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Hu LK, Liu YH, Yang K, Chen N, Ma LL, Yan YX. Association between hypertriglyceridemic-waist phenotype and circadian syndrome risk: a longitudinal cohort study. Hormones (Athens) 2023; 22:457-466. [PMID: 37423976 DOI: 10.1007/s42000-023-00462-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 06/22/2023] [Indexed: 07/11/2023]
Abstract
Recently, circadian syndrome (CircS) has been proposed as a new predictor of cardiometabolic risk. We aimed to investigate the relationship between the hypertriglyceridemic-waist phenotype and its dynamic status with CircS in China. We conducted a two-stage study based on the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2015. Multivariate logistic regression models in cross-sectional analysis and Cox proportional hazards regression models in longitudinal analysis were used to estimate the associations of hypertriglyceridemic-waist phenotypes with CircS and its components. We then applied multiple logistic regression analysis to evaluate the odds ratios (ORs) and 95% confidence intervals (CIs) for CircS risk by transformation into the hypertriglyceridemic-waist phenotype. A total of 9863 participants were included in the cross-sectional analysis and 3884 participants in the longitudinal analysis. Compared with normal waist circumference (WC) and normal triglyceride (TG) level (NWNT), CircS risk was increased with enlarged WC and high TG level (EWHT) (hazard ratio (HR) 3.87 [95% CI: 2.38, 5.39]). Similar results were observed in subgroup analyses by sex, age, smoking status, and drinking status. During follow-up, CircS risk was increased in group K (stable EWNT during follow-up) (OR 9.97 [95% CI: 6.41, 15.49]) compared with group A (stable NWNT during follow-up), while group L (baseline enlarged WC and normal TG level transformed to follow-up EWHT) had the highest risk of CircS (OR 116.07 [95% CI: 72.77, 185.14]). In conclusion, the hypertriglyceridemic-waist phenotype and its dynamic status were associated with the risk of developing CircS in Chinese adults.
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Affiliation(s)
- Li-Kun Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, No. 10 Xitoutiao, You'anmenWai, Fengtai District, Beijing, 100069, China
| | - Yu-Hong Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, No. 10 Xitoutiao, You'anmenWai, Fengtai District, Beijing, 100069, China
| | - Kun Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, No. 10 Xitoutiao, You'anmenWai, Fengtai District, Beijing, 100069, China
| | - Ning Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, No. 10 Xitoutiao, You'anmenWai, Fengtai District, Beijing, 100069, China
| | - Lin-Lin Ma
- Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, No. 10 Xitoutiao, You'anmenWai, Fengtai District, Beijing, 100069, China
| | - Yu-Xiang Yan
- Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, No. 10 Xitoutiao, You'anmenWai, Fengtai District, Beijing, 100069, China.
- Municipal Key Laboratory of Clinical Epidemiology, Beijing, 100069, China.
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Qie R, Li Q, Zhao Y, Han M, Liu D, Guo C, Zhou Q, Tian G, Huang S, Wu X, Zhang Y, Qin P, Li H, Wang J, Cheng R, Lin J, Sun X, Wu Y, Li Y, Yang X, Zhao Y, Feng Y, Zhang M, Hu D. Association of hypertriglyceridemic waist-to-height ratio and its dynamic status with risk of type 2 diabetes mellitus: The Rural Chinese Cohort Study. Diabetes Res Clin Pract 2021; 179:108997. [PMID: 34371063 DOI: 10.1016/j.diabres.2021.108997] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Revised: 05/25/2021] [Accepted: 08/04/2021] [Indexed: 11/29/2022]
Abstract
AIMS To evaluate the risk of type 2 diabetes mellitus (T2DM) in a prospective study with hypertriglyceridemic waist-to-height ratio (HWHtR) and its dynamic status. METHODS We collected data for 12,248 participants ≥18 years in this study. Cox's proportional-hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for T2DM risk by baseline HWHtR. Multiple logistic regression analysis was used to estimate odds ratios (ORs) and 95% CIs for T2DM risk by transformation in HWHtR. RESULTS We identified 839 T2DM cases during a median follow-up of 5.92 years. Compared with normal TG level and normal WHtR, T2DM risk was increased with high TG level and high WHtR (aHR 2.04, 95% CI 1.49-2.79). Similar results were observed in subgroup analyses by sex and age. During follow-up, T2DM risk was increased with stable high TG level and high WHtR (aOR 4.45, 95% CI 2.76-7.17) compared with stable normal TG level and normal WHtR. The results above were robust in sensitivity analyses. CONCLUSIONS HWHtR phenotype and its dynamic status were associated with risk of T2DM. Our study suggests that primary prevention and avoiding the appearance of the HWHtR phenotype in the rural Chinese population may reduce the T2DM risk.
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Affiliation(s)
- Ranran Qie
- Department of Endocrinology, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, PR China.; Study Team of Shenzhen's Sanming Project, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Quanman Li
- Department of Endocrinology, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, PR China.; Study Team of Shenzhen's Sanming Project, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Yang Zhao
- Study Team of Shenzhen's Sanming Project, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Minghui Han
- Study Team of Shenzhen's Sanming Project, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Dechen Liu
- Study Team of Shenzhen's Sanming Project, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Chunmei Guo
- Study Team of Shenzhen's Sanming Project, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Qionggui Zhou
- School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Gang Tian
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Shengbing Huang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Xiaoyan Wu
- School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Yanyan Zhang
- School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Pei Qin
- School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Honghui Li
- Study Team of Shenzhen's Sanming Project, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Jian Wang
- Study Team of Shenzhen's Sanming Project, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Ruirong Cheng
- Study Team of Shenzhen's Sanming Project, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Jinchun Lin
- Study Team of Shenzhen's Sanming Project, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Xizhuo Sun
- Study Team of Shenzhen's Sanming Project, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Yuying Wu
- School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Yang Li
- School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Xingjin Yang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Yang Zhao
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Yifei Feng
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Ming Zhang
- School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Dongsheng Hu
- Department of Endocrinology, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, PR China.; Study Team of Shenzhen's Sanming Project, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China.
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