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The entire Medicare population was used to establish a relationship between all-cause mortality and small particulate matter in the air. Even at concentrations below current air-quality standards, higher levels of particulate matter were associated with higher rates of death. The adverse health effects associated with long-term exposure to air pollution are well documented. 1 , 2 Studies suggest that fine particles (particles with a mass median aerodynamic diameter of less than 2.5 μm [PM 2.5 ]) are a public health concern, 3 with exposure linked to decreased life expectancy. 4 – 6 Long-term exposure to ozone has also been associated with reduced survival in several recent studies, although evidence is sparse. 4 , 7 – 9 Studies with large cohorts have investigated the relationship between long-term exposures to PM 2.5 and ozone and mortality 4 , 9 – 13 ; others have estimated the health effects of fine particles at . . .

AbstractObjectiveTo assess risks and costs of hospital admission associated with short term exposure to fine particulate matter with diameter less than 2.5 µm (PM2.5) for 214 mutually exclusive disease groups.DesignTime stratified, case crossover analyses with conditional logistic regressions adjusted for non-linear confounding effects of meteorological variables.SettingMedicare inpatient hospital claims in the United States, 2000-12 (n=95 277 169).ParticipantsAll Medicare fee-for-service beneficiaries aged 65 or older admitted to hospital.Main outcome measuresRisk of hospital admission, number of admissions, days in hospital, inpatient and post-acute care costs, and value of statistical life (that is, the economic value used to measure the cost of avoiding a death) due to the lives lost at discharge for 214 disease groups.ResultsPositive associations between short term exposure to PM2.5 and risk of hospital admission were found for several prevalent but rarely studied diseases, such as septicemia, fluid and electrolyte disorders, and acute and unspecified renal failure. Positive associations were also found between risk of hospital admission and cardiovascular and respiratory diseases, Parkinson’s disease, diabetes, phlebitis, thrombophlebitis, and thromboembolism, confirming previously published results. These associations remained consistent when restricted to days with a daily PM2.5 concentration below the WHO air quality guideline for the 24 hour average exposure to PM2.5. For the rarely studied diseases, each 1 µg/m3 increase in short term PM2.5 was associated with an annual increase of 2050 hospital admissions (95% confidence interval 1914 to 2187 admissions), 12 216 days in hospital (11 358 to 13 075), US$31m (£24m, €28m; $29m to $34m) in inpatient and post-acute care costs, and $2.5bn ($2.0bn to $2.9bn) in value of statistical life. For diseases with a previously known association, each 1 µg/m3 increase in short term exposure to PM2.5 was associated with an annual increase of 3642 hospital admissions (3434 to 3851), 20 098 days in hospital (18 950 to 21 247), $69m ($65m to $73m) in inpatient and post-acute care costs, and $4.1bn ($3.5bn to $4.7bn) in value of statistical life.ConclusionsNew causes and previously identified causes of hospital admission associated with short term exposure to PM2.5 were found. These associations remained even at a daily PM2.5 concentration below the WHO 24 hour guideline. Substantial economic costs were linked to a small increase in short term PM2.5.

BACKGROUND:Although the association between exposure to particulate matter (PM) mass and mortality is well established, there remains uncertainty about which chemical components of PM are most harmful to human health. METHODS:A hierarchical approach was used to determine how the association between daily PM2.5 mass and mortality was modified by PM2.5 composition in 25 US communities. First, the association between daily PM2.5 and mortality was determined for each community and season using Poisson regression. Second, we used meta-regression to examine how the pooled association was modified by community and season-specific particle composition. RESULTS:There was a 0.74% (95% confidence interval = 0.41%–1.07%) increase in nonaccidental deaths associated with a 10 μg/m increase in 2-day averaged PM2.5 mass concentration. This association was smaller in the west (0.51% [0.10%–0.92%]) than in the east (0.92% [0.23%–1.36%]), and was highest in spring (1.88% [0.23%–1.36%]). It was increased when PM2.5 mass contained a higher proportion of aluminum (interquartile range = 0.58%), arsenic (0.55%), sulfate (0.51%), silicon (0.41%), and nickel (0.37%). The combination of aluminum, sulfate, and nickel also modified the effect. These species proportions explained residual variability between the community-specific PM2.5 mass effect estimates. CONCLUSIONS:This study shows that certain chemical species modify the association between PM2.5 and mortality and illustrates that mass alone is not a sufficient metric when evaluating health effects of PM exposure.

Background. Little is known about the health risks of air pollution and cardiorespiratory diseases, globally, across regions and populations, which may differ because of external factors. Objectives. We systematically reviewed the evidence on the association between air pollution and cardiorespiratory diseases (hospital admissions and mortality), including variability by energy, transportation, socioeconomic status, and air quality. Search Methods. We conducted a literature search (PubMed and Web of Science) for studies published between 2006 and May 11, 2016. Selection Criteria. We included studies if they met all of the following criteria: (1) considered at least 1 of these air pollutants: carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone, or particulate matter (PM 2.5 or PM 10 ); (2) reported risk for hospital admissions, mortality, or both; (3) presented individual results for respiratory diseases, cardiovascular diseases, or both; (4) considered the age groups younger than 5 years, older than 65 years, or all ages; and (5) did not segregate the analysis by gender. Data Collection and Analysis. We extracted data from each study, including location, health outcome, and risk estimates. We performed a meta-analysis to estimate the overall effect and to account for both within- and between-study heterogeneity. Then, we applied a model selection (least absolute shrinkage and selection operator) to assess the modifier variables, and, lastly, we performed meta-regression analyses to evaluate the modifier variables contributing to heterogeneity among studies. Main Results. We assessed 2183 studies, of which we selected 529 for in-depth review, and 70 articles fulfilled our study inclusion criteria. The 70 studies selected for meta-analysis encompass more than 30 million events across 28 countries. We found positive associations between cardiorespiratory diseases and different air pollutants. For example, when we considered only the association between PM 2.5 and respiratory diseases ( Figure 1 , we observed a risk equal to 2.7% (95% confidence interval = 0.9%, 7.7%). Our results showed statistical significance in the test of moderators for all pollutants, suggesting that the modifier variables influence the average cardiorespiratory disease risk and may explain the varying effects of air pollution. Conclusions. Variables related to aspects of energy, transportation, and socioeconomic status may explain the varying effect size of the association between air pollution and cardiorespiratory diseases. Public Health Implications. Our study provides a transferable model to estimate the health effects of air pollutants to support the creation of environmental health public policies for national and international intervention.

Background Although the association between exposure to particulate matter and health is well established, there remains uncertainty as to whether certain chemical components are more harmful than others. We explored whether the association between cause-specific hospital admissions and PM 2.5 was modified by PM 2.5 chemical composition. Methods We estimated the association between daily PM 2.5 and emergency hospital admissions for cardiac causes (CVD), myocardial infarction (MI), congestive heart failure (CHF), respiratory disease, and diabetes in 26 US communities, for the years 2000-2003. Using meta-regression, we examined how this association was modified by season- and community-specific PM 2.5 composition, controlling for seasonal temperature as a surrogate for ventilation. Results For a 10 μg/m 3 increase in 2-day averaged PM 2.5 concentration we found an increase of 1.89% (95% CI: 1.34- 2.45) in CVD, 2.25% (95% CI: 1.10- 3.42) in MI, 1.85% (95% CI: 1.19- 2.51) in CHF, 2.74% (95% CI: 1.30- 4.2) in diabetes, and 2.07% (95% CI: 1.20- 2.95) in respiratory admissions. The association between PM 2.5 and CVD admissions was significantly modified when the mass was high in Br, Cr, Ni, and Na + , while mass high in As, Cr, Mn, OC, Ni, and Na + modified MI, and mass high in As, OC, and SO 4 2- modified diabetes admissions. For these species, an interquartile range increase in their relative proportion was associated with a 1-2% additional increase in daily admissions per 10 μg/m 3 increase in mass. Conclusions We found that PM 2.5 mass higher in Ni, As, and Cr, as well as Br and OC significantly increased its effect on hospital admissions. This result suggests that particles from industrial combustion sources and traffic may, on average, have greater toxicity.

Recognizing associations between exposure to common environmental toxicants and mental disorders such as depression is crucial for guiding targeted mechanism research and the initiation of disease prevention efforts. To comprehensively screen and assess the associations between potential environmental toxicants and depressive symptoms and to assess whether systemic inflammation serves as a mediator. A total of 3427 participants from the 2013-2014 and 2015-2016 waves of the National Health and Nutrition Examination and Survey who had information on blood or urine concentrations of environmental toxicants and depression scores assessed by the 9-item Patient Health Questionnaire (PHQ-9) were included. Statistical analysis was performed from July 1, 2023, to January 31, 2024. Sixty-two toxicants in 10 categories included acrylamide, arsenic, ethylene oxide, formaldehyde, iodine, metals, nicotine metabolites, polycyclic aromatic hydrocarbons, volatile organic compound (VOC) metabolites; and perchlorate, nitrate, and thiocyanate. An exposome-wide association study and the deletion-substitution-addition algorithm were used to assess associations with depression scores (PHQ-9 ≥5) adjusted for other important covariates. A mediation analysis framework was used to evaluate the mediating role of systemic inflammation assessed by the peripheral white blood cell count. Among the 3427 adults included, 1735 (50.6%) were women, 2683 (78.3%) were younger than 65 years, and 744 (21.7%) were 65 years or older, with 839 (24.5%) having depressive symptoms. In terms of race and ethnicity, 570 participants (16.6%) were Mexican American, 679 (19.8%) were non-Hispanic Black, and 1314 (38.3%) were non-Hispanic White. We identified associations between 27 chemical compounds or metals in 6 of 10 categories of environmental toxicants and the prevalence of depressive symptoms, including the VOC metabolites N-acetyl-S-(2-hydroxy-3-butenyl)-l-cysteine (odds ratio [OR], 1.74 [95% CI, 1.38, 2.18]) and total nicotine equivalent-2 (OR, 1.42 [95% CI, 1.26-1.59]). Men and younger individuals appear more vulnerable to environmental toxicants than women and older individuals. Peripheral white blood cell count mediated 5% to 19% of the associations. In this representative cross-sectional study of adults with environmental toxicant exposures, 6 categories of environmental toxicants were associated with depressive symptoms with mediation by systemic inflammation. This research provides insight into selecting environmental targets for mechanistic research into the causes of depression and facilitating efforts to reduce environmental exposures.

Few studies have examined associations between long-term exposure to fine particulate matter (PM2.5) and lung function decline in adults. To determine if exposure to traffic and PM2.5 is associated with longitudinal changes in lung function in a population-based cohort in the Northeastern United States, where pollution levels are relatively low. FEV1 and FVC were measured up to two times between 1995 and 2011 among 6,339 participants of the Framingham Offspring or Third Generation studies. We tested associations between residential proximity to a major roadway and PM2.5 exposure in 2001 (estimated by a land-use model using satellite measurements of aerosol optical thickness) and lung function. We examined differences in average lung function using mixed-effects models and differences in lung function decline using linear regression models. Current smokers were excluded. Models were adjusted for age, sex, height, weight, pack-years, socioeconomic status indicators, cohort, time, season, and weather. Living less than 100 m from a major roadway was associated with a 23.2 ml (95% confidence interval [CI], -44.4 to -1.9) lower FEV1 and a 5.0 ml/yr (95% CI, -9.0 to -0.9) faster decline in FEV1 compared with more than 400 m. Each 2 μg/m(3) increase in average of PM2.5 was associated with a 13.5 ml (95% CI, -26.6 to -0.3) lower FEV1 and a 2.1 ml/yr (95% CI, -4.1 to -0.2) faster decline in FEV1. There were similar associations with FVC. Associations with FEV1/FVC ratio were weak or absent. Long-term exposure to traffic and PM2.5, at relatively low levels, was associated with lower FEV1 and FVC and an accelerated rate of lung function decline.

Background The mechanism for spread of SARS-CoV-2 has been attributed to large particles produced by coughing and sneezing. There is controversy whether smaller airborne particles may transport SARS-CoV-2. Smaller particles, particularly fine particulate matter (≤ 2.5 µm in diameter), can remain airborne for longer periods than larger particles and after inhalation will penetrate deeply into the lungs. Little is known about the size distribution and location of airborne SARS-CoV-2 RNA. Methods As a measure of hospital-related exposure, air samples of three particle sizes (> 10.0 µm, 10.0–2.5 µm, and ≤ 2.5 µm) were collected in a Boston, Massachusetts (USA) hospital from April to May 2020 ( N  = 90 size-fractionated samples). Locations included outside negative-pressure COVID-19 wards, a hospital ward not directly involved in COVID-19 patient care, and the emergency department. Results SARS-CoV-2 RNA was present in 9% of samples and in all size fractions at concentrations of 5 to 51 copies m −3 . Locations outside COVID-19 wards had the fewest positive samples. A non-COVID-19 ward had the highest number of positive samples, likely reflecting staff congregation. The probability of a positive sample was positively associated ( r  = 0.95, p  < 0.01) with the number of COVID-19 patients in the hospital. The number of COVID-19 patients in the hospital was positively associated ( r  = 0.99, p  < 0.01) with the number of new daily cases in Massachusetts. Conclusions More frequent detection of positive samples in non-COVID-19 than COVID-19 hospital areas indicates effectiveness of COVID-ward hospital controls in controlling air concentrations and suggests the potential for disease spread in areas without the strictest precautions. The positive associations regarding the probability of a positive sample, COVID-19 cases in the hospital, and cases in Massachusetts suggests that hospital air sample positivity was related to community burden. SARS-CoV-2 RNA with fine particulate matter supports the possibility of airborne transmission over distances greater than six feet. The findings support guidelines that limit exposure to airborne particles including fine particles capable of longer distance transport and greater lung penetration.

Numerous studies have demonstrated that fine particulate matter (PM(sub 2.5), particles smaller than 2.5 micrometers in aerodynamic diameter) is associated with adverse health outcomes. The use of ground monitoring stations of PM(sub 2.5) to assess personal exposure, however, induces measurement error. Land-use regression provides spatially resolved predictions but land-use terms do not vary temporally. Meanwhile, the advent of satellite-retrieved aerosol optical depth (AOD) products have made possible to predict the spatial and temporal patterns of PM(sub 2.5) exposures. In this paper, we used AOD data with other PM(sub 2.5) variables, such as meteorological variables, land-use regression, and spatial smoothing to predict daily concentrations of PM(sub 2.5) at a 1 sq km resolution of the Southeastern United States including the seven states of Georgia, North Carolina, South Carolina, Alabama, Tennessee, Mississippi, and Florida for the years from 2003 to 2011. We divided the study area into three regions and applied separate mixed-effect models to calibrate AOD using ground PM(sub 2.5) measurements and other spatiotemporal predictors. Using 10-fold cross-validation, we obtained out of sample R2 values of 0.77, 0.81, and 0.70 with the square root of the mean squared prediction errors of 2.89, 2.51, and 2.82 cu micrograms for regions 1, 2, and 3, respectively. The slopes of the relationships between predicted PM2.5 and held out measurements were approximately 1 indicating no bias between the observed and modeled PM(sub 2.5) concentrations. Predictions can be used in epidemiological studies investigating the effects of both acute and chronic exposures to PM(sub 2.5). Our model results will also extend the existing studies on PM(sub 2.5) which have mostly focused on urban areas because of the paucity of monitors in rural areas.

Particulate matter with aerodynamic diameter <2.5  μ m (PM 2.5 ) is associated with asthma exacerbation. In the Children’s Air Pollution Asthma Study, we investigated the longitudinal association of PM 2.5 and its components from indoor and outdoor sources with cough and wheeze symptoms in 36 asthmatic children. The sulfur tracer method was used to estimate infiltration factors. Mixed proportional odds models for an ordinal response were used to relate daily cough and wheeze scores to PM 2.5 exposures. The odds ratio associated with being above a given symptom score for a SD increase in PM 2.5 from indoor sources (PM IS ) was 1.24 (95% confidence interval: 0.92–1.68) for cough and 1.63 (1.11–2.39) for wheeze. Ozone was associated with wheeze (1.82, 1.19–2.80), and cough was associated with indoor PM 2.5 components from outdoor sources (denoted with subscript “OS”) bromine (Br OS : 1.32, 1.05–1.67), chlorine (Cl OS : 1.27, 1.02–1.59) and pyrolyzed organic carbon (OP OS : 1.49, 1.12–1.99). The highest effects were seen in the winter for cough with sulfur (S OS : 2.28, 1.01–5.16) and wheeze with organic carbon fraction 2 (OC2 OS : 7.46, 1.19–46.60). Our results indicate that exposure to components originating from outdoor sources of photochemistry, diesel and fuel oil combustion is associated with symptom’s exacerbation, especially in the winter. PM 2.5 mass of indoor origin was more strongly associated with wheeze than with cough.