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

Abstract #120968

Sanae Inagami, MD, MPH, General Internal Medicine/Health Services Research, West Los Angeles VA/UCLA, Box 111G, 11301 Wilshire Blvd, Los Angeles, CA 90073, 310-478-3711, sinagami@ucla.edu, Deborah A. Cohen, MD, MPH, Health, RAND Corporation, 1700 Main Street, Santa Monica, CA 90405, and Brian K. Finch, PhD, RAND Health, RAND, 1700 Main Street, Santa Monica, CA 90405.

Background:  Residential neighborhood disadvantage has been associated with increased body mass index (BMI) of individuals.   In separate studies residential neighborhood disadvantage has also been associated with grocery stores selling fewer fruits and vegetables, whole grain and low fat products and with individuals eating less healthfully.  We examined whether the location of grocery stores where individuals shop influence their BMI.

Methods:  We linked the 2000 US Census data with the Los Angeles Family and Neighborhood Study (L.A.FANS) database, which consists of 3424 adults sampled from 65 neighborhoods in Los Angeles County. Multilevel linear regressions were used to estimate associations between BMI and socioeconomic characteristics of grocery store locations after adjustment for individual-level factors and socioeconomic characteristics of residential neighborhoods.

Results:  Residence in disadvantaged neighborhoods was associated with increased BMI.  Individuals have higher BMI if they reside in lower SES areas and reside in areas where the average person frequents grocery stores located in more disadvantaged neighborhoods.  Those who own cars and travel further to their grocery stores also have higher BMI. 

Conclusions:   Location of grocery stores and distance traveled to grocery stores are independent predictors of BMI.

Table:  Mean Tract SES difference between Residential and Grocery Store Neighborhoods and Distance Traveled to Grocery Store Predicts BMI

BMI	Total Sample (n=2143)
	Model B		Model C		Model D
	b	P	b	p	b	p
Residential SES:  Very Low	1.52	.0008	2.11	<.0001	2.29	<.0001
Residential SES:  Low	1.17	.0006	1.5	.0007	1.64	.0002
Residential SES: High	.896	.045	1.05	.0173	1.18	.0075
Residential SES: Very High	Reference Category
Disadvantage Score Difference*			.229	.01	.239	.008
Distance:  >1.75 miles					.773	.0162
Distance:  1-1.75 miles					,114	.723
Distance:  0-1 miles					.217	.483
Distance:  0 miles	Reference Category

*Disadvantage Score Difference between Grocery Store Neighborhood SES area and Residential Neighborhood SES Area.

Learning Objectives: At the end of the session the participant will be able to

• Recognize that grocery store quality may not be captured by residential SES measures as most grocery stores where people frequent are not located in the same area as where people reside.
• Articulate how grocery store locations affect BMI through distance measures and SES characteristics of grocery store locations.
• Recognize that even if we don't know where individuals shopped, BMI is predicted by where their neighbors shopped.
• Identify the competing theories that explain objective 3.

Keywords: Obesity, Epidemiology

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.