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. 2025 Mar 14:16:1549954.
doi: 10.3389/fendo.2025.1549954. eCollection 2025.

Study on the association between visceral adiposity index and diabetic kidney disease in hospitalized patients with type 2 diabetes mellitus in China

Xin Zhao  1 , Jianbin Sun  1 , Sixu Xin  1 , Xiaomei Zhang  1
Affiliations

Study on the association between visceral adiposity index and diabetic kidney disease in hospitalized patients with type 2 diabetes mellitus in China

Xin Zhao et al. Front Endocrinol (Lausanne). .

Abstract

Objective: This study aims to explore the correlation between visceral adiposity index (VAI) and diabetes kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM), so as to provide a clinical basis for the prevention and treatment of DKD.

Methods: This study retrospectively analyzed 1817 patients with T2DM hospitalized in the department of Endocrinology, Peking University International Hospital from January 2017 to August 2021, including 1053 males and 764 females. According the level of VAI, subjects were divided into three groups.

Results: (1) The results showed that with the increase of VAI level, the proportion of DKD gradually increased, and there was a statistical difference (p < 0.05). With the increase of VAI levels, there is an increasing trend in males, age, WC, BMI, WHtR, WHR, VAI, LAP, ABSI, C-Index, CUN-BAE, SBP, DBP, HbA1c, FBG, PBG, UACR, TG, while HDL-C levels show a decreasing trend (p all <0.05). (2)Logistic regression showed that after adjusting age, sex, diabetic duration, smoking, drinking, BP, blood glucose and blood lipids, high level of VAI was an independent risk factor for DKD (HR=1.38, 95% CI 1.18, 1.63). (3)The model to predict the risk of DKD using anthropometric indicators, showed that the AUC of the models ranked VAI>ABSI>C-index>WHR>AVI=BRI>BMI>CUN-BAE>LAP>WHtR.(4)The predictive ability for DKD of Model 1 with VAI was higher than that of Model 2 with BMI.

Conclusion: The increase of VAI is an independent predictor of DKD occurrence in patients with T2DM, which provides a certain clinical basis for preventing the development of DKD in patients with T2DM.

Keywords: abdominal volume index; body round index; conicity index; diabetic kidney disease; lipid accumulation product; type 2 diabetes mellitus; visceral adiposity index.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The ROC curve results of all anthropometric indicators for DKD prediction (A), and decision curve analysis results of all anthropometric indicators for DKD prediction (B). ROC, receiver operating characteristic; BMI, body mass index; WHR, waist-to-hip ratio; WHtR, waist-to-height ratio; VAI, visceral adipose index; BRI, body roundness index; C-index, Conicity index; AVI, abdominal volume index; ABSI, a body shape index; CUN-BAE, Clínica Universidad de Navarra-Body Adiposity Estimator; LAP, lipid accumulation product; DKD, diabetes kidney disease.
Figure 2
Figure 2
The comparison of the ROC curves (A), and decision curve analysis results (B) of for the risk of DKD with VAI and BMI. ROC, receiver operating characteristic; BMI, body mass index; VAI, visceral adipose index; DKD, diabetes kidney disease.
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References

    1. Wang L, Peng W, Zhao Z, Zhang M, Shi Z, Song Z, et al. . Prevalence and treatment of diabetes in China, 2013-2018. Jama. (2021) 326:2498–506. doi: 10.1001/jama.2021.22208 - DOI - PMC - PubMed
    1. Sun H, Saeedi P, Karuranga S, Pinkepank M, Ogurtsova K, Duncan BB, et al. . IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Res Clin Pract. (2022) 183:109119. doi: 10.1016/j.diabres.2021.109119 - DOI - PMC - PubMed
    1. Zhang J, Fang L, Qiu L, Huang L, Zhu W, Yu Y, et al. . Comparison of the ability to identify arterial stiffness between two new anthropometric indices and classical obesity indices in Chinese adults. Atherosclerosis. (2017) 263:263–71. doi: 10.1016/j.atherosclerosis.2017.06.031 - DOI - PubMed
    1. Li R, Li Q, Cui M, Ying Z, Li L, Zhong T, et al. . Visceral adiposity index, lipid accumulation product and intracranial atherosclerotic stenosis in middle-aged and elderly Chinese. Sci Rep. (2017) 7:7951. doi: 10.1038/s41598-017-07811-7 - DOI - PMC - PubMed
    1. Krakauer NY, Krakauer JC. A new body shape index predicts mortality hazard independently of body mass index. PloS One. (2012) 7:e39504. doi: 10.1371/journal.pone.0039504 - DOI - PMC - PubMed