Relative Humidity, Temperature, and Hypertensive Disorders of Pregnancy: Findings from the Project Viva Cohort.

BACKGROUND: Preeclampsia is a multi-system hypertensive disorder of pregnancy that is a leading cause of maternal and fetal morbidity and mortality. Prior studies disagree on the cause and even the presence of seasonal patterns in its incidence. Using unsuitable time windows for seasonal exposures can bias model results, potentially explaining these inconsistencies. OBJECTIVES: We aimed to investigate humidity and temperature as possible causes for seasonal trends in preeclampsia in Project Viva, a prebirth cohort in Boston, Massachusetts, considering only exposure windows that precede disease onset. METHODS: Using the Parameter-elevation Relationships on Independent Slopes Model (PRISM) Climate Dataset, we estimated daily residential temperature and relative humidity (RH) exposures during pregnancy. Our primary multinomial regression adjusted for person-level covariates and season. Secondary analyses included distributed lag models (DLMs) and adjusted for ambient air pollutants including fine particulates (PM2.5). We used Generalized Additive Mixed Models (GAMMs) for systolic blood pressure (SBP) trajectories across hypertensive disorder statuses to confirm exposure timing. RESULTS: While preeclampsia is typically diagnosed late in pregnancy, GAMM-fitted SBP trajectories for preeclamptic and non-preeclamptic women began to diverge at around 20 weeks' gestation, confirming the need to only consider early exposures. In the primary analysis with 1776 women, RH in the early second trimester, weeks 14-20, was associated with significantly higher odds of preeclampsia (OR per IQR increase: 1.81, 95% CI: 1.10, 2.97). The DLM corroborated this window, finding a positive association from weeks 12-20. There were no other significant associations between RH or temperature and preeclampsia or gestational hypertension in any other time period. DISCUSSION: The association between preeclampsia and RH in the early second trimester was robust to model choice, suggesting that RH may contribute to seasonal trends in preeclampsia incidence. Differences between these results and those of prior studies could be attributable to exposure timing differences.

Longitudinal associations between ambient PM2.5 exposure and lipid levels in two Indian cities.

Background: Exposure to ambient PM2.5 is known to affect lipid metabolism through systemic inflammation and oxidative stress. Evidence from developing countries, such as India with high levels of ambient PM2.5 and distinct lipid profiles, is sparse. Methods: Longitudinal nonlinear mixed-effects analysis was conducted on >10,000 participants of Centre for cArdiometabolic Risk Reduction in South Asia (CARRS) cohort in Chennai and Delhi, India. We examined associations between 1-month and 1-year average ambient PM2.5 exposure derived from the spatiotemporal model and lipid levels (total cholesterol [TC], triglycerides [TRIG], high-density lipoprotein cholesterol [HDL-C], and low-density lipoprotein cholesterol [LDL-C]) measured longitudinally, adjusting for residential and neighborhood-level confounders. Results: The mean annual exposure in Chennai and Delhi was 40 and 102 µg/m3 respectively. Elevated ambient PM2.5 levels were associated with an increase in LDL-C and TC at levels up to 100 µg/m3 in both cities and beyond 125 µg/m3 in Delhi. TRIG levels in Chennai increased until 40 µg/m3 for both short- and long-term exposures, then stabilized or declined, while in Delhi, there was a consistent rise with increasing annual exposures. HDL-C showed an increase in both cities against monthly average exposure. HDL-C decreased slightly in Chennai with an increase in long-term exposure, whereas it decreased beyond 130 µg/m3 in Delhi. Conclusion: These findings demonstrate diverse associations between a wide range of ambient PM2.5 and lipid levels in an understudied South Asian population. Further research is needed to establish causality and develop targeted interventions to mitigate the impact of air pollution on lipid metabolism and cardiovascular health.

Indoor and ambient black carbon and fine particulate matter associations with blood biomarkers in COPD patients.

BACKGROUND: Systemic inflammation contributes to cardiovascular risk and chronic obstructive pulmonary disease (COPD) pathophysiology. Associations between systemic inflammation and exposure to ambient fine particulate matter (PM ≤ 2.5 µm diameter; PM2.5), and black carbon (BC), a PM2.5 component attributable to traffic and other sources of combustion, infiltrating indoors are not well described. METHODS: Between 2012 and 2017, COPD patients completed in-home air sampling over one-week intervals, up to four times (seasonally), followed by measurement of plasma biomarkers of systemic inflammation, C-reactive protein (CRP) and interleukin-6 (IL-6), and endothelial activation, soluble vascular adhesion molecule-1 (sVCAM-1). Ambient PM2.5, BC and sulfur were measured at a central site. The ratio of indoor/ambient sulfur in PM2.5, a surrogate for fine particle infiltration, was used to estimate indoor BC and PM2.5 of ambient origin. Linear mixed effects regression with a random intercept for each participant was used to assess associations between indoor and indoor of ambient origin PM2.5 and BC with each biomarker. RESULTS: 144 participants resulting in 482 observations were included in the analysis. There were significant positive associations between indoor BC and indoor BC of ambient origin with CRP [%-increase per interquartile range (IQR);95 % CI (13.2 %;5.2-21.8 and 11.4 %;1.7-22.1, respectively)]. Associations with indoor PM2.5 and indoor PM2.5 of ambient origin were weaker. There were no associations with IL-6 or sVCAM-1. CONCLUSIONS: In homes of patients with COPD without major sources of combustion, indoor BC is mainly attributable to the infiltration of ambient sources of combustion indoors. Indoor BC of ambient origin is associated with increases in systemic inflammation in patients with COPD, even when staying indoors.

Exposure-response associations between chronic exposure to fine particulate matter and risks of hospital admission for major cardiovascular diseases: population based cohort study.

OBJECTIVE: To estimate exposure-response associations between chronic exposure to fine particulate matter (PM2.5) and risks of the first hospital admission for major cardiovascular disease (CVD) subtypes. DESIGN: Population based cohort study. SETTING: Contiguous US. PARTICIPANTS: 59 761 494 Medicare fee-for-service beneficiaries aged ≥65 years during 2000-16. Calibrated PM2.5 predictions were linked to each participant's residential zip code as proxy exposure measurements. MAIN OUTCOME MEASURES: Risk of the first hospital admission during follow-up for ischemic heart disease, cerebrovascular disease, heart failure, cardiomyopathy, arrhythmia, valvular heart disease, thoracic and abdominal aortic aneurysms, or a composite of these CVD subtypes. A causal framework robust against confounding bias and bias arising from errors in exposure measurements was developed for exposure-response estimations. RESULTS: Three year average PM2.5 exposure was associated with increased relative risks of first hospital admissions for ischemic heart disease, cerebrovascular disease, heart failure, cardiomyopathy, arrhythmia, and thoracic and abdominal aortic aneurysms. For composite CVD, the exposure-response curve showed monotonically increased risk associated with PM2.5: compared with exposures ≤5 µg/m3 (the World Health Organization air quality guideline), the relative risk at exposures between 9 and 10 µg/m3, which encompassed the US national average of 9.7 µg/m3 during the study period, was 1.29 (95% confidence interval 1.28 to 1.30). On an absolute scale, the risk of hospital admission for composite CVD increased from 2.59% with exposures ≤5 µg/m3 to 3.35% at exposures between 9 and 10 µg/m3. The effects persisted for at least three years after exposure to PM2.5. Age, education, accessibility to healthcare, and neighborhood deprivation level appeared to modify susceptibility to PM2.5. CONCLUSIONS: The findings of this study suggest that no safe threshold exists for the chronic effect of PM2.5 on overall cardiovascular health. Substantial benefits could be attained through adherence to the WHO air quality guideline.

Long-term exposure to PM2.5 species and all-cause mortality among Medicare patients using mixtures analyses.

BACKGROUND: The relationship between long-term exposure to PM2.5 and mortality is well-established; however, the role of individual species is less understood. OBJECTIVES: In this study, we assess the overall effect of long-term exposure to PM2.5 as a mixture of species and identify the most harmful of those species while controlling for the others. METHODS: We looked at changes in mortality among Medicare participants 65 years of age or older from 2000 to 2018 in response to changes in annual levels of 15 PM2.5 components, namely: organic carbon, elemental carbon, nickel, lead, zinc, sulfate, potassium, vanadium, nitrate, silicon, copper, iron, ammonium, calcium, and bromine. Data on exposure were derived from high-resolution, spatio-temporal models which were then aggregated to ZIP code. We used the rate of deaths in each ZIP code per year as the outcome of interest. Covariates included demographic, temperature, socioeconomic, and access-to-care variables. We used a mixtures approach, a weighted quantile sum, to analyze the joint effects of PM2.5 species on mortality. We further looked at the effects of the components when PM2.5 mass levels were at concentrations below 8 µg/m3, and effect modification by sex, race, Medicaid status, and Census division. RESULTS: We found that for each decile increase in the levels of the PM2.5 mixture, the rate of all-cause mortality increased by 1.4% (95% CI: 1.3%-1.4%), the rate of cardiovascular mortality increased by 2.1% (95% CI: 2.0%-2.2%), and the rate of respiratory mortality increased by 1.7% (95% CI: 1.5%-1.9%). These effects estimates remained significant and slightly higher when we restricted to lower concentrations. The highest weights for harmful effects were due to organic carbon, nickel, zinc, sulfate, and vanadium. CONCLUSIONS: Long-term exposure to PM2.5 species, as a mixture, increased the risk of all-cause, cardiovascular, and respiratory mortality.

Prenatal exposure to air pollution and BWGA Z-score: Modifying effects of placenta leukocyte telomere length and infant sex.

BACKGROUND: Air pollutants, such as fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3), have been associated with adverse birth outcomes, including low birth weight, often exhibiting sex-specific effects. However, the modifying effect of placental telomere length (TL), reflecting cumulative lifetime oxidative stress in mothers, remains unexplored. METHOD: Using data from a Northeastern U.S. birth cohort (n = 306), we employed linear regression and weighted quantile sum models to assess trimester-average air pollution exposures and birth weight for gestational age (BWGA) z-scores. Placental TL, categorized by median split, was considered as an effect modifier. Interactions among air pollutants, placental TL, infant sex, and BWGA z-score were evaluated. RESULTS: Without placental TL as a modifier, only 1st trimester O3 was significantly associated with BWGA z-scores (coefficient: 0.33, 95% CI: 0.03, 0.63). In models considering TL interactions, a significant modifying effect was observed between 3rd trimester NO2 and BWGA z-scores (interaction p-value = 0.02). Specifically, a one interquartile range (1-IQR) increase in 3rd trimester NO2 was linked to a 0.28 (95% CI: 0.06, 0.52) change in BWGA z-score among shorter placental TL group, with no significant association among longer TL group. Among male infants, there were significant associations between 3rd trimester PM2.5 exposure and BWGA z-scores in the longer TL group (coefficient: -0.34, 95% CI: -0.61, -0.02), and between 1st trimester O3 exposure and BWGA z-scores among males in the shorter TL group (coefficient: 0.59, 95% CI: 0.06, 1.08). For females, only a negative association in 2nd trimester mixture model was observed within the longer TL group (coefficient: -0.10, 95% CI: -0.21, -0.01). CONCLUSION: These findings highlight the need to consider the complex interactions among prenatal air pollutant exposures, placental TL, and fetal sex to better elucidate those at greatest risk for adverse birth outcomes.

Long-term association of air pollution and incidence of lung cancer among older Americans: A national study in the Medicare cohort.

BACKGROUND: Despite strong evidence of the association of fine particulate matter (PM2.5) exposure with an increased risk of lung cancer mortality, few studies had investigated associations of multiple pollutants simultaneously, or with incidence, or using causal methods. Disparities were also understudied. OBJECTIVES: We investigated long-term effects of PM2.5, nitrogen dioxide (NO2), warm-season ozone, and particle radioactivity (PR) exposures on lung cancer incidence in a nationwide cohort. METHODS: We conducted a cohort study with Medicare beneficiaries (aged ≥ 65 years) continuously enrolled in the fee-for-service program in the contiguous US from 2001 to 2016. Air pollution exposure was averaged across three years and assigned based on ZIP code of residence. We fitted Cox proportional hazards models to estimate the hazard ratio (HR) for lung cancer incidence, adjusted for individual- and neighborhood-level confounders. As a sensitivity analysis, we evaluated the causal relationships using inverse probability weights. We further assessed effect modifications by individual- and neighborhood-level covariates. RESULTS: We identified 166,860 lung cancer cases of 12,429,951 studied beneficiaries. In the multi-pollutant model, PM2.5 and NO2 exposures were statistically significantly associated with increased lung cancer incidence, while PR was marginally significantly associated. Specifically, the HR was 1.008 (95% confidence interval [CI]: 1.005, 1.011) per 1-µg/m3 increase in PM2.5, 1.013 (95% CI: 1.012, 1.013) per 1-ppb increase in NO2, and 1.005 (0.999, 1.012) per 1-mBq/m3 increase in PR. At low exposure levels, all pollutants were associated with increased lung cancer incidence. Men, older individuals, Blacks, and residents of low-income neighborhoods experienced larger effects of PM2.5 and PR. DISCUSSION: Long-term PM2.5, NO2, and PR exposures were independently associated with increased lung cancer incidence among the national elderly population. Low-exposure analysis indicated that current national standards for PM2.5 and NO2 were not restrictive enough to protect public health, underscoring the need for more stringent air quality regulations.

Pulmonary, inflammatory, and oxidative effects of indoor nitrogen dioxide in patients with COPD.

Introduction: Indoor nitrogen dioxide (NO2) sources include gas heating, cooking, and infiltration from outdoors. Associations with pulmonary function, systemic inflammation, and oxidative stress in patients with chronic obstructive pulmonary disease (COPD) are uncertain. Methods: We recruited 144 COPD patients at the VA Boston Healthcare System between 2012 and 2017. In-home NO2 was measured using an Ogawa passive sampling badge for a week seasonally followed by measuring plasma biomarkers of systemic inflammation (C-reactive protein [CRP] and interleukin-6 [IL-6]), urinary oxidative stress biomarkers (8-hydroxy-2'deoxyguanosine [8-OHdG] and malondialdehyde [MDA]), and pre- and postbronchodilator spirometry. Linear mixed effects regression with a random intercept for each subject was used to assess associations with weekly NO2. Effect modification by COPD severity and by body mass index (BMI) was examined using multiplicative interaction terms and stratum-specific effect estimates. Results: Median (25%ile, 75%ile) concentration of indoor NO2 was 6.8 (4.4, 11.2) ppb. There were no associations observed between NO2 with CRP, 8-OHdG, or MDA. Although the confidence intervals were wide, there was a reduction in prebronchodilator FEV1 and FVC among participants with more severe COPD (FEV1: -17.36 mL; -58.35, 23.60 and FVC: -28.22 mL; -91.49, 35.07) that was greater than in patients with less severe COPD (FEV1: -1.64 mL; -24.80, 21.57 and FVC: -6.22 mL; -42.16, 29.71). In participants with a BMI <30, there was a reduction in FEV1 and FVC. Conclusions: Low-level indoor NO2 was not associated with systemic inflammation or oxidative stress. There was a suggestive association with reduced lung function among patients with more severe COPD and among patients with a lower BMI.

PM2.5 exposure, glycemic markers and incidence of type 2 diabetes in two large Indian cities.

INTRODUCTION: Exposure to fine particulate matter has been associated with several cardiovascular and cardiometabolic diseases. However, such evidence mostly originates from low-pollution settings or cross-sectional studies, thus necessitating evidence from regions with high air pollution levels, such as India, where the burden of non-communicable diseases is high. RESEARCH DESIGN AND METHODS: We studied the associations between ambient PM2.5 levels and fasting plasma glucose (FPG), glycosylated hemoglobin (HbA1c) and incident type 2 diabetes mellitus (T2DM) among 12 064 participants in an adult cohort from urban Chennai and Delhi, India. A meta-analytic approach was used to combine estimates, obtained from mixed-effects models and proportional hazards models, from the two cities. RESULTS: We observed that 10 µg/m3 differences in monthly average exposure to PM2.5 was associated with a 0.40 mg/dL increase in FPG (95% CI 0.22 to 0.58) and 0.021 unit increase in HbA1c (95% CI 0.009 to 0.032). Further, 10 µg/m3 differences in annual average PM2.5 was associated with 1.22 (95% CI 1.09 to 1.36) times increased risk of incident T2DM, with non-linear exposure response. CONCLUSIONS: We observed evidence of temporal association between PM2.5 exposure, and higher FPG and incident T2DM in two urban environments in India, thus highlighting the potential for population-based mitigation policies to reduce the growing burden of diabetes.

Long-Term Exposure to Ambient PM2.5 and Hospitalizations for Myocardial Infarction Among US Residents: A Difference-in-Differences Analysis.

Background Air pollution has been recognized as an untraditional risk factor for myocardial infarction (MI). However, the MI risk attributable to long-term exposure to fine particulate matter ≤2.5 µm in aerodynamic diameter (PM2.5) is unclear, especially in younger populations, and few studies have represented the general population or had power to examine comorbidities. Methods and Results We applied the difference-in-differences approach to estimate the relationship between annual PM2.5 exposure and hospitalizations for MI among US residents and further identified potential susceptible subpopulations. All hospital admissions for MI in 10 US states over the period 2002 to 2016 were obtained from the Healthcare Cost and Utilization Project State Inpatient Database. In total, 1 914 684 MI hospital admissions from 8106 zip codes were included in this study. We observed a 1.35% (95% CI, 1.11-1.59) increase in MI hospitalization rate for 1-µg/m3 increase in annual PM2.5 exposure. The estimate was robust to adjustment for surface pressure, relative humidity, and copollutants. In the population exposed to ≤12 µg/m3, there was a larger increment of 2.17% (95% CI, 1.79-2.56) in hospitalization rate associated with 1-µg/m3 increase in PM2.5. Young people (0-34 years of age) and elderly people (≥75 years of age) were the 2 most susceptible age groups. Residents living in more densely populated or poorer areas and individuals with comorbidities were observed to be at a greater risk. Conclusions This study indicates long-term residential exposure to PM2.5 could increase risk of MI among the general US population, people with comorbidities, and poorer individuals. The association persists below current standards.

Long-term exposure to ambient fine particulate components and leukocyte epigenome-wide DNA Methylation in older men: the Normative Aging Study.

BACKGROUND: Epigenome-wide association studies of ambient fine particulate matter (PM2.5) have been reported. However, few have examined PM2.5 components (PMCs) and sources or included repeated measures. The lack of high-resolution exposure measurements is the key limitation. We hypothesized that significant changes in DNA methylation might vary by PMCs and the sources. METHODS: We predicted the annual average of 14 PMCs using novel high-resolution exposure models across the contiguous U.S., between 2000-2018. The resolution was 50 m × 50 m in the Greater Boston Area. We also identified PM2.5 sources using positive matrix factorization. We repeatedly collected blood samples and measured leukocyte DNAm with the Illumina HumanMethylation450K BeadChip in the Normative Aging Study. We then used median regression with subject-specific intercepts to estimate the associations between long-term (one-year) exposure to PMCs / PM2.5 sources and DNA methylation at individual cytosine-phosphate-guanine CpG sites. Significant probes were identified by the number of independent degrees of freedom approach, using the number of principal components explaining > 95% of the variation of the DNA methylation data. We also performed regional and pathway analyses to identify significant regions and pathways. RESULTS: We included 669 men with 1,178 visits between 2000-2013. The subjects had a mean age of 75 years. The identified probes, regions, and pathways varied by PMCs and their sources. For example, iron was associated with 6 probes and 6 regions, whereas nitrate was associated with 15 probes and 3 regions. The identified pathways from biomass burning, coal burning, and heavy fuel oil combustion sources were associated with cancer, inflammation, and cardiovascular diseases, whereas there were no pathways associated with all traffic. CONCLUSIONS: Our findings showed that the effects of PM2.5 on DNAm varied by its PMCs and sources.

Climate Penalty on Air Pollution Abated by Anthropogenic Emission Reductions in the United States.

Climate change poses direct and indirect threats to public health, including exacerbating air pollution. However, how a warmer temperature deteriorates air quality, known as the "climate penalty" effect, remains highly uncertain in the United States, particularly under rapid reduction in anthropogenic emissions. Here we examined the sensitivity of surface-level fine particulate matter (PM2.5) and ozone (O3) to summer temperature anomalies in the contiguous US and their decadal changes using high-resolution datasets generated by machine learning models. Our findings demonstrate that, in the eastern US, efficient emission control strategies have significantly reduced the climate penalty effects on PM2.5 and O3, lowering the associated population exposure. In contrast, summer and annual PM2.5 in the western US became more sensitive to temperature, highlighting the urgent need for the management and mitigation of worsening wildfires. Our results have important implications for air quality management and risk assessments of future climate change.

Seasonal Temperature Variability and Mortality in the Medicare Population.

BACKGROUND: Seasonal temperature variability remains understudied and may be modified by climate change. Most temperature-mortality studies examine short-term exposures using time-series data. These studies are limited by regional adaptation, short-term mortality displacement, and an inability to observe longer-term relationships in temperature and mortality. Seasonal temperature and cohort analyses allow the long-term effects of regional climatic change on mortality to be analyzed. OBJECTIVES: We aimed to carry out one of the first investigations of seasonal temperature variability and mortality across the contiguous United States. We also investigated factors that modify this association. Using adapted quasi-experimental methods, we hoped to account for unobserved confounding and to investigate regional adaptation and acclimatization at the ZIP code level. METHODS: We examined the mean and standard deviation (SD) of daily temperature in the warm (April-September) and cold (October-March) season in the Medicare cohort from 2000 to 2016. This cohort comprised 622,427,230 y of person-time in all adults over the age of 65 y from 2000 to 2016. We used daily mean temperature obtained from gridMET to develop yearly seasonal temperature variables for each ZIP code. We used an adapted difference-in-difference approach model with a three-tiered clustering approach and meta-analysis to observe the relationship between temperature variability and mortality within ZIP codes. Effect modification was assessed with stratified analyses by race and population density. RESULTS: For every 1°C increase in the SD of warm and cold season temperature, the mortality rate increased by 1.54% [95% confidence interval (CI): 0.73%, 2.15%] and 0.69% (95% CI: 0.22%, 1.15%) respectively. We did not see significant effects for seasonal mean temperatures. Participants who were classified by Medicare into an "other" race group had smaller effects than those classified as White for Cold and Cold SD and areas with lower population density had larger effects for Warm SD. DISCUSSION: Warm and cold season temperature variability were significantly associated with increased mortality rates in U.S. individuals over the age of 65 y, even after controlling for seasonal temperature averages. Warm and cold season mean temperatures showed null effects on mortality. Cold SD had a larger effect size for those who were in the racial subgroup other, whereas Warm SD was more harmful for those living in lower population density areas. This study adds to the growing calls for urgent climate mitigation and environmental health adaptation and resiliency. https://doi.org/10.1289/EHP11588.

Association of low and high ambient temperature with mortality for cardiorespiratory diseases in Brazil.

Extreme temperatures are a major public health concern, as they have been linked to an increased risk of mortality from circulatory and respiratory diseases. Brazil, a country with vast geographic and climatic variations, is particularly vulnerable to the health impacts of extreme temperatures. In this study, we examined the nationwide (considering 5572 municipalities) association of low and high ambient temperature (1st and 99th percentiles) with daily mortality for circulatory and respiratory diseases in Brazil between 2003 and 2017. We used an extension of the two-stage time-series design. First, we applied a case time series design in combination with distributed lag non-linear modeling (DLMN) framework to assess the association by Brazilian region. Here, the analyses were stratified by sex, age group (15-45, 46-65, and >65 years), and cause of death (respiratory and circulatory mortality). In the second stage, we performed a meta-analysis to estimate pooled effects across the Brazilian regions. Our study population included 1,071,090 death records due to cardiorespiratory diseases in Brazil over the study period. We found increased risk of respiratory and circulatory mortality associated with low and high ambient temperatures. The pooled national results for the whole population (all ages and sex) suggest a relative risk (RR) of 1.27 (95% CI: 1.16; 1.37) and 1.11 (95% CI: 1.01; 1.21) associated with circulatory mortality during cold and heat exposure, respectively. For respiratory mortality, we estimated a RR of 1.16 (95% CI: 1.08; 1.25) during cold exposure and a RR of 1.14 (95% CI: 0.99; 1.28) during heat exposure. The national meta-analysis indicated robust positive associations for circulatory mortality on cold days across several subgroups by sex and age, while only a few subgroups presented robust positive associations for circulatory mortality on warm days and respiratory mortality on both cold and warm days. These findings have important public health implications for Brazil and suggest the need for targeted interventions to mitigate the adverse effects of extreme temperatures on human health.

Indoor (residential) and ambient particulate matter associations with urinary oxidative stress biomarkers in a COPD cohort.

OBJECTIVES: Oxidative stress contributes to chronic obstructive pulmonary disease (COPD) pathophysiology. Associations between indoor (residential) exposure to particulate matter ≤2.5 µm in diameter (PM2.5) and one of its components, black carbon (BC), and oxidative stress are ill-defined. METHODS: Between 2012 and 2017, 140 patients with COPD completed in-home air sampling over one week intervals, followed by collection of urine samples to measure oxidative stress biomarkers, malondialdehyde (MDA), a marker of lipid peroxidation, and 8-hydroxy-2' -deoxyguanosine (8-OHdG), a marker of oxidative DNA damage. Ambient (central site) BC and PM2.5 were measured, and the ratio of indoor/ambient sulfur in PM2.5, a surrogate for residential ventilation and particle infiltration, was used to estimate indoor BC and PM2.5 of outdoor origin. Mixed effects linear regression models with a participant-specific random intercept were used to assess associations with oxidative biomarkers, adjusting for personal characteristics. RESULTS: There were positive associations (% increase per IQR; 95 % CI) of directly measured indoor BC with total MDA (6.96; 1.54, 12.69) and 8-OHdG (4.18; -0.67, 9.27), and similar associations with both indoor BC of outdoor origin and ambient BC. There were no associations with directly measured indoor PM2.5, but there were positive associations between indoor PM2.5 of outdoor origin and total MDA (5.40; -0.91, 12.11) and 8-OHdG (8.02; 2.14, 14.25). CONCLUSIONS: In homes with few indoor combustion sources, directly measured indoor BC, estimates of indoor BC and PM2.5 of outdoor origin, and ambient BC, were positively associated with urinary biomarkers of oxidative stress. This suggests that the infiltration of particulate matter from outdoor sources, attributable to traffic and other sources of combustion, promotes oxidative stress in COPD patients.

Associations between long-term fine particulate matter exposure and hospital procedures in heart failure patients.

BACKGROUND: Ambient fine particulate matter (PM2.5) contributes to global morbidity and mortality. One way to understand the health effects of PM2.5 is by examining its impact on performed hospital procedures, particularly among those with existing chronic disease. However, such studies are rare. Here, we investigated the associations between annual average PM2.5 and hospital procedures among individuals with heart failure. METHODS: Using electronic health records from the University of North Carolina Healthcare System, we created a retrospective cohort of 15,979 heart failure patients who had at least one of 53 common (frequency > 10%) procedures. We used daily modeled PM2.5 at 1x1 km resolution to estimate the annual average PM2.5 at the time of heart failure diagnosis. We used quasi-Poisson models to estimate associations between PM2.5 and the number of performed hospital procedures over the follow-up period (12/31/2016 or date of death) while adjusting for age at heart failure diagnosis, race, sex, year of visit, and socioeconomic status. RESULTS: A 1 µg/m3 increase in annual average PM2.5 was associated with increased glycosylated hemoglobin tests (10.8%; 95% confidence interval = 6.56%, 15.1%), prothrombin time tests (15.8%; 95% confidence interval = 9.07%, 22.9%), and stress tests (6.84%; 95% confidence interval = 3.65%, 10.1%). Results were stable under multiple sensitivity analyses. CONCLUSIONS: These results suggest that long-term PM2.5 exposure is associated with an increased need for diagnostic testing on heart failure patients. Overall, these associations give a unique lens into patient morbidity and potential drivers of healthcare costs linked to PM2.5 exposure.

Intermediate and long-term exposure to air pollution and temperature and the extracellular microRNA profile of participants in the normative aging study (NAS).

BACKGROUND: The molecular effects of intermediate and long-term exposure to air pollution and temperature, such as those on extracellular microRNA (ex-miRNA) are not well understood but may have clinical consequences. OBJECTIVES: To assess the association between exposure to ambient air pollution and temperature and ex-miRNA profiles. METHODS: Our study population consisted of 734 participants in the Normative Aging Study (NAS) between 1999 and 2015. We used high-resolution models to estimate four-week, eight-week, twelve-week, six-month, and one-year moving averages of PM2.5, O3, NO2, and ambient temperature based on geo-coded residential addresses. The outcome of interest was the extracellular microRNA (ex-miRNA) profile of each participant over time. We used a longitudinal quantile regression approach to estimate the association between the exposures and each ex-miRNA. Results were corrected for multiple comparisons and ex-miRNAs that were still significantly associated with the exposures were further analyzed using KEGG pathway analysis and Ingenuity Pathway Analysis. RESULTS: We found 151 significant associations between levels of PM2.5, O3, NO2, and ambient temperature and 82 unique ex-miRNAs across multiple quantiles. Most of the significant results were associations with intermediate-term exposure to O3, long-term exposure to PM2.5, and both intermediate and long-term exposure to ambient temperature. The exposures were most often associated with the 75th and 90th percentile of the outcomes. Pathway analyses of significant ex-miRNAs revealed their involvement in biological pathways involving cell function and communication as well as clinical diseases such as cardiovascular disease, respiratory disease, and neurological disease. CONCLUSION: Our results show that intermediate and long-term exposure to all our exposures of interest were associated with changes in the ex-miRNA profile of study participants. Further studies on environmental risk factors and ex-miRNAs are warranted.

Short-term associations between ambient air pollution and emergency department visits for Alzheimer's disease and related dementias.

Dementia is a seriously disabling illness with substantial economic and social burdens. Alzheimer's disease and its related dementias (AD/ADRD) constitute about two-thirds of dementias. AD/ADRD patients have a high prevalence of comorbid conditions that are known to be exacerbated by exposure to ambient air pollution. Existing studies mostly focused on the long-term association between air pollution and AD/ADRD morbidity, while very few have investigated short-term associations. This study aims to estimate short-term associations between AD/ADRD emergency department (ED) visits and three common air pollutants: fine particulate matter (PM2.5), nitrogen dioxide (NO2), and warm-season ozone. Methods: For the period 2005 to 2015, we analyzed over 7.5 million AD/ADRD ED visits in five US states (California, Missouri, North Carolina, New Jersey, and New York) using a time-stratified case-crossover design with conditional logistic regression. Daily estimated PM2.5, NO2, and warm-season ozone concentrations at 1 km spatial resolution were aggregated to the ZIP code level as exposure. Results: The most consistent positive association was found for NO2. Across five states, a 17.1 ppb increase in NO2 concentration over a 4-day period was associated with a 0.61% (95% confidence interval = 0.27%, 0.95%) increase in AD/ADRD ED visits. For PM2.5, a positive association with AD/ADRD ED visits was found only in New York (0.64%, 95% confidence interval = 0.26%, 1.01% per 6.3 µg/m3). Associations with warm-season ozone levels were null. Conclusions: Our results suggest AD/ADRD patients are vulnerable to short-term health effects of ambient air pollution and strategies to lower exposure may reduce morbidity.

Association of Long-term Exposure to Air Pollution With Late-Life Depression in Older Adults in the US.

Importance: Emerging evidence has suggested harmful associations of air pollutants with neurodegenerative diseases among older adults. However, little is known about outcomes regarding late-life mental disorders, such as geriatric depression. Objective: To investigate if long-term exposure to air pollution is associated with increased risk of late-life depression diagnosis among older adults in the US. Design, Setting, and Participants: This population-based longitudinal cohort study consisted of US Medicare enrollees older than 64 years. Data were obtained from the US Centers for Medicare and Medicaid Services Chronic Conditions Warehouse. The participants were continuously enrolled in the Fee-for-Service program and both Medicare Part A and Part B. After the 5-year washout period at entry, a total of 8 907 422 unique individuals were covered over the study period of 2005 to 2016, who contributed to 1 526 690 late-onset depression diagnoses. Data analyses were performed between March 2022 and November 2022. Exposures: The exposures consisted of residential long-term exposure to fine particulate matter (PM2.5), measured in micrograms per cubic meter; nitrogen dioxide (NO2), measured in parts per billion; and ozone (O3), measured in parts per billion. Main Outcomes and Measures: Late-life depression diagnoses were identified via information from all available Medicare claims (ie, hospital inpatient, skilled nursing facility, home health agency, hospital outpatient, and physician visits). Date of the first occurrence was obtained. Hazard ratios and percentage change in risk were estimated via stratified Cox proportional hazards models accounting for climate coexposures, neighborhood greenness, socioeconomic conditions, health care access, and urbanicity level. Results: A total of 8 907 422 Medicare enrollees were included in this study with 56.8% being female individuals and 90.2% being White individuals. The mean (SD) age at entry (after washout period) was 73.7 (4.8) years. Each 5-unit increase in long-term mean exposure to PM2.5, NO2, and O3 was associated with an adjusted percentage increase in depression risk of 0.91% (95% CI, 0.02%-1.81%), 0.61% (95% CI, 0.31%- 0.92%), and 2.13% (95% CI, 1.63%-2.64%), respectively, based on a tripollutant model. Effect size heterogeneity was found among subpopulations by comorbidity condition and neighborhood contextual backgrounds. Conclusions and Relevance: In this cohort study among US Medicare enrollees, harmful associations were observed between long-term exposure to air pollution and increased risk of late-life depression diagnosis.

Long-term air pollution exposure and diabetes risk in American older adults: A national secondary data-based cohort study.

Type 2 diabetes is a major public health concern. Several studies have found an increased diabetes risk associated with long-term air pollution exposure. However, most current studies are limited in their generalizability, exposure assessment, or the ability to differentiate incidence and prevalence cases. We assessed the association between air pollution and first documented diabetes occurrence in a national U.S. cohort of older adults to estimate diabetes risk. We included all Medicare enrollees 65 years and older in the fee-for-service program, part A and part B, in the contiguous United States (2000-2016). Participants were followed annually until the first recorded diabetes diagnosis, end of enrollment, or death (264, 869, 458 person-years). We obtained annual estimates of fine particulate matter (PM2.5), nitrogen dioxide (NO2), and warm-months ozone (O3) exposures from highly spatiotemporally resolved prediction models. We assessed the simultaneous effects of the pollutants on diabetes risk using survival analyses. We repeated the models in cohorts restricted to ZIP codes with air pollution levels not exceeding the national ambient air quality standards (NAAQS) during the study period. We identified 10, 024, 879 diabetes cases of 41, 780, 637 people (3.8% of person-years). The hazard ratio (HR) for first diabetes occurrence was 1.074 (95% CI 1.058; 1.089) for 5 µg/m3 increase in PM2.5, 1.055 (95% CI 1.050; 1.060) for 5 ppb increase in NO2, and 0.999 (95% CI 0.993; 1.004) for 5 ppb increase in O3. Both for NO2 and PM2.5 there was evidence of non-linear exposure-response curves with stronger associations at lower levels (NO2 ≤ 36 ppb, PM2.5 ≤ 8.2 µg/m3). Furthermore, associations remained in the restricted low-level cohorts. The O3-diabetes exposure-response relationship differed greatly between models and require further investigation. In conclusion, exposures to PM2.5 and NO2 are associated with increased diabetes risk, even when restricting the exposure to levels below the NAAQS set by the U.S. EPA.