct targeted health education campaigns to raise awareness about the benefits of antenatal care and address cultural and social barriers that may prevent women from seeking care.

5. Financial Incentives: Introduce financial incentives, such as conditional cash transfers or vouchers, to encourage pregnant women to attend antenatal care visits and overcome financial barriers.

6. Transportation Support: Provide transportation support, such as subsidized or free transportation services, to help pregnant women reach healthcare facilities for antenatal care appointments.

7. Task Shifting: Train and empower lower-level healthcare providers, such as nurses and midwives, to provide antenatal care services, thereby increasing the availability of care in underserved areas.

8. Integration of Services: Integrate antenatal care services with other healthcare services, such as family planning and immunization, to improve efficiency and convenience for pregnant women.

9. Quality Improvement Initiatives: Implement quality improvement initiatives in healthcare facilities to ensure that antenatal care services are delivered in a respectful, timely, and effective manner, thereby increasing women’s satisfaction and willingness to seek care.

10. Partnerships and Collaboration: Foster partnerships and collaboration between government agencies, non-governmental organizations, and private sector entities to leverage resources and expertise in improving access to maternal health services.

It is important to note that the specific context and needs of the target population should be considered when implementing these innovations.

AI Innovations Description

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

1. Community Awareness Campaign: Implement an intensive health education campaign targeting pregnant women and their families to increase awareness about the importance of antenatal care (ANC) services. This campaign should emphasize the benefits of regular ANC visits for both the mother and the child’s health.

2. Mobile Health (mHealth) Solutions: Develop and promote the use of mobile health applications or text message reminders to provide pregnant women with timely information and reminders about ANC appointments. These digital tools can help overcome barriers such as lack of awareness or forgetfulness.

3. Strengthening Health Infrastructure: Invest in improving the availability and accessibility of ANC services by expanding healthcare facilities, particularly in rural areas. This includes ensuring the availability of skilled healthcare providers, necessary equipment, and supplies for ANC services.

4. Financial Support: Implement financial assistance programs or health insurance schemes to reduce the financial burden associated with ANC services. This can help address the disparity in ANC service utilization among different socioeconomic groups.

5. Partnerships and Collaboration: Foster partnerships between government agencies, non-governmental organizations, and community-based organizations to collectively work towards improving access to maternal health services. Collaboration can help leverage resources, expertise, and reach a wider population.

6. Targeted Interventions: Tailor interventions based on identified factors associated with ANC service uptake, such as education level, access to mass media, pregnancy complications, and age. For example, targeted educational programs can be designed for women with lower education levels or those living in rural areas.

7. Continuous Monitoring and Evaluation: Establish a robust monitoring and evaluation system to track the progress and impact of the implemented interventions. Regular data collection and analysis will help identify areas for improvement and ensure the effectiveness of the innovation.

By implementing these recommendations, it is expected that access to maternal health services, specifically ANC, will improve, leading to better health outcomes for both mothers and children in Ethiopia.

AI Innovations Methodology

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

1. Increase community awareness: Intensive health education programs should be implemented to raise awareness about the importance of antenatal care (ANC) services among pregnant women and their families. This can be done through community outreach programs, media campaigns, and educational materials.

2. Improve access to ANC services: Efforts should be made to ensure that ANC services are easily accessible to pregnant women, especially in rural areas. This can include establishing more health facilities, mobile clinics, and transportation services to overcome geographical barriers.

3. Address socio-economic factors: Strategies should be developed to address socio-economic factors that affect ANC service uptake. This can include providing financial support or incentives for pregnant women from low-income backgrounds, as well as promoting women’s education and empowerment.

4. Strengthen healthcare systems: Investments should be made to strengthen healthcare systems, including training healthcare providers on ANC guidelines and best practices, ensuring the availability of essential supplies and equipment, and improving the quality of ANC services.

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

1. Define the target population: Determine the specific population group that will be the focus of the simulation, such as pregnant women in a particular region or country.

2. Collect baseline data: Gather data on the current utilization of ANC services, including the number of ANC visits and associated factors, from surveys or existing databases.

3. Develop a simulation model: Create a mathematical or statistical model that incorporates the recommendations and factors identified in the study. This model should simulate the impact of the recommendations on ANC service uptake, taking into account the specific factors associated with utilization.

4. Input data and parameters: Input the baseline data and parameters into the simulation model, including information on the target population, the impact of the recommendations, and any other relevant variables.

5. Run the simulation: Execute the simulation model to generate results that estimate the potential impact of the recommendations on improving access to maternal health. This could include projected changes in ANC service uptake rates, as well as any associated factors or outcomes.

6. Analyze and interpret the results: Analyze the simulation results to understand the potential impact of the recommendations on improving access to maternal health. This could involve comparing the projected changes in ANC service uptake rates with the baseline data, identifying any significant associations or trends, and assessing the overall effectiveness of the recommendations.

7. Validate and refine the model: Validate the simulation model by comparing the projected results with real-world data or expert opinions. Refine the model as necessary to improve its accuracy and reliability.

8. Communicate the findings: Present the simulation findings in a clear and concise manner, highlighting the potential impact of the recommendations on improving access to maternal health. This information can be used to inform policy decisions, resource allocation, and program planning to enhance maternal healthcare services.

Author

Dima Health

Statistics:

Citations: 7

Identifiers:

DOI: 10.1136/bmjopen-2020-043904

Research Areas:

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

Study Countries:

Ethiopia

Study Design:

Cohort Study, Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Female