Evidence map›Paper›PMID 33454564›Full record

ArticleHealth & place2021

Examine the associations between perceived neighborhood conditions, physical activity, and mental health during the COVID-19 pandemic.

Yong Yang, Xiaoling Xiang

Open access · greenAbstract read
In one paragraph

Article in Health & place, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
5.4field-weighted citation impact, top 4% 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

27 citing papers in PubMed, 1 synthesis or guideline pooled it, 59 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

2 authors at 2 institutions in 1 country.

Yong YangSchool of Public Health, University of Memphis, Memphis, TN, 38152, USA. Electronic address: yyang15@memphis.edu.
Xiaoling XiangSchool of Social Work, University of Michigan, Ann Arbor, MI, 48109, USA.
University of Memphis · USUniversity of Michigan–Ann Arbor · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study examined how neighborhood conditions changed and how neighborhood conditions were associated with physical activity and mental health during the COVID-19 pandemic among Americans. The major outcomes were stratified by the neighborhood's poverty and regression models were used to assess the associations between neighborhood conditions and their change during the pandemic and the outcomes of physical activity and mental health. The results show that low-poverty neighborhoods had more health-promoting neighborhood conditions before the outbreak and more positive changes during the outbreak. Health-promoting neighborhood conditions were associated with higher physical activity and moderate physical activity and lack of negative neighborhood conditions such as crime/violence and traffic were associated with a lower risk of mental health problems including loneliness, depression, and anxiety. Mental health problems were also significantly associated with the COVID-19 infection and death and household income level. Our findings suggest that it is plausible that the disparities of physical activity and mental health by neighborhood exacerbate due to the pandemic and people who living in socioeconomically disadvantaged neighborhoods bear increasingly disproportionate burden.

Indexed as

Health Status DisparitiesAdultCOVID-19ExerciseFemaleHumansMaleMental HealthMiddle AgedResidence CharacteristicsSurveys and QuestionnairesUnited StatesCOVID-19Mental healthNeighborhood conditionsPhysical activity

Identifiers

PMID33454564
PMCPMC9760872
OpenAlexW3118839486

What OpenQuestion holds

Textmetadata
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.