Date(s) - Apr 23, 2021
12:00 pm - 1:00 pm


NIA Aging Centers’ Collaborative Virtual Methods Workshop Series

The workshop series is co-sponsored by: 
– Center for Aging and Policy Studies, Syracuse/Cornell/U-Albany
– Center for Advancing Sociodemographic and Economic Study of Alzheimer’s Disease, USC/Stanford/UT Austin
– Center on Aging & Population Sciences, UT Austin
– Center for the Demography of Health and Aging, UW-Madison.

This particular workshop is organized by:
Center for Aging and Policy Studies, Syracuse/Cornell/U-Albany

Workshop Title: Estimating neighborhood deprivation indices with Bayesian regression models

Speaker: David Wheeler

Workshop Description: For some health outcomes, we are interested in estimating the effect of simultaneous exposure to many factors. Some examples of multidimensional exposures include using many socioeconomic variables measured in an area to represent neighborhood deprivation and using many chemical concentrations measured in the home as a chemical mixture. Using many exposures as opposed to only one yields a more comprehensive assessment of environmental risk, however, including many exposures that happen to be correlated in traditional regression models leads to collinearity issues and interpretation problems. One solution is to build an index of the correlated variables and estimate the effect of exposure to all variables together. Some tradition approaches to constructing an index include summing z-scores, principal component analysis (PCA), and factor analysis. However, there are issues with these approaches that lead to suboptimal estimation of exposure effects in health assessment studies. This talk will introduce the use of Bayesian index regression models for estimating neighborhood deprivation indices and their association with a health outcome that overcomes the issues with existing approaches. For demonstrating the application of the Bayesian index model approach, there will be numerous examples of estimating neighborhood deprivation indices for rates of childhood elevated blood lead levels.

Bio: Dr. Wheeler is an Associate Professor in the Department of Biostatistics in the School of Medicine at Virginia Commonwealth University (VCU). Dr. Wheeler holds a BA in Geography from Syracuse University, an MS in Statistics, an MA and PhD in Geography from The Ohio State University, and an MPH from the Harvard University School of Public Health. Before arriving at VCU, Dr. Wheeler was a Cancer Prevention Fellow in the Division of Cancer Epidemiology and Genetics at the National Cancer Institute. Dr. Wheeler conducts research in spatial, environmental, and cancer epidemiology with a focus on the analysis of correlated environmental exposures and modeling spatial patterns in disease risk. He currently is the principal investigator of an R01 and an R21 from the National Cancer Institute studying environmental risk factors for smoke exposure and cancer. Dr. Wheeler also teaches graduate courses on spatial data analysis and using geographic information systems in Public Health at VCU.

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