Evidence map›Paper›PMID 36114535›Full record

ArticleBMC public health2022

COVID-Inconfidentes: how did COVID-19 and work from home influence the prevalence of leisure-time physical inactivity? An analysis of before and during the pandemic.

Samara Silva Moura, Luiz Antônio Alves Menezes-Júnior, Ana Maria Sampaio Rocha, Luciano Garcia Lourenção, Júlia Cristina Cardoso Carraro, George Luiz Lins Machado-Coelho, Adriana Lúcia Meireles

Abstract read
In one paragraph

Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

7 authors.

Samara Silva MouraNutrition School, Post-Graduate Program in Health and Nutrition, Federal University of Ouro, Preto, Diogo de Vasconcelos 122, Ouro Preto, Minas Gerais, Brazil. samara.moura@aluno.ufop.edu.br.
Luiz Antônio Alves Menezes-JúniorNutrition School, Post-Graduate Program in Health and Nutrition, Federal University of Ouro, Preto, Diogo de Vasconcelos 122, Ouro Preto, Minas Gerais, Brazil.
Ana Maria Sampaio RochaEpidemiology Laboratory, Medical School, Federal University of Ouro Preto, Ouro Preto, Minas Gerais, Brazil.
Luciano Garcia LourençãoEpidemiology Laboratory, Medical School, Federal University of Ouro Preto, Ouro Preto, Minas Gerais, Brazil.
Júlia Cristina Cardoso CarraroNutrition School, Post-Graduate Program in Health and Nutrition, Federal University of Ouro, Preto, Diogo de Vasconcelos 122, Ouro Preto, Minas Gerais, Brazil.
George Luiz Lins Machado-CoelhoNutrition School, Post-Graduate Program in Health and Nutrition, Federal University of Ouro, Preto, Diogo de Vasconcelos 122, Ouro Preto, Minas Gerais, Brazil.
Adriana Lúcia MeirelesNutrition School, Post-Graduate Program in Health and Nutrition, Federal University of Ouro, Preto, Diogo de Vasconcelos 122, Ouro Preto, Minas Gerais, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has brought drastic changes to the lives of the global population. The restrictions imposed by government agencies impacted the daily lives of citizens, influencing several health behaviors, such as physical activity (PA). Thus, the present study aimed to assess the prevalence of physical inactivity (PI) and its associated factors before and during the COVID-19 pandemic.

methodsA population-based household seroepidemiological survey was conducted in two Brazilian municipalities located in the state of Minas Gerais, in which 1750 volunteers were interviewed between October and December 2020. Face-to-face interviews were conducted using a structured questionnaire in an electronic format. The moments considered for the PI analysis were M0 (before the pandemic), M1 (from March to July 2020), and M2 (from October to December 2020). Descriptive statistics and univariate and multivariate logistic regression were used to examine the factors associated with PI before (M0) and during the pandemic (M1 and M2).

resultsThe prevalence of PI was higher in the first months of the pandemic (M1) (67.3%; 95% confidence interval (CI): 62.4-71.9) than in the months from October to December 2020 (M2) (58.7%; 95% CI: 52.8-64.3); however, at both times (M1 and M2), PI was more prevalent than in the period before the pandemic started (M0) (39.7%; 95% CI: 35.6-43.8). Individuals who were overweight, obese, and had low educational levels were more likely to be physically inactive. At both M1 and M2, individuals who worked at a work from home were less likely to have PI.

conclusionsThe results suggest that the COVID-19 pandemic negatively influenced PA, substantially increasing the prevalence of PI. The determinants associated with PI were education, body mass index, and work from home.

Indexed as

COVID-19PandemicsHumansLeisure ActivitiesPrevalenceSedentary BehaviorSocioeconomic FactorsTeleworkingCOVID-19Health researchPhysical inactivitySocial isolation

Identifiers

PMID36114535
PMCPMC9482310

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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.