Evidence map›Paper›PMID 32475076›Full record

ArticleObesity (Silver Spring, Md.)2020

Geographic and Longitudinal Trends in Media Framing of Obesity in the United States.

Jonathan Chiang, Abigail Arons, Jennifer L Pomeranz, Arjumand Siddiqi, Rita Hamad

Open access · greenAbstract read
In one paragraph

Article in Obesity (Silver Spring, Md.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
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

5 citing papers in PubMed, 12 citations in OpenAlex.

  1. Trial
  2. United States Long-Term Trends in Adult BMI (1959-2018): Unraveling the Roots of the Obesity Epidemic.International journal of environmental research and public health · 2024
    Article
  3. Review
  4. Article
  5. Article
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

5 authors at 5 institutions in 3 countries.

Jonathan ChiangDepartment of Medicine, Stanford University, Stanford, California, USA.
Abigail AronsDepartment of Internal Medicine, University of California Los Angeles, Los Angeles, California, USA.ORCID 0000-0002-9140-2130
Jennifer L PomeranzDepartment of Public Health Policy and Management, College of Global Public Health, New York University, New York, New York, USA.
Arjumand SiddiqiDivision of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
Rita HamadDepartment of Family & Community Medicine, Philip R. Lee Institute for Health Policy Studies, University of California San Francisco, San Francisco, California, USA.ORCID 0000-0003-0730-4077
New York University · USStanford University · USUniversity of California, Los Angeles · USUniversity of California, San Francisco · USUniversity of North Carolina at Chapel Hill · US

Funding

Stanford Center for Clinical & Translational Education and Research (Spectrum)UL1TR003142 · NCATS · STANFORD UNIVERSITY · PI O'HARA, RUTH M · 2019 to 2023
$45.0M
Spectrum Stanford Center for clinical and Translational Research and EducationUL1TR001085 · NCATS · STANFORD UNIVERSITY · PI CULLEN, MARK RICHARD, GREENBERG, HARRY BERNARD · 2013 to 2017
$37.1M
Assessing the Impact of Educational Interventions on Reducing Disparities in Hypertension and Related BiomarkersK08HL132106 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HAMAD, RITA · 2016 to 2019
$668k
NCATS NIH HHS UL1 TR001085NCATS NIH HHS UL1 TR003142NHLBI NIH HHS K08 HL132106NIH HHS K08 HL132106NIH HHS UL1 TR001085
6 · The paper itself

Abstract

objectiveThe media's framing of public health issues is closely linked to public opinion on these issues and support for interventions to address them. This study characterized geographic and temporal variation in the US media's framing of obesity across states from 2006 to 2015.

methodsNewspaper articles that mentioned the term obesity were drawn from Access World News (NewsBank, Inc., Naples, Florida), a comprehensive online database (N = 364,288). This study employed automated content analysis, a machine learning technique, to categorize articles as (1) attributing obesity to individual-level causes (e.g., lifestyle behaviors), (2) attributing obesity to environmental/systemic causes (e.g., neighborhood walkability), (3) attributing obesity to both individual-level causes and environmental/systemic causes, or (4) articles without any such attribution framework.

resultsNationwide across all years, a higher proportion of articles focused on individual-level attribution of obesity than environmental-level attribution or both. Missouri and Idaho had the highest proportions of articles with an individual framework, and Nevada, Arkansas, and Wisconsin had the highest proportions of articles with an environmental framework.

conclusionsThis analysis demonstrates that US media sources heavily focus on an individual framing of obesity, which may be informing public perceptions of obesity. By highlighting differences in obesity media portrayal, this study could inform research to understand why particular states represent outliers and how this may affect obesity policy making.

Indexed as

HumansLongitudinal StudiesMass MediaObesityUnited States

Identifiers

PMID32475076
PMCPMC7311269
OpenAlexW3029437950

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.