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BackgroundPrenatal indoor air pollution and maternal psychosocial factors have been associated with adverse psychopathology. We used environmental exposure mixture methodology to investigate joint effects of both exposure classes on child behavior trajectories.MethodsFor 360 children from the South African Drakenstein Child Health Study, we created trajectories of Child Behavior Checklist scores (24, 42, 60 months) using latent class linear mixed effects models. Indoor air pollutants and psychosocial factors were measured during pregnancy (2ndtrimester). After adjusting for confounding, single-exposure effects (per natural log-1 unit increase) were assessed using polytomous logistic regression models; joint effects using self-organizing maps (SOM), and principal component (PC) analysis.ResultsHigh externalizing trajectory was associated with increased particulate matter (PM10) exposure (OR [95%-CI]: 1.25 [1.01,1.55]) and SOM exposure profile most associated with smoking (2.67 [1.14,6.27]). Medium internalizing trajectory was associated with increased emotional intimate partner violence (2.66 [1.17,5.57]), increasing trajectory with increased benzene (1.24 [1.02,1.51]) and toluene (1.21 [1.02,1.44]) and the PC most correlated with benzene and toluene (1.25 [1.02, 1.54]).ConclusionsPrenatal exposure to environmental pollutants and psychosocial factors was associated with internalizing and externalizing child behavior trajectories. Understanding joint effects of adverse exposure mixtures will facilitate targeted interventions to prevent childhood psychopathology.

BackgroundAir 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.ObjectivesThis 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.MethodsPerceived 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.ResultsParticipants 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, indicating 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 decrease (95% CI: -0.06, -0.01) in CFI score).DiscussionObserved 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.

BackgroundAir pollution has been associated with cognitive decline among 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 cognitive function among the elderly.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 cognition. 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 using 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 interactions between all air pollutants and N-SES for CFI (p-valuesx, and PM2.5 were associated with 5.4% (95%-confidence interval, -0.2,11.4), 4.9% (-0.4,10.4), and 9.8% (2.2,18.0) increases in CFI, respectively. In lowest N-SES suburban areas, IQR increases in CO, NOx, and PM2.5 were associated with higher increases in CFI, namely 13.4% (1.3,26.9), 13.4% (0.3,28.2), and 17.6% (2.8,34.5), 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 in the context of environmental injustice.