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BACKGROUND: While mounting evidence suggests a connection between environmental contaminants and sleep problems, it remains uncertain whether exposure to volatile organic compounds (VOCs) specifically is associated with such problems. METHODS: Data from the National Health and Nutrition Examination Survey program's five survey cycles (2005-2006, 2011-2018) were used to conduct cross-sectional research. Data on short sleep duration (SSD) and self-reported trouble sleeping were collected from questionnaire data. Data on urine VOCs were gathered from laboratory data. The association between urinary VOCs and sleep problems was examined using weighted generalized linear models and the restricted cubic spline (RCS), weighted quantile sum (WQS), and quantile-based g-calculation (QGC) methods. RESULTS: In all, a total of 4131 general adult individuals were included in this study. The prevalence of SSD and self-reported trouble sleeping was 34.11% and 25.03%, respectively. 3,4-MHA, AAMA, AMCC, SBMA, and MA were risk factors for SSD after adjusting several covariates, with the largest effect being AMCC (OR = 1.47, 95% CI: 1.08, 2.02). Risk factors for sleep issues included AAMA, AMCC, CEMA, CYMA, DGBMA, 2HPMA, 3HPMA, MA, and PGA, with AMCC having the highest impact with an OR of 1.69 (95% CI: 1.28, 2.22). Both the WQS model and the QGC model showed that the co-exposure to VOCs was positively associated with SSD and self-reported trouble sleeping, with AMCC being the most influential VOC. CONCLUSIONS: According to our research, high levels of single or mixed urine VOCs are linked to a higher prevalence of SSD and self-reported trouble sleeping in the general adult population of the United States. Further prospective and experimental studies are needed in the future to validate these potential relationships and explore the underlying mechanisms.
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Background: The coronavirus disease 2019 (COVID-19) is a severe acute respiratory disease that poses a continuous threat to global public health. Many non-pharmacological interventions (NPIs) have been implemented to control the COVID-19 pandemic since the beginning. The aim of this study was to assess the impact of various NPIs on COVID-19 mortality during pre-vaccination and vaccination periods. Methods: The COVID-19 data used in this study comes from Our World in Data, we used the Oxford Strict Index (OSI) and its five combination interventions as independent variables. The COVID-19 mortality date (MRT) was defined as a date when daily rate of 0.02 COVID-19 deaths per 100,000 population in a country was reached, and the COVID-19 vaccination date (VRT) was defined as people vaccinated reaching 70%. Linear regression and random forest models were used to estimate the impact of various NPI implementation interventions during pre-vaccination and vaccination periods. The performance of models was assessed among others with Shapley Additive Explanations (SHAP) explaining the prediction capability of the model. Results: During the pre-vaccination period, the various NPIs had strong protective effect. When the COVID-19 MRT was reached, for every unit increase in OSI, the cumulative mortality as of June 30, 2020 decreased by 0.71 deaths per 100,000 people. Restrictions in travel (SHAP 1.68) and cancelation of public events and gatherings (1.37) had major reducing effect on COVID-19 mortality, while staying at home (0.26) and school and workplace closure (0.26) had less effect. Post vaccination period, the effects of NPI reduced significantly: cancelation of public events and gatherings (0.25), staying at home (0.22), restrictions in travel (0.14), and school and workplace closure (0.06). Conclusion: Continued efforts are still needed to promote vaccination to build sufficient immunity to COVID-19 in the population. Until herd immunity is achieved, NPI is still important for COVID-19 prevention and control. At the beginning of the COVID-19 pandemic, the stringency of NPI implementation had a significant negative association with COVID-19 mortality; however, this association was no longer significant after the vaccination rate reached 70%. As vaccination progresses, "cancelation of public events and gatherings" become more important for COVID-19 mortality.
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Inflammation and the coagulation cascade are considered to be the potential mechanisms of ambient particulate matter (PM) exposure-induced adverse cardiovascular events. Tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), interleukin-8 (IL-8), and fibrinogen are arguably the four most commonly assayed markers to reflect the relationships of PM with inflammation and blood coagulation. This review summarized and quantitatively analyzed the existing studies reporting short- and long-term associations of PM2.5(PM with an aerodynamic diameter ≤2.5 µm)/PM10 (PM with an aerodynamic diameter≤10 µm) with important inflammation and blood coagulation markers (TNF-α, IL-6, IL-8, fibrinogen). We reviewed relevant studies published up to July 2020, using three English databases (PubMed, Web of Science, Embase) and two Chinese databases (Wang-Fang, China National Knowledge Infrastructure). The OHAT tool, with some modification, was applied to evaluate risk of bias. Meta-analyses were conducted with random-effects models for calculating the pooled estimate of markers. To assess the potential effect modifiers and the source of heterogeneity, we conducted subgroup analyses and meta-regression analyses where appropriate. The assessment and correction of publication bias were based on Begg's and Egger's test and "trim-and-fill" analysis. We identified 44 eligible studies. For short-term PM exposure, the percent change of a 10 µg/m3 PM2.5 increase on TNF-α and fibrinogen was 3.51% (95% confidence interval (CI): 1.21%, 5.81%) and 0.54% (95% confidence interval (CI): 0.21%, 0.86%) respectively. We also found a significant short-term association between PM10 and fibrinogen (percent change = 0.17%, 95% CI: 0.04%, 0.29%). Overall analysis showed that long-term associations of fibrinogen with PM2.5 and PM10 were not significant. Subgroup analysis showed that long-term associations of fibrinogen with PM2.5 and PM10 were significant only found in studies conducted in Asia. Our findings support significant short-term associations of PM with TNF-α and fibrinogen. Future epidemiological studies should address the role long-term PM exposure plays in inflammation and blood coagulation markers level change.