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The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has indirectly produced both positive and negative effects on the environment, particularly in terms of air quality. Our study aimed to determine these effects in the city of Tehran by comparing the ambient PM2.5 and PM10 levels recorded at 22 air quality monitoring stations during the outbreak (20 February–2 April 2020) with those from the corresponding period last year (20 February–3 April 2019). Contrary to expectation, the average concentrations of both the PM2.5 and the PM10 were markedly higher during the former, increasing by 20.5% and 15.7%, respectively, for the first month of the outbreak (20 February–19 March 2020) and by 23.5% and 20.0% for the subsequent Nowruz New Year holidays (from late March till early April), which resulted in overall increases of 20.5% and 16.5% for the entire period. The non-integrated responses to the pandemic, including the failure to close administrative centers and, in particular, the recommendation to maintain social distancing by reducing public transportation use (prompting citizens to travel by private vehicle), have worsened the ambient air quality in Tehran, providing an exceptional opportunity to evaluate the direct/indirect influence of air quality policies and emission control measures on PM2.5 and PM10. Because of the significant association between the lethality of coronavirus disease 2019 (COVID-19) and exposure to ambient air pollution, the rise in airborne PM2.5 during this outbreak may increase the mortality rate of SARS-CoV-2.

This study systematically reviewed all the cohort studies investigating the relationship between long-term exposure to PM2.5 and any health outcome until February 2018. We searched ISI Web of Knowledge, Pubmed, and Scopus databases for peer-reviewed journal research articles published in English. We only extracted the results of the single-pollutant main analysis of each study, excluding the effect modifications and sensitivity analyses. Out of the initial 9523 articles, 203 articles were ultimately included for analysis. Based on the different characteristics of studies such as study design, outcome, exposure assessment method, and statistical model, we calculated the number and relative frequency of analyses with statistically significant and insignificant results. Most of the studies were prospective (84.8%), assessed both genders (66.5%), and focused on a specific age range (86.8%). Most of the articles (78.1%) had used modeling techniques for exposure assessment of cohorts’ participants. Among the total of 317 health outcomes, the most investigated outcomes include mortality due to cardiovascular disease (6.19%), all causes (5.48%), lung cancer (4.00%), ischemic heart disease (3.50%), and non-accidental causes (3.50%). The percentage of analyses with statistically significant results were higher among studies that used prospective design, mortality as the outcome, fixed stations as exposure assessment method, hazard ratio as risk measure, and no covariate adjustment. We can somehow conclude that the choice of right characteristics for cohort studies can make a difference in their results.

BACKGROUND: Despite frequent warnings of irreversible side effects of smoking in public media, the consumption of cigarette is increasing dramatically in both developed and developing countries. Cigarette smoke contains different kinds of chemicals, which all capable of inducing free radical production. There are studies supporting the idea that these free radicals have adverse effects in body and causing oxidative stress. Total antioxidant capacity (TAC) is considered as the total effect of all antioxidants and total oxidant status (TOS) shows the total effect of all oxidants existing in body fluids. Therefore, this research focused on the measurement and comparison of these markers in the serum of university students. METHODS: This study designed to determine the total antioxidant capacity, total oxidant status and oxidative stress index levels in the serum of active smokers, passive smokers and non-smokers in university students. A total of 150 participants were included in the study. The study population consisted of 50 smokers, 50 passive smokers and 50 nonsmokers. In serum samples, the levels of TAC and TOS were measured by spectrophotometric method using Rel Assay Diagnostics kit. Oxidative stress index was calculated through the TOS/TAC formula in three groups. RESULTS: The mean value TAC levels in serum samples of the three groups of smokers, passive smokers and nonsmokers were 1.096, 1.220 and 1.844 mmol Trolox equivalent/L, respectively, which were significantly greater in nonsmokers than smokers and passive smokers. The mean value TOS levels in serum samples of the three groups of smokers, passive smokers and nonsmokers were 13.747, 11.099 and 7.6510 µmol H2O2 equivalent/L, respectively, which were significantly lower in nonsmokers than two other groups. OSI values in smokers and passive smokers were significantly higher than the control group. CONCLUSIONS: According to our findings, the antioxidant capacity in all smokers (active and inactive) was less than the control group (non-smokers). The results of this study showed that smoking reduces the activity of the antioxidant defense system and activates the oxidative stress system in the body. Based on these findings, it can be clearly concluded that the decrease in antioxidant capacity in smokers is associated with increased production of oxidants and free radicals.

Particulate-filtering respirators (PFRs) have been recommended as a practical personal-level intervention to protect individuals from the health effects of particulate matter exposure. However, the cardiovascular benefits of PFRs including improvements in key surrogate endpoints remain unclear. We performed a systematic review and meta-analysis of randomized studies (wearing versus not wearing PFRs) reporting the effects on blood pressure (BP) and heart rate variability (HRV). The search was performed on January 3, 2022 to identify published papers until this date. We queried three English databases, including PubMed, Web of Science Core Collection and Scopus. Of 527 articles identified, eight trials enrolling 312 participants (mean age ± standard deviation: 36 ± 19.8; 132 female) met our inclusion criteria for analyses. Study participants wore PFRs from 2 to 48 h during intervention periods. Wearing PFRs was associated with a non-significant pooled mean difference of -0.78 mmHg (95% confidence interval [CI]: -2.06, 0.50) and -0.49 mmHg (95%CI: -1.37, 0.38) in systolic and diastolic BP (SBP and DBP). There was a marginally significant reduction of mean arterial pressure (MAP) by nearly 1.1 mmHg (95%CI: -2.13, 0.01). The use of PFRs was associated with a significant increase of 38.92 ms

The impact of bioaerosols in municipal solid waste management is nowadays identified as a growing health concern worldwide. In this study, exposure to endotoxin in composting facilities and its association with lung function and clinical symptoms was investigated in Tehran municipal solid waste management complex (Aradkooh) as one of the largest solid waste management facilities in the Middle East. Airborne endotoxins were collected between June and July 2019 and the concentrations were determined by Limulus Amebocyte Lysate (LAL) method. Healthy workers with no history of respiratory disease were recruited and data on clinical symptoms (cough, phlegm, wheezing, dyspnea, fatigue, headache, eye irritation, runny nose, runny eyes, and sore throat) was obtained by the modified American Thoracic Society questionnaire, and spirometric measurement was performed by an expert. The binary logistic regression test was used and adjusted for confounding variables. The results didn't show any difference in lung function parameters (FEV1, FVC, FEV1/FVC, PEF, FEF25-75%), and most of the respiratory symptoms despite a relatively high difference in the concentration of endotoxin observed in air samples of different locations. Only the increased risk of cough (OR 10.5, 95% CI: 2.4 to 44.8 in the moderately exposed group and 7.8, 95% CI: 1.6 to 39.1 in highly exposed ones), fatigue (OR 3.7, 95% CI: 1.2 to 11.7), and headache (OR 6.02, 95% CI: 1.4 to 24.5) were found in the exposed groups compared to controls after adjusting for age, active and passive smoking. However, findings of the study might be underestimated due to some issues including healthy worker effect, intra and intersubject variability, and self-reporting bias, thereby the results should be interpreted with caution. Although we did not find any relationship, due to the high concentrations of endotoxins observed in some sites, it is recommended to consider some possible prevention measures such as using personal protective equipment to reduce the exposure of workers at an acceptable level.

Some recent human and animal studies have suggested that air pollution may affect the central nervous system and contribute to neurodevelopmental outcomes, such as autism spectrum disorder (ASD). We aimed to investigate the association between long-term exposure to ambient air pollution and increased odds of ASD among 2 to 10-year-old children. We conducted a case-control study in Tehran, Iran. Cases were 134 children born between 2004 and 2012 diagnosed with ASD whose mothers were resident in Tehran during their pregnancy, and controls were 388 children without ASD randomly selected from public schools and kindergartens. Land-use regression models were used to estimate their annual mean exposure to ambient particulate matter with aerodynamic diameter ≤10 μm (PM10), sulfur dioxide (SO2), benzene, toluene, ethylbenzene, p-xylene, o-xylene, m-xylene (BTEX), and total BTEX. Logistic regression was used for the analyses and adjusted for possible confounding variables. The odds ratios per 1 unit increase in pollutants in the adjusted models were 1.00 (95% CI: 0.99, 1.01) for PM10, 0.99 (95% CI: 0.99, 1.00) for SO2, 0.96 (0.83, 1.11) for benzene, 1.00 (0.96, 1.04) for toluene, 0.95 (0.79, 1.16) for ethylbenzene, 1.00 (0.78, 1.27) for p-xylene, 1.09 (0.94, 1.27) for o-xylene, 1.01 (0.92, 1.12) for m-xylene, and 0.99 (0.97, 1.01) for total BTEX. We did not find the evidence of association between estimated annual mean exposure to abovementioned ambient air pollutants and increased odds of ASD in children. However, our findings might be due to some important limitations. Further research with better control of confounding variables, improved spatiotemporal exposure estimates, and inclusion of other important markers of air pollution is recommended.

To investigate spatial inequality of ambient air pollutants and comparison of their heterogeneity and homogeneity across Tehran, the following quantitative indicators were utilized: coefficient of divergence (COD), the 90th percentile of the absolute differences between ambient air pollutant concentrations and coefficient of variation (CV). Real-time hourly concentrations of particulate matter (PM) and gaseous air pollutants (GAPs) of twenty-two air quality monitoring stations (AQMSs) were obtained from Tehran Air Quality Control Company (TAQCC) in 2017. Annual mean concentrations of PM2.5, PM10–2.5, and PM10 (PMX) ranged from 21.7 to 40.5, 37.3 to 75.0 and 58.0 to 110.4 μg m−3, respectively. Annual mean PM2.5 and PM10 concentrations were higher than the World Health Organization air quality guideline (WHO AQG) and national standard levels. NO2, O3, SO2 and CO annual mean concentrations ranged from 27.0 to 76.8, 15.5 to 25.1, 4.6 to 12.2 ppb, and 1.9 to 3.8 ppm over AQMSs, respectively. Our generated spatial maps exhibited that ambient PMX concentrations increased from the north into south and south-western areas as the hotspots of ambient PMX in Tehran. O3 hotspots were observed in the north and south-west, while NO2 hotspots were in the west and south. COD values of PMX demonstrated more results lower than the 0.2 cut off compared to GAPs; indicating high to moderate spatial homogeneity for PMX and moderate to high spatial heterogeneity for GAPs. Regarding CV approach, the spatial variabilities of air pollutants followed in the order of O3 (87.3%) > SO2 (65.2%) > CO (61.8%) > PM10–2.5 (52.5%) > PM2.5 (48.9%) > NO2 (48.1%) > PM10 (42.9%), which were mainly in agreement with COD results, except for NO2. COD values observed a statistically (P