The Obesity Paradox in Heart Failure Patients with Preserved Versus Reduced Ejection Fraction: a Meta-Analysis of Individual Patient Data

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ORIGINAL ARTICLE The obesity paradox in heart failure patients with preserved versus reduced ejection fraction: a meta-analysis of individual patient data

R Padwal1, FA McAlister1, JJV McMurray2, MR Cowie3, M Rich4, S Pocock5, K Swedberg6, A Maggioni7, G Gamble8, C Ariti5, N Earle8, G Whalley9, KK Poppe8, RN Doughty8 and A Bayes-Genis10 for the Meta-analysis Global Group in Chronic Heart Failure (MAGGIC) Investigators11

BACKGROUND: In heart failure (HF), obesity, defined as body mass index (BMI) X30 kg m À 2, is paradoxically associated with higher survival rates compared with normal-weight patients (the ‘obesity paradox’). We sought to determine if the obesity paradox differed by HF subtype (reduced ejection fraction (HF-REF) versus preserved ejection fraction (HF-PEF)). PATIENTS AND METHODS: A sub-analysis of the MAGGIC meta-analysis of patient-level data from 14 HF studies was performed. Subjects were divided into five BMI groups: o22.5, 22.5–24.9 (referent), 25–29.9, 30–34.9 and X35 kg m À 2. Cox proportional hazards models adjusted for age, sex, aetiology (ischaemic or non-ischaemic), hypertension, diabetes and baseline blood pressure, stratified by study, were used to examine the independent association between BMI and 3-year total mortality. Analyses were conducted for the overall group and within HF-REF and HF-PEF groups. RESULTS: BMI data were available for 23 967 subjects (mean age, 66.8 years; 32% women; 46% NYHA Class II; 50% Class III) and 5609 (23%) died by 3 years. Obese patients were younger, more likely to receive cardiovascular (CV) drug treatment, and had higher comorbidity burdens. Compared with BMI levels between 22.5 and 24.9 kg m À 2, the adjusted relative hazards for 3-year mortality in subjects with HF-REF were: hazard ratios (HR) ¼ 1.31 (95% confidence interval ¼ 1.15–1.50) for BMI o22.5, 0.85 (0.76–0.96) for BMI 25.0–29.9, 0.64 (0.55–0.74) for BMI 30.0–34.9 and 0.95 (0.78–1.15) for BMI X35. Corresponding adjusted HRs for those with HF-PEF were: 1.12 (95% confidence interval ¼ 0.80–1.57) for BMI o22.5, 0.74 (0.56–0.97) for BMI 25.0–29.9, 0.64 (0.46–0.88) for BMI 30.0–34.9 and 0.71 (0.49–1.05) for BMI X35. CONCLUSIONS: In patients with chronic HF, the obesity paradox was present in both those with reduced and preserved ventricular systolic function. Mortality in both HF subtypes was U-shaped, with a nadir at 30.0–34.9 kg m À 2.

International Journal of Obesity (2014) 38, 1110–1114; doi:10.1038/ijo.2013.203 Keywords: body mass index; heart failure; prognosis; obesity paradox; ejection fraction

INTRODUCTION were largely performed in patients with HF-REF.2 In addition, Obesity, defined as a body mass index (BMI) X30 kg m À 2,isan discrepant findings have been reported. For example, independent risk factor for CV morbidity and mortality and an observational study of 4700 subjects hospitalized with HF doubles the risk of heart failure (HF).1 In the presence of reported that obese subjects with HF-PEF had lower mortality established HF, obesity has been paradoxically associated with a compared with normal weight subjects (hazard ratio (HR) ¼ 0.77 reduced risk of mortality, a finding that has been termed ‘the (0.70–0.86)), whereas obese subjects with HF-REF exhibited obesity paradox’.2,3 Several explanations for the obesity paradox increased mortality risk than leaner patients with HF-REF have been proposed and it is currently unclear if it is a true (HR ¼ 1.21 (1.01–1.45)).9 Thus, there is a need to clarify whether phenomenon or a consequence of methodological bias.3–7 the paradox is specific to one HF subtype or is found to an Two major subtypes of HF exist—HF with reduced ejection equivalent degree in both HF-PEF and HF-REF. fraction (HF-REF) and HF with preserved ejection fraction (HF-PEF). We used the Meta-analysis Global Group in Chronic Heart Although patients with HF-REF exhibit higher mortality rates, both Failure (MAGGIC) individual patient data meta-analysis to explore subtypes confer a high absolute mortality risk (B120–140 deaths the relationship between BMI and survival and whether the per 1000 patient years).8 Studies describing the obesity paradox association was similar in those with HF-REF and HF-PEF.

1Department of Medicine, University of Alberta, Edmonton, Canada; 2BHF Cardiovascular Research Centre, University of Glasgow, Glasgow, UK; 3Faculty of Medicine, National Heart and Lung Institute, Imperial College London (Royal Brompton Hospital), London, UK; 4Washington University School of Medicine, St Louis, MO, USA; 5Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK; 6Department of Emergency and Cardiovascular Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; 7ANMCO Research Center, Florence, Italy; 8Department of Medicine and National Institute for Health Innovation, University of Auckland, Auckland, New Zealand; 9Faculty of Social and Health Sciences, UNITEC Institute of Technology, Auckland, New Zealand and 10Department of Medicine, Hospital Universitari Germans Trias i Pujol UAB, Barcelona, Spain. Correspondence: Dr R Padwal, General Internal Medicine and Clinical Pharmacology, 2F1.26 WMC, University of Alberta Hospital, 8440 112 Street, Edmonton, Alberta T6G 2B7, Canada. E-mail: [email protected] 11See appendix. Received 27 August 2013; revised 3 October 2013; accepted 15 October 2013; accepted article preview online 31 October 2013; advance online publication, 26 November 2013 Obesity paradox in heart failure R Padwal et al 1111 PATIENTS AND METHODS using the Cochran-Armitage trend test for ordered categorical data. Detailed methods, including details about study selection criteria, included Confidence intervals around person time rates were calculated using studies, and main results of the MAGGIC meta-analysis have been Miettinen’s exact test (http://www.openepi.com, accessed on 11 June described elsewhere.8 In this analysis, we pooled the data from the 14 2013). The Cox proportional hazard of time to all cause death within 3 studies that measured BMI at baseline and included at least 3 years of years from baseline study visit was used to model the hazard of BMI strata, follow-up. Left ventricular ejection fraction (LVEF) was not an entry adjusted for age, sex, LVEF group, ischaemic aetiology, hypertension, criterion for any of the studies. The meta-analysis protocol was approved diabetes, systolic blood pressure and atrial fibrillation. Models were by the University of Auckland Human Subjects Ethics Committee. Data constructed from those individuals with complete data for each model. (including demographics, comorbidities, therapy, symptom status, clinical Imputation of missing data was not performed. Unless otherwise stated, variables, laboratory variables, and outcomes) from the individual studies SAS v9.2 (SAS Institute Inc., Cary, NC, USA) were used for all analyses. were re-coded into a uniform format at the Central Coordinating Centre at All tests were two-tailed and Po0.05 was considered significant. the University of Auckland and incorporated into one database. For this analysis, HF-PEF was defined as a baseline LVEF X50%. Covariates were also defined at baseline. BMI was calculated by taking the weight in kilograms and dividing by the square of the height (in meters). RESULTS Subjects were stratified according to BMI levels (o22.5, 22.5–24.9 BMI data were available for 23 976 patients from 14 studies (mean 2 (referent), 25.0–29.9, 30.0–34.9 and X35.0 kg m À ). Sensitivity analyses age, 66.8 years; 32% women). Most patients had NYHA class II were performed by repeating the analyses within each HF subtype; in the (46%) or III (50%) symptoms. A total of 5609 (23%) patients died World Health Organization BMI strata (o18.5, 18.5–24.9, 25–29.9 over the 914 (interquartile range ¼ 316–1096) day follow-up andX30 kg m À 2); in patients with and without oedema (as a proxy measure for fluid overload); and in subjects in whom estimated glomerular period. filtration rate data were available. The baseline characteristics of patients by BMI group and Data are presented as mean (standard deviation) unless otherwise stratified by HF subtype are shown in Table 1. In both the HF-PEF stated. To compare baseline characteristics, tests for linear trend were and HF-REF subgroups, low-BMI subjects were older and more constructed from orthogonal contrasts for continuous variables and by frequently women. In contrast, hypertension and diabetes were

Table 1. Baseline characteristics by BMI strata and HF subtype

BMI HF-REF HF-PEF

o22.5 22.5–24.9 25–29.9 30–34.9 X35 P-valuea o22.5 22.5–24.9 25–29.9 30–34.9 X35 P-valuea

N (14 studies) 3073 3747 7144 2751 987 950 1140 2326 1269 589 Age, years (s.d.) 69 (13) 67 (12) 66 (11) 63 (11) 60 (11) o0.0001 74 (12) 72 (12) 70 (11) 68 (10) 64 (11) o0.0001 Women, % 40 25 22 25 35 o0.0001 63 44 41 49 55 0.0009

Medical history Hypertension 25 31 37 49 59 o0.0001 32 41 48 61 68 o0.0001 Myocardial infarction 44 50 50 48 40 0.964 21 27 29 28 22 0.096 Atrial ﬁbrillation 22 23 22 25 26 0.015 33 28 27 27 26 0.0009 Diabetes 13 17 22 31 39 o0.0001 11 15 19 28 36 o0.0001 Ischaemic aetiology 52 57 59 56 47 0.475 40 45 48 44 35 0.493

Medication ACEi or ARB 68 72 70 68 65 0.207 32 35 36 42 36 0.0006 Beta-blocker 30 38 42 48 49 o0.0001 25 34 40 43 42 o0.0001 Diuretic 86 83 83 84 89 0.654 76 76 74 81 86 o0.0001 Spironolactone 28 25 23 25 25 0.0093 18 17 16 15 20 0.817 Digoxin 59 53 49 46 46 o0.0001 42 35 32 28 25 o0.0001

Clinical status NYHA class (I/II/III/IV) 7/42/41/10 9/45/38/8 8/47/39/6 6/46/43/6 4/37/54/5 12/46/32/10 13/51/30/6 14/51/28/7 11/51/30/7 5/45/43/7 Heart rate, bpm 79 (18) 78 (18) 77 (17) 79 (18) 79 (17) 0.589 80 (22) 77 (20) 76 (20) 76 (19) 78 (18) 0.1 SBP, mm Hg 124 (21) 126 (20) 129 (20) 132 (20) 133 (20) o0.0001 135 (22) 137 (24) 139 (22) 140 (21) 142 (20) o0.0001 DBP, mm Hg 74 (12) 76 (11) 77 (11) 79 (12) 80 (12) o0.0001 75 (12) 77 (12) 80 (12) 80 (12) 81 (12) o0.0001 LVEF % (med, IQR) 30 (22,37) 31 (24,38) 33 (25,39) 33 (26,40) 34 (27,42) o0.0001 60 (56,60) 60 (54,60) 60 (54,61) 60 (55,62) 60 (56,63) 0.0003 N All-cause deaths 1027 985 1558 471 201 o0.0001 330 298 468 191 80 o0.0001 Abbreviations: ACEi, angiotensin-converting enzyme inhibitors; ARB, angiotensin II receptor blockers; BMI, body mass index; DBP, diastolic blood pressure; HF, heart failure; HF-PEF, heart failure with preserved ejection fraction; HF-REF, heart failure with reduced ejection fraction; LVEF, left ventricular ejection fraction; NYHA, New York Heart Association; SBP, systolic blood pressure. aP-values indicate tests for linear trend constructed from orthogonal contrasts for continuous variables and by using the Cochran-Armitage trend test for ordered categorical data.

Figure 1. Hazard ratios for total mortality. Data represent hazard ratios for total mortality with 95% conﬁdence intervals. Hazard ratios are adjusted for age and sex and stratiﬁed by study. BMI, body mass index; HF-REF, heart failure with reduced ejection fraction; HF-PEF, heart failure with preserved ejection fraction.

& 2014 Macmillan Publishers Limited International Journal of Obesity (2014) 1110 – 1114 Obesity paradox in heart failure R Padwal et al 1112 more common in overweight (BMI ¼ 25.0–29.9 kg m À 2) and obese strata, with 3-year mortality of 15% and 14%, respectively. By patients. Both systolic and diastolic blood pressure increased with contrast, the HF-REF o22.5 kg m À 2 stratum exhibited the highest increasing BMI strata. Angiotensin-converting enzyme inhibitors or 3-year mortality at 40%. angiotensin II receptor blockers, diuretics, spironolactone and digoxin were more often used in HF-REF subjects than HF-PEF Sensitivity analyses subjects in all BMI strata. Beta-blockers and diuretics were more Analyses were repeated within the HF-REF and HF-PEF subgroups often prescribed in high-BMI subjects, whereas digoxin was more À 2 commonly used in subjects with low-BMI levels. with BMI strata set at o20, 20–24.9, 25–29.9 and X30 kg m and The relative hazards for death from any cause (adjusted for age according to the presence/absence of oedema. The results of and sex, stratified by study) are shown in Figure 1. Compared with these sensitivity analyses were consistent with the main analyses patients with BMI levels between 22.5–24.9 kg m À 2 (reference (Figure 3 for presence/absence of oedema; other data not shown). group), patients in higher BMI categories had lower risk of death in In addition, in the subgroup of patients in which estimated the overall study population and in both HF-REF and HF-PEF glomerular filtration rate was available and included in the subgroups (with the lowest risk in the 30–34.9 kg m À 2 stratum). multivariable analysis (n ¼ 12 417), no appreciable differences Lower BMI was associated with a higher risk of all-cause death. In from the main analysis were found in the adjusted HR for each the fully adjusted model (age, sex, atrial fibrillation, LVEF group, BMI strata (data not shown). hypertension, ischaemic aetiology, systolic blood pressure and diabetes), a similar pattern was seen across BMI strata for both all- cause mortality (Table 2). DISCUSSION Figure 2 illustrates the 3-year mortality trends for the BMI We found that increasing BMI was associated with a lower risk groups stratified by HF subtype. The lowest risk of death was of total mortality both in patients with HF-REF and those with found in the HF-PEF 30–34.9 kg m À 2 and HF-PEF X35 kg m À 2 HF-PEF, with the lowest risk of mortality found in subjects with BMI levels between 30 and 34.9 kg m À 2 in both groups. This expands on our earlier report of a mortality risk score in MAGGIC that found BMI was one of the variables associated with a Table 2. Adjusted hazard ratios lower risk of mortality—in the current study, we examined the 10 BMI (kg m À 2) Hazard ratio (95% CI) impact of BMI in various patient strata defined by LVEF. The lower mortality risk found with increasing BMI levels was Whole group HF-REF HF-PEF attenuated after adjustment for potential confounders but still n ¼ 14 332 n ¼ 11 249 n ¼ 3083 remained clinically and statistically significant in the higher BMI strata. Our findings were robust to sensitivity analyses and confirm o22.5 1.29 (1.14, 1.46) 1.31 (1.15, 1.50) 1.12 (0.80, 1.57) 22.5–24.9 1 1 1 the presence of the obesity paradox regardless of LVEF. To our 25–29.9 0.84 (0.75, 0.93) 0.85 (0.76, 0.96) 0.74 (0.56, 0.97) knowledge, this is the largest published study with the most 30–34.9 0.64 (0.55, 0.73) 0.64 (0.55, 0.74) 0.64 (0.46, 0.88) robust covariate adjustments exploring the obesity paradox in X35 0.88 (0.74, 1.05) 0.95 (0.78, 1.15) 0.71 (0.49, 1.05) HF-REF 1.53 (1.37, 1.71) — — patients with HF-PEF. SBP (continuous) 0.991 (0.989, 0.993) 0.991 (0.988, 0.993) 0.995 (0.990, 0.999) There continues to be considerable debate regarding the Age 1.04 (1.03, 1.04) 1.04 (1.03 1.04) 1.06 (1.05, 1.08) origins of the obesity paradox and whether or not it represents a Sex (male) 1.23 (1.12, 1.35) 1.20 (1.08 1.33) 1.43 (1.17, 1.75) 3–6 Atrial fibrillation 1.26 (1.16, 1.38) 1.28 (1.16, 1.42) 1.19 (0.95, 1.49) valid phenomenon. It has been described in a broad spectrum Hypertension 1.04 (0.95, 1.13) 1.04 (0.94, 1.14) 1.03 (0.82, 1.29) of disease states characterized by malnutrition, inflammation and Ischaemic aetiology 1.22 (1.12, 1.34) 1.27 (1.15, 1.41) 1.04 (0.85, 1.28) Diabetes 1.59 (1.46, 1.74) 1.56 (1.42, 1.72) 1.82 (1.47, 2.26) cachexia, including (but not limited to) chronic infections, rheumatologic conditions, chronic lung disease, sepsis and Abbreviations: BMI, body mass index; CI, confidence interval; HF-PEF, heart coronary disease.11,12 Some contend that it is the result of failure with preserved ejection fraction; HF-REF, heart failure with reduced residual confounding resulting from factors such as smoking ejection fraction; SBP, systolic blood pressure. (which decreases body weight but increases mortality),

Figure 2. Total mortality stratiﬁed by BMI and HF subtype. BMI, body mass index; HF-REF, heart failure with reduced ejection fraction; HF-PEF, heart failure with preserved ejection fraction.

International Journal of Obesity (2014) 1110 – 1114 & 2014 Macmillan Publishers Limited Obesity paradox in heart failure R Padwal et al 1113

Figure 3. Total mortality in BMI strata, by the presence or absence of oedema. Data represent hazard ratios for total mortality with 95% confidence intervals. Hazard ratios are adjusted for age, sex, atrial fibrillation, diabetes, hypertension and ischaemic aetiology. BMI, body mass index; HF-REF, heart failure with reduced ejection fraction; HF-PEF, heart failure with preserved ejection fraction. unrecognized systemic illness or unintentional weight loss but the Although our study reports on a large, well categorized and importance of these factors as epidemiological confounders has heterogeneous cohort, there are limitations. Importantly, we lack recently been challenged.6,13 Others contend that the paradox is information on body composition, measures of central adiposity, due to selection bias (that is, unhealthiest obese dying before they inflammatory markers and CV fitness and thus cannot adjust for have the opportunity to develop chronic disease) and the absence these potential confounders. Missing BMI data can be a limitation of the paradox in some (but notably not all) healthy population- of any such study reporting associations of BMI and outcome, based cohorts supports this position.4 Statistical methods although only 16% of subjects in the 14 studies in the current employing population representative data to adjust for potential analysis had missing BMI data. selection bias does result in disappearance of the paradox and In conclusion, we confirmed that in patients with chronic HF the reappearance of the ‘expected’ increased risk association between obesity paradox was present in both those with reduced and obesity and mortality.5 Certainly, the published data do support preserved ventricular systolic function. Mortality in both HF subtypes the contention that obese patients with HF do systematically differ was U-shaped, with a nadir at BMI levels of 30.0–34.9 kg m À 2. from the non-obese in ways that may improve prognosis (for This raises questions about whether encouraging weight loss in example, they are consistently younger with higher blood obese individuals with HF should be recommended. Randomized pressure and more likely to receive drug therapy)3 but it is controlled trials will be required to definitively settle this issue. notable that in our study the paradox was still present even after adjustment for these factors. The use of BMI as a proxy measure for obesity has also been proposed as a potential explanation for the apparent association CONFLICT OF INTEREST between obesity and survival advantage. BMI appears to more The authors declare no conflict of interest. closely reflect lean mass rather than fat mass in HF patients.14,15 Increasing BMI may therefore reflect less cachexia, greater fitness and/or greater metabolic reserve instead of greater adiposity.14–16 Indeed, CV fitness is a key effect modifier for the relationship ACKNOWLEDGEMENTS between obesity and mortality, conferring a survival benefit FAM is supported by salary awards from Alberta Innovates-Health Solutions and the independent of adiposity in observational studies.17–19 Notably, Capital Health Chair in Cardiovascular Outcomes Research; KKP is supported by a the few studies that have used other measures of adiposity in HF Research Fellowship from the New Zealand Heart Foundation; RND holds the New patients, such as waist circumference or fat percentage Zealand Heart Foundation Chair in Heart Health; and MRC is supported by the National Institute for Health Research Cardiovascular Biomedical Research Unit at the ascertained by skin fold measurement, have also found the 17,20,21 Royal Brompton Hospital, London, UK. RP and FAM are supported by an alternate paradox to be present. In contrast, studies in patients with funding plan from the Government of Alberta. The MAGGIC meta-analysis was coronary disease have reported increasing mortality with supported by grants from the New Zealand National Heart Foundation, the University 22 increasing levels of central adiposity. Further complicating of Auckland and the University of Glasgow. matters, obese individuals with HF losing more than 5% of their initial body weight exhibit a higher mortality risk than those gaining weight (intentionality of weight loss was unknown in this study).23 Findings such as these may indicate that the obesity DISCLAIMER paradox may represent a valid phenomenon, with increasing These sponsors had no role in the design, conduct, data management adiposity protective against the malnutrition–inflammation– and analysis, manuscript preparation or review, nor in the authorization for cachexia complex that characterizes the HF state.3 submission.

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APPENDIX DIG Trial: DIG limited access data, Ali Ahmed; Euro HF Survey: MAGGIC Executive Group: MJ Lenzen, WJM Scholte op Reimer, E Boersma, PJMJ Vantrimpont, C Berry, R Doughty, C Granger, L Køber, B Massie, F McAlister, F Follath, K Swedberg, J Cleland, M Komajda; Gotsman: I Gotsman, J McMurray, S Pocock, K Poppe, K Swedberg, J Somaratne, D Zwas, D Planer, T Azaz-Livshits, D Admon, C Lotan, A Keren; G Whalley. Grigorian-Shamagian: L Grigorian-Shamagian, A Varela-Roman, P Mazoń-Ramos, P Rigeiro-Veloso, MA Bandin-Dieguez, MAGGIC Steering Group: JR Gonzalez-Juanatey; Guazzi: M Guazzi, J Myers, R Arena; Heart Failure Clinic Edmonton: FA McAlister, J Ezekowitz, A Ahmed, B Andersson, A Bayes-Genis, C Berry, M Cowie, PW Armstrong, Bibiana Cujec, Ian Paterson; Hillingdon: MR Cowie, R Cubbon, R Doughty, J Ezekowitz, J Gonzalez-Juanatey, M Gorini, DA Wood, AJS Coats, SG Thompson, V Suresh, PA Poole-Wilson, I Gotsman, L Grigorian-Shamagian, M Guazzi, M Kearney, L Køber, GC Sutton; HOLA: M Martıńez-Selle´s, JAG Robles, L Prieto, M Komajda, A di Lenarda, M Lenzen, D Lucci, S Macıń, B Madsen, MD Munõa, E Frades, O Dıáz-Castro, J Almendral; Italian HF A Maggioni, M Martıńez-Selle´s, F McAlister, F Oliva, K Poppe, Registry (IN-CHF): L Tarantini, P Faggiano, M Senni, D Lucci, D M Rich, M Richards, M Senni, I Squire, G Taffet, L Tarantini, Bertoli, M Porcu, C Opasich, L Tavazzi, AP Maggioni; Kirk: V Kirk, C Tribouilloy, R Troughton, H Tsutsui, G Whalley. M Bay, J Parner, K Krogsgaard, TM Herzog, S Boesgaard, C Hassager, OW Nielsen, J Aldershvile, H Nielsen L Kober; Macin: MAGGIC Coordinating Centre: SM Macıń, ER Perna, JP Cimbaro Canella, P Alvarenga, R Pantich, R Doughty, N Earle, GD Gamble, K Poppe, G Whalley, the University NRıós, EF Farias, JR Badaracco; Madsen: BK Madsen, JF Hansen, of Auckland, New Zealand. KH Stokholm, J Brons, D Husum, LS Mortensen; MUSIC: ABayes-Genis, R Vazquez, T Puig, C Fernandez-Palomeque, A Bardajı´, D Pascual-Figal, JOrdon˜ez-Llanos, M Valdes, A Gabarrus, R Pavon, L Pastor, MAGGIC Statistical Group: JR Gonzalez-Juanatey, J Almendral, M Fiol,V Nieto, C Macaya, C Ariti, J Dobson, GD Gamble, S Pocock, K Poppe. J Cinca, A Bayes de Luna; Newton: JD Newton, HM Blackledge, IB Squire; NPC I: SP Wright, GA Whalley, RN Doughty; Rich (data set 1): R Kerzner, BF Gage, KE Freedland, MW Rich: Rich (data set 2): Studies included: BC Huynh, A Rovner, KE Freedland, RM Carney, MW Rich; Taffet: AHFMS: RN Doughty, G Whalley; Andersson (2 data sets): GE Taffet, TA Teasdale, AJ Bleyer, NJ Kutka, RJ Luchi; Tribouilloy: B Andersson, C Hall; BATTLESCARRED and Richards: AM Richards, C Tribouilloy, D Rusinaru, H Mahjoub, V Soulie`re, F Le´vy, M Peltier; R Troughton, J Lainchbury; Berry: C Berry, K Hogg, J Norrie, Tsutsui: H Tsutsui, M Tsuchihashi, A Takeshita; UK Heart Study: K Stevenson, M Brett, J McMurray; CHARM: MA Pfeffer, PA MacCarthy, MT Kearney, J Nolan, AJ Lee, RJ Prescott, AM Shah, K Swedberg, CB Granger, P Held, JJV McMurray, EL Michelson, WP Brooksby, KAA Fox; Varela-Roman: A Varela-Roman, B Olofsson, J O¨ stergren, S Yusuf for the CHARM Investigators and JR Gonzalez-Juanatey, P Basante, R Trillo, J Garcia-Seara, Committees; Diamond and ECHOS: L Køber, C Torp-Pedersen; JL Martinez-Sande, F Gude.

International Journal of Obesity (2014) 1110 – 1114 & 2014 Macmillan Publishers Limited