Evidence map›Paper›PMID 40682745›Full record

ReviewCurrent heart failure reports2025

Relative Fat Mass: Refining Adiposity Measurement in the Era Beyond Body Mass Index.

Navin Suthahar, Emily S Lau, Gianluigi Savarese

Abstract readReview
In one paragraph

Review in Current heart failure reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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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

3 authors.

Navin SuthaharDepartment of Cardiology, Cardiovascular Research Institute, Thorax Center, Erasmus Medical Center, Rotterdam, The Netherlands. n.suthahar@erasmusmc.nl.ORCID http://orcid.org/0000-0002-7781-2897
Emily S LauHeart and Vascular Institute, Division of Cardiology, Mass General Brigham, Boston, MA, USA.ORCID http://orcid.org/0000-0001-9361-6397
Gianluigi SavareseDepartment of Clinical Science and Education, Södersjukhuset; Karolinska Institutet, Stockholm, Sweden.ORCID http://orcid.org/0000-0001-7732-0887

Funding

HFpEF Susceptibility in Women: The Role of InflammationK23HL159243 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI Emily Lau · 2022 to 2026
$1.1M
Nederlandse Organisatie voor Wetenschappelijk Onderzoek 101095426 (EnerLIGHT project, funded through the ERA4Health CARDINNOV 2023 call, under the EU Horizon Europe Research and Innovation Programme)NHLBI NIH HHS K23 HL159243
6 · The paper itself

Abstract

purpose of reviewTo position relative fat mass (RFM) as a more accurate, physiologically grounded, and clinically useful alternative to body mass index (BMI) for assessing adiposity and predicting cardiometabolic risk, including heart failure.  RECENT

findingsRFM estimates body fat percentage using a sex-specific formula based on waist circumference and height. RFM not only correlates more strongly with fat mass than BMI, but also shows a weaker correlation with muscle mass. This distinction helps reduce lean mass-related confounding in the assessment of adiposity. In clinical studies, RFM has emerged as a robust predictor of incident heart failure, cardiometabolic disease, and all-cause mortality.  RFM avoids misclassification of adiposity in individuals with high muscle mass and better reflects abdominal adiposity than BMI. As the prevalence of heart failure and other obesity-related diseases continues to rise, RFM offers a practical and intuitive tool for assessment of adiposity and heart failure risk - challenging the long-standing dominance of BMI.

Indexed as

Adipose TissueAdiposityBody Mass IndexHeart FailureObesityHumansBody Mass IndexCardiometabolic DiseaseHeart FailureMuscle MassObesity ParadoxRelative Fat Mass

Identifiers

PMID40682745
PMCPMC12276095

What OpenQuestion holds

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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.