A scalar-on-quantile-function approach for estimating short-term health effects of environmental exposures.

Environmental epidemiologic studies routinely utilize aggregate health outcomes to estimate effects of short-term (eg, daily) exposures that are available at increasingly fine spatial resolutions. However, areal averages are typically used to derive population-level exposure, which cannot capture the spatial variation and individual heterogeneity in exposures that may occur within the spatial and temporal unit of interest (eg, within a day or ZIP code). We propose a general modeling approach to incorporate within-unit exposure heterogeneity in health analyses via exposure quantile functions. Furthermore, by viewing the exposure quantile function as a functional covariate, our approach provides additional flexibility in characterizing associations at different quantile levels. We apply the proposed approach to an analysis of air pollution and emergency department (ED) visits in Atlanta over 4 years. The analysis utilizes daily ZIP code-level distributions of personal exposures to 4 traffic-related ambient air pollutants simulated from the Stochastic Human Exposure and Dose Simulator. Our analyses find that effects of carbon monoxide on respiratory and cardiovascular disease ED visits are more pronounced with changes in lower quantiles of the population's exposure. Software for implement is provided in the R package nbRegQF.

Time-series analysis of temperature variability and cardiovascular emergency department visits in Atlanta over a 27-year period.

BACKGROUND: Short-term temperature variability, defined as the temperature range occurring within a short time span at a given location, appears to be increasing with climate change. Such variation in temperature may influence acute health outcomes, especially cardiovascular diseases (CVD). Most research on temperature variability has focused on the impact of within-day diurnal temperature range, but temperature variability over a period of a few days may also be health-relevant through its impact on thermoregulation and autonomic cardiac functioning. To address this research gap, this study utilized a database of emergency department (ED) visits for a variety of cardiovascular health outcomes over a 27-year period to investigate the influence of three-day temperature variability on CVD. METHODS: For the period of 1993-2019, we analyzed over 12 million CVD ED visits in Atlanta using a Poisson log-linear model with overdispersion. Temperature variability was defined as the standard deviation of the minimum and maximum temperatures during the current day and the previous two days. We controlled for mean temperature, dew point temperature, long-term time trends, federal holidays, and day of week. We stratified the analysis by age group, season, and decade. RESULTS: All cardiovascular outcomes assessed, except for hypertension, were positively associated with increasing temperature variability, with the strongest effects observed for stroke and peripheral vascular disease. In stratified analyses, adverse associations with temperature variability were consistently highest in the moderate-temperature season (October and March-May) and in the 65 + age group for all outcomes. CONCLUSIONS: Our results suggest that CVD morbidity is impacted by short-term temperature variability, and that patients aged 65 and older are at increased risk. These effects were more pronounced in the moderate-temperature season and are likely driven by the Spring season in Atlanta. Public health practitioners and patient care providers can use this knowledge to better prepare patients during seasons with high temperature variability or ahead of large shifts in temperature.

Differential DNA methylation in the brain as potential mediator of the association between traffic-related PM2.5 and neuropathology markers of Alzheimer's disease.

INTRODUCTION: Growing evidence indicates that fine particulate matter (PM2.5) is a risk factor for Alzheimer's disease (AD), but the underlying mechanisms have been insufficiently investigated. We hypothesized differential DNA methylation (DNAm) in brain tissue as a potential mediator of this association. METHODS: We assessed genome-wide DNAm (Illumina EPIC BeadChips) in prefrontal cortex tissue and three AD-related neuropathological markers (Braak stage, CERAD, ABC score) for 159 donors, and estimated donors' residential traffic-related PM2.5 exposure 1, 3, and 5 years prior to death. We used a combination of the Meet-in-the-Middle approach, high-dimensional mediation analysis, and causal mediation analysis to identify potential mediating CpGs. RESULTS: PM2.5 was significantly associated with differential DNAm at cg25433380 and cg10495669. Twenty-four CpG sites were identified as mediators of the association between PM2.5 exposure and neuropathology markers, several located in genes related to neuroinflammation. DISCUSSION: Our findings suggest differential DNAm related to neuroinflammation mediates the association between traffic-related PM2.5 and AD. HIGHLIGHTS: First study to evaluate the potential mediation effect of DNA methylation for the association between PM2.5 exposure and neuropathological changes of Alzheimer's disease. Study was based on brain tissues rarely investigated in previous air pollution research. Cg10495669, assigned to RBCK1 gene playing a role in inflammation, was associated consistently with 1-year, 3-year, and 5-year traffic-related PM2.5 exposures prior to death. Meet-in-the-middle approach and high-dimensional mediation analysis were used simultaneously to increase the potential of identifying the differentially methylated CpGs. Differential DNAm related to neuroinflammation was found to mediate the association between traffic-related PM2.5 and Alzheimer's disease.

Associations of pollen and cardiovascular disease morbidity in Atlanta during 1993-2018.

Background: Pollen exposure is associated with substantial respiratory morbidity, but its potential impact on cardiovascular disease (CVD) remains less understood. This study aimed to investigate the associations between daily levels of 13 pollen types and emergency department (ED) visits for eight CVD outcomes over a 26-year period in Atlanta, GA. Methods: We acquired pollen data from Atlanta Allergy & Asthma, a nationally certified pollen counting station, and ED visit data from individual hospitals and the Georgia Hospital Association. We performed time-series analyses using quasi-Poisson distributed lag models, with primary analyses assessing 3-day (lag 0-2 days) pollen levels. Models controlled for temporally varying covariates, including air pollutants. Results: During 1993-2018, there were 1,573,968 CVD ED visits. Most pairwise models of the 13 pollen types and eight CVD outcomes showed no association, with a few exceptions potentially due to chance. Conclusion: We found limited evidence of the impact of pollen on cardiovascular morbidity in Atlanta. Further study on pollen exposures in different climactic zones and exploration of pollen-pollution mixture effects is warranted.

Assessment of census-tract level socioeconomic position as a modifier of the relationship between short-term PM2.5 exposure and cardiovascular emergency department visits in Missouri.

INTRODUCTION: Ambient particulate matter ≤ 2.5 µm in aerodynamic diameter (PM2.5) exposure elevates the risk for cardiovascular disease morbidity (CVDM). The aim of this study is to characterise which area-level measures of socioeconomic position (SEP) modify the relationship between PM2.5 exposure and CVDM in Missouri at the census-tract (CT) level. METHODS: We use individual level Missouri emergency department (ED) admissions data (n=3 284 956), modelled PM2.5 data, and yearly CT data from 2012 to 2016 to conduct a two-stage analysis. Stage one uses a case-crossover approach with conditional logistic regression to establish the baseline risk of ED visits associated with IQR changes in PM2.5. In the second stage, we use multivariate metaregression to examine how CT-level SEP modifies the relationship between ambient PM2.5 exposure and CVDM. RESULTS: We find that overall, ambient PM2.5 exposure is associated with increased risk for CVDM. We test effect modification in statewide and urban CTs, and in the warm season only. Effect modification results suggest that among SEP measures, poverty is most consistently associated with increased risk for CVDM. For example, across Missouri, the highest poverty CTs are at an elevated risk for CVDM (OR=1.010 (95% CI 1.007 to 1.014)) compared with the lowest poverty CTs (OR=1.004 (95% CI 1.000 to 1.008)). Other SEP modifiers generally display an inconsistent or null effect. CONCLUSION: Overall, we find some evidence that area-level SEP modifies the relationship between ambient PM2.5 exposure and CVDM, and suggest that the relationship between air-pollution, area-level SEP and CVDM may be sensitive to spatial scale.

Joint effects of air pollution and neighborhood socioeconomic status on cognitive decline - Mediation by depression, high cholesterol levels, and high blood pressure.

Air pollution and neighborhood socioeconomic status (N-SES) are associated with adverse cardiovascular health and neuropsychiatric functioning in older adults. This study examines the degree to which the joint effects of air pollution and N-SES on the cognitive decline are mediated by high cholesterol levels, high blood pressure (HBP), and depression. In the Emory Healthy Aging Study, 14,390 participants aged 50+ years from Metro Atlanta, GA, were assessed for subjective cognitive decline using the cognitive function instrument (CFI). Information on the prior diagnosis of high cholesterol, HBP, and depression was collected through the Health History Questionnaire. Participants' census tracts were assigned 3-year average concentrations of 12 air pollutants and 16 N-SES characteristics. We used the unsupervised clustering algorithm Self-Organizing Maps (SOM) to create 6 exposure clusters based on the joint distribution of air pollution and N-SES in each census tract. Linear regression analysis was used to estimate the effects of the SOM cluster indicator on CFI, adjusting for age, race/ethnicity, education, and neighborhood residential stability. The proportion of the association mediated by high cholesterol levels, HBP, and depression was calculated by comparing the total and direct effects of SOM clusters on CFI. Depression mediated up to 87 % of the association between SOM clusters and CFI. For example, participants living in the high N-SES and high air pollution cluster had CFI scores 0.05 (95 %-CI:0.01,0.09) points higher on average compared to those from the high N-SES and low air pollution cluster; after adjusting for depression, this association was attenuated to 0.01 (95 %-CI:-0.04,0.05). HBP mediated up to 8 % of the association between SOM clusters and CFI and high cholesterol up to 5 %. Air pollution and N-SES associated cognitive decline was partially mediated by depression. Only a small portion (<10 %) of the association was mediated by HBP and high cholesterol.

Association between Fine Particulate Matter Exposure and Cerebrospinal Fluid Biomarkers of Alzheimer's Disease among a Cognitively Healthy Population-Based Cohort.

BACKGROUND: Epidemiological evidence suggests air pollution adversely affects cognition and increases the risk of Alzheimer's disease (AD), but little is known about the biological effects of fine particulate matter (PM2.5, particulate matter with aerodynamic diameter ≤2.5µm) on early predictors of future disease risk. OBJECTIVES: We investigated the association between 1-, 3-, and 5-y exposure to ambient and traffic-related PM2.5 and cerebrospinal fluid (CSF) biomarkers of AD. METHODS: We conducted a cross-sectional analysis using data from 1,113 cognitively healthy adults (45-75 y of age) from the Emory Healthy Brain Study in Georgia in the United States. CSF biomarker concentrations of Aß42, tTau, and pTau, were collected at enrollment (2016-2020) and analyzed with the Roche Elecsys system. Annual ambient and traffic-related residential PM2.5 concentrations were estimated at a 1-km and 250-m resolution, respectively, and computed for each participant's geocoded address, using three exposure time periods based on specimen collection date. Associations between PM2.5 and CSF biomarker concentrations, considering continuous and dichotomous (dichotomized at clinical cutoffs) outcomes, were estimated with multiple linear/logistic regression, respectively, controlling for potential confounders (age, gender, race, ethnicity, body mass index, and neighborhood socioeconomic status). RESULTS: Interquartile range (IQR; IQR=0.845) increases in 1-y [ß:-0.101; 95% confidence interval (CI): -0.18, -0.02] and 3-y (ß:-0.078; 95% CI: -0.15, -0.00) ambient PM2.5 exposures were negatively associated with Aß42 CSF concentrations. Associations between ambient PM2.5 and Aß42 were similar for 5-y estimates (ß:-0.076; 95% CI: -0.160, 0.005). Dichotomized CSF variables revealed similar associations between ambient PM2.5 and Aß42. Associations with traffic-related PM2.5 were similar but not significant. Associations between PM2.5 exposures and tTau, pTau tTau/Aß42, or pTau/Aß42 levels were mainly null. CONCLUSION: In our study, consistent trends were found between 1-y PM2.5 exposure and decreased CSF Aß42, which suggests an accumulation of amyloid plaques in the brain and an increased risk of developing AD. https://doi.org/10.1289/EHP13503.

Dust storms and cardiorespiratory emergency department visits in three Southwestern United States: application of a monitoring-based exposure metric.

Climate change is projected to increase the risk of dust storms, particularly in subtropical dryland, including the southwestern US. Research on dust storm's health impacts in the US is limited and hindered by challenges in dust storm identification. This study assesses the potential link between dust storms and cardiorespiratory emergency department (ED) visits in the southwestern US. We acquired data for 2005-2016 from eight IMPROVE (Interagency Monitoring of PROtected Visual Environments) sites in Arizona, California, and Utah. We applied a validated algorithm to identify dust storm days at each site. We acquired patient-level ED visit data from state agencies and ascertained visits for respiratory, cardiovascular, and cause-specific subgroups among patients residing in ZIP codes within 50 km of an IMPROVE site. Using a case-crossover design, we estimated short-term associations of ED visits and dust storms, controlling for temporally varying covariates. During 2005-2016, 40 dust storm days occurred at the eight IMPROVE sites. Mean PM10 and PM2.5 levels were three to six times greater on dust storm days compared to non-dust storm days. Over the study period, there were 2 524 259 respiratory and 2 805 925 cardiovascular ED visits. At lags of 1, 2, and 3 days after a dust storm, we observed 3.7% (95% CI: 1.0%, 7.6%), 4.9% (95% CI: 1.1%, 8.9%), and 5.0% (95% CI: 1.3%, 8.9%) elevated odds of respiratory ED visits compared to non-dust storm days. Estimated associations of dust storm days and cardiovascular disease ED visits were largely consistent with the null. Using a monitoring-based exposure metric, we observed associations among dust storms and respiratory ED visits. The results add to growing evidence of the health threat posed by dust storms. The dust storm metric was limited by lack of daily data; future research should consider information from satellite and numerical models to enhance dust storm characterization.

Association of PM2.5 Exposure and Alzheimer Disease Pathology in Brain Bank Donors-Effect Modification by APOE Genotype.

BACKGROUND AND OBJECTIVES: Fine particulate matter (PM2.5) exposure has been found to be associated with Alzheimer disease (AD) and is hypothesized to cause inflammation and oxidative stress in the brain, contributing to neuropathology. The APOE gene, a major genetic risk factor of AD, has been hypothesized to modify the association between PM2.5 and AD. However, little prior research exists to support these hypotheses. This study investigates the association between traffic-related PM2.5 and AD hallmark pathology, including effect modification by APOE genotype, in an autopsy cohort. METHODS: A cross-sectional study was conducted using brain tissue donors enrolled in the Emory Goizueta AD Research Center who died before 2020 (n = 224). Donors were assessed for AD pathology including the Braak stage, Consortium to Establish a Registry for AD (CERAD) score, and combined AD neuropathologic change (ABC) score. Traffic-related PM2.5 concentrations were modeled for the metro-Atlanta area during 2002-2019 with a spatial resolution of 200-250 m. One-year, 3-year, and 5-year average PM2.5 concentrations before death were matched to participants' home address. We assessed the association between traffic-related PM2.5 and AD hallmark pathology and effect modification by APOE genotype, using adjusted ordinal logistic regression models. RESULTS: Among the 224 participants, the mean age of death was 76 years, and 57% had at least 1 APOE ε4 copy. Traffic-related PM2.5 was significantly associated with the CERAD score for the 1-year exposure window (odds ratio [OR] 1.92; 95% CI 1.12-3.30) and the 3-year exposure window (OR 1.87; 95% CI 1.01-3.17). PM2.5 was also associated with higher Braak stage and ABC score albeit nonsignificantly. The strongest associations between PM2.5 and neuropathology markers were among those without APOE ε4 alleles (e.g., for the CERAD score and 1-year exposure window, OR 2.31; 95% CI 1.36-3.94), though interaction between PM2.5 and APOE genotype was not statistically significant. DISCUSSION: Our study found traffic-related PM2.5 exposure was associated with the CERAD score in an autopsy cohort, contributing to epidemiologic evidence that PM2.5 affects ß-amyloid deposition in the brain. This association was particularly strong among donors without APOE ε4 alleles. Future studies should further investigate the biological mechanisms behind this association.

Association between outdoor temperature and fatal police shootings in the United States, 2015-2021.

Background: Here, we investigate the association between outdoor temperature and fatal police shootings in the United States between 2015 and 2021. Methods: We conducted a time-stratified case-crossover study. Data on fatal police shootings were from the Washington Post's Fatal Force database and temperature data were from Daymet. Results: A 5°C increase in maximum same-day temperature was associated with a 1.033 (95% CI = 1.002, 1.065) increased odds of a fatal police shooting. In stratified analyses, the strongest associations were observed in victims who were armed (OR, 1.052 [95% CI = 1.017, 1.088), White (OR, 1.052 [95% CI = 1.006, 1.100), or aged 45+ (OR, 1.110 [95% CI = 1.044, 1.181]). In additional subgroup analyses, relative risks were also generally higher among those who were armed. Conclusions: There is evidence of an association between outdoor temperature and fatal police shootings in the United States, particularly when the victims were reported as armed. This study cannot determine if the associations are a result of any specific causes (e.g., increased police aggression or other factors).