Apolipoprotein B/apolipoprotein A-I ratio in relation to the metabolic syndrome, its components, total cholesterol and low-density lipoprotein cholesterol in the population of Georgia

The study was designed to assess the association of ApolipoproteinB/ApolipoproteinA-I (ApoB/ApoA-I) ratio with metabolic syndrome, its components, total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) in the population of Georgia. The subjects were 1522 Georgians of Caucasian origin aged 18-80 (653 women and 869 men) without diabetes mellitus. The subjects were divided into two groups. High ApoB/ApoA-I ratio group was defined as gender-specific upper quartile (≥0.88 for women and (≥1.0 for men) and low ApoB/ApoA-I ratio group as the remaining three quartiles (<0.88 for women and <1.0 for men). ApoB/ApoA-I ratio was significantly higher in patients with vs. without MetS (p<.0001). Mean values of ApoB/ApoA-I ratio significantly increased as the numbers of MetS components increased (p<.0001 in both sexes). After adjustment for age and gender, ApoB/ApoA-I ratio was associated significantly with MetS as definition (OR=1.86), IR as definition (OR=9.83), LDL-C (OR=1.99), systolic pressure (OR=3.31), diastolic pressure (OR=1.64), fasting glucose (OR=2.46), triglycerides (OR=2.52), high-density lipoprotein cholesterol (OR=7.08) (all p<0.05).

Association of the apolipoprotein b/apolipoprotein a-I ratio, metabolic syndrome components, total cholesterol, and low-density lipoprotein cholesterol with insulin resistance in the population of georgia

The study was designed to assess the association between insulin resistance (IR) and apolipoprotein B/apolipoprotein A-I ratio (ApoB/ApoA-I ratio), metabolic syndrome (MetS) components, total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C) in the nondiabetic population of Georgia. The subjects were 1522 Georgians of Caucasian origin (mean age = 45 years, 653 women) without diabetes who had visited the clinics for a related health checkup between 2012 and 2013. IR was calculated using the computer homeostasis model assessment (HOMA2-IR) and was defined as the upper quartile. MetS was diagnosed using the updated ATP-III definition of the metabolic syndrome. Logistic and multiple regression models were used to estimate the association between IR and other components. IR was positively correlated with age, ApoB, ApoB/ApoA-I ratio, MetS components (excluding high-density lipoprotein cholesterol-HDL-C), LDL-C, fasting insulin, and TC and negatively correlated with HDL-C and ApoA-I in both sexes (all P < 0.001). In the logistic regression models, gender, age, ApoB/ApoA-I ratio, diastolic pressure, HDL-C, LDL-C, fasting glucose, and triglycerides were the covariates significantly associated with IR (OR: 8.64, 1.03, 17.95, 1.06, 0.13, 1.17, 3.75, and 2.29, resp.; all P < 0.05). Multiple regression models demonstrated that these components (except for HDL-C) made an independent contribution to the prediction of HOMA2 (all P < 0.05).