Applications of GIS in Analyzing Health Disparities Among the Elderly and Health Center Service Area Coverage: Community Model, Lahansai District, Buriram, Thailand

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R. Piwpong
P. Sujayanont
J. Jundaeng
J. Krates
R. Kijphati
C. Nithikathkul

Abstract

Thailand’s aging population has led to a growing demand for healthcare services, particularly for elderly individuals with chronic conditions or physical limitations. Geographic Information Systems (GIS) offer valuable tools for healthcare planning and management by providing spatial data that can improve resource allocation. This study utilized GIS to assess the healthcare needs of the elderly population in rural Thailand, specifically focusing on the Nong Waeng Sub-district of Lahansai District, Buriram. The study targeted 2,244 individuals aged 60 and above, from which 495 participants were randomly selected. GIS tools were used to map elderly households through GPS coordinates, while health assessments were conducted, including cognitive impairment screening (Mini-Cog), Activities of Daily Living (ADL) evaluations, and fall risk assessments. A GIS-based database was created to analyze the spatial distribution of elderly residents and their associated health risks. Spatial mapping revealed significant disparities, such as the prevalence of chronic diseases (hypertension: 22.42%, diabetes: 11.92%), cognitive impairment (dementia rates ranging from 7.52% to 41.00% across villages), and high fall risks (56.6% overall, with a peak of 52.47% in Nong Wa Mai). While most elderly individuals were independent in daily activities (96.99–99.50% ADL scores), clusters of high fall risk and chronic disease were identified. Healthcare coverage was uneven, with the Nong Ta Yao Health Center serving the majority of residents within a 3-kilometer radius. The study demonstrated that GIS can be a powerful tool for targeting interventions, such as prioritizing fall prevention and chronic disease management, while also revealing gaps in caregiver coverage. Stakeholders expressed high satisfaction with the GIS-driven insights (mean score: 4.32). This approach offers a valuable framework for evidence-based strategies to improve long-term care systems and enhance the quality of life for the elderly in Thailand.

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How to Cite
Piwpong, R., Sujayanont, P., Jundaeng, J., Krates, J., Kijphati, R., & Nithikathkul, C. (2025). Applications of GIS in Analyzing Health Disparities Among the Elderly and Health Center Service Area Coverage: Community Model, Lahansai District, Buriram, Thailand. International Journal of Geoinformatics, 21(4), 131–148. https://doi.org/10.52939/ijg.v21i4.4075
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