Association of obesity and metabolic syndrome with the severity and outcome of intermittent claudication

Article Outline

• Abstract
• Methods
  • Patients
  • Clinical definitions
  • Blood analysis
  • Assessment of obesity and metabolic syndrome
  • Objective assessment of peripheral vascular disease
  • Follow-up
  • Statistical analysis
• Results
  • Characteristics of patients in relation to obesity and metabolic syndrome
  • Relationship between obesity or metabolic syndrome and severity of peripheral arterial disease
  • Effect of obesity and metabolic syndrome on intermediate outcome
• Discussion
• Author contributions
• Acknowledgment
• References
• Copyright

Background

Obesity is recognized as an independent predictor of coronary artery disease; however, its importance in peripheral arterial disease is less clear. The aim of this study was to assess the association between obesity and the severity and outcome of intermittent claudication.

Methods

This study was a prospective cohort study based at a tertiary referral center. Sixty patients with intermittent claudication selected for conservative treatment were assessed for obesity and metabolic syndrome by using the International Diabetes Federation definition. Other risk factors, including diabetes, hypertension, smoking history, serum lipids, adipocytokines, and C-reactive protein, were measured by clinical and blood assessment. Obesity and metabolic syndrome were related to the severity of peripheral arterial disease, defined by ankle-brachial pressure index and graded treadmill measured maximum walking distance (MWD) and initial claudication distance, by using multiple linear regression analysis allowing for traditional atherosclerotic risk factors. Patients were followed up for 24 months, and combined outcome was reported in terms of death, cardiovascular events, or requirement for revascularization. The effect of obesity and metabolic syndrome on outcome was investigated by using Kaplan-Meier and Cox proportional hazard analysis.

Results

Obesity and serum adiponectin were independently associated with the severity of peripheral arterial disease measured by ankle-brachial pressure index (P = .03 and .001), initial claudication distance (P = .009 and .03), and MWD (P = .001 and .04). Metabolic syndrome was independently associated only with MWD (P = .02). By 24 months, outcome events occurred in 37% ± 7% and 43% ± 9% of patients with metabolic syndrome or obesity, respectively, compared with 0% and 11% ± 6% of those without these diagnoses. Waist circumference independently predicted the likelihood of outcome events (relative risk, 1.16; 95% confidence interval, 1.08-1.26; P < .001).

Conclusions

These findings, if confirmed in other cohorts, suggest the importance of treating obesity in patients with intermittent claudication. Serum adiponectin concentrations may be an important guide to the efficacy of treatment in patients with intermittent claudication and obesity.

The increasing incidence of obesity has focused research on this modifiable risk factor for cardiovascular disease.¹, ² There is particular interest in a constellation of risk factors associated with obesity, known as the metabolic syndrome, that are thought to result from insulin resistance.³ Some, but not all, studies suggest an independent association between obesity or metabolic syndrome and coronary events.⁴, ⁵, ⁶, ⁷ Because peripheral arterial disease is common in patients with diabetes mellitus, it is not surprising that metabolic syndrome has been particularly linked with lower limb artery disease.⁸, ⁹ In animal models, obesity has been specifically linked with impaired limb blood flow.¹⁰ The interpretation of studies of obesity and metabolic syndrome is complicated by the use of a number of different definitions and evidence; depending on which criteria are used, the outcome varies.⁴, ¹¹ Two large population studies found no association between body mass index and symptomatic or asymptomatic lower limb artery disease.¹², ¹³ In one of these studies in which 708 men were examined, a waist-hip ratio above the median was independently associated with peripheral arterial disease at an odds ratio of 1.7.¹³ These findings support studies of coronary artery disease indicating that abdominal girth is a much more important risk factor for vascular disease than body mass index.⁴ It has been suggested that screening patients with demonstrated vascular disease for obesity and metabolic syndrome may identify high-risk subgroups to direct intensive treatment.¹⁴ Few studies have examined the effect of obesity and metabolic syndrome on the outcome in patients with existing peripheral arterial disease. In this study, we assessed the prevalence of metabolic syndrome and obesity in a cohort of patients with intermittent claudication. We used girth measurements and the International Diabetes Federation definition of metabolic syndrome.¹⁵ We assessed two hypotheses: (1) that obesity and/or metabolic syndrome is associated with more severe intermittent claudication and (2) that obesity and/or metabolic syndrome is associated with a poorer prognosis during follow-up, as evidenced by more frequent cardiovascular or revascularization events.

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Methods 

Patients 

Approval for this study was provided by the ethics committees of the Townsville Hospital, the Mater Hospital, and James Cook University. In this prospective study, we consecutively assessed patients with symptomatic peripheral arterial disease referred to the Townsville Hospital. Patients were initially assessed by a consultant vascular surgeon to identify those with intermittent claudication secondary to peripheral arterial disease. Intermittent claudication was defined by an appropriate history, a positive Edinburgh claudication questionnaire response, and an ankle-brachial pressure index (ABPI) less than 0.9.¹⁶ Patients with critical ischemia (rest pain or tissue loss) or nonvascular symptoms were excluded. Because only patients with lifestyle-limiting intermittent claudication are referred to the vascular clinic, all patients underwent a computed tomographic angiogram to assess whether endovascular therapies were feasible. Because the second aim of this study was to assess the association between obesity and cardiovascular or revascularization events, patients selected for endovascular or open vascular surgery were excluded. The remaining patients who had intermittent claudication and were selected for medical treatment were eligible for the study. Medical treatment consisted of advice on exercise, smoking cessation, and control of cardiovascular risk factors under the supervision of a cardiovascular physician. As a result, 10 and 6 patients were started on treatment for diabetes and dyslipidemia, respectively. The patients had detailed further assessment, including recording of medical history, examination, blood, and imaging findings.

Clinical definitions 

Hypertension was defined by systolic blood pressure of 130 mm Hg or higher, diastolic blood pressure of 85 mm Hg or higher, or previously diagnosed and treated high blood pressure.¹⁵ Diabetes was defined by a fasting blood glucose of 7.0 mmol/L or higher or, for patients with fasting glucose between 6.1 and 6.9 mmol/L, a positive oral glucose tolerance test.¹⁷ Cigarette smoking classification was based on a history as current smokers (smoked within the last month), ex-smokers (given up for more than 1 month), and never-smokers. Ischemic heart disease was defined by a history of myocardial infarction, angina, or coronary revascularization. Cerebrovascular disease was defined by a history of stroke, transient ischemic attack, or cerebral revascularization. Dyslipidemia was defined according to the European Joint Society of Cardiologists criteria as total cholesterol of 4.5 mmol/L or higher, low-density lipoprotein 2.5 mmol/L or higher, or current lipid-lowering treatment.¹⁸

Blood analysis 

Blood was collected after an overnight fast and assessed for full blood count, urea and electrolytes, glucose, cholesterol, triglycerides, high-density lipoprotein (HDL), low-density lipoprotein, and C-reactive protein (CRP), as previously described.¹⁹ Blood glucose was measured by the glucose oxidase method, lipids by automated enzymatic methods, and CRP by particle-enhanced turbidimetry (Roche Diagnostics, Basel, Switzerland).¹⁹ Serum was stored at −80°C for later batch assessment of adiponectin, leptin, and resistin concentrations by using enzyme-linked immunosorbent assay (R&D Systems). Intra-assay and interassay coefficients of variation for these assays are between 3% and 6% in our laboratory.

Assessment of obesity and metabolic syndrome 

On entry into the study, patients’ weight, height, and waist and hip circumference were measured in accordance with guidelines of the International Society for the Advancement of Kinanthropometry.²⁰ The percentage body fat was measured by bioelectrical impedance scales (TBF 521; Tanita Corporation of America, Arlington Heights, Ill).²¹ Body mass index was calculated as weight in kilograms divided by height in meters squared. Obesity and metabolic syndrome were defined by using the International Diabetes Federation classification, which uses varying waist circumferences for different populations. In our study, because patients were of European origin, we defined obesity as a waist circumference of 94 cm or greater for men and 80 cm or greater in women.¹⁵ Metabolic syndrome was diagnosed when obesity was present in addition to two of the following: fasting triglycerides 1.7 mmol/L or more or specific treatment to decrease triglycerides; HDL less than 1.03 mmol/L in men or less than 1.29 mmol/L in women or specific treatment to increase HDL; hypertension; fasting glucose 5.6 mmol/L or more; or treated diabetes mellitus.¹⁵

Objective assessment of peripheral vascular disease 

A consultant vascular surgeon documented the presence of peripheral pulses and reviewed the computed tomographic angiogram. The site of arterial occlusions or stenoses greater than 50% was documented from the angiogram, and the peripheral vascular disease was recorded as aortoiliac, infrainguinal, or combined. ABPI measurements were performed by a qualified sonographer. Participants rested supine for 10 minutes before measurement of the ABPI. The ABPI was calculated by measuring the systolic blood pressure at the ankle (taking the highest of either the dorsalis pedis or posterior tibial arteries) with a handheld bidirectional Doppler scanner (MD6; D.E. Hokanson Inc., Bellevue, Wash, USA) and then dividing that value by the systolic blood pressure in the brachial artery.²² Larger sphygmomanometer cuffs were used in obese patients. Treadmill assessment was also performed. Patients were initially familiarized with walking on the treadmill by a practice session. Maximum walking distance (MWD) and initial claudication distance (ICD) were subsequently measured during a graded treadmill test.²³ The treadmill test commenced at 3.2 km/h and an incline of 0%, and the incline was increased by 2% every 2 minutes until voluntary exhaustion or maximal claudication pain.²⁴

Follow-up 

Patients were followed up at 3, 6, 12, 18, and 24 months. Notes were flagged to identify events outside the review visits. The following end points were noted: death, myocardial infarction, stroke, and coronary or peripheral revascularization.

Statistical analysis 

Data were recorded in a spreadsheet (Excel; Microsoft, Redmond, Wash) and transferred to a statistical package for analysis (SPSS 12.0; SPSS Inc, Chicago, Ill). Initially the relationships between waist circumference, waist-hip ratio, and circulating adipocytokines and ABPI, ICD, and MWD were assessed. To investigate the independent association of obesity and metabolic syndrome with the severity of intermittent claudication, multiple linear regression analysis was performed by using the dependent variables ABPI, ICD, or MWD and the covariants age, sex, smoking history, diabetes, hypertension, and dyslipidemia (the last three criteria were not included in metabolic syndrome analyses because these are part of the diagnostic criteria). The influence of obesity or metabolic syndrome on combined end points during follow-up was assessed with Kaplan-Meier analysis. Because all events occurred in patients with metabolic syndrome, we used a surrogate marker of obesity—ie, waist circumference—to perform a Cox proportional hazard analysis allowing for other determinants of cardiovascular events (age, sex, smoking, diabetes, hypertension, and dyslipidemia).

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Results 

Characteristics of patients in relation to obesity and metabolic syndrome 

Between June 2003 and June 2005, 60 patients were entered into the study, of whom 48 were defined as obese and 44 as having metabolic syndrome. The characteristics of patients in relation to whether they were obese or had metabolic syndrome are illustrated in Table I.

Table I. Characteristics of patients with intermittent claudication in relation to obesity and metabolic syndrome

Variable	Overall	Obesity		Metabolic syndrome
		Present	Absent	Present	Absent
n	60	48	12	44	16
Age (y)	67.3±7.8	68.40±7.41	63.00±8.34	68.70±7.67	63.50±7.20
Male	30	28	2	28	2
Current smoker	18	12	6	12	6
Ex-smoker	28	28	0	28	0
Nonsmoker	14	8	6	4	10
Diabetes mellitus	22	19	3	19	3
Hypertension	46	38	8	34	12
IHD	18	15	3	15	3
CVD	8	6	2	6	2
Waist circumference (cm)	94.71±13.97	99.55±10.02	75.32±10.23	100.87±9.41	77.75±9.80
Waist-hip ratio	0.901±0.091	0.928±0.071	0.795±0.084	0.939±0.064	0.798±0.072
BMI (kg/m2)	28.37±4.39	29.86±3.22	22.40±3.27	30.17±3.19	23.43±3.36
% Fat	33.21±7.22	36.11±6.42	30.11±6.82	34.10±7.40	30.78±6.27
Cholesterol (mmol/L)⁎	4.99±1.12	4.97±1.16	5.07±0.99	4.94±1.20	5.13±0.87
Triglyceride (mmol/L)†	1.75±0.98	1.88±1.03	1.23±0.51	1.96±1.04	1.18±0.46
HDL (mmol/L)⁎	1.45±0.43	1.41±0.45	1.58±0.30	1.39±0.46	1.61±0.27
LDL (mmol/L)⁎	2.77±1.03	2.73±1.03	2.94±1.04	2.69±1.07	2.99±0.91
CRP (mg/L)	4.56±7.13	5.31±7.79	1.63±1.68	5.59±8.07	1.78±1.69
Lowest ABPI	0.61±0.14	0.58±0.13	0.70±0.08	0.58±0.14	0.67±0.08
MWD (m)	425.54±279.90	371.85±232.28	640.24±356.11	373.44±237.19	568.79±342.08
ICD (m)	219.71±214.20	182.67±186.12	367.87±261.04	190.30±191.57	300.57±256.40
Adiponectin (μg/mL)	10.15±3.17	9.40±2.81	13.14±2.86	9.71±2.73	11.37±4.00
Leptin (ng/mL)	83.25±94.08	90.99±101.25	52.28±48.60	87.95±105.03	70.32±54.32
Resistin (ng/mL)	20.61±19.50	21.40±21.37	17.46±8.57	21.92±22.15	17.00±8.39

IHD, Ischemic heart disease; CVD, cerebrovascular disease; BMI, body mass index; HDL, high-density lipoprotein; LDL, low-density lipoprotein; CRP, C-reactive protein; ABPI, ankle-brachial pressure index; MWD, maximum walking distance; ICD, initial claudication distance.

Shown are numbers or mean ± SD.

Relationship between obesity or metabolic syndrome and severity of peripheral arterial disease 

Waist-hip ratio, but not waist circumference, was correlated with the severity of peripheral arterial disease as assessed by ABPI (r = 0.41; P = .001; Fig, a), but not by MWD (r = 0.18; P = .17) or ICD (r = 0.21; P = .10). The severity of peripheral arterial disease by all three different definitions was correlated with serum adiponectin concentrations (Fig, b-d). Allowing for other known determinants of atherosclerosis, obesity was independently associated with the severity of lower limb artery disease (Table II). Metabolic syndrome was associated with the severity of intermittent claudication as defined by MWD only (standardized coefficient = −0.343; P = .02), allowing for age, sex, and smoking history. The adipocytokines adiponectin and leptin were strongly associated with ABPI after adjustment for traditional cardiovascular risk factors (Table III). Serum adiponectin was also weakly independently associated with MWD (standardized coefficient = 0.277; P = .04) and ICD (standardized coefficient = 0.292; P = .03).

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• Fig. 

  Scatterplots showing the relationship between waist-hip ratio or serum adiponectin and the severity of lower limb artery disease. Waist-hip ratio was correlated with ankle-brachial pressure index (ABPI) (a, r = −0.41; P = .001). Serum adiponectin was correlated with ABPI (b, r = 0.31; P = .01), maximum walking distance (MWD) (c, r = 0.26; P = .04), and initial claudication distance (ICD) (d, r = 0.36; P = .005).

Table II. Multiple regression models relating traditional risk factors and obesity to severity of peripheral arterial disease

PAD, Peripheral arterial disease; ABPI, ankle-brachial pressure index; ICD, initial claudication distance; MWD, maximum walking distance.

Overall model: ABPI, F = 3.52, P = .004; ICD, F = 2.35, P = .03; MWD, F = 0.69, P = .003.

Table III. Multiple regression model relating traditional risk factors and adipocytokines to ABPI

ABPI, Ankle-brachial pressure index.

Overall model: F = 5.04; P < .001.

Effect of obesity and metabolic syndrome on intermediate outcome 

Patients were followed up for a minimum of 12 months unless they experienced a terminal event. Three patients died 15, 21, and 22 months after entry into the study. Although no autopsies were performed, the deaths were all believed to be secondary to cardiac events. Twelve further cardiovascular events occurred. Four patients had nonfatal myocardial infarctions, and one was treated by a coronary artery bypass graft. Three patient experienced minor strokes, and one subsequently underwent a carotid endarterectomy. Two patients developed critical lower limb ischemia and required open arterial reconstruction (aortic bypass and femoropopliteal bypass). Three patients had deterioration of their intermittent claudication and underwent peripheral revascularization. By Kaplan-Meier analysis at 24 months, the incidence of cardiovascular events was 37.2% ± 7.4% and 42.8% ± 9.1% in patients with metabolic syndrome and obesity, respectively, compared with 0% and 11.2% ± 6.1% in patients without these diagnoses. Because no event occurred in patients without metabolic syndrome, it was problematic to relate obesity and metabolic syndrome independently to cardiovascular outcome. We therefore used waist circumference as a continuous variable and performed Cox proportional hazard analysis. Waist circumference was independently associated with an increased risk of cardiovascular events (Table IV).

Table IV. Predictors of outcome events

CI, Confidence interval.

Overall model: χ² = 32.4; P < .001.

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Discussion 

The incidence of obesity is increasing, and there is now greater focus on this risk factor as a cause of coronary artery disease.¹, ², ³, ⁴, ⁵, ⁶ Lower limb artery disease is present in approximately 10% of the population over 60 years old, but in comparison with ischemic heart disease, it is poorly investigated.²⁵ The importance of obesity in the development and progression of peripheral arterial disease has received relatively little attention. The recent American task force practice guidelines for the management of patients with peripheral arterial disease did not consider obesity as a treatable cause of lower limb artery disease.²⁶ Some, but not all, studies have correlated obesity with the presence of lower limb artery disease, particularly when obesity is defined by abdominal girth measurements.⁷, ⁸, ⁹, ¹², ¹³, ¹⁴, ²⁷, ²⁸ However, there are few investigations of how obesity affects the severity and outcome of lower limb artery disease.

This study suggests the importance of obesity in predicting more severe lower limb artery disease and worse outcomes during follow-up in patients with intermittent claudication. Obesity independently predicted more severe intermittent claudication as assessed by ABPI, ICD, or MWD (Table II). Metabolic syndrome was associated only with MWD. The most important finding of this study was the poor outcome of patients with obesity or metabolic syndrome during intermediate-term follow-up. All the patients who had a cardiovascular event during follow-up had metabolic syndrome. Although as a result of this disparity it was not possible to include metabolic syndrome in a Cox proportional hazard analysis, we did assess the independent association between waist circumference and outcome events (Table IV). This analysis demonstrated an important association between larger waist circumference and increased outcome events.

The correlation between serum adiponectin and all three measures of the severity of peripheral arterial disease suggests that this adipocytokine plays an important role in the poor prognosis associated with obesity in patients with lower limb ischemia (Fig). Both adiponectin and leptin were particularly associated with ABPI after adjustment for other cardiovascular risk factors. Serum adiponectin levels have been previously negatively correlated with coronary artery disease severity and progression.²⁹, ³⁰ Recently, Iwashima and colleagues³¹ reported an association between ABPI and serum adiponectin, although the investigators did not perform any functional tests of peripheral arterial disease. In animal models, adiponectin has been demonstrated to protect against the development of atherosclerosis.³² Several mechanisms have been suggested for this protective effect, including inhibition of thrombus formation and inflammation.³³, ³⁴, ³⁵

Interpretation of this study must take into account several limitations. In developing this study, we believed that it was important to enter a homogenous group of patients—ie, patients with intermittent claudication planned to be treated conservatively. These tight entry criteria and the detailed number of investigations performed restricted the sample size. It will be important to confirm our findings in a larger cohort. We also plan to extend the follow-up for this group to assess whether the identified differences persist in the long term. We defined outcome in this study in terms of the clinical end points death, cardiovascular events, and revascularization. Most events during follow-up (10/15) were cardiovascular events. Five additional patients required revascularization for the development of critical ischemia (n = 2) or worsening intermittent claudication (n = 3). Decisions to perform revascularization in patients with intermittent claudication can be influenced by factors unrelated to the progression of peripheral arterial disease: eg, the type of arterial occlusive lesion. However, because most outcome events in this study were unrelated to revascularization for intermittent claudication, we do not believe that these factors altered our results. Ideally, other measures of outcome, such as health-related quality of life or objective assessments of peripheral arterial disease, would have been valuable to assess.³⁶

In conclusion, the findings of this study suggest that obesity and metabolic syndrome predict poor outcome for patients with peripheral vascular disease. Interventions to target this problem in patients with lower limb artery disease are required.

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Author contributions 

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We thank R. Kerr, K. Sangla, S. Glanville, and the staff of the Townsville Hospital Vascular Out-Patients for their help with this study.

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