Evidence map›Paper›PMID 40858793›Full record

ArticleInternational journal of obesity (2005)2025

Perirenal fat: a neglected fat depot shaping heterogeneity of obesity along with hepatic fat.

Yixin Chen, Ting Zhang, Baoding Qin, Yi Yang, Lin Wu, Yuchan Wang, Zijian Mo, Ruomi Guo, Mengyin Cai, Guojun Shi and 3 more

Abstract read
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In one paragraph

Article in International journal of obesity (2005), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

13 authors.

Yixin Chen *Department of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology & Guangzhou Municipal Key Laboratory of Mechanistic and Translational Obesity Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Ting Zhang *Department of Medical Ultrasound, Guangdong Provincial Key Laboratory of Diabetology & Guangzhou Municipal Key Laboratory of Mechanistic and Translational Obesity Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Baoding QinDepartment of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology & Guangzhou Municipal Key Laboratory of Mechanistic and Translational Obesity Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Yi YangDepartment of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology & Guangzhou Municipal Key Laboratory of Mechanistic and Translational Obesity Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Lin WuDepartment of Cardiology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Yuchan WangDepartment of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology & Guangzhou Municipal Key Laboratory of Mechanistic and Translational Obesity Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Zijian MoDepartment of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology & Guangzhou Municipal Key Laboratory of Mechanistic and Translational Obesity Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Ruomi GuoDepartment of Radiology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Mengyin CaiDepartment of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology & Guangzhou Municipal Key Laboratory of Mechanistic and Translational Obesity Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Guojun ShiDepartment of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology & Guangzhou Municipal Key Laboratory of Mechanistic and Translational Obesity Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.ORCID http://orcid.org/0000-0002-3098-6662
Yanhua ZhuDepartment of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology & Guangzhou Municipal Key Laboratory of Mechanistic and Translational Obesity Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China. zhuyanh2@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0003-2775-9538
Jie ZengDepartment of Medical Ultrasound, Guangdong Provincial Key Laboratory of Diabetology & Guangzhou Municipal Key Laboratory of Mechanistic and Translational Obesity Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China. zengjie5@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0003-0159-8051
Yanming ChenDepartment of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology & Guangzhou Municipal Key Laboratory of Mechanistic and Translational Obesity Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China. chyanm@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0001-6856-9058

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveObesity is a heterogeneous condition that leads to diverse cardiovascular and metabolic outcomes. This study aimed to identify the primary visceral fats contributing to metabolically unhealthy obesity and to investigate the characteristics of fat distribution associated with different obesity-related complications.

methodsA retrospective analysis was conducted on fat-selective magnetic resonance images (MRI) from 319 individuals with a BMI ≥24 kg/m². Participants were categorized into four groups: solely obesity, T2DM, hypertension, and dyslipidemia, to examine differences in the distribution of hepatic, pancreatic, preperitoneal, mesenteric, and perirenal fat (PrFT). Correlation analyses were performed to elucidate relationships between visceral fat deposits and obesity-related characteristics. Logistic regression identified key fat deposition sites associated with common obesity-related complications. Additionally, the limitations of single-site fat measurements in capturing the heterogeneity of obesity were examined.

resultsPrFT exhibited the strongest correlation with blood pressure (r = 0.225 ~ 0.306, all p < 0.001) among all visceral fats, and the hypertensive individuals with obesity presented the highest PrFT. Hepatic fat showed the highest association with glucose metabolism (r = 0.188 ~ 0.407 all p < 0.01), as evidenced by higher hepatic fat content in the T2DM group compared to other groups. Risk of metabolic syndrome increased by 3.06-fold (95% CI:1.35-6.93, p = 0.007) and 6.79-fold (95% CI:2.45-18.83, p < 0.001) with moderate and severe fatty steatosis compared to those without hepatic steatosis. A 2.24-fold (95% CI:1.27-3.97, p = 0.006) increase in metabolic syndrome likelihood was observed for each 1 cm increment in PrFT.

conclusionsBesides hepatic fat, perirenal fat is also a key determinant for metabolic syndrome. Patients with various metabolic abnormalities present distinct patterns of visceral fat distribution, which could be simply profiled by perirenal and hepatic fat quantification.

Indexed as

Intra-Abdominal FatLiverObesityAdultFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedRetrospective Studies

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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.