Literature DB >> 18247121

Comparing Perception-Based and Geographic Information System (GIS)-based characterizations of the local food environment.

Latetia V Moore1, Ana V Diez Roux, Shannon Brines.   

Abstract

Measuring features of the local food environment has been a major challenge in studying the effect of the environment on diet. This study examined associations between alternate ways of characterizing the local food environment by comparing Geographic Information System (GIS)-derived densities of various types of stores to perception-based measures of the availability of healthy foods. Survey questions rating the availability of produce and low-fat products in neighborhoods were aggregated into a healthy food availability score for 5,774 residents of North Carolina, Maryland, and New York. Densities of supermarkets and smaller stores per square mile were computed for 1 mile around each respondent's residence using kernel estimation. The number of different store types in the area was used to measure variety in the food environment. Linear regression was used to examine associations of store densities and variety with reported availability. Respondents living in areas with lower densities of supermarkets rated the selection and availability of produce and low-fat foods 17% lower than those in areas with the highest densities of supermarkets (95% CL, -18.8, -15.1). In areas without supermarkets, low densities of smaller stores and less store variety were associated with worse perceived availability of healthy foods only in North Carolina (8.8% lower availability, 95% CL, -13.8, -3.4 for lowest vs. highest small-store density; 10.5% lower 95% CL, -16.0, -4.7 for least vs. most store variety). In contrast, higher smaller store densities and more variety were associated with worse perceived healthy food availability in Maryland. Perception- and GIS-based characterizations of the environment are associated but are not identical. Combinations of different types of measures may yield more valid measures of the environment.

Mesh:

Year:  2008        PMID: 18247121      PMCID: PMC2430123          DOI: 10.1007/s11524-008-9259-x

Source DB:  PubMed          Journal:  J Urban Health        ISSN: 1099-3460            Impact factor:   3.671


  32 in total

1.  Associations between self-reported and objective physical environmental factors and use of a community rail-trail.

Authors:  P J Troped; R P Saunders; R R Pate; B Reininger; J R Ureda; S J Thompson
Journal:  Prev Med       Date:  2001-02       Impact factor: 4.018

2.  Socioeconomic status differences in recreational physical activity levels and real and perceived access to a supportive physical environment.

Authors:  Billie Giles-Corti; Robert J Donovan
Journal:  Prev Med       Date:  2002-12       Impact factor: 4.018

3.  Environmental measures of physical activity supports: perception versus reality.

Authors:  Karen A Kirtland; Dwayne E Porter; Cheryl L Addy; Matthew J Neet; Joel E Williams; Patricia A Sharpe; Linda J Neff; C Dexter Kimsey; Barbara E Ainsworth
Journal:  Am J Prev Med       Date:  2003-05       Impact factor: 5.043

4.  Improving the nutritional resource environment for healthy living through community-based participatory research.

Authors:  David C Sloane; Allison L Diamant; LaVonna B Lewis; Antronette K Yancey; Gwendolyn Flynn; Lori Miller Nascimento; William J McCarthy; Joyce Jones Guinyard; Michael R Cousineau
Journal:  J Gen Intern Med       Date:  2003-07       Impact factor: 5.128

5.  Correlates of recreational and transportation physical activity among adults in a New England community.

Authors:  Philip J Troped; Ruth P Saunders; Russell R Pate; Belinda Reininger; Cheryl L Addy
Journal:  Prev Med       Date:  2003-10       Impact factor: 4.018

Review 6.  A site-specific literature review of policy and environmental interventions that promote physical activity and nutrition for cardiovascular health: what works?

Authors:  Dyann M Matson-Koffman; J Nell Brownstein; Jennifer A Neiner; Mary L Greaney
Journal:  Am J Health Promot       Date:  2005 Jan-Feb

7.  The accuracy of address coding and the effects of coding errors.

Authors:  Nataliya Kravets; Wilbur C Hadden
Journal:  Health Place       Date:  2005-09-12       Impact factor: 4.078

8.  Filling the gaps: spatial interpolation of residential survey data in the estimation of neighborhood characteristics.

Authors:  Amy H Auchincloss; Ana V Diez Roux; Daniel G Brown; Trivellore E Raghunathan; Christine A Erdmann
Journal:  Epidemiology       Date:  2007-07       Impact factor: 4.822

9.  Fruit and vegetable intake in African Americans income and store characteristics.

Authors:  Shannon N Zenk; Amy J Schulz; Teretha Hollis-Neely; Richard T Campbell; Nellie Holmes; Gloria Watkins; Robin Nwankwo; Angela Odoms-Young
Journal:  Am J Prev Med       Date:  2005-07       Impact factor: 5.043

10.  Neighbourhood differences in diet: the Atherosclerosis Risk in Communities (ARIC) Study.

Authors:  A V Diez-Roux; F J Nieto; L Caulfield; H A Tyroler; R L Watson; M Szklo
Journal:  J Epidemiol Community Health       Date:  1999-01       Impact factor: 3.710

View more
  57 in total

1.  Assessing the psychometric and ecometric properties of neighborhood scales in developing countries: Saúde em Beagá Study, Belo Horizonte, Brazil, 2008-2009.

Authors:  Amélia Augusta de Lima Friche; Ana V Diez-Roux; Cibele Comini César; César Coelho Xavier; Fernando Augusto Proietti; Waleska Teixeira Caiaffa
Journal:  J Urban Health       Date:  2013-04       Impact factor: 3.671

2.  The relationship between diet and perceived and objective access to supermarkets among low-income housing residents.

Authors:  Caitlin E Caspi; Ichiro Kawachi; S V Subramanian; Gary Adamkiewicz; Glorian Sorensen
Journal:  Soc Sci Med       Date:  2012-06-09       Impact factor: 4.634

3.  Measuring availability of healthy foods: agreement between directly measured and self-reported data.

Authors:  Latetia V Moore; Ana V Diez Roux; Manuel Franco
Journal:  Am J Epidemiol       Date:  2012-01-24       Impact factor: 4.897

4.  The contribution of urban foodways to health disparities.

Authors:  Carolyn C Cannuscio; Eve E Weiss; David A Asch
Journal:  J Urban Health       Date:  2010-05       Impact factor: 3.671

5.  Do people really know what food retailers exist in their neighborhood? Examining GIS-based and perceived presence of retail food outlets in an eight-county region of South Carolina.

Authors:  Timothy L Barnes; Bethany A Bell; Darcy A Freedman; Natalie Colabianchi; Angela D Liese
Journal:  Spat Spatiotemporal Epidemiol       Date:  2015-05-09

6.  Perceptions of the food environment are associated with fast-food (not fruit-and-vegetable) consumption: findings from multi-level models.

Authors:  Sean C Lucan; Nandita Mitra
Journal:  Int J Public Health       Date:  2011-07-20       Impact factor: 3.380

7.  Test-retest reliability of a questionnaire measuring perceptions of neighborhood food environment.

Authors:  Xiaoguang Ma; Timothy L Barnes; Darcy A Freedman; Bethany A Bell; Natalie Colabianchi; Angela D Liese
Journal:  Health Place       Date:  2013-02-04       Impact factor: 4.078

8.  Differences in food environment perceptions and spatial attributes of food shopping between residents of low and high food access areas.

Authors:  Inderbir Sohi; Bethany A Bell; Jihong Liu; Sarah E Battersby; Angela D Liese
Journal:  J Nutr Educ Behav       Date:  2014-02-20       Impact factor: 3.045

9.  Food access and perceptions of the community and household food environment as correlates of fruit and vegetable intake among rural seniors.

Authors:  Joseph R Sharkey; Cassandra M Johnson; Wesley R Dean
Journal:  BMC Geriatr       Date:  2010-06-02       Impact factor: 3.921

10.  Spatial patterns of diabetes related health problems for vulnerable populations in Los Angeles.

Authors:  Andrew J Curtis; Wei-An Andy Lee
Journal:  Int J Health Geogr       Date:  2010-08-27       Impact factor: 3.918

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.