47 research outputs found

    Sleep quality, sleep duration, and sleep disturbances among hospital night workers:a prospective cohort study

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    Purpose:This study aimed to assess among hospital night workers (i) to what extent sleep quality, sleep duration and sleep disturbances overlap, and (ii) associations between sociodemographic factors, lifestyle factors and work characteristics and sleep components.Methods:Data were used from 467 hospital night workers participating in the Klokwerk + study, a prospective cohort study with two measurements. Sleep quality was measured by the Pittsburgh Sleep Quality Index, sleep duration and sleep disturbances were measured by the Medical Outcomes Study Sleep Scale. The overlap between the three sleep measures was visualized with a Venn diagram and the proportions of overlap was calculated. Associations between independent variables (sociodemographic factors, lifestyle factors and work characteristics) and the three sleep outcomes were estimated using between-within Poisson regression models.Results:About 50% of the hospital night workers had at least one poor sleep outcome. Overlap in poor sleep outcomes was apparent for 36.8% of these workers, while the majority had a poor outcome in one of the sleep components only (63.1%). Former smoking had a significant association with poor sleep quality. For most independent variables no associations with poor sleep outcomes were observed.Conclusion:Our findings suggest that sleep quality, sleep duration and sleep disturbances are separate entities and should be studied separately. Lifestyle factors and work characteristics were generally not associated with poor sleep. Since these factors can have an acute effect on sleep, future research should consider ecological momentary assessment to examine how exposure and outcomes (co)vary within-persons, over time, and across contexts.Trial registration Netherlands Trial Register trial number NL56022.041.1

    Mental health of healthcare workers during the first year of the COVID-19 pandemic in the Netherlands: a longitudinal study

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    PurposeIn March 2020, the WHO declared COVID-19 a pandemic. Previous virus outbreaks, such as the SARS outbreak in 2003, appeared to have a great impact on the mental health of healthcare workers. The aim of this study is to examine to what extent mental health of healthcare workers differed from non-healthcare workers during the first year of the COVID-19 pandemic.MethodsWe used data from a large-scale longitudinal online survey conducted by the Corona Behavioral Unit in the Netherlands. Eleven measurement rounds were analyzed, from April 2020 to March 2021 (N = 16,615; number of observations = 64,206). Mental health, as measured by the 5-item Mental Health Inventory, was compared between healthcare workers and non-healthcare workers over time, by performing linear GEE-analyses.ResultsMental health scores were higher among healthcare workers compared to non-healthcare workers during the first year of the pandemic (1.29 on a 0–100 scale, 95%-CI = 0.75–1.84). During peak periods of the pandemic, with over 100 hospital admissions or over 25 ICU admissions per day and subsequently more restrictive measures, mental health scores were observed to be lower in both healthcare workers and non-healthcare workers.ConclusionDuring the first year of the COVID-19 pandemic, we observed no relevant difference in mental health between healthcare workers and non-healthcare workers in the Netherlands. To be better prepared for another pandemic, future research should investigate which factors hinder and which factors support healthcare workers to maintain a good mental health

    Nachtwerk in breder perspectief

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    Werkende vrouwen in de overgang

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    Physical activity of workers with and without chronic diseases

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    OBJECTIVE: To contribute to the development of measures that increase physical activity (PA) levels in workers with and without chronic diseases, insight into workers' PA level is needed. Therefore, this study examined the association between the number of chronic diseases and PA in a Dutch working population. METHODS: Data of 131,032 workers from the Dutch Public Health Monitor 2012 were used in this cross-sectional study conducted in 2015 in the Netherlands. PA was operationalized as adherence (yes/no) to three PA guidelines. One of these was the American College of Sports Medicine (ACSM) guideline (≥ 3 days/week, ≥ 20 min/day of vigorous-intensity activities). Also, the amount of moderate- and vigorous-intensity PA in min/week for those who were physically active for > 0 min/week was calculated. Associations between chronic diseases (0, 1, ≥ 2 chronic diseases) and PA were examined using logistic regression and Generalized Estimating Equations stratified for age (19-54 years/55-64 years). RESULTS: Workers aged 19-54 years with one (OR = 0.90 (99% CI = 0.84-0.95)) and multiple chronic diseases (OR = 0.76 (99% CI = 0.69-0.83)) had lower odds of adhering to the ACSM-guideline than workers without chronic diseases. Similar patterns were found for older workers. Younger workers with one (B = 24.44 (99% CI = 8.59-40.30)) and multiple chronic diseases (B = 49.11 (99% CI = 26.61-71.61)) had a higher amount of moderate PA than workers without chronic diseases. CONCLUSION: Workers with chronic diseases adhered less often to the ACSM-guideline, but among workers aged 19-54 years who were physically active for > 0 min/week, those with chronic diseases spent more time in moderate-intensity PA than those without chronic diseases

    Shift work and its relation with meal and snack patterns among healthcare workers.

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    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 esti-mated 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

    Sickness absenteeism, work performance, and healthcare use due to respiratory infections for shift and non-shift workers.

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    This study aimed to compare sickness absenteeism, work performance, and healthcare use due to respiratory infections, as well as general sickness absenteeism and work performance between shift and non-shift workers. In this study, 589 shift and non-shift workers employed in hospitals were included. For 6 months, participants kept a daily record of their influenza-like illness/acute respiratory infection (ILI/ARI) symptoms using a diary application. After an episode of ILI/ARI symptoms ended, participants (n = 531) were questioned about their sickness absenteeism (occurrence and duration in hours), work performance (on a 10 point scale), and healthcare use during the ILI/ARI episode. At the end of the 6 months follow-up, participants (n = 498) were also asked about general sickness absenteeism and work performance in the past 4 weeks. Mixed-model and regression analyses were used to compare absenteeism, work performance, and healthcare use between shift and non-shift workers. No differences were found in sickness absenteeism [Odds Ratio (OR) = 1.00 (95%‒Confidence Interval (CI): 0.61‒1.64)] and work performance [Regression coefficient (B) = −0.19 (95%‒CI: −0.65‒0.26)] due to ILI/ARI between shift and non-shift workers. In addition, healthcare use due to ILI/ARI was similar between shift and non-shift workers. Furthermore, similar general sickness absenteeism rates and work performance levels were found between shift and non-shift workers. As this is the first study that examined the associations with shift work due to ILI/ARI, further studies are needed to confirm our findings
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