Field validation of listings of food stores and commercial physical activity establishments from secondary data
Open Access
- 10 November 2008
- journal article
- research article
- Published by Springer Science and Business Media LLC in International Journal of Behavioral Nutrition and Physical Activity
- Vol. 5 (1), 58
- https://doi.org/10.1186/1479-5868-5-58
Abstract
Background: Food- and activity-related establishments are increasingly viewed as neighbourhood resources that potentially condition health-related behaviour. The primary objective of the current study was to establish, using ground truthing (on-site verification), the validity of measures of availability of food stores and physical activity establishments that were obtained from commercial database and Internet searches. A secondary objective was to examine differences in validity results according to neighbourhood characteristics and commercial establishment categories. Methods: Lists of food stores and physical activity-related establishments in 12 census tracts within the Montreal metropolitan region were compiled using a commercial database (n = 171 establishments) and Internet search engines (n = 123 establishments). Ground truthing through field observations was performed to assess the presence of listed establishments and identify those absent. Percentage agreement, sensitivity (proportion of establishments found in the field that were listed), and positive predictive value (proportion of listed establishments found in the field) were calculated and contrasted according to data sources, census tracts characteristics, and establishment categories. Results: Agreement with field observations was good (0.73) for the commercial list, and moderate (0.60) for the Internet-based list. The commercial list was superior to the Internet-based list for correctly listing establishments present in the field (sensitivity), but slightly inferior in terms of the likelihood that a listed establishment was present in the field (positive predictive value). Agreement was higher for food stores than for activity-related establishments. Conclusion: Commercial data sources may provide a valid alternative to field observations and could prove a valuable tool in the evaluation of commercial environments relevant to eating behaviour. In contrast, this study did not find strong evidence in support of commercial and Internet data sources to represent neighbourhood opportunities for active lifestyle.This publication has 31 references indexed in Scilit:
- Validation of a GIS Facilities Database: Quantification and Implications of ErrorAnnals of Epidemiology, 2008
- Socioeconomic and food-related physical characteristics of the neighbourhood environment are associated with body mass indexJournal of Epidemiology and Community Health, 2007
- Availability of Recreational Resources and Physical Activity in AdultsAmerican Journal of Public Health, 2007
- Association of the Built Environment With Physical Activity and Obesity in Older PersonsAmerican Journal of Public Health, 2007
- Environment, Obesity, and Cardiovascular Disease Risk in Low-Income WomenAmerican Journal of Preventive Medicine, 2006
- Inequality in the Built Environment Underlies Key Health Disparities in Physical Activity and ObesityPEDIATRICS, 2006
- Objective Measures of Neighborhood Environment and Physical Activity in Older WomenAmerican Journal of Preventive Medicine, 2005
- Fast food, race/ethnicity, and income: A geographic analysisAmerican Journal of Preventive Medicine, 2004
- A Structural Model of Health Behavior: A Pragmatic Approach to Explain and Influence Health Behaviors at the Population LevelPreventive Medicine, 2000
- Social class and preventive health behaviour: a British example.Journal of Epidemiology and Community Health, 1995