Lin Yu-Chun, Yan Huang-Ting
Department of Chinese Medicine, China Medical University Hospital, Taichung, Taiwan.
Graduate Institute of Integrated Medicine, College of Chinese Medicine, China Medical University, Taichung, Taiwan.
Aging Clin Exp Res. 2024 Dec 3;36(1):233. doi: 10.1007/s40520-024-02887-4.
The frailty index is widely used in clinical and community settings to assess health status. This study aimed to identify the potential phenotypes of frail older adults and examine their relationship with health consequences compared with existing frailty measures.
The 11-year follow-up data from the Taiwan Longitudinal Study on Aging, covering 5,334 individuals aged ≥ 50 years, were analyzed using random-effects panel logit models. We identified three frailty phenotypes: energy-based frailty (EBF), sarcopenia-based frailty (SBF), and hybrid-based frailty (HBF). Existing frailty measures such as the Study of Osteoporotic Fractures (SOF), Fatigue, Resistance, Ambulation, Illness, and Loss of weight (FRAIL), and Fried scales were applied. We examined their correlation with health outcomes, such as falls and fractures, depression, comorbidities, hospitalization, emergency department visits, and mortality, adjusting for individual-level characteristics.
Individuals with only EBF were found to be at a lower risk of falls and fractures than their counterparts with only SBF (adjusted odds ratio [AOR] = 0.13, 95% confidence interval [CI] = 0.03-0.46). Depression was less likely in the SBF group than in the EBF group (AOR = 0.02, 95% CI = 0.01-0.05). Hybrid-based frail older adults were more likely to be hospitalized (AOR = 1.84, 95% CI = 1.08-3.14) and have emergency department visits (AOR = 2.03, 95% CI = 1.15-3.58). Frailty assessed using existing measures was associated with adverse health outcomes.
The proposed frailty phenotype classification differs from the existing frailty measures in its ability to distinguish the corresponding phenotypes underlying various health consequences. Governments may develop strategies based on frailty phenotypes to mitigate adverse health consequences.
衰弱指数在临床和社区环境中被广泛用于评估健康状况。本研究旨在识别衰弱老年人的潜在表型,并与现有的衰弱测量方法相比,检验它们与健康后果之间的关系。
使用随机效应面板logit模型分析了台湾老龄化纵向研究的11年随访数据,该研究涵盖了5334名年龄≥50岁的个体。我们识别出三种衰弱表型:基于能量的衰弱(EBF)、基于肌肉减少症的衰弱(SBF)和基于混合因素的衰弱(HBF)。应用了现有的衰弱测量方法,如骨质疏松性骨折研究(SOF)、疲劳、抵抗力、活动能力、疾病和体重减轻(FRAIL)以及Fried量表。我们在调整个体水平特征后,检验了它们与跌倒、骨折、抑郁、合并症、住院、急诊就诊和死亡率等健康结局的相关性。
仅患有EBF的个体跌倒和骨折的风险低于仅患有SBF的个体(调整后的优势比[AOR]=0.13,95%置信区间[CI]=0.03-0.46)。SBF组的抑郁发生率低于EBF组(AOR=0.02,95%CI=0.01-0.05)。基于混合因素的衰弱老年人更有可能住院(AOR=1.84,95%CI=1.08-3.14)和急诊就诊(AOR=2.03,95%CI=1.15-3.58)。使用现有测量方法评估的衰弱与不良健康结局相关。
所提出的衰弱表型分类在区分各种健康后果背后的相应表型的能力方面与现有的衰弱测量方法不同。政府可以基于衰弱表型制定策略,以减轻不良健康后果。