Evidence map›Paper›PMID 30832631›Full record

ArticleBMC public health2019

Technically measured compositional physical work demands and prospective register-based sickness absence (PODESA): a study protocol.

Sofie Dencker-Larsen, Charlotte Lund Rasmussen, Sannie Vester Thorsen, Els Clays, Thomas Lund, Merete Labriola, Ole Steen Mortensen, Marie Birk Jørgensen, Nidhi Gupta, Charlotte Diana Nørregaard Rasmussen and 1 more

Abstract read
In one paragraph

Article in BMC public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–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

10 citing papers in PubMed.

  1. Article
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  5. Article
  6. Article
  7. Work-Time Compositions of Physical Behaviors and Trajectories of Sick Leave Due to Musculoskeletal Pain.International journal of environmental research and public health · 2021
    Article
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  9. Article
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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

11 authors.

Sofie Dencker-LarsenNational Research Centre for the Working Environment, Lersø Parkallé 105, Copenhagen, Denmark. sdl@nrcwe.dk.ORCID http://orcid.org/0000-0001-9023-3403
Charlotte Lund RasmussenNational Research Centre for the Working Environment, Lersø Parkallé 105, Copenhagen, Denmark.
Sannie Vester ThorsenNational Research Centre for the Working Environment, Lersø Parkallé 105, Copenhagen, Denmark.
Els ClaysDepartment of Public Health and Primary Care, Ghent University, 4K3 (ingang 42), Corneel Heymanslaan 10, B-9000, Ghent, Belgium.
Thomas LundCenter for Social Medicine, Frederiksberg and Bispebjerg Hospital, Nordre Fasanvej 57, 2000, Frederiksberg, Denmark.
Merete LabriolaDepartment of Public Health, Aarhus University, Bartholins Allé 2, 8000, Aarhus, Denmark.
Ole Steen MortensenSection of Social Medicine, University of Copenhagen, Øster Farimagsgade 5, 1014, Copenhagen, Denmark.
Marie Birk JørgensenDepartment of Forensic Science, University of Copenhagen, 2100, Copenhagen, Denmark.
Nidhi GuptaNational Research Centre for the Working Environment, Lersø Parkallé 105, Copenhagen, Denmark.
Charlotte Diana Nørregaard RasmussenNational Research Centre for the Working Environment, Lersø Parkallé 105, Copenhagen, Denmark.
Andreas HoltermannNational Research Centre for the Working Environment, Lersø Parkallé 105, Copenhagen, Denmark.

Funding

The Danish Working Environment Research Fund 01-2015-09
6 · The paper itself

Abstract

backgroundVarious physical work demands are shown to be associated with sickness absence. However, these studies have: (a) predominantly used self-reported data on physical work demands that have been shown to be inaccurate compared with technical measurements, (b) principally focused on various physical work demands in 'isolation', i.e. ignoring their co-dependency - compositional nature -, and (c) mainly used register data on long-term sickness absence. The present article describes the protocol of a study with the objective of investigating the association between technically measured compositional data on physical work demands and prospective long- and short-term register-based data on sickness absence.

methods'The technically measured compositional Physical wOrk DEmands and prospective association with register-based Sickness Absence study (PODESA)' comprises data from two Danish cohorts (NOMAD and DPhacto) primarily on blue-collar workers. In the PODESA cohort, data on 1108 workers were collected at baseline (between 2011 and 2014). The cohort data comprise, e.g., self-reported information on descriptives, lifestyle, workday, and health, as well as accelerometer-based measurements of physical work demands (physical activity, movements, and postures). These baseline measurements are linked with prospective register-based data on sickness absence for up to four years after baseline. The prospective association between physical work demands and sickness absence will be analysed using a Compositional Data Analysis approach. DISCUSSION: PODESA provides a unique possibility of unravelling which combinations of physical work demands are associated with prospective sickness absence. PODESA employs technically measured information on physical work demands (taking into account the compositionality of physical work demand data) and prospective sickness absence data. The findings from PODESA can be used to develop strengthened preventive interventions for sickness absence. Results are expected in 2019-2021.

Indexed as

AbsenteeismOccupational HealthAdultDenmarkFemaleHumansMaleMiddle AgedOccupationsProspective StudiesSelf ReportSick LeaveWorkplaceAccelerometersCompositional data analysis (CoDA)Physical activity at workSick-leaveTime-use epidemiology

Identifiers

PMID30832631
PMCPMC6398236

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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.