Evaluation of the Association between Obesity Markers and Type 2 Diabetes: A Cohort Study Based on a Physical Examination Population

Purpose. To evaluate the predictive effect of different obesity markers on the risk of developing type 2 diabetes in a population of healthy individuals who underwent physical examination and to provide a reference for the early detection of individuals at risk of diabetes. Methods. This retrospecti...

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Bibliographic Details
Published in:Journal of diabetes research 2021-12, Vol.2021, p.6503339-8
Main Authors: Yang, Tengfei, Zhao, Bo, Pei, Dongmei
Format: Article
Language:English
Subjects:
Adult
Alcohol
Area Under Curve
Biomarkers - analysis
Biomarkers - blood
Biomarkers - metabolism
Blood pressure
Body Mass Index
Cohort analysis
Cohort Studies
Diabetes
Diabetes Mellitus, Type 2 - blood
Female
Humans
Lipids
Male
Middle Aged
Obesity
Obesity - blood
Physical Examination
Physical examinations
Proportional Hazards Models
Retrospective Studies
Risk Factors
ROC Curve
Triglycerides
Variables
Waist Circumference
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Summary:Purpose. To evaluate the predictive effect of different obesity markers on the risk of developing type 2 diabetes in a population of healthy individuals who underwent physical examination and to provide a reference for the early detection of individuals at risk of diabetes. Methods. This retrospective cohort study included 15206 healthy subjects who underwent a physical examination (8307 men and 6899 women). Information on the study population was obtained from the Dryad Digital Repository. Cox proportional risk models were used to calculate the hazard ratio (HR) and 95% confidence interval (CI) of different obesity markers, including the lipid accumulation index (LAP), body mass index (BMI), waist-to-height ratio (WHtR), visceral adiposity index (VAI), and body roundness index (BRI) on the development of type 2 diabetes. The effectiveness of each obesity marker in predicting the risk of developing type 2 diabetes was analyzed using the receiver operating characteristic curve (ROC curve) and the area under the curve (AUC). Results. After a mean follow-up of 5.4 years, there were 372 new cases of type 2 diabetes. After correcting for confounding factors such as age, sex, smoking, alcohol consumption, exercise, and blood pressure, Cox proportional risk model analysis showed that elevations in BMI, LAP, WHtR, VAI, and BRI increased the risk of developing type 2 diabetes. The ROC curve results showed that LAP was the best predictor of the risk of developing diabetes, with an AUC (95% CI) of 0.759 (0.752–0.766), an optimal cutoff value of 16.04, a sensitivity of 0.72, and a specificity of 0.69. Conclusion. An increase in the BMI, LAP, WHtR, VAI, and BRI can increase the risk of developing type 2 diabetes, with LAP being the best predictor of this risk.
ISSN:2314-6745
2314-6753
DOI:10.1155/2021/6503339