Evidence map›Paper›PMID 33219935›Full record

ArticleAging clinical and experimental research2021

Association between organ damage and visceral adiposity index in community-dwelling elderly Chinese population: the Northern Shanghai Study.

Chong Xu, Song Zhao, Shikai Yu, Chen Chi, Ximin Fan, Hongwei Ji, Rusitanmujiang Maimaitiaili, Jiadela Teliewubai, Xiaofeng Li, Yi Zhang and 1 more

Registry-linked trialAbstract read
PubMed Publisher
In one paragraph

Article in Aging clinical and experimental research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02368938 (Prognosis Factors of Mortality and Cardiovascular Diseases in the Elderly Chinese), which is not on this map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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.

NCT02368938 unknown statusnot on this map

Prognosis Factors of Mortality and Cardiovascular Diseases in the Elderly Chinese: the Northern Shanghai Study

TypeobservationalSponsorShanghai 10th People's HospitalRan2014Enrolled5,000ConditionsCardiovascular Risk Factor
3 · Its place in the literature

Who cites it

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

  1. Pooled it
  2. The Predictive Value of Insulin Resistance Surrogates for Diabetic Kidney Disease in Type 2 Diabetes Mellitus.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2025
    Article
  3. Article
  4. Review
  5. 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

11 authors.

Chong Xu *Department of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Road, Shanghai, 200072, China.
Song Zhao *Department of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Road, Shanghai, 200072, China.
Shikai YuDepartment of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Road, Shanghai, 200072, China.
Chen ChiDepartment of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Road, Shanghai, 200072, China.
Ximin FanDepartment of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Road, Shanghai, 200072, China.
Hongwei JiDepartment of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Road, Shanghai, 200072, China.
Rusitanmujiang MaimaitiailiDepartment of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Road, Shanghai, 200072, China.
Jiadela TeliewubaiDepartment of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Road, Shanghai, 200072, China.
Xiaofeng LiDepartment of Emergency, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Road, Shanghai, 200072, China.
Yi ZhangDepartment of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Road, Shanghai, 200072, China. yizshcn@gmail.com.ORCID http://orcid.org/0000-0001-8693-3554
Yawei XuDepartment of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Road, Shanghai, 200072, China. xuyawei@tongji.edu.cn.

Funding

Key Technologies Research and Development Program 2017YFC0111800National Natural Science Foundation of China 81670377Shanghai Excellent Young Scholars Program 2017YQ065Shanghai Municipal Health Bureau 15GWZK1002
6 · The paper itself

Abstract

backgroundThe visceral adiposity index (VAI) is a newly developing indicator about visceral fat function and insulin resistance. This research aims to assess the association between organ damage and VAI in the community-dwelling elderly Chinese population.

methodsIn total, 3363 elderly participants were recruited between June 2014 and August 2019. VAI was used to measure visceral adipose accumulation, and organ damage was measured with standardized methods, including arterial stiffness, lower extremity atherosclerosis, carotid hypertrophy, left ventricular hypertrophy, micro-albuminuria, and chronic kidney disease.

resultsAccording to multivariable linear regression analysis, VAI was related to carotid-femoral pulse wave velocity (cf-PWV; β = 0.047, P = 0.024), urine albumin to creatinine ratio (UACR; β = 3.893, P = 0.008), estimated glomerular filtration rate (eGFR; β =  - 0.526, P = 0.003) and log

conclusionsSince higher VAI is related to increased risk of arterial stiffness and CKD, it may serve as a useful index for the assessment of arteriosclerosis and CKD in elderly population.

trial registrationNSS, NCT02368938.

Indexed as

Pulse Wave AnalysisVascular StiffnessAdiposityAgedChinaCross-Sectional StudiesHumansIndependent LivingRisk FactorsElderlyOrgan damageVisceral adiposityVisceral adiposity index

Identifiers

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Registered trials

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.