Evidence map›Paper›PMID 39271702›Full record

ArticleScientific reports2024

Using anthropometric parameters to predict insulin resistance among patients without diabetes mellitus.

Jiajun Liu, Xueshan Jin, Ziyi Feng, Jieming Huang

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

3 citing papers in PubMed.

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4 · The record

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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.

Jiajun Liu *The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Xueshan Jin *The Affiliated Jiangmen TCM Hospital, Jinan University, Jiangmen, Guangdong, China.
Ziyi FengThe First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Jieming HuangThe First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China. 1223912678@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Anthropometric parameters are widely used in the clinical assessment of hypertension, type 2 diabetes, and cardiovascular disease. However, few studies have compared the association between different anthropometric parameters and insulin resistance (IR). This study was aimed at investigating the relationship between 6 indicators, including body mass index (BMI), calf circumference (CC), arm circumference (AC), thigh circumference (TC), waist circumference (WC), waist-height ratio (WHtR), and IR. Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) was used to measure IR. Weighted linear regression was used to assess the relationship between different parameters and IR. The receiver operating characteristic curve (ROC) was employed to compare the strength of the relationship between different anthropometric parameters and IR. A total of 8069 participants were enrolled in our study, including 4873 without IR and 3196 with IR. The weighted linear regression results showed that BMI, CC, AC, TC and WC were significantly correlated with IR, except WHtR. After adjusting for multiple confounding factors, we found that BMI, AC and WC were significantly positively correlated with IR, while TC was significantly negatively correlated with IR. Logistic regression results showed that a larger TC was associated with a decreased risk of IR. In addition, BMI and WC had similar areas under the curve (AUC: 0.780, 95% CI 0.770-0.790; AUC: 0.774, 95% CI 0.763-0.784, respectively), which were higher than TC and AC (AUC: 0.698, 95% CI 0.687-0.710, AUC: 0.746, 95% CI 0.735-0.757, respectively). To our knowledge, this is the first study to report a negative correlation between TC and IR among patients without diabetes mellitus. Therefore, TC may be a new tool to guide public health and a clinical predictor of IR in non-diabetic patients.

Indexed as

AnthropometryBody Mass IndexInsulin ResistanceWaist CircumferenceAdultDiabetes Mellitus, Type 2FemaleHumansMaleMiddle AgedROC CurveWaist-Height RatioAnthropometric parameterArm circumferenceBody mass indexInsulin resistanceNational health and nutrition examination survey (NHANES)Thigh circumferenceWaist circumference

Identifiers

PMID39271702
PMCPMC11399142

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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.