This study aimed to investigate the change in diet quality in addition to dietary adherence to the planetary health diet during night shifts in healthcare workers. This observational follow-up study involved 450 healthcare workers working night shifts (327 females, 123 males). A survey form requesting sociodemographic information (gender, age, marital status), job title, sleeping duration during the night shift, 24 h dietary records for pre-night-shift, during night shift, and post-night-shift, and anthropometric measurements (body weight and height) was applied. The scores of the Planetary Health Diet Index (PHDI) and the Healthy Eating Index 2020 (HEI-2020) were calculated according to the dietary records. The total HEI-2020 and PHDI scores decreased significantly (p < 0.05) during the night shift (44.0 ± 8.8 and 48.3 ± 13.2, respectively) compared to pre-night-shift (46.1 ± 9.2 and 51.9 ± 13.4, respectively) and increased post-night-shift (44.7 ± 9.9 and 50.6 ± 14.9, respectively), with no statistically significant difference between pre- and post-night-shift. There was a significant main effect of night shift working on total PHDI (F(896, 2) = 8.208, p < 0.001, ηp2 = 0.018) and HEI-2020 scores (F(894, 2) = 6.277, p = 0.002, ηp2 = 0.014). Despite healthcare workers\' knowledge of health factors, night shifts lead to poor dietary choices. To improve diet quality and sustainability, it is crucial to enhance access to healthy food options in their work environment.

BACKGROUND: The hypothesis of this study is night shift work exposure can increase the risk of female breast cancer. To validate this hypothesis, the authors conducted a two-stage dose-response meta-analysis with improved quality on this topic.
METHODS: The medical librarian searched PubMed, EMBASE, and the Cochrane Library on December 30th, 2022. The eight inclusion criteria were determined and strictly applied to the selection process. A reliable dose-response meta-analysis methodology was applied.
RESULTS: Reliable 10 cohort (total cases: 15,953, and total person-years: 6,812,138) and 11 case-control reports (total cases: 9196, and total controls:12,210) were included in the final analysis. The pooled risk ratio (RR) of female breast cancer (from cohort studies) for 1, 10, 20, and 30 years of night shift work exposure was 1.0042 (95% CI 1.0014-1.0070), 1.0425 (95% CI 1.0138-1.0719), 1.0867 (95% CI 1.0278-1.1490), and 1.1328 (95% CI 1.0419-1.2317), respectively. The pooled odds ratio (OR) of female breast cancer (from case-control studies) for 1, 10, 20, and 30 years of night shift work exposure was 1.0213 (95% CI 1.0108-1.0319), 1.2346 (95% CI 1.1129-1.3695), 1.5242 (95% CI 1.2386-1.8756), and 1.8817 (95% CI 1.3784-2.5687), respectively.
CONCLUSIONS: This study has several strengths from the perspective of a dose-response meta-analysis: Strictly applied eight inclusion criteria, separately synthesized RRs from cohort studies and ORs from case-control studies, clearly defined exposure dose, years of night shift work for each risk estimate, a reliable dose-response meta-analysis methodology, and careful considering of selection, exposure, and outcome biases and confounder adjustment for each study. This careful consideration of potential biases and confounding led to the exclusion of unreliable two cohort and five case-control studies.

Shift work has become increasingly common in modern society. Shift work has been associated with a range of negative health outcomes. Therefore, this 10-years retrospective cohort study, aimed to investigate the relationship between shift work and blood and metabolic parameters. This retrospective cohort study was conducted in a metal parts manufacturing industry in 2023. In this study, 204 shift workers and 204 day workers were examined. All the studied blood and metabolic parameters were collected by reviewing the medical records of all participants during a 10-years period (2013-2022). Moreover, the amounts of physical, chemical, and ergonomics harmful agents in the work environment were investigated. All the collected data were analyzed using SPSS version 25.0. The values of Body Mass Index (BMI), Red Blood Cell Count (RBC), Platelets Count (PLT), Thyroid-Stimulating Hormone Level (TSH), Fasting Blood Sugar Level (FBS), Creatinine, Triglyceride (TG), Liver Enzymes level (SGOT and SGPT), and Systolic Blood Pressure (SBP) were higher among the shift work employees, and a significant difference was observed between the values of these parameters between the two groups. The results of logistic regression showed that the highest effect of shift work was observed on the parameters of FBS, TG, SGPT, TSH, Physical activity, BMI, Sleep duration, PLT, and Sleep quality with beta coefficient values of 0.49, 0.33, 0.29, 0.29, 0.20, 0.18, 0.14, 0.13 and, 0.11, respectively (p-value < 0.01). The present study contributes to a growing body of evidence that blood and metabolic factors are likely to be influenced by shift work. These findings have important implications for policy makers, highlighting the need for interventions to mitigate the negative health effects of shift work on workers.

Using the 2010-2019 Comprehensive Survey of Living Conditions (CSLC) conducted in Japan, we examined the impact of long working hours on mental health in Japan while addressing the endogeneity issue arising from non-random selection bias. We assessed the variations in the effects of long working hours on mental health across different groups. The results show that first, individuals working longer hours (55 h or more per week) exhibited a higher likelihood of developing mental illness than those working regular hours or fewer hours. Second, the negative effect of long working hours on mental health is more pronounced among non-regular workers than among regular workers. Third, the effect of long working hours on mental health varies among different demographic groups, with a greater impact observed among women, managers, non-regular workers, employees in small- or large-sized firms, and those in smaller cities compared to their counterparts. Thus, to enhance worker productivity, the Japanese government should address the issue of long working hours to improve employees\' mental well-being. Initiatives aimed at promoting work-life balance, family-friendly policies, and measures to ameliorate working conditions are expected to help mitigate the challenges associated with long working hours and mental health issues, especially among non-regular workers.

OBJECTIVE: The prevalence of 12-hour shift work is increasing in various occupations. Shift work has been linked to circadian rhythm disruption, which may lead to hormonal changes and metabolic disorders, including alterations in glucose, lipid, and purine metabolism. Despite this, there is limited research on the potential connection between work shifts and abnormal serum uric acid (SUA) levels. Furthermore, the factors that contribute to abnormal SUA levels in shift workers are not well-understood. Therefore, this study aimed to analyze the SUA levels of shift workers employed in an aircraft maintenance company, investigate the potential association between shift work and SUA levels, and explore the factors that may influence abnormal SUA levels in shift workers.
METHODS: A total of 2263 male workers from an aircraft maintenance company were included in this study using the cluster sampling method. The workers were divided into two groups based on their working shifts: night shift (N = 1047, 46.27%) and day working (N = 1216, 53.73%). A survey was conducted between April 1st and June 30th, 2022 to gather information on work, lifestyle, physical examination results, and other relevant factors. The survey included a self-designed demographic information questionnaire to collect data on workers\' characteristics, medical history, years of employment, smoking and drinking habits, and main lifestyle behaviors. The workers\' SUA levels were measured using uricase colorimetry. One-way ANOVA was used to compare the difference in the abnormal detection rate of SUA between the two groups, and multi-factor logistic regression analysis was used to identify the factors that influence abnormal SUA levels.
RESULTS: The study indicated that 48.9% of night shift workers and 43.8% in the regular day workers had abnormal SUA levels, with a significant difference between the two groups (χ2 = 6.125, P = 0.013). Factors such as circadian rhythm type, shift work, age, the taste of diet, type of diet, smoking, overweight or obesity based on body mass index (BMI), concentration of urine creatinine (CREA), total cholesterol, triglyceride, and low-density lipoprotein cholesterol were found to be correlated with SUA abnormalities (P < 0.05). The risk of developing SUA abnormalities was found to be higher in individuals with an intermittent (OR = 1.34, 95% CI: 0.83-2.12, P < 0.05) or evening circadian rhythm type (OR = 1.45, 95% CI: 0.86-2.43, P > 0.05) compared to those with a morning type. Additionally, factors such as night shift work, a high-sodium diet, smoking, a diet high in meat and low in vegetables, being overweight or obese, and higher levels of CREA were also found to increase the risk of developing SUA abnormalities. The study also revealed a significant dose-response relationship between BMI and abnormal uric acid levels. After controlling for other factors, the risk of developing SUA abnormalities was found to be 1.18 times higher in the night shift work group than in the day work group (OR = 1.18, 95% CI:1.02-1.34, P = 0.01).
CONCLUSIONS: Shift work has been linked to a higher risk of developing SUA abnormalities, and there are several factors that may contribute to this risk. To prevent diseases, it is recommended that enterprises implement better health monitoring and management practices for shift workers.

This study aimed to explore the relationship between shift-working nurses\' social jetlag and body mass index (BMI) and provide a theoretical basis for nursing managers to develop appropriate health interventions. Shift work is unavoidable in nursing and is associated with circadian rhythm disorders. Social jetlag is prevalent in shift-working nurses and is associated with adverse health outcomes (particularly metabolism-related indicators). BMI is a significant metabolic indicator, and research has demonstrated its effectiveness in predicting the formation of metabolic syndrome. The relationship between social jetlag and BMI can be explained by considering physiological, psychological, and behavioral factors. However, most studies on social jetlag and health status are focused on non-shift nurse populations, with fewer studies on shift workers. Five tertiary hospitals located at similar latitudes in Southwest China were selected for the study. We surveyed 429 shift-working nurses using sociodemographic data, the Munich Chronotype Questionnaire for Shift Workers, and BMI. The restricted cubic spline model was used to analyze the relationship between social jetlag and BMI among shift-working nurses, and segmented linear regression was performed around the inflection point using multiple linear regression analysis. The results revealed that social jetlag (82.0 [85.0] min) was experienced by 64.6% of the shift-working nurses. After controlling for confounding variables, the model with seven knots had the lowest accepted Akaike information criterion value, and there was a U-shaped relationship between shift-working nurses\' BMI and social jetlag in this model; its inflection (lowest) point of 20.7 was considered the cut-off point. Segmented regression showed that for BMI < 20.7, BMI was significantly negative with standardized social jetlag; whereas with BMI > 20.7, BMI was significantly positive with standardized social jetlag. BMI has a U-shaped relationship with social jetlag, and attention should be paid to overweight or underweight shift-working nurses to detect early circadian rhythm disorder. Shift-working nurses with high social jetlag tended to have higher/lower BMI, which should be further investigated in the future, to minimize metabolic diseases among them.

This study aimed to elucidate the effects of long day and night shifts on immune cells in a population of nurses. This cross-sectional study in December 2019 was based on a group of nurses. 1568 physically healthy caregivers were included, including 1540 women and 28 men. 1093 nurses had long-term shift work (working in a rotating system for > 1 year). The receiver operating characteristic curve, Ensemble Learning, and Logistic regression analyses were used to evaluate factors related to long-term shift work. The night shift group nurses had significantly higher MPV, PLCR, and WBC and significantly lower BASO%, ELR, MCHC, PLR, RDW-CV, and RDW-SD (P < 0.01). ROC curves showed that WBC, PLR, ELR, RDW_CV, and BASO% were more related to the night shift. Ensemble Learning, combined with the LASSO model, finally filtered out three indicators of night shifts related to ELR, WBC, and RDW_SD. Finally, logistic regression analysis showed that the nurses\' night shift situation greatly influenced two peripheral blood ELR and WBC indicators (ELR: log (OR) =  - 3.9, 95% CI: - 5.8- - 2.0; WBC: log (OR) = 0.25, 95% CI: 0.18-0.32). Finally, we showed that, unlike WBC, the relative riskiness of ELR showed opposite results among junior nurses and middle-senior nurses (log (OR) 6.5 (95% CI: 1.2, 13) and - 7.1 (95% CI: - 10, - 3.8), respectively). Our study found that prolonged night shifts were associated with abnormal WBC and ELR, but after strict age matching, WBC remained significantly different. These findings help to confirm that COVID-19 and tumorigenesis (e.g., breast cancer) are significantly associated with circadian rhythm disruption. However, more detailed studies are needed to confirm this.

暂无摘要。

UNASSIGNED: Misaligned dietary rhythmicity has been associated with metabolic diseases; however, its association with mental health remains largely unexplored.
UNASSIGNED: To examine the association between dietary rhythms and the mental health condition of shift workers, specifically airline crew members.
UNASSIGNED: This cross-sectional study analyzed data collected from the Civil Aviation Health Cohort of China, an ongoing large-scale health survey of pilots, flight attendants, and air security officers employed by major airline companies in China. Participants aged 18 to 60 years were invited through text messages to complete a web-based survey. The data collection period was December 2022 to March 2023. Statistical analysis was performed from July 24, 2023, to April 12, 2024.
UNASSIGNED: Data on timing of breakfast and dinner on workdays and rest days, daily time windows for food intake, and meal and eating jet lags were collected and calculated.
UNASSIGNED: Anxiety and depressive symptoms were measured using the 7-item Generalized Anxiety Disorder Assessment and the 9-item Patient Health Questionnaire. Multivariate logistic regressions were performed to evaluate the associations of anxiety and depression with meal timing, eating window time, meal jet lag (ie, delayed meals), and eating jet lag (ie, delayed eating). All models were adjusted for individual socioeconomic, demographic, and lifestyle characteristics.
UNASSIGNED: Of the 22 617 participants (median [IQR] age, 29.1 [26.3-33.7] years; 13 712 males [60.6%]), 1755 (7.8%) had anxiety and 2768 (12.2%) had depression. After controlling for confounding factors, having dinner after 8 pm on morning-shift days was associated with increased odds of anxiety (adjusted odds ratio [AOR], 1.78; 95% CI, 1.53-2.05) and depression (AOR, 2.01; 95% CI, 1.78-2.27), compared with consuming dinner before 8 pm. Similar results were observed on night-shift days and rest days. An eating window of less than 12 hours was associated with reduced odds of anxiety (AOR, 0.84; 95% CI, 0.75-0.93) and depression (AOR, 0.81; 95% CI, 0.75-0.89) on morning-shift days; the results remained significant on rest days. Delayed dinner on morning-shift days was associated with increased odds of anxiety (AOR, 1.32; 95% CI, 1.13-1.54) and depression (AOR, 1.39; 95% CI, 1.22-1.58). On night-shift days, delayed dinner was associated with higher odds of anxiety (AOR, 1.22; 95% CI, 1.06-1.39) and depression (AOR, 1.21; 95% CI, 1.08-1.36). On morning-shift days, delayed eating rhythms were associated with higher odds of depression (AOR, 1.35; 95% CI, 1.13-1.61), whereas advanced eating rhythms were associated with lower odds of anxiety (AOR, 0.78; 95% CI, 0.70-0.87).
UNASSIGNED: This cross-sectional study found that meal timing, long eating window, and meal jet lags were associated with increased odds of depression and anxiety. These findings underscore the need for interventions and supportive policies that help mitigate the adverse implications of shift work and irregular working hours for the mental health of shift workers.

BACKGROUND: Shift work is associated with susceptibility to several neuropsychiatric disorders. This study aims to investigate the effect of shift work on the incidence of neuropsychiatric disorders, and highlighting how individual variability may influence the association.
METHODS: UK Biobank participants with employment information were included. Cox survival was conducted in main and subgroup analyses. Correlation analyses explored the impact of shift work on brain structures, and mediation analyses were performed to elucidate the shared underlying mechanisms. Shift work tolerance was evaluated through survival analyses contrasting the risks associated with five neuropsychiatric disorders in shift versus non-shift workers across different demographic or occupational strata.
RESULTS: The analysis encompassed 254,646 participants. Shift work was associated with higher risk of dementia (HR 1.29, 95 % CI 1.10-1.52), anxiety (1.08, 1.01-1.15), depression (1.29, 1.22-1.36), and sleep disorders (1.18, 1.09-1.28), but not stroke (p = 0.20). Shift work was correlated with decreasing volume of various brain regions, particularly in thalamus, lateral orbitofrontal, and middle temporal. Mediation analysis revealed that increased immune response and glucose levels are common pathways linking shift work to these disorders. We observed diversity in shift work tolerance across different individual characteristics, among which socioeconomic status and length of working hours were the most essential.
CONCLUSIONS: Self-reported employment information may cause misclassification and recall bias. And since we focused on the middle-aged population, the conclusions may not be representative of younger or older populations.
CONCLUSIONS: Our findings indicated the need to monitor shift worker health and provide personalized management to help adapt to shift work.