Zhiyuan Wu1, Jinqi Wang2, Zhiwei Li3, Ze Han4, Xinlei Miao5, Xiangtong Liu6, Xia Li7, Wei Wang8, Xiuhua Guo9, Lixin Tao10. 1. Beijing Municipal Key Laboratory of Clinical Epidemiology, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Department of Public Health, School of Medical and Health Sciences, Edith Cowan University, Perth, Australia. Electronic address: wuxiaozhi@ccmu.edu.cn. 2. Beijing Municipal Key Laboratory of Clinical Epidemiology, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China. Electronic address: cmuwangjinqi@163.com. 3. Beijing Municipal Key Laboratory of Clinical Epidemiology, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China. Electronic address: 15128472546@163.com. 4. Beijing Municipal Key Laboratory of Clinical Epidemiology, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China. Electronic address: hz18843113362@163.com. 5. Beijing Municipal Key Laboratory of Clinical Epidemiology, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China. Electronic address: miaoxinlei1030@163.com. 6. Beijing Municipal Key Laboratory of Clinical Epidemiology, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China. Electronic address: lxiangtong@163.com. 7. Department of Mathematics and Statistics, La Trobe University, Melbourne, Australia. Electronic address: x.li2@latrobe.edu.au. 8. Department of Public Health, School of Medical and Health Sciences, Edith Cowan University, Perth, Australia. Electronic address: wei.wang@ecu.edu.au. 9. Beijing Municipal Key Laboratory of Clinical Epidemiology, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China. Electronic address: statguo@ccmu.edu.cn. 10. Beijing Municipal Key Laboratory of Clinical Epidemiology, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China. Electronic address: taolixin@ccmu.edu.cn.
Abstract
BACKGROUND AND AIMS: The association of the triglyceride glucose (TyG) index with carotid atherosclerosis has not been reported in longitudinal studies. The present study aimed to investigate whether the TyG index increases the risk of carotid atherosclerosis incidence. METHODS AND RESULTS: This study included data from the Beijing Health Management Cohort (BHMC; n = 6955) and the Beijing Physical Examination Cohort (BPEC; n = 8473). Participants without a history of carotid atherosclerosis who underwent health examination in 2011 or 2012 were annually followed until 2019. The TyG index was denoted as ln [triglycerides (mmol/L)∗fasting glucose (mmol/L)/2]. During a median follow-up of 5.02 years and 5.36 years, 1441 individuals in the BHMC group and 2181 individuals in the BPEC group developed carotid plaque, respectively. The adjusted hazard ratios (HRs) of the continuous TyG index were 1.253 (95% CI, 1.044 to 1.505) and 1.252 (95% CI, 1.091 to 1.437) for the BHMC and BPEC groups, respectively. Individuals in the highest quartile of the TyG index were associated with an increased risk of carotid plaque compared with those in the lowest quartile (BHMC: HR, 1.366; 95% CI, 1.101 to 1.695, P for trend = 0.010; BPEC: HR, 1.379; 95% CI, 1.196 to 1.591, P for trend = 0.013). CONCLUSION: These findings suggested that a higher TyG index increases the risk of carotid atherosclerosis incidence in the general population.
BACKGROUND AND AIMS: The association of the triglycerideglucose (TyG) index with carotid atherosclerosis has not been reported in longitudinal studies. The present study aimed to investigate whether the TyG index increases the risk of carotid atherosclerosis incidence. METHODS AND RESULTS: This study included data from the Beijing Health Management Cohort (BHMC; n = 6955) and the Beijing Physical Examination Cohort (BPEC; n = 8473). Participants without a history of carotid atherosclerosis who underwent health examination in 2011 or 2012 were annually followed until 2019. The TyG index was denoted as ln [triglycerides (mmol/L)∗fasting glucose (mmol/L)/2]. During a median follow-up of 5.02 years and 5.36 years, 1441 individuals in the BHMC group and 2181 individuals in the BPEC group developed carotid plaque, respectively. The adjusted hazard ratios (HRs) of the continuous TyG index were 1.253 (95% CI, 1.044 to 1.505) and 1.252 (95% CI, 1.091 to 1.437) for the BHMC and BPEC groups, respectively. Individuals in the highest quartile of the TyG index were associated with an increased risk of carotid plaque compared with those in the lowest quartile (BHMC: HR, 1.366; 95% CI, 1.101 to 1.695, P for trend = 0.010; BPEC: HR, 1.379; 95% CI, 1.196 to 1.591, P for trend = 0.013). CONCLUSION: These findings suggested that a higher TyG index increases the risk of carotid atherosclerosis incidence in the general population.