Active ageing behaviors among urban older adults in disaster-prone communities using confirmatory factor analysis of health behavior constructs
Issued Date
2026-12-01
Resource Type
eISSN
20452322
Scopus ID
2-s2.0-105040367447
Pubmed ID
41936599
Journal Title
Scientific Reports
Volume
16
Issue
1
Rights Holder(s)
SCOPUS
Bibliographic Citation
Scientific Reports Vol.16 No.1 (2026)
Suggested Citation
Muenboonme W., Nunthaitaweekul P., Rattakul B., Tienpratarn W. Active ageing behaviors among urban older adults in disaster-prone communities using confirmatory factor analysis of health behavior constructs. Scientific Reports Vol.16 No.1 (2026). doi:10.1038/s41598-026-46240-3 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/117139
Title
Active ageing behaviors among urban older adults in disaster-prone communities using confirmatory factor analysis of health behavior constructs
Corresponding Author(s)
Other Contributor(s)
Abstract
Older adults in disaster-prone urban areas face elevated risks from environmental hazards, chronic disease, and social vulnerabilities. Although active ageing is widely promoted, limited evidence has validated its behavioral domains in hazard-prone urban contexts. This study aimed to examine the factorial structure of active ageing behaviors and identify sociodemographic influences among older adults in Bangkok, Thailand. A cross-sectional survey was conducted using a multistage sampling design, involving purposive selection of disaster-prone districts followed by random sampling at subsequent stages, among 500 older adults in Bangkok. Data were collected through structured, interviewer-administered questionnaires based on the WHO Active Ageing Framework, covering six domains. Confirmatory Factor Analysis (CFA) and Generalized Structural Equation Modeling (GSEM) were performed using maximum likelihood estimation with robust standard errors. CFA supported a four-factor model comprising dietary behavior, stress management, self-care, and substance avoidance with significant loadings (β = 0.711–1.095) and excellent fit (CFI = 0.991, TLI = 0.972, RMSEA = 0.057, SRMR = 0.020). Substance avoidance and stress management were most salient. The six-factor model including exercise and oral care showed poor fit. GSEM indicated that male sex was negatively associated with active ageing (β = − 0.23, p < 0.001), while higher education, cohabitation, and chronic disease were positive predictors. The validated four-domain model highlights active ageing as both behavioral and socially embedded. Strengthening behavioral resilience and addressing social and environmental barriers are essential for interventions and policies in disaster-prone urban ageing populations.