Association of Serum High-Density Lipoprotein Cholesterol with High Blood Pressures at Checkup: Results of Kanagawa Investigation of Total Checkup Data from the National Database-9 (KITCHEN-9)

Nakajima, Kei; Igata, Manami; Higuchi, Ryota; Tanaka, Kotone; Mizusawa, Kaori; Nakamura, Teiji

doi:10.3390/jcm10215118

Cited by 4 publications

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“…Dyslipidemia, either an increase in LDL-C or a decrease in HDL-C, also plays an important role in the development of CVD. Meanwhile, the biological interrelation between hypertension and LDL-C [ 13 , 68 ] or HDL-C [ 12 , 69 , 70 ] has been documented. The structural and functional change in LDL-C and HDL-C, inflammation, and oxidative stress may be associated with vascular atherosclerotic processes, and lead to elevation of blood pressure [ 71 ].…”

Section: Discussionmentioning

confidence: 99%

“…The relationships between HDL-C concentration categories and blood pressure are U- or J-shaped [ 69 , 70 , 72 , 73 , 74 ]. In the Kanagawa Investigation of Total Checkup Data from the National Database-9 study, Nakajima et al [ 70 ] found inverted J-shaped relationships between HDL-C and odds ratios for hypertension (≥140/90 mmHg) using the logistic regression analysis method, and both low and extremely high HDL-C concentrations are associated with high blood pressure within both sexes. In the South-West Seoul (SWS) Study, the elderly population with prehypertension combined with low HDL-C showed a twofold higher risk of all-cause mortality (HR: 2.01; 95% CI: 1.11–3.64) [ 69 ].…”

Section: Discussionmentioning

confidence: 99%

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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

et al. 2022

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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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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Integrating Health Data-Driven Machine Learning Algorithms to Evaluate Risk Factors of Early Stage Hypertension at Different Levels of HDL and LDL Cholesterol

et al. 2022

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“…In recent years, we have demonstrated the association of extremely high HDL-C, mostly defined as > 100 mg/dL, with diabetes [17], high blood pressure [18], and hypertensive retinopathy [31]. All of these are well-known risk factors for the incidence of kidney disease and proteinuria [1,2,4].…”

Section: Discussionmentioning

confidence: 99%

“…In recent years, we conducted large community-based studies [17,18] showing that very or extremely high HDL-C levels, such as levels over 100 mg/dL or below 50 mg/ dL, may be associated with diabetes and hypertension. These two diseases can impair kidney function over the time and eventually elicit proteinuria, mostly involving albuminuria [1,4].…”

Section: Introductionmentioning

confidence: 99%

U-Shaped Relationship Between Proteinuria and High-Density Lipoprotein Cholesterol: Results of Cross-Sectional and Six Years Cohort Studies (KITCHEN-10)

Igata

Nakajima

2022

J Clin Med Res

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Background: Although a very high level of high-density lipoprotein cholesterol (HDL-C) may be a potential cardiovascular disease risk factor, the detail and underlying mechanism remain unclear. Therefore, we examined the associations of serum HDL-C with the incidence of proteinuria, a predictor for cardiovascular disease, in a community-based study. Methods:We investigated clinical parameters, including serum HDL-C and proteinuria, among 1,191,409 people aged 40 -74 years who underwent a health checkup in a cross-sectional study. In the cohort study, the incidence of proteinuria after 6 years was investigated in 451,987 participants without proteinuria at baseline, who were simultaneously enrolled in the cross-sectional study. Results:The prevalence of proteinuria showed a U-shaped relationship with 10 HDL-C categories, with a minimum of 60 -89 mg/dL in the cross-sectional study. Logistic regression analysis showed similar U-shaped relationships between odds ratios for proteinuria and HDL-C categories, with a minimum of 70 -79 mg/dL. The associations between very high HDL-C (≥ 90 mg/dL) and proteinuria were strengthened after adjustment for body mass index (BMI). In the cohort study, a crude L-shaped relationship was observed between the incidence of proteinuria and baseline HDL-C, which turned into U-shaped relationship after adjustment for baseline BMI and HDL-C after 6 years.Conclusions: Low and very high levels of HDL-C may be associated with the incidence of proteinuria, and BMI may be a potent contributing factor to the underlying mechanism.

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The newly proposed alanine aminotransferase to high-density lipoprotein cholesterol ratio has shown effectiveness in identifying non-alcoholic fatty liver disease

Qiu,

Kuang,

Yang

et al. 2023

Front. Endocrinol.

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ObjectiveAlanine 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.MethodsWe 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.ResultsWe 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.ConclusionThis 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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Association of Serum High-Density Lipoprotein Cholesterol with High Blood Pressures at Checkup: Results of Kanagawa Investigation of Total Checkup Data from the National Database-9 (KITCHEN-9)

Cited by 4 publications

References 46 publications

Integrating Health Data-Driven Machine Learning Algorithms to Evaluate Risk Factors of Early Stage Hypertension at Different Levels of HDL and LDL Cholesterol

Integrating Health Data-Driven Machine Learning Algorithms to Evaluate Risk Factors of Early Stage Hypertension at Different Levels of HDL and LDL Cholesterol

U-Shaped Relationship Between Proteinuria and High-Density Lipoprotein Cholesterol: Results of Cross-Sectional and Six Years Cohort Studies (KITCHEN-10)

The newly proposed alanine aminotransferase to high-density lipoprotein cholesterol ratio has shown effectiveness in identifying non-alcoholic fatty liver disease

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