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.
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.
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.
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.
This study aimed to estimate acute effects of roster characteristics on fatigue and sleep quality and investigated whether these effects differed by individual characteristics.
Using an ecological ...measurement assessment survey, fatigue and sleep quality were daily measured among 223 shift workers for up to eight weeks. A questionnaire assessed baseline characteristics, and roster data were retrieved from the company registers to determine roster parameters. The effects between each shift parameter on fatigue and sleep quality were estimated with random- and fixed-effects models.
Compared to day shifts, night shifts were related to fatigue β=0.22; 95% confidence interval (CI) 0.05-0.39 and poorer sleep quality (β=0.64; 95% CI 0.47-0.80), and more successive night shifts with more fatigue (up to β=0.68; 95% CI 0.49-0.87 for ≥2 nights). Fatigue was increased after a quick return (<11 hours) (β=1.94; 95% CI 1.57-2.31) or 11-16 hours (β=0.43; 95% CI 0.26-0.61) compared to >16 hours between shifts. Compared to forward rotation, stable (β=0.22; 95% CI 0.01-0.43) and backward rotation (β=0.49; 95% CI 0.23-0.74) were also associated with more fatigue. Workers with a morning or intermediate chronotype had poorer sleep quality after a night shift, while workers with poor health reported poor sleep quality as well as more fatigue after a night shift.
To alleviate acute effects of shift work on fatigue, shift schedules should be optimized by ensuring more time to recover and rotate forwards.
Objectives Shift workers are prone to obesity and associated co-morbidities such as diabetes and cardiovascular disease. Sleep restriction associated with shift work results in dramatic endocrine and ...metabolic effects that predispose shift workers to these adverse health consequences. While sleep restriction has been associated with increased caloric intake, food preference may also play a key role in weight gain associated with shift work. This study examined the impact of an overnight simulated night shift on food preference. Methods Sixteen participants mean 20.1, standard deviation (SD) 1.4 years; 8 women underwent a simulated night shift and control condition in a counterbalanced order. On the following morning, participants were provided an opportunity for breakfast that included high- and low-fat food options (mean 64.8% and 6.4% fat, respectively). Results Participants ate significantly more high-fat breakfast items after the simulated night shift than after the control condition 167.3, standard error of the mean (SEM) 28.7) g versus 211.4 (SEM 35.6) g; P=0.012. The preference for high-fat food was apparent among the majority of individuals following the simulated night shift (81%), but not for the control condition (43%). Shift work and control conditions did not differ, however, in the total amount of food or calories consumed. Conclusions A simulated night shift leads to preference for high-fat food during a subsequent breakfast opportunity. These results suggest that food choice may contribute to weight-related chronic health problems commonly seen among night shift workers.
Purpose
Whether chronotype affects the health outcomes of night shift work populations is unknown. This study aimed to assess the influence of different chronotypes in the rotating night shift ...population on sleep status, mood, blood pressure (BP), and heart rate variability (HRV), as well as the circadian rhythm of BP and HRV.
Methods
A total of 208 rotating night shift workers were included. All participants completed structured questionnaires to assess chronotype, mood and sleep status. During their daily lives outside of the night shift, they underwent 24-hour Holter electrocardiogram monitoring and 24-hour ambulatory blood pressure monitoring. Day-time and night-time BP and BP dipping were obtained. Day-time and night-time HRV values (SDNN, RMSSD, LF, HF, LF nu, SD1, SD2 and SD2/SD1) were calculated and fitted to the cosine period curve. Three circandian parameters (mesor, amplitude and acrophase) were extracted to quantify the circadian rhythm of the HRV indices.
Results
Among all three groups, E-type showed more fatigue and sleepiness. In addition, E-type showed blunted diastolic BP dipping. Notably, E-type showed association with higher RMSSD, LF, HF and SD1 in the night time, and higher mesors of RMSSD and LF and amplitude of SD2/SD1 in circadian analysis.
Conclusion
Chronotype is a factor affecting fatigue, sleepiness and cardiovascular circadian rhythms of rotating night shift workers. Chronotype should be taken into consideration for managing night-shift rotation to promote occupational health.
Regular sleep is very important for human health; however, the short-term and long-term effects of nightshift with sleep deprivation and disturbance on human metabolism, such as oxidative stress, ...have not been effectively evaluated based on a realistic cohort. We conducted the first long-term follow-up cohort study to evaluate the effect of nightshift work on DNA damage.
We recruited 16 healthy volunteers (aged 33 ± 5 years) working night shifts at the Department of Laboratory Medicine at a local hospital. Their matched serum and urine samples were collected at four time points: before, during (twice), and after the nightshift period. The levels of 8-oxo-7,8-dihydroguanosine (8-oxoG) and 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxodG), two important nucleic-acid damage markers, were accurately determined based on a robust self-established LC‒MS/MS method. The Mann-Whitney U or Kruskal-Wallis test was used for comparisons, and Pearson's or Spearman's correlation analysis was used to calculate the correlation coefficients.
The levels of serum 8-oxodG, estimated glomerular filtration rate-corrected serum 8-oxodG, and the serum-to-urine 8-oxodG ratio significantly increased during the nightshift period. These levels were significantly higher than pre-nightshift work level even after 1 month of discontinuation, but no such significant change was found for 8-oxoG. Moreover, 8-oxoG and 8-oxodG levels were significantly positively associated with many routine biomarkers, such as total bilirubin and urea levels, and significantly negatively associated with serum lipids, such as total cholesterol levels.
The results of our cohort study suggested that working night shifts may increase oxidative DNA damage even after a month of discontinuing nightshift work. Further studies with large-scale cohorts, different nightshift modes, and longer follow-up times are needed to clarify the short- and long-term effects of night shifts on DNA damage and find effective solutions to combat the negative effects.
To explore the association between behavioural characteristics with the prevalence of abdominal obesity (AO) among a population of Southern Brazilian shift working women.
A cross-sectional study was ...conducted. AO was estimated using waist circumference (WC), and it was used to classify women as having AO (WC ≥ 88 cm). Prevalence ratios were estimated using Poisson regression with robust variance.
A large plastic utensils company in Southern Brazil.
450 female shift workers.
The prevalence of the AO in the women shift workers was 44·5 % (95 % CI 40·0, 49·2 %). In night shift workers, the prevalence of AO was 56·1 % compared with 40·9 % among hybrid shift workers. After adjustments for covariates, women who were current smokers had a decrease in the prevalence of AO compared with those who never smoked. Women who had three or fewer meals per day had a 46 % increase in the AO prevalence compared with those eating more frequent meals. Night shift work was associated with increase in AO prevalence compared with hybrid shift (PR 1·33; 95 % CI: 1·08, 1·64).
Our findings indicate that behavioural characteristics are associated with a high prevalence of AO in female shift workers, thus suggesting that behavioural modifications among women working shifts, such as increase in meal frequency and physical activity, may reduce AO.
The objective of this work was to evaluate the magnitude of COVID-19 spread and the related risk factors among hospital nurses employed in a COVID hospital in Rome, before the beginning of the ...vaccination programmes commenced in 2021. Participants periodically underwent (every 15-30 days) nasopharyngeal swab and/or blood sample for SARS-CoV-2 IgG examination. From 1 March 2020 to 31 December 2020, we found 162 cases of COVID-19 infection (
= 143 nasopharyngeal swab and
= 19 IgG-positive) in a total of 918 hospital nurses (17.6%). Most SARS-CoV-2-infected hospital nurses were night shift workers (NSWs), smokers, with higher BMI and lower mean age than that of individuals who tested negative. After adjusting for covariates, age (OR = 0.923, 95% C.I. 0.895-0.952), night shift work (OR = 2.056, 95% C.I. 1.320-2.300), smoking status (OR = 1.603, 95% C.I. 1.080-2.378) and working in high-risk settings (OR = 1.607, 95% C.I. 1.036-2.593) were significantly associated with SARS-CoV-2 hospital infection, whereas BMI was not significantly related. In conclusion, we found a high prevalence of SARS-CoV-2 infection among hospital nurses at a Rome COVID hospital in the pre-vaccination period. Smoking, young age, night shift work and high-risk hospital settings are relevant risk factors for hospital SARS-CoV-2 infection; therefore, a close health surveillance should be necessary among hospital nurses exposed to SARS-CoV-2.
Objectives The objective was to investigate effects of timed bright light treatment on subjective and objective measures of sleepiness during three consecutive night shifts among hospital nurses. ...Methods Thirty-five nurses were exposed to bright light (10,000 lux) and red dim light (100 lux) during three consecutive night shifts in a counter-balanced crossover trial lasting nine days, which included three days before and three days after the three night shifts. Light exposure for 30 minutes was scheduled between 02:00-03:00 hours on night 1, and thereafter delayed by one hour per night in order to delay the circadian rhythm. Subjective sleepiness was measured daily (heavy eyelids, reduced performance) and every second hour while awake (Karolinska Sleepiness Scale, KSS). Objective sleepiness (Psychomotor Vigilance Task, PVT) was measured at 05:00 hours during each night shift. Beyond nocturnal light exposure on the night shifts, no behavioral restrictions or recommendations were given at or off work. Results Bright light treatment significantly reduced heavy eyelids during night shifts. However, results on KSS and PVT were unaffected by bright light. There were no differences in subjective sleepiness during the three days following the night shifts. Conclusions This bright light treatment protocol did not convincingly reduce sleepiness among nurses during three consecutive night shifts. Nor did bright light impede the readaptation back to a day-oriented rhythm following the night shift period. Too few consecutive night shifts, inappropriate timing of light, and possible use of other countermeasures are among the explanations for the limited effects of bright light in the present study.
Healthcare workers need to be at work 24 h a day to ensure continuity of care in hospitals. However, shift work - particularly night shifts - can have negative acute and long-term effects on health ...and productivity due to disturbances in the circadian rhythm. Shift work is also associated with unhealthy lifestyle behaviors such as poor sleep hygiene and diet. The PerfectFit@Night intervention aims to improve sleep and recovery, and reduce fatigue, and therewith contribute to sustainable employability of healthcare workers. The current study describes the intervention and the evaluation and implementation.
The study population will consist of healthcare workers, nurses and physicians, with night shifts in a large Dutch academic hospital. The intervention consists of individual and environmental intervention elements: i) an e-learning for healthcare workers to increase knowledge and awareness on a healthy lifestyle during night shifts, ii) a powernap bed to take powernaps during night shifts, iii) the availability of healthy food at the department during night shifts, iv) a workshop on healthy rostering at the level of the department, and v) individual sleep coaching among the high risk group. In a longitudinal prospective study, data will be collected 1 month before the start of the intervention, in the week before the start of the intervention, and three and 6 months after the start of the intervention. The primary outcomes are sleep, fatigue, and need for recovery. The implementation process will be evaluated using the framework of Steckler and Linnan. Cost-benefit analyses from the employers perspective will be conducted to understand the possible financial consequences or benefits of the implementation of PerfectFit@Night.
The feasibility and effectiveness of this workplace health promotion program will be investigated by means of an effect, process and economic evaluation. If proven effective, PerfectFit@Night can be implemented on a larger scale within the healthcare sector.
Netherlands Trial Register trial number NL9224 . Registered 17 January 2021.
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