Putting Co-Exposures on Equal Footing: An Ecological Analysis of Same-Scale Measures of Air Pollution and Social Factors on Cardiovascular Disease in New York City

Abstract

Epidemiologic evidence consistently links urban air pollution exposures to health, even after adjustment for potential spatial confounding by socioeconomic position (SEP), given concerns that air pollution sources may be clustered in and around lower-SEP communities. SEP, however, is often measured with less spatial and temporal resolution than are air pollution exposures (i.e., census-tract socio-demographics vs. fine-scale spatio-temporal air pollution models). Although many questions remain regarding the most appropriate, meaningful scales for the measurement and evaluation of each type of exposure, we aimed to compare associations for multiple air pollutants and social factors against cardiovascular disease (CVD) event rates, with each exposure measured at equal spatial and temporal resolution. We found that, in multivariable census-tract-level models including both types of exposures, most pollutant–CVD associations were non-significant, while most social factors retained significance. Similarly, the magnitude of association was higher for an IQR-range difference in the social factors than in pollutant concentrations. We found that when offered equal spatial and temporal resolution, CVD was more strongly associated with social factors than with air pollutant exposures in census-tract-level analyses in New York City.

Confounding by Socioeconomic Status in Epidemiological Studies of Air Pollution and Health: Challenges and Opportunities

“…Others find similar magnitudes for SES indices in comparison with individual indicators of poverty, income, education, or occupation ( Hajat et al. 2013 ; Humphrey et al. 2019 ).…”

“…The environmental epidemiology and exposure science communities have made great efforts in recent years toward vastly improving the spatial and temporal precision of AP exposure estimates for epidemiological research. These efforts have not been matched by a concurrent improvement in the precision with which SES factors are measured in studies of AP effects on health ( Humphrey et al. 2019 ).…”

“…This issue of differential spatial classification between SES and environmental exposures is important, in that each may truly operate at a different meaningful spatial scale ( Humphrey et al. 2019 ); for example, many air pollutants follow a physical decay in concentrations going away from sources (i.e., concentrations reduce substantially within several hundred meters of a roadway) ( Karner et al.…”

“…Experimenting with indicators from different domains (e.g., income, education) and including indicators from different geographic scales (e.g., individual and neighborhood) may help alleviate residual confounding. Ideally, SES variables should be specified with the most resolution and granularity possible and in a manner that captures as much variance as possible in epidemiologic models (i.e., continuous variables, nonlinear forms) ( Humphrey et al. 2019 ).…”

Population responses to environmental change: looking back, looking forward

“…Even more importantly, they include social characteristics of neighborhoods (such as the poverty rate) that are likely correlated with exposure to lead paint or air pollution and that also affect income mobility, teenage birth, and incarceration. Research on the effects of chemical hazards on individual health outcomes that controls for neighborhood poverty is surprisingly rare (for exceptions, see Ailshire & Crimmins, 2014;Humphrey et al, 2019;Kravitz-Wirtz et al, 2018). Demographers would do well to fully integrate the multidimensionality of environments in their future research, 3 as well as to consider a full range of pathways implicated in their effects.…”