GIS-Linked Spatial Contextualization of Depression-Related Service Needs among Older Adults in Lat Yai Subdistrict, Samut Songkhram Province, Thailand

Abstract

Depression among older adults is shaped by individual, household, economic, and community-level contexts. This study restructured a cross-sectional survey of older adults in Lat Yai Subdistrict, Mueang District, Samut Songkhram Province, Thailand, into a geoinformatics-oriented manuscript by linking survey findings with official aggregate village-level spatial data. The survey included 380 older adults selected from a population of 3,428. Depression was assessed using the Thai Geriatric Depression Scale, while demographic, economic, living-arrangement, morbidity, and family relationship variables were collected through structured questionnaires. Associations between categorical variables and depression were examined using chi-square tests, and the relationship between family relationship score and depression was analysed using Pearson's correlation. To strengthen the GIS contribution without overinterpreting the original survey, village-level older-adult service-register data from the official 3 Doctor system were linked with village point coordinates in WGS84. The GIS component was designed as a descriptive spatial-context map showing the distribution of registered older-adult functional-status records and homebound or bedridden records; it did not estimate village-level depression prevalence or depression risk. Most respondents had no depression (85.79%), while 8.16%, 5.26%, and 0.79% had mild, moderate, and severe depression, respectively. Age, income, marital status, income source, and income adequacy were significantly associated with depression. Family relationship had a significant negative correlation with depression. The GIS output supports public-health planning by indicating where screening outreach and home-visit integration may be operationally important, while avoiding ecological inference from non-geocoded depression outcomes.