1
|
Mo Z, Han Y, Cao C, Huang Q, Hu Y, Yu Z, Hu H. Association between non-high-density lipoprotein to high-density lipoprotein ratio and reversion to normoglycemia in people with impaired fasting glucose: a 5-year retrospective cohort study. Diabetol Metab Syndr 2023; 15:259. [PMID: 38105214 PMCID: PMC10726583 DOI: 10.1186/s13098-023-01237-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 11/29/2023] [Indexed: 12/19/2023] Open
Abstract
OBJECTIVE The relationship between the non-high-density lipoprotein to high-density lipoprotein ratio (non-HDL-c/HDL-c ratio) and changes in glycemic status as well as the development of type 2 diabetes mellitus (T2DM) has been well established. However, there is a lack of evidence concerning the association between the non-HDL-c/HDL-c ratio and the reversal of normoglycemia in individuals with impaired fasting glucose (IFG). Therefore, this study aimed to examine the connection between the non-HDL-c/HDL-c ratio and the likelihood of reverting to normoglycemia among people with IFG. METHODS This retrospective cohort study examined data collected from 15,524 non-selective participants with IFG at the Rich Healthcare Group in China between January 2010 and 2016. The Cox proportional-hazards regression model was used to investigate the connection between the baseline non-HDL-c/HDL-c ratio and the probability of reverting to normoglycemia. We were able to discover the non-linear association between the non-HDL-c/HDL-c ratio and reversion to normoglycemia using a Cox proportional hazards regression model with cubical spline smoothing. We also performed several sensitivity and subgroup analyses. A competing risk multivariate Cox regression was utilized as well to examine the development to diabetes as a competing risk for the reversal of normoglycemic events. RESULTS In our study, a total of 15,524 individuals participated, with a mean age of 50.9 ± 13.5 years, and 64.7% were male. The average baseline non-HDL-c/HDL-c ratio was 2.9 ± 0.9. Over a median follow-up period of 2.9 years, we observed a reversion rate to normoglycemia of 41.8%. After adjusting for covariates, our findings revealed a negative association between the non-HDL-c/HDL-c ratio and the likelihood of reverting to normoglycemia (HR = 0.71, 95% CI 0.69-0.74). Notably, we identified a non-linear relationship between the non-HDL-c/HDL-c ratio and the probability of transitioning from IFG to normoglycemia. We found an inflection point at a non-HDL-c/HDL-c ratio of 3.1, with HRs of 0.63 (95% CI 0.69, 0.74) on the left side and 0.78 (95% CI 0.74, 0.83) on the right side of the point. Competing risks multivariate Cox's regression, sensitivity analysis, and subgroup analysis consistently supported our robust results. CONCLUSION Our study has revealed a negative and non-linear relationship between the non-HDL-c/HDL-c ratio and reversion to normoglycemia in Chinese people with IFG. Specifically, when the non-HDL-c/HDL-c ratio was below 3.1, a significant and negative association with reversion to normoglycemia was observed. Furthermore, keeping the non-HDL-c/HDL-c ratio below 3.1 significantly elevated the probability of returning to normoglycemia.
Collapse
Affiliation(s)
- Zihe Mo
- Department of Physical Examination, Dongguan Tungwah Hospital, No. 1 Dongcheng Road, Dongcheng Street, Dongguan, 523000, Guangdong, China
| | - Yong Han
- Department of Emergency, Shenzhen Second People's Hospital, Shenzhen, 518000, Guangdong, China
- Department of Emergency, The First Affiliated Hospital of Shenzhen University, Shenzhen, 518000, Guangdong, China
| | - Changchun Cao
- Department of Rehabilitation, Shenzhen Dapeng New District Nan'ao People's Hospital, Shenzhen, 518000, Guangdong, China
| | - Qingli Huang
- Department of Physical Examination, Dongguan Tungwah Hospital, No. 1 Dongcheng Road, Dongcheng Street, Dongguan, 523000, Guangdong, China
| | - Yanhua Hu
- College of Information Science and Engineering, Liuzhou Institute of Technology, No. 99, Xinliu Avenue, Yufeng District, Liuzhou, 545616, Guangxi Zhuang Autonomous Region, China.
| | - Zhiqun Yu
- Department of Physical Examination, Dongguan Tungwah Hospital, No. 1 Dongcheng Road, Dongcheng Street, Dongguan, 523000, Guangdong, China.
| | - Haofei Hu
- Department of Nephrology, Shenzhen Second People's Hospital, No.3002 Sungang Road, Futian District, Shenzhen, 518000, Guangdong, China.
- Department of Nephrology, The First Affiliated Hospital of Shenzhen University, Shenzhen, 518000, Guangdong, China.
| |
Collapse
|
2
|
Wu Y, Wei Q, Li H, Yang H, Wu Y, Yu Y, Chen Q, He B, Chen F. Association of remnant cholesterol with hypertension, type 2 diabetes, and their coexistence: the mediating role of inflammation-related indicators. Lipids Health Dis 2023; 22:158. [PMID: 37752554 PMCID: PMC10521406 DOI: 10.1186/s12944-023-01915-y] [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: 07/25/2023] [Accepted: 09/03/2023] [Indexed: 09/28/2023] Open
Abstract
PURPOSE Cholesterol metabolism is a risk factor for cardiovascular disease, and recent studies have shown that cholesterol metabolism poses a residual risk of cardiovascular disease even when conventional lipid risk factors are in the optimal range. The association between remnant cholesterol (RC) and cardiovascular disease has been demonstrated; however, its association with hypertension, type 2 diabetes mellitus (T2DM), and the concomitance of the two diseases requires further study. This study aimed to evaluate the association of RC with hypertension, T2DM, and both in a large sample of the U.S. population, and to further explore the potential mechanisms involved. METHODS This cross-sectional study used data from the 2005-2018 cycles of the National Health and Nutrition Examination Survey (N = 17,749). Univariable and multivariable logistic regression analyses were performed to explore the relationships of RC with hypertension, T2DM, and both comorbidities. A restricted cubic spline regression model was used to reveal the dose effect. Mediation analyses were performed to explore the potential mediating roles of inflammation-related indicators in these associations. RESULTS Of the 17,749 participants included (mean [SD] age: 41.57 [0.23] years; women: 8983 (50.6%), men: 8766 (49.4%)), the prevalence of hypertension, T2DM, and their co-occurrence was 32.6%, 16.1%, and 11.0%, respectively. Higher RC concentrations were associated with an increased risk of hypertension, T2DM, and their co-occurrence (adjusted odds ratios for per unit increase in RC were 1.068, 2.259, and 2.362, and 95% confidence intervals were 1.063-1.073, 1.797-2.838, and 1.834-3.041, respectively), with a linear dose-response relationship. Even when conventional lipids were present at normal levels, positive associations were observed. Inflammation-related indicators (leukocytes, lymphocytes, monocytes, and neutrophils) partially mediated these associations. Among these, leukocytes had the greatest mediating effect (10.8%, 14.5%, and 14.0%, respectively). CONCLUSION The results of this study provide evidence that RC is associated with the risk of hypertension, T2DM, and their co-occurrence, possibly mediated by an inflammatory response.
Collapse
Affiliation(s)
- Yuxuan Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Qinfei Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Husheng Li
- Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Han Yang
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Yuying Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Yiming Yu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Qiansi Chen
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Baochang He
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Fa Chen
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China.
- Clinical Research Unit, The Second Affiliated Hospital, Fujian Medical University, Quanzhou, China.
| |
Collapse
|
3
|
Gao Y, Hu Y, Xiang L. Remnant cholesterol, but not other cholesterol parameters, is associated with gestational diabetes mellitus in pregnant women: a prospective cohort study. J Transl Med 2023; 21:531. [PMID: 37544989 PMCID: PMC10405385 DOI: 10.1186/s12967-023-04322-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 07/01/2023] [Indexed: 08/08/2023] Open
Abstract
OBJECTIVE No evidence has been found of a relationship between remnant cholesterol (RC) and the likelihood of gestational diabetes mellitus (GDM) in pregnant women. The aim of our study was to investigate the link between serum RC at 12-14 weeks of gestation and the risk of GDM. METHODS This was a secondary analysis with data from a prospective cohort study in Korea. A total of 590 single pregnant women attending two hospitals in Korea, up to 14 weeks gestation, from November 2014 to July 2016 were included in the study. The formula used to calculate RC in detail was RC (mg/dL) = TC (mg/dL)-HDL-c (mg/dL)-LDL-c (mg/dL). Logistic regression models were employed to examine the relationship between RC and GDM and explore the association between other lipoprotein cholesterol parameters and the risk of GDM. Furthermore, receiver operating characteristic (ROC) analysis was performed to assess the ability of RC to identify GDM. Additionally, sensitivity and subgroup analyses were conducted. RESULTS The mean age of participants was 32.06 ± 3.80 years. The median of RC was 34.66 mg/dL. 37 pregnant women (6.27%) were eventually diagnosed with GDM. Multivariate adjusted logistic regression analysis showed that RC was positively associated with the risk of GDM (OR = 1.458, 95% CI 1.221, 1.741). There was no significant association between other lipoprotein cholesterols (including TC, LDL-c, HDL-c) and the risk of GDM. The area under the ROC curve for RC as a predictor of GDM was 0.8038 (95% CI 0.7338-0.8738), and the optimal RC cut-off was 24.30 mg/dL. Our findings were demonstrated to be robust by performing a series of sensitivity analyses. CONCLUSION Serum RC levels at 12-14 weeks of gestation are positively associated with GDM risk in pregnant women. RC in early pregnancy is an early warning indicator of GDM in pregnant women, especially those with normal HDL-c, LDL-c, and TC that are easily overlooked. There is a high risk of developing GDM in pregnant women whose RC is more than 24.30 mg/dL. This study may help optimize GDM prevention in pregnant women and facilitate communication between physicians, pregnant patients, and their families.
Collapse
Affiliation(s)
- Yajing Gao
- Department of Anesthesiology, Affiliated Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, 518028, China
| | - Yanhua Hu
- College of Information Science and Engineering, Liuzhou Institute of Technology, No. 99, Xinliu Avenue, Yufeng District, Liuzhou, 545616, Guangxi Zhuang Autonomous Region, China.
| | - Lan Xiang
- School of Medical Technology and Nursing, Shenzhen Polytechnic, No.113, Tongfa Road 113, Nanshan District, Shenzhen, 518055, Guangdong, China.
| |
Collapse
|
4
|
Zhou Y, Yang G, Qu C, Chen J, Qian Y, Yuan L, Mao T, Xu Y, Li X, Zhen S, Liu S. Predictive performance of lipid parameters in identifying undiagnosed diabetes and prediabetes: a cross-sectional study in eastern China. BMC Endocr Disord 2022; 22:76. [PMID: 35331213 PMCID: PMC8952267 DOI: 10.1186/s12902-022-00984-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 03/08/2022] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Dyslipidaemia is a risk factor for abnormal blood glucose. However, studies on the predictive values of lipid markers in prediabetes and diabetes simultaneously are limited. This study aimed to assess the associations and predictive abilities of lipid indices and abnormal blood glucose. METHODS A sample of 7667 participants without diabetes were enrolled in this cross-sectional study conducted in 2016, and all of them were classified as having normal glucose tolerance (NGT), prediabetes or diabetes. Blood glucose, blood pressure and lipid parameters (triglycerides, TG; total cholesterol, TC; high-density lipoprotein cholesterol, HDL-C; low-density lipoprotein cholesterol, LDL-C; non-high-density lipoprotein cholesterol, non-HDL-C; and triglyceride glucose index, TyG) were evaluated or calculated. Logistic regression models were used to analyse the association between lipids and abnormal blood glucose. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to assess the discriminatory power of lipid parameters for detecting prediabetes or diabetes. RESULTS After adjustment for potential confounding factors, the TyG was the strongest marker related to abnormal blood glucose compared to other lipid indices, with odds ratios of 2.111 for prediabetes and 5.423 for diabetes. For prediabetes, the AUCs of the TG, TC, HDL-C, LDL-C, TC/HDL-C, TG/HDL-C, non-HDL-C and TyG indices were 0.605, 0.617, 0.481, 0.615, 0.603, 0.590, 0.626 and 0.660, respectively, and the cut-off points were 1.34, 4.59, 1.42, 2.69, 3.39, 1.00, 3.19 and 8.52, respectively. For diabetes, the AUCs of the TG, TC, HDL-C, LDL-C, TC/HDL-C, TG/HDL-C, non-HDL-C and TyG indices were 0.712, 0.679, 0.440, 0.652, 0.686, 0.692, 0.705, and 0.827, respectively, and the cut-off points were 1.35, 4.68, 1.42, 2.61, 3.44, 0.98, 3.13 and 8.80, respectively. CONCLUSIONS The TyG, TG and non-HDL-C, especially TyG, are accessible biomarkers for screening individuals with undiagnosed diabetes.
Collapse
Affiliation(s)
- Yimin Zhou
- Department of Social Medicine and Health Education, School of Public Health, Nanjing Medical University, 818 Tianyuan East Road, Nanjing, 211166, China
| | - Guoping Yang
- Department of Health Education, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, 210009, China
| | - Chen Qu
- Department of Health Education, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, 210009, China
| | - Jiaping Chen
- Department of Epidemiology, School of Public Health, Nanjing Medical University, 818 Tianyuan East Road, Nanjing, 211166, China
| | - Yinan Qian
- Department of Social Medicine and Health Education, School of Public Health, Nanjing Medical University, 818 Tianyuan East Road, Nanjing, 211166, China
| | - Lei Yuan
- Department of Social Medicine and Health Education, School of Public Health, Nanjing Medical University, 818 Tianyuan East Road, Nanjing, 211166, China
| | - Tao Mao
- Department of Health Education, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, 210009, China
| | - Yan Xu
- Department of Health Education, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, 210009, China
| | - Xiaoning Li
- Department of Health Education, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, 210009, China
| | - Shiqi Zhen
- Department of Health Education, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, 210009, China.
| | - Sijun Liu
- Department of Social Medicine and Health Education, School of Public Health, Nanjing Medical University, 818 Tianyuan East Road, Nanjing, 211166, China.
| |
Collapse
|
5
|
Sheng G, Liu D, Kuang M, Zhong Y, Zhang S, Zou Y. Utility of Non-High-Density Lipoprotein Cholesterol to High-Density Lipoprotein Cholesterol Ratio in Evaluating Incident Diabetes Risk. Diabetes Metab Syndr Obes 2022; 15:1677-1686. [PMID: 35669362 PMCID: PMC9166911 DOI: 10.2147/dmso.s355980] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 05/25/2022] [Indexed: 11/23/2022] Open
Abstract
PURPOSE Diabetes is one of the most prevalent chronic diseases in the world, and its prevalence is expected to rise further. To help understand the utility of the ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol (NHHR) in diabetes prevention, this large-scale longitudinal cohort study aims to explore the association of NHHR with diabetes risk and compare it as a risk predictor with conventional lipid parameters. PATIENTS AND METHODS This observational study extracted data from the NAGALA longitudinal cohort study conducted in Japan between 2004 and 2015. Multivariate Cox regression analysis was used to evaluate the association between NHHR and the risk of diabetes. The dose-response relationship was analyzed by restricted cubic spline (RCS) regression and the potential risk threshold was estimated. The receiver operator characteristic curve (ROC) was used to analyze and calculate the predictive value and optimal threshold of NHHR and other conventional lipids for new-onset diabetes. RESULTS Of the 15,464 people aged 18-79, 373 (2.41%) were diagnosed with new-onset diabetes during the study period, with a median age of 46 years. The sensitivity analysis based on multivariate adjustment showed that the independent positive correlation between diabetes and NHHR was stable in different populations. RCS and ROC analysis indicated that the association between NHHR and diabetes was non-linear, and the NHHR was a better marker for predicting diabetes risk than other conventional lipid parameters; Additionally, it is worth noting that an NHHR of approximately 2.74 may be the optimal threshold for intervention in diabetes risk. CONCLUSION In the general population, NHHR is a better marker for predicting diabetes risk than conventional lipid parameters, and an NHHR of about 2.74 may be the optimal threshold for assessing diabetes risk.
Collapse
Affiliation(s)
- Guotai Sheng
- Cardiology Department, Jiangxi Provincial People’s Hospital, Nanchang, Jiangxi Provincial, 330006, People’s Republic of China
| | - Dingyang Liu
- Cardiology Department, Jiangxi Provincial People’s Hospital, Nanchang, Jiangxi Provincial, 330006, People’s Republic of China
| | - Maobin Kuang
- Cardiology Department, Jiangxi Provincial People’s Hospital, Nanchang, Jiangxi Provincial, 330006, People’s Republic of China
| | - Yanjia Zhong
- Endocrinology Department, Jiangxi Provincial People’s Hospital, Nanchang, Jiangxi Province, 330006, People’s Republic of China
| | - Shuhua Zhang
- Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People’s Hospital, Nanchang, Jiangxi Provincial, People’s Republic of China
| | - Yang Zou
- Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People’s Hospital, Nanchang, Jiangxi Provincial, People’s Republic of China
- Correspondence: Yang Zou, Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People’s Hospital, Nanchang, Jiangxi Provincial, People’s Republic of China, Email
| |
Collapse
|
6
|
Ye Y, Gao J, Liang J, Yang Y, Lv C, Chen M, Wang J, Zhu D, Rong R, Xu M, Zhu T, Yu M. Association between preoperative lipid profiles and new-onset diabetes after transplantation in Chinese kidney transplant recipients: A retrospective cohort study. J Clin Lab Anal 2021; 35:e23867. [PMID: 34101909 PMCID: PMC8373348 DOI: 10.1002/jcla.23867] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 04/28/2021] [Accepted: 05/22/2021] [Indexed: 02/06/2023] Open
Abstract
Background This study investigated the association between the preoperative lipid profiles and new‐onset diabetes after transplantation (NODAT) in Chinese kidney transplant recipients (KTRs). Methods In this study, of 1140 KTRs registered between January 1993 and March 2018 in Zhongshan Hospital, Fudan University, 449 were enrolled. Clinical data, obtained through a chart review of the patient records in the medical record system, were evaluated, and NODAT was diagnosed based on the American Diabetes Association guidelines. Multivariate Cox regression analysis was conducted to determine whether the preoperative lipid profiles in KTRs were independently associated with NODAT incidence. The preoperative lipid profiles were analyzed as continuous variables and grouped into tertiles. Smooth curve fitting was used to confirm the linear associations. Results During a median follow‐up of 28.03 (interquartile range 12.00–84.23) months, 104 of the 449 (23.16%) participants developed NODAT. The multivariate model analysis, adjusted for all potential covariates, showed that increased values of the following parameters were associated with NODAT (hazard ratio, 95% confidence interval): preoperative total cholesterol (TC; 1.25, 1.09–1.58, p = 0.0495), low‐density lipoprotein cholesterol (LDL‐C; 1.33, 1.02–1.75, p = 0.0352), non‐high‐density lipoprotein cholesterol (non‐HDL‐C; 1.41, 1.09–1.82, p = 0.0084), TC/HDL‐C (1.28, 1.06–1.54, p = 0.0109), and non‐HDL‐C/HDL‐C (1.26, 1.05–1.52, p = 0.0138). However, the association between the preoperative triglyceride, HDL‐C, or TG/HDL‐C and NODAT was not significant. Conclusions Preoperative TC, LDL‐C, non‐HDL‐C, TC/HDL‐C, and non‐HDL‐C/HDL‐C were independent risk factors for NODAT.
Collapse
Affiliation(s)
- Yangli Ye
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, P.R. China
| | - Jian Gao
- Center of Clinical Epidemiology and Evidence-based Medicine, Fudan University, Shanghai, P.R. China
| | - Jing Liang
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, P.R. China
| | - Yinqiu Yang
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, P.R. China
| | - Chaoyang Lv
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, P.R. China.,Department of Geriatric Endocrinology, Zhengzhou Seventh People's Hospital, Henan, P.R. China
| | - Minling Chen
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, P.R. China.,Departments of Endocrinology and Metabolism, People's Hospital Affiliated to Fujian University of Traditional Chinese Medicine (The People's Hospital of Fujian Province, Fuzhou, P.R. China
| | - Jina Wang
- Department of Urology, Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, P.R. China
| | - Dong Zhu
- Department of Urology, Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, P.R. China
| | - Ruiming Rong
- Department of Urology, Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, P.R. China
| | - Ming Xu
- Department of Urology, Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, P.R. China
| | - Tongyu Zhu
- Department of Urology, Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, P.R. China
| | - Mingxiang Yu
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, P.R. China
| |
Collapse
|
7
|
Gao L, Zhang Y, Wang X, Dong H. Association of apolipoproteins A1 and B with type 2 diabetes and fasting blood glucose: a cross-sectional study. BMC Endocr Disord 2021; 21:59. [PMID: 33794863 PMCID: PMC8017773 DOI: 10.1186/s12902-021-00726-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 03/25/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Apolipoprotein (Apo) may be associated with type 2 diabetes (T2D), however, little is known whether or not serum apolipoproteins are correlated with fasting blood glucose (FBG) and the prevalence of T2D in Chinese populations. In this study, we examined the association of serum ApoA1, ApoB, and the ratio of ApoB/ApoA1 (ApoB/A1 ratio) with T2D and FBG level, and compared apolipoprotein indicators in predicting T2D in Chinese adults. METHODS A total of 1027 subjects were enrolled in this cross-sectional study. The association of ApoA1, ApoB, and ApoB/A1 ratio with T2D prevalence was determined using logistic regression models. Multivariate-analysis of covariance (ANCOVA) was performed for comparisons of the mean difference in FBG level. RESULTS We found that ApoB and ApoB/A1 ratio were positively associated with T2D prevalence and FBG, while inverse association was noted between ApoA1 and T2D prevalence as well as FBG. Stratified analyses for sex, age, body mass index (BMI), smoking, and alcohol consumption showed no significant difference for the association of ApoA1, ApoB, and ApoB/A1 ratio with the prevalence of T2D among subgroups (all p-interactions> 0.05). Nonetheless, ApoA1 poorly performed in predicting T2D as it provided an AUC value of 0.310 that was significantly lower than those observed for ApoB (AUC value: 0.631) and ApoB/A1 ratio (AUC value: 0.685). Finally, path analyses indicated that the association between ApoB and T2D was mediated by BMI. CONCLUSIONS This study reveals the association of serum ApoA1, ApoB, and ApoB/A1 ratio with T2D and FBG in Chinese adults, suggesting that ApoB and ApoB/A1 ratio may be early indicators for predicting T2D. Prospective investigation in large cohort is needed.
Collapse
Affiliation(s)
- Liang Gao
- Department of Clinical Laboratory, Affiliated Maternity & Child Health Care Hospital of Nantong University, Nantong, 226018, Jiangsu Province, China
| | - Yaju Zhang
- Finance Section, Affiliated Traditional Chinese Medicine Hospital of Nantong University, Nantong, 226018, Jiangsu Province, China
| | - Xingmin Wang
- Nantong Institute of Genetics and Reproductive Medicine, Affiliated Maternity & Child Health Care Hospital of Nantong University, Nantong, 226018, Jiangsu Province, China.
| | - Hongli Dong
- Scientific Education Section, Affiliated Maternity & Child Health Care Hospital of Nantong University, Nantong, 226018, Jiangsu Province, China.
| |
Collapse
|
8
|
Xie G, Zhong Y, Yang S, Zou Y. Remnant Cholesterol is an Independent Predictor of New-Onset Diabetes: A Single-Center Cohort Study. Diabetes Metab Syndr Obes 2021; 14:4735-4745. [PMID: 34887671 PMCID: PMC8652915 DOI: 10.2147/dmso.s341285] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 11/23/2021] [Indexed: 12/25/2022] Open
Abstract
PURPOSE Remnant cholesterol (RC) is the cholesterol of triglyceride-rich lipoproteins, which has a high degree of atherogenic effect. To date, epidemiological evidence supports that higher RC levels lead to a greater risk of adverse cardiovascular events in patients with diabetes, but the nature of the association between RC levels and diabetes risk remains unclear. This study was designed to assess the association of RC with the risk of new-onset diabetes and to investigate whether there is a causal relationship between the two. PATIENTS AND METHODS The subjects included 15,464 individuals of the general population who participated in a health examination. Subjects were quartered according to the RC quartile, and the Cox proportional hazard model was used to assess the independent association between RC and new-onset diabetes. RESULTS During an average observation period of 6.13 years, 2.41% of the subjects were diagnosed with new-onset diabetes. Kaplan-Meier analysis showed that the 13-year cumulative diabetes rates corresponding to the RC quartile were 8.62%, 2.49%, 12.78%, and 17.91%. Multivariate Cox regression analysis indicated that higher RC levels were independently associated with an increased risk of new-onset diabetes (HR: 2.44, 95% CI: 1.50-3.89). Additionally, according to the results of receiver operating characteristic curve analysis, RC had the largest area under the curve (0.7314) compared to traditional lipid parameters in predicting new-onset diabetes. CONCLUSION These results indicated that RC is an important independent predictor of new-onset diabetes in the general population.
Collapse
Affiliation(s)
- Guobo Xie
- Cardiology Department, Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, Nanchang, Jiangxi, People’s Republic of China
| | - Yanjia Zhong
- Endocrinology Department, Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, Nanchang, Jiangxi, People’s Republic of China
| | - Shuo Yang
- Cardiology Department, Dean County People’s Hospital, Jiujiang, Jiangxi, People’s Republic of China
| | - Yang Zou
- From the Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, Nanchang, Jiangxi, People’s Republic of China
- Correspondence: Yang Zou Email
| |
Collapse
|
9
|
He Y, Chiang C, Gebremariam LW, Hirakawa Y, Yatsuya H, Aoyama A. Factors Associated With Prediabetes and Diabetes Among Public Employees in Northern Ethiopia. Asia Pac J Public Health 2020; 33:242-250. [PMID: 33289398 DOI: 10.1177/1010539520974848] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The increasing burden of diabetes mellitus is one of the major public health challenges in African countries, including Ethiopia. This is the first study aimed to identify factors associated with prediabetes and diabetes defined by both fasting blood glucose and glycated hemoglobin in Ethiopians. We analyzed data of a cross-sectional survey (1372 adults aged 25-64 years) conducted between October 2015 and February 2016; multinomial logistic regression models were applied. Abdominal obesity, total cholesterol, and non-high-density lipoprotein cholesterol were independently associated with prediabetes and diabetes in both sexes. Increased triglycerides and religious fasting practices were independently associated with prediabetes and diabetes only in men; hypertension was associated with prediabetes and diabetes only in women, while high-density lipoprotein cholesterol was not associated with prediabetes and diabetes in either sex. Sex differences in the association of triglycerides, hypertension, and dietary habit suggest that different approaches of lifestyle modification may be required for men and women.
Collapse
Affiliation(s)
| | | | | | | | - Hiroshi Yatsuya
- Nagoya University, Nagoya, Japan.,Fujita Health University, Toyoake, Aichi, Japan
| | - Atsuko Aoyama
- Nagoya University, Nagoya, Japan.,Nagoya University of Arts and Sciences, Nisshin, Aichi, Japan
| |
Collapse
|
10
|
Han M, Li Q, Qie R, Guo C, Zhou Q, Tian G, Huang S, Wu X, Ren Y, Zhao Y, Liu D, Zhang D, Liu L, Liu F, Chen X, Cheng C, Li Y, Yang X, Zhao Y, Feng Y, Liu Y, Li H, Sun X, Qin P, Chen Q, Zhang M, Hu D, Lu J. Association of non-HDL-C/HDL-C ratio and its dynamic changes with incident type 2 diabetes mellitus: The Rural Chinese Cohort Study. J Diabetes Complications 2020; 34:107712. [PMID: 32919864 DOI: 10.1016/j.jdiacomp.2020.107712] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 06/03/2020] [Accepted: 08/18/2020] [Indexed: 02/06/2023]
Abstract
BACKGROUND We aimed to evaluate the association of the ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol (non-HDL-C/HDL-C) and its dynamic changes with incident type 2 diabetes mellitus (T2DM). METHODS A total of 11,487 nondiabetic participants ≥18 years old in rural China were recruited in 2007-2008 and followed up in 2013-2014. A Cox proportional-hazards model was used to assess the risk of incident T2DM by quartiles of baseline non-HDL-C/HDL-C ratio and dynamic absolute and relative changes in non-HDL-C/HDL-C ratio, estimating hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS Risk of incident T2DM was increased with quartiles 2, 3, and 4 versus quartile 1 of baseline non-HDL-C/HDL-C ratio (HR 1.46 [95% CI 1.08-1.98], 1.51 [1.12-2.03], and 2.16 [1.62-2.88], Ptrend < 0.001). As compared with stable non-HDL-C/HDL-C ratio during follow-up, an absolute gain in non-HDL-C/HDL-C ratio was associated with increased risk of T2DM (HR 1.67 [95% CI 1.25-2.24] for quartile 3 and 2.00 [1.52-2.61] for quartile 4). A relative increase in non-HDL-C/HDL-C ratio was also associated with increased risk of T2DM (HR 1.56 [95% CI 1.19-2.04] for quartile 3 and 1.97 [1.49-2.60] for quartile 4). Subgroup analyses showed that the association of non-HDL-C/HDL-C ratio with T2DM risk remained consistent. CONCLUSIONS Increased non-HDL-C/HDL-C ratio is associated with increased risk of incident T2DM among rural Chinese adults, so the index may be an important indicator for identifying individuals at T2DM risk.
Collapse
Affiliation(s)
- Minghui Han
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Quanman Li
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Ranran Qie
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Chunmei Guo
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Qionggui Zhou
- Department of Epidemiology, 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
- Department of Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Yongcheng Ren
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China; Department of Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, 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; Department of Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Dechen Liu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China; Department of Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Dongdong Zhang
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Leilei Liu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Feiyan Liu
- Department of Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Xu Chen
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Cheng Cheng
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Yang Li
- Department of Epidemiology, 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
| | - Yu Liu
- The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Honghui Li
- The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Xizhuo Sun
- The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Pei Qin
- Department of Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Qing Chen
- Department of Mental Health, Bao'an Chronic Diseases Prevent and Cure Hospital, Shenzhen, Guangdong, People's Republic of China
| | - Ming Zhang
- Department of Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Dongsheng Hu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Jie Lu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China.
| |
Collapse
|
11
|
Miller M. Increased CVD Risk in Young Adults With Elevated Non–HDL-C. J Am Coll Cardiol 2019; 74:80-82. [DOI: 10.1016/j.jacc.2019.04.048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Accepted: 04/09/2019] [Indexed: 11/29/2022]
|
12
|
Guo W, Qin P, Lu J, Li X, Zhu W, Xu N, Wang J, Zhang Q. Diagnostic values and appropriate cutoff points of lipid ratios in patients with abnormal glucose tolerance status: a cross-sectional study. Lipids Health Dis 2019; 18:130. [PMID: 31153374 PMCID: PMC6545201 DOI: 10.1186/s12944-019-1070-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 05/17/2019] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Lipid ratios, for example total cholesterol/high-density lipoprotein cholesterol (TC/HDL-C) and triglyceride/high-density lipoprotein cholesterol (TG/HDL-C), are associated with type 2 diabetes mellitus (T2DM). However, the predictive values of lipid ratios in prediabetes remain unclear. The aims of this study were: 1) to investigate the association between lipid ratios and abnormal glucose tolerance; 2) to compare the predictive significance of lipid ratios with commonly used indicators of lipid variables in clinical practice in a Chinese population. METHODS The cross-sectional study enrolled 2680 participants from the Health Promotion Center of the First Affiliated Hospital of Nanjing Medical University. All participants received a 75 g oral glucose tolerance test. Blood samples were obtained at baseline and 120 min after glucose ingestion. Participants were classified as normal glucose tolerance (NGT), impaired glucose regulation (IGR), and T2DM. The odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using logistic regression model. The receiver operating characteristic (ROC) curve was used to identify the cutoff points of lipid and lipid ratios. The area under the receiver operating characteristic curve (AUROC), sensitivity and specificity were calculated to estimate their diagnostic values. RESULTS TC, TG, TC/HDL-C, TG/HDL-C and non-HDL-C were significantly correlated with both prediabetes and T2DM after adjustment for other risk factors such as blood glucose, whereas LDL-C was only positively correlated with prediabetes. TG and TG/HDL-C showed higher diagnostic values for prediabetes and T2DM than TC, LDL-C, HDL-C, TC/HDL-C and non-HDL-C, with the AUC values over 0.70. For predicting prediabetes, the optimal cutoff point was 1.36 mmol/l for TG and 1.13 for TG/HDL-C. For predicting T2DM, the optimal cutoff point was 1.46 mmol/l for TG and 1.22 for TG/HDL-C. CONCLUSIONS Both TG and TG/HDL-C are promising biomarkers for distinguishing individuals with abnormal glucose tolerance, and can be used to predict prediabetes and T2DM in Chinese population.
Collapse
Affiliation(s)
- Wen Guo
- Department of Health Promotion Center, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China
| | - Pei Qin
- Department of Health Promotion Center, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China
| | - Jing Lu
- Department of Health Promotion Center, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China
| | - Xiaona Li
- Department of Health Promotion Center, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China
| | - Wenfang Zhu
- Department of Health Promotion Center, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China
| | - Nianzhen Xu
- Department of Health Promotion Center, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China
| | - Jianming Wang
- School of Public Health, Nanjing Medical University, 818 Tianyuan East Road, Nanjing, 211166, China.
| | - Qun Zhang
- Department of Health Promotion Center, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China.
| |
Collapse
|
13
|
Chou YC, You SL, Bai CH, Liao YC, Wei CY, Sun CA. Utility of apolipoprotein measurements in predicting incident type 2 diabetes: A Chinese cohort study. J Formos Med Assoc 2019; 119:51-58. [PMID: 30905491 DOI: 10.1016/j.jfma.2019.03.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Revised: 02/18/2019] [Accepted: 03/04/2019] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND/PURPOSE There is conflicting data regarding the utility of measuring apolipoproteins in addition to traditional lipid measures in risk assessment of cardiometabolic diseases. The aim of this study was to determine whether apolipoprotein measurements can improve the ability to predict the future development of type 2 diabetes beyond what is possible based on traditional type 2 diabetes risk factors and clinical routine lipid measurements. METHODS A total of 4,223 Chinese adults without diabetes were followed for a mean duration of 5.42 years. The hazard ratios (HRs) with 95% confidence intervals (CIs) derived from the Cox proportional hazards model were used to analyze the longitudinal associations of apolipoprotein B (apo B), apolipoprotein A-I (apo A-I), and the apo B/apo A-I ratio with the risk of type 2 diabetes. Further, the analysis of the area under receiver operating characteristics curves (AUC) was performed to test the predictive value of apolipoprotein measurements. RESULTS After adjusting for potential confounders, the HRs of diabetes consistently showed an increasing trend across both the apo B and the apo B/apo A-I ratio quartiles (p for trend = 0.004). In analyses of AUC, the predictive ability for type 2 diabetes risk for the apo B and the apo B/apo A-I ratio was superior to that of routine lipid and lipoprotein measurements. CONCLUSION Apolipoprotein measurements significantly predict diabetes risk in an Asian population. Furthermore, the predictive ability of apo B alone to detect diabetes was comparable with that of the apo B/apo A-I ratio and better than the routine lipid measurements.
Collapse
Affiliation(s)
- Yu-Ching Chou
- School of Public Health, National Defense Medical Center, Taipei City, Taiwan, Republic of China
| | - San-Lin You
- Department of Medicine, College of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan, Republic of China; Big Data Research Center, College of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan, Republic of China
| | - Chyi-Huey Bai
- School of Public Health, College of Public Health and Nutrition, Taipei Medical University, Taiepi City, Taiwan, Republic of China
| | - Yu-Chan Liao
- School of Public Health, National Defense Medical Center, Taipei City, Taiwan, Republic of China
| | - Cheng-Yu Wei
- Department of Exercise and Health Promotion, College of Education, Chinese Culture University, New Taipei City, Taiwan, Republic of China
| | - Chien-An Sun
- Big Data Research Center, College of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan, Republic of China; Department of Public Health, College of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan, Republic of China.
| |
Collapse
|
14
|
Liu L, Li Q, Yuan Z, Zhao M, Zhang X, Zhang H, Zheng D, Xu J, Gao L, Guan Q, Zhao J, Proud CG, Wang X, Hou X. Non-high-density lipoprotein cholesterol is more informative than traditional cholesterol indices in predicting diabetes risk for women with normal glucose tolerance. J Diabetes Investig 2018. [PMID: 29542288 PMCID: PMC6215933 DOI: 10.1111/jdi.12837] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Aims/Introduction Limited data are available regarding the performance of non‐high‐density lipoprotein cholesterol (non‐HDL) in predicting incident diabetes. We aimed to analyze the association between non‐HDL and development of diabetes, and to estimate the cut‐off point of non‐HDL for discriminating incident diabetes in people with normal glucose tolerance. Materials and Methods Of 3,653 middle‐aged and elderly Chinese with normal glucose tolerance at enrollment, 1,025 men and 1,805 women returned to the 3‐year follow up and were involved in the final analysis. Logistic regression analysis was used to test the association between cholesterol indices and incident diabetes, and receiver operating characteristic analyses were used to identify the optimal cut‐off of each cholesterol variable for incident diabetes. Results Non‐HDL was an independent risk factor for diabetes for women, but not for men. In women, a 1‐standard deviation increment in non‐HDL was associated with a 1.43‐fold higher risk of diabetes (95% confidence interval 1.14–1.79; P = 0.002), whereas odds ratios for total cholesterol and low‐density lipoprotein cholesterol were 1.33 (95% confidence interval 1.06–1.67; P = 0.015) and 1.30 (95% confidence interval 1.04–1.64; P = 0.024), respectively. The discriminatory power and the optimal cut‐off value of non‐HDL for incident diabetes increased across body mass index categories. For women with obesity, the threshold of non‐HDL for screening of diabetes was estimated as 3.51 mmol/L. Conclusions Non‐HDL had better performance than traditional cholesterol indices in predicting diabetes in women, but not in men. A body mass index‐specific threshold value for a non‐HDL‐controlling target is required in the prevention of type 2 diabetes.
Collapse
Affiliation(s)
- Lu Liu
- Department of Endocrinology, Shandong Provincial Hospital affiliated to Shandong University, Jinan, China.,Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, China.,Institute of Endocrinology and Metabolism, Shandong Academy of Clinical Medicine, Jinan, China
| | - Qiu Li
- Department of Endocrinology, Shandong Provincial Hospital affiliated to Shandong University, Jinan, China.,Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, China.,Institute of Endocrinology and Metabolism, Shandong Academy of Clinical Medicine, Jinan, China
| | - Zhongshang Yuan
- Department of Epidemiology and Biostatistics, School of Public Health, Shandong University, Jinan, China
| | - Meng Zhao
- Department of Endocrinology, Shandong Provincial Hospital affiliated to Shandong University, Jinan, China.,Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, China.,Institute of Endocrinology and Metabolism, Shandong Academy of Clinical Medicine, Jinan, China
| | - Xu Zhang
- Department of Endocrinology, Shandong Provincial Hospital affiliated to Shandong University, Jinan, China.,Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, China.,Institute of Endocrinology and Metabolism, Shandong Academy of Clinical Medicine, Jinan, China
| | - Haiqing Zhang
- Department of Endocrinology, Shandong Provincial Hospital affiliated to Shandong University, Jinan, China.,Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, China.,Institute of Endocrinology and Metabolism, Shandong Academy of Clinical Medicine, Jinan, China
| | - Dongmei Zheng
- Department of Endocrinology, Shandong Provincial Hospital affiliated to Shandong University, Jinan, China.,Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, China.,Institute of Endocrinology and Metabolism, Shandong Academy of Clinical Medicine, Jinan, China
| | - Jin Xu
- Department of Endocrinology, Shandong Provincial Hospital affiliated to Shandong University, Jinan, China.,Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, China.,Institute of Endocrinology and Metabolism, Shandong Academy of Clinical Medicine, Jinan, China
| | - Ling Gao
- Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, China.,Institute of Endocrinology and Metabolism, Shandong Academy of Clinical Medicine, Jinan, China.,Scientific Center, Shandong Provincial Hospital affiliated to Shandong University, Jinan, China
| | - Qingbo Guan
- Department of Endocrinology, Shandong Provincial Hospital affiliated to Shandong University, Jinan, China.,Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, China.,Institute of Endocrinology and Metabolism, Shandong Academy of Clinical Medicine, Jinan, China
| | - Jiajun Zhao
- Department of Endocrinology, Shandong Provincial Hospital affiliated to Shandong University, Jinan, China.,Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, China.,Institute of Endocrinology and Metabolism, Shandong Academy of Clinical Medicine, Jinan, China
| | - Christopher G Proud
- Nutrition and Metabolism, South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia.,School of Biological Sciences, University of Adelaide, Adelaide, South Australia, Australia
| | - Xuemin Wang
- Nutrition and Metabolism, South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia.,School of Biological Sciences, University of Adelaide, Adelaide, South Australia, Australia
| | - Xu Hou
- Department of Endocrinology, Shandong Provincial Hospital affiliated to Shandong University, Jinan, China.,Shandong Clinical Medical Center of Endocrinology and Metabolism, Jinan, China.,Institute of Endocrinology and Metabolism, Shandong Academy of Clinical Medicine, Jinan, China
| | | |
Collapse
|
15
|
Riediger ND, Clark K, Lukianchuk V, Roulette J, Bruce S. Fasting triglycerides as a predictor of incident diabetes, insulin resistance and β-cell function in a Canadian First Nation. Int J Circumpolar Health 2018; 76:1310444. [PMID: 28406758 PMCID: PMC5405443 DOI: 10.1080/22423982.2017.1310444] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Background: Diabetes prevalence is substantially higher among Canadian First Nations populations than the non-First Nation population. Fasting serum triglycerides have been found to be an important predictor of incident diabetes among non-indigenous populations. However, there is a great need to understand diabetes progression within specific ethnic groups, particularly First Nations populations. Objective: The purpose of this study was to test for an association between fasting serum triglycerides and incident diabetes, changes in insulin resistance and changes in β-cell function in a Manitoba First Nation cohort. Methods: Study data were from two diabetes screening studies in Sandy Bay First Nation in Manitoba, Canada, collected in 2002/2003 and 2011/2012. The cohort was composed of respondents to both screening studies (n=171). Fasting blood samples and anthropometric, health and demographic data were collected. A generalised linear model with Poisson distribution was used to test for an association between fasting triglycerides and incident diabetes. Results: There were 35 incident cases of diabetes among 128 persons without diabetes at baseline. Participants who developed incident type 2 diabetes were significantly older and had significantly higher body mass index (BMI; p=0.012), total cholesterol (p=0.007), fasting triglycerides (p<0.001), and Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) (p<0.001). Fasting triglyceride level was found to be a statistically significant positive predictor of incident diabetes independent of age, sex and waist circumference at baseline. Participants with triglycerides in the highest tertile (≥2.11 mmol/l) had a 4.0-times higher risk of developing incident diabetes compared to those in the lowest tertile (p=0.03). Notably, neither waist circumference nor BMI were significant predictors of incident diabetes independent of age, sex and triglycerides. Conclusion: Fasting triglycerides may be useful as a clinical predictor of insulin resistance and diabetes development among First Nations populations. Unlike other ethnic groups, BMI and waist circumference may be less important factors in diabetes development.
Collapse
Affiliation(s)
- Natalie D Riediger
- a Department of Community Health Sciences, Rady Faculty of Health Sciences , University of Manitoba , Winnipeg , Canada.,b Manitoba First Nations Centre for Aboriginal Health Research, Rady Faculty of Health Sciences , University of Manitoba , Winnipeg , Canada.,c Department of Human Nutritional Sciences, Faculty of Agricultural and Food Sciences , University of Manitoba , Winnipeg , Canada
| | - Kirsten Clark
- d Northern Remote Family Medicine Residency , University of Manitoba , Winnipeg , Canada
| | | | - Joanne Roulette
- e Sandy Bay First Nation Health Centre , Sandy Bay First Nation , Canada
| | - Sharon Bruce
- a Department of Community Health Sciences, Rady Faculty of Health Sciences , University of Manitoba , Winnipeg , Canada
| |
Collapse
|
16
|
Zhang M, Zhou J, Liu Y, Sun X, Luo X, Han C, Zhang L, Wang B, Ren Y, Zhao Y, Zhang D, Liu X, Hu D. Risk of type 2 diabetes mellitus associated with plasma lipid levels: The rural Chinese cohort study. Diabetes Res Clin Pract 2018; 135:150-157. [PMID: 29155120 DOI: 10.1016/j.diabres.2017.11.011] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2017] [Revised: 06/08/2017] [Accepted: 11/10/2017] [Indexed: 11/30/2022]
Abstract
AIM To investigate the association of type 2 diabetes mellitus (T2DM) risk and plasma lipid levels in rural Chinese. METHODS Each lipid variable was divided into quartiles and dichotomized by clinical cutoff points. Cox proportional-hazards model was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of T2DM risk and plasma lipid levels and explore the interaction between plasma lipid levels and other risk factors. RESULTS 11,929 participants were included in the analysis. We documented 720 incident cases of T2DM over 70,720.84 person-years of follow-up, for an incidence of 10.18/1,000 person-years. In the multivariable-adjusted model, risk of T2DM was increased with the highest versus lowest quartiles of total cholesterol (TC) and triglycerides (TG) levels and TC/high-density lipoprotein-cholesterol (HDL-C) and TG/HDL-C ratios. The HRs (95% CIs) for the fourth quartiles, for example, were 1.34 (1.03-1.74), 2.32 (1.73-3.13), 1.66 (1.23-2.25), and 1.84 (1.38-2.45), respectively. In addition, risk of T2DM was increased with high TG level and TC/HDL-C and TG/HDL-C ratios by clinical cutoffs. The HRs (95% CIs) were 1.50 (1.25-1.80), 1.24 (1.03-1.48), and 1.44 (1.18-1.75), respectively. Risk of T2DM was associated with interactions between all lipid variables and age and BMI. TG level and TG/HDL-C ratio additionally interacted with gender (all Pinteraction < 0.0001). CONCLUSIONS Risk of T2DM was increased with elevated serum levels of TC and TG and TC/HDL-C and TG/HDL-C ratios and also with interactions between high TC and TG levels and TC/HDL-C and TG/HDL-C ratios and age and BMI in a rural Chinese population.
Collapse
Affiliation(s)
- Ming Zhang
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, 3688 Nanhai Avenue, Shenzhen 518060, Guangdong, China
| | - Junmei Zhou
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, 3688 Nanhai Avenue, Shenzhen 518060, Guangdong, China
| | - Yu Liu
- The Affiliated Luohu Hospital of Shenzhen University Health Sciences Center, 47 Youyi Road, Shenzhen 518001, Guangdong, China
| | - Xizhuo Sun
- The Affiliated Luohu Hospital of Shenzhen University Health Sciences Center, 47 Youyi Road, Shenzhen 518001, Guangdong, China
| | - Xinping Luo
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, 3688 Nanhai Avenue, Shenzhen 518060, Guangdong, China
| | - Chengyi Han
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, 3688 Nanhai Avenue, Shenzhen 518060, Guangdong, China; Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, Henan, China
| | - Lu Zhang
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, 3688 Nanhai Avenue, Shenzhen 518060, Guangdong, China; Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, Henan, China
| | - Bingyuan Wang
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, 3688 Nanhai Avenue, Shenzhen 518060, Guangdong, China; Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, Henan, China
| | - Yongcheng Ren
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, 3688 Nanhai Avenue, Shenzhen 518060, Guangdong, China; Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, Henan, China
| | - Yang Zhao
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, 3688 Nanhai Avenue, Shenzhen 518060, Guangdong, China; Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, Henan, China
| | - Dongdong Zhang
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, 3688 Nanhai Avenue, Shenzhen 518060, Guangdong, China; Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, Henan, China
| | - Xuejiao Liu
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, 3688 Nanhai Avenue, Shenzhen 518060, Guangdong, China; Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, Henan, China
| | - Dongsheng Hu
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, 3688 Nanhai Avenue, Shenzhen 518060, Guangdong, China.
| |
Collapse
|
17
|
Wang H, Guo X, Chen Y, Li Z, Xu J, Sun Y. Relation of four nontraditional lipid profiles to diabetes in rural Chinese H-type hypertension population. Lipids Health Dis 2017; 16:199. [PMID: 29020963 PMCID: PMC5637264 DOI: 10.1186/s12944-017-0590-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2017] [Accepted: 10/04/2017] [Indexed: 01/09/2023] Open
Abstract
Background Mounting evidence suggested that nontraditional lipid profiles have been recognized as a reliable indicator for unfavorable cardiovascular events. The purpose of this study was to explore the role of nontraditional lipid profiles as potential clinical indices for the assessment of prevalent diabetes in rural Chinese H-type hypertension population. Methods During 2012 to 2013, we conducted a large cross-sectional study of 2944 H-type hypertension participants (≥35 years of age) from rural areas in northeast China. Subjects underwent accurate assessment of lipid profiles, fasting plasma glucose (FPG), homocysteine (Hcy) according to standard protocols. Results The proportion of diabetes showed a graded and linear increase across the quartiles for all four nontraditional lipid parameters. Nontraditional lipid variables were independent determinants of FPG, and its correlation for TG/HDL-C was strongest, whether potential confounders were adjusted or not. Multivariable logistic regression analysis established that the highest triglycerides (TG)/ high-density lipoprotein cholesterol (HDL-C) quartile manifested the largest ORs of prevalent diabetes (OR: 3.275, 95%CI: 2.109–5.087) compared with the lowest quartile. The fully adjusted ORs (95%CI) were 2.753 (1.783–4.252), 2.178 (1.415–2.351), 1.648 (1.097–2.478) for the top quartile of total cholesterol (TC)/HDL-C, low-density lipoprotein cholesterol (LDL-C)/HDL-C, and non-high-density lipoprotein cholesterol (non-HDL-C), respectively. On the basis of the area under receiver-operating characteristic curve (AUC), TG/HDL-C showed the optimal discriminating power for diabetes (AUC: 0.684, 95% CI: 0.650–0.718). Conclusions Nontraditional lipid profiles (TG/HDL-C, TC/HDL-C, LDL-C/HDL-C and non-HDL-C) were all consistently and independently correlated with prevalent diabetes among the H-type hypertension population in rural China. TG/HDL-C was prone to be more profitable in assessing the risk of prevalent diabetes and should be encouraged as an effective clinical tool for monitoring and targeted intervention of diabetes in H-type hypertension adults.
Collapse
Affiliation(s)
- Haoyu Wang
- Department of Cardiology, The First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, Liaoning, People's Republic of China
| | - Xiaofan Guo
- Department of Cardiology, The First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, Liaoning, People's Republic of China
| | - Yintao Chen
- Department of Cardiology, The First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, Liaoning, People's Republic of China
| | - Zhao Li
- Department of Cardiology, The First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, Liaoning, People's Republic of China
| | - Jiaqi Xu
- Department of Cardiology, The First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, Liaoning, People's Republic of China
| | - Yingxian Sun
- Department of Cardiology, The First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, Liaoning, People's Republic of China.
| |
Collapse
|
18
|
Benes LB, Bassi NS, Davidson MH. Omega-3 carboxylic acids monotherapy and combination with statins in the management of dyslipidemia. Vasc Health Risk Manag 2016; 12:481-490. [PMID: 28003756 PMCID: PMC5161399 DOI: 10.2147/vhrm.s58149] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
The 2013 American College of Cardiology/American Heart Association guidelines on cholesterol management placed greater emphasis on statin therapy given the well-established benefits in primary and secondary prevention of cardiovascular disease. Residual risk may remain after statin initiation, in part because of triglyceride-rich lipoprotein cholesterol. Several large trials have failed to show benefit with non-statin cholesterol-lowering medications in the reduction of cardiovascular events. Yet, subgroup analyses showed a benefit in those with hypertriglyceridemia and lower high-density lipoprotein cholesterol level, a high-risk pattern of dyslipidemia. This review discusses the benefits of omega-3 carboxylic acids, a recently approved formulation of omega-3 fatty acid with enhanced bioavailability, in the treatment of dyslipidemia both as monotherapy and combination therapy with a statin.
Collapse
Affiliation(s)
| | - Nikhil S Bassi
- Department of Medicine, University of Chicago, Chicago, IL, USA
| | | |
Collapse
|
19
|
Strufaldi MWL, Souza FISD, Puccini RF, Franco MDCP. Family history of cardiovascular disease and non-HDL cholesterol in prepubescent non-obese children. Rev Assoc Med Bras (1992) 2016; 62:347-52. [PMID: 27437681 DOI: 10.1590/1806-9282.62.04.347] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2015] [Accepted: 06/21/2015] [Indexed: 11/22/2022] Open
Abstract
OBJECTIVE To describe the values of non-HDL cholesterol (NHDL-c) and the frequency of a family history of early cardiovascular disease (family HCVD) in healthy prepubescent children. Analyze the association between NHDL-c and family HCVD, and possible associations with other risk factors for cardiovascular disease (CVD). METHOD Cross-sectional study including 269 prepubescent (aged 6-10 years) schoolchildren with a normal body mass index (+1SD<BMI>-2SD). DATA COLLECTED Family HCVD; weight and height, waist circumference and systemic blood pressure; lipid profile (total cholesterol TC, HDL-c, triglycerides and LDL-c), NHDL-c calculation (CT-HDL-c, cut-off = 145 mg/dL) and insulin resistance (HOMA-IR). RESULTS High levels were found for NHDL-c in 10 (3.7%) of these schoolchildren, and family early HCVD was found in 46 (17.1%) of them. There was a weak association between family HCVD and NHDL-c (Cramer's-V-test = 0.120; p=0.050). Among the children with NHDL-c≥145 mg/dL, 4 (40%) have family HCVD. The presence of family HCVD was not associated with the variables being studied. The variables independently associated with NHDL-c ≥ 145 mg/dL were: HOMA-IR (OR=1.7; 95CI 1.1-2.6) and diastolic blood pressure (OR=1.1; 95CI 1.02-1.2). CONCLUSION NHDL-c values were associated with blood pressure and insulin resistance. Family HCVD was not associated with other classic risk factors for CVD, even though the frequency found was five times higher than that of high NHDL-c.
Collapse
Affiliation(s)
- Maria Wany Louzada Strufaldi
- PhD - Adjunct Professor, Department of Pediatrics, Escola Paulista de Medicina, Universidade Federal de São Paulo (Unifesp), São Paulo, SP, Brazil
| | - Fabíola Isabel Suano de Souza
- PhD - Adjunct Professor, Department of Pediatrics, Escola Paulista de Medicina, Universidade Federal de São Paulo (Unifesp), São Paulo, SP, Brazil.,PhD - Professor, Department of Pediatrics, Faculdade de Medicina do ABC (FMABC), Santo André, SP, Brazil
| | - Rosana Fiorini Puccini
- PhD - Full Professor, Department of Pediatrics, Escola Paulista de Medicina, Unifesp, São Paulo, SP, Brazil
| | - Maria do Carmo Pinho Franco
- PhD - Adjunct Professor, Department of Physiology, Escola Paulista de Medicina, Unifesp, São Paulo, SP, Brazil
| |
Collapse
|
20
|
Song Q, Liu X, Wang A, Wang Y, Zhou Y, Zhou W, Wang X. Associations between non-traditional lipid measures and risk for type 2 diabetes mellitus in a Chinese community population: a cross-sectional study. Lipids Health Dis 2016; 15:70. [PMID: 27044245 PMCID: PMC4820983 DOI: 10.1186/s12944-016-0239-y] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2016] [Accepted: 03/30/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND This study investigated associations between type 2 diabetes mellitus and non-traditional lipid measures (total cholesterol (TC)/high-density lipoprotein cholesterol (HDL-C), triglycerides (TG)/HDL-C, and non-HDL-C). METHODS We conducted a community-based, cross-sectional study of 9 078 participants aged 18 years or older (4 768 men and 4 310 women) who lived in the Jidong community, Tangshan, China. The adjusted odds ratios for type 2 diabetes were calculated for every standard deviation change in TC, log-transformed TG, HDL-C, LDL-C, non-HDL-C, TC/HDL-C, and log-transformed TG/HDL-C using multivariate logistic regression analysis. Receiver operating characteristic (ROC) curve analysis was used to define the points of maximum sum of sensitivity and specificity for each lipid measure as a predictor for type 2 diabetes. RESULTS Prevalence of type 2 diabetes was 6.29%. Higher TC, TG, LDL-C, non-HDL-C, TC/HDL-C, and TG/HDL-C, and lower HDL-C levels were individually associated with type 2 diabetes in multivariate analyses (all P < 0.05). TC/HDL-C was superior at discriminating between participants with and without type 2 diabetes compared with LDL-C (comparing ROC: P < 0.001), HDL-C (P < 0.001), TG (P = 0.012), TC (P < 0.001), non-HDL-C (P = 0.001), and TG/HDL-C (P = 0.03). The cutoff point for TC/HDL-C was 1.30 mmol/L in this population from the Jidong community. Sensitivity and specificity values for TC/HDL-C were 0.77 and 0.53, respectively. CONCLUSIONS TC/HDL-C is associated with type 2 diabetes and is superior to LDL-C and HDL-C as a risk marker in this population.
Collapse
Affiliation(s)
- Qiaofeng Song
- Department of Cardiology, Tangshan People's Hospital, North China University of Science and Technology, No.65 Shengli Road, Lunan District, Tangshan, 063000, China
| | - Xiaoxue Liu
- Department of Cardiology, Tangshan People's Hospital, North China University of Science and Technology, No.65 Shengli Road, Lunan District, Tangshan, 063000, China
| | - Anxin Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China.,Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Youxin Wang
- Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, 100050, China
| | - Yong Zhou
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Wenhua Zhou
- Department of Cardiology, Tangshan People's Hospital, North China University of Science and Technology, No.65 Shengli Road, Lunan District, Tangshan, 063000, China
| | - Xizhu Wang
- Department of Cardiology, Tangshan People's Hospital, North China University of Science and Technology, No.65 Shengli Road, Lunan District, Tangshan, 063000, China.
| |
Collapse
|
21
|
Saito E, Okada T, Abe Y, Kazama M, Yonezawa R, Kuromori Y, Iwata F, Hara M. Non-high-density Lipoprotein Cholesterol Levels in Japanese Obese Boys with Metabolic Syndrome. J Atheroscler Thromb 2015; 23:105-11. [PMID: 26412493 DOI: 10.5551/jat.30692] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
AIM To investigate the relationship between the clustering of metabolic syndrome (MetS) components and non-high-density lipoprotein cholesterol (non-HDL-C) levels in Japanese obese boys. METHODS Subjects were 58 obese boys aged 12.0±2.6 years, which were categorized into three subgroups: abdominal obesity, pre-MetS (abdominal obesity+1 component), and MetS (abdominal obesity+2 or more components). RESULTS Sixteen (27.6%) and 32 (55.2%) of the obese boys were diagnosed as pre-MetS and MetS, respectively. The mean non-HDL-C level in total subjects was 139.0±36.4 mg/dl and that in boys with abdominal obesity, pre-MetS, and MetS were 112.9±34.4, 135.4±37.9, and 149.0±32.6 mg/dl, respectively (p=0.0183, ANOVA). CONCLUSIONS Japanese obese boys with MetS exhibited elevated non-HDL-C levels, suggesting that they may have a higher risk for the development of atherosclerotic diseases.
Collapse
Affiliation(s)
- Emiko Saito
- Department of Pediatrics and Child Health, Nihon University School of Medicine
| | | | | | | | | | | | | | | |
Collapse
|
22
|
Fujihara K, Sugawara A, Heianza Y, Sairenchi T, Irie F, Iso H, Doi M, Shimano H, Watanabe H, Sone H, Ota H. Utility of the triglyceride level for predicting incident diabetes mellitus according to the fasting status and body mass index category: the Ibaraki Prefectural Health Study. J Atheroscler Thromb 2014; 21:1152-69. [PMID: 25030050 DOI: 10.5551/jat.22913] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
AIM The levels of lipids, especially triglycerides (TG), and obesity are associated with diabetes mellitus (DM). Although typically measured in fasting individuals, non-fasting lipid measurements play an important role in predicting future DM. This study compared the predictive efficacy of lipid variables according to the fasting status and body mass index (BMI) category. METHODS Data were collected for 39,196 nondiabetic men and 87,980 nondiabetic women 40-79years of age who underwent health checkups in Ibaraki-Prefecture, Japan in 1993 and were followed through 2007. The hazard ratios (HRs) for DM in relation to sex, the fasting status and BMI were estimated using a Cox proportional hazards model. RESULTS A total of 8,867 participants, 4,012 men and 4,855 women, developed DM during a mean follow-up of 5.5 years. TG was found to be an independent predictor of incident DM in both fasting and non-fasting men and non-fasting women. The multivariable-adjusted HR for DM according to the TG quartile (Q) 4 vs. Q1 was 1.18 (95% confidence interval (CI): 1.05, 1.34) in the non-fasting men with a normal BMI (18.5-24.9). This trend was also observed in the non-fasting women with a normal BMI. That is, the multivariable-adjusted HRs for DM for TG Q2, Q3 and Q4 compared with Q1 were 1.07 (95% CI: 0.94, 1.23), 1.17 (95%CI: 1.03, 1.34) and 1.48 (95%CI: 1.30, 1.69), respectively. CONCLUSIONS The fasting and non-fasting TG levels in men and non-fasting TG levels in women are predictive of future DM among those with a normal BMI. Clinicians must pay attention to those individuals at high risk for DM.
Collapse
Affiliation(s)
- Kazuya Fujihara
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Faculty of Medicine, University of Tsukuba
| | | | | | | | | | | | | | | | | | | | | |
Collapse
|
23
|
Jian ZH, Lung CC, Ko PC, Sun YH, Huang JY, Ho CC, Ho CY, Chiang YC, Chen CJ, Liaw YP. The association between the apolipoprotein A1/ high density lipoprotein -cholesterol and diabetes in Taiwan - a cross-sectional study. BMC Endocr Disord 2013; 13:42. [PMID: 24093822 PMCID: PMC3851878 DOI: 10.1186/1472-6823-13-42] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2013] [Accepted: 09/18/2013] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Traditional lipid indices have been associated with type 2 diabetes, but it remains uncertain which lipid index is the best discriminator for diabetes. In this study, we aimed to assess lipoproteins, traditional lipid variables, and other variables to discover their association with diabetes in the Taiwanese population. METHODS Data from a nationwide cross-sectional population-based survey of 3087 men and 3373 women in 2002 were analyzed in this study. All participants were assessed for anthropometry, glycosylated hemoglobin, fasting sugar and lipid profiles with triglycerides, high density lipoprotein-cholesterol (HDL-C), low density lipoprotein-cholesterol (LDL-C), and apolipoprotein A1 (ApoA1) and B (ApoB). The ratio of LDL-C/HDL-C, ApoB/ApoA1, ApoB/LDL-C and ApoA1/HDL-C and other variables were analyzed to determine their potential roles in type 2 diabetes in the Taiwanese population. The Odds ratios (ORs) of the risk variables for diabetes were estimated using logistic regression and were adjusted for confounding factors. RESULTS The increased ratio of ApoA1/HDL-C was significantly associated with diabetes in men (top tertile vs. lowest: OR 2.98; 95% CI: 1.12 - 7.92; P-trend = 0.030) and women (top tertile vs. lowest: OR 2.15; 95% CI: 1.00 - 4.59; P-trend = 0.047). A modest increased diabetic risk was evident with ApoB/LDL-C in women (top tertile vs. lowest: OR 2.03; 95% CI: 1.07- 3.85; P-trend = 0.028), but not in men (top tertile v. lowest: OR 1.69; 95% CI: 0.79- 3.62; P-trend = 0.198). CONCLUSIONS ApoA1/HDL-C had a significant linear association with diabetes in both sexes and was superior to other lipid and lipoprotein variables among the general Taiwanese population.
Collapse
Affiliation(s)
- Zhi-Hong Jian
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung City, Taiwan
| | - Chia-Chi Lung
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung City, Taiwan
- Department of Family and Community Medicine, Chung Shan Medical, University Hospital, Taichung City 40201, Taiwan
| | - Pei-Chieh Ko
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung City, Taiwan
| | - Yi-Hua Sun
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung City, Taiwan
- Department of Dentistry, Chung Shan Medical University, Taichung 40201, Taiwan
| | - Jing-Yang Huang
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung City, Taiwan
| | - Chien-Chang Ho
- Department of Health and Leisure Management, Yuanpei University, Hsinchu, Taiwan
| | - Chia-Yo Ho
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung City, Taiwan
| | - Yi-Chen Chiang
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung City, Taiwan
| | - Chien-Jen Chen
- Genomics Research Center, Academia Sinica, Taipei, Taiwan
- Graduate Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Yung-Po Liaw
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung City, Taiwan
- Department of Family and Community Medicine, Chung Shan Medical, University Hospital, Taichung City 40201, Taiwan
| |
Collapse
|