Use of causal language in observational studies of obesity and nutrition
Open accessAbstract
OBJECTIVE: To assess the inappropriate use of causal language in studies on obesity and nutrition. METHODS: Titles and abstracts of 525 peer-reviewed papers in the 4 leading journals in the fields of obesity and nutrition were scrutinized for language implying causality in observational studies published in 2006. RESULTS: Such misleading language appeared in 161 papers (31%) independent of funding source. Remarkably 49% of studies lacking statistically significant primary outcomes used misleading language compared to 29% of those with p values ≤0.05 (chi square p < 0.001). Exculpatory language was present in the body of the text in 19%; of the 161 studies. CONCLUSION: We suggest that editors and reviewers evaluate submissions for misleading reporting.
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Implication of a causal relationship even after stating that the evidence is insufficient to reach causal conclusions may introduce error into bodies of published literature.
“Publication bias [20, 21], lack of replicability and replication [22], implication of a causal relationship even after stating that the evidence is insufficient to reach causal conclusions [23–25], and related phenomena may also introduce error into bodies of published literature.”
From Causal language and strength of inference in academic and media articles shared in social media (CLAIMS): A systematic review (2018) · cites this paper as [23]
Nearly a third of 525 papers in top obesity or nutrition journals make inappropriate causal claims in their abstracts or titles.
“One analysis found that nearly a third of 525 papers in top obesity or nutrition journals make inappropriate causal claims in their abstracts or titles (37)”
From Misinformation in and about science (2021) · cites this paper as [37]
Assuming causation from observational evidence is common.
“Assuming causation from observational evidence is common (34, 35).”
From Issues with data and analyses: Errors, underlying themes, and potential solutions (2018) · cites this paper as [35]
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- Authors
- Cofield, S. S., Corona, R. V., & Allison, D. B.
- Affiliations
- University of Alabama (US)
- University of Alabama at Birmingham (US)
- Venue
- Obesity Facts
- Publisher
- S. Karger AG
- Published
- 2010
- Volume
- 3
- Issue
- 6
- Pages
- 353-356
- ISSN
- 1662-4025 (ISSN-L)
- 1662-4033
- PMC
- PMC3280017
- OpenAlex
- W2151304832
- Semantic Scholar
- 00e3cd0a4f036ce7a874ab9a1f15814ba0b887bb
- Cited by
- 74
- References
- 9
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 7 · 2023: 6 · 2022: 10 · 2021: 5 · 2020: 7 · 2019: 5 · 2018: 9 · 2017: 3 · 2016: 5 · 2015: 3 · 2013: 1 · 2012: 4
- FWCI
- 2.32
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Obesity Facts (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health
- National Institute of Diabetes and Digestive and Kidney Diseases (P30DK056336)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Academic Writing and Publishing
- Keywords
- causal language, observational studies, obesity, nutrition, statistical significance, peer review, editorial evaluation
- MeSH terms
- Data Interpretation, Statistical, Humans, Language, Terminology as Topic, Obesity, Periodicals as Topic, Research Support as Topic, Risk Factors, Reproducibility of Results, Bibliometrics, Bias, Epidemiologic Studies, Risk Assessment, Nutritional Sciences
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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