Evidence map›Paper›PMID 38395814›Full record

ArticleBMC public health2024

1 km of living area: age differences in the association between neighborhood environment perception and self-rated health among Chinese people.

Yuexuan Mu, Shu Ge, Benfeng Du

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.1field-weighted citation impact, top 14% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

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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

3 authors at 3 institutions in 2 countries.

Yuexuan MuSchool of Public health, Soochow University, Jiangsu, China.
Shu GeSchool of Sociology and Population Studies, Renmin University of China, Beijing, China.
Benfeng DuSchool of Sociology and Population Studies, Renmin University of China, Beijing, China. dubenfeng@ruc.edu.cn.
Mohammed Bin Rashid School of Government · AERenmin University of China · CNSoochow University · CN

Funding

National Natural Science Foundation of China 71974194National Social Science Foundation Key Projects 21AZD073
6 · The paper itself

Abstract

objectivesThis study aimed to explore the age differences in the relationship between neighborhood environment perception and self-rated health among Chinese people. STUDY

designThis is cross-sectional study.

methodsThe participants were 2,631 residents aged 18 and above from 2021 Chinese General Social Survey (CGSS). Self-rated health was reported by residents. Neighborhood environment was measured by respondents' subjective perception of 1 km living area. Ordered logit regression models were used to examine the relationship between neighborhood environment perception and self-rated health.

resultsIn summary, 42.08% were classified as young adults, and 57.92% were classified as middle-aged and older adults. Young adults with higher perception of neighborhood social environment were more likely to perceive good health. Neighborhood built environment was significantly associated with self-rated health among middle-aged and older adults.

conclusionThe neighborhood environment is an important predictor of the health of its residents. Neighborhood environmental modifications should be tailored to meet the needs of different age groups, promoting health equity.

Indexed as

East Asian PeopleHealth StatusResidence CharacteristicsAdultAgedCross-Sectional StudiesHumansMiddle AgedNeighborhood CharacteristicsPerceptionYoung AdultAge differenceBuilt environmentNeighborhood environment perceptionSelf-rated healthSocial environment

Identifiers

PMID38395814
PMCPMC10885538
OpenAlexW4392121152

What OpenQuestion holds

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LicenceCC BY
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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.