A causal exposure response function with local adjustment for\n confounding: Estimating health effects of exposure to low levels of ambient\n fine particulate matter

The Clean Air Act mandates that the National Ambient Air Quality Standards\n(NAAQS) must be routinely assessed to protect populations based on the latest\nscience. Therefore, researchers should continue to address whether exposure to\nlevels of air pollution below the NAAQS is harmful to human health. The\ncontentious nature surrounding environmental regulations urges us to cast this\nquestion within a causal inference framework. Parametric and semi-parametric\nregression approaches have been used to estimate the exposure-response (ER)\ncurve between ambient air pollution and health outcomes. Most of these\napproaches are not formulated within a causal framework, adjust for the same\ncovariates across all levels of exposure, and do not account for model\nuncertainty. We introduce a Bayesian framework for the estimation of a causal\nER curve called LERCA (Local Exposure Response Confounding Adjustment), which\nallows for different confounders and different strength of confounding at the\ndifferent exposure levels; and propagates uncertainty regarding confounders'\nselection and the shape of the ER. LERCA provides a principled way of assessing\nthe covariates' confounding importance at different exposure levels, providing\nresearchers with information regarding the variables to adjust for in\nregression models. Using simulations, we show that state of the art approaches\nperform poorly in estimating the ER curve in the presence of local confounding.\nLERCA is used to evaluate the relationship between exposure to ambient PM2.5\nand cardiovascular hospitalizations for 5,362 zip codes in the US, while\nadjusting for a potentially varying set of confounders across the exposure\nrange. Ambient PM2.5 leads to an increase in cardiovascular hospitalization\nrates when focusing at the low exposure range. Our results indicate that there\nis no threshold for the effect of PM2.5 on cardiovascular hospitalizations.\n