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The Association of Long-Term Exposure to Particulate Matter Air Pollution with Brain MRI Findings: The ARIC Study.

ABSTRACT: BACKGROUND:Increasing evidence links higher particulate matter (PM) air pollution exposure to late-life cognitive impairment. However, few studies have considered associations between direct estimates of long-term past exposures and brain MRI findings indicative of neurodegeneration or cerebrovascular disease. OBJECTIVE:Our objective was to quantify the association between brain MRI findings and PM exposures approximately 5 to 20 y prior to MRI in the Atherosclerosis Risk in Communities (ARIC) study. METHODS:ARIC is based in four U.S. sites: Washington County, Maryland; Minneapolis suburbs, Minnesota; Forsyth County, North Carolina; and Jackson, Mississippi. A subset of ARIC participants underwent 3T brain MRI in 2011-2013 (n=1,753). We estimated mean exposures to PM with an aerodynamic diameter less than 10 or 2.5?m (PM10 and PM2.5) in 1990-1998, 1999-2007, and 1990-2007 at the residential addresses of eligible participants with MRI data. We estimated site-specific associations between PM and brain MRI findings and used random-effect, inverse variance-weighted meta-analysis to combine them. RESULTS:In pooled analyses, higher mean PM2.5 and PM10 exposure in all time periods were associated with smaller deep-gray brain volumes, but not other MRI markers. Higher PM2.5 exposures were consistently associated with smaller total and regional brain volumes in Minnesota, but not elsewhere. CONCLUSIONS:Long-term past PM exposure in was not associated with markers of cerebrovascular disease. Higher long-term past PM exposures were associated with smaller deep-gray volumes overall, and higher PM2.5 exposures were associated with smaller brain volumes in the Minnesota site. Further work is needed to understand the sources of heterogeneity across sites. https://doi.org/10.1289/EHP2152.

SUBMITTER: Power MC

PROVIDER: S-EPMC6066342 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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The Association of Long-Term Exposure to Particulate Matter Air Pollution with Brain MRI Findings: The ARIC Study.

Power Melinda C MC Lamichhane Archana P AP Liao Duanping D Xu Xiaohui X Jack Clifford R CR Gottesman Rebecca F RF Mosley Thomas T Stewart James D JD Yanosky Jeff D JD Whitsel Eric A EA

Environmental health perspectives 20180216 2

<h4>Background</h4>Increasing evidence links higher particulate matter (PM) air pollution exposure to late-life cognitive impairment. However, few studies have considered associations between direct estimates of long-term past exposures and brain MRI findings indicative of neurodegeneration or cerebrovascular disease.<h4>Objective</h4>Our objective was to quantify the association between brain MRI findings and PM exposures approximately 5 to 20 y prior to MRI in the Atherosclerosis Risk in Commu ...[more]

PMID: 29467108

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Project description:BackgroundPrevious studies suggest that certain dietary patterns and constituents may be beneficial to brain health. Airborne exposures to fine particulate matter [particulate matter with aerodynamic diameter ≤2.5μm (PM2.5)] are neurotoxic, but the combined effects of dietary patterns and PM2.5 have not been investigated.ObjectivesWe examined whether previously reported association between PM2.5 exposure and lower white matter volume (WMV) differed between women whose usual diet during the last 3 months before baseline was more or less consistent with a Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND)-like diet, a dietary pattern that may slow neurodegenerative changes.MethodsThis study included 1,302 U.S. women who were 65-79 y old and free of dementia in the period 1996-1998 (baseline). In the period 2005-2006, structural brain magnetic resonance imaging (MRI) scans were performed to estimate normal-appearing brain volumes (excluding areas with evidence of small vessel ischemic disease). Baseline MIND diet scores were derived from a food frequency questionnaire. Three-year average PM2.5 exposure prior to MRI was estimated using geocoded participant addresses and a spatiotemporal model.ResultsAverage total and temporal lobe WMVs were 0.74 cm3 [95% confidence interval (CI): 0.001, 1.48) and 0.19 cm3 (95% CI: 0.002, 0.37) higher, respectively, with each 0.5-point increase in the MIND score and were 4.16 cm3 (95% CI: -6.99, -1.33) and 1.46 cm3 (95% CI: -2.16, -0.76) lower, respectively, with each interquartile range (IQR) (IQR=3.22 μg/m3) increase in PM2.5. The inverse association between PM2.5 per IQR and WMV was stronger (p-interaction<0.001) among women with MIND scores below the median (for total WMV, -12.47 cm3; 95% CI: -17.17, -7.78), but absent in women with scores above the median (0.16 cm3; 95% CI: -3.41, 3.72), with similar patterns for WMV in the frontal, parietal, and temporal lobes. For total cerebral and hippocampus brain volumes or WMV in the corpus callosum, the associations with PM2.5 were not significantly different for women with high MIND scores and women with low MIND scores.DiscussionIn this cohort of U.S. women, PM2.5 exposure was associated with lower MRI-based WMV, an indication of brain aging, only among women whose usual diet was less consistent with the MIND-like dietary pattern at baseline. https://doi.org/10.1289/EHP8036.

Project description:BackgroundCOVID-19 is a lung disease, and there is medical evidence that air pollution is one of the external causes of lung diseases. Fine particulate matter is one of the air pollutants that damages pulmonary tissue. The combination of the coronavirus and fine particulate matter air pollution may exacerbate the coronavirus' effect on human health.Research questionThis paper considers whether the long-term concentration of fine particulate matter of different sizes changes the number of detected coronavirus infections and the number of COVID-19 fatalities in Germany.Study designData from 400 German counties for fine particulate air pollution from 2002 to 2020 are used to measure the long-term impact of air pollution. Kriging interpolation is applied to complement data gaps. With an ecological study, the correlation between average particulate matter air pollution and COVID-19 cases, as well as fatalities, are estimated with OLS regressions. Thereby, socioeconomic and demographic covariates are included.Main findingsAn increase in the average long-term air pollution of 1 μg/m3 particulate matter PM2.5 is correlated with 199.46 (SD = 29.66) more COVID-19 cases per 100,000 inhabitants in Germany. For PM10 the respective increase is 52.38 (SD = 12.99) more cases per 100,000 inhabitants. The number of COVID-19 deaths were also positively correlated with PM2.5 and PM10 (6.18, SD = 1.44, respectively 2.11, SD = 0.71, additional COVID-19 deaths per 100,000 inhabitants).ConclusionLong-term fine particulate air pollution is suspected as causing higher numbers of COVID-19 cases. Higher long-term air pollution may even increase COVID-19 death rates. We find that the results of the correlation analysis without controls are retained in a regression analysis with controls for relevant confounding factors. Nevertheless, additional epidemiological investigations are required to test the causality of particulate matter air pollution for COVID-19 cases and the severity.

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The Association of Long-Term Exposure to Particulate Matter Air Pollution with Brain MRI Findings: The ARIC Study.

Publications

The Association of Long-Term Exposure to Particulate Matter Air Pollution with Brain MRI Findings: The ARIC Study.

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