Effects of Nightshift Work on Blood Metabolites in Female Nurses and Paramedic Staff: A Cross-sectional Study.

Nightshift work disturbs the circadian rhythm, which might contribute to the development of cardio-metabolic disorders. In this cross-sectional study, we aimed to gain insight into perturbations of disease relevant metabolic pathways due to nightshift work. We characterized the metabolic profiles of 237 female nurses and paramedic staff participating in the Klokwerk study using the Nightingale Health platform. We performed analyses on plasma levels of 225 metabolites, including cholesterol, triglycerides, fatty acids, and amino acids. Using both principal component- and univariate-regression, we compared metabolic profiles of nightshift workers to metabolic profiles from workers that did not work night shifts (defined as day workers). We also assessed whether differential effects were observed between recently started versus more experienced workers. Within the group of nightshift workers, we compared metabolic profiles measured right after a nightshift with metabolic profiles measured on a day when no nightshift work was conducted. We observed evidence for an impact of nightshift work on the presence of unfavorable fatty acid profiles in blood. Amongst the fatty acids, effects were most prominent for PUFA/FA ratios (consistently decreased) and SFA/FA ratios (consistently elevated). This pattern of less favorable fatty acid profiles was also observed in samples collected directly after a night shift. Amino acid levels (histidine, glutamine, isoleucine, and leucine) and lipoproteins (especially HDL-cholesterol, VLDL-cholesterol, and triglycerides) were elevated when comparing nightshift workers with day workers. Amino acid levels were decreased in the samples that were collected directly after working a nightshift (compared to levels in samples that were collected during a non-nightshift period). The observed effects were generally more pronounced in samples collected directly after the nightshift and among recently started compared to more experienced nightshift workers. Our finding of a suggested impact of shift work on impaired lipid metabolism is in line with evidence that links disruption of circadian rhythmicity to obesity and metabolic disorders.

Disentangling associations between multiple environmental exposures and all-cause mortality: an analysis of European administrative and traditional cohorts.

Background: We evaluated the independent and joint effects of air pollution, land/built environment characteristics, and ambient temperature on all-cause mortality as part of the EXPANSE project. Methods: We collected data from six administrative cohorts covering Catalonia, Greece, the Netherlands, Rome, Sweden, and Switzerland and three traditional cohorts in Sweden, the Netherlands, and Germany. Participants were linked to spatial exposure estimates derived from hybrid land use regression models and satellite data for: air pollution [fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC), warm season ozone (O3)], land/built environment [normalized difference vegetation index (NDVI), distance to water, impervious surfaces], and ambient temperature (the mean and standard deviation of warm and cool season temperature). We applied Cox proportional hazard models accounting for several cohort-specific individual and area-level variables. We evaluated the associations through single and multiexposure models, and interactions between exposures. The joint effects were estimated using the cumulative risk index (CRI). Cohort-specific hazard ratios (HR) were combined using random-effects meta-analyses. Results: We observed over 3.1 million deaths out of approximately 204 million person-years. In administrative cohorts, increased exposure to PM2.5, NO2, and BC was significantly associated with all-cause mortality (pooled HRs: 1.054, 1.033, and 1.032, respectively). We observed an adverse effect of increased impervious surface and mean season-specific temperature, and a protective effect of increased O3, NDVI, distance to water, and temperature variation on all-cause mortality. The effects of PM2.5 were higher in areas with lower (10th percentile) compared to higher (90th percentile) NDVI levels [pooled HRs: 1.054 (95% confidence interval (CI) 1.030-1.079) vs. 1.038 (95% CI 0.964-1.118)]. A similar pattern was observed for NO2. The CRI of air pollutants (PM2.5 or NO2) plus NDVI and mean warm season temperature resulted in a stronger effect compared to single-exposure HRs: [PM2.5 pooled HR: 1.061 (95% CI 1.021-1.102); NO2 pooled HR: 1.041 (95% CI 1.025-1.057)]. Non-significant effects of similar patterns were observed in traditional cohorts. Discussion: The findings of our study not only support the independent effects of long-term exposure to air pollution and greenness, but also highlight the increased effect when interplaying with other environmental exposures.

High-Performance Data Processing Workflow Incorporating Effect-Directed Analysis for Feature Prioritization in Suspect and Nontarget Screening.

Effect-directed analysis (EDA) aims at the detection of bioactive chemicals of emerging concern (CECs) by combining toxicity testing and high-resolution mass spectrometry (HRMS). However, consolidation of toxicological and chemical analysis techniques to identify bioactive CECs remains challenging and laborious. In this study, we incorporate state-of-the-art identification approaches in EDA and propose a robust workflow for the high-throughput screening of CECs in environmental and human samples. Three different sample types were extracted and chemically analyzed using a single high-performance liquid chromatography HRMS method. Chemical features were annotated by suspect screening with several reference databases. Annotation quality was assessed using an automated scoring system. In parallel, the extracts were fractionated into 80 micro-fractions each covering a couple of seconds from the chromatogram run and tested for bioactivity in two bioassays. The EDA workflow prioritized and identified chemical features related to bioactive fractions with varying levels of confidence. Confidence levels were improved with the in silico software tools MetFrag and the retention time indices platform. The toxicological and chemical data quality was comparable between the use of single and multiple technical replicates. The proposed workflow incorporating EDA for feature prioritization in suspect and nontarget screening paves the way for the routine identification of CECs in a high-throughput manner.

Plasma sCD36 as non-circadian marker of chronic circadian disturbance in shift workers.

Shift work induces chronic circadian disturbance, which might result in increased health risks, including cardio-metabolic diseases. Previously, we identified sCD36 as a potential non-circadian biomarker of chronic circadian disturbance in mice. The aim of the current study (n = 232 individuals) was to identify whether sCD36 measured in plasma can be used as a non-circadian marker of chronic circadian disturbance in humans, which would allow its use to measure the effects of interventions and monitoring in large-scale studies. We compared levels of plasma sCD36 of day workers with recent (< 2 years) and experienced (> 5 years) night-shift workers within the Klokwerk study. We detected no differences in sCD36 levels between day workers and recent or experienced night-shift workers, measured during a day or afternoon shift. In addition, sCD36 levels measured directly after a night shift were not different from sCD36 levels measured during day or afternoon shifts, indicating no acute effect of night shifts on sCD36 levels in our study. In summary, our study does not show a relation between night-shift work experience (recent or long-term) and plasma levels of sCD36. Since we do not know if and for which time span night-shift work is associated with changes in sCD36 levels, and our study was relatively small and cross-sectional, further evidence for an association between chronic circadian disruption and this candidate biomarker sCD36 should be gathered from large cohort studies.

Diet, Physical Activity, and Daylight Exposure Patterns in Night-Shift Workers and Day Workers.

Background: Night-shift work has been reported to have an impact on nutrition, daylight exposure, and physical activity, which might play a role in observed health effects. Because these exposures show diurnal variation, and shift work has been related with disturbances in the circadian rhythm, the timing of assessment of these factors requires careful consideration. Our aim was to describe the changes in patterns of diet, physical activity, and daylight exposure associated with night-shift work. Methods: We conducted an observational study among female healthcare workers either regularly working night shifts or not working night shifts. We assessed physical activity and daylight exposure using continuous monitoring devices for 48 h. We logged dietary patterns (24 h) and other health- and work-associated characteristics. Two measurement sessions were conducted when participants did 'not' work night shifts, and one session was conducted during a night-shift period. Results: Our study included 69 night-shift workers and 21 day workers. On days in which they conduct work but no night work, night-shift workers had similar physical activity and 24-h caloric intake, yet higher overall daylight exposures than day workers and were more often exposed around noon instead of mainly around 1800h. Night-shift workers were less exposed to daylight during the night-shift session compared to the non-night-shift session. Total caloric intakes did not significantly differ between sessions, but we did observe a shorter maximum fasting interval, more eating moments, and a higher percentage of fat intake during the night-shift session. Conclusion: Observed differences in diet, physical activity, and exposure to daylight primarily manifested themselves through changes in exposure patterns, highlighting the importance of time-resolved measurements in night-shift-work research. Patterns in daylight exposure were primarily related to time of waking up and working schedule, whereas timing of dinner seemed primarily governed by social conventions.

Night shift work and abnormal liver function: is non-alcohol fatty liver a necessary mediator?

OBJECTIVES: Accumulated evidence implies that night shift work may trigger liver dysfunction. Non-alcoholic fatty liver (NAFL) is suggested to be a necessary mediator in this process. This study aimed to examine the relationship between night shift work and elevated level of alanine transaminase (e-ALT) of workers and investigate the potential mediation effect of NAFL. METHODS: This study included all male workers from the baseline survey of a cohort of night shift workers. Information on demographics, lifestyle and lifetime working schedule was collected by face-to-face interview. Liver sonography was used to identify NAFL cases. Serum ALT level was detected by an automatic biochemical analyser. e-ALT was defined as ALT >40 U/L. Logistic regression models were used to evaluate ORs, and mediation analysis was employed to examine the mediation effect. RESULTS: Among 4740 male workers, 39.5% were night shift workers. Night shift workers had an increased risk of e-ALT (OR, 1.19, 95% CI 1.00 to 1.42). With the increase in night shift years, the OR of e-ALT increased from 1.03 (95% CI 0.77 to 1.36) to 1.60 (95% CI 1.08 to 2.39) among workers without NAFL. A similar trend was not found among workers with NAFL. In addition, no significant mediation effect of NAFL in the association between night shift work and e-ALT was found. CONCLUSIONS: Night shift work is positively associated with abnormal liver function, in particular among workers without NAFL. Shift work involving circadian disruption is likely to exert a direct effect on liver dysfunction rather than rely on the mediation effect of NAFL.