S1 File -

<div> Introduction Accessing affordable and high-quality healthcare remains a persistent challenge in low- and middle-income countries like Ethiopia. Community-based health insurance (CBHI) programs offer a promising solution to expand healthcare coverage and provide financial protection, particularly for vulnerable populations such as women. This study aimed to investigate the factors that influence CBHI enrollment among women in Sidama National Regional State, Ethiopia, using a multilevel analysis. Methods A community-based cross-sectional study was conducted using a multistage sampling technique from December 15<sup>th</sup> to January 12<sup>th</sup>, 2024, in the central Sidama zone, Sidama National Regional State. The study included 835 women aged 18 years and older, residing both in rural and urban areas. Face-to-face interviews were conducted using a pre-tested questionnaire to collect comprehensive data on socio-demographic, economic, and scheme-related factors. Data collection utilized the Open Data Kit mobile application, and data analysis was performed using Stata version 16, employing multilevel modified Poisson modeling to identify determinants of CBHI enrollment. Results Among 845 samples, 835 women were interviewed, resulting in a response rate of 98.8%. Individual-level factors such as older age (APR = 1.02, 95%CI: 1.01–1.03, p<0.001), larger family size (APR = 1.09, 95%CI: 1.03–1.16, p = 0.001), and moderate wealth index (APR = 2.72, 95%CI: 1.28–5.79, p = 0.009) showed positive associations with CBHI enrollment, depicted a higher likelihood of individuals joining the insurance scheme. In addition, at the community level, higher rates of women’s literacy (APR = 1.73, 1.18–2.55, p = 0.005), and women’s autonomy (APR = 2.64, 95%CI: 1.50–4.65, p = 0.001) were positively correlated with CBHI enrollment. Conclusions The study revealed that the enrollment rate among women in the CBHI scheme was 35%, indicating a need for improved outreach efforts. Significant factors that affected enrollment included older age, larger family size, and moderate wealth. Additionally, positive community-level influences such as higher literacy rates and increased autonomy for women contributed to higher enrollment. To improve CBHI enrollment, the target should focus on younger women and those from smaller families. Financial support, such as subsidies for low-income women, can also encourage participation. Investing in women’s literacy and empowerment programs will enable them to make informed health choices, thereby increasing enrollment. Finally, ongoing research is necessary to track enrollment trends and identify barriers. Utilizing qualitative methods will yield insights into women’s perceptions of CBHI, facilitating more effective strategies. Implementing these recommendations can enhance women’s access to healthcare through CBHI. </div>

Publication Details

Journal
Figshare
Published
2025-02-03
DOI
https://doi.org/10.1371/journal.pone.0316948.s001
Primary Topic
Global Maternal and Child Health
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

S1 File -

Figshare
Global Maternal and Child Health
article

S1 File -

article en

Abstract

<div> Introduction Accessing affordable and high-quality healthcare remains a persistent challenge in low- and middle-income countries like Ethiopia. Community-based health insurance (CBHI) programs offer a promising solution to expand healthcare coverage and provide financial protection, particularly for vulnerable populations such as women. This study aimed to investigate the factors that influence CBHI enrollment among women in Sidama National Regional State, Ethiopia, using a multilevel analysis. Methods A community-based cross-sectional study was conducted using a multistage sampling technique from December 15<sup>th</sup> to January 12<sup>th</sup>, 2024, in the central Sidama zone, Sidama National Regional State. The study included 835 women aged 18 years and older, residing both in rural and urban areas. Face-to-face interviews were conducted using a pre-tested questionnaire to collect comprehensive data on socio-demographic, economic, and scheme-related factors. Data collection utilized the Open Data Kit mobile application, and data analysis was performed using Stata version 16, employing multilevel modified Poisson modeling to identify determinants of CBHI enrollment. Results Among 845 samples, 835 women were interviewed, resulting in a response rate of 98.8%. Individual-level factors such as older age (APR = 1.02, 95%CI: 1.01–1.03, p<0.001), larger family size (APR = 1.09, 95%CI: 1.03–1.16, p = 0.001), and moderate wealth index (APR = 2.72, 95%CI: 1.28–5.79, p = 0.009) showed positive associations with CBHI enrollment, depicted a higher likelihood of individuals joining the insurance scheme. In addition, at the community level, higher rates of women’s literacy (APR = 1.73, 1.18–2.55, p = 0.005), and women’s autonomy (APR = 2.64, 95%CI: 1.50–4.65, p = 0.001) were positively correlated with CBHI enrollment. Conclusions The study revealed that the enrollment rate among women in the CBHI scheme was 35%, indicating a need for improved outreach efforts. Significant factors that affected enrollment included older age, larger family size, and moderate wealth. Additionally, positive community-level influences such as higher literacy rates and increased autonomy for women contributed to higher enrollment. To improve CBHI enrollment, the target should focus on younger women and those from smaller families. Financial support, such as subsidies for low-income women, can also encourage participation. Investing in women’s literacy and empowerment programs will enable them to make informed health choices, thereby increasing enrollment. Finally, ongoing research is necessary to track enrollment trends and identify barriers. Utilizing qualitative methods will yield insights into women’s perceptions of CBHI, facilitating more effective strategies. Implementing these recommendations can enhance women’s access to healthcare through CBHI. </div>

Figshare
Quality Education
Openalex Percentile: Top 49%
Global Maternal and Child Health
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.