Evidence map›Paper›PMID 32437358›Full record

ArticlePloS one2020

Mid-upper arm circumference as a simple tool for identifying central obesity and insulin resistance in type 2 diabetes.

Yanhua Zhu, Qiongyan Lin, Yao Zhang, Hongrong Deng, Xiling Hu, Xubin Yang, Bin Yao

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
4.3field-weighted citation impact, top 4% of its field
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

32 citing papers in PubMed, 51 citations in OpenAlex.

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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

7 authors at 1 institution in 1 country.

Yanhua ZhuDepartment of Endocrinology, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Qiongyan LinDepartment of Endocrinology, Jieyang People's Hospital (Jieyang Affiliated Hospital, Sun Yat-sen University), Jieyang, Guangdong, China.
Yao ZhangDepartment of Endocrinology, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Hongrong DengDepartment of Endocrinology, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Xiling HuDepartment of Endocrinology, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Xubin YangDepartment of Endocrinology, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Bin YaoDepartment of Endocrinology, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.ORCID 0000-0002-1999-301X
Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOur research aimed to explore the correlation between mid-upper arm circumference (MUAC) and central obesity and insulin resistance (IR) in Chinese subjects with type 2 diabetes. MATERIALS: A total of 103 participants (60 men) were recruited in our study. MUAC was measured around the mid-arm between the shoulder and elbow. Waist circumference (WC) was obtained as central obesity parameter, and the IR parameter of Homeostasis Model Assessment-Insulin Resistance (HOMA-IR) was calculated. The subjects were divided into three groups according to the tertiles cut-points of MUAC level.

resultsBody mass index (BMI), WC, the percentages of central obesity and HOMA-IR were significantly higher in the groups with higher MUAC than those in the group with lower MUAC (all P < 0.05). Pearson analysis showed that MUAC was correlated with BMI, WC, waist-to-hip ratio (WHR), logHOMA-IR, low density lipoprotein cholesterol (LDL-C), uric acid (UA) and high density lipoprotein cholesterol (HDL-C) in all subjects. Multivariate linear regression analysis revealed that MUAC was independently associated with logHOMA-IR (β = 0.036, P<0.001) after adjusting for age, gender, WHR, UA, TG, LDL-C and HDL-C. Binary logistic regression analysis revealed that MUAC was an independent predictor of central obesity (OR: 2.129, 95%CI: 1.311-3.457, P = 0.002). Furthermore, MUAC≥30.9cm for male and ≥30.0cm for female were the optimal cutoff values for identifying central obesity.

conclusionsOur study indicated that among Chinese subjects with type 2 diabetes, MUAC is a simple and effective tool for the determination of central obesity and IR. Additionally, the larger MUAC is proved to be more associated with metabolic risk factors of higher UA and LDL-C and lowever HDL-C.

Indexed as

Body Mass IndexInsulin ResistanceArmBlood GlucoseChinaDiabetes Mellitus, Type 2FemaleHumansIncidenceMaleMiddle AgedObesity, AbdominalRisk FactorsWaist CircumferenceBlood Glucose

Identifiers

PMID32437358
PMCPMC7241705
OpenAlexW3027281179

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.