Association Between Insulin Resistance and Cardiovascular Disease Risk Varies According to Glucose Tolerance Status: A Nationwide Prospective Cohort Study.
Abstract | OBJECTIVE: RESEARCH DESIGN AND METHODS: We analyzed a nationwide sample of 111,576 adults without CVD at baseline, using data from the China Cardiometabolic Disease and Cancer Cohort Study. Insulin resistance was estimated by sex-specific HOMA of insulin resistance (HOMA-IR) quartiles for participants with normal glucose tolerance, prediabetes, or diabetes, separately, and by 1 SD of HOMA-IR for the overall study participants. We used Cox proportional hazards models to examine the association between insulin resistance and incident CVD according to glucose tolerance status and evaluate the CVD risk associated with the combined categories of insulin resistance and obesity in prediabetes and diabetes, as compared with normal glucose tolerance. Models were adjusted for age, sex, education attainment, alcohol drinking, smoking, physical activity, and diet quality. RESULTS: In participants with normal glucose tolerance, prediabetes, and diabetes defined by three glucose parameters, multivariable-adjusted hazard ratios (95% CIs) for incident CVD associated with the highest versus the lowest quartile of HOMA-IR were 1.03 (0.82-1.30), 1.23 (1.07-1.42), and 1.61 (1.30-2.00), respectively; the corresponding values for CVD per 1-SD increase in HOMA-IR were 1.04 (0.92-1.18), 1.12 (1.06-1.18), and 1.15 (1.09-1.21), respectively (P for interaction = 0.011). Compared with participants with normal glucose tolerance, in participants with prediabetes, the combination of the highest HOMA-IR quartile and obesity showed 17% (95% CI 2-34%) higher risk of CVD, while the combination of the lowest two HOMA-IR quartiles and nonobesity showed 15-17% lower risk of CVD. In participants with diabetes, the upper two HOMA-IR quartiles exhibited 44-77% higher risk of CVD, regardless of obesity status. Consistent findings were observed for glucose tolerance status defined by different combinations of glycemic parameters. CONCLUSIONS:
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Authors | Tiange Wang, Mian Li, Tianshu Zeng, Ruying Hu, Yu Xu, Min Xu, Zhiyun Zhao, Yuhong Chen, Shuangyuan Wang, Hong Lin, Xuefeng Yu, Gang Chen, Qing Su, Yiming Mu, Lulu Chen, Xulei Tang, Li Yan, Guijun Qin, Qin Wan, Zhengnan Gao, Guixia Wang, Feixia Shen, Zuojie Luo, Yingfen Qin, Li Chen, Yanan Huo, Qiang Li, Zhen Ye, Yinfei Zhang, Chao Liu, Youmin Wang, Shengli Wu, Tao Yang, Huacong Deng, Jiajun Zhao, Lixin Shi, Guang Ning, Yufang Bi, Weiqing Wang, Jieli Lu |
Journal | Diabetes care
(Diabetes Care)
Vol. 45
Issue 8
Pg. 1863-1872
(08 01 2022)
ISSN: 1935-5548 [Electronic] United States |
PMID | 35700159
(Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
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Copyright | © 2022 by the American Diabetes Association. |
Chemical References |
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Topics |
- Adult
- Blood Glucose
- Cardiovascular Diseases
(complications, etiology)
- Cohort Studies
- Diabetes Mellitus
- Female
- Humans
- Insulin Resistance
- Male
- Obesity
(complications, epidemiology)
- Prediabetic State
(complications, epidemiology)
- Prospective Studies
- Risk Factors
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