Prevalence and associated factors of pre-frailty and frailty among Thai community-dwelling older adults aged 65 years and above - Manorangsan, Sukwida; Chaiparinya, Pawan; Mongkolsomlit, Sirima; Boonyong, Sujitra (Journal of Associated Medical Sciences, 2025)
Background: As Thailand’s aging population grows rapidly, frailty status may develop and have serious implications. Early detection or prevention can be encouraged, especially prior to the emergence of advanced frailty and functional deterioration. Pre-frailty and frailty should be identified and investigated. Objectives: To explore the prevalence of frailty statuses and their associations with sociodemographic characteristics among Thai older adults. Materials and methods: This study was a cross-sectional design. Two hundred sixty-eight Thai community-dwelling older adults aged ≥65 years were recruited. Their physical frailty status was determined using the Fried frailty phenotypic criteria, which comprise weakness, slowness, low physical activity, weight loss, and exhaustion. Multinomial (Polytomous) logistic regression was used to detect associations between frailty status and sociodemographics. Results: Among participants, the prevalences of pre-frailty, frailty, and robustness were 38.4%, 42.5%, and 19.0%, respectively. In the multivariate-adjusted model, pre-frailty was significantly associated with age (relative risk ratio(RRR)=1.10; 95% confidence interval (CI)=1.01-1.18, p=0.020), occupation as governor or owner (RRR=0.37; 95%CI=0.15-0.92, p=0.032), and housewife (RRR=0.29; 95%CI=0.09-0.93, p=0.037). Likewise, frailty was associated with age (RRR=1.28; 95%CI=1.18-1.39, p<0.001), gender (RRR=0.34; 95%CI=0.14-0.85, p=0.021), BMI (RRR=0.88; 95%CI=0.79-0.98, p=0.019), and education (RRR=0.23l; 95%CI=0.09-0.58, p=0.002). Additionally, comorbidity with ≥3 diseases was significantly associated with frailty (RRR=16.34; 95%CI=1.64-162.46, p=0.017). Conclusion: Our findings reveal comparable prevalence rates of pre-frailty and frailty among Thai older adults. While age and occupation were associated with pre-frailty, a broader range of factors, including age, gender, BMI, comorbidities, and education, showed associations with frailty. These results underscore the importance of considering multiple factors collectively when screening or assessing an elderly individual’s risk of developing pre-frailty or frailty.