Evidence map›Paper›PMID 29454330›Full record

ArticleBMC nephrology2018

Comparison of visceral, body fat indices and anthropometric measures in relation to chronic kidney disease among Chinese adults from a large scale cross-sectional study.

Ying Dong, Zengwu Wang, Zuo Chen, Xin Wang, Linfeng Zhang, Jingyu Nie, Congyi Zheng, Jiali Wang, Lan Shao, Ye Tian and 1 more

Abstract readComparative Study
In one paragraph

Article in BMC nephrology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

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

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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.

Ying DongDivision of Prevention and Community Health, National Center for Cardiovascular Disease, Fuwai Hospital, Pecking Union Medical College & Chinese Academy of Medical Sciences, Beijing, 102308, China.
Zengwu WangDivision of Prevention and Community Health, National Center for Cardiovascular Disease, Fuwai Hospital, Pecking Union Medical College & Chinese Academy of Medical Sciences, Beijing, 102308, China. wangzengwu@foxmail.com.
Zuo ChenDivision of Prevention and Community Health, National Center for Cardiovascular Disease, Fuwai Hospital, Pecking Union Medical College & Chinese Academy of Medical Sciences, Beijing, 102308, China.
Xin WangDivision of Prevention and Community Health, National Center for Cardiovascular Disease, Fuwai Hospital, Pecking Union Medical College & Chinese Academy of Medical Sciences, Beijing, 102308, China.
Linfeng ZhangDivision of Prevention and Community Health, National Center for Cardiovascular Disease, Fuwai Hospital, Pecking Union Medical College & Chinese Academy of Medical Sciences, Beijing, 102308, China.
Jingyu NieDivision of Prevention and Community Health, National Center for Cardiovascular Disease, Fuwai Hospital, Pecking Union Medical College & Chinese Academy of Medical Sciences, Beijing, 102308, China.
Congyi ZhengDivision of Prevention and Community Health, National Center for Cardiovascular Disease, Fuwai Hospital, Pecking Union Medical College & Chinese Academy of Medical Sciences, Beijing, 102308, China.
Jiali WangDivision of Prevention and Community Health, National Center for Cardiovascular Disease, Fuwai Hospital, Pecking Union Medical College & Chinese Academy of Medical Sciences, Beijing, 102308, China.
Lan ShaoDivision of Prevention and Community Health, National Center for Cardiovascular Disease, Fuwai Hospital, Pecking Union Medical College & Chinese Academy of Medical Sciences, Beijing, 102308, China.
Ye TianDivision of Prevention and Community Health, National Center for Cardiovascular Disease, Fuwai Hospital, Pecking Union Medical College & Chinese Academy of Medical Sciences, Beijing, 102308, China.
Runlin GaoFuwai Hospital, Pecking Union Medical College & Chinese Academy of Medical Sciences, Beijing, 100037, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe aim of the study was to assess the association between chronic kidney disease (CKD) and obesity in predicting CKD among Chinese adults, distinguishing between 5 different adiposity indices: visceral fat index (VFI), percentage body fat (PBF), body mass index (BMI), waist circumference (WC) and waist-to-height ratio (WHtR).

methodsA total of 29,516 participants aged 35 years or above were selected using a stratified multistage random sampling method across China during 2012-2015. CKD was defined as an estimated glomerular filtration (eGFR) < 60 ml/min/1.72m

resultsThe overall weighted prevalence of CKD was 3.94% (3.62% in males and 4.25% in females). All five adiposity indices had significant negative correlations to eGFR (P < 0.05). The area under the ROC (receiver operating characteristic) curves (AUC) for PBF was almost significantly larger than the other adiposity indices (P < 0.001). In addition, PBF yielded the highest Youden index in identifying CKD (male: 0.15; female: 0.20). In the logistic analysis, PBF had the highest crude odds ratios (ORs) in both males (OR: 1.819, 95% CI 1.559-2.123) and females (OR: 2.268, 95% CI 1.980-2.597). After adjusted for age, smoking status, alcohol use, education level, marital status, rural vs. urban area, geographic regions, and diagnosis of hypertension, diabetes mellitus, myocardial infarction and stroke, the ORs on PBF remained significant for both genders (P < 0.05).

conclusionsObesity is associated with an increased risk of CKD. Furthermore, PBF was a better predictor for identifying CKD than other adiposity indices (BMI, WC, WHtR, and VFI).

Indexed as

Adipose TissueAdiposityAdultAgedAnthropometryChinaCross-Sectional StudiesFemaleHumansIntra-Abdominal FatMaleMiddle AgedObesityRenal Insufficiency, ChronicWaist CircumferenceAdiposity indicesChinese adultsChronic kidney diseaseCross-sectional studyPercentage body fat

Identifiers

PMID29454330
PMCPMC5816526

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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.