Estimating exposure response functions using ambient pollution concentrations

TL;DR

This paper introduces a Bayesian modeling approach to estimate health effects of air pollution by simulating individual exposures from ambient pollution data, accounting for confounders and biases, and applying it to respiratory mortality in London.

Contribution

It develops a general framework combining computer simulation and hierarchical Bayesian inference to estimate exposure-response functions for environmental hazards.

Findings

Estimated exposure-response relationship for PM10 and respiratory mortality.

Comparison of ambient concentration effects versus estimated personal exposures.

Demonstration of the method's applicability to urban air pollution health studies.

Abstract

This paper presents an approach to estimating the health effects of an environmental hazard. The approach is general in nature, but is applied here to the case of air pollution. It uses a computer model involving ambient pollution and temperature inputs, to simulate the exposures experienced by individuals in an urban area, whilst incorporating the mechanisms that determine exposures. The output from the model comprises a set of daily exposures for a sample of individuals from the population of interest. These daily exposures are approximated by parametric distributions, so that the predictive exposure distribution of a randomly selected individual can be generated. These distributions are then incorporated into a hierarchical Bayesian framework (with inference using Markov Chain Monte Carlo simulation) in order to examine the relationship between short-term changes in exposures and health outcomes, whilst making allowance for long-term trends, seasonality, the effect of potential confounders and the possibility of ecological bias. The paper applies this approach to particulate pollution (PM$_{10}$) and respiratory mortality counts for seniors in greater London ($\geq$65 years) during 1997. Within this substantive epidemiological study, the effects on health of ambient concentrations and (estimated) personal exposures are compared.