Evidence map›Paper›PMID 28982371›Full record

ArticleBMC public health2017

Physical activity, obesity and mortality: does pattern of physical activity have stronger epidemiological associations?

Adrian E Bauman, Anne C Grunseit, Vegar Rangul, Berit L Heitmann

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC public health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 3 pooled it
2.6field-weighted citation impact, top 10% 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

21 citing papers in PubMed, 3 syntheses or guidelines pooled it, 47 citations in OpenAlex.

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  11. Anthropometric Assessment of General and Central Obesity in Urban Moroccan Women.International journal of environmental research and public health · 2022
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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

4 authors at 2 institutions in 3 countries.

Adrian E BaumanPrevention Research Collaboration, School of Public Health, University of Sydney, Level 6, Charles Perkins Centre, Johns Hopkins Drive, Sydney, NSW, 2006, Australia.
Anne C GrunseitPrevention Research Collaboration, School of Public Health, University of Sydney, Level 6, Charles Perkins Centre, Johns Hopkins Drive, Sydney, NSW, 2006, Australia. anne.grunseit@sydney.edu.au.ORCID 0000-0003-1250-3265
Vegar RangulHUNT Research Centre, Faculty of Medicine, Department of Public health and General practice, NTNU - Norwegian University of Science and Technology, Levanger, Norway.
Berit L HeitmannThe Boden Institute of Obesity, Nutrition, Exercise & Eating Disorders, University of Sydney, Sydney, NSW, 2006, Australia.
The University of Sydney · AUNorwegian University of Science and Technology · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMost studies of physical activity (PA) epidemiology use behaviour measured at a single time-point. We examined whether 'PA patterns' (consistently low, consistently high or inconsistent PA levels over time) showed different epidemiological relationships for anthropometric and mortality outcomes, compared to single time-point measure of PA.

methodsData were the Danish MONICA (MONItoring Trends and Determinants in CArdiovascular Disease) study over three waves 1982-3 (time 1), 1987-8 (time 2) and 1993-4 (time 3). Associations between leisure time single time-point PA levels at time 1 and time 3, and sport and active travel at times 1 and 2 with BMI, waist, hip circumference and mortality (death from coronary heart disease (CHD) and cardiovascular disease (CVD)) were compared to 'PA patterns' spanning multiple time points. PA pattern classified participants' PA as either 1) inactive or low PA at both time points; 2) moderate level PA at time 1 and high activity at time 3; or 3) a 'mixed PA pattern' indicating a varying levels of activity over time. Similarly, sport and active travel were also classified as indicating stable low, stable high and mixed patterns.

resultsThe moderately and highly active groups for PA at times 1 and 3 had up to 1.7 cm lower increase in waist circumference compared with the inactive/low active group. Across 'PA patterns', 'active maintainers' had a 2.0 cm lower waist circumference than 'inactive/low maintainers'. Waist circumference was inversely related to sport but not active travel. CHD risk did not vary by activity levels at time 1, but was reduced significantly by 43% for high PA at time 3 (vs 'inactive' group) and among 'active maintainers' (vs 'inactive/low maintainers') by 62%. 'Sport pattern' showed stronger reductions in mortality for cardiovascular disease and CHD deaths among sport maintainers, than the single time point measures.

conclusionsPA patterns demonstrated a stronger association with a number of anthropometric and mortality outcomes than the single time-point measures. Operationalising PA as a sustained behavioural pattern may address some of the known under-estimation of risk for poor health in PA self-report measurements and better reflect exposure for epidemiological analysis of risk of health outcomes.

Indexed as

AdultAnthropometryCardiovascular DiseasesCoronary DiseaseDenmarkExerciseFemaleHumansMaleMiddle AgedObesityRisk AssessmentCardiovascular diseaseHip circumferenceWaist circumference

Identifiers

PMID28982371
PMCPMC5629749
OpenAlexW2762611236

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.