ArticleJournal of cancer education : the official journal of the American Association for Cancer Education2016
"Obesity is the New Major Cause of Cancer": Connections Between Obesity and Cancer on Facebook and Twitter.
Article in Journal of cancer education : the official journal of the American Association for Cancer Education, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 40 citations in OpenAlex.
- Pooled it
- Using Social Media to Understand Web-Based Social Factors Concerning Obesity: Systematic Review.JMIR public health and surveillance · 2022Pooled it
- Exploring Social Media Posts on Lifestyle Behaviors: Sentiment and Content Analysis.JMIR infodemiology · 2025Article
- How do electronic personal health information technologies enhance obesity prevention behaviors? Examining the roles of obesity risk perception and body weight.BMC public health · 2025Article
- "Mars Bar and a Tin of Red Bull Kept Me and My Patients Alive": Exploring Barriers to Healthy Eating through Facebook Comments of Shiftworkers.Nutrients · 2023Article
- Deep Neural Networks for Simultaneously Capturing Public Topics and Sentiments During a Pandemic: Application on a COVID-19 Tweet Data Set.JMIR medical informatics · 2022Article
- Using Machine Learning for Pharmacovigilance: A Systematic Review.Pharmaceutics · 2022Review
- How Are the Links between Alcohol Consumption and Breast Cancer Portrayed in Australian Newspapers?: A Paired Thematic and Framing Media Analysis.International journal of environmental research and public health · 2021Article
- Overcoming Alzheimer's Disease Stigma by Leveraging Artificial Intelligence and Blockchain Technologies.Brain sciences · 2020Review
- Using Facebook for Qualitative Research: A Brief Primer.Journal of medical Internet research · 2019Article
- How has big data contributed to obesity research? A review of the literature.International journal of obesity (2005) · 2018Review
- Sentiment Analysis of Health Care Tweets: Review of the Methods Used.JMIR public health and surveillance · 2018Review
- Public Perceptions Regarding Use of Virtual Reality in Health Care: A Social Media Content Analysis Using Facebook.Journal of medical Internet research · 2017Article
- Advancing Cancer Prevention and Behavior Theory in the Era of Big Data.Journal of cancer prevention · 2016Article
- Leveraging Social Media to Promote Public Health Knowledge: Example of Cancer Awareness via Twitter.JMIR public health and surveillanceArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Social media interactions can inform public health risk perceptions. While research has examined the risk relationships between obesity and cancer, public attitudes about their associations remain largely unknown. We explored how these constructs were discussed together on two social media platforms. Publicly accessible Facebook and Twitter posts from a 2-month period in 2012 containing references to obesity ("obese/obesity," "overweight," and "fat") and cancer-related words were extracted (N = 3702 posts). Data cleaning yielded a final set of 1382 posts (Facebook: N = 291; Twitter: N = 1091). Using a mixed-methods approach, themes were inductively generated, and sentiment valence, structural elements, and epistemic stance were coded. Seven relational themes emerged: obesity is associated with cancer (n = 389), additional factors are associated with both obesity and cancer (n = 335), obesity causes cancer (n = 85), cancer causes obesity (n = 6), obesity is not linked to cancer (n = 13), co-occurrence (n = 492), and obesity is valued differently than cancer (n = 60). Fifty-nine percent of posts focused on an associative or causal link between obesity and cancer. Thirty-one percent of posts contained positive and/or negative sentiment. Facebook was more likely to contain any sentiment, but Twitter contained proportionately more negative sentiment. Concurrent qualitative analysis revealed a dominance of individual blame for overweight/obese persons and more support and empathy for cancer survivors. Our study reflects wide recognition of the evidence linking obesity to increased risk of cancer, a diverse set of factors perceived to be dually associated with both conditions and differing attribution of responsibility. We demonstrate that social media monitoring can provide an important gauge of public health risk perception.
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What OpenQuestion holds
Registered trials
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.