Evidence map›Paper›PMID 38100109›Full record

ArticleJAMA network open2023

Menu Labeling and Calories Purchased in Restaurants in a US National Fast Food Chain.

Pasquale E Rummo, Tod Mijanovich, Erilia Wu, Lloyd Heng, Emil Hafeez, Marie A Bragg, Simon A Jones, Beth C Weitzman, Brian Elbel

Abstract read
In one paragraph

Article in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Trial
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Pasquale E RummoDepartment of Population Health, New York University Grossman School of Medicine, New York.
Tod MijanovichSteinhardt School of Culture, Education, and Human Development, New York University, New York.
Erilia WuDepartment of Population Health, New York University Grossman School of Medicine, New York.
Lloyd HengDepartment of Population Health, New York University Grossman School of Medicine, New York.
Emil HafeezDepartment of Population Health, New York University Grossman School of Medicine, New York.
Marie A BraggDepartment of Population Health, New York University Grossman School of Medicine, New York.
Simon A JonesDepartment of Population Health, New York University Grossman School of Medicine, New York.
Beth C WeitzmanWagner Graduate School of Public Service, New York University, New York.
Brian ElbelDepartment of Population Health, New York University Grossman School of Medicine, New York.

Funding

New York Regional Center for Diabetes Translation Research - Translational Intervention Methodology CoreP30DK111022 · NIDDK · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI JEFFREY GONZALEZ · 2016 to 2026
$7.8M
Using National Sales Data to Understand the Influence of Menu Labeling PolicyR01HL147474 · NHLBI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ELBEL, BRIAN · 2019 to 2022
$3.3M
Examining the Mechanisms Underlying the Influence of Facebook Food Advertisements on Adolescents' Eating Behaviors: Randomized Controlled TrialsR01CA248441 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI BRAGG, MARIE · 2021 to 2025
$2.5M
NCI NIH HHS R01 CA248441NHLBI NIH HHS R01 HL147474NIDDK NIH HHS P30 DK111022
6 · The paper itself

Abstract

Importance: Menu labeling has been implemented in restaurants in some US jurisdictions as early as 2008, but the extent to which menu labeling is associated with calories purchased is unclear. Objective: To estimate the association of menu labeling with calories and nutrients purchased and assess geographic variation in results. Design, Setting, and Participants: A cohort study was conducted with a quasi-experimental design using actual transaction data from Taco Bell restaurants from calendar years 2007 to 2014 US restaurants with menu labeling matched to comparison restaurants using synthetic control methods. Data were analyzed from May to October 2023. Exposure: Menu labeling policies in 6 US jurisdictions. Main Outcomes and Measures: The primary outcome was calories per transaction. Secondary outcomes included total and saturated fat, carbohydrates, protein, sugar, fiber, and sodium. Results: The final sample included 2329 restaurants, with menu labeling in 474 (31 468 restaurant-month observations). Most restaurants (94.3%) were located in California. Difference-in-differences model results indicated that customers purchased 24.7 (95% CI, 23.6-25.7) fewer calories per transaction from restaurants in the menu labeling group in the 3- to 24-month follow-up period vs the comparison group, including 21.9 (95% CI, 20.9-22.9) fewer calories in the 3- to 12-month follow-up period and 25.0 (95% CI, 24.0-26.1) fewer calories in the 13- to 24-month follow-up period. Changes in the nutrient content of transactions were consistent with calorie estimates. Findings in California were similar to overall estimates in magnitude and direction; yet, among restaurants outside of California, no association was observed in the 3- to 24-month period. The outcome of menu labeling also differed by item category and time of day, with a larger decrease in the number of tacos vs other items purchased and a larger decrease in calories purchased during breakfast vs other times of the day in the 3- to 24-month period. Conclusions and Relevance: In this quasi-experimental cohort study, fewer calories were purchased in restaurants with calorie labels compared with those with no labels, suggesting that consumers are sensitive to calorie information on menu boards, although associations differed by location.

Indexed as

Fast FoodsRestaurantsCohort StudiesEnergy IntakeHumansPolicy

Identifiers

PMID38100109
PMCPMC10724762

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.