Evaluating the role of the Health Bazaar Initiative on Sexual and Reproductive Health Service Utilization in Ethiopia: A Comparative Analysis of community- based interventions

Evaluating the role of the Health Bazaar Initiative on Sexual and Reproductive Health Service Utilization in Ethiopia: A Comparative Analysis of community- based interventions | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluating the role of the Health Bazaar Initiative on Sexual and Reproductive Health Service Utilization in Ethiopia: A Comparative Analysis of community- based interventions Muluken Dessalegn, Woldu Kidanie, Sintayehu Abebe, Geteneh Moges, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6457796/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Nov, 2025 Read the published version in Reproductive Health → Version 1 posted 9 You are reading this latest preprint version Abstract Background: Access to Sexual and Reproductive Health (SRH) services remains a significant public health challenge, particularly in rural and underserved areas. The Health Bazaar initiative was introduced as a community-based intervention to improve SRH service utilization and family planning uptake among reproductive-age women in Ethiopia. This study evaluates the effectiveness of the Health Bazaar model in improving access to SRH services, institutional delivery, antenatal care (ANC), postnatal care (PNC), and contraceptive utilization in intervention (Health Bazaar) compared to non-intervention areas (running SRH services in the routine health system). Methods: A comparative cross-sectional study was conducted in five Ethiopian regions where the Health Bazaar model was implemented. Data were collected from 1,284 reproductive-age women (15–49 years), equally distributed between intervention (n=642) and non-intervention (n=642) areas. Additionally, secondary data from the District Health Information System (DHIS2) (2018–2024) were analysed to assess trends in SRH service utilization. A multistage cluster sampling approach was used, and data were analysed using descriptive statistics, trend analysis, and multilevel mixed-effects logistic regression to identify factors associated with SRH service uptake. Results: The study found that SRH service utilization was significantly higher in intervention areas (65.1%) compared to non-intervention areas (47.6%) (p < 0.001). Contraceptive prevalence was also higher in intervention areas (53.3% vs. 41.8%, p = 0.001), with injectables (45.8%) and implants (44.5%) being the most commonly used methods. ANC service utilization was higher in intervention areas (87.3%) compared to non-intervention areas (77.1%), and institutional delivery rates were 89.4% in intervention areas compared to 80.6% in non-intervention areas. Trend analysis showed a greater increase in ANC (10.2 per quarter), institutional deliveries (5.8 per quarter), and PNC utilization (9.5 per quarter) in intervention areas compared to non-intervention areas. These differences remained statistically significant after adjusting for potential confounding factors, including age, marital status, education, household income, region, and participation in SRH-related discussions. Conclusion: The study findings demonstrate that the Health Bazaar intervention significantly improved SRH service utilization, family planning uptake, and maternal health service access in Ethiopia. The community-driven model holds potential for scaling up to further enhance SRH services in similar low-resource settings. Future interventions should focus on addressing remaining barriers such as awareness gaps, distance to health facilities, and socio-cultural influences to maximize impact. Sexual and Reproductive Health Family Planning Community-Based Health Interventions Maternal Health Services Ethiopia Figures Figure 1 Figure 2 Figure 3 Figure 4 Plain English Summary Many women in rural and hard-to-reach areas of Ethiopia face serious challenges when it comes to accessing sexual and reproductive health (SRH) services, such as family planning, antenatal care, and skilled birth assistance. These challenges include long distances to health facilities, lack of information, cultural beliefs, and economic hardship. To address this problem, Amref Health Africa implemented a new approach called the Health Bazaar—a mobile, community-based health event that brings SRH services directly to the people. These events provide information, free health services, and create safe spaces for women to learn and ask questions about their health. This study compared health outcomes between areas where Health Bazaars were held and areas that continued with regular health services. We collected data from over 1,200 women and reviewed health system records to see if the intervention made a difference. The results showed that women in Health Bazaar areas were more likely to use contraceptives, attend antenatal care, give birth at health facilities, and receive postnatal care. These improvements were significantly higher than in areas without the intervention. Women also reported feeling more informed and supported in making decisions about their reproductive health. Our findings suggest that the Health Bazaar model is a promising strategy to improve access to SRH services in underserved communities. With proper support and investment, this approach could be scaled up across similar low-resource settings to help ensure that all women—no matter where they live—can access the care they need. 1. Background Sexual and reproductive health (SRH) services play a crucial role in improving maternal health outcomes, reducing maternal mortality, and enhancing the overall well-being of women of reproductive age. Over the past two decades ( 1 ), Ethiopia has made significant progress in expanding SRH services through a combination of government-led initiatives and international partnerships. These efforts have resulted in increased contraceptive use, higher antenatal care (ANC) attendance, and greater access to skilled birth attendants ( 2 , 3 ). However, despite these advancements, maternal mortality rates remain high when compared to global standards ( 4 ). SRH service disparities remain a pressing public health issue in Ethiopia, particularly affecting pastoralist and agrarian communities. While the national average for modern contraceptive use among women is 41%, it drops to below 20% in many pastoralist areas ( 5 ). Similarly, institutional delivery rates are above 80% in urban centres like Addis Ababa but fall below 30% in remote rural regions ( 6 ). These inequities are driven by multiple factors: over 30% of healthcare costs are still paid out-of-pocket despite the scale-up of community-based health insurance (CBHI) to over 827 woredas; geographic inaccessibility in sparsely populated or mobile pastoralist zones; deep-rooted sociocultural norms that restrict women’s autonomy; and shortages in trained health providers and youth-friendly services ( 4 – 8 ). Adolescents and young women are disproportionately affected due to early marriage and limited access to education and SRH information. Addressing these gaps requires targeted, community-based interventions and strengthened health systems that reflect the needs and realities of Ethiopia’s most marginalized populations ( 5 ). Ethiopia has implemented various health interventions to improve maternal and reproductive health. One of the most influential programs is the Health Extension Program (HEP), which deploys Health Extension Workers (HEWs) to provide SRH services at the community level ( 9 ). Additionally, the government has expanded free maternal healthcare services in public health facilities, covering family planning, ANC, and institutional delivery services ( 5 , 10 ). However, the delivery of demand-responsive health services remains limited, especially for adolescents, unmarried youth, and marginalized groups who face barriers such as stigma, lack of privacy, and inflexible service models ( 11 , 12 ). Despite increased access, the system largely remains supply-driven, with minimal integration of innovative approaches like mobile health, digital platforms, or comprehensive youth-focused models that include mental health, life skills, and financial empowerment. This gap highlights the urgent need for more user-centered, inclusive service delivery mechanisms to improve uptake and equity in SRH access ( 13 , 14 ). Financial barriers have been addressed through CBHI, which aims to reduce out-of-pocket expenditures and improve healthcare access for low-income populations ( 5 , 15 ). Large-scale public health campaigns have also played a role in increasing awareness and acceptance of contraceptive methods, contributing to a rise in contraceptive prevalence rates ( 16 ). While these initiatives have improved overall SRH service uptake, inconsistent in implementation and significant disparities persists especially in rural and pastoralist regions where healthcare infrastructure is weak and sociocultural barriers are high ( 7 , 17 ). This highlights the need to explore alternative approaches that can more effectively reach and engage these communities. One such intervention is the Health Bazaar model, which was implemented by Amref Health Africa in Ethiopia as part of the RESET Plus family planning project. This approach integrates SRH services into mobile, community-based health events, making them more accessible to women in hard-to-reach areas. While this intervention has been operational from 2022 to 2024 its impact on SRH service uptake has not been systematically evaluated or documented. Given the persistent gaps in SRH service utilization in Ethiopia, this study seeks to assess the effectiveness of the Health Bazaar model in increasing the uptake of SRH services. Specifically, it aims to compare SRH service utilization rates among women in Health Bazaar intervention areas versus non-intervention areas within the Amref RESET Plus family planning project ( 18 ). Despite the growing body of research on SRH in Ethiopia, previous studies have several limitations. First, most evaluations have focused on facility-based service delivery, neglecting the potential of community-driven models, such as the Health Bazaar, to reach underserved populations ( 14 ). Second, disaggregated data comparing intervention and non-intervention sites are scarce, making it difficult to assess the effectiveness of specific interventions. Third, existing studies have not sufficiently examined the influence of contextual factors, such as geographic location, cultural beliefs, and economic constraints, on SRH service uptake. These gaps in research underscore the need for a comprehensive study that evaluates community-based health service delivery models and their impact on SRH service utilization in Ethiopia. Despite the documented progress in Ethiopia’s SRH sector, the effectiveness of mobile, community-integrated health service delivery models in increasing SRH service uptake has not been well studied. Additionally, there is limited research on the sustainability and scalability of interventions like the Health Bazaar. Another key gap in knowledge is understanding the role of individual- and community-level factors—such as education, household income, and cultural norms—in influencing SRH service utilization ( 6 , 15 ). This study aims to estimate the effects of the Health Bazaar intervention by comparing SRH service uptake in intervention and non-intervention areas. The findings will provide evidence-based insights to guide the scale up of community-driven health service delivery models and support national health policy decisions for improving SRH services in Ethiopia. 2. Methods 2.1 Study Design This study employed a comparative cross-sectional design with a multilevel mixed-effects analysis to assess the impact of the Health Bazaar intervention on SRH service uptake in Ethiopia. It integrated both primary data collection—through structured surveys—and secondary data analysis using client flow data extracted from the DHIS2 system, enabling a comprehensive assessment of trends in SRH service utilization across intervention and non-intervention areas. 2.2 Study setting and period The EU’s Resilience Building in Ethiopia (RESET) program is a multi-phase initiative targeting vulnerable, drought-prone regions to address root causes of instability, displacement, and irregular migration. Below are key elements of its implementation across Ethiopian clusters: the primary goal ( https://www.eeas.europa.eu/node/47222_fr ) is strengthen resilience to natural and human-induced crises (e.g., droughts, conflicts), create economic opportunities to reduce distress migration, improve access to basic services (healthcare, water, education) and disaster risk management. The geographic focus of the program targets am five regions: Afar, Amhara, Oromia, SNNPR, and Key Clusters includes Wag Himra (Amhara), Afar (Afar), Siti/Liben (Somali), Bale/Borena (Oromia), Wolayta/South Omo (South Ethiopia). These areas were selected for their high vulnerability to climate shocks, food insecurity, and proximity to migration routes (e.g., borders with Kenya, Somalia, Djibouti). It has three Implementation Phases from 2012 to 2024. The study focused on the intervention of phases Implemented by Amref health Africa in Ethiopia. The RESET Plus I family planning project, the second phase of the initiative (2022 − 2024), is being implemented across five clusters/zones in four regions covering 16 woredas in Ethiopia. The project is managed by Amref Health Africa Italy, in collaboration with Amref Health Africa Ethiopia (lead in-country), Women Empowerment in Action, and the Kulich Youth Reproductive Health and Development Organization (KYRHDO). The study intervention areas include hard-to-reach, rural, and pastoralist districts in four of the regions where access to SRH services are typically limited. In addition to the intervention areas, a control group was selected from non-intervention areas, ensuring that any potential spillover effects from the intervention sites were accounted for in the comparison (Table 1 ). Health Bazaar Operational Definition and Implementation A Health Bazaar is a community-based, mobile health service delivery model designed to improve access to SRH services by bringing healthcare providers closer to communities in underserved areas. These events are typically organized in open spaces within villages or near primary healthcare facilities, allowing for both service provision and community engagement. The implementation of health bazaars involved: Planning and Mobilization: Community sensitization activities were conducted through local leaders, health extension workers, and social mobilization campaigns to raise awareness about the health bazaar events. Service Provision: A range of SRH services, including contraceptive provision, ANC, skilled birth attendance referrals, HIV testing, and health education, were offered. Health Promotion and Education: Trained health professionals provided health education sessions to promote the utilization of available SRH services. Collaboration with Local Stakeholders: Health bazaars were organized in partnership with local health offices, community leaders, and non-governmental organizations to enhance service coverage and ensure sustainability. Data Collection and Monitoring: Service utilization data were recorded at each event to track the number of individuals served and measure key SRH indicators. Table 1 Health Bazaar Intervention and Non-Intervention Study Sites in Ethiopia (2024) Cluster Intervention District Non-Intervention District South Omo Hamer Benasemay Borana Moyale Dillo Wolaita Duguna Fango Boloso Bombe Waghimra Sekota Zuria Dahana Afar Afambo Bidu 2.3. Study Population and Data Sources 2.3.1. Comparative Cross-Sectional Study The source population consisted of women of reproductive age (15–49 years) residing in both the Health Bazaar intervention and non-intervention areas. The study population was selected from districts where the Health Bazaar program was implemented, along with matched non-intervention districts. 2.3.2. Secondary Data Sources To analyze trends in sexual and reproductive health (SRH) service utilization, data were extracted from DHIS2 for both intervention and non-intervention sites. The extracted data covered the period 2018 to 2024 to assess trends in SRH indicators. 2.4. Inclusion and Exclusion Criteria 2.4.1. Inclusion Criteria Comparative Cross-Sectional Study: All women of reproductive age (15–49 years) living in the selected intervention and non-intervention districts who are willing to provide consent were eligible for inclusion. Trend Analysis: All available SRH service utilization indicators from DHIS2 were included. 2.4.2. Exclusion Criteria Women who had lived in the study area for less than six months were excluded. 2.5. Sample Size Determination The required sample size was calculated using the double population proportion formula, with the following assumptions: 95% confidence interval, 80% power, 15% non-response rate, Design effect of 2 (to account for multistage sampling). Based on the assumption that the Health Bazaar intervention would improve SRH service utilization by 15% compared to non-intervention areas, the final sample size was 1340 women (670 in the intervention group and 670 in the non-intervention group). 2.6. Sampling Procedure A multistage cluster sampling approach was used for the comparative cross-sectional survey. 1. Stage 1: All districts in the intervention and non-intervention areas were listed. One intervention and one non-intervention district were randomly selected from each cluster. 2. Stage 2: Two kebeles were randomly selected—one from the Health Bazaar intervention area and one from the non-intervention area. After estimating the expected number of women of reproductive age (15–49 years) in each kebele, systematic random sampling was used to select study participants. If a household had more than one eligible participant, one was randomly selected. 2.7. Study Variables 2.7.1. Dependent Variable SRH Service Utilization 2.7.2. Independent Variables Individual-Level Factors: Age, religion, ethnicity, occupation, marital status, educational status, family size, discussion with husband about SRH issues. Community-Level Factors: Residence in an intervention vs. non-intervention area, cluster, region, and broader community influences. Cluster-Level Factors: District-level variations were considered for multilevel regression analysis. 2.8. Operational Definitions SRH Service Utilization: Measured based on self-reported use of at least one SRH service in the past six months (family planning, Antenatal care, Institutional delivery, postnatal care, contraceptive or SRH education/counselling). 2.9. Data Collection Tools and Procedures The questionnaire was adapted from WHO Global Standards for SRH Services and validated through expert review. The tool was translated into local languages and pre-tested before data collection. Trained data collectors administered the survey through face-to-face interviews. 2.9.1. Secondary Data Extraction DHIS2 data were retrieved using a structured extraction checklist, focusing on key SRH indicators. 2.10. Data Quality Assurance Pre-testing was conducted before data collection, and necessary modifications were made. Data collectors underwent two days of training on data collection tools and interviewing techniques. Supervision and daily data quality checks were implemented. Data consistency and completeness were verified at the end of each collection day. 2.11. Data Management and Analysis Descriptive statistics were used to compare SRH service utilization across intervention and non-intervention groups. Trend analysis was conducted to assess changes in SRH service uptake over time. A two-level multilevel mixed-effects logistic regression was applied to account for hierarchical data structure. For the nature of such kind of data, a multilevel mixed effects regression analysis is preferred because the hierarchical nature of the data violated the principles of independence and homogeneity required for a single level analysis. This approach allows researchers to examine phenomena that occur at multiple levels within a hierarchical structure, providing a more comprehensive understanding of complex relationships by considering both individual-level and group-level factors simultaneously, which is particularly valuable when studying data where individuals are nested within groups ( 15 ). In addition, to identify individual and community level factors associated with SRH service uptake, a two-level multilevel mixed effects multivariable binary logistic regression has been used to address the hierarchical nature of the data. For such kind of data nature, a multilevel mixed effects regression analysis is preferred because the hierarchical nature of the data violated the principles of independence and homogeneity required for a single level analysis. The measure of the fixed effects was reported using Adjusted Odds Ratio (AORs) with 95% CI and p values. Also, the measures random effects were estimated as intra class correlation coefficients (ICC) and proportional change in variances (PCV) were also used to compute for each model with respect to the empty model to understand the relative contributions of both individual and community level variables to the higher-level variance on SRH service uptakes ( 15 ). Model selection was based on Akaike information criterion (AIC) and Bayesian information criteria (BIC), ensuring the best fit. AIC is more relevant for exploratory analysis in this context and BIC is more relevant for identifying the best model in fitting variables to estimate the association between dependent variable and independent variables. 3. Results 3.1 Sociodemographic Characteristics From the total calculated sample size 1340, 1,289 reproductive-age women (15–49 years) participated in the study, with a 96.2% response rate. The sample comprised 663 women from intervention areas (Health Bazaar model) and 623 from non-intervention areas. The mean age of participants was 27.8 years (SD: ±6.4), with almost three-quarters (72.5%) being married. Literacy rates were significantly higher in intervention areas (52.7%) compared to non-intervention areas (45.3%) (p = 0.03). A greater proportion of women in intervention areas reported household incomes above the poverty line (58.6%) compared to non-intervention areas (50.1%) (p = 0.02) (Table 2 ). Table 2 Distribution of participants in intervention and non-intervention areas for Health Bazaar, 2024. Variable Category Intervention (%) Total (%) Yes (%) No (%) Cluster Borena Cluster 129 (19.4) 126 (20.1) 255 (20.0) South Omo Custer 140 (21.1) 119 (19.0) 259 (20.06) Wolayita Cluster 136 (20.8) 125 (20.0) 261 (20.4) Afar Cluster 129 (19.4) 129 (20.6) 258 (20.0) Waghemira Cluster 129 (19.4) 127 (20.3) 256 (20.0) Total 663 (51.4) 626 (48.6) 1289 (100) 3.2. Sexual and Reproductive Health (SRH) Service Utilization and Family Planning Of the total women included in the survey, 730 (56.6%) had visited a health facility for SRH services in the last six months. A significantly higher proportion of women from intervention areas (65.1%) accessed SRHservices compared to those in non-intervention areas (47.6%) (Chi-square = 43.6, p < 0.001). The most reported reasons for visiting health facilities included family planning (79.2%), SRH counselling (61.4%), and ANC follow-up (34.8%). During the survey, 47.2% of reproductive-age women were using contraceptive methods (53.3% from intervention and 41.8% from non-intervention areas) with a statistically significant difference (Chi-square = 12.8, p < 0.001). The most frequently used contraceptive methods were injectables (45.8%) and implants (44.5%). Among those who visited health facilities for contraceptive services, 55.8% received counselling on method options, 54.5% were informed about possible side effects, and 44.0% were given guidance on managing potential complications before their next visit (Table 3 ). A total of 46.5% of participants underwent HIV testing and counselling services, with significantly higher rates in intervention areas (51.6%) than in non-intervention areas (41.1%) (Chi-square = 14.35, p < 0.001). Barriers to SRH service utilization were also assessed, with 63.0% of women citing a lack of awareness, 28.1% believing SRH services were unnecessary, and 3.6% reporting long distances to health facilities as reasons for not seeking services. Table 3 Current contraceptive use, related side effects and contents of consultation in intervention and non-interventions areas, 2024. Variable Category Intervention Total Yes No Current contraceptive use Yes 347 (53.3) 262 (41.8) 609 (47.24) No 316 (46.7) 364 (57.2) 680 (52.76) Discussion with partners about FP Yes 418 (71.6) 330 (59.7) 748 (65.7) No 166 (28.4) 224 (40.4) 390 (34.3) Type of contraceptive used currently Injectable 158(45.5) 120 (45.8) 279 (45.8) Implants 154 (44.4) 117 (44.7) 271 (44.5) IUCD 24 (6.9) 16 (6.1) 40 (6.6) Others 10 (3.3)) 9 (3.5) 189 (3.0) Report side effect Yes 192 (55.33) 140 (53.4) 332 (54.52) No 155 (44.67) 122 (46.6) 277 (45.48) Contents of consultation Explain about methods 201 (57.9) 69 (26.3) 340 (55.8) Describe possible side effects 168 (48.4) 164 (62.6) 332 (54.5) Explain what to do for any problems before the next visit 129 (37.2) 139 (53.1) 268 (44.0) Explains the possibility of changing method if you are not happy with it 145 (41.8) 107 (40.8) 252 (41.4) Demonstrate how to use it 119 (34.3) 97 (37.0) 216 (35.5) Explain where to go for follow up visit 114 (32.9) 78 (29.8) 192 (31.5) Explain about other methods 67 (19.3) 37 (14.1) 107 (17.6) Other 1 (0.3) 0 1 (0.2) Trends in Contraceptive Uptake A six-year trend analysis of intrauterine contraceptive device (IUCD) acceptors indicated a notable difference between intervention and non-intervention areas. Figure 1 shows a significant increase in IUCD acceptors in intervention areas (slope 0.0616 per quarter) compared to non-intervention areas (slope 0.0219 per quarter) highlighting the greater impact of Health Bazaar impact on IUCD uptake. Similarly, new acceptors of implants showed an increasing trend in both groups, although the rate of increase was higher in intervention areas (4.8 per quarter) compared to non-intervention areas (3.3 per quarter) (Fig. 1 ). 3.4. Maternal Health Service Utilization: Antenatal Care, Institutional Delivery, and Postnatal Care Antenatal Care Utilization Among the surveyed reproductive-age women, 16.1% were pregnant at the time of the study. Among these, 82.1% had at least one ANC follow-up, with the majority receiving services from health centres (71.2%). A higher proportion of pregnant women in intervention areas (87.3%) attended at least one ANC visit compared to those in non-intervention areas (77.1%). The main barriers to ANC utilization included distance to health facilities (40.5%), lack of awareness (37.8%), and being too busy to attend services (21.6%). Trend analysis showed a higher increase in ANC utilization over time in intervention areas compared to non-intervention areas. The number of women attending at least one ANC visit increased by 10.2 per quarter in intervention areas, while in non-intervention areas, it increased by 3.2 per quarter. Similarly, women completing four or more ANC visits (ANC4+) increased at a faster rate in intervention areas (10.2 per quarter) compared to non-intervention areas (3.2 per quarter) (Fig. 2 ). Institutional Delivery Among the 343 women (26.6%) who gave birth in the last 12 months, 84.3% delivered in health facilities, with a significantly higher proportion of women in intervention areas (89.4%) utilizing institutional delivery services compared to those in non-intervention areas (80.6%). The main reasons for home delivery included lack of partner support (14.0%), lack of transportation (30.0%), lack of awareness (44.0%), distance to facilities (20.0%), and preference for home-based care (30.0%). The trend analysis of institutional deliveries revealed a greater increase in intervention areas (5.8 per quarter) compared to non-intervention areas (4.6 per quarter) (Fig. 3 ). Postnatal Care Utilization Among the women who delivered, 64.7% received postnatal care (PNC) services, with higher utilization in intervention areas (66.5%) compared to non-intervention areas (63.0%) (Chi-square = 0.57, p > 0.05). Most PNC users accessed services at health centres (59.9%), followed by health posts (28.4%) and hospitals (10.8%). The major barriers to PNC utilization included lack of awareness (68.6%), distance to health facilities (14.0%), and lack of transport services (9.1%). Trend analysis indicated that PNC service utilization increased by 9.5 per quarter in intervention areas, whereas in non-intervention areas, the increase was 4.4 per quarter (Fig. 4 ). 3.5. Factors Associated with SRH Service Uptake A multilevel mixed-effects logistic regression identified key individual- and community-level determinants influencing the utilization of sexual and reproductive health (SRH) services. Age was a significant predictor, with women aged 19–49 years being more likely to use SRH services compared to younger women aged 15–18 years (AOR = 2.45, 95% CI: 1.15–6.69, p = 0.002). Marital status also influenced SRH utilization, as married women were less likely to seek SRH services compared to single women (AOR = 0.57, 95% CI: 0.07–0.64, p = 0.015). Engagement in discussions about SRH emerged as a strong predictor, with women who actively participated in SRH-related conversations being three times more likely to use SRH services (AOR = 3.21, 95% CI: 2.10–4.91, p < 0.001). Finally, residence in a Health Bazaar intervention area significantly increased the likelihood of SRH service utilization (AOR = 1.89, 95% CI: 1.32–2.69, p < 0.001). The intra-class correlation coefficient (ICC) decreased from 34–0.6%, suggesting that individual-level factors, particularly SRH discussions, had a major influence on service utilization (Table 4 ). Table 4 Factors Associated with Sexual and Reproductive Health (SRH) Service Uptake, Ethiopia 2024. Variables Category Model 2 Model 3 Model 4 Individual level factors Age of women 15–18 years 1 1 19–49 years 4.17(2.30,7.55) 2.78 (1.15,6.69)*** Religion Orthodox Christian 1 1 Protestant 0.87 (0.50,1.50) 0.99 (0.57,1.75) Muslim 1.23 (0.52,2.92) 1.21 (0.46,3.21) Catholic 1.13 (0.34,3.78) 1.48 (0.46,4.80) Other 0.91 (0.43,1.86) 1.16 (0.56,2.43) Ethnicity Amhara 1 1 Wolayita 2.02 (0.73,5.78) 1.43 (0.23,8.90) Afar 0.26 (0.09,0.78)* 0.50 (0.12,2.09) Oromo 5.50(1.75,17.00)** 1.80 (0.25,12.98) Agew 2.42 (0.23, 26.3) 3.32 (0.33,31.8) Hammer 0.42(0.14,1.28) 0.32 (0.06,1.76) Other 0.36 (0.13,0.99)* 0.25 (0.05, 1.36) Occupation Employed 1 1 Student 0.36 (0.21,0.62)*** 1.61(0.65,4.12) Unemployed 0.65 (0.47,0.90)** 0.73 (0.49,2.09) Marital status Married 1 1 Separated 0.21 (0.06,0.68)* 0.21 (0.07,0.64)* Single 1.07 (0.44, 2.64) 1.06(0.41,2.70) Divorced 2.43 (1.08,5.87)* 2.31 (0.96,5.55) Widowed 0.66 (0.24, 1.77) 0.71 (0.26,1.87) Educational status Cannot read and write 1 1 Only can write and write 1.12(0.66, 1.89) 1.02 (0.61,1.71) Primary school 1.07(0.71,1.62) 0.99 (0.65, 1.51) Secondary school 1.48(0.85,2.58) 1.34 (0.76, 2.37) Above secondary 0.92 (0.45,1.88) 0.80 (0.38, 1.68) Discussion with husband Yes 1 1 No 0.31(0.22,0.44)*** 0.29 (0.21,0.41)*** No husband 0.10(0.03,0.21)*** 0.08 (0.04,0.16)** Family size ≤ 4.3 *average 1 1 > 4.3 0.71(0.48,1.05) 0.66 (0.48, 0 .92)* Community level factors Study group Intervention 1 1 Non-intervention 0.38(0.28,0.53)*** 0.39(0.28,0.54)*** Residence Urban and semi urban 1 1 Rural 1.18 (0.79,1.77) 0.86 (0.53,1.39) Cluster Borena 1 1 Waghemira 0.11 (0.06,0.23)*** 0.17 (0.02, 1.55) Afar 0.06 (0.02, 0.08)*** 0.11 (0.01,1.10) South Omo 0.05 (0.23,0.09)*** 0.16 (0.04,0.66)** Wolyita 0.27 (0.15, 0.49)*** 0.27 (0.06,1.17) 4. Discussion This study evaluated the impact of the Health Bazaar model on sexual and reproductive health (SRH) service utilization among women of reproductive age in Ethiopia. The findings indicate that the intervention significantly improved modern contraceptive use, antenatal care (ANC) attendance, institutional delivery, and HIV testing and counselling services compared to non-intervention areas. Specifically, family planning service uptake was higher in intervention areas (53.3%) than in non-intervention areas (41.8%) (p = 0.001). Likewise, a higher proportion of women in intervention areas (87.2%) attended at least one ANC visit, compared to 71.1% in non-intervention areas (p = 0.001). Institutional deliveries were also more common among women in intervention areas (89.4%) compared to non-intervention areas (80.6%) (p = 0.02). These findings align with the study’s primary objective of assessing whether community-based interventions, such as the Health Bazaar, improve SRH service utilization and maternal health outcomes. Over the three-year implementation period of the Health Bazaar intervention, a consistent upward trend in the utilization of SRH services was observed in the intervention areas. This trend was confirmed through both primary data and DHIS2 trend analysis, which demonstrated higher and faster growth in service uptake—including family planning, ANC, institutional delivery, PNC, and HIV testing—compared to non-intervention areas. Multilevel mixed-effects logistic regression further substantiated this trend, revealing that women in Health Bazaar intervention areas were significantly more likely to utilize SRH services. Specifically, being in an intervention area was associated with 61% higher odds of SRH service uptake (AOR: 1.52; 95% CI: 1.09–2.08) compared to non-intervention areas. This suggests a strong, independent effect of the Health Bazaar model, even after adjusting for individual-level and community-level variables. This improvement can be attributed to several mechanisms embedded within the Health Bazaar model: increased physical accessibility, integration of SRH education with service delivery, and active community engagement. By addressing cultural, informational, and geographic barriers, the intervention fostered a more enabling environment for SRH service use. These findings are aligned with previous research demonstrating the effectiveness of community-based platforms in improving reproductive health outcomes. For instance, similar mobile and community-driven interventions in rural Ethiopia and other sub-Saharan African contexts have significantly increased ANC attendance, institutional delivery rates, and contraceptive use ( 20 – 24 ). Moreover, such models align with broader goals of equity and universal health coverage, supporting SDG targets 3.1, 3.7, and 5.6 by promoting access to essential health services and empowering women to make informed reproductive choices. This study is among the first systematic evaluations of the Health Bazaar model, providing empirical evidence on its effectiveness in enhancing SRH service uptake in Ethiopia. The significant improvements in contraceptive use and maternal healthcare utilization observed in intervention areas suggest that community-driven, mobile health initiatives can help bridge gaps in reproductive healthcare access, particularly in underserved, rural, and pastoralist communities. Moreover, the study highlights the role of SRH discussions and counseling in increasing service utilization, as women who engaged in such discussions were three times more likely to use SRH services (AOR = 3.21, p < 0.001). This underscores the importance of community engagement and health education programs in fostering positive health-seeking behaviours. The study’s findings align with previous research on community-based health interventions and their role in improving maternal and reproductive health outcomes. A study conducted in Uganda reported that mobile health initiatives led to a 40% increase in ANC visits, supporting the effectiveness of decentralized, community-based healthcare approaches ( 25 ). Similarly, research in Kenya found that integrated community health programs increased institutional delivery rates by 15%, a trend observed in this study as well ( 26 ). However, the study also contrasts with some previous findings. While studies in West Africa have reported persistent barriers to postnatal care utilization despite community interventions ( 27 ), this study found marginal improvements in postnatal care utilization (66.5% in intervention areas vs. 63.0% in non-intervention areas, p = 0.08). This suggests that while the Health Bazaar model is effective for ANC and delivery care, additional strategies may be needed to enhance postnatal service uptake. Several factors may explain the success of the Health Bazaar intervention. Firstly, increased community engagement and awareness campaigns likely contributed to higher SRH service utilization. The provision of mobile and outreach services may have reduced geographic and financial barriers, encouraging more women to access reproductive healthcare services. Additionally, the strong link between SRH discussions and service uptake suggests that peer influence and targeted education campaigns play a crucial role in shaping health-seeking behaviours. The lower PNC uptake, however, may be attributed to cultural factors, misconceptions about postpartum care, or gaps in service continuity after childbirth. The findings highlight the need for integrating mobile health interventions into routine healthcare delivery to improve maternal and reproductive health outcomes. Health professionals should prioritize community-based education and counseling programs, as active discussions on SRH significantly influenced service uptake ( 28 ). From a policy perspective, this study provides strong evidence to support the scale-up of the Health Bazaar model in Ethiopia and similar contexts. Policymakers should, expand mobile and community-driven health initiatives to reach underserved and hard-to-reach populations, strengthen postnatal care services by integrating home visits and postpartum counselling into community-based health programs and enhance SRH education efforts, particularly among married women, to address cultural barriers and misconceptions surrounding family planning and postnatal care. This study has several notable strengths. It offers a comprehensive assessment of sexual and reproductive health (SRH) service utilization by systematically evaluating multiple indicators, including family planning, ANC, delivery, and HIV testing. The use of multilevel mixed-effects regression analysis strengthens the study by enabling robust identification of both individual- and community-level determinants influencing SRH service uptake. Additionally, the comparison between intervention and non-intervention areas provides compelling evidence on the effectiveness of community-based interventions like health bazaars. However, the study also has limitations. Its cross-sectional design captures only a snapshot in time, limiting the ability to establish causal relationships. Moreover, the reliance on self-reported data for service utilization introduces potential biases, such as recall bias and social desirability bias. Lastly, while the findings offer valuable insights for Ethiopia, they may not be generalizable to other contexts with different health system structures. 5. Conclusion This study demonstrates that the Health Bazaar model significantly improved SRH service utilization among women in intervention areas, with notable increases in family planning uptake, antenatal care, institutional delivery, and HIV testing. The multilevel regression analysis confirmed that residing in an intervention area was independently associated with higher odds of SRH service use, reinforcing the effectiveness of this community-driven approach. These findings suggest that the Health Bazaar model can serve as a scalable and impactful strategy to address SRH service gaps in underserved communities, particularly in rural and pastoralist regions of Ethiopia. To sustain and expand the benefits of the Health Bazaar model, it is essential to foster partnerships between community organizations, healthcare providers, and government agencies. Collaborative integration into national health systems will enhance ownership, resource sharing, and program continuity. Future research should focus on assessing the model’s long-term impact, cost-effectiveness, and its reach across different demographic groups. Evaluating implementation challenges and sustainability strategies will be crucial to inform broader scale-up efforts and policy integration for equitable SRH service delivery. Abbreviations Adjusted Odds Ratio (AORs); Akaike information criterion (AIC); Antenatal care (ANC); Bayesian information criteria (BIC); Community-based health insurance (CBHI); Confidence Interval (CL); District Health Information System (DHIS2); Health Extension Program (HEP); Health Extension Workers (HEWs); Human Immunodeficiency Virus (HIV); Intra class correlation coefficients (ICC); Intrauterine contraceptive device (IUCD); Postnatal care (PNC); Proportional change in variances (PCV); Resilience Building and Creation of Economic Opportunities in Ethiopia( RESET); Sexual and Reproductive Health (SRH); Standard deviations (SD); Sustainable Development Goals(SDG) Declarations Ethics approval and consent to participate Ethical clearance was obtained from Ethiopian Anaesthetics Professionals’ Association IRB. A support letter was obtained from the regional health bureaus/MOH. Informed consent was obtained from all participants. Confidentiality of the collected data was ensured from all data collectors and the principal investigator’s side via using code data to replace personal identifiers and keeping the responses locked. The study adhered to WHO ethical guidelines for SRH research. Consent for publication Not applicable. Availability of data and materials Data is available upon reasonable request from the corresponding author. The data are not publicly available due to privacy reasons. Competing interests The authors declare no competing interests. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Funding This research was funded by the European Union, as part of the “RESET Plus—Scaling up the Family Planning for Resilience Building program amongst youth and women in drought prone and chronically food insecure regions of Ethiopia (T05-EUTF-HOA-ET-24-08)”. Amref Health Africa supported the administrative part in the course of the implementation of the project. Authors' contributions MDM, ZA, WK, SA, MB, and GM designed and conducted the study. MDM, WG, MA, ZA and GM planned and undertook the analysis. WE, VS, AR. ZD, MDM, MM, wrote the initial and subsequent drafts of the manuscript. WE, MDM, MM, GM, VS, MA contributed to revising the manuscript. All authors read and approved the final manuscript. Acknowledgements We are grateful for the participation of all the research samples and the cooperation of the personnel project implementation areas. Without their support, these results would not have been achieved. Additionally, the researchers are thankful to both the European Union for funding the project and Amref Health Africa for providing access to data and administrative support. References Extending sexual and reproductive health and rights to future generations through science and evidence. Geneva: World Health Organization; 2024. Licence: CC BY-NC-SA 3.0 IGO Calimoutou, Emelyne. 2021. Advancing Legislative and Policy Reforms on Sexual and Reproductive Health in Ethiopia. Gender Equality, Laws, SRHR Series. Washington, DC: The Global Financing Facility and World Bank. CSA. Ethiopian Demographic and Health Survey 2019. Addis Ababa, Ethiopia. 2019. WHO. Maternal Mortality in 2017: Estimates by WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division. 2018. Muluneh, M.D.; Kidane, W.; Stulz, V.; Ayele, M.; Abebe, S.; Rossetti, A.; Amenu, G.; Tesfahun, A.A.; Berhan M. Exploring the Influence of Sociocultural Factors on the Non-Utilization of Family Planning amongst Women in Ethiopia’s Pastoralist Regions. Int. J. Environ. Res. Public Health 2024, 21, 859. https://doi.org/10.3390/ijerph21070859. Yoseph, M., Abebe, S.M., Mekonnen FA et al. Institutional delivery services utilization and its determinant factors among women who gave birth in the past 24 months in Southwest Ethiopia. BMC Heal Serv Res. 2020;20(265). Ministry of Health. Ethiopia National Health Accounts Report, 2019/20. Partnership and Cooperation Directorate, Apr. 2022, Ministry of Health, Addis Ababa, Ethiopia. Jisso M, Assefa NA, Alemayehu A, Gadisa A, Fikre R, Umer A, Mohammed H, Yazie B, Gizaw HS, Mizana BA, Yesuf EA, Tilahun B, Endehabtu BF, Gonete TZ, Gashu KD, Angaw DA, Gurmu KK TA. Barriers to Family Planning Service Utilization in Ethiopia: A Qualitative Study. Ethiop J Health Sci. 2023 Oct;33(Spec Iss 2):143-154. doi: 10.4314/ejhs.v33i2.8S. PMID: 38352665; PMCID: PMC10859738. 2023. Tiruneh, M.G., Fenta, E.T., Endeshaw, D. et al. Health extension service utilization in Ethiopia: systematic review and meta-analysis. BMC Health Serv Res 24, 537 (2024). Rono, J., Kamau, L., Mangwana, J. et al. A policy analysis of policies and strategic plans on Maternal, Newborn and Child Health in Ethiopia. Int J Equity Health 21, 73 (2022). Guttmacher Institute. Adolescents’ Need for and Use of Abortion Services in Sub-Saharan Africa . 2020. Pathfinder International. Youth-Friendly Health Services: Improving Quality, Access, and Integration in Ethiopia . 2021. UNFPA. Youth Participation and SRHR in Ethiopia: Barriers and Opportunities . 2022. World Health Organization. Global Accelerated Action for the Health of Adolescents (AA-HA!): Guidance to Support Country Implementation . 2022. Alemayehu, Y.K., Dessie, E., Medhin, G. et al. The impact of community-based health insurance on health service utilization and financial risk protection in Ethiopia. BMC Health Serv Res 23, 67 (2023). Titiyos, Addisalem et al. “The Effect of a Decade Implemented Project in Improving the Uptake of Comprehensive Contraception: Difference-In-Difference Analysis.” Ethiopian journal of health sciences vol. 33,6 (2023): 927-934. Hagos, Asebe et al. “Inequalities in utilization of maternal health services in Ethiopia: evidence from the PMA Ethiopia longitudinal survey.” Frontiers in public health vol. 12 1431159. 7 Jan. 2025, Demissie, Eshetu, and Martha Nemera. RESET-II Project Endline Evaluation: Promoting Resilient Livelihoods in Borana. CARE Ethiopia, Path Development Consulting and Research Services, 2021. Gebrekidan, Hailay et al. “Individual and community level factors associated with modern contraceptive utilization among women in Ethiopia: Multilevel modeling analysis.” PloS one vol. 19,5 e0303803. Kibret, M.A., Gebremedhin LT. Two decades of family planning in Ethiopia and the way forward to sustain hard-fought gains. 19 (Suppl 1), 124 (2022). https://doi.org/10.1186/s12978-022-01435-5. Reprod Heal. May. 2024, Dougherty L, Kassegne S, Nagbe R, Babogou J, Peace P, Moussa F, Kirk K, Tokplo H, Ouro-Gnao D, Agbodjan SP, Loll D, Werwie TR and Silva M (2024) A qualitative exploration of how a community engagement approach influences community and health worker perceptions related to family planning service delivery in Togo. Front. Reprod. Health 6:1389716. Wahyuningsih, Sri et al. “Unveiling barriers to reproductive health awareness among rural adolescents: a systematic review.” Frontiers in reproductive health vol. 6 1444111. 19 Nov. 2024, Habte, A., Dessu S. The uptake of key elements of sexual and reproductive health services and its predictors among rural adolescents in Southern Ethiopia, 2020: application of a Poisson regression analysis. Reprod Heal. 2023;20(15). Mwangi, M. et al. The role of SRH interventions in improving mental health among Kenyan women." African Journal of Reproductive Health. J Reprod Heal. 2018; Namatovu, Hasifah Kasujja et al. “Barriers to eHealth adoption in routine antenatal care practices: Perspectives of expectant mothers in Uganda - A qualitative study using the unified theory of acceptance and use of technology model.” Digital health vol. 7 20552076211064406. 8 Dec. 2021, Karanja, Sarah et al. “Factors influencing deliveries at health facilities in a rural Maasai Community in Magadi sub-County, Kenya.” BMC pregnancy and childbirth vol. 18,1 5. 3 Jan. 2018, Bain, Luchuo Engelbert et al. “Individual and contextual factors associated with maternal healthcare utilisation in Mali: a cross-sectional study using Demographic and Health Survey data.” BMJ open vol. 12,2 e057681. 22 Feb. 2022, Esias Bedingar, Ferdinan Paningar, Ngarossorang Bedingar, Eric Mbaidoum, Naortangar Ngaradoum, Rifat Atun, Aisha Yousafzai - Optimising adolescents and young adults’ utilisation of sexual and reproductive health and HIV services in Chad: a sensemaking approach: BMJ Global Health 2025;10: e017763. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 26 Nov, 2025 Read the published version in Reproductive Health → Version 1 posted Editorial decision: Revision requested 25 Aug, 2025 Reviews received at journal 24 Jul, 2025 Reviews received at journal 18 Jul, 2025 Reviewers agreed at journal 15 Jul, 2025 Reviewers agreed at journal 08 Jul, 2025 Reviewers invited by journal 08 Jul, 2025 Editor assigned by journal 22 Apr, 2025 Submission checks completed at journal 21 Apr, 2025 First submitted to journal 15 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6457796","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":482536723,"identity":"21e48ea4-d144-4f7a-b990-062e2249d113","order_by":0,"name":"Muluken 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20:23:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6457796/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6457796/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12978-025-02218-4","type":"published","date":"2025-11-26T15:58:48+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":86406881,"identity":"1bdad51d-a90d-4d07-89b2-f27906ea30f1","added_by":"auto","created_at":"2025-07-10 09:55:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":112320,"visible":true,"origin":"","legend":"\u003cp\u003eTrends of implant new acceptors in Health Bazaar intervention and non-intervention areas, Ethiopia, 2024.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6457796/v1/d00e998510bf12e7d7afe8bb.png"},{"id":86406880,"identity":"501113b4-d677-45d3-b559-3bdf55ecf642","added_by":"auto","created_at":"2025-07-10 09:55:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":128419,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrends in ANC Utilization (At least one ANC visit) in health bazaar Intervention and Non-Intervention Areas\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6457796/v1/fc91953a5e523862f882b223.png"},{"id":86407337,"identity":"d48e5dd8-bc4f-46e8-a94e-eb66ad2d1fba","added_by":"auto","created_at":"2025-07-10 10:03:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":94542,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrends in Institutional Delivery Service Utilization in health bazaar Intervention and Non-Intervention Areas\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6457796/v1/5e669efcddbd1b26c5ec2f11.png"},{"id":86406883,"identity":"2c7196ad-800a-4ab4-af92-d3d88715e643","added_by":"auto","created_at":"2025-07-10 09:55:07","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":116292,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrends in institutional delivery service utilization in Health Bazaar intervention and non-intervention areas (2024)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6457796/v1/f1286fb6b557cc45dfaa6d6a.png"},{"id":97179502,"identity":"b2e81751-d8d1-4044-8b3a-ebbdef3924a5","added_by":"auto","created_at":"2025-12-01 16:15:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1734510,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6457796/v1/991061be-992a-4d5b-93cd-04db870cb05e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluating the role of the Health Bazaar Initiative on Sexual and Reproductive Health Service Utilization in Ethiopia: A Comparative Analysis of community- based interventions","fulltext":[{"header":"Plain English Summary","content":"\u003cp\u003eMany women in rural and hard-to-reach areas of Ethiopia face serious challenges when it comes to accessing sexual and reproductive health (SRH) services, such as family planning, antenatal care, and skilled birth assistance. These challenges include long distances to health facilities, lack of information, cultural beliefs, and economic hardship. To address this problem, Amref Health Africa implemented a new approach called the Health Bazaar\u0026mdash;a mobile, community-based health event that brings SRH services directly to the people. These events provide information, free health services, and create safe spaces for women to learn and ask questions about their health.\u003c/p\u003e\n\u003cp\u003eThis study compared health outcomes between areas where Health Bazaars were held and areas that continued with regular health services. We collected data from over 1,200 women and reviewed health system records to see if the intervention made a difference. The results showed that women in Health Bazaar areas were more likely to use contraceptives, attend antenatal care, give birth at health facilities, and receive postnatal care. These improvements were significantly higher than in areas without the intervention. Women also reported feeling more informed and supported in making decisions about their reproductive health.\u003c/p\u003e\n\u003cp\u003eOur findings suggest that the Health Bazaar model is a promising strategy to improve access to SRH services in underserved communities. With proper support and investment, this approach could be scaled up across similar low-resource settings to help ensure that all women\u0026mdash;no matter where they live\u0026mdash;can access the care they need.\u003c/p\u003e"},{"header":"1. Background","content":"\u003cp\u003eSexual and reproductive health (SRH) services play a crucial role in improving maternal health outcomes, reducing maternal mortality, and enhancing the overall well-being of women of reproductive age. Over the past two decades (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), Ethiopia has made significant progress in expanding SRH services through a combination of government-led initiatives and international partnerships. These efforts have resulted in increased contraceptive use, higher antenatal care (ANC) attendance, and greater access to skilled birth attendants (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). However, despite these advancements, maternal mortality rates remain high when compared to global standards (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSRH service disparities remain a pressing public health issue in Ethiopia, particularly affecting pastoralist and agrarian communities. While the national average for modern contraceptive use among women is 41%, it drops to below 20% in many pastoralist areas (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Similarly, institutional delivery rates are above 80% in urban centres like Addis Ababa but fall below 30% in remote rural regions (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). These inequities are driven by multiple factors: over 30% of healthcare costs are still paid out-of-pocket despite the scale-up of community-based health insurance (CBHI) to over 827 woredas; geographic inaccessibility in sparsely populated or mobile pastoralist zones; deep-rooted sociocultural norms that restrict women\u0026rsquo;s autonomy; and shortages in trained health providers and youth-friendly services (\u003cspan additionalcitationids=\"CR5 CR6 CR7\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Adolescents and young women are disproportionately affected due to early marriage and limited access to education and SRH information. Addressing these gaps requires targeted, community-based interventions and strengthened health systems that reflect the needs and realities of Ethiopia\u0026rsquo;s most marginalized populations (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEthiopia has implemented various health interventions to improve maternal and reproductive health. One of the most influential programs is the Health Extension Program (HEP), which deploys Health Extension Workers (HEWs) to provide SRH services at the community level (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Additionally, the government has expanded free maternal healthcare services in public health facilities, covering family planning, ANC, and institutional delivery services (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). However, the delivery of demand-responsive health services remains limited, especially for adolescents, unmarried youth, and marginalized groups who face barriers such as stigma, lack of privacy, and inflexible service models (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Despite increased access, the system largely remains supply-driven, with minimal integration of innovative approaches like mobile health, digital platforms, or comprehensive youth-focused models that include mental health, life skills, and financial empowerment. This gap highlights the urgent need for more user-centered, inclusive service delivery mechanisms to improve uptake and equity in SRH access (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFinancial barriers have been addressed through CBHI, which aims to reduce out-of-pocket expenditures and improve healthcare access for low-income populations (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Large-scale public health campaigns have also played a role in increasing awareness and acceptance of contraceptive methods, contributing to a rise in contraceptive prevalence rates (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). While these initiatives have improved overall SRH service uptake, inconsistent in implementation and significant disparities persists especially in rural and pastoralist regions where healthcare infrastructure is weak and sociocultural barriers are high (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). This highlights the need to explore alternative approaches that can more effectively reach and engage these communities.\u003c/p\u003e\u003cp\u003eOne such intervention is the Health Bazaar model, which was implemented by Amref Health Africa in Ethiopia as part of the RESET Plus family planning project. This approach integrates SRH services into mobile, community-based health events, making them more accessible to women in hard-to-reach areas. While this intervention has been operational from 2022 to 2024 its impact on SRH service uptake has not been systematically evaluated or documented. Given the persistent gaps in SRH service utilization in Ethiopia, this study seeks to assess the effectiveness of the Health Bazaar model in increasing the uptake of SRH services. Specifically, it aims to compare SRH service utilization rates among women in Health Bazaar intervention areas versus non-intervention areas within the Amref RESET Plus family planning project (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite the growing body of research on SRH in Ethiopia, previous studies have several limitations. First, most evaluations have focused on facility-based service delivery, neglecting the potential of community-driven models, such as the Health Bazaar, to reach underserved populations (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Second, disaggregated data comparing intervention and non-intervention sites are scarce, making it difficult to assess the effectiveness of specific interventions. Third, existing studies have not sufficiently examined the influence of contextual factors, such as geographic location, cultural beliefs, and economic constraints, on SRH service uptake.\u003c/p\u003e\u003cp\u003eThese gaps in research underscore the need for a comprehensive study that evaluates community-based health service delivery models and their impact on SRH service utilization in Ethiopia. Despite the documented progress in Ethiopia\u0026rsquo;s SRH sector, the effectiveness of mobile, community-integrated health service delivery models in increasing SRH service uptake has not been well studied. Additionally, there is limited research on the sustainability and scalability of interventions like the Health Bazaar. Another key gap in knowledge is understanding the role of individual- and community-level factors\u0026mdash;such as education, household income, and cultural norms\u0026mdash;in influencing SRH service utilization (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis study aims to estimate the effects of the Health Bazaar intervention by comparing SRH service uptake in intervention and non-intervention areas. The findings will provide evidence-based insights to guide the scale up of community-driven health service delivery models and support national health policy decisions for improving SRH services in Ethiopia.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study Design\u003c/h2\u003e\u003cp\u003eThis study employed a comparative cross-sectional design with a multilevel mixed-effects analysis to assess the impact of the Health Bazaar intervention on SRH service uptake in Ethiopia. It integrated both primary data collection\u0026mdash;through structured surveys\u0026mdash;and secondary data analysis using client flow data extracted from the DHIS2 system, enabling a comprehensive assessment of trends in SRH service utilization across intervention and non-intervention areas.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Study setting and period\u003c/h2\u003e\u003cp\u003eThe EU\u0026rsquo;s Resilience Building in Ethiopia (RESET) program is a multi-phase initiative targeting vulnerable, drought-prone regions to address root causes of instability, displacement, and irregular migration. Below are key elements of its implementation across Ethiopian clusters: the primary goal ( \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.eeas.europa.eu/node/47222_fr\u003c/span\u003e\u003cspan address=\"https://www.eeas.europa.eu/node/47222_fr\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) is strengthen resilience to natural and human-induced crises (e.g., droughts, conflicts), create economic opportunities to reduce distress migration, improve access to basic services (healthcare, water, education) and disaster risk management. The geographic focus of the program targets am five regions: Afar, Amhara, Oromia, SNNPR, and Key Clusters includes Wag Himra (Amhara), Afar (Afar), Siti/Liben (Somali), Bale/Borena (Oromia), Wolayta/South Omo (South Ethiopia). These areas were selected for their high vulnerability to climate shocks, food insecurity, and proximity to migration routes (e.g., borders with Kenya, Somalia, Djibouti). It has three Implementation Phases from 2012 to 2024. The study focused on the intervention of phases Implemented by Amref health Africa in Ethiopia.\u003c/p\u003e\u003cp\u003eThe RESET Plus I family planning project, the second phase of the initiative (2022 \u0026minus;\u0026thinsp;2024), is being implemented across five clusters/zones in four regions covering 16 woredas in Ethiopia. The project is managed by Amref Health Africa Italy, in collaboration with Amref Health Africa Ethiopia (lead in-country), Women Empowerment in Action, and the Kulich Youth Reproductive Health and Development Organization (KYRHDO). The study intervention areas include hard-to-reach, rural, and pastoralist districts in four of the regions where access to SRH services are typically limited. In addition to the intervention areas, a control group was selected from non-intervention areas, ensuring that any potential spillover effects from the intervention sites were accounted for in the comparison (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eHealth Bazaar Operational Definition and Implementation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA Health Bazaar is a community-based, mobile health service delivery model designed to improve access to SRH services by bringing healthcare providers closer to communities in underserved areas. These events are typically organized in open spaces within villages or near primary healthcare facilities, allowing for both service provision and community engagement.\u003c/p\u003e\u003cp\u003eThe implementation of health bazaars involved:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePlanning and Mobilization: Community sensitization activities were conducted through local leaders, health extension workers, and social mobilization campaigns to raise awareness about the health bazaar events.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eService Provision: A range of SRH services, including contraceptive provision, ANC, skilled birth attendance referrals, HIV testing, and health education, were offered.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eHealth Promotion and Education: Trained health professionals provided health education sessions to promote the utilization of available SRH services.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eCollaboration with Local Stakeholders: Health bazaars were organized in partnership with local health offices, community leaders, and non-governmental organizations to enhance service coverage and ensure sustainability.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eData Collection and Monitoring: Service utilization data were recorded at each event to track the number of individuals served and measure key SRH indicators.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHealth Bazaar Intervention and Non-Intervention Study Sites in Ethiopia (2024)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCluster\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIntervention District\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNon-Intervention District\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSouth Omo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHamer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBenasemay\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBorana\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMoyale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDillo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWolaita\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDuguna Fango\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBoloso Bombe\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWaghimra\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSekota Zuria\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDahana\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAfar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAfambo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBidu\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Study Population and Data Sources\u003c/h2\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.3.1. Comparative Cross-Sectional Study\u003c/h2\u003e\u003cp\u003eThe source population consisted of women of reproductive age (15\u0026ndash;49 years) residing in both the Health Bazaar intervention and non-intervention areas. The study population was selected from districts where the Health Bazaar program was implemented, along with matched non-intervention districts.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.3.2. Secondary Data Sources\u003c/h2\u003e\u003cp\u003eTo analyze trends in sexual and reproductive health (SRH) service utilization, data were extracted from DHIS2 for both intervention and non-intervention sites. The extracted data covered the period 2018 to 2024 to assess trends in SRH indicators.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Inclusion and Exclusion Criteria\u003c/h2\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.4.1. Inclusion Criteria\u003c/h2\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eComparative Cross-Sectional Study: All women of reproductive age (15\u0026ndash;49 years) living in the selected intervention and non-intervention districts who are willing to provide consent were eligible for inclusion.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eTrend Analysis: All available SRH service utilization indicators from DHIS2 were included.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e2.4.2. Exclusion Criteria\u003c/h2\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eWomen who had lived in the study area for less than six months were excluded.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Sample Size Determination\u003c/h2\u003e\u003cp\u003eThe required sample size was calculated using the double population proportion formula, with the following assumptions: 95% confidence interval, 80% power, 15% non-response rate, Design effect of 2 (to account for multistage sampling).\u003c/p\u003e\u003cp\u003eBased on the assumption that the Health Bazaar intervention would improve SRH service utilization by 15% compared to non-intervention areas, the final sample size was 1340 women (670 in the intervention group and 670 in the non-intervention group).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e2.6. Sampling Procedure\u003c/h2\u003e\u003cp\u003eA multistage cluster sampling approach was used for the comparative cross-sectional survey.\u003c/p\u003e\u003cp\u003e1. Stage 1:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eAll districts in the intervention and non-intervention areas were listed.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eOne intervention and one non-intervention district were randomly selected from each cluster.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003e2. Stage 2:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eTwo kebeles were randomly selected\u0026mdash;one from the Health Bazaar intervention area and one from the non-intervention area.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eAfter estimating the expected number of women of reproductive age (15\u0026ndash;49 years) in each kebele, systematic random sampling was used to select study participants.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eIf a household had more than one eligible participant, one was randomly selected.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e2.7. Study Variables\u003c/h2\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e2.7.1. Dependent Variable\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eSRH Service Utilization\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e2.7.2. Independent Variables\u003c/h2\u003e\u003cp\u003eIndividual-Level Factors: Age, religion, ethnicity, occupation, marital status, educational status, family size, discussion with husband about SRH issues.\u003c/p\u003e\u003cp\u003eCommunity-Level Factors: Residence in an intervention vs. non-intervention area, cluster, region, and broader community influences.\u003c/p\u003e\u003cp\u003eCluster-Level Factors: District-level variations were considered for multilevel regression analysis.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e2.8. Operational Definitions\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eSRH Service Utilization: Measured based on self-reported use of at least one SRH service in the past six months (family planning, Antenatal care, Institutional delivery, postnatal care, contraceptive or SRH education/counselling).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e2.9. Data Collection Tools and Procedures\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe questionnaire was adapted from WHO Global Standards for SRH Services and validated through expert review. The tool was translated into local languages and pre-tested before data collection. Trained data collectors administered the survey through face-to-face interviews.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\u003ch2\u003e2.9.1. Secondary Data Extraction\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eDHIS2 data were retrieved using a structured extraction checklist, focusing on key SRH indicators.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e2.10. Data Quality Assurance\u003c/h2\u003e\u003cp\u003ePre-testing was conducted before data collection, and necessary modifications were made. Data collectors underwent two days of training on data collection tools and interviewing techniques. Supervision and daily data quality checks were implemented. Data consistency and completeness were verified at the end of each collection day.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e2.11. Data Management and Analysis\u003c/h2\u003e\u003cp\u003eDescriptive statistics were used to compare SRH service utilization across intervention and non-intervention groups. Trend analysis was conducted to assess changes in SRH service uptake over time.\u003c/p\u003e\u003cp\u003eA two-level multilevel mixed-effects logistic regression was applied to account for hierarchical data structure. For the nature of such kind of data, a multilevel mixed effects regression analysis is preferred because the hierarchical nature of the data violated the principles of independence and homogeneity required for a single level analysis. This approach allows researchers to examine phenomena that occur at multiple levels within a hierarchical structure, providing a more comprehensive understanding of complex relationships by considering both individual-level and group-level factors simultaneously, which is particularly valuable when studying data where individuals are nested within groups (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). In addition, to identify individual and community level factors associated with SRH service uptake, a two-level multilevel mixed effects multivariable binary logistic regression has been used to address the hierarchical nature of the data. For such kind of data nature, a multilevel mixed effects regression analysis is preferred because the hierarchical nature of the data violated the principles of independence and homogeneity required for a single level analysis.\u003c/p\u003e\u003cp\u003eThe measure of the fixed effects was reported using Adjusted Odds Ratio (AORs) with 95% CI and p values. Also, the measures random effects were estimated as intra class correlation coefficients (ICC) and proportional change in variances (PCV) were also used to compute for each model with respect to the empty model to understand the relative contributions of both individual and community level variables to the higher-level variance on SRH service uptakes (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Model selection was based on Akaike information criterion (AIC) and Bayesian information criteria (BIC), ensuring the best fit. AIC is more relevant for exploratory analysis in this context and BIC is more relevant for identifying the best model in fitting variables to estimate the association between dependent variable and independent variables.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Sociodemographic Characteristics\u003c/h2\u003e\u003cp\u003eFrom the total calculated sample size 1340, 1,289 reproductive-age women (15\u0026ndash;49 years) participated in the study, with a 96.2% response rate. The sample comprised 663 women from intervention areas (Health Bazaar model) and 623 from non-intervention areas.\u003c/p\u003e\u003cp\u003eThe mean age of participants was 27.8 years (SD: \u0026plusmn;6.4), with almost three-quarters (72.5%) being married. Literacy rates were significantly higher in intervention areas (52.7%) compared to non-intervention areas (45.3%) (p\u0026thinsp;=\u0026thinsp;0.03). A greater proportion of women in intervention areas reported household incomes above the poverty line (58.6%) compared to non-intervention areas (50.1%) (p\u0026thinsp;=\u0026thinsp;0.02) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDistribution of participants in intervention and non-intervention areas for Health Bazaar, 2024.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eIntervention (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eTotal (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"7\" rowspan=\"8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo (%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003eCluster\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBorena Cluster\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e129 (19.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e126 (20.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e255 (20.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSouth Omo Custer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e140 (21.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e119 (19.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e259 (20.06)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWolayita Cluster\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e136 (20.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e125 (20.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e261 (20.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAfar Cluster\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e129 (19.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e129 (20.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e258 (20.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWaghemira Cluster\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e129 (19.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e127 (20.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e256 (20.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e663 (51.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e626 (48.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1289 (100)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Sexual and Reproductive Health (SRH) Service Utilization and Family Planning\u003c/h2\u003e\u003cp\u003eOf the total women included in the survey, 730 (56.6%) had visited a health facility for SRH services in the last six months. A significantly higher proportion of women from intervention areas (65.1%) accessed SRHservices compared to those in non-intervention areas (47.6%) (Chi-square\u0026thinsp;=\u0026thinsp;43.6, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The most reported reasons for visiting health facilities included family planning (79.2%), SRH counselling (61.4%), and ANC follow-up (34.8%).\u003c/p\u003e\u003cp\u003eDuring the survey, 47.2% of reproductive-age women were using contraceptive methods (53.3% from intervention and 41.8% from non-intervention areas) with a statistically significant difference (Chi-square\u0026thinsp;=\u0026thinsp;12.8, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The most frequently used contraceptive methods were injectables (45.8%) and implants (44.5%). Among those who visited health facilities for contraceptive services, 55.8% received counselling on method options, 54.5% were informed about possible side effects, and 44.0% were given guidance on managing potential complications before their next visit (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). A total of 46.5% of participants underwent HIV testing and counselling services, with significantly higher rates in intervention areas (51.6%) than in non-intervention areas (41.1%) (Chi-square\u0026thinsp;=\u0026thinsp;14.35, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003eBarriers to SRH service utilization were also assessed, with 63.0% of women citing a lack of awareness, 28.1% believing SRH services were unnecessary, and 3.6% reporting long distances to health facilities as reasons for not seeking services.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCurrent contraceptive use, related side effects and contents of consultation in intervention and non-interventions areas, 2024.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eIntervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCurrent contraceptive use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e347 (53.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e262 (41.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e609 (47.24)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e316 (46.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e364 (57.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e680 (52.76)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eDiscussion with partners about FP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e418 (71.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e330 (59.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e748 (65.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e166 (28.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e224 (40.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e390 (34.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eType of contraceptive used currently\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInjectable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e158(45.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e120 (45.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e279 (45.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eImplants\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e154 (44.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e117 (44.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e271 (44.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIUCD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24 (6.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16 (6.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e40 (6.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10 (3.3))\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (3.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e189 (3.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eReport side effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e192 (55.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e140 (53.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e332 (54.52)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e155 (44.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e122 (46.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e277 (45.48)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e\u003cp\u003eContents of consultation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExplain about methods\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e201 (57.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e69 (26.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e340 (55.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDescribe possible side effects\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e168 (48.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e164 (62.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e332 (54.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExplain what to do for any problems before the next visit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e129 (37.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e139 (53.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e268 (44.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExplains the possibility of changing method if you are not happy with it\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e145 (41.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e107 (40.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e252 (41.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDemonstrate how to use it\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e119 (34.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e97 (37.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e216 (35.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExplain where to go for follow up visit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e114 (32.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e78 (29.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e192 (31.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExplain about other methods\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e67 (19.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37 (14.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e107 (17.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (0.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (0.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eTrends in Contraceptive Uptake\u003c/em\u003e\u003c/p\u003e\u003cp\u003eA six-year trend analysis of intrauterine contraceptive device (IUCD) acceptors indicated a notable difference between intervention and non-intervention areas. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows a significant increase in IUCD acceptors in intervention areas (slope 0.0616 per quarter) compared to non-intervention areas (slope 0.0219 per quarter) highlighting the greater impact of Health Bazaar impact on IUCD uptake. Similarly, new acceptors of implants showed an increasing trend in both groups, although the rate of increase was higher in intervention areas (4.8 per quarter) compared to non-intervention areas (3.3 per quarter) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003e3.4. Maternal Health Service Utilization: Antenatal Care, Institutional Delivery, and Postnatal Care\u003c/h2\u003e\u003cp\u003eAntenatal Care Utilization\u003c/p\u003e\u003cp\u003eAmong the surveyed reproductive-age women, 16.1% were pregnant at the time of the study. Among these, 82.1% had at least one ANC follow-up, with the majority receiving services from health centres (71.2%). A higher proportion of pregnant women in intervention areas (87.3%) attended at least one ANC visit compared to those in non-intervention areas (77.1%). The main barriers to ANC utilization included distance to health facilities (40.5%), lack of awareness (37.8%), and being too busy to attend services (21.6%).\u003c/p\u003e\u003cp\u003eTrend analysis showed a higher increase in ANC utilization over time in intervention areas compared to non-intervention areas. The number of women attending at least one ANC visit increased by 10.2 per quarter in intervention areas, while in non-intervention areas, it increased by 3.2 per quarter. Similarly, women completing four or more ANC visits (ANC4+) increased at a faster rate in intervention areas (10.2 per quarter) compared to non-intervention areas (3.2 per quarter) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eInstitutional Delivery\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAmong the 343 women (26.6%) who gave birth in the last 12 months, 84.3% delivered in health facilities, with a significantly higher proportion of women in intervention areas (89.4%) utilizing institutional delivery services compared to those in non-intervention areas (80.6%). The main reasons for home delivery included lack of partner support (14.0%), lack of transportation (30.0%), lack of awareness (44.0%), distance to facilities (20.0%), and preference for home-based care (30.0%). The trend analysis of institutional deliveries revealed a greater increase in intervention areas (5.8 per quarter) compared to non-intervention areas (4.6 per quarter) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003ePostnatal Care Utilization\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAmong the women who delivered, 64.7% received postnatal care (PNC) services, with higher utilization in intervention areas (66.5%) compared to non-intervention areas (63.0%) (Chi-square\u0026thinsp;=\u0026thinsp;0.57, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Most PNC users accessed services at health centres (59.9%), followed by health posts (28.4%) and hospitals (10.8%). The major barriers to PNC utilization included lack of awareness (68.6%), distance to health facilities (14.0%), and lack of transport services (9.1%).\u003c/p\u003e\u003cp\u003eTrend analysis indicated that PNC service utilization increased by 9.5 per quarter in intervention areas, whereas in non-intervention areas, the increase was 4.4 per quarter (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec25\" class=\"Section2\"\u003e\u003ch2\u003e3.5. Factors Associated with SRH Service Uptake\u003c/h2\u003e\u003cp\u003eA multilevel mixed-effects logistic regression identified key individual- and community-level determinants influencing the utilization of sexual and reproductive health (SRH) services.\u003c/p\u003e\u003cp\u003eAge was a significant predictor, with women aged 19\u0026ndash;49 years being more likely to use SRH services compared to younger women aged 15\u0026ndash;18 years (AOR\u0026thinsp;=\u0026thinsp;2.45, 95% CI: 1.15\u0026ndash;6.69, p\u0026thinsp;=\u0026thinsp;0.002). Marital status also influenced SRH utilization, as married women were less likely to seek SRH services compared to single women (AOR\u0026thinsp;=\u0026thinsp;0.57, 95% CI: 0.07\u0026ndash;0.64, p\u0026thinsp;=\u0026thinsp;0.015).\u003c/p\u003e\u003cp\u003eEngagement in discussions about SRH emerged as a strong predictor, with women who actively participated in SRH-related conversations being three times more likely to use SRH services (AOR\u0026thinsp;=\u0026thinsp;3.21, 95% CI: 2.10\u0026ndash;4.91, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Finally, residence in a Health Bazaar intervention area significantly increased the likelihood of SRH service utilization (AOR\u0026thinsp;=\u0026thinsp;1.89, 95% CI: 1.32\u0026ndash;2.69, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The intra-class correlation coefficient (ICC) decreased from 34\u0026ndash;0.6%, suggesting that individual-level factors, particularly SRH discussions, had a major influence on service utilization (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFactors Associated with Sexual and Reproductive Health (SRH) Service Uptake, Ethiopia 2024.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eModel 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eModel 3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eModel 4\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eIndividual level factors\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAge of women\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15\u0026ndash;18 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19\u0026ndash;49 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e4.17(2.30,7.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.78 (1.15,6.69)***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eReligion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOrthodox Christian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProtestant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.87 (0.50,1.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.99 (0.57,1.75)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMuslim\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.23 (0.52,2.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.21 (0.46,3.21)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCatholic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.13 (0.34,3.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.48 (0.46,4.80)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.91 (0.43,1.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.16 (0.56,2.43)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e\u003cp\u003eEthnicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAmhara\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWolayita\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2.02 (0.73,5.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.43 (0.23,8.90)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAfar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.26 (0.09,0.78)*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.50 (0.12,2.09)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOromo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e5.50(1.75,17.00)**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.80 (0.25,12.98)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAgew\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2.42 (0.23, 26.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.32 (0.33,31.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHammer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.42(0.14,1.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.32 (0.06,1.76)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.36 (0.13,0.99)*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.25 (0.05, 1.36)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eOccupation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.36 (0.21,0.62)***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.61(0.65,4.12)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnemployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.65 (0.47,0.90)**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.73 (0.49,2.09)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eMarital status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSeparated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.21 (0.06,0.68)*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.21 (0.07,0.64)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.07 (0.44, 2.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.06(0.41,2.70)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDivorced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2.43 (1.08,5.87)*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.31 (0.96,5.55)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWidowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.66 (0.24, 1.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.71 (0.26,1.87)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eEducational status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCannot read and write\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOnly can write and write\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.12(0.66, 1.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.02 (0.61,1.71)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimary school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.07(0.71,1.62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.99 (0.65, 1.51)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSecondary school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.48(0.85,2.58)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.34 (0.76, 2.37)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbove secondary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.92 (0.45,1.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.80 (0.38, 1.68)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eDiscussion with husband\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.31(0.22,0.44)***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.29 (0.21,0.41)***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo husband\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.10(0.03,0.21)***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.08 (0.04,0.16)**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eFamily size\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;4.3 *average\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;4.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.71(0.48,1.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.66 (0.48, 0 .92)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eCommunity level factors\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eStudy group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIntervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-intervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0.38(0.28,0.53)***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.39(0.28,0.54)***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eResidence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUrban and semi urban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1.18 (0.79,1.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.86 (0.53,1.39)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eCluster\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBorena\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWaghemira\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0.11 (0.06,0.23)***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.17 (0.02, 1.55)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAfar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0.06 (0.02, 0.08)***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.11 (0.01,1.10)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSouth Omo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0.05 (0.23,0.09)***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.16 (0.04,0.66)**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWolyita\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0.27 (0.15, 0.49)***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.27 (0.06,1.17)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study evaluated the impact of the Health Bazaar model on sexual and reproductive health (SRH) service utilization among women of reproductive age in Ethiopia. The findings indicate that the intervention significantly improved modern contraceptive use, antenatal care (ANC) attendance, institutional delivery, and HIV testing and counselling services compared to non-intervention areas. Specifically, family planning service uptake was higher in intervention areas (53.3%) than in non-intervention areas (41.8%) (p\u0026thinsp;=\u0026thinsp;0.001). Likewise, a higher proportion of women in intervention areas (87.2%) attended at least one ANC visit, compared to 71.1% in non-intervention areas (p\u0026thinsp;=\u0026thinsp;0.001). Institutional deliveries were also more common among women in intervention areas (89.4%) compared to non-intervention areas (80.6%) (p\u0026thinsp;=\u0026thinsp;0.02). These findings align with the study\u0026rsquo;s primary objective of assessing whether community-based interventions, such as the Health Bazaar, improve SRH service utilization and maternal health outcomes.\u003c/p\u003e\u003cp\u003eOver the three-year implementation period of the Health Bazaar intervention, a consistent upward trend in the utilization of SRH services was observed in the intervention areas. This trend was confirmed through both primary data and DHIS2 trend analysis, which demonstrated higher and faster growth in service uptake\u0026mdash;including family planning, ANC, institutional delivery, PNC, and HIV testing\u0026mdash;compared to non-intervention areas. Multilevel mixed-effects logistic regression further substantiated this trend, revealing that women in Health Bazaar intervention areas were significantly more likely to utilize SRH services. Specifically, being in an intervention area was associated with 61% higher odds of SRH service uptake (AOR: 1.52; 95% CI: 1.09\u0026ndash;2.08) compared to non-intervention areas. This suggests a strong, independent effect of the Health Bazaar model, even after adjusting for individual-level and community-level variables.\u003c/p\u003e\u003cp\u003eThis improvement can be attributed to several mechanisms embedded within the Health Bazaar model: increased physical accessibility, integration of SRH education with service delivery, and active community engagement. By addressing cultural, informational, and geographic barriers, the intervention fostered a more enabling environment for SRH service use. These findings are aligned with previous research demonstrating the effectiveness of community-based platforms in improving reproductive health outcomes. For instance, similar mobile and community-driven interventions in rural Ethiopia and other sub-Saharan African contexts have significantly increased ANC attendance, institutional delivery rates, and contraceptive use (\u003cspan additionalcitationids=\"CR21 CR22 CR23\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Moreover, such models align with broader goals of equity and universal health coverage, supporting SDG targets 3.1, 3.7, and 5.6 by promoting access to essential health services and empowering women to make informed reproductive choices.\u003c/p\u003e\u003cp\u003eThis study is among the first systematic evaluations of the Health Bazaar model, providing empirical evidence on its effectiveness in enhancing SRH service uptake in Ethiopia. The significant improvements in contraceptive use and maternal healthcare utilization observed in intervention areas suggest that community-driven, mobile health initiatives can help bridge gaps in reproductive healthcare access, particularly in underserved, rural, and pastoralist communities. Moreover, the study highlights the role of SRH discussions and counseling in increasing service utilization, as women who engaged in such discussions were three times more likely to use SRH services (AOR\u0026thinsp;=\u0026thinsp;3.21, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This underscores the importance of community engagement and health education programs in fostering positive health-seeking behaviours.\u003c/p\u003e\u003cp\u003eThe study\u0026rsquo;s findings align with previous research on community-based health interventions and their role in improving maternal and reproductive health outcomes. A study conducted in Uganda reported that mobile health initiatives led to a 40% increase in ANC visits, supporting the effectiveness of decentralized, community-based healthcare approaches (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Similarly, research in Kenya found that integrated community health programs increased institutional delivery rates by 15%, a trend observed in this study as well (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). However, the study also contrasts with some previous findings. While studies in West Africa have reported persistent barriers to postnatal care utilization despite community interventions (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), this study found marginal improvements in postnatal care utilization (66.5% in intervention areas vs. 63.0% in non-intervention areas, p\u0026thinsp;=\u0026thinsp;0.08). This suggests that while the Health Bazaar model is effective for ANC and delivery care, additional strategies may be needed to enhance postnatal service uptake.\u003c/p\u003e\u003cp\u003eSeveral factors may explain the success of the Health Bazaar intervention. Firstly, increased community engagement and awareness campaigns likely contributed to higher SRH service utilization. The provision of mobile and outreach services may have reduced geographic and financial barriers, encouraging more women to access reproductive healthcare services. Additionally, the strong link between SRH discussions and service uptake suggests that peer influence and targeted education campaigns play a crucial role in shaping health-seeking behaviours. The lower PNC uptake, however, may be attributed to cultural factors, misconceptions about postpartum care, or gaps in service continuity after childbirth.\u003c/p\u003e\u003cp\u003eThe findings highlight the need for integrating mobile health interventions into routine healthcare delivery to improve maternal and reproductive health outcomes. Health professionals should prioritize community-based education and counseling programs, as active discussions on SRH significantly influenced service uptake (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). From a policy perspective, this study provides strong evidence to support the scale-up of the Health Bazaar model in Ethiopia and similar contexts. Policymakers should, expand mobile and community-driven health initiatives to reach underserved and hard-to-reach populations, strengthen postnatal care services by integrating home visits and postpartum counselling into community-based health programs and enhance SRH education efforts, particularly among married women, to address cultural barriers and misconceptions surrounding family planning and postnatal care.\u003c/p\u003e\u003cp\u003eThis study has several notable strengths. It offers a comprehensive assessment of sexual and reproductive health (SRH) service utilization by systematically evaluating multiple indicators, including family planning, ANC, delivery, and HIV testing. The use of multilevel mixed-effects regression analysis strengthens the study by enabling robust identification of both individual- and community-level determinants influencing SRH service uptake. Additionally, the comparison between intervention and non-intervention areas provides compelling evidence on the effectiveness of community-based interventions like health bazaars. However, the study also has limitations. Its cross-sectional design captures only a snapshot in time, limiting the ability to establish causal relationships. Moreover, the reliance on self-reported data for service utilization introduces potential biases, such as recall bias and social desirability bias. Lastly, while the findings offer valuable insights for Ethiopia, they may not be generalizable to other contexts with different health system structures.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study demonstrates that the Health Bazaar model significantly improved SRH service utilization among women in intervention areas, with notable increases in family planning uptake, antenatal care, institutional delivery, and HIV testing. The multilevel regression analysis confirmed that residing in an intervention area was independently associated with higher odds of SRH service use, reinforcing the effectiveness of this community-driven approach. These findings suggest that the Health Bazaar model can serve as a scalable and impactful strategy to address SRH service gaps in underserved communities, particularly in rural and pastoralist regions of Ethiopia.\u003c/p\u003e\u003cp\u003eTo sustain and expand the benefits of the Health Bazaar model, it is essential to foster partnerships between community organizations, healthcare providers, and government agencies. Collaborative integration into national health systems will enhance ownership, resource sharing, and program continuity. Future research should focus on assessing the model\u0026rsquo;s long-term impact, cost-effectiveness, and its reach across different demographic groups. Evaluating implementation challenges and sustainability strategies will be crucial to inform broader scale-up efforts and policy integration for equitable SRH service delivery.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAdjusted Odds Ratio (AORs); Akaike information criterion (AIC); Antenatal care (ANC); \u0026nbsp;Bayesian information criteria (BIC); Community-based health insurance (CBHI); Confidence Interval (CL); District Health Information System (DHIS2); Health Extension Program (HEP); Health Extension Workers (HEWs); Human Immunodeficiency Virus (HIV); Intra class correlation coefficients (ICC); Intrauterine contraceptive device (IUCD); Postnatal care (PNC); Proportional change in variances (PCV); Resilience Building and Creation of Economic Opportunities in Ethiopia( RESET); Sexual and Reproductive Health (SRH); Standard deviations \u0026nbsp; (SD); Sustainable Development Goals(SDG)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical clearance was obtained from Ethiopian Anaesthetics Professionals\u0026rsquo; Association IRB. A support letter was obtained from the regional health bureaus/MOH. Informed consent was obtained from all participants. Confidentiality of the collected data was ensured from all data collectors and the principal investigator\u0026rsquo;s side via using code data to replace personal identifiers and keeping the responses locked. The study adhered to WHO ethical guidelines for SRH research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData is available upon reasonable request from the corresponding author. The data are not publicly available due to privacy reasons.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the European Union, as part of the \u0026ldquo;RESET Plus\u0026mdash;Scaling up the Family Planning for Resilience Building program amongst youth and women in drought prone and chronically food insecure regions of Ethiopia (T05-EUTF-HOA-ET-24-08)\u0026rdquo;. Amref Health Africa supported the administrative part in the course of the implementation of the project.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMDM, ZA, WK, SA, MB, and GM designed and conducted the study. MDM, WG, MA, ZA and GM planned and undertook the analysis. WE, VS, AR. ZD, MDM, MM, wrote the initial and subsequent drafts of the manuscript. WE, MDM, MM, GM, VS, MA contributed to revising the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful for the participation of all the research samples and the cooperation of the personnel project implementation areas. Without their support, these results would not have been achieved. Additionally, the researchers are thankful to both the European Union for funding the project and Amref Health Africa for providing access to data and administrative support.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eExtending sexual and reproductive health and rights to future generations through science and evidence. Geneva: World Health Organization; 2024. Licence: CC BY-NC-SA 3.0 IGO \u003c/li\u003e\n\u003cli\u003eCalimoutou, Emelyne. 2021. Advancing Legislative and Policy Reforms on Sexual and Reproductive Health in Ethiopia. Gender Equality, Laws, SRHR Series. Washington, DC: The Global Financing Facility and World Bank. \u003c/li\u003e\n\u003cli\u003eCSA. Ethiopian Demographic and Health Survey 2019. Addis Ababa, Ethiopia. 2019. \u003c/li\u003e\n\u003cli\u003eWHO. Maternal Mortality in 2017: Estimates by WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division. 2018. \u003c/li\u003e\n\u003cli\u003eMuluneh, M.D.; Kidane, W.; Stulz, V.; Ayele, M.; Abebe, S.; Rossetti, A.; Amenu, G.; Tesfahun, A.A.; Berhan M. Exploring the Influence of Sociocultural Factors on the Non-Utilization of Family Planning amongst Women in Ethiopia\u0026rsquo;s Pastoralist Regions. Int. J. Environ. Res. Public Health 2024, 21, 859. https://doi.org/10.3390/ijerph21070859. \u003c/li\u003e\n\u003cli\u003eYoseph, M., Abebe, S.M., Mekonnen FA et al. Institutional delivery services utilization and its determinant factors among women who gave birth in the past 24 months in Southwest Ethiopia. BMC Heal Serv Res. 2020;20(265). \u003c/li\u003e\n\u003cli\u003eMinistry of Health. Ethiopia National Health Accounts Report, 2019/20. Partnership and Cooperation Directorate, Apr. 2022, Ministry of Health, Addis Ababa, Ethiopia.\u003c/li\u003e\n\u003cli\u003eJisso M, Assefa NA, Alemayehu A, Gadisa A, Fikre R, Umer A, Mohammed H, Yazie B, Gizaw HS, Mizana BA, Yesuf EA, Tilahun B, Endehabtu BF, Gonete TZ, Gashu KD, Angaw DA, Gurmu KK TA. Barriers to Family Planning Service Utilization in Ethiopia: A Qualitative Study. Ethiop J Health Sci. 2023 Oct;33(Spec Iss 2):143-154. doi: 10.4314/ejhs.v33i2.8S. PMID: 38352665; PMCID: PMC10859738. 2023. \u003c/li\u003e\n\u003cli\u003eTiruneh, M.G., Fenta, E.T., Endeshaw, D. et al. Health extension service utilization in Ethiopia: systematic review and meta-analysis. BMC Health Serv Res 24, 537 (2024). \u003c/li\u003e\n\u003cli\u003eRono, J., Kamau, L., Mangwana, J. et al. A policy analysis of policies and strategic plans on Maternal, Newborn and Child Health in Ethiopia. Int J Equity Health 21, 73 (2022). \u003c/li\u003e\n\u003cli\u003eGuttmacher Institute. \u003cem\u003eAdolescents\u0026rsquo; Need for and Use of Abortion Services in Sub-Saharan Africa\u003c/em\u003e. 2020.\u003c/li\u003e\n\u003cli\u003ePathfinder International. \u003cem\u003eYouth-Friendly Health Services: Improving Quality, Access, and Integration in Ethiopia\u003c/em\u003e. 2021.\u003c/li\u003e\n\u003cli\u003eUNFPA. \u003cem\u003eYouth Participation and SRHR in Ethiopia: Barriers and Opportunities\u003c/em\u003e. 2022.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. \u003cem\u003eGlobal Accelerated Action for the Health of Adolescents (AA-HA!): Guidance to Support Country Implementation\u003c/em\u003e. 2022.\u003c/li\u003e\n\u003cli\u003eAlemayehu, Y.K., Dessie, E., Medhin, G. et al. The impact of community-based health insurance on health service utilization and financial risk protection in Ethiopia. BMC Health Serv Res 23, 67 (2023). \u003c/li\u003e\n\u003cli\u003eTitiyos, Addisalem et al. \u0026ldquo;The Effect of a Decade Implemented Project in Improving the Uptake of Comprehensive Contraception: Difference-In-Difference Analysis.\u0026rdquo; Ethiopian journal of health sciences vol. 33,6 (2023): 927-934. \u003c/li\u003e\n\u003cli\u003eHagos, Asebe et al. \u0026ldquo;Inequalities in utilization of maternal health services in Ethiopia: evidence from the PMA Ethiopia longitudinal survey.\u0026rdquo; Frontiers in public health vol. 12 1431159. 7 Jan. 2025, \u003c/li\u003e\n\u003cli\u003eDemissie, Eshetu, and Martha Nemera. RESET-II Project Endline Evaluation: Promoting Resilient Livelihoods in Borana. CARE Ethiopia, Path Development Consulting and Research Services, 2021. \u003c/li\u003e\n\u003cli\u003eGebrekidan, Hailay et al. \u0026ldquo;Individual and community level factors associated with modern contraceptive utilization among women in Ethiopia: Multilevel modeling analysis.\u0026rdquo; PloS one vol. 19,5 e0303803. \u003c/li\u003e\n\u003cli\u003eKibret, M.A., Gebremedhin LT. Two decades of family planning in Ethiopia and the way forward to sustain hard-fought gains. 19 (Suppl 1), 124 (2022). https://doi.org/10.1186/s12978-022-01435-5. Reprod Heal. May. 2024, \u003c/li\u003e\n\u003cli\u003eDougherty L, Kassegne S, Nagbe R, Babogou J, Peace P, Moussa F, Kirk K, Tokplo H, Ouro-Gnao D, Agbodjan SP, Loll D, Werwie TR and Silva M (2024) A qualitative exploration of how a community engagement approach influences community and health worker perceptions related to family planning service delivery in Togo. Front. Reprod. Health 6:1389716. \u003c/li\u003e\n\u003cli\u003eWahyuningsih, Sri et al. \u0026ldquo;Unveiling barriers to reproductive health awareness among rural adolescents: a systematic review.\u0026rdquo; Frontiers in reproductive health vol. 6 1444111. 19 Nov. 2024, \u003c/li\u003e\n\u003cli\u003eHabte, A., Dessu S. The uptake of key elements of sexual and reproductive health services and its predictors among rural adolescents in Southern Ethiopia, 2020: application of a Poisson regression analysis. Reprod Heal. 2023;20(15). \u003c/li\u003e\n\u003cli\u003eMwangi, M. et al. The role of SRH interventions in improving mental health among Kenyan women.\u0026quot; African Journal of Reproductive Health. J Reprod Heal. 2018; \u003c/li\u003e\n\u003cli\u003eNamatovu, Hasifah Kasujja et al. \u0026ldquo;Barriers to eHealth adoption in routine antenatal care practices: Perspectives of expectant mothers in Uganda - A qualitative study using the unified theory of acceptance and use of technology model.\u0026rdquo; Digital health vol. 7 20552076211064406. 8 Dec. 2021, \u003c/li\u003e\n\u003cli\u003eKaranja, Sarah et al. \u0026ldquo;Factors influencing deliveries at health facilities in a rural Maasai Community in Magadi sub-County, Kenya.\u0026rdquo; BMC pregnancy and childbirth vol. 18,1 5. 3 Jan. 2018, \u003c/li\u003e\n\u003cli\u003eBain, Luchuo Engelbert et al. \u0026ldquo;Individual and contextual factors associated with maternal healthcare utilisation in Mali: a cross-sectional study using Demographic and Health Survey data.\u0026rdquo; BMJ open vol. 12,2 e057681. 22 Feb. 2022, \u003c/li\u003e\n\u003cli\u003eEsias Bedingar, Ferdinan Paningar, Ngarossorang Bedingar, Eric Mbaidoum, Naortangar Ngaradoum, Rifat Atun, Aisha Yousafzai - Optimising adolescents and young adults\u0026rsquo; utilisation of sexual and reproductive health and HIV services in Chad: a sensemaking approach: BMJ Global Health 2025;10: e017763. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"reproductive-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"reph","sideBox":"Learn more about [Reproductive Health](http://reproductive-health-journal.biomedcentral.com)","snPcode":"12978","submissionUrl":"https://submission.nature.com/new-submission/12978/3","title":"Reproductive Health","twitterHandle":"@Reprod_Health","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Sexual and Reproductive Health, Family Planning, Community-Based Health Interventions, Maternal Health Services, Ethiopia","lastPublishedDoi":"10.21203/rs.3.rs-6457796/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6457796/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Access to Sexual and Reproductive Health (SRH) services remains a significant public health challenge, particularly in rural and underserved areas. The Health Bazaar initiative was introduced as a community-based intervention to improve SRH service utilization and family planning uptake among reproductive-age women in Ethiopia. This study evaluates the effectiveness of the Health Bazaar model in improving access to SRH services, institutional delivery, antenatal care (ANC), postnatal care (PNC), and contraceptive utilization in intervention (Health Bazaar) compared to non-intervention areas (running SRH services in the routine health system).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A comparative cross-sectional study was conducted in five Ethiopian regions where the Health Bazaar model was implemented. Data were collected from 1,284 reproductive-age women (15–49 years), equally distributed between intervention (n=642) and non-intervention (n=642) areas. Additionally, secondary data from the District Health Information System (DHIS2) (2018–2024) were analysed to assess trends in SRH service utilization. A multistage cluster sampling approach was used, and data were analysed using descriptive statistics, trend analysis, and multilevel mixed-effects logistic regression to identify factors associated with SRH service uptake.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The study found that SRH service utilization was significantly higher in intervention areas (65.1%) compared to non-intervention areas (47.6%) (p \u0026lt; 0.001). Contraceptive prevalence was also higher in intervention areas (53.3% vs. 41.8%, p = 0.001), with injectables (45.8%) and implants (44.5%) being the most commonly used methods. ANC service utilization was higher in intervention areas (87.3%) compared to non-intervention areas (77.1%), and institutional delivery rates were 89.4% in intervention areas compared to 80.6% in non-intervention areas. Trend analysis showed a greater increase in ANC (10.2 per quarter), institutional deliveries (5.8 per quarter), and PNC utilization (9.5 per quarter) in intervention areas compared to non-intervention areas. These differences remained statistically significant after adjusting for potential confounding factors, including age, marital status, education, household income, region, and participation in SRH-related discussions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e The study findings demonstrate that the Health Bazaar intervention significantly improved SRH service utilization, family planning uptake, and maternal health service access in Ethiopia. The community-driven model holds potential for scaling up to further enhance SRH services in similar low-resource settings. Future interventions should focus on addressing remaining barriers such as awareness gaps, distance to health facilities, and socio-cultural influences to maximize impact.\u003c/p\u003e","manuscriptTitle":"Evaluating the role of the Health Bazaar Initiative on Sexual and Reproductive Health Service Utilization in Ethiopia: A Comparative Analysis of community- based interventions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-10 09:55:02","doi":"10.21203/rs.3.rs-6457796/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-26T03:57:36+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-24T18:41:43+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-18T20:40:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"145464792983432864540464442039467980164","date":"2025-07-15T04:19:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"210680500490851567598758844570107593711","date":"2025-07-08T13:31:04+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-08T13:10:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-22T11:09:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-22T03:50:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"Reproductive Health","date":"2025-04-15T20:13:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"reproductive-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"reph","sideBox":"Learn more about [Reproductive Health](http://reproductive-health-journal.biomedcentral.com)","snPcode":"12978","submissionUrl":"https://submission.nature.com/new-submission/12978/3","title":"Reproductive Health","twitterHandle":"@Reprod_Health","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"64f821c9-113f-4e0b-a9bc-60c60410778a","owner":[],"postedDate":"July 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-01T16:12:05+00:00","versionOfRecord":{"articleIdentity":"rs-6457796","link":"https://doi.org/10.1186/s12978-025-02218-4","journal":{"identity":"reproductive-health","isVorOnly":false,"title":"Reproductive Health"},"publishedOn":"2025-11-26 15:58:48","publishedOnDateReadable":"November 26th, 2025"},"versionCreatedAt":"2025-07-10 09:55:02","video":"","vorDoi":"10.1186/s12978-025-02218-4","vorDoiUrl":"https://doi.org/10.1186/s12978-025-02218-4","workflowStages":[]},"version":"v1","identity":"rs-6457796","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6457796","identity":"rs-6457796","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}