Abstract

Background/Aim: Long-term air pollution (AP) is associated with cognitive impairment and altered brain structure. These changes are also observed during normal aging. Studies in younger children additionally hint at an age-related functional brain reorganization, i.e. reduced resting-state functional connectivity (RSFC) within functional brain networks and increased RSFC between different brain networks. The current study examined the associations between long-term AP and ambient noise (AN) with RSFC reorganization in older adults.Methods: We used data from participants of the German 1000BRAINS study. To measure AP at the participant’s residences for the years 2000-2003, we applied land use regression and spatiotemporal European Air Pollution Dispersion Chemistry Transport modeling. Exposure to AN was modeled as weighted 24-h (LDEN) means and night-time (LNIGHT) means. Between 2011 and 2015, resting-state functional imaging brain scans were acquired. We defined seven resting-state brain networks (RSN): visual, sensorimotor, dorsal- and ventral attention, limbic, frontoparietal and default RSN and evaluated the degree of segregation as the ratio of within-network RSFC and inter-network RSFC. Multiple linear regression models adjusted for age, sex, socioeconomic status and lifestyle variables were used to estimate the relationship of AP and AN with RSFC.Results: The analysis included 583 participants (44.1% female, mean age of 56 years). Overall, clearly decreased segregation patterns were not visible. Weak associations of particular matter (PM2.5), soot and particle number concentration with decreased segregation were observed in the sensorimotor RSN (i.e. 0.088 [95%-Confidence-Interval: -0.170; -0.006] per 1.41 µg/m3 increase in PM2.5). For a 10 dB(A) increase of LDEN and LNIGHT, we observed weak decreases in segregation of the visual RSN.Conclusions: In accordance with major aging theories, higher exposure to AP and AN could possibly lead to an acceleration of age-related functional brain reorganization. To verify these findings, further studies with larger sample size are needed.

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