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Change in waist circumference and the progression of subclinical atherosclerosis in type 2 diabetes patients
Obesity Research & Clinical Practice (2011) 5, e202—e209
ORIGINAL ARTICLE
Change in waist circumference and the progression of subclinical atherosclerosis in type 2 diabetes patients Ji Sun Nam a, Minho Cho a, Jong Suk Park a,b, Chul Woo Ahn a,b,∗, Bong Soo Cha a, Eun Jig Lee a, Sung Kil Lim a, Kyung Rae Kim a, Hyun Chul Lee a a
Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea Severance Institute for Vascular and Metabolic Research, Gangnam Severance Hospital, Seoul, Republic of Korea
b
Received 14 August 2010 ; received in revised form 29 December 2010; accepted 18 January 2011
KEYWORDS Waist circumference; Intima media thickness; Type 2 diabetes mellitus
Summary Objective: We aimed to assess the effect of reducing body weight, waist circumference, and various metabolic parameters on the progression of carotid intima media thickness (IMT) in Korean type 2 diabetes patients. Methods: This study comprised of 173 patients. Anthropometric measurements, metabolic parameters, and carotid IMT were measured at baseline and 1 year later. Results: There were significant differences in waist circumference, HbA1c, and mean left and right IMT after 1 year. The change in waist circumference correlated with changes in HbA1c and changes in right and left IMT after adjusting for age, sex, and medications that could influence the IMT. In multiple regression analysis, the change in waist circumference was a significant predictor of the progression of maximum right and left IMT, with a marginal significance for the latter, and mean left IMT, independent of changes in body weight, BMI, HbA1c level, and the use of antihyperlipidemic, antiplatelet agents and thiazolidinediones. Conclusion: Controlling abdominal obesity seems to have a significant impact on the progression of subclinical atherosclerosis in patients with diabetes, and therefore, more efforts should be made toward reducing waist circumference to inhibit overt atherosclerotic diseases. © 2011 Published by Elsevier Ltd on behalf of Asian Oceanian Association for the Study of Obesity.
∗ Corresponding author at: Division of Endocrinology, Department for Internal Medicine, Yonsei University College of Medicine, Gangnam Severance Hospital, 612 Eonjuro, Gangnam-gu, 135-270 Seoul, Republic of Korea. Tel.: +82 2 2019 3339; fax: +82 2 3463 3882. E-mail address: [email protected] (C.W. Ahn).
1871-403X/$ — see front matter © 2011 Published by Elsevier Ltd on behalf of Asian Oceanian Association for the Study of Obesity.
doi:10.1016/j.orcp.2011.01.003
Change in waist circumference
Introduction Patient with diabetes are at three to four folds increased risk for developing cardiovascular and cerebrovascular diseases, and these are major causes of death in these patients [1]. Accelerated atherosclerosis is known to begin from the prediabetic stage [2], and thus the importance of early diagnosis and early intervention of diabetic macrovascular complications has been emphasized. The measurement of carotid intima media thickness (IMT) using high resolution B-mode ultrasound is one of the most widely used and reliable ways to assess subclinical as well as overt atherosclerosis in normal healthy, prediabetic, and diabetic patients, and it allows a quantitative as well as qualitative measurement of atherosclerosis [3,4]. Carotid artery IMT is associated with cardiovascular diseases, coronary atherosclerosis, and various risk factors for atherosclerosis, including components of the metabolic syndrome [4,5]. Furthermore, it predicts future cardiovascular events in subjects regardless of age, sex, and degree of glucose tolerance [4—6]. Patients with diabetes have increased IMT compared to normal and impaired glucose tolerant subjects [7]. Many efforts have been made to assess factors associated with the progression of IMT and find ways to delay its progression. In various cross sectional studies, anthropometric measurements like body weight, body mass index (BMI), and waist circumference, and metabolic parameters including triglycerides, low-density lipoprotein (LDL)-cholesterol level, inflammatory markers, and measures of insulin resistance have been shown to be in close relationships with carotid IMT [8—10]. In addition, lipid lowering agents [11], glucose lowering drugs like peroxisome proliferator-activated receptor r agonist [12] and alpha-glucosidase inhibitor [13], and antihypertensive drugs including certain angiotension-converting enzyme (ACE) inhibitors and angiotension II receptor blockers (ARB) [14] significantly reduced the progression of carotid IMT. Intensive lifestyle modification accompanied by weight loss and improved blood pressure, HbA1c and plasma glucose level resulted in a delayed progression of carotid IMT in patients with type 2 diabetes [15]. Abdominal obesity has been proven to be a better marker of cardiovascular diseases and metabolic syndrome than body weight or BMI [16], but in a clinical practice, waist circumference is often neglected. Our study results emphasize the importance of reducing waist circumference for the prevention of the progression of subclinical atherosclerosis. Although there are numerous
e203 cross-sectional studies that assessed factors related to atherosclerosis as well as factors that predict its progression [15—17], a prospective study that evaluated the association between changes in body weight and changes in waist circumference and the progression of carotid IMT in diabetes patients in Korea is lacking. In this study, we aimed to assess the effects of changes in body weight, waist circumference, and various metabolic parameters on the progression of carotid IMT in Korean obese and non-obese, type 2 diabetes patients.
Patients and methods Subjects This study comprised of 173 patients who are being followed for type 2 at the outpatient clinic of the department of Endocrinology and Metabolism at Gangnam Severance Hospital, Seoul, Korea. Patients with a history of ischemic heart disease, stroke, peripheral vascular diseases, chronic renal failure (Cr > 1.5 mg/dL), thyroid disease, neoplasm, and any acute or chronic inflammatory diseases were excluded. Current medications, including antihypertensives, lipid lowering drugs, and oral hypoglycemic agents or insulin, and smoking status were assessed in each patient. Body weight and height were measured in the morning with light clothing without shoes. BMI was calculated as body weight in kilograms divided by height in meters squared (kg/m2 ). Waist circumference was measured at the midway between the lower border of the rib cage and the iliac crest. The cutoff point of waist circumference for abdominal obesity was 85 cm for females and 90 cm for males according to the criteria for Korean metabolic syndrome by Korean Diabetes Association [18]. Blood pressure was taken after 5 min of rest. All participants gave the informed consent, and the study was approved by the Institutional Review Board of Gangnam Severance Hospital.
Biochemical measurements Blood sampling was done after an overnight fast. Serum glucose level was measured immediately by an autoanalyzer using the hexokinase method (Roche, Hitachi 747). HbA1c was measured by the high performance liquid chromatography method (Bio-Rad, Variant II). Serum insulin and c-peptide were determined by an enzyme chemiluminescence immuno-assay (ECIA, DPC, Immulite 2000), and insulin resistance was estimated using a Homeostasis Model Assessment of Insulin Resistance
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Table 1
Anthropometric and biochemical characteristics at baseline and 1 year follow-up. Total (n = 173) Baseline
Weight (kg) BMI (kg/m2 ) WC (cm) FPG (mg/dL) PPG (mg/dL) TC (mg/dL) TG (mg/dL) LDL-C (mg/dL) HDL-C (mg/dL) HbA1c (%) SBP (mmHg) DBP (mmHg) HOMA-IR Mean IMT, Rt (mm) Mean IMT, Lt Max IMT, Rt Max IMT, Lt
65.4 23.9 86.2 144.3 188.6 189.2 154.7 110.0 49.6 7.6 123.7 78.0 2.7 0.60 0.63 0.72 0.74
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
1 year f/u 11.8 3.1 9.2 74.6 12.7 38.4 32.6 51.2 11.4 2.3 13.1 9.4 2.3 0.15 0.17 0.23 0.21
65.1 23.1 84.3 127.9 169.3 179.6** 151.4 101.2 48.8 6.9 122.0 76.9 2.7 0.62 0.65 0.74 0.76
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
11.6 3.1 8.6*** 50.5** 7.4† 38.2 106.8 32.6** 12.9 1.7*** 13.3† 9.0 2.3 0.16* 0.17* 0.21 0.25
Abdominal obesity (+) (n = 95)
Abdominal obesity (−) (n = 78)
Baseline
Baseline
68.0 25.3 91.6 134.6 188.8 196.2 155.0 49.2 113.2 7.2 124.8 78.2 3.1 0.61 0.66 0.72 0.77
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
1 year f/u 12.4 2.9 7.7 60.3 96.3 36.2 92.1 10.7 33.4 1.7 12.1 8.6 1.9 0.15 0.18 0.17 0.23
67.1 25.2 86.9 128.3 166.5 187.5 145.1 108.9 48.9 6.8 124.8 78.2 4.0 0.61 0.67 0.71 0.78
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
12.3 2.9 8.6*** 54.1 64.9 37.1† 76.4 30.7* 12.4 1.4** 21.1 8.6 2.7 0.16 0.16 0.21 0.25
62.2 22.4 79.7 147.2 196.8 178.3 150.5 50.8 97.5 7.8 122.5 77.7 2.2 0.59 0.61 0.69 0.73
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
1 year f/u 10.1 2.6 6.2 71.2 115.8 36.9 121.6 13.3 36.2 2.6 14.3 10.4 2.4 0.16 0.15 0.20 0.21
62.6 22.7 80.8 127.8 168.1 169.2 155.1 90.0 49.0 7.0 122.5 77,7 2.9 0.59 0.62 0.69 0.72
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
10.3 2.6† 7.5 44.2* 71.0 36,6 131.0 32.9† 12.2 2.0** 14.3† 10.4† 5.5 0.16 0.18 0.22 0.29
Data are mean ± S/D; BMI, body mass index; WC, waist circumference; FPG, fasting plasma glucose; TC, total cholesterol; TG, triglyceride; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; HbA1c, hemoglobin A1c; SBP, systolic blood pressure; DBP, diastolic blood pressure; HOMA-IR, homeostasis model assessment of insulin resistance. † P < 0.1 compared to baseline value. * P < 0.05 compared to baseline value. ** P < 0.01 compared to baseline value. *** P < 0.001 compared to baseline value.
J.S. Nam et al.
Change in waist circumference
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Figure 1 Correlations between changes in waist circumference and changes in IMT.
(HOMA-IR) index, calculated from the following formula: HOMA-IR = fasting insulin (U/mL) × fasting plasma glucose (mmol/L)/22.5. Serum total cholesterol and HDL-cholesterol were assessed by the enzymatic methods (Daiichi, Hitachi 747) and serum triglycerides were measured by the enzymatic colorimetric methods (Roche, Hitachi 747). Serum LDL-cholesterol level was calculated according to the Friedewald formula.
B-mode ultrasonographic measurement of carotid IMT Carotid atherosclerosis was measured with high resolution B-mode ultrasonography (SSD-3500plus, ALOKA, Tokyo, Japan) using 10 MHz linear transducer. Patients were in supine position with the neck extended. IMT was measured in the longitudinal plane on the far wall of the common carotid artery, and it was the distance between the inner echogenic line representing the intima-blood junction and the outer echogenic line representing the adventitia-media junction. The maximum IMT and those measured 1 cm upstream and downstream from the maximum IMT were measured bilaterally, and thus total of six IMT values were obtained in each subject. After freezing the image, the electronic caliper was used to measure the distance, and the maximum IMT and mean IMT from six measurements were used in the analysis. All measurements were performed by a single, experienced sonographer.
Follow-up study The same anthropometric, biochemical parameters, and carotid artery IMT were measured 1 year later. Medication history during the 1 year follow-
up period was assessed, and those administered for more than 3 months were considered to have an influence on IMT.
Statistical analyses Values were defined as mean ± standard deviation. For comparison of baseline values, independent paired T test was used. For comparison of results at baseline and at the follow-up, paired-sample T test was performed. Differences in the variables were calculated by subtracting follow-up variables from the baseline variables, except for intima media thickness, which was calculated by subtracting the baseline value from the follow-up value. To assess the relationships between various parameters and the change of IMT spearman correlation analysis and multiple regression analysis were performed. The use of anti-platelet agents, anti-hyperlipidemic agents, and thiazolidinediones (Table 2) were included as confounding variables. P < 0.05 was considered statistically significant. Statistical analysis was performed using SPSS for Windows (version 12.0; Chicago, IL, USA). Table 2 Medications that have been administered for more than 3 months during the follow-up period. Drugs Anti-platelet agents Anti-hyperlipidemic agents Anti-diabetic drugs Insulin Sulfonylurea or meglitinides Metformin Thiazolidinediones Alpha glucosidase inhibitor
Number of patients (%) 102 (59.0%) 58 (33.5%) 16 (9.2%) 75 (43.4%) 52 (30.1%) 17 (9.8%) 6 (3.5%)
J.S. Nam et al.
In multiple regression analysis, the change in waist circumference was a significant predictor
± ± ± ± ± ± ± ± ± ± ↑/↔
−0.7 −0.3 −2.6 0.5 17 0.9 −9.4 −0.3 −1.4 −7.1 3.0 1.3 6.2 2.4 78.6 122 45.7 77.4 7.7 41.7 ± ± ± ± ± ± ± ± ± ±
↓
−0.2 −0.2 0.7 1.2 22.6 51.5 −8.4 15 −0.6 −12.7 −0.1 −0.05 0.4 1.2 20.3 50.3 −14.2 13.3 −0.9 −17.4 0.8 −2.6 3.6 0.1 −4.3 −15.5 −8.8 −9.5 −1.5 −5.4 1.5 0.2 3.5 0.6 13.1 6.9 −7.4 −9.1 0.8 −12.3
↑/↔
± ± ± ± ± ± ± ± ± ±
2.7 19.3 6.5 0.9 75.4 6.7 34.6 69.2 9.8 30.5
↑/↔
± ± ± ± ± ± ± ± ± ±
3.2* 1.6 5.8† 1.1* 46 65.1 45.3 70.0 7.2 36.9
0.8 −0.2 6.0 0.5 21.2 21.2 −7.3 −10.2 2.1 −12.4
± ± ± ± ± ± ± ± ± ±
3.2 1.7 5.7 1.3 74.6 73.7 50.4 74.7 6.2 38.8
↑/↔
± ± ± ± ± ± ± ± ± ±
2.8 19.7 6.5† 0.8 47.9† 32.7† 28.4 65 10† 28.5
↓
± ± ± ± ± ± ± ± ± ±
3.1 1.2 6.9 2.5 75.5 135 35.7 82.4 6.4 28.8 ↓ ↓
−0.7 −0.4 −2.3 0.5 19.2 10.3 −4.3 1.7 −1.2 −1.8
± ± ± ± ± ± ± ± ± ±
2.6 1.3 5.9† 1.4 73.2 51.4 50.5 176.7 8.6 50.5
Left max Left mean Left maximum Left mean
0.3 −2.8 5.86 0.1 2.7 −7.64 −8.7 −10.4 −0.4 −5.3 Weight BMI WC HbA1c FPG PPG TC TG HDL-C LDL-C
Independent predictors of the progression of IMT
Abdominal obesity (−)
When comparing various parameters between patients with progressive or unchanged IMT with those with regressed IMT, there were significant differences in changes in HbA1c level, postprandial glucose level, and waist circumference. In subgroup analysis for patients with and without abdominal obesity, in both groups, the degree of change in waist circumference was significantly different between patients with progressive IMT and with regressed IMT (Table 3). In the correlation analysis, the change in waist circumference correlated with a change in HbA1c (r2 = −0.115, P = 0.076) and changes in mean right IMT (r2 = −0.145, P = 0.025), maximum right IMT (r2 = −0.239, P = 0.001), mean left IMT (r2 = −0.146, P = 0.024), and maximum left IMT (r2 = −0.119, P = 0.066) after adjusting for age, sex, and medications that could influence IMT, including anti-platelet agents, lipid lowering drugs, and thiazolidinediones (Fig. 1). In contrast, no correlations were found between changes in IMT and changes in body weight or BMI. In patients with improved abdominal obesity, the progression of IMT was significantly less than those with no change or increase in waist circumference at the follow-up study (Table 4).
Abdominal obesity (+)
Relationship between changes in anthropometric parameters and changes in progression of IMT
Comparing changes in metabolic parameters over 1 year between patients with progressive IMT and regressed or same IMT at 1 year follow-up.
Among 173 patients, there were significant improvements in waist circumference, HbA1c, fasting plasma glucose, total cholesterol, and LDL-cholesterol level (all P < 0.05). In terms of carotid artery IMT, there were significant increases in mean left and right IMT (Table 1). When separate analysis was done to patients with and without abdominal obesity, there was a significant reduction in waist circumference only in the obese group (Table 1). During the follow-up period, 59% of patients were on anti-platelet agents, and 34% were on antihyperlipidemic medications (Table 2).
Table 3
Anthropometric and biochemical characteristics of patients at baseline and 1 year follow-up
2.6 1.3 6.5* 1.5 69.8 53.2 43.3 181 7.5 41.1
Results
Data are mean ± S/D; BMI, body mass index; WC, waist circumference; FPG, fasting plasma glucose; TC, total cholesterol; TG, triglyceride; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; HbA1c, hemoglobin A1c. † P < 0.1 compared to patients with improved IMT. * P < 0.05 compared to patients with improved IMT.
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of the progression of maximum right and mean left IMT, independent of changes in body weight, HbA1c level, smoking, and the use of anti-platelet, anti-hyperlipidemic agents, and thiazolidinediones (Table 5).
0.030 0.040 0.613 0.017
P-Value
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0.02 0.02 0.00 0.03 0.15 0.16 0.21 0.22 ± ± ± ± 0.64 0.62 0.73 0.73 0.14 0.15 0.22 0.19 ± ± ± ± −0.04 −0.02 −0.01 −0.02 0.19 0.15 0.31 0.21 Abbreviation: = follow-up IMT − baseline IMT.
± ± ± ± 0.64 0.58 0.77 0.67 0.18 0.15 0.22 0.18 ± ± ± ± 0.66 0.60 0.78 0.71 Left mean IMT Right mean IMT Left max IMT Right max IMT
Baseline
Follow-up
± ± ± ±
0.13 0.10 0.21 0.13
Baseline
0.61 0.60 0.73 0.70
Follow-up
Increased or same waist circumference (n = 86) (mean ± S.D.)
± ± ± ±
0.16 0.12 0.15 0.11
Discussion
Decreased waist circumference (n = 87) (mean ± S.D.)
Table 4 Comparing progression of IMT between patients with decreased waist circumference with those with same or increased waist circumference at 1 year follow-up.
Change in waist circumference
The present study is a prospective study assessing anthropometric and biochemical parameters and carotid IMT in patients with type 2 diabetes. It demonstrates that the change in waist circumference predicts the progression of IMT independent of body weight, HbA1c, smoking, and medications that may influence the IMT. Our study results are in line with previous studies which have demonstrated close relationships between abdominal obesity and clinical atherosclerotic events or subclinical atherosclerosis in cross sectional as well as prospective studies [16,19,20]. These studies emphasized the importance of baseline waist circumference as a marker of atherosclerotic event or the progression of atherosclerosis, but none studied how the change in waist circumference over a certain period is related to the progression of IMT. In a clinical practice, patients with diabetes are educated about healthy diet and exercise, and encouraged to maintain an ideal body weight. Many doctors monitor body weight, but although its importance is well known, waist circumference is often neglected [21]. Some patients find it easier to lose abdominal obesity, but have a hard time losing overall weight, and others, vice versa. Our study emphasizes the importance of reducing waist circumference independent of body weight, and it applies to both patients with and, to a less extent, to those without abdominal obesity. Waist circumference has several advantages over BMI or body weight. First, it correlates well with body fat, including both subcutaneous and visceral fat while BMI measures both fat and lean mass [21]. Although there are few studies that showed only a marginal or no superiority of waist circumference over BMI in predicting obesity-related mortality [22—25], many large population studies demonstrated a strong correlation between waist circumference and cardiometabolic risk as well as diabetes after adjusting for BMI [21,26,27]. The accumulation of visceral fat is associated with an atherogenic dyslipidemia, insulin resistance, and a prothrombotic state [21]. Visceral fats are believed to secrete inflammatory mediators
e208 Table 5
J.S. Nam et al. Multiple regression analyses with changes in IMT as a dependent variable. Abdominal obesity (+)
Weight WC HbA1c Smoking Use of lipid lowering drugs Use of TZD Use of Anti-platelet agents
Abdominal obesity (−)
Mean IMT, Lt (ˇ)
Max IMT, Lt (ˇ)
Mean IMT, Lt (ˇ)
Max IMT, Lt (ˇ)
−0.368* −0.273* 0.200† 0.027 0.055 −0.035 0.017
0.035 −0.245† −0.085 −0.153 −0.075 0.017 0.008
−0.107 −0.090 −0.070 0.094 0.210 −0.171 0.192
−0.054 −0.244 −0.160 −0.027 0.060 −0.013 0.032
Abbreviations: WC, waist circumference; TZD, thiazolidinedione 2 = 0.247, 0.082, 0.143, 0.095, respectively. P < 0.05, 0.5 < † P < 0.1.
and pathogenic adipocytokines, which then cause endothelial dysfunction and lead to atherosclerosis [21]. Our finding further strengthens these observations since it shows a cause-and-result relationship between waist circumference and subclinical atherosclerosis. A decrease in waist circumference in patients with and without abdominal obesity attenuated the progression of IMT, although at a lesser degree in lean patients. This is also in line with the results of recent studies which showed patients with and without central obesity benefited from weight and waist loss in terms of cardiometabolic risk factors [25,28]. There are several limitations in this study. First of all, some of the analysis did not reach a statistical significance due to a relatively small number of study subjects, and they should be confirmed by a large population study in the future. Secondly, 1 year follow-up period may be not long enough to observe significant changes in IMT. Although the progression of IMT was alleviated by several lipid lowering or antiplatelet drugs, atherosclerosis is a slow process, and a longer follow-up period to waist circumference was the only measure that represented abdominal obesity. Other tools such as computerized tomography or magnetic resonance imaging would have been more objective and reproducible measures. In addition, for an ethical reason, we did not control medications, including those that may influence the progression of IMT, during the follow-up period. We considered medications that were administered for more than 3 months to have an influence on IMT, and thus, included them as confounding variables during the analysis. Moreover, patients were treated on same standards of care, and thus the medication pattern was similar. Lastly, to prove our hypothesis that a reduced waist circumference which represents a less visceral fat, would lead to a lower circulating pathogenic adipocytokines, and prevent
the progression of atherosclerosis, measurement of adipocytokines is crucial. A future study should include baseline and follow-up measurement of various candidate adipocytokines. In summary, controlling abdominal obesity seems to have a significant impact on the progression of subclinical atherosclerosis in patients with diabetes or prediabetes, and more emphasis should be given to the waist circumference to inhibit overt atherosclerotic diseases.
Disclosure statement The authors state no conflict of interest to declare.
Acknowledgements This study was supported by a grant of the Seoul R&BD Program, Republic of Korea (10526).
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ORIGINAL ARTICLE
Change in waist circumference and the progression of subclinical atherosclerosis in type 2 diabetes patients Ji Sun Nam a, Minho Cho a, Jong Suk Park a,b, Chul Woo Ahn a,b,∗, Bong Soo Cha a, Eun Jig Lee a, Sung Kil Lim a, Kyung Rae Kim a, Hyun Chul Lee a a
Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea Severance Institute for Vascular and Metabolic Research, Gangnam Severance Hospital, Seoul, Republic of Korea
b
Received 14 August 2010 ; received in revised form 29 December 2010; accepted 18 January 2011
KEYWORDS Waist circumference; Intima media thickness; Type 2 diabetes mellitus
Summary Objective: We aimed to assess the effect of reducing body weight, waist circumference, and various metabolic parameters on the progression of carotid intima media thickness (IMT) in Korean type 2 diabetes patients. Methods: This study comprised of 173 patients. Anthropometric measurements, metabolic parameters, and carotid IMT were measured at baseline and 1 year later. Results: There were significant differences in waist circumference, HbA1c, and mean left and right IMT after 1 year. The change in waist circumference correlated with changes in HbA1c and changes in right and left IMT after adjusting for age, sex, and medications that could influence the IMT. In multiple regression analysis, the change in waist circumference was a significant predictor of the progression of maximum right and left IMT, with a marginal significance for the latter, and mean left IMT, independent of changes in body weight, BMI, HbA1c level, and the use of antihyperlipidemic, antiplatelet agents and thiazolidinediones. Conclusion: Controlling abdominal obesity seems to have a significant impact on the progression of subclinical atherosclerosis in patients with diabetes, and therefore, more efforts should be made toward reducing waist circumference to inhibit overt atherosclerotic diseases. © 2011 Published by Elsevier Ltd on behalf of Asian Oceanian Association for the Study of Obesity.
∗ Corresponding author at: Division of Endocrinology, Department for Internal Medicine, Yonsei University College of Medicine, Gangnam Severance Hospital, 612 Eonjuro, Gangnam-gu, 135-270 Seoul, Republic of Korea. Tel.: +82 2 2019 3339; fax: +82 2 3463 3882. E-mail address: [email protected] (C.W. Ahn).
1871-403X/$ — see front matter © 2011 Published by Elsevier Ltd on behalf of Asian Oceanian Association for the Study of Obesity.
doi:10.1016/j.orcp.2011.01.003
Change in waist circumference
Introduction Patient with diabetes are at three to four folds increased risk for developing cardiovascular and cerebrovascular diseases, and these are major causes of death in these patients [1]. Accelerated atherosclerosis is known to begin from the prediabetic stage [2], and thus the importance of early diagnosis and early intervention of diabetic macrovascular complications has been emphasized. The measurement of carotid intima media thickness (IMT) using high resolution B-mode ultrasound is one of the most widely used and reliable ways to assess subclinical as well as overt atherosclerosis in normal healthy, prediabetic, and diabetic patients, and it allows a quantitative as well as qualitative measurement of atherosclerosis [3,4]. Carotid artery IMT is associated with cardiovascular diseases, coronary atherosclerosis, and various risk factors for atherosclerosis, including components of the metabolic syndrome [4,5]. Furthermore, it predicts future cardiovascular events in subjects regardless of age, sex, and degree of glucose tolerance [4—6]. Patients with diabetes have increased IMT compared to normal and impaired glucose tolerant subjects [7]. Many efforts have been made to assess factors associated with the progression of IMT and find ways to delay its progression. In various cross sectional studies, anthropometric measurements like body weight, body mass index (BMI), and waist circumference, and metabolic parameters including triglycerides, low-density lipoprotein (LDL)-cholesterol level, inflammatory markers, and measures of insulin resistance have been shown to be in close relationships with carotid IMT [8—10]. In addition, lipid lowering agents [11], glucose lowering drugs like peroxisome proliferator-activated receptor r agonist [12] and alpha-glucosidase inhibitor [13], and antihypertensive drugs including certain angiotension-converting enzyme (ACE) inhibitors and angiotension II receptor blockers (ARB) [14] significantly reduced the progression of carotid IMT. Intensive lifestyle modification accompanied by weight loss and improved blood pressure, HbA1c and plasma glucose level resulted in a delayed progression of carotid IMT in patients with type 2 diabetes [15]. Abdominal obesity has been proven to be a better marker of cardiovascular diseases and metabolic syndrome than body weight or BMI [16], but in a clinical practice, waist circumference is often neglected. Our study results emphasize the importance of reducing waist circumference for the prevention of the progression of subclinical atherosclerosis. Although there are numerous
e203 cross-sectional studies that assessed factors related to atherosclerosis as well as factors that predict its progression [15—17], a prospective study that evaluated the association between changes in body weight and changes in waist circumference and the progression of carotid IMT in diabetes patients in Korea is lacking. In this study, we aimed to assess the effects of changes in body weight, waist circumference, and various metabolic parameters on the progression of carotid IMT in Korean obese and non-obese, type 2 diabetes patients.
Patients and methods Subjects This study comprised of 173 patients who are being followed for type 2 at the outpatient clinic of the department of Endocrinology and Metabolism at Gangnam Severance Hospital, Seoul, Korea. Patients with a history of ischemic heart disease, stroke, peripheral vascular diseases, chronic renal failure (Cr > 1.5 mg/dL), thyroid disease, neoplasm, and any acute or chronic inflammatory diseases were excluded. Current medications, including antihypertensives, lipid lowering drugs, and oral hypoglycemic agents or insulin, and smoking status were assessed in each patient. Body weight and height were measured in the morning with light clothing without shoes. BMI was calculated as body weight in kilograms divided by height in meters squared (kg/m2 ). Waist circumference was measured at the midway between the lower border of the rib cage and the iliac crest. The cutoff point of waist circumference for abdominal obesity was 85 cm for females and 90 cm for males according to the criteria for Korean metabolic syndrome by Korean Diabetes Association [18]. Blood pressure was taken after 5 min of rest. All participants gave the informed consent, and the study was approved by the Institutional Review Board of Gangnam Severance Hospital.
Biochemical measurements Blood sampling was done after an overnight fast. Serum glucose level was measured immediately by an autoanalyzer using the hexokinase method (Roche, Hitachi 747). HbA1c was measured by the high performance liquid chromatography method (Bio-Rad, Variant II). Serum insulin and c-peptide were determined by an enzyme chemiluminescence immuno-assay (ECIA, DPC, Immulite 2000), and insulin resistance was estimated using a Homeostasis Model Assessment of Insulin Resistance
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Table 1
Anthropometric and biochemical characteristics at baseline and 1 year follow-up. Total (n = 173) Baseline
Weight (kg) BMI (kg/m2 ) WC (cm) FPG (mg/dL) PPG (mg/dL) TC (mg/dL) TG (mg/dL) LDL-C (mg/dL) HDL-C (mg/dL) HbA1c (%) SBP (mmHg) DBP (mmHg) HOMA-IR Mean IMT, Rt (mm) Mean IMT, Lt Max IMT, Rt Max IMT, Lt
65.4 23.9 86.2 144.3 188.6 189.2 154.7 110.0 49.6 7.6 123.7 78.0 2.7 0.60 0.63 0.72 0.74
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
1 year f/u 11.8 3.1 9.2 74.6 12.7 38.4 32.6 51.2 11.4 2.3 13.1 9.4 2.3 0.15 0.17 0.23 0.21
65.1 23.1 84.3 127.9 169.3 179.6** 151.4 101.2 48.8 6.9 122.0 76.9 2.7 0.62 0.65 0.74 0.76
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
11.6 3.1 8.6*** 50.5** 7.4† 38.2 106.8 32.6** 12.9 1.7*** 13.3† 9.0 2.3 0.16* 0.17* 0.21 0.25
Abdominal obesity (+) (n = 95)
Abdominal obesity (−) (n = 78)
Baseline
Baseline
68.0 25.3 91.6 134.6 188.8 196.2 155.0 49.2 113.2 7.2 124.8 78.2 3.1 0.61 0.66 0.72 0.77
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
1 year f/u 12.4 2.9 7.7 60.3 96.3 36.2 92.1 10.7 33.4 1.7 12.1 8.6 1.9 0.15 0.18 0.17 0.23
67.1 25.2 86.9 128.3 166.5 187.5 145.1 108.9 48.9 6.8 124.8 78.2 4.0 0.61 0.67 0.71 0.78
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
12.3 2.9 8.6*** 54.1 64.9 37.1† 76.4 30.7* 12.4 1.4** 21.1 8.6 2.7 0.16 0.16 0.21 0.25
62.2 22.4 79.7 147.2 196.8 178.3 150.5 50.8 97.5 7.8 122.5 77.7 2.2 0.59 0.61 0.69 0.73
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
1 year f/u 10.1 2.6 6.2 71.2 115.8 36.9 121.6 13.3 36.2 2.6 14.3 10.4 2.4 0.16 0.15 0.20 0.21
62.6 22.7 80.8 127.8 168.1 169.2 155.1 90.0 49.0 7.0 122.5 77,7 2.9 0.59 0.62 0.69 0.72
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
10.3 2.6† 7.5 44.2* 71.0 36,6 131.0 32.9† 12.2 2.0** 14.3† 10.4† 5.5 0.16 0.18 0.22 0.29
Data are mean ± S/D; BMI, body mass index; WC, waist circumference; FPG, fasting plasma glucose; TC, total cholesterol; TG, triglyceride; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; HbA1c, hemoglobin A1c; SBP, systolic blood pressure; DBP, diastolic blood pressure; HOMA-IR, homeostasis model assessment of insulin resistance. † P < 0.1 compared to baseline value. * P < 0.05 compared to baseline value. ** P < 0.01 compared to baseline value. *** P < 0.001 compared to baseline value.
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Figure 1 Correlations between changes in waist circumference and changes in IMT.
(HOMA-IR) index, calculated from the following formula: HOMA-IR = fasting insulin (U/mL) × fasting plasma glucose (mmol/L)/22.5. Serum total cholesterol and HDL-cholesterol were assessed by the enzymatic methods (Daiichi, Hitachi 747) and serum triglycerides were measured by the enzymatic colorimetric methods (Roche, Hitachi 747). Serum LDL-cholesterol level was calculated according to the Friedewald formula.
B-mode ultrasonographic measurement of carotid IMT Carotid atherosclerosis was measured with high resolution B-mode ultrasonography (SSD-3500plus, ALOKA, Tokyo, Japan) using 10 MHz linear transducer. Patients were in supine position with the neck extended. IMT was measured in the longitudinal plane on the far wall of the common carotid artery, and it was the distance between the inner echogenic line representing the intima-blood junction and the outer echogenic line representing the adventitia-media junction. The maximum IMT and those measured 1 cm upstream and downstream from the maximum IMT were measured bilaterally, and thus total of six IMT values were obtained in each subject. After freezing the image, the electronic caliper was used to measure the distance, and the maximum IMT and mean IMT from six measurements were used in the analysis. All measurements were performed by a single, experienced sonographer.
Follow-up study The same anthropometric, biochemical parameters, and carotid artery IMT were measured 1 year later. Medication history during the 1 year follow-
up period was assessed, and those administered for more than 3 months were considered to have an influence on IMT.
Statistical analyses Values were defined as mean ± standard deviation. For comparison of baseline values, independent paired T test was used. For comparison of results at baseline and at the follow-up, paired-sample T test was performed. Differences in the variables were calculated by subtracting follow-up variables from the baseline variables, except for intima media thickness, which was calculated by subtracting the baseline value from the follow-up value. To assess the relationships between various parameters and the change of IMT spearman correlation analysis and multiple regression analysis were performed. The use of anti-platelet agents, anti-hyperlipidemic agents, and thiazolidinediones (Table 2) were included as confounding variables. P < 0.05 was considered statistically significant. Statistical analysis was performed using SPSS for Windows (version 12.0; Chicago, IL, USA). Table 2 Medications that have been administered for more than 3 months during the follow-up period. Drugs Anti-platelet agents Anti-hyperlipidemic agents Anti-diabetic drugs Insulin Sulfonylurea or meglitinides Metformin Thiazolidinediones Alpha glucosidase inhibitor
Number of patients (%) 102 (59.0%) 58 (33.5%) 16 (9.2%) 75 (43.4%) 52 (30.1%) 17 (9.8%) 6 (3.5%)
J.S. Nam et al.
In multiple regression analysis, the change in waist circumference was a significant predictor
± ± ± ± ± ± ± ± ± ± ↑/↔
−0.7 −0.3 −2.6 0.5 17 0.9 −9.4 −0.3 −1.4 −7.1 3.0 1.3 6.2 2.4 78.6 122 45.7 77.4 7.7 41.7 ± ± ± ± ± ± ± ± ± ±
↓
−0.2 −0.2 0.7 1.2 22.6 51.5 −8.4 15 −0.6 −12.7 −0.1 −0.05 0.4 1.2 20.3 50.3 −14.2 13.3 −0.9 −17.4 0.8 −2.6 3.6 0.1 −4.3 −15.5 −8.8 −9.5 −1.5 −5.4 1.5 0.2 3.5 0.6 13.1 6.9 −7.4 −9.1 0.8 −12.3
↑/↔
± ± ± ± ± ± ± ± ± ±
2.7 19.3 6.5 0.9 75.4 6.7 34.6 69.2 9.8 30.5
↑/↔
± ± ± ± ± ± ± ± ± ±
3.2* 1.6 5.8† 1.1* 46 65.1 45.3 70.0 7.2 36.9
0.8 −0.2 6.0 0.5 21.2 21.2 −7.3 −10.2 2.1 −12.4
± ± ± ± ± ± ± ± ± ±
3.2 1.7 5.7 1.3 74.6 73.7 50.4 74.7 6.2 38.8
↑/↔
± ± ± ± ± ± ± ± ± ±
2.8 19.7 6.5† 0.8 47.9† 32.7† 28.4 65 10† 28.5
↓
± ± ± ± ± ± ± ± ± ±
3.1 1.2 6.9 2.5 75.5 135 35.7 82.4 6.4 28.8 ↓ ↓
−0.7 −0.4 −2.3 0.5 19.2 10.3 −4.3 1.7 −1.2 −1.8
± ± ± ± ± ± ± ± ± ±
2.6 1.3 5.9† 1.4 73.2 51.4 50.5 176.7 8.6 50.5
Left max Left mean Left maximum Left mean
0.3 −2.8 5.86 0.1 2.7 −7.64 −8.7 −10.4 −0.4 −5.3 Weight BMI WC HbA1c FPG PPG TC TG HDL-C LDL-C
Independent predictors of the progression of IMT
Abdominal obesity (−)
When comparing various parameters between patients with progressive or unchanged IMT with those with regressed IMT, there were significant differences in changes in HbA1c level, postprandial glucose level, and waist circumference. In subgroup analysis for patients with and without abdominal obesity, in both groups, the degree of change in waist circumference was significantly different between patients with progressive IMT and with regressed IMT (Table 3). In the correlation analysis, the change in waist circumference correlated with a change in HbA1c (r2 = −0.115, P = 0.076) and changes in mean right IMT (r2 = −0.145, P = 0.025), maximum right IMT (r2 = −0.239, P = 0.001), mean left IMT (r2 = −0.146, P = 0.024), and maximum left IMT (r2 = −0.119, P = 0.066) after adjusting for age, sex, and medications that could influence IMT, including anti-platelet agents, lipid lowering drugs, and thiazolidinediones (Fig. 1). In contrast, no correlations were found between changes in IMT and changes in body weight or BMI. In patients with improved abdominal obesity, the progression of IMT was significantly less than those with no change or increase in waist circumference at the follow-up study (Table 4).
Abdominal obesity (+)
Relationship between changes in anthropometric parameters and changes in progression of IMT
Comparing changes in metabolic parameters over 1 year between patients with progressive IMT and regressed or same IMT at 1 year follow-up.
Among 173 patients, there were significant improvements in waist circumference, HbA1c, fasting plasma glucose, total cholesterol, and LDL-cholesterol level (all P < 0.05). In terms of carotid artery IMT, there were significant increases in mean left and right IMT (Table 1). When separate analysis was done to patients with and without abdominal obesity, there was a significant reduction in waist circumference only in the obese group (Table 1). During the follow-up period, 59% of patients were on anti-platelet agents, and 34% were on antihyperlipidemic medications (Table 2).
Table 3
Anthropometric and biochemical characteristics of patients at baseline and 1 year follow-up
2.6 1.3 6.5* 1.5 69.8 53.2 43.3 181 7.5 41.1
Results
Data are mean ± S/D; BMI, body mass index; WC, waist circumference; FPG, fasting plasma glucose; TC, total cholesterol; TG, triglyceride; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; HbA1c, hemoglobin A1c. † P < 0.1 compared to patients with improved IMT. * P < 0.05 compared to patients with improved IMT.
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of the progression of maximum right and mean left IMT, independent of changes in body weight, HbA1c level, smoking, and the use of anti-platelet, anti-hyperlipidemic agents, and thiazolidinediones (Table 5).
0.030 0.040 0.613 0.017
P-Value
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0.02 0.02 0.00 0.03 0.15 0.16 0.21 0.22 ± ± ± ± 0.64 0.62 0.73 0.73 0.14 0.15 0.22 0.19 ± ± ± ± −0.04 −0.02 −0.01 −0.02 0.19 0.15 0.31 0.21 Abbreviation: = follow-up IMT − baseline IMT.
± ± ± ± 0.64 0.58 0.77 0.67 0.18 0.15 0.22 0.18 ± ± ± ± 0.66 0.60 0.78 0.71 Left mean IMT Right mean IMT Left max IMT Right max IMT
Baseline
Follow-up
± ± ± ±
0.13 0.10 0.21 0.13
Baseline
0.61 0.60 0.73 0.70
Follow-up
Increased or same waist circumference (n = 86) (mean ± S.D.)
± ± ± ±
0.16 0.12 0.15 0.11
Discussion
Decreased waist circumference (n = 87) (mean ± S.D.)
Table 4 Comparing progression of IMT between patients with decreased waist circumference with those with same or increased waist circumference at 1 year follow-up.
Change in waist circumference
The present study is a prospective study assessing anthropometric and biochemical parameters and carotid IMT in patients with type 2 diabetes. It demonstrates that the change in waist circumference predicts the progression of IMT independent of body weight, HbA1c, smoking, and medications that may influence the IMT. Our study results are in line with previous studies which have demonstrated close relationships between abdominal obesity and clinical atherosclerotic events or subclinical atherosclerosis in cross sectional as well as prospective studies [16,19,20]. These studies emphasized the importance of baseline waist circumference as a marker of atherosclerotic event or the progression of atherosclerosis, but none studied how the change in waist circumference over a certain period is related to the progression of IMT. In a clinical practice, patients with diabetes are educated about healthy diet and exercise, and encouraged to maintain an ideal body weight. Many doctors monitor body weight, but although its importance is well known, waist circumference is often neglected [21]. Some patients find it easier to lose abdominal obesity, but have a hard time losing overall weight, and others, vice versa. Our study emphasizes the importance of reducing waist circumference independent of body weight, and it applies to both patients with and, to a less extent, to those without abdominal obesity. Waist circumference has several advantages over BMI or body weight. First, it correlates well with body fat, including both subcutaneous and visceral fat while BMI measures both fat and lean mass [21]. Although there are few studies that showed only a marginal or no superiority of waist circumference over BMI in predicting obesity-related mortality [22—25], many large population studies demonstrated a strong correlation between waist circumference and cardiometabolic risk as well as diabetes after adjusting for BMI [21,26,27]. The accumulation of visceral fat is associated with an atherogenic dyslipidemia, insulin resistance, and a prothrombotic state [21]. Visceral fats are believed to secrete inflammatory mediators
e208 Table 5
J.S. Nam et al. Multiple regression analyses with changes in IMT as a dependent variable. Abdominal obesity (+)
Weight WC HbA1c Smoking Use of lipid lowering drugs Use of TZD Use of Anti-platelet agents
Abdominal obesity (−)
Mean IMT, Lt (ˇ)
Max IMT, Lt (ˇ)
Mean IMT, Lt (ˇ)
Max IMT, Lt (ˇ)
−0.368* −0.273* 0.200† 0.027 0.055 −0.035 0.017
0.035 −0.245† −0.085 −0.153 −0.075 0.017 0.008
−0.107 −0.090 −0.070 0.094 0.210 −0.171 0.192
−0.054 −0.244 −0.160 −0.027 0.060 −0.013 0.032
Abbreviations: WC, waist circumference; TZD, thiazolidinedione 2 = 0.247, 0.082, 0.143, 0.095, respectively. P < 0.05, 0.5 < † P < 0.1.
and pathogenic adipocytokines, which then cause endothelial dysfunction and lead to atherosclerosis [21]. Our finding further strengthens these observations since it shows a cause-and-result relationship between waist circumference and subclinical atherosclerosis. A decrease in waist circumference in patients with and without abdominal obesity attenuated the progression of IMT, although at a lesser degree in lean patients. This is also in line with the results of recent studies which showed patients with and without central obesity benefited from weight and waist loss in terms of cardiometabolic risk factors [25,28]. There are several limitations in this study. First of all, some of the analysis did not reach a statistical significance due to a relatively small number of study subjects, and they should be confirmed by a large population study in the future. Secondly, 1 year follow-up period may be not long enough to observe significant changes in IMT. Although the progression of IMT was alleviated by several lipid lowering or antiplatelet drugs, atherosclerosis is a slow process, and a longer follow-up period to waist circumference was the only measure that represented abdominal obesity. Other tools such as computerized tomography or magnetic resonance imaging would have been more objective and reproducible measures. In addition, for an ethical reason, we did not control medications, including those that may influence the progression of IMT, during the follow-up period. We considered medications that were administered for more than 3 months to have an influence on IMT, and thus, included them as confounding variables during the analysis. Moreover, patients were treated on same standards of care, and thus the medication pattern was similar. Lastly, to prove our hypothesis that a reduced waist circumference which represents a less visceral fat, would lead to a lower circulating pathogenic adipocytokines, and prevent
the progression of atherosclerosis, measurement of adipocytokines is crucial. A future study should include baseline and follow-up measurement of various candidate adipocytokines. In summary, controlling abdominal obesity seems to have a significant impact on the progression of subclinical atherosclerosis in patients with diabetes or prediabetes, and more emphasis should be given to the waist circumference to inhibit overt atherosclerotic diseases.
Disclosure statement The authors state no conflict of interest to declare.
Acknowledgements This study was supported by a grant of the Seoul R&BD Program, Republic of Korea (10526).
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