Exploring the Socio-economic Determinants of Healthcare Utilization in Homabay County Using Binary Logistic Regression Models

Abstract

Access to healthcare services is vital for human development, with various factors influencing accessibility, including financial status, cultural norms, geographic location, and educational level. These factors collectively impact how healthcare is accessed and utilized, underscoring the need for strategies to improve access (Flaubert et al., 2021). In Kenya, persistent disparities in healthcare utilization are influenced by various factors such as funding and uneven resource distribution (Vincent Okungu, 2023). Understanding these factors is crucial for devising strategies to enhance healthcare access This study utilizes various binary logistic regression models, specifically logistic regression models with and without interaction terms. Furthermore, a stepwise logistic regression technique was employed to analyze the impact of socio-economic factors on healthcare utilization in Homabay County, Kenya. The selection of stepwise logistic regression was based on its ability to systematically identify and incorporate important predictors of healthcare utilization, thus ensuring both simplicity and accuracy in capturing the socio-economic determinants. Through the stepwise selection process, variables such as education status, marital status, and recent illness were identified as significant predictors of healthcare utilization. Specifically, individuals without formal education were significantly more likely to utilize healthcare services compared to those with formal education (education status: OR = 0.473, p = 0.000213). Furthermore, unmarried individuals showed higher healthcare utilization rates than married individuals (marital status: OR = 0.659, p = 0.001999). Notably, experiencing an illness in the last four weeks emerged as the strongest predictor of healthcare utilization (illness last 4 weeks: OR = 77.215, p < 2e-16). In contrast, gender, employment status, and health rating status did not demonstrate significant effects in the final model. These findings highlight the need for targeted interventions to address healthcare access challenges in Homabay County. By focusing on education, marital status, and recent illness, policymakers and healthcare providers can develop strategies to improve healthcare utilization and address disparities.