We investigated and quantified the predictability of frailty associated with musculoskeletal parameters. This longitudinal study included 287 men aged ≥ 50 yr at baseline (2001-2006) from the Geelong Osteoporosis Study. Baseline musculoskeletal measures included femoral neck bone mineral density (BMD), appendicular lean mass index (ALMI, kg/m2) and whole-body fat mass index (FMI, kg/m2) and lower-limb strength. Frailty at the 15 yr-follow-up (2016-2019) was defined as ≥ 3 and non-frail as < 3, of the following: unintentional weight loss, weakness, low physical activity, exhaustion, and slowness. Binary regression models and AUROC curves quantified the attributable risk of musculoskeletal factors to frailty and their predictive ability. Potential confounders included anthropometry, smoking, alcohol, FMI, socioeconomic status and comorbidities. Forty-eight (16.7%) men were frail at 15 yr-follow-up. Musculoskeletal models were better predictors of frailty compared to the referent (confounders only) model (AUROC for musculoskeletal factors 0.74 vs 0.67 for the referent model). The model with the highest AUROC (0.74; 95% CI 0.66-0.82) included BMD, ALMI and muscle strength (hip abductors) and was better than the referent model that included only lifestyle factors (p = 0.046). Musculoskeletal parameters improved the predictability model as measured by AUROC for frailty after 15 years. In general, muscle models performed better compared to bone models. Musculoskeletal parameters improved the predictability of frailty of the referent model that included lifestyle factors. Muscle deficits accounted for a greater proportion of the risk for frailty than did bone deficits. Targeting musculoskeletal health could be a possible avenue of intervention in regards to frailty.
Keywords: Attributable risk; Frailty; Osteoporosis; Prediction; Sarcopenia.
© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.