IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i20p10794-d656329.html
   My bibliography  Save this article

The Federal Menu Labeling Law and Twitter Discussions about Calories in the United States: An Interrupted Time-Series Analysis

Author

Listed:
  • Yulin Hswen

    (Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158, USA
    Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA 94158, USA
    Computational Epidemiology Lab, Harvard Medical School, Boston, MA 02215, USA
    Innovation Program, Boston Children’s Hospital, Boston, MA 02215, USA)

  • Alyssa J. Moran

    (Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MA 21205, USA)

  • Siona Prasad

    (Harvard University, Cambridge, MA 02138, USA)

  • Anna Li

    (Harvard University, Cambridge, MA 02138, USA)

  • Denise Simon

    (Harvard Pilgrim Health Care, Boston, MA 02215, USA)

  • Lauren Cleveland

    (Harvard Pilgrim Health Care, Boston, MA 02215, USA)

  • Jared B. Hawkins

    (Computational Epidemiology Lab, Harvard Medical School, Boston, MA 02215, USA
    Innovation Program, Boston Children’s Hospital, Boston, MA 02215, USA)

  • John S. Brownstein

    (Computational Epidemiology Lab, Harvard Medical School, Boston, MA 02215, USA
    Innovation Program, Boston Children’s Hospital, Boston, MA 02215, USA)

  • Jason Block

    (Harvard Pilgrim Health Care, Boston, MA 02215, USA)

Abstract

Public awareness of calories in food sold in retail establishments is a primary objective of the menu labeling law. This study explores the extent to which we can use social media and internet search queries to understand whether the federal calorie labeling law increased awareness of calories. To evaluate the association of the federal menu labeling law with tweeting about calories we retrieved tweets that contained the term “calorie(s)” from the CompEpi Geo Twitter Database from 1 January through 31 December in 2016 and 2018. Within the same time period, we also retrieved time-series data for search queries related to calories via Google Trends (GT). Interrupted time-series analysis was used to test whether the federal menu labeling law was associated with a change in mentions of “calorie(s)” on Twitter and relative search queries to calories on GT. Before the implementation of the federal calorie labeling law on 7 May 2018, there was a significant decrease in the baseline trend of 4.37 × 10 −8 (SE = 1.25 × 10 −8 , p < 0.001) mean daily ratio of calorie(s) tweets. A significant increase in post-implementation slope of 3.19 × 10 −8 (SE = 1.34 × 10 −8 , p < 0.018) mean daily ratio of calorie(s) tweets was seen compared to the pre-implementation slope. An interrupted time-series (ITS) analysis showed a small, statistically significant upward trend of 0.0043 (SE = 0.036, p < 0.001) weekly search queries for calories pre-implementation, with no significant level change post-implementation. There was a decrease in trend of 1.22 (SE = 0.27, p < 0.001) in search queries for calories post-implementation. The federal calorie labeling law was associated with a 173% relative increase in the trend of mean daily ratio of tweets and a -28381% relative change in trend for search queries for calories. Twitter results demonstrate an increase in awareness of calories because of the addition of menu labels. Google Trends results imply that fewer people are searching for the calorie content of their meal, which may no longer be needed since calorie information is provided at point of purchase. Given our findings, discussions online about calories may provide a signal of an increased awareness in the implementation of calorie labels.

Suggested Citation

  • Yulin Hswen & Alyssa J. Moran & Siona Prasad & Anna Li & Denise Simon & Lauren Cleveland & Jared B. Hawkins & John S. Brownstein & Jason Block, 2021. "The Federal Menu Labeling Law and Twitter Discussions about Calories in the United States: An Interrupted Time-Series Analysis," IJERPH, MDPI, vol. 18(20), pages 1-11, October.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:20:p:10794-:d:656329
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/20/10794/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/20/10794/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Franckle, R.L. & Block, J.P. & Roberto, C.A., 2016. "Calorie underestimation when buying high-calorie beverages in fast-food contexts," American Journal of Public Health, American Public Health Association, vol. 106(7), pages 1254-1255.
    2. Burton, S. & Creyer, E.H. & Kees, J. & Huggins, K., 2006. "Attacking the obesity epidemic: The potential health benefits of providing nutrition information in restaurants," American Journal of Public Health, American Public Health Association, vol. 96(9), pages 1669-1675.
    3. Yu-Xiao Zhu & Junming Huang & Zi-Ke Zhang & Qian-Ming Zhang & Tao Zhou & Yong-Yeol Ahn, 2013. "Geography and Similarity of Regional Cuisines in China," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-8, November.
    4. Eui-Ki Kim & Jong Hyeon Seok & Jang Seok Oh & Hyong Woo Lee & Kyung Hyun Kim, 2013. "Use of Hangeul Twitter to Track and Predict Human Influenza Infection," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-11, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Graham, Hope E. & Vestal, Mallory K. & Guerrero, Bridget L., 2015. ""Go-Slow-Whoa!": Will Nutritional Information Influence Adolescent Food Choices and Lead to a Healthier Generation?," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 206007, Agricultural and Applied Economics Association.
    2. Frans Folkvord & Maud van der Zanden & Sara Pabian, 2020. "Taste and Health Information on Fast Food Menus to Encourage Young Adults to Choose Healthy Food Products: An Experimental Study," IJERPH, MDPI, vol. 17(19), pages 1-13, September.
    3. Andreas C. Drichoutis & Panagiotis Lazaridis & Rodolfo M. Nayga, 2009. "Would consumers value food-away-from-home products with nutritional labels?," Agribusiness, John Wiley & Sons, Ltd., vol. 25(4), pages 550-575.
    4. Shimokawa, Satoru, 2016. "Why can calorie posting be apparently ineffective? The roles of two conflicting learning effects," Food Policy, Elsevier, vol. 64(C), pages 107-120.
    5. John Cawley & Alex Susskind & Barton Willage, 2020. "The Impact of Information Disclosure on Consumer Behavior: Evidence from a Randomized Field Experiment of Calorie Labels on Restaurant Menus," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(4), pages 1020-1042, September.
    6. Ellison, Brenna D. & Lusk, Jayson L. & Davis, David W., 2012. "The Value and Cost of Restaurant Calorie Labels: Results from a Field Experiment," 2012 AAEA/EAAE Food Environment Symposium 123529, Agricultural and Applied Economics Association.
    7. Strupat, Christoph & Farfán, Gabriela & Moritz, Laura & Negre, Mario & Vakis, Renos, 2021. "Obesity and food away from home: What drives the socioeconomic gradient in excess body weight?," Economics & Human Biology, Elsevier, vol. 43(C).
    8. Aner Tal, 2021. "Wanting More, Seeing Less: Hunger Reduces Calorie Evaluations," IJERPH, MDPI, vol. 18(23), pages 1-12, November.
    9. Linda Thunström & Jonas Nordström & Jason F. Shogren & Mariah Ehmke & Klaas Veld, 2016. "Strategic self-ignorance," Journal of Risk and Uncertainty, Springer, vol. 52(2), pages 117-136, April.
    10. Jain, Anupam & Bagler, Ganesh, 2018. "Culinary evolution models for Indian cuisines," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 170-176.
    11. Ping Zhang & Xin Wei & Guirong Mao, 2024. "Cultural diversity, social integration, and migrant entrepreneurship—evidence from the China migrants dynamic survey," Small Business Economics, Springer, vol. 62(3), pages 1135-1155, March.
    12. Jessica E. Todd & Lisa Mancino & Brandon J. Restrepo & Claudine Kavanaugh & Chris Dicken & Vince Breneman, 2021. "Food Away From Home And Caloric Intake: The Role Of Restaurant Menu Labeling Laws," Economic Inquiry, Western Economic Association International, vol. 59(1), pages 53-71, January.
    13. Christine Ye & J. Cronin & John Peloza, 2015. "The Role of Corporate Social Responsibility in Consumer Evaluation of Nutrition Information Disclosure by Retail Restaurants," Journal of Business Ethics, Springer, vol. 130(2), pages 313-326, August.
    14. Shimokawa, Satoru, 2013. "Two Asymmetric and Conflicting Learning Effects of Calorie Posting on Overeating: Laboratory Snack Choice Experiment," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 149687, Agricultural and Applied Economics Association.
    15. Jingmin Ding & Yuewen Sun & Yuan Li & Jing He & Harriet Sinclair & Wenwen Du & Huijun Wang & Puhong Zhang, 2020. "Systematic Review on International Salt Reduction Policy in Restaurants," IJERPH, MDPI, vol. 17(24), pages 1-25, December.
    16. Pierrick Gomez & Carolina O. C. Werle & Olivier Corneille, 2017. "The pitfall of nutrition facts label fluency: easier-to-process nutrition information enhances purchase intentions for unhealthy food products," Marketing Letters, Springer, vol. 28(1), pages 15-27, March.
    17. Ma, Chao & Song, Ze & Sun, Xuhui & Zhao, Guangchuan, 2015. "Will Low-Income Populations Love Spicy Foods More? Accounting for Tastes," MPRA Paper 68415, University Library of Munich, Germany.
    18. Hoefkens, Christine & Veettil, Prakashan Chellattan & Van Huylenbroeck, Guido & Van Camp, John & Verbeke, Wim, 2012. "What nutrition label to use in a catering environment? A discrete choice experiment," Food Policy, Elsevier, vol. 37(6), pages 741-750.
    19. Julie S. Downs & Jessica Wisdom & George Loewenstein, 2015. "Helping Consumers Use Nutrition Information: Effects of Format and Presentation," American Journal of Health Economics, University of Chicago Press, vol. 1(3), pages 326-344, Summer.
    20. Weathers, Danny & Siemens, Jennifer Christie, 2018. "Measures of state self-control and its causes for trackable activities," Journal of Business Research, Elsevier, vol. 93(C), pages 1-11.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:18:y:2021:i:20:p:10794-:d:656329. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.