Evidence map›Paper›PMID 42038251›Full record

ArticleClinical interventions in aging2026

Identification of a High Visceral Adiposity Phenotype: A Cluster Analysis-Based Stratification of NAFLD Risk in the Elderly.

Zhongjun Shen, Qian Zhang, Jingjin Tao, Yuying Nie, Qi Liu, He Wang, Zhongxin Li, Chong Wang, Shuo Yang, Liyan Cui

Abstract read
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Article in Clinical interventions in aging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Zhongjun Shen *Department of Clinical Laboratory, Peking University Third Hospital, Beijing, People's Republic of China.
Qian Zhang *Department of Clinical Laboratory, Peking University Third Hospital, Beijing, People's Republic of China.
Jingjin TaoDepartment of Clinical Laboratory, Peking University Third Hospital, Beijing, People's Republic of China.
Yuying NieDepartment of Clinical Laboratory, Peking University Third Hospital, Beijing, People's Republic of China.
Qi LiuDepartment of Clinical Laboratory, Peking University Third Hospital, Beijing, People's Republic of China.
He WangDepartment of Clinical Laboratory, Peking University Third Hospital, Beijing, People's Republic of China.
Zhongxin LiDepartment of Clinical Laboratory, Peking University Third Hospital, Beijing, People's Republic of China.
Chong WangDepartment of Clinical Laboratory, Peking University Third Hospital, Beijing, People's Republic of China.
Shuo YangDepartment of Clinical Laboratory, Peking University Third Hospital, Beijing, People's Republic of China.
Liyan CuiDepartment of Clinical Laboratory, Peking University Third Hospital, Beijing, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Non-alcoholic fatty liver disease (NAFLD), the most prevalent chronic liver disease globally, is closely linked to obesity and metabolic dysregulation. However, the relative contributions of overall adiposity versus body fat distribution patterns to NAFLD pathogenesis, particularly in the elderly population, remain incompletely understood. Objective: This study aimed to investigate the association between cluster-derived body composition phenotypes and NAFLD risk, and identify independent risk factors for NAFLD. Methods: This cross-sectional study enrolled 239 elderly participants. Body composition parameters (whole-body and regional fat percentages, visceral adipose tissue (VAT) area, fat-free mass) were measured via dual-energy X-ray absorptiometry (DXA). Participants were divided into NAFLD and non-NAFLD groups by abdominal ultrasonography. Inter-group comparisons were performed with Student's t-tests and chi-square tests. Cluster analysis was applied to identify distinct body composition phenotypes. Univariate and multivariate logistic regression were used to screen independent NAFLD risk factors, and ROC curve analysis evaluated the model's predictive performance. Results: The NAFLD group showed more prominent central obesity ( Conclusion: In the elderly, visceral fat accumulation and central fat distribution, rather than overall adiposity itself, are key body composition features linked to NAFLD. The high visceral fat central obesity phenotype correlates with the highest metabolic risk and NAFLD prevalence, and the trunk-to-leg fat ratio is a robust NAFLD predictor.

Indexed as

AdiposityIntra-Abdominal FatNon-alcoholic Fatty Liver DiseaseObesity, AbdominalAbsorptiometry, PhotonAgedBody CompositionBody Mass IndexCluster AnalysisCross-Sectional StudiesFemaleHumansLogistic ModelsMaleMiddle AgedPhenotypeadipose tissue distributionbody compositionnon-alcoholic fatty liver diseasevisceral fat

Identifiers

PMID42038251
PMCPMC13110045

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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.