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


Journal

BMC public health
ISSN: 1471-2458
Titre abrégé: BMC Public Health
Pays: England
ID NLM: 100968562

Informations de publication

Date de publication:
04 Mar 2019
Historique:
received: 12 11 2018
accepted: 22 02 2019
entrez: 6 3 2019
pubmed: 6 3 2019
medline: 27 4 2019
Statut: epublish

Résumé

Various 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. '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. 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.

Sections du résumé

BACKGROUND BACKGROUND
Various 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 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 CONCLUSIONS
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.

Identifiants

pubmed: 30832631
doi: 10.1186/s12889-019-6581-z
pii: 10.1186/s12889-019-6581-z
pmc: PMC6398236
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

257

Subventions

Organisme : The Danish Working Environment Research Fund
ID : 01-2015-09

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Auteurs

Sofie Dencker-Larsen (S)

National Research Centre for the Working Environment, Lersø Parkallé 105, Copenhagen, Denmark. sdl@nrcwe.dk.

Charlotte Lund Rasmussen (CL)

National Research Centre for the Working Environment, Lersø Parkallé 105, Copenhagen, Denmark.
Section of Social Medicine, University of Copenhagen, Øster Farimagsgade 5, 1014, Copenhagen, Denmark.

Sannie Vester Thorsen (SV)

National Research Centre for the Working Environment, Lersø Parkallé 105, Copenhagen, Denmark.

Els Clays (E)

Department of Public Health and Primary Care, Ghent University, 4K3 (ingang 42), Corneel Heymanslaan 10, B-9000, Ghent, Belgium.

Thomas Lund (T)

Center for Social Medicine, Frederiksberg and Bispebjerg Hospital, Nordre Fasanvej 57, 2000, Frederiksberg, Denmark.

Merete Labriola (M)

Department of Public Health, Aarhus University, Bartholins Allé 2, 8000, Aarhus, Denmark.

Ole Steen Mortensen (OS)

Section of Social Medicine, University of Copenhagen, Øster Farimagsgade 5, 1014, Copenhagen, Denmark.
Department of Occupational and Social Medicine, Holbæk Hospital, Smedelundsgade 60, 4300, Holbæk, Denmark.

Marie Birk Jørgensen (MB)

Department of Forensic Science, University of Copenhagen, 2100, Copenhagen, Denmark.

Nidhi Gupta (N)

National Research Centre for the Working Environment, Lersø Parkallé 105, Copenhagen, Denmark.

Charlotte Diana Nørregaard Rasmussen (CDN)

National Research Centre for the Working Environment, Lersø Parkallé 105, Copenhagen, Denmark.

Andreas Holtermann (A)

National Research Centre for the Working Environment, Lersø Parkallé 105, Copenhagen, Denmark.
Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Campusvej 55, 5230, Odense, Denmark.

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Classifications MeSH