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"Night work"
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Overnight : journeys, conversations and stories after dark
There is something special about the night. For many, just the idea of it conjures thoughts of starlit skies, romance, refuge, of being tucked up in bed. For some, the night means fear, vulnerability, danger, sleeplessness. For others still, nightfall signals the start of work. At night things go bump, monsters hide under beds, owls take wing and foxes prowl. 'Overnight' is a celebration of all things nocturnal, of those who labour while the rest of us sleep: the bakers, health workers, sailors, couriers, broadcasters, drivers, fishers, the men and women of the emergency services and more. And it is also a hymn to nighttime wildlife, dreams and art. We'll hang out with bats and look at the stars. We'll learn what Moomintroll has to teach us about insomnia. We'll travel by ship, train, racing car and foot. There will be more than one surprise along the way.
BOOK
Work Schedule and Physically Demanding work in Relation to Menstrual Function: the Nurses' Health Study 3
Objectives This study aimed to evaluate occupational exposures and menstrual cycle characteristics among nurses. Methods Using cross-sectional data collected in 2010–2012 from 6309 nurses aged 21–45 years, we investigated nurses' menstrual function in the Nurses' Health Study 3. We used multivariable regression modeling to analyze the associations between occupational exposures and prevalence of irregular cycles and long and short cycle lengths. Results The cohort reported cycle length as <21 (1.5%), 21–25 (15.6%), 26–31 (69.7%), and 32–50 (13.2%) days. In addition, 19% of participants reported irregular cycles. Working ≥41 hours/week was associated with a 16% [95% confidence interval (95% CI): 4–29%] higher prevalence of irregular cycles and a higher prevalence of very short (<21-day) cycles [prevalence odds ratio (OR) 1.93, 95% CI 1.24–3.01] in adjusted models. Irregular menstrual cycles were more prevalent among women working nights only (32% higher; 95% CI 15–51%) or rotating nights (27% higher, 95% CI 10–47%), and was associated with the number of night shifts per month (P for trend <0.0001). Rotating night schedule was associated with long (32–50 day) cycles (OR 1.28, 95% CI 1.03–1.61). Heavy lifting was associated with a higher prevalence of irregular cycles (34% higher), and the prevalence of cycles <21 days and 21–25 day cycles increased with increasing heavy lifting at work (P for trend <0.02 for each endpoint). Conclusion Night work, long hours, and physically demanding work might relate to menstrual disturbances.
Journal Article
Night job
When the sun sets, Dad's night shift as a school custodian is just beginning. What is it like to work at night, while the rest of the city is asleep? The smell of lilacs in the night air, the dusky highway in the moonlight, and glimpses of shy, nighttime animals all make the dark seem almost magical. But what makes the night shift really special is being with Dad.
Book
How to schedule night shift work in order to reduce health and safety risks
Objectives This discussion paper aims to provide scientifically based recommendations on night shift schedules, including consecutive shifts, shift intervals and duration of shifts, which may reduce health and safety risks. Short-term physiological effects in terms of circadian disruption, inadequate sleep duration and quality, and fatigue were considered as possible links between night shift work and selected health and safety risks, namely, cancer, cardio-metabolic disease, injuries, and pregnancy-related outcomes. Method In early 2020, 15 experienced shift work researchers participated in a workshop where they identified relevant scientific literature within their main research area. Results Knowledge gaps and possible recommendations were discussed based on the current evidence. The consensus was that schedules which reduce circadian disruption may reduce cancer risk, particularly for breast cancer, and schedules that optimize sleep and reduce fatigue may reduce the occurrence of injuries. This is generally achieved with fewer consecutive night shifts, sufficient shift intervals, and shorter night shift duration. Conclusions Based on the limited, existing literature, we recommend that in order to reduce the risk of injuries and possibly breast cancer, night shift schedules have: (i) ≤3 consecutive night shifts; (ii) shift intervals of ≥11 hours; and (iii) ≤9 hours shift duration. In special cases - eg, oil rigs and other isolated workplaces with better possibilities to adapt to daytime sleep - additional or other recommendations may apply. Finally, to reduce risk of miscarriage, pregnant women should not work more than one night shift in a week.
Journal Article
Shift work schedule and night work load
Objectives The aim of this study was to investigate changes in body mass index (BMI) between different work schedules and different average number of yearly night shifts over a four-year follow-up period. Methods A prospective study of Norwegian nurses (N=2965) with different work schedules was conducted: day only, two-shift rotation (day and evening shifts), three-shift rotation (day, evening and night shifts), night only, those who changed towards night shifts, and those who changed away from schedules containing night shifts. Paired student's t-tests were used to evaluate within subgroup changes in BMI. Multiple linear regression analysis was used to evaluate between groups effects on BMI when adjusting for BMI at baseline, sex, age, marital status, children living at home, and years since graduation. The same regression model was used to evaluate the effect of average number of yearly night shifts on BMI change. Results We found that night workers [mean difference (MD) 1.30 (95% CI 0.70-1.90)], two shift workers [MD 0.48 (95% CI 0.20-0.75)], three shift workers [MD 0.46 (95% CI 0.30-0.62)], and those who changed work schedule away from [MD 0.57 (95% CI 0.17-0.84)] or towards night work [MD 0.63 (95% CI 0.20-1.05)] all had significant BMI gain (P<0.01) during the follow-up period. However, day workers had a non-significant BMI gain. Using adjusted multiple linear regressions, we found that night workers had significantly larger BMI gain compared to day workers [B=0.89 (95% CI 0.06-1.72), P<0.05]. We did not find any significant association between average number of yearly night shifts and BMI change using our multiple linear regression model. Conclusions After adjusting for possible confounders, we found that BMI increased significantly more among night workers compared to day workers.
Journal Article
Night-Shift Work and Breast Cancer-A Systematic Review and Meta-Analysis
Objective The aim of this review was to synthesize the evidence on the potential relationship between nightshift work and breast cancer. Methods We searched multiple databases for studies comparing women in shift work to those with no-shift work reporting incidence of breast cancer. We calculated incremental risk ratios (RR) per five years of nightshift work and per 300 night shift increases in exposure and combined these in a random effects dose—response meta-analysis. We assessed study quality in ten domains of bias. Results We identified 16 studies: 12 case—control and 4 cohort studies. There was a 9% risk increase per five years of night-shift work exposure in case—control studies [RR 1.09, 95% confidence interval (95% CI) 1.02—1.20; I 2 =37%, 9 studies], but not in cohort studies (RR 1.01, 95% CI 0.97—1.05; I 2 =53%, 3 studies). Heterogeneity was significant overall (I 2 =55%, 12 studies). Results for 300 night shifts were similar (RR 1.04, 95% CI 1.00—1.10; I 2 =58%, 8 studies). Sensitivity analysis using exposure transformations such as cubic splines, a fixed-effect model, or including only better quality studies did not change the results. None of the 16 studies had a low risk of bias, and 6 studies had a moderate risk. Conclusions Based on the low quality of exposure data and the difference in effect by study design, our findings indicate insufficient evidence for a link between night-shift work and breast cancer. Objective prospective exposure measurement is needed in future studies.
Journal Article
Breast Cancer among Shift Workers: Results of the WOLF Longitudinal Cohort Study
Objective The aim of this study was to investigate whether shift work (with or without night work) is associated with increased risk of breast cancer. Methods The population consisted of 4036 women. Data were obtained from WOLF (Work, Lipids, and Fibrinogen), a longitudinal cohort study. Information about baseline characteristics was based on questionnaire responses and medical examination. Cancer incidence from baseline to follow-up was obtained from the national cancer registry. Two exposure groups were identified: shift work with and without night work. The group with day work only was used as the reference group in the analysis. Cox regression analysis was used to calculate relative risk. Results In total, 94 women developed breast cancer during follow-up. The average follow-up time was 12.4 years. The hazard ratio for breast cancer was 1.23 [95% confidence interval (95% CI) 0.70—2.17] for shifts without night work and 2.02 (95% CI 1.03—3.95) for shifts with night work. When including only women <60 years of age, the risk estimates were 1.18 (95% CI 0.67—2.07) for shifts without night work, and 2.15 (95% CI 1.10—4.21) for shifts with night work. Conclusions Our results indicate an increased risk for breast cancer among women who work shifts that includes night work.
Journal Article
Associations between long-term night shift work and incidence of chronic obstructive pulmonary disease: a prospective cohort study of 277,059 UK Biobank participants
Background
Little is known about the effects of night shifts and their interactions with genetic factors on chronic obstructive pulmonary disease (COPD). In this study, we aim to investigate relationships between long-term night shift work exposure and COPD risk, and assess modification effects of genetic predisposition.
Methods
A total of 277,059 subjects who were in paid employment or self-employed were included in the UK Biobank. Information on current and lifetime employment was obtained, and a weighted COPD-specific genetic risk score (GRS) was constructed. We used Cox proportional hazard models to investigate associations between night shift work and COPD risk, and their interaction with COPD-specific GRS.
Results
The cohort study included 277,059 participants (133,063 men [48.03%]; mean [SD] age, 52.71 [7.08] years). During a median follow-up of 12.87 years, we documented 6558 incidents of COPD. From day work, irregular night shifts to regular night shifts, there was an increased trend in COPD incidence (
P
for trend < 0.001). Compared with day workers, the hazard ratio (HR) and 95% confidence interval (CI) of COPD was 1.28 (1.20, 1.37) for subjects with rarely/sometimes night shifts and 1.49 (1.35, 1.66) for those with permanent night shifts. Besides, the longer durations (especially in subjects with night shifts ≥ 10 years) and increasing monthly frequency of night shifts (in workers with > 8 nights/month) were associated with a higher COPD risk. Additionally, there was an additive interaction between night shifts and genetic susceptibility on the COPD risk. Subjects with permanent night shifts and high genetic risk had the highest risk of COPD (HR: 1.90 [95% CI: 1.63, 2.22]), with day workers with low genetic risk as a reference.
Conclusions
Long-term night shift exposure is associated with a higher risk of COPD. Our findings suggest that decreasing the frequency and duration of night shifts may offer a promising approach to mitigating respiratory disease incidence in night shift workers, particularly in light of individual susceptibility.
Journal Article
Night-shift work and susceptibility to infectious diseases: a systematic review and meta-analysis
OBJECTIVES: A growing body of research on infection susceptibility among night-shift workers has emerged, particularly since the COVID-19 pandemic. However, a comprehensive overview is still lacking. Therefore, this review aimed to synthesize the evidence on the association between night-shift work and susceptibility to infectious diseases. METHODS: Embase and PsycINFO were systematically searched for studies published up to September 2024. Studies were included if they comprised a working population, night-shift workers were compared to non-shift workers, and the outcome was an infectious disease. Results were descriptively synthesized for common respiratory infections (flu and common cold), SARS-CoV-2 infection, and other infections. Pooled effect estimates were calculated using random-effects meta-analysis. RESULTS: In total, 16 articles describing 14 studies among 191 320 workers were included. Based on 4 studies, night-shift work was not associated with a significantly increased risk of common respiratory infections [odds ratio (OR) 1.11, 95% confidence interval (CI) 0.97–1.27, I 2 =65.8%[. However, night-shift workers had a higher risk of SARS-CoV-2 infection than non-shift workers (OR 1.31, 95% CI 1.09–1.58, I 2 =92.2%, N=10 studies). This association was stronger in higher-quality studies and studies conducted in the first year of the COVID-19 pandemic. For other infections, insufficient studies were available to conduct a meta-analysis. The certainty of evidence was graded very low due to a limited number of (prospective cohort) studies and high inconsistency in the available studies. CONCLUSIONS: This systematic review and meta-analysis showed that night-shift work was associated with an increased risk of SARS-CoV-2 infection, but not of common respiratory infections. To address the lack of high-certainty evidence, more studies are needed that apply a prospective design with appropriate adjustment for confounding factors and more extensive information on night-shift work exposure.
Journal Article