Publications by authors named "Joel D Schwartz"

133 Publications

Long-Term Exposure to Particulate Air Pollution Is Associated With 30-Day Readmissions and Hospital Visits Among Patients With Heart Failure.

J Am Heart Assoc 2021 May 4:e019430. Epub 2021 May 4.

Center for Public Health and Environmental Assessment US Environmental Protection Agency Chapel Hill NC.

Background Long-term air pollution exposure is a significant risk factor for inpatient hospital admissions in the general population. However, we lack information on whether long-term air pollution exposure is a risk factor for hospital readmissions, particularly in individuals with elevated readmission rates. Methods and Results We determined the number of readmissions and total hospital visits (outpatient visits+emergency room visits+inpatient admissions) for 20 920 individuals with heart failure. We used quasi-Poisson regression models to associate annual average fine particulate matter at the date of heart failure diagnosis with the number of hospital visits and 30-day readmissions. We used inverse probability weights to balance the distribution of confounders and adjust for the competing risk of death. Models were adjusted for age, race, sex, smoking status, urbanicity, year of diagnosis, short-term fine particulate matter exposure, comorbid disease, and socioeconomic status. A 1-µg/m increase in fine particulate matter was associated with a 9.31% increase (95% CI, 7.85%-10.8%) in total hospital visits, a 4.35% increase (95% CI, 1.12%-7.68%) in inpatient admissions, and a 14.2% increase (95% CI, 8.41%-20.2%) in 30-day readmissions. Associations were robust to different modeling approaches. Conclusions These results highlight the potential for air pollution to play a role in hospital use, particularly hospital visits and readmissions. Given the elevated frequency of hospitalizations and readmissions among patients with heart failure, these results also represent an important insight into modifiable environmental risk factors that may improve outcomes and reduce hospital use among patients with heart failure.
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http://dx.doi.org/10.1161/JAHA.120.019430DOI Listing
May 2021

The effect of prenatal temperature and PM exposure on birthweight: Weekly windows of exposure throughout the pregnancy.

Environ Int 2021 Apr 30;155:106588. Epub 2021 Apr 30.

Icahn School of Medicine at Mount Sinai, Department of Environmental Medicine and Public Health, New York, NY, USA.

Background: Birthweight is a strong predictor of normal growth, healthy development, and survival. Several studies have found associations between temperature, fine particulate matter (PM), and birth weight. However, the relevant timing of exposures varies between studies and is yet unclear. Therefore, we assessed the difference in term birthweight (TBW) associated with weekly exposure to temperature and PM throughout 37 weeks of gestation.

Methods: We included all singleton live term births in Massachusetts, U.S between 2004 and 2015 (n = 712,438). Weekly PM and temperature predictions were estimated on a 1 km grid from satellite-based models. We utilized a distributed lag nonlinear model (DLNM) to estimate the difference in TBW associated with weekly exposures from the last menstrual period to 37 weeks of gestation.

Results: We found a nonlinear association with prenatal temperature exposure. Larger effects were observed in warmer temperatures, where higher temperatures were negatively associated with TBW. Temperature effects were larger in the first and final weeks of gestation. We observed a negative difference in TBW associated with PM exposure. Overall, a 1 µg/m increase in prenatal exposure was associated with 3.9 g lower TBW (95% CI -5.0 g; -2.9 g). PM effects were larger in the final weeks of gestation.

Conclusion: We found heat and PM exposure to be related to lower TBW. Our findings suggest that women are more susceptible to both exposures towards the end of pregnancy. Susceptibility to heat was higher in the initial weeks of pregnancy as well. These critical windows of susceptibility can be communicated to pregnant women during routine prenatal visits to increase awareness and target interventions to reduce exposures.
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http://dx.doi.org/10.1016/j.envint.2021.106588DOI Listing
April 2021

Ambient PM species and ultrafine particle exposure and their differential metabolomic signatures.

Environ Int 2021 06 24;151:106447. Epub 2021 Feb 24.

Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA; Channing Division of Network Medicine; Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02129, USA; Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.

Background: The metabolomic signatures of short- and long-term exposure to PM have been reported and linked to inflammation and oxidative stress. However, little is known about the relative contribution of the specific PM species (hence sources) that drive these metabolomic signatures.

Objectives: We aimed to determine the relative contribution of the different species of PM exposure to the perturbed metabolic pathways related to changes in the plasma metabolome.

Methods: We performed mass-spectrometry based metabolomic profiling of plasma samples among men from the Normative Aging Study to identify metabolic pathways associated with PM species. The exposure windows included short-term (one, seven-, and thirty-day moving average) and long-term (one year moving average). We used linear mixed-effect regression with subject-specific intercepts while simultaneously adjusting for PM, NO, O, temperature, relative humidity, and covariates and correcting for multiple testing. We also used independent component analysis (ICA) to examine the relative contribution of patterns of PM species.

Results: Between 2000 and 2016, 456 men provided 648 blood samples, in which 1158 metabolites were quantified. We chose 305 metabolites for the short-term and 288 metabolites for the long-term exposure in this analysis that were significantly associated (p-value < 0.01) with PM to include in our PM species analysis. On average, men were 75.0 years old and their body mass index was 27.7 kg/m. Only 3% were current smokers. In the adjusted models, ultrafine particles (UFPs) were the most significant species of short-term PM exposure followed by nickel, vanadium, potassium, silicon, and aluminum. Black carbon, vanadium, zinc, nickel, iron, copper, and selenium were the significant species of long-term PM exposure. We identified several metabolic pathways perturbed with PM species including glycerophospholipid, sphingolipid, and glutathione. These pathways are involved in inflammation, oxidative stress, immunity, and nucleic acid damage and repair. Results were overlapped with the ICA.

Conclusions: We identified several significant perturbed plasma metabolites and metabolic pathways associated with exposure to PM species. These species are associated with traffic, fuel oil, and wood smoke. This is the largest study to report a metabolomic signature of PM species' exposure and the first to use ICA.
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http://dx.doi.org/10.1016/j.envint.2021.106447DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7994935PMC
June 2021

Long-Term Association of Air Pollution and Hospital Admissions Among Medicare Participants Using a Doubly Robust Additive Model.

Circulation 2021 Apr 22;143(16):1584-1596. Epub 2021 Feb 22.

Department of Environmental Health, Harvard TH Chan School of Public Health, Boston, MA (M.D.Y., Y.W., Q.D., Y.W., W.J.R., L.S., J.S.E., P.K., J.D.S.).

Background: Studies examining the nonfatal health outcomes of exposure to air pollution have been limited by the number of pollutants studied and focus on short-term exposures.

Methods: We examined the relationship between long-term exposure to fine particulate matter with an aerodynamic diameter <2.5 micrometers (PM), NO, and tropospheric ozone and hospital admissions for 4 cardiovascular and respiratory outcomes (myocardial infarction, ischemic stroke, atrial fibrillation and flutter, and pneumonia) among the Medicare population of the United States. We used a doubly robust method for our statistical analysis, which relies on both inverse probability weighting and adjustment in the outcome model to account for confounding. The results from this regression are on an additive scale. We further looked at this relationship at lower pollutant concentrations, which are consistent with typical exposure levels in the United States, and among potentially susceptible subgroups.

Results: Long-term exposure to fine PM was associated with an increased risk of all outcomes with the highest effect seen for stroke with a 0.0091% (95% CI, 0.0086-0.0097) increase in the risk of stroke for each 1-µg/m increase in annual levels. This translated to 2536 (95% CI, 2383-2691) cases of hospital admissions with ischemic stroke per year, which can be attributed to each 1-unit increase in fine particulate matter levels among the study population. NO was associated with an increase in the risk of admission with stroke by 0.00059% (95% CI, 0.00039-0.00075) and atrial fibrillation by 0.00129% (95% CI, 0.00114-0.00148) per ppb and tropospheric ozone was associated with an increase in the risk of admission with pneumonia by 0.00413% (95% CI, 0.00376-0.00447) per parts per billion. At lower concentrations, all pollutants were consistently associated with an increased risk for all our studied outcomes.

Conclusions: Long-term exposure to air pollutants poses a significant risk to cardiovascular and respiratory health among the elderly population in the United States, with the greatest increase in the association per unit of exposure occurring at lower concentrations.
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http://dx.doi.org/10.1161/CIRCULATIONAHA.120.050252DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055197PMC
April 2021

Metabolomic signatures of the long-term exposure to air pollution and temperature.

Environ Health 2021 Jan 7;20(1). Epub 2021 Jan 7.

Department of Environmental Health, Harvard T. H. Chan School of Public Health, Landmark Center, Room 414C, 401 Park Dr, Boston, MA, 02215, USA.

Background: Long-term exposures to air pollution has been reported to be associated with inflammation and oxidative stress. However, the underlying metabolic mechanisms remain poorly understood.

Objectives: We aimed to determine the changes in the blood metabolome and thus the metabolic pathways associated with long-term exposure to outdoor air pollution and ambient temperature.

Methods: We quantified metabolites using mass-spectrometry based global untargeted metabolomic profiling of plasma samples among men from the Normative Aging Study (NAS). We estimated the association between long-term exposure to PM, NO, O, and temperature (annual average of central site monitors) with metabolites and their associated metabolic pathways. We used multivariable linear mixed-effect regression models (LMEM) while simultaneously adjusting for the four exposures and potential confounding and correcting for multiple testing. As a reduction method for the intercorrelated metabolites (outcome), we further used an independent component analysis (ICA) and conducted LMEM with the same exposures.

Results: Men (N = 456) provided 648 blood samples between 2000 and 2016 in which 1158 metabolites were quantified. On average, men were 75.0 years and had an average body mass index of 27.7 kg/m. Almost all men (97%) were not current smokers. The adjusted analysis showed statistically significant associations with several metabolites (58 metabolites with PM, 15 metabolites with NO, and 6 metabolites with temperature) while no metabolites were associated with O. One out of five ICA factors (factor 2) was significantly associated with PM. We identified eight perturbed metabolic pathways with long-term exposure to PM and temperature: glycerophospholipid, sphingolipid, glutathione, beta-alanine, propanoate, and purine metabolism, biosynthesis of unsaturated fatty acids, and taurine and hypotaurine metabolism. These pathways are related to inflammation, oxidative stress, immunity, and nucleic acid damage and repair.

Conclusions: Using a global untargeted metabolomic approach, we identified several significant metabolites and metabolic pathways associated with long-term exposure to PM, NO and temperature. This study is the largest metabolomics study of long-term air pollution, to date, the first study to report a metabolomic signature of long-term temperature exposure, and the first to use ICA in the analysis of both.
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http://dx.doi.org/10.1186/s12940-020-00683-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788989PMC
January 2021

Ambient Particle Components and Newborn Blood Pressure in Project Viva.

J Am Heart Assoc 2021 Jan 29;10(1):e016935. Epub 2020 Dec 29.

Department of Environmental Health Harvard School of Public Health Boston MA.

Background Both elemental metals and particulate air pollution have been reported to influence adult blood pressure (BP). The aim of this study is to examine which elemental components of particle mass with diameter ≤2.5 μm (PM) are responsible for previously reported associations between PM and neonatal BP. Methods and Results We studied 1131 mother-infant pairs in Project Viva, a Boston-area prebirth cohort. We measured systolic BP (SBP) and diastolic BP (DBP) at a mean age of 30 hours. We calculated average exposures during the 2 to 7 days before birth for the PM components-aluminum, arsenic, bromine, sulfur, copper, iron, zinc, nickel, vanadium, titanium, magnesium, potassium, silicon, sodium, chlorine, calcium, and lead-measured at the Harvard supersite. Adjusting for covariates and PM, we applied regression models to examine associations between PM components and median SBP and DBP, and used variable selection methods to select which components were more strongly associated with each BP outcome. We found consistent results with higher nickel associated with significantly higher SBP and DBP, and higher zinc associated with lower SBP and DBP. For an interquartile range increase in the log Z score (1.4) of nickel, we found a 1.78 mm Hg (95% CI, 0.72-2.84) increase in SBP and a 1.30 (95% CI, 0.54-2.06) increase in DBP. Increased zinc (interquartile range log Z score 1.2) was associated with decreased SBP (-1.29 mm Hg; 95% CI, -2.09 to -0.50) and DBP (-0.85 mm Hg; 95% CI: -1.42 to -0.29). Conclusions Our findings suggest that prenatal exposures to particulate matter components, and particularly nickel, may increase newborn BP.
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http://dx.doi.org/10.1161/JAHA.120.016935DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7955476PMC
January 2021

DNA methylation-based biomarkers of age acceleration and all-cause death, myocardial infarction, stroke, and cancer in two cohorts: The NAS, and KORA F4.

EBioMedicine 2021 Jan 3;63:103151. Epub 2020 Dec 3.

Department of Environmental Health, Harvard T.H. Chan School of Public Health, 401 Park Drive, West of Landmark Center, Boston, MA 02215, United States.

Background: DNA methylation (DNAm) may play a role in age-related outcomes. It is not yet known which DNAm-based biomarkers of age acceleration (BoAA) has the strongest association with age-related endpoints.

Methods: We collected the blood samples from two independent cohorts: the Normative Ageing Study, and the Cooperative Health Research in the Region of Augsburg cohort. We measured epigenome-wide DNAm level, and generated five DNAm BoAA at baseline. We used Cox proportional hazards model to analyze the relationships between BoAA and all-cause death. We applied the Fine and Gray competing risk model to estimate the risk of BoAA on myocardial infarction (MI), stroke, and cancer, accounting for death of other reasons as the competing risks. We used random-effects meta-analyses to pool the individual results, with adjustment for multiple testing.

Findings: The mean chronological ages in the two cohorts were 74, and 61, respectively. Baseline GrimAgeAccel, and DNAm-related mortality risk score (DNAmRS) both had strong associations with all-cause death, MI, and stroke, independent from chronological age. For example, a one standard deviation (SD) increment in GrimAgeAccel was significantly associated with increased risk of all-cause death [hazard ratio (HR): 2.01; 95% confidence interval (CI), 1.15, 3.50], higher risk of MI (HR: 1.44; 95% CI, 1.16, 1.79), and elevated risk of stroke (HR: 1.42; 95% CI, 1.06, 1.91). There were no associations between any BoAA and cancer.

Interpretation: From the public health perspective, GrimAgeAccel is the most useful tool for identifying at-risk elderly, and evaluating the efficacy of anti-aging interventions.

Funding: National Institute of Environmental Health Sciences of U.S., Harvard Chan-NIEHS Center for Environmental Health, German Federal Ministry of Education and Research, and the State of Bavaria in Germany.
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http://dx.doi.org/10.1016/j.ebiom.2020.103151DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7724153PMC
January 2021

Estimating the Combined Effects of Natural and Built Environmental Exposures on Birthweight among Urban Residents in Massachusetts.

Int J Environ Res Public Health 2020 11 27;17(23). Epub 2020 Nov 27.

Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.

Intrauterine growth has health implications both in childhood and adulthood. Birthweight is partially determined by prenatal environmental exposures. We aim to identify important predictors of birthweight out of a set of environmental, built environment exposures, and socioeconomic environment variables during pregnancy (i.e., fine particulate matter (PM), temperature, greenness, walkability, noise, and economic indices). We included all singleton live births of mothers who resided in urban census block-groups and delivered in Massachusetts between 2001 and 2011 ( = 640,659). We used an elastic-net model to select important predictors of birthweight and constructed a multivariate model including the selected predictors, with adjustment for confounders. We additionally used a weighted quantile sum regression to assess the contribution of each exposure to differences in birthweight. All exposures were selected as important predictors of birthweight. In the multivariate model, lower birthweight was significantly associated with lower greenness and with higher temperature, walkability, noise, and segregation of the "high income" group. Treating the exposures individually, nighttime noise had the highest weight in its contribution to lower birthweight. In conclusion, after accounting for individual confounders, maternal environmental exposures, built environment exposures, and socioeconomic environment during pregnancy were important predictors of birthweight, emphasizing the role of these exposures in fetal growth and development.
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http://dx.doi.org/10.3390/ijerph17238805DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7731163PMC
November 2020

Comparison of temperature-mortality associations estimated with different exposure metrics.

Environ Epidemiol 2019 Oct 14;3(5):e072. Epub 2019 Oct 14.

Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island.

Studies of the short-term association between ambient temperature and mortality often use temperature observations from a single monitoring station, frequently located at the nearest airport, to represent the exposure of individuals living across large areas. Population-weighted temperature estimates constructed from gridded meteorological data may offer an opportunity to improve exposure assessment in locations where station observations do not fully capture the average exposure of the population of interest.

Methods: We compared the association between daily mean temperature and mortality in each of 113 United States counties using (1) temperature observations from a single weather station and (2) population-weighted temperature estimates constructed from a gridded meteorological dataset. We used distributed lag nonlinear models to estimate the 21-day cumulative association between temperature and mortality in each county, 1987-2006, adjusting for seasonal and long-term trends, day of week, and holidays.

Results: In the majority (73.4%) of counties, the relative risk of death on extremely hot days (99th percentile of weather station temperature) versus the minimum mortality temperature was larger when generated from the population-weighted estimates. In contrast, relative risks on extremely cold days (first percentile of weather station temperature) were often larger when generated from the weather station observations. In most counties, the difference in associations estimated from the two temperature metrics was small.

Conclusions: In a large, multi-site analysis, temperature-mortality associations were largely similar when estimated from weather station observations versus population-weighted temperature estimates. However, spatially refined exposure data may be more appropriate for analyses seeking to elucidate local health effects.
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http://dx.doi.org/10.1097/EE9.0000000000000072DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7608890PMC
October 2019

Prenatal exposure to particulate air pollution and gestational age at delivery in Massachusetts neonates 2001-2015: A perspective of causal modeling and health disparities.

Environ Epidemiol 2020 Oct 14;4(5):e113. Epub 2020 Sep 14.

Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.

There is a lack of evidence on causal effects of air pollution on gestational age (GA) at delivery.

Methods: Inverse probability weighting (IPW) quantile regression was applied to derive causal marginal population-level GA reduction for GA percentiles associated with increased ambient particulate matter with diameter <2.5 μm (PM) levels at maternal residential address for each trimester and the month preceding delivery using Massachusetts birth registry 2001 to 2015. Stratified analyses were conducted for neonatal sex, maternal age/race/education, and extreme ambient temperature conditions.

Results: For neonates at 2.5th, 10th, 25th, 50th, 75th, and 97.5th percentiles of GA at delivery, we estimated an adjusted GA reduction of 4.2 days (95% confidence interval [CI] = 3.4, 5.0), 1.9 days (1.6, 2.1), 1.2 days (1.0, 1.4), 0.82 days (0.72, 0.92), 0.74 days (0.54, 0.94), and 0.54 days (0.15, 0.93) for each 5 μg/m3 increment in third trimester average PM levels. Final gestational month average exposure yielded a similar effect with greater magnitude. Male neonates and neonates of younger (younger than 35 years) and African American mothers as well as with high/low extreme temperature exposure in third trimester were more affected. Estimates were consistently higher at lower GA percentiles, indicating preterm/early-term births being more affected. Low-exposure analyses yielded similar results, restricting to areas with PM levels under US ambient annual standard of 12 μg/m.

Conclusions: Prenatal exposure to PM in late pregnancy reduced GA at delivery among Massachusetts neonates, especially among preterm/early-term births, male neonates, and neonates of younger and African American mothers. Exposure to extremely high/low temperature amplifies the effect of PM on GA.
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http://dx.doi.org/10.1097/EE9.0000000000000113DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7595249PMC
October 2020

Schools exposure to air pollution sources in Brazil: A nationwide assessment of more than 180 thousand schools.

Sci Total Environ 2021 Apr 21;763:143027. Epub 2020 Oct 21.

Department of Environmental Health, Harvard TH Chan School of Public Health, Boston, MA, United States.

A growing body of evidence demonstrates that children at schools who are exposed to increased concentrations of air pollutants may have a higher risk for several health problems, including cognitive deficits. In this paper we estimate the exposure to air pollution sources at 186,080 schools in Brazil. Specifically, we accounted for the exposure to three proxies of air pollution source emissions, including distance to roadways, the extent of roadways within a buffer around each school, and the number of wildfire occurrences within a buffer around each school. About 25% of the Brazilian schools evaluated in our study are located within a distance ≤250 m of a major roadway, have ≥2 km of roadway within a buffer of 1 km, and have ≥7 wildfires records within a buffer of 10 km. Our results indicate significant prevalence ratio of these schools exposed to air pollution sources when we stratified the analyses by socioeconomic factors, including geographic (public schools had an increased likelihood of being exposed), economic (low-income areas had an increased likelihood of being exposed), health (overall, areas with low public health status had an increased likelihood of being exposed), and educational conditions (overall, areas with low educational indicator had an increased likelihood of being exposed). For example, we estimated that private schools were 15% (95% CI: 13-17%) less likely to be located within 250 m of a major roadway compared with public schools; schools in areas with low child mortality were 35% (95% CI: 34-37%) less likely to be within 250 m of a major roadway; and schools in regions with low expected years of schooling were 25% (95% CI: 22-28%) more likely to be located within 250 m of a major roadway. The analysis of the spatial patterns shows that a substantial number of schools (36-54%, depending on the air pollution source) has a positive autocorrelation, suggesting that exposure level at these schools are similar to their neighbors. Estimating children's exposure to air pollutants at school is crucial for future public policies to develop effective environmental, transportation, educational, and urban planning interventions that may protect students from exposure to environmental hazards and improve their safety, health, and learning performance.
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http://dx.doi.org/10.1016/j.scitotenv.2020.143027DOI Listing
April 2021

PM and hospital admissions among Medicare enrollees with chronic debilitating brain disorders.

Sci Total Environ 2021 Feb 3;755(Pt 2):142524. Epub 2020 Oct 3.

Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Background: Although long-term exposure to particulate matter<2.5 μm (PM) has been linked to chronic debilitating brain disorders (CDBD), the role of short-term exposure in health care demand, and increased susceptibility for PM-related health conditions, among Medicare enrollees with CDBD has received little attention. We used a causal modeling approach to assess the effect of short-term high PM exposure on all-cause admissions, and prevalent cause-specific admissions among Medicare enrollees with CDBD (Parkinson's disease-PD, Alzheimer's disease-AD and other dementia).

Methods: We constructed daily zipcode counts of hospital admissions of Medicare beneficiaries older than 65 across the United-States (2000-2014). We obtained daily PM estimates from a satellite-based model. A propensity score matching approach was applied to match high-pollution (PM > 17.4 μg/m) to low-pollution zip code-days with similar background characteristics. Then, we estimated the percent change in admissions attributable to high pollution. We repeated the models restricting the analysis to zipcode-days with PM below of 35 μg/m.

Results: We observed significant increases in all-cause hospital admissions (2.53% in PD and 2.49% in AD/dementia) attributable to high PM exposure. The largest observed effect for common causes was for pneumonia and urinary tract infection. All the effects were larger in CDBD compared to the general Medicare population, and similarly strong at levels of exposure considered safe by the EPA.

Conclusion: We found Medicare beneficiaries with CDBD to be at higher risk of being admitted to the hospital following acute exposure to PM levels well below the National Ambient Air Quality Standard defined as safe by the EPA.
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http://dx.doi.org/10.1016/j.scitotenv.2020.142524DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7749824PMC
February 2021

Unconventional oil and gas development and ambient particle radioactivity.

Nat Commun 2020 10 13;11(1):5002. Epub 2020 Oct 13.

Department of Environmental Health, Harvard T.H Chan School of Public Health, Boston, MA, 02114, USA.

Unconventional oil and natural gas development (UOGD) expanded extensively in the United States from the early 2000s. However, the influence of UOGD on the radioactivity of ambient particulate is not well understood. We collected the ambient particle radioactivity (PR) measurements of RadNet, a nationwide environmental radiation monitoring network. We obtained the information of over 1.5 million wells from the Enverus database. We investigated the association between the upwind UOGD well count and the downwind gross-beta radiation with adjustment for environmental factors governing the natural emission and transport of radioactivity. Our statistical analysis found that an additional 100 upwind UOGD wells within 20 km is associated with an increase of 0.024 mBq/m (95% confidence interval [CI], 0.020, 0.028 mBq/m) in the gross-beta particle radiation downwind. Based on the published health analysis of PR, the widespread UOGD could induce adverse health effects to residents living close to UOGD by elevating PR.
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http://dx.doi.org/10.1038/s41467-020-18226-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7553919PMC
October 2020

Ambient air pollution and risk of pregnancy loss among women undergoing assisted reproduction.

Environ Res 2020 12 13;191:110201. Epub 2020 Sep 13.

Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Vincent Obstetrics and Gynecology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.

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), ozone (O), fine particulate matter <2.5 μm (PM), and black carbon (BC) exposures using validated spatiotemporal models estimated from first positive hCG test until day of failure or live birth. Air pollution exposures were averaged over the past week and the whole pregnancy. Multivariable Cox proportional hazards models were used to estimate the hazards ratio (HR) for pregnancy loss for an interquartile range (IQR) increase in pollutant exposure. We tested for violation of proportional hazards by considering an interaction between time (in days) since positive hCG (<30 days vs. ≥30 days) and air pollution. The incidence of pregnancy loss was 29 per 100 confirmed pregnancies (n = 99). Among pregnancies not resulting in live birth, the median (IQR) time to loss was 21 (11, 30) days following positive hCG. Average past week exposures to NO, O, PM, and BC were not associated with time to pregnancy loss. Exposure throughout pregnancy to NO was not associated with pregnancy loss; however, there was a statistically significant interaction with time (p-for-interaction<0.001). Specifically, an IQR increase in exposure to NO was positively associated with pregnancy loss after 30 days (HR = 1.34, 95% CI: 1.13, 1.58), but not in the first 30 days after positive hCG (HR = 0.83, 95% CI: 0.57, 1.20). Overall pregnancy exposure to O, PM, and BC were not associated with pregnancy loss regardless of timing. Models evaluating joint effects of all pollutants yielded similar findings. In conclusion, acute and chronic exposure to NO, O, PM, and BC were not associated with risk of pregnancy loss; however, higher exposure to NO throughout pregnancy was associated with increased risk of loss 30 days after positive hCG. In this cohort, later pregnancy losses appeared more susceptible to the detrimental effects of air pollution exposure.
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http://dx.doi.org/10.1016/j.envres.2020.110201DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7658021PMC
December 2020

Exposure to Particulate Matter Is Associated With Elevated Blood Pressure and Incident Hypertension in Urban India.

Hypertension 2020 10 17;76(4):1289-1298. Epub 2020 Aug 17.

Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA (B.K., J.D.S.).

Ambient air pollution, specifically particulate matter of diameter <2.5 μm, is reportedly associated with cardiovascular disease risk. However, evidence linking particulate matter of diameter <2.5 μm and blood pressure (BP) is largely from cross-sectional studies and from settings with lower concentrations of particulate matter of diameter <2.5 μm, with exposures not accounting for myriad time-varying and other factors such as built environment. This study aimed to study the association between long- and short-term ambient particulate matter of diameter <2.5 μm exposure from a hybrid spatiotemporal model at 1-km×1-km spatial resolution with longitudinally measured systolic and diastolic BP and incident hypertension in 5342 participants from urban Delhi, India, within an ongoing representative urban adult cohort study. Median annual and monthly exposure at baseline was 92.1 μg/m (interquartile range, 87.6-95.7) and 82.4 μg/m (interquartile range, 68.4-107.0), respectively. We observed higher average systolic BP (1.77 mm Hg [95% CI, 0.97-2.56] and 3.33 mm Hg [95% CI, 1.12-5.52]) per interquartile range differences in monthly and annual exposures, respectively, after adjusting for covariates. Additionally, interquartile range differences in long-term exposures of 1, 1.5, and 2 years increased the risk of incident hypertension by 1.53× (95% CI, 1.19-1.96), 1.59× (95% CI, 1.31-1.92), and 1.16× (95% CI, 0.95-1.43), respectively. Observed effects were larger in individuals with higher waist-hip ratios. Our data strongly support a temporal association between high levels of ambient air pollution, higher systolic BP, and incident hypertension. Given that high BP is an important risk factor of cardiovascular disease, reducing ambient air pollution is likely to have meaningful clinical and public health benefits.
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http://dx.doi.org/10.1161/HYPERTENSIONAHA.120.15373DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7484465PMC
October 2020

Accelerated epigenetic aging as a risk factor for chronic obstructive pulmonary disease and decreased lung function in two prospective cohort studies.

Aging (Albany NY) 2020 08 3;12(16):16539-16554. Epub 2020 Aug 3.

Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Chapel Hill, NC 27709, USA.

Chronic obstructive pulmonary disease (COPD) is a frequent diagnosis in older individuals and contributor to global morbidity and mortality. Given the link between lung disease and aging, we need to understand how molecular indicators of aging relate to lung function and disease. Using data from the population-based KORA (Cooperative Health Research in the Region of Augsburg) surveys, we associated baseline epigenetic (DNA methylation) age acceleration with incident COPD and lung function. Models were adjusted for age, sex, smoking, height, weight, and baseline lung disease as appropriate. Associations were replicated in the Normative Aging Study. Of 770 KORA participants, 131 developed incident COPD over 7 years. Baseline accelerated epigenetic aging was significantly associated with incident COPD. The change in age acceleration (follow-up - baseline) was more strongly associated with COPD than baseline aging alone. The association between the change in age acceleration between baseline and follow-up and incident COPD replicated in the Normative Aging Study. Associations with spirometric lung function parameters were weaker than those with COPD, but a meta-analysis of both cohorts provide suggestive evidence of associations. Accelerated epigenetic aging, both baseline measures and changes over time, may be a risk factor for COPD and reduced lung function.
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http://dx.doi.org/10.18632/aging.103784DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7485704PMC
August 2020

Race or racial segregation? Modification of the PM2.5 and cardiovascular mortality association.

PLoS One 2020 27;15(7):e0236479. Epub 2020 Jul 27.

Exposure, Epidemiology, and Risk Program, Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America.

Background: Many studies have identified an inequitable distribution of exposure to PM2.5 (particulate matter less than 2.5 microns) by race. We investigated the association of PM2.5 and cardiovascular mortality considering both the decedents' race and neighborhood racial composition as potential modifiers.

Methods: We obtained geocoded cardiovascular mortality records of all black and white decedents from urban block-groups in Massachusetts between 2001 and 2011 (n = 130,863). We examined the association between PM2.5 and cardiovascular mortality, and assessed effect modification by three types of racial modifiers: decedents' race, census block-group percent black and white, and two novel measures of racial segregation. The Racial Residential Segregation (RRS) quantifies the concentration of non-Hispanic blacks and whites in each block-group. The Index of Racial Dissimilarity measures dissimilarity in non-Hispanic black and white racial distribution between the smaller census block-group and larger tract.

Results: We found a 2.35%(95%CI: 0.92%;3.79%) increase in mortality for each 10μg/m3 increase in two-day average exposure to PM2.5. The effect was modified by the block-group racial composition, with higher risks in block-groups with the highest percentage of black residents (interaction p-value = 0.04), and in block-groups with the lowest RRS (i.e. higher black to white resident ratio, interaction p-value = 0.072). Racial dissimilarity did not modify the associations.

Conclusion: Current levels of PM2.5 are associated with increased cardiovascular deaths in Massachusetts, with different risks between areas with different racial composition and segregation. This suggests that pollution reductions in neighborhoods with the highest percentage of non-Hispanic blacks would be most beneficial in reducing cardiovascular mortality and disparities.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0236479PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7384646PMC
September 2020

The impact of measurement error in modeled ambient particles exposures on health effect estimates in multilevel analysis: A simulation study.

Environ Epidemiol 2020 Jun 27;4(3):e094. Epub 2020 May 27.

Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece.

Various spatiotemporal models have been proposed for predicting ambient particulate exposure for inclusion in epidemiological analyses. We investigated the effect of measurement error in the prediction of particulate matter with diameter <10 µm (PM) and <2.5 µm (PM) concentrations on the estimation of health effects.

Methods: We sampled 1,000 small administrative areas in London, United Kingdom, and simulated the "true" underlying daily exposure surfaces for PM and PM for 2009-2013 incorporating temporal variation and spatial covariance informed by the extensive London monitoring network. We added measurement error assessed by comparing measurements at fixed sites and predictions from spatiotemporal land-use regression (LUR) models; dispersion models; models using satellite data and applying machine learning algorithms; and combinations of these methods through generalized additive models. Two health outcomes were simulated to assess whether the bias varies with the effect size. We applied multilevel Poisson regression to simultaneously model the effect of long- and short-term pollutant exposure. For each scenario, we ran 1,000 simulations to assess measurement error impact on health effect estimation.

Results: For long-term exposure to particles, we observed bias toward the null, except for traffic PM for which only LUR underestimated the effect. For short-term exposure, results were variable between exposure models and bias ranged from -11% (underestimate) to 20% (overestimate) for PM and of -20% to 17% for PM. Integration of models performed best in almost all cases.

Conclusions: No single exposure model performed optimally across scenarios. In most cases, measurement error resulted in attenuation of the effect estimate.
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http://dx.doi.org/10.1097/EE9.0000000000000094DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7319186PMC
June 2020

Comparing the performance of air pollution models for nitrogen dioxide and ozone in the context of a multilevel epidemiological analysis.

Environ Epidemiol 2020 Jun 13;4(3):e093. Epub 2020 May 13.

Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece.

Using modeled air pollutant predictions as exposure variables in epidemiological analyses can produce bias in health effect estimation. We used statistical simulation to estimate these biases and compare different air pollution models for London.

Methods: Our simulations were based on a sample of 1,000 small geographical areas within London, United Kingdom. "True" pollutant data (daily mean nitrogen dioxide [NO] and ozone [O]) were simulated to include spatio-temporal variation and spatial covariance. All-cause mortality and cardiovascular hospital admissions were simulated from "true" pollution data using prespecified effect parameters for short and long-term exposure within a multilevel Poisson model. We compared: land use regression (LUR) models, dispersion models, LUR models including dispersion output as a spline (hybrid1), and generalized additive models combining splines in LUR and dispersion outputs (hybrid2). Validation datasets (model versus fixed-site monitor) were used to define simulation scenarios.

Results: For the LUR models, bias estimates ranged from -56% to +7% for short-term exposure and -98% to -68% for long-term exposure and for the dispersion models from -33% to -15% and -52% to +0.5%, respectively. Hybrid1 provided little if any additional benefit, but hybrid2 appeared optimal in terms of bias estimates for short-term (-17% to +11%) and long-term (-28% to +11%) exposure and in preserving coverage probability and statistical power.

Conclusions: Although exposure error can produce substantial negative bias (i.e., towards the null), combining outputs from different air pollution modeling approaches may reduce bias in health effect estimation leading to improved impact evaluation of abatement policies.
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http://dx.doi.org/10.1097/EE9.0000000000000093DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7319188PMC
June 2020

Causal Effects of Air Pollution on Mortality Rate in Massachusetts.

Am J Epidemiol 2020 11;189(11):1316-1323

Air pollution epidemiology studies have primarily investigated long- and short-term exposures separately, have used multiplicative models, and have been associational studies. Implementing a generalized propensity score adjustment approach with 3.8 billion person-days of follow-up, we simultaneously assessed causal associations of long-term (1-year moving average) and short-term (2-day moving average) exposure to particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5), ozone, and nitrogen dioxide with all-cause mortality on an additive scale among Medicare beneficiaries in Massachusetts (2000-2012). We found that long- and short-term PM2.5, ozone, and nitrogen dioxide exposures were all associated with increased mortality risk. Specifically, per 10 million person-days, each 1-μg/m3 increase in long- and short-term PM2.5 exposure was associated with 35.4 (95% confidence interval (CI): 33.4, 37.6) and 3.04 (95% CI: 2.17, 3.94) excess deaths, respectively; each 1-part per billion (ppb) increase in long- and short-term ozone exposure was associated with 2.35 (95% CI: 1.08, 3.61) and 2.41 (95% CI: 1.81, 2.91) excess deaths, respectively; and each 1-ppb increase in long- and short-term nitrogen dioxide exposure was associated with 3.24 (95% CI: 2.75, 3.77) and 5.60 (95% CI: 5.24, 5.98) excess deaths, respectively. Mortality associated with long-term PM2.5 and ozone exposure increased substantially at low levels. The findings suggested that air pollution was causally associated with mortality, even at levels below national standards.
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http://dx.doi.org/10.1093/aje/kwaa098DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7604530PMC
November 2020

Ambient particle radioactivity and gestational diabetes: A cohort study of more than 1 million pregnant women in Massachusetts, USA.

Sci Total Environ 2020 Sep 11;733:139340. Epub 2020 May 11.

Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Background: Exposure to ionizing radiation increases the risk of chronic metabolic disorders such as insulin resistance and type 2 diabetes. Internal ionizing radiation from inhaled radioactive aerosol may contribute to the associations between fine particulate matter (PM) and gestational diabetes mellitus (GDM).

Methods: We used the Massachusetts Registry of Vital Records to study 1,061,937 pregnant women from 2001 to 2015 with a singleton pregnancy without pre-existing diabetes. Gross β activity measured by seven monitors of the U.S. Environmental Protection Agency's RadNet monitoring network was utilized to represent ambient particle radioactivity (PR). We obtained GDM status from birth certificates and used logistic regression analyses adjusted for socio-demographics, maternal comorbidities, PM, temperature and relative humidity. We also examined effect modification by smoking habits.

Results: Ambient particle radioactivity exposure during first and second trimester of pregnancy was associated with higher odds of GDM (OR: 1.18 (95% CI 1.10 to 1.22). Controlling for PM did not substantially change the effects of PR on GDM. In women that reported being former or current smokers, the association between PR and GDM was null. In the full cohort, the overall effect of PM on GDM without adjusting for PR was not significant.

Conclusion: This is the first population-based study to examine the association between particle radioactivity and gestational diabetes mellitus - one of the most common pregnancy-related diseases with lifelong effects for the mother and the fetus. This finding has important public health policy implications because it enhances our understanding about the toxicity of PR, a modifiable risk factor, which to date, has been considered only as an indoor and occupational air quality risk.
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http://dx.doi.org/10.1016/j.scitotenv.2020.139340DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7472683PMC
September 2020

Ensemble averaging based assessment of spatiotemporal variations in ambient PM concentrations over Delhi, India, during 2010-2016.

Atmos Environ (1994) 2020 Mar 27;224. Epub 2020 Jan 27.

Harvard School of Public Health, Boston, USA.

Elevated levels of ambient air pollution has been implicated as a major risk factor for morbidities and premature mortality in India, with particularly high concentrations of particulate matter in the Indo-Gangetic plain. High resolution spatiotemporal estimates of such exposures are critical to assess health effects at an individual level. This article retrospectively assesses daily average PM exposure at 1 km × 1 km grids in Delhi, India from 2010-2016, using multiple data sources and ensemble averaging approaches. We used a multi-stage modeling exercise involving satellite data, land use variables, reanalysis based meteorological variables and population density. A calibration regression was used to model PM: PM to counter the sparsity of ground monitoring data. The relationship between PM and its spatiotemporal predictors was modeled using six learners; generalized additive models, elastic net, support vector regressions, random forests, neural networks and extreme gradient boosting. Subsequently, these predictions were combined under a generalized additive model framework using a tensor product based spatial smoothing. Overall cross-validated prediction accuracy of the model was 80% over the study period with high spatial model accuracy and predicted annual average concentrations ranging from 87 to 138 μg/m. Annual average root mean squared errors for the ensemble averaged predictions were in the range 39.7-62.7 μg/m with prediction bias ranging between 4.6-11.2 μg/m. In addition, tree based learners such as random forests and extreme gradient boosting outperformed other algorithms. Our findings indicate important seasonal and geographical differences in particulate matter concentrations within Delhi over a significant period of time, with meteorological and land use features that discriminate most and least polluted regions. This exposure assessment can be used to estimate dose response relationships more accurately over a wide range of particulate matter concentrations.
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http://dx.doi.org/10.1016/j.atmosenv.2020.117309DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219795PMC
March 2020

Exposure to Particle Beta Radiation in Greater Massachusetts and Factors Influencing Its Spatial and Temporal Variability.

Environ Sci Technol 2020 06 12;54(11):6575-6583. Epub 2020 May 12.

Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston Massachusetts 02115, United States.

Particle radioactivity is a property of airborne particles caused by the presence of naturally occurring or anthropogenic radionuclides. Recent studies have found associations between particle radioactivity and adverse health outcomes, including changes in blood pressure and lung function. However, the spatiotemporal distribution of particle radioactivity and factors influencing its variability have not been extensively studied. We address these knowledge gaps using measurements of gross beta activity, collected at seven Environmental Protection Agency (EPA) RadNet monitors located in and around Massachusetts. We apply back-trajectory analysis to identify prevailing air mass trajectories and find that these trajectories strongly influence seasonal trends in beta activity. We also evaluate the effects of different meteorological predictors on daily beta activity concentrations using a mixed-effect model. Important predictors of beta activity include air mass trajectories, temperature, and relative humidity. Finally, we create a series of random forest models to impute missing beta activity concentrations at each RadNet monitor for use in future health studies. This is the first study to analyze spatiotemporal trends in particle radioactivity using measurements from the EPA RadNet system.
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http://dx.doi.org/10.1021/acs.est.0c00454DOI Listing
June 2020

Racial Disparities in Associations between Neighborhood Demographic Polarization and Birth Weight.

Int J Environ Res Public Health 2020 04 28;17(9). Epub 2020 Apr 28.

Department of Environmental Health, Harvard TH Chan School of Public Health, Boston, MA 02215, USA.

Neighborhood demographic polarization, or the extent to which a privileged population group outnumbers a deprived group, can affect health by influencing social dynamics. While using birth records from 2001 to 2013 in Massachusetts ( = 629,675), we estimated the effect of two demographic indices, racial residential polarization (RRP) and economic residential polarization (ERP), on birth weight outcomes, which are established predictors of the newborn's future morbidity and mortality risk. Higher RRP and ERP was each associated with higher continuous birth weight and lower odds for low birth weight and small for gestational age, with evidence for effect modification by maternal race. On average, per interquartile range increase in RRP, the birth weight was 10.0 g (95% confidence interval: 8.0, 12.0) higher among babies born to white mothers versus 6.9 g (95% CI: 4.8, 9.0) higher among those born to black mothers. For ERP, it was 18.6 g (95% CI: 15.7, 21.5) higher among those that were born to white mothers versus 1.8 g (95% CI: -4.2, 7.8) higher among those born to black mothers. Racial and economic polarization towards more privileged groups was associated with healthier birth weight outcomes, with greater estimated effects in babies that were born to white mothers than those born to black mothers.
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http://dx.doi.org/10.3390/ijerph17093076DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7246784PMC
April 2020

Short-term exposure to ambient particle gamma radioactivity is associated with increased risk for all-cause non-accidental and cardiovascular mortality.

Sci Total Environ 2020 Jun 7;721:137793. Epub 2020 Mar 7.

Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston 02115, USA.

Background: Recent studies have found that particulate matter (PM) attached radioactivity was associated with certain adverse health effects including increased blood pressure and lung dysfunction. However, there has been no investigation on the direct effect of PM radioactivity on mortality.

Methods: Exposures to ambient PM gamma activities were determined using U.S. EPA RadNet data. Data on daily deaths were obtained from individual state Departments of Public Health. We used a generalized additive quasi-Poisson model to estimate the associations between two-day average ambient PM gamma activities (gamma2 through gamma9) with all-cause non-accidental and cardiovascular daily deaths for each of 18 US cities, for each season, adjusting for two-day average PM exposure, temperature, relative humidity, day of week and long-term trends. Subsequently, we used random-effects meta-analysis to estimate the overall effect in the 18 cities for each season.

Results: We found that all-cause non-accidental daily mortality in spring season was positively associated with two-day average ambient PM gamma activities in spring, with significant results for gamma2, gamma5 and gamma6. Similarly, cardiovascular daily mortality was positively associated with two-day average ambient PM gamma activities, with significant results for gamma2, gamma4, gamma5, gamma6, gamma7 and gamma9. For the spring season, each interquartile range (IQR) increase of two-day averaged ambient PM gamma activity was associated with increase in all-cause daily deaths, ranging from 0.15% (95% Confidence Interval (CI): -0.36%, 0.65%) to 1.03 (95%CI: 0.18%, 1.89%). Each IQR was also associated with increase in cardiovascular daily deaths, ranging from 0.01% (95%CI: -0.89, 0.92) to 2.95% (95%CI: 1.33, 4.59). For other seasons overall we found statistically insignificant associations of PM radioactivity with mortality.

Conclusions: Our findings suggest that there are potential systemic toxic effects of inhalation of radionuclides attached to ambient air particles.
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http://dx.doi.org/10.1016/j.scitotenv.2020.137793DOI Listing
June 2020

Effects of particulate matter gamma radiation on oxidative stress biomarkers in COPD patients.

J Expo Sci Environ Epidemiol 2020 Feb 3. Epub 2020 Feb 3.

Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.

Inhalation of particulate matter (PM) radioactivity is an important pathway of ionizing radiation exposure. We investigated the associations between short-term exposures to PM gamma radioactivity with oxidative stress in COPD patients. Urinary concentrations of 8-hydroxy-2'-deoxyguanosine (8-OHdG) and malondialdehyde (MDA) of 81 COPD patients from Eastern Massachusetts were measured 1-4 times during 2012-2014. Daily ambient and indoor PM gamma activities (gamma-3 through gamma-9) were calculated based on EPA RadNet data and indoor-outdoor infiltration ratios. Linear mixed-effects models were used to examine the associations between biomarkers with PM gamma activities for moving averages from urine collection day to 7 days before. Our results indicate that ambient and indoor PM gamma activities were positively associated with 8-OHdG, with stronger effects for exposure windows closer to urine collection day. For per interquartile range increase in indoor PM gamma activities averaged over urine collection day and 1 day before, 8-OHdG increased from 3.41% (95% CI: -0.88, 7.88) to 8.87% (95% CI: 2.98, 15.1), adjusted for indoor black carbon. For MDA, the timing of greatest effects across the exposure week varied but was nearly all positive. These findings provide insight into the toxigenic properties associated with PM radioactivity and suggest that these exposures promote systemic oxidative stress.
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http://dx.doi.org/10.1038/s41370-020-0204-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7396311PMC
February 2020

Short term exposure to fine particulate matter and hospital admission risks and costs in the Medicare population: time stratified, case crossover study.

BMJ 2019 11 27;367:l6258. Epub 2019 Nov 27.

Department of Environmental Health, Harvard T H Chan School of Public Health, Boston, MA, USA.

Objective: To assess risks and costs of hospital admission associated with short term exposure to fine particulate matter with diameter less than 2.5 µm (PM) for 214 mutually exclusive disease groups.

Design: Time stratified, case crossover analyses with conditional logistic regressions adjusted for non-linear confounding effects of meteorological variables.

Setting: Medicare inpatient hospital claims in the United States, 2000-12 (n=95 277 169).

Participants: All Medicare fee-for-service beneficiaries aged 65 or older admitted to hospital.

Main Outcome Measures: Risk 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.

Results: Positive associations between short term exposure to PM 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 PM concentration below the WHO air quality guideline for the 24 hour average exposure to PM. For the rarely studied diseases, each 1 µg/m increase in short term PM 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/m increase in short term exposure to PM 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.

Conclusions: New causes and previously identified causes of hospital admission associated with short term exposure to PM were found. These associations remained even at a daily PM concentration below the WHO 24 hour guideline. Substantial economic costs were linked to a small increase in short term PM.
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http://dx.doi.org/10.1136/bmj.l6258DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6880251PMC
November 2019

Children's acute respiratory symptoms associated with PM estimates in two sequential representative surveys from the Mexico City Metropolitan Area.

Environ Res 2020 01 2;180:108868. Epub 2019 Nov 2.

Department of Environmental Health, Center for Population Health Research, National Institute of Public Health, Cuernavaca, Morelos, Mexico.

Background: Respiratory diseases are a major component of morbidity in children and their symptoms may be spatially and temporally exacerbated by exposure gradients of fine particulate matter (PM) in large polluted urban areas, like the Mexico City Metropolitan Area (MCMA).

Objectives: To analyze the association between satellite-derived and interpolated PM estimates with children's (≤9 years old) acute respiratory symptoms (ARS) in two probabilistic samples representing the MCMA.

Methods: We obtained ARS data from the 2006 and 2012 National Surveys for Health and Nutrition (ENSaNut). Two week average exposure to PM was assessed for each household with spatial estimates from a hybrid model with satellite measurements of aerosol optical depth (AOD-PM) and also with interpolated PM measurements from ground stations, from the Mexico City monitoring network (MNW-PM). We used survey-adjusted logistic regressions to analyze the association between PM estimates and ARS reported on children.

Results: A total of 1,005 and 1,233 children were surveyed in 2006 and 2012 representing 3.1 and 3.5 million children, respectively. For the same years and over the periods of study, the estimated prevalence of ARS decreased from 49.4% (95% CI: 44.9,53.9%) to 37.8% (95% CI: 34,41.7%). AOD-PM and MNW-PM estimates were associated with significantly higher reports of ARS in children 0-4 years old [OR = 1.29 (95% (CI): 0.99,1.68) and OR = 1.24 (95% CI: 1.08,1.42), respectively]. We observed positive non-significant associations in 2012 in both age groups and in 2006 for children 5-9 years old. No statistically significant differences in health effect estimates of PM were found comparing AOD-PM or MNW-PM for exposure assessment.

Conclusions: Our findings suggest that PM is a risk factor for the prevalence of ARS in children and expand the growing evidence of the utility of new satellite AOD-based methods for estimating health effects from acute exposure to PM.
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http://dx.doi.org/10.1016/j.envres.2019.108868DOI Listing
January 2020

Short-term exposures to particulate matter gamma radiation activities and biomarkers of systemic inflammation and endothelial activation in COPD patients.

Environ Res 2020 01 19;180:108841. Epub 2019 Oct 19.

Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Background: We hypothesized that particulate matter (PM) gamma activity (gamma radiation associated with PM) is associated with systemic effects.

Objective: Examine short-term relationships between ambient and indoor exposures to PM gamma activities with systemic inflammation and endothelial activation in chronic obstructive pulmonary disease (COPD) patients.

Methods: In 85 COPD patients from Eastern Massachusetts, USA from 2012 to 2014, plasma C-reactive protein (CRP), interleukin-6 (IL-6), and soluble vascular cell adhesion molecule-1 (sVCAM-1) were measured seasonally up to four times. We used US EPA RadNet data measuring ambient gamma radiation attached to PM adjusted for background radiation, and estimated in-home gamma radiation exposures using the ratio of in-home-to-ambient sulfur in PM. Linear mixed-effects regression models were used to determine associations between moving averages of PM gamma activities through the week before phlebotomy with these biomarkers. We explored ambient and indoor PM, black carbon (BC), and NO as confounders.

Results: Ambient and indoor PM gamma activities measured as energy spectra classes 3 through 9 were positively associated with CRP and IL-6. For example, averaged from phlebotomy day through previous 6 days, each IQR increase in indoor PM gamma activity for each spectra class, was associated with an CRP increase ranging from 7.45% (95%CI: 2.77, 12.4) to 13.4% (95%CI: 5.82, 21.4) and for ambient exposures were associated with an increase of 8.75% (95%CI: -0.57, 18.95) to 14.8% (95%CI: 4.5, 26.0). Indoor exposures were associated with IL-6 increase of 3.56% (95%CI: 0.31, 6.91) to 6.46% (95%CI:1.33, 11.85) and ambient exposures were associated with an increase of 0.03% (95%CI: -6.37, 6.87) to 3.50% (95%CI: -3.15, 10.61). There were no positive associations with sVCAM-1. Sensitivity analyses using two-pollutant models showed similar effects.

Conclusions: Our results demonstrate that short-term exposures to environmental PM gamma radiation activities were associated with systemic inflammation in COPD patients.
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http://dx.doi.org/10.1016/j.envres.2019.108841DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6983292PMC
January 2020

Blood DNA methylation biomarkers of cumulative lead exposure in adults.

J Expo Sci Environ Epidemiol 2021 02 21;31(1):108-116. Epub 2019 Oct 21.

Mailman School of Public Health, Columbia University, New York, NY, USA.

Background: Lead is a ubiquitous toxicant following three compartment kinetics with the longest half-life found in bones. Patella and tibia lead levels-validated measures of cumulative exposure-require specialized X-ray-fluorescence-spectroscopy available only in a few centers worldwide. We developed minimally invasive biomarkers reflecting individual cumulative lead exposure using blood DNA methylation profiles-obtainable via Illumina 450K or IlluminaEPIC bead-chip assays.

Methods: We developed and tested two methylation-based biomarkers from 348 Normative Aging Study (NAS) elderly men. We selected methylation sites with strong associations with bone lead levels via robust regressions analysis and constructed the biomarkers using elastic nets. Results were validated in a NAS subset, reporting specificity, and sensitivity.

Findings: Participants were 73 years old on average (standard deviation, SD = 6), with moderate lead levels of (mean ± SD patella: 27 ± 18 µg/g; tibia:21 ± 13 µg/g). Methylation-based biomarkers for lead in patella and tibia included 59 and 138 DNA methylation sites, respectively. Estimated lead levels were significantly correlated with actual measured values, (r = 0.62 patella, r = 0.59 tibia) and had low mean square error (MSE) (MSE = 0.68 patella, MSE = 0.53 tibia). Means and distributions of the estimated and actual lead levels were not significantly different across patella and tibia bones (p > 0.05). Methylation-based biomarkers discriminated participants highly exposed (>median) to lead with a specificity of 74 and 73% for patella and tibia lead levels, respectively, with 70% sensitivity.

Interpretation: DNA methylation-based lead biomarkers are novel tools that can be used to reconstruct decades' worth of individual cumulative lead exposure using only blood DNA methylation profiles and may help identify the consequences of cumulative exposure.
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http://dx.doi.org/10.1038/s41370-019-0183-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7170756PMC
February 2021