Evidence map›Paper›PMID 38453802›Full record

ArticleHistory and philosophy of the life sciences2024

Forgetting how we ate: personalised nutrition and the strategic uses of history.

Christopher Mayes, Maurizio Meloni

Open access · hybridAbstract read
In one paragraph

Article in History and philosophy of the life sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.8field-weighted citation impact, top 10% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Review
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

2 authors at 1 institution in 1 country.

Christopher MayesSchool of Humanities and Social Sciences, Deakin University, Geelong, Australia. christopher.mayes@deakin.edu.au.ORCID http://orcid.org/0000-0003-2674-6225
Maurizio MeloniSchool of Humanities and Social Sciences, Deakin University, Geelong, Australia.ORCID http://orcid.org/0000-0003-2570-3872
Deakin University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Personalised nutrition (PN) has emerged over the past twenty years as a promising area of research in the postgenomic era and has been popularized as the new big thing out of molecular biology. Advocates of PN claim that previous approaches to nutrition sought general and universal guidance that applied to all people. In contrast, they contend that PN operates with the principle that "one size does not fit all" when it comes to dietary guidance. While the molecular mechanisms studied within PN are new, the notion of a personal dietary regime guided by medical advice has a much longer history that can be traced back to Galen's "On Food and Diet" or Ibn Sina's (westernized as Avicenna) "Canon of Medicine". Yet this history is either wholly ignored or misleadingly appropriated by PN proponents. This (mis)use of history, we argue helps to sustain the hype of the novelty of the proposed field and potential commodification of molecular advice that undermines longer histories of food management in premodern and non-Western cultures. Moreover, it elides how the longer history of nutritional advice always happened in a heavily moralized, gendered, and racialized context deeply entwined with collective technologies of power, not just individual advice. This article aims at offering a wider appreciation of this longer history to nuance the hype and exceptionalism surrounding contemporary claims.

Indexed as

MedicineFoodHumansFood ethicsHistory of nutritionHumoralismPersonalised nutritionPostgenomics

Identifiers

PMID38453802
PMCPMC10920492
OpenAlexW4392564086

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.