The spatial analysis of multimorbidity in Thai Cohort Study

Background: This study used Thai Cohort Study (TCS) data to investigate the spatial and sociodemographic determinants of multimorbidity (two or more chronic conditions coexistence on one person) prevalence in Thailand in 2013. Methods: Crude and age-adjusted prevalence were calculated for each province. Hotspot analysis was conducted to identify regions with statistically significant hotspots and cold spots, including areas without significant clustering. Then, ordinal logistic regression was used to identify sociodemographic background variables that predict hotpots. Results: The highest age-adjusted provincial level prevalence of multimorbidity was in Sing Buri (18.26%). Sak Lek District in Phichit Province also had the highest age-adjusted district level prevalence of multimorbidity at 37.13%. The cold spots region in crude and age-adjusted prevalence of multimorbidity were clustered in Southern Thailand. Forty-eight districts were identified as hotspots in both crude and age-adjusted multimorbidity prevalence, 19 of which are in Bangkok (the capital). Population density (person/km ², odd ratio, provincial level: OR:1.00, 95% CI: 1.00–1.01; district level: OR: 1.01, 95% CI: 1.00–1.01), Aging index (provincial level: OR:1.03, 95% CI: 1.01–1.04; district level: OR: 1.01, 95% CI: 1.00–1.01), and average educational years (provincial level: OR:1.92, 95% CI: 1.07–3.48; district level: OR: 1.27, 95% CI: 1.02–2.26) were greater in hot spots areas. Conclusion: This study shows that the prevalence of multimorbidity in Thailand is positively correlated with the degree of development of the region. Spatial cluster analysis provides new evidence for policymakers to design tailored interventions to target multimorbidity and allocate health resources to areas of unmet need.