The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Evaluation of a Voluntary Menu-Labeling Program in Full-Service Restaurants
Open accessAbstract
Objectives. We assessed whether labeling restaurant menus with information on the nutrient content of menu items would cause customers to alter their ordering patterns. Methods. Six full-service restaurants in Pierce County, Washington, added nutrition information to their menus, and they provided data on entrée sales for 30 days before and 30 days after the information was added. We assessed the prelabeling versus postlabeling difference in nutrient content of entrées sold, and we surveyed restaurant patrons about whether they noticed the nutrition information and used it in their ordering. Results. The average postlabeling entrée sold contained about 15 fewer calories, 1.5 fewer grams of fat, and 45 fewer milligrams of sodium than did the average entrée sold before labeling. Seventy-one percent of patrons reported noticing the nutrition information; 20.4% reported ordering an entrée lower in calories as a result, and 16.5% reported ordering an entrée lower in fat as a result. Conclusions. The concentration of calorie reduction among 20.4% of patrons means that each calorie-reducing patron ordered about 75 fewer calories than they did before labeling. Thus, providing nutrition information on restaurant menus may encourage a subset of restaurant patrons to significantly alter their food choices.
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“Similarly, a comparison of meals purchased at full-service restaurants in Washington state found that adding caloric and nutrient information to menus was associated with selection of entrees that were lower in calories, fat, and sodium during the next month.118”
From Population Approaches to Improve Diet, Physical Activity, and Smoking Habits: A Scientific Statement From the American Heart Association (2012) · cites this paper as [118]
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Cites
Preventing Childhood Obesity: Health in the Balance
Koplan, J. P., Liverman, C. T., & Kraak, V. A. (2005) · PsycEXTRA Dataset · doi:10.1037/e407782005-001 · Cited by 1,717
The economics of obesity: dietary energy density and energy cost
Drewnowski, A., & Darmon, N. (2005) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/82.1.265s · Cited by 1,011
US Department of Health & Human Services; Public Health Service; Office of Surgeon General (2001) · PsycEXTRA Dataset · doi:10.1037/e301232004-001 · Cited by 1,001
Guthrie, J. F., Lin, B.-H., & Frazao, E. (2002) · Journal of Nutrition Education and Behavior · doi:10.1016/s1499-4046(06)60083-3 · Cited by 973
Burton, S., Creyer, E. H., Kees, J., & Huggins, K. A. (2006) · American Journal of Public Health · doi:10.2105/ajph.2004.054973 · Cited by 408
Purchasing Behavior and Calorie Information at Fast-Food Chains in New York City, 2007
Bassett, M. T., Dumanovsky, T., Huang, C., Silver, L. D., Young, C., Nonas, C., Matte, T. D., Chideya, S., & Frieden, T. R. (2008) · American Journal of Public Health · doi:10.2105/ajph.2008.135020 · Cited by 259
Eating as an automatic behavior.
Cohen, D. A., & Farley, T. A. (2008) · PubMed Central · Cited by 208
THE INFLUENCE OF CALORIC INFORMATION ON CAFETERIA FOOD CHOICES
Dubbert, P. M., Johnson, W. G., Schlundt, D. G., & Montague, N. W. (1984) · Journal of Applied Behavior Analysis · doi:10.1901/jaba.1984.17-85 · Cited by 90
Changing Food Selections in a Public Cafeteria
Cinciripini, P. M. (1984) · Behavior Modification · doi:10.1177/01454455840084004 · Cited by 82
Stereotypical thinking about foods and perceived capacity to promote weight gain
Oakes, M. E. (2005) · Appetite · doi:10.1016/j.appet.2005.03.010 · Cited by 81
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Rummo, P. E., Hafeez, E., Mijanovich, T., Heng, L., Wu, E., Weitzman, B. C., Bragg, M. A., Jones, S., & Elbel, B. D. (2025) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2025.108113
Li, J., Yu, T., & Lin, Y. (2026) · Applied Psychology Health and Well-Being · doi:10.1111/aphw.70160
Bailey, R. L., Park, S. Y., Ichplani, P., & Lee, S. (2026) · Nutrients · doi:10.3390/nu18162620
Maddock, J. E., Hayes, D., John, T. L. S., Rajan, R., & Canyon, D. V. (2012) · Europe PMC (PubMed Central)
Metadata
- Authors
- Pulos, E., & Leng, K.
- Affiliations
- Tacoma Pierce County Health Department (US)
- Venue
- American Journal of Public Health
- Publisher
- American Public Health Association
- Published
- 2010-06
- Volume
- 100
- Issue
- 6
- Pages
- 1035-1039
- ISSN
- 0090-0036 (ISSN-L)
- 1541-0048
- PMC
- PMC2866595
- OpenAlex
- W2167393090
- Cited by
- 204
- References
- 14
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 3 · 2023: 9 · 2022: 8 · 2021: 5 · 2020: 15 · 2019: 14 · 2018: 9 · 2017: 15 · 2016: 17 · 2015: 21 · 2014: 18 · 2013: 30 · 2012: 18
- FWCI
- 20.60
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- American Journal of Public Health (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Consumer Attitudes and Food Labeling
- Health Sciences › Nursing › Nutrition and Dietetics › Nutrition, Health and Food Behavior
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
- Keywords
- menu labeling, nutrition information, full-service restaurants, calorie reduction, food choice, sodium intake, dietary fat intake, restaurant customers
- MeSH terms
- Food Labeling, Food Preferences, Humans, Nutritive Value, Restaurants, Washington, Program Evaluation, Voluntary Programs
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