Author
Listed:
- Shukang Wang
(Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44, Wenhuaxi Street, Jinan 250012, Shandong, China
Institute for Medical Dataology, Shandong University, 12550, Erhuandong Street, Jinan 250002, Shandong, China)
- Xiaokang Ji
(Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44, Wenhuaxi Street, Jinan 250012, Shandong, China
Institute for Medical Dataology, Shandong University, 12550, Erhuandong Street, Jinan 250002, Shandong, China)
- Zhentang Zhang
(Qingdao West Coast New District Center for Disease Control and Prevention, 567, Lingshanwan Street, Huangdao District, Qingdao 266400, China)
- Fuzhong Xue
(Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44, Wenhuaxi Street, Jinan 250012, Shandong, China
Institute for Medical Dataology, Shandong University, 12550, Erhuandong Street, Jinan 250002, Shandong, China)
Abstract
Glycosylated hemoglobin (HbA1c) was the best indicator of glycemic control, which did not show the dynamic relationship between glycemic control and lipid profiles. In order to guide the health management of Type 2 diabetes (T2D), we assessed the levels of lipid profiles and fasting plasma glucose (FPG) and displayed the relationship between FPG control and lipid profiles. We conducted a cross-sectional study that included 5822 participants. Descriptive statistics were conducted according to gender and glycemic status respectively. Comparisons for the control of lipid profiles were conducted according to glycemic control. Four logistic regression models were generated to analyze the relationship between lipid profiles and glycemic control according to different confounding factors. The metabolic control percentage of FPG, triglyceride (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C) and low density lipoprotein cholesterol (LDL-C) was 27.50%, 73.10%, 28.10%, 64.20% and 44.80% respectively. In the fourth model with the most confounding factors, the odds ratios (ORs) and 95% confidence intervals (CIs) of TG, TC, LDL-C and HDL-C were 0.989 (0.935, 1.046), 0.862 (0.823, 0.903), 0.987 (0.920, 1.060) and 2.173 (1.761, 2.683). TC and HDL-C were statistically significant, and TG and LDL-C were not statistically significant with adjustment for different confounding factors. In conclusion, FPG was significantly associated with HDL and TC and was not associated with LDL and TG. Our findings suggested that TC and HDL should be focused on in the process of T2D health management.
Suggested Citation
Shukang Wang & Xiaokang Ji & Zhentang Zhang & Fuzhong Xue, 2020.
"Relationship between Lipid Profiles and Glycemic Control Among Patients with Type 2 Diabetes in Qingdao, China,"
IJERPH, MDPI, vol. 17(15), pages 1-11, July.
Handle:
RePEc:gam:jijerp:v:17:y:2020:i:15:p:5317-:d:388794
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