Background Frailty was an age-related geriatric syndrome, with its prevalence among Chinese older adults being notably high and demonstrating a rising trend over time. Obesity was closely associated with the development of numerous diseases, but its relationship with frailty remained controversial. This uncertainty was potentially attributable to limitations of conventional obesity indicators in characterizing adipose tissue distribution. Therefore, investigating the associations between multiple adiposity metrics and frailty was important for to advance the understanding of frailty pathogenesis and developing preventive interventions.
Objective This study investigates the relationship between various obesity indicators and frailty, providing a scientific basis for the early prevention and control of frailty in older adults.
Methods In this study, a total of 1 429 elderly people aged 60 years and above were surveyed in six rural villages in Jingyuan County, Gansu Province, from March to May 2023. After further exclusions, a final sample of 1 153 participants was included in the analysis. The FRAIL scale was utilized to assess the frailty status of the elderly. Based on Chinese obesity criteria, waist circumference and BMI were categorized, and waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body roundness index (BRI), and Chinese visceral adiposity index (CVAI) were grouped by quartiles. Multivariate Logistic regression, restricted cubic splines, and receiver operating characteristic (ROC) curve analysis were employed to explore the relationship between different obesity indicators and frailty.
Results This study included 1 153 elderly participants aged≥60 years, comprising 474 males (41.11%) and 679 females (58.89%), with a mean age of 70.86±4.76 years. Based on FRAIL scale assessments, 226 participants were identified as frail and 927 as non-frail, resulting in a frailty prevalence of 19.60%. The adjusted multivariate Logistic regression analysis revealed that central obesity, moderate to severe obesity (reference: normal BMI), Q3 and Q4 (reference: Q1) levels of WHR, and Q4 (reference: Q1) levels of WHtR, BRI, and CVAI were significant risk factors for frailty in the elderly population (P<0.05), with progressively increasing risks of frailty associated with elevated levels of waist circumference, BMI, WHR, WHtR, BRI, and CVAI (Ptrend<0.05). The restricted cubic spline (RCS) curve indicated that waist circumference, BMI, WHtR, BRI, and CVAI were linearly and positively correlated with the risk of frailty in the elderly (Plinear<0.05). The ROC curve analysis demonstrated that that the predictive capacity for frailty in the elderly was possessed by waist circumference, BMI, WHR, WHtR, BRI, and CVAI, with area under the curve (AUC) of 0.557 (95%CI=0.515-0.598), 0.570 (95%CI=0.528-0.612), 0.558 (95%CI=0.515-0.600), 0.610 (95%CI=0.568-0.652), 0.610 (95%CI=0.568-0.652), and 0.586 (95%CI=0.546-0.626), respectively (P<0.05). Additionally, WHtR, BRI, and CVAI demonstrated better predictive ability compared to waist circumference (Z=-5.443, P<0.001; Z=-5.443, P<0.001; Z=-2.595, P=0.009), and both WHtR and BRI showed better predictive ability compared to BMI (Z=-2.885, P=0.004; Z=-2.884, P=0.004).
Conclusion In rural regions, among the elderly population aged 60 and above, obesity indicators such as waist circumference, BMI, WHR, WHtR, BRI, and CVAI were positively correlated with the risk of frailty in the elderly. Among these indicators, WHtR and BRI showed better predictive ability for frailty.