Spatial health effects analysis with uncertain residential locations.

Statistical Methods in Medical Research
Brian J ReichMatthew J Strickland

Abstract

Spatial epidemiology has benefited greatly from advances in geographic information system technology, which permits extensive study of associations between various health responses and a wide array of socio-economic and environmental factors. However, many spatial epidemiological datasets have missing values for a substantial proportion of spatial variables, such as the census tract of residence of study participants. The standard approach is to discard these observations and analyze only complete observations. In this article, we propose a new hierarchical Bayesian spatial model to handle missing observation locations. Our model utilizes all available information to learn about the missing locations and propagates uncertainty about the missing locations throughout the model. We show via a simulation study that this method can lead to more efficient epidemiological analysis. The method is applied to a study of the relationship between fine particulate matter and birth outcomes is southeast Georgia, where we find smaller posterior variance for most parameters using our missing data model compared to the standard complete case model.

References

Sep 16, 2005·Health & Place·Nataliya Kravets, Wilbur C Hadden
Apr 6, 2007·Environmental Health : a Global Access Science Source·Matthew J StricklandAdolfo Correa
Jan 25, 2008·International Journal of Health Geographics·Kevin A Henry, Francis P Boscoe
Nov 27, 2008·International Journal of Health Geographics·Daniel W GoldbergMyles G Cockburn
Jul 25, 2009·Statistics in Medicine·David LunnNicky Best
Jul 16, 2010·The Annals of Applied Statistics·Brian J Reich, Dipankar Bandyopadhyay

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Citations

Jul 3, 2016·International Journal of Health Geographics·Zhijie ZhangQingwu Jiang
Dec 7, 2018·International Journal of Environmental Research and Public Health·Jeremy MennisKevin Henry
Jul 15, 2015·Substance Use & Misuse·Jennifer Nutton, Elizabeth Fast

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