Fine particulate matter-sudden death association modified by ventricular hypertrophy and inflammation: a case-crossover study.

Background: Sudden death accounts for approximately 10% of deaths among working-age adults and is associated with poor air quality. Objectives: To identify high-risk groups and potential modifiers and mediators of risk, we explored previously established associations between fine particulate matter (PM2.5) and sudden death stratified by potential risk factors. Methods: Sudden death victims in Wake County, NC, from 1 March 2013 to 28 February 2015 were identified by screening Emergency Medical Systems reports and adjudicated (n = 399). Daily PM2.5 concentrations for Wake County from the Air Quality Data Mart were linked to event and control periods. Potential modifiers included greenspace metrics, clinical conditions, left ventricular hypertrophy (LVH), and neutrophil-to-lymphocyte ratio (NLR). Using a case-crossover design, conditional logistic regression estimated the OR (95%CI) for sudden death for a 5 µg/m3 increase in PM2.5 with a 1-day lag, adjusted for temperature and humidity, across risk factor strata. Results: Individuals having LVH or an NLR above 2.5 had PM2.5 associations of greater magnitude than those without [with LVH OR: 1.90 (1.04, 3.50); NLR > 2.5: 1.25 (0.89, 1.76)]. PM2.5 was generally less impactful for individuals living in areas with higher levels of greenspace. Conclusion: LVH and inflammation may be the final step in the causal pathway whereby poor air quality and traditional risk factors trigger arrhythmia or myocardial ischemia and sudden death. The combination of statistical evidence with clinical knowledge can inform medical providers of underlying risks for their patients generally, while our findings here may help guide interventions to mitigate the incidence of sudden death.

Systematic review and meta-analysis of birth weight and perfluorohexane sulfonate exposures: examination of sample timing and study confidence.

We examined the association between mean birth weight (BW) differences and perfluorohexane sulfonate (PFHxS) exposure biomarkers.We fit a random effects model to estimate the overall pooled effect and for different strata based on biomarker sample timing and overall study confidence. We also conducted an analysis to examine the impact of a continuous measure of gestational age sample timing on the overall pooled effect.We detected a -7.9 g (95% CI -15.0 to -0.7; pQ=0.85; I2=0%) BW decrease per ln ng/mL PFHxS increase based on 27 studies. The 11 medium confidence studies (ß=-10.0 g; 95% CI -21.1 to 1.1) showed larger deficits than 12 high (ß=-6.8 g; 95% CI -16.3 to 2.8) and 4 low confidence studies (ß=-1.5 g; 95% CI -51.6 to 48.7). 10 studies with mid-pregnancy to late-pregnancy sampling periods showed smaller deficits (ß=-3.9 g; 95% CI -17.7 to 9.9) than 5 post-partum studies (ß=-28.3 g; 95% CI -69.3 to 12.7) and 12 early sampling studies (ß=-7.6 g; 95% CI -16.2 to 1.1). 6 of 12 studies with the earliest sampling timing showed results closer to the null.Overall, we detected a small but statistically significant BW deficit across 27 studies. We saw comparable BW deficit magnitudes in both the medium and high confidence studies as well as the early pregnancy group. Despite no definitive pattern by sample timing, larger deficits were seen in postpartum studies. We also saw results closer to the null for a subset of studies restricted to the earliest biomarker collection times. Serial pregnancy sampling, improved precision in gestational age estimates and more standardised reporting of sample variation and exposure units in future epidemiologic research may offer a greater understanding of the relationship between PFHxS on BW and any potential impact of pregnancy haemodynamics.

Identifying groups of children's social mobility opportunity for public health applications using k-means clustering.

Background: The Opportunity Atlas project is a pioneering effort to trace social mobility and adulthood socioeconomic outcomes back to childhood residence. Half of the variation in adulthood socioeconomic outcomes was explainable by neighborhood-level socioeconomic characteristics during childhood. Clustering census tracts by Opportunity Atlas characteristics would allow for further exploration of variance in social mobility. Our objectives here are to identify and describe spatial clustering trends within Opportunity Atlas outcomes. Methods: We utilized a k-means clustering machine learning approach with four outcome variables (individual income, incarceration rate, employment, and percent of residents living in a neighborhood with low levels of poverty) each given at five parental income levels (1st, 25th, 50th, 75th, and 100th percentiles of the national distribution) to create clusters of census tracts across the contiguous United States (US) and within each Environmental Protection Agency region. Results: At the national level, the algorithm identified seven distinct clusters; the highest opportunity clusters occurred in the Northern Midwest and Northeast, and the lowest opportunity clusters occurred in rural areas of the Southwest and Southeast. For regional analyses, we identified between five to nine clusters within each region. PCA loadings fluctuate across parental income levels; income and low poverty neighborhood residence explain a substantial amount of variance across all variables, but there are differences in contributions across parental income levels for many components. Conclusions: Using data from the Opportunity Atlas, we have taken four social mobility opportunity outcome variables each stratified at five parental income levels and created nationwide and EPA region-specific clusters that group together census tracts with similar opportunity profiles. The development of clusters that can serve as a combined index of social mobility opportunity is an important contribution of this work, and this in turn can be employed in future investigations of factors associated with children's social mobility.

Short-term exposure to air pollution and infant mortality: A systematic review and meta-analysis.

BACKGROUND AND AIM: Infant mortality is a widely reported indicator of population health and a leading public health concern. In this systematic review and meta-analysis, we review the available literature for epidemiologic evidence of the association between short-term air pollution exposure and infant mortality. METHODS: Relevant publications were identified through PubMed and Web of Science databases using comprehensive search terms and screened using predefined inclusion/exclusion criteria. We extracted data from included studies and applied a systematic rubric for evaluating study quality across domains including participant selection, outcome, exposure, confounding, analysis, selective reporting, sensitivity, and overall quality. We performed meta-analyses, using both fixed and random-effect methods, and estimated pooled odds ratios (ORs) and 95 % confidence intervals (95%CI) for pollutants (nitrogen dioxide (NO2), sulfur dioxide (SO2), coarse particulate matter (PM10), fine particulate matter (PM2.5), ozone (O3), carbon monoxide (CO)) and infant mortality, neonatal mortality, or postneonatal mortality. RESULTS: Our search returned 549 studies. We excluded 490 studies in the abstract screening phase and an additional 37 studies in the full text screening phase, leaving 22 studies for inclusion. Among these 22 studies, 14 included effect estimates for PM10, 13 for O3, 11 for both NO2 and CO, 8 for SO2, and 3 for PM2.5. We did not calculate a pooled OR for PM2.5 due to the limited number of studies available and demonstrated heterogeneity in the effect estimates. The pooled ORs (95%CI) with the greatest magnitudes were for a 10-ppb increase in SO2 or NO2 concentration in the days before death (1.07 [95%CI: 1.02, 1.12], 1.04 [95%CI: 1.01, 1.08], respectively). The pooled OR for PM10 was 1.02 (95%CI: 1.00, 1.03), and the pooled ORs for CO and O3 were 1.01 (95%CI: 1.00, 1.02) and 0.99 (95%CI: 0.97, 1.01). CONCLUSIONS: Increased exposure to SO2, NO2, PM10, or CO is associated with infant mortality across studies.

Effect measure modification of the association between short-term exposures to PM2.5 and hospitalizations by longs-term PM2.5 exposure among a cohort of people with Chronic Obstructive Pulmonary Disease (COPD) in North Carolina, 2002-2015.

BACKGROUND: Approximately nine million adults in the United States are living with chronic obstructive pulmonary disease (COPD), and positive associations between short-term air pollution exposure and increased risk of COPD hospitalizations in older adults are consistently reported. We examined the association between short-term PM2.5 exposure and hospitalizations and assessed if there is modification by long-term exposure in a cohort of individuals with COPD. METHODS: In a time-referent case-crossover design, we used a cohort of randomly selected individuals with electronic health records from the University of North Carolina Healthcare System, restricted to patients with a medical encounter coded with a COPD diagnosis from 2004-2016 (n = 520), and estimated ambient PM2.5 concentrations from an ensemble model. Odds ratios and 95% confidence intervals (OR (95%CI)) were estimated with conditional logistic regression for respiratory-related, cardiovascular (CVD), and all-cause hospitalizations. Exposures examined were 0-2 and 0-3 day lags of PM2.5 concentration, adjusting for daily census-tract temperature and humidity, and models were stratified by long-term (annual average) PM2.5 concentration at the median value. RESULTS: We observed generally null or low-magnitude negative associations with short-term PM2.5 exposure and respiratory-related (OR per 5 µg/m3 increase in 3-day lag PM2.5: 0.971 (0.885, 1.066)), CVD (2-day lag: 0.976 (0.900, 1.058) and all-cause (3 day lag: 1.003 (0.927, 1.086)) hospitalizations. Associations between short-term PM2.5 exposure and hospitalizations were higher among patients residing in areas with higher levels of annual PM2.5 concentrations (OR per 5 µg/m3 in 3-day lag PM2.5 for all-cause hospitalizations: 1.066 (0.958, 1.185)) than those in areas with lower annual PM2.5 concentrations (OR per 5 µg/m3 in 3-day lag PM2.5 for all-cause hospitalizations: 0.914 (0.804, 1.039)). CONCLUISONS: Differences in associations demonstrate that people in areas with higher annual PM2.5 exposure may be associated with higher risk of hospitalization during short-term increases in PM2.5 exposure.

Interplay of gestational parent exposure to ambient air pollution and diet characteristics on preterm birth.

BACKGROUND: Despite many efforts, preterm birth (PTB) is poorly understood and remains a major public health problem in the United States. Toxicological work suggests gestational parent (GP) diet may modify the effect of ambient pollutants on birth outcomes. We assessed risk of PTB in humans in relation to fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) and variation by diet. METHODS: 684 GP-singleton infant pairs in the Newborn Epigenetics Study prospective birth cohort were attributed ambient air pollutant exposures for each trimester based on residence. Total energy intake, percent of energy intake from saturated fat, and percent of energy intake from total fat were dichotomized at the 75th percentile. >We used log binomial regressions to estimate risk ratios (RR (95%CI)) for PTB by pollutant interquartile ranges, adjusting for GP age, pre-pregnancy body mass index, GP race/ethnicity, GP education, season of conception, household income, and each diet factor. We assessed departure from additivity using interaction contrast ratios (ICRs). We addressed missing covariate data with multiple imputation. RESULTS: Point estimates suggest that O3 may be inversely associated with PTB when exposure occurs in trimester 2 (min RR: 0.77, 95% CI: 0.39, 1.49), but may be harmful when exposure occurs in trimester 3 (max RR: 1.51, 95% CI: 0.62, 3.64). Additionally, PM2.5 may be inversely associated with PTB when considered with total fat and saturated fat in trimester 2. Imprecise ICRs suggest departure from additivity (evidence of modification) with some pollutant-diet combinations. CONCLUSIONS: While confidence intervals are wide, we observed potential modification of pollutant associations by dietary factors. It is imperative that large cohorts collect the required data to examine this topic, as more power is necessary to investigate the nuances suggested by this work.

Associations between weekly gestational exposure of fine particulate matter, ozone, and nitrogen dioxide and preterm birth in a North Carolina Birth Cohort, 2003-2015.

Background: Preterm birth (PTB; <37 weeks completed gestation) is associated with exposure to air pollution, though variability in association magnitude and direction across exposure windows exists. We evaluated associations between weekly gestational exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) with PTB in a North Carolina Birth Cohort from 2003 to 2015 (N = 1,367,517). Methods: Daily average PM2.5 and daily 8-hour maximum NO2 concentration estimates were obtained from a hybrid ensemble model with a spatial resolution of 1 km2. Daily 8-hour maximum census tract-level concentration estimates for O3 were obtained from the EPA's Fused Air Quality Surface Using Downscaling model. Air pollutant concentrations were linked by census tract to residential address at delivery and averaged across each week of pregnancy. Modified Poisson regression models with robust errors were used to estimate risk differences (RD [95% confidence intervals (CI)]) for an interquartile range increase in pollutants per 10,000 births, adjusted for potential confounders. Results: Associations were similar in magnitude across weeks. We observed positive associations for PM2.5 and O3 exposures, but generally null associations with NO2. RDs ranged from 15 (95% CI = 11, 18) to 32 (27, 37) per 10,000 births for PM2.5; from -7 (-14, -1) to 0 (-5, 4) for NO2; and from 4 (1, 7) to 13 (10, 16) for O3. Conclusion: Our results show that increased PM2.5 exposure is associated with an increased risk of PTB across gestational weeks, and these associations persist in multipollutant models with NO2 and/or O3.

Are the adverse health effects of air pollution modified among active children and adolescents? A review of the literature.

Air pollution exposure is associated with negative health consequences among children and adolescents. Physical activity is recommended for all children/adolescents due to benefits to health and development. However, it is unclear if physically active children have additional protective benefits when exposed to higher levels of air pollution, compared to less active children. This systematic review evaluates all available literature since 2000 and examines if effect measure modification (EMM) exists between air pollution exposure and health outcomes among children/adolescents partaking in regular physical activity. PubMed, Science Direct, Scopus, Web of Science, and ProQuest Agricultural & Environmental Science databases were queried, identifying 2686 articles. Title/abstract screening and full-text review eliminated 2620 articles, and 56 articles were removed for evaluating individuals >21, leaving 10 articles for review. Of the included articles, half were conducted in China, three in the United States, and one each in Indonesia and Germany. Seven articles identified EMM between active children and air-pollution related health outcomes. Five of these indicated that children/adolescents do not experience any additional benefits from being physically active in higher levels of air pollution, with some studies implying active children may experience additional detriments, compared to less active children. However, the remaining two EMM studies highlighted modest benefits of having a higher activity level, even in polluted air. Overall, active children/adolescents may be at greater risk from air pollution exposure, but results were not consistent across all studies. Future studies assessing the intersection between air pollution and regular physical activity among children would be useful.

Beneficial Use Impairments, Degradation of Aesthetics, and Human Health: A Review.

In environmental programs and blue/green space development, improving aesthetics is a common goal. There is broad interest in understanding the relationship between ecologically sound environments that people find aesthetically pleasing and human health. However, to date, few studies have adequately assessed this relationship, and no summaries or reviews of this line of research exist. Therefore, we undertook a systematic literature review to determine the state of science and identify critical needs to advance the field. Keywords identified from both aesthetics and loss of habitat literature were searched in PubMed and Web of Science databases. After full text screening, 19 studies were included in the review. Most of these studies examined some measure of greenspace/bluespace, primarily proximity. Only one study investigated the impacts of making space quality changes on a health metric. The studies identified for this review continue to support links between green space and various metrics of health, with additional evidence for blue space benefits on health. No studies to date adequately address questions surrounding the beneficial use impairment degradation of aesthetics and how improving either environmental quality (remediation) or ecological health (restoration) efforts have impacted the health of those communities.

A cross-sectional study of brownfields and birth defects.

BACKGROUND: Brownfields are a multitude of abandoned and disused sites, spanning many former purposes. Brownfields represent a heterogenous yet ubiquitous exposure for many Americans, which may contain hazardous wastes and represent urban blight. Neonates and pregnant individuals are often sensitive to subtle environmental exposures. We evaluate whether residential brownfield exposure is associated with birth defects. METHODS: Using North Carolina birth records from 2003 to 2015, we sampled 753,195 births with 39,495 defects identified. We examined defect groups and 30 distinct phenotypes. Number of brownfields within 2,000 m of the residential address at birth was summed. We utilized mixed effects multivariable logistic regression models adjusted for demographic and environmental covariates available from birth records, 2010 Census, and EPA's Environmental Quality Index to estimate odds ratios (OR) and 95% confidence intervals (CI). RESULTS: We observed positive associations between cardiovascular and external defect groups (OR [95% CI]: 1.07 [1.02-1.13] and 1.17 [1.01-1.35], respectively) and any brownfield exposure. We also observed positive associations with atrial septal and ventricular septal defects (1.08 [1.01-1.16] and 1.15 [1.03-1.28], respectively), congenital cataracts (1.38 [0.98-1.96]), and an inverse association with gastroschisis (0.74 [0.58-0.94]). Effect estimates for several additional defects were positive, though we observed null associations for most group and individual defects. Additional analyses indicated an exposure-response relationship for several defects across levels of brownfield exposure. CONCLUSIONS: Our results indicate that residential proximity to brownfields is associated with birth defects, especially cardiovascular and external defects. In-depth analyses of individual defects and specific contaminants or brownfield sites may reveal additional novel associations.

Estimating exposure to neighborhood crime by race and ethnicity for public health research.

BACKGROUND: Police-reported crime data (hereafter "crime") is routinely used as a psychosocial stressor in public health research, yet few studies have jointly examined (a) differences in crime exposure based on participant race and ethnicity, (b) differences in measures of crime exposure, and (c) considerations for how exposure to police is captured in police-recorded crime data. We estimate neighborhood exposure to crime and discuss the implications of structural differences in exposure to crime and police based on race and ethnicity. METHODS: Using GPS coordinates from 1188 participants in the Newborn Epigenetics Study, we estimated gestational exposure to crime provided by the Durham, North Carolina, Police Department within (a) 800 m and (b) the Census block group of residence. We controlled for non-overlapping spatial boundaries in crime, Census, residential, and police data to report crime spatial (crime per km2) and population (crime per 1000 people per km2) density. RESULTS: We demonstrate dramatic disparities in exposure to crime based on participant race and ethnicity and highlight variability in these disparities based on the type of crime and crime measurement method chosen. CONCLUSIONS: Public health researchers should give thoughtful consideration when using police-reported crime data to measure and model exposure to crime in the United States, as police-reported data encompasses joint exposure to police and crime in the neighborhood setting.

Ozone exposure during early pregnancy and preterm birth: A systematic review and meta-analysis.

Exposure to ozone has been linked to reproductive outcomes, including preterm birth. In this systematic review, we summarize published epidemiologic cohort and case-control studies examining ozone exposures (estimated on a continuous scale) in early pregnancy (1st and 2nd trimesters (T1, T2)) and preterm birth using ratio measures, and perform a meta-analysis to evaluate the potential relationship between them. Studies were identified by searching PubMed and Web of Science, screened according to predefined inclusion/exclusion criteria, and evaluated for study quality. We extracted study data including effect estimates, confidence limits, study location, study years, ozone exposure assessment method, and mean or median ozone concentrations. Nineteen studies were identified and included, of which 18 examined T1 exposure (17 reported effect estimates), and 15 examined T2 exposure. Random effects meta-analysis was performed in the metafor package, R 3.5.3. The pooled OR (95% CI) for a 10 ppb increase in ozone exposure in T1 was 1.06 (1.03, 1.10) with a 95% prediction interval of 0.95, 1.19; for T2 it was 1.05 (1.02, 1.08) with a 95% prediction interval of 0.95, 1.16. Effect estimates for both exposure periods showed high heterogeneity. In meta-regression analyses of study characteristics, study location (continent) explained some (~20%) heterogeneity for T1 exposure studies, but no characteristic explained a substantial amount of heterogeneity for T2 exposure studies. Increased ozone exposure during early pregnancy is associated with preterm birth across studies.

Aggregated cumulative county arsenic in drinking water and associations with bladder, colorectal, and kidney cancers, accounting for population served.

BACKGROUND: Many studies neglect to account for variation in population served by community water systems (CWSs) when aggregating CWS-level contaminant concentrations to county level. OBJECTIVE: In an ecological epidemiologic analysis, we explored two methods-unweighted and weighted (proportion of CWS population served by county population)-to account for population served by CWS in association between arsenic and three cancers to determine the impact of population served on aggregated measures of exposure. METHODS: CWS arsenic concentration data for 19 states were obtained from Centers for Disease Control and Prevention (CDC) National Environmental Public Health Tracking Network for 2000-10, aggregated to county level, and linked to county-level cancer data for 2011-5 from National Cancer Institute and CDC State Cancer Profiles. Negative binomial regression models estimated adjusted risk ratios (aRR) and 95% confidence intervals (CI) between county-level bladder, colorectal, and kidney cancers and quartiles of aggregated cumulative county-level arsenic concentration (ppb-years). RESULTS: We observed positive associations between the highest quartile of exposure, compared to the lowest, of aggregated cumulative county-level arsenic concentration (ppb-year) for bladder [weighted aRR: 1.89(1.53, 2.35)], colorectal [1.64(1.33, 2.01)], and kidney [1.69(1.37, 2.09)] cancers. We observed stronger associations utilizing the weighted exposure assessment method. However, inferences from this study are limited due to the ecologic nature of the analyses and different analytic study designs are needed to assess the utility that the weighted by CWS population served metric has for exposure assessment. SIGNIFICANCE: Weighting by CWS population served accounts for some potential exposure assignment error in epidemiologic analysis.

Exploration of PM mass, source, and component-related factors that might explain heterogeneity in daily PM2.5-mortality associations across the United States.

Multi-city epidemiologic studies examining short-term (daily) differences in fine particulate matter (PM2.5) provide evidence of substantial spatial heterogeneity in city-specific mortality risk estimates across the United States. Because PM2.5 is a mixture of particles, both directly emitted from sources or formed through atmospheric reactions, some of this heterogeneity may be due to regional variations in PM2.5 toxicity. Using inverse variance weighted linear regression, we examined change in percent change in mortality in association with 24 "exposure" determinants representing three basic groupings based on potential explanations for differences in PM toxicity - size, source, and composition. Percent changes in mortality for the PM2.5-mortality association for 313 core-based statistical areas and their metropolitan divisions over 1999-2005 were used as the outcome. Several determinants were identified as potential contributors to heterogeneity: all mass fraction determinants, vehicle miles traveled (VMT) for diesel total, VMT gas per capita, PM2.5 ammonium, PM2.5 nitrate, and PM2.5 sulfate. In multivariable models, only daily correlation of PM2.5 with PM10 and long-term average PM2.5 mass concentration were retained, explaining approximately 10% of total variability. The results of this analysis contribute to the growing body of literature specifically focusing on assessing the underlying basis of the observed spatial heterogeneity in PM2.5-mortality effect estimates, continuing to demonstrate that this heterogeneity is multifactorial and not attributable to a single aspect of PM.

Associations between cumulative environmental quality and ten selected birth defects in Texas.

BACKGROUND: Causes of most birth defects are largely unknown. Genetics, maternal factors (e.g., age, smoking) and environmental exposures have all been linked to some birth defects, including neural tube, oral cleft, limb reduction, and gastroschisis; however, the contribution of cumulative exposures across several environmental domains in association with these defects is not well understood. METHODS: The Environmental Quality Index (EQI) and its domains (air, water, land, sociodemographic, built) were used to estimate county-level cumulative environmental exposures from 2006-2010 and matched to birth defects identified from Texas Birth Defects Registry and live birth records from births in years 2007-2010 (N = 1,610,709). Poisson regression models estimated prevalence ratios (PR) and 95% confidence intervals (CI) for associations between 10 birth defects and the EQI. RESULTS: We observed some positive associations between worst environmental quality and neural tube, anencephaly, spina bifida, oral cleft, cleft palate, cleft lip with and without cleft palate, and gastroschisis [PR range: 1.12-1.55], but near null associations with limb reduction defects. Among domain specific results, we observed the strongest positive associations with the sociodemographic domain across birth defects but varied positive associations among the air and water domains, and negative or null associations with the land and built domains. Overall, few exposure-response patterns were evident. CONCLUSIONS: Our results highlight the complexities of cumulative, simultaneous environmental exposures in the prevalence rates of 10 selected birth defects. We were able to explore the impact of overall and domain specific environmental quality on birth defects and identify potential domain specific drivers of these associations.

Acute effects of short-term exposure to air pollution while being physically active, the potential for modification: A review of the literature.

The science behind the combined effect of (and possible interaction between) physical activity and air pollution exposure on health endpoints is not well established, despite the fact that independent effects of physical activity and air pollution on health are well known. The objective of this review is to systematically assess the available literature pertaining to exposure to air pollution while being physically active, in order to assess statistical interaction. Articles published during 2000-2020 were identified by searching PubMed, Science Direct, and ProQuest Agricultural & Environmental Science Database for terms encompassing air pollution and exercise/physical activity. Articles were included if they examined the following four scenarios: at rest in clean air, physical activity in clean air, at rest in polluted air, and physical activity in polluted air. Risk of bias assessment was performed on all included articles. We identified 25 articles for inclusion and determined risk of bias was low to moderate. Nine articles identified evidence of statistical interaction between air pollution exposure and physical activity, while 16 identified no such interaction. However, pollutant levels, exercise intensity, and the population studied appeared to influence statistical interaction. Even in low levels of air pollution, low-intensity activities (i.e., walking), may intensify the negative impacts of air pollution, particularly among those with pre-existing conditions. However, among healthy adults, the review suggests that exercise is generally beneficial even in high air pollution environments. Particularly, the review indicates that moderate to high-intensity exercise may neutralize any short-term negative effects of air pollution.

A case-crossover analysis of the relationship of air pollution with out-of-hospital sudden unexpected death in Wake County, North Carolina (2013-2015).

Out-of-hospital sudden unexpected deaths are non-accidental deaths that occur without obvious underlying causes and may account for 10% of natural deaths before age 65. Short-term exposure to ambient air pollution is associated with all-cause (non-accidental) and cause-specific (e.g., cardiovascular) mortality, and with immediate exposures often yielding the highest magnitude risk estimates. Few studies have focused on short-term exposure to air pollution and sudden unexpected deaths. Using the University of North Carolina Sudden Unexpected Death in North Carolina population, we examine associations between short-term criteria air pollutant exposures with sudden unexpected deaths using a time-stratified case-crossover design, with data on criteria air pollutants from the Environmental Protection Agency's Air Quality System. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using conditional logistic regression with air pollutant exposures scaled to roughly inter-quartile ranges; models were adjusted for average temperature and relative humidity on event day and preceding 3 days. Potential for confounding by co-pollutants were examined in two pollutant models. ORs for PM2.5 at lag day 1 were elevated (adjusted OR for 5 µg/m3 increase: 1.17 (0.98, 1.40)), and were robust to co-pollutant adjustment. Elevated odds were observed for SO2 at lag day 0, and reduced odds for O3 at lag day 0; however, these associations were somewhat attenuated toward the null (SO2) or were not robust (O3) to co-pollutant adjustment. This analysis in a racially and socioeconomically diverse cohort, with a more inclusive definition of sudden unexpected death than is typically employed offers evidence that PM2.5 may be a clinically relevant trigger of sudden unexpected deaths in susceptible individuals.

Divergent trends in life expectancy across the rural-urban gradient and association with specific racial proportions in the contiguous USA 2000-2005.

OBJECTIVES: To estimate county-level adult life expectancy for Whites, Black/African Americans (Black), American Indian/Alaska Native (AIAN) and Asian/Pacific Islander (Asian) populations and assess the difference across racial groups in the relationship among life expectancy, rurality and specific race proportion. METHODS: We used individual-level death data to estimate county-level life expectancy at age 25 (e25) for Whites, Black, AIAN and Asian in the contiguous USA for 2000-2005. Race-sex-stratified models were used to examine the associations among e25, rurality and specific race proportion, adjusted for socioeconomic variables. RESULTS: Lower e25 was found in the central USA for AIANs and in the west coast for Asians. We found higher e25 in the most rural areas for Whites but in the most urban areas for AIAN and Asians. The associations between specific race proportion and e25 were positive or null for Whites but were negative for Blacks, AIAN, and Asians. The relationship between specific race proportion and e25 varied across rurality. CONCLUSIONS: Identifying differences in adult life expectancy, both across and within racial groups, provides new insights into the geographic determinants of life expectancy disparities.