Evidence map›Paper›PMID 29372543›Full record

ArticleEating and weight disorders : EWD2018

Identification of chronic kidney disease risk in relatively lean Southern Chinese: the hypertriglyceridemic waist phenotype vs. anthropometric indexes.

Chaomin Zhou, Yongqiang Li, Xiaofei Shao, Hequn Zou

Abstract read
In one paragraph

Article in Eating and weight disorders : EWD, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 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

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 2 syntheses or guidelines 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

4 authors.

Chaomin ZhouDepartment of Nephrology, The People's Hospital of Guizhou Province, Guiyang, 550002, China.ORCID http://orcid.org/0000-0002-0817-4078
Yongqiang LiDepartment of Nephrology, Institute of Nephrology and Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, 510630, China.
Xiaofei ShaoDepartment of Nephrology, Institute of Nephrology and Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, 510630, China.
Hequn ZouDepartment of Nephrology, Institute of Nephrology and Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, 510630, China. 15186986606@163.com.

Funding

Guangdong Province Science and Technologue Program No. 2011B031800386
6 · The paper itself

Abstract

purposeAssessing and comparing the ability of the hypertriglyceridemic waist (HW) phenotype and anthropometric obesity indexes to identify subjects at high risk of chronic kidney disease (CKD) in a relatively lean population in South China.

methodsUsing data from a community-based, cross-sectional study conducted in Zhuhai City, Southern China, we examined associations between the HW phenotype, anthropometric obesity indexes, and incident CKD risk in a relatively lean population. Multiple logistic regression analyses were used to evaluate the associations.

resultsThe HW phenotype associated with CKD significantly in the unadjusted analysis (OR 3.53, 95% CI 1.65-7.52, P = 0.001). Further adjustment for gender, age, and other potential confounding variables had an impact on the odd ratios (OR); the OR decreased but still existed (OR 2.91, 95% 1.23-6.87, P = 0.016). The association of the HW phenotype with CKD remained significant after further adjustment for hypertension and diabetes. No significant association between the anthropometric indexes and incident CKD was found.

conclusionThe HW phenotype, but not the anthropometric indexes, is associated with an elevated risk of CKD in relatively lean subjects. The HW phenotype appears to be a better predictor of CKD than the anthropometric indexes. LEVEL OF EVIDENCE: Level V, descriptive study.

Indexed as

AdultAgedAnthropometryChinaCross-Sectional StudiesFemaleHumansHypertriglyceridemic WaistMaleMiddle AgedPhenotypeRenal Insufficiency, ChronicRisk FactorsWaist CircumferenceAnthropometric indexesChronic kidney diseaseHypertriglyceridemic waist phenotypeVisceral adiposity

Identifiers

PMID29372543
PMCPMC6244600

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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.