Association between hemoglobin A_1c, carotid atherosclerosis, arterial stiffness, and peripheral arterial disease in Korean type 2 diabetic patients

Article Outline

• Abstract
• 1. Introduction
• 2. Patients and methods
  • 2.1. Subjects
  • 2.2. CCA-IMT, carotid plaque, ABI, and baPWV
  • 2.3. Statistical analysis
• 3. Results
  • 3.1. General and biochemical characteristics
  • 3.2. Odds ratios for carotid plaque and PAD according to HbA1c tertiles
  • 3.3. Comparison of CCA-IMT and baPWV means according to tertiles of HbA1c
• 4. Discussion
• References
• Copyright

Abstract 

Aims

To evaluate the association between hemoglobin A_1c (HbA_1c), carotid atherosclerosis, arterial stiffness, and peripheral arterial disease (PAD) in Korean type 2 diabetic patients.

Methods

A total of 370 type 2 diabetic patients registered with the public health center in Gokseng-gun, Korea, participated in this study. Following an overnight fast, venous blood was collected and analyzed by high-performance liquid chromatography. The carotid intima-media thickness (IMT), amount of carotid plaque, brachial ankle pulse wave velocity (baPWV), and ankle-brachial index (ABI) of each patient were also assessed.

Results

For categorical variables, we performed logistic regression after adjustment for other CVD risk factors. There was a significant association between HbA_1c and carotid plaque [OR 2.66, 95% confidence interval (CI) 1.01 to 5.67 for the highest vs. the lowest tertile of HbA_1c], and PAD (OR 3.75, 95% CI 1.30 to 10.81). For continuous variables, we performed analysis of covariance (ANCOVA) after adjustment for other covariates. The mean values of common carotid artery intima-media thickness (CCA-IMT) and baPWV were not significantly different according to the HbA_1c tertiles.

Conclusion

HbA_1c was significantly associated with carotid plaque and PAD, but not CCA-IMT and baPWV in Korean type 2 diabetic patients.

Keywords: Diabetes mellitus, Type 2, Hemoglobin A, Glycosylated, Carotid atherosclerosis, Arterial stiffness, Peripheral vascular disease

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1. Introduction 

Diabetes and its associated complications are becoming a major burden to public health. The global prevalence of diabetes was estimated to be 171 million in 2000 (Wild et al., 2004); thus, glycemic control is an increasingly important clinical issue. Therefore, efforts to reduce the incidence of coronary heart disease (CHD) through risk factor evaluation should be the primary focus when caring for diabetic patients. One of these major risk factors is hyperglycemia.

Hemoglobin A_1c (HbA_1c) can be used to quantify average blood glucose levels over a 3-month period. Many studies have reported that high levels of HbA_1c are strongly associated with an increased risk of cardiovascular disease (CVD) (Selvin et al., 2004) and microvascular complications (Shichiri & Kishikawa, 2000, The Diabetes Control and Complications Trial Research Group, 1993, UK, 1998) such as nephropathy and retinopathy. It is unknown, however, whether HbA_1c levels are strongly associated with macrovascular complications such as stroke, atherosclerosis, CVD, and peripheral arterial disease (PAD). In one general population cohort study, HbA_1c was significantly associated with both all-cause and ischemic heart disease mortality (Hirai et al., 2008); however, in a separate general population cohort study, this relationship was not observed (de Vegt et al., 1999). Even after analyzing the results of the United Kingdom Prospective Diabetes Study (UKPDS) study, which is the largest and longest-running study of type 2 diabetes, it is unknown whether glucose control reduces a patient's risk of CVD (Genuth et al., 2003).

On the other hand, many surrogate measures for CVD that estimate subclinical atherosclerosis have been developed. For example, carotid artery intima-media thickness (IMT) is correlated with coronary artery disease, stroke, and several other risk factors (Chambless & Folsom, 2000, Grobbee & Bots, 1994, O'Leary & Polak, 1999, Onbas & Kantarci, 2005, Touboul & Elbaz, 2000, Tsivgoulis & Vemmos, 2006). Carotid plaque possesses different pathogenic characteristics as compared with IMT; however, both IMT and carotid plaque share a common association with atherosclerosis and ischemic heart symptoms (Androulakis & Andrikopoulos, 2000, Golledge & Greenhalgh, 2000). The ankle-brachial index (ABI) is an easy measure of the severity of PAD; therefore, ABI is commonly used to screen for peripheral vascular disease (PVD) in diabetic patients (Laurent et al., 2001). Finally, pulse wave velocity (PWV) has been identified as a strong independent predictor of cardiovascular risk (Blacher & Asmar, 1999, Blacher & Guerin, 1999).

Many studies have evaluated the association between these measures and HbA_1c; however, most researchers have only studied the association of HbA_1c with one or two variables. Therefore, it has been difficult to assess the association between HbA_1c and various subclinical atherosclerosis phenotypes.

In the present study, we measured HbA_1c, CCA-IMT, carotid plaque, baPWV, and ABI, and evaluated the overall association between HbA_1c levels, carotid atherosclerosis, arterial stiffness, and PAD in Korean type 2 diabetic patients.

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2. Patients and methods 

2.1. Subjects 

Of the 594 type 2 diabetics registered with the public health center in Gokseng-gun, Jeollanamdo, Korea, a total of 380 chose to participate in this study. Ten patients were excluded because they could not provide a blood sample; therefore, 370 (62.3%) patients were included in the study. Well-trained examiners interviewed the patients using a questionnaire that included questions regarding cigarette use, consumption of alcohol, physical activity, duration of diabetes, and antihypertension medication use.

Weight was measured to the nearest 0.1 kg while the subjects were dressed in light clothes. Height was measured to the nearest 0.1 cm in stocking feet. Abdominal circumference was measured to the nearest 0.1 cm at expiration through a horizontal plane around the abdomen at the level of the midpoint between the lowest rib and iliac crest. Blood pressure (BP) was measured twice using a standard mercury sphygmomanometer after the subjects had rested for at least 5 min.

Following an overnight fast, venous blood was collected and the serum was separated on-site and stored at −70°C until further analysis. The total cholesterol, high-density lipoprotein (HDL) cholesterol, and triglyceride concentrations were analyzed using enzymatic methods. All sera were examined using an automatic analyzer (Hitachi-7600, Hitachi, Ltd., Tokyo, Japan). Low-density lipoprotein (LDL) cholesterol was measured as proposed by Friedewald et al. (1972), except when the triglyceride level exceeded 400 mg/dl. In such instances, the data were treated as missing. The HbA_1c levels were analyzed by high-performance liquid chromatography using the VARIANT II system (Bio-Rad, Hercules, CA, USA). All subjects gave informed consent. The Chonnam National University Hospital institutional review board approved this study.

2.2. CCA-IMT, carotid plaque, ABI, and baPWV 

Well-trained medical doctors, who were blind to the subjects' clinical and laboratory information, performed ultrasonographic scans of the carotid arteries using high-resolution mode B ultrasound (SONOACE 9900, Medison, Korea) with an electrical linear array transducer (7.5 MHz). IMT was defined as the distance from the leading edge of the first echogenic line to the second echogenic line, which indicated the media–adventitia interface. Images of the thickest point within 10 mm from the common carotid artery (CCA) to the carotid bulb were saved as CCA-IMT and then measured using SigmaScan Pro version 5.0.0 (SPSS, Inc., Chicago, IL, USA). We used the mean of the right and left CCA-IMT in the analysis.

Two ultrasonography technicians evaluated the CCA, carotid bulb, and internal carotid artery in both sides to determine the amount of carotid plaque. Protrusions into the lumen that were 100% thicker than the nearest area were defined as plaque. If the plaque was the thickest point, the distance to the nearest point without plaque was defined as the IMT. We repeated ultrasound examinations in 189 subjects to ensure measurement reproducibility. The correlation coefficients for the intra- and interobserver variations were 0.90 and 0.86, respectively, for CCA-IMT. The kappa coefficients were 0.85 for within-examiner agreement and 0.76 for between-examiner agreement.

After at least a 5-min rest, the ABI and brachial-ankle PWV were calculated automatically in the supine position using the VP-1000 system (Colin Co., Komaki, Japan) with cuffs around both arms and ankles. If any of the ABIs was less than 0.9, the patient was defined as having PAD.

2.3. Statistical analysis 

Statistical analysis was done using SPSS 15.0 (SPSS). The plaque was dichotomized according to the number of carotid plaques (≤2 or >2), while PAD was dichotomized according to the ABI value (≤0.9 or >0.9). A logistic regression was used to provide odds ratios (ORs) for the categorical variables, carotid plaque and PAD data, according to the tertile of HbA_1c. Analysis of covariance (ANCOVA) was used to compare the means of the continuous variables, CCA-IMT and baPWV data, according to the HbA_1c tertiles. When we calculated PWV, we excluded the subjects whose ABI was less than 0.9 or who had CVD history. We defined hypertension as systolic BP ≥140 mmHg or diastolic BP ≥90 mmHg or taking antihypertension medication.

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3. Results 

3.1. General and biochemical characteristics 

General and biochemical characteristics of the 370 study subjects (121 men and 249 women) are presented in Table 1. Both age and age at diabetic diagnosis tended to decrease in patients with higher levels of HbA_1c. In contrast, diabetic duration, triglycerides, and fasting plasma glucose tended to increase in patients with lower HbA_1c. Lastly, patients with higher HbA_1c levels weighed more and a lower percentage tended to have ABIs ≥0.9.

Table 1. General and biochemical characteristics

Values are given as the mean±S.D. or n (%).

BMI, Body mass index; BP, blood pressure; HDL, high-density lipoprotein; LDL, low-density lipoprotein; HbA_1c, glycated hemoglobin; CCA, common carotid artery; IMT, intima-media thickness; baPWV, brachial-ankle pulse wave velocity; ABI, ankle-brachial index.

3.2. Odds ratios for carotid plaque and PAD according to HbA_1c tertiles 

The ORs for carotid plaque and PAD according to tertiles of HbA_1c are listed in Table 2. For plaque, the crude ORs for increasing tertiles of HbA_1c were not statistically significant; however, after adjusting for other covariates (i.e., sex, age, BMI, smoking, diabetic duration, hypertension, HDL, LDL, triglyceride, and fasting glucose) the OR showed that HbA_1c was significantly associated with plaque [OR 2.66, 95% confidence interval (CI) 1.01 to 5.67 for the highest vs. the lowest tertile of HbA_1c]. For PAD, the crude ORs for increasing tertiles of HbA_1c were marginally associated (OR 2.33, 95% CI 0.97 to 5.60). When we adjusted for other CV risk factors, HbA_1c was significantly associated with PAD (OR 3.75, 95% CI 1.30 to 10.81).

Table 2. Odds ratios for carotid plaque and PAD according to HbA_1c tertiles

PAD, Peripheral arterial disease.

Values are shown as OR (95% CI).

3.3. Comparison of CCA-IMT and baPWV means according to tertiles of HbA_1c 

The mean and standard errors for CCA-IMT and baPWV according to tertiles of HbA_1c are listed in Table 3. For CCA-IMT, the mean value was not significantly different when adjusted for other covariates (0.71, 0.73, 0.75; P=.120). Similarly, for baPWV, the mean value was not significantly different after adjusting for other CV risk factors (1770.4, 1770.4, 1833.3; P=.395).

Table 3. Comparison of CCA-IMT and baPWV means according to tertiles of HbA_1c

Values are shown as mean (S.E.).

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4. Discussion 

In the present study, we evaluated the association between HbA_1c, carotid atherosclerosis, arterial stiffness, and PAD in Korean type 2 diabetic patients. The ORs showed that HbA_1c is strongly associated with plaque and PAD after adjusting for other CVD risk factors such as sex, age, BMI, smoking, diabetic duration, hypertension, HDL, LDL, triglyceride, and fasting glucose. Based on an ANCOVA, the mean values of CCA-IMT and baPWV are not significantly different, according to HbA_1c tertile, after adjusting for other CV risk factors.

Similar to our results (OR 2.66, 95% CI 1.06 to 6.66 for the highest vs. the lowest tertile of HbA_1c), some studies have shown an association between HbA_1c and carotid plaque. In a previous study of 5960 subjects, HbA_1c was found to be significantly associated with carotid plaque (Jorgensen et al., 2004). When the researchers categorized HbA_1c into five groups, the prevalence of carotid plaque increased according to HbA_1c level (P for the trend=.002). Furthermore, when they categorized carotid plaque into four groups according to echogenicity (echogenic, predominantly echogenic, echolucent, and predominantly echolucent), the OR showed that HbA_1c was significantly associated with echogenic plaque (OR 5.81, 95% CI 1.37 to 24.73 for the highest vs. the lowest HbA_1c group). In addition, Ishizaka et al. (2003) studied the association between insulin resistance and carotid arteriosclerosis in 1238 subjects. They reported that HbA_1c is associated with carotid plaque and each 1% increase in HbA_1c is associated with a 34% increased risk of carotid plaque (95% CI 1.13 to 1.58).

In the present study, the mean value of CCA-IMT was not significantly different according to HbA_1c tertiles after adjusting for other CV risk factors (0.71, 0.73, 0.75; P=.120). Previous studies that have examined the relationship between HbA_1c and IMT appear to be controversial. In a study of 125 type 2 diabetic patients, researchers investigated the risk factors for asymptomatic atherosclerosis (Goya et al., 2003). Based on univariate and multivariate regression analyses, HbA_1c was not associated with mean IMT (β=0.045 and P=.620) and was not an independent risk factor for IMT. Similarly, in another study examining 71 newly diagnosed type 2 diabetes, there was no significant correlation between HbA_1c and IMT (β=−0.05 and P=NS) after adjusting for sex and age (β=−0.13 and P=NS) (Temelkova-Kurktschiev et al., 1999). In contrast, a cross-sectional study of 2060 diabetics found that there was a significant association between HbA_1c and IMT (Selvin et al., 2005). When ORs were calculated for thick IMT in the highest vs. lowest quartile of HbA_1c, the OR was 2.46 (95% CI 1.16 to 5.03) in unknown diabetic subjects and 2.62 (95% CI 1.36 to 5.06) in known diabetic subjects.

In the present study, the mean values of baPWV were not significantly different according to HbA_1c tertile after adjusting for other CV risk factors (1770.4, 1759.9, 1833.3; P=.395). In a study examining 292 hemodialysis patients, it was reported that HbA_1c was not significantly correlated with baPWV (r=0.092 and P=.125) and was not an independent factor for baPWV (Kumeda et al., 2008). Another study investigated the correlation between carotid IMT and PWV in 271 type 2 diabetic patients and 285 age-matched control subjects. These researchers found that carotid IMT and PWV were significantly higher in type 2 diabetic patients as compared with control subjects. Inconsistent with our results, however, HbA_1c was not an independent risk factor for carotid IMT and PWV in diabetic patients (Taniwaki et al., 1999).

Consistent with our results (OR 3.75, 95% CI 1.30 to 10.81 for the highest vs. the lowest tertile of HbA_1c), many studies have shown an association between HbA_1c and PAD. For example, Selvin et al. (2006) investigated a cohort composed of 1894 middle-aged diabetic patients for a duration of 9.8 years. They estimated the Cox proportional hazards risk of PAD by HbA_1c tertile and reported that the relative risk for PAD-related hospitalization by HbA_1c tertile was 2.73 (95% CI 1.16 to 6.40) for the second vs. the lowest tertile and 4.56 (95% CI 1.86 to 11.18) for the highest vs. the lowest tertile. In another study examining the relationship between increased HbA_1c levels and PAD in 224 patients with diabetes mellitus, increased HbA_1c levels were associated with a higher prevalence of severe PAD (Aronow et al., 2007). Adler et al. (2002) followed UKPDS subjects for up to 6 years and investigated the association between PVD incidence and other risk factors. They demonstrated that hyperglycemia was an independent risk factor for PVD in type 2 diabetes and each 1% increase in HbA_1c was associated with a 28% increased risk of PVD (OR 1.28, 95% CI 1.12 to 1.46).

The mechanisms by which hyperglycemia might lead to arteriopathy might become clear by recent studies. Accumulated advanced glycosylation end products have been known to be related with glycation and preferential oxidation of LDL and subsequent uptake by macrophages to form foam cells (Bowie et al., 1993), and, consequently, glycemia increases atherosclerosis (Ceriello et al., 1992). In addition, hyperglycemia increases protein kinase C activity, which may increase the risk of diabetic complications (Koya & King, 1998).

The atherosclerotic process consists of two different aspects: one is structural process (atherosis) and the other is functional process (sclerosis). IMT and also carotid plaque and ABI may assess the structure, and PWV may be a functional marker (Taniwaki et al., 1999). Based on our results, HbA_1c was associated with carotid plaque and PAD, but not CCA-IMT among structure markers nor baPWV, a functional marker. The exact reasons are unknown. One possible explanation is that, even though they are similar, they are not identical components (Bonithon-Kopp & Touboul, 1996, Forrest & Becker, 2000). Because the pathologic characteristics of IMT differ, at least in part, from those of plaque, some risk factors may differentially affect IMT and plaque (Ishizaka et al., 2003). In addition, thick IMT may precede plaque formation and increased IMT is a predictor for incidence of plaque (Zureik et al., 2000). Because the diabetic duration of our patients was long, the diabetic state itself may have more influence on the earlier marker, CCA-IMT, than plaque so the effects of HbA_1c are masked.

For dissociation between hyperglycemia and baPWV, one possible explanation is that arterial stiffness is strongly related to the ageing process (Benetos et al., 1993) because the arterial functional properties could be changed due to the fatiguing effects of cyclic stress, acting over many decades on the inert nonliving elastic fibers, with subsequent stretching of the artery wall and remodeling (O'Rourke, 1990). Since our patients are very old people, the ageing effect was so great that the effects of hyperglycemia may be covered.

Since glycated hemoglobin was first used, 30 years ago, to estimate glycemia levels in diabetic patients (Bunn & Gabbay, 1978, Koenig & Peterson, 1976), many clinical researchers have investigated the association between HbA_1c and diabetes complications. Among them, two major long-term multicenter studies that have been conducted are the Diabetes Control and Complications Trial (DCCT) in Type 1 subjects (The Diabetes Control and Complications Trial Research Group, 1993, The Diabetes Control and Complications Trial Research Group, 1995a, The Diabetes Control and Complications Trial Research Group, 1995b, The Diabetes Control and Complications Trial Research Group, 1996) and the UKPDS in Type 2 subjects (UK, 1998, UK Prospective Diabetes Study Group , 1999, Adler & Stratton, 2000). The DCCT provided strong evidence for a correlation between HbA_1c and microvascular disease (The Diabetes Control and Complications Trial Research Group, 1993); however, the relationship between HbA_1c and macrovascular disease was less clear (UK Prospective Diabetes Study Group, 1998). The usefulness of HbA_1c in type 2 diabetes was questioned over 10 years ago (McCance et al., 1988); postprandial hyperglycemia or glycemic spikes are thought to be a more predictive independent risk factor for CVD in type 2 diabetes patients than HbA_1c (Bonora & Muggeo, 2001, Lefebvre & Scheen, 1998, Temelkova-Kurktschiev & Koehler, 2000). It would have been beneficial to measure postprandial hyperglycemia or glycemic spikes and compare these measurements to HbA_1c; however, we did not have the ability to measure these factors in the present study.

This study possesses limitations inherent to any cross-sectional study. Specifically, we could not directly observe the incidence of CHD and PAD events but, instead, attempted to predict CHD and PAD incidence based on such indicators as IMT, carotid plaque, baPWV, and ABI. Despite its limitations, this study is a valuable evaluation of the association between HbA_1c and various subclinical atherosclerosis phenotypes, such as CCA-IMT, carotid plaque, ABI, and baPWV, in a single population.

In conclusion, HbA_1c was significantly associated with carotid plaque and PAD, but not carotid IMT and baPWV in Korean type 2 diabetic patients. Additional prospective studies are required to fully evaluate the mechanism underlying these associations in Korean patients with type 2 diabetes.

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