Skip to main content Accessibility help
×
Home

Assessing the validity of commercial and municipal food environment data sets in Vancouver, Canada

  • Madeleine IG Daepp (a1) and Jennifer Black (a2)

Abstract

Objective

The present study assessed systematic bias and the effects of data set error on the validity of food environment measures in two municipal and two commercial secondary data sets.

Design

Sensitivity, positive predictive value (PPV) and concordance were calculated by comparing two municipal and two commercial secondary data sets with ground-truthed data collected within 800 m buffers surrounding twenty-six schools. Logistic regression examined associations of sensitivity and PPV with commercial density and neighbourhood socio-economic deprivation. Kendall’s τ estimated correlations between density and proximity of food outlets near schools constructed with secondary data sets v. ground-truthed data.

Setting

Vancouver, Canada.

Subjects

Food retailers located within 800 m of twenty-six schools

Results

All data sets scored relatively poorly across validity measures, although, overall, municipal data sets had higher levels of validity than did commercial data sets. Food outlets were more likely to be missing from municipal health inspections lists and commercial data sets in neighbourhoods with higher commercial density. Still, both proximity and density measures constructed from all secondary data sets were highly correlated (Kendall’s τ>0·70) with measures constructed from ground-truthed data.

Conclusions

Despite relatively low levels of validity in all secondary data sets examined, food environment measures constructed from secondary data sets remained highly correlated with ground-truthed data. Findings suggest that secondary data sets can be used to measure the food environment, although estimates should be treated with caution in areas with high commercial density.

  • View HTML
    • Send article to Kindle

      To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

      Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      Assessing the validity of commercial and municipal food environment data sets in Vancouver, Canada
      Available formats
      ×

      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

      Assessing the validity of commercial and municipal food environment data sets in Vancouver, Canada
      Available formats
      ×

      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

      Assessing the validity of commercial and municipal food environment data sets in Vancouver, Canada
      Available formats
      ×

Copyright

Corresponding author

*Corresponding author: Email mdaepp@mit.edu

References

Hide All
1. Patterson, C, Guariguata, L, Dahlquist, G et al. (2014) Diabetes in the young – a global view and worldwide estimates of numbers of children with type 1 diabetes. Diabetes Res Clin Pract 103, 161175.
2. Ng, M, Fleming, T, Robinson, M et al. (2014) Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 384, 766781.
3. Caspi, CE, Sorensen, G, Subramanian, SV et al. (2012) The local food environment and diet: a systematic review. Health Place 18, 11721187.
4. Ver Ploeg, M, Breneman, V, Farrigan, K et al. (2009) Access to Affordable and Nutritious Food – Measuring and Understanding Food Deserts and Their Consequences: Report to Congress. Administrative Publication no. AP-036. Washington, DC: US Department of Agriculture, Economic Research Service; available at https://www.ers.usda.gov/publications/pub-details/?pubid=42729
5. Fluornoy, R (2010) Health food, healthy communities: promising strategies to improve access to fresh, healthy food and transform communities. http://www.ca-ilg.org/sites/main/files/file-attachments/resources__hfhc_short_final.pdf (accessed May 2017).
6. Zenk, SN, Thatcher, E, Reina, M et al. (2015) Local food environments and diet-related health outcomes: a systematic review of local food environments, body weight, and other diet-related health outcomes. In Local Food Environments: Food Access in America, pp. 191192 [KB Morland, editor]. Boca Raton, FL: CRC Press.
7. Mair, JS, Pierce, MW & Teret, SP (2005) The Use of Zoning to Restrict Fast Food Outlets: A Potential Strategy to Combat Obesity, pp. 51–53. Baltimore, MD: The Center for Law and the Public’s Health, Johns Hopkins & Georgetown Universities; available at http://www.publichealthlaw.net/Zoning%20Fast%20Food%20Outlets.pdf
8. Glanz, K, Sallis, JF, Saelens, BE et al. (2005) Healthy nutrition environments: concepts and measures. Am J Health Promot 19, 330333.
9. Sturm, R & Cohen, DA (2009) Zoning for health? The year-old ban on new fast-food restaurants in South LA. Health Aff (Millwood) 28, w1088w1097.
10. Héroux, M, Iannotti, RJ, Currie, D et al. (2012) The food retail environment in school neighborhoods and its relation to lunchtime eating behaviors in youth from three countries. Health Place 18, 12401247.
11. Moore, LV & Diez-Roux, AV (2015) Measurement and analytical issues involved in the estimation of the effects of local food environments on health behaviors and health outcomes. In Local Food Environments: Food Access in America, pp. 205226 [KB Morland, editor]. Boca Raton, FL: CRC Press.
12. Fleischhacker, SE, Evenson, KR, Sharkey, J et al. (2013) Validity of secondary retail food outlet data: a systematic review. Am J Prev Med 45, 462473.
13. Lucan, SC (2015) Concerning limitations of food-environment research: a narrative review and commentary framed around obesity and diet-related diseases in youth. J Acad Nutr Diet 2, 205212.
14. DMTI Spatial, Inc. (2003) Enhanced Point of Interest Layers [2003]. http://hdl.handle.net.ezproxy.library.ubc.ca/11272/NBRIL (accessed June 2016).
15. DMTI Spatial, Inc. (2006) Enhanced Point of Interest Layers [2006]. http://hdl.handle.net.ezproxy.library.ubc.ca/11272/KDY86 (accessed June 2016).
16. DMTI Spatial, Inc. (2009) Enhanced Point of Interest Layers [v.2009.3] http://hdl.handle.net.ezproxy.library.ubc.ca/11272/JGQ3B (accessed June 2016).
17. Seliske, LM, Pickett, W, Boyce, WF et al. (2009) Density and type of food retailers surrounding Canadian schools: variations across socioeconomic status. Health Place 15, 903907.
18. Seliske, LM, Pickett, W, Boyce, WF et al. (2009) Association between the food retail environment surrounding schools and overweight in Canadian youth. Public Health Nutr 12, 13841391.
19. Laxer, RE & Janssen, I (2013) The proportion of excessive fast-food consumption attributable to the neighbourhood food environment among youth living within 1 km of their school. Appl Physiol Nutr Metab 39, 480486.
20. Hosler, AS & Dharssi, A (2010) Identifying retail food stores to evaluate the food environment. Am J Prev Med 39, 4144.
21. Toft, U, Erbs-Maibing, P & Glümer, C (2011) Identifying fast-food restaurants using a central register as a measure of the food environment. Scand J Public Health 39, 864869.
22. Paquet, C, Daniel, M, Kestens, Y et al. (2008) Field validation of listings of food stores and commercial physical activity establishments from secondary data. Int J Behav Nutr Phys Act 5, 58.
23. Cummins, S & Macintyre, S (2009) Are secondary data sources on the neighbourhood food environment accurate? Case-study in Glasgow, UK. Prev Med 49, 527528.
24. Bader, MDM, Ailshire, JA, Morenoff, JD et al. (2010) Measurement of the local food environment: a comparison of existing data sources. Am J Epidemiol 171, 609617.
25. Lake, AA, Burgoine, T, Stamp, E et al. (2012) The foodscape: classification and field validation of secondary data sources across urban/rural and socio-economic classifications in England. Int J Behav Nutr Phys Act 9, 37.
26. Rossen, LM, Pollack, KM & Curriero, FC (2012) Verification of retail food outlet location data from a local health department using ground-truthing and remote-sensing technology: assessing differences by neighborhood characteristics. Health Place 18, 956962.
27. Burgoine, T & Harrison, F (2013) Comparing the accuracy of two secondary food environment data sources in the UK across socio-economic and urban/rural divides. Int J Health Geogr 12, 2.
28. Clary, CM & Kestens, Y (2013) Field validation of secondary data sources: a novel measure of representativity applied to a Canadian food outlet database. Int J Behav Nutr Phys Act 10, 77.
29. Rummo, PE, Gordon-Larsen, P & Albrecht, SS (2015) Field validation of food outlet databases: the Latino food environment in North Carolina, USA. Public Health Nutr 18, 977982.
30. Longacre, MR, Primack, BA, Owens, PM et al. (2011) Public directory data sources do not accurately characterize the food environment in two predominantly rural states. J Am Diet Assoc 111, 577582.
31. Liese, AD, Colabianchi, N, Lamichhane, AP et al. (2010) Validation of 3 food outlet databases: completeness and geospatial accuracy in rural and urban food environments. Am J Epidemiol 172, 13241333.
32. Powell, LM, Han, E, Zenk, SN et al. (2011) Field validation of secondary commercial data sources on the retail food outlet environment in the US. Health Place 17, 11221131.
33. Seliske, L, Pickett, W, Bates, R et al. (2012) Field validation of food service listings: a comparison of commercial and online geographic information system databases. Int J Environ Res Public Health 9, 26012607.
34. City of Vancouver (2013) What feeds us: Vancouver Food Strategy. http://vancouver.ca/files/cov/vancouver-food-strategy-final.PDF (accessed February 2017).
35. Statistics Canada (2016) Population and Dwelling Count Highlight Tables, 2011 Census. http://www12.statcan.gc.ca/census-recensement/2011/dp-pd/hlt-fst/pd-pl/Table-Tableau.cfm (accessed June 2016).
36. City of Vancouver (2015) Business Licences. http://data.vancouver.ca/datacatalogue/businessLicence.htm (accessed October 2015).
37. Vancouver Coastal Health (2015) Inspection Reports. http://www.vch.ca/your- environment/facility- licensing/residential- care/inspection- reports/ (accessed October 2015).
38. Pitney Bowes Software (2012) Canada Business Data. Troy, NY: Pitney Bowes Software Inc.
39. DMTI Spatial, Inc. (2013) EPOI v2013.3. http://hdl.handle.net.ezproxy.library.ubc.ca/ (accessed May 2015).
40. Ahmadi, N, Black, JL, Velazquez, CE et al. (2015) Associations between socio-economic status and school-day dietary intake in a sample of grade 5–8 students in Vancouver, Canada. Public Health Nutr 18, 764773.
41. Velazquez, CE, Black, JL, Billette, JMM et al. (2015) A comparison of dietary practices at or en route to school between elementary and secondary school students in Vancouver, Canada. J Acad Nutr Diet 115, 13081317.
42. Fleischhacker, SE, Rodriguez, DA, Evenson, KR et al. (2012) Evidence for validity of five secondary data sources for enumerating retail food outlets in seven American Indian communities in North Carolina. Int J Behav Nutr Phys Act 9, 137.
43. Williams, J, Scarborough, P, Matthews, A et al. (2014) A systematic review of the influence of the retail food environment around schools on obesity-related outcomes. Obes Rev 15, 359374.
44. US Census Bureau (2016) North American Industry Classification System: Introduction to NAICS. http://www.census.gov/eos/www/naics/ (accessed June 2016).
45. Bell, N, Schuurman, N, Oliver, L et al. (2007) Towards the construction of place-specific measures of deprivation: a case study from the Vancouver metropolitan area. Can Geogr 51, 444461.
46. Bell, N & Hayes, MV (2012) The Vancouver Area Neighbourhood Deprivation Index (VANDIX): a census-based tool for assessing small-area variations in health status. Can J Public Health 103, 8 Suppl. 2, S28S32.
47. Census Dictionary (2011) Dissemination Area (DA). https://www12.statcan.gc.ca/census-recensement/2011/ref/dict/geo021-eng.cfm (accessed December 2016).
48. British Columbia Ministry of Education (2016) BC Schools – School Locations. https://catalogue.data.gov.bc.ca/dataset/bc-schools-school-locations (accessed June 2016).
49. Lucan, SC, Maroko, AR, Bumol, J et al. (2013) Business list vs ground observation for measuring a food environment: saving time or waste of time (or worse)? J Acad Nutr Diet 113, 13321339.
50. DMTI Spatial, Inc. (2013) CanMap Streetfiles, v2013.3. http://hdl.handle.net.ezproxy.library.ubc.ca/ (accessed May 2015).
51. Oliver, LN, Schuurman, N & Hall, AW (2007) Comparing circular and network buffers to examine the influence of land use on walking for leisure and errands. Int J Health Geogr 6, 41.
52. Environmental Systems Research Institute, Inc. (2015) ArcGIS Desktop: Release 10.3.1. Redlands. CA: ESRI.
53. Han, E, Powell, LM, Zenk, SN et al. (2012) Classification bias in commercial business lists for retail food stores in the US. Int J Behav Nutr Phys Act 9, 46.
54. R Core Team (2016) R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing; available at https://www.R-project.org
55. Auchincloss, AH, Moore, KAB, Moore, LV et al. (2012) Improving retrospective characterization of the food environment for a large region in the United States during a historic time period. Health Place 18, 13411347.
56. Hoehner, CM & Schootman, M (2010) Concordance of commercial data sources for neighborhood-effects studies. J Urban Health 87, 713725.
57. Winkler, WE (1990) String comparator metrics and enhanced decision rules in the Fellegi–Sunter model of record linkage. In Proceedings of the Section on Survey Research Methods, pp. S354–S369. Alexandria, VA: American Statistical Association.
58. Sariyar, M & Borg, A (2010) The RecordLinkage package: detecting errors in data. R J 2, 6167.
59. Newson, R (2002) Parameters behind ‘nonparametric’ statistics: Kendall’s tau, Somers’ D and median differences. STATA J 2, 454464.
60. Signorell, A (2016) DescTools: Tools for Descriptive Statistics. https://cran.r-project.org/web/packages/DescTools/index.html (accessed September 2016).
61. McHugh, ML (2012) Interrater reliability: the kappa statistic. Biochem Med 22, 276282.
62. Lake, AA, Burgoine, T, Greenhalgh, F et al. (2010) The foodscape: classification and field validation of secondary data sources. Health Place 16, 666673.
63. Ma, X, Battersby, SE, Bell, BA et al. (2013) Variation in low food access areas due to data source inaccuracies. Appl Geogr 45, 131137.
64. Lebel, A, Daepp, MIG, Block, JP et al. (2017) Quantifying the foodscape: a systematic review and meta-analysis of the validity of commercially available business data. PLoS ONE 12, e0174417.
65. Jones, KK, Zenk, SN, Tarlov, E et al. (2017) A step-by-step approach to improve data quality when using commercial business lists to characterize retail food environments. BMC Res Notes 10, 35.

Keywords

Related content

Powered by UNSILO
Type Description Title
PDF
Supplementary materials

Daepp and Black supplementary material S1
Daepp and Black supplementary material

 PDF (19.9 MB)
19.9 MB
PDF
Supplementary materials

Daepp and Black supplementary material S2
Daepp and Black supplementary material

 PDF (64 KB)
64 KB

Assessing the validity of commercial and municipal food environment data sets in Vancouver, Canada

  • Madeleine IG Daepp (a1) and Jennifer Black (a2)

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed.