A systematic review and meta-analysis of the association between shift work and metabolic syndrome: The roles of sleep, gender, and type of shift work.

This study was conducted to investigate the association between shift work and metabolic syndrome (MetS) and quantify the roles of sleep, gender, and type of shift work. We searched online databases, including PubMed, Scopus, and Web of Science on November 17, 2019. Of the 821 articles identified, 38 observational studies (27 cross-sectional, 10 cohorts, and one nested case-control), conducted on 128,416 participants, met our eligibility criteria. The pooled Odds ratio (OR) and 95% Confidence interval (CI) of MetS in shift-versus day-workers were estimated as 1.14 (1.07, 1.21) and 1.11 (1.06, 1.17) for the unadjusted and adjusted models. This association remained significant only for the studies with a cross-sectional design. There was a significantly higher odds of MetS in the studies conducted only on females (1.13 [1.06, 1.20]) or males (1.12 [1.02, 1.21]). The pooled adjusted OR (95% CI) for the studies without and with sleep adjustment was calculated as 1.14 (1.08, 1.21) and 1.29 (1.06, 1.52). We observed that rotating shift workers had stronger odds of MetS than the other shift workers. In conclusion, our findings revealed the significant odds of an association between shift work and MetS and different effects for sleep, gender, and type of shift work.

The association between urinary metabolites of polycyclic aromatic hydrocarbons and diabetes: A systematic review and meta-analysis study.

To examine the association between urinary metabolites of polycyclic aromatic hydrocarbons (OH-PAHs) and diabetes, online databases, including PubMed, Scopus, and Web of Science, were searched on July 17, 2019. Of the 668 articles identified through searching, six cross-sectional studies involving 24,406 participants were included. The pooled odds ratio (OR) and 95% confidence interval (CI) were calculated using a random-effect model. Heterogeneity was measured by reporting the I-square index. Moreover, subgroup analysis according to types of metabolites was performed. We found a significantly higher odds of diabetes in the highest versus the lowest category of urinary naphthalene (NAP), fluorine (FLU), phenanthrene (PHEN), and total OH-PAH metabolites. The pooled OR (95% CI) was estimated at 1.47 (1.17, 1.78), 1.50 (1.29, 1.71), 1.41 (1.21, 1.60), and 1.61 (1.01, 2.21), respectively. We also found a significant association per 1-fold increase in FLU (OR = 1.09, 95% CI [1.00, 1.19]) and PHEN (OR = 1.19, 95% CI [1.08, 1.30]) metabolites. In subgroup analysis stratified by types of OH-PAH metabolites, A significant stronger odds of diabetes was observed in the highest versus the lowest category of 2-PHEN (OR = 1.66, 95% CI [1.32, 2.00]), 2-NAP (OR = 1.66, 95% CI [1.16, 2.17]), 2-FLU (OR = 1.62, 95% CI [1.28, 1.97]), and 9-FLU (OR = 1.62, 95% CI [1.21, 2.04]) metabolites. Furthermore, there was a meaningfully greater likelihood of diabetes per 1-fold increase in 2-FLU (OR = 1.34, 95% CI [1.10, 1.57]), 2-PHEN (OR = 1.33, 95% CI [1.14, 1.51]), and 3-PHEN (OR = 1.19, 95% CI [1.04, 1.34]) metabolites. In conclusion, our study suggests the significant odds of association between urinary OH-PAH metabolites and diabetes.