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

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.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2024-09-13
DOI
https://doi.org/10.1038/s41598-024-57020-2
Citations
4
Primary Topic
Diabetes, Cardiovascular Risks, and Lipoproteins
Type
article
Field-Weighted Citation Impact
1.43
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Xueshan Jin, Jieming Huang, Ziyi Feng, Jiajun Liu
4 citations
Scientific Reports
Diabetes, Cardiovascular Risks, and Lipoproteins
1.43
article

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

Xueshan Jin, Jieming Huang, Ziyi Feng, Jiajun Liu
article en
4 citations

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.

Scientific ReportsVol. 14(1)
Guangzhou University of Chinese Medicine (CN), First Affiliated Hospital of Guangzhou University of Chinese Medicine (CN), Jiangmen Wuyi Traditional Chinese Medicine Hospital (CN), Jiangmen Central Hospital (CN)
Zero hunger
Openalex Percentile: Top 16%
Diabetes, Cardiovascular Risks, and Lipoproteins
1.43
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.