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Heydarzadeh F, Mohammadi F, Yadegar A, Mohammadi Naeini A, Nabipoorashrafi SA, Rabizadeh S, Esteghamati A, Nakhjavani M. Increased high-density lipoprotein cholesterol in patients with type 2 diabetes and its correlates: a cross-sectional, matched case-control survey. Eur J Med Res 2024; 29:355. [PMID: 38956709 PMCID: PMC11218062 DOI: 10.1186/s40001-024-01950-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 06/25/2024] [Indexed: 07/04/2024] Open
Abstract
BACKGROUND So far, high-density lipoprotein cholesterol (HDL-C) levels and mortality were shown to have a U-shaped relationship. Additionally, high HDL-C levels increase the risk of developing a variety of diseases. However, a paucity of data exists regarding the characteristics of people with high HDL-C levels. The aim of this study was to assess the demographics and characteristics of patients with high HDL-C levels and compare their features with normal and low HDL-C groups. METHODS As a cross-sectional, matched case-control study, a total of 510 patients with type 2 diabetes (T2D) were enrolled in the study and categorized into three matched groups according to their HDL-C concentrations. The studied groups were matched by their age and gender. Restricted cubic spline (RCS) curves were designed to evaluate the relationship between height, blood pressure, triglyceride, and vitamin D concentrations with the probability of having high HDL-C levels. Furthermore, violin plots were conducted to illustrate the distribution of continuous variables within each group. RESULTS This study showed that having high HDL-C (more than 70 mg/dL) compared to having low HDL-C (less than 40 mg/dL in men and 50 mg/dL in women) was significantly associated with height (OR 0.918, 95% CI 0.866-0.974), systolic blood pressure (SBP) (0.941, 0.910-0.972), vitamin D (0.970, 0.941-0.999), and triglyceride (0.992, 0.987-0.998) serum concentrations. Further analysis investigated that having high HDL-C levels compared to desired HDL-C levels (40 ≤ HDL-C levels < 70 in men and 50 ≤ HDL-C levels < 70 in women) was inversely associated with having SPB values greater than 130 mmHg. Besides, sufficient vitamin D levels (above 20 ng/ml) could 0.349 times decrease the odds of having high HDL-C versus normal HDL-C levels. CONCLUSION Sufficient vitamin D levels, SPB values higher than 130 mmHg, as well as increased triglyceride levels, were inversely associated with having high HDL levels. However, higher height values were associated with a decreased likelihood of having high HDL.
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Affiliation(s)
- Fatemeh Heydarzadeh
- Endocrinology and Metabolism Research Center (EMRC), Vali-Asr Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Fatemeh Mohammadi
- Endocrinology and Metabolism Research Center (EMRC), Vali-Asr Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Amirhossein Yadegar
- Endocrinology and Metabolism Research Center (EMRC), Vali-Asr Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Ali Mohammadi Naeini
- Endocrinology and Metabolism Research Center (EMRC), Vali-Asr Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyed Ali Nabipoorashrafi
- Endocrinology and Metabolism Research Center (EMRC), Vali-Asr Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Soghra Rabizadeh
- Endocrinology and Metabolism Research Center (EMRC), Vali-Asr Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Alireza Esteghamati
- Endocrinology and Metabolism Research Center (EMRC), Vali-Asr Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Manouchehr Nakhjavani
- Endocrinology and Metabolism Research Center (EMRC), Vali-Asr Hospital, Tehran University of Medical Sciences, Tehran, Iran.
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He S, Yu C, Kuang M, Qiu J, Yang R, Zhang S, Sheng G, Zou Y. Alanine aminotransferase to high- density lipoprotein cholesterol ratio is positively correlated with the occurrence of diabetes in the Chinese population: a population-based cohort study. Front Endocrinol (Lausanne) 2023; 14:1266692. [PMID: 38089616 PMCID: PMC10715265 DOI: 10.3389/fendo.2023.1266692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 11/10/2023] [Indexed: 12/18/2023] Open
Abstract
Objective Both alanine aminotransferase (ALT) and high-density lipoprotein cholesterol (HDL-C) are closely related to glucose homeostasis in the body, and the main objective of this study was to investigate the association between ALT to HDL-C ratio (ALT/HDL-C ratio) and the risk of diabetes in a Chinese population. Methods The current study included 116,251 participants who underwent a healthy physical examination, and the study endpoint was defined as a diagnosis of new-onset diabetes. Multivariate Cox regression models and receiver operator characteristic curves were used to assess the association of the ALT/HDL-C ratio with diabetes onset. Results During the average observation period of 3.10 years, a total of 2,674 (2.3%) participants were diagnosed with new-onset diabetes, including 1,883 (1.62%) males and 791 (0.68%) females. After fully adjusting for confounding factors, we found a significant positive association between the ALT/HDL-C ratio and the risk of diabetes [Hazard ratios 1.06, 95% confidence intervals: 1.05, 1.06], and this association was significantly higher in males, obese individuals [body mass index ≥ 28 kg/m2] and individuals aged < 60 years (All P interaction < 0.05). In addition, the ALT/HDL-C ratio was significantly better than its components ALT and HDL-C in predicting diabetes in the Chinese population. Conclusion There was a positive relationship between ALT/HDL-C ratio and diabetes risk in the Chinese population, and this relationship was significantly stronger in males, obese individuals, and individuals younger than 60 years old.
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Affiliation(s)
- Shiming He
- Department of Internal Medicine, Medical College of Nanchang University, Jiangxi Provincial People’s Hospital, Nanchang, Jiangxi, China
- Jiangxi Provincial Geriatric Hospital, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
- Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
| | - Changhui Yu
- Department of Internal Medicine, Medical College of Nanchang University, Jiangxi Provincial People’s Hospital, Nanchang, Jiangxi, China
- Jiangxi Provincial Geriatric Hospital, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
- Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
| | - Maobin Kuang
- Department of Internal Medicine, Medical College of Nanchang University, Jiangxi Provincial People’s Hospital, Nanchang, Jiangxi, China
- Jiangxi Provincial Geriatric Hospital, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
- Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
| | - Jiajun Qiu
- Department of Internal Medicine, Medical College of Nanchang University, Jiangxi Provincial People’s Hospital, Nanchang, Jiangxi, China
- Jiangxi Provincial Geriatric Hospital, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
- Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
| | - Ruijuan Yang
- Department of Internal Medicine, Medical College of Nanchang University, Jiangxi Provincial People’s Hospital, Nanchang, Jiangxi, China
- Department of Endocrinology, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
| | - Shuhua Zhang
- Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
| | - Guotai Sheng
- Jiangxi Provincial Geriatric Hospital, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
| | - Yang Zou
- Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
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Qiu J, Kuang M, Yang R, Yu C, He S, Sheng G, Zou Y. The newly proposed alanine aminotransferase to high-density lipoprotein cholesterol ratio has shown effectiveness in identifying non-alcoholic fatty liver disease. Front Endocrinol (Lausanne) 2023; 14:1239398. [PMID: 37727457 PMCID: PMC10505795 DOI: 10.3389/fendo.2023.1239398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 08/14/2023] [Indexed: 09/21/2023] Open
Abstract
Objective Alanine aminotransferase (ALT) and high-density lipoprotein cholesterol (HDL-C) are important predictive factors for non-alcoholic fatty liver disease (NAFLD). The aim of this study was to analyze the association between the ALT/HDL-C ratio and NAFLD. Methods We conducted a retrospective analysis of data from 14,251 individuals participating in the NAGALA project's health screening program. The presence of NAFLD was diagnosed based on the participants' alcohol consumption status and liver ultrasonography images. Multivariable logistic regression models were used to assess the association between the ALT/HDL-C ratio and NAFLD. Receiver operating characteristic (ROC) analysis was performed to determine and compare the effectiveness of ALT, HDL-C, the aspartate aminotransferase to HDL-C (AST/HDL-C) ratio, the gamma-glutamyl transferase to HDL-C (GGT/HDL-C) ratio and the ALT/HDL-C ratio in identifying NAFLD. Results We observed a significant positive association between the ALT/HDL-C ratio and the prevalence of NAFLD. For each standard deviation (SD) increase in the ALT/HDL-C ratio, the adjusted odds ratio (OR) for NAFLD among the participants was 3.05 [95% confidence interval (CI): 2.63, 3.53], with the highest quartile of ALT/HDL-C ratio having a 9.96-fold increased risk compared to the lowest quartile. In further subgroup analyses stratified by gender, age, and waist circumference (WC), we observed a significantly higher risk of NAFLD associated with the ALT/HDL-C ratio among individuals aged ≥45 years, males, and those who were abdominal obesity. Furthermore, based on the results of ROC analysis, we found that the ALT/HDL-C ratio [area under the curves (AUC): 0.8553] was significantly superior to ALT, HDL-C, AST/HDL-C ratio and GGT/HDL-C ratio in identifying NAFLD (All Delong P<0.05); the threshold of suggested ALT/HDL-C ratio for identifying NAFLD was 15.97. Conclusion This population-based study demonstrates a positive association between the ALT/HDL-C ratio and NAFLD. The ALT/HDL-C ratio can effectively identify individuals with NAFLD.
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Affiliation(s)
- Jiajun Qiu
- Department of Internal Medicine, Medical College of Nanchang University, Jiangxi Provincial People's Hospital, Nanchang, Jiangxi, China
- Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
| | - Maobin Kuang
- Department of Internal Medicine, Medical College of Nanchang University, Jiangxi Provincial People's Hospital, Nanchang, Jiangxi, China
- Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
| | - Ruijuan Yang
- Department of Internal Medicine, Medical College of Nanchang University, Jiangxi Provincial People's Hospital, Nanchang, Jiangxi, China
- Department of Endocrinology, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
| | - Changhui Yu
- Department of Internal Medicine, Medical College of Nanchang University, Jiangxi Provincial People's Hospital, Nanchang, Jiangxi, China
- Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
| | - Shiming He
- Department of Internal Medicine, Medical College of Nanchang University, Jiangxi Provincial People's Hospital, Nanchang, Jiangxi, China
- Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
| | - Guotai Sheng
- Jiangxi Provincial Geriatric Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
- Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
| | - Yang Zou
- Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
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Integrating Health Data-Driven Machine Learning Algorithms to Evaluate Risk Factors of Early Stage Hypertension at Different Levels of HDL and LDL Cholesterol. Diagnostics (Basel) 2022; 12:diagnostics12081965. [PMID: 36010315 PMCID: PMC9407063 DOI: 10.3390/diagnostics12081965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 08/08/2022] [Accepted: 08/11/2022] [Indexed: 11/26/2022] Open
Abstract
Purpose: Cardiovascular disease (CVD) is a major worldwide health burden. As the risk factors of CVD, hypertension, and hyperlipidemia are most mentioned. Early stage hypertension in the population with dyslipidemia is an important public health hazard. This study was the application of data-driven machine learning (ML), demonstrating complex relationships between risk factors and outcomes and promising predictive performance with vast amounts of medical data, aimed to investigate the association between dyslipidemia and the incidence of early stage hypertension in a large cohort with normal blood pressure at baseline. Methods: This study analyzed annual health screening data for 71,108 people from 2005 to 2017, including data for 27 risk-related indicators, sourced from the MJ Group, a major health screening center in Taiwan. We used five machine learning (ML) methods—stochastic gradient boosting (SGB), multivariate adaptive regression splines (MARS), least absolute shrinkage and selection operator regression (Lasso), ridge regression (Ridge), and gradient boosting with categorical features support (CatBoost)—to develop a multi-stage ML algorithm-based prediction scheme and then evaluate important risk factors at the early stage of hypertension, especially for groups with high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) levels within or out of the reference range. Results: Age, body mass index, waist circumference, waist-to-hip ratio, fasting plasma glucose, and C-reactive protein (CRP) were associated with hypertension. The hemoglobin level was also a positive contributor to blood pressure elevation and it appeared among the top three important risk factors in all LDL-C/HDL-C groups; therefore, these variables may be important in affecting blood pressure in the early stage of hypertension. A residual contribution to blood pressure elevation was found in groups with increased LDL-C. This suggests that LDL-C levels are associated with CPR levels, and that the LDL-C level may be an important factor for predicting the development of hypertension. Conclusion: The five prediction models provided similar classifications of risk factors. The results of this study show that an increase in LDL-C is more important than the start of a drop in HDL-C in health screening of sub-healthy adults. The findings of this study should be of value to health awareness raising about hypertension and further discussion and follow-up research.
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