Fires as a source of annual ambient PM2.5 exposure and chronic health impacts in Europe

Chronic exposure to ambient PM2.5 is the largest environmental health risk in Europe. We used a chemical transport model and recent exposure response functions to simulate ambient PM2.5, contribution from fires and related health impacts over Europe from 1990 to 2019. Our estimation indicates that the excess death burden from exposure to ambient PM2.5 declined across Europe at a rate of 10,000 deaths per year, from 0.57 million (95 % confidence intervals: 0.44-0.75 million) in 1990 to 0.28 million (0.19-0.42 million) in the specified period. Among these excess deaths, approximately 99 % were among adults, while only around 1 % occurred among children. Our findings reveal a steady increase in fire mortality fractions (excess deaths from fires per 1000 deaths from ambient PM2.5) from 2 in 1990 to 13 in 2019. Notably, countries in Eastern Europe exhibited significantly higher fire mortality fractions and experienced more pronounced increases compared to those in Western and Central Europe. We performed sensitivity analyses by considering fire PM2.5 to be more toxic as compared to other sources, as indicated by recent studies. By considering fire PM2.5 to be more toxic than other PM2.5 sources results in an increased relative contribution of fires to excess deaths, reaching 2.5-13 % in 2019. Our results indicate the requirement of larger mitigation and adaptation efforts and more sustainable forest management policies to avert the rising health burden from fires.

Association of ambient PM2.5 concentration with tuberculosis reactivation diseases-an integrated spatio-temporal analysis

Objectives

While the plausible role of ambient particulate matter (PM)2.5 exposure in tuberculosis (TB) reactivation has been inferred from in vitro experiments, epidemiologic evidence is lacking. We examined the relationship between ambient PM2.5 concentration and pulmonary TB (PTB) in an intermediate TB endemicity city dominated by reactivation diseases.

Methods

Spatio-temporal analyses were performed on TB notification data and satellite-based annual mean PM2.5 concentration in Hong Kong. A total of 52,623 PTB cases from 2005-2018 were mapped to over 400 subdistrict units. PTB standardized notification ratio by population subgroups (elderly aged ≥65, middle-aged 50-64, and young adults aged 15-49) was calculated and correlated with ambient PM2.5 concentration.

Results

Significant associations were detected between high ambient PM2.5 concentration and increased PTB among the elderly. Such associations were stable to the adjustment for socio-economic factors and other criteria pollutants. Unstable patterns of association between PM2.5 and PTB risk were observed in the middle-aged population and young adults, for which the observed associations were confounded by other criteria pollutants.

Conclusion

With elderly PTB almost exclusively attributable to reactivation, our findings suggested that increased TB reactivations have occurred in association with high ambient PM2.5 exposure, lending support to preventive measures that minimize PM2.5-related TB reactivation.

Life-course exposure to ambient fine particulate matter and hypertension in adulthood: a longitudinal cohort study

PM_2.5-hypertension association were well documented in adults, while the effects of life-course exposure to PM_2.5 on adulthood hypertension remained unclear. This study aimed to investigate the associations between life-course exposure to ambient PM_2.5 and incident hypertension in adulthood in Asia. We included 4272 participants with 17,814 medical visits from two open cohorts in Taiwan and Hong Kong between 2000 and 2018. We used a satellite-based model to assess 2-year average PM_2.5 exposure at a resolution of 1 km². A linear mixed model was used to examine the association with blood pressure. A Cox regression model with time-dependent covariates was used to examine the overall association with the development of hypertension in adulthood. Life-course mixed models were used to examine the effects of PM_2.5 exposure at different life stages on blood pressure and hypertension. For every 10 μg/m³ increase in PM_2.5, the overall risk of adulthood hypertension increased by 40% (95% confidence interval [CI] 8-80%). The health effects of PM_2.5 exposure at different life-stages on incident hypertension were generally independent of each other. In critical model, the risk of developing hypertension increased 23%, 27%, and 55% for each 10 μg/m³ increase in PM_2.5 exposure during school age, adolescence, and adulthood, respectively. Similar associations were found between life-course PM_2.5 exposure and blood pressure. Association between PM_2.5 and adulthood hypertension can be traced back to childhood. Our study suggests that life-course control of air pollution exposure should be implemented to alleviate the huge burden of adulthood hypertension.

The global burden of disease attributable to ambient fine particulate matter in 204 countries and territories, 1990-2019: A systematic analysis of the Global Burden of Disease Study 2019

Understanding the spatio-temporal patterns of the disease burden attributable to ambient PM2.5 across the world is essential for the prevention of related diseases, as well as ambient PM2.5 control. Following the framework and methodology of the Global Burden of Disease Study (GBD) in 2019, the global, regional, and national data on ambient PM2.5-attributable death and disability-adjusted life years (DALYs), and the age-standardized rates of mortality (ASMR) and disability-adjusted life years (ASDR) were summarized based on age, gender, year, location and specific diseases. We calculated the average annual percentage change (AAPC) to depict the secular trends of ASMR and ASDR from 1990 to 2019. In 2019, the global ambient PM2.5-related deaths and DALYs were 4,140,970 and 118.2 million, respectively, with 1,702,150 deaths and 47.5 million DALYs for females and 2,438,820 deaths and 70.7 million DALYs for male. In the 13 level-three causes, ischemic heart disease, stroke, chronic obstructive and pulmonary disease (COPD) were the leading three causes of deaths and DALYs attributable to ambient PM2.5. The number of global deaths and DALYs attributable to ambient PM2.5 has increased by 102.3% and 67.7% from 1990 to 2019, respectively. However, ASMR and ASDR showed little change. In the 13 level-three diseases, ischemic heart disease, stroke, COPD, diabetes mellitus, and lung cancer were the top five contributors to the increase of global deaths or DALYs, among which diabetes mellitus had the fastest increase of ASMR and ASDR, with AAPC of 1.5 (95% CI: 1.43, 1.58) and 2.21 (95% CI: 2.15, 2.27), respectively. The population attributable fractions (PAF) of causes in ASMR or ASDR varied significantly across regions, of which PAF of COPD, stroke and lung cancer were the top three. Regarding the GBD region, high PAF mainly occurred in North Africa and Middle East, South Asia, and East Asia. The age-specific PAFs of ischemic heart disease and stroke deaths and DALYs due to ambient PM2.5 were negatively correlated with age. ASMR and ASDR of overall PM2.5 related-burden showed an inverted "V/U" relationship with the socio-demographic index (SDI). The AAPC of ASMR and ASDR of the overall causes showed a strong negative correlation with SDI in 2019, especially at the SDI larger than 0.5. The deaths and DALYs attributable to ambient PM2.5 continued to increase under the context of population growth and aging. Decision-makers should consider controlling the PM2.5 emission when developing the economy.

Frailty Risk in Older Adults Associated With Long-Term Exposure to Ambient PM2.5 in 6 Middle-Income Countries

BACKGROUND

A series of studies have explored the health effects of long-term exposure to ambient PM2.5 among older adults. However, few studies have investigated the adverse effect of long-term exposure to ambient PM2.5 on frailty, and the results are inconclusive. This study sought to investigate the associations between long-term exposure to ambient PM2.5 and frailty in 6 low- and middle-income countries.

METHODS

We included an analytical sample of 34 138 individuals aged 50 and older from the Study on global AGEing and adult health Wave 1 (2007/2010). Air pollution estimates were generated using a standard methodology derived from Moderate Resolution Imaging Spectroradiometer observations and Multiangle Imaging Spectroradiometer instruments from the Terra satellite, along with simulations from the GEOS-Chem chemical transport model. A 3-level hierarchical logistic model was used to evaluate the association between frailty index and long-term PM2.5 exposure at 3 levels (individual, province, and country).

RESULTS

In rural areas, each 10 μg/m3 increase in ambient PM2.5 was associated with a 30% increase in the odds of frailty (OR = 1.30, 95% CI: 1.21-1.39) after adjusting for various potential confounding factors. The gender-stratified analysis showed that the association seemed to be slightly stronger in men (OR = 1.31, 95% CI: 1.18-1.46) than in women (OR = 1.21, 95% CI: 1.07-1.36) in rural areas.

CONCLUSION

In a large sample of community-based older adults from 6 middle-income countries, we found evidence that long-term PM2.5 exposure was associated with frailty in rural areas.

Global burden of COPD attributable to ambient PM2.5 in 204 countries and territories, 1990 to 2019: A systematic analysis for the Global Burden of Disease Study 2019

The global spatiotemporal pattern of the COPD burden attributable to ambient PM2.5 is unknown in the context of the continuing increase in exposure to ambient PM2.5. Data on COPD burden attributable to ambient PM2.5 from 1990 to 2019 were retrieved from the Global Burden of Disease Study 2019. Cases and age-standardized rates of COPD mortality (ASMR) and disability-adjusted life years (ASDR) were estimated by age, sex, region, and country. The estimated annual percentage change (EAPC) was calculated to quantify the secular trends of ASMR and ASDR from 1990 to 2019. Globally, the number of COPD deaths and DALYs attributable to ambient PM2.5 both increased by over 90% from 1990 to 2019, but ASMR and ASDR both slightly decreased, with EAPC of -0.58 (95% CI: -0.72, -0.44) and -0.40 (95% CI: -0.51, -0.29), respectively. Most COPD deaths and DALYs attributable to PM2.5 occurred in the middle sociodemographic index (SDI) region, but the fastest growth of ASMR and ASDR occurred in the low SDI region, with EAPCs of 2.41 (95% CI: 2.23, 2.59) and 2.34 (95% CI: 2.16, 2.52), respectively. East Asia and South Asia were the high-risk areas of COPD deaths and DALYs attributable to PM2.5, among which China and India were the countries with the heaviest burden. COPD deaths and DALYs attributable to PM2.5 mainly occurred in individuals 70-89 years old and 60-84 years old, respectively. The age-specific rates of mortality and DALYs had a rapid increase in low and low-middle SDI regions from 1990 to 2019. The ASMR or ASDR had a reverse V-shaped relationship with SDI. In summary, the ambient PM2.5-attributable COPD burden is socioeconomic- and age-dependent, and it mediates the heterogeneity of spatial and temporal distribution. Low- and middle-income countries endure the highest ambient PM2.5-attributable COPD burden due to the high exposure to PM2.5 and poor availability and affordability of medicines and diagnostic tests.

Combined effects of chronic PM2.5 exposure and habitual exercise on cancer mortality: a longitudinal cohort study

BACKGROUND

Exercise may increase the inhalation and deposition of air pollutants, which may counteract its beneficial effects. We thus examined the combined effects of chronic exposure to fine particulate matter (PM2.5) and habitual exercise on the risk of death from cancer in Taiwan.

PATIENTS AND METHODS

A total of 384 128 adults (≥18 years of age) were recruited for a medical screening programme between 2001 and 2016, yielding 842 384 medical-examination records. All participants were followed up until 31 May 2019. Vital data were obtained from the National Death Registry of Taiwan and the ambient PM2.5 exposure was estimated using a satellite-based spatiotemporal model. Information on habitual exercise was collected using a standard self-administered questionnaire. The time-dependent Cox-regression model was used to evaluate the combined effects.

RESULTS

A greater amount of habitual exercise was associated with lower risk of death from cancer, whilst a higher level of PM2.5 exposure was associated with a higher risk of death from cancer. The inverse associations of habitual exercise with death from cancer were not modified by chronic exposure to PM2.5. The participants in the group with a high level of exercise and a low level of PM2.5 exposure exhibited a 35% lower risk of death from cancer than those in the group with a low level of exercise and a high level of PM2.5 exposure (95% confidence interval: 28%, 42%).

CONCLUSIONS

Increased levels of exercise and reduced exposure levels of PM2.5 are associated with a lower risk of death from cancer. Habitual exercise reduces the risk of death from cancer regardless of the levels of chronic PM2.5 exposure. Our results indicate that habitual exercise is a suitable health-promotion strategy even for people who reside in moderately polluted regions.

Global PM2.5-attributable health burden from 1990 to 2017: Estimates from the Global Burden of disease study 2017

BACKGROUND

Long-term exposure to ambient and household particulate matter (PM2.5) causes death and health loss, and both are the leading risk factor to global disease burden. We assessed spatiotemporal trends of ambient and household PM2.5 attributable burdens across various diseases at the global, regional, and national levels from 1990 to 2017.

METHODS

Data on PM2.5-attributable disease burdens were extracted from the Global Burden of Disease (GBD) study 2017. Numbers and age-standardized rates (ASRs) of deaths, disability-adjusted life years (DALYs) and corresponding estimated annual percentage change (EAPC) were estimated by disease, age, sex, Socio-demographic Index (SDI), locations.

RESULTS

Exposure to PM2.5 contributed to 4.58 million deaths and 142.52 million DALYs globally in 2017, among which ambient PM2.5 contributed to 64.2% deaths and 58.3% DALYs. ASRs of deaths and DALYs in 2017 decreased to 59.62/10⁵ persons with an EAPC of -2.15 (95% CI: 2.21 to -2.09) and 1856.61/10⁵ persons with an EAPC of -2.58 (95% CI: 2.64 to -2.51), respectively compared to those in 1990. Ambient PM2.5-attributable Non-communicable diseases (NCDs) have dominated major concern in middle and low SDI countries especially in South Asia and East Asia, while household PM2.5-attributable lower respiratory infections (LRIs) still caused the largest burden in low SDI countries in Africa and Asia. Those under 5 and over 70 years old had the largest burdens in PM2.5 attributable LRI and NCDs, respectively.

CONCLUSION

In conclusion, ambient PM2.5-attributable NCDs have threatened public health in middle and low SDI countries, while household PM2.5-attributable LRI still caused the largest burden in low SDI countries. More positive strategies should be tailored to reduce PM2.5-attributable burdens considering specific settings globally.

Concentrations and mortality due to short- and long-term exposure to PM2.5 in a megacity of Iran (2014-2019)

The present study aimed to survey the spatial and temporal trends of ambient concentration of PM_2.5 and to estimate mortality attributed to short- and long-term exposure to PM_2.5 in Isfahan from March 2014 to March 2019 using the AirQ⁺ software. The hourly concentrations of PM_2.5 were obtained from the Isfahan Department of Environment and Isfahan Air Quality Monitoring Center. Then, the 24-h mean concentration of PM_2.5 for each station was calculated using the Excel software. According to the results, the annual mean concentration of PM_2.5 in 2014-2019 was 29.9-50.9 μg/m³, approximately 3-5 times higher than the WHO guideline (10 μg/m³). The data showed that people of Isfahan in almost 58% to 96% of the days of a year were exposed to PM_2.5 higher than the WHO daily guideline. The concentrations of PM_2.5 in cold months such as October, November, December and January were higher than those in the other months. The zoning of the annual concentrations of PM_2.5 in urban areas showed that the highest PM_2.5 concentrations were related to the northern, northwestern, southern and central areas of the city. On average, from 2014 to 2019, the number of deaths due to natural mortality, lung cancer (LC), chronic obstructive pulmonary disease (COPD), ischemic heart disease (IHD) and stroke associated with ambient PM_2.5 were 948, 16, 18, 281 and 60, respectively. The present study estimated that on average, 14.29% of the total mortality, 17.2% of lung cancer (LC), 15.54% of chronic obstructive pulmonary disease (COPD), 17.12% of ischemic heart disease (IHD) and 14.94% of stroke mortalities were related to long-term exposure to ambient PM_2.5. So provincial managers and politicians must adopt appropriate strategies to control air pollution and reduce the attributable health effects and economic losses.

Imputation methods for addressing missing data in short-term monitoring of air pollutants

Monitoring of environmental contaminants is a critical part of exposure sciences research and public health practice. Missing data are often encountered when performing short-term monitoring (<24 h) of air pollutants with real-time monitors, especially in resource-limited areas. Approaches for handling consecutive periods of missing and incomplete data in this context remain unclear. Our aim is to evaluate existing imputation methods for handling missing data for real-time monitors operating for short durations. In a current field-study, realtime PM2.5 monitors were placed outside of 20 households and ran for 24-hours. Missing data was simulated in these households at four consecutive periods of missingness (20%, 40%, 60%, 80%). Univariate (Mean, Median, Last Observation Carried Forward, Kalman Filter, Random, Markov) and multivariate time-series (Predictive Mean Matching, Row Mean Method) methods were used to impute missing concentrations, and performance was evaluated using five error metrics (Absolute Bias, Percent Absolute Error in Means, R2 Coefficient of Determination, Root Mean Square Error, Mean Absolute Error). Univariate methods of Markov, random, and mean imputations were the best performing methods that yielded 24-hour mean concentrations with the lowest error and highest R2 values across all levels of missingness. When evaluating error metrics minute-by-minute, Kalman filters, median, and Markov methods performed well at low levels of missingness (20-40%). However, at higher levels of missingness (60-80%), Markov, random, median, and mean imputation performed best on average. Multivariate methods were the worst performing imputation methods across all levels of missingness. Imputation using univariate methods may provide a reasonable solution to addressing missing data for short-term monitoring of air pollutants, especially in resource-limited areas. Further efforts are needed to evaluate imputation methods that are generalizable across a diverse range of study environments.

Pollution characteristics and chronic health risk assessment of metals and metalloids in ambient PM2.5 in Licheng District, Jinan, China

PM_2.5 samples were collected at the Wangsheren primary school site in Licheng District of Jinan, China, during 2016. Eleven metals and metalloids including Al, As, Be, Cd, Cr, Hg, Mn, Ni, Pb, Sb and Se in PM_2.5 were measured by inductively coupled plasma-mass spectroscopy. The annual average mass concentration of PM_2.5 was found to be 88.7 μg m^-3. The highest PM_2.5 concentrations were obtained during the heating seasons of winter and spring. The concentrations of metals and metalloids in PM_2.5 were in a descending order of Al, Pb, Mn, As, Se, Cr, Sb, Ni, Cd, Hg and Be. The enrichment factors showed that Pb, Mn, As, Se, Cr, Sb, Ni, Cd, Hg originated from anthropogenic sources. Factor analysis indicated that the main sources of the metals were coal combustion dust, soil dust, metallurgical industry, brake abrasion of vehicles and other mixed sources. Coal combustion dust was the primary source of metal pollution in PM_2.5. Non-carcinogenic risks associated with exposure through the respiratory system were between 6.30 × 10^-4 and 7.62 × 10^-1, which were lower than the safe limit (1). The carcinogenic risks of Cr, As and Cd were 3.17 × 10^-5, 1.52 × 10^-5, 2.22 × 10^-6, respectively, which were higher than the precautionary criterion (10^-6/year). This study indicates that the air pollution of PM_2.5 is of public health concern in Licheng District of Jinan, particularly related to potential carcinogenic metals of As, Cr and Cd. Intervention action is needed to reduce the emission sources of these elements, especially coal combustion in winter heating season.

BAYESIAN METHODS FOR MULTIPLE MEDIATORS: RELATING PRINCIPAL STRATIFICATION AND CAUSAL MEDIATION IN THE ANALYSIS OF POWER PLANT EMISSION CONTROLS

Emission control technologies installed on power plants are a key feature of many air pollution regulations in the US. While such regulations are predicated on the presumed relationships between emissions, ambient air pollution, and human health, many of these relationships have never been empirically verified. The goal of this paper is to develop new statistical methods to quantify these relationships. We frame this problem as one of mediation analysis to evaluate the extent to which the effect of a particular control technology on ambient pollution is mediated through causal effects on power plant emissions. Since power plants emit various compounds that contribute to ambient pollution, we develop new methods for multiple intermediate variables that are measured contemporaneously, may interact with one another, and may exhibit joint mediating effects. Specifically, we propose new methods leveraging two related frameworks for causal inference in the presence of mediating variables: principal stratification and causal mediation analysis. We define principal effects based on multiple mediators, and also introduce a new decomposition of the total effect of an intervention on ambient pollution into the natural direct effect and natural indirect effects for all combinations of mediators. Both approaches are anchored to the same observed-data models, which we specify with Bayesian nonparametric techniques. We provide assumptions for estimating principal causal effects, then augment these with an additional assumption required for causal mediation analysis. The two analyses, interpreted in tandem, provide the first empirical investigation of the presumed causal pathways that motivate important air quality regulatory policies.