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The impact of body mass index on clinical outcomes after acute myocardial infarction
International Journal of Cardiology 145 (2010) 476–480
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International Journal of Cardiology j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / i j c a r d
The impact of body mass index on clinical outcomes after acute myocardial infarction Doron Aronson a,c,⁎, Mithal Nassar b,c, Taly Goldberg a,c, Michael Kapeliovich a,c, Haim Hammerman a,c, Zaher S. Azzam b,c a b c
Department of Cardiology, Rambam Medical Center, Technion, Israel Institute of Technology, Haifa, Israel Internal Medicine B, Rambam Medical Center, Technion, Israel Institute of Technology, Haifa, Israel Rappaport Faculty of Medicine and Research Institute, Technion, Israel Institute of Technology, Haifa, Israel
a r t i c l e
i n f o
Article history: Received 9 July 2009 Received in revised form 4 December 2009 Accepted 24 December 2009 Available online 22 January 2010 Keywords: Anemia Body mass index Heart failure Myocardial infarction Prognosis
a b s t r a c t Background: Several studies indicated that an elevated body mass index (BMI) is associated with a lower rate of mortality in patients with acute myocardial infarction (AMI). However, the existence of the obesity paradox in AMI patients remains controversial. Methods: We examined the association of BMI and clinical outcomes in 2157 patient with AMI (mean followup of 26 months). BMI was categorized into 9 groups (b 18.5, 18.5 to 20.9, 21.0 to 23.4, 23.5 to 24.9, 25.0 to 26.4, 26.5 to 27.9, 28.0 to 29.9, 30.0 to 34.9, and ≥ 35.0 kg/m2). Cox regression was used to calculate hazard ratios (HR) for the various BMI categories, adjusting for the clinical variables, left ventricular ejection fraction, and hemoglobin level. Results: BMI had a U-shaped association with mortality. Relative to the lowest mortality group (BMI of 26.5 to 27.9 kg/m2), the adjusted HRs for mortality were increased only in the lower (HR 2.3; 95% CI 1.3–4.2) and upper (HR 1.8; 95% 1.2–2.9) BMI categories. There was a significant interaction between BMI and anemia (P = 0.0003) such that the U-shaped relationship between BMI and mortality was present mainly in patients with anemia. Patients in the lower and upper BMI categories and concomitant anemia had a striking increase in mortality (adjusted HR 5.1, 95% CI 1.9–11.7 and 3.2, 95% CI 1.5–7.0, respectively). Conclusion: Both obesity and underweight are associated with increased mortality in patients with AMI. The risk of mortality is particularly high among underweight and obese patients with anemia. © 2010 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Obesity is a major public health problem in the United States and worldwide. Nearly 60% of the adult population in the United States are overweight or obese [1]. In the general population, overweight and obesity are associated with increased risk of cardiovascular diseases, including coronary disease, heart failure and atrial fibrillation [2–8]. Therefore, many patients with acute coronary syndromes are overweight or obese [9–11]. Despite the cardiovascular risks associated with overweight and obesity that are observed in the general population, several chronic disease states including stable coronary disease, heart failure, and end-stage renal disease, as well as elderly populations have exhibited a reversal of the traditional obesity epidemiology. In these studies, elevated BMI has been associated with improved survival — a phenomenon that has been termed the obesity paradox [12–15]. Although the association between BMI and adverse cardiovascular outcomes within the general population is well established, its influence on clinical outcomes in the setting of acute coronary syndromes ⁎ Corresponding author. Department of Cardiology, Rambam Medical Center, POB 9602, Haifa 31096, Israel. Tel.: + 972 48 542790; fax: + 972 48 542176. E-mail address: [email protected] (D. Aronson). 0167-5273/$ – see front matter © 2010 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.ijcard.2009.12.029
is controversial. In patients with acute myocardial infarction (AMI), several studies reported that high BMI exerts a protective effect on survival [9,14,15]. By contrast, some studies found no evidence for the existence of the obesity paradox [11], while other studies described a U-shaped relationship between BMI and outcome [10]. In the present study we used a prospective database [16] to investigate the association between BMI and risk of all-cause mortality and other adverse cardiovascular outcomes in patients with AMI. The database provided an opportunity to study the relationship between BMI and cardiovascular outcomes, controlling for the confounding risk factors as well as the severity of concomitant anemia, a general marker of chronic disease and poor health. 2. Methods The study included patients presenting to the intensive coronary care unit of Rambam Medical Center with AMI between July 2001 and September 2007. AMI was diagnosed based on the European Society of Cardiology and American College of Cardiology criteria [17]. The institutional review committee on human research approved the study protocol. The height and weight were measured in the hospital and used to calculate the BMI. BMI was divided into 9 categories of BMI based on the National Institutes of Health— AARP cohort (b 18.5, 18.5 to 20.9, 21.0 to 23.4, 23.5 to 24.9, 25.0 to 26.4, 26.5 to 27.9, 28.0 to 29.9, 30.0 to 34.9, and ≥ 35.0 kg/m2) [18,19]. These categories incorporate World Health Organization (WHO) and the National Heart, Lung, and Blood Institute
D. Aronson et al. / International Journal of Cardiology 145 (2010) 476–480 criteria definitions of underweight (BMI, b 18.5 kg/m2), normal weight (18.5 to b 25.0 kg/m2), overweight (25.0 to b 30.0 kg/m2), and obesity (≥ 30.0 kg/m2) [20]. We also analyzed the relationship between BMI and mortality after dividing the study population into deciles of the BMI distribution. Hemoglobin levels were obtained and analyzed using the Advia 120 Hematology Analyzer (Siemens Healthcare Diagnostics). Anemia was defined as hemoglobin levels lower than 13 g/dL in men and 12 g/dL in women, in accordance with the WHO criteria [21]. Left ventricular ejection fraction (LVEF) was assessed by echocardiography and classified as normal (≥ 55%), mildly reduced (45–54%), moderately reduced (30–44%) and severely reduced (b 30%) [22]. 2.1. Study endpoints The primary end point of the study was all-cause mortality [23]. Following hospital discharge, clinical endpoint information was acquired by reviewing the national death registry and by contacting each patient individually. Secondary endpoints included 1) the development of heart failure (defined as new-onset heart failure requiring readmission to hospital); and 2) recurrent infarction. The secondary endpoints were confirmed using hospital records and discharge summaries. 2.2. Statistical analysis Continuous variables are presented as mean (SD) or medians (with interquartile ranges), and categorical variables as numbers and percentages. The baseline characteristics of the groups were compared using analysis of variance for continuous variables and by χ2 statistic for categorical variables. Survival curves were constructed using the Kaplan–Meier method, and comparisons were made using the log-rank test. Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CI) for various BMI categories. Multivariate-adjusted HRs were calculated using patients in the BMI category with the lowest mortality as the reference group. Stepwise Cox proportional hazards models with backward selection were used to calculate hazard ratios (HRs) and 95% confidence intervals (CI) for BMI categories. The Cox models were adjusted for age, gender, previous infarction, history of diabetes, hypertension, smoking status, serum creatinine, anterior location of the infarction, STelevation infarction, Killip class at admission and coronary revascularization during hospital course. All multivariable models were further adjusted LVEF and hemoglobin levels. The proportional hazard assumption was evaluated and satisfied for these multivariable survival analyses by examining plots of Schoenfeld residuals for each covariate. The presence of a linear or U-shaped (quadratic term) association was tested using the median of BMI in each category as a continuous variable in the Cox proportional hazards regression models. P values for the quadratic term from the Cox proportional hazards regression models are reported because linear terms were not statistically significant (all P N 0.05). Linearity of BMI was studied by adding to the model the predefined groups along with the continuous variable. If the set of BMI categories were without importance, linearity was accepted. Our analysis also focused on the possible interaction between BMI and anemia. The existence of an interaction was formally evaluated with the use of Cox regression model incorporating terms for the main effect of BMI, the main effect of hemoglobin, and the interaction between BMI and hemoglobin. Two-sided, 95% likelihood ratio confidence intervals (CI) were constructed, and an α-level of 0.05 was used to declare statistical significance of the interaction term. We performed stratified analyses to assess whether the association between BMI and the risk of death varied according to anemia status. Differences were considered statistically significant at the 2-sided P b 0.05 level. Statistical analyses were performed using the SPSS statistical software version 15.0 (Chicago, IL). 3. Results 3.1. Patients The study included 2157 patients presenting to the intensive coronary care unit of Rambam Medical Center with AMI between July 2001 and June 2008. AMI was diagnosed based on the European Society of Cardiology and American College of Cardiology criteria [17]. The institutional review committee on human research approved the study protocol. Mean BMI was 27.7 ± 4.8 kg/m2 and the majority of patients (74.0%) had a BMI above 25.0 kg/m2. Baseline demography and characteristics of the study population in the 9 categories of BMI are presented in Table 1. There were significant differences between the 9 BMI groups. Patients with higher BMI were more likely to be younger, hypertensive and diabetic. The prevalence of female gender was higher in both underweight and obese patients. Notably, patients in the upper BMI category were more likely to present with clinical evidence for heart failure despite similar left ventricular systolic function. Anemia was more prevalent among patients with lower BMI. The use of acute medications varied across the BMI subgroups. Beta-blockers, angiotensin-converting enzyme inhibitors and statin were prescribed more often in patients with a higher BMI. Coronary revascularization was used less frequently in underweight patients.
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3.2. BMI and mortality During a mean follow-up of 26 months (range 6 to 79), 390 patients died, with 14 (53.8%), 17 (21.5%), 51 (21.4%), 64 (21.3%), 47 (16.0%), 46 (14.5%), 50 (14.6%), 68 (15.7) and 33 (26.2%) of deaths occurring in the respective BMI groups. There was a statistically significant U-shaped association between BMI and all-cause mortality (P b 0.0001). Kaplan–Meier analysis showed that the lowest mortality occurred in patients with a BMI of 26.5 to 27.9 kg/m2 and the highest mortality in both underweight and obese patients (Fig. 1). Unadjusted Cox model demonstrated a U-shaped relation BMI and the risk of death, with the lowest risks of all-cause mortality at a BMI of 26.5 to 27.9 kg/m2. There was an increased risk of death in the lowest BMI categories (BMI b 25.0 kg/m2) and patients in the upper BMI category (BMI ≥ 35.0 kg/m2) (Fig. 2A). The U-shaped association between BMI and all-cause mortality remained after further multivariable adjustments for clinical variables, LVEF and hemoglobin levels (P = 0.003). After multivariable adjustment, the effect of BMI was attenuated but patients in the lowest BMI category (BMI b 18.5 kg/m2) and patients in upper BMI category (BMI ≥ 35.0 kg/m2) remained at a significantly higher risk for mortality (Fig. 2B). Similar results were obtained when the relation between BMI and mortality was analyzed using deciles of BMI. The adjusted risk of death in the lowest BMI decile (b 22.3 kg/m2) was increased by a factor of 1.7 (95% CI, 1.1 to 2.8) and by a factor of 1.9 (95% CI 1.2 to 3.1) in the upper BMI decile (N33.2 kg/m2). 3.3. Secondary endpoints During the follow-up period, 171 patients were readmitted for the treatment of heart failure and 140 were readmitted for recurrent infarction. In a univariable Cox model, only patients in the upper BMI category were at a higher risk for heart failure with a hazard ratio of 2.4 (95% CI 1.3 to 4.7; P = 0.005). After multivariable adjustments, patients in this category remained at a significantly higher risk for heart failure (adjusted HR 2.0, 95% CI 1.1 to 3.7; P = 0.03). In contrast, the incidence of recurrent infarction was not significantly different across categories of BMI. 3.4. Interaction between BMI and anemia There was a significant association between anemia (WHO criteria) and mortality (hazard ratio 2.1, 95% CI 1.7 2.6; P b 0.0001). However, in a Cox regression analysis, there was a significant interaction between BMI and anemia in an unadjusted model containing only the main effects of BMI and anemia (P = 0.002) and in the fully adjusted model (P = 0.0003). Subsequent analyses were therefore performed after dividing the study population into 2 groups based on the presence (n = 466) or absence (n = 1691) of anemia. Fig. 3 shows the adjusted hazard ratios compared to the group with the lowest mortality (26.5 to 27.9 kg/m2, in patients with or without anemia). The U-shaped relationship between BMI and mortality was present mainly in the subgroup of patients with anemia, with a striking increase in mortality in patients with BMI below 18.5 kg/m2 and above 35.0 kg/m2 (Fig. 3).
4. Discussion In the present study of a large, unselected cohort of AMI patients, the associations of BMI with the risk of death were U-shaped, with higher risks observed in the lower and upper BMI categories. After adjustments for the clinical variables, LVEF and hemoglobin levels, there was no evidence for an inverse relationship between BMI and death (the obesity paradox). Patients with BMI N 35 kg/m2 were at increased risk for mortality and the development of heart failure during follow-up. In addition, there was a significant interaction between anemia and BMI, such that obese patients with anemia exhibited a striking increase in mortality. 4.1. The obesity paradox In contrast to the increased risk for cardiovascular events associated with overweight and obesity in the general population, recent studies suggested that in several groups of patients with cardiovascular diseases, particularly heart failure [12,13,24] and acute coronary syndromes [9,14,15], elevated BMI is associated with better survival. An apparent protective effect of high BMI on mortality has been found in randomized trials of patients with unstable angina and non-STelevation myocardial infarction [15] or ST-elevation myocardial infarction [14].
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Table 1 Baseline clinical characteristics according to BMI category. Body mass index (kg/m2) Characteristic
b 18.5 (n = 26)
18.5–20.9 (n = 79)
21.0–23.4 (n = 238)
23.5–24.9 (n = 301)
25.0–26.4 (n = 294)
26.5–27.9 (n = 317)
28.0–29.9 (n = 342)
30.0–34.9 (n = 434)
≥35.0 (n = 126)
P value
Age (years) Female gender Previous infarct Smoker Hypertension Diabetes Creatinine (mg/dL) Baseline hemoglobin (g/dL) Anemia (WHO) Systolic BP (mm Hg) Heart rate (bpm) Killip class N 1 ST-elevation infarction Anterior infarction Ejection fraction (%) In hospital medications Anti platelet agents Beta-blockers ACE inhibitors/ARBs Statins Coronary revascularization
68 ± 17 11 (42) 9 (35) 7 (30) 14 (54) 2 (8) 1.0 ± 0.6 12.5 ± 1.8 11 (42) 121 ± 28 85 ± 25 7 (27) 17 (65) 13 (50) 41 ± 13
65 ± 13 27 (34) 14 (18) 41 (52) 34 (43) 15 (19) 1.0 ± 0.4 13.4 ± 1.9 26 (33) 125 ± 29 76 ± 21 21 (27) 62 (79) 39 (49) 46 ± 13
64 ± 13 56 (24) 49 (21) 90 (38) 102 (43) 56 (24) 1.0 ± 0.5 13.5 ± 1.8 68 (29) 128 ± 27 77 ± 18 53 (22) 199 (84) 104 (44) 44 ± 13
62 ± 13 49 (16) 61 (20) 113 (38) 130 (43) 79 (26) 1.1 ± 0.7 14.0 ± 1.8 60 (20) 130 ± 26 77 ± 19 60 (20) 244 (81) 114 (38) 45 ± 13
61 ± 12 39 (13) 64 (22) 114 (39) 130 (44) 68 (23) 1.0 ± 0.7 14.0 ± 1.8 57 (20) 129 ± 24 75 ± 17 52 (18) 245 (83) 125 (43) 44 ± 12
61 ± 12 60 (19) 66 (21) 129 (41) 165 (52) 91 (29) 1.1 ± 0.5 14.0 ± 1.8 65 (21) 131 ± 27 78 ± 18 63 (20) 258 (81) 139 (44) 45 ± 12
60 ± 12 61 (18) 91 (27) 142 (42) 193 (56) 111 (33) 1.1 ± 0.7 14.1 ± 1.8 70 (21) 133 ± 25 77 ± 17 71 (21) 271 (79) 129 (38) 45 ± 12
59 ± 12 110 (25) 112 (26) 187 (43) 245 (57) 155 (36) 1.0 ± 0.7 14.1 ± 2.3 82 (19) 134 ± 24 79 ± 17 90 (21) 352 (81) 185 (43) 45 ± 13
60 ± 13 46 (37) 33 (26) 43 (34) 97 (77) 54 (43) 1.2 ± 0.9 13.7± 27 (21) 133 ± 26 82 ± 19 42 (33) 89 (71) 54 (43) 44 ± 13
b 0.0001 b 0.0001 0.18 0.16 b 0.0001 b 0.0001 0.74 b 0.0001 0.003 0.004 0.003 0.04 0.06 0.44 0.65
25 (96) 15 (58) 17 (65) 14 (54) 7 (27)
77 60 59 57 35
228 190 179 170 124
290 231 228 224 157
289 242 234 229 156
312 263 259 251 179
338 303 288 286 182
428 375 361 360 254
121 (96) 104 (83) 104 (83) 101 (80) 57 (45)
0.11 b 0.0001 0.01 b 0.0001 0.01
(98) (76) (77) (72) (44)
(96) (80) (75) (71) (52)
(96) (77) (76) (74) (52)
(98) (82) (80) (78) (53)
(98) (83) (82) (79) (57)
(99) (87) (84) (84) (53)
(99) (86) (83) (83) (59)
Values are expressed as number (%) of patients, mean value ± SD. ACE = angiotensin-converting enzyme; ARB = angiotensin receptor blockers.
Because most patients with acute coronary syndromes are overweight or obese, these findings may have important clinical implications in terms of recommendations concerning optimal weight and weight loss in this population. However, other studies were unable to demonstrate a protective effect of obesity in patients with acute myocardial infarction [11]. Furthermore, some studies reported
Fig. 1. Kaplan–Meier plot showing the crude cumulative incidence of death according to the 5 BMI categories. P b 0.0001 by the log-rank test for the overall comparison among the groups.
Fig. 2. Unadjusted (A) and adjusted (B) hazard ratios (and 95% confidence intervals) for mortality in the six BMI categories. The reference group in each stratum is patients with BMI of 26.5 to 27.9 kg/m2.
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who already developed coronary plaque rupture, obesity which contributes to the progression of coronary atherosclerosis in the general population, may be less important in determining the risk for recurrent atherothrombotic events as compared to inflammation [32], platelet hyperaggregability [33] and complications of coronary interventions including stent thrombosis.
4.3. Interaction of BMI with anemia
Fig. 3. Adjusted hazard ratios for mortality in the six BMI categories according to anemia status. The reference group in each stratum is patients with BMI of 26.5 to 27.9 kg/m2.
a U-shaped relationship between BMI and clinical outcomes after an acute coronary syndrome [9,10]. Our results support a nonlinear relationship between BMI and hazard of mortality which changes rapidly at low and high BMI, corresponding to classes II and III obesity [20]. After adjustments, BMI had a neutral effect on mortality and other clinical outcomes except for the extremes of the BMI spectrum. Thus, the results of the present could not support the existence of any protective effect of obesity, and suggest that BMI above the threshold of 35 kg/m2 should be considered an important risk factor for death following AMI. Our findings are consistent with several studies in patients with acute coronary syndromes [9,10], as well as with large studies in the general population that established the existence of a U-shaped relationship between BMI and mortality with increased risk among subjects with the lowest and highest BMI [2,5,18,25–27]. In these studies of Western populations, the lowest all-cause mortality occurred in persons with a BMI between 23.0 and 27.0 kg/m2, and the risk associated with elevated BMI is apparent at BMI values of 30 kg/m2 or even lower [5,25,26]. In the present study, a higher risk for heart failure and death was observed only for BMI ≥ 35 kg/m2. Thus, although there was no evidence for the obesity paradox, the Ushaped relationship between BMI and mortality appears to be shifted toward higher BMI values in patients with AMI as compared with the general population. 4.2. BMI and heart failure Our results highlight the important contribution of heart failure to the poor outcome of patients with obesity after AMI. Patients with BMI N 35.0 kg/m2 were at higher risk for both heart failure and death. The development of late heart failure in patients after myocardial infarction is particularly ominous because these patients have several fold increase in the risk of death when compared to other myocardial infarction survivors [28]. In the general population, the risk of developing heart failure approximately doubles in obese (≥30 kg/m2) individuals, as compared to subjects with normal BMI [2]. Several factors promote the development of heart failure in obesity, including increased blood volume, concomitant hypertension, left ventricular hypertrophy and excess of fatty acids that can directly damage cardiac myocytes [29,30]. By contrast, although obesity is associated with multiple risk factors for the development of atherosclerosis [31], such as sedentary lifestyle, type 2 diabetes, hypertension, and dyslipidemia, recurrent infarction was not associated with BMI. In patients after incident AMI
Previous studies of the relationship between BMI and clinical outcomes in patients with acute coronary syndromes did not consider the potential impact of anemia — a powerful independent indicator of mortality and heart failure in patients with AMI [34,35]. We observed a significant interaction between BMI and hemoglobin with regard to the risk of death. The U-shaped relationship between BMI and mortality was stronger among patients with concomitant anemia at baseline such that the mortality risk associated with obesity occurred predominantly in patients with anemia. This effect modification indicates that anemia at hospital admission strengthened the risk associated with underweight and obesity. The finding that low BMI was associated with increased mortality mainly in the subgroup of patients with anemia suggests that the increased mortality in these patients is partly secondary to underlying chronic conditions and general poor health. There are several possible explanations for the impact of concomitant anemia on the risk of death among obese patients. The adaptive responses to anemia may lead to left ventricular dilatation and eccentric remodelling which may have deleterious effects on the myocardium, including higher oxygen consumption and increased diastolic wall stress [36,37]. The ability of anemia to promote left ventricular dilatation may be particularly deleterious in obese patients in the post infarction period because both obesity [30] and anemia [36] lead to volume expansion, increase in left ventricular preload and eccentric hypertrophy. Both anemia and obesity may increase sympathetic neural activity [38], which can exacerbate myocardial ischemia and heart failure.
4.4. Study limitations Several study limitations should be considered in the interpretation of the results. There was no information regarding the duration of obesity, changes in BMI occurring during follow-up, differences in physical activity and cardiorespiratory fitness. We did not obtain other measures of obesity such as waist-to-hip ratio or waist circumference (an anthropometric index usually considered a surrogate marker of abdominal fat mass, subcutaneous and intra abdominal). These measures of adiposity may better reflect body fat content and distribution when compared with BMI. However, waist circumference has not been shown to be a better predictor of death than BMI in patients with acute coronary syndromes [11]. The strength of this study includes prospectively collected data of consecutive unselected patients. We adjusted for numerous confounding factors, left ventricular function and the degree of anemia was included in the multivariable analysis. In addition we performed separate analyses for heart failure and recurrent infarctions. Our Cox models did not adjust for medical therapies because these therapies were administered at different time points with respect to the time of admission, and in many cases for clinical indications that may also affect clinical outcomes (e.g. angiotensin-converting enzyme inhibitors or beta-blockers for heart failure). We believe that such an analysis might bias the results because agents that are known to reduce the risk of mortality would be associated with higher incidence of mortality and heart failure (i.e. “reverse causation”). However, lack of adjustments for medical therapies may also introduce a bias.
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4.5. Conclusion Our study indicates that both obesity and underweight are associated with increased mortality from all causes in patients with AMI. The risk of mortality is particularly high among underweight and obese patients with concomitant anemia. Acknowledgment The authors of this manuscript have certified that they comply with the Principles of Ethical Publishing in the International Journal of Cardiology [39]. References [1] Must A, Spadano J, Coakley EH, Field AE, Colditz G, Dietz WH. The disease burden associated with overweight and obesity. JAMA 1999;282:1523–9. [2] Kenchaiah S, Evans JC, Levy D, et al. Obesity and the risk of heart failure. N Engl J Med 2002;347:305–13. [3] Wessel TR, Arant CB, Olson MB, et al. Relationship of physical fitness vs body mass index with coronary artery disease and cardiovascular events in women. JAMA 2004;292:1179–87. [4] Yusuf S, Hawken S, Ounpuu S, et al. Obesity and the risk of myocardial infarction in 27,000 participants from 52 countries: a case–control study. Lancet 2005;366: 1640–9. [5] Calle EE, Thun MJ, Petrelli JM, Rodriguez C, Heath Jr CW. Body-mass index and mortality in a prospective cohort of U.S. adults. N Engl J Med 1999;341:1097–105. [6] Wilson PW, Bozeman SR, Burton TM, Hoaglin DC, Ben-Joseph R, Pashos CL. Prediction of first events of coronary heart disease and stroke with consideration of adiposity. Circulation 2008;118:124–30. [7] Tsang TS, Barnes ME, Miyasaka Y, et al. Obesity as a risk factor for the progression of paroxysmal to permanent atrial fibrillation: a longitudinal cohort study of 21 years. Eur Heart J 2008;29:2227–33. [8] Wang TJ, Parise H, Levy D, et al. Obesity and the risk of new-onset atrial fibrillation. JAMA 2004;292:2471–7. [9] Diercks DB, Roe MT, Mulgund J, et al. The obesity paradox in non-ST-segment elevation acute coronary syndromes: results from the Can Rapid risk stratification of Unstable angina patients Suppress ADverse outcomes with Early implementation of the American College of Cardiology/American Heart Association Guidelines Quality Improvement Initiative. Am Heart J 2006;152:140–8. [10] Eisenstein EL, McGuire DK, Bhapkar MV, et al. Elevated body mass index and intermediate-term clinical outcomes after acute coronary syndromes. Am J Med 2005;118:981–90. [11] Zeller M, Steg PG, Ravisy J, et al. Relation between body mass index, waist circumference, and death after acute myocardial infarction. Circulation 2008;118: 482–90. [12] Kalantar-Zadeh K, Block G, Horwich T, Fonarow GC. Reverse epidemiology of conventional cardiovascular risk factors in patients with chronic heart failure. J Am Coll Cardiol 2004;43:1439–44. [13] Oreopoulos A, Padwal R, Norris CM, Mullen JC, Pretorius V, Kalantar-Zadeh K. Effect of obesity on short- and long-term mortality postcoronary revascularization: a meta-analysis. Obesity (Silver Spring) 2008;16:442–50. [14] Mehta L, Devlin W, McCullough PA, et al. Impact of body mass index on outcomes after percutaneous coronary intervention in patients with acute myocardial infarction. Am J Cardiol 2007;99:906–10. [15] Buettner HJ, Mueller C, Gick M, et al. The impact of obesity on mortality in UA/nonST-segment elevation myocardial infarction. Eur Heart J 2007;28:1694–701.
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International Journal of Cardiology j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / i j c a r d
The impact of body mass index on clinical outcomes after acute myocardial infarction Doron Aronson a,c,⁎, Mithal Nassar b,c, Taly Goldberg a,c, Michael Kapeliovich a,c, Haim Hammerman a,c, Zaher S. Azzam b,c a b c
Department of Cardiology, Rambam Medical Center, Technion, Israel Institute of Technology, Haifa, Israel Internal Medicine B, Rambam Medical Center, Technion, Israel Institute of Technology, Haifa, Israel Rappaport Faculty of Medicine and Research Institute, Technion, Israel Institute of Technology, Haifa, Israel
a r t i c l e
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Article history: Received 9 July 2009 Received in revised form 4 December 2009 Accepted 24 December 2009 Available online 22 January 2010 Keywords: Anemia Body mass index Heart failure Myocardial infarction Prognosis
a b s t r a c t Background: Several studies indicated that an elevated body mass index (BMI) is associated with a lower rate of mortality in patients with acute myocardial infarction (AMI). However, the existence of the obesity paradox in AMI patients remains controversial. Methods: We examined the association of BMI and clinical outcomes in 2157 patient with AMI (mean followup of 26 months). BMI was categorized into 9 groups (b 18.5, 18.5 to 20.9, 21.0 to 23.4, 23.5 to 24.9, 25.0 to 26.4, 26.5 to 27.9, 28.0 to 29.9, 30.0 to 34.9, and ≥ 35.0 kg/m2). Cox regression was used to calculate hazard ratios (HR) for the various BMI categories, adjusting for the clinical variables, left ventricular ejection fraction, and hemoglobin level. Results: BMI had a U-shaped association with mortality. Relative to the lowest mortality group (BMI of 26.5 to 27.9 kg/m2), the adjusted HRs for mortality were increased only in the lower (HR 2.3; 95% CI 1.3–4.2) and upper (HR 1.8; 95% 1.2–2.9) BMI categories. There was a significant interaction between BMI and anemia (P = 0.0003) such that the U-shaped relationship between BMI and mortality was present mainly in patients with anemia. Patients in the lower and upper BMI categories and concomitant anemia had a striking increase in mortality (adjusted HR 5.1, 95% CI 1.9–11.7 and 3.2, 95% CI 1.5–7.0, respectively). Conclusion: Both obesity and underweight are associated with increased mortality in patients with AMI. The risk of mortality is particularly high among underweight and obese patients with anemia. © 2010 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Obesity is a major public health problem in the United States and worldwide. Nearly 60% of the adult population in the United States are overweight or obese [1]. In the general population, overweight and obesity are associated with increased risk of cardiovascular diseases, including coronary disease, heart failure and atrial fibrillation [2–8]. Therefore, many patients with acute coronary syndromes are overweight or obese [9–11]. Despite the cardiovascular risks associated with overweight and obesity that are observed in the general population, several chronic disease states including stable coronary disease, heart failure, and end-stage renal disease, as well as elderly populations have exhibited a reversal of the traditional obesity epidemiology. In these studies, elevated BMI has been associated with improved survival — a phenomenon that has been termed the obesity paradox [12–15]. Although the association between BMI and adverse cardiovascular outcomes within the general population is well established, its influence on clinical outcomes in the setting of acute coronary syndromes ⁎ Corresponding author. Department of Cardiology, Rambam Medical Center, POB 9602, Haifa 31096, Israel. Tel.: + 972 48 542790; fax: + 972 48 542176. E-mail address: [email protected] (D. Aronson). 0167-5273/$ – see front matter © 2010 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.ijcard.2009.12.029
is controversial. In patients with acute myocardial infarction (AMI), several studies reported that high BMI exerts a protective effect on survival [9,14,15]. By contrast, some studies found no evidence for the existence of the obesity paradox [11], while other studies described a U-shaped relationship between BMI and outcome [10]. In the present study we used a prospective database [16] to investigate the association between BMI and risk of all-cause mortality and other adverse cardiovascular outcomes in patients with AMI. The database provided an opportunity to study the relationship between BMI and cardiovascular outcomes, controlling for the confounding risk factors as well as the severity of concomitant anemia, a general marker of chronic disease and poor health. 2. Methods The study included patients presenting to the intensive coronary care unit of Rambam Medical Center with AMI between July 2001 and September 2007. AMI was diagnosed based on the European Society of Cardiology and American College of Cardiology criteria [17]. The institutional review committee on human research approved the study protocol. The height and weight were measured in the hospital and used to calculate the BMI. BMI was divided into 9 categories of BMI based on the National Institutes of Health— AARP cohort (b 18.5, 18.5 to 20.9, 21.0 to 23.4, 23.5 to 24.9, 25.0 to 26.4, 26.5 to 27.9, 28.0 to 29.9, 30.0 to 34.9, and ≥ 35.0 kg/m2) [18,19]. These categories incorporate World Health Organization (WHO) and the National Heart, Lung, and Blood Institute
D. Aronson et al. / International Journal of Cardiology 145 (2010) 476–480 criteria definitions of underweight (BMI, b 18.5 kg/m2), normal weight (18.5 to b 25.0 kg/m2), overweight (25.0 to b 30.0 kg/m2), and obesity (≥ 30.0 kg/m2) [20]. We also analyzed the relationship between BMI and mortality after dividing the study population into deciles of the BMI distribution. Hemoglobin levels were obtained and analyzed using the Advia 120 Hematology Analyzer (Siemens Healthcare Diagnostics). Anemia was defined as hemoglobin levels lower than 13 g/dL in men and 12 g/dL in women, in accordance with the WHO criteria [21]. Left ventricular ejection fraction (LVEF) was assessed by echocardiography and classified as normal (≥ 55%), mildly reduced (45–54%), moderately reduced (30–44%) and severely reduced (b 30%) [22]. 2.1. Study endpoints The primary end point of the study was all-cause mortality [23]. Following hospital discharge, clinical endpoint information was acquired by reviewing the national death registry and by contacting each patient individually. Secondary endpoints included 1) the development of heart failure (defined as new-onset heart failure requiring readmission to hospital); and 2) recurrent infarction. The secondary endpoints were confirmed using hospital records and discharge summaries. 2.2. Statistical analysis Continuous variables are presented as mean (SD) or medians (with interquartile ranges), and categorical variables as numbers and percentages. The baseline characteristics of the groups were compared using analysis of variance for continuous variables and by χ2 statistic for categorical variables. Survival curves were constructed using the Kaplan–Meier method, and comparisons were made using the log-rank test. Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CI) for various BMI categories. Multivariate-adjusted HRs were calculated using patients in the BMI category with the lowest mortality as the reference group. Stepwise Cox proportional hazards models with backward selection were used to calculate hazard ratios (HRs) and 95% confidence intervals (CI) for BMI categories. The Cox models were adjusted for age, gender, previous infarction, history of diabetes, hypertension, smoking status, serum creatinine, anterior location of the infarction, STelevation infarction, Killip class at admission and coronary revascularization during hospital course. All multivariable models were further adjusted LVEF and hemoglobin levels. The proportional hazard assumption was evaluated and satisfied for these multivariable survival analyses by examining plots of Schoenfeld residuals for each covariate. The presence of a linear or U-shaped (quadratic term) association was tested using the median of BMI in each category as a continuous variable in the Cox proportional hazards regression models. P values for the quadratic term from the Cox proportional hazards regression models are reported because linear terms were not statistically significant (all P N 0.05). Linearity of BMI was studied by adding to the model the predefined groups along with the continuous variable. If the set of BMI categories were without importance, linearity was accepted. Our analysis also focused on the possible interaction between BMI and anemia. The existence of an interaction was formally evaluated with the use of Cox regression model incorporating terms for the main effect of BMI, the main effect of hemoglobin, and the interaction between BMI and hemoglobin. Two-sided, 95% likelihood ratio confidence intervals (CI) were constructed, and an α-level of 0.05 was used to declare statistical significance of the interaction term. We performed stratified analyses to assess whether the association between BMI and the risk of death varied according to anemia status. Differences were considered statistically significant at the 2-sided P b 0.05 level. Statistical analyses were performed using the SPSS statistical software version 15.0 (Chicago, IL). 3. Results 3.1. Patients The study included 2157 patients presenting to the intensive coronary care unit of Rambam Medical Center with AMI between July 2001 and June 2008. AMI was diagnosed based on the European Society of Cardiology and American College of Cardiology criteria [17]. The institutional review committee on human research approved the study protocol. Mean BMI was 27.7 ± 4.8 kg/m2 and the majority of patients (74.0%) had a BMI above 25.0 kg/m2. Baseline demography and characteristics of the study population in the 9 categories of BMI are presented in Table 1. There were significant differences between the 9 BMI groups. Patients with higher BMI were more likely to be younger, hypertensive and diabetic. The prevalence of female gender was higher in both underweight and obese patients. Notably, patients in the upper BMI category were more likely to present with clinical evidence for heart failure despite similar left ventricular systolic function. Anemia was more prevalent among patients with lower BMI. The use of acute medications varied across the BMI subgroups. Beta-blockers, angiotensin-converting enzyme inhibitors and statin were prescribed more often in patients with a higher BMI. Coronary revascularization was used less frequently in underweight patients.
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3.2. BMI and mortality During a mean follow-up of 26 months (range 6 to 79), 390 patients died, with 14 (53.8%), 17 (21.5%), 51 (21.4%), 64 (21.3%), 47 (16.0%), 46 (14.5%), 50 (14.6%), 68 (15.7) and 33 (26.2%) of deaths occurring in the respective BMI groups. There was a statistically significant U-shaped association between BMI and all-cause mortality (P b 0.0001). Kaplan–Meier analysis showed that the lowest mortality occurred in patients with a BMI of 26.5 to 27.9 kg/m2 and the highest mortality in both underweight and obese patients (Fig. 1). Unadjusted Cox model demonstrated a U-shaped relation BMI and the risk of death, with the lowest risks of all-cause mortality at a BMI of 26.5 to 27.9 kg/m2. There was an increased risk of death in the lowest BMI categories (BMI b 25.0 kg/m2) and patients in the upper BMI category (BMI ≥ 35.0 kg/m2) (Fig. 2A). The U-shaped association between BMI and all-cause mortality remained after further multivariable adjustments for clinical variables, LVEF and hemoglobin levels (P = 0.003). After multivariable adjustment, the effect of BMI was attenuated but patients in the lowest BMI category (BMI b 18.5 kg/m2) and patients in upper BMI category (BMI ≥ 35.0 kg/m2) remained at a significantly higher risk for mortality (Fig. 2B). Similar results were obtained when the relation between BMI and mortality was analyzed using deciles of BMI. The adjusted risk of death in the lowest BMI decile (b 22.3 kg/m2) was increased by a factor of 1.7 (95% CI, 1.1 to 2.8) and by a factor of 1.9 (95% CI 1.2 to 3.1) in the upper BMI decile (N33.2 kg/m2). 3.3. Secondary endpoints During the follow-up period, 171 patients were readmitted for the treatment of heart failure and 140 were readmitted for recurrent infarction. In a univariable Cox model, only patients in the upper BMI category were at a higher risk for heart failure with a hazard ratio of 2.4 (95% CI 1.3 to 4.7; P = 0.005). After multivariable adjustments, patients in this category remained at a significantly higher risk for heart failure (adjusted HR 2.0, 95% CI 1.1 to 3.7; P = 0.03). In contrast, the incidence of recurrent infarction was not significantly different across categories of BMI. 3.4. Interaction between BMI and anemia There was a significant association between anemia (WHO criteria) and mortality (hazard ratio 2.1, 95% CI 1.7 2.6; P b 0.0001). However, in a Cox regression analysis, there was a significant interaction between BMI and anemia in an unadjusted model containing only the main effects of BMI and anemia (P = 0.002) and in the fully adjusted model (P = 0.0003). Subsequent analyses were therefore performed after dividing the study population into 2 groups based on the presence (n = 466) or absence (n = 1691) of anemia. Fig. 3 shows the adjusted hazard ratios compared to the group with the lowest mortality (26.5 to 27.9 kg/m2, in patients with or without anemia). The U-shaped relationship between BMI and mortality was present mainly in the subgroup of patients with anemia, with a striking increase in mortality in patients with BMI below 18.5 kg/m2 and above 35.0 kg/m2 (Fig. 3).
4. Discussion In the present study of a large, unselected cohort of AMI patients, the associations of BMI with the risk of death were U-shaped, with higher risks observed in the lower and upper BMI categories. After adjustments for the clinical variables, LVEF and hemoglobin levels, there was no evidence for an inverse relationship between BMI and death (the obesity paradox). Patients with BMI N 35 kg/m2 were at increased risk for mortality and the development of heart failure during follow-up. In addition, there was a significant interaction between anemia and BMI, such that obese patients with anemia exhibited a striking increase in mortality. 4.1. The obesity paradox In contrast to the increased risk for cardiovascular events associated with overweight and obesity in the general population, recent studies suggested that in several groups of patients with cardiovascular diseases, particularly heart failure [12,13,24] and acute coronary syndromes [9,14,15], elevated BMI is associated with better survival. An apparent protective effect of high BMI on mortality has been found in randomized trials of patients with unstable angina and non-STelevation myocardial infarction [15] or ST-elevation myocardial infarction [14].
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Table 1 Baseline clinical characteristics according to BMI category. Body mass index (kg/m2) Characteristic
b 18.5 (n = 26)
18.5–20.9 (n = 79)
21.0–23.4 (n = 238)
23.5–24.9 (n = 301)
25.0–26.4 (n = 294)
26.5–27.9 (n = 317)
28.0–29.9 (n = 342)
30.0–34.9 (n = 434)
≥35.0 (n = 126)
P value
Age (years) Female gender Previous infarct Smoker Hypertension Diabetes Creatinine (mg/dL) Baseline hemoglobin (g/dL) Anemia (WHO) Systolic BP (mm Hg) Heart rate (bpm) Killip class N 1 ST-elevation infarction Anterior infarction Ejection fraction (%) In hospital medications Anti platelet agents Beta-blockers ACE inhibitors/ARBs Statins Coronary revascularization
68 ± 17 11 (42) 9 (35) 7 (30) 14 (54) 2 (8) 1.0 ± 0.6 12.5 ± 1.8 11 (42) 121 ± 28 85 ± 25 7 (27) 17 (65) 13 (50) 41 ± 13
65 ± 13 27 (34) 14 (18) 41 (52) 34 (43) 15 (19) 1.0 ± 0.4 13.4 ± 1.9 26 (33) 125 ± 29 76 ± 21 21 (27) 62 (79) 39 (49) 46 ± 13
64 ± 13 56 (24) 49 (21) 90 (38) 102 (43) 56 (24) 1.0 ± 0.5 13.5 ± 1.8 68 (29) 128 ± 27 77 ± 18 53 (22) 199 (84) 104 (44) 44 ± 13
62 ± 13 49 (16) 61 (20) 113 (38) 130 (43) 79 (26) 1.1 ± 0.7 14.0 ± 1.8 60 (20) 130 ± 26 77 ± 19 60 (20) 244 (81) 114 (38) 45 ± 13
61 ± 12 39 (13) 64 (22) 114 (39) 130 (44) 68 (23) 1.0 ± 0.7 14.0 ± 1.8 57 (20) 129 ± 24 75 ± 17 52 (18) 245 (83) 125 (43) 44 ± 12
61 ± 12 60 (19) 66 (21) 129 (41) 165 (52) 91 (29) 1.1 ± 0.5 14.0 ± 1.8 65 (21) 131 ± 27 78 ± 18 63 (20) 258 (81) 139 (44) 45 ± 12
60 ± 12 61 (18) 91 (27) 142 (42) 193 (56) 111 (33) 1.1 ± 0.7 14.1 ± 1.8 70 (21) 133 ± 25 77 ± 17 71 (21) 271 (79) 129 (38) 45 ± 12
59 ± 12 110 (25) 112 (26) 187 (43) 245 (57) 155 (36) 1.0 ± 0.7 14.1 ± 2.3 82 (19) 134 ± 24 79 ± 17 90 (21) 352 (81) 185 (43) 45 ± 13
60 ± 13 46 (37) 33 (26) 43 (34) 97 (77) 54 (43) 1.2 ± 0.9 13.7± 27 (21) 133 ± 26 82 ± 19 42 (33) 89 (71) 54 (43) 44 ± 13
b 0.0001 b 0.0001 0.18 0.16 b 0.0001 b 0.0001 0.74 b 0.0001 0.003 0.004 0.003 0.04 0.06 0.44 0.65
25 (96) 15 (58) 17 (65) 14 (54) 7 (27)
77 60 59 57 35
228 190 179 170 124
290 231 228 224 157
289 242 234 229 156
312 263 259 251 179
338 303 288 286 182
428 375 361 360 254
121 (96) 104 (83) 104 (83) 101 (80) 57 (45)
0.11 b 0.0001 0.01 b 0.0001 0.01
(98) (76) (77) (72) (44)
(96) (80) (75) (71) (52)
(96) (77) (76) (74) (52)
(98) (82) (80) (78) (53)
(98) (83) (82) (79) (57)
(99) (87) (84) (84) (53)
(99) (86) (83) (83) (59)
Values are expressed as number (%) of patients, mean value ± SD. ACE = angiotensin-converting enzyme; ARB = angiotensin receptor blockers.
Because most patients with acute coronary syndromes are overweight or obese, these findings may have important clinical implications in terms of recommendations concerning optimal weight and weight loss in this population. However, other studies were unable to demonstrate a protective effect of obesity in patients with acute myocardial infarction [11]. Furthermore, some studies reported
Fig. 1. Kaplan–Meier plot showing the crude cumulative incidence of death according to the 5 BMI categories. P b 0.0001 by the log-rank test for the overall comparison among the groups.
Fig. 2. Unadjusted (A) and adjusted (B) hazard ratios (and 95% confidence intervals) for mortality in the six BMI categories. The reference group in each stratum is patients with BMI of 26.5 to 27.9 kg/m2.
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who already developed coronary plaque rupture, obesity which contributes to the progression of coronary atherosclerosis in the general population, may be less important in determining the risk for recurrent atherothrombotic events as compared to inflammation [32], platelet hyperaggregability [33] and complications of coronary interventions including stent thrombosis.
4.3. Interaction of BMI with anemia
Fig. 3. Adjusted hazard ratios for mortality in the six BMI categories according to anemia status. The reference group in each stratum is patients with BMI of 26.5 to 27.9 kg/m2.
a U-shaped relationship between BMI and clinical outcomes after an acute coronary syndrome [9,10]. Our results support a nonlinear relationship between BMI and hazard of mortality which changes rapidly at low and high BMI, corresponding to classes II and III obesity [20]. After adjustments, BMI had a neutral effect on mortality and other clinical outcomes except for the extremes of the BMI spectrum. Thus, the results of the present could not support the existence of any protective effect of obesity, and suggest that BMI above the threshold of 35 kg/m2 should be considered an important risk factor for death following AMI. Our findings are consistent with several studies in patients with acute coronary syndromes [9,10], as well as with large studies in the general population that established the existence of a U-shaped relationship between BMI and mortality with increased risk among subjects with the lowest and highest BMI [2,5,18,25–27]. In these studies of Western populations, the lowest all-cause mortality occurred in persons with a BMI between 23.0 and 27.0 kg/m2, and the risk associated with elevated BMI is apparent at BMI values of 30 kg/m2 or even lower [5,25,26]. In the present study, a higher risk for heart failure and death was observed only for BMI ≥ 35 kg/m2. Thus, although there was no evidence for the obesity paradox, the Ushaped relationship between BMI and mortality appears to be shifted toward higher BMI values in patients with AMI as compared with the general population. 4.2. BMI and heart failure Our results highlight the important contribution of heart failure to the poor outcome of patients with obesity after AMI. Patients with BMI N 35.0 kg/m2 were at higher risk for both heart failure and death. The development of late heart failure in patients after myocardial infarction is particularly ominous because these patients have several fold increase in the risk of death when compared to other myocardial infarction survivors [28]. In the general population, the risk of developing heart failure approximately doubles in obese (≥30 kg/m2) individuals, as compared to subjects with normal BMI [2]. Several factors promote the development of heart failure in obesity, including increased blood volume, concomitant hypertension, left ventricular hypertrophy and excess of fatty acids that can directly damage cardiac myocytes [29,30]. By contrast, although obesity is associated with multiple risk factors for the development of atherosclerosis [31], such as sedentary lifestyle, type 2 diabetes, hypertension, and dyslipidemia, recurrent infarction was not associated with BMI. In patients after incident AMI
Previous studies of the relationship between BMI and clinical outcomes in patients with acute coronary syndromes did not consider the potential impact of anemia — a powerful independent indicator of mortality and heart failure in patients with AMI [34,35]. We observed a significant interaction between BMI and hemoglobin with regard to the risk of death. The U-shaped relationship between BMI and mortality was stronger among patients with concomitant anemia at baseline such that the mortality risk associated with obesity occurred predominantly in patients with anemia. This effect modification indicates that anemia at hospital admission strengthened the risk associated with underweight and obesity. The finding that low BMI was associated with increased mortality mainly in the subgroup of patients with anemia suggests that the increased mortality in these patients is partly secondary to underlying chronic conditions and general poor health. There are several possible explanations for the impact of concomitant anemia on the risk of death among obese patients. The adaptive responses to anemia may lead to left ventricular dilatation and eccentric remodelling which may have deleterious effects on the myocardium, including higher oxygen consumption and increased diastolic wall stress [36,37]. The ability of anemia to promote left ventricular dilatation may be particularly deleterious in obese patients in the post infarction period because both obesity [30] and anemia [36] lead to volume expansion, increase in left ventricular preload and eccentric hypertrophy. Both anemia and obesity may increase sympathetic neural activity [38], which can exacerbate myocardial ischemia and heart failure.
4.4. Study limitations Several study limitations should be considered in the interpretation of the results. There was no information regarding the duration of obesity, changes in BMI occurring during follow-up, differences in physical activity and cardiorespiratory fitness. We did not obtain other measures of obesity such as waist-to-hip ratio or waist circumference (an anthropometric index usually considered a surrogate marker of abdominal fat mass, subcutaneous and intra abdominal). These measures of adiposity may better reflect body fat content and distribution when compared with BMI. However, waist circumference has not been shown to be a better predictor of death than BMI in patients with acute coronary syndromes [11]. The strength of this study includes prospectively collected data of consecutive unselected patients. We adjusted for numerous confounding factors, left ventricular function and the degree of anemia was included in the multivariable analysis. In addition we performed separate analyses for heart failure and recurrent infarctions. Our Cox models did not adjust for medical therapies because these therapies were administered at different time points with respect to the time of admission, and in many cases for clinical indications that may also affect clinical outcomes (e.g. angiotensin-converting enzyme inhibitors or beta-blockers for heart failure). We believe that such an analysis might bias the results because agents that are known to reduce the risk of mortality would be associated with higher incidence of mortality and heart failure (i.e. “reverse causation”). However, lack of adjustments for medical therapies may also introduce a bias.
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4.5. Conclusion Our study indicates that both obesity and underweight are associated with increased mortality from all causes in patients with AMI. The risk of mortality is particularly high among underweight and obese patients with concomitant anemia. Acknowledgment The authors of this manuscript have certified that they comply with the Principles of Ethical Publishing in the International Journal of Cardiology [39]. References [1] Must A, Spadano J, Coakley EH, Field AE, Colditz G, Dietz WH. The disease burden associated with overweight and obesity. JAMA 1999;282:1523–9. [2] Kenchaiah S, Evans JC, Levy D, et al. Obesity and the risk of heart failure. N Engl J Med 2002;347:305–13. [3] Wessel TR, Arant CB, Olson MB, et al. Relationship of physical fitness vs body mass index with coronary artery disease and cardiovascular events in women. JAMA 2004;292:1179–87. [4] Yusuf S, Hawken S, Ounpuu S, et al. Obesity and the risk of myocardial infarction in 27,000 participants from 52 countries: a case–control study. Lancet 2005;366: 1640–9. [5] Calle EE, Thun MJ, Petrelli JM, Rodriguez C, Heath Jr CW. Body-mass index and mortality in a prospective cohort of U.S. adults. N Engl J Med 1999;341:1097–105. [6] Wilson PW, Bozeman SR, Burton TM, Hoaglin DC, Ben-Joseph R, Pashos CL. Prediction of first events of coronary heart disease and stroke with consideration of adiposity. Circulation 2008;118:124–30. [7] Tsang TS, Barnes ME, Miyasaka Y, et al. Obesity as a risk factor for the progression of paroxysmal to permanent atrial fibrillation: a longitudinal cohort study of 21 years. Eur Heart J 2008;29:2227–33. [8] Wang TJ, Parise H, Levy D, et al. Obesity and the risk of new-onset atrial fibrillation. JAMA 2004;292:2471–7. [9] Diercks DB, Roe MT, Mulgund J, et al. The obesity paradox in non-ST-segment elevation acute coronary syndromes: results from the Can Rapid risk stratification of Unstable angina patients Suppress ADverse outcomes with Early implementation of the American College of Cardiology/American Heart Association Guidelines Quality Improvement Initiative. Am Heart J 2006;152:140–8. [10] Eisenstein EL, McGuire DK, Bhapkar MV, et al. Elevated body mass index and intermediate-term clinical outcomes after acute coronary syndromes. Am J Med 2005;118:981–90. [11] Zeller M, Steg PG, Ravisy J, et al. Relation between body mass index, waist circumference, and death after acute myocardial infarction. Circulation 2008;118: 482–90. [12] Kalantar-Zadeh K, Block G, Horwich T, Fonarow GC. Reverse epidemiology of conventional cardiovascular risk factors in patients with chronic heart failure. J Am Coll Cardiol 2004;43:1439–44. [13] Oreopoulos A, Padwal R, Norris CM, Mullen JC, Pretorius V, Kalantar-Zadeh K. Effect of obesity on short- and long-term mortality postcoronary revascularization: a meta-analysis. Obesity (Silver Spring) 2008;16:442–50. [14] Mehta L, Devlin W, McCullough PA, et al. Impact of body mass index on outcomes after percutaneous coronary intervention in patients with acute myocardial infarction. Am J Cardiol 2007;99:906–10. [15] Buettner HJ, Mueller C, Gick M, et al. The impact of obesity on mortality in UA/nonST-segment elevation myocardial infarction. Eur Heart J 2007;28:1694–701.
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