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. 2025 Jan;32(1):87-98.
doi: 10.1007/s40292-024-00683-9. Epub 2024 Nov 27.

The Association between Serum Lipid Profile Levels and Hypertension Grades: A Cross-Sectional Study at a Health Examination Center

Ling Huang #  1 , Zhangyi Liu #  1 , Huayang Zhang #  1 , Dan Li  1 , Zhiyi Li  1 , Jie Huang  1 , Jie He  1 , Lin Lu  1 , Hu Wen  1 , Huan Yuan  1 , Yinshan Gu  1 , Yunli Ye  2 , Jian Lu  1 , Bin Liao  3 , Zhengye Li  4 , Lin Wu  5 , Jinbo Liu  6 , Miaoling Li  7
Affiliations

The Association between Serum Lipid Profile Levels and Hypertension Grades: A Cross-Sectional Study at a Health Examination Center

Ling Huang et al. High Blood Press Cardiovasc Prev. 2025 Jan.

Abstract

Introduction: Hypertension and dyslipidemia are major cardiovascular risk factors that often coexist. Hyperlipidemia is a crucial modifiable risk factor in preventing cardiovascular disease.

Aim: We aimed to explore the relationship between lipid levels and the grading of hypertension in a community-based adult population.

Methods: A total of 63,091 non-employed individuals were included in this study. Measurements included systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), fasting plasma glucose (FPG), alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (STB), serum creatinine (SCr), blood urea nitrogen (BUN), total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-c), and high-density lipoprotein cholesterol (HDL-c). Chi-square and t-tests were used to obtain basic population characteristics. Multivariate logistic regression was used to evaluate the association between the prevalence of hypertension and lipid profiles, as well as to identify influencing factors. A P-value < 0.05 was considered statistically significant. Statistical charts were utilized to analyze the relationship between lipid parameters and hypertension grades.

Results: A total of 30,588 men and 32,503 women with an average age of 64.57 ± 12.5 years participated in this study. After adjusting STB and TC, every 1 mmol/L increase in TG and LDL-c was associated with a 6.0% and 6.5% increase in the prevalence of hypertension, respectively. Conversely, for every 1 mmol/L increase in HDL-c, the prevalence of hypertension decreased by 4.1%. Increases in TG and LDL-c levels were observed across all grades of hypertension, while very high HDL-c was significantly associated in grade III hypertension (1.54→1.66 mmol/L). Additionally, age, BMI, FPG, ALT, AST, SCr, and BUN significantly influenced the association between hypertension and lipid levels.

Conclusion: Hyperlipidemia and hypertension often coexist in health examination populations. Elevated levels of TG and LDL-C are associated with all grades of hypertension, while extremely high HDL-C level is linked to more severe hypertension.

Keywords: Cross-sectional study; Dyslipidemia; Health examination; Hypertension grades.

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Conflict of interest statement

Declarations. Data Availability: The datasets used and/or analyzed in the current study are available from the corresponding author Miaoling Li (limiaolingcc@swmu.edu.cn) upon reasonable request. Conflict of interest: The authors have no conflicts of interest to declare. Statement of Ethics: The study was reviewed and approved by the Ethics Committee of Xuyong County People’s Hospital (Xuyong, China). Written informed consent was obtained from all participants after oral and written information was provided. Funding Sources: This work was supported by the Fund of the Science and Technology Strategic Cooperation Project of the Government of Luzhou (2019LZXNYDF02) and Sichuan Science and Technology Program (2022YFS0610). Author Contributions: The members for data collection, analysis, and manuscript writing were as follows: Ling Huang, Zhangyi Liu, and Huayang Zhang contributed to the conceptualization, data acquisition, and analysis. Dan Li, Zhiyi Li, Jie Huang, Jie He, and Lin Lu contributed to data curation and formal analysis. Huan Yuan, Hu Wen, Yinshan Gu, Jian Lu and Yunli Ye contributed to the investigation and methodology. Bin Liao and Miaoling Li provided funds support and project administration. Zhengye Li, Jingbo Liu, and Miaoling Li contributed to software and visualization. Miaoling Li, Ling Huang, Huayang Zhang and Zhangyi Liu drafted Writing– review & editing the manuscript. All authors critically revised the manuscript.

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