The Association Between Obesity and Urban Food Environments

Department of Community Health Sciences, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, Suite 2301, New Orleans, LA 70112, USA.
Journal of Urban Health (Impact Factor: 1.9). 05/2010; 87(5):771-81. DOI: 10.1007/s11524-010-9460-6
Source: PubMed


Several studies have examined associations between the food retail environment and obesity, though virtually no work has been done in the urban South, where obesity rates are among the highest in the country. This study assessed associations between access to food retail outlets and obesity in New Orleans. Data on individual characteristics and body weight were collected by telephone interviews from a random sample of adults (N = 3,925) living in New Orleans in 2004-2005. The neighborhood of each individual was geo-mapped by creating a 2-km buffer around the center point of the census tract in which they lived. Food retailer counts were created by summing the total number of each food store type and fast food establishment within this 2-km neighborhood. Hierarchical linear models assessed associations between access to food retailers and obesity status. After adjusting for individual characteristics, each additional supermarket in a respondent's neighborhood was associated with a reduced odds for obesity (OR 0.93, 95% CI 0.88-0.99). Fast food restaurant (OR 1.01, 95% CI 1.00-1.02) and convenience store (OR 1.01, 95% CI 1.00-1.02) access were each predictive of greater obesity odds. An individual's access to food stores and fast food restaurants may play a part in determining weight status. Future studies with longitudinal and experimental designs are needed to test whether modifications in the food environment may assist in the prevention of obesity.

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    • "While emerging evidence supports the use of system and environmental change strategies [5, 7, 22], there remains a paucity of research that has fully elucidated the interactions between these structural modifications and individual health behavior change. To achieve meaningful outcomes in community and individual health, interventions often require substantive tailoring to match the needs and the unique social, epidemiological, and ecological characteristics of the target subpopulations [21, 23]. Oka and colleagues (2013), for instance, analyzed a community-based epidemiologic survey using multilevel modeling to better understand area-based variations in obesity [24]. "
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    ABSTRACT: Although US obesity prevention efforts have begun to implement a variety of system and environmental change strategies to address the underlying socioecological barriers to healthy eating, factors which can impede or facilitate community acceptance of such interventions are often poorly understood. This is due, in part, to the paucity of subpopulation health data that are available to help guide local planning and decision-making. We contribute to this gap in practice by examining area-specific health data for a population targeted by federally funded nutrition interventions in Los Angeles County. Using data from a local health assessment that collected information on sociodemographics, self-reported health behaviors, and objectively measured height, weight, and blood pressure for a subset of low-income adults (n = 720), we compared health risks and predictors of healthy eating across at-risk groups using multivariable modeling analyses. Our main findings indicate being a woman and having high self-efficacy in reading Nutrition Facts labels were strong predictors of healthy eating (P < 0.05). These findings suggest that intervening with women may help increase the reach of these nutrition interventions, and that improving self-efficacy in healthy eating through public education and/or by other means can help prime at-risk groups to accept and take advantage of these food environment changes.
    Journal of obesity 03/2014; 2014(2):908391. DOI:10.1155/2014/908391
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    • "This could create difficulty in finding statistically significant differences compared with objective measures. For example, Bodor JN et al. described a high risk of obesity associated with fast food restaurants and convenience stores, but had not considered neighborhood quality and safety variables [36]; 2) Studies where they relate obesity to physical environmental factors usually work with adult population samples [22,36]; 3) The magnitude of the associations found between obesity and environmental characteristics are usually very weak, 1.01 (1.00 – 1.02) for fast food restaurants and obesity in Bodor’s study [36]; and 4) Alternatively, environmental factors could indirectly influence obesity-related behavior through individual and familial variables, which can be very important in children [23]. Whatever the reason is for why environmental factors were not significant in this study is beyond the scope of this research. "
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    ABSTRACT: There is a growing worldwide trend of obesity in children. Identifying the causes and modifiable factors associated with child obesity is important in order to design effective public health strategies.Our objective was to provide empirical evidence of the association that some individual and environmental factors may have with child excess weight. A cross-sectional study was performed using multi-stage probability sampling of 978 Spanish children aged between 8 and 17 years, with objectively measured height and weight, along with other individual, family and neighborhood variables. Crude and adjusted odds ratios were calculated. In 2012, 4 in 10 children were either overweight or obese with a higher prevalence amongst males and in the 8-12 year age group. Child obesity was associated negatively with the socio-economic status of the adult responsible for the child's diet, OR 0.78 (CI95% 0.59-1.00), girls OR 0.75 (CI95% 0.57-0.99), older age of the child (0.41; CI95% 0.31-0.55), daily breakfast (OR 0.59; p = 0.028) and half an hour or more of physical activity every day. No association was found for neighborhood variables relating to perceived neighborhood quality and safety. This study identifies potential modifiable factors such as physical activity, daily breakfast and caregiver education as areas for public health policies. To be successful, an intervention should take into account both individual and family factors when designing prevention strategies to combat the worldwide epidemic of child excess weight.
    BMC Pediatrics 01/2014; 14(1):3. DOI:10.1186/1471-2431-14-3 · 1.93 Impact Factor
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    • "Moreover, the social environment can also affect healthy eating habits. Communities with higher socioeconomic deprivation have fewer opportunities to access healthy food [15,16] or to practice physical activity, either for leisure or for travel by foot or bicycle [17,18]. Thus, obesity-related policies and programs should encourage individual changes as well as changes to the society and the environment in which people live and work [19]. "
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    ABSTRACT: Obesity is a significant global public health problem and the main cause of many chronic diseases in both developed and developing countries. The increase in obesity in different populations worldwide cannot be explained solely by metabolic and genetic factors; environmental and social factors also have a strong association with obesity. Thus, it is believed that the current obesity epidemic is the result of a complex combination of genetic factors and an obesogenic environment .The purpose of this study was to evaluate individual variables and variables within the built and social environment for their potential association with overweight and obesity in an urban Brazilian population. Cross-sectional study was carried out in a sample of 3404 adults living in the urban area of the city. Information from the surveillance system for chronic diseases of Brazilian Ministry of Health was used and individual data was collected by telephone interviews. The database was geocoded using the Brazilian System of Postal Codes for participant residences. An updated, existing list based on the current addresses of supermarkets and hypermarkets in the city was used as an indicator variable of the availability and access to food. Georeferenced information on parks, public squares, places for practicing physical activity and the population density were also used to create data on the built environment. To characterize the social environment, we used the health vulnerability index (HVI) and georeferenced data for homicide locations. The prevalence was 44% for overweight, poisson regression was used to create the final model. The environment variables that independently associated with overweight were the highest population density, very high health vulnerability index and the homicide rate adjusted for individuals variables. The results of the current study illustrate and confirm some important associations between individual and environmental variables and overweight in a representative sample of adults in the Brazilian urban context. The social environment variables relating to the socioeconomic deprivation of the neighborhood and the built environment variables relating to higher walkability were significantly associated with overweight and obesity in Belo Horizonte.
    BMC Public Health 10/2013; 13(1):988. DOI:10.1186/1471-2458-13-988 · 2.26 Impact Factor
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