Evidence map›Paper›PMID 39145159›Full record

ArticleFrontiers in public health2024

Exploring the group heterogeneity in the impact of social cohesion on the walking frequency of older adults in China.

Jingwen Ma, Wu 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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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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

2 authors.

Jingwen MaSchool of Public Administration, Dalian University of Technology, Dalian, China.
Wu LiFaculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Walkable neighborhoods are closely related to an increase in walking frequency and the strengthening of social cohesion. These factors, in turn, contribute to lower BMI and other positive health-related outcomes. However, with a rapid increase in aging populations in China and the fact that women are facing more challenges than men as they age, especially mobility challenges because they tend to live longer leading to probabilities to become widowed. Nevertheless, less attention has been paid to understanding the gender difference between these relationships. Methods: Based on a survey of 533 older adults in Dalian, China, this study tried to investigate the intertwined relationship between perceived walkability, social cohesion, walking frequency, and BMI. A Structural Equation Model (SEM) and multiple-group analysis were applied to test the proposed framework. Results: First, results show that gender differences existed among the above interrelationships, and the most substantial gender gap was found in effects of social cohesion on BMI. Second, perceived walkability only has a direct effect (0.149) on walking frequencies for female seniors. Third, although the relationships between perceived walkability and BMI are not directly related in both male and female models, the indirect connection (-0.053) is substituted for female seniors. Besides, the inhibiting effect of walking on BMI, which is -0.511, is also valid for female seniors. Finally, in terms of the role of social cohesion, both the positive impacts of perceived walkability on it (0.225 for males and 0.325 for females) and its promoting effects on walking have been confirmed in male (0.142) and female models (0.103). The negative direct effect of social cohesion on BMI (-0.083) is only confirmed in male seniors. Conclusion: Insights derived from this analysis can help bring forward gender-specific interventions to build a more inclusive walkable and social environment to improve the mobility and physical health of older adults.

Indexed as

Body Mass IndexWalkingAgedAged, 80 and overChinaEnvironment DesignFemaleHumansMaleMiddle AgedResidence CharacteristicsSex FactorsSurveys and Questionnairesagingbody mass index (BMI)built environmentmultiple-group analysisperceived walkabilitystructural equation model (SEM)

Identifiers

PMID39145159
PMCPMC11322150

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LicenceCC BY
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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.