ArticleBMC public health2025
Modeling determinants of accessibility for healthcare services in rural and urban areas of Dodoma, Tanzania.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Health system responsiveness to older adults with functional limitations and socio-economic vulnerability in India.Global health action · 2026Article
- Prevalence and determinants of deworming uptake among under-five children in Tanzania: evidence from the Tanzania Demographic and Health Survey 2022.Tropical medicine and health · 2026Article
- Culturally tailored mHealth interventions for chronic low back pain in rural sub-Saharan Africa: a systematic review protocol.BMJ open · 2026Article
- Knowledge, attitudes, and practices in cardiometabolic health among adolescents and adults in HIV care in Dar es Salaam, Tanzania.Frontiers in public health · 2026Article
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3 authors.
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Abstract
backgroundHealthcare accessibility remains a critical challenge in many low-and middle-income countries, where disparities between rural and urban areas persist. This study, conducted in Dodoma region, Tanzania, models the determinants of healthcare accessibility, aiming to generate evidence that informs policy interventions for equitable healthcare service delivery in underserved populations.
methodsA cross-sectional survey design was adopted. Data were collected from 1,009 households (urban 556; rural 453) across four selected districts withing Dodoma region, Tanzania, using a structured questionnaire digitized and implemented through KoboToolbox. The bivariate analysis and binary logistics regression were used to assess the determinants of healthcare accessibility. Fairlie decomposition was also used to assess and explain the healthcare accessibility disparity between urban and rural areas.
resultsAmong the 1,009 households surveyed, 45% had access to healthcare services, with urban households having higher access compared to rural households. Significant determinants of healthcare accessibility included healthcare insurance cover [(AOR = 72.006 p < 0.001), CI:19.573 - 264.895], household size [(AOR = 0.713, p < 0.05), CI: 0.536 - 0.947], age of the head of household [(AOR = 0.830 p < 0.001), CI:0.785 - 0.878], and Out-of-pocket costs used for the last illness episodes [(AOR = 0.404 p < 0.01), CI:0.139 -1.167]. Additionally, decision-making authority within households, payment methods, and the presence of chronic illness showed significant or partial influence on accessibility. Fairlie's decomposition revealed that health insurance and the age of the head of household account for the largest (93.4%) share of the disparity in healthcare accessibility between urban and rural households. These findings underscore the complexity of healthcare access, providing actionable insights for policy interventions to address rural-urban disparities.
conclusionThe study highlights the importance of health insurance coverage in improving healthcare access, emphasizing the need for targeted policy interventions to address rural-urban disparities and improve health outcomes, considering unique rural household needs.
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