Evidence map›Paper›PMID 33889002›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2021

Visceral Obesity-Related Indices in the Identification of Individuals with Metabolic Syndrome Among Different Ethnicities in Xinjiang, China.

Xianghui Zhang, Yusong Ding, Yinbao Shao, Jia He, Jiaolong Ma, Heng Guo, Mulatibieke Keerman, Jiaming Liu, Huili Si, Shuxia Guo and 1 more

Abstract read
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Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

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6citing papers in PubMed, 1 pooled it
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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

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

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Xianghui Zhang *Department of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, People's Republic of China.
Yusong Ding *Department of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, People's Republic of China.
Yinbao ShaoDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, People's Republic of China.
Jia HeDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, People's Republic of China.
Jiaolong MaDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, People's Republic of China.
Heng GuoDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, People's Republic of China.
Mulatibieke KeermanDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, People's Republic of China.
Jiaming LiuDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, People's Republic of China.
Huili SiDepartment of Neurology, Shihezi People's Hospital, Shihezi, Xinjiang, People's Republic of China.
Shuxia GuoDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, People's Republic of China.ORCID 0000-0002-8139-2813
Rulin MaDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFew studies have focused on the predictive ability of visceral obesity-related indices for metabolic syndrome (MetS), especially in different ethnic groups. This study aimed to evaluate the applicability of visceral obesity-related indices for MetS screening among three major ethnic groups living in remote rural areas of Xinjiang.

methodsBased on multistage stratified cluster random sampling method, 3,192 Uyghurs, 3,054 Kazakhs, and 3,658 Hans were recruited from Xinjiang, China. The Joint Interim Statement (JIS) criteria were used to define MetS. The receiver operating characteristic curve (ROC), area under the ROC curve (AUC), and predictive value of each visceral obesity-related index were used to evaluate the predictive ability of MetS.

resultsAfter adjusting for potential confounding factors, the lipid accumulation product (LAP), Chinese visceral adiposity index (CVAI), waist-to-height ratio (WHtR), and atherogenic index of plasma (AIP) were significantly correlated with MetS for each ethnic group, and the odds ratios (ORs) for MetS increased across quartiles. LAP was best able to identify MetS status in Kazakhs (AUC=0.853) and Uyghurs (AUC=0.851), with optimal cut-offs being 36.3 and 28.2, respectively. Both LAP (AUC=0.798) and CVAI (AUC=0.791) most accurately identified MetS status in Hans, with the optimal cut-offs being 27.3 and 85.0, respectively. Moreover, the AUC of the combination of these visceral obesity-related indices is higher for each ethnic group. However, compared with LAP, the improved value of combined screening was not significant.

conclusionLAP had the best discriminative capability for the screening of MetS among Kazakhs, Uyghurs, and Hans. The screening ability of CVAI for MetS was similar to that of LAP in Hans. Thus, LAP may be a complementary indicator for assessing MetS in various ethnic groups.

Indexed as

ethnic groupsmetabolic syndromescreeningvisceral obesity-related indices

Identifiers

PMID33889002
PMCPMC8055644

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