Evidence map›Paper›PMID 40707700›Full record

ReviewNature reviews. Endocrinology2025

Body weight regulation models in humans: insights for testing their validity.

Rodrigo Fernández-Verdejo, Eric Ravussin, Jose E Galgani

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. 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

3 authors.

Rodrigo Fernández-VerdejoPennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA, USA. Rodrigo.Fernandez@pbrc.edu.ORCID http://orcid.org/0000-0002-5948-2281
Eric RavussinPennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA, USA.ORCID http://orcid.org/0000-0003-2129-547X
Jose E GalganiPennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA, USA. jgalgani@uc.cl.ORCID http://orcid.org/0000-0001-9793-8561

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Maintaining a 'healthy' body weight is crucial for survival and involves a partially understood regulatory system that adjusts energy intake and energy output (expenditure and losses) for that purpose. Several models of body weight regulation exist, but experiments testing their validity are lacking. This Review elaborates on how to test the validity of body weight regulation models in humans. We begin by highlighting the interaction between the obesogenic environment and the individual's biological sensitivity to such environment, which triggers obesity in many, but not all, individuals. We discuss the identity of the regulated parameter(s), often considered to be body weight or body adiposity. We then focus on two models: set point and dual-intervention point. Under the set point model, obesity results from a malfunction of the system (leptin resistance) for preventing weight increases above the defended value. Under the dual-intervention point model, obesity occurs because the system tolerates a wide range of weights in some individuals. This key difference predicts different compensatory responses to energy balance perturbations in individuals according to their weight status, thus becoming instrumental in testing the validity of the models. Finally, we discuss the design of proof-of-concept experiments to advance the understanding of body weight regulation in humans.

Indexed as

Body WeightModels, BiologicalEnergy IntakeEnergy MetabolismHumansObesity

Identifiers

What OpenQuestion holds

Textmetadata
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.