Abstract

BackgroundFew studies have explored patterns of physical activity (PA) and examined their relationship with depression among community-dwelling older adults. We aimed to identify the patterns of PA through a person-centered analytical approach and examine the association between quantity and patterns of PA, and depression among community-dwelling older adults.MethodsWe conducted a cross-sectional survey study in the Minhang district, Shanghai, China, in August 2019, and used a self-administered questionnaire to collect data through home visits. The total sample included 2525 older adults. This study used the Physical Activity Scale for the Elderly (PASE) to assess the quantity of PA in older adults. Depression was evaluated with the Geriatric Depression Scale (GDS). Latent class analysis (LCA) was used to identify subpopulations by shared item response patterns. Logistic regressions were performed to estimate the relationship between PASE score, patterns of PA, and depression. An exploratory analysis of joint levels and patterns of PA effects on depression was based on sample subgroups with combinations of levels and patterns of PA. Logistic regression was used to calculate the odds ratio for combined subgroups.ResultsFour latent classes were identified: “domestic types,” “athletic types,” “gardening/caring types,” and “walkers.” PASE scores and patterns of PA both were associated with depression. Older adults who were the most active (PASE quartile: 75–100%) and the athletic types had the strongest significant association with depression (OR = 0.19, 95% CI: 0.06–0.65), followed by those who were the most active (PASE quartile: 75–100%) and the walkers (OR = 0.28, 95% CI: 0.14–0.57) when compared with older adults with the least activity (PASE quartile: 0–25%) and domestic types.ConclusionThis study suggests both the quantity and patterns of physical activity are associated with depressive symptoms among community-dwelling older adults. Population-level intervention should encourage community-dwelling older adults to increase their quantity of PA to reduce the risk of depression. Athletics and walkers are recommended. To develop individual-level tailored interventions, more attention should be paid to older adults who are highly engaged in gardening/caring for others.

Highlights

  • Few studies have explored patterns of physical activity (PA) and examined their relationship with depression among community-dwelling older adults

  • To develop individual-level tailored interventions, more attention should be paid to older adults who are highly engaged in gardening/caring for others

  • Older adults who were the most active (PASE quartile: 75–100%) and the athletic types had the strongest significant association with depression (OR = 0.19, 95% CI: 0.06–0.65), followed by those who were the most active (PASE quartile: 75–100%) and the walkers (OR = 0.28, 95% CI: 0.14–0.57) when compared with older adults with the least activity (PASE quartile: 0–25%) and domestic types

Read more

Summary

Introduction

Few studies have explored patterns of physical activity (PA) and examined their relationship with depression among community-dwelling older adults. We aimed to identify the patterns of PA through a person-centered analytical approach and examine the association between quantity and patterns of PA, and depression among community-dwelling older adults. Previous studies have focused on the quantity or levels of PA and their relationship with depression in older people [16, 17]. Some studies showed that PA with higher frequency or moderateto-vigorous PA were associated with lower odds of depression [18, 19]; some suggested that light physical activity or lower frequency were protective [20, 21]. Research showed that high levels of PA across multiple domains, or athletic pattern were at lower risk for depression [22]. Knowledge about the joint effects of patterns of PA and levels of PA on depression risk would be helpful

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call