Predictors of maternal and newborn health service utilization across the continuum of care in Ethiopia: A multilevel analysis

PLoS ONE, Volume 17, No. 2 February, Year 2022

Interpretation

Background The continuum of care for maternal and newborn health is a systematic approach for delivery of an integrated effective package of life-saving interventions throughout pregnancy, childbirth, and postpartum as well as across levels of service delivery to women and newborns. Nonetheless, in low-income countries, coverage of these interventions across the life cycle continuum is low. This study examined the predictors of utilization of maternal and newborn health care services along the continuum of care in Ethiopia. Methods This was a cross-sectional population-based study. We measured maternal and newborn health care utilization practices among women who had live births in the last 12 months preceding the survey in Amhara, Oromia, SNNP, and Tigray regions of Ethiopia. We fitted multilevel random-effects logistic regression models to examine the predictors of the continuum of care accounting for the survey design, and individual, and contextual characteristics of the respondents. Results Our analysis revealed that only one-fifth of women utilized maternal and newborn health services across the antepartum, intrapartum, and postpartum continuum; most women discontinued at the postpartum stage. Continued use of services varied significantly across wealth, model family, prenatal stay at maternity waiting homes, antenatal care in the first trimester, complete antenatal care service, and the administrative region at all antepartum, intrapartum, and postpartum stages. Moreover, family conversation during pregnancy [AOR: 2.12; 95% CI: 1.56–2.88], delivery by cesarean [AOR: 2.70; 95% CI: 1.82–4.02] and birth notified to health extension workers [AOR: 1.95; 95% CI: 1.56–2.43] were found to be predictors of the continuum of care at the postpartum stage. Conclusion In Ethiopia, despite good access to antepartum care, compliance with continuity of care across the pathway decreased with significant inequitable distributions, the poorest segment of the population being at most disadvantage. The main modifiable program factors connected to the continued uptake of maternal health services include family conversation, pregnant women conference, complete antenatal care, antenatal care in the first trimester, and birth notification. Administratively, Ethiopia is divided into 12 geographic regions where regions are divided into zones, which are internally divided into woredas (i.e., districts) and each woreda into the smallest administrative unit called kebeles. In Ethiopia packages of maternal and newborn health interventions are delivered through home-based, community-based, and facility-based service delivery modalities. The country’s health system has primary level care (encompassing a primary hospital, health centers, and health posts), secondary level care, and tertiary level care [21]. The primary health care provides preventive and promotive community and outreach services through the expansion of the Health Extension Program (HEP), the national flagship community-based health care delivery system, and the engagement of community volunteers [21, 22]. The country developed different strategies and programs to improve maternal survival which include strengthening and promoting skilled delivery through community mobilization [23]. The government has also provided ambulances to districts to mitigate transportation barriers, trained and deploy midwives and mid-level professionals, to improve access to, and utilization of maternal and newborn health services [22, 23]. In line with the national health agenda, the Last Ten Kilometers (L10K) project of JSI Research and Training Institute Inc. has supported the HEP to engage local communities to improve high-impact reproductive, maternal, newborn, and child health care behavior and practices in four of the most populous regions of the country (i.e., Amhara, Oromia, Southern Nations, Nationalities and Peoples [SNNP], and Tigray) since 2008. Between 2013 and 2017, the project scaled its platform activities in 115 woredas to engage local communities to identify and address barriers to access maternal and newborn health services particularly to identify pregnant women and ensure they received antenatal, intrapartum, and postpartum care. Besides, since 2014, L10K has implemented family conversation and birth notification strategies to promote birth preparedness, essential newborn care, and early postnatal care [24]. The data used for this study were obtained from a cross-sectional population-based study representing the 115 rural woredas which were carried out by L10K Project from October‐November 2017. The survey population included women of the reproductive age group (15–49 years) who had a live birth in the 12 months before the survey. The survey employed a two-stage stratified cluster sampling method stratified by the administrative region where kebeles were selected first as primary sampling units with the probability of selection being proportionate to its population size. This was undertaken to enumerate a representative sample of 2,724 women aged 15 to 49 years who had a live birth in the 12 months preceding the survey. The details of the design are described elsewhere [25]. The data were gathered through face-to-face interviews with mothers. During the interview, information about household and socio-demographic characteristics of mothers, awareness and access to health services, and experiences related to the women’s use of maternal health services, was collected from women with children in their first year of life. The questionnaire (S1 Appendix) was translated into local languages (Amharic, Oromifa, and Tigrigna). Details of data collection processes are described elsewhere [26]. The adequacy of the sample size to address the study objective was assured considering 95% confidence level (Zα/2 = 1.96), design effect (D = 2), and power of 80% for double population formula for comparative cross-sectional study design. Based on Anderson’s health-seeking behavior model [27], a health service utilization model that provides a framework to systematically describe factors that influence individual decisions to use (or not use) health care services, researchers considered different exposure variables [5, 28] including lack of women’s autonomy, 1–2 parity, no media exposure, no difficulty of distance to access medical care, no difficulty of transport arrangement to access medical care, no maternal education, and poorest wealth quintile as exposure and highest parity/5+, having autonomy, exposed to media, having difficulty of distance and transport arrangement to access medical care, higher education, and richest wealth quintile as non-exposure. Adding a 10% non-response rate, the maximum sample size obtained by women’s autonomy to healthcare decision-making was 2,501 for completed CoC at pregnancy [28]. The outcome variables of interest of the study were the uptake of the CoC at antepartum, intrapartum, and postpartum stages: 1) continuum of care at the antepartum stage is women who received four or more antenatal care (ANC4+) visits, 2) continuum of care at the intrapartum stage is those women who continued use of skilled birth attendance after receiving ANC4+ visits, and 3) continuum of care at the postpartum stage or complete continuum is those women who received PNC for the mothers and their newborns, within six weeks of their delivery (either in a facility or at home) after receiving both ANC4+ visits and delivered by skilled assistance. Description and measurement of variables are presented in Table 1 below. For selecting predictor variables at individual and community levels, we adopted Anderson’s behavioral model for healthcare use [27]. The individual-level variables include wealth status, maternal education, distance to the health facility, being a model family, participation in pregnancy conference, having family conversation, early ANC booking, complete ANC service, and use of MWHs for prenatal stay. Besides, infant’s birth weight, mode of delivery and birth notification are included as predictor variables for CoC at the postpartum stage. The community variables considered in the study include region and area of residence (clusters/kebeles). Data were analyzed using Stata version 15. The characteristics of the sample respondents were described by a set of background characteristics. The difference in the characteristics of the respondents was examined using Pearson’s chi-square statistics adjusted for cluster survey design effects. Bivariate and multivariable mixed-effects logistic regression analyses were used to examine the predictors of the CoC accounting for cluster survey design, and the individual, and contextual characteristics of the respondents. We fitted three sequential random-effects logit regression models to examine the patterns of care-seeking and factors predicting the continuation of care. We fitted Model I among women receiving ANC4+ as the outcome (i.e., coded 1 for receiving ANC4+, otherwise 0); Model II among women who received ANC4+ to determine the factors associated with the continuity having skilled birth attendance (i.e., coded 1 for receiving ANC4+ and SBA, otherwise 0); and Model III fitted for women who received ANC4+ and SBA to identify factors associated with women returning for PNC visits or completion of the CoC (i.e., coded 1 for receiving ANC, SBA, and PNC, otherwise 0). The random-effects model accounts for the fact that people who live in the same area share similar characteristics and examine the proportion of variance explained by community-level factors (unobserved). We present the adjusted odds ratios and confidence intervals at the 95% level wherever applicable. The global Wald’s statistics, the likelihood ratio test of the cluster-level random effects, and sensitivity of the quadrature approximation were used to assess the goodness-of-fit of the models. Regression diagnostic Akaike Information Criterion (AIC) was used to determine the suitability of the model. For this study, we obtained permission to use the data from the JSI, and ethics approval was obtained from the Research and Ethics Committee of the Department of Health Studies of the University of Gondar (reference number V/P/RCS/05/2505/2019; dated 25 August 2019). The original study was ethically approved by the Ethical Review Boards of Amhara, Oromia, SNNP, and Tigray Regional Health Bureaus, and JSI. Verbal consent from respondents was sought and documented by interviewers before interviewing. Voluntary participation was ensured during interviews [25].

AI Digest

Study Justification:

– The study aims to examine the predictors of utilization of maternal and newborn health care services along the continuum of care in Ethiopia.
– The continuum of care approach is a systematic approach for delivering integrated life-saving interventions throughout pregnancy, childbirth, and postpartum, but coverage of these interventions is low in low-income countries.
– Understanding the predictors of utilization can help identify barriers and inform interventions to improve access and utilization of maternal and newborn health services.

Study Highlights:

– Only one-fifth of women in Ethiopia utilized maternal and newborn health services across the antepartum, intrapartum, and postpartum continuum.
– Most women discontinued using services at the postpartum stage.
– Factors associated with continued use of services included wealth, model family status, prenatal stay at maternity waiting homes, early antenatal care, complete antenatal care, and administrative region.
– Family conversation during pregnancy, delivery by cesarean, and birth notification to health extension workers were predictors of continued care at the postpartum stage.
– Compliance with continuity of care decreased with significant inequitable distributions, with the poorest segment of the population being most disadvantaged.

Recommendations for Lay Reader and Policy Maker:

– Improve access and utilization of maternal and newborn health services across the continuum of care.
– Strengthen interventions to address barriers to utilization, such as improving wealth equity, promoting early antenatal care, and ensuring access to maternity waiting homes.
– Enhance family conversations during pregnancy to promote birth preparedness and essential newborn care.
– Increase awareness and utilization of complete antenatal care services.
– Strengthen birth notification strategies to improve postpartum care.

Key Role Players:

– Ministry of Health: Responsible for policy development and implementation of maternal and newborn health programs.
– Health Extension Workers: Provide community-based health care services and play a crucial role in promoting maternal and newborn health.
– Health Facilities: Provide antenatal, intrapartum, and postpartum care services.
– Community Volunteers: Engage with local communities to improve health care behavior and practices.
– Non-Governmental Organizations: Support implementation of maternal and newborn health programs and interventions.

Cost Items for Planning Recommendations:

– Training and capacity building for health workers and volunteers.
– Infrastructure development, including the establishment and maintenance of health facilities and maternity waiting homes.
– Supply and distribution of essential maternal and newborn health commodities.
– Community mobilization and awareness campaigns.
– Monitoring and evaluation of program implementation.
– Research and data collection to inform evidence-based interventions.
Please note that the cost items provided are general categories and not actual cost estimates. The actual cost will depend 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 relatively strong, but there are some areas for improvement. The study design is cross-sectional, which limits the ability to establish causality. Additionally, the abstract does not provide information on the sample size or response rate, which could affect the generalizability of the findings. To improve the evidence, future studies could consider using a longitudinal design to better understand the predictors of maternal and newborn health service utilization. Additionally, providing information on the sample size and response rate would enhance the transparency and reliability of the study.

Abstract

Administratively, Ethiopia is divided into 12 geographic regions where regions are divided into zones, which are internally divided into woredas (i.e., districts) and each woreda into the smallest administrative unit called kebeles. In Ethiopia packages of maternal and newborn health interventions are delivered through home-based, community-based, and facility-based service delivery modalities. The country’s health system has primary level care (encompassing a primary hospital, health centers, and health posts), secondary level care, and tertiary level care [21]. The primary health care provides preventive and promotive community and outreach services through the expansion of the Health Extension Program (HEP), the national flagship community-based health care delivery system, and the engagement of community volunteers [21, 22]. The country developed different strategies and programs to improve maternal survival which include strengthening and promoting skilled delivery through community mobilization [23]. The government has also provided ambulances to districts to mitigate transportation barriers, trained and deploy midwives and mid-level professionals, to improve access to, and utilization of maternal and newborn health services [22, 23]. In line with the national health agenda, the Last Ten Kilometers (L10K) project of JSI Research and Training Institute Inc. has supported the HEP to engage local communities to improve high-impact reproductive, maternal, newborn, and child health care behavior and practices in four of the most populous regions of the country (i.e., Amhara, Oromia, Southern Nations, Nationalities and Peoples [SNNP], and Tigray) since 2008. Between 2013 and 2017, the project scaled its platform activities in 115 woredas to engage local communities to identify and address barriers to access maternal and newborn health services particularly to identify pregnant women and ensure they received antenatal, intrapartum, and postpartum care. Besides, since 2014, L10K has implemented family conversation and birth notification strategies to promote birth preparedness, essential newborn care, and early postnatal care [24]. The data used for this study were obtained from a cross-sectional population-based study representing the 115 rural woredas which were carried out by L10K Project from October‐November 2017. The survey population included women of the reproductive age group (15–49 years) who had a live birth in the 12 months before the survey. The survey employed a two-stage stratified cluster sampling method stratified by the administrative region where kebeles were selected first as primary sampling units with the probability of selection being proportionate to its population size. This was undertaken to enumerate a representative sample of 2,724 women aged 15 to 49 years who had a live birth in the 12 months preceding the survey. The details of the design are described elsewhere [25]. The data were gathered through face-to-face interviews with mothers. During the interview, information about household and socio-demographic characteristics of mothers, awareness and access to health services, and experiences related to the women’s use of maternal health services, was collected from women with children in their first year of life. The questionnaire (S1 Appendix) was translated into local languages (Amharic, Oromifa, and Tigrigna). Details of data collection processes are described elsewhere [26]. The adequacy of the sample size to address the study objective was assured considering 95% confidence level (Zα/2 = 1.96), design effect (D = 2), and power of 80% for double population formula for comparative cross-sectional study design. Based on Anderson’s health-seeking behavior model [27], a health service utilization model that provides a framework to systematically describe factors that influence individual decisions to use (or not use) health care services, researchers considered different exposure variables [5, 28] including lack of women’s autonomy, 1–2 parity, no media exposure, no difficulty of distance to access medical care, no difficulty of transport arrangement to access medical care, no maternal education, and poorest wealth quintile as exposure and highest parity/5+, having autonomy, exposed to media, having difficulty of distance and transport arrangement to access medical care, higher education, and richest wealth quintile as non-exposure. Adding a 10% non-response rate, the maximum sample size obtained by women’s autonomy to healthcare decision-making was 2,501 for completed CoC at pregnancy [28]. The outcome variables of interest of the study were the uptake of the CoC at antepartum, intrapartum, and postpartum stages: 1) continuum of care at the antepartum stage is women who received four or more antenatal care (ANC4+) visits, 2) continuum of care at the intrapartum stage is those women who continued use of skilled birth attendance after receiving ANC4+ visits, and 3) continuum of care at the postpartum stage or complete continuum is those women who received PNC for the mothers and their newborns, within six weeks of their delivery (either in a facility or at home) after receiving both ANC4+ visits and delivered by skilled assistance. Description and measurement of variables are presented in Table 1 below. For selecting predictor variables at individual and community levels, we adopted Anderson’s behavioral model for healthcare use [27]. The individual-level variables include wealth status, maternal education, distance to the health facility, being a model family, participation in pregnancy conference, having family conversation, early ANC booking, complete ANC service, and use of MWHs for prenatal stay. Besides, infant’s birth weight, mode of delivery and birth notification are included as predictor variables for CoC at the postpartum stage. The community variables considered in the study include region and area of residence (clusters/kebeles). Data were analyzed using Stata version 15. The characteristics of the sample respondents were described by a set of background characteristics. The difference in the characteristics of the respondents was examined using Pearson’s chi-square statistics adjusted for cluster survey design effects. Bivariate and multivariable mixed-effects logistic regression analyses were used to examine the predictors of the CoC accounting for cluster survey design, and the individual, and contextual characteristics of the respondents. We fitted three sequential random-effects logit regression models to examine the patterns of care-seeking and factors predicting the continuation of care. We fitted Model I among women receiving ANC4+ as the outcome (i.e., coded 1 for receiving ANC4+, otherwise 0); Model II among women who received ANC4+ to determine the factors associated with the continuity having skilled birth attendance (i.e., coded 1 for receiving ANC4+ and SBA, otherwise 0); and Model III fitted for women who received ANC4+ and SBA to identify factors associated with women returning for PNC visits or completion of the CoC (i.e., coded 1 for receiving ANC, SBA, and PNC, otherwise 0). The random-effects model accounts for the fact that people who live in the same area share similar characteristics and examine the proportion of variance explained by community-level factors (unobserved). We present the adjusted odds ratios and confidence intervals at the 95% level wherever applicable. The global Wald’s statistics, the likelihood ratio test of the cluster-level random effects, and sensitivity of the quadrature approximation were used to assess the goodness-of-fit of the models. Regression diagnostic Akaike Information Criterion (AIC) was used to determine the suitability of the model. For this study, we obtained permission to use the data from the JSI, and ethics approval was obtained from the Research and Ethics Committee of the Department of Health Studies of the University of Gondar (reference number V/P/RCS/05/2505/2019; dated 25 August 2019). The original study was ethically approved by the Ethical Review Boards of Amhara, Oromia, SNNP, and Tigray Regional Health Bureaus, and JSI. Verbal consent from respondents was sought and documented by interviewers before interviewing. Voluntary participation was ensured during interviews [25].

Materials

Innovations

The study titled “Predictors of maternal and newborn health service utilization across the continuum of care in Ethiopia: A multilevel analysis” provides valuable insights into improving access to maternal health in Ethiopia. Based on the findings of the study, the following recommendations can be developed into innovations to enhance access to maternal health:

1. Strengthening the Health Extension Program (HEP): Innovations can focus on expanding and improving the HEP to provide preventive and promotive services related to maternal and newborn health. This can include training and deploying more health extension workers, engaging community volunteers, and enhancing community mobilization efforts.

2. Enhancing community engagement: Innovations can involve strategies to actively engage local communities in identifying and addressing barriers to accessing maternal and newborn health services. This can be achieved through initiatives like the Last Ten Kilometers (L10K) project, which promotes community involvement in improving reproductive, maternal, newborn, and child health care behavior and practices.

3. Promoting birth preparedness and essential newborn care: Innovations can focus on implementing strategies like family conversations and birth notification to raise awareness and promote birth preparedness, essential newborn care, and early postnatal care.

4. Improving transportation infrastructure: Innovations can address transportation barriers by providing ambulances to districts, especially in remote areas, to facilitate timely access to maternal health services.

5. Addressing socioeconomic disparities: Innovations should prioritize addressing socioeconomic disparities in accessing maternal health services. This can involve targeted interventions to improve access for the poorest segments of the population, such as providing financial support or incentives for utilizing maternal health services.

6. Strengthening antenatal care services: Innovations can focus on improving the quality and availability of antenatal care services, including early booking and complete antenatal care.

By implementing these recommendations as innovative interventions, access to maternal health services in Ethiopia can be improved, leading to better health outcomes for mothers and newborns.

AI Innovations Description

1. Strengthening the Health Extension Program (HEP): The HEP is a community-based health care delivery system in Ethiopia. Innovations can focus on expanding and improving the HEP to provide preventive and promotive services related to maternal and newborn health. This can include training and deploying more health extension workers, engaging community volunteers, and enhancing community mobilization efforts.

2. Enhancing community engagement: Innovations can involve strategies to actively engage local communities in identifying and addressing barriers to accessing maternal and newborn health services. This can be achieved through initiatives like the Last Ten Kilometers (L10K) project, which promotes community involvement in improving reproductive, maternal, newborn, and child health care behavior and practices.

3. Promoting birth preparedness and essential newborn care: Innovations can focus on implementing strategies like family conversations and birth notification to raise awareness and promote birth preparedness, essential newborn care, and early postnatal care. These strategies can be integrated into existing programs and initiatives to ensure comprehensive care throughout the continuum.

4. Improving transportation infrastructure: Innovations can address transportation barriers by providing ambulances to districts, especially in remote areas, to facilitate timely access to maternal health services. This can help overcome geographical challenges and ensure that pregnant women can reach health facilities for antenatal, intrapartum, and postpartum care.

5. Addressing socioeconomic disparities: Innovations should prioritize addressing socioeconomic disparities in accessing maternal health services. This can involve targeted interventions to improve access for the poorest segments of the population, such as providing financial support or incentives for utilizing maternal health services.

6. Strengthening antenatal care services: Innovations can focus on improving the quality and availability of antenatal care services, including early booking and complete antenatal care. This can be achieved through training and capacity building for health care providers, ensuring the availability of necessary equipment and supplies, and promoting community awareness about the importance of antenatal care.

By implementing these recommendations as innovative interventions, access to maternal health services in Ethiopia can be improved, leading to better health outcomes for mothers and newborns.

AI Innovations Methodology

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

1. Define the target population: Identify the specific population group or region in Ethiopia that will be the focus of the simulation. This could be a specific district, region, or the entire country, depending on the scope of the simulation.

2. Collect baseline data: Gather relevant data on the current status of maternal health access in the target population. This can include information on utilization rates of maternal and newborn health services, socioeconomic indicators, transportation infrastructure, and existing healthcare programs.

3. Develop a simulation model: Create a mathematical or computational model that represents the target population and simulates the impact of the recommendations. The model should incorporate factors such as population demographics, healthcare infrastructure, socioeconomic disparities, and the proposed innovations.

4. Define intervention scenarios: Based on the recommendations, define different intervention scenarios that can be simulated. For example, one scenario could involve strengthening the Health Extension Program (HEP) by training and deploying more health extension workers, while another scenario could focus on improving transportation infrastructure by providing ambulances to remote areas.

5. Input data and run simulations: Input the baseline data into the simulation model and run the simulations for each intervention scenario. The model should generate outputs that quantify the impact of each scenario on access to maternal health services, such as changes in utilization rates, reduction in socioeconomic disparities, or improvements in transportation access.

6. Analyze and interpret results: Analyze the simulation results to assess the effectiveness of each intervention scenario in improving access to maternal health. Compare the outcomes of different scenarios to identify the most impactful innovations. Interpret the results in the context of the target population and consider any limitations or assumptions of the simulation model.

7. Communicate findings and recommendations: Present the simulation findings in a clear and concise manner, highlighting the potential benefits of implementing the recommended innovations. Provide actionable recommendations based on the simulation results, taking into account the specific context and resources available in Ethiopia.

By following this methodology, policymakers and stakeholders can gain valuable insights into the potential impact of the recommendations on improving access to maternal health in Ethiopia. This can inform decision-making and guide the implementation of innovative interventions to enhance maternal health services.

Author

Dima Health

Statistics:

Citations: 3

Identifiers:

DOI: 10.1371/journal.pone.0264612

Research Areas:

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

Study Countries:

Ethiopia

Study Design:

Cross Sectional Study, Grounded Theory

Study Approach:

Quantitative

Participants Gender:

Female