PloS one · 2026
Exploring the association between Frailty Index and Knee osteoarthritis in middle-aged and older Chinese adults: A cross-sectional analysis of data from the China Health and Retirement Longitudinal Study.
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Zhu Na, Lin Hongming, Yu Jia, Yang Rong, Tao Danhao, Huang Guoxin, Qian Da, Liu Yu, Chen Bingqian
Аннотация
OBJECTIVE: To explore the relationship between Frailty Index (FI) and Knee osteoarthritis (KOA) in Chinese people aged 45 and above.
METHODS: Data on symptomatic KOA, FI, and over ten covariates were from the China Health and Retirement Longitudinal Study (CHARLS). Logistic regression and restricted cubic splines (RCS) were used to analyze the correlation. Subgroup and interaction analyses were also conducted, and FI was divided into quartiles to assess result stability. Six machine learning constructs were used to build predictive models, which were then evaluated.
RESULTS: Among 29,105 participants, 5,012 had symptomatic KOA. Weighted multivariate logistic results showed a correlation between KOA and frailty (OR 3.63(3.48,3.78)), present across quartiles. Subgroup analyses revealed potential effects of various factors on their association, with significant interactions found for gender, education, place of residence, alcohol consumption, hypertension, and dyslipidemia. RCS results indicated a logarithmic non-linear relationship between symptomatic KOA and frailty. The area under the curve of the Random Forest Machine model is 0.90, and it performs best on the calibration curve and decision curve analysis.
CONCLUSION: This study showed a nonlinear relationship between FI and KOA in middle-aged and older Chinese adults, with higher FI scores linked to higher KOA prevalence and a significant inflection point, informing focused KOA interventions in aging populations.
METHODS: Data on symptomatic KOA, FI, and over ten covariates were from the China Health and Retirement Longitudinal Study (CHARLS). Logistic regression and restricted cubic splines (RCS) were used to analyze the correlation. Subgroup and interaction analyses were also conducted, and FI was divided into quartiles to assess result stability. Six machine learning constructs were used to build predictive models, which were then evaluated.
RESULTS: Among 29,105 participants, 5,012 had symptomatic KOA. Weighted multivariate logistic results showed a correlation between KOA and frailty (OR 3.63(3.48,3.78)), present across quartiles. Subgroup analyses revealed potential effects of various factors on their association, with significant interactions found for gender, education, place of residence, alcohol consumption, hypertension, and dyslipidemia. RCS results indicated a logarithmic non-linear relationship between symptomatic KOA and frailty. The area under the curve of the Random Forest Machine model is 0.90, and it performs best on the calibration curve and decision curve analysis.
CONCLUSION: This study showed a nonlinear relationship between FI and KOA in middle-aged and older Chinese adults, with higher FI scores linked to higher KOA prevalence and a significant inflection point, informing focused KOA interventions in aging populations.