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.
Highlights
Excessive time spent sitting and standing have both received considerable attention as possible risk factors for musculoskeletal disorders [1,2], cardiovascular diseases [3,4,5] and early mortality [6].Incorporating moderate to vigorous physical activity, such as walking, in daily routines shows numerous health benefits [7,8] and may counteract some of the detrimental health effects of prolonged sitting [9].evidence has predominantly been obtained from studies of leisure-time behaviors
We have recently shown that calibration within a compositional data analysis (CoDA) framework can be effective in improving the accuracy of self-reported time in a single behavior among office workers [35]
Our findings suggest that calibration using a CoDA approach is a promising tool for improving accuracy in studies based on self-reported physical behaviors
Summary
Excessive time spent sitting and standing have both received considerable attention as possible risk factors for musculoskeletal disorders [1,2], cardiovascular diseases [3,4,5] and early mortality [6].Incorporating moderate to vigorous physical activity, such as walking, in daily routines shows numerous health benefits [7,8] and may counteract some of the detrimental health effects of prolonged sitting [9].evidence has predominantly been obtained from studies of leisure-time behaviors. Incorporating moderate to vigorous physical activity, such as walking, in daily routines shows numerous health benefits [7,8] and may counteract some of the detrimental health effects of prolonged sitting [9]. There is a growing interest in understanding how physical behaviors at work (including sitting, standing and walking) contribute to overall physical activity and health [10,11]; epidemiological studies investigating these associations remain inconclusive [10,12,13]. Studies devoted to physical behaviors and health have often relied on self-reported behavioral estimates. Self-reported estimates have been shown to disagree with objective measurements, for example, accelerometry [14,15,16,17,18].
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Environmental Research and Public Health
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
