Evidence map›Paper›PMID 42045672›Full record

ReviewNature reviews. Endocrinology2026

Clinical obesity in Asian people: bridging the gap between adiposity and disease.

Soo Lim, Linong Ji, Kwang Wei Tham, Anoop Misra, Takashi Kadowaki

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In one paragraph

Review in Nature reviews. Endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
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.

Soo LimDepartment of Internal Medicine, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea. limsoo@snu.ac.kr.ORCID http://orcid.org/0000-0002-4137-1671
Linong JiDepartment of Endocrinology and Metabolism, Peking University People's Hospital, Beijing, China.
Kwang Wei ThamDepartment of Endocrinology, Woodlands Health, National Healthcare Group, Singapore, Singapore.ORCID http://orcid.org/0000-0003-1904-5711
Anoop MisraFortis-C-DOC Centre of Excellence for Diabetes, Metabolic Diseases and Endocrinology, New Delhi, India.
Takashi KadowakiDepartment of Internal Medicine, Toranomon Hospital, Tokyo, Japan. T-kadowaki@toranomon.kkr.or.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This Perspective argues for a reconceptualization of clinical obesity in Asian populations, moving beyond BMI-centric definitions towards an adiposity-based and function-based framework. Asian populations exhibit a distinctive obesity phenotype, characterized by excess visceral and ectopic adipose tissue accumulation, reduced β-cell reserve, sarcopenic obesity and heightened cardiometabolic risk at lower BMI thresholds than for white European and North American populations, leading to systematic under-recognition of obesity-related disease when conventional criteria are applied. Building on the Lancet Commission's framework for defining and diagnosing clinical obesity, we propose an integrated approach that combines anthropometric measures, body composition assessment, metabolic and organ-specific markers and emerging biomarkers to distinguish preclinical obesity from clinical obesity on the basis of organ dysfunction and functional impairment. This approach improves risk stratification, supports earlier and more precise diagnosis and informs stage-specific management, including lifestyle intervention, pharmacotherapy and metabolic surgery, particularly in Asian populations. We discuss implications for clinical practice, prevention strategies and public health policy, emphasizing the need to align clinical guidelines, reimbursement systems and education with a function-based definition of obesity. Finally, we highlight key research priorities, including validation of biomarker-driven classifications, assessment of long-term clinical and economic outcomes and development of scalable diagnostic tools, to advance precision care and metabolic health equity across diverse Asian populations.

Indexed as

AdiposityAsian PeopleObesityBiomarkersBody CompositionBody Mass IndexHumansBiomarkers

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.