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Calibration of self-reported physical behaviours among office workers: A compositional data analysis
Vrije Universiteit Amsterdam, Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.
Vrije Universiteit Amsterdam, Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.
University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational Health Science and Psychology, Occupational Health Science. University of Gävle, Centre for Musculoskeletal Research.ORCID iD: 0000-0003-2939-0236
University of Gävle, Centre for Musculoskeletal Research. University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational Health Science and Psychology, Occupational Health Science.ORCID iD: 0000-0003-1443-6211
2019 (English)In: ICAMPAM 2019: Oral Abstracts, Maastricht: ICAMPAM , 2019, article id O.11.2Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

The aim of this study was to develop and evaluate calibration models to predict objectively measured time spent sitting, standing and walking during office work from self-reported time-use compositions using a compositional data analysis (CoDA) approach. Ninety-nine office workers (49 women) at the Swedish Transport Administration participated in an intervention study on relocation to activity-based offices. At baseline and at a 3-months follow-up, physical behaviours (sitting, standing and walking) at work were assessed for five days using a thigh-mounted accelerometer (Actigraph) and by self-report (IPAQ). The time-use composition of the three behaviours was expressed in terms of isometric log-ratios (ILR). Calibration models predicting accelerometry-based time-use from self-reported compositions were constructed using linear regression on baseline data, and then validated using follow-up data. The accelerometer data showed that, on average, workers spent 69.9% of their day sitting, 23.7% standing, and 6.4% walking. The corresponding percentages for self-reports were 71.7%, 21.6%, and 7.4%, respectively. Non-calibrated self-reports were biased: the RMS errors obtained from the ILRs expressing sitting, standing and walking were 0.73, 1.09 and 1.05, respectively. Calibration models reduced these errors by 45% (sitting), 56% (standing), and 76% (walking). Validation of the calibration models using follow-up data from the same workers showed calibration remained equally effective; RMS errors were reduced by 55% (sitting), 58% (standing), and 75% (walking). In conclusion, calibration models for compositional time-use data were effective in reducing bias in self-reported physical behaviours at work, and the models remained effective when used on new data from the same workers. Calibrated self-reports may represent a cost-effective method for obtaining physical behaviour data with a satisfying accuracy in large-scale cohort and intervention studies.

Place, publisher, year, edition, pages
Maastricht: ICAMPAM , 2019. article id O.11.2
National Category
Occupational Health and Environmental Health
Identifiers
URN: urn:nbn:se:hig:diva-30410OAI: oai:DiVA.org:hig-30410DiVA, id: diva2:1335355
Conference
ICAMPAM, June 26-28 2019, Maastricht, Netherlands
Available from: 2019-07-05 Created: 2019-07-05 Last updated: 2019-08-29Bibliographically approved

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Jackson, JennieMathiassen, Svend Erik

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