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

Autor: Ole Steen Mortensen, Els Clays, Sannie Vester Thorsen, Sofie Dencker-Larsen, Andreas Holtermann, Charlotte Diana Nørregaard Rasmussen, Marie Birk Jørgensen, Merete Labriola, Charlotte Lund Rasmussen, Nidhi Gupta, Thomas Lund
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Gerontology
Male
Denmark
Sick-leave
Social Sciences
FUTURE DISABILITY PENSION
Study Protocol
0302 clinical medicine
Workplace/statistics & numerical data
Absenteeism
Medicine and Health Sciences
Medicine
030212 general & internal medicine
Prospective Studies
Time-use epidemiology
Workplace
POPULATION
education.field_of_study
lcsh:Public aspects of medicine
SEDENTARY BEHAVIOR
ASSOCIATION
Middle Aged
Physical work
Sick leave
Cohort
SHORT-TERM
Female
Sick Leave
Adult
EXPOSURES
Sick Leave/statistics & numerical data
Population
030209 endocrinology & metabolism
Physical activity at work
Occupations/statistics & numerical data
03 medical and health sciences
LEAVE
Humans
Occupations
VALIDITY
education
Baseline (configuration management)
Occupational Health
Protocol (science)
Descriptive statistics
business.industry
Public Health
Environmental and Occupational Health
Compositional data analysis (CoDA)
PSYCHOSOCIAL RISK-FACTORS
lcsh:RA1-1270
MARKER
Self Report
Biostatistics
Accelerometers
business
Zdroj: BMC PUBLIC HEALTH
Dencker-Larsen, S, Rasmussen, C L, Thorsen, S V, Clays, E, Lund, T, Labriola, M, Mortensen, O S, Jørgensen, M B, Gupta, N, Rasmussen, C D N & Holtermann, A 2019, ' Technically measured compositional physical work demands and prospective register-based sickness absence (PODESA) : a study protocol ', BMC Public Health, vol. 19, 257 . https://doi.org/10.1186/s12889-019-6581-z
BMC Public Health
Dencker-Larsen, S, Rasmussen, C L, Thorsen, S V, Clays, E, Lund, T, Labriola, M, Mortensen, O S, Jørgensen, M B, Gupta, N, Rasmussen, C L & Holtermann, A 2019, ' Technically measured compositional physical work demands and prospective register-based sickness absence (PODESA) : a study protocol ', BMC Public Health, vol. 19, 257 . https://doi.org/10.1186/s12889-019-6581-z
BMC Public Health, Vol 19, Iss 1, Pp 1-8 (2019)
ISSN: 1471-2458
Popis: 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: '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.
Databáze: OpenAIRE
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