Volume 22 Issue 3
Mar.  2024
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Article Navigation >  Chinese Journal of General Practice  > 2024  >  22(3): 393-397
GUO Ni, JI Yanmei, MENG Ni, LI Jisheng, HE Xianyu, DAO Mengyao, JIN Xingfang. Study on the predictive value of innovative adipose indexes for metabolic syndrome of Yi people in Yunnan Province[J]. Chinese Journal of General Practice, 2024, 22(3): 393-397. doi: 10.16766/j.cnki.issn.1674-4152.003410
Citation: GUO Ni, JI Yanmei, MENG Ni, LI Jisheng, HE Xianyu, DAO Mengyao, JIN Xingfang. Study on the predictive value of innovative adipose indexes for metabolic syndrome of Yi people in Yunnan Province[J]. Chinese Journal of General Practice, 2024, 22(3): 393-397. doi: 10.16766/j.cnki.issn.1674-4152.003410
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Study on the predictive value of innovative adipose indexes for metabolic syndrome of Yi people in Yunnan Province

doi: 10.16766/j.cnki.issn.1674-4152.003410
  • 1.

    Department of Cardiovascular Medicine, Yan ' an Hospital Affiliated to Kunming Medical University, Kunming, Yunnan 650051, China

Funds:

 202307AB110005

  • Received Date: 2023-10-19
    Available Online: 2024-05-27
    Abstract
  •   Objective  To compare the predictive value of innovative and traditional adiposity indices for metabolic syndrome (MS) risk in the Yi people of Yunnan Province.  Methods  A total of 508 residents from 3 Yi settlements in Yunnan Province were selected by random cluster sampling during November 2018 to September 2023. The traditional adipose indexes of waist circumference, hip circumference, BMI, waist-to-height ratio (WHtR) and related laboratory indexes were collected, and the innovative adipose indexes of China visceral adipose index (CVAI), visceral adipose index (VAI) and lipid accumulation product (LAP) were calculated. Statistical analysis was performed.  Results  The prevalence of metabolic syndrome was 20.01% (102/508) in the in the Yi population of Yunnan Province. Spearman correlation analysis showed that MS was significantly correlated with all adiposity indices. ROC curve analysis showed that the area under the curve of each adipose indexes was greater than 0.7, and the AUC of CVAI was the largest (AUC=0.872). The optimal cut-off values of CVAI, VAI and LAP were 120.20, 2.02 and 56.36, respectively. In different gender and body mass subgroups, the predictive value of the innovative adipose indexes is better than that of the traditional indices. According to the optimal cut-off value of the ROC curve, the groups were defined as C0 (CVAI < 120.20), C1 (CVAI≥120.20), V0 (VAI < 2.02), V1 (VAI≥2.02), L0 (LAP < 56.36) and L1 (LAP≥56.36), Multivariate logistic regression analysis showed that the risk of MS was 8.484 times higher in group C1 than in group C0. The risk of MS was 13.602 times higher in group V1 than in group V0. The risk of MS was 4.916 times higher in group C1 than in group C0.  Conclusion  The innovative adipose index has certain advantages in predicting MS in the Yi population of Yunnan Province, but the traditional index is also valuable when the relevant lipid index is missing. When the innovative adipose indexes exceed the optimal cut-off value, the risk of MS is significantly increased.

     

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