Evidence map›Paper›PMID 41332856›Full record

ArticlemedRxiv : the preprint server for health sciences2025

The Impact of Fatty Acid Reporting Methods on Associations with Cardiometabolic Biomarkers.

Brian Hallmark, Manja M Zec, Laurel Johnstone, Carrie S Standage-Beier, Susan Sergeant, Justin Snider, J Thomas Brenna, Floyd H Chilton

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Laurel Johnstone
Carrie S Standage-Beier
Susan Sergeant

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Global dietary guidelines for polyunsaturated fatty acids (PUFAs), especially linoleic acid (LA) and its metabolite arachidonic acid (ARA), remain debated. Almost all research to date has used fatty acid (FA) data expressed as percent of total FA (% total). Objective: The objective of this study was to determine whether expressing fatty acid (FA) data as % of total or as absolute concentrations alters associations with clinical biomarkers. Methods: Serum FA data obtained via electron capture negative-ion mass spectrometry was obtained from NHANES. Each FA was expressed both as % total and absolute concentration (µmol/L). Associations were examined between individual and total FAs and a panel of lipid and non-lipid biomarkers, including total cholesterol, LDL-C, HDL-C, triglycerides, blood pressure, body mass index, waist circumference, glucose, and insulin. Results: Associations between LA and clinical biomarkers including triglycerides, cholesterol, HDL-C, BMI, glucose, and insulin, reversed direction depending on whether LA was expressed as % total or as a concentration. Similar reversals were observed for ARA, DHA, DPA, and stearic acid. Increases in total FA levels were accompanied by decreases in % total of several PUFAs and HUFAs, despite rising absolute concentrations. Total FA was positively associated, often strongly, with nine clinical markers and negatively associated with HDL-C. Conclusions: Expression format significantly impacts observed FA associations. Reliance on % total FA values alone may misrepresent true associations between individual FAs and clinical endpoints, especially when the total fatty acid pool also changes size. To develop effective dietary guidance or clinical recommendations, it is essential to consider the underlying FA biology and total FA pool size when determining whether % total or absolute FA concentrations are more appropriate.

Identifiers

PMID41332856
PMCPMC12668038

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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.