Background and Purpose:
Lipid levels are established risk factors for ischemic heart disease, but uncertainty persists about the relevance of lipids for first ischemic stroke (IS). The goal of this study was to evaluate whether lipid profiles are risk factors for first IS in a Chinese hypertensive population.
Methods:
Our study population was selected from 300,000 individuals registered from 2016-2018 in the Lianyungang and Rongcheng “H-type hypertension prevention and control public service project”. Hypertensive patients with stroke data from the Chinese centers for disease control and prevention (CDC, 2013-2018) who had complete records (physical exam, questionnaire, and biological samples) were selected as cases. We used a nested case-control study design and matched 3615 ischemic stroke cases with an equal number of controls (hypertensive patients without stroke) for age±1 years, sex, and village. The crude and adjusted risks of first ischemic stroke were estimated by ORs and 95% CIs using conditional logistic regression, with or without adjustment for pertinent covariates.
Results:
Participants with first IS had higher blood pressure, body mass index, fasting glucose, triglycerides, and low-density lipoprotein cholesterol. High-density lipoprotein cholesterol (HDL-C) was significantly and inversely associated with IS risk (OR, 0.71; 95% CI: 0.61-0.82). When HDL was assessed as quartiles, the lowest quartile was used as reference, a significantly lower risk for IS was found in the highest quartile (HDL-C ≥ 1.8mmol/L: OR, 0.70; 95% CI: 0.59-0.82). There was a significant positive association between TG and the risk of IS (per SD increment; OR, 1.13; 95% CI, 1.07-1.20). Consistently, a significantly higher risk of first IS was found in quartile 4 (≥1.8 mmol/L: OR, 1.41; 95% CI, 1.20-1.65) compared with those in quartile 1 (<0.9 mmol/L).
Conclusions:
HDL-C levels inversely associated with first IS. These results differ from existing evidence from western populations, highlighting potential differences in Chinese populations. These differences can be attributed to multiple factors, including genetics, diet and lifestyle and call for further study to investigate potential explanatory mechanisms.