Abstract

BackgroundAir pollution has been associated with cognitive function in the elderly. Previous studies have not evaluated the simultaneous effect of neighborhood-level socioeconomic status (N-SES), which can be an essential source of bias. ObjectivesWe explored N-SES as a confounder and effect modifier in a cross-sectional study of air pollution and subjective cognitive function. MethodsWe included 12,058 participants age 50+ years from the Emory Healthy Aging Study in Metro Atlanta using the Cognitive Function Instrument (CFI) score as our outcome, with higher scores representing worse subjective cognitive function. We estimated 9-year average ambient carbon monoxide (CO), nitrogen oxides (NOx), and fine particulate matter (PM2.5) concentrations at residential addresses using a fusion of dispersion and chemical transport models. We collected census-tract level N-SES indicators and created two composite measures via principal component analysis and k-means clustering. Associations between pollutants and CFI and effect modification by N-SES were estimated via linear regression models adjusted for age, education, race and N-SES. ResultsN-SES confounded the association between air pollution and CFI, independent of individual characteristics. We found significant effect modifications by N-SES for the association between air pollution and CFI (p-values<0.001) suggesting that effects of air pollution differ depending on N-SES. Participants living in areas with low N-SES were most vulnerable to air pollution. In the lowest N-SES urban areas, interquartile range (IQR) increases in CO, NOx, and PM2.5 were associated with 5.4% (95%-confidence interval, −0.2,11.3), 4.9% (−0.4,10.4), and 9.8% (2.2,18.0) changes in CFI, respectively. In lowest N-SES suburban areas, IQR increases in CO, NOx, and PM2.5 were associated with higher changes in CFI, namely 13.0% (0.9,26.5), 13.0% (−0.1,27.8), and 17.3% (2.5,34.2), respectively. DiscussionN-SES is an important confounder and effect modifier in our study. This finding could have implications for studying health effects of air pollution and identifying susceptible populations.

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