Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, South Australia, 5005, Australia.
Digital Health Research Centre, College of Nursing and Health Sciences, Flinders University, Adelaide, South Australia, 5005, Australia.
BMC Geriatr. 2020 Mar 6;20(1):96. doi: 10.1186/s12877-020-1490-7.
There is little known about pre-frailty attributes or when changes which contribute to frailty might be detectable and amenable to change. This study explores pre-frailty and frailty in independent community-dwelling adults aged 40-75 years.
Participants were recruited through local council networks, a national bank and one university in Adelaide, Australia. Fried frailty phenotype scores were calculated from measures of unintentional weight loss, exhaustion, low physical activity levels, poor hand grip strength and slow walking speed. Participants were identified as not frail (no phenotypes), pre-frail (one or two phenotypes) or frail (three or more phenotypes). Factor analysis was applied to binary forms of 25 published frailty measures Differences were tested in mean factor scores between the three Fried frailty phenotypes and ROC curves estimated predictive capacity of factors.
Of 656 participants (67% female; mean age 59.9 years, SD 10.6) 59.2% were classified as not frail, 39.0% pre-frail and 1.8% frail. There were no gender or age differences. Seven frailty factors were identified, incorporating all 25 frailty measures. Factors 1 and 7 significantly predicted progression from not-frail to pre-frail (Factor 1 AUC 0.64 (95%CI 0.60-0.68, combined dynamic trunk stability and lower limb functional strength, balance, foot sensation, hearing, lean muscle mass and low BMI; Factor 7 AUC 0.55 (95%CI 0.52-0.59) comprising continence and nutrition. Factors 3 and 4 significantly predicted progression from pre-frail to frail (Factor 3 AUC 0.65 (95% CI 0.59-0.70)), combining living alone, sleep quality, depression and anxiety, and lung function; Factor 4 AUC 0.60 (95%CI 0.54-0.66) comprising perceived exertion on exercise, and falls history.
This research identified pre-frailty and frailty states in people aged in their 40s and 50s. Pre-frailty in body systems performance can be detected by a range of mutable measures, and interventions to prevent progression to frailty could be commenced from the fourth decade of life.
对于脆弱前期特征或导致脆弱的变化何时变得可检测并可改变，人们知之甚少。本研究旨在探讨 40-75 岁独立社区居住的成年人中的脆弱前期和脆弱。
参与者通过地方议会网络、一家全国性银行和澳大利亚阿德莱德的一所大学招募。通过非故意体重减轻、疲惫、体力活动水平低、握力差和步行速度慢等指标计算 Fried 衰弱表型评分。参与者被确定为不虚弱（无表型）、衰弱前期（一种或两种表型）或衰弱（三种或更多表型）。应用因子分析对 25 项已发表的衰弱测量的二分形式进行分析。在三个 Fried 衰弱表型之间测试均值因子评分的差异，并估计因素的 ROC 曲线预测能力。
在 656 名参与者中（67%为女性；平均年龄 59.9 岁，标准差 10.6），59.2%被归类为不虚弱，39.0%为衰弱前期，1.8%为衰弱。无性别或年龄差异。确定了 7 个衰弱因子，包含所有 25 项衰弱测量。因子 1 和 7 显著预测从不虚弱到衰弱前期的进展（因子 1 AUC 0.64[95%CI 0.60-0.68]，包含动态躯干稳定性和下肢功能力量、平衡、足部感觉、听力、瘦肌肉质量和低 BMI；因子 7 AUC 0.55[95%CI 0.52-0.59]包含尿失禁和营养）。因子 3 和 4 显著预测从不虚弱到衰弱前期的进展（因子 3 AUC 0.65[95%CI 0.59-0.70]），包含独居、睡眠质量、抑郁和焦虑以及肺功能；因子 4 AUC 0.60[95%CI 0.54-0.66]包含运动时的感知用力和跌倒史。
本研究确定了 40 多岁和 50 多岁人群中的脆弱前期和脆弱状态。身体系统功能的脆弱前期可以通过一系列可改变的测量来检测，并且可以从 40 多岁开始进行预防进展为脆弱的干预措施。
