CORRELATION BETWEEN HEMOGLOBIN A1C AND SERUM LIPID PROFILE WITH TYPE 2 DIABETES: A CROSS-SECTIONAL STUDY

Background: Diabetes is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both. Patients with type 2 diabetes (T2DM) have an increased prevalence ofdyslipidemia, which contributes to their high risk of cardiovascular diseases (CVDs). This study is an attempt to determine the correlation between hemoglobin A1C (HbA1c) and serum lipid profile and to evaluate the importance of HbA1c as an indicator of dyslipidemia with Type II diabetes mellitus. Methods: The study had 240 participants between the age groups of 20-70 years included 80 males and 40 females in diabetic group whereas the control group included 78 males and 42 females. T.cholesterol, Triglycerides, HDL were calculated by semi automated analyzer and LDL and VLDL were calculated by FriedewaldÃƒÂƒÃ‚Â¢ÃƒÂ‚Ã‚Â€ÃƒÂ‚Ã‚Â™s Formula. HbA1c was measured by turbidMetric Method. Results: Data was represented as mean ÃƒÂƒÃ‚Â‚ÃƒÂ‚Ã‚Â± standard deviation or median with statistically significant values of T. Cholesterol, LDL, HDL, TGs and HbA1c (P< 0.001). There was a significant positive correlation between HbA1c, TC, TG, and LDL-C. Patients with HbA1c value greater than 7.0% had significantly higher value of cholesterol, LDL-C, and compared with patients with an HbA1c value up to 7.0%. Conclusion: Significant positive correlation of HbA1c with Lipid profiles in our study suggests that HbA1c can also be used as a predictor of dyslipidemia in addition to a glycemic control parameter for prevention of complication.

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Correlation between hemoglobin A1c and serum lipid profile in Afghani patients with type 2 diabetes: hemoglobin A1c prognosticates dyslipidemia

Therapeutic Advances in Endocrinology and Metabolism ◽

10.1177/2042018817692296 ◽

2017 ◽

Vol 8 (4) ◽

pp. 51-57 ◽

Cited By ~ 10

Author(s):

Arshad Hussain ◽

Iftikhar Ali ◽

Muhammad Ijaz ◽

Afaq Rahim

Keyword(s):

Type 2 Diabetes ◽

Lipid Profile ◽

Serum Lipid ◽

Hemoglobin A1c ◽

Linear Regression Analysis ◽

Density Lipoprotein ◽

Preventive Measure ◽

Lipoprotein Cholesterol ◽

Serum Lipid Profile

Background: Patients with type 2 diabetes (T2DM) have an increased prevalence of dyslipidemia, which contributes to their high risk of cardiovascular diseases (CVDs). This study is an attempt to determine the correlation between hemoglobin A1c (HbA1c) and serum lipid profile and to evaluate the importance of HbA1c as an indicator of dyslipidemia in Afghani patients with T2DM. Methods: A total of 401 Afghani patients with T2DM (men, 175; women, 226; mean age, 51.29 years) were included in this study. The whole blood and sera were analyzed for fasting blood sugar (FBS), HbA1c, total cholesterol (TC), triglycerides (TGs), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C). Dyslipidemia was defined according to the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) guidelines. Diabetes was defined as per American Diabetes Association criteria. The correlation of FBS, HbA1c with lipid ratios and individual lipid indexes were analyzed. The statistical analysis was done by SPSS statistical package version 16.0. Results: The mean age ± standard deviation of male and female patients were 51.71 ± 11.70 and 50.97 ± 10.23 years respectively. There was a significant positive correlation between HbA1c, TC, TG, LDL-C and LDL-C/HDL-C ratio. The correlation between HbA1c and HDL-C was negative and was statistically nonsignificant. Furthermore, HbA1c was found to be a predictor of hypercholesterolemia, LDL-C and TG via a linear regression analysis. Patients with HbA1c value greater than 7.0% had significantly higher value of cholesterol, LDL-C, and LDL-C/HDL-C ratio compared with patients with an HbA1c value up to 7.0%. Conclusions: Apart from a reliable glycemic index, HbA1c can also be used as a predictor of dyslipidemia and thus early diagnosis of dyslipidemia can be used as a preventive measure for the development of CVD in patients with T2DM.

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