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Statistical Methods to Study Variation in the Associations between Food Store Availability and Body Mass in the Multi-Ethnic Study of Atherosclerosis

Citation

Baek, Jonggyu; Hirsch, Jana A.; Moore, Kari A. B.; Tabb, Loni Philip; Barrientos-Gutierrez, Tonatiuh; Lisabeth, Lynda D.; Diez-Roux, Ana V.; & Sanchez, Brisa N. (2017). Statistical Methods to Study Variation in the Associations between Food Store Availability and Body Mass in the Multi-Ethnic Study of Atherosclerosis. Epidemiology, 28(3), 403-411. PMCID: PMC5378605

Abstract

Research linking characteristics of the neighborhood environment to health has relied on traditional regression methods where pre-specified distances from participant’s locations or areas are used to operationalize neighborhood-level measures. Since the relevant spatial scale of neighborhood environment measures may differ across places or individuals, using pre-specified distances could result in biased association estimates or efficiency losses. We use novel hierarchical distributed lag models and data from the Multi-ethnic Study of Atherosclerosis (MESA) to: 1) examine whether and how the association between the availability of favorable food stores and body mass index (BMI) depends on continuous distance from participant locations (instead of traditional buffers), thus allowing us to indirectly infer the spatial scale at which this association operates; 2) examine if the spatial scale and magnitude of the association differs across six MESA sites and 3) across individuals. As expected, we found that the association between higher availability of favorable food stores within closer distances from participant’s residential location was stronger than at farther distances, and that the magnitude of the adjusted association declined quickly from zero to two miles. Furthermore, between individual heterogeneity in the scale and magnitude of the association was present; the extent of this heterogeneity was different across the MESA sites. Individual heterogeneity was partially explained by sex. This study illustrated novel methods to examine how neighborhood environmental factors may be differentially associated with health at different scales, providing nuance to previous research that ignored the heterogeneity found across individuals and contexts.

URL

http://dx.doi.org/10.1097/EDE.0000000000000631

Reference Type

Journal Article

Year Published

2017

Journal Title

Epidemiology

Author(s)

Baek, Jonggyu
Hirsch, Jana A.
Moore, Kari A. B.
Tabb, Loni Philip
Barrientos-Gutierrez, Tonatiuh
Lisabeth, Lynda D.
Diez-Roux, Ana V.
Sanchez, Brisa N.

PMCID

PMC5378605