METHODS: Data were obtained from Japan\'s National Center for Geriatrics and Gerontology Study of Geriatric Syndromes (NCGG-SGS). Social activity was evaluated across 16 domains. Disability was determined using data extracted from Japan\'s long-term care insurance system.
RESULTS: Data from 4998 older adults were analyzed; among them, 422 (8.4 %) developed a disability within 35 months (Interquartile range: 32-39). The Cox proportional hazards model was used to assess 16 domains of social activity. The results yielded risk factors for disability incidence in six social activity domains: work, travel, hobbies, babysitting, family caregiving, and events. The coefficients for these activities were assigned weights of 3, 3, 2, 1, 1, and 1, respectively. The weighted social activity scoring model significantly improved the ability to predict disability incidence when the number of social activities in which individuals participated was considered (social activity score: area under the curve [AUC] 0.691, 95 % confidence interval [CI] 0.664-0.717; number of social activities: AUC 0.681, 95 % CI 0.654-0.707, P = 0.042).
CONCLUSIONS: The composite score derived from the weighted social activity scoring model serves as a valuable tool due to its enhanced predictability, which complements established background factors associated with the incidence of disability in older adults.
方法:数据来自日本国家老年病和老年病综合征研究中心(NCGG-SGS)。社会活动在16个领域进行了评估。残疾是使用从日本长期护理保险制度中提取的数据确定的。
结果:分析了4998名老年人的数据;其中,422(8.4%)在35个月内出现残疾(四分位数范围:32-39)。Cox比例风险模型用于评估社会活动的16个领域。结果得出了六个社会活动领域残疾发生率的风险因素:工作,旅行,爱好,保姆,家庭照顾,和事件。这些活动的系数分别被赋予3、3、2、1、1和1的权重。当考虑个人参与的社交活动次数时,加权社交活动评分模型显着提高了预测残疾发生率的能力(社交活动得分:曲线下面积[AUC]0.691,95%置信区间[CI]0.664-0.717;社交活动次数:AUC0.681,95%CI0.654-0.707,P=0.042)。
结论:从加权社会活动评分模型得出的综合评分由于其增强的可预测性而成为有价值的工具,这补充了与老年人残疾发生率相关的既定背景因素。