Analysis of the Current Status and Associated Factors of Premature Frailty in Adults Aged 18-59 Years Based on the NHANES Database

This study aims to determine the prevalence of premature frailty in adults aged 18-59 years, and identify modifiable factors associated with its occurrence. The findings will facilitate targeted screening for high-risk individuals and inform primary prevention strategies to mitigate development of premature frailty.

This study analyzed data from the National Health and Nutrition Examination Survey (NHANES, 2005-2018), including adults aged 18-59 years. Premature frailty was defined using a 49 item frailty index (FI) based on the deficit accumulation model. We assessed nutritional status, depressive symptoms, and physical activity (PA), respectively. Multivariable logistic regression identified factors associated with premature frailty, with covariates selected via univariate screening (p < 0.05). Random forest modeling ranked variable importance, and restricted cubic splines examined nonlinear associations between continuous predictors and frailty risk.

A total of 4173 participants were included in this study, with 49.2% male and 50.8% female. The highest prevalence of premature frailty was observed in the 40-59 age group, accounting for 67.3% of cases. Logistic regression results showed that depression score, sleep condition, and age were associated factors for premature frailty, while education level, marital status, ratio of family income to poverty (PIR), alcohol intake, Healthy Eating Index (HEI) score, and PA were protective factors. Based on the random forest model, depression scores, sleep condition, and PA were identified as the top three associated factors for premature frailty. Restricted cubic spline analysis revealed potential nonlinear relationships between premature frailty and depression scores, PA, PIR, and alcohol intake, while suggesting a possible linear relationship with HEI score.

Multiple factors are associated with the occurrence of premature frailty, among which depression, PA, and sleep condition are the three most prominent. In clinical practice, healthcare professionals should prioritize high-risk populations by implementing effective interventions such as psychological care, health education, and targeted treatments.