Evidence map›Paper›PMID 29249555›Full record

ArticleAmerican journal of preventive medicine2018

Simulating the Impact of Sugar-Sweetened Beverage Warning Labels in Three Cities.

Bruce Y Lee, Marie C Ferguson, Daniel L Hertenstein, Atif Adam, Eli Zenkov, Peggy I Wang, Michelle S Wong, Joel Gittelsohn, Yeeli Mui, Shawn T Brown

Abstract read
In one paragraph

Article in American journal of preventive medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 5 pooled it
–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

34 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
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  4. Complex Systems Approaches to Diet: A Systematic Review.American journal of preventive medicine · 2019
    Pooled it
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  11. Simulated retail food environments: A literature review of systems science approaches to advance equity in access to healthy diets.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2025
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Bruce Y LeeGlobal Obesity Prevention Center (GOPC), Johns Hopkins University, Baltimore, Maryland; Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland. Electronic address: brucelee@jhu.edu.
Marie C FergusonGlobal Obesity Prevention Center (GOPC), Johns Hopkins University, Baltimore, Maryland; Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Daniel L HertensteinGlobal Obesity Prevention Center (GOPC), Johns Hopkins University, Baltimore, Maryland; Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Atif AdamGlobal Obesity Prevention Center (GOPC), Johns Hopkins University, Baltimore, Maryland; Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Eli ZenkovGlobal Obesity Prevention Center (GOPC), Johns Hopkins University, Baltimore, Maryland; Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, Pennsylvania.
Peggy I WangGlobal Obesity Prevention Center (GOPC), Johns Hopkins University, Baltimore, Maryland; Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Michelle S WongGlobal Obesity Prevention Center (GOPC), Johns Hopkins University, Baltimore, Maryland; Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Joel GittelsohnGlobal Obesity Prevention Center (GOPC), Johns Hopkins University, Baltimore, Maryland; Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Yeeli MuiDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Shawn T BrownGlobal Obesity Prevention Center (GOPC), Johns Hopkins University, Baltimore, Maryland; Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, Pennsylvania.

Funding

MULTILEVEL SYSTEMS-ORIENTED CHILDHOOD OBESITY STUDY IN CHINAU54HD070725 · NICHD · JOHNS HOPKINS UNIVERSITY · PI WANG, YOUFA · 2011 to 2016
$15.9M
Virtual Population Obesity Prevention (VPOP) Labs: Computational, Multi-Scale Models for Obesity SolutionsU01HD086861 · NICHD · JOHNS HOPKINS UNIVERSITY · PI LEE, BRUCE Y · 2015 to 2019
$2.8M
Regional Healthcare Ecosystem Analyst for Healthcare Associated InfectionsR01HS023317 · AHRQ · JOHNS HOPKINS UNIVERSITY · PI LEE, BRUCE Y · 2014 to 2014
$2.4M
AHRQ HHS R01 HS023317NICHD NIH HHS U01 HD086861NICHD NIH HHS U54 HD070725
6 · The paper itself

Abstract

introductionA number of locations have been considering sugar-sweetened beverage point-of-purchase warning label policies to help address rising adolescent overweight and obesity prevalence.

methodsTo explore the impact of such policies, in 2016 detailed agent-based models of Baltimore, Philadelphia, and San Francisco were developed, representing their populations, school locations, and food sources, using data from various sources collected between 2005 and 2014. The model simulated, over a 7-year period, the mean change in BMI and obesity prevalence in each of the cities from sugar-sweetened beverage warning label policies.

resultsData analysis conducted between 2016 and 2017 found that implementing sugar-sweetened beverage warning labels at all sugar-sweetened beverage retailers lowered obesity prevalence among adolescents in all three cities. Point-of-purchase labels with 8% efficacy (i.e., labels reducing probability of sugar-sweetened beverage consumption by 8%) resulted in the following percentage changes in obesity prevalence: Baltimore: -1.69% (95% CI= -2.75%, -0.97%, p<0.001); San Francisco: -4.08% (95% CI= -5.96%, -2.2%, p<0.001); Philadelphia: -2.17% (95% CI= -3.07%, -1.42%, p<0.001).

conclusionsAgent-based simulations showed how warning labels may decrease overweight and obesity prevalence in a variety of circumstances with label efficacy and literacy rate identified as potential drivers. Implementing a warning label policy may lead to a reduction in obesity prevalence. Focusing on warning label design and store compliance, especially at supermarkets, may further increase the health impact.

Indexed as

Models, BiologicalAdolescentBaltimoreBeveragesChildEnergy IntakeFemaleHumansMaleNutritive SweetenersOverweightPhiladelphiaPrevalenceProduct LabelingSan FranciscoSchoolsNutritive Sweeteners

Identifiers

PMID29249555
PMCPMC5783749

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.