A latent profile analysis of rest–activity behavior patterns among community-dwelling older adults and its relationship with intrinsic capacity

Abstract

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.

Keywords

• Rest–activity behavior
• Intrinsic capacity
• Older adults
• Latent profile analysis