PDF(Pubmed)
Abstract：
Rest-activity behavior clusters within individuals to form patterns are of significant importance to their intrinsic capacity (IC), yet they have rarely been studied. A total of 1253 community-dwelling older adults were recruited between July and December 2021 based on the baseline survey database of the Fujian Prospective Cohort Study on Aging. Latent profile analysis was used to identify profiles of participants based on rest-activity behaviors, whereas logistic regression analysis was carried out to investigate the relationship between profiles and IC. We identified three latent profiles including: (1) Profile 1-labeled \"Gorillas\": High physical activity (PA), moderate sedentary behaviors (SB), screen time (ST) and sleep (n = 154, 12%), (2) Profile 2-labeled as \"Zebras\": Moderate PA, low SB, ST and high sleep (n = 779, 62%), and (3) Profile 3-labeled as\"Koalas\": High SB, ST, low PA and sleep (n = 320, 26%). Logistic regression revealed a negative correlation between low IC and the \"Gorillas\" profile (β = - 0.945, P < 0.001) as well as the \"Zebras\" profile (β = - 0.693, P < 0.001) among community-dwelling older adults, with the \"Koalas\" profile showing the weakest IC compared to the other profiles. The demographic traits i.e., female, older age, living alone, and low educational level also correlated with low IC. Identifying trends of rest-activity behaviors may help in drawing focus on older adults at risk of decreasing IC, and develop personalized improvement plans for IC.
摘要：
个体内的休息活动行为集群形成模式对他们的内在能力(IC)具有重要意义，然而，他们很少被研究。根据福建省老龄化前瞻性队列研究的基线调查数据库，在2021年7月至12月间共招募了1253名社区居住的老年人。潜在轮廓分析用于根据休息-活动行为识别参与者的轮廓，而进行逻辑回归分析以调查配置文件和IC之间的关系。我们确定了三个潜在的概况，包括：（1）概况1标记为“大猩猩”：高体力活动（PA），中度久坐行为（SB），屏幕时间(ST)和睡眠(n=154，12%)，（2）配置文件2-标记为“斑马”：中度PA，低SB,ST和高睡眠（n=779，62%），和(3)配置文件3-标记为“考拉”：高SB，ST,低PA和睡眠（n=320，26％）。Logistic回归显示低IC与“大猩猩”轮廓（β=-0.945，P<0.001）和“斑马”轮廓（β=-0.693，P<0.001）之间呈负相关。居住的老年人，与其他配置文件相比，“考拉”配置文件显示出最弱的IC。人口特征，即，女性,年龄较大,独自生活,低教育水平也与低IC相关。确定休息-活动行为的趋势可能有助于将注意力集中在有IC降低风险的老年人身上。并制定IC的个性化改进计划。
