Associations between long‐term air pollution exposure and plasma amyloid beta in very old adults. (31st December 2021)

• Record Type: Journal Article
• Authors: Park, Christina; Hajat, Anjum; Leary, Cindy S.; Ilango, Sindana; Semmens, Erin O.; Adam, Claire; Fitzpatrick, Annette L.; Lopez, Oscar L.; Kaufman, Joel D.
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 5
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12-31
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.054700
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Animal studies suggest associations between exposure to air pollutants and increased amyloid beta (Aβ) pathology. However, there is limited research evaluating the relationship of air pollution to Aβ levels in human populations. Therefore, this study examined the role of long‐term air pollution exposure in plasma amyloid levels in a US cohort of older adults. Method: This cross‐sectional study included participants from the Ginkgo Evaluation of Memory Study, a longitudinal cohort of older adults (aged 75 years and older) recruited from four US communities who were dementia free at baseline. Plasma Aβ1‐40 levels were measured in 2000‐2002 and again in 2007‐2008 and log transformed for analyses. We applied validated fine‐scale spatiotemporal models to estimate fine particulate matter (PM2.5 ), coarse particles (PM10 ) and nitrogen dioxide (NO2 ) at participant residential addresses. Address history was constructed up to 20 years prior to visit dates using LexisNexis, a commercial credit reporting company. Exposure to air pollutants was averaged over multiple time periods (from one to 20 years) prior to plasma collection. We estimated percent differences (95% CIs) from ordinary least squares and linear mixed‐effect regression models for baseline and repeated measures data, respectively. All models were adjusted for age, race, gender, site, education, treatment, cystatin c, neighborhood deprivation index, alcohol intake, smoking status, pack‐years of smoking, passive smoke exposure and gait speed. Result: This study included 3, 029 participants with measured Aβ1‐40. A 3 µg/m 3 (interquartile range (IQR)) higher PM10 over 10 years was associated with higher levels of Aβ1‐40 at baseline: percent difference 1.80% (95% CI: 0.22%, 3.40%). We also observed a positive association of increased magnitude in repeated measures analyses: percent difference 5.20% (95% CI: 3.69%, 6.72%). Similar associations between PM2.5 (IQR = 2 µg/m 3 ) and NO2 (IQR = 7 ppb) and Aβ1‐40 were found in repeated measures analyses. Findings from other pollutants and exposure periods are presented in Figure 1. Conclusion: These findings provide some of the first epidemiologic evidence suggesting long‐term concentrations of PM2.5, PM10 and NO2 are associated with increased Aβ1‐40.