Calibration of Self-Reported Time Spent Sitting, Standing and Walking among Office Workers: A Compositional Data Analysis

David M. Hallman, Svend Erik Mathiassen, Allard J. van der Beek, Jennie A. Jackson and Pieter Coenen
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David M. Hallman: Centre for Musculoskeletal Research, Department of Occupational Health Sciences and Psychology, University of Gävle, 80637 Gävle, Sweden
Svend Erik Mathiassen: Centre for Musculoskeletal Research, Department of Occupational Health Sciences and Psychology, University of Gävle, 80637 Gävle, Sweden
Allard J. van der Beek: Department of Public and Occupational Health, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute, 1081 BT Amsterdam, The Netherlands
Jennie A. Jackson: Centre for Musculoskeletal Research, Department of Occupational Health Sciences and Psychology, University of Gävle, 80637 Gävle, Sweden
Pieter Coenen: Department of Public and Occupational Health, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute, 1081 BT Amsterdam, The Netherlands

IJERPH, 2019, vol. 16, issue 17, 1-15

Abstract: We developed and evaluated calibration models predicting objectively measured sitting, standing and walking time from self-reported data using a compositional data analysis (CoDA) approach. A total of 98 office workers (48 women) at the Swedish Transport Administration participated. At baseline and three-months follow-up, time spent sitting, standing and walking at work was assessed for five working days using a thigh-worn accelerometer (Actigraph), as well as by self-report (IPAQ). Individual compositions of time spent in the three behaviors were expressed by isometric log-ratios (ILR). Calibration models predicting objectively measured ILRs from self-reported ILRs were constructed using baseline data, and then validated using follow-up data. Un-calibrated self-reports were inaccurate; root-mean-square (RMS) errors of ILRs for sitting, standing and walking were 1.21, 1.24 and 1.03, respectively. Calibration reduced these errors to 36% (sitting), 40% (standing), and 24% (walking) of those prior to calibration. Calibration models remained effective for follow-up data, reducing RMS errors to 33% (sitting), 51% (standing), and 31% (walking). Thus, compositional calibration models were effective in reducing errors in self-reported physical behaviors during office work. Calibration of self-reports may present a cost-effective method for obtaining physical behavior data with satisfying accuracy in large-scale cohort and intervention studies.

Keywords: physical activity; sedentary behavior; office work; accuracy; calibration; compositional data analysis (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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