Table_1_Association between cognitive frailty and falls among older community dwellers in China: A Chinese longitudinal healthy longevity survey-based study.XLSX

BackgroundThe combined effect of cognitive impairment (CoI) and frailty on falls is controversial. This study aimed to explore whether older adults with cognitive frailty (CF) were at a higher risk of falls than those with only CoI or frailty and to present a fall prediction model based on CF.MethodsA total of 4,067 adults aged ≥ 60 years were included from the Chinese Longitudinal Healthy Longevity Survey through face-to-face interviews. Cognitive function and frailty were assessed using the mini-mental state examination scale and frailty index, respectively. Logistic regression was used to determine fall-associated risk factors and develop a fall prediction model. A nomogram was then plotted. The model performance was evaluated using the area under the curve (AUC), concordance index (C-index), and calibration curve. All analyses were performed using SPSS and R statistical packages.ResultsThe prevalence of CF and falls were 1.4 and 19.4%, respectively. After adjusting for covariates, the odds ratio of CF, frailty only, and CoI only for falls were 2.27 (95% CI: 1.29–3.97), 1.41 (95% CI: 1.16–1.73), and 0.99 (95% CI: 0.43–2.29), respectively. CF, sex, age, hearing difficulty, depression, anxiety, disability in instrumental activities of daily living, and serious illness in the past 2 years were independently associated with falls. A prediction model based on these factors yielded an AUC of 0.646 and a C-index of 0.641.ConclusionCognitive frailty (CF) exerted a cumulative effect on falls than did CoI or frailty alone. Joint assessments of cognitive function and frailty status may be beneficial for fall risk screening in community. A prediction model using CF as a factor could be helpful for this process.

背景：认知障碍（CoI）与衰弱对跌倒的综合影响尚存争议。本研究旨在探讨认知衰弱（CF）的老年人是否比仅患有CoI或衰弱者有更高的跌倒风险，并提出基于CF的跌倒预测模型。方法：共纳入来自中国健康长寿纵向调查的4,067名≥60岁的成年人，通过面对面访谈评估认知功能和衰弱程度，分别使用简易精神状态检查量表和衰弱指数。通过逻辑回归确定与跌倒相关的风险因素并开发跌倒预测模型。随后绘制了诺谟图。使用曲线下面积（AUC）、一致性指数（C-index）和校准曲线评估模型性能。所有分析均使用SPSS和R统计软件包进行。结果：CF和跌倒的患病率分别为1.4%和19.4%。调整协变量后，CF、仅衰弱和仅CoI的跌倒的比值比（OR）分别为2.27（95% CI：1.29–3.97）、1.41（95% CI：1.16–1.73）和0.99（95% CI：0.43–2.29）。CF、性别、年龄、听力困难、抑郁、焦虑、日常生活活动能力障碍以及过去两年内的严重疾病与跌倒独立相关。基于这些因素的预测模型产生AUC为0.646和C-index为0.641。结论：认知衰弱（CF）对跌倒的影响大于单独的CoI或衰弱。对认知功能和衰弱状态的联合评估可能有助于社区的跌倒风险筛查。以CF为因素的预测模型可能有助于这一过程。