Back to Annual Meeting Page		American Public Health Association 133rd Annual Meeting & Exposition December 10-14, 2005 Philadelphia, PA

Abstract #114751

John O. Davies-Cole, PhD, MPH¹, Gebreyesus Kidane, PhD, MPH¹, and Garret Lum, MPH². (1) Bureau of Epidemiology and Health Risk Assessment, District of Columbia Department of Health, 825 North Capitol Street, NE, Third Floor, Washington, DC 20002, 202-442-9138, john.davies-cole@dc.gov, (2) Bureau of Epidemiology and Health Risk Assessment, Department of Health, 825 North Capitol St NE, Washington, DC 20002

Introduction: Obesity and related diseases in persons over fifty years are of growing concern to policy makers in the District of Columbia. An assessment of obesity and various risk factors is an important step in designing model programs to improve the health and well being of residents. Objectives: This study was designed to correlate racial disparities in obesity with socioeconomic status in District residents, aged 50 years and older, and use Geographic Information Systems (GIS) to map their distribution. Methods: The data for this study were obtained from the Behavioral Risk Factor Surveillance System (BRFSS) database. The prevalence of obesity was determined using the Body Mass Index (BMI). Statistical analyses were conducted using the SUDAAN and SAS statistical software packages. The distribution of risk factors was mapped using Arcview 3.2 GIS software. Results: The highest prevalence of obesity was found in the poorest parts of the District but concentrated in certain zip codes. Low obesity prevalence was found in specific zip codes even in wards with the highest risks. The risk of obesity at age group 55-64 years was more than double that for age group 25-34 years. Although the lowest rate of obesity was found in the over $50,000 income group, the percentage of Blacks who are obese in this income group was more than twice that of whites. Conclusion: Policy-makers and program planners must be educated so that interventions could be focused in those parts of the District that are in greatest need.

Learning Objectives:

• To understand the use of Geographic information Systems (GIS) in mapping distribution of obesity and its various risk factors
• To identify wards and specific zip codes with the highest prevalence of obesity
• To Identify some risk factors for obesity in the 50 plus age group
• To Illustrate the importance of focusing interventions on areas where the need is greatest

Keywords: Chronic Diseases, Obesity

Presenting author's disclosure statement:

I wish to disclose that I have NO financial interests or other relationship with the manufactures of commercial products, suppliers of commercial services or commercial supporters.