142nd APHA Annual Meeting and Exposition

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Association between BMI and Elevation of Residence: A Multilevel Study Using NHANES Participants

142nd APHA Annual Meeting and Exposition (November 15 - November 19, 2014): http://www.apha.org/events-and-meetings/annual
Monday, November 17, 2014

Chi Li, MS, MA , School of Public Health, LSUHSC-New Orleans, New Orleans, LA
Richard Scribner, MD, MPH , Epidemiology, LSU School of Public Health, New Orleans, LA
Claudia Leonardi, Ph.D. , Biostatistics Program, Louisiana State University Health Sciences Center, School of Public Health, New Orleans, LA
Neal Simonsen, PhD, MS , Consultant, New Orleans, LA
Background: The literature has shown that leptin concentrations tend to rise at high altitudes. However, few studies have examined the association between obesity and elevation of residence, especially at small geographical scales. The purpose of this study was to determine whether elevation of residence is associated with BMI at the census tract level.

Methods: Multilevel analyses of Continuous NHANES 2003-2006 participants (n=4,190) nested in the census tract of residence were conducted. BMI was derived from the directly measured individual height and weight in NHANES. Elevation data was obtained from the 2009 National Elevation Database (NED) and used to calculate tract-level mean elevation by using ArcGIS 10.2 zonal statistics. Additional individual level characteristics potentially associated with BMI (i.e., age, race/ethnicity, gender, household income, marital status, education, smoking status, and nativity) were also included in our models.

Results: ANOVA analysis of BMI in individual level models found that a significant amount of the variance in BMI was explained by residence location. Multilevel analyses indicated a strong effect for tract-level elevation and BMI, as well. This effect persisted after controlling for individual demographic and socioeconomic characteristics.

Conclusion: Elevation of residence was found to be inversely associated with BMI of participants in the continuous NHANES by both individual and multilevel models. Future analyses should consider the duration of individual residence.

Learning Areas:

Public health or related research
Social and behavioral sciences

Learning Objectives:
Demonstrate an application of multilevel analysis and GIS methods to explore obesity disparity. Describe the association between elevation of residence and obesity at a small geographical level

Keyword(s): Obesity, Epidemiology

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have been involved in multiple projects focusing on using social and environmental determinants to solve public health related issues. My background in Geography, GIS, and Environmental Sciences make me a qualified author for these interdisciplinary field.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.