Prenatal hiv test uptake and its associated factors for prevention of mother to child transmission of hiv in East Africa

International Journal of Environmental Research and Public Health, Volume 18, No. 10, Year 2021

Interpretation

Identifying the socioeconomic and structural issues that act as enablers and/or barriers to HIV testing services is critical in combatting HIV/AIDS amongst mothers and children in Africa. In this study, we used a weighted sample of 46,645 women aged 15–49 who gave birth in the two years preceding the survey from the recent DHS dataset of ten East African countries. Multivariable logistic regression was used to investigate the factors associated with prenatal HIV test uptake in East Africa. The overall prenatal HIV test uptake for the prevention of mother-to-child transmission (PMTCT) of HIV was 80.8% (95% CI: 74.5–78.9%) in East Africa, with highest in Rwanda (97.9%, 95% CI: 97.2–98.3%) and lowest in Comoros (17.0%, 95% CI: 13.9–20.7%). Common factors associated with prenatal HIV test service uptake were higher maternal education level (AOR = 1.29; 95% CI: 1.10–1.50 for primary education and AOR = 1.96; 95% CI: 1.53–2.51 for secondary or higher education), higher partner education level (AOR = 1.24; 95% CI: 1.06–1.45 for primary education and AOR = 1.56; 95% CI: 1.26–1.94 for secondary or higher school), women from higher household wealth index (AOR = 1.29; 95% CI: 1.11–1.50 for middle wealth index; AOR= 1.57; 95% CL: 1.17–2.11 for rich wealth index), improved maternal exposure to the media, and increased awareness about MTCT of HIV. However, residents living in rural communities (AOR=0.66; 95% CI: 0.51–0.85) and travelling long distances to the health facility (AOR = 0.8; 95% CI: 0.69–0.91) were associated with non-use of prenatal HIV test service in East African countries. In each East African country, factors associated with prenatal HIV test uptake for PMTCT varied. In conclusion, the pooled prenatal HIV test uptake for PMTCT of HIV was low in East Africa compared to the global target. Scaling up interventions to improve enablers whilst addressing barriers to the use of prenatal HIV test services are essential to end the HIV/AIDS epidemic in East African countries. This analytical cross-sectional study used data from the DHS program [34]. The DHS are nationally representative household surveys that provide data for a wide range of monitoring and impact evaluation indicators in the areas of population, health and nutrition [35]. The information on the HIV testing during antenatal care and birth in the two years preceding the survey for each woman in the sample was found in the women’s individual records of DHS. The most recent data from 10 countries in WHO regions of East Africa [31,32] with completed DHS datasets between 2011 and 2017 were included in this study. This period covered the transition between the completion of the Millennium Development Goals (MDG’s) and the commencement of the Sustainable Development Goals (SDGs) and this evidence will appreciate the achievement of the MDGs and will be useful as a baseline for the SDGs. Included countries in the analysis were Burundi (DHS, 2016–2017), Comoros (DHS, 2012), Ethiopia (DHS, 2016), Kenya (DHS, 2014), Malawi (DHS, 2015–2016), Mozambique (DHS, 2011), Rwanda (DHS, 2014–2015), Uganda (DHS, 2016), Zambia (DHS, 2013–2014), and Zimbabwe (DHS, 2015). Pooled DHS datasets from 10 East African countries were done by creating a country-specific cluster and country-specific strata. Accordingly, in the present study, we used a total weighted sample of 46,645 women age 15–49 years who gave birth in the two years preceding the survey to determine the pooled magnitude and determinants of prenatal HIV test uptake across East Africa countries. The DHS employed a cross-sectional study design with a stratified two-stage sampling strategy, where country was divided into enumeration areas (clusters) based on the census frames in the country, and then, households were randomly selected within each cluster. Furthermore, since the DHS surveys were intended to address household-based health issues, strata for urban and rural households were used for the selection of respondents. The DHS follows a standard procedure of data collection and presentation (similar questionnaires) and uses the same definition of terms. The DHS data were collected by the country-specific department of health and population, in collaboration with Inner City Fund (ICF) International using standardized household questionnaires. The detailed methodology of the survey design, sample selection, survey tools and data collection are described elsewhere [36,37]. In this study, prenatal HIV test uptake was measured as the proportion of women who tested for HIV and received their HIV test result during pregnancy, consistent with the PMTCT strategy [38,39]. Therefore, for this study prenatal HIV test uptake was coded as “1” if a woman was tested for HIV and received the HIV test result during antenatal care or before birth, otherwise coded as “0” if the woman did not test for HIV or tested but did not receive the test result during antenatal care or before birth. We adapted the most recent/the fourth phase/behavioral model of health service utilization by Ronald M. Andersen for this study [40]. It is a well-validated and most widely adopted theoretical framework that permits systematic identification of factors that influence individual decisions to use or not to use available health care services [40]. Several studies have used this conceptual model to study health care utilization [41,42,43,44]. The selection of study variables to be included in this study was done based on the purpose of this research, previously published literature from low- and middle-income countries [45,46], and the availability of information regarding the relevant variables. Study variables were categorized into community levels, predisposing, enabling and need factors based on the modified Andersen model [40]. Accordingly, the following were variables extracted from the DHS data and their classification for this study. Community level factors reflect the contextual or environmental characteristics affecting the use of health services. Included are place of residence (categorized as rural or urban) and country of residence (Burundi, Comoros, Ethiopia, Kenya, Malawi, Rwanda, Tanzania, Mozambique, Uganda, Zambia). Burundi was selected as the reference country as it is the first country on the list of East African countries. Predisposing factors reflect the individuals’ characteristics that influence the propensity to use health services before illness onset. It consists of maternal age (classified as 15–24, 25–34, and 35–49 years), maternal and partner educational level (categorized as no education, primary or secondary and above education) and employment status (categorized as not working, formal employment and non-formal employment). Women’s history of any sexual violence by her husband/partner (categorized as yes or no), women listening to the radio (categorized as yes or no), watching television (categorized as yes or no) and reading magazines or newspapers (categorized as yes or no) were the other predisposing factors. Enabling factors encompass personal or community resources that can promote or inhibit access to health services. These included wealth index, the household wealth index for the pooled dataset, which was constructed using the ‘hv271′ variable. The ‘hv271′ is a household’s wealth index value generated by the product of standardized scores (z-scores) and factor coefficient scores (factor loadings) of wealth indicators [47]. Within the household wealth index categories, the bottom 20% of households were arbitrarily referred to as the poorest households, and the top 20% as the wealthiest households and they were grouped into poor, middle and rich based on previously published studies [48]. Women’s involvement in household decisions is derived from four different household decisions including decisions to seek health care, decisions on large household purchases, decisions on what to do with the money the husband earns and decisions to visit family/relatives. It is categorized as involved in the household decision if a woman decides on one or more household decisions, otherwise not involved. Perceived distance to health facilities was dichotomously categorized as challenging or not. Women’s awareness about MTCT of HIV during pregnancy, awareness of MTCT during birth and awareness of MTCT during breastfeeding were all classified as yes or no. Need factors represent the potential needs of health service use according to the women’s perceived or evaluated health status which includes women’s intention for the pregnancy (categorized as desired pregnancy if the pregnancy is wanted, otherwise unwanted pregnancy). The analysis is based on pooled DHS datasets from 10 East African countries by creating country-specific clustering and country-specific strata using similar methods employed by Agho et al. [49]. Throughout the analysis population-level weight was used to adjust for the imbalance of country-specific populations across East Africa countries. Descriptive statistics such as percentage, frequency counts, the prevalence of prenatal HIV test uptake and its 95% confidence intervals were conducted for all East African countries and each country. Logistic regression models were used to investigate the influence of the study factors on prenatal HIV test uptake in PMTCT of HIV services after adjusting for country-specific cluster and population level weights using the “svy: logistic” command. Four-stage modeling using the adapted Andersen’s behavioral model of health service utilization was executed to determine the adjusted odds ratios and compare the relative influence of the four kinds of factors on prenatal HIV test uptake for PMTCT of HIV services [40]. Community level factors (place of residence and country of residence) were entered in the first stage model. In the second stage model, community level factors and predisposing factors (maternal age, maternal education, partner education, history of sexual violence, maternal employment, women listen to the radio, watch television, and read newspapers) were included. In the third stage, the second stage model was added to enabling factors (household wealth index, women’s involvement in household decisions, health facility distance, aware MTCT during pregnancy, aware MTCT during birth and aware MTCT during breastfeeding) followed by the fourth or final stages, in which the third stage model was then added to the need factors (desire for the pregnancy). Adjusted odds ratios (AORs) with their 95% confidence intervals (CIs) and p-value < 0.05 were estimated to determine the presence of association between study factors and prenatal HIV test uptake. All statistical analyses were conducted using STATA version 14.2 (Stata Corp, College Station, TX, USA).

AI Digest

Study Justification:

– Identifying socioeconomic and structural issues that act as enablers and/or barriers to HIV testing services is crucial in combating HIV/AIDS among mothers and children in Africa.
– This study aims to determine the factors associated with prenatal HIV test uptake in East Africa to inform interventions and improve prevention of mother-to-child transmission (PMTCT) of HIV.

Highlights:

– The overall prenatal HIV test uptake for PMTCT in East Africa was 80.8%, with the highest uptake in Rwanda (97.9%) and the lowest in Comoros (17.0%).
– Factors associated with prenatal HIV test service uptake included higher maternal and partner education levels, higher household wealth index, improved maternal exposure to media, and increased awareness about MTCT of HIV.
– However, residents living in rural communities and traveling long distances to health facilities were associated with non-use of prenatal HIV test services in East African countries.
– Factors associated with prenatal HIV test uptake varied in each East African country.

Recommendations:

– Scaling up interventions to improve enablers and address barriers to the use of prenatal HIV test services is essential to end the HIV/AIDS epidemic in East African countries.
– Interventions should focus on increasing education levels, improving access to health facilities in rural areas, and reducing travel distances.
– Increasing awareness about MTCT of HIV and promoting media exposure can also contribute to higher prenatal HIV test uptake.

Key Role Players:

– Ministry of Health in each East African country
– Non-governmental organizations (NGOs) working on HIV/AIDS prevention and maternal health
– Healthcare providers and professionals
– Community leaders and influencers
– Media organizations and journalists

Cost Items for Planning Recommendations:

– Education and training programs for healthcare providers and professionals
– Development and dissemination of educational materials and campaigns
– Infrastructure development to improve access to health facilities in rural areas
– Transportation services to reduce travel distances for pregnant women
– Media campaigns and advertisements to increase awareness about MTCT of HIV
– Monitoring and evaluation activities to assess the impact of interventions

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is strong, but there are some areas for improvement. The study used a large weighted sample and employed multivariable logistic regression to investigate the factors associated with prenatal HIV test uptake in East Africa. The study also provided specific percentages and confidence intervals for the overall prenatal HIV test uptake in East Africa and for each country. However, the abstract could be improved by providing more information on the representativeness of the sample and the generalizability of the findings. Additionally, it would be helpful to include information on the limitations of the study and suggestions for future research.

Abstract

This analytical cross-sectional study used data from the DHS program [34]. The DHS are nationally representative household surveys that provide data for a wide range of monitoring and impact evaluation indicators in the areas of population, health and nutrition [35]. The information on the HIV testing during antenatal care and birth in the two years preceding the survey for each woman in the sample was found in the women’s individual records of DHS. The most recent data from 10 countries in WHO regions of East Africa [31,32] with completed DHS datasets between 2011 and 2017 were included in this study. This period covered the transition between the completion of the Millennium Development Goals (MDG’s) and the commencement of the Sustainable Development Goals (SDGs) and this evidence will appreciate the achievement of the MDGs and will be useful as a baseline for the SDGs. Included countries in the analysis were Burundi (DHS, 2016–2017), Comoros (DHS, 2012), Ethiopia (DHS, 2016), Kenya (DHS, 2014), Malawi (DHS, 2015–2016), Mozambique (DHS, 2011), Rwanda (DHS, 2014–2015), Uganda (DHS, 2016), Zambia (DHS, 2013–2014), and Zimbabwe (DHS, 2015). Pooled DHS datasets from 10 East African countries were done by creating a country-specific cluster and country-specific strata. Accordingly, in the present study, we used a total weighted sample of 46,645 women age 15–49 years who gave birth in the two years preceding the survey to determine the pooled magnitude and determinants of prenatal HIV test uptake across East Africa countries. The DHS employed a cross-sectional study design with a stratified two-stage sampling strategy, where country was divided into enumeration areas (clusters) based on the census frames in the country, and then, households were randomly selected within each cluster. Furthermore, since the DHS surveys were intended to address household-based health issues, strata for urban and rural households were used for the selection of respondents. The DHS follows a standard procedure of data collection and presentation (similar questionnaires) and uses the same definition of terms. The DHS data were collected by the country-specific department of health and population, in collaboration with Inner City Fund (ICF) International using standardized household questionnaires. The detailed methodology of the survey design, sample selection, survey tools and data collection are described elsewhere [36,37]. In this study, prenatal HIV test uptake was measured as the proportion of women who tested for HIV and received their HIV test result during pregnancy, consistent with the PMTCT strategy [38,39]. Therefore, for this study prenatal HIV test uptake was coded as “1” if a woman was tested for HIV and received the HIV test result during antenatal care or before birth, otherwise coded as “0” if the woman did not test for HIV or tested but did not receive the test result during antenatal care or before birth. We adapted the most recent/the fourth phase/behavioral model of health service utilization by Ronald M. Andersen for this study [40]. It is a well-validated and most widely adopted theoretical framework that permits systematic identification of factors that influence individual decisions to use or not to use available health care services [40]. Several studies have used this conceptual model to study health care utilization [41,42,43,44]. The selection of study variables to be included in this study was done based on the purpose of this research, previously published literature from low- and middle-income countries [45,46], and the availability of information regarding the relevant variables. Study variables were categorized into community levels, predisposing, enabling and need factors based on the modified Andersen model [40]. Accordingly, the following were variables extracted from the DHS data and their classification for this study. Community level factors reflect the contextual or environmental characteristics affecting the use of health services. Included are place of residence (categorized as rural or urban) and country of residence (Burundi, Comoros, Ethiopia, Kenya, Malawi, Rwanda, Tanzania, Mozambique, Uganda, Zambia). Burundi was selected as the reference country as it is the first country on the list of East African countries. Predisposing factors reflect the individuals’ characteristics that influence the propensity to use health services before illness onset. It consists of maternal age (classified as 15–24, 25–34, and 35–49 years), maternal and partner educational level (categorized as no education, primary or secondary and above education) and employment status (categorized as not working, formal employment and non-formal employment). Women’s history of any sexual violence by her husband/partner (categorized as yes or no), women listening to the radio (categorized as yes or no), watching television (categorized as yes or no) and reading magazines or newspapers (categorized as yes or no) were the other predisposing factors. Enabling factors encompass personal or community resources that can promote or inhibit access to health services. These included wealth index, the household wealth index for the pooled dataset, which was constructed using the ‘hv271′ variable. The ‘hv271′ is a household’s wealth index value generated by the product of standardized scores (z-scores) and factor coefficient scores (factor loadings) of wealth indicators [47]. Within the household wealth index categories, the bottom 20% of households were arbitrarily referred to as the poorest households, and the top 20% as the wealthiest households and they were grouped into poor, middle and rich based on previously published studies [48]. Women’s involvement in household decisions is derived from four different household decisions including decisions to seek health care, decisions on large household purchases, decisions on what to do with the money the husband earns and decisions to visit family/relatives. It is categorized as involved in the household decision if a woman decides on one or more household decisions, otherwise not involved. Perceived distance to health facilities was dichotomously categorized as challenging or not. Women’s awareness about MTCT of HIV during pregnancy, awareness of MTCT during birth and awareness of MTCT during breastfeeding were all classified as yes or no. Need factors represent the potential needs of health service use according to the women’s perceived or evaluated health status which includes women’s intention for the pregnancy (categorized as desired pregnancy if the pregnancy is wanted, otherwise unwanted pregnancy). The analysis is based on pooled DHS datasets from 10 East African countries by creating country-specific clustering and country-specific strata using similar methods employed by Agho et al. [49]. Throughout the analysis population-level weight was used to adjust for the imbalance of country-specific populations across East Africa countries. Descriptive statistics such as percentage, frequency counts, the prevalence of prenatal HIV test uptake and its 95% confidence intervals were conducted for all East African countries and each country. Logistic regression models were used to investigate the influence of the study factors on prenatal HIV test uptake in PMTCT of HIV services after adjusting for country-specific cluster and population level weights using the “svy: logistic” command. Four-stage modeling using the adapted Andersen’s behavioral model of health service utilization was executed to determine the adjusted odds ratios and compare the relative influence of the four kinds of factors on prenatal HIV test uptake for PMTCT of HIV services [40]. Community level factors (place of residence and country of residence) were entered in the first stage model. In the second stage model, community level factors and predisposing factors (maternal age, maternal education, partner education, history of sexual violence, maternal employment, women listen to the radio, watch television, and read newspapers) were included. In the third stage, the second stage model was added to enabling factors (household wealth index, women’s involvement in household decisions, health facility distance, aware MTCT during pregnancy, aware MTCT during birth and aware MTCT during breastfeeding) followed by the fourth or final stages, in which the third stage model was then added to the need factors (desire for the pregnancy). Adjusted odds ratios (AORs) with their 95% confidence intervals (CIs) and p-value < 0.05 were estimated to determine the presence of association between study factors and prenatal HIV test uptake. All statistical analyses were conducted using STATA version 14.2 (Stata Corp, College Station, TX, USA).

Materials

https://efashare.b-cdn.net/materials/6bf5f644700868c4a2fdfc366a026e217a7edb4ed6a7b1332d5dcd1a5fac7051/ijerph-18-05289-s001.zip

Innovations

Based on the information provided, here are some potential innovations that could improve access to maternal health, specifically in relation to prenatal HIV testing for the prevention of mother-to-child transmission (PMTCT) of HIV in East Africa:

1. Mobile Health (mHealth) Interventions: Develop and implement mobile health applications or text messaging services to provide information and reminders about prenatal HIV testing, as well as facilitate appointment scheduling and follow-up care.

2. Community-Based Outreach Programs: Establish community-based programs that educate and raise awareness about the importance of prenatal HIV testing, targeting rural areas and marginalized populations. These programs could include community health workers who provide information, counseling, and support to pregnant women.

3. Transportation Support: Implement transportation support systems to address the barrier of long distances to health facilities. This could involve providing transportation vouchers or arranging transportation services for pregnant women to access prenatal care and HIV testing.

4. Integration of Services: Integrate prenatal HIV testing with other maternal health services, such as antenatal care visits, to ensure that pregnant women have easy access to comprehensive care in one location. This could improve convenience and increase the likelihood of HIV testing uptake.

5. Task Shifting: Train and empower non-specialist healthcare providers, such as nurses and midwives, to conduct prenatal HIV testing. This could help alleviate the shortage of specialized healthcare professionals and increase access to testing services in remote areas.

6. Financial Support: Develop and implement financial assistance programs to reduce the financial burden associated with prenatal HIV testing. This could involve subsidizing the cost of testing or providing financial incentives for pregnant women to undergo testing.

7. Quality Improvement Initiatives: Implement quality improvement initiatives to ensure that prenatal HIV testing services are consistently available, accessible, and of high quality. This could involve regular monitoring and evaluation of service delivery, as well as training healthcare providers to deliver culturally sensitive and patient-centered care.

These are just a few potential innovations that could be considered to improve access to maternal health, specifically in relation to prenatal HIV testing for PMTCT in East Africa. It is important to note that the implementation of these innovations should be context-specific and tailored to the unique needs and challenges of each country or region.

AI Innovations Description

Based on the description provided, the recommendation to improve access to maternal health in East Africa is to scale up interventions that address the barriers and improve the enablers to the use of prenatal HIV test services.

Some of the factors associated with prenatal HIV test service uptake in East Africa include higher maternal and partner education levels, higher household wealth index, improved maternal exposure to the media, and increased awareness about mother-to-child transmission (MTCT) of HIV. These factors act as enablers and are positively associated with prenatal HIV test uptake.

However, residents living in rural communities and those traveling long distances to health facilities are associated with non-use of prenatal HIV test services. These factors act as barriers and negatively impact access to maternal health services.

To address these barriers and improve access to maternal health, the following recommendations can be considered:

1. Improve infrastructure and transportation: Enhance the availability and accessibility of health facilities in rural areas by investing in infrastructure and transportation systems. This can include building more health clinics and improving road networks to reduce travel distances and time.

2. Mobile health services: Implement mobile health services, such as mobile clinics or telemedicine, to reach remote areas where access to health facilities is limited. This can provide prenatal HIV testing and other maternal health services directly to communities that are geographically isolated.

3. Community-based education and awareness programs: Conduct community-based education programs to increase awareness about the importance of prenatal HIV testing and the prevention of mother-to-child transmission of HIV. This can involve engaging community leaders, local health workers, and community health volunteers to disseminate information and address misconceptions.

4. Financial support and incentives: Provide financial support and incentives to encourage pregnant women, especially those from low-income households, to access prenatal HIV testing. This can include subsidizing the cost of testing or providing incentives such as transportation vouchers or cash transfers.

5. Strengthen health systems: Strengthen the overall health system by improving the quality and availability of maternal health services. This can involve training healthcare providers on prenatal HIV testing and PMTCT, ensuring the availability of testing kits and medications, and implementing quality assurance mechanisms.

By implementing these recommendations, it is possible to improve access to maternal health services, including prenatal HIV testing, in East Africa. This can contribute to the prevention of mother-to-child transmission of HIV and ultimately help end the HIV/AIDS epidemic in the region.

AI Innovations Methodology

Based on the provided description, here are some potential recommendations to improve access to maternal health in East Africa:

1. Strengthening maternal education: Promote and provide accessible education for women, particularly in rural areas, to increase their knowledge and awareness about maternal health, including the importance of prenatal HIV testing.

2. Partner involvement: Encourage the involvement of partners in maternal health care, including prenatal HIV testing, by providing education and awareness programs targeting men.

3. Improving household wealth: Implement interventions to address poverty and improve household wealth, as higher household wealth has been associated with increased uptake of prenatal HIV testing.

4. Enhancing media exposure: Increase access to media platforms such as radio, television, and newspapers to disseminate information about maternal health and the prevention of mother-to-child transmission of HIV.

5. Addressing geographical barriers: Develop strategies to overcome the challenges faced by women living in rural communities and those who have to travel long distances to access health facilities. This can include establishing mobile health clinics or providing transportation services.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Define indicators: Identify specific indicators to measure the impact of the recommendations, such as the percentage increase in prenatal HIV test uptake, the reduction in geographical barriers, or the improvement in maternal education levels.

2. Data collection: Collect data on the current status of the indicators in the target population, including information on maternal education, partner involvement, household wealth, media exposure, and geographical barriers.

3. Intervention implementation: Implement the recommended interventions in a selected sample population or community. This could involve targeted educational programs, economic empowerment initiatives, media campaigns, or infrastructure improvements.

4. Monitor and evaluate: Continuously monitor and evaluate the impact of the interventions on the selected indicators. This can be done through surveys, interviews, or data analysis.

5. Analyze and compare: Analyze the data collected before and after the implementation of the interventions to assess the changes in the indicators. Compare the results to determine the effectiveness of the recommendations in improving access to maternal health.

6. Adjust and refine: Based on the findings, make adjustments and refinements to the interventions as needed. This iterative process allows for continuous improvement and optimization of the strategies to achieve the desired outcomes.

By following this methodology, policymakers and healthcare providers can assess the effectiveness of the recommendations and make informed decisions on scaling up successful interventions to improve access to maternal health in East Africa.

Author

Dima Health

Statistics:

Citations: 3

Identifiers:

DOI: 10.3390/ijerph18105289

ISSN: 16617827

Research Areas:

Community Interventions, Food Security, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants, Violence and Injury

Study Countries:

Burundi, Comoros, Ethiopia, Kenya, Malawi, Mozambique, Multi-Countries, Rwanda, Tanzania, Uganda, Zambia, Zimbabwe

Study Design:

Cross Sectional Study, Grounded Theory

Study Approach:

Quantitative

Participants Gender:

Female