AimsThis study aimed to evaluate the associations between types of night shift work and different indices of obesity using the baseline information from a prospective cohort study of night shift workers in China.MethodsA total of 3,871 workers from five companies were recruited from the baseline survey. A structured self-administered questionnaire was employed to collect the participants’ demographic information, lifetime working history, and lifestyle habits. Participants were grouped into rotating, permanent and irregular night shift work groups. Anthropometric parameters were assessed by healthcare professionals. Multiple logistic regression models were used to evaluate the associations between night shift work and different indices of obesity.ResultsNight shift workers had increased risk of overweight and obesity, and odds ratios (ORs) were 1.17 (95% CI, 0.97–1.41) and 1.27 (95% CI, 0.74–2.18), respectively. Abdominal obesity had a significant but marginal association with night shift work (OR = 1.20, 95% CI, 1.01–1.43). A positive gradient between the number of years of night shift work and overweight or abdominal obesity was observed. Permanent night shift work showed the highest odds of being overweight (OR = 3.94, 95% CI, 1.40–11.03) and having increased abdominal obesity (OR = 3.34, 95% CI, 1.19–9.37). Irregular night shift work was also significantly associated with overweight (OR = 1.56, 95% CI, 1.13–2.14), but its association with abdominal obesity was borderline (OR = 1.26, 95% CI, 0.94–1.69). By contrast, the association between rotating night shift work and these parameters was not significant.ConclusionPermanent and irregular night shift work were more likely to be associated with overweight or abdominal obesity than rotating night shift work. These associations need to be verified in prospective cohort studies.

ObjectivesAccumulated 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.MethodsThis 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.ResultsAmong 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.ConclusionsNight 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.

This study aims to develop an artificial intelligence (AI)-based model to assist radiologists in pneumoconiosis screening and staging using chest radiographs. The model, based on chest radiographs, was developed using a training cohort and validated using an independent test cohort. Every image in the training and test datasets were labeled by experienced radiologists in a double-blinded fashion. The computational model started by segmenting the lung field into six subregions. Then, convolutional neural network classification model was used to predict the opacity level for each subregion respectively. Finally, the diagnosis for each subject (normal, stage I, II, or III pneumoconiosis) was determined by summarizing the subregion-based prediction results. For the independent test cohort, pneumoconiosis screening accuracy was 0.973, with both sensitivity and specificity greater than 0.97. The accuracy for pneumoconiosis staging was 0.927, better than that achieved by two groups of radiologists (0.87 and 0.84, respectively). This study develops a deep learning-based model for screening and staging of pneumoconiosis using man-annotated chest radiographs. The model outperformed two groups of radiologists in the accuracy of pneumoconiosis staging. This pioneer work demonstrates the feasibility and efficiency of AI-assisted radiography screening and diagnosis in occupational lung diseases.

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ObjectivesExperimental studies suggested that bisphenol A (BPA) exposure increased the risk of metabolic syndrome (MetS) through the mechanism of insulin resistance. All previous epidemiological studies of BPA and MetS were cross-sectional studies, and their findings were mixed. This study aims to provide further evidence on the association between urinary BPA and risk of MetS using a prospective cohort study in China.MethodsThe study population was from the Shenzhen Night shift workers’ cohort. A total of 1227 male workers were recruited from the baseline survey in 2013 and then followed until 2017. Modified Adult Treatment Panel III criteria were used to identify the cases of MetS. Urinary BPA concentration was assessed using high-performance liquid chromatography–tandem mass spectrometry, and it was categorised into three subgroups by tertiles to obtain the adjusted HR (aHR) and 95% CI using Cox proportional hazard model.ResultsDuring 4 years of follow-up, 200 subjects developed MetS. Compared with the lowest urinary BPA subgroup, a weakly increased risk of MetS was suggested among those with the middle (aHR=1.19, 95% CI 0.87 to 1.63) and high level of urinary BPA (aHR=1.16, 95% CI 0.84 to 1.59); however, the significant association with MetS was restricted primarily to the smokers, showing a positive gradient with urinary BPA (middle level: aHR=2.40, 95% CI 1.13 to 5.08; high level: aHR=2.87, 95% CI 1.38 to 5.98; p trend=0.010).ConclusionThis prospective cohort study provided further evidence that exposure to BPA may increase the risk of MetS, and this association was further positively modified by cigarette smoking.