Unscientific Beliefs about Scientific Topics in Nutrition is a research paper published in Advances in Nutrition (2014). On theSindex it has a DataRank of 2.9. It has been cited 54 times, with 40 citing works in its 1-hop citation network.
Humans interact with food daily. Such repeated exposure creates a widespread, superficial familiarity with nutrition. Personal familiarity with nutrition from individual and cultural perspectives may give rise to beliefs about food not grounded in scientific evidence. In this summary of the session entitled “Unscientific Beliefs about Scientific Topics in Nutrition,” we discuss accumulated work illustrating and quantifying potentially misleading practices in the conduct and, more so, reporting of nutrition science along with proposed approaches to amelioration. We begin by defining “unscientific beliefs” and from where such beliefs may come, followed by discussing how large bodies of nutritional epidemiologic observations not only create highly improbable patterns of association but implausible magnitudes of implied effect. Poor reporting practices, biases, and methodologic issues that have distorted scientific understandings of nutrition are presented, followed by potential influences of conflicts of interest that extend beyond financial considerations. We conclude with recommendations for improving the conduct, reporting, and communication of nutrition-related research to ground discussions in evidence rather than solely on beliefs.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.601
From this paper's citation signal
Citation Network Contribution
2.3
From 35 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 21% comes from its base citations and 79% from the citation network (35 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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