부산대학교 도서관

Introduction: Preventive nutritional management of frailty, a multidimensional intermediate status in the ageing process, may reduce the risk of adverse health‐related outcomes. We investigated the ability of a measure combining physical frailty with nutritional imbalance, defined as nutritional frailty, to predict all‐cause mortality over a period of up to 8 years. Methods: We analysed data on 1,943 older adults from the population‐based 'Salus in Apulia Study'. Physical frailty was operationalized using Cardiovascular Health Study criteria and cognitive frailty by combining physical frailty with cognitive impairment. A novel five‐item construct was built to assess the extent of nutritional imbalance identified with a machine learning algorithm. Cox models and Kaplan–Meier survival probability analyses of physical frailty, nutritional imbalance (two or more of the following: low body mass index, low skeletal muscle index, ≥2.3 g/day sodium intake, <3.35 g/day potassium intake and <9.9 g/day iron intake), cognitive frailty and the novel nutritional frailty phenotype (physical frailty plus nutritional imbalance) were applied to assess all‐cause mortality risk, adjusted for age, sex, education and multimorbidity. Results: The overall prevalence of nutritional frailty was 4.52% (95% confidence interval, CI:3.55–5.44), being more frequent in males. Subjects with nutritional frailty were at higher risk for all‐cause mortality [hazard ratio (HR):2.31; 95%CI:1.41–3.79] than those with physical frailty (HR:1.45,95% CI:1.0–2.02), nutritional imbalance (HR:1.39; 95%CI:1.05–1.83) and cognitive frailty (HR:1.06; 95%CI:0.56–2.01). Conclusions: Efforts to identify, manage and prevent frailty should include the nutritional domain. The nutritional frailty phenotype may highlight major nutritional determinants that could drive survival and health trajectories in older adults. [ABSTRACT FROM AUTHOR]