The association of exposure to air pollution and depression in women; a cross-sectional study of a middle-income country.

Air pollution exposure has been related with mental disorders, especially depression; however, the available evidence on these associations in Low and Middle-Income Countries (LMICs) is scarce. Therefore, we aimed to assess the relationship between particulate matter (PM) exposure and indicators of traffic with depressive symptoms in women of Sabzevar, Iran. This cross-sectional study was based on 741 women aged 15-45 years (adults) in 2019. The annual average of PM10, PM2.5 and PM1 at home was estimated using land use regression (LUR) models. Street map of Sabzevar was used to calculate the indicators of traffic, i.e., the proximity to major roads and total street length buffers with 100, 300 and 500 m radii around the participants' homes. We used the Center for Epidemiological Studies- Depression (CESD-20) Scale in the general population to measure depression scores. Quasi-Poisson models and logistic regression were used to examine the association and odds ratios of exposure to air pollution and depression scores adjusted for relevant covariates. Exposure to PM10, PM2.5 and PM1 and total street length in 100 m buffer were significantly associated with higher depression scores. In fully adjusted model, an interquartile range (IQR) increase in PM10, PM2.5 and PM1 concentration as well as total street length in 100 m buffer was associated with 1.25 (95% CI:1.03, 1.52, P-value = 0.02), 1.16 (95% CI: 1.06, 1.26, P-value< 0.01), 1.16 (95% CI: 1.03, 1.29, P-Value = 0.01) and 1.15 (95% CI: 1.06, 1.25, P-value< 0.01) odds of clinical depression, respectively. For street length in 300 and 500 m buffers and proximity to major roads, no statistically significant increased risk of clinical depression were observed. Overall, our findings recommended that air pollution exposure has increased the risk of clinical depression in women.

Association of greenspace exposure with telomere length in preschool children.

Exposure to greenspace has been associated with a wide range of health benefits; however, the available evidence on the association of this exposure with telomere length (TL), an early marker of ageing, is still scarce. We investigated the association of greenspace exposure with TL in a sample of 200 preschool children (aged 5-7 years) residing in Sabzevar, Iran (2017). We comprehensively characterized different aspects of greenspace exposure encompassing residential, kindergarten, and total (including both residential and kindergarten) surrounding greenspace (using satellite-derived Normalized Difference Vegetation Index), residential and kindergarten distance to green spaces, time spent in private gardens and public green spaces, and the number of plant pots at home. Relative leukocyte TL (LTL) in blood samples of the study participants was measured using quantitative polymerase chain reaction (qPCR). We applied mixed effects linear regression models with kindergarten and qPCR plate as random effects, to estimate the association of indicators of greenspace exposure (one at a time) with LTL, controlled for relevant covariates. We observed an inverse association between distance from home and kindergarten to green spaces larger than 5000 m2 and LTL. Moreover, higher total surrounding greenspace at 300m and 500m buffers and higher surrounding greenspace at 300m buffer around kindergarten and home were associated with longer LTL. Furthermore, longer time spent (h/week) in the public green spaces was associated with longer LTL. Our findings for residential and kindergarten distance to any green space (regardless of the size), residential surrounding greenspace at 100m and 500m buffers, kindergarten surrounding greenspace at 100m buffer, time spent in private gardens (h/week) and the number of plant pots at home were not conclusive. Our findings were generally suggestive for a positive association between greenspace exposure and LTL in preschool children. More studies are needed to confirm these findings in other settings with different climates and populations.

Asthma disease as cause of admission to hospitals due to exposure to ambient oxidants in Mashhad, Iran.

Nowadays, asthma is one of the most common chronic respiratory diseases, worldwide. Many reports have emphasized the correlation between the short-term exposure to the ambient air pollutants and acute respiratory diseases, especially among children with asthmatic symptoms. The aim of this study was to evaluate the relationship between the exposure to three atmospheric antioxidants (NO2, SO2, and O3) and hospital admission due to asthmatic disease (HAAD) in the city of Mashhad, Iran. The concentrations of atmospheric antioxidants were obtained from the real-time monitoring stations located in the city. The collected data were employed for developing predictive models in the AirQ software. In order to investigate the association between short-term exposure to air pollutants and HAAD, the study participants were categorized into two age groups: less than 15 and from 15 to 64 years old. The results indicated that in people less than 15 years increase in NO2 (attributable proportion (AP) = 3.775%, 95% CI 0.897-6.883%), SO2 (AP = 3.649%, 95% CI 1.295-5.937%), and O3 (AP = 0.554%,95% CI 0.00-3.321) results in increase in HAAD. While for those aged between 15 and 64 years, the AP was 4.192% (95% CI 0.450-7.662%) for NO2; 0.0% (95% CI 0.00-1.687%) for SO2; and 0.236% (95% CI 0.00-1.216%) for O3. The number of asthmatic cases who were less than 15 years admitted to the hospitals during the study period was higher than that of those within the age groups between 15 and 64 years as a consequence of exposure to NO2 (101 vs. 75), SO2 (98 vs. 0), and O3 (15 vs. 3), respectively. To the best of our knowledge, the AirQ model has not been applied before to estimate the effect of atmospheric antioxidant exposure on hospital admission because of asthma disease. Eventually, this model is proposed to be applicable for other cities around the world.

A time series analysis of environmental and metrological factors impact on cutaneous leishmaniasis incidence in an endemic area of Dehloran, Iran.

The aim of this study was to investigate the relationship between the environmental and metrological variables and cutaneous leishmaniasis (CL) transmission and its prediction in a region susceptible to this disease prevalence using a time series model. The accurate locations of 4437 CL diagnosed from 2011 to 2015 were obtained to be used in the time series model. Temperature, number of days with temperature over 30 °C, and number of earthquake were related to CL incidence using the Seasonal Auto-correlated Integrated Moving Average (SARIMA) model according to the Box-Jenkins method. In addition, the relationship between land use and surface soil type in 500- and 1000-m radius around the CL patients were investigated. The SARIMA models showed significant associations between environmental and meteorological variables and CL incidence adjusted for seasonality and auto-correlation. The result indicated that there are need more robust preventive programs in earthquake-prone areas with high temperature and inceptisol soil type than other areas. In addition, the region with these characteristics should be considered as high-risk areas for CL prevalence.

Mortality and morbidity due to exposure to outdoor air pollution in Mashhad metropolis, Iran. The AirQ model approach.

In the past two decades, epidemiological studies have shown that air pollution is one of the causes of morbidity and mortality. In this study the effect of PM10, PM2.5, NO2, SO2 and O3 pollutants on human health among the inhabitants of Mashhad has been evaluated. To evaluate the health effects due to air pollution, the AirQ model software 3.3.2, developed by WHO European Centre for Environment and Health, was used. The daily data related to the pollutants listed above has been used for the short term health effects (total mortality, cardiovascular and respiratory mortality, hospitalization due to cardiovascular and respiratory diseases, chronic obstructive pulmonary disease and acute myocardial infarction). PM2.5 had the most health effects on Mashhad inhabitants. With increasing in each 10µg/m3, relative risk rate of pollutant concentration for total mortality due to PM10, PM2.5, SO2, NO2 and O3 was increased of 0.6%, 1.5%, 0.4%, 0.3% and 0.46% respectively and, the attributable proportion of total mortality attributed to these pollutants was respectively equal to 4.24%, 4.57%, 0.99%, 2.21%, 2.08%, and 1.61% (CI 95%) of the total mortality (correct for the non-accident) occurred in the year of study. The results of this study have a good compatibly with other studies conducted on the effects of air pollution on humans. The AirQ software model can be used in decision-makings as a useful and easy tool.