Evidence map›Paper›PMID 38235011›Full record

ArticleHealth promotion perspectives2023

Relationships between physical activity and other health-related measures using state-based prevalence estimates.

Peter D Hart, Nestor Asiamah, Getu Teferi, Ivan Uher

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Article in Health promotion perspectives, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Peter D HartGlenville State University, Glenville, WV 26351, USA.ORCID https://orcid.org/0000-0002-4947-9310
Nestor AsiamahSchool of Health and Social Care, University of Essex, Colchester, UK.
Getu TeferiDepartment of Sports Science, Debremarkos University, Debremarkos, Ethiopia.
Ivan UherInstitute of Physical Education and Sport, Pavol Jozef Šafárik University, 040 01 Košice, Slovakia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Both physical activity and muscle-strengthening activity have known relationships with other health-related variables such as alcohol and tobacco use, diet, and health-related quality of life (HRQOL). The purpose of this study was to explore and quantify the associations between physical activity measures and health-related variables at the higher state level. Methods: This cross-sectional study used data from the 2017 and 2019 Behavioral Risk Factor Surveillance System surveys. State-based prevalence (%) estimates were computed for meeting physical activity guidelines (PA), meeting muscle-strengthening activity guidelines (MS), both PA and MS (MB), drinking alcohol (D1), heavy alcohol drinking (HD), fruit consumption (F1), vegetable consumption (V1), good self-rated health (GH), overweight (OW), obesity (OB), current smoking (SN), and smokeless tobacco use (SL). Descriptive statistics, correlation coefficients, and data visualization methods were employed. Results: Strongest associations were seen between PA and F1 (2017: Conclusion: This study used high-level data to support the many known relationships between PA measures and health-related variables.

Indexed as

Behavioral risk factor surveillance systemHealth behaviorMuscle stretching exercisesObesityPhysical activity

Identifiers

PMID38235011
PMCPMC10790124

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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.