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Adiposity facilitates increased strength capacity in heart failure patients with reduced ejection fraction
International Journal of Cardiology 167 (2013) 2468–2471
Contents lists available at ScienceDirect
International Journal of Cardiology journal homepage: www.elsevier.com/locate/ijcard
Adiposity facilitates increased strength capacity in heart failure patients with reduced ejection fraction☆ Alexandra Zavin a, Karla Daniels a, Ross Arena b, Kelly Allsup a, Antonio Lazzari c, d, Jacob Joseph e, h, P. Christian Schulze f, Stewart H. Lecker g, Daniel E. Forman a, e, h,⁎ a
New England Geriatric Research, Education, and Clinical Center, VA Boston Healthcare System, Boston, MA, United States Department of Orthopaedics and Rehabilitation, Physical Therapy Program and Department of Internal Medicine, Division of Cardiology, University of New Mexico School of Medicine, Albuquerque, NM, United States c Division of Rheumatology, VA Boston Healthcare System, Boston, MA, United States d Boston University School of Medicine, Boston, MA, United States e Division of Cardiovascular Medicine, VA Boston Healthcare System, Boston, MA, United States f Division of Cardiovascular Medicine, Columbia University Medical Center, New York, NY, United States g Division of Nephrology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States h Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States b
a r t i c l e
i n f o
Article history: Received 6 March 2012 Received in revised form 1 June 2012 Accepted 7 June 2012 Available online 27 June 2012 Keywords: Physical function Body composition Adiposity
a b s t r a c t Background: Obesity is associated with relatively improved prognosis among heart failure (HF) patients. Mechanisms explaining this so-called “obesity paradox” have been unclear. We hypothesized that increased adiposity may contribute to increased strength capacity, and may thereby facilitate clinical benefits. Methods and results: In a controlled, cross-sectional study, adults aged ≥ 50 years with HF with reduced ejection fraction (HFREF) (LVEF ≤ 40%) were compared to age matched controls. Body composition was determined by dual-energy X-ray absorptiometry (DXA). Aerobic (cardiopulmonary exercise testing), maximum strength (one repetition maximum [1RM]), and power (submaximal resistance/time) were assessed. 70 adults (31 HFREF, 39 controls; mean age 66.2 ± 9.6 years) were studied. Peak oxygen consumption (VO2) (15.4 ± 4.2 vs. 23.4 ± 6.6 ml O2·kg − 1·min − 1, p b 0.0001), 1RM (154.8 ± 52.0 vs. 195.3 ± 56.8 kg, p b 0.01) and power (226.4 ± 99.2 vs. 313.3 ± 130.6, p b 0.01) were lower in HFREF vs. controls. 1RM correlated with total fat (r = 0.56, p b 0.01), leg fat (r = 0.45, p b 0.05) and arm fat (r = 0.39, p b 0.05) in HFREF. Moreover, among HFREF patients with a high (≥ 30 kg/m2) body mass index (BMI), 1RM and fat mass were significantly greater than those with lower (b 30 kg/m 2) BMIs. Correlations between 1RM and total fat (r = 0.65, p b 0.05) and leg fat (r = 0.64, p b 0.05) were particularly notable in the high BMI subgroup. Conclusion: Increased adiposity correlates with relatively greater strength in HFREF patients which may explain some of the clinical benefits that result from obesity. © 2012 Elsevier Ireland Ltd. All rights reserved.
1. Introduction While obesity is generally considered detrimental to those who are healthy [1,2], increased adiposity is associated with a relatively better prognosis among older adults with heart failure with reduced ejection fraction (HFREF) [3]. This so-called obesity paradox is often attributed to the “cardio-protective benefits” [4–7], of adipose tissue wherein adipose tissue is thought to impart neuroendocrine and metabolic benefits [8–10]. While a multitude of studies corroborate the
☆ This study was funded by: VA Merit Award F4726R, Ubiquitin Proteolysis and PGC-1α in Skeletal Muscle in Heart Failure. ⁎ Corresponding author at: Division of Cardiovascular Medicine, Brigham and Women's Hospital, 75 Francis St. Boston, MA 02115, United States. Tel.: + 1 857 307 1989; fax: + 1 857 307 1955. E-mail address: [email protected] (D.E. Forman). 0167-5273/$ – see front matter © 2012 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.ijcard.2012.06.007
favorable implications of obesity in heart failure (HF) patients, mechanisms of cardiac benefit remain controversial [11]. We hypothesized that the benefits of adiposity may relate to functional implications of body composition. Adults with surplus body fat carry extra weight throughout the course of daily living. Differences in prognosis may result from what is a defacto resistance training stimulus and relates to differences in body composition and strength. Although elevated body mass index (BMI) of ≥30 kg/m 2 is usually used to demarcate excess adiposity, simple quantification of body habitus does not discriminate between lean muscle and fat tissue [12]. Using dual energy X-ray absorptiometry (DXA) to more accurately quantify adiposity and fat distribution in HF patients and agematched controls, we studied the impact of aerobic and strength performance relative to fat and lean body tissue. Functional decline is typical among HFREF patients, with poor prognostic implications as well as diminished quality of life, increased
A. Zavin et al. / International Journal of Cardiology 167 (2013) 2468–2471
frailty, and reduced independence [13,14]. Diminished muscular strength is also typical [15,16]. The relationship of lean body mass, fat mass, and the relative implications on aerobic and strength abilities have not been delineated. High fat mass may impart paradoxical health benefits by its favorable functional ramifications. 2. Materials and methods Non-cachectic (BMI ≥ 18.5), clinically stable, male HFREF patients aged 50 years and older were compared to age-matched controls. All patients were on a standard regimen of evidence-based HF therapy with medications and doses determined by their primary cardiologists. All HFREF patients were euvolemic during a physical exam immediately prior to the functional assessments. Additionally, each HFREF patient completed an echocardiogram within 6 months of enrollment to confirm a left ventricular ejection fraction (LVEF) ≤ 40%. Both HF patients and control subjects were excluded if they had neurological dysfunction, musculoskeletal problems, or severe pulmonary disease, which might have confounded functional assessments. Control subjects had no history of cardiovascular disease. Control candidates or HFREF patients who exercised ≥150 min/week for the three months prior to enrollment were also excluded to avoid confounding effects of exercise training. The study was approved by the VA Institutional Review Board and informed consent was obtained from each subject. Exercise testing was completed on a motorized treadmill using a modified Balke protocol [17] in conjunction with ventilatory expired gas analysis through a snorkel device [18]. The ventilatory expired gas analysis system (MedGraphics BreezeSuite St. Paul, MN) was calibrated prior to each test. ECG waveforms, blood pressure, oxygen saturation, and subjective symptoms were assessed before, during, and after exercise, in routine clinical fashion. Peak oxygen consumption (VO2) was defined as the 30-second averaged value during the last stage of exercise. Ventilatory anaerobic threshold (VAT) was determined by the V-slope method [19]. Ventilatory efficiency represented as the ventilation to carbon dioxide production (VE/VCO2) slope was evaluated during exercise. VE and VCO2 values, acquired from the initiation of exercise to maximal exertion, were input into a spreadsheet software (Microsoft Excel, Microsoft Corp., Bellevue, WA) to calculate the VE/VCO2 slope via least squares linear regression (y= mx+ b, m = slope). All of the subjects achieved a minimum peak respiratory exchange ratio (RER) of 1.0, ensuring a standard of high physical exertion [20] among patients who had predominantly sedentary lifestyles. Muscle strength and power were measured using a pneumatic leg press (Keiser A420, Fresno, CA). To assess maximal strength capacity, participants performed a leg press (i.e. knee extension and flexion) initially using a minimal weight. Subjects rated the leg press according to the rating of perceived exertion (RPE) using the Borg scale [21] The physiologist then increased the weight and the participant completed another leg press with the heavier weight and rated the difficulty of the leg press. The weight was progressively increased until the participant was unable to complete a full repetition. The last weight that was used to complete a full repetition was recorded as the one repetition maximum (1RM). Thereafter, the resistance was reduced to 60% of the 1RM, and subjects completed up to 30 repetitions continuously to assess submaximal power. A desktop computer was connected to the leg press machine, which generated power curves (watts) for each leg press. Upon completion of the 30 repetitions, the peak for each curve was determined and averaged with one another. Total and anthropometric lean and fat mass were measured with iDXA (GE Lunar, Madison, WI) and analyses were performed using Encore 13.60 software. The DXA scanner (Lunar iDXA, Madison, WI 53718,) was calibrated with a phantom provided by GE Healthcare, prior to each scan, according to manufacturer's specifications [22]. iDXA is a fan beam system which uses a staggered array of sixty-four detectors (CZTHD digital detectors) to enhance precision and eliminate dead space between detectors, thus creating a high resolution image [23]. DXA measurements were normalized to height. SAS statistical software version 9.0 (SAS, Cary, NC) was used to analyze the data and values are reported as mean ± SD (unless otherwise indicated). Comparison of HF and controls was determined using non-paired t-tests and Pearson correlations were used to evaluate the correlation coefficients. A p-value of b 0.05 was used to define statistical significance for all tests.
3. Results Seventy subjects (31 HF patients [mean age 67.4 ± 8.9 years] and 39 controls [mean age 65.3 ± 10.1 years]) were assessed. All subjects were male. Table 1 lists the demographics and medications among the study population. Table 2 demonstrates impaired aerobic ability in HF patients evidenced by a significantly decreased peak VO2 and VAT and an increased VE/VCO2 slope. Strength and power were also decreased in HF patients, suggesting further abnormalities in peripheral skeletal muscle function. Leg lean muscle mass was diminished in HF patients
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Table 1 Participant demographics.
Age (years) Weight (kg) Height (meters) Medications Beta-blocker ACE-inhibitor ARB Statin Diuretics
HF
Controls
Significance
67.4 ± 8.9 86.0 ± 27.4 1.7 ± 0.07
65.3 ± 10.1 86.6 ± 14.9 1.7 ± 0.09
0.37 0.91 0.98
23 25 2 24 20
2 6 2 16 5
b 0.0001 b 0.0001 0.80 b 0.001 b 0.0001
HF indicates heart failure; ACE, angiotensin converting enzyme; ARB, angiotensin II receptor blocker.
but since “lean tissue” measures incorporate both bone and muscle tissues, isolated skeletal muscle implications are uncertain. Total adiposity was similar between HF patients and controls. Table 3 demonstrates the lack of correlation between lean mass and aerobic indices in HF patients. However, Table 4 shows that lean mass is significantly associated with strength capacity in HF patients, suggesting that lean mass has a greater influence on strength than aerobic ability. Table 4 also shows that fat mass correlates with strength; correlations were stronger in the HF group than in the controls. To further compare the effects of fat and lean body mass on strength capacity, HF patients were stratified into groups according to a b30 kg/m 2 (n = 21) and ≥ 30 kg/m 2 (n = 10) BMI threshold; mean BMI 25.0 ±3.1 vs. 37.0 ±7.5 kg/m2, p b 0.001, respectively. Although aerobic indices were similar between the two groups [peak VO2 (14.9 ±4.3 vs. 15.6 ±4.2 mlO2·kg− 1·min− 1, p= 0.66), VAT (11.0 ±2.7 vs. 10.9 ± 1.7 mlO2·kg− 1·min− 1, p= 0.84), and VE/VCO2 slope (36.9 ±13.2 vs. 35.1 ±9.4, p= 0.67)], those in the high BMI group had a significantly higher 1RM (181.0± 55.6 vs. 141.6 ±46.0 kg, pb 0.05). Fat mass, as assessed by DXA, was increased in the high BMI subgroup: total fat mass (26.5 ± 10.1 vs. 12.1 ± 3.9 kg, p b 0.01) as well as leg fat mass (7.2 ± 3.4 vs. 3.3 ± 1.2 kg, p b 0.01), and arm fat mass (2.4 ± 1.0 vs. 1.2 ± 0.5 kg, p b 0.01). 1RM correlated positively with total fat (r = 0.65, p b 0.05) and leg fat (r = 0.64, p b 0.05) only in the HF group with high BMI. Patients in the high BMI group also had increased total lean mass (36.4 ±4.3 vs. 29.7±2.6 kg, pb 0.0001) as well as leg lean mass (12.3± 2.1 vs. 9.4±1.2 kg, p b 0.01) and arm lean mass (4.3±0.7 vs. 3.5± 0.5 kg, pb 0.01). However, there were no significant correlations between lean mass and function in this group.
Table 2 Differences in function and body composition between HF patients and control subjects.
Aerobic capacity Peak VO2 (ml·kg− 1·min− 1) VAT (ml·kg− 1·min− 1) VE/VCO2 slope Strength capacity 1RM (kg) Power (watts) DXA fat and lean body mass distributions (normalized to height) Total lean (kg) Legs lean (kg) Arms lean (kg) Total fat (kg) Leg fat (kg) Arm fat (kg)
HF
Controls
Significance
15.4 ± 4.2 10.9 ± 2.1 35.7 ± 10.6
23.4 ± 6.6 14.4 ± 4.0 29.1 ± 4.6
b 0.0001 b 0.0001 b 0.01
154.8 ± 52.0 226.4 ± 99.2
195.3 ± 56.8 313.3 ± 130.6
b 0.01 b 0.01
31.2 ± 4.8 10.3 ± 2.0 3.8 ± 0.7 16.7 ± 9.4 4.6 ± 2.8 1.6 ± .9
32.5 ± 3.8 11.1 ± 1.4 4.0 ± 0.9 16.3 ± 5.0 4.3 ± 1.4 1.6 ± 0.6
0.20 b 0.05 0.24 0.82 0.62 0.80
Peak VO2 indicates maximal oxygen consumption; VAT oxygen consumption at anaerobic threshold; VE/VCO2 slope ventilatory efficiency; 1RM the one repetition maximum.
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A. Zavin et al. / International Journal of Cardiology 167 (2013) 2468–2471
Table 3 Correlations between aerobic capacity and body anthropometrics in HF patients and controls. Peak VO2 HF
VAT Controls
VE/VCO2 slope
HF
Controls
HF
Controls
Lean body tissue distribution Total lean − 0.18 0.17 Legs lean − 0.13 0.26 Arms lean − 0.04 0.44†
− 0.06 − 0.09 0.05
0.05 0.19 0.21
− 0.08 − 0.11 − 0.18
− 0.09 − 0.02 − 0.22
Adipose tissue distribution Total fat − 0.17 − 0.23 Leg fat − 0.21 − 0.22 Arm fat − 0.27 − 0.22
− 0.17 − 0.19 − 0.28
− 0.17 − 0.14 − 0.17
− 0.10 − 0.06 − 0.06
0.04 − 0.10 − 0.03
Peak VO2 indicates maximal oxygen consumption; VAT oxygen consumption at anaerobic threshold; VE/VCO2 slope ventilatory efficiency. † p b 0.01.
elevated in the patients with BMI ≥30 kg/m2, only fat mass correlated with strength, possibly indicating a unique health benefit from adiposity. Lavie et al. [4] demonstrated that HF patients who suffered cardiovascular events had lower BMIs and body surface areas than those who did not experience an event over two-years. This study suggests that a greater fat mass in HF patients protects them from clinical events. Those with less fat mass, including those who had similar amounts of lean tissue, were more likely to develop an event. Despite Lavie's study and others indicating lower mortality rates among obese HF patients [3,6,25,26], clarification regarding the cardioprotective aspects of fat is needed. It remains unclear if fat provides direct benefits or if it primarily stimulates muscle mass and strength. These differences have bearing on HF management priorities as well as other chronic disease for which body composition affects clinical course and prognosis (e.g., kidney disease [27,28], and chronic obstructive pulmonary disease [29]). 4.1. Limitations
4. Discussion The obesity paradox insinuates that increased body fat imparts protective benefits in a HF population. The current investigation shows that adiposity correlates with strength capacity in HFREF patients. Paradoxical benefits of obesity might relate to increased strength and/ or the metabolic, biological, and/or physiological derivatives of increased strength capacity. HFREF patients were subdivided into groups with high and low BMI; in the subgroup with BMI ≥30 kg/m 2, both fat mass and lean body mass were greater than in the subgroup with BMI b30 kg/m 2, but only fat mass correlated to strength capacity. This suggests that fat itself may underlie a fundamental functional benefit rather than it serving primarily as a stimulus for increased lean body mass as its only mechanism of benefit. Nonetheless, the coexistence of higher fat and lean body mass among those with high BMI highlights the complex interrelationship between fat and lean body mass in relation to high BMI. Our findings are consistent with those of Anker et al. [24] who showed that the ability to perform work in HF reflects measures of both distance and mass. HF patients who carry more mass (i.e. those who are overweight or obese) over a longer distance are inevitably doing more work. This study indicates that overweight and obese adults inevitably incorporate strength training into everyday activities, since their muscles must support excess adipose tissue as compared to normal or under-weight patients. We extend these findings by applying DXA to show that HFREF patients with increased body fat achieve greater strength capacities. While lean muscle and fat mass were both
Table 4 Correlations between strength capacity and body composition in HF patients and controls. 1RM HF
Power Controls
HF
Controls
Lean body tissue distribution Total lean 0.54† Legs lean 0.53† Arms lean 0.48†
0.63‡ 0.54‡ 0.38⁎
0.19 0.13 0.34
0.16 0.11 0.12
Body fat distribution Total fat 0.56† Leg fat 0.45⁎ Arm fat 0.39⁎
0.40⁎ 0.37⁎ 0.41⁎
0.24 0.06 0.23
0.17 0.11 0.14
1RM is the one repetition maximum. ⁎ p b 0.05. † p b 0.01. ‡ p b 0.001.
While our study population was small, our data distinguished functional ramifications in HF vs. controls that were consistent with larger studies, corroborating the implications of body composition data. Furthermore, our protocol was rigorous, with comprehensive physical function assessments as well as DXA scans, providing an important and relatively exceptional opportunity for novel assessments of body composition and exercise attributes. While a cardiologist examined each patient prior to enrollment to ensure that they were euvolemic and stable, some patients may have had water retention which could potentially have confounded DXA assessments. Additionally, diet and serology (including adipocytokines) were not measured and these would have helped refine/enhance our conclusions. Our study also only enrolled male subjects and therefore further evaluation is needed to determine the effects of adipose tissue on function in the female population. This is not a longitudinal study and further research is therefore needed to determine prognostic implications. Finally, this study relied on a cross-sectional design; further research is needed to clarify causal benefits of adipose tissue. 4.2. Conclusion Fat mass is related to increased muscle strength in obese HF patients, probably as a natural source of chronic resistance exercise, with paradoxical beneficial implications on health. Acknowledgments The authors of this manuscript have certified that they comply with the Principles of Ethical Publishing in the International Journal of Cardiology. References [1] Nicklas B, Cesari M, Penninx W, et al. Abdominal obesity is an independent risk factor for chronic heart failure in older people. J Am Geriatr Soc 2006;54:413–20. [2] Lloyd-Jones D, Adams R, Brown T, et al. Heart disease and stroke statistics—2010 update: a report from the American Heart Association. Circulation 2010;121: e46–215. [3] Romero-Corral A, Montari V, Somers V, et al. Association of bodyweight with total mortality and with cardiovascular events in coronary artery disease: a systemic review of cohort studies. Lancet 2006;368:666–78. [4] Lavie C, Milani R, Ventura H. Body composition and heart failure prevalence and prognosis: getting to the fat of the matter in the “obesity paradox”. Mayo Clin Proc 2010;85(7):605–8. [5] Arena R, Lavie C. The obesity paradox and outcome in heart failure: is excess bodyweight truly protective? Future Cardiol 2010;6:1–6. [6] Oreopoulos A, Padwal R, Kalantar-Zadeh K, Fonarow G, Norris C, McAlister F. Body mass index and mortality in heart failure: a meta-analysis. Am Heart J 2008;156: 13–22. [7] Lavie C, Osman A, Milani R, Mehra M. Body composition and prognosis in chronic systolic heart failure: the obesity paradox. Am J Cardiol 2003;91(7):891–4.
A. Zavin et al. / International Journal of Cardiology 167 (2013) 2468–2471 [8] Kistorp C, Faber J, Galatius S, et al. Plasma adiponectin, body mass index, and mortality in patients with crhonic heart failure. Circulation 2005;112:1756–62. [9] Rauchhaus M, Koloczek V, Volk H, et al. Inflammatory cytokines and the possible immunological role for lipoproteins in chronic heart failure. Int J Cardiol 2000;76: 125–33. [10] Aquilani R, Rovere ML, Febo O, et al. Preserved muscle protein metabolism in obese patients with chronic heart failure. Int J Cardiol 2012 Oct 4;160:102–8. [11] Adamopoulos C, Meyer P, Desai R, et al. Absence of obesity paradox in patients with chronic heart failure and diabetes mellitus: a propensity-matched study. Eur J Heart Fail 2011;13:200–6. [12] Oreopoulos A, Ezekowitz J, McAlister F, et al. Association between direct measures of body composition and prognostic factors in chronic heart failure. Mayo Clin Proc 2010;85:609–17. [13] Silventoinen K, Magnusson P, Tynelius P, Batty G, Rasmussen F. Association of body size and muscle strength with incidence of coronary heart disease and cerebrovascular disease: a population-based cohort study of one million Swedish men. Int J Epidemiol 2009;38:110–8. [14] Artero E, Lee D, Ruiz J, et al. A prospective study of muscular strength and all-cause mortality in men with hypertension. J Am Coll Cardiol 2011;57:1831–7. [15] Harrington D, Anker S, Chua T, et al. Skeletal muscle function and its relation to exercise tolerance in chronic heart failure. J Am Coll Cardiol 1997;30:1758–64. [16] Anker S, Swan J, Volterrani M, et al. The influence of muscle mass, strength, fatigability and blood flow on exercise capacity in cachectic and non-cachectic patients with chronic heart failure. Eur Heart J 1997;18:259–69. [17] Balke B, Ware R. An experimental study of physical fitness of Air Force personnel. U S Armed Forces Med J 1959;10:675–88.
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[18] Forman D, Myers J, Guazzi M, Celli B, Arena R. Cardiopulmonary exercise testing: relevant but underused. Postgrad Med 2010;122(6):68–86. [19] Beaver W, Wasserman K, Whipp B. A new method for detecting anaerobic threshold by gas exchange. J Appl Physiol 1986;60:2020–7. [20] Balady G, Arena R, Sietsema K, et al. Clinician's guide to cardiopulmonary exercise testing in adults. A scientific statement from the American Heart Association. Circulation 2010;122:191–225. [21] Borg G. Perceived exertion. Exerc Sport Sci Rev 1974;2:131–53. [22] Hull H, He Q, Thornton J, et al. iDXA, prodigy, and DPXL dual-energy X-ray absorptiometry whole-body scans: a cross-calibration study. J Clin Densitom 2009;12:95–102. [23] Hind K, Oldroyd B, Truscott J. In vivo precision of the GE Lunar iDXA densitometer for the measurement of total body composition and fat distribution in adults. Eur J Clin Nutr 2011;65:140–2. [24] Anker S, Haehling Sv. The obesity paradox in heart failure: accepting reality and making rational decisions. Clin Pharmacol Ther 2011;90(1):188–90. [25] Lavie C, Milani R, Artham S, Patel D, Ventura H. The obesity paradox, weight loss, and coronary disease. Am J Med 2009;122:1107–14. [26] Lavie C, Schutter A, Patel D, Artham S, Milani R. Body composition and coronary heart disease mortality — an obesity or a lean paradox? Mayo Clin Proc 2011;86(9):857–84. [27] Schmidt D, Salahudeen A. The obesity-survival paradox in hemodialysis patients: why do overweight hemodialysis patients live longer? Nutr Clin Pract 2007;22: 11–5. [28] Johansen K, Young B, Kaysen G, Chertow G. Association of body size with outcomes among patients beginning dialysis. Am J Clin Nutr 2004;80:324–32. [29] Blum A, Simsolo C, Sirchan R, Haiek S. “Obesity paradox” in chronic obstructive pulmonary disease. IMAJ 2011;13:672–5.
Contents lists available at ScienceDirect
International Journal of Cardiology journal homepage: www.elsevier.com/locate/ijcard
Adiposity facilitates increased strength capacity in heart failure patients with reduced ejection fraction☆ Alexandra Zavin a, Karla Daniels a, Ross Arena b, Kelly Allsup a, Antonio Lazzari c, d, Jacob Joseph e, h, P. Christian Schulze f, Stewart H. Lecker g, Daniel E. Forman a, e, h,⁎ a
New England Geriatric Research, Education, and Clinical Center, VA Boston Healthcare System, Boston, MA, United States Department of Orthopaedics and Rehabilitation, Physical Therapy Program and Department of Internal Medicine, Division of Cardiology, University of New Mexico School of Medicine, Albuquerque, NM, United States c Division of Rheumatology, VA Boston Healthcare System, Boston, MA, United States d Boston University School of Medicine, Boston, MA, United States e Division of Cardiovascular Medicine, VA Boston Healthcare System, Boston, MA, United States f Division of Cardiovascular Medicine, Columbia University Medical Center, New York, NY, United States g Division of Nephrology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States h Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States b
a r t i c l e
i n f o
Article history: Received 6 March 2012 Received in revised form 1 June 2012 Accepted 7 June 2012 Available online 27 June 2012 Keywords: Physical function Body composition Adiposity
a b s t r a c t Background: Obesity is associated with relatively improved prognosis among heart failure (HF) patients. Mechanisms explaining this so-called “obesity paradox” have been unclear. We hypothesized that increased adiposity may contribute to increased strength capacity, and may thereby facilitate clinical benefits. Methods and results: In a controlled, cross-sectional study, adults aged ≥ 50 years with HF with reduced ejection fraction (HFREF) (LVEF ≤ 40%) were compared to age matched controls. Body composition was determined by dual-energy X-ray absorptiometry (DXA). Aerobic (cardiopulmonary exercise testing), maximum strength (one repetition maximum [1RM]), and power (submaximal resistance/time) were assessed. 70 adults (31 HFREF, 39 controls; mean age 66.2 ± 9.6 years) were studied. Peak oxygen consumption (VO2) (15.4 ± 4.2 vs. 23.4 ± 6.6 ml O2·kg − 1·min − 1, p b 0.0001), 1RM (154.8 ± 52.0 vs. 195.3 ± 56.8 kg, p b 0.01) and power (226.4 ± 99.2 vs. 313.3 ± 130.6, p b 0.01) were lower in HFREF vs. controls. 1RM correlated with total fat (r = 0.56, p b 0.01), leg fat (r = 0.45, p b 0.05) and arm fat (r = 0.39, p b 0.05) in HFREF. Moreover, among HFREF patients with a high (≥ 30 kg/m2) body mass index (BMI), 1RM and fat mass were significantly greater than those with lower (b 30 kg/m 2) BMIs. Correlations between 1RM and total fat (r = 0.65, p b 0.05) and leg fat (r = 0.64, p b 0.05) were particularly notable in the high BMI subgroup. Conclusion: Increased adiposity correlates with relatively greater strength in HFREF patients which may explain some of the clinical benefits that result from obesity. © 2012 Elsevier Ireland Ltd. All rights reserved.
1. Introduction While obesity is generally considered detrimental to those who are healthy [1,2], increased adiposity is associated with a relatively better prognosis among older adults with heart failure with reduced ejection fraction (HFREF) [3]. This so-called obesity paradox is often attributed to the “cardio-protective benefits” [4–7], of adipose tissue wherein adipose tissue is thought to impart neuroendocrine and metabolic benefits [8–10]. While a multitude of studies corroborate the
☆ This study was funded by: VA Merit Award F4726R, Ubiquitin Proteolysis and PGC-1α in Skeletal Muscle in Heart Failure. ⁎ Corresponding author at: Division of Cardiovascular Medicine, Brigham and Women's Hospital, 75 Francis St. Boston, MA 02115, United States. Tel.: + 1 857 307 1989; fax: + 1 857 307 1955. E-mail address: [email protected] (D.E. Forman). 0167-5273/$ – see front matter © 2012 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.ijcard.2012.06.007
favorable implications of obesity in heart failure (HF) patients, mechanisms of cardiac benefit remain controversial [11]. We hypothesized that the benefits of adiposity may relate to functional implications of body composition. Adults with surplus body fat carry extra weight throughout the course of daily living. Differences in prognosis may result from what is a defacto resistance training stimulus and relates to differences in body composition and strength. Although elevated body mass index (BMI) of ≥30 kg/m 2 is usually used to demarcate excess adiposity, simple quantification of body habitus does not discriminate between lean muscle and fat tissue [12]. Using dual energy X-ray absorptiometry (DXA) to more accurately quantify adiposity and fat distribution in HF patients and agematched controls, we studied the impact of aerobic and strength performance relative to fat and lean body tissue. Functional decline is typical among HFREF patients, with poor prognostic implications as well as diminished quality of life, increased
A. Zavin et al. / International Journal of Cardiology 167 (2013) 2468–2471
frailty, and reduced independence [13,14]. Diminished muscular strength is also typical [15,16]. The relationship of lean body mass, fat mass, and the relative implications on aerobic and strength abilities have not been delineated. High fat mass may impart paradoxical health benefits by its favorable functional ramifications. 2. Materials and methods Non-cachectic (BMI ≥ 18.5), clinically stable, male HFREF patients aged 50 years and older were compared to age-matched controls. All patients were on a standard regimen of evidence-based HF therapy with medications and doses determined by their primary cardiologists. All HFREF patients were euvolemic during a physical exam immediately prior to the functional assessments. Additionally, each HFREF patient completed an echocardiogram within 6 months of enrollment to confirm a left ventricular ejection fraction (LVEF) ≤ 40%. Both HF patients and control subjects were excluded if they had neurological dysfunction, musculoskeletal problems, or severe pulmonary disease, which might have confounded functional assessments. Control subjects had no history of cardiovascular disease. Control candidates or HFREF patients who exercised ≥150 min/week for the three months prior to enrollment were also excluded to avoid confounding effects of exercise training. The study was approved by the VA Institutional Review Board and informed consent was obtained from each subject. Exercise testing was completed on a motorized treadmill using a modified Balke protocol [17] in conjunction with ventilatory expired gas analysis through a snorkel device [18]. The ventilatory expired gas analysis system (MedGraphics BreezeSuite St. Paul, MN) was calibrated prior to each test. ECG waveforms, blood pressure, oxygen saturation, and subjective symptoms were assessed before, during, and after exercise, in routine clinical fashion. Peak oxygen consumption (VO2) was defined as the 30-second averaged value during the last stage of exercise. Ventilatory anaerobic threshold (VAT) was determined by the V-slope method [19]. Ventilatory efficiency represented as the ventilation to carbon dioxide production (VE/VCO2) slope was evaluated during exercise. VE and VCO2 values, acquired from the initiation of exercise to maximal exertion, were input into a spreadsheet software (Microsoft Excel, Microsoft Corp., Bellevue, WA) to calculate the VE/VCO2 slope via least squares linear regression (y= mx+ b, m = slope). All of the subjects achieved a minimum peak respiratory exchange ratio (RER) of 1.0, ensuring a standard of high physical exertion [20] among patients who had predominantly sedentary lifestyles. Muscle strength and power were measured using a pneumatic leg press (Keiser A420, Fresno, CA). To assess maximal strength capacity, participants performed a leg press (i.e. knee extension and flexion) initially using a minimal weight. Subjects rated the leg press according to the rating of perceived exertion (RPE) using the Borg scale [21] The physiologist then increased the weight and the participant completed another leg press with the heavier weight and rated the difficulty of the leg press. The weight was progressively increased until the participant was unable to complete a full repetition. The last weight that was used to complete a full repetition was recorded as the one repetition maximum (1RM). Thereafter, the resistance was reduced to 60% of the 1RM, and subjects completed up to 30 repetitions continuously to assess submaximal power. A desktop computer was connected to the leg press machine, which generated power curves (watts) for each leg press. Upon completion of the 30 repetitions, the peak for each curve was determined and averaged with one another. Total and anthropometric lean and fat mass were measured with iDXA (GE Lunar, Madison, WI) and analyses were performed using Encore 13.60 software. The DXA scanner (Lunar iDXA, Madison, WI 53718,) was calibrated with a phantom provided by GE Healthcare, prior to each scan, according to manufacturer's specifications [22]. iDXA is a fan beam system which uses a staggered array of sixty-four detectors (CZTHD digital detectors) to enhance precision and eliminate dead space between detectors, thus creating a high resolution image [23]. DXA measurements were normalized to height. SAS statistical software version 9.0 (SAS, Cary, NC) was used to analyze the data and values are reported as mean ± SD (unless otherwise indicated). Comparison of HF and controls was determined using non-paired t-tests and Pearson correlations were used to evaluate the correlation coefficients. A p-value of b 0.05 was used to define statistical significance for all tests.
3. Results Seventy subjects (31 HF patients [mean age 67.4 ± 8.9 years] and 39 controls [mean age 65.3 ± 10.1 years]) were assessed. All subjects were male. Table 1 lists the demographics and medications among the study population. Table 2 demonstrates impaired aerobic ability in HF patients evidenced by a significantly decreased peak VO2 and VAT and an increased VE/VCO2 slope. Strength and power were also decreased in HF patients, suggesting further abnormalities in peripheral skeletal muscle function. Leg lean muscle mass was diminished in HF patients
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Table 1 Participant demographics.
Age (years) Weight (kg) Height (meters) Medications Beta-blocker ACE-inhibitor ARB Statin Diuretics
HF
Controls
Significance
67.4 ± 8.9 86.0 ± 27.4 1.7 ± 0.07
65.3 ± 10.1 86.6 ± 14.9 1.7 ± 0.09
0.37 0.91 0.98
23 25 2 24 20
2 6 2 16 5
b 0.0001 b 0.0001 0.80 b 0.001 b 0.0001
HF indicates heart failure; ACE, angiotensin converting enzyme; ARB, angiotensin II receptor blocker.
but since “lean tissue” measures incorporate both bone and muscle tissues, isolated skeletal muscle implications are uncertain. Total adiposity was similar between HF patients and controls. Table 3 demonstrates the lack of correlation between lean mass and aerobic indices in HF patients. However, Table 4 shows that lean mass is significantly associated with strength capacity in HF patients, suggesting that lean mass has a greater influence on strength than aerobic ability. Table 4 also shows that fat mass correlates with strength; correlations were stronger in the HF group than in the controls. To further compare the effects of fat and lean body mass on strength capacity, HF patients were stratified into groups according to a b30 kg/m 2 (n = 21) and ≥ 30 kg/m 2 (n = 10) BMI threshold; mean BMI 25.0 ±3.1 vs. 37.0 ±7.5 kg/m2, p b 0.001, respectively. Although aerobic indices were similar between the two groups [peak VO2 (14.9 ±4.3 vs. 15.6 ±4.2 mlO2·kg− 1·min− 1, p= 0.66), VAT (11.0 ±2.7 vs. 10.9 ± 1.7 mlO2·kg− 1·min− 1, p= 0.84), and VE/VCO2 slope (36.9 ±13.2 vs. 35.1 ±9.4, p= 0.67)], those in the high BMI group had a significantly higher 1RM (181.0± 55.6 vs. 141.6 ±46.0 kg, pb 0.05). Fat mass, as assessed by DXA, was increased in the high BMI subgroup: total fat mass (26.5 ± 10.1 vs. 12.1 ± 3.9 kg, p b 0.01) as well as leg fat mass (7.2 ± 3.4 vs. 3.3 ± 1.2 kg, p b 0.01), and arm fat mass (2.4 ± 1.0 vs. 1.2 ± 0.5 kg, p b 0.01). 1RM correlated positively with total fat (r = 0.65, p b 0.05) and leg fat (r = 0.64, p b 0.05) only in the HF group with high BMI. Patients in the high BMI group also had increased total lean mass (36.4 ±4.3 vs. 29.7±2.6 kg, pb 0.0001) as well as leg lean mass (12.3± 2.1 vs. 9.4±1.2 kg, p b 0.01) and arm lean mass (4.3±0.7 vs. 3.5± 0.5 kg, pb 0.01). However, there were no significant correlations between lean mass and function in this group.
Table 2 Differences in function and body composition between HF patients and control subjects.
Aerobic capacity Peak VO2 (ml·kg− 1·min− 1) VAT (ml·kg− 1·min− 1) VE/VCO2 slope Strength capacity 1RM (kg) Power (watts) DXA fat and lean body mass distributions (normalized to height) Total lean (kg) Legs lean (kg) Arms lean (kg) Total fat (kg) Leg fat (kg) Arm fat (kg)
HF
Controls
Significance
15.4 ± 4.2 10.9 ± 2.1 35.7 ± 10.6
23.4 ± 6.6 14.4 ± 4.0 29.1 ± 4.6
b 0.0001 b 0.0001 b 0.01
154.8 ± 52.0 226.4 ± 99.2
195.3 ± 56.8 313.3 ± 130.6
b 0.01 b 0.01
31.2 ± 4.8 10.3 ± 2.0 3.8 ± 0.7 16.7 ± 9.4 4.6 ± 2.8 1.6 ± .9
32.5 ± 3.8 11.1 ± 1.4 4.0 ± 0.9 16.3 ± 5.0 4.3 ± 1.4 1.6 ± 0.6
0.20 b 0.05 0.24 0.82 0.62 0.80
Peak VO2 indicates maximal oxygen consumption; VAT oxygen consumption at anaerobic threshold; VE/VCO2 slope ventilatory efficiency; 1RM the one repetition maximum.
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Table 3 Correlations between aerobic capacity and body anthropometrics in HF patients and controls. Peak VO2 HF
VAT Controls
VE/VCO2 slope
HF
Controls
HF
Controls
Lean body tissue distribution Total lean − 0.18 0.17 Legs lean − 0.13 0.26 Arms lean − 0.04 0.44†
− 0.06 − 0.09 0.05
0.05 0.19 0.21
− 0.08 − 0.11 − 0.18
− 0.09 − 0.02 − 0.22
Adipose tissue distribution Total fat − 0.17 − 0.23 Leg fat − 0.21 − 0.22 Arm fat − 0.27 − 0.22
− 0.17 − 0.19 − 0.28
− 0.17 − 0.14 − 0.17
− 0.10 − 0.06 − 0.06
0.04 − 0.10 − 0.03
Peak VO2 indicates maximal oxygen consumption; VAT oxygen consumption at anaerobic threshold; VE/VCO2 slope ventilatory efficiency. † p b 0.01.
elevated in the patients with BMI ≥30 kg/m2, only fat mass correlated with strength, possibly indicating a unique health benefit from adiposity. Lavie et al. [4] demonstrated that HF patients who suffered cardiovascular events had lower BMIs and body surface areas than those who did not experience an event over two-years. This study suggests that a greater fat mass in HF patients protects them from clinical events. Those with less fat mass, including those who had similar amounts of lean tissue, were more likely to develop an event. Despite Lavie's study and others indicating lower mortality rates among obese HF patients [3,6,25,26], clarification regarding the cardioprotective aspects of fat is needed. It remains unclear if fat provides direct benefits or if it primarily stimulates muscle mass and strength. These differences have bearing on HF management priorities as well as other chronic disease for which body composition affects clinical course and prognosis (e.g., kidney disease [27,28], and chronic obstructive pulmonary disease [29]). 4.1. Limitations
4. Discussion The obesity paradox insinuates that increased body fat imparts protective benefits in a HF population. The current investigation shows that adiposity correlates with strength capacity in HFREF patients. Paradoxical benefits of obesity might relate to increased strength and/ or the metabolic, biological, and/or physiological derivatives of increased strength capacity. HFREF patients were subdivided into groups with high and low BMI; in the subgroup with BMI ≥30 kg/m 2, both fat mass and lean body mass were greater than in the subgroup with BMI b30 kg/m 2, but only fat mass correlated to strength capacity. This suggests that fat itself may underlie a fundamental functional benefit rather than it serving primarily as a stimulus for increased lean body mass as its only mechanism of benefit. Nonetheless, the coexistence of higher fat and lean body mass among those with high BMI highlights the complex interrelationship between fat and lean body mass in relation to high BMI. Our findings are consistent with those of Anker et al. [24] who showed that the ability to perform work in HF reflects measures of both distance and mass. HF patients who carry more mass (i.e. those who are overweight or obese) over a longer distance are inevitably doing more work. This study indicates that overweight and obese adults inevitably incorporate strength training into everyday activities, since their muscles must support excess adipose tissue as compared to normal or under-weight patients. We extend these findings by applying DXA to show that HFREF patients with increased body fat achieve greater strength capacities. While lean muscle and fat mass were both
Table 4 Correlations between strength capacity and body composition in HF patients and controls. 1RM HF
Power Controls
HF
Controls
Lean body tissue distribution Total lean 0.54† Legs lean 0.53† Arms lean 0.48†
0.63‡ 0.54‡ 0.38⁎
0.19 0.13 0.34
0.16 0.11 0.12
Body fat distribution Total fat 0.56† Leg fat 0.45⁎ Arm fat 0.39⁎
0.40⁎ 0.37⁎ 0.41⁎
0.24 0.06 0.23
0.17 0.11 0.14
1RM is the one repetition maximum. ⁎ p b 0.05. † p b 0.01. ‡ p b 0.001.
While our study population was small, our data distinguished functional ramifications in HF vs. controls that were consistent with larger studies, corroborating the implications of body composition data. Furthermore, our protocol was rigorous, with comprehensive physical function assessments as well as DXA scans, providing an important and relatively exceptional opportunity for novel assessments of body composition and exercise attributes. While a cardiologist examined each patient prior to enrollment to ensure that they were euvolemic and stable, some patients may have had water retention which could potentially have confounded DXA assessments. Additionally, diet and serology (including adipocytokines) were not measured and these would have helped refine/enhance our conclusions. Our study also only enrolled male subjects and therefore further evaluation is needed to determine the effects of adipose tissue on function in the female population. This is not a longitudinal study and further research is therefore needed to determine prognostic implications. Finally, this study relied on a cross-sectional design; further research is needed to clarify causal benefits of adipose tissue. 4.2. Conclusion Fat mass is related to increased muscle strength in obese HF patients, probably as a natural source of chronic resistance exercise, with paradoxical beneficial implications on health. Acknowledgments The authors of this manuscript have certified that they comply with the Principles of Ethical Publishing in the International Journal of Cardiology. References [1] Nicklas B, Cesari M, Penninx W, et al. Abdominal obesity is an independent risk factor for chronic heart failure in older people. J Am Geriatr Soc 2006;54:413–20. [2] Lloyd-Jones D, Adams R, Brown T, et al. Heart disease and stroke statistics—2010 update: a report from the American Heart Association. Circulation 2010;121: e46–215. [3] Romero-Corral A, Montari V, Somers V, et al. Association of bodyweight with total mortality and with cardiovascular events in coronary artery disease: a systemic review of cohort studies. Lancet 2006;368:666–78. [4] Lavie C, Milani R, Ventura H. Body composition and heart failure prevalence and prognosis: getting to the fat of the matter in the “obesity paradox”. Mayo Clin Proc 2010;85(7):605–8. [5] Arena R, Lavie C. The obesity paradox and outcome in heart failure: is excess bodyweight truly protective? Future Cardiol 2010;6:1–6. [6] Oreopoulos A, Padwal R, Kalantar-Zadeh K, Fonarow G, Norris C, McAlister F. Body mass index and mortality in heart failure: a meta-analysis. Am Heart J 2008;156: 13–22. [7] Lavie C, Osman A, Milani R, Mehra M. Body composition and prognosis in chronic systolic heart failure: the obesity paradox. Am J Cardiol 2003;91(7):891–4.
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