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Chen X, Ding J, Shi Z, Bai K, Shi S, Tian Q. Association of longitudinal trajectories of fasting plasma glucose with all-cause and cardiovascular mortality among a Chinese older population: a retrospective cohort study. BMC Public Health 2024; 24:1335. [PMID: 38760762 PMCID: PMC11102116 DOI: 10.1186/s12889-024-18823-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Accepted: 05/10/2024] [Indexed: 05/19/2024] Open
Abstract
The association between fasting plasma glucose (FPG), an important indicator of overall glycemic status, and the risk of cardiovascular mortality has been well investigated. The longitudinal study can repeatedly collect measured results for the variables to be studied and then consider the potential effects of intraindividual changes in measurement. This study aimed to identify long-term FPG trajectories and investigate the association between trajectory groups and cardiovascular and all-cause mortality. A latent class growth mixture modeling (LCGMM) was used to identify FPG trajectories. Cox proportional hazard models were used to estimate associations between FPG trajectories and the risk of all-cause and cardiovascular mortality. A U-shaped relationship between FPG and all-cause and cardiovascular mortality was observed in the restricted cubic spline regression models. Two FPG longitudinal trajectories of low-level (mean FPG = 5.12mmol/L) and high-level (mean FPG = 6.74mmol/L) were identified by LCGMM. After being adjusted for potential confounders, compared with the low-level category, the hazard ratios (HRs) for all-cause and cardiovascular mortality were 1.23(1.16-1.30) and 1.25(1.16-1.35), respectively, for the high-level group. Long-term FPG trajectories are significantly associated with and potentially impact the risk of all-cause and cardiovascular mortality.
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Affiliation(s)
- Xuejiao Chen
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Jiacheng Ding
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Zhan Shi
- Department of pharmacy, Zhengzhou people's hospital, Zhengzhou, Henan, People's Republic of China
| | - Kaizhi Bai
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Songhe Shi
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Qingfeng Tian
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China.
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Wang Y, Zhang X, Li Y, Gui J, Mei Y, Yang X, Liu H, Guo LL, Li J, Lei Y, Li X, Sun L, Yang L, Yuan T, Wang C, Zhang D, Li J, Liu M, Hua Y, Zhang L. Obesity- and lipid-related indices as a predictor of type 2 diabetes in a national cohort study. Front Endocrinol (Lausanne) 2024; 14:1331739. [PMID: 38356678 PMCID: PMC10864443 DOI: 10.3389/fendo.2023.1331739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 12/26/2023] [Indexed: 02/16/2024] Open
Abstract
Objective Type 2 diabetes mellitus (T2DM) remains a major and widespread public health concern throughout the world. The prevalence of T2DM in the elderly has risen to the top of the list of public health concerns. In this study, obesity- and lipid-related indices were used to predict T2DM in middle-aged and elderly Chinese adults. Methods The data came from the China Health and Retirement Longitudinal Study (CHARLS), including 7902 middle-aged and elderly participants aged 45 years or above. The study assessed the association of obesity- and lipid-related indices and T2DM by measuring 13 indicators, including body mass index (BMI), waist circumference(WC), waist-height ratio (WHtR), conicity index(CI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), a body shape index (ABSI), body roundness index (BRI), triglyceride glucose index (TyG-index) and its correlation index (TyG-BMI, TyG-WC, TyG-WHtR). The association of 13 obesity- and lipid-related indices with T2DM was investigated by binary logistic regression. Additionally, the predictive anthropometric index was evaluated, and the ideal cut-off value was established using the receiver operating characteristic (ROC) curve analysis and area under the curve (AUC). Results The study included 7902 participants, of whom 3638(46.04) and 4264(53.96) were male and female. The prevalence of T2DM in mid-aged and old adults in China was 9.02% in males and 9.15% in females. All the above 13 indicators show a modest predictive power (AUC>0.5), which was significant for predicting T2DM in adults (middle-aged and elderly people) in China (P<0.05). The results revealed that TyG-WHtR [AUC =0.600, 95%CI: 0.566-0.634] in males and in females [AUC =0.664, 95%CI: 0.636-0.691] was the best predictor of T2DM (P<0.05). Conclusion Most obesity- and lipid-related indices have important value in predicting T2DM. Our results can provide measures for the early identification of T2DM in mid-aged and elderly Chinese to reduce the prevalence of T2DM and improve health.
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Affiliation(s)
- Ying Wang
- Department of Graduate School, Wannan Medical College, Wuhu, An Hui, China
| | - Xiaoyun Zhang
- Department of Graduate School, Wannan Medical College, Wuhu, An Hui, China
| | - Yuqing Li
- Department of Graduate School, Wannan Medical College, Wuhu, An Hui, China
| | - Jiaofeng Gui
- Department of Graduate School, Wannan Medical College, Wuhu, An Hui, China
| | - Yujin Mei
- Department of Graduate School, Wannan Medical College, Wuhu, An Hui, China
| | - Xue Yang
- Department of Graduate School, Wannan Medical College, Wuhu, An Hui, China
| | - Haiyang Liu
- Student Health Center, Wannan Medical College, Wuhu, An Hui, China
| | - Lei-lei Guo
- Department of Surgical Nursing, School of Nursing, Jinzhou Medical University, Linghe District, Jinzhou, Liaoning, China
| | - Jinlong Li
- Department of Occupational and Environmental Health, Key Laboratory of Occupational Health and Safety for Coal Industry in Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan, Hebei, China
| | - Yunxiao Lei
- Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Xiaoping Li
- Department of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Lu Sun
- Department of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Liu Yang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Ting Yuan
- Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Congzhi Wang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Dongmei Zhang
- Department of Pediatric Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Jing Li
- Department of Surgical Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu, An Hui, China
| | - Mingming Liu
- Department of Surgical Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu, An Hui, China
| | - Ying Hua
- Rehabilitation Nursing, School of Nursing, Wanna Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu, An Hui, China
| | - Lin Zhang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
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Geng S, Chen X, Bai K, Ding J, Li H, Shi S. Association of the Clínica Universidad de Navarra-Body Adiposity Estimator With Type 2 Diabetes: A Retrospective Cohort Study. Int J Public Health 2023; 68:1606063. [PMID: 37810434 PMCID: PMC10551821 DOI: 10.3389/ijph.2023.1606063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 09/05/2023] [Indexed: 10/10/2023] Open
Abstract
Objectives: Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) is considered to be a more accurate indicator of body fat estimation. We aimed to investigate the association of CUN-BAE with the risk of type 2 diabetes mellitus (T2DM) and to compare the strength of the association between CUN-BAE, body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR) and T2DM. Methods: The data were obtained from the annual health checkup database of residents in Xinzheng, China. From January 2011 to December 2021, 80,555 subjects aged ≥45 years met the inclusion criteria. Cox proportional hazard regression models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for CUN-BAE, BMI, WC, and WHtR in T2DM. Results: During a mean follow-up of 6.26 years, T2DM occurred in 12,967 subjects. The multivariable-adjusted HRs (95% CIs) of T2DM (highest vs. reference group) were 1.994 (1.811-2.196) for CUN-BAE, 1.751 (1.665-1.842) for WC, 1.715 (1.631-1.804) for WHtR, and 1.510 (1.436-1.588) for BMI, respectively. In addition, the risk of T2DM increased with baseline CUN-BAE (HR: 1.374; 95% CI: 1.328, 1.421), WC (HR: 1.236; 95% CI: 1.215, 1.256), WHtR (HR: 1.228; 95% CI: 1.208, 1.248), and BMI (HR: 1.175; 95% CI: 1.156, 1.195). Conclusion: Compared to BMI, WC or WHtR, CUN-BAE may more adequately reflect the adverse effects of adiposity on the risk of T2DM.
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Affiliation(s)
| | | | | | | | | | - Songhe Shi
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
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Optimal body composition indices cutoff values based on all-cause mortality in the elderly. Exp Gerontol 2023; 171:112026. [PMID: 36400117 DOI: 10.1016/j.exger.2022.112026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 10/31/2022] [Accepted: 11/07/2022] [Indexed: 11/16/2022]
Abstract
The cutoffs of body composition indices are inconclusive in older populations. This study is designed toward determining the optimal cutoffs of the body composition indices based on the association with all-cause mortality. During 2009 and 2010, a cohort population of 1200 was enrolled in central western Taiwan. Of the 1200 subjects, 428 older subjects (mean age: 72.5 ± 5.4 yrs.; 47.7 % were women) were censored in this study. The waist circumference (WC) and body mass index (BMI) were measured using standard anthropometric methods. A multi-frequency bioelectrical impedance analysis device was utilized to estimate each participant's body composition indices, including percent body fat (PBF) and skeletal muscle mass index (SMMI). All claims records of death from 2009 to 2018 in the National Health Insurance Research Databank were identified. A receiver operating characteristic curve method and the highest Youden index were used to identify the optimal cutoffs. A Cox proportional hazards regression analysis was used to model associations between each of the recommended cutoff values with all-cause mortality. The all-cause mortality rate was 20.09 % after a follow-up period of 5.86 ± 2.39 person-years. The significant indices cutoff value was identified to be WC (86.7 cm) for older women and BMI (23.8 kg/m2) and as WC (77.6 cm), and SMMI (8.7 kg/m2) for older men. The recommended optimal cutoffs of the body composition indices were gender-specific and can be utilized to predict the risk of all-cause mortality.
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Ding J, Chen X, Shi Z, Bai K, Shi S. Association of body roundness index and its trajectories with all-cause and cardiovascular mortality among a Chinese middle-aged and older population: A retrospective cohort study. Front Public Health 2023; 11:1107158. [PMID: 37033022 PMCID: PMC10076882 DOI: 10.3389/fpubh.2023.1107158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Accepted: 03/08/2023] [Indexed: 04/11/2023] Open
Abstract
Objectives The body roundness index (BRI) is a novel anthropometric index that is a better indicator for predicting fat distribution than the body mass index (BMI). The longitudinal study can repeatedly collect measured results for the variables to be studied and then consider the potential effects of intraindividual changes in measurement. However, few population-based, longitudinal studies of BRI have been conducted, especially among the Chinese population. The study aimed to investigate the association of BRI and its longitudinal trajectories with all-cause and cardiovascular mortality. Methods A total of 71,166 participants with four times BRI measurements between January 2010 and December 2019 were included in this longitudinal study, with a median follow-up was 7.93 years, and 11,538 deaths were recorded, of which 5,892 deaths were due to cardiovascular disease (CVD). A latent class growth mixture modeling (LCGMM) was used to identify BRI trajectories. Cox proportional hazard models were used to estimate associations between BRI trajectories and the risk of all-cause and cardiovascular mortality. Results In the restricted cubic spline regression models, a U-shaped relationship between BRI and all-cause and cardiovascular mortality was observed. Three BRI longitudinal trajectories of low-stable (mean BRI = 2.59), moderate-stable (mean BRI = 3.30), and high-stable (mean BRI = 3.65) were identified by LCGMM. After being adjusted for potential confounders, the HRs for all-cause mortality were 1.18 (1.13-1.24) for the moderate-stable group and 1.74 (1.66-1.82) for the high-stable group compared to the low-stable group. The HRs for cardiovascular mortality were 1.12 (1.05-1.18) for the moderate-stable group and 1.64 (1.53-1.75) for the high-stable group compared to the low-stable group. Conclusion A nonlinear association of BRI with all-cause and cardiovascular mortality was observed, and participants in the higher BRI longitudinal trajectory group were significantly associated with an increased risk of all-cause and cardiovascular mortality.
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Affiliation(s)
- Jiacheng Ding
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Xuejiao Chen
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Zhan Shi
- Department of Pharmacy, Zhengzhou People’s Hospital, Zhengzhou, Henan, China
| | - Kaizhi Bai
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Songhe Shi
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
- *Correspondence: Songhe Shi,
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