Atmospheric benzene, toluene, ethylbenzene, and xylenes (BTEX) can lead to multiple health injuries. However, what remains uncertain is the effect of long-term exposure to low levels of BTEX. Thus, we determined the BTEX levels in the air from the refueling and office areas in gas stations. Then we collected workers’ (200 refueling vs. 52 office workers) peripheral blood samples to analyze the serum total-superoxide dismutase (T-SOD), glutathione (GSH), malondialdehyde (MDA), and 8-hydroxydeoxyguanosine (8-OHdG) levels. DNA damage was analyzed by the comet assay and micronucleus test in buccal epithelial cells. We found that the levels of BTEX in refueling areas were significantly higher than those in office areas (p < 0.001). The serum T-SOD and GSH of refueling workers were significantly lower than those in office workers (p < 0.001). By contrast, the serum MDA and 8-OHdG of refueling workers were significantly higher than those of office workers (p < 0.001, MDA; p = 0.025, 8-OHdG). Furthermore, tail and Olive tail moments in refueling workers were longer (p = 0.004, tail moment; p = 0.001, Olive tail moment), and the micronucleus rate was higher (p < 0.001) than those in office workers. Taken together, long-term exposure to low levels of BTEX may reduce the antioxidant ability and increase the risk of DNA damage in refueling workers of gas stations.

Background: Understanding the interplay among dietary patterns, screen time, and depressive symptoms among adolescents is crucial for the development of effective prevention strategies. This study aimed to explore the associations between dietary patterns, screen time, and their combined effects on depressive symptoms among high school students in Shandong Province, China. Methods: Utilizing the Database of Youth Health (DYH) from the China Population Health Science Data Center in 2020, demographic characteristics, food intake frequencies, and screen time information were collected from 8,276 high school students aged 12–20 years in Shandong Province, China. Principal component analysis was employed to identify distinct dietary patterns, and logistic regression analysis was used to assess the associations of dietary patterns and screen time single and co-exposure with depressive symptoms. Results: The prevalence of depressive symptoms among adolescents in Shandong Province stood at 18.9%. Principal component analysis identified three main dietary patterns: balanced dietary patterns, high-protein dietary patterns, and processed dietary patterns. In comparison to students who maintained balanced dietary patterns, those who followed processed dietary patterns demonstrated a higher risk of depressive symptoms, exhibiting odds ratios (ORs) and 95% confidence intervals (CIs) of 1.62 (1.40–1.88). Additionally, adolescents whose screen time ≥ 2 h/d faced a greater risk of depressive symptoms than those whose screen time was < 2 h/d (OR = 1.46, 95% CI 1.25–1.70). Adolescents in high-protein dietary patterns with screen time ≥ 2 h/d, processed dietary patterns with screen time < 2 h/d, and processed dietary patterns with screen time ≥ 2 h/d all showed elevated risks of depressive symptoms. The respective ORs (95% CIs) for these groups were 1.71 (1.27–2.31), 1.60 (1.36–1.89), and 2.34 (1.86–2.94). Conclusions: Our findings demonstrate that co-exposure to high-protein dietary patterns and screen time ≥ 2 h/d is significantly associated with increased risk of depressive symptoms in adolescents. Notably, processed dietary patterns exhibit a more pronounced association, demonstrating heightened depressive symptom risks even when combined with either shorter (< 2 h/d) or longer (≥ 2 h/d) screen time durations.

Background: The relationships between the dietary inflammatory index (DII), body mass index (BMI), and waist‒to-hip ratio (WtHR) and both diagnosed diabetes mellitus (DDM) and undiagnosed diabetes mellitus (UDDM), as well as the contributions of these factors, have not yet been comprehensively evaluated. This study aimed to investigate this association and elucidate the roles of DII, BMI, and the WtHR in the development of diabetes. Methods: This was a cross-sectional study involving 3687 participants aged 18 to 69 years were selected from the China National Nutrition and Health Survey (CNNHS 2010 to 2013) and the China Adult Chronic Disease and Nutrition Surveillance (CACDNS 2015) in Guangxi. DII scores were calculated from a 3-day, 24-hour (3d 24 h) dietary survey combined with the weighing method. Unconditional logistic regression, restricted cubic spline (RCS), and weighted quantile sum (WQS) models were utilized to assess the associations between DII, BMI, WtHR, and both DDM and UDDM. Results: The overall prevalence of TDM was 6.6%, comprising 40.6% DDM and 59.4% UDDM cases. Compared with Q1 (the lowest proinflammatory group), subjects in Q4 and Q5 exhibited significantly higher TDM risk, with ORs (95% CI) of 1.65 (1.06, 2.56) and 1.88 (1.21, 2.92), respectively. This association was particularly pronounced in UDDM, where a significant dose-response relationship emerged (P-trend = 0.006), with Q5 demonstrating the highest diabetes risk which OR (95% CI) was 1.98 (1.16, 3.40). DII scores and the risks of TDM and UDDM were linear (all P values < 0.05) but no association between the DII and DDM risk. There is a nonlinear relationship between BMI and DDM risk, a linear relationship with UDDM risk, and significant positive correlations between the WtHR and both DDM and UDDM risk. WtHR emerged as the primary contributor (weight = 0.69) in participants with DDM. For participants with UDDM, DII emerged as the primary determinant, outweighing BMI (weight = 0.37 vs. 0.35) and the WtHR (weight = 0.28). Conclusions: A high-proinflammatory diet is significantly linked to increased risks of both DDM and UDDM. BMI and the WtHR also exert substantial yet differential influences.