Article

You are where you shop: Grocery store locations, weight, and neighborhoods

Veterans Affairs Health Services and Research Development, VA Greater Los Angeles Health Care System, Division of General Internal Medicine, Los Angeles, California 90073, USA.
American Journal of Preventive Medicine (Impact Factor: 4.28). 08/2006; 31(1):10-7. DOI: 10.1016/j.amepre.2006.03.019
Source: PubMed

ABSTRACT Residents in poor neighborhoods have higher body mass index (BMI) and eat less healthfully. One possible reason might be the quality of available foods in their area. Location of grocery stores where individuals shop and its association with BMI were examined.
The 2000 U.S. Census data were linked with the Los Angeles Family and Neighborhood Study (L.A.FANS) database, which consists of 2620 adults sampled from 65 neighborhoods in Los Angeles County between 2000 and 2002. In 2005, multilevel linear regressions were used to estimate the associations between BMI and socioeconomic characteristics of grocery store locations after adjustment for individual-level factors and socioeconomic characteristics of residential neighborhoods.
Individuals have higher BMI if they reside in disadvantaged areas and in areas where the average person frequents grocery stores located in more disadvantaged neighborhoods. Those who own cars and travel farther to their grocery stores also have higher BMI. When controlling for grocery store census tract socioeconomic status (SES), the association between residential census tract SES and BMI becomes stronger.
Where people shop for groceries and distance traveled to grocery stores are independently associated with BMI. Exposure to grocery store mediates and suppresses the association of residential neighborhoods with BMI and could explain why previous studies may not have found robust associations between residential neighborhood predictors and BMI.

Download full-text

Full-text

Available from: Brian Karl Finch, Dec 19, 2013
1 Follower
 · 
308 Views
  • Source
    • "At present, the overall annual cost of being obese is $2,646 for an obese man and $4,879 for an obese woman [5]. However, the magnitude of health impacts depends on the levels of obesity-related diseases, socioeconomic and behavioral characteristics of individuals and environmental and geographical characteristics of a particular region [16] [17] [18] [19]. High obesity is linked with more disease and less quality of life [8] [9]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Many research outcomes highlight the use of behavioral changes to combat obesity. This study attempts to examine and discuss the potential use of physical activity and less energy intakes in mitigating obesity among the adults in Appalachia, USA. Within the context of utility theory and behavioral aspect of energy balances of an individual, a system of simultaneous equations with three endogenous variables; decision to reduce energy intakes, time engaged in physical activity and Body Mass Index (BMI) were used for the analysis. The results highlight the potentials of weight control by reducing energy intakes and engaging in more physical activity. Importantly, the results emphasize that elderly individuals are less likely to engage in physical activity and reduce energy intakes to control BMI at the same time. The individuals with high BMI values are more likely to reduce energy intakes than engage in physical activity. The male are more likely to engage in physical activity to control obesity than reducing energy intakes while the female are more likely to reduce energy intakes than engaging in physical activity. Higher income generation, job opportunities, service of health professionals, and availability of recreational facilities play a key role in changing behaviors for controlling obesity. Keywords: Appalachia, obesity, energy intakes, physical activity
    01/2014; 2(4):176-181. DOI:10.12691/ajphr-2-4-8
  • Source
    • "Several scholars have commented in recent years on the need for future research to incorporate food environments encountered outside the neighborhood (Papas et al., 2007; Jeffery et al., 2006; Inagami et al., 2006). Using neighborhoods as the basis for describing the food environment leads to some notable limitations. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Several studies have demonstrated relationships between neighborhood-level retail food environments and obesity, race/ethnicity, and socioeconomic status. Most, however, have been limited by the use of residential neighborhoods to define food environments. This study recruited 121 participants to supply three days of Global Positioning System (GPS) tracking data to explore daily activity spaces and food environments. Participants also answered two surveys regarding personal characteristics, and diet and food purchasing. Several food environment measures were calculated for food locations within a half-mile of their GPS tracks. Non-parametric statistics examined (1) differences between activity- and neighborhood-based food environments, (2) associations between personal characteristics and activity-based food environments, and (3) associations between diet, purchasing, and activity-based food environments. Activity- and neighborhood-based food environments were significantly different. Several associations were observed among activity-based food environment measures and personal characteristics. Dietary intake, food purchasing, and obesity were associated with some activity-based food environment measures.
    12/2012; 3(4):287-295. DOI:10.1016/j.sste.2012.09.001
  • Source
    • "Lack of access to F&V is an important risk factor contributing to inadequate F&V consumption (Larson et al., 2009), especially among low-income individuals who are likely to live in communities with limited numbers of fully stocked grocery stores (Morland et al., 2002, 2006; Morland and Evenson, 2009; Powell et al., 2007). Not only do low-income communities tend to have fewer fully-stocked grocery stores, these stores also tend to carry produce of less variety and lower quality than do grocery stores in more affluent communities (Sloane et al., 2003; Kumar et al.,2011; Inagami et al., 2006; Zenk et al., 2006). Therefore, in order to increase F&V consumption among individuals living in low-income communities, there is a strong need to find evidencebased strategies that increase access to fresh and quality F&V. "
    [Show abstract] [Hide abstract]
    ABSTRACT: The purpose of this longitudinal pilot study was to measure the impact of introducing farm stands in low-income communities with limited access to fresh and quality fruits and vegetables (F&V) on residents' F&V consumption. Two farm stands were placed outside two local community sites one day a week for 12 weeks. A variety of locally grown, culturally appropriate produce was sold at the stands. Data on F&V intake, awareness and usage of farmers' markets, family behaviors, and importance of eating F&V were collected from individuals (n=61) before and after farm stands were placed in the two communities. Paired sample t-tests, chi-square and McNemar tests were used to evaluate the impact of the intervention on the outcome variables. Significance level was set at p<.05. Significant increases were found for participants' consumption of fruit, fruit juice, tomatoes, green salad, and other vegetables (P<.05). Additionally, participants also reported increases in mediating variables of F&V consumption. This study underscores the potential of farmers' markets to increase F&V consumption through increasing F&V access in low-income communities.
    Health & Place 05/2012; 18(5):1137-43. DOI:10.1016/j.healthplace.2012.04.007 · 2.44 Impact Factor
Show more