Biomarker-based visceral adiposity score and incident type 2 diabetes in the multiethnic cohort

Maskarinec, Gertraud; Raquinio, Phyllis; Setiawan, Veronica Wendy; Ernst, Thomas; Franke, Adrian A.; Buchthal, Steven; Shepherd, John; Wilkens, Lynne R.; Lim, Unhee; Marchand, Loı̈c Le

doi:10.1016/j.annepidem.2021.07.002

Cited by 2 publications

(1 citation statement)

References 31 publications

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“… 9 Studies have shown that evaluation of visceral adipose tissue is critical in determining the risk of developing type 2 diabetes. 10 The methods to detect visceral adipose tissue include computed tomography (CT), and magnetic resonance imaging (MRI), 11 which can distinguish between various types of body fat distribution, particularly subcutaneous and visceral adipose tissue. However, they are not practical for routine clinical practices in a general population on account of the radiation exposure, time requirements and high costs.…”

Section: Introductionmentioning

confidence: 99%

Correlation Between the Variability of Different Obesity Indices and Diabetic Kidney Disease: A Retrospective Cohort Study Based on Populations in Taiwan

Sun,

Wang,

Yun

et al. 2023

DMSO

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Purpose To investigate the association of five obesity indices and the variability of these indices with diabetic kidney disease (DKD) in patients with type 2 diabetes and compare the predictive validity of these markers for the risk of DKD in this large longitudinal cohort study. Patients and Methods A total of 2659 patients with type 2 diabetes who did not have DKD were enrolled between 2006 and 2019 at Lee’s United Clinic in Taiwan. Data were collected for each subject, including demographic data, personal medical history, clinical parameters and calculated Body mass index (BMI), visceral adiposity index (VAI), lipid accumulation product (LAP), body roundness index (BRI) and variability of five obesity indices. Cox regression analysis was performed to determine the relationship between different obesity indicators and DKD risk. Cox’s proportional hazards model was evaluated the predictive effect of obesity indices on DKD. Results The risk of developing DKD increased with an increase in the BRI, LAP, VAI, WC and BMI (all P trend<0.05), and the variability of VAI was significantly associated with DKD [HR=1.132, 95% CI (1.001, 1.281)] after adjusting for corresponding variables. BRI had the strongest predictive effect on DKD. BRI had the best predictive performance, with AUC of 0.807, 0.663 and 0.673 at 1, 3 and 5 years, respectively. Cox regression analysis of risk factors for DKD in patients stratified by BRI quartiles showed that patients in the Q4 group had the highest risk of developing DKD [HR=1.356, 95% CI (1.131, 1.626)]. Conclusion BMI, WC, VAI, LAP, BRI and VAI variability were associated with a significant increase in the risk of DKD events, and BRI was superior and alternative obesity index for predicting DKD.

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Section: Introductionmentioning

confidence: 99%

Correlation Between the Variability of Different Obesity Indices and Diabetic Kidney Disease: A Retrospective Cohort Study Based on Populations in Taiwan

Sun,

Wang,

Yun

et al. 2023

DMSO

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Association Between Visceral Obesity Index and Diabetes: A Systematic Review and Meta-analysis

Deng,

Chen,

Zhang

et al. 2024

The Journal of Clinical Endocrinology &Amp; Metabolism

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Content The correlation between visceral obesity index (VAI) and diabetes and accuracy of early prediction of diabetes are still controversial. Objective This study aims to review the relationship between high level of VAI and diabetes, and early predictive value of diabetes. Data Sources The databases of PubMed, Cochrane, Embase, and Web of Science were searched until October 17, 2023. Study Selection After adjusting for confounding factors, the original study on the association between VAI and diabetes was analyzed. Data Extraction We extracted odds ratio (OR) between VAI and diabetes management after controlling for mixed factors, and the sensitivity, specificity and diagnostic four grid table for early prediction of diabetes. Data Synthesis 53 studies, comprising 595,946 participants were included. The findings of the meta-analysis elucidated that in cohort studies, a high VAI significantly increased the risk of diabetes mellitus in males (OR = 2.83 (95% CI: 2.30-3.49)) and females (OR = 3.32 (95% CI: 2.48-4.45)). The ROC, sensitivity, and specificity of VAI for early prediction of diabetes in males were 0.64 (95% CI: 0.62-0.66), 0.57 (95% CI: 0.53-0.61), and 0.65 (95% CI: 0.61-0.69), respectively, and 0.67 (95% CI: 0.65-0.69), 0.66 (95% CI: 0.60-0.71), and 0.61 (95% CI: 0.57-0.66) in females, respectively. Conclusions VAI is an independent predictor of the risk of diabetes, yet its predictive accuracy remains limited. In future studies, determine whether VAI can be utilized in conjunction with other related indicators to early predict the risk of diabetes, to enhance the accuracy of prediction of the risk of diabetes.

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Biomarker-based visceral adiposity score and incident type 2 diabetes in the multiethnic cohort

Cited by 2 publications

References 31 publications

Correlation Between the Variability of Different Obesity Indices and Diabetic Kidney Disease: A Retrospective Cohort Study Based on Populations in Taiwan

Correlation Between the Variability of Different Obesity Indices and Diabetic Kidney Disease: A Retrospective Cohort Study Based on Populations in Taiwan

Association Between Visceral Obesity Index and Diabetes: A Systematic Review and Meta-analysis

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