A common spatial factor analysis model for measured neighborhood-level characteristics: The Multi-Ethnic Study of Atherosclerosis. (November 2015)

• Record Type: Journal Article
• Authors: Nethery, Rachel C.; Warren, Joshua L.; Herring, Amy H.; Moore, Kari A.B.; Evenson, Kelly R.; Diez-Roux, Ana V.
• Is Part Of: Health & place. Volume 36(2015:Nov.)
• Page Start: 35
• Page End: 46
• Publication Date: 2015-11
• Subjects: Bayesian analysis -- Factor analysis -- Spatial statistics -- Body mass index; Health -- Social aspects -- Periodicals; Health services accessibility -- Periodicals; Public health -- Periodicals; Political planning -- Periodicals; Social medicine -- Periodicals; Epidemiology -- Periodicals; Health Policy -- Periodicals; Health Services Accessibility -- Periodicals; Public Health -- Periodicals; Public Policy -- Periodicals; Sociology, Medical -- Periodicals; Épidémiologie -- Périodiques; Politique sanitaire -- Périodiques; Santé, Services de -- Accessibilité -- Périodiques; Health services accessibility; Health -- Social aspects; Political planning; Public health; Social medicine; Periodicals; 613
• DOI: 10.1016/j.healthplace.2015.08.009
• Languages: English
• ISSNs: 1353-8292

Abstract

Abstract: The purpose of this study was to reduce the dimensionality of a set of neighborhood-level variables collected on participants in the Multi-Ethnic Study of Atherosclerosis (MESA) while appropriately accounting for the spatial structure of the data. A common spatial factor analysis model in the Bayesian setting was utilized in order to properly characterize dependencies in the data. Results suggest that use of the spatial factor model can result in more precise estimation of factor scores, improved insight into the spatial patterns in the data, and the ability to more accurately assess associations between the neighborhood environment and health outcomes.