Advances in Understanding Air Pollution and CVD

Mortality attributable to PM2.5 from wildland fires in California from 2008 to 2018

In California, wildfire risk and severity have grown substantially in the last several decades. Research has characterized extensive adverse health impacts from exposure to wildfire-attributable fine particulate matter (PM2.5), but few studies have quantified long-term outcomes, and none have used a wildfire-specific chronic dose-response mortality coefficient. Here, we quantified the mortality burden for PM2.5 exposure from California fires from 2008 to 2018 using Community Multiscale Air Quality modeling system wildland fire PM2.5 estimates. We used a concentration-response function for PM2.5, applying ZIP code-level mortality data and an estimated wildfire-specific dose-response coefficient accounting for the likely toxicity of wildfire smoke. We estimate a total of 52,480 to 55,710 premature deaths are attributable to wildland fire PM2.5 over the 11-year period with respect to two exposure scenarios, equating to an economic impact of $432 to $456 billion. These findings extend evidence on climate-related health impacts, suggesting that wildfires account for a greater mortality and economic burden than indicated by earlier studies.

Integrating traffic pollution dispersion into spatiotemporal NO2 prediction

Accurately predicting ambient NO2 concentrations has great public health importance, as traffic-related air pollution is of major concern in urban areas. In this study, we present a novel approach incorporating traffic contribution to NO2 prediction in a fine-scale spatiotemporal model. We used nationally available traffic estimate dataset in a scalable dispersion model, Research LINE source dispersion model (RLINE). RLINE estimates then served as an additional input for a validated spatiotemporal pollution modeling approach. Our analysis uses measurement data collected by the Multi-Ethnic Study of Atherosclerosis and Air Pollution in the greater Los Angeles area between 2006 and 2009. We predicted road-type-specific annual average daily traffic (AADT) on road segments via national-level spatial regression models with nearest-neighbor Gaussian processes (spNNGP); the spNNGP models were trained based on over half a million point-level traffic volume measurements nationwide. AADT estimates on all highways were combined with meteorological data in RLINE models. We evaluated two strategies to integrate RLINE estimates into spatiotemporal NO2 models: 1) incorporating RLINE estimates as a space-only covariate and, 2) as a spatiotemporal covariate. The results showed that integrating the RLINE estimates as a space-only covariate improved overall cross-validation R2 from 0.83 to 0.84, and root mean squared error (RMSE) from 3.58 to 3.48 ppb. Incorporating the estimates as a spatiotemporal covariate resulted in similar model improvement. The improvement of our spatiotemporal model was more profound in roadside monitors alongside highways, with R2 increasing from 0.56 to 0.66 and RMSE decreasing from 3.52 to 3.11 ppb. The observed improvement indicates that the RLINE estimates enhanced the model's predictive capabilities for roadside NO2 concentration gradients even after considering a comprehensive list of geographic covariates including the distance to roads. Our proposed modeling framework can be generalized to improve high-resolution prediction of NO2 exposure - especially near major roads in the U.S.

Disentangling impacts of multiple pollutants on acute cardiovascular events in New York city: A case-crossover analysis

BACKGROUND

Ambient air pollution contributes to an estimated 6.67 million deaths annually, and has been linked to cardiovascular disease (CVD), the leading cause of death. Short-term increases in air pollution have been associated with increased risk of CVD event, though relatively few studies have directly compared effects of multiple pollutants using fine-scale spatio-temporal data, thoroughly adjusting for co-pollutants and temperature, in an exhaustive citywide hospitals dataset, towards identifying key pollution sources within the urban environment to most reduce, and reduce disparities in, the leading cause of death worldwide.

OBJECTIVES

We aimed to examine multiple pollutants against multiple CVD diagnoses, across lag days, in models adjusted for co-pollutants and meteorology, and inherently adjusted by design for non-time-varying individual and aggregate-level covariates, using fine-scale space-time exposure estimates, in an exhaustive dataset of emergency department visits and hospitalizations across an entire city, thereby capturing the full population-at-risk.

METHODS

We used conditional logistic regression in a case-crossover design - inherently controlling for all confounders not varying within case month - to examine associations between spatio-temporal nitrogen dioxide (NO2), fine particulate matter (PM2.5), sulfur dioxide (SO2), and ozone (O3) in New York City, 2005-2011, on individual risk of acute CVD event (n = 837,523), by sub-diagnosis [ischemic heart disease (IHD), heart failure (HF), stroke, ischemic stroke, acute myocardial infarction].

RESULTS

We found significant same-day associations between NO2 and risk of overall CVD, IHD, and HF - and between PM2.5 and overall CVD or HF event risk - robust to all adjustments and multiple comparisons. Results were comparable by sex and race - though median age at CVD was 10 years younger for Black New Yorkers than White New Yorkers. Associations for NO2 were comparable for adults younger or older than 69 years, though PM2.5 associations were stronger among older adults.

DISCUSSION

Our results indicate immediate, robust effects of combustion-related pollution on CVD risk, by sub-diagnosis. Though acute impacts differed minimally by age, sex, or race, the much younger age-at-event for Black New Yorkers calls attention to cumulative social susceptibility.

Particulate Matter Air Pollution is a Significant Risk Factor for Cardiovascular Disease

Air pollution is responsible worldwide for 9-12 million deaths annually. The major contributor to air pollution is particulate matter ≤2.5 µg per cubic meter of air (PM2.5) from vehicles, industrial emissions, and wildfire smoke. United States ambient air standards recommend annual average PM2.5 concentrations of ≤12 μg/m³ while European standards allow an average annual PM2.5 concentration of ≤20 μg/m3. However, significant PM2.5 cardiovascular and pulmonary health risks exist below these concentrations. Chronic PM2.5 exposure significantly increases major cardiovascular and pulmonary event risks in Americans by 8 to more than 20% for each 10-μg/m3 increase in PM2.5. PM2.5-induced increases in lipid peroxidation, induction of vascular inflammation and endothelial cell injury initiate and propagate respiratory diseases, coronary and carotid atherosclerosis. PM2.5 can cause atherosclerotic vascular plaque rupture and myocardial infarction and stroke by activating metalloproteinases. This article discusses PM2.5 effects on the cardiovascular and pulmonary systems, specific PM2.5 pathophysiologic mechanisms contributing to cardiopulmonary disease, and preventive measures to limit the cardiovascular and pulmonary effects of PM2.5.

Spatiotemporal distribution characteristics and influencing factors of the rate of cardiovascular hospitalization in Ganzhou city of China

Aims

The objective of this study was to analyze hospitalization rates for cardiovascular diseases (CVD) in Ganzhou City, Jiangxi Province of China from 2015 to 2020 and to uncover the spatiotemporal distribution characteristics and influencing factors, and thus to provide reference for the prevention and control of CVD and public health resources planning.

Methods

The hospitalization data for CVDs from 2016 to 2020 was obtained from the First Affiliated Hospital of Gannan Medical University, and ArcGIS 10.8, SaTScan 9.5, and Matlab 20.0 were used to analyze the spatial autocorrelation, spatiotemporal scan statistics, and potential affecting factors of the hospitalization rates.

Results

The hospitalization rate for CVDs in Ganzhou City showed a slightly increasing trend from 2016 to 2020, with higher rates in winter and summer than that in spring and autumn, and the individuals aged 61 and above constitute a higher proportion compared to other age groups. Additionally, there was a positive correlation between hospitalization rates for CVDs and the counties and districts in Ganzhou City, with high-high aggregation areas mainly distributed in Nankang District, the western urban area of Ganzhou City. The spatial scan analysis identified three different types of significant aggregation areas: high-risk, low-risk, and middle-risk areas. The high-risk area was mainly centered around Zhanggong District or Shangyu County in the central and western regions, with a disease hospitalization rate 2-3 times higher than the rest areas. The study also found that environmental meteorological factors such as the annual average concentration of NO2, O3, average annual temperature, and annual maximum temperature diurnal range had a significant positive effect on hospitalization rates for CVDs in Ganzhou City, with O3 concentration and average annual temperature having significant positive indirect spatial spillover effects.

Conclusion

Winter and summer are the seasons with high hospitalization rate of cardiovascular diseases. County residents aged 61 and above are the higher-risk population that needs to pay more attention on for prevention and control of CVD in Ganzhou City, which exhibits significant spatiotemporal clustering. The urban areas of Zhanggong and Nankang in Ganzhou City are the key areas for prevention and control of CVD. The hospitalization rate of CVD in Ganzhou City is influenced by the aforementioned four environmental meteorological factors, with the annual maximum temperature diurnal range showing the most significant positive direct effect.

Exposure assessment for air pollution epidemiology: A scoping review of emerging monitoring platforms and designs

BACKGROUND

Both exposure monitoring and exposure prediction have played key roles in assessing individual-level long-term exposure to air pollutants and their associations with human health. While there have been notable advances in exposure prediction methods, improvements in monitoring designs are also necessary, particularly given new monitoring paradigms leveraging low-cost sensors and mobile platforms.

OBJECTIVES

We aim to provide a conceptual summary of novel monitoring designs for air pollution cohort studies that leverage new paradigms and technologies, to investigate their characteristics in real-world examples, and to offer practical guidance to future studies.

METHODS

We propose a conceptual summary that focuses on two overarching types of monitoring designs, mobile and non-mobile, as well as their subtypes. We define mobile designs as monitoring from a moving platform, and non-mobile designs as stationary monitoring from permanent or temporary locations. We only consider non-mobile studies with cost-effective sampling devices. Then we discuss similarities and differences across previous studies with respect to spatial and temporal representation, data comparability between design classes, and the data leveraged for model development. Finally, we provide specific suggestions for future monitoring designs.

RESULTS

Most mobile and non-mobile monitoring studies selected monitoring sites based on land use instead of residential locations, and deployed monitors over limited time periods. Some studies applied multiple design and/or sub-design classes to the same area, time period, or instrumentation, to allow comparison. Even fewer studies leveraged monitoring data from different designs to improve exposure assessment by capitalizing on different strengths. In order to maximize the benefit of new monitoring technologies, future studies should adopt monitoring designs that prioritize residence-based site selection with comprehensive temporal coverage and leverage data from different designs for model development in the presence of good data compatibility.

DISCUSSION

Our conceptual overview provides practical guidance on novel exposure assessment monitoring for epidemiological applications.

Traffic-related air pollution, biomarkers of metabolic dysfunction, oxidative stress, and CC16 in children

BACKGROUND

Previous research has revealed links between air pollution exposure and metabolic syndrome in adults; however, these associations are less explored in children.

OBJECTIVE

This study aims to investigate the association between traffic-related air pollutants (TRAP) and biomarkers of metabolic dysregulation, oxidative stress, and lung epithelial damage in children.

METHODS

We conducted cross-sectional analyses in a sample of predominantly Latinx, low-income children (n = 218) to examine associations between air pollutants (nitrogen dioxide (NO₂), nitrogen oxides (NO_x), elemental carbon, polycyclic aromatic hydrocarbons, carbon monoxide (CO), fine particulates (PM_2.5)) and biomarkers of metabolic function (high-density lipoprotein (HDL), hemoglobin A1c (HbA1c), oxidative stress (8-isoprostane), and lung epithelial damage (club cell protein 16 (CC16)).

RESULTS

HDL cholesterol showed an inverse association with NO₂ and NO_x, with the strongest relationship between HDL and 3-month exposure to NO₂ (-15.4 mg/dL per IQR increase in 3-month NO₂, 95% CI = -27.4, -3.4). 8-isoprostane showed a consistent pattern of increasing values with 1-day and 1-week exposure across all pollutants. Non-significant increases in % HbA1c were found during 1-month time frames and decreasing CC16 in 3-month exposure time frames.

CONCLUSION

Our results suggest that TRAP is significantly associated with decreased HDL cholesterol in longer-term time frames and elevated 8-isoprostane in shorter-term time frames. TRAP could have the potential to influence lifelong metabolic patterns, through metabolic effects in childhood.

Long-Term Exposures to Air Pollutants and Risk of Peripheral Arterial Occlusive Disease: A Nationwide Cohort Study in Taiwan

Air pollution is one of the most alarming environmental issues which causes multiple health hazards. An association between air pollution and cardiovascular diseases has been established through many prior studies. In this study, we aimed to evaluate the risk of long-term exposure to air pollution (PM_2.5, CO, and NO₂) and its association with the risk of developing peripheral arterial occlusive disease (PAOD). PAOD is a condition involving impairment of perfusion of blood in the distal parts of the aorta due to narrowing of the arteries (arterial stenosis) and has been reported as a risk factor for developing cardiovascular diseases. Furthermore, the risk of PAOD increases with age, and hence is a serious public health issue and a cause for concern, especially for an aging society such as Taiwan. Two national-scale databases from Taiwan, the national health insurance database (NHIRD) and the Taiwan air quality-monitoring database (TAQMD), were linked to conduct this cohort study between 2003 and 2013. Cox proportional hazards regression with time-dependent modeling was used to evaluate the hazard ratio (HR) for PAOD with respect to daily exposure to air pollutants. The concentrations of each of the pollutants of interest (PM_2.5, NO₂, and CO) were categorized into four categories according to the daily average concentration of air pollutants for every quarter of the year, Q1 to Q4 (Q4 = highest). The cumulative incidence of PAOD was examined by Kaplan–Meier analysis with two-tailed log-rank test. A total of 1,598 PAOD cases were identified during the 10-year follow-up period, along with 98,540 non-PAOD controls. In the multivariate analysis, after adjusting for age, gender, urbanization level, residential area, baseline comorbidities, and medications, the adjusted HRs were PM_2.5 = 1.14 (95% CI 1.13–1.16), NO₂ = 1.03 (95% CI 1.02–1.04), and CO = 2.35 (95% CI 1.95–2.84). Kaplan–Meier analysis showed that CO (P < 0.0001) and PM_2.5 (P < 0.0001) concentrations were strongly and positively associated with the cumulative incidence of PAOD during the follow-up period. Findings from this study established that prolonged exposure to air pollutants CO and PM_2.5 are significant factors that, among other well-known causes, may also play a potential role in PAOD pathogenesis.

Local attributable burden disease to PM 2.5 ambient air pollution in Medellín, Colombia, 2010-2016

Background: Exposure to 2.5-micron diameter air pollutants (PM _2.5) has been associated with an increased risk of illness and death worldwide; however, in Latin American health impacts assessment of this risk factor is scarce. Medellín is one of the most polluted cities in the region, with a population growth rate that is twice as high as that of other Colombian cities, which implies a growing population at risk.

Methods: A descriptive study of the disease burden was carried out using the city as the unit of observation. Health events were selected based on epidemiologic evidence and the availability of the population attributable fraction associated with PM _2.5. The mortality records were taken from the module of deceased of the Single Registry of Affiliates of the Health System; the morbidity records were taken from the Individual Health Services Registries. For the estimation of the burden of disease, the current Global Burden of Disease guidelines were followed.

Results: Attributable disability-adjusted life years to exposure to ambient PM _2.5 pollution (DALYs _PM2.5) constituted 13.8% of total burden of the city. Males showed the greatest loss of DALYs _PM2.5 due to acute events, while in women the greatest loss was due to chronic events. Ischemic heart disease, chronic diseases of the lower respiratory tract, and influenza and pneumonia were the events that contributed the most to DALYs _PM2.5. 71.4% of the DALYs _PM2.5 corresponded to mortality, mainly in the population over 65 years of age. Regarding attributable morbidity, acute events were more prevalent in both sexes, especially due to respiratory diseases

Conclusion: Premature death among the elderly population has the greatest weight on burden of disease attributable to ambient PM _2.5 pollution, mainly due to respiratory and cardiovascular diseases, without significant differences according to gender.

Acute Effects of Air Pollution on Ischemic Heart Disease Hospitalizations: A Population-Based Time-Series Study in Wuhan, China, 2017-2018

Evidence of the acute effects of air pollutants on ischemic heart disease (IHD) hospitalizations based on the entire population of a megacity in central China is lacking. All IHD hospitalization records from 2017 to 2018 were obtained from the Wuhan Information Center of Health and Family Planning. Daily air pollutant concentrations and meteorological data were synchronously collected from the Wuhan Environmental Protection Bureau. A time-series study using generalized additive models was conducted to systematically examine the associations between air pollutants and IHD hospitalizations. Stratified analyses by gender, age, season, hypertension, diabetes, and hyperlipidemia were performed. In total, 139,616 IHD hospitalizations were included. Short-term exposure to air pollutants was positively associated with IHD hospitalizations. The age group ≥76 was at higher exposure risk, and the associations appeared to be more evident in cold seasons. PM_2.5 and PM₁₀ appeared to have greater effects on males and those without hypertension or diabetes, whereas NO₂ and SO₂ had greater effects on females and those with hypertension or diabetes. The risk of IHD hospitalization due to air pollutants was greater in people without hyperlipidemia. Our study provides new evidence of the effects of air pollution on the increased incidence of IHD in central China.

Clinical and biomarker modifiers of vitamin D treatment response: the Multi-Ethnic Study of Atherosclerosis

BACKGROUND

Different 25-hydroxyvitamin D [25(OH)D] thresholds for treatment with vitamin D supplementation have been suggested and are derived almost exclusively from observational studies. Whether other characteristics, including race/ethnicity, BMI, and estimated glomerular filtration rate (eGFR), should also influence the threshold for treatment is unknown.

OBJECTIVES

The aim was to identify clinical and biomarker characteristics that modify the response to vitamin D supplementation.

METHODS

A total of 666 older adults in the Multi-Ethnic Study of Atherosclerosis (MESA) were randomly assigned to 16 wk of oral vitamin D3 (2000 IU/d; n = 499) or placebo (n = 167). Primary outcomes were changes in serum parathyroid hormone (PTH) and 1,25-dihydroxyvitamin D [1,25(OH)2D] concentrations from baseline to 16 wk.

RESULTS

Among 666 participants randomly assigned (mean age: 72 y; 53% female; 66% racial/ethnic minority), 611 (92%) completed the study. The mean (SD) change in PTH was -3 (16) pg/mL with vitamin D3 compared with 2 (18) pg/mL with placebo (estimated mean difference: -5; 95% CI: -8, -2 pg/mL). Within the vitamin D3 group, lower baseline 25-hydroxyvitamin D [25(OH)D] was associated with a larger decline in PTH in a nonlinear fashion. With baseline 25(OH)D ≥30 ng/mL as the reference, 25(OH)D <20 ng/mL was associated with a larger decline in PTH with vitamin D3 supplementation (-10; 95% CI: -15, -6 pg/mL), whereas 25(OH)D of 20-30 ng/mL was not (-2; 95% CI: -6, 1 pg/mL). A segmented threshold model identified a baseline 25(OH)D concentration of 21 (95% CI: 13, 31) ng/mL as an inflection point for difference in change in PTH. Race/ethnicity, BMI, and eGFR did not modify vitamin D treatment response. There was no significant change in 1,25(OH)2D in either treatment group.

CONCLUSIONS

Of characteristics most commonly associated with vitamin D metabolism, only baseline 25(OH)D <20 ng/mL modified the PTH response to vitamin D supplementation, providing support from a clinical trial to use this threshold to define insufficiency. This trial was registered at clinicaltrials.gov as NCT02925195.

Local attributable burden disease to PM 2.5 ambient air pollution in Medellín, Colombia, 2010-2016

Background: Exposure to 2.5-micron diameter air pollutants (PM _2.5) has been associated with an increased risk of illness and death worldwide; however, in Latin American health impacts assessment of this risk factor is scarce. Medellín is one of the most polluted cities in the region, with a population growth rate that is twice as high as that of other Colombian cities, which implies a growing population at risk. Methods: A descriptive study of the disease burden was carried out using the city as the unit of observation. Health events were selected based on epidemiologic evidence and the availability of the population attributable fraction associated with PM _2.5. The mortality records were taken from the module of deceased of the Single Registry of Affiliates of the Health System; the morbidity records were taken from the Individual Health Services Registries. For the estimation of the burden of disease, the current Global Burden of Disease guidelines were followed. Results: Attributable disability-adjusted life years to exposure to ambient PM _2.5 pollution (DALYs _PM2.5) constituted 13.8% of total burden of the city. Males showed the greatest loss of DALYs _PM2.5 due to acute events, while in women the greatest loss was due to chronic events. Ischemic heart disease, chronic diseases of the lower respiratory tract, and influenza and pneumonia were the events that contributed the most to DALYs _PM2.5. 71.4% of the DALYs _PM2.5 corresponded to mortality, mainly in the population over 65 years of age. Regarding attributable morbidity, acute events were more prevalent in both sexes, especially due to respiratory diseases Conclusion: Premature death among the elderly population has the greatest weight on burden of disease attributable to ambient PM _2.5 pollution, mainly due to respiratory and cardiovascular diseases, without significant differences according to gender.

Clinical Treatment Analysis and Imaging Study of Patients with Acute Angina in Cardiovascular Medicine

With the accelerating pace of life, increasing stress and unhealthy diet make cardiovascular disease one of the important diseases that endanger human health, among which the incidence of acute angina is gradually increasing. At present, there are many clinical treatment studies on acute angina pectoris, but the relevant imaging analysis is very lacking. In order to study the clinical treatment of patients with acute angina pectoris and analyze the relevant medical images, to arrive at a more effective treatment method, this article launched an in-depth study. First, we selected 88 patients with acute angina in a hospital as the research object and randomly divided them into a control group (n = 44) and an experimental group (n = 44) Yan et al. (2020). The control group was treated with conventional acute angina pectoris drugs, while the experimental group was treated with clopidogrel on this basis. The two groups were treated at the same time, and the treatment time lasted for 3 months. Then, the risk factors of the two groups of patients were analyzed, and the differences were statistically significant (P < 0.05). Then, the medical images of the two groups of patients were analyzed, and the diastolic blood pressure, systolic blood pressure, and coronary artery stenosis were compared before and after treatment. After treatment, the diastolic blood pressure and systolic blood pressure of the experimental group were 88.31 ± 3.15 mmHg and 125.63 ± 4.16 mmHg, respectively. The proportion of patients with zero-vessel disease and single-vessel disease in the experimental group increased to 15.91% and 56.82%. The treatment plan received by the experimental group patients had a better improvement effect. Finally, the clinical efficacy was compared. The total effective rates of the control and experimental groups were 72.7% and 88.6%, respectively. This shows that the treatment method adopted by the experimental group of patients has a better curative effect and is worthy of clinical promotion.

Social Susceptibility to Multiple Air Pollutants in Cardiovascular Disease

INTRODUCTION

Cardiovascular disease (CVD) is the leading cause of death in the United States, and substantial research has linked ambient air pollution to elevated rates of CVD etiology and events. Much of this research identified increased effects of air pollution in lower socioeconomic position (SEP) communities, where pollution exposures are also often higher. The complex spatial confounding between air pollution and SEP makes it very challenging, however, to disentangle the impacts of these very different exposure types and to accurately assess their interactions. The specific causal components (i.e., specific social stressors) underlying this SEP-related susceptibility remain unknown, because there are myriad pathways through which poverty and/or lower-SEP conditions may influence pollution susceptibility - including diet, smoking, coexposures in the home and occupational environments, health behaviors, and healthcare access. Growing evidence suggests that a substantial portion of SEP-related susceptibility may be due to chronic psychosocial stress - given the known wide-ranging impacts of chronic stress on immune, endocrine, and metabolic function - and to a higher prevalence of unpredictable chronic stressors in many lower-SEP communities, including violence, job insecurity, and housing instability. As such, elucidating susceptibility to pollution in the etiology of CVD, and in the risk of CVD events, has been identified as a research priority. This interplay among social and environmental conditions may be particularly relevant for CVD, because pollution and chronic stress both impact inflammation, metabolic function, oxidative stress, hypertension, atherosclerosis, and other processes relevant to CVD etiology. Because pollution exposures are often spatially patterned by SEP, disentangling their effects - and quantifying any interplay - is especially challenging. Doing so, however, would help to improve our ability to identify and characterize susceptible populations and to improve our understanding of how community stressors may alter responses to multiple air pollutants. More clearly characterizing susceptible populations will improve our ability to design and target interventions more effectively (and cost-effectively) and may reveal greater benefits of pollution reduction in susceptible communities, strengthening cost-benefit and accountability analyses, ultimately reducing the disproportionate burden of CVD and reducing health disparities.

METHODS

In the current study, we aimed to quantify combined effects of multiple pollutants and stressor exposures on CVD events, using a number of unique datasets we have compiled and verified, including the following. 1. Poverty metrics, violent crime rates, a composite socioeconomic deprivation index (SDI), an index of racial and economic segregation, noise disturbance metrics, and three composite spatial factors produced from a factor analysis of 27 community stressors. All indicators have citywide coverage and were verified against individual reports of stress and stressor exposure, in citywide focus groups and surveys. 2. Spatial surfaces for multiple pollutants from the New York City (NYC) Community Air Survey (NYCCAS), which monitored multiple pollutants year-round at 150 sites and used land use regression (LUR) modeling to estimate fine-scale (100-m) intra-urban spatial variance in fine particles (PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3). 3. Daily data and time-trends derived from all U.S. Environmental Protection Agency (EPA) Air Quality System (AQS) monitors in NYC for 2005-2011, which we combined with NYCCAS surfaces to create residence- and day-specific spatiotemporal exposure estimates. 4. Complete data on in- and out-patient unscheduled CVD events presented in NYC hospitals for 2005-2011 (n = 1,113,185) from the New York State (NYS) Department of Health's Statewide Planning and Research Cooperative System (SPARCS). In the study, we quantified relationships between multiple pollutant exposures and both community CVD event rates and individual risk of CVD events in NYC and tested whether pollution-CVD associations varied by community SEP and social stressor exposures. We hypothesized (1) that greater chronic community-level SEP, stressor, and pollution exposures would be associated with higher community CVD rates; (2) that spatiotemporal variations in multiple pollutants would be associated with excess risk of CVD events; and (3) that pollution-CVD associations would be stronger in communities of lower SEP or higher stressor exposures.

RESULTS

To first understand the separate and combined associations with CVD for both stressors and pollutants measured at the same spatial and temporal scale of resolution, we used ecological cross-sectional models to examine spatial relationships between multiple chronic pollutant and stressor exposures and age-adjusted community CVD rates. Using census-tract-level annual averages (n = 2,167), we compared associations with CVD rates for multiple pollutant concentrations and social stressors. We found that associations with community CVD rates were consistently stronger for social stressors than for pollutants, in terms of both magnitude and significance. We note, however, that this result may be driven by the relatively greater variation (on a proportional basis) for stressors than for pollutants in NYC. We also tested effect modification of pollutant-CVD associations by each social stressor and found evidence of stronger associations for NO2, PM2.5, and wintertime SO2 with CVD rates, particularly across quintiles of increasing community violence or assault rates (P trend < 0.0001). To examine individual-level associations between spatiotemporal exposures to multiple pollutants and the risk of CVD events, across multiple lag days, we examined the combined effects of multiple pollutant exposures, using spatiotemporal (day- and residence-specific) pollution exposure estimates and hospital data on individual CVD events in case-crossover models, which inherently adjust for nontime-varying individual confounders (e.g., sex and race) and comorbidities. We found consistent significant relationships only for same-day pollutant exposures and the risk of CVD events, suggesting very acute impacts of pollution on CVD risk. Associations with CVD were positive for NO2, PM2.5, and SO2, as hypothesized, and we found inverse associations for O3 (a secondary pollutant chemically decreased ["scavenged"] by fresh emissions that, in NYC, displays spatial and temporal patterns opposite those of NO2). Finally, to test effect modification by chronic community social stressors on the relationships between spatiotemporal pollution measures and the risk of CVD events, we used individual-level case-crossover models, adding interaction terms with categorical versions of each social stressor. We found that associations between NO2 and the risk of CVD events were significantly elevated only in communities with the highest exposures to social stressors (i.e., in the highest quintiles of poverty, socioeconomic deprivation, violence, or assault). The largest positive associations for PM2.5 and winter SO2 were generally found in the highest-stressor communities but were not significant in any quintile. We again found inverse associations for O3, which were likewise stronger for individuals living in communities with greater stressor exposures.

CONCLUSIONS

In ecological models, we found stronger relationships with community CVD rates for social stressors than for pollutant exposures. In case-crossover analyses, higher exposures to NO2, PM2.5, and SO2 were associated with greater excess risk of CVD events but only on the case day (there were no consistent significant lagged-day effects). In effect-modification analyses at both the community and individual level, we found evidence of stronger pollution-CVD associations in communities with higher stressor exposures. Given substantial spatial confounding across multiple social stressors, further research is needed to disentangle these effects in order to identify the predominant social stressors driving this observed differential susceptibility.

Bayesian Wavelet-packet Historical Functional Linear Models

Historical Functional Linear Models (HFLM) quantify associations between a functional predictor and functional outcome where the predictor is an exposure variable that occurs before, or at least concurrently with, the outcome. Prior work on the HFLM has largely focused on estimation of a surface that represents a time-varying association between the functional outcome and the functional exposure. This existing work has employed frequentist and spline-based estimation methods, with little attention paid to formal inference or adjustment for multiple testing and no approaches that implement wavelet-bases. In this work, we propose a new functional regression model that estimates the time-varying, lagged association between a functional outcome and a functional exposure. Building off of recently developed function-on-function regression methods, the model employs a novel use the wavelet-packet decomposition of the exposure and outcome functions that allows us to strictly enforce the temporal ordering of exposure and outcome, which is not possible with existing wavelet-based functional models. Using a fully Bayesian approach, we conduct formal inference on the time-varying lagged association, while adjusting for multiple testing. We investigate the operating characteristics of our wavelet-packet HFLM and compare them to those of two existing estimation procedures in simulation. We also assess several inference techniques and use the model to analyze data on the impact of lagged exposure to particulate matter finer than 2.5μg, or PM_2.5, on heart rate variability in a cohort of journeyman boilermakers during the morning of a typical day's shift.

Cardiovascular effects of air pollution: current evidence from animal and human studies

Air pollution is a global health concern. Particulate matter (PM)_2.5, a component of ambient air pollution, has been identified by the World Health Organization as one of the pollutants that poses the greatest threat to public health. Cardiovascular health effects have been extensively documented, and these effects are still being researched to provide an overview of recent literature regarding air pollution-associated cardiovascular morbidity and mortality in humans. Additionally, potential mechanisms through which air pollutants affect the cardiovascular system are discussed based on human and additional animal studies. We used the strategy of a narrative review to summarize the scientific literature of studies that were published in the past 7 yr. Searches were carried out on PubMed and Web of Science using predefined search queries. We obtained an initial set of 800 publications that were filtered to 78 publications that were relevant to include in this review. Analysis of the literature showed significant associations between air pollution, especially PM_2.5, and the risk of elevated blood pressure (BP), acute coronary syndrome, myocardial infarction (MI), cardiac arrhythmia, and heart failure (HF). Prominent mechanisms that underlie the adverse effects of air pollution include oxidative stress, systemic inflammation, endothelial dysfunction, autonomic imbalance, and thrombogenicity. The current review underscores the relevance of air pollution as a global health concern that affects cardiovascular health. More rigorous standards are needed to reduce the cardiovascular disease burden imposed by air pollution. Continued research on the health impact of air pollution is needed to provide further insight.

Associations Between Neighborhood Park Access and Longitudinal Change in Cognition in Older Adults: The Multi-Ethnic Study of Atherosclerosis

BACKGROUND

Preliminary evidence suggests associations between neighborhood park access and better late-life cognition and reduced Alzheimer's disease (AD) risk.

OBJECTIVE

Examine associations between neighborhood park access and longitudinal change in cognition among U.S. older adults without dementia.

METHODS

We used 2000-2018 observational data from the population-based, multi-site Multi-Ethnic Study of Atherosclerosis (n = 1,733). Measures included proportion of neighborhood park space (park access), distance to nearest park, and 6-year dichotomous and continuous change in scores on the Cognitive Abilities Screening Instrument (CASI; global cognition) and Digit Symbol Coding task (processing speed). Multivariable random intercept models tested main associations and mediation by depressive symptoms, physical activity, and PM2.5 exposure. Effect modification by race (African Americans/Blacks versus Whites) was tested using interaction terms.

RESULTS

Greater park access (equivalent to 10%more in 1/2-mile around home) was associated with maintained/improved CASI score over six years independent of several covariates including individual- and neighborhood-level socioeconomic status (Odds ratio: 1.04; 95%confidence interval: 1.00-1.08). No other associations were observed with the dichotomous or continuous measures of cognitive change and no mediators were found. While a borderline association was seen between greater park access and maintained/improved CASI for African Americans/Blacks but not for Whites, effect modification was not confirmed by testing interaction terms.

CONCLUSION

Neighborhood park access may help maintain/improve late-life global cognition. However, our findings need replication in other population-based studies and regions. Additionally, studies are needed to determine if associations between park access and change in cognition vary by race/ethnicity to inform intervention efforts.

Increased serum levels of aldehydes are associated with cardiovascular disease and cardiovascular risk factors in adults

Previous studies have identified several genetic and environmental risk factors for cardiovascular disease (CVD), but little is known about the associations between serum aldehydes and CVD risk. Herein, we examined associations between serum levels of aldehydes and the risk of CVD and CVD subtypes among 1947 U.S. adults participating in the National Health and Nutrition Examination Survey (NHANES) 2013-2014. Bayesian kernel machine regression (BKMR) was used to analyze the combined effect of serum aldehydes on the overall risk of CVD. We found that isopentanaldehyde concentrations were positively associated with the odds of CVD (adjusted odds ratio (aOR): 2.17; 95 % confidence interval (95 % CI): 1.36, 3.46). The result of BKMR also indicated a positive association of mixed aldehydes with CVD risk. Isopentanaldehyde had the highest posterior inclusion probabilities (PIP = 0.90). Each one-unit (ng/mL) increase in the isopentanaldehyde concentration was associated with a 25.0 mg/dL increase in triglycerides and a 0.9 × 10⁹/L increase in white blood cell (WBC) count in the fully adjusted model. Current evidence suggests that isopentanaldehyde may increase the risk of CVD by elevating triglycerides and WBC count.

THE EXPOSOME IN HUMAN EVOLUTION: FROM DUST TO DIESEL

Global exposures to air pollution and cigarette smoke are novel in human evolutionary history and are associated with about 16 million premature deaths per year. We investigate the history of the human exposome for relationships between novel environmental toxins and genetic changes during human evolution in six phases. Phase I: With increased walking on savannas, early human ancestors inhaled crustal dust, fecal aerosols, and spores; carrion scavenging introduced new infectious pathogens. Phase II: Domestic fire exposed early Homo to novel toxins from smoke and cooking. Phases III and IV: Neolithic to preindustrial Homo sapiens incurred infectious pathogens from domestic animals and dense communities with limited sanitation. Phase V: Industrialization introduced novel toxins from fossil fuels, industrial chemicals, and tobacco at the same time infectious pathogens were diminishing. Thereby, pathogen-driven causes of mortality were replaced by chronic diseases driven by sterile inflammogens, exogenous and endogenous. Phase VI: Considers future health during global warming with increased air pollution and infections. We hypothesize that adaptation to some ancient toxins persists in genetic variations associated with inflammation and longevity.

Putting Co-Exposures on Equal Footing: An Ecological Analysis of Same-Scale Measures of Air Pollution and Social Factors on Cardiovascular Disease in New York City

Epidemiologic evidence consistently links urban air pollution exposures to health, even after adjustment for potential spatial confounding by socioeconomic position (SEP), given concerns that air pollution sources may be clustered in and around lower-SEP communities. SEP, however, is often measured with less spatial and temporal resolution than are air pollution exposures (i.e., census-tract socio-demographics vs. fine-scale spatio-temporal air pollution models). Although many questions remain regarding the most appropriate, meaningful scales for the measurement and evaluation of each type of exposure, we aimed to compare associations for multiple air pollutants and social factors against cardiovascular disease (CVD) event rates, with each exposure measured at equal spatial and temporal resolution. We found that, in multivariable census-tract-level models including both types of exposures, most pollutant-CVD associations were non-significant, while most social factors retained significance. Similarly, the magnitude of association was higher for an IQR-range difference in the social factors than in pollutant concentrations. We found that when offered equal spatial and temporal resolution, CVD was more strongly associated with social factors than with air pollutant exposures in census-tract-level analyses in New York City.

The Alzheimer's Disease Exposome

INTRODUCTION

Environmental factors are poorly understood in the etiology of Alzheimer's disease (AD) and related dementias. The importance of environmental factors in gene environment interactions (GxE) is suggested by wide individual differences in cognitive loss, even for carriers of AD-risk genetic variants.

RESULTS AND DISCUSSION

We propose the "AD exposome" to comprehensively assess the modifiable environmental factors relevant to genetic underpinnings of cognitive aging and AD. Analysis of endogenous and exogenous environmental factors requires multi-generational consideration of these interactions over age and time (GxExT). New computational approaches to the multi-level complexities may identify accessible interventions for individual brain aging. International collaborations on diverse populations are needed to identify the most relevant exposures over the life course for GxE interactions.

Application of the Public Health Exposome Framework to Estimate Phenotypes of Resilience in a Model Ohio African-American Women's Cohort

We report integration of the United States Environmental Protection Agency's (USEPA) United States Environmental Justice Screen (EJSCREEN) database with our Public Health Exposome dataset to interrogate 9232 census blocks to model the complexity of relationships among environmental and socio-demographic variables toward estimating adverse pregnancy outcomes [low birth weight (LBW) and pre-term birth (PTB)] in all Ohio counties. Using a hill-climbing algorithm in R software, we derived a Bayesian network that mapped all controlled associations among all variables available by applying a mapping algorithm. The results revealed 17 environmental and socio-demographic variables that were represented by nodes containing 69 links accounting for a network with 32.85% density and average degree of 9.2 showing the most connected nodes in the center of the model. The model predicts that the socio-economic variables low income, minority, and under age five populations are correlated and associated with the environmental variables; particulate matter (PM_2.5) level in air, proximity to risk management facilities, and proximity to direct discharges in water are linked to PTB and LBW in 88 Ohio counties. The methodology used to derive significant associations of chemical and non-chemical stressors linked to PTB and LBW from indices of geo-coded environmental neighborhood deprivation serves as a proxy for design of an African-American women's cohort to be recruited in Ohio counties from federally qualified community health centers within the 9232 census blocks. The results have implications for the development of severity scores for endo-phenotypes of resilience based on associations and linkages for different chemical and non-chemical stressors that have been shown to moderate cardio-metabolic disease within a population health context.

The role of air pollution and lung function in cognitive impairment

Air pollution has been associated with impaired lung and cognitive function, especially impairment in visuo-construction performance (VCP). In this article, we evaluate whether the effect of air pollution on VCP is mediated by lung function.

We used data from the SALIA cohort (baseline 1985–1994 and follow-up 2007–2010) including 587 women aged 55 years at baseline. Particulate matter (PM) and nitrogen dioxide (NO2) exposures at baseline were estimated via land-use regression models. Lung function was characterised by averages between baseline and follow-up. We used age- and height-controlled Global Lung Initiative (GLI) z-scores of forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC. VCP was assessed at follow-up with the CERAD-Plus neuropsychological test battery and causal mediation analysis was conducted.

An increase of one interquartile range in FEV1 and FVC was positively associated with VCP (β=0.18 (95% CI 0.02–0.34) and β=0.23 (95% CI 0.07–0.39), respectively). The proportion of the association between NO2 on VCP mediated by FEV1 was 6.2% and this was higher in never smokers (7.2%) and non-carriers of the APOE-ε4 allele (11.2%). However, none of the mediations were statistically significant.

In conclusion, air pollution associated VCP was partially mediated by lung function. Further studies on the mechanisms underlying this pathway are required to develop new strategies to prevent air pollution induced cognitive impairment.