Evidence map›Paper›PMID 34674657›Full record

ArticleBMC geriatrics2021

Patterns of physical activity and their relationship with depression among community-dwelling older adults in Shanghai, China: a latent class approach.

Yan Liang, Xinghui Li, Tingting Yang, Mengying Li, Ye Ruan, Yinghua Yang, Yanyan Huang, Yihua Jiang, Ying Wang

Open access · goldAbstract read
In one paragraph

Article in BMC geriatrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
1.3field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 2 syntheses or guidelines pooled it, 20 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Is Physical Activity Related to Depression and Anxiety among Adults? Observations from a Noncommunicable Disease Screening Clinic in North India.Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 4 institutions in 1 country.

Yan Liang *School of Nursing, Fudan University, Shanghai, 200032, China.
Xinghui Li *Fudan University School of Public Health, Shanghai, 200032, China.
Tingting YangFudan University School of Public Health, Shanghai, 200032, China.
Mengying LiFudan University School of Public Health, Shanghai, 200032, China.
Ye RuanShanghai Center for Disease Control and Prevention, Shanghai, 200336, China.
Yinghua YangShanghai Center for Clinical Laboratory, Shanghai, 200126, China.
Yanyan HuangDepartment of Geriatrics, Huashan Hospital Fudan University, Shanghai, 200040, China.
Yihua JiangShanghai Medicine-Mental Health Center of Minhang District, 130 DongAn Road, Shanghai, 200032, China. mhjswszx@126.com.
Ying WangFudan University School of Public Health, Shanghai, 200032, China. wangying1013@fudan.edu.cn.
Fudan University · CNShanghai Clinical Research Center · CNShanghai Mental Health Center · CNShanghai Municipal Center For Disease Control Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

DepressionIndependent LivingAgedChinaCross-Sectional StudiesExerciseHumansDepressionLatent class analysis, LCAOlder adultsPatternsPhysical activity

Identifiers

PMID34674657
PMCPMC8532283
OpenAlexW3116143087

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.