Calorie labeling and consumer estimation of calories purchased

Glen B. Taksler, Brian D. Elbel

Research output: Contribution to journalArticle

Abstract

Background: Studies rarely find fewer calories purchased following calorie labeling implementation. However, few studies consider whether estimates of the number of calories purchased improved following calorie labeling legislation. Findings: Researchers surveyed customers and collected purchase receipts at fast food restaurants in the United States cities of Philadelphia (which implemented calorie labeling policies) and Baltimore (a matched comparison city) in December 2009 (pre-implementation) and June 2010 (post-implementation). A difference-in-difference design was used to examine the difference between estimated and actual calories purchased, and the odds of underestimating calories. Participants in both cities, both pre- and post-calorie labeling, tended to underestimate calories purchased, by an average 216-409 calories. Adjusted difference-in-differences in estimated-actual calories were significant for individuals who ordered small meals and those with some college education (accuracy in Philadelphia improved by 78 and 231 calories, respectively, relative to Baltimore, p = 0.03-0.04). However, categorical accuracy was similar; the adjusted odds ratio [AOR] for underestimation by >100 calories was 0.90 (p = 0.48) in difference-in-difference models. Accuracy was most improved for subjects with a BA or higher education (AOR = 0.25, p < 0.001) and for individuals ordering small meals (AOR = 0.54, p = 0.001). Accuracy worsened for females (AOR = 1.38, p < 0.001) and for individuals ordering large meals (AOR = 1.27, p = 0.028). Conclusions: We concluded that the odds of underestimating calories varied by subgroup, suggesting that at some level, consumers may incorporate labeling information.

Original languageEnglish (US)
Article number91
JournalInternational Journal of Behavioral Nutrition and Physical Activity
Volume11
Issue number1
DOIs
StatePublished - Jul 12 2014

Fingerprint

Odds Ratio
Meals
Baltimore
Fast Foods
Education
Restaurants
Legislation
Research Personnel

Keywords

  • Caloric restriction
  • Diet
  • Energy intake
  • Health policy
  • Obesity

ASJC Scopus subject areas

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

Cite this

Calorie labeling and consumer estimation of calories purchased. / Taksler, Glen B.; Elbel, Brian D.

In: International Journal of Behavioral Nutrition and Physical Activity, Vol. 11, No. 1, 91, 12.07.2014.

Research output: Contribution to journalArticle

@article{8a822e05122247d89fbdfbc919353eae,
title = "Calorie labeling and consumer estimation of calories purchased",
abstract = "Background: Studies rarely find fewer calories purchased following calorie labeling implementation. However, few studies consider whether estimates of the number of calories purchased improved following calorie labeling legislation. Findings: Researchers surveyed customers and collected purchase receipts at fast food restaurants in the United States cities of Philadelphia (which implemented calorie labeling policies) and Baltimore (a matched comparison city) in December 2009 (pre-implementation) and June 2010 (post-implementation). A difference-in-difference design was used to examine the difference between estimated and actual calories purchased, and the odds of underestimating calories. Participants in both cities, both pre- and post-calorie labeling, tended to underestimate calories purchased, by an average 216-409 calories. Adjusted difference-in-differences in estimated-actual calories were significant for individuals who ordered small meals and those with some college education (accuracy in Philadelphia improved by 78 and 231 calories, respectively, relative to Baltimore, p = 0.03-0.04). However, categorical accuracy was similar; the adjusted odds ratio [AOR] for underestimation by >100 calories was 0.90 (p = 0.48) in difference-in-difference models. Accuracy was most improved for subjects with a BA or higher education (AOR = 0.25, p < 0.001) and for individuals ordering small meals (AOR = 0.54, p = 0.001). Accuracy worsened for females (AOR = 1.38, p < 0.001) and for individuals ordering large meals (AOR = 1.27, p = 0.028). Conclusions: We concluded that the odds of underestimating calories varied by subgroup, suggesting that at some level, consumers may incorporate labeling information.",
keywords = "Caloric restriction, Diet, Energy intake, Health policy, Obesity",
author = "Taksler, {Glen B.} and Elbel, {Brian D.}",
year = "2014",
month = "7",
day = "12",
doi = "10.1186/s12966-014-0091-2",
language = "English (US)",
volume = "11",
journal = "International Journal of Behavioral Nutrition and Physical Activity",
issn = "1479-5868",
publisher = "BioMed Central",
number = "1",

}

TY - JOUR

T1 - Calorie labeling and consumer estimation of calories purchased

AU - Taksler, Glen B.

AU - Elbel, Brian D.

PY - 2014/7/12

Y1 - 2014/7/12

N2 - Background: Studies rarely find fewer calories purchased following calorie labeling implementation. However, few studies consider whether estimates of the number of calories purchased improved following calorie labeling legislation. Findings: Researchers surveyed customers and collected purchase receipts at fast food restaurants in the United States cities of Philadelphia (which implemented calorie labeling policies) and Baltimore (a matched comparison city) in December 2009 (pre-implementation) and June 2010 (post-implementation). A difference-in-difference design was used to examine the difference between estimated and actual calories purchased, and the odds of underestimating calories. Participants in both cities, both pre- and post-calorie labeling, tended to underestimate calories purchased, by an average 216-409 calories. Adjusted difference-in-differences in estimated-actual calories were significant for individuals who ordered small meals and those with some college education (accuracy in Philadelphia improved by 78 and 231 calories, respectively, relative to Baltimore, p = 0.03-0.04). However, categorical accuracy was similar; the adjusted odds ratio [AOR] for underestimation by >100 calories was 0.90 (p = 0.48) in difference-in-difference models. Accuracy was most improved for subjects with a BA or higher education (AOR = 0.25, p < 0.001) and for individuals ordering small meals (AOR = 0.54, p = 0.001). Accuracy worsened for females (AOR = 1.38, p < 0.001) and for individuals ordering large meals (AOR = 1.27, p = 0.028). Conclusions: We concluded that the odds of underestimating calories varied by subgroup, suggesting that at some level, consumers may incorporate labeling information.

AB - Background: Studies rarely find fewer calories purchased following calorie labeling implementation. However, few studies consider whether estimates of the number of calories purchased improved following calorie labeling legislation. Findings: Researchers surveyed customers and collected purchase receipts at fast food restaurants in the United States cities of Philadelphia (which implemented calorie labeling policies) and Baltimore (a matched comparison city) in December 2009 (pre-implementation) and June 2010 (post-implementation). A difference-in-difference design was used to examine the difference between estimated and actual calories purchased, and the odds of underestimating calories. Participants in both cities, both pre- and post-calorie labeling, tended to underestimate calories purchased, by an average 216-409 calories. Adjusted difference-in-differences in estimated-actual calories were significant for individuals who ordered small meals and those with some college education (accuracy in Philadelphia improved by 78 and 231 calories, respectively, relative to Baltimore, p = 0.03-0.04). However, categorical accuracy was similar; the adjusted odds ratio [AOR] for underestimation by >100 calories was 0.90 (p = 0.48) in difference-in-difference models. Accuracy was most improved for subjects with a BA or higher education (AOR = 0.25, p < 0.001) and for individuals ordering small meals (AOR = 0.54, p = 0.001). Accuracy worsened for females (AOR = 1.38, p < 0.001) and for individuals ordering large meals (AOR = 1.27, p = 0.028). Conclusions: We concluded that the odds of underestimating calories varied by subgroup, suggesting that at some level, consumers may incorporate labeling information.

KW - Caloric restriction

KW - Diet

KW - Energy intake

KW - Health policy

KW - Obesity

UR - http://www.scopus.com/inward/record.url?scp=84904271095&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84904271095&partnerID=8YFLogxK

U2 - 10.1186/s12966-014-0091-2

DO - 10.1186/s12966-014-0091-2

M3 - Article

C2 - 25015547

AN - SCOPUS:84904271095

VL - 11

JO - International Journal of Behavioral Nutrition and Physical Activity

JF - International Journal of Behavioral Nutrition and Physical Activity

SN - 1479-5868

IS - 1

M1 - 91

ER -