A comparison of PM2.5 exposure estimates from different estimation methods and their associations with cognitive testing and brain MRI outcomes.

BACKGROUND: Reported associations between particulate matter with aerodynamic diameter ≤2.5 µm (PM2.5) and cognitive outcomes remain mixed. Differences in exposure estimation method may contribute to this heterogeneity. OBJECTIVES: To assess agreement between PM2.5 exposure concentrations across 11 exposure estimation methods and to compare resulting associations between PM2.5 and cognitive or MRI outcomes. METHODS: We used Visit 5 (2011-2013) cognitive testing and brain MRI data from the Atherosclerosis Risk in Communities (ARIC) Study. We derived address-linked average 2000-2007 PM2.5 exposure concentrations in areas immediately surrounding the four ARIC recruitment sites (Forsyth County, NC; Jackson, MS; suburbs of Minneapolis, MN; Washington County, MD) using 11 estimation methods. We assessed agreement between method-specific PM2.5 concentrations using descriptive statistics and plots, overall and by site. We used adjusted linear regression to estimate associations of method-specific PM2.5 exposure estimates with cognitive scores (n = 4678) and MRI outcomes (n = 1518) stratified by study site and combined site-specific estimates using meta-analyses to derive overall estimates. We explored the potential impact of unmeasured confounding by spatially patterned factors. RESULTS: Exposure estimates from most methods had high agreement across sites, but low agreement within sites. Within-site exposure variation was limited for some methods. Consistently null findings for the PM2.5-cognitive outcome associations regardless of method precluded empirical conclusions about the potential impact of method on study findings in contexts where positive associations are observed. Not accounting for study site led to consistent, adverse associations, regardless of exposure estimation method, suggesting the potential for substantial bias due to residual confounding by spatially patterned factors. DISCUSSION: PM2.5 estimation methods agreed across sites but not within sites. Choice of estimation method may impact findings when participants are concentrated in small geographic areas. Understanding unmeasured confounding by factors that are spatially patterned may be particularly important in studies of air pollution and cognitive or brain health.

Drought severity and all-cause mortality rates among adults in the United States: 1968-2014.

BACKGROUND: Little is known about the effect of drought on all-cause mortality, especially in higher income countries such as the United States. As the frequency and severity of droughts are likely to increase, understanding the connections between drought and mortality becomes increasingly important. METHODS: Our exposure variable was an annual cumulative drought severity score based on the 1-month, county-level Standardized Precipitation Evapotranspiration Index. The outcome variables of demographic subgroup-specific all-cause mortality count data per year were obtained from the National Vital Statistics System. Any counts below 10 deaths were censored in that demographic group per county. We modeled county-stratum-year mortality using interval-censored negative binomial regression with county-level random intercepts, for each combined age-race-sex stratum either with or without further stratification by climate regions. Fixed effects meta-regression was used to test the associations between age, race, sex, and region with the drought-mortality regression coefficients. Predictive margins were then calculated from the meta-regression model to estimate larger subgroup (e.g., 'race' or 'sex') associations of drought with mortality. RESULTS: Most of the results were null for associations between drought severity and mortality, across joint strata of race, age, sex and region, but incidence rate ratios (IRRs) for 17 subgroups were significant after accounting for the multiple testing; ten were < 1 indicating a possible protective effect of drought on mortality for that particular subpopulation. The meta-regression indicated heterogeneity in the association of drought with mortality according to race, climate region, and age, but not by sex. Marginal means of the estimated log-incidence rate ratios differed significantly from zero for age groups 25-34, 35-44, 45-54 and 55-64; for the white race group; and for the South, West and Southwest regions, in the analysis that included wet county-years. The margin of the meta-regression model suggested a slightly negative, but not statistically significant, association of drought with same-year mortality in the overall population. CONCLUSIONS: There were significant, heterogeneous-direction associations in subpopulation-stratified models, after controlling for multiple comparisons, suggesting that the impacts of drought on mortality may not be monolithic across the United States. Meta-regression identified systematic differences in the associations of drought severity with all-cause mortality according to climate region, race, and age. These findings suggest there may be important contextual differences in the effects of drought severity on mortality, motivating further work focused on local mechanisms. We speculate that some of the estimated negative associations of drought severity with same-year mortality could be consistent with either a protective effect of drought on total mortality in the same year, or with a delayed health effect of drought beyond the same year. Further research is needed to clarify associations of drought with more specific causes of death and with sublethal health outcomes, for specific subpopulations, and considering lagged effects occurring beyond the same year as the drought.

Temporal Trends in Per- and Polyfluoroalkyl Substances in Bottlenose Dolphins (Tursiops truncatus) of Indian River Lagoon, Florida and Charleston, South Carolina.

Temporal trends in plasma concentrations of per- and polyfluoroalkyl substances (PFAS) in free-ranging bottlenose dolphins (Tursiops truncatus) inhabiting two geographic areas: Indian River Lagoon, Florida over the years 2003-2015 and the waters surrounding Charleston, South Carolina over 2003-2013, were examined. Nine PFAS met the inclusion criteria for analysis based on percent of values below level of detection and sampling years. Proportionate percentiles parametric quantile regression assuming lognormal distributions was used to estimate the average ratio of PFAS concentrations per year for each chemical. Plasma concentrations decreased over time for perfluorodecanoate (PFDA), perfluorohexane sulfonate (PFHxS), perfluorooctanoate (PFOA), perfluorooctane sulfonate (PFOS), and perfluoroundecanoate (PFUnDA) in both locations. Perfluorononanoate (PFNA) decreased with time in Indian River Lagoon dolphins. Perfluorododecanoate (PFDoDA) concentrations significantly increased over time among female Indian River Lagoon dolphins. Regulation and phaseout of specific PFAS groups may have led to the decreasing levels of those PFAS and increasing levels of other replacement PFAS.

Association of Gaseous Ambient Air Pollution and Dementia-Related Neuroimaging Markers in the ARIC Cohort, Comparing Exposure Estimation Methods and Confounding by Study Site.

BACKGROUND: Evidence linking gaseous air pollution to late-life brain health is mixed. OBJECTIVE: We explored associations between exposure to gaseous pollutants and brain magnetic resonance imaging (MRI) markers among Atherosclerosis Risk in Communities (ARIC) Study participants, with attention to the influence of exposure estimation method and confounding by site. METHODS: We considered data from 1,665 eligible ARIC participants recruited from four US sites in the period 1987-1989 with valid brain MRI data from Visit 5 (2011-2013). We estimated 10-y (2001-2010) mean carbon monoxide (CO), nitrogen dioxide (NO2), nitrogen oxides (NOx), and 8- and 24-h ozone (O3) concentrations at participant addresses, using multiple exposure estimation methods. We estimated site-specific associations between pollutant exposures and brain MRI outcomes (total and regional volumes; presence of microhemorrhages, infarcts, lacunes, and severe white matter hyperintensities), using adjusted linear and logistic regression models. We compared meta-analytically combined site-specific associations to analyses that did not account for site. RESULTS: Within-site exposure distributions varied across exposure estimation methods. Meta-analytic associations were generally not statistically significant regardless of exposure, outcome, or exposure estimation method; point estimates often suggested associations between higher NO2 and NOx and smaller temporal lobe, deep gray, hippocampal, frontal lobe, and Alzheimer disease signature region of interest volumes and between higher CO and smaller temporal and frontal lobe volumes. Analyses that did not account for study site more often yielded significant associations and sometimes different direction of associations. DISCUSSION: Patterns of local variation in estimated air pollution concentrations differ by estimation method. Although we did not find strong evidence supporting impact of gaseous pollutants on brain changes detectable by MRI, point estimates suggested associations between higher exposure to CO, NOx, and NO2 and smaller regional brain volumes. Analyses of air pollution and dementia-related outcomes that do not adjust for location likely underestimate uncertainty and may be susceptible to confounding bias. https://doi.org/10.1289/EHP13906.

Comparison of PM2.5 Air Pollution Exposures and Health Effects Associations Using 11 Different Modeling Approaches in the Women's Health Initiative Memory Study (WHIMS).

BACKGROUND: Many approaches to quantifying air pollution exposures have been developed. However, the impact of choice of approach on air pollution estimates and health-effects associations remains unclear. OBJECTIVES: Our objective is to compare particulate matter with aerodynamic diameter ≤2.5µm (PM2.5) concentrations and resulting health effects associations using multiple estimation approaches previously used in epidemiologic analyses. METHODS: We assigned annual PM2.5 exposure estimates from 1999 to 2004 derived from 11 different approaches to Women's Health Initiative Memory Study (WHIMS) participant addresses within the contiguous US. Approaches included geostatistical interpolation approaches, land-use regression or spatiotemporal models, satellite-derived approaches, air dispersion and chemical transport models, and hybrid models. We used descriptive statistics and plots to assess relative and absolute agreement among exposure estimates and examined the impact of approach on associations between PM2.5 and death due to natural causes, cardiovascular disease (CVD) mortality, and incident CVD events, adjusting for individual-level covariates and climate-based region. RESULTS: With a few exceptions, relative agreement of approach-specific PM2.5 exposure estimates was high for PM2.5 concentrations across the contiguous US. Agreement among approach-specific exposure estimates was stronger near PM2.5 monitors, in certain regions of the country, and in 2004 vs. 1999. Collectively, our results suggest but do not quantify lower agreement at local spatial scales for PM2.5. There was no evidence of large differences in health effects associations with PM2.5 among estimation approaches in analyses adjusted for climate region. CONCLUSIONS: Different estimation approaches produced similar spatial patterns of PM2.5 concentrations across the contiguous US and in areas with dense monitoring data, and PM2.5-health effects associations were similar among estimation approaches. PM2.5 estimates and PM2.5-health effects associations may differ more in samples drawn from smaller areas or areas without substantial monitoring data, or in analyses with finer adjustment for participant location. Our results can inform decisions about PM2.5 estimation approach in epidemiologic studies, as investigators balance concerns about bias, efficiency, and resource allocation. Future work is needed to understand whether these conclusions also apply in the context of other air pollutants of interest. https://doi.org/10.1289/EHP12995.

The association of long-term exposure to criteria air pollutants, fine particulate matter components, and airborne trace metals with late-life brain amyloid burden in the Atherosclerosis Risk in Communities (ARIC) study.

BACKGROUND: Studies suggest associations between long-term ambient air pollution exposure and outcomes related to Alzheimer's disease (AD). Whether a link exists between pollutants and brain amyloid accumulation, a biomarker of AD, is unclear. We assessed whether long-term air pollutant exposures are associated with late-life brain amyloid deposition in Atherosclerosis Risk in Communities (ARIC) study participants. METHODS: We used a chemical transport model with data fusion to estimate ambient concentrations of PM2.5 and its components, NO2, NOx, O3 (24-hour and 8-hour), CO, and airborne trace metals. We linked concentrations to geocoded participant addresses and calculated 10-year mean exposures (2002 to 2011). Brain amyloid deposition was measured using florbetapir amyloid positron emission tomography (PET) scans in 346 participants without dementia in 2012-2014, and we defined amyloid positivity as a global cortical standardized uptake value ratio ≥ the sample median of 1.2. We used logistic regression models to quantify the association between amyloid positivity and each air pollutant, adjusting for putative confounders. In sensitivity analyses, we considered whether use of alternate air pollution estimation approaches impacted findings for PM2.5, NO2, NOx, and 24-hour O3. RESULTS: At PET imaging, eligible participants (N = 318) had a mean age of 78 years, 56% were female, 43% were Black, and 27% had mild cognitive impairment. We did not find evidence of associations between long-term exposure to any pollutant and brain amyloid positivity in adjusted models. Findings were materially unchanged in sensitivity analyses using alternate air pollution estimation approaches for PM2.5, NO2, NOx, and 24-hour O3. CONCLUSIONS: Air pollution may impact cognition and dementia independent of amyloid accumulation, though whether air pollution influences AD pathogenesis later in the disease course or at higher exposure levels deserves further consideration.

Characteristics of movers and predictors of residential mobility in the Atherosclerosis Risk in Communities (ARIC) cohort.

Current efforts to characterize movers and identify predictors of moving have been limited. We used the ARIC cohort to characterize non-movers, short-distance movers, and long-distance movers, and employed best subset algorithms to identify important predictors of moving, including interactions between characteristics. Short- and long-distance movers were notably different from non-movers, and important predictors of moving differed based on the distance of the residential move. Importantly, systematic inclusion of interaction terms enhanced model fit and was substantively meaningful. This work has important implications for epidemiologic studies of contextual exposures and those treating residential mobility as an exposure.

Air Quality Awareness and Behaviors of U.S. Adolescents With and Without Asthma.

INTRODUCTION: Among U.S. adolescents, the knowledge that air pollution can impact health is relatively high and varies by the demographics of the respondents and the places they live, but the influence of asthma status is unknown. This study assesses the role of asthma in U.S. adolescents' awareness, perceptions, and behaviors related to air pollution. METHODS: In 2020, data were analyzed from 817 adolescents aged 12-17 years who responded to the 2020 Porter Novelli Public Services YouthStyles survey, a nationally representative survey of U.S. adolescents. Respondents self-reported having or having had asthma in the past year and their awareness, perceptions, and behaviors related to air pollution. For each aspect of air quality awareness, perception, and behavior, weighted percentages of responses were calculated by asthma status. RESULTS: Overall, an estimated 11.5% of U.S. adolescents self-reported asthma. Awareness that air pollution can impact health, awareness that respondents can limit their air pollution exposure, and having heard or read about air quality alerts were similar among adolescents with and without asthma, with some differences reported in where they heard or read about air quality alerts. Those with asthma reported discussing with a health professional about ways to limit exposure more frequently than those without asthma. CONCLUSIONS: Despite the well-known risk of asthma exacerbations from air pollution exposure, air quality awareness was similar among adolescents with and without asthma. These findings reveal the areas in which air quality awareness and behaviors to reduce exposure can be improved among adolescents with and without asthma.

Outdoor Air Quality Awareness, Perceptions, and Behaviors Among U.S. Children Aged 12-17 Years, 2015-2018.

PURPOSE: This study aimed to assess U.S. adolescents' perceptions and knowledge about air quality and their behaviors aimed to reduce air pollution exposure and whether they vary by demographic characteristics. METHODS: We analyzed data from the Porter Novelli Public Services YouthStyles survey, a nationally representative survey of U.S. adolescents aged 12-17 years. In survey years 2015-2018, a total of 3,547 adolescents self-reported awareness, perceptions, and behaviors related to air pollution. We calculated weighted percentages of respondents reporting each aspect of air quality awareness, perception, and behaviors overall and by categories of age, gender, parental education, metropolitan status, region, and survey year. RESULTS: Overall, an estimated 81% of U.S. adolescents thought outdoor air pollution could impact health, 52% thought there were things they could do to limit their or their family's exposure, 19% were aware of air quality alerts, 46% of those who thought or were informed air quality was bad did something differently, and 19% always or usually avoided busy roads to reduce air pollution exposure; differences were reported by some demographic variables. CONCLUSIONS: Among U.S. adolescents, awareness that air pollution could impact health was relatively high. However, gaps were found in the awareness of the potential impacts and other aspects of awareness and perceptions related to air pollution and the engagement in behaviors to reduce exposure, some of which varied by demographic characteristics. These results can be used to inform interventions that increase awareness and behaviors to reduce air pollution exposures among U.S. adolescents.