Short-term effects of ambient (outdoor) air pollution on cardiovascular death in Tehran, Iran – a time series study

Assessing the short-term effects of PM2.5 and O3 on cardiovascular mortality using high-resolution exposure: a time-stratified case cross-over study in Southwestern China

Air pollution is a major risk factor of cardiovascular disease (CVD). To date, limited studies have estimated the effects of ambient air pollution on CVD mortality using high-resolution exposure assessment, which might fail to capture the spatial variation in exposure and introduce bias in results. Besides, the three-year action plan (TYAP, 2018-2020) was released; thus, the constitution and health effect of air pollutants may have changed. In this study, we estimated the short-term effect exposed to particulate matters with parameter less than 2.5 µm (PM2.5) and ozone (O3) with 0.05° × 0.05° resolution on CVD mortality and measured the influence of TYAP in the associations. We used random forest models with spatial weight matrices to attain high-resolution pollutant concentrations and conditional Poisson regression to assess the relationship between air pollution and cardiovascular mortality. With an increase of 10 µg/m3 in PM2.5 and O3 during 2018-2021 in the Sichuan Basin (SCB), CVD mortality increased 1.0134 (95% CI 1.0102, 1.0166) and 1.0083 (95% CI 1.0060, 1.0107), respectively, using high-resolution air pollutant concentration, comparing to 1.0070 (95% CI 1.0052, 1.0087) and 1.0057 (95% CI 1.0037, 1.0078) using data from air quality monitoring stations (AQMs). After TYAP, the relative risk (RR) due to PM2.5 rose up to 1.0149 (95% CI 1.0054, 1.0243), and the RR due to O3 rose up to 1.0089 (95% CI 1.0030, 1.0148) in Sichuan Province. We found significantly positive association of cardiovascular mortality and air pollution in Sichuan Province. And using high-resolution exposure would be more accurate to estimate the effect of air pollution on CVD. After TYAP, the cardiovascular mortality risk estimation due to PM2.5 decreased in elderly in SCB, and the risk due to O3 increased in Sichuan Province.

A quantitative assessment of natural and anthropogenic effects on the occurrence of high air pollution loading in Dhaka and neighboring cities and health consequences

Although existing studies mainly focused on the air quality status in Bangladesh, quantifying the natural and manmade effects, the frequency of high pollution levels, and the associated health risks remained beyond detailed investigation. Air quality and meteorological data from the Department of Environment for 2012-2019 were analyzed, attempting to answer those questions. Cluster analysis of PM2.5, PM10, and gaseous pollutants implied that Dhaka and neighboring cities, Narayangonj and Gazipur, are from similar sources compared to the other major cities in the country. Apart from the transboundary sources, land use types and climate parameters unevenly affected local pollution loadings across city domains. The particulate concentrations persistently remained above the national standard for almost half the year, with the peaks during the dry months. Even though nitrogen oxides remained high in all three cities, other gaseous pollutants, such as CO and O3, except SO2, showed elevated concentrations solely in Dhaka city. Concentrations of gaseous pollutants in Dhaka vary spatially, but no statistical differences could be discerned between the working days and holidays. Frequency analysis results and hazard quotients revealed the likelihood of adverse health outcomes in Narayangonj ensuing from particulate exposures surpasses the other cities for different age, gender, and occupation groups. Nonetheless, school-aged children and construction workers were most at risk from chronic exposure to gaseous pollutants mostly in Dhaka. One limitation of this study was that the routine air quality monitoring happens just from five sites, making the evidence-based study concerning health outcomes quite challenging.

Air Pollution and Hospital Admission for Epilepsy in Kerman, Iran

Background: This study aimed to investigate the relation between air pollution and epilepsy admissions in Kerman, Iran. Methods: In this ecological study, the concentrations of ambient air pollutants and meteorological data were obtained from Kerman Environmental Protection Agency and Kerman Meteorology Organization, respectively. Additionally, epilepsy admission data were obtained from Kerman’s Shafa hospital epilepsy registry. Generalized additive models with lags up to 7 days were used to estimate rate ratios (RRs). Results: Within 2008 to 2020, 894 epilepsy admissions occurred in Kerman, 498 cases (55.7%) of whom were male. The strongest relations of epilepsy admission were observed in the over 59-year group for carbon monoxide (CO) in lag 0 (RR = 2.1455, 95% CI: 1.5823 - 2.9091), nitrogen dioxide (NO2) in lag 0 (RR = 1.0409, 95% CI: 1.0282 - 1.0537), and particulate matter under 2.5 microns (PM2.5) in lag 5 (RR = 1.0157, 95% CI: 1.0062 - 1.0252). There were also significant associations for particulate matter under 10 microns (PM10) in the under 18-year group in lag 2 (RR = 1.0064, 95% CI: 1.0029 - 1.0098), ozone in lag 0 (RR = 0.9671, 95% CI: 0.9581 - 0.9761), and sulfur dioxide in lag 5 (RR = 0.9937, 95% CI: 0.9891 - 0.9983). Conclusions: Exposure to CO, NO2, PM2.5, or PM10 air pollutants might be a risk factor for epilepsy admissions in Kerman. Epilepsy patients should better stay away from exposure to polluted air. Staying at home on polluted days or residing in areas with less air pollution might be an option.

A Review of Studies Using Air Q Software for Prediction of Air Pollution Health Effects in Iran

PURPOSE OF REVIEW

Exposure to air pollutants may lead to various health effects and is a major public health issue. Concerns about these effects exist in both developed and developing countries. The Air Q software was developed to estimate the health impacts of air pollution based on reported levels of air pollutants in real world studies. In Iran several studies have been conducted to estimate human morbidity and mortality based on this software. We conducted this review to summarize articles which have predicted the effects of air pollution on human health in Iran using Air Q. We conducted a systematic search for relevant studies published until 24 April 2021 in Web of Science, PubMed, Scopus, and SID (Scientific Information Database which includes articles in Farsi language). We applied no time or language restrictions.

RECENT FINDINGS

A total of 44 studies out of 525 identified articles met our inclusion criteria. The main air pollutants under investigation were particulate matter (PM), NO₂, O₃, and SO₂. Most studies were conducted in metropolitan areas, such as Ahvaz (9 studies), Tehran (9 studies), and Shiraz (7 studies). In all studies, the levels of most air pollutants were higher than the 2005 WHO guideline levels and were predicted to be related to considerable health effects. However, it was not possible to aggregate the results and report the total number of casualties during these years, because studies were done in different cities with fluctuating levels of multiple pollutants and in different years and time frames. This systematic review showed that air pollution remains at unacceptably high levels resulting in substantial detrimental health effects in various Iranian cities. Using clean renewable energies, increasing human capital, and increasing green spaces and vegetation can help improve air pollution and decrease human casualties in Iran.

Forecasts of cardiac and respiratory mortality in Tehran, Iran, using ARIMAX and CNN-LSTM models

Cardiovascular diseases belong to the leading causes of disability and premature death worldwide, including in Iran. It is predicted that the burden of the disease in Iran in 2025 will be more than doubled compared to 2005. Therefore, many forecasting models have been used to predict disease progression, estimate mortality rates, and assess risk factors. Our study focused on two time series prediction on models: autoregressive integrated moving average with exogenous variable (ARIMAX) and Convolutional neural network-long short-term memory network (CNN-LSTM). ARIMAX (6,1,6) had the best MSE of 0.655 among time series regression models. The prediction of this model shows a significant association in lag 4 and lag 6. Nitrogen dioxide (NO₂) was also significant in lag 6, while CNN-LSTM had a much better MSE of 0.21. For the time series analysis and forecasts studied in this paper, deep learning models provided more accurate results than classical methods such as ARIMAX.

Effects of ambient air pollutants on hospital admissions and deaths for cardiovascular diseases: a time series analysis in Tehran

Short-term exposures to air pollution have been associated with various adverse health effects. In this study, we investigated the associations between ambient air pollutants with the number of hospital admissions and mortality from cardiovascular diseases (CVDs). This time series study was conducted in Tehran for the years 2014-2017 (1220 day). We collected the ambient air pollutant concentration data from the regulatory monitoring stations. The health data were obtained from the Ministry of Health and Medical Education. A distributed lag non-linear model (DLNM) was used for the analyses. Total CVDs and ischemic heart disease (IHD) admissions were associated with CO for each 1 mg/m³ increase at lags of 6 and 7 days. Also, there was a positive association between total CVDs (RR 1.01; 1.001 to 1.03), IHD (RR 1.04; 1.006 to 1.07), and cerebrovascular diseases (RR 1.03; 1.005 to 1.07) mortality with SO₂ at a lag of 4 days. PM_2.5 and PM₁₀ were associated with cerebrovascular disease admissions in females aged 16-65 years and 16 years and younger for each 10 µg/m³ increase, respectively. Short-term exposure to SO₂, NO₂, and CO was associated with hospital admissions and mortality for CVDs, IHD, cerebrovascular diseases, and other cardiovascular diseases at different lags. Moreover, females were more affected by ambient air pollutants than males in terms of their burden of CVDs. Therefore, identifying the likely harmful effects of pollutants given their current concentrations requires the planning and implementation of strategies to reduce air pollution.

Ambient air pollution and multiple sclerosis: a systematic review

OBJECTIVES

Some studies have shown that environmental risk factors, including air pollution, might be related to the incidence or recurrence of multiple sclerosis (MS). This systematic review was conducted to investigate the relation between air pollution and MS.

METHODS

A systematic search was conducted in PubMed, Scopus, Science Direct, Embase, and Web of Science; until January 2020 with no restrictions. The search strategy was conducted with air pollution key words such as CO, PM_2.5, PM₁₀, SO₂, and NO₂, for exposure and the key word "Multiple sclerosis" as the outcome.

RESULTS

Eventually, after applying the inclusion and exclusion criteria, 17 articles were included. The methodologies and outcomes reported were heterogeneous and different metrics had been used in the results; therefore conducting a meta-analysis was not possible. Eight studies had analyzed the relation between particulate matter (PM) and the prevalence or relapse of MS and had observed a significant relation. NO₂ and NOx were associated with recurrence or prevalence of MS in three studies. But, in three cohort studies, no association was observed between air pollution and recurrence or occurrence of MS.

CONCLUSIONS

The results of this systematic review show that outdoor air pollution, especially PM and nitrogen oxides might be related to the prevalence or relapse of MS.

Short-term exposure to nitrogen dioxide and mortality: A systematic review and meta-analysis

BACKGROUND

Ambient air pollution has been characterized as a leading cause of mortality worldwide and has been associated with cardiovascular and respiratory diseases. There is increasing evidence that short-term exposure to nitrogen dioxide (NO₂), is related to adverse health effects and mortality.

METHODS

We conducted a systematic review of short-term NO₂ and daily mortality, which were indexed in PubMed and Embase up to June 2021. We calculated random-effects estimates by different continents and globally, and tested for heterogeneity and publication bias.

RESULTS

We included 87 articles in our quantitative analysis. NO₂ and all-cause as well as cause-specific mortality were positively associated in the main analysis. For all-cause mortality, a 10 ppb increase in NO₂ was associated with a 1.58% (95%CI 1.28%-1.88%, I² = 96.3%, Eggers' test p < 0.01, N = 57) increase in the risk of death. For cause-specific mortality, a 10 ppb increase in NO₂ was associated with a 1.72% (95%CI 1.41%-2.04%, I² = 87.4%, Eggers' test p < 0.01, N = 42) increase in cardiovascular mortality and a 2.05% (95%CI 1.52%-2.59%, I² = 78.5%, Eggers' test p < 0.01, N = 38) increase in respiratory mortality. In the sensitivity analysis, the meta-estimates for all-cause mortality, cardiovascular and respiratory mortality were nearly identical. The heterogeneity would decline to varying degrees through regional and study-design stratification.

CONCLUSIONS

This study provides evidence of an association between short-term exposure to NO₂, a proxy for traffic-sourced air pollutants, and all-cause, cardiovascular and respiratory mortality.

Relationship between ambient black carbon and daily mortality in Tehran, Iran: a distributed lag nonlinear time series analysis

PURPOSE

The aim of the present study was to investigate the effect of short-term exposure to ambient black carbon (BC) on daily cause-specific mortality, including mortality due to respiratory, cardiovascular, ischemic heart and cerebrovascular diseases in Tehran, Iran.

MATERIALS AND METHODS

Daily non-accidental death counts, meteorological data and hourly concentrations of air pollutants from 2014 to 2017 were collected in Tehran. A distributed lag non-linear model was used to assess the association between exposure to BC and daily mortality.

RESULTS

The mean daily BC concentration during the study period was 3.96 ± 1.19 µg/m³. The results indicated that BC was significantly associated with cardiovascular, ischemic heart disease, and cerebrovascular mortality, but not with respiratory mortality. In first model, each 10 µg/m³ increase in at lag 3, lag 4 and lag 5 were associated with cardiovascular mortality in 16-65 year age group with the relative risks (RRs) of 1.17 (95 % CI: 1.02-1.33), 1.17 (95 % CI: 1.04-1.31) and 1.12 (95 % CI: 1.02-1.24), respectively. The highest mortality rate per 10 µg/m³ increase in exposure was found for ischemic heart diseases with RR of 3.98 (95 % CI: 1.04-1.81, lag 01) for 16-65 age group. Cerebrovascular mortality was associated with 10 µg/m³ increases in non-cumulative exposure with RR of 1.17 (95 % 1.009-1.35, lag 5) in the age group ≥ 65 years. In the second model for a 10 µg/m³ increase in BC, cardiovascular mortality at specific lag days (5 and 6 days) in the age group ≤ 16 years were associated with RR of 1.34 (95 % CI 1.08-1.66) and 1.35(95 % CI 1.02-1.77), respectively.

CONCLUSIONS

This study in Tehran found significant effects of BC exposure on daily mortality for cardiovascular, ischemic heart disease, cerebrovascular disease.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s40201-021-00659-0.