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Objective: Working from home during the COVID-19 pandemic has affected many workers' daily life and possibly their physical activity behavior. We studied the longitudinal association of working from home during the pandemic with physical activity and sedentary behavior., Methods: Longitudinal data from 17 questionnaire rounds of the Lifelines COVID-19 cohort (March 2020-February 2021) were used. In total, 33 325 workers were included. In every round, participants reported their current work situation: location, home, or hybrid (working on location and from home). Physical activity levels and sedentary behavior before and during the pandemic were asked. Logistic generalized estimating equations adjusted for demographic/work/health covariates were used to study the association of work situation with physical activity and sedentary behavior., Results: Home workers were less likely to meet the recommended ≥150 minutes/week of moderate-to-vigorous-intensity activity during the pandemic than location workers [odds ratio (OR) 0.93, 95% confidence interval (CI) 0.90-0.96] and more likely to be less physically active than before the pandemic (OR 1.09, 95% CI 1.04-1.14). Furthermore, compared to location workers, home and hybrid workers were more likely to be more sedentary (sitting ≥8 hours/day) on workdays during than before the pandemic (OR 1.51, 95% CI 1.39-1.64/1.36-1.68, respectively)., Conclusions: Compared to location workers, home workers (and to a lesser extent hybrid workers) were more often physically inactive and sedentary during than before the COVID-19 pandemic. As a substantial part of the working population may continue to work (partly) from home after the pandemic, workers should be supported to increase activity and reduce sitting while working from home.

Objectives Shift work may be associated with an increased incidence of respiratory infections. However, underlying mechanisms are unclear. Therefore, our aim was to examine the mediating role of sleep, physical activity, and diet in the association between shift work and respiratory infections. Methods This prospective cohort study included 396 shift and non-shift workers employed in hospitals. At baseline, sleep duration and physical activity were measured using actigraphy and sleep/activity diaries, sleep quality was reported, and frequency of meal and snack consumption was measured using food diaries. In the following six months, participants used a smartphone application to report their influenza-like illness/acute respiratory infection (ILI/ARI) symptoms daily. Mediation analysis of sleep, physical activity, and diet as potential mediators of the effect of shift work on ILI/ARI incidence rate was performed using structural equation modeling with negative binomial and logistic regression. Results Shift workers had a 23% [incidence rate ratio (IRR) 1.23, 95% CI 1.01-1.49] higher incidence rate of ILI/ARI than non-shift workers. After adding the potential mediators to the model, this reduced to 15% (IRR 1.15, 95% CI 0.94-1.40). The largest mediating (ie, indirect) effect was found for poor sleep quality, with shift workers having 29% more ILI/ARI episodes via the pathway of poorer sleep quality (IRR 1.29, 95% CI 1.02-1.95). Conclusions Compared to non-shift workers, shift workers had a higher incidence rate of ILI/ARI that was partly mediated by poorer sleep quality. Therefore, it may be relevant for future research to focus on perceived sleep quality as an underlying mechanism in the relation between shift work and increased infection susceptibility.

Objective Unfavorable eating patterns might contribute to the adverse health effects of shift work. Our objective was to examine differences in meal and snack frequency, as well as the quality of snacks, between shift and day workers and between different types of shifts. Methods Cross-sectional data from 485 healthcare workers aged 18-65 years of the Klokwerk+ cohort study was used. Dietary intake was assessed using 3-day food diaries, and meals and snacks were classified by the food-based classification of eating episodes method. Using multivariable-adjusted regression analyses, we estimated differences in meal and snack frequency and the quality of snacks between shift and day workers. Within the shift working group, eating frequency on day, evening, and night shifts were compared to work-free days. Results Meal and snack frequency as well as the quality of snacks showed no significant differences between shift and day workers (P≥0.05). Shift workers had a higher frequency of high-quality snacks [β 0.29, 95% confidence interval (CI) 0.12-0.46] and a lower frequency of low-quality snacks (β -0.29, 95% CI -0.49- -0.09) on evening shifts compared to their work-free days. Compared to work-free days, shift workers had a higher frequency of high-quality snacks on days shifts (β 0.24, 95% CI 0.10-0.38), and only those aged ≤40 years had a higher frequency of snacks on night shifts (β 0.53, 95% CI 0.06-1.00) (interaction by age P<0.05). Conclusion This study observed no differences between day and shift workers either in meal and snack frequency or in the quality of snacks. However, snacking patterns differed across shifts. Future research should investigate whether these snacking patterns contribute to the adverse health effects of shift work.

Objectives Shift work may alter workers' leisure-time and occupational physical activity (PA) levels, which might be one of the potential underlying mechanisms of the negative health effects of shift work. Therefore, we compared objectively measured PA levels between hospital shift and non-shift workers. Methods Data were used from Klokwerk+, a cohort study examining the health effects of shift work among healthcare workers employed in hospitals. In total, 401 shift workers and 78 non-shift workers were included, all of whom wore Actigraph GT3X accelerometers for up to seven days. Time spent sedentary, standing, walking, running, stairclimbing, and cycling during leisure time and at work was estimated using Acti4 software. Linear regression was used to compare proportions of time spent in these activities between hospital shift and non-shift workers. Results Average accelerometer wear-time was 105.9 [standard deviation (SD) 14.0] waking hours over an average of 6.9 (SD 0.6) days. No differences between hospital shift and non-shift workers were found in leisure-time PA (P>0.05). At work, shift workers were less sedentary [B=-10.6% (95% CI -14.3- -6.8)] and spent larger proportions of time standing [B=9.5% (95% CI 6.4-12.6)] and walking [B=1.2% (95% CI 0.1-2.2)] than non-shift workers. However, these differences in occupational PA became smaller when the number of night shifts during accelerometer wear-time increased. Conclusions Leisure-time PA levels of hospital shift workers were similar to those of non-shift workers, but shift workers were less sedentary and more physically active (ie, standing/walking) at work. Future research to the role of occupational activities in the health effects of shift work is recommended.