Evidence map›Paper›PMID 33148214›Full record

ArticleBMC public health2020

Lifestyle-associated health risk indicators across a wide range of occupational groups: a cross-sectional analysis in 72,855 workers.

Daniel Väisänen, Lena V Kallings, Gunnar Andersson, Peter Wallin, Erik Hemmingsson, Elin Ekblom-Bak

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
8.1field-weighted citation impact, top 2% 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

36 citing papers in PubMed, 54 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

6 authors at 1 institution in 1 country.

Daniel VäisänenDepartment of Physical Activity and Health, The Swedish School of Sport and Health Sciences, Stockholm, Sweden. daniel.vaisanen@gih.se.ORCID http://orcid.org/0000-0002-0958-0094
Lena V KallingsDepartment of Physical Activity and Health, The Swedish School of Sport and Health Sciences, Stockholm, Sweden.
Gunnar AnderssonHPI Health Profile Institute, Stockholm, Sweden.
Peter WallinHPI Health Profile Institute, Stockholm, Sweden.
Erik HemmingssonDepartment of Physical Activity and Health, The Swedish School of Sport and Health Sciences, Stockholm, Sweden.
Elin Ekblom-BakDepartment of Physical Activity and Health, The Swedish School of Sport and Health Sciences, Stockholm, Sweden.
Swedish School of Sport and Health Sciences · SE

Funding

Forskningsrådet om Hälsa, Arbetsliv och Välfärd 2018-00384Hjärt-Lungfonden 20180636
6 · The paper itself

Abstract

backgroundIdentify and compare health risk indicators for common chronic diseases between different occupational groups.

methodsA total of 72,855 participants (41% women) participating in an occupational health service screening in 2014-2019 were included. Occupation was defined by the Swedish Standard Classification of Occupation, and divided into nine major and additionally eight sub-major groups. These were analysed separately, as white- and blue-collar occupations and as low- and high-skilled occupations. Seven health risk indicators were self-reported: exercise, physical work situation, sitting at work and leisure, smoking, diet, and perceived health, whereas cardiorespiratory fitness, BMI and blood pressure were measured. These were further dichotomized (yes/no) and as clustering of risk indicators (≥3 vs. <3).

resultsThe greatest variation in OR across sub-major and major occupational groups were seen for daily smoking (OR = 0.68 to OR = 5.12), physically demanding work (OR = 0.55 to OR = 45.74) and high sitting at work (OR = 0.04 to OR = 1.86). For clustering of health risk indicators, blue-collar workers had significantly higher clustering of health risks (OR: 1.80; 95% CI 1.71-1.90) compared to white-collar workers (reference). Compared to high-skilled white-collar workers, low-skilled white-collar workers had similar OR (2.00; 1.88-2.13) as high-skilled blue-collar workers (1.98; 1.86-2.12), with low-skilled blue-collar workers having the highest clustered risk (2.32; 2.17-2.48).

conclusionThere were large differences in health risk indicators across occupational groups, mainly between high-skilled white-collar occupations and the other occupations, with important variations also between major and sub-major occupational groups. Future health interventions should target the occupational groups identified with the highest risk for effective disease prevention.

Indexed as

Chronic DiseaseLife StyleOccupationsAdultBlood PressureBody Mass IndexCardiorespiratory FitnessCross-Sectional StudiesDietExerciseFemaleHumansLeisure ActivitiesMaleMiddle AgedOdds RatioBlue-collarCardiorespiratory fitnessLifestyleLow- and high-skilled occupationsOccupational groupsOccupationsPhysical activity patternRisk indicatorsWhite-collar

Identifiers

PMID33148214
PMCPMC7641800
OpenAlexW3096170166

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.