Journal of diabetes investigation · 2025
Anthropometric and lipid indices in relation to prediabetes and diabetes: A cross-sectional study in resource-limited areas of northwestern China.
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Ma Ling, Cheng Yin, Wu Lanqiqi, Shi Hongjuan, Liu Yining, Ma Jinyu, Tong Huitian, Shi Chao
Аннотация
AIMS: This cross-sectional study was conducted to assess the association of triglyceridemic-waist phenotype, waist-to-height ratio (WHtR), lipid accumulation product (LAP), visceral adiposity index (VAI), and triglyceride-glucose (TyG) index with prediabetes and diabetes (PAD) using data from the Ningxia Cardiovascular Disorders and Related Risk Factors Survey.
MATERIALS AND METHODS: This study included 10,803 patients. Logistic regression analysis and restricted cubic splines were applied to identify the association between the PAD and each index. The receiver operating characteristic curve was analyzed to identify and compare the discriminative power of different indexes in identifying PAD.
RESULTS: A total of 43.87% patients were diagnosed with prediabetes and 11.75% patients were diagnosed with diabetes. After adjusting for confounders, participants with elevated high triglyceride levels with increased waist circumference (HTGW) were associated with a 2.65-fold (odds ratio [OR] 2.65, 95% confidence interval [95% CI] 2.31-3.03) risk of PAD. Comparing with the lowest quartile, those in the highest quartile of WHtR, LAP, VAI, and TyG index had a significantly increased risk of developing PAD. TyG index (area under the curve [AUC] 0.71, 95% CI 0.70-0.72) was better than WHtR (AUC 0.66, 95% CI 0.65-0.67), LAP (AUC 0.68, 95% CI 0.67-0.69), and VAI (AUC 0.65, 95% CI 0.64-0.66) at predicting the risk of PAD.
CONCLUSIONS: The HTGW and elevated WHtR, LAP, VAI, and TyG index are associated with a greater risk of PAD. The TyG index is a more favorable anthropometric measure for predicting PAD, but its clinical utility needs to be validated in prospective cohorts, especially in resource-limited areas.
MATERIALS AND METHODS: This study included 10,803 patients. Logistic regression analysis and restricted cubic splines were applied to identify the association between the PAD and each index. The receiver operating characteristic curve was analyzed to identify and compare the discriminative power of different indexes in identifying PAD.
RESULTS: A total of 43.87% patients were diagnosed with prediabetes and 11.75% patients were diagnosed with diabetes. After adjusting for confounders, participants with elevated high triglyceride levels with increased waist circumference (HTGW) were associated with a 2.65-fold (odds ratio [OR] 2.65, 95% confidence interval [95% CI] 2.31-3.03) risk of PAD. Comparing with the lowest quartile, those in the highest quartile of WHtR, LAP, VAI, and TyG index had a significantly increased risk of developing PAD. TyG index (area under the curve [AUC] 0.71, 95% CI 0.70-0.72) was better than WHtR (AUC 0.66, 95% CI 0.65-0.67), LAP (AUC 0.68, 95% CI 0.67-0.69), and VAI (AUC 0.65, 95% CI 0.64-0.66) at predicting the risk of PAD.
CONCLUSIONS: The HTGW and elevated WHtR, LAP, VAI, and TyG index are associated with a greater risk of PAD. The TyG index is a more favorable anthropometric measure for predicting PAD, but its clinical utility needs to be validated in prospective cohorts, especially in resource-limited areas.