Technically measured compositional physical work demands and prospective register-based sickness absence (PODESA): a study protocol.
Accelerometers
Compositional data analysis (CoDA)
Physical activity at work
Sick-leave
Time-use epidemiology
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
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
257Subventions
Organisme : The Danish Working Environment Research Fund
ID : 01-2015-09
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