Relationship of small dense low-density lipoprotein cholesterol level with pre-diabetes and newly detected type 2 diabetes

小而密低密度脂蛋白胆固醇水平与糖尿病前期和新诊断的2型糖尿病的关系

阅读:1

Abstract

To evaluate the relationship of serum small dense low-density lipoprotein cholesterol (sdLDL-C) level with pre-diabetes (PD) and newly detected type 2 diabetes (NT2D) in a Chinese adults population, a cross-sectional study was conducted in 2022 from May 26 to September 17. Permanent residents at the age of 30-69 years who lived in two communities in Zhejiang Province, China, and participated in a community health checkup were selected as the survey objects. According to their fasting plasma glucose and glycosylated hemoglobin, the eligible subjects were divided into normal blood glucose group, PD group, and NT2D group. Logistic regression model was used to explore the effect of sdLDL-C level on PD and NT2D, and restricted cubic spline (RCS) was adopted to display the nonlinear dose-response relationship of sdLDL-C with the prevalence of PD and NT2D. A total of 3570 subjects were included with a median age of 58 (52, 64) years, and 58.7% (2097) were women. The prevalence of PD was 53.6% (1913 cases), and NT2D was 9.2% (327 cases). Logistic regression analysis showed that after controlling the confounding factors (including LDL-C), for every 0.1 mmol/L increase in sdLDL-C, the risk of developing PD and NT2D increased by 3.4% (OR = 1.034, 95%CI:1.002-1.067) and 15.7% (OR = 1.157, 95%CI: 1.097-1.220), respectively. The RCS curves showed that with the increase of sdLDL-C, both the risk of PD (P = 0.037) and NT2D (P < 0.001) increased, but there were no nonlinear dose-response relationships between sdLDL-C with PD (P for non-linearity = 0.142) and NT2D (P for non-linearity = 0.227). Subjects are at increased risk of PD and NT2D with increase of serum sdLDL-C level. sdLDL-C is a promising risk factor for PD and NT2D independent of LDL-C.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。