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Published in final edited form as: J Vasc Surg. 2010 Apr 10;51(6):1436–1441. doi: 10.1016/j.jvs.2009.12.072

RESTING ENERGY EXPENDITURE IN PATIENTS WITH INTERMITTENT CLAUDICATION AND CRITICAL LIMB ISCHEMIA

Andrew W Gardner 1,2,3, Polly S Montgomery 1,2,3
PMCID: PMC2874602  NIHMSID: NIHMS196048  PMID: 20382493

Abstract

Purpose

The primary aim was to compare the resting energy expenditure of patients with intermittent claudication and critical limb ischemia. A secondary aim was to identify predictors of resting energy expenditure,

Design

One hundred patients limited by intermittent claudication and 40 patients with critical limb ischemia participated in this study. Patients were assessed on resting energy expenditure, body composition, ankle/brachial index (ABI), and calf blood flow.

Results

Patients with critical limb ischemia had a lower resting energy expenditure than patients with intermittent claudication (1429 ± 190 kcal/day vs. 1563 ± 229 kcal/day; p = 0.004), as well as higher body fat percentage (34.8 ± 7.8% vs. 31.5 ± 7.8%; p = 0.037), higher fat mass (30.0 ± 9.3 kg vs. 26.2 ± 8.9 kg; p = 0.016), and lower ABI (0.31 ± 0.11 vs. 0.79 ± 0.23; p < 0.001). Resting energy expenditure was predicted by fat free mass (p < 0.0001), age (p < 0.0001), ABI (p < 0.0001), ethnicity (p < 0.0001), calf blood flow (p = 0.005), and diabetes (p = 0.008). Resting energy expenditure remained lower in the patients with critical limb ischemia after adjusting for clinical characteristics plus fat free mass (1473 ± 27.8 kcal/day [mean ± SEM] vs. 1527 ± 19.3 kcal/day; p = 0.031), but was no longer different between groups after further adjustment for ABI and calf blood flow (1494 ± 25.2 kcal/day vs. 1505 ± 17.7 kcal/day (p = 0.269).

Conclusion

Resting energy expenditure is decreased with a progression in PAD symptoms from intermittent claudication to critical limb ischemia. Furthermore, patients with critical limb ischemia who are most susceptible for decline in resting energy expenditure are older, African-American patients with diabetes. The lower resting energy expenditure of patients with critical limb ischemia, combined with their sedentary lifestyle, suggests that they are at high risk for long-term positive energy balance and weight gain.

INTRODUCTION

Peripheral arterial disease (PAD) is prevalent in 12% of the United States population, and is associated with increased morbidity1–5 and mortality.6 Ambulatory dysfunction and lower physical activity level of patients with PAD places them at greater risk for disuse atrophy of the lower extremity musculature7 than is typically observed with normal aging.8 Fat free mass is the largest contributor to resting energy expenditure in healthy controls,9 and in patients with PAD and intermittent claudication.10

Patients with intermittent claudication have lower whole-body resting energy expenditure than age-matched controls,10 even after adjustment for fat free mass. The group difference in resting energy expenditure disappears after further adjustment for ankle/brachial index (ABI) and calf blood flow, indicating that peripheral vascular measures as well as fat free mass are predictive of resting energy expenditure.10 Thus, patients with intermittent claudication are more likely than controls to have an energy imbalance favoring fat accumulation, increasing the risk for obesity, abdominal obesity, and metabolic syndrome.11;12 Patients with critical limb ischemia and rest pain may be even more prone to an impaired resting energy expenditure than patients with intermittent claudication, due to greater leg ischemia, disuse muscle atrophy, and muscle denervation.13 However, little is known about whole-body resting energy expenditure in patients with critical limb ischemia.

The primary purpose of this study was to compare the resting energy expenditure of patients with intermittent claudication and critical limb ischemia. We hypothesized that the resting energy expenditure is lower in patients with critical limb ischemia due to ischemia of the lower extremity musculature. A secondary aim was to identify predictors of resting energy expenditure, in which we hypothesized that fat free mass, ABI, and calf blood flow are the primary predictors.

METHODS

SUBJECTS

Recruitment

Patients participated in this study in the Geriatrics, Research, Education, and Clinical Center at the Maryland Veterans Affairs Health Care System (MVAHCS) at Baltimore. Patients were recruited from the Vascular Clinic at the site of the Baltimore MVAHCS, as well as by newspaper advertisements for a free evaluation of peripheral vascular function and physical function. The procedures used in this study were approved by the Institutional Review Boards at the University of Maryland and the MVAHCS at Baltimore. Written informed consent was obtained from each patient prior to investigation.

Screening

Patients were included in this study if they had Fontaine stage II or stage III PAD14 defined by the following inclusion criteria: (a) a history of intermittent claudication and an ABI ≤ 0.90 for patients with intermittent claudication,15 (b) a history of rest pain and an ABI ≤ 0.40 for patients with critical limb ischemia,15 and (c) nonsmoking status defined as not having smoked over the preceding year, and confirmed by having the patients breathe into a 2000 Series Ecolyzer carbon monoxide analyzer (National Draeger, Inc., Pittsburgh, PA) to assess the concentration of carbon monoxide in the expired air. Patients were excluded from this study for the following conditions: (a) absence of PAD (ABI > 0.90),15 (b) inability to obtain an ABI measure due to non-compressible vessels, (c) asymptomatic PAD (Fontaine stage I PAD), (d) severe PAD with tissue loss (Fontaine stage IV) or active infection in the lower extremity, (e) current smoking, (f) use of medications indicated for the treatment of intermittent claudication (cilostazol and pentoxifylline), and (g) active cancer, renal disease, or liver disease. A total of 140 patients were deemed eligible for this investigation, whereas 38 patients were ineligible.

MEASUREMENTS

Medical History and Physical Examination

Demographic information, height, weight, body mass index (BMI), waist and hip circumferences,16 cardiovascular risk factors, co-morbid conditions, claudication history, and a list of current medications were obtained during a physical examination and medical history interview.

Resting Energy Expenditure

On a subsequent visit, subjects arrived at the laboratory and were tested between 0700 and 0900 hours after a 12-hour overnight fast. A plexiglas ventilated hood was placed over the patient’s heads as they rested supine in a darkened, quiet room maintained at 24 °C. Oxygen consumption and carbon dioxide production were determined over 45 minutes of supine rest with a computerized open-circuit indirect calorimeter (Deltatrac Sensormedics Metabolic Monitor model 125, Anaheim, CA).17 The first 15 minutes of the test habituated patients to the instrumentation and testing procedures. During the final 30 minutes of the test, oxygen consumption and carbon dioxide production values were obtained and used to calculate resting energy expenditure.18

Body Composition

Percent body fat was determined after a 12-hour overnight fast by a total body scan with dual energy X-ray absorptiometry (model DPX-L, LUNAR Radiation, Madison, WI) in the supine position.7 All scans were analyzed using the LUNAR Version 1.3 DPX-L extended analysis program for body composition.7

ABI

After 10 minutes of supine rest, ankle and brachial systolic pressures were obtained as previously described.2;19 Measurements were taken from the posterior tibial and dorsalis pedis arteries in both legs. The higher arterial pressure from the more severely diseased leg was recorded as the ankle systolic pressure. Brachial arterial pressure was recorded from the arm yielding the higher systolic pressure. From these measures, ankle/brachial index (ABI) was calculated as ankle systolic pressure / brachial systolic pressure.19 The test-retest intraclass reliability coefficient is R = 0.96 for ABI.2

Calf Blood Flow

Following the measurement of ABI, calf blood flow in the more severely diseased leg was obtained by venous occlusion strain-gauge plethysmography. A mercury strain gauge was placed around the calf at the maximal circumference, and arterial blood flow to the foot was temporarily occluded by an ankle cuff inflated to 300 mm Hg. Calf blood flow was measured by inflating a thigh cuff to a venous occlusion pressure of 50 mm Hg. The ankle and thigh cuffs were deflated immediately after the calf blood flow measurement was obtained, and this measurement was repeated five times. The average of the five trials was calculated and used for calf blood flow.20 The test-retest intraclass reliability coefficient is R = 0.86 for calf blood flow.20

STATISTICAL ANALYSES

Unpaired t-tests were used to compare differences between the patients with intermittent claudication and critical limb ischemia for parametric measures, and Mann-Whitney U-tests were used to compare the groups for non-parametric measures. Stepwise multiple regression was performed to identify predictors of resting energy expenditure. The clinical, body composition, and peripheral hemodynamic measures that were considered in the modeling were age, gender, ethnicity, diabetes, hypertension, dyslipidemia, abdominal obesity, obesity, body mass, fat mass, fat free mass, body fat percentage, body mass index, waist/hip ratio, ankle systolic blood pressure, ABI, and calf blood flow. All analyses were performed using the SPSS-PC statistical package. Statistical significance was set at p < 0.05. Measurements are presented as means ± standard deviations.

RESULTS

The clinical characteristics, peripheral hemodynamic measures, and body composition of the patients with intermittent claudication and critical limb ischemia are shown in Table I. Patients with critical limb ischemia were older (p = 0.039), had a lower proportion of Caucasians (p = 0.018), and a higher prevalence of diabetes (p = 0.041), hypertension (p = 0.010), dyslipidemia (p = 0.023), abdominal obesity (p = 0.018), and obesity (p = 0.033) than patients with intermittent claudication. Furthermore, patients with critical limb ischemia had lower values for ankle systolic blood pressure (p < 0.001) and ABI (p < 0.001), and higher values for body mass (p = 0.033), fat mass (p = 0.016), body fat percentage (p = 0.037), body mass index (p = 0.040), and waist/hip ratio (p = 0.017). The resting energy expenditure measures of patients with intermittent claudication and critical limb ischemia are shown in Table II. Patients with critical limb ischemia had lower values for resting energy expenditure (p = 0.024), resting oxygen uptake (p = 0.025), and a trend for lower carbon dioxide production (p = 0.063) than patients with intermittent claudication.

Table I.

Clinical characteristics, peripheral hemodynamic measures, and body composition of patients with peripheral arterial disease. Values are means (SD) or percentages.

Variables Intermittent
Claudication
Group
(n = 100)		 Critical Limb
Ischemia
Group
(n = 40)		 P Value
Age (years) 68 (8) 71 (6) 0.039
Ankle Systolic Blood Pressure (mmHg) 106 (32) 45 (19) < 0.001
Ankle/Brachial Index 0.79 (0.23) 0.31 (0.11) < 0.001
Calf Blood Flow (%/min) 3.71 (1.33) 3.62 (1.30) 0.712
Resting Heart Rate (b/min) 62 (10) 64 (11) 0.206
Body Mass (kg) 82.1 (13.2) 86.3 (12.7) 0.033
Fat Mass (kg) 26.2 (8.9) 30.0 (9.3) 0.016
Fat Free Mass (kg) 55.9 (9.1) 56.3 (7.6) 0.498
Body Fat (%) 31.5 (7.8) 34.8 (7.8) 0.037
Body Mass Index 27.7 (4.0) 29.9 (4.6) 0.040
Waist/Hip Ratio 0.93 (0.07) 0.97 (0.08) 0.017
Sex (% Men) 85 85 1.000
Ethnicity (% Caucasian) 76 55 0.018
Diabetes (% yes) 24 40 0.041
Hypertension (% yes) 57 80 0.010
Dyslipidemia (% yes) 47 65 0.023
Abdominal Obesity (% yes) 44 65 0.018
Obesity (% yes) 33 48 0.033
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Abdominal obesity was defined as having a waist girth > 88 cm in women, and > 102 cm in men. Obesity was defined as having a body mass index ≥ 30 kg / m2.

Table II.

Resting energy expenditure measures of patients with peripheral arterial disease. Values are means (SD).

Variables Intermittent
Claudication
Group
(n = 100)		 Critical Limb
Ischemia
Group
(n = 40)		 P Value
Resting Energy Expenditure (kcal/d) 1563 (229) 1429 (190) 0.004
Resting Oxygen Uptake (ml/min) 228.7 (41.2) 209.0 (41.8) 0.005
Resting Carbon Dioxide Production (ml/min) 187.5 (30.8) 173.3 (32.6) 0.063
Respiratory Exchange Ratio 0.82 (0.05) 0.83 (0.05) 0.396
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The multiple regression model predicting resting energy expenditure from clinical characteristics, body composition, and peripheral hemodynamic measures is shown in Table III. Significant variables entering the model for resting energy expenditure included fat free mass (p < 0.0001), age (p < 0.0001), ABI (p < 0.0001), ethnicity (p < 0.0001), calf blood flow (p = 0.0050), and diabetes (p = 0.0081). The model coefficients shown in Table III indicate that resting energy expenditure was positively associated with fat free mass, ABI, and calf blood flow, and was negatively associated with age, ethnicity (lower values for African-Americans compared to Caucasians), and diabetes.

Table III.

Multiple regression model predicting resting energy expenditure from clinical characteristics, peripheral hemodynamic measures, and body composition measures in patients with peripheral arterial disase.

Independent
Variable		 Model Coefficient (SE) 95% CI P-value
Fat Free Mass 22.934 (1.577) 19.798 to 26.071 < 0.0001
Age − 11.471 (1.932) − 15.315 to − 7.628 < 0.0001
ABI 5.123 (1.901) 1.322 to 8.924 < 0.0001
Ethnicity − 101.212 (27.207) − 155.335 to − 47.089 < 0.0001
Calf Blood Flow 29.756 (10.407) 9.052 to 50.459 0.0050
Diabetes −65.2925 (16.315) −97.923 to −32.663 0.0081
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*

Overall model results: F-test statistic = 74.29 with (6,133) degrees of freedom, p < 0.0001, Multiple R = 0.907, R2=0.823.

The adjusted resting energy expenditure of patients with intermittent claudication and critical limb ischemia is displayed in Table IV. Resting energy expenditure remained lower in the patients with critical limb ischemia after adjusting for clinical characteristics (model 1; p = 0.016), and clinical characteristics plus fat free mass (model 2; p = 0.031). Resting energy expenditure was no longer different between the patients with intermittent claudication and critical limb ischemia after further adjustment for ABI and calf blood flow (model 3; p = 0.269).

Table IV.

Adjusted resting energy expenditure of patients with peripheral arterial disease. Values are means (SEM).

Variables Intermittent
Claudication
Group
(n = 100)		 Critical Limb
Ischemia Group
(n = 40)		 P Value
Model 1: Adjusted Resting Energy
Expenditure (kcal/d) 1551 (20.8) 1445 (29.7) 0.016
Model 2: Adjusted Resting Energy
Expenditure (kcal/d) 1527 (19.3) 1473 (27.8) 0.031
Model 3: Adjusted Resting Energy
Expenditure (kcal/d) 1505 (17.7) 1494 (25.2) 0.269
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Model 1: resting energy expenditure is adjusted for age, body mass index, waist/hip ratio, gender, ethnicity, diabetes, hypertension, dyslipidemia, abdominal obesity, and obesity.

Model 2: resting energy expenditure is adjusted for the variables in model 1, plus fat free mass.

Model 3: resting energy expenditure is adjusted for the variables in model 1 and 2, plus ankle/brachial index and calf blood flow.

DISCUSSION

The main findings of this investigation were that: (a) resting energy expenditure was lower in patients with critical limb ischemia than in patients with intermittent claudication, , (b) fat free mass was the strongest predictor of resting energy expenditure, and (c) age, ABI, ethnicity, calf blood flow, and diabetes were additional predictors of resting energy expenditure after adjusting for fat free mass.

Differences in resting energy expenditure and fat free mass

To our knowledge, this is the first investigation to examine the whole-body resting energy expenditure in patients with critical limb ischemia. Resting energy expenditure was 134 kcal/day lower in patients with critical limb ischemia than in patients with intermittent claudication, increasing their risk of being in positive energy balance. The long-term metabolic impact of expending 134 fewer calories per day is substantial, as this equates to over six kilograms of weight gain per year, thereby increasing the risk for obesity, abdominal obesity, and metabolic syndrome. Even after adjusting for clinical characteristics and fat free mass, patients with critical ischemia still had a lower resting energy expenditure, possibly due to lower oxygen uptake of the lower extremities,21 as well as greater muscular ischemia. Since patients with critical limb ischemia engage in less daily physical activity22 than patients with intermittent claudication,4 the estimated weight gain solely from lower resting energy expenditure is an underestimate of the potential total weight gain. However, our data on body weight is in contrast to a previous report showing a non-significant trend for lower body mass index in patients with critical limb ischemia than in controls.23 This discrepancy may be due to our selection of only non-smoking patients because of the metabolic effects of smoking, which may be an important factor for the lower body weight found in PAD patients who smoke.20 Another possibility for the discrepant findings is that our patients with critical limb ischemia may have had a chronically higher caloric intake than patients in the previous report.

Other predictors of resting energy expenditure

Fat free mass was the strongest predictor of resting energy expenditure, thus supporting previous work.9 However, fat free mass was not the only predictor or resting energy expenditure, as other factors included in the model were age, ABI, ethnicity, calf blood flow, and diabetes. The fact that fat free mass did not entirely explain differences in resting energy expenditure is supported by others,24;25 and several possible reasons exist. One possibility is that the muscle mass of the lower extremities is less metabolically active with more severe PAD. This is supported by previous work demonstrating a 50% reduction in oxygen uptake of the calf musculature, measured by near infrared spectroscopy, in patients with PAD than in controls.21 Previous reports also have found that PAD is associated with impaired muscle oxygen utilization during the onset of exercise,26;27 as well as a higher percentage of angular fibers, indicative of muscle denervation.13;28 Additionally, patients with PAD have a lower percentage of slow-twitch muscle fibers, lower capillary-to-fiber ratio, and lower number of capillaries in contact with each individual muscle fiber than age-matched controls.29 All of these factors could be amplified with progression of PAD, and thus contribute to lower resting energy expenditure per kilogram of fat free mass in patients with critical limb ischemia due to their greater PAD severity.

Once fat free mass entered the regression model, the associations between the remaining variables and resting energy expenditure were assessed with the differences in fat free mass being controlled. Other predictors of resting energy expenditure included clinical characteristics such as age, ethnicity, and diabetes, and peripheral hemodynamic measures such as ABI and calf blood flow. Our findings in PAD patients support previous studies reporting reduced resting energy expenditure with age30 and in African-Americans compared to Caucasians,31 and impaired skeletal muscle oxygen uptake kinetics due to microvascular dysfunction in PAD patients with diabetes.32 This is supported by a recent observation that African-American patients with PAD have impaired small artery elasticity compared to their Caucasian counterparts, indicating worse microvascular function.33 Our finding that diabetes reduces resting energy expenditure in PAD patients is in contrast to observations of higher values in diabetic patients without PAD,31;34 suggesting that impairment in oxygen delivery to skeletal muscle in PAD patients has a greater net influence on reducing resting energy expenditure than hyperglycemia has on increasing resting energy expenditure.34

ABI and calf blood flow were additional predictors of resting energy expenditure, even after adjustment of fat free mass and clinical characteristics, suggesting that both the macrocirculation and the nutritive circulation impact resting energy expenditure in PAD patients. This finding supports previous work that resting energy expenditure is not entirely explained by fat free mass and body composition.24;25 Thus, the greater hemodynamic impairment in patients with critical limb ischemia, as measured by ABI, is an additional factor related to resting energy expenditure. Although the two groups had similar calf blood flow at rest, our data suggest that small differences in calf blood flow, reflecting nutritive circulation, explain additional variance in resting energy expenditure. After ABI, and calf blood flow are included in the model, the resting energy expenditure was similar between the patients with critical limb ischemia and patients with intermittent claudication, and no additional measurements were predictive of resting energy expenditure.

Clinical implications and study limitations

It is not clear from this investigation whether lower resting energy expenditure is a consequence of critical limb ischemia, or vice versa. Regardless, further work is needed to examine whether resting energy expenditure is modifiable through interventions designed to increase peripheral hemodynamic measures, fat free mass, and to improve the management of diabetes, particularly in older, African-American patients with critical limb ischemia. Possible interventions may include a walking program to increase total daily energy expenditure and the microcirculation of the lower extremities, resistance training to increase fat free mass, and more optimal medication therapy, particularly in patients with diabetes. We have recently found that painful ambulation is more metabolically costly than pain-free ambulation in patients with intermittent claudication.35 Thus, even a modest amount of ambulation done carefully at slow cadence in patients with critical limb ischemia may be a feasible approach to increase energy expenditure and counteract their otherwise sedentary lifestyle22 without causing undue injury to the lower extremities.

There are several limitations to this study. The cross-sectional design comparing patients with intermittent claudication and critical limb ischemia does not allow causality be established, as it is possible that patients with critical limb ischemia had lower resting energy expenditure prior to the development of their more advanced symptoms. Furthermore, it is possible that other co-morbid conditions not evaluated in this study were related to their lower resting energy expenditure. The present findings are also limited to PAD patients with intermittent claudication or critical limb ischemia and rest pain who are current non-smokers, and may not be generalized to patients with less severe (Fontaine stage I) and more severe (Fontaine stage IV) PAD, or to patients who are current smokers. However, these populations had the typical high prevalence of risk factors for PAD, including diabetes, hypertension, dyslipidemia, and obesity. Thus, we believe the findings of this study are representative of non-smoking patients with intermittent claudication and with critical limb ischemia and rest pain.

In conclusion, resting energy expenditure is decreased with a progression in PAD symptoms from intermittent claudication to critical limb ischemia. Furthermore, patients with critical limb ischemia who are most susceptible for decline in resting energy expenditure are older, African-American patients with diabetes. The lower resting energy expenditure of patients with critical limb ischemia, combined with their sedentary lifestyle,22 suggests that they are at high risk for long-term positive energy balance and weight gain.

Acknowledgments

Andrew W. Gardner, Ph.D., was supported by grants from the National Institute on Aging (NIA) (R01-AG-16685, K01-00657), by a Claude D. Pepper Older American Independence Center grant from NIA (P60-AG12583), by a Geriatric, Research, Education, and Clinical Center grant (GRECC) from the Veterans Affairs administration, and by a National Institutes of Health, National Center for Research Resources, General Clinical Research Center grant (M01-RR-14467). The final peer-reviewed version of this manuscript is subject to the NIH Public Access Policy, and will be submitted to PubMed Central.

Footnotes

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