Classification bias in commercial business lists for retail food stores in the U.S.

Euna Han, Lisa M. Powell, Shannon N. Zenk, Leah Rimkus, Punam Ohri-Vachaspati, Frank J. Chaloupka

Research output: Contribution to journalArticle

44 Citations (Scopus)

Abstract

Background: Aspects of the food environment such as the availability of different types of food stores have recently emerged as key modifiable factors that may contribute to the increased prevalence of obesity. Given that many of these studies have derived their results based on secondary datasets and the relationship of food stores with individual weight outcomes has been reported to vary by store type, it is important to understand the extent to which often-used secondary data correctly classify food stores. We evaluated the classification bias of food stores in Dun & Bradstreet (D&B) and InfoUSA commercial business lists.Methods: We performed a full census in 274 randomly selected census tracts in the Chicago metropolitan area and collected detailed store attributes inside stores for classification. Store attributes were compared by classification match status and store type. Systematic classification bias by census tract characteristics was assessed in multivariate regression.Results: D&B had a higher classification match rate than InfoUSA for supermarkets and grocery stores, while InfoUSA was higher for convenience stores. Both lists were more likely to correctly classify large supermarkets, grocery stores, and convenience stores with more cash registers and different types of service counters (supermarkets and grocery stores only). The likelihood of a correct classification match for supermarkets and grocery stores did not vary systemically by tract characteristics whereas convenience stores were more likely to be misclassified in predominately Black tracts.Conclusion: Researches can rely on classification of food stores in commercial datasets for supermarkets and grocery stores whereas classifications for convenience and specialty food stores are subject to some systematic bias by neighborhood racial/ethnic composition.

Original languageEnglish
Article number46
JournalInternational Journal of Behavioral Nutrition and Physical Activity
Volume9
DOIs
Publication statusPublished - 2012 Apr 18

Fingerprint

Food
Censuses
Fast Foods
Obesity
Weights and Measures
Research
Datasets

All Science Journal Classification (ASJC) codes

  • Medicine (miscellaneous)
  • Physical Therapy, Sports Therapy and Rehabilitation
  • Nutrition and Dietetics

Cite this

Han, Euna ; Powell, Lisa M. ; Zenk, Shannon N. ; Rimkus, Leah ; Ohri-Vachaspati, Punam ; Chaloupka, Frank J. / Classification bias in commercial business lists for retail food stores in the U.S. In: International Journal of Behavioral Nutrition and Physical Activity. 2012 ; Vol. 9.
@article{896f612cc3ec4ddc95e738f260c2ed96,
title = "Classification bias in commercial business lists for retail food stores in the U.S.",
abstract = "Background: Aspects of the food environment such as the availability of different types of food stores have recently emerged as key modifiable factors that may contribute to the increased prevalence of obesity. Given that many of these studies have derived their results based on secondary datasets and the relationship of food stores with individual weight outcomes has been reported to vary by store type, it is important to understand the extent to which often-used secondary data correctly classify food stores. We evaluated the classification bias of food stores in Dun & Bradstreet (D&B) and InfoUSA commercial business lists.Methods: We performed a full census in 274 randomly selected census tracts in the Chicago metropolitan area and collected detailed store attributes inside stores for classification. Store attributes were compared by classification match status and store type. Systematic classification bias by census tract characteristics was assessed in multivariate regression.Results: D&B had a higher classification match rate than InfoUSA for supermarkets and grocery stores, while InfoUSA was higher for convenience stores. Both lists were more likely to correctly classify large supermarkets, grocery stores, and convenience stores with more cash registers and different types of service counters (supermarkets and grocery stores only). The likelihood of a correct classification match for supermarkets and grocery stores did not vary systemically by tract characteristics whereas convenience stores were more likely to be misclassified in predominately Black tracts.Conclusion: Researches can rely on classification of food stores in commercial datasets for supermarkets and grocery stores whereas classifications for convenience and specialty food stores are subject to some systematic bias by neighborhood racial/ethnic composition.",
author = "Euna Han and Powell, {Lisa M.} and Zenk, {Shannon N.} and Leah Rimkus and Punam Ohri-Vachaspati and Chaloupka, {Frank J.}",
year = "2012",
month = "4",
day = "18",
doi = "10.1186/1479-5868-9-46",
language = "English",
volume = "9",
journal = "International Journal of Behavioral Nutrition and Physical Activity",
issn = "1479-5868",
publisher = "BioMed Central",

}

Classification bias in commercial business lists for retail food stores in the U.S. / Han, Euna; Powell, Lisa M.; Zenk, Shannon N.; Rimkus, Leah; Ohri-Vachaspati, Punam; Chaloupka, Frank J.

In: International Journal of Behavioral Nutrition and Physical Activity, Vol. 9, 46, 18.04.2012.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Classification bias in commercial business lists for retail food stores in the U.S.

AU - Han, Euna

AU - Powell, Lisa M.

AU - Zenk, Shannon N.

AU - Rimkus, Leah

AU - Ohri-Vachaspati, Punam

AU - Chaloupka, Frank J.

PY - 2012/4/18

Y1 - 2012/4/18

N2 - Background: Aspects of the food environment such as the availability of different types of food stores have recently emerged as key modifiable factors that may contribute to the increased prevalence of obesity. Given that many of these studies have derived their results based on secondary datasets and the relationship of food stores with individual weight outcomes has been reported to vary by store type, it is important to understand the extent to which often-used secondary data correctly classify food stores. We evaluated the classification bias of food stores in Dun & Bradstreet (D&B) and InfoUSA commercial business lists.Methods: We performed a full census in 274 randomly selected census tracts in the Chicago metropolitan area and collected detailed store attributes inside stores for classification. Store attributes were compared by classification match status and store type. Systematic classification bias by census tract characteristics was assessed in multivariate regression.Results: D&B had a higher classification match rate than InfoUSA for supermarkets and grocery stores, while InfoUSA was higher for convenience stores. Both lists were more likely to correctly classify large supermarkets, grocery stores, and convenience stores with more cash registers and different types of service counters (supermarkets and grocery stores only). The likelihood of a correct classification match for supermarkets and grocery stores did not vary systemically by tract characteristics whereas convenience stores were more likely to be misclassified in predominately Black tracts.Conclusion: Researches can rely on classification of food stores in commercial datasets for supermarkets and grocery stores whereas classifications for convenience and specialty food stores are subject to some systematic bias by neighborhood racial/ethnic composition.

AB - Background: Aspects of the food environment such as the availability of different types of food stores have recently emerged as key modifiable factors that may contribute to the increased prevalence of obesity. Given that many of these studies have derived their results based on secondary datasets and the relationship of food stores with individual weight outcomes has been reported to vary by store type, it is important to understand the extent to which often-used secondary data correctly classify food stores. We evaluated the classification bias of food stores in Dun & Bradstreet (D&B) and InfoUSA commercial business lists.Methods: We performed a full census in 274 randomly selected census tracts in the Chicago metropolitan area and collected detailed store attributes inside stores for classification. Store attributes were compared by classification match status and store type. Systematic classification bias by census tract characteristics was assessed in multivariate regression.Results: D&B had a higher classification match rate than InfoUSA for supermarkets and grocery stores, while InfoUSA was higher for convenience stores. Both lists were more likely to correctly classify large supermarkets, grocery stores, and convenience stores with more cash registers and different types of service counters (supermarkets and grocery stores only). The likelihood of a correct classification match for supermarkets and grocery stores did not vary systemically by tract characteristics whereas convenience stores were more likely to be misclassified in predominately Black tracts.Conclusion: Researches can rely on classification of food stores in commercial datasets for supermarkets and grocery stores whereas classifications for convenience and specialty food stores are subject to some systematic bias by neighborhood racial/ethnic composition.

UR - http://www.scopus.com/inward/record.url?scp=84862180650&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84862180650&partnerID=8YFLogxK

U2 - 10.1186/1479-5868-9-46

DO - 10.1186/1479-5868-9-46

M3 - Article

VL - 9

JO - International Journal of Behavioral Nutrition and Physical Activity

JF - International Journal of Behavioral Nutrition and Physical Activity

SN - 1479-5868

M1 - 46

ER -