Jonathan Chiang1, Abigail Arons2,3, Jennifer L Pomeranz4, Arjumand Siddiqi5,6, Rita Hamad7. 1. Department of Medicine, Stanford University, Stanford, California, USA. 2. Department of Internal Medicine, University of California Los Angeles, Los Angeles, California, USA. 3. Department of Pediatrics, University of California Los Angeles, Los Angeles, California, USA. 4. Department of Public Health Policy and Management, College of Global Public Health, New York University, New York, New York, USA. 5. Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada. 6. Department of Health Behavior, Gillings School of Global Public Health, University of North Carolina Chapel Hill, Chapel Hill, North Carolina, USA. 7. Department of Family & Community Medicine, Philip R. Lee Institute for Health Policy Studies, University of California San Francisco, San Francisco, California, USA.
Abstract
OBJECTIVE: The 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. METHODS: Newspaper 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. RESULTS: Nationwide 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. CONCLUSIONS: This 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.
OBJECTIVE: The 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. METHODS: Newspaper 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. RESULTS: Nationwide 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. CONCLUSIONS: This 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.
Authors: Pamela Mejia; Lori Dorfman; Andrew Cheyne; Laura Nixon; Lissy Friedman; Mark Gottlieb; Richard Daynard Journal: Am J Public Health Date: 2014-04-17 Impact factor: 9.308
Authors: Heide Weishaar; Lori Dorfman; Nicholas Freudenberg; Benjamin Hawkins; Katherine Smith; Oliver Razum; Shona Hilton Journal: BMC Public Health Date: 2016-08-30 Impact factor: 3.295
Authors: Shelly Soffer; Eyal Zimlichman; Matthew A Levin; Alexis M Zebrowski; Benjamin S Glicksberg; Robert Freeman; David L Reich; Eyal Klang Journal: Obes Sci Pract Date: 2022-03-24
Authors: James P Reynolds; Milica Vasiljevic; Mark Pilling; Marissa G Hall; Kurt M Ribisl; Theresa M Marteau Journal: Int J Environ Res Public Health Date: 2020-09-08 Impact factor: 3.390