Calibration of self-reported physical behaviours among office workers: A compositional data analysis
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
Research subject
Health-Promoting Work
Identifiers
URN: urn:nbn:se:hig:diva-30410OAI: oai:DiVA.org:hig-30410DiVA, id: diva2:1335355
Conference
ICAMPAM, June 26-28 2019, Maastricht, Netherlands
2019-07-052019-07-052020-11-23Bibliographically approved