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

Author:

Liu Jiajun1,Jin Xueshan2,Feng Ziyi1,Huang Jieming1

Affiliation:

1. The First Affiliated Hospital of Guangzhou University of Chinese Medicine

2. Jinan University

Abstract

Abstract Background: 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. Methods: 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. Results: A total of 8,069 participants were enrolled in our study, including 4,873 without IR and 3,196 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). Conclusions: 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.

Publisher

Research Square Platform LLC

Reference29 articles.

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