Ambient Particulate Matter Pollution Research Articles

Exploring the contributions of major emission sources to PM2.5 and attributable health burdens in China

Ambient fine particulate matter (PM2.5) pollution is the principal environmental risk factor for health burdens in China. Identifying the sectoral contributions of pollutant emissions sources on multiple spatiotemporal scales can help in the formulation of specific strategies. In this study, we used sensitivity analysis to explore the specific contributions of seven major emission sources to ambient PM2.5 and attributable premature mortality across mainland China. In 2016, about 60% of China's population lived in areas with PM2.5 concentrations above the Chinese Ambient Air Quality Standard of 35 μg/m3. This percentage was expected to decrease to 35% and 39% if industrial and residential emissions were fully eliminated. In densely populated and highly polluted regions, residential sources contributed about 50% of the PM2.5 exposure in winter, while industrial sources contributed the most (29–51%) in the remaining seasons. The three major sectoral contributors to PM2.5-related deaths were industry (247,000 cases, 35%), residential sources (219,000 cases, 31%), and natural sources (87,000, 12%). The relative contributions of the different sectors varied in the different provinces, with industrial sources making the largest contribution in Shanghai (65%), while residential sources predominated in Heilongjiang (63%), and natural sources dominated in Xinjiang (82%). The contributions of the agricultural (11%), transportation (6%), and power (3%) sources were relatively low in China, but emissions mitigation was still effective in densely populated areas. In conclusion, to effectively alleviate health burdens across China, priority should be given to controlling residential emissions in winter and industrial emissions all year round, taking additional measures to curb emissions from other sources in urban hotspots, and formulating air pollution control strategies tailored to local conditions.

Disease burden and attributable risk factors of neonatal disorders and their specific causes in China from 1990 to 2019 and its prediction to 2024

BackgroundNeonatal health is a cornerstone for the healthy development of the next generation and a driving force for the progress of population and society in the future. Updated information on the burden of neonatal disorders (NDs) are of great importance for evidence-based health care planning in China, whereas such an estimate has been lacking at national level. This study aims to estimate the temporal trends and the attributable burdens of selected risk factors of NDs and their specific causes in China from 1990 to 2019, and to predict the possible trends between 2020 and 2024.MethodsData was explored from the Global Burden of Disease study (GBD) 2019. Six measures were used: incidence, mortality, prevalence, disability-adjusted life years (DALYs), years lived with disability (YLDs), and years of life lost (YLLs). Absolute numbers and age-standardized rates (with 95% uncertainty intervals) were calculated. The specific causes of NDs mainly included neonatal preterm birth (NPB), neonatal encephalopathy due to birth asphyxia and trauma (NE), neonatal sepsis and other neonatal infections (NS), and hemolytic disease and other neonatal jaundice (HD). An autoregressive integrated moving average (ARIMA) model was used to forecast disease burden from 2020 to 2024.ResultsThere were notable decreasing trends in the number of deaths (84.3%), incidence (30.3%), DALYs (73.5%) and YLLs (84.3%), while increasing trends in the number of prevalence (102.3%) and YLDs (172.7%) from 1990 to 2019, respectively. The corresponding age-standardized rates changed by -74.9%, 0.1%, -65.8%, -74.9%, 86.8% and 155.1%, respectively. Four specific causes of NDs followed some similar and different patterns. The prediction results of the ARIMA model shown that all measures still maintained the original trends in the next five years. Low birth weight, short gestation, ambient particulate matter pollution and household air pollution from solid fuels were the four leading risk factors.ConclusionThe health burden due to NDs is declining and is likely to continue to decline in the future in China. Delaying the increasing burden of disability may be the next target of concern. Targeted prevention and control strategies for specific causes of NDs are urgently needed to reduce the disease burden.

A satellite-driven model to estimate long-term particulate sulfate levels and attributable mortality burden in China

Ambient fine particulate matter (PM2.5) pollution is a major environmental and public health challenge in China. In the recent decade, the PM2.5 level has decreased mainly driven by reductions in particulate sulfate as a result of large-scale desulfurization efforts in coal-fired power plants and industrial facilities. Emerging evidence also points to the differential toxicity of particulate sulfate affecting human health. However, estimating the long-term spatiotemporal trend of sulfate is difficult because a ground monitoring network of PM2.5 constituents has not been established in China. Spaceborne sensors such as the Multi-angle Imaging SpectroRadiometer (MISR) instrument can provide complementary information on aerosol size and type. With the help of state-of-the-art machine learning techniques, we developed a sulfate prediction model under support from available ground measurements, MISR-retrieved aerosol microphysical properties, and atmospheric reanalysis data at a spatial resolution of 0.1°. Our sulfate model performed well with an out-of-bag cross-validationR2 of 0.68 at the daily level and 0.93 at the monthly level. We found that the national mean population-weighted sulfate concentration was relatively stable before the Air Pollution Prevention and Control Action Plan was enforced in 2013, ranging from 10.4 to 11.5 µg m−3. But the sulfate level dramatically decreased to 7.7 µg m−3 in 2018, with a change rate of −28.7 % from 2013 to 2018. Correspondingly, the annual mean total non-accidental and cardiopulmonary deaths attributed to sulfate decreased by 40.7 % and 42.3 %, respectively. The long-term, full-coverage sulfate level estimates will support future studies on evaluating air quality policies and understanding the adverse health effect of particulate sulfate.

Particulate matter 2.5, metropolitan status, and heart failure outcomes in US counties: A nationwide ecologic analysis.

The relationship between particulate matter with a diameter of 2.5 micrometers or less (PM2.5) and heart failure (HF) hospitalizations and mortality in the US is unclear. Prior studies are limited to studying the effects of daily PM2.5 exposure on HF hospitalizations in specific geographic regions. Because PM2.5 can vary by geography, this study examines the effects of annual ambient PM2.5 exposure on HF hospitalizations and mortality at a county-level across the US. A cross-sectional analysis of county-level ambient PM2.5 concentration, HF hospitalizations, and HF mortality across 3135 US counties nationwide was performed, adjusting for county-level demographics, socioeconomic factors, comorbidities, and healthcare-associated behaviors. There was a moderate correlation between county PM2.5 and HF hospitalization among Medicare beneficiaries (r = 0.41) and a weak correlation between county PM2.5 and HF mortality (r = 0.08) (p-values < 0.01). After adjustment for various county level covariates, every 1 ug/m3 increase in annual PM2.5 concentration was associated with an increase of 0.51 HF Hospitalizations/1,000 Medicare Beneficiaries and 0.74 HF deaths/100,000 residents (p-values < 0.05). In addition, the relationship between PM2.5 and HF hospitalizations was similar when factoring in metropolitan status of the counties. In conclusion, increased ambient PM2.5 concentration level was associated with increased incidence of HF hospitalizations and mortality at the county level across the US. This calls for future studies exploring policies that reduce ambient particulate matter pollution and their downstream effects on potentially improving HF outcomes.

Long-term exposure to ambient particulate matter and kidney function in older adults

BackgroundAccumulating studies have linked ambient particulate matter (PM) pollution to impaired kidney function, but the results are still inconsistent and the effect of particulate matter with an aerodynamic diameter ≤1 μm (PM1) on the kidney remains less clear. ObjectiveThis study aimed to investigate the association of long-term exposure to ambient PM1, particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5), and particulate matter with an aerodynamic diameter ≤10 μm (PM10) with kidney function in older adults. MethodsIn this cross-sectional study, we investigated 199,635 adults who were ≥65 years and underwent physical examinations in 695 community health service centers in Shenzhen, China from 2018 to 2019. An estimated glomerular filtration rate (eGFR) of each subject was derived by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. Chronic kidney disease (CKD) was defined as eGFR <60 ml/min/1.73 m2. Proteinuria was assessed by a urine dipstick test on freshly voided urine. A validated 10 km × 10 km grid dataset was used to assess long-term residential exposure to PM1, PM2.5, and PM10 for each subject. Linear regression models and logistic regression models were implemented to quantify the association of exposure to PM with eGFR level, CKD, and proteinuria. ResultsEach 10 μg/m3 increase of exposure to PM1, PM2.5, and PM10 was associated with a 0.9%, 2.7%, and 1.0% decrease in eGFR level, an 18%, 36%, and 17% increase in odds of CKD, and a 15%, 11%, and 10% increase in odds of proteinuria, respectively (all p < 0.05). The associations of exposure to PM with the eGFR level and CKD were stronger among women and subjects who were aged <75 years, never smoked, and never drank alcohol. ConclusionsLong-term exposure to ambient PM1, PM2.5, and PM10 was significantly associated with kidney function impairment in older adults.

Short-term ambient particulate matter pollution of different sizes and respiratory hospital admission in the Beibu Gulf area of Southern China

BackgroundAmbient particulate matter (PM) pollution is associated with occurrence of respiratory diseases; however, limited evidence exists on the effects of PM1 due to lack of ground-based PM1 measurements. ObjectiveTo examine the associations of short-term exposure to PM1, PM2.5 and PM10 with respiratory hospital admission, as well as the attributable burden. MethodsA total of 558,012 respiratory hospital admissions records were collected from 15 cities in the northeast Beibu Gulf of China from 2013 to 2016. Short-term exposures to pollutants (PM1, PM2.5 and PM10) were estimated using a bilinear interpolation approach at residential addresses. A time-stratified case-crossover design was constructed to estimate the associations and the burden of respiratory admissions attributable to ambient air pollution. ResultsWe observed significant associations between PM and respiratory hospitalizations. Odds ratios per 10 μg/m3 increment in two-day averaged concentration were 1.017 (95% CI: 1.012, 1.021) for PM1, 1.010 (95% CI: 1.007, 1.013) for PM2.5, and 1.007 (95% CI: 1.006, 1.009) for PM10. Males in the warm season appeared to be more vulnerable to the impacts of ambient PM pollutants. We further estimated that 3.0% (95% CI: 2.7%, 3.2%), 6.5% (95% CI: 5.9%, 6.8%) and 1.8% (95% CI: 1.6%, 1.9%) of respiratory hospital admissions were attributable to short-term exposure of PM1, PM2.5 and PM10, respectively. ConclusionsShort-term exposure to ambient PM might be an important risk factor for respiratory diseases hospital admissions. If environmental PM air pollutants were reduced to current guideline levels set forth by the government, a substantial proportion of respiratory hospitalizations would be mitigated as a result.

Global attributed burden of death for air pollution: Demographic decomposition and birth cohort effect

BackgroundTo identify the high-risk pollutants and evolving patterns of attributed mortality burden, more detailed evidence is needed to examine the contribution of different air pollutants to death across the disease spectrum, particularly considering population change as well as the context of the era. MethodsWe explored the evolving patterns of all-cause and disease-specific deaths attributed to overall air pollution and its main subcategories by using the estimated annual percentage change and additionally assessing the contribution of population growth and ageing to death burden using the decomposition method. Age-period-cohort model and Joinpoint analysis were used to evaluate birth cohort effects specific-disease death burden owing to high-risk air pollution subcategories. FindingsThe number of deaths caused by air pollution increased by 2.62 %, which was driven by ambient particulate matter pollution and ambient ozone pollution, whereas household air pollution decreased. Population ageing contributed 28.88 % of the deaths increase change for air pollution. Compared with other subcategories, the age-standardized mortality rate (ASMR) attributed to ambient particulate matter pollution remained the heaviest attributed death burden, comprehensively considering of bivariate burden. In 2019, ischemic heart disease attributed to ambient particulate matter pollution exhibited the highest ASMR, which may be impacted by a rapid increase era from 1950 to 1980 birth cohort in woman and 1970 to 1990 birth cohort in man. Diabetes mellitus attributed to ambient particulate matter pollution showed the largest increase for ASMR, which was driven primarily by men born 1910–1975 and women born 1950–1975.Uzbekistan showed the highest ASMR for ischemic heart disease, with Equatorial Guinea showing the fastest increase for diabetes mellitus. ConclusionPriority intervention targets for air pollution and health should emphasize the susceptibility of the elderly population as well as the structural factors of the era, in particular sensitive diseases to the ambient particulate matter pollution.

The burden of chronic obstructive pulmonary disease and its attributable risk factors in the Middle East and North Africa region, 1990–2019

BackgroundChronic obstructive pulmonary disease (COPD) is a preventable and treatable disease that is characterised by persistent respiratory symptoms and airflow limitation. The present study reported the burden of COPD, and its attributable risk factors, in the Middle East and North Africa (MENA) region between 1990 and 2019, by age, sex and socio-demographic index (SDI).MethodsData from the Global Burden of Disease (GBD) 2019 study were used to report the burden of COPD in the MENA countries. The prevalence, deaths, and disability-adjusted life-years (DALYs) were presented as counts and age-standardised rates per 100,000 population, with their associated 95% uncertainty intervals (UIs).ResultsIn 2019, the regional age-standardised point prevalence and rates of death due to COPD were 2333.9 (2230.1, 2443.6) and 26.1 (22.2, 29.5) per 100,000, which represent a 30.6% (28.2%, 33.0%) increase and an 18.0% (2.8%, 30.9%) decrease, respectively, since 1990. The regional age-standardised DALY rate in 2019 was 649.1 (574.6, 717.7) per 100,000, which had decreased by 11.8% (0.9%, 21.1%) since 1990. Turkey had the highest age-standardised point prevalence in 2019 [3287.1 (3187.4, 3380.3)], while Afghanistan had the highest age-standardised death [40.4 (24.2, 52.6)] and DALY [964.5 (681.8, 1203.2)] rates. The regional age-standardised point prevalence, death and DALY rates in 2019 increased with advancing age and were higher in males in almost all age groups. There was a U-shaped association between SDI and the burden of COPD over the period 1990 to 2019. Moreover, in 2019 smoking (43.7%), ambient particulate matter pollution (22.8%) and occupational particulate matter (11.4%) had the largest proportion of attributable DALYs for both sexes.ConclusionsCOPD is one of the leading causes of death and disability in the MENA region, although the age-standardised burden has decreased over the last 30 years. Nevertheless, COPD accounted for a substantial number of deaths and DALYs, especially among the elderly. Programs targeting risk factors, like smoking, should be taken into consideration.

Abstract 9844: Particulate Matter 2.5, Metropolitan Status, and Heart Failure Outcomes in US Counties: A Nationwide Ecologic Analysis

Epidemiological data on the relationship of particulate matter with a diameter of 2.5 micrometers or less (PM 2.5 ) with heart failure (HF) hospitalizations and mortality in the US are limited. Prior studies have focused on the effects of daily PM 2.5 exposure and HF hospitalizations in specific geographic locales in the US. Since PM 2.5 varies by geography, this study aimed to evaluate the relationship between annual ambient PM 2.5 concentration levels and HF hospitalizations and death at a county level across the US. We performed a cross-sectional analysis of county level HF hospitalizations, mortality, and ambient PM 2.5 concentration levels across 3135 US counties nationwide with adjustments for county-level demographics, socioeconomic factors, comorbidities, and healthcare-associated behaviors. County PM 2.5 showed a moderate correlation with HF hospitalization among Medicare beneficiaries (r=0.41) and a weak correlation with the overall county HF mortality (r=0.08) (p-values &lt; 0.01). There was an increase of 0.51 HF Hospitalizations/1,000 Medicare Beneficiaries and 0.74 HF deaths/100,000 residents for every 1 ug/m 3 increase in annual PM 2.5 concentration after adjustment for various county level covariates. The relationship between PM 2.5 concentration levels and both HF hospitalization and mortality remained significant after adjustment for county covariates. Additionally, the association between PM 2.5 and HF hospitalizations was comparable by metropolitan status of the counties. In conclusion, ambient PM 2.5 concentration level was associated with higher incidence of HF hospitalizations and deaths at the county level across the 3100 US counties. Future studies to examine policies aimed at reducing ambient particulate matter pollution and downstream effect of improving HF outcomes are warranted.

Disease burden and risk factors of ischemic heart disease in China during 1990-2019 based on the Global Burden of Disease 2019 report: A systematic analysis.

The aim of this study was to identify the disease burden and risk factors of ischemic heart disease (IHD) in China, during 1990-2019, through a systematic analysis using the Global Burden of Disease (GBD) 2019 report in order to provide first-hand information for primary and secondary prevention of IHD in China. Data on the rates of incidence, death, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life years (DALYs) of IHD were obtained from GBD2019 to determine the disease burden and risk factors of IHD in China. The rates of incidence, death, YLLs, YLDs, and DALYs of IHD in China increased at different levels during 1990-2019. The annual rate of change in incidence, death, YLLs, YLDs, and DALYs of IHD were 1.31%, 1.57%, 0.93%, 1.14%, and 0.94%, respectively. In 2019, the YLDs of IHD in Chinese women were higher, while the rates of incidence and death, YLLs, and DALYs were lower in Chinese women than in Chinese men. The disease burden of IHD had significant age differences, and people aged ≥70 years had the highest disease burden. A total of 24 risk factors were associated with the rates of death and DALYs of IHD, and the five most significant risk factors were high systolic blood pressure, high LDL cholesterol (LDL-C), smoking, ambient particulate matter pollution, and intake of a high-sodium diet. From 1990 to 2019, a high annual rate of change in IHD-related deaths and DALYs was observed due to ambient particulate matter pollution, high body mass index (BMI), and intake of a diet high in processed meat. The results of the study revealed that the disease burden of IHD in China was on the rise, especially in people aged ≥70 years. The main disease burden of IHD in male patients was premature death and that in female patients was disability. Environmental, behavioral, and metabolic factors were considered the three main risks of the disease burden of IHD, with metabolic factors having the greatest impact. Therefore, periodic health check-ups and high-risk factor interventions for key populations should be strengthened from the grassroots level, which are conducive to further reducing the disease burden of IHD in China.

Calibrating networks of low-cost air quality sensors

Abstract. Ambient fine particulate matter (PM2.5) pollution is a major health risk. Networks of low-cost sensors (LCS) are increasingly being used to understand local-scale air pollution variation. However, measurements from LCS have uncertainties that can act as a potential barrier to effective decision making. LCS data thus need adequate calibration to obtain good quality PM2.5 estimates. In order to develop calibration factors, one or more LCS are typically co-located with reference monitors for short or long periods of time. A calibration model is then developed that characterizes the relationships between the raw output of the LCS and measurements from the reference monitors. This calibration model is then typically transferred from the co-located sensors to other sensors in the network. Calibration models tend to be evaluated based on their performance only at co-location sites. It is often implicitly assumed that the conditions at the relatively sparse co-location sites are representative of the LCS network overall and that the calibration model developed is not overfitted to the co-location sites. Little work has explicitly evaluated how transferable calibration models developed at co-location sites are to the rest of an LCS network, even after appropriate cross-validation. Further, few studies have evaluated the sensitivity of key LCS use cases, such as hotspot detection, to the calibration model applied. Finally, there has been a dearth of research on how the duration of co-location (short-term or long-term) can impact these results. This paper attempts to fill these gaps using data from a dense network of LCS monitors in Denver deployed through the city's “Love My Air” program. It offers a series of transferability metrics for calibration models that can be used in other LCS networks and some suggestions as to which calibration model would be most useful for achieving different end goals.

Lockdown Amid COVID-19 Ascendancy over Ambient Particulate Matter Pollution Anomaly.

Air is a diverse mixture of gaseous and suspended solid particles. Several new substances are being added to the air daily, polluting it and causing human health effects. Particulate matter (PM) is the primary health concern among these air toxins. The World Health Organization (WHO) addressed the fact that particulate pollution affects human health more severely than other air pollutants. The spread of air pollution and viruses, two of our millennium’s most serious concerns, have been linked closely. Coronavirus disease 2019 (COVID-19) can spread through the air, and PM could act as a host to spread the virus beyond those in close contact. Studies on COVID-19 cover diverse environmental segments and become complicated with time. As PM pollution is related to everyday life, an essential awareness regarding PM-impacted COVID-19 among the masses is required, which can help researchers understand the various features of ambient particulate pollution, particularly in the era of COVID-19. Given this, the present work provides an overview of the recent developments in COVID-19 research linked to ambient particulate studies. This review summarizes the effect of the lockdown on the characteristics of ambient particulate matter pollution, the transmission mechanism of COVID-19, and the combined health repercussions of PM pollution. In addition to a comprehensive evaluation of the implementation of the lockdown, its rationales—based on topographic and socioeconomic dynamics—are also discussed in detail. The current review is expected to encourage and motivate academics to concentrate on improving air quality management and COVID-19 control.

Burden of Disease Due to Ambient Particulate Matter in Germany-Explaining the Differences in the Available Estimates.

Ambient particulate matter (PM2.5) pollution is an important threat to human health. The aim of this study is to estimate the environmental burden of disease (EBD) for the German population associated with PM2.5 exposure in Germany for the years 2010 until 2018. The EBD method was used to quantify relevant indicators, e.g., disability-adjusted life years (DALYs), and the life table approach was used to estimate the reduction in life expectancy caused by long-term PM2.5 exposure. The impact of varying assumptions and input data was assessed. From 2010 to 2018 in Germany, the annual population-weighted PM2.5 concentration declined from 13.7 to 10.8 µg/m3. The estimates of annual PM2.5-attributable DALYs for all disease outcomes showed a downward trend. In 2018, the highest EBD was estimated for ischemic heart disease (101.776; 95% uncertainty interval (UI) 62,713–145,644), followed by lung cancer (60,843; 95% UI 43,380–79,379). The estimates for Germany differ from those provided by other institutions. This is mainly related to considerable differences in the input data, the use of a specific German national life expectancy and the selected relative risks. A transparent description of input data, computational steps, and assumptions is essential to explain differing results of EBD studies to improve methodological credibility and trust in the results. Furthermore, the different calculated indicators should be explained and interpreted with caution.

Risk-benefit analysis of the association of ambient fine particulate matter pollution and physical activity with age-related cataract: A prospective cohort study

The aim of this study was to examine the associations of fine particulate matter (PM2.5) and physical activity (PA) with age-related cataract and its subtypes, and to explore potential interactions between PM2.5 and PA. A total of 291,627 participants enrolled in the UK Biobank cohort during 2006–2010 was included. The annual mean concentration of PM2.5 at each participant's residential address was estimated using Land Use Regression models. PA was measured using the International Physical Activity Questionnaire. Cox proportional hazards model was used to examine the associations of PM2.5 and PA with incident age-related cataract, and to assess their interactions on additive and multiplicative scales. We identified 12,826 incident cases of age-related cataract, including 7686 cases of nuclear cataract and 5140 cases of non-nuclear cataract. Higher PM2.5 exposure was associated with a higher risk of age-related cataract [HR = 1.140; 95% CI: 1.105, 1.177; per 1 μg/m3 increase], and the association was stronger for non-nuclear cataract than for nuclear cataract. There was a negative association between PA and cataract [HR = 0.925; 95% CI: 0.879, 0.974; comparing high to low level]. No clear evidence of the interactions between PM2.5 and PA was found. Our findings indicated that high PM2.5 exposure and low levels of PA were independently associated with increased risks of incident age-related cataract.

Time trends in the burden of stroke and subtypes attributable to PM2.5 in China from 1990 to 2019.

BackgroundIncreasing studies have found that PM2.5 has large adverse effects on stroke mortality. We want to investigate the long-term trends in the mortality of stroke attributable to ambient particulate matter pollution and household air pollution to provide evidence facilitating the design of policy.MethodsThe deaths data of stroke and its subtypes attributable to PM2.5 were obtained from the Global Burden of Disease (GBD) 2019, analyzed by Joinpoint regression software and the age-period-cohort (APC) method to assess the magnitude of the trends in mortality and the temporal trends in the mortality rate by age, period, and cohort.ResultsFrom 1990 to 2019, the age-standardized mortality rate (ASMR) attributable to PM2.5 exposure trended downwards, but the trends of ambient particulate matter pollution and household air pollution were opposite. The trends varied among subtypes, the AAPC of intracerebral hemorrhage, ischemic stroke, and subarachnoid hemorrhage attributable to PM2.5 were 0.7, 2.5, and−3.3%, respectively. The longitudinal age curve of the APC model showed that the mortality rates due to PM2.5 exposure increased with age. The period RRs of ischemic stroke due to ambient particulate matter pollution increased significantly. The cohort RRs of ambient particulate matter pollution increased among those born from 1905 to 1990. The net drifts of all subtypes attributable to PM2.5 were below 0, but owing to the increase of ambient particulate matter pollution, the range of the decline was small. Males had higher net drift values, compared with females.ConclusionsAmbient particulate matter pollution has become the main type of PM2.5 leading to stroke in China. PM2.5 exposure is more harmful to ischemic stroke, males, and elderly. Chinese government should pay attention to the long-term impact of ambient air pollution on stroke and take effective public health policies and interventions.

Trends of global and regional aetiologies, risk factors and mortality of lower respiratory infections from 1990 to 2019: An analysis for the Global Burden of Disease Study 2019.

Lower respiratory infections (LRIs) are a leading cause of death worldwide. We aimed to estimate the trends of global and regional aetiologies, risk factors and mortality of LRIs from 1990 to 2019. From the Global Burden of Disease (GBD) Study 2019, we collected relevant data, including annual LRI deaths, mortality and deaths and mortality attributable to the four high-burden aetiologies and 14 risk factors during 1990-2019. To quantify the temporal trends, estimated annual percentage changes (EAPCs) were calculated by fitting linear regression model. Globally, the age-standardized mortality due to LRIs decreased by an average of 2.39% (95% CI 2.33%-2.45%) per year, from 66.67 deaths per 100,000 in 1990 to 35.72 deaths per 100,000 in 2019. Low Socio-demographic Index regions, South Asia and Sub-Saharan Africa had the heaviest burden of LRIs. The age-standardized mortality decreased in 18 GBD regions, whereas increased in Southern Latin America (EAPC = 1.20, 95% CI 1.03-1.37). LRIs led to considerable deaths among children under 5 years and adults older than 70 years. Streptococcus pneumoniae was the first leading aetiology, accounting for over 50% of LRI deaths. Household air pollution from solid fuels, child wasting and ambient particulate matter pollution were the three leading risk factors for LRI mortality in 2019. LRIs remain an important health problem globally, especially in some vulnerable areas and among children under 5 and adults over 70 years. Future researches focusing on the aetiologies and risk factors for LRIs are needed to provide targeted and updated prevention strategies.

Long-term air pollution and risk of amyotrophic lateral sclerosis mortality in the Women's Health Initiative cohort

BackgroundAmyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder with no cure. Although the etiology of sporadic ALS is largely unknown, environmental exposures may affect ALS risk. ObjectiveWe investigated relationships between exposure to long-term ambient particulate matter (PM) and gaseous air pollution (AP) and ALS mortality. MethodsWithin the Women's Health Initiative (WHI) cohort of 161,808 postmenopausal women aged 50–79 years at baseline (1993–1998), we performed a nested case-control study of 256 ALS deaths and 2486 matched controls with emphasis on PM constituents (PM2.5, PM10, and coarse PM [PM10-2.5]) and gaseous pollutants (NOx, NO2, SO2, and ozone). Time-varying AP exposures estimates were averaged 5, 7.5, and 10 years prior to ALS death using both a GIS-based spatiotemporal generalized additive mixed model and ordinary kriging (empirical and multiple imputation, MI). Conditional logistic regression was used to estimate the relative risk of ALS death. ResultsIn general, PM2.5 and PM10-related risks were not significantly elevated using either method. However, for PM10-2.5, odds ratios (ORs) were >1.0 for both methods at all time periods using MI and empirical data for PM10-2.5 (coarse) except for 5 and 7.5 years using the kriging method with covariate adjustment. ConclusionThis investigation adds to the body of information on long-term ambient AP exposure and ALS mortality. Specifically, the 2019 US Environmental Protection Agency (EPA) Integrated Science Assessment summarized the neurotoxic effects of PM2.5, PM10, and PM10-2.5. The conclusion was that evidence of an effect of coarse PM is suggestive but the data is presently not sufficient to infer a causal relationship. Further research on AP and ALS is warranted. As time from symptom onset to death in ALS is ∼2–4 years, earlier AP measures may also be of interest to ALS development. This is the first study of ALS and AP in postmenopausal women controlling for individual-level confounders.

Ambient particulate matter pollution of different sizes associated with recurrent stroke hospitalization in China: A cohort study of 1.07 million stroke patients

BackgroundTo estimate the associations between ambient particulate matter (PM) pollution of different sizes (PM1, PM2.5, and PM10) and risk of rehospitalization among stroke patients, as well as the attributable burden in China. MethodsWe built a cohort of 1,066,752 participants with an index stroke hospitalization in Sichuan, China from 2017 to 2019. Seven-day and annual average exposures to PM pollution prior to the date of the index hospitalization were linked with residential address using a bilinear interpolation approach. Cox proportional hazard models were constructed to assess the association between ambient PM and the risk of rehospitalization. The burden of stroke rehospitalization was estimated using a counterfactual approach. Results245,457 (23.0 %) participants experienced rehospitalization during a mean of 1.15 years (SD: 0.90 years) of follow-up. Seven-day average concentrations of PM were associated with increased risk of rehospitalization: the hazard ratios (HRs) per 10 μg/m3 were 1.034 (95 % confidence interval [CI]: 1.029–1.038) for PM1, 1.033 (1.031–1.036) for PM2.5, and 1.030 (1.028–1.031) for PM10; the hazard ratios were larger for annual average concentrations: 1.082 (1.074–1.090) for PM1, 1.109 (1.104–1.114) for PM2.5, and 1.103 (1.099–1.106) for PM10. The associations were stronger in participants who were female, of minority ethnicity (non-Han Chinese), who suffered from an ischemic stroke, and those admitted under normal conditions. Population attributable fractions for stroke rehospitalization ranged from 4.66 % (95 % CI: 1.69 % to 7.63 %) for the 7-day average of PM1 to 17.05 % (14.27 % to 19.83 %) for the annual average of PM10; the reducible average cost of rehospitalization per participant attributable to PM ranged from 492.09 (178.19 to 806) RMB for the 7-day average of PM1 to 1801.65 (1507.89 to 2095.41) RMB for the annual average of PM10. ConclusionsAmbient PM pollution may increase the risk of rehospitalization in stroke patients and is responsible for a significant burden of stroke rehospitalization.

Epidemiological trends and incidence prediction of lung cancer in China based on the Global Burden of Disease study 2019.

Lung cancer remains the most common malignancy in China. This study aims to provide scientific support for the prevention and treatment of lung cancer by analyzing the epidemiological trends of lung cancer in China from 1990 to 2019. Based on the global health exchange database (GHDx), joinpoint and age-period-cohort analyses were performed to explore the trend of lung cancer incidence and mortality rates from 1990 to 2019. According to incidence rates from 1990 to 2019, a model was constructed to predict the incidence rates in the next 5 years. In addition, changes in risk factors associated with lung cancer deaths were compared between 1990 and 2019 and between males and females in 2019. The results are as follows. The age-standardized incidence rates (ASIRs), and age-standardized death rates (ASDRs) of lung cancer among Chinese had overall upward trends from 1990 to 2019. The ASDRs of females and males in China decreased since 2010. Interestingly, from 2016 to 2019, the ASIRs and ASDRs of females rose significantly. The age-period-cohort model showed that the incidence and mortality rates of lung cancer in China increased with age, and the growth rate accelerated after 45 years old. After 2004, the relative risks of lung cancer incidence increased with the passage of the period. Also, after the 1950–1954 birth cohort, the risks of lung cancer incidence and death began to decrease. The autoregressive integrated moving average (ARIMA) model predicted that the incidence rates of lung cancer in China would continue to rise in the next 5 years. The top five risk factors for lung cancer deaths of both genders in 2019 were smoking, ambient particulate matter pollution, secondhand smoke, high fasting plasma glucose, and household air pollution from solid fuels. The above results provided precise clues for the prevention and treatment of lung cancer in China.

Ambient Air Pollution and Preeclampsia Onset in Massachusetts, United States

Background and Aim: Ambient particulate matter and gaseous air pollution have been linked to preeclampsia. However, despite the recognition that preeclampsia is likely a heterogenous syndrome with distinct pathogenic mechanisms, few studies have examined the association between air pollution and subtypes of preeclampsia. Our objective was to examine differential impacts of air pollution on early- vs. late-onset (i.e., diagnosed in or after 34th gestation week) preeclampsia among pregnant women in the Boston, Massachusetts based biorepository, LIFECODES. Methods: Preeclampsia was diagnosed according to the American College of Obstetrics and Gynecologists guidelines and each case was reviewed by a panel Maternal–Fetal Medicine–certified physicians. Women’s exposures to ozone and fine particulate matter (PM2.5) during pregnancy were estimated based on geocoded residential addresses using U.S. Environmental Protection Agency’s Fused Air Quality Surface Using Downscaling Files. Cox proportional hazards models and multinomial logistic regression were used to examine the associations of ozone and PM2.5 with preeclampsia and its onsets. Hazard ratio (HR), odds ratio (OR), and 95% confidence interval (95% CI) for each interquartile range increase in exposures were reported. Results: A total of 3,316 pregnant women were included. In the cox model, higher exposures to ozone during pregnancy were associated with higher hazard being diagnosed with preeclampsia (HR: 1.67, 95% CI: 1.16, 2.40). In the multinomial logistic regression model, ozone was significantly associated with early-onset preeclampsia (OR: 2.50, 95% CI: 1.48, 4.21) but not late-onset preeclampsia (OR: 1.34, 95% CI: 0.96, 1.88), and PM2.5 was significantly associated with both early- (OR: 1.62, 95% CI: 1.07, 2.45) and late-onset preeclampsia (OR: 1.32, 95% CI: 1.02, 1.71). Conclusions: Exposures to ozone and PM2.5 were significantly associated preeclampsia. This association was significant with respect to ozone exposure in the earlier onset, but not later onset, preeclampsia. This study highlights the importance of assessing the heterogeneity in preeclampsia.