Air quality in Tehran, Iran : evaluating acute health effects and modeling the long-term spatial variability

The burden of disease due to air pollution can be very large because of its acute and chronic effects. This dissertation focused on these two key challenges in the megacity of Tehran, Iran. First, it assessed short-term exposure to ambient air pollutants and their association with daily mortality. Second, it assessed long-term exposures for different air pollutants, which is a prerequisite for the investigation of their chronic health effects. The first part found that the effect of air pollutants on mortality was immediate, and that it increased steadily over a period of weeks. The second part found that concentrations of various air pollutants were very high in Tehran, comparable with those reported for other megacities in Asia. Further, spatial land-use regression (LUR) models were developed for multiple pollutants, and showed that the city center was the most polluted area. Even so, more than 80% of Tehran had benzene concentrations above air quality standard of 5 µg/m3 set by European Union and Iranian Government. The thesis also included a systematic review of the global literature on LUR models for volatile organic compounds and found that the study in Tehran has been the largest to assess all BTEX (benzene, toluene, ethylbenzene, and xylenes) species in a megacity. The methods and models developed for this PhD dissertation opened up new avenues for the next generation of air pollution monitoring, modelling, and epidemiology in Iran

Air pollution, environmental chemicals, and smoking may trigger vitamin D deficiency: Evidence and potential mechanisms

Beyond vitamin D (VD) effect on bone homeostasis, numerous physiological functions in human health have been described for this versatile prohormone. In 2016, 95% of the world's population lived in areas where annual mean ambient particulate matter (<2.5 μm) levels exceeded the World Health Organization guideline value (Shaddick et al., 2018). On the other hand, industries disperse thousands of chemicals continually into the environment. Further, considerable fraction of populations are exposed to tobacco smoke. All of these may disrupt biochemical pathways and cause detrimental consequences, such as VD deficiency (VDD). In spite of the remarkable number of studies conducted on the role of some of the above mentioned exposures on VDD, the literature suffers from two main shortcomings: (1) an overview of the impacts of environmental exposures on the levels of main VD metabolites, and (2) credible engaged mechanisms in VDD because of those exposures. To summarize explanations for these unclear topics, we conducted the present review, using relevant keywords in the PubMed database, to investigate the adverse effects of exposure to air pollution, some environmental chemicals, and smoking on the VD metabolism, and incorporate relevant potential pathways disrupting VD endocrine system (VDES) leading to VDD. Air pollution may lead to the reduction of VD cutaneous production either directly by blocking ultraviolet B photons or indirectly by decreasing outdoor activity. Heavy metals may reduce VD serum levels by increasing renal tubular dysfunction, as well as downregulating the transcription of cytochrome P450 mixed-function oxidases (CYPs). Endocrine-disrupting chemicals (EDCs) may inhibit the activity and expression of CYPs, and indirectly cause VDD through weight gain and dysregulation of thyroid hormone, parathyroid hormone, and calcium homeostasis. Smoking through several pathways decreases serum 25(OH)D and 1,25(OH)2D levels, VD intake from diet, and the cutaneous production of VD through skin aging. In summary, disturbance in the cutaneous production of cholecalciferol, decreased intestinal intake of VD, the modulation of genes involved in VD homeostasis, and decreased local production of calcitriol in target tissues are the most likely mechanisms that involve in decreasing the serum VD levels

Long-term exposure to air pollution and stroke incidence:A Danish Nurse cohort study

Ambient air pollution has been linked to stroke, but few studies have examined in detail stroke subtypes and confounding by road traffic noise, which was recently associated with stroke. Here we examined the association between long-term exposure to air pollution and incidence of stroke (overall, ischemic, hemorrhagic), adjusting for road traffic noise. In a nationwide Danish Nurse Cohort consisting of 23,423 nurses, recruited in 1993 or 1999, we identified 1,078 incident cases of stroke (944 ischemic and 134 hemorrhagic) up to December 31, 2014, defined as first-ever hospital contact. The full residential address histories since 1970 were obtained for each participant and the annual means of air pollutants (particulate matter with diameter < 2.5 μm and < 10 μm (PM2.5 and PM10), nitrogen dioxide (NO2), nitrogen oxides (NOx)) and road traffic noise were determined using validated models. Time-varying Cox regression models were used to estimate hazard ratios (HR) (95% confidence intervals (CI)) for the associations of one-, three, and 23-year running mean of air pollutants with stroke adjusting for potential confounders and noise. In fully adjusted models, the HRs (95% CI) per interquartile range increase in one-year running mean of PM2.5 and overall, ischemic, and hemorrhagic stroke were 1.12 (1.01–1.25), 1.13 (1.01–1.26), and 1.07 (0.80–1.44), respectively, and remained unchanged after adjustment for noise. Long-term exposure to ambient PM2.5 was associated with the risk of stroke independent of road traffic noise

Short-term associations between daily mortality and ambient particulate matter, nitrogen dioxide, and the air quality index in a Middle Eastern megacity.

There is limited evidence for short-term association between mortality and ambient air pollution in the Middle East and no study has evaluated exposure windows of about a month prior to death. We investigated all-cause non-accidental daily mortality and its association with fine particulate matter (PM2.5), nitrogen dioxide (NO2), and the Air Quality Index (AQI) from March 2011 through March 2014 in the megacity of Tehran, Iran. Generalized additive quasi-Poisson models were used within a distributed lag linear modeling framework to estimate the cumulative effects of PM2.5, NO2, and the AQI up to a lag of 45 days. We further conducted multi-pollutant models and also stratified the analyses by sex, age group, and season. The relative risk (95% confidence interval (CI)) for all seasons, both sexes and all ages at lag 0 for PM2.5, NO2, and AQI were 1.004 (1.001, 1.007), 1.003 (0.999, 1.007), and 1.004 (1.001, 1.007), respectively, per inter-quartile range (IQR) increment (18.8??g/m3 for PM2.5, 12.6?ppb for NO2, and 31.5 for AQI). In multi-pollutant models, the PM2.5 associations were almost independent from NO2. However, the RRs for NO2 were slightly attenuated after adjustment for PM2.5 but they were still largely independent from PM2.5. The cumulative relative risks (95% CI) per IQR increment reached maximum during the cooler months, including: 1.13 (1.06, 1.20) for PM2.5 at lag 0-31 (for females, all ages); 1.17 (1.10, 1.25) for NO2 at lag 0-45 (for males, all ages); and 1.13 (1.07, 1.20) for the AQI at lag 0-30 (for females, all ages). Generally, the RRs were slightly larger for NO2 than PM2.5 and AQI. We found somewhat larger RRs in females, age group >65 years of age, and in cooler months. In summary, positive associations were found in most models. This is the first study to report short-term associations between all-cause non-accidental mortality and ambient PM2.5 and NO2 in Iran

Long-term exposure to ambient fine particulate components and leukocyte epigenome-wide DNA Methylation in older men: the Normative Aging Study

Background Epigenome-wide association studies of ambient fine particulate matter (PM2.5) have been reported. However, few have examined PM2.5 components (PMCs) and sources or included repeated measures. The lack of high-resolution exposure measurements is the key limitation. We hypothesized that significant changes in DNA methylation might vary by PMCs and the sources. Methods We predicted the annual average of 14 PMCs using novel high-resolution exposure models across the contiguous U.S., between 2000–2018. The resolution was 50 m × 50 m in the Greater Boston Area. We also identified PM2.5 sources using positive matrix factorization. We repeatedly collected blood samples and measured leukocyte DNAm with the Illumina HumanMethylation450K BeadChip in the Normative Aging Study. We then used median regression with subject-specific intercepts to estimate the associations between long-term (one-year) exposure to PMCs / PM2.5 sources and DNA methylation at individual cytosine-phosphate-guanine CpG sites. Significant probes were identified by the number of independent degrees of freedom approach, using the number of principal components explaining > 95% of the variation of the DNA methylation data. We also performed regional and pathway analyses to identify significant regions and pathways. Results We included 669 men with 1,178 visits between 2000–2013. The subjects had a mean age of 75 years. The identified probes, regions, and pathways varied by PMCs and their sources. For example, iron was associated with 6 probes and 6 regions, whereas nitrate was associated with 15 probes and 3 regions. The identified pathways from biomass burning, coal burning, and heavy fuel oil combustion sources were associated with cancer, inflammation, and cardiovascular diseases, whereas there were no pathways associated with all traffic. Conclusions Our findings showed that the effects of PM2.5 on DNAm varied by its PMCs and sources

Harnessing AI to unmask Copenhagen's invisible air pollutants: A study on three ultrafine particle metrics

Ultrafine particles (UFPs) are airborne particles with a diameter of less than 100 nm. They are emitted from various sources, such as traffic, combustion, and industrial processes, and can have adverse effects on human health. Long-term mean ambient average particle size (APS) in the UFP range varies over space within cities, with locations near UFP sources having typically smaller APS. Spatial models for lung deposited surface area (LDSA) within urban areas are limited and currently there is no model for APS in any European city. We collected particle number concentration (PNC), LDSA, and APS data over one-year monitoring campaign from May 2021 to May 2022 across 27 locations and estimated annual mean in Copenhagen, Denmark, and obtained additionally annual mean PNC data from 6 state-owned continuous monitors. We developed 94 predictor variables, and machine learning models (random forest and bagged tree) were developed for PNC, LDSA, and APS. The annual mean PNC, LDSA, and APS were, respectively, 5523 pt/cm 3, 12.0 μm 2/cm 3, and 46.1 nm. The final R 2 values by random forest (RF) model were 0.93 for PNC, 0.88 for LDSA, and 0.85 for APS. The 10-fold, repeated 10-times cross-validation R 2 values were 0.65, 0.67, and 0.60 for PNC, LDSA, and APS, respectively. The root mean square error for final RF models were 296 pt/cm 3, 0.48 μm 2/cm 3, and 1.60 nm for PNC, LDSA, and APS, respectively. Traffic-related variables, such as length of major roads within buffers 100-150 m and distance to streets with various speed limits were amongst the highly-ranked predictors for our models. Overall, our ML models achieved high R 2 values and low errors, providing insights into UFP exposure in a European city where average PNC is quite low. These hyperlocal predictions can be used to study health effects of UFPs in the Danish Capital

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015

Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defi ned criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specifi c DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI).Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defi ned criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specifi c DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI)

Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990-2015 : a systematic analysis for the Global Burden of Disease Study 2015

Background Non-fatal outcomes of disease and injury increasingly detract from the ability of the world's population to live in full health, a trend largely attributable to an epidemiological transition in many countries from causes affecting children, to non-communicable diseases (NCDs) more common in adults. For the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015), we estimated the incidence, prevalence, and years lived with disability for diseases and injuries at the global, regional, and national scale over the period of 1990 to 2015. Methods We estimated incidence and prevalence by age, sex, cause, year, and geography with a wide range of updated and standardised analytical procedures. Improvements from GBD 2013 included the addition of new data sources, updates to literature reviews for 85 causes, and the identification and inclusion of additional studies published up to November, 2015, to expand the database used for estimation of non-fatal outcomes to 60 900 unique data sources. Prevalence and incidence by cause and sequelae were determined with DisMod-MR 2.1, an improved version of the DisMod-MR Bayesian meta-regression tool first developed for GBD 2010 and GBD 2013. For some causes, we used alternative modelling strategies where the complexity of the disease was not suited to DisMod-MR 2.1 or where incidence and prevalence needed to be determined from other data. For GBD 2015 we created a summary indicator that combines measures of income per capita, educational attainment, and fertility (the Socio-demographic Index [SDI]) and used it to compare observed patterns of health loss to the expected pattern for countries or locations with similar SDI scores. Findings We generated 9.3 billion estimates from the various combinations of prevalence, incidence, and YLDs for causes, sequelae, and impairments by age, sex, geography, and year. In 2015, two causes had acute incidences in excess of 1 billion: upper respiratory infections (17.2 billion, 95% uncertainty interval [UI] 15.4-19.2 billion) and diarrhoeal diseases (2.39 billion, 2.30-2.50 billion). Eight causes of chronic disease and injury each affected more than 10% of the world's population in 2015: permanent caries, tension-type headache, iron-deficiency anaemia, age-related and other hearing loss, migraine, genital herpes, refraction and accommodation disorders, and ascariasis. The impairment that affected the greatest number of people in 2015 was anaemia, with 2.36 billion (2.35-2.37 billion) individuals affected. The second and third leading impairments by number of individuals affected were hearing loss and vision loss, respectively. Between 2005 and 2015, there was little change in the leading causes of years lived with disability (YLDs) on a global basis. NCDs accounted for 18 of the leading 20 causes of age-standardised YLDs on a global scale. Where rates were decreasing, the rate of decrease for YLDs was slower than that of years of life lost (YLLs) for nearly every cause included in our analysis. For low SDI geographies, Group 1 causes typically accounted for 20-30% of total disability, largely attributable to nutritional deficiencies, malaria, neglected tropical diseases, HIV/AIDS, and tuberculosis. Lower back and neck pain was the leading global cause of disability in 2015 in most countries. The leading cause was sense organ disorders in 22 countries in Asia and Africa and one in central Latin America; diabetes in four countries in Oceania; HIV/AIDS in three southern sub-Saharan African countries; collective violence and legal intervention in two north African and Middle Eastern countries; iron-deficiency anaemia in Somalia and Venezuela; depression in Uganda; onchoceriasis in Liberia; and other neglected tropical diseases in the Democratic Republic of the Congo. Interpretation Ageing of the world's population is increasing the number of people living with sequelae of diseases and injuries. Shifts in the epidemiological profile driven by socioeconomic change also contribute to the continued increase in years lived with disability (YLDs) as well as the rate of increase in YLDs. Despite limitations imposed by gaps in data availability and the variable quality of the data available, the standardised and comprehensive approach of the GBD study provides opportunities to examine broad trends, compare those trends between countries or subnational geographies, benchmark against locations at similar stages of development, and gauge the strength or weakness of the estimates available. Copyright (C) The Author(s). Published by Elsevier Ltd.Peer reviewe

Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990-2015:a systematic analysis for the Global Burden of Disease Study 2015

Background Healthy life expectancy (HALE) and disability-adjusted life-years (DALYs) provide summary measures of health across geographies and time that can inform assessments of epidemiological patterns and health system performance, help to prioritise investments in research and development, and monitor progress toward the Sustainable Development Goals (SDGs). We aimed to provide updated HALE and DALYs for geographies worldwide and evaluate how disease burden changes with development. Methods We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) for all-cause mortality, cause-specifi c mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2015. We calculated DALYs by summing years of life lost (YLLs) and years of life lived with disability (YLDs) for each geography, age group, sex, and year. We estimated HALE using the Sullivan method, which draws from age-specifi c death rates and YLDs per capita. We then assessed how observed levels of DALYs and HALE differed from expected trends calculated with the Socio-demographic Index (SDI), a composite indicator constructed from measures of income per capita, average years of schooling, and total fertility rate. Findings Total global DALYs remained largely unchanged from 1990 to 2015, with decreases in communicable, neonatal, maternal, and nutritional (Group 1) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). Much of this epidemiological transition was caused by changes in population growth and ageing, but it was accelerated by widespread improvements in SDI that also correlated strongly with the increasing importance of NCDs. Both total DALYs and age-standardised DALY rates due to most Group 1 causes significantly decreased by 2015, and although total burden climbed for the majority of NCDs, age-standardised DALY rates due to NCDs declined. Nonetheless, age-standardised DALY rates due to several high-burden NCDs (including osteoarthritis, drug use disorders, depression, diabetes, congenital birth defects, and skin, oral, and sense organ diseases) either increased or remained unchanged, leading to increases in their relative ranking in many geographies. From 2005 to 2015, HALE at birth increased by an average of 2·9 years (95% uncertainty interval 2·9–3·0) for men and 3·5 years (3·4–3·7) for women, while HALE at age 65 years improved by 0·85 years (0·78–0·92) and 1·2 years (1·1–1·3), respectively. Rising SDI was associated with consistently higher HALE and a somewhat smaller proportion of life spent with functional health loss; however, rising SDI was related to increases in total disability. Many countries and territories in central America and eastern sub-Saharan Africa had increasingly lower rates of disease burden than expected given their SDI. At the same time, a subset of geographies recorded a growing gap between observed and expected levels of DALYs, a trend driven mainly by rising burden due to war, interpersonal violence, and various NCDs. Interpretation Health is improving globally, but this means more populations are spending more time with functional health loss, an absolute expansion of morbidity. The proportion of life spent in ill health decreases somewhat with increasing SDI, a relative compression of morbidity, which supports continued eff orts to elevate personal income, improve education, and limit fertility. Our analysis of DALYs and HALE and their relationship to SDI represents a robust framework on which to benchmark geography-specifi c health performance and SDG progress. Countryspecific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform financial and research investments, prevention efforts, health policies, and health system improvement initiatives for all countries along the development continuum.</p