Evidence mapPaperPMID 42297907Full record

ReviewNature metabolism2026

Adiposity and cancer: epidemiology, mechanisms and future perspectives.

Eleanor L Watts, Amparo Gonzalez-Feliciano, Marc J Gunter, Nilanjan Chatterjee, Steven C Moore

Abstract readReview
In one paragraph

Review in Nature metabolism, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  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

5 authors.

Eleanor L WattsDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA. eleanor.watts@nih.gov.ORCID http://orcid.org/0000-0001-9229-2589
Amparo Gonzalez-FelicianoDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
Marc J Gunter *Cancer Epidemiology and Prevention Research Unit, School of Public Health, Imperial College London, London, UK. m.gunter@imperial.ac.uk.
Nilanjan Chatterjee *Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA. nchatte2@jhu.edu.ORCID http://orcid.org/0000-0002-9060-008X
Steven C Moore *Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA. steve.moore@nih.gov.ORCID http://orcid.org/0000-0002-8169-1661

Funding

Intramural NIH HHS Z99 CA999999U.S. Department of Health & Human Services | National Institutes of Health (NIH) U01CA284209
6 · The paper itself

Abstract

Excess adiposity is a major modifiable risk factor for at least 19 cancer types, and the burden of obesity-related cancer is expected to rise substantially in the coming decades. A comprehensive understanding of underlying mechanisms and precise risk associations will be critical to inform targeted prevention strategies and reduce this burden. In this Review, we examine key biological mechanisms linking adiposity and cancer, including sex hormones, hyperinsulinaemia and chronic inflammation, alongside emerging insights from omics technologies, and tumour subtype-specific associations. We also highlight priorities for future research, including imaging-based adiposity measures, integration of multi-omics approaches and expanded data collection in lower-income settings and understudied populations. Finally, we consider the potential implications of emerging obesity pharmacotherapies, which may facilitate substantial weight loss at scale.

Indexed as

AdiposityNeoplasmsObesityAnimalsHumansRisk Factors

Identifiers

PMID42297907
PMCPMC13426884

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.