Sitting, standing and moving during work and leisure among male and female office workers of different age: a compositional data analysis

Intervention studies aiming at changing movement behavior have usually not accounted for the compositional nature of time-use data. Compositional data analysis (CoDA) has been suggested as a useful strategy for analyzing such data. The aim of this study was to examine the effects of two multi-component interventions on 24-h movement behavior (using CoDA) and on cardiorespiratory fitness among office workers; one focusing on reducing sedentariness and the other on increasing physical activity. Office workers (n = 263) were cluster randomized into one of two 6-month intervention groups, or a control group. Time spent in sedentary behavior, light-intensity, moderate and vigorous physical activity, and time in bed were assessed using accelerometers and diaries, both for 24 h in total, and for work and leisure time separately. Cardiorespiratory fitness was estimated using a sub-maximal cycle ergometer test. Intervention effects were analyzed using linear mixed models. No intervention effects were found, either for 24-h behaviors in total, or for work and leisure time behaviors separately. Cardiorespiratory fitness did not change significantly. Despite a thorough analysis of 24-h behaviors using CoDA, no intervention effects were found, neither for behaviors in total, nor for work and leisure time behaviors separately. Cardiorespiratory fitness did not change significantly. Although the design of the multi-component interventions was based on theoretical frameworks, and included cognitive behavioral therapy counselling, which has been proven effective in other populations, issues related to implementation of and compliance with some intervention components may have led to the observed lack of intervention effect.

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

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16173111 ◽

2019 ◽

Vol 16 (17) ◽

pp. 3111 ◽

Cited By ~ 5

Author(s):

David M. Hallman ◽

Svend Erik Mathiassen ◽

Allard J. van der Beek ◽

Jennie A. Jackson ◽

Pieter Coenen

Keyword(s):

Data Analysis ◽

Compositional Data ◽

Self Report ◽

Office Workers ◽

Compositional Data Analysis ◽

Calibration Models ◽

Self Reports ◽

Objectively Measured ◽

Rms Errors

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.

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Physical Behaviours in Brazilian Office Workers Working from Home during the COVID-19 Pandemic, Compared to before the Pandemic: A Compositional Data Analysis

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18126278 ◽

2021 ◽

Vol 18 (12) ◽

pp. 6278

Author(s):

Luiz Augusto Brusaca ◽

Dechristian França Barbieri ◽

Svend Erik Mathiassen ◽

Andreas Holtermann ◽

Ana Beatriz Oliveira

Keyword(s):

Data Analysis ◽

Repeated Measures ◽

Compositional Data ◽

Office Workers ◽

Compositional Data Analysis ◽

Working At Home ◽

Work From Home ◽

Time In Bed ◽

Objectively Measured ◽

Log Ratio

Work from home has increased greatly during the COVID-19 pandemic, and concerns have been raised that this would change physical behaviours. In the present study, 11 Brazilian office workers (five women, six men; mean [SD] age 39.3 [9.6] years) wore two triaxial accelerometers fixed on the upper back and right thigh continuously for five days, including a weekend, before COVID-19 (September 2019), and again while working at home during COVID-19 (July 2020). We determined time used in five behaviours: sedentary, standing, light physical activity (LPA), moderate-to-vigorous activity (MVPA), and time-in-bed. Data on these behaviours were processed using Compositional Data Analysis, and behaviours observed pre-COVID19 and during-COVID19 were compared using repeated-measures MANOVA. On workdays during-COVID19, participants spent 667 min sedentary, 176 standing, 74 LPA, 51 MVPA and 472 time-in-bed; corresponding numbers pre-COVID were 689, 180, 81, 72 and 418 min. Tests confirmed that less time was spent in bed pre-COVID19 (log-ratio −0.12 [95% CI −0.19; −0.08]) and more time in MVPA (log-ratio 0.35, [95% CI 0.08; 0.70]). Behaviours during the weekend changed only marginally. While small, this study is the first to report objectively measured physical behaviours during workdays as well as weekends in the same subjects before and during the COVID-19 pandemic.

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Correction of bias in self-reported sitting time among office workers – a study based on compositional data analysis

Scandinavian Journal of Work Environment & Health ◽

10.5271/sjweh.3827 ◽

2019 ◽

Vol 46 (1) ◽

pp. 32-42 ◽

Cited By ~ 4

Author(s):

Pieter Coenen ◽

SvendErik Mathiassen ◽

Allard J van der Beek ◽

David M Hallman

Keyword(s):

Data Analysis ◽

Compositional Data ◽

Office Workers ◽

Sitting Time ◽

Compositional Data Analysis

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Author response for "The “Goldilocks Day” for children's skeletal health: compositional data analysis of 24‐hour activity behaviors"

10.1002/jbmr.4143/v2/response1 ◽

2020 ◽

Author(s):

Dorothea Dumuid ◽

Peter Simm ◽

Melissa Wake ◽

David Burgner ◽

Markus Juonala ◽

...

Keyword(s):

Data Analysis ◽

Compositional Data ◽

Author Response ◽

Compositional Data Analysis ◽

Skeletal Health

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Review for "The “Goldilocks Day” for children's skeletal health: compositional data analysis of 24‐hour activity behaviors"

10.1002/jbmr.4143/v1/review1 ◽

2020 ◽

Keyword(s):

Data Analysis ◽

Compositional Data ◽

Compositional Data Analysis ◽

Skeletal Health

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Insights on the characteristics and sources of gas from an underground coal mine using compositional data analysis

International Journal of Coal Geology ◽

10.1016/j.coal.2021.103767 ◽

2021 ◽

pp. 103767

Author(s):

C. Özgen Karacan ◽

Josep Antoni Martín-Fernández ◽

Leslie F. Ruppert ◽

Ricardo A. Olea

Keyword(s):

Data Analysis ◽

Coal Mine ◽

Compositional Data ◽

Compositional Data Analysis ◽

Underground Coal Mine

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The Gut Microbiota of Healthy Aged Chinese Is Similar to That of the Healthy Young

mSphere ◽

10.1128/msphere.00327-17 ◽

2017 ◽

Vol 2 (5) ◽

Cited By ~ 65

Author(s):

Gaorui Bian ◽

Gregory B. Gloor ◽

Aihua Gong ◽

Changsheng Jia ◽

Wei Zhang ◽

...

Keyword(s):

Data Analysis ◽

Gut Microbiota ◽

Large Scale ◽

Compositional Data ◽

Healthy Lifestyle ◽

Compositional Data Analysis ◽

Surprising Result ◽

Microbiota Composition ◽

Cross Sectional ◽

Age Cohorts

ABSTRACT We report the large-scale use of compositional data analysis to establish a baseline microbiota composition in an extremely healthy cohort of the Chinese population. This baseline will serve for comparison for future cohorts with chronic or acute disease. In addition to the expected difference in the microbiota of children and adults, we found that the microbiota of the elderly in this population was similar in almost all respects to that of healthy people in the same population who are scores of years younger. We speculate that this similarity is a consequence of an active healthy lifestyle and diet, although cause and effect cannot be ascribed in this (or any other) cross-sectional design. One surprising result was that the gut microbiota of persons in their 20s was distinct from those of other age cohorts, and this result was replicated, suggesting that it is a reproducible finding and distinct from those of other populations. The microbiota of the aged is variously described as being more or less diverse than that of younger cohorts, but the comparison groups used and the definitions of the aged population differ between experiments. The differences are often described by null hypothesis statistical tests, which are notoriously irreproducible when dealing with large multivariate samples. We collected and examined the gut microbiota of a cross-sectional cohort of more than 1,000 very healthy Chinese individuals who spanned ages from 3 to over 100 years. The analysis of 16S rRNA gene sequencing results used a compositional data analysis paradigm coupled with measures of effect size, where ordination, differential abundance, and correlation can be explored and analyzed in a unified and reproducible framework. Our analysis showed several surprising results compared to other cohorts. First, the overall microbiota composition of the healthy aged group was similar to that of people decades younger. Second, the major differences between groups in the gut microbiota profiles were found before age 20. Third, the gut microbiota differed little between individuals from the ages of 30 to >100. Fourth, the gut microbiota of males appeared to be more variable than that of females. Taken together, the present findings suggest that the microbiota of the healthy aged in this cross-sectional study differ little from that of the healthy young in the same population, although the minor variations that do exist depend upon the comparison cohort. IMPORTANCE We report the large-scale use of compositional data analysis to establish a baseline microbiota composition in an extremely healthy cohort of the Chinese population. This baseline will serve for comparison for future cohorts with chronic or acute disease. In addition to the expected difference in the microbiota of children and adults, we found that the microbiota of the elderly in this population was similar in almost all respects to that of healthy people in the same population who are scores of years younger. We speculate that this similarity is a consequence of an active healthy lifestyle and diet, although cause and effect cannot be ascribed in this (or any other) cross-sectional design. One surprising result was that the gut microbiota of persons in their 20s was distinct from those of other age cohorts, and this result was replicated, suggesting that it is a reproducible finding and distinct from those of other populations.

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