The complex relationship of air pollution and neighborhood socioeconomic status and their association with cognitive decline

被引:18
|
作者
Christensen, Grace M. [1 ]
Li, Zhenjiang [2 ]
Pearce, John [3 ]
Marcus, Michele [1 ,2 ]
Lah, James J. [4 ]
Waller, Lance A. [2 ,5 ]
Ebelt, Stefanie [1 ,2 ]
Huls, Anke [1 ,2 ]
机构
[1] Emory Univ, Rollins Sch Publ Hlth, Dept Epidemiol, Atlanta, GA 30322 USA
[2] Emory Univ, Rollins Sch Publ Hlth, Gangarosa Dept Environm Hlth, Atlanta, GA USA
[3] Med Univ South Carolina, Coll Med, Dept Publ Hlth Sci, Charleston, SC USA
[4] Emory Univ, Sch Med, Dept Neurol, Atlanta, GA 30322 USA
[5] Emory Univ, Rollins Sch Publ Hlth, Dept Biostat & Bioinformat, Atlanta, GA 30322 USA
关键词
Air pollution; Socioeconomic status; Cognitive functioning; Joint effects; Environmental mixtures; Epidemiology; HEALTH; DEMENTIA; REGRESSION; MIXTURES; BRAIN; RISK;
D O I
10.1016/j.envint.2022.107416
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Background: Air pollution and neighborhood socioeconomic status (nSES) have been shown to affect cognitive decline in older adults. In previous studies, nSES acts as both a confounder and an effect modifier between air pollution and cognitive decline. Objectives: This study aims to examine the individual and joint effects of air pollution and nSES on cognitive decline on adults 50 years and older in Metro Atlanta, USA. Methods: Perceived memory and cognitive decline was assessed in 11,897 participants aged 50+ years from the Emory Healthy Aging Study (EHAS) using the cognitive function instrument (CFI). Three-year average air pollution concentrations for 12 pollutants and 16 nSES characteristics were matched to participants using census tracts. Individual exposure linear regression and LASSO models explore individual exposure effects. Environmental mixture modeling methods including, self-organizing maps (SOM), Bayesian kernel machine regression (BKMR), and quantile-based G-computation explore joint effects, and effect modification between air pollutants and nSES characteristics on cognitive decline. Results: Participants living in areas with higher air pollution concentrations and lower nSES experienced higher CFI scores (beta: 0.121; 95 % CI: 0.076, 0.167) compared to participants living in areas with low air pollution and high nSES. Additionally, the BKMR model showed a significant overall mixture effect on cognitive decline, suggesting synergy between air pollution and nSES. These joint effects explain protective effects observed in single-pollutant linear regression models, even after adjustment for confounding by nSES (e.g., an IQR increase in CO was associated with a 0.038-point lower (95 % CI: -0.06, -0.01) CFI score). Discussion: Observed protective effects of single air pollutants on cognitive decline can be explained by joint effects and effect modification of air pollutants and nSES. Researchers must consider nSES as an effect modifier if not a co-exposure to better understand the complex relationships between air pollution and nSES in urban settings.
引用
收藏
页数:10
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