Evidence map›Paper›PMID 39473594›Full record

ArticleFrontiers in public health2024

The effect of community environment on the trajectory of depressive symptoms and cohort differences among middle-aged and older Chinese adults.

Xuyang Li

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

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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

2 citing papers in PubMed.

  1. Article
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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

1 author.

Xuyang LiSchool of Public Health, Wuhan University, Wuhan, Hubei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Urbanization has changed the living environment of middle-aged and older Chinese adults, but it also brings certain mental pressure to them. Few studies have explored the effect of community environment on the development trajectory and the cohort differences of depressive symptoms in Chinese individuals. Methods: Based on the longitudinal data of the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2020, using three-level hierarchical linear growth model, this study examined the effect of community environment on the trajectory of depressive symptoms and cohort differences among middle-aged and older Chinese adults in five cohorts from 1920 to 1929, 1930-1939, 1940-1949, 1950-1959, and 1960-1966. Results: The results of this study showed that middle-aged and older adult individuals who lived in neighborhoods with better community physical and social environments had a protective effect on depressive symptoms. There was a cohort difference in the development of depressive symptoms among middle-aged and older Chinese adults. The baseline depressive symptoms in the later birth cohorts were higher than those in the earliest cohort, and the development rate were also significantly higher. The role of community environment in the development rate of depressive symptoms among middle-aged and older adult individuals varied across the cohort. A better community social environment had a more significant moderating effect on the development rate of depressive symptoms in the early birth cohort (1930-1939), and a better physical environment had a more significant moderating effect on the development rate of depressive symptoms in the 1940-1949 cohort. Conclusion: Under the strategic background of healthy aging in China, the construction and improvement of community environment should become an important part of coping with the realistic challenges of the aging population, such as the expanding scale of depressed population among the middle-aged and older adult individual.

Indexed as

DepressionResidence CharacteristicsAgedChinaCohort StudiesEast Asian PeopleFemaleHumansLongitudinal StudiesMaleMiddle AgedSocial Environmentcohort differencescommunity environmentdepressive symptomsdevelopment trajectorymulti-level growth model

Identifiers

PMID39473594
PMCPMC11518782

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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.