Quantifying the foodscape: A systematic review and meta-analysis of the validity of commercially available business data

Alexandre Lebel; Madeleine I G Daepp; Jason P Block; Renée Walker; Benoît Lalonde; Yan Kestens; S V Subramanian

doi:10.1371/journal.pone.0174417

Quantifying the foodscape: A systematic review and meta-analysis of the validity of commercially available business data

PLoS One. 2017 Mar 30;12(3):e0174417. doi: 10.1371/journal.pone.0174417. eCollection 2017.

Authors

Alexandre Lebel^{1

2}, Madeleine I G Daepp³, Jason P Block⁴, Renée Walker⁵, Benoît Lalonde¹, Yan Kestens^{6

7}, S V Subramanian⁸

Affiliations

¹ Evaluation Platform on Obesity Prevention, Quebec Heart and Lung Institute Research Centre, Quebec City (QC), Canada.
² Graduate School of Urban Planning and Land Management, Laval University, Quebec City (QC), Canada.
³ Department of Urban Studies & Planning, Massachusetts Institute of Technology, Cambridge (MA), United States of America.
⁴ Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston (MA), United States of America.
⁵ Zilber School of Public Health, University of Wisconsin, Milwaukee (WI), United States of America.
⁶ Social and Preventive Medicine Department, Université de Montréal, Montréal (QC), Canada.
⁷ Research Centre of Centre hospitalier de l'Université de Montréal, Montréal (QC), Canada.
⁸ Department of Social and Behavioral Sciences, Harvard School of Public Health, Boston (MA), United States of America.

Abstract

This paper reviews studies of the validity of commercially available business (CAB) data on food establishments ("the foodscape"), offering a meta-analysis of characteristics associated with CAB quality and a case study evaluating the performance of commonly-used validity indicators describing the foodscape. Existing validation studies report a broad range in CAB data quality, although most studies conclude that CAB quality is "moderate" to "substantial". We conclude that current studies may underestimate the quality of CAB data. We recommend that future validation studies use density-adjusted and exposure measures to offer a more meaningful characterization of the relationship of data error with spatial exposure.

Publication types

Meta-Analysis
Review
Systematic Review

MeSH terms

Commerce*
Feeding Behavior*
Food Preferences
Food Supply
Residence Characteristics

Grants and funding

This project was supported by the Evaluation Platform on Obesity Prevention and the Foundation of the Quebec Heart and Lung Institute (3207). AL is partially funded by the Quebec’s Funds for Health Research (FQS109600). SVS was partially supported by the Robert Wood Johnson Investigator Award in Health Policy Research. JB was supported by a career development award from the National Institutes of Health (K23HL111211). MD was supported by the Li Tze Fong Fellowship from the University of British Columbia and a National Science Foundation Graduate Research Fellowship.