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Our study adds to the sparse literature that examines whether arterial stiffness, related to cardiovascular risk, increases with exposure to air pollution. We assessed the associations between spatiotemporally resolved air pollutants and vascular and hemodynamic parameters in an elderly population-based in Eastern Massachusetts.Among 397 men living in Eastern Massachusetts between 2007 and 2013, we utilized time-varying linear mixed-effects regressions to examine associations between central augmentation index (%) and central pulse pressure (mmHg) and short-term (0-7 days) exposure to air pollution concentrations (fine particulate matter (PMWe found consistent results that higher short-term PMShort-term PM

BACKGROUND: The physical environmental risk factors for psychotic disorders are poorly understood. This study aimed to examine the associations between exposure to ambient air pollution, climate measures and risk of hospitalization for psychotic disorders and uncover potential disparities by demographic, community factors. METHODS: Using Health Cost and Utilization Project (HCUP) State Inpatient Databases (SIDs), we applied zero-inflated negative binomial regression to obtain relative risks of hospitalization due to psychotic disorders associated with increases in residential exposure to ambient air pollution (fine particulate matter, PM(2.5); nitrogen dioxide, NO(2)), temperature and cumulative precipitation. The analysis covered all-age residents in eight U.S. states over the period of 2002 – 2016. We additionally investigated modification by age, sex and area-level poverty, percent of blacks and Hispanics. RESULTS: Over the study period and among the covered areas, we identified 1,211,100 admissions due to psychotic disorders. For each interquartile (IQR) increase in exposure to PM(2.5) and NO(2), we observed a relative risk (RR) of 1.11 (95% confidence interval (CI) = 1.09, 1.13) and 1.27 (95% CI = 1.24, 1.31), respectively. For each 1 °C increase of temperature, the RR was 1.03 (95% CI = 1.03, 1.04). Males were more affected by NO(2). Older age residents (>= 30 yrs.) were more sensitive to PM(2.5) and temperature. Population living in economically disadvantaged areas were more affected by air pollution. CONCLUSIONS: The study suggests that living in areas with higher levels of air pollutants and ambient temperature could contribute to additional risk of inpatient care for individuals with psychotic disorders.

Short-term exposure to high or low temperatures is associated with increased mortality and morbidity. Less is known about effects of long-term exposure to high or low temperatures. Prolonged exposure to high or low temperatures might contribute to pathophysiological mechanisms, thereby influencing the development of diseases. Our aim was to evaluate associations of long-term temperature exposure with cardiovascular disease (CVD) hospitalizations.We constructed an open cohort consisting of all fee-for-service Medicare beneficiaries, aged ≥65, living in the contiguous US from 2000 through 2016 (∼61.6 million individuals). We used data from the 4 km Gridded Surface Meteorological dataset to assess the summer (June-August) and winter (December-February) average daily maximum temperature for each year for each zip code. Cox-equivalent Poisson models were used to estimate associations with first CVD hospitalization, after adjustment for potential confounders. We performed stratified analyses to assess potential effect modification by sex, age, race, Medicaid eligibility and relative humidity.Higher summer average and lower winter average temperatures were associated with an increased risk of CVD hospitalization. We found a HR of 1.068 (95% CI: 1.063, 1.074) per IQR increase (5.2 °C) for summer average temperature and a HR of 1.022 (95% CI: 1.017, 1.028) per IQR decrease (11.7 °C) for winter average temperature. Positive associations of higher summer average temperatures were strongest for individuals aged75 years, Medicaid eligible, and White individuals. Positive associations of lower winter average temperatures were strongest for individuals aged75 years and Black individuals, and individuals living in low relative humidity areas.Living in areas with high summer average temperatures or low winter average temperatures could increase the risk of CVD hospitalizations. The magnitude of the associations of summer and winter average temperatures differs by demographics and relative humidity levels.

Many studies have found associations between early life air pollution exposure and subsequent onset of autism spectrum disorder (ASD). However, characteristics that affect susceptibility remain unclear.This systematic review examined epidemiologic studies on the modifying roles of social, child, genetic and maternal characteristics in associations between prenatal and early postnatal air pollution exposure and ASD.A systematic literature search in PubMed and Embase was conducted. Studies that examined modifiers of the association between air pollution and ASD were included.A total of 19 publications examined modifiers of the associations between early life air pollution exposures and ASD. In general, estimates of effects on risk of ASD in boys were larger than in girls (based on 11 studies). Results from studies of effects of family education (2 studies) and neighborhood deprivation (2 studies) on air pollution-ASD associations were inconsistent. Limited data (1 study) suggest pregnant women with insufficient folic acid intake might be more susceptible to ambient particulate matter less than 2.5 μm (PMChild's sex, maternal nutrition or diabetes, socioeconomic factors, and child risk genotypes were reported to modify the effect of early-life air pollutants on ASD risk in the epidemiologic literature. However, the sparsity of studies on comparable modifying hypotheses precludes conclusive findings. Further research is needed to identify susceptible populations and potential targets for preventive intervention.

BACKGROUND: It is not known whether environmental gamma radiation measured in US cities has detectable adverse health effects. We assessed whether short-term exposure to gamma radiation emitted from ambient air particles [gamma particle activity (PRγ)] is associated with reduced pulmonary function in chronic obstructive pulmonary disease (COPD) patients. OBJECTIVE: We hypothesize that the inhalation of gamma radiation emitted from ambient air particles may be associated with reduced pulmonary function in individuals with COPD. METHODS: In 125 patients with COPD from Eastern Massachusetts who had up to 4 seasonal one-week assessments of particulate matter ≤ 2.5 pm (PM(2.5)), black carbon (BC), and sulfur followed by spirometry. The US EPA continuously monitors ambient gamma (γ) radiation including γ released from radionuclides attached to particulate matter that is recorded as 9 γ-energy spectra classes (i = 3–9) in counts per minute (CPMγ) in the Boston area (USA). We analyzed the associations between ambient and indoor PRγi (up to one week) and pre and post-bronchodilator (BD) forced expiratory volume in 1 s (FEV(1)) and with forced vital capacity (FVC) using mixed-effects regression models. We estimated indoor PRγi using the ratio of the indoor-to-outdoor sulfur in PM(2.5) as a proxy for infiltration of ambient radionuclide-associated particles. RESULTS: Overall, exposures to ambient and indoor PRγi were associated with a similar decrease in pre- and post- BD FEV(1) and FVC. For example, ambient PRγ(3) exposure averaged from the day of pulmonary function testing through the previous 3 days [IQR of 55.1 counts per minute (CPMγ)] was associated with a decrease in pre-BD FEV(1) of 21.0 ml (95%CI: −38.5 to −3.0 ml; p < 0.01) and pre-BD FVC of 27.5 ml [95% confidence interval (CI): −50.7 to −5.0 ml; p < 0.01] with similar effects adjusting for indoor and outdoor BC and PM(2.5). CONCLUSION: Our results show that short-term ambient and indoor exposures to environmental gamma radiation associated with particulate matter are associated with reduced pre- and post- BD pulmonary function in patients with COPD.

Background Short-term exposure to air pollution has been associated with cardiovascular events, potentially by promoting endothelial cell activation and inflammation. A few large-scale studies have examined the associations and have had mixed results. Methods We included 3820 non-current smoking participants (mean age 56 years, 54% women) from the Framingham Offspring cohort examinations 7 (1998–2001) and 8 (2005–2008), and Third Generation cohort examination 1 (2002–2005), who lived within 50 km of a central monitoring station. We calculated the 1- to 7-day moving averages of fine particulate matter (PM2.5), black carbon (BC), sulfate (SO42-), nitrogen oxides (NOx), and ozone before examination visits. We used linear mixed effect models for P-selectin, monocyte chemoattractant protein 1 (MCP-1), intercellular adhesion molecule 1, lipoprotein-associated phospholipase A2 activity and mass, and osteoprotegerin that were measured up to twice, and linear regression models for CD40 ligand and interleukin-18 that were measured once, adjusting for demographics, life style and clinical factors, socioeconomic position, time, and meteorology. Results We found negative associations of PM2.5 and BC with P-selectin, of ozone with MCP-1, and of SO42- and NOx with osteoprotegerin. At the 5-day moving average, a 5 µg/m3 higher PM2.5 was associated with 1.6% (95% CI: − 2.8, − 0.3) lower levels of P-selectin; a 10 ppb higher ozone was associated with 1.7% (95% CI: − 3.2, − 0.1) lower levels of MCP-1; and a 20 ppb higher NOx was associated with 2.0% (95% CI: − 3.6, − 0.4) lower levels of osteoprotegerin. Conclusions We did not find evidence of positive associations between short-term air pollution exposure and endothelial cell activation. On the contrary, short-term exposure to higher levels of ambient pollutants were associated with lower levels of P-selectin, MCP-1, and osteoprotegerin in the Framingham Heart Study.

Exposure to fine particulate matter (2.5 mm in aerodynamic diameter, PMWe conducted a health impact assessment for 2015 using a model predicting U.S. PMWe estimated the deaths would fall by 104,786 (95% CI 57,016-135,726) and 112,040 (95% CI 63,261-159,116) attributable to 40% reduction and reduction to the county minimum PMOur study provides evidence of major health benefits expected from reducing PM

Many studies have reported that PM

Epidemiologic studies have found associations between fine particulate matter (PM(2.5)) exposure and adverse health effects using exposure models that incorporate monitoring data and other relevant information. Here, we use nine PM(2.5) concentration models (i.e., exposure models) that span a wide range of methods to investigate i) PM(2.5) concentrations in 2011, ii) potential changes in PM(2.5) concentrations between 2011 and 2028 due to on-the-books regulations, and iii) PM(2.5) exposure for the U.S. population and four racial/ethnic groups. The exposure models included two geophysical chemical transport models (CTMs), two interpolation methods, a satellite-derived aerosol optical depth-based method, a Bayesian statistical regression model, and three data-rich machine learning methods. We focused on annual predictions that were regridded to 12-km resolution over the conterminous U.S., but also considered 1-km predictions in sensitivity analyses. The exposure models predicted broadly consistent PM(2.5) concentrations, with relatively high concentrations on average over the eastern U.S. and greater variability in the western U.S. However, differences in national concentration distributions (median standard deviation: 1.00 μg m(−3)) and spatial distributions over urban areas were evident. Further exploration of these differences and their implications for specific applications would be valuable. PM(2.5) concentrations were estimated to decrease by about 1 μg m(−3) on average due to modeled emission changes between 2011 and 2028, with decreases of more than 3 μg m(−3) in areas with relatively high 2011 concentrations that were projected to experience relatively large emission reductions. Agreement among models was closer for population-weighted than uniformly weighted averages across the domain. About 50% of the population was estimated to experience PM(2.5) concentrations less than 10 μg m(−3) in 2011 and PM(2.5) improvements of about 2 μg m(−3) due to modeled emission changes between 2011 and 2028. Two inequality metrics were used to characterize differences in exposure among the four racial/ethnic groups. The metrics generally yielded consistent information and suggest that the modeled emission reductions between 2011 and 2028 would reduce absolute exposure inequality on average.

Background Studies on high temperatures and mortality have not focused on underdeveloped tropical regions and have reported the associations of different temperature metrics without conducting model selection. Methods We collected daily mortality and meteorological data including ambient temperatures and humidity in Ahmedabad during summer, 1987–2017. We proposed two cross-validation (CV) approaches to compare semiparametric quasi-Poisson models with different temperature metrics and heat wave definitions. Using the fittest model, we estimated heat-mortality associations among general population and subpopulations. We also conducted separate analyses for 1987–2002 and 2003–2017 to evaluate temporal heterogeneity. Findings The model with maximum and minimum temperatures and without heat wave indicator gave the best performance. With this model, we found a substantial and significant increase in mortality rate starting from maximum temperature at 42 °C and from minimum temperature at 28 °C: 1 °C increase in maximum and minimum temperatures at lag 0 were associated with 9.56% (95% confidence interval [CI]: 6.64%, 12.56%) and 9.82% (95% CI: 6.33%, 13.42%) increase in mortality risk, respectively. People aged ≥65 years and lived in South residential zone where most slums were located, were more vulnerable. We observed flatter increases in mortality risk associated with high temperatures comparing the period of 2003–2017 to 1987–2002. Interpretation The analyses provided better understanding of the relationship of high temperatures with mortality in underdeveloped tropical regions and important implications in developing heat warning system for local government. The proposed CV approaches will benefit future scientific work.

Accumulating evidence suggests that air pollution increases pregnancy loss; however, most previous studies have focused on case identification from medical records, which may underrepresent early pregnancy losses. Our objective was to investigate the association between acute and chronic exposure to ambient air pollution and time to pregnancy loss among women undergoing assisted reproductive technologies (ART) who are closely followed throughout early pregnancy. We included 275 women (345 human chorionic gonadotropin (hCG)-confirmed pregnancies) undergoing ART at a New England academic fertility center. We estimated daily nitrogen dioxide (NO(2)), ozone (O(3)), fine particulate matter

It has been hypothesized that solar and geomagnetic activity can affect the function of the autonomic nervous system (ANS) and melatonin secretion, both of which may influence immune response. We investigated the association between solar geomagnetic activity and white blood cell counts in the Normative Aging Study (NAS) Cohort between 2000 and 2013. Linear mixed effects models with moving day averages ranging from 0 to 28 days were used to evaluate the effects of solar activity measures, interplanetary magnetic field (IMF), and sunspot number (SSN), and a measure of geomagnetic activity, K Index (K), on total white blood cell (WBC), neutrophil, monocytes, lymphocyte, eosinophil, and basophil concentrations. After adjusting for demographic and health-related factors, there were consistently significant associations between IMF, SSN, and Kp index, with reductions in total WBC, neutrophils, and basophil counts. These associations were stronger with longer moving averages. The associations were similar after adjusting for ambient air particulate pollution and particle radioactivity. Our findings suggest that periods of increased solar and geomagnetic activity result in lower WBC, neutrophil, and basophil counts that may contribute to mil mild immune suppression.

BACKGROUND: Several studies have shown that exposure to particulate matter (PM) may lead to increased systemic blood pressure, but the underlying biological mechanisms remain unknown. Emerging evidence shows that extracellular vesicle-enriched miRNAs (evmiRNAs) are associated with PM exposure and cardiovascular risk. In this study, we investigated the role of evmiRNAs in the association between PM and blood pressure, as well as their epigenetic regulation by DNA methylation. METHODS: Participants (n=22, men) were randomly selected from the Veterans Affairs Normative Aging Study (NAS). Long-term (1-year and 6-month average) PM(2.5) exposure was estimated at 1×1-km resolution using spatio-temporal prediction models and BC was estimated using validated time varying land use regression models. We analyzed 31 evmiRNAs detected in ≥90% of all individuals and for statistical analysis, we used mixed effects models with random intercept adjusted for age, body mass index, smoking, C-reactive protein, platelets, and white blood cells. RESULTS: We found that per each 2-standard deviations increase in 6-month PM(2.5) ambient levels, there was an increase in 0.19 mm Hg (95% Confidence Interval [95%CI]: 0.11, 0.28 mmHg; p

BACKGROUND: Prenatal particulate air pollution exposure may alter lung growth and development in utero in a time-sensitive and sex-specific manner, resulting in reduced lung function in childhood. Such relationships have not been examined for nitrate (NO(3)(−)). METHODS: We implemented Bayesian distributed lag interaction models (BDLIMs) to identify sensitive prenatal windows for the influence of NO(3)(−) on lung function at age 7 years, assessing effect modification by fetal sex. Analyses included 191 mother-child dyads. Daily ambient NO(3)(−) exposure over pregnancy was estimated using a hybrid chemical transport (Geos-Chem)/land-use regression model. Spirometry was performed at mean (SD) age of 6.99 (0.89) years, with forced expiratory volume in one second (FEV(1)) and forced vital capacity (FVC) z-scores accounting for child age, sex, height and race/ethnicity. RESULTS: Most mothers were Hispanic (65%) or Black (22%), had ≤ high school education (67%), and never smoked (71%); 17% children had asthma. BDILMs adjusted for maternal age and education and child’s asthma identified an early sensitive window of 6-12 weeks gestation, during which increased NO(3)(−) was significantly associated with reduced FEV(1) z-scores specifically among boys. BDLIM analyses demonstrated similar sex-specific patterns for FVC. CONCLUSION: Early gestational NO(3)(−) exposure is associated with reduced child lung function, especially in boys.

Rationale Evidence linking traffic-related particle exposure to systemic effects in chronic obstructive lung disease (COPD) patients is limited. Objectives Assess relationships between indoor black carbon (BC), a tracer of traffic-related particles, and plasma biomarkers of systemic inflammation and endothelial activation. Methods BC was measured by reflectance in fine particle samples over a mean of 7.6 days in homes of 85 COPD patients up to 4 times seasonally over a year. After the completion of sampling, plasma C-reactive protein (CRP), interleukin-6 (IL-6), and soluble vascular adhesion molecule-1 (sVCAM-1) were measured. Current smokers and homes with major sources of BC were excluded; therefore, indoor BC was primarily a measure of infiltrated outdoor BC. Mixed effects regression models with a random intercept for each participant were used to assess BC effects at different times (1–9 days before phlebotomy) and in the multi-day sample. Results Measured median BC was 0.19 µg/m3 (interquartile range, IQR=0.22 µg/m3). Adjusting for season, race, age, BMI, heart disease, diabetes, ambient temperature, relative humidity, a recent cold or similar illness, and blood draw time, there was a positive relationship between BC and CRP. The largest effect size was for BC averaged over the previous seven days (11.8% increase in CRP per IQR; 95%CI = 1.8–22.9). Effects were greatest among non-statin users and persons with diabetes. There were positive effects of BC on IL-6 only in non-statin users. There were no associations with sVCAM-1. Conclusions These results demonstrate exposure-response relationships between indoor BC with biomarkers of systemic inflammation in COPD patients, with stronger relationships in persons not using statins and with diabetes.

The relationship between ambient fine particulate matter (PM(2.5)) and metabolic syndrome (MetS) is understudied. It also remains unknown whether familial factors play a role in this relationship. In a study of 566 middle-aged twins, we examined the association of PM(2.5) with MetS risk factors, measured by a MetS score as a summation of individual risk factors (range, 0 to 5). High-resolution PM(2.5) estimates were obtained through previously validated models that incorporated monitor and satellite derived data. We estimated two-year average PM(2.5) concentrations based on the ZIP code of each twin’s residence. We used ordinal response models adapted for twin studies. When treating twins as individuals, the odds ratio of having 1-point higher MetS score was 1.78 for each 10 μg/m(3)-increase in exposure to PM(2.5) (confidence interval [CI]: 1.01, 3.15), after adjusting for potential confounders. This association was mainly between pairs; the odds ratio was 1.97 (CI: 1.01, 3.84) for each 10 μg/m(3)-increase in the average pairwise exposure level. We found no significant difference in MetS scores within pairs who were discordant for PM(2.5) exposure. In conclusion, higher PM(2.5) in residence area is associated with more MetS risk factors. This association, however, is confounded by shared familial factors.

Background A growing body of evidence links maternal exposure to particulate matter Methods We evaluated PM2.5 exposure and placental RNA-sequencing data among study participants enrolled in the Rhode Island Child Health Study (RICHS). Daily residential PM2.5 levels were estimated using a hybrid model incorporating land-use regression and satellite remote sensing data. Distributed lag models were implemented to assess the impact on infant birthweight due to PM2.5 weekly averages ranging from 12 weeks prior to gestation until birth. Correlations were assessed between PM2.5 levels averaged across the identified window of susceptibility and a placental transcriptome-wide gene coexpression network previously generated using the WGCNA R package. Results We identified a sensitive window spanning 12 weeks prior to and 13 weeks into gestation during which maternal PM2.5 exposure is significantly associated with reduced infant birthweight. Two placental coexpression modules enriched for genes involved in amino acid transport and cellular respiration were correlated with infant birthweight as well as maternal PM2.5 exposure levels averaged across the identified growth restriction window. Conclusion Our findings suggest that maternal PM2.5 exposure may alter placental programming of fetal growth, with potential implications for downstream health effects, including susceptibility to cardiometabolic health outcomes and viral infections.

Fine ambient particulate matter has been widely associated with multiple health effects. Mitigation hinges on understanding which sources are contributing to its toxicity. Black Carbon (BC), an indicator of particles generated from traffic sources, has been associated with a number of health effects however due to its high spatial variability, its concentration is difficult to estimate. We previously fit a model estimating BC concentrations in the greater Boston area; however this model was built using limited monitoring data and could not capture the complex spatio-temporal patterns of ambient BC. In order to improve our predictive ability, we obtained more data for a total of 24,301 measurements from 368 monitors over a 12 year period in Massachusetts, Rhode Island and New Hampshire. We also used Nu-Support Vector Regression (nu-SVR) – a machine learning technique which incorporates nonlinear terms and higher order interactions, with appropriate regularization of parameter estimates. We then used a generalized additive model to refit the residuals from the nu-SVR and added the residual predictions to our earlier estimates. Both spatial and temporal predictors were included in the model which allowed us to capture the change in spatial patterns of BC over time. The 10 fold cross validated (CV) R2 of the model was good in both cold (10-fold CV R2 = 0.87) and warm seasons (CV R2 = 0.79). We have successfully built a model that can be used to estimate short and long-term exposures to BC and will be useful for studies looking at various health outcomes in MA, RI and Southern NH.

Adverse cardiovascular events have been linked with PMWe utilized a cohort of 5679 patients who had undergone a cardiac catheterization between 2002-2009 and resided in NC. Exposure to PMWe found that the elevated odds for CAD23 and MI were nearly equivalent for all exposure assessment methods. One difference was that data from AQS and the census tract CMAQ showed a rural/urban difference in relative risk, which was not apparent with the satellite or 12km-CMAQ models.Long-term air pollution exposure was associated with coronary artery disease for both modeled and monitored data.

Background Airborne particulate matter (PM) may induce epigenetic changes that potentially lead to chronic diseases. Histone modifications regulate gene expression by influencing chromatin structure that can change gene expression status. We evaluated whether traffic-derived PM exposure is associated with four types of environmentally inducible global histone H3 modifications. Methods The Beijing Truck Driver Air Pollution Study included 60 truck drivers and 60 office workers examined twice, 1–2 weeks apart, for ambient PM10 (both day-of and 14-day average exposures), personal PM2.5, black carbon (BC), and elemental components (potassium, sulfur, iron, silicon, aluminum, zinc, calcium, and titanium). For both PM10 measures, we obtained hourly ambient PM10 data for the study period from the Beijing Municipal Environmental Bureau's 27 representatively distributed monitoring stations. We then calculated a 24 h average for each examination day and a moving average of ambient PM10 measured in the 14 days prior to each examination. Examinations measured global levels of H3 lysine 9 acetylation (H3K9ac), H3 lysine 9 tri-methylation (H3K9me3), H3 lysine 27 tri-methylation (H3K27me3), and H3 lysine 36 tri-methylation (H3K36me3) in blood leukocytes collected after work. We used adjusted linear mixed-effect models to examine percent changes in histone modifications per each μg/m3 increase in PM exposure. Results In all participants each μg/m3 increase in 14-day average ambient PM10 exposure was associated with lower H3K27me3 (β=−1.1%, 95% CI: −1.6, −0.6) and H3K36me3 levels (β=−0.8%, 95% CI: −1.4, −0.1). Occupation-stratified analyses showed associations between BC and both H3K9ac and H3K36me3 that were stronger in office workers (β=4.6%, 95% CI: 0.9, 8.4; and β=4.1%, 95% CI: 1.3; 7.0 respectively) than in truck drivers (β=0.1%, 95% CI: −1.3, 1.5; and β=0.9%, 95% CI: −0.9, 2.7, respectively; both pinteraction Conclusions Our results suggest a possible role of global histone H3 modifications in effects of traffic-derived PM exposures, particularly BC exposure. Future studies should assess the roles of these modifications in human diseases and as potential mediators of air pollution-induced disease, in particular BC exposure.

BACKGROUND: Although many studies have established significant associations between short-term air pollution and the risk of getting cardiovascular diseases, there is a lack of evidence based on causal distributed lag modeling. METHODS: Inverse probability weighting (ipw) propensity score models along with conditional logistic outcome regression models based on a case-crossover study design were applied to get the causal unconstrained distributed (lag0–lag5) as well as cumulative lag effect of short-term exposure to PM2.5/Ozone on hospital admissions of acute myocardial infarction (AMI), congestive heart failure (CHF) and ischemic stroke (IS) among New England Medicare participants during 2000–2012. Effect modification by gender, race, secondary diagnosis of Chronic Obstructive Pulmonary Diseases (COPD) and Diabetes (DM) was explored. RESULTS: Each 10 μg/m3 increase in lag0–lag5 cumulative PM2.5 exposure was associated with an increase of 4.3% (95% confidence interval: 2.2%, 6.4%, percentage change) in AMI hospital admission rate, an increase of 3.9% (2.4%, 5.5%) in CHF rate and an increase of 2.6% (0.4%, 4.7%) in IS rate. A weakened lagging effect of PM2.5 from lag0 to lag5 could be observed. No cumulative short-term effect of ozone on CVD was found. People with secondary diagnosis of COPD, diabetes, female gender and black race are sensitive population. CONCLUSIONS: Based on our causal distributed lag modeling, we found that short-term exposure to an increased ambient PM2.5 level had the potential to induce higher risk of CVD hospitalization in a causal way. More attention should be paid to population of COPD, diabetes, female gender and black race.

The burning of fossil fuels – especially coal, petrol, and diesel – is a major source of airborne fine particulate matter (PM2.5), and a key contributor to the global burden of mortality and disease. Previous risk assessments have examined the health response to total PM2.5, not just PM2.5 from fossil fuel combustion, and have used a concentration-response function with limited support from the literature and data at both high and low concentrations. This assessment examines mortality associated with PM2.5 from only fossil fuel combustion, making use of a recent meta-analysis of newer studies with a wider range of exposure. We also estimated mortality due to lower respiratory infections (LRI) among children under the age of five in the Americas and Europe, regions for which we have reliable data on the relative risk of this health outcome from PM2.5 exposure. We used the chemical transport model GEOS-Chem to estimate global exposure levels to fossil-fuel related PM2.5 in 2012. Relative risks of mortality were modeled using functions that link long-term exposure to PM2.5 and mortality, incorporating nonlinearity in the concentration response. We estimate a global total of 10.2 (95% CI: −47.1 to 17.0) million premature deaths annually attributable to the fossil-fuel component of PM2.5. The greatest mortality impact is estimated over regions with substantial fossil fuel related PM2.5, notably China (3.9 million), India (2.5 million) and parts of eastern US, Europe and Southeast Asia. The estimate for China predates substantial decline in fossil fuel emissions and decreases to 2.4 million premature deaths due to 43.7% reduction in fossil fuel PM2.5 from 2012 to 2018 bringing the global total to 8.7 (95% CI: −1.8 to 14.0) million premature deaths. We also estimated excess annual deaths due to LRI in children (0–4 years old) of 876 in North America, 747 in South America, and 605 in Europe. This study demonstrates that the fossil fuel component of PM2.5 contributes a large mortality burden. The steeper concentration-response function slope at lower concentrations leads to larger estimates than previously found in Europe and North America, and the slower drop-off in slope at higher concentrations results in larger estimates in Asia. Fossil fuel combustion can be more readily controlled than other sources and precursors of PM2.5 such as dust or wildfire smoke, so this is a clear message to policymakers and stakeholders to further incentivize a shift to clean sources of energy.

BACKGROUND: Natural vegetation, or greenness, is thought to improve health through its ability to buffer and reduce harmful environmental exposures as well as relieve stress, promote physical activity, restore attention, and increase social cohesion. In concert, these effects could help mitigate the detrimental effects of air pollution on reproductive aging in women. METHODS: Our analysis included 565 women attending the Massachusetts General Hospital Fertility Center (2004–2014) who had a measured antral follicle count (AFC), a marker of ovarian reserve. We calculated peak residential greenness in the year prior to AFC using 250m(2) normalized difference vegetation index (NDVI) from the Terra and Aqua satellites operated by the United States National Aeronautics and Space Administration. Validated spatiotemporal models estimated daily residential exposure to particulate matter

Epidemiologic studies have found associations between fine particulate matter (PM2.5) exposure and adverse health effects using exposure models that incorporate monitoring data and other relevant information. Here, we use nine PM2.5 concentration models (i.e., exposure models) that span a wide range of methods to investigate i) PM2.5 concentrations in 2011, ii) potential changes in PM2.5 concentrations between 2011 and 2028 due to on-the-books regulations, and iii) PM2.5 exposure for the U.S. population and four racial/ethnic groups. The exposure models included two geophysical chemical transport models (CTMs), two interpolation methods, a satellite-derived aerosol optical depth-based method, a Bayesian statistical regression model, and three data-rich machine learning methods. We focused on annual predictions that were regridded to 12-km resolution over the conterminous U.S., but also considered 1-km predictions in sensitivity analyses. The exposure models predicted broadly consistent PM2.5 concentrations, with relatively high concentrations on average over the eastern U.S. and greater variability in the western U.S. However, differences in national concentration distributions (median standard deviation: 1.00 μg m-3) and spatial distributions over urban areas were evident. Further exploration of these differences and their implications for specific applications would be valuable. PM2.5 concentrations were estimated to decrease by about 1 μg m-3 on average due to modeled emission changes between 2011 and 2028, with decreases of more than 3 μg m-3 in areas with relatively high 2011 concentrations that were projected to experience relatively large emission reductions. Agreement among models was closer for population-weighted than uniformly weighted averages across the domain. About 50% of the population was estimated to experience PM2.5 concentrations less than 10 μg m-3 in 2011 and PM2.5 improvements of about 2 μg m-3 due to modeled emission changes between 2011 and 2028. Two inequality metrics were used to characterize differences in exposure among the four racial/ethnic groups. The metrics generally yielded consistent information and suggest that the modeled emission reductions between 2011 and 2028 would reduce absolute exposure inequality on average.

Many studies have reported that PM2.5 was associated with mortality, but these were criticized for unmeasured confounding, not using causal modeling, and not focusing on changes in exposure and mortality rates. Recent studies have used propensity scores, a causal modeling approach that requires the assumption of no unmeasured confounders. We used differences in differences, a causal modeling approach that focuses on exposure changes, and controls for unmeasured confounders by design to analyze PM2.5 and mortality in the U.S. Medicare population, with 623, 036, 820 person-years of follow-up, and 29, 481, 444 deaths. We expanded the approach by clustering ZIP codes into 32 groups based on racial, behavioral and socioeconomic characteristics, and analyzing each cluster separately. We controlled for multiple time varying confounders within each cluster. A separate analysis examined participants whose exposure was always below 12 μg/m3. We found an increase of 1 μg/m3 in PM2.5 produced an increased risk of dying in that year of 3.85 × 10−4 (95% CI 1.95 × 10−4, 5.76 × 10−4). This corresponds to 14,000 early deaths per year per 1 μg/m3. When restricted to exposures below 12 μg/m3, the increased mortality risk was 4.26 × 10−4 (95% CI 1.43 × 10−4, 7.09 × 10−4). Using a causal modeling approach robust to omitted confounders, we found associations of PM2.5 with increased death rates, including below U.S. and E.U. standards.

Temperature has been related to mean differences in DNA methylation. However, heterogeneity in these associations may exist across the distribution of methylation outcomes. This study examined whether the association between three-week averaged of temperature and methylation differs across quantiles of the methylation distributions in nine candidate genes. We measured gene-specific blood methylation repeatedly in 777 elderly men participating in the Normative Aging Study (1999–2010). We fit quantile regressions for longitudinal data to investigate whether the associations of temperature on methylation (expressed as %5mC) varied across the distribution of the methylation outcomes. We observed heterogeneity in the associations of temperature across percentiles of methylation in F3, TLR-2, CRAT, iNOS, and ICAM-1 genes. For instance, an increase in three-week temperature exposure was associated with a longer left-tail of the F3 methylation distribution. A 5°C increase in temperature was associated with a 0.15%5mC (95% confidence interval (CI): −0.27, −0.04) decrease on the 20th quantile of F3 methylation, but was not significantly related to the 80th quantile of this distribution (Estimate:0.06%5mC, 95%CI: −0.22, 0.35). Individuals with low values of F3, TLR-2, CRAT, and iNOS methylation, as well as a high value of ICAM-1 methylation, may be more susceptible to temperature effects on systemic inflammation.

Few studies have examined the association between ambient temperature and cognitive function, or used exposure to temperature at a given address instead of a single stationary monitor. The existing literature on the temperature-cognition relationship has mostly consisted of experimental studies that involve a small sample size and a few specific temperature values. In the current study, we examined the association between residential air temperature and Mini-Mental State Examination (MMSE) scores, a quantitative measurement of cognitive function, in a longitudinal cohort of elderly men. Residential air temperature was estimated by a novel spatiotemporal approach that incorporates satellite remote sensing, land use regression, meteorological variables and spatial smoothing in the Northeastern USA. We then applied logistic regression generalized estimating equations to examine the relationship between residential temperature (range: −5.8~25.7 degrees C), and the risk of low MMSE scores (MMSE scores ≤ 25) among 594 elderly men (1,085 visits in total) from the Veterans Affairs Normative Aging Study, 2000–2008. Sensitivity analysis on visits wherein subjects lived within 30 km of the clinic center in Massachusetts or aged ≥ 70 years was also evaluated. A statistically significant, U-shaped association between residential air temperature and low MMSE score (p-value = 0.036) was observed. Sensitivity analysis suggested that the estimated effect remains among individuals aged ≥ 70 years. In conclusion, the data suggest that risk of low MMSE scores is highest when temperature is either high or low, and lowest when ambient temperature is approximately within 10–15 degrees C in a cohort of elderly men. Further research is needed to confirm our findings and assess generalizability to other populations.

BACKGROUND: Lead (Pb) is widespread and exposure to this non-essential heavy metal can cause multiple negative health effects; however the mechanisms underlying these effects remain incompletely understood. OBJECTIVES: To identify plasma metabolomic signatures of Pb exposure, as measured in blood and toenails. METHODS: In a subset of men from the VA Normative Aging Study, mass-spectrometry based plasma metabolomic profiling was performed. Pb levels were measured in blood samples and toenail clippings collected concurrently. Multivariable linear regression models, smoothing splines and Pathway analyses were employed to identify metabolites associated with Pb exposure. RESULTS: In 399 men, 858 metabolites were measured and passed QC, of which 154 (17.9%) were significantly associated with blood Pb (p < 0.05). Eleven of these passed stringent correction for multiple testing, including pro-hydroxy-pro (β(95%CI): 1.52 (0.93,2.12), p = 7.18×10(−7)), N-acetylglycine (β(95%CI): 1.44 (0.85,2.02), p = 1.12×10(−6)), tartarate (β(95%CI): 0.68 (0.35,1.00), p = 4.84×10(−5)), vanillylmandelate (β(95%CI): 1.05 (0.47,1.63), p = 4.44×10(−7)), and lysine (β(95%CI): 1.88 (−2.8,−0.95), p = 9.10×10(−5)). A subset of 48 men had a second blood sample collected a mean of 6.1 years after their first. Three of the top eleven metabolites were also significant in this second blood sample. Furthermore, we identified 70 plasma metabolites associated with Pb as measured in toenails. Twenty-three plasma metabolites were significantly associated with both blood and toenail measures, while others appeared to be specific to the biosample in which Pb was measured. For example, benzanoate metabolism appeared to be of importance with the longer-term exposure assessed by toenails. DISCUSSION: Pb exposure is responsible for 0.6% of the global burden of disease and metabolomics is particularly well-suited to explore its pathogenic mechanisms. In this study, we identified metabolites and metabolomic pathways associated with Pb exposure that suggest that Pb exposure acts through oxidative stress and immune dysfunction. These findings help us to better understand the biology of this important public health burden.

Background Globally, toxic metal exposures are a well-recognized risk factor for many adverse health outcomes. DNA methylation-based measures of biological aging are predictive of disease, but have poorly understood relationships with metal exposures. Objective We performed a pilot study examining the relationships of 24-h urine metal concentrations with three novel DNA methylation-based measures of biological aging: DNAmAge, GrimAge, and PhenoAge. Methods We utilized a previously established urine panel of five common metals [arsenic (As), cadmium (Cd), lead (Pb), manganese (Mn), and mercury (Hg)] found in a subset of the elderly US Veterans Affairs Normative Aging Study cohort (N = 48). The measures of DNA methylation-based biological age were calculated using CpG sites on the Illumina HumanMethylation450 BeadChip. Bayesian Kernel Machine Regression (BKMR) was used to determine metals most important to the aging outcomes and the relationship of the cumulative metal mixture with the outcomes. Individual relationships of important metals with the biological aging outcomes were modeled using fully-adjusted linear models controlling for chronological age, renal function, and lifestyle/environmental factors. Results Mn was selected as important to PhenoAge. A 1 ng/mL increase in urine Mn was associated with a 9.93-year increase in PhenoAge (95%CI: 1.24, 18.61, p = 0.03). The cumulative urine metal mixture was associated with increases in PhenoAge. Compared to a model where each metal in the mixture is set to its 50th percentile value, every one-unit increase of the cumulative mixture with each metal at its 70th percentile was associated with a 2.53-year increase in PhenoAge (95%CI: 0.10, 4.96, P Conclusion Our results add novel evidence that metals detected in urine are associated with increases in biological aging and suggest that these DNA methylation-based measures may be useful for identifying individuals at-risk for diseases related to toxic metal exposures. Further research is necessary to confirm these findings more broadly.

Background Although many studies have established significant associations between short-term air pollution and the risk of getting cardiovascular diseases, there is a lack of evidence based on causal distributed lag modeling. Methods Inverse probability weighting (ipw) propensity score models along with conditional logistic outcome regression models based on a case-crossover study design were applied to get the causal unconstrained distributed (lag0-lag5) as well as cumulative lag effect of short-term exposure to PM2.5/Ozone on hospital admissions of acute myocardial infarction (AMI), congestive heart failure (CHF) and ischemic stroke (IS) among New England Medicare participants during 2000–2012. Effect modification by gender, race, secondary diagnosis of Chronic Obstructive Pulmonary Diseases (COPD) and Diabetes (DM) was explored. Results Each 10 μg/m3 increase in lag0-lag5 cumulative PM2.5 exposure was associated with an increase of 4.3% (95% confidence interval: 2.2%, 6.4%, percentage change) in AMI hospital admission rate, an increase of 3.9% (2.4%, 5.5%) in CHF rate and an increase of 2.6% (0.4%, 4.7%) in IS rate. A weakened lagging effect of PM2.5 from lag0 to lag5 could be observed. No cumulative short-term effect of ozone on CVD was found. People with secondary diagnosis of COPD, diabetes, female gender and black race are sensitive population. Conclusions Based on our causal distributed lag modeling, we found that short-term exposure to an increased ambient PM2.5 level had the potential to induce higher risk of CVD hospitalization in a causal way. More attention should be paid to population of COPD, diabetes, female gender and black race.

Prenatal traffic-related air pollution exposure is linked to adverse birth outcomes. However, modifying effects of maternal body mass index (BMI) and infant sex remain virtually unexplored.We examined whether associations between prenatal air pollution and birth weight differed by sex and maternal BMI in 670 urban ethnically mixed mother-child pairs.Black carbon (BC) levels were estimated using a validated spatio-temporal land-use regression (LUR) model; fine particulate matter (PM2.5) was estimated using a hybrid LUR model incorporating satellite-derived Aerosol Optical Depth measures. Using stratified multivariable-adjusted regression analyses, we examined whether associations between prenatal air pollution and calculated birth weight for gestational age (BWGA) z-scores varied by sex and maternal pre-pregnancy BMI.Median birth weight was 3.3±0.6kg; 33% of mothers were obese (BMI ≥30kg/m(3)). In stratified analyses, the association between higher PM2.5 and lower birth weight was significant in males of obese mothers (-0.42 unit of BWGA z-score change per IQR increase in PM2.5, 95%CI: -0.79 to -0.06) ( PM2.5×sex×obesity Pinteraction=0.02). Results were similar for BC models (Pinteraction=0.002).Associations of prenatal exposure to traffic-related air pollution and reduced birth weight were most evident in males born to obese mothers.

Long-term exposure to ambient fine particulate matter (≤ 2.5 μg/mWe systematically searched all published cohort studies examining the association between long term exposure to PMA total of 53 studies that provided 135 estimates of the quantitative association between the risk of mortality and exposure to PMThis meta-analysis provides strong evidence for the adverse effect of PM

Background How adaptation and intensity of heat waves affect heat wave-related mortality is unclear, making health projections difficult. Methods We estimated the effect of heat waves, the effect of the intensity of heat waves, and adaptation on mortality in 209 U.S. cities with 168 million people during 1962–2006. We improved the standard time-series models by incorporating the intensity of heat waves using excess heat factor (EHF) and estimating adaptation empirically using interactions with yearly mean summer temperature (MST). We combined the epidemiological estimates for heat wave, intensity, and adaptation with the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model dataset to project heat wave-related mortality by 2050. Results The effect of heat waves increased with its intensity. Adaptation to heat waves occurred, which was shown by the decreasing effect of heat waves with MST. However, adaptation was lessened as MST increased. Ignoring adaptation in projections would result in a substantial overestimate of the projected heat wave-related mortality (by 277–747% in 2050). Incorporating the empirically estimated adaptation into projections would result in little change in the projected heat wave-related mortality between 2006 and 2050. This differs regionally, however, with increasing mortality over time for cities in the southern and western U.S. but decreasing mortality over time for the north. Conclusions Accounting for adaptation is important to reduce bias in the projections of heat wave-related mortality. The finding that the southern and western U.S. are the areas that face increasing heat-related deaths is novel, and indicates that more regional adaptation strategies are needed.

Background Evolving animal studies and limited epidemiological data show that prenatal air pollution exposure is associated with childhood obesity. Timing of exposure and child sex may play an important role in these associations. We applied an innovative method to examine sex-specific sensitive prenatal windows of exposure to PM2.5 on anthropometric measures in preschool-aged children. Methods Analyses included 239 children born ≥ 37 weeks gestation in an ethnically-mixed lower-income urban birth cohort. Prenatal daily PM2.5 exposure was estimated using a validated satellite-based spatio-temporal model. Body mass index z-score (BMI-z), fat mass, % body fat, subscapular and triceps skinfold thickness, waist and hip circumferences and waist-to-hip ratio (WHR) were assessed at age 4.0 ± 0.7 years. Using Bayesian distributed lag interaction models (BDLIMs), we examined sex differences in sensitive windows of weekly averaged PM2.5 levels on these measures, adjusting for child age, maternal age, education, race/ethnicity, and pre-pregnancy BMI. Results Mothers were primarily Hispanic (55%) or Black (26%), had ≤ 12 years of education (66%) and never smoked (80%). Increased PM2.5 exposure 8–17 and 15–22 weeks gestation was significantly associated with increased BMI z-scores and fat mass in boys, but not in girls. Higher PM2.5 exposure 10–29 weeks gestation was significantly associated with increased WHR in girls, but not in boys. Prenatal PM2.5 was not significantly associated with other measures of body composition. Estimated cumulative effects across pregnancy, accounting for sensitive windows and within-window effects, were 0.21 (95%CI = 0.01–0.37) for BMI-z and 0.36 (95%CI = 0.12–0.68) for fat mass (kg) in boys, and 0.02 (95%CI = 0.01–0.03) for WHR in girls, all per µg/m3 increase in PM2.5. Conclusions Increased prenatal PM2.5 exposure was more strongly associated with indices of increased whole body size in boys and with an indicator of body shape in girls. Methods to better characterize vulnerable windows may provide insight into underlying mechanisms contributing to sex-specific associations.

Hot weather increases risk of mortality. Previous studies used different sets of weather variables to characterize heat stress, resulting in variation in heat-mortality associations depending on the metric used. We employed a statistical learning method - random forests - to examine which of the various weather variables had the greatest impact on heat-related mortality. We compiled a summertime daily weather and mortality counts dataset from four U.S. cities (Chicago, IL; Detroit, MI; Philadelphia, PA; and Phoenix, AZ) from 1998 to 2006. A variety of weather variables were ranked in predicting deviation from typical daily all-cause and cause-specific death counts. Ranks of weather variables varied with city and health outcome. Apparent temperature appeared to be the most important predictor of heat-related mortality for all-cause mortality. Absolute humidity was, on average, most frequently selected as one of the top variables for all-cause mortality and seven cause-specific mortality categories. Our analysis affirms that apparent temperature is a reasonable variable for activating heat alerts and warnings, which are commonly based on predictions of total mortality in next few days. Additionally, absolute humidity should be included in future heat-health studies. Finally, random forests can be used to guide the choice of weather variables in heat epidemiology studies.

Higher long-term cumulative lead exposure predicts faster cognitive decline in older men, but evidence of an association in women is lacking.To determine if there is an association between lead exposure and cognitive decline in women.This study considers a sample of 584 women from the Nurses' Health Study who live in or near Boston, Massachusetts. We quantified lead exposure using biomarkers of lead exposure assessed in 1993-2004 and evaluated cognitive decline by repeated performance on a telephone battery of cognitive tests primarily assessing learning, memory, executive function, and attention completed in 1995-2008. All cognitive test scores were z-transformed for use in analyses. We used linear mixed models with random effects to quantify the association between each lead biomarker and change in cognition overall and on each individual test.Consideration of individual tests showed greater cognitive decline with increased tibia lead concentrations, a measure of long-term cumulative exposure, for story memory and category fluency. The estimated excess annual decline in overall cognitive test z-score per SD increase in tibia bone lead concentration was suggestive, although the confidence intervals included the null (0.024 standard units, 95% confidence interval: -0.053, 0.004 - an additional decline in function equivalent to being 0.33 years older). We found little support for associations between cognitive decline and patella or blood lead, which provide integrated measures of exposure over shorter timeframes.Long-term cumulative lead exposure may be weakly associated with faster cognitive decline in community-dwelling women, at least in some cognitive domains.

Background Continuing chronic and sporadic high-level of lead exposure in some regions in the U.S. has directed public attention to the effects of lead on human health. Long-term lead exposure has been associated with faster cognitive decline in older individuals; however, genetic susceptibility to lead-related cognitive decline during aging has been poorly studied. Methods We determined the interaction of APOE- epsilon variants and environmental lead exposure in relation to age-related cognitive decline. We measured tibia bone lead by K-shell-x-ray fluorescence, APOE -epsilon variants by multiplex PCR and global cognitive z-scores in 489 men from the VA-Normative Aging Study. To determine global cognitive z-scores we incorporated multiple cognitive assessments, including word list memory task, digit span backwards, verbal fluency test, sum of drawings, and pattern comparison task, which were assessed at multiple visits. We used linear mixed-effect models with random intercepts for individual and for cognitive test. Results An interquartile range (IQR:14.23 μg/g) increase in tibia lead concentration was associated with a 0.06 (95% confidence interval [95%CI]: −0.11 to −0.01) lower global cognition z-score. In the presence of both e4 alleles, one IQR increase in tibia lead was associated with 0.57 (95%CI: −0.97 to −0.16; p-value for interaction: 0.03) lower total cognition z-score. A borderline association was observed in presence of one e4 allele (Estimate-effect per 1-IQR increase: −0.11, 95%CI: −0.22, 0.01) as well as lack of association in individuals without APOE e4 allele. Conclusions Our findings suggest that individuals carrying both e4 alleles are more susceptible to lead impact on global cognitive decline during aging.

While exposures to high and low air temperatures are associated with cardiovascular mortality, the underlying mechanisms are poorly understood. The risk factors for cardiovascular disease include high levels of total cholesterol and low-density lipoprotein (LDL), and low levels of high-density lipoprotein (HDL). We investigated whether temperature was associated with changes in circulating lipid levels, and whether this might explain part of the association with increased cardiovascular events.The study cohort consisted of 478 men in the greater Boston area with a mean age of 74.2 years. They visited the clinic every 3-5 years between 1995 and 2008 for physical examination and to complete questionnaires. We excluded from analyses all men taking statin medication and all days with missing data, resulting in a total of 862 visits. Associations between three temperature variables (ambient, apparent, and dew point temperature) and serum lipid levels (total cholesterol, HDL, LDL, and triglycerides) were studied with linear mixed models that included possible confounders such as air pollution and a random intercept for each subject.We found that HDL decreased -1.76% (95% CI: from -3.17 to -0.32, lag 2 days), and -5.58% (95% CI: from -8.87 to -2.16, moving average of 4 weeks) for each 5°C increase in mean ambient temperature. For the same increase in mean ambient temperature, LDL increased by 1.74% (95% CI: 0.07-3.44, lag 1 day) and 1.87% (95% CI: 0.14-3.63, lag 2 days). These results were also similar for apparent and dew point temperatures. No changes were found in total cholesterol or triglycerides in relation to temperature increase.Changes in HDL and LDL levels associated with an increase in ambient temperature may be among the underlying mechanisms of temperature-related cardiovascular mortality.

The relationship between ambient air pollution and daily mortality in seven major cities of Korea for the period 1991-1997 was examined. These cities account for half of the Korean population (about 22 million). The observed concentrations of sulfur dioxide (SO(2), mean=23.3 ppb), ozone (O(3), mean=23.7 ppb), and total suspended particulates (TSP, mean=77.9 microg/m(3)) during the study period were at levels below Korea's current ambient air quality standards. Generalized additive models were applied to allow for the highly flexible fitting of seasonal and long-term time trends in air pollution as well as nonlinear associations with weather variables, such as air temperature and relative humidity. In city-specific analyses, an increase of 50 ppb of SO(2) corresponded to 1-12% more deaths, given constant weather conditions. The risk of all-cause mortality was estimated to increase by 0.5-4%, with an increase in the 2-day moving average of TSP levels equal to 100 microg/m(3). In multipollutant models with pooled data, we found that the estimated risk of death by SO(2) was notably unaffected by adding the other two pollutants (TSP and O(3)) to the model and was statistically significant in various regression models. The rate ratio (RR) for SO(2) remained elevated, indicating an excess mortality of 3% 50 ppb (RR=1.03; 95% CI, 1.01-1.05). TSP's effect on mortality maintained its significance with O(3), but not with SO(2). This implies that there may be collinearity problems where TSP and SO(2) are included in the same model or that TSP may function less than SO(2) as a surrogate for fine particles in the ambient air of Korea. In conclusion, increased mortality was associated with air pollution at SO(2) levels below the current recommendation for air quality. Further research is needed to clarify the relationship between SO(2) and fine particles in Korea.

In 1992, the U.S. Congress passed the Residential Lead-Based Paint Hazard Reduction Act, which requires the promulgation of health-based dust lead and soil lead standards for residential dwellings to prevent undue lead exposure in children. Unfortunately, the levels of lead in house dust and soil that are associated with elevated blood lead levels among U.S. children remain poorly defined. This pooled analysis was done to estimate the contributions of lead-contaminated house dust and soil to children's blood lead levels. The results of this pooled analysis, the most comprehensive existing epidemiologic analysis of childhood lead exposure, confirm that lead-contaminated house dust is the major source of lead exposure for children. These analyses further demonstrate that a strong relationship between interior dust lead loading and children's blood lead levels persists at dust lead levels considerably below the U.S. Department of Housing and Urban Development's current postabatement standards and the Environmental Protection Agency's guidance levels. Finally, these analyses demonstrate that a child's age, race, mouthing behaviors, and study-site specific factors influence the predicted blood lead level at a given level of exposure. These data can be used to estimate the potential health impact of alternative health-based lead standards for residential sources of lead exposure.

The air pollution disaster in London in 1952 established that very high levels of particulate-based smog can cause dramatic increases in daily mortality. Recently, more than a dozen studies at much lower particle concentrations have reported evidence that exposure to lower levels of airborne particles results in smaller, but nonzero increases in daily mortality. These studies were examined in a meta-analysis. A primary focus of the meta-analysis was to examine effect size estimates across large differences in both the levels of potential confounding factors and in their correlation with airborne particle concentration. In the primary meta-analysis, airborne particle concentration was a significant risk factor for elevated mortality (RR = 1.06, 95% CI = 1.05-1.07). The relative risk is for a 100 micrograms/m3 increase in TSP concentration. While mortality peaked in the cold months in all locations, in the majority of the studies airborne particle concentrations were highest in the warm months, indicating that seasonal patterns were not responsible for the observed associations. The relative risk was 1.06 (95% CI = 1.05-1.07) when the analysis was restricted to cities with summer peaking pollution. The relative risk was identical in cities with above average annual temperatures and cities with colder climates. It was also identical in drier and more humid climates, and similar across a wide range of correlations between temperature and airborne particle concentrations. These results suggest that inadequate weather control was not responsible for the association. A detailed examination of data from Philadelphia showed that control for season and weather was adequate for removing all long-term seasonal and subseasonal patterns from the mortality data, and that using a very flexible nonlinear fit to the weather factors did not disturb the association with TSP. The most reasonable interpretation of this pattern of results is that the association is causal. This is supported by other studies which have reported that particulate air pollution was associated with lung function deficits, increased symptoms, and increased hospitalization.

The association between total daily mortality and air pollution was investigated for a 1-year period (September 1985 through August 1986) in St. Louis and in the counties in eastern Tennessee surrounding Kingston/Harriman. The purpose of this study was to evaluate the relative importance of various measures of particulate and gaseous air pollution as predictors of daily mortality. Concentrations of inhalable particles (PM 10 ), fine particles (PM 2.5 ), the elemental composition of these particles, and aerosols acidity were measured daily during the period of study. The effect of each air pollutant on daily mortality was estimated after controlling for meteorologic and seasonal influences. Total mortality in St. Louis was found to increase 16% (95% CI − 1 to 33%) for each 100 μg/m 3 increase in PM 10 , and by 17% (95% CI − 12 to 57%) in eastern Tennessee. Positive but progressively weaker associations were found with PM 2.5 , sulfate, and aerosol acidity concentrations in both communities. Associations with gaseous pollutants—sulfur dioxide, nitrogen dioxide, and ozone—were all far from statistical significance. Because of the short monitoring period for daily particulate air pollution, the power of this study to detect associations was limited. Nevertheless, statistically significant associations with PM 10 were found in St. Louis, and, more importantly, the estimated effects were consistent between the two communities studied and with other reported analyses of the effects of particles on daily mortality. These data suggest that the acidity of particles is not as important in associations with daily mortality as the mass concentrations of particles.

Particulate air pollution has been associated with increased mortality during episodes of high pollution concentrations. The relationship at lower concentrations has been more controversial, as has the relative role of particles and sulfur dioxide. Replication has been difficult because suspended particle concentrations are usually measured only every sixth day in the U.S. This study used concurrent measurements of total suspended particulates (TSP) and airport visibility from every sixth day sampling for 10 years to fit a predictive model for TSP. Predicted daily TSP concentrations were then correlated with daily mortality counts in Poisson regression models controlling for season, weather, time trends, overdispersion, and serial correlation. A significant correlation (P less than 0.0001) was found between predicted TSP and daily mortality. This correlation was independent of sulfur dioxide, but not vice versa. The magnitude of the effect was very similar to results recently reported from Steubenville, Ohio (using actual TSP measurements), with each 100 micrograms/m3 increase in TSP resulting in a 6% increase in mortality. Graphical analysis indicated a dose-response relationship with no evidence of a threshold down to concentrations below half of the National Ambient Air Quality Standards for particulate matter.

While lead paint has long been known to be a major source of lead poisoning, only a few small epidemiologic studies have attempted to assess directly the relative risk of lead poisoning due to the presence of lead paint. Using data from over 200,000 screening tests of children in the city of Chicago performed between 1976 and 1980, the relative risks can be quantified for children living in a major urban area. Lead paint was found to be a significant predictor of the probability of a child having lead toxicity. As expected, the reduction in leaded gasoline sales during the period reduced mean blood lead levels and increased the percentage of lead toxic children whose toxicity could be attributed to paint lead. Poisson regression models indicated that with the elimination of leaded gasoline, the relative risk of lead toxicity given lead paint exposure was 5.70 (95% CI, 4.13-7.86) during the winter and fall. The relative risk rose to 12.81 (95% CI, 7.33-22.4) in the spring and 15.8 (95% CI, 8.90-28.1) in the summer, probably due to increased exposure to window wells.

To assess the strength of the association between blood lead and children's IQ, a meta-analysis of the studies examining the relationship in school age children was performed. Emphasis was given to the size of the effect, since that allows comparisons that are informative about potential confounding and effect modifiers. Sensitivity analyses were also performed. A highly significant association was found between lead exposure and children's IQ (P < 0.001). An increase in blood lead from 10 to 20 micrograms/dl was associated with a decrease of 2.6 IQ points in the meta-analysis. This result was robust to inclusion or exclusion of the strongest individual studies and to relaxing the age requirements (school age children) of the meta-analysis. Adding eight studies with effect estimates of 0 would still leave a significant association with blood lead (P < 0.01). There was no evidence that the effect was limited to disadvantaged children and there was a suggestion of the opposite. The studies with mean blood lead levels of 15 micrograms/dl or lower in their sample had higher estimated blood lead slopes, suggesting that a threshold at 10 micrograms/dl is implausible. The study with the lowest mean blood lead level was examined using nonparametric smoothing. It showed no evidence of a threshold down to blood lead concentrations of 1 microgram/dl. Lead interferes with GABAergic and dopaminergic neurotransmission. It has been shown to bind to the NMDA receptor and inhibit long-term potentiation in the hippocampal region of the brain. Moreover, experimental studies have demonstrated that blood levels of 10 micrograms/dl interfere with a broad range of cognitive function in primates. Given this support, these associations in humans should be considered causal.

The air pollution disasters in London in 1952, the Meuse valley in 1930, and in Donoroa, Pennsylvania, in 1948 made it clear that extremely high levels of particulate-based smog could produce large increases in the daily mortality rate. Recent studies of fluctuations in daily air pollution and daily mortality have reported associations at much lower concentrations in London during the 1960s and in Philadelphia, Steubenville, Santa Clara, St. Louis, Utah valley, Detroit, and eastern Tennessee in the 1970s and 1980s. Whether these associations are causal or not is a matter of considerable public health concern. If the detailed pattern of the deaths at these lower concentrations appeared similar to the pattern in London, this would strengthen the argument for causality. To examine this issue, the death certificates from Philadelphia were examined on the 5% of the days with the highest particulate air pollution and the 5% of the days with the lowest particulate air pollution during the years 1973-1980. There was little difference in weather between the high and low pollution days, but total suspended particulate matter concentrations averaged 141 micrograms/m3 on the high pollution days versus 47 micrograms/m3 on the low pollution days. The relative risk of dying on the high pollution days was 1.08 P < 0.0001. The relative increase was higher for COPD (1.25) and pneumonia (1.13). Deaths were also elevated for heart disease and stroke; however, there was a substantial increase in the reports of respiratory factors as contributing causes for those underlying causes of death. Dead-on-arrival deaths and deaths outside of hospitals and clinics were also disproportionately increased. This paralleled the pattern seen in London in 1952. The age pattern of the relative risk of death was also similar. This adds to the evidence that the association is causal.

Chronic exposure to particulates has been associated with increased rates of bronchitis and other respiratory ailments, with loss of lung function, and with increased risk of lung cancer. Despite these findings, debate continues about the adverse health effects of exposure to airborne particles at concentrations often seen in urban areas. This issue was examined by looking at reported rates of chronic respiratory illness by standardized questionnaire across 53 urban areas in the United States. Diagnosis of respiratory illness by an examining physician in the First National Health and Nutrition Examination Survey was also considered as an outcome. After controlling for age, race, sex, and cigarette smoking, annual average total suspended particulate concentrations (TSP) were associated with increased risk of chronic bronchitis (odds ratio (OR) = 1.07, 95% confidence interval (CI) 1.02-1.12) and of a respiratory diagnosis by the examining physician (OR = 1.06, 95% CI = 1.02-1.11). The odds ratios are for a 10 micrograms/m3 increase in TSP. When the analysis was restricted to never smokers, the associations remained, with a slight increase in the relative odds associated with airborne particles. Plots of the relative odds by quartiles of TSP exposure, adjusting for covariates, showed dose-dependent increases in risk with increasing exposure. The risk appeared to continue to concentrations below the ambient air quality standard. Given the other recent findings of both acute and chronic effects of particulate pollution, these associations are likely causal.

To assess the impact of short-term exposure to air pollution on respiratory illness in children we recruited pediatricians and hospitals in five German cities to report daily counts of children's visits for croup symptoms and obstructive bronchitis. Data were collected for at least 2 years in each location. These symptoms are predominantly found in very young children, with the croup reporting peaking at 2 years of age and obstructive bronchitis at 1 year. Attacks of croup and obstructive bronchitis were relatively rare events: the mean number of cases of croup per day in each city ranged from 0.5 to 3, and obstructive bronchitis was even less frequent. A total of 6330 cases of croup and 4755 cases of obstructive bronchitis were observed during the study. The distributions of these events were quite skewed and were modeled as a Poisson process. To focus the analysis on short-term correlations and avoid seasonal confounding, biannual, annual (seasonal), and six shorter term cycles were controlled for in the regression models. After controlling for short-term weather factors, total suspended particulate matter (TSP) and nitrogen dioxide (NO2) were associated with croup cases. An increase in TSP levels from 10 micrograms/m3 to 70 micrograms/m3 was associated with a 27% increase in cases of croup; the same increase in NO2 levels resulted in a 28% increase in cases. No pollutant was associated with daily cases of obstructive bronchitis.