Dr. Jennifer Bobb (Harvard University)

Title: Beyond the one-exposure, one-outcome paradigm for scientific discovery in environmental epidemiology

Abstract: The most common approach in environmental epidemiology is to hypothesize a relationship between a particular exposure and a particular outcome and then estimate the health risks. In this talk I will present two case studies from my research that move beyond this standard one-exposure, one-outcome paradigm. The first case study considers the problem of estimating the effects of multiple exposures on a single outcome. We propose a new approach for estimating the health effects of multi-pollutant mixtures, Bayesian kernel machine regression, which simultaneously estimates the (potentially high-dimensional) exposure-response function and incorporates variable selection to identify important mixture components. The second case study considers the effects of a single exposure (heat waves) on multiple outcomes (cause-specific hospitalization rates). Rather than pre-specifying a small number of individual diseases, we jointly consider all 15,000 possible discharge diagnosis codes and identify the full spectrum of diseases associated with exposure to heat waves among 23.7 million older adults. Through these case studies, we find that approaches that consider multiple exposures and/or multiple outcomes have the potential to lead to new scientific insights.