Donate Help Contact The AHA Sign In Home
American Heart Association
Circulation
Search: search_blue_button Advanced Search
« Previous Article | Table of Contents | Next Article »
Circulation. 2007;116:627-636
Published online before print July 16, 2007, doi: 10.1161/CIRCULATIONAHA.106.679779
CLINICAL PERSPECTIVE
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Correction
Right arrow Correction (v116,pe136)
Right arrow All Versions of this Article:
116/6/627    most recent
CIRCULATIONAHA.106.679779v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Request Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Kenchaiah, S.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Kenchaiah, S.
Right arrowPubmed/NCBI databases
*Compound via MeSH
*Substance via MeSH
Medline Plus Health Information
*Heart Failure
Related Collections
Right arrow Clinical Studies
Right arrow Epidemiology
Right arrow Congestive
Right arrow Obesity
Right arrow Risk Factors

(Circulation. 2007;116:627-636.)
© 2007 American Heart Association, Inc.

Heart Failure

Body Mass Index and Prognosis in Patients With Chronic Heart Failure

Insights From the Candesartan in Heart failure: Assessment of Reduction in Mortality and morbidity (CHARM) Program

Satish Kenchaiah, MD, MPH; Stuart J. Pocock, PhD; Duolao Wang, PhD; Peter V. Finn, MD; Leonardo A.M. Zornoff, MD, PhD; Hicham Skali, MD, ScM; Marc A. Pfeffer, MD, PhD; Salim Yusuf, MD, DPhil; Karl Swedberg, MD, PhD; Eric L. Michelson, MD; Christopher B. Granger, MD; John J.V. McMurray, MD; Scott D. Solomon, MD, for the CHARM Investigators

From the Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Mass (S.K., P.V.F., L.A.M.Z., H.S., M.A.P., S.D.S.); Medical Statistics Unit, London School of Hygiene and Tropical Medicine, London, UK (S.J.P., D.W.); McMaster University and Hamilton Health Sciences, Hamilton, Ontario, Canada (S.Y.); Sahlgrenska Academy, Göteborg University, Göteborg, Sweden (K.S.); AstraZeneca LP, Wilmington, Del (E.L.M.); Duke University Medical Center, Durham, NC (C.B.G.); and University of Glasgow, Glasgow, UK (J.J.V.M.).

Correspondence to Satish Kenchaiah, MD, MPH, Brigham and Women’s Hospital, Cardiovascular Division, 15 Francis St, PBB-A-Ground, Boston, MA 02115. E-mail skenchaiah{at}rics.bwh.harvard.edu

Received December 12, 2006; accepted May 15, 2007.


*    Abstract
up arrowTop
 *Abstract
down arrowIntroduction
 down arrowMethods
 down arrowResults
 down arrowDiscussion
 down arrowReferences
 
Background— In individuals without known cardiovascular disease, elevated body mass index (BMI) (weight/height2) is associated with an increased risk of death. However, in patients with certain specific chronic diseases, including heart failure, low BMI has been associated with increased mortality.

Methods and Results— We examined the influence of BMI on prognosis using Cox proportional hazards models in 7599 patients (mean age, 65 years; 35% women) with symptomatic heart failure (New York Heart Association class II to IV) and a broad spectrum of left ventricular ejection fractions (mean, 39%) in the Candesartan in Heart failure: Assessment of Reduction in Mortality and morbidity (CHARM) program. During a median follow-up of 37.7 months, 1831 patients died. After adjustment for potential confounders, compared with patients with BMI between 30 and 34.9, patients in lower BMI categories had a graded increase in the risk of death. The hazard ratios (95% confidence intervals) were 1.22 (1.06 to 1.41), 1.46 (1.24 to 1.71), and 1.69 (1.43 to 2.01) among those with BMI of 25 to 29.9, 22.5 to 24.9, and <22.5, respectively. The increase in risk of death among patients with BMI ≥35 was not statistically significant (hazard ratio, 1.17; 95% confidence interval, 0.95 to 1.43). The association between BMI and mortality was not altered by age, smoking status, or left ventricular ejection fraction (P for interaction >0.20). However, lower BMI was associated with a greater risk of all-cause death in patients without edema but not in patients with edema (P for interaction <0.0001). Lower BMI was associated with a greater risk of cardiovascular death and noncardiovascular death. Baseline BMI did not influence the risk of hospitalization for worsening heart failure or due to all causes.

Conclusions— In patients with symptomatic heart failure and either reduced or preserved left ventricular systolic function, underweight or low BMI was associated with increased mortality, primarily in patients without evidence of fluid overload (edema).


Key Words: heart failure • morbidity • mortality • obesity • prognosis


*    Introduction
up arrowTop
 up arrowAbstract
 *Introduction
down arrowMethods
 down arrowResults
 down arrowDiscussion
 down arrowReferences
 
Elevated body mass index (BMI) is a major risk factor for the development of heart failure (HF).1–4 In individuals free of cardiovascular disease, a curvilinear association has been described between BMI and the risk of overall mortality, in which mortality was increased at the lowest and highest extremes and decreased in the middle.5,6 However, in patients with established HF, increased BMI has been noted to have an inverse,7–13 no,14 or nonsignificant15 association with the risk of mortality. Most of these studies were not conducted in a contemporary time period in patients receiving modern evidence-based treatments, and HF patients with a wide range of left ventricular ejection fractions were not evaluated. Thus, in patients with chronic HF, the prognostic significance of BMI on the risk of all-cause death, cause-specific death, and morbid outcomes remains unclear.

Editorial p 588

Clinical Perspective p 636

Accordingly, we examined the impact of BMI on prognosis in patients with symptomatic HF and either reduced or preserved left ventricular systolic function from the Candesartan in Heart failure: Assessment of Reduction in Mortality and morbidity (CHARM) program. We hypothesized that in patients with chronic HF, low BMI (and elevated BMI) would be associated with an increased risk of death and unfavorable cardiovascular outcomes.


*    Methods
up arrowTop
 up arrowAbstract
 up arrowIntroduction
 *Methods
down arrowResults
 down arrowDiscussion
 down arrowReferences
 
The design and results of the CHARM program have been published previously.16,17 Briefly, CHARM was a multinational, double-blind, placebo-controlled program of clinical trials conducted between March 1999 and March 2003 that evaluated the efficacy of candesartan in 7599 men and women aged ≥18 years who had symptomatic chronic HF (New York Heart Association class II to IV, regardless of left ventricular ejection fraction) and were either receiving or not receiving an angiotensin-converting enzyme inhibitor at baseline. Patients with serum creatinine ≥265 mmol/L; serum potassium ≥5.5 mmol/L; known bilateral renal artery stenosis; symptomatic hypotension; critical aortic or mitral stenosis; recent myocardial infarction, stroke, or open-heart surgery (within 4 weeks); use of an angiotensin-receptor blocker in the previous 2 weeks; any noncardiac disease judged likely to limit 2-year survival; and those unwilling to provide consent, as well as women of childbearing potential not using adequate contraception, were excluded. Planned duration of treatment and follow-up ranged from 24 to 48 months.

Covariates and Outcomes
All information on covariates including demographics, height and weight, cardiovascular risk factors, symptoms and signs of HF, and concomitant medications was ascertained at the time of enrollment. Presence or absence of pitting edema in the feet, ankle, leg, or sacrum was documented. BMI was calculated as weight in kilograms divided by the square of the height in meters. The individual outcomes considered in the present investigation were all-cause death (the primary outcome of the CHARM overall program), cardiovascular death, noncardiovascular death, hospitalization for worsening HF, and hospitalization for all causes. The composite outcomes evaluated were cardiovascular death or hospitalization for worsening HF (the primary composite outcome of each of the 3 individual CHARM trials), all-cause death or hospitalization for worsening HF, and all-cause death or hospitalization for all causes. The integrated end point assessed was days alive out of hospital during 1 and 2 years of follow-up. All outcomes were determined by an independent adjudication committee using prespecified definitions and blinded to the baseline BMI status. A death was considered cardiovascular unless a specific noncardiovascular cause was identified. Hospitalization for worsening HF was defined as an unexpected admission to hospital for treatment of HF or when HF became a major component of the patient’s hospital admission. A patient admitted for this reason had to show symptoms and signs of worsening HF and require treatment with intravenous diuretics. Evidence of worsening HF had to include at least 1 of the following items: increasing dyspnea on exertion, orthopnea, nocturnal dyspnea, pulmonary edema, increasing peripheral edema, increasing fatigue or decreasing exercise tolerance, renal hypoperfusion (ie, worsening renal function), raised jugular venous pressure, and radiological signs of HF.

Statistical Analyses
We evaluated BMI both as a continuous (for every 1-kg/m2 decrease) and as a categorical variable (<22.5, 22.5 to 24.9, 25.0 to 29.9, 30.0 to 34.9 [referent], and ≥35.0 kg/m2). The BMI categories were primarily based on cut points recommended by the World Health Organization18 and endorsed by the National Institutes of Health.19

We calculated mean±SD for continuous variables and proportions for categorical variables at baseline for each category of BMI. We constructed linear or logistic regression models for baseline variables with BMI as a continuous variable (per 1-kg/m2 change) and presented probability values as an estimate of their association. To evaluate the association between BMI and the risk of various outcomes defined as time to first event, we calculated unadjusted, age- and sex-adjusted, and multivariable-adjusted hazard ratios (HRs), 95% confidence intervals (CIs), and 2-sided probability values using Cox proportional hazards regression models. We performed linear regression analyses to assess the relation between BMI and the integrated end point of days alive out of hospital during 1 year and 2 years of follow-up. In multivariable models, we adjusted for all important predictors of mortality and morbidity identified in a previous investigation in the CHARM program.20 These variables, in the order of strength of association with all-cause death, were age (per 10 years over age 60 years), left ventricular ejection fraction (per 5% decrease below 45%), diabetes mellitus (none [referent], insulin treated, and oral therapy or diet only), male sex, New York Heart Association class (II [referent], III, and IV), current smoking, bundle-branch block, cardiomegaly, previous hospitalization for HF (none [referent], ≤6 months, >6 months), diastolic blood pressure (per 10-mm Hg decrease), duration of HF >2 years, previous myocardial infarction, edema, heart rate (per 10-bpm increase), pulmonary crackles, pulmonary edema, mitral regurgitation, atrial fibrillation, rest dyspnea, and study treatment (candesartan versus placebo). To assess the shape of the association between BMI and all-cause death, we introduced terms with common transformations of BMI inclusive of linear, quadratic, linear plus quadratic, logarithmic, squared root, exponential, and categorical (groups as specified above) in multivariable models.

In multivariable models evaluating BMI as a continuous variable (per 1-kg/m2 change), we examined for interaction of the effect of BMI on all-cause mortality and hospitalization for worsening HF by age (per 1-year change and as a dichotomous variable: <median and ≥median), smoking status (never/past smokers and current smokers), edema status (without edema and with edema), and left ventricular ejection fraction (per 5% decrease below 45% and as a dichotomous variable: ≤40% and >40%).

We performed all analyses using SAS software version 9.1.21 We considered a 2-sided probability value of <0.05 as statistically significant.

The authors had full access to and take full responsibility for the integrity of the data. All authors have read and agree to the manuscript as written.


*    Results
up arrowTop
 up arrowAbstract
 up arrowIntroduction
 up arrowMethods
 *Results
down arrowDiscussion
 down arrowReferences
 
Baseline Characteristics
The mean (±SD) and median BMIs in the CHARM cohort were 28.3 (±5.4) and 27.6, respectively, and ranged from 14.3 to 57.4 kg/m2. Approximately 40% of the patients with HF had BMI between 25.0 and 30.0 kg/m2, and {approx}11% were in the lowest (<22.5 kg/m2) and highest (≥35 kg/m2) BMI categories, respectively.

BMI was inversely related to age; patients in the heaviest category were on average 8.6 years younger than patients in the leanest category (Table 1Down). Women were more likely to be in the leanest or the heaviest BMI category. Increasing BMI was associated with a higher New York Heart Association functional class, heart rate, blood pressure, and left ventricular ejection fraction. Greater proportions of individuals in lower BMI categories were current cigarette smokers and had previous history of myocardial infarction and bundle-branch block. Although the duration of HF did not differ across categories of BMI, a greater proportion of patients with lower BMI were hospitalized for HF within 6 months before enrollment. As anticipated, hypertension and diabetes mellitus were noted more commonly in higher BMI categories. Whereas ischemic heart disease was the predominant cause of HF in lower BMI categories, hypertension was the primary factor attributable to HF in higher BMI categories. Rest dyspnea, orthopnea, paroxysmal nocturnal dyspnea, and edema were more likely to be noted in individuals with higher BMI, and S3 gallop, pulmonary crackles, pulmonary edema, and cardiomegaly were more prevalent in patients with a lower BMI. A similar proportion of individuals were on candesartan therapy in each category of BMI.


View this table:
[in this window]
[in a new window]

  		TABLE 1. Baseline Characteristics According to the Category of BMI in the CHARM Study*


View this table:
[in this window]
[in a new window]

  		TABLE 1. Continued

BMI and Risk of Death
During a median follow-up of 37.7 months, 1831 patients (24.1%) died. For BMI categories <35.0 kg/m2, crude cumulative incidence of all-cause death increased progressively with decreasing categories of BMI (Figure 1, log-rank P of test for equality <0.0001). In unadjusted analyses, every 1-kg/m2 decrease in BMI was associated with a 5.3% increase in the risk of all-cause death (Table 2). After adjustment for age and sex, the increase in the risk of all-cause death was 3.3%, which did not change materially after additional adjustment for all other important predictors of all-cause death. In fully adjusted models, compared with patients with BMI between 30 and 34.9 kg/m2, patients in lower BMI categories had a graded increase in the risk of all-cause death: 22.3% increase in patients with BMI between 25 and 29.9, 45.7% increase in patients with BMI between 22.5 and 24.9, and 69.4% increase among patients with BMI <22.5 kg/m2 (Table 2). The 26.4% increase in the risk of all-cause death among patients with BMI ≥35 in age- and sex-adjusted analyses was attenuated to 16.8% and did not reach statistical significance in fully adjusted analyses.


Figure 1185339
View larger version (14K):
[in this window]
[in a new window]

  		Figure 1. Cumulative incidence curves for all-cause death according to category of BMI at the baseline examination. Vertical bars indicate SEs of the incidence estimates at 3 years of follow-up. Data shown are truncated at 3.5 years.


View this table:
[in this window]
[in a new window]

  		TABLE 2. Results of Multivariable Cox Proportional Hazards Models Examining the Relation of BMI to the Risk of Various Outcomes

In multivariable analyses evaluating the shape of the association between BMI and all-cause death, linear plus quadratic BMI terms had the best goodness of fit ({chi}2 [2]=54.9, P<0.0001), suggestive of a nonlinear (U- or J-shaped) association between BMI and all-cause death. Logarithmic ({chi}2 [1]=41.8, P<0.0001) and categorical ({chi}2 [4]=48.5, P<0.0001) terms had similar goodness of fit, followed by square root ({chi}2 [1]=37.5, P<0.0001), exponential ({chi}2 [1]=30.6, P<0.0001), and quadratic BMI ({chi}2 [1]=24.7, P<0.0001).

Patients in lower BMI groups were at a greater risk of cardiovascular death as well as noncardiovascular death (Table 2). A trend was evident toward increasing noncardiovascular deaths in the highest BMI category.

BMI and Risk of Hospitalization for Worsening HF
No linear association existed between BMI and the risk of hospitalization for worsening HF (Table 2). In age- and sex-adjusted models, compared with the group with BMI between 30.0 and 34.9 kg/m2, an 18.3% (borderline statistical significance) and 26.6% increase existed in risk of hospitalization for worsening HF in the lowest and highest category, respectively (Table 2). This association was attenuated and no longer significant, however, in fully adjusted models.

No statistically significant association was present between BMI and the risk of composite of cardiovascular death or hospitalization for worsening HF (data not shown). The association of BMI with the risk of the composite of all-cause death or hospitalization for worsening HF was similar to that with all-cause death alone (Table 2).

BMI and Risk of Hospitalization for All Causes
During follow-up, 4797 (63.1%; 40.8 per 100 person-years of follow-up) were hospitalized for all causes. Baseline BMI did not influence the risk of hospitalization for all causes. In fully adjusted models, compared with patients with BMI of 30 to 34.9, the HRs (95% CIs) were 1.07 (0.96 to 1.19; P=0.20), 0.98 (0.89 to 1.08; P=0.73), 1.03 (0.89 to 1.05; P=0.39), and 1.09 (0.94 to 1.17; P=0.36) for patients with BMI <22.5, 22.5 to 24.9, 25 to 29.9, and ≥35, respectively. The results for composite of all-cause death or hospitalization for all causes were similar to those for hospitalization for all causes (data not shown).

BMI and Days Alive Out of Hospital
In fully adjusted models, every 1-kg/m2 decrease in BMI was associated with 0.6 (95% CI, 0.3 to 0.9; P<0.0001) and 1.9 (95% CI, 1.1 to 2.6; P<0.0001) fewer days alive out of hospital during 1 and 2 years of follow-up, respectively. In models evaluating BMI as a categorical variable, however, evidence existed of a possible inverted J-shaped association between BMI and days alive out of hospital characterized by a statistically significant stepwise decrease below and a decrease (albeit statistically nonsignificant) above BMI of 30 to 34.9 (Figure 2).


Figure 2185339
View larger version (12K):
[in this window]
[in a new window]

  		Figure 2. Results of fully adjusted linear regression analyses evaluating the relation between BMI and days alive out of hospital during 1 and 2 years of follow-up. BMI between 30 and 34.9 was the reference category. Vertical bars represent 95% CIs. *P<0.0001.

Effect Modification
The association between BMI and the risk of all-cause death and hospitalization for worsening HF did not depend on age, smoking status, or left ventricular ejection fraction (all P for interaction >0.20). Lower BMI was associated with higher risk of mortality in patients with impaired as well as preserved left ventricular ejection fraction (Table 3). However, lower BMI was associated with a greater risk of all-cause death in patients without edema but not in patients with edema (Table 3; P for interaction <0.0001). The HRs for each 1-kg/m2 decrease in BMI were 1.05 (95% CI, 1.03 to 1.06; P<0.0001) in patients without edema and 1.00 (95% CI, 0.99 to 1.02; P=0.71) in patients with edema. Similar results were noted for both cardiovascular and noncardiovascular death (data not shown). Edema status or left ventricular ejection fraction at baseline did not influence the association between BMI and the risk of hospitalization for worsening HF (Table 3; P for interaction >0.30).


View this table:
[in this window]
[in a new window]

  		TABLE 3. Results of Multivariable Cox Proportional Hazards Models Examining the Relation of BMI to the Risk of All-Cause Death and Hospitalization for Worsening HF According to Left Ventricular Ejection Fraction and Edema Status at Baseline Examination


*    Discussion
up arrowTop
 up arrowAbstract
 up arrowIntroduction
 up arrowMethods
 up arrowResults
 *Discussion
down arrowReferences
 
In CHARM patients, lowest mortality was noted in patients with BMI between 30 and 34.9, a progressive increase in mortality was evident below this range, and a plateau or increase was observed above this range (U- or J-shaped association). By the same token, highest number of days alive out of hospital during 1 or 2 years of follow-up was observed in patients with BMI between 30 and 34.9, with a stepwise decrease in days alive out of hospital below and a modest decrease above this range (inverted J-shaped association). Lower BMI was associated with a greater risk of death, cardiovascular death, and noncardiovascular death (including cancer deaths). The relation between BMI and the risk of all-cause death was not altered by age, smoking status, or left ventricular ejection fraction. The increased risk of death among patients with low BMI was evident primarily in the absence of edema, an indicator of fluid overload status.

Few studies have addressed the issue of shape of the association between BMI and all-cause death in chronic HF patients. In a report from the Digitalis Investigation Group (DIG) trial, unadjusted analyses using polynomial logistic regression revealed a nonlinear association between BMI and death.13 In the present investigation, age- and sex-adjusted as well as multivariable time-to-event analyses that accounted for major indicators of poor prognosis also suggest a nonlinear (U- or J-shaped) relation between BMI and mortality. Commensurate with this finding, an inverted J-shaped association was noted between BMI and days alive out of hospital, a type of quality of life-adjusted survival that accounted for multiple hospitalizations during the period of evaluation.

Edema increases BMI on the basis of fluid excess rather than solid tissue mass. Results of our investigation suggest that in patients with chronic HF, baseline BMI can be a useful indicator of mortality primarily in the absence of edema.

In the DIG trial13 as well as in our present investigation, in which relatively younger (mean age, 63 to 65 years) and stable HF patients were enrolled, left ventricular systolic dysfunction, as assessed by estimates of left ventricular ejection fraction, did not alter the effects of BMI on the risk of all-cause death. In the Danish Investigations of Arrhythmia and Mortality (DIAMOND) congestive heart failure study, in which older (mean age, 72 years) HF patients admitted for new-onset or worsening HF were enrolled, in patients with left ventricular systolic dysfunction, as assessed by wall motion index, higher BMI was associated with a greater risk of all-cause death, whereas in patients with normal left ventricular systolic function, lower BMI posed a greater risk of all-cause death.12 The differences in study population and mode of ascertainment of left ventricular systolic function may partially explain the disparity in interaction of left ventricular function and BMI and the risk of mortality.

In our analyses as well as in the study by DIG investigators,13 BMI did not influence the risk of hospitalization for HF in multivariable analyses. The lack of association with this sensitive clinical measure of HF severity, along with the similarity of effect of BMI on cardiovascular and noncardiovascular deaths, suggests that low BMI is a general marker (not a causal factor) of ill health.

A number of hypotheses have been put forth to explain the association between lower BMI and increased risk of mortality in HF patients.22–25 Lower BMI in patients with "prevalent" HF, as in the present and other previously published studies,7–9,11–14 may have been due to preceding involuntary weight loss or cardiac cachexia, a heightened metabolic or increased catabolic state26 associated with worse prognosis.8,27,28 By the same token, higher BMI, except when produced by edema, might indicate a greater metabolic reserve, increased tolerance to metabolic stress,29 and/or a less severe form of HF, and consequently may have a better prognosis.30 Elevated BMI may be associated with reduced cardiac sympathetic activity,31 attenuated neurohormonal response to stress,32 lower proinflammatory cytokine levels, and lesser catabolic-anabolic imbalance,33 all of which bode a better prognosis. Increased production of leptin34 and soluble receptors of tumor necrosis factor35 in adipose tissues may reduce the detrimental effects of tumor necrosis factor, a proinflammatory cytokine. Individuals with higher BMI, presumably due to lower natriuretic peptide levels,36,37 may manifest symptoms and signs of HF at a younger age with consequent longer survival after diagnosis (lead-time bias).

Elevated BMI may increase the risk of death and unfavorable cardiovascular outcomes by promoting risk factors for cardiovascular disease19,38 and by influencing abnormal left ventricular remodeling.39 Extreme BMI may continue to pose greater hemodynamic stress on the heart that could be deleterious. The improvement in functional class and pump function noted in smaller studies in which extremely obese HF patients have undergone marked weight reductions40,41 lends credence to this notion.

The strengths of our investigation include a large sample size, multicenter setting, inclusion of a broad spectrum of left ventricular ejection fractions in patients with symptomatic HF on evidence-based treatments in a contemporary time period, assessment of edema status, availability of information on most covariates of interest (including duration of HF) for multivariable analyses, nearly complete follow-up of patients during the 2- to 4-year study period, and objective ascertainment of all study end points by an independent committee blinded to BMI status at enrollment. Several limitations of these analyses should also be noted. We did not have data on body weights at the time of first diagnosis of HF to ascertain the influence of weight change subsequent to the time of first diagnosis on the risk of death or cardiovascular outcomes. Selection bias is likely in all prognostic studies conducted on patients with prevalent HF (in which BMI at the time of onset of HF is unavailable, and changes in body weight preceding their inclusion in various categories of BMI are uncertain).24 Except for edema status, we did not have data on body composition or percent body fat to evaluate the impact of each component (muscle, bone, and fat tissue) on the risk of clinical outcomes.42 Results of analyses stratified according to baseline edema status should be interpreted with caution given the small sample size of patients with edema in lower-BMI groups. We did not have other baseline data such as serum albumin levels for all participants, which may have allowed further elucidation of underweight status versus cardiac cachexia (or protein-calorie malnutrition) in patients with the lowest BMI values. Higher-BMI patients with HF were younger at the time of enrollment than lower-BMI patients, suggesting lead-time bias as a possible explanation for the association between higher BMI and better survival. However, the similar duration of HF in all BMI groups and absence of interaction between age and BMI and the risk of death in multivariable analyses do not support this explanation. Because a majority of patients studied were of European origin, the generalizability of our findings to other races and ethnic groups is another limitation.

We conclude that in patients with symptomatic and chronic HF, underweight status or low BMI is associated with a greater risk of all-cause death, and mild to moderate overweight status is associated with the lowest risk. The implication of moderate to extreme BMI on prognosis is uncertain. Lower BMI is an indicator of poor survival, primarily in the absence of fluid overload. Our findings warrant additional research, especially in community-based settings among patients with new-onset HF, to assess the impact of BMI, ascertained in close proximity to the first diagnosis of HF, on morbidity and mortality.


*    Acknowledgments
 
Source of Funding

The CHARM program was funded by AstraZeneca, which was responsible for data collection.

Disclosures

The data analysis for this article was performed independently by Drs Kenchaiah, Pocock, and Wang. The Executive Committee (Drs Pfeffer, Swedberg, Granger, McMurray, and Yusuf) supervised the management of the study and were primarily responsible for the interpretation of the data and review and approval of the manuscript. Dr Michelson is an employee of AstraZeneca. Drs Pocock, Pfeffer, Yusuf, Swedberg, Granger, McMurray, and Solomon have received research grants, honoraria for lectures, and/or consulting fees from AstraZeneca. The remaining authors report no conflicts.


*    References
up arrowTop
 up arrowAbstract
 up arrowIntroduction
 up arrowMethods
 up arrowResults
 up arrowDiscussion
 *References
 

  1. Chen YT, Vaccarino V, Williams CS, Butler J, Berkman LF, Krumholz HM. Risk factors for heart failure in the elderly: a prospective community-based study. Am J Med. 1999; 106: 605–612.[CrossRef][Medline] [Order article via Infotrieve]
  2. He J, Ogden LG, Bazzano LA, Vupputuri S, Loria C, Whelton PK. Risk factors for congestive heart failure in US men and women: NHANES I epidemiologic follow-up study. Arch Intern Med. 2001; 161: 996–1002.[Abstract/Free Full Text]
  3. Wilhelmsen L, Rosengren A, Eriksson H, Lappas G. Heart failure in the general population of men: morbidity, risk factors and prognosis. J Intern Med. 2001; 249: 253–261.[CrossRef][Medline] [Order article via Infotrieve]
  4. Kenchaiah S, Evans JC, Levy D, Wilson PW, Benjamin EJ, Larson MG, Kannel WB, Vasan RS. Obesity and the risk of heart failure. N Engl J Med. 2002; 347: 305–313.[Abstract/Free Full Text]
  5. Manson JE, Willett WC, Stampfer MJ, Colditz GA, Hunter DJ, Hankinson SE, Hennekens CH, Speizer FE. Body weight and mortality among women. N Engl J Med. 1995; 333: 677–685.[Abstract/Free Full Text]
  6. Calle EE, Thun MJ, Petrelli JM, Rodriguez C, Heath CW Jr. Body-mass index and mortality in a prospective cohort of U.S. adults. N Engl J Med. 1999; 341: 1097–1105.[Abstract/Free Full Text]
  7. Lissner L, Odell PM, D’Agostino RB, Stokes J III, Kreger BE, Belanger AJ, Brownell KD. Variability of body weight and health outcomes in the Framingham population. N Engl J Med. 1991; 324: 1839–1844.[Abstract]
  8. Anker SD, Ponikowski P, Varney S, Chua TP, Clark AL, Webb-Peploe KM, Harrington D, Kox WJ, Poole-Wilson PA, Coats AJ. Wasting as independent risk factor for mortality in chronic heart failure. Lancet. 1997; 349: 1050–1053.[CrossRef][Medline] [Order article via Infotrieve]
  9. Mosterd A, Cost B, Hoes AW, de Bruijne MC, Deckers JW, Hofman A, Grobbee DE. The prognosis of heart failure in the general population: the Rotterdam Study. Eur Heart J. 2001; 22: 1318–1327.[Abstract/Free Full Text]
  10. Lissin LW, Gauri AJ, Froelicher VF, Ghayoumi A, Myers J, Giacommini J. The prognostic value of body mass index and standard exercise testing in male veterans with congestive heart failure. J Card Fail. 2002; 8: 206–215.[CrossRef][Medline] [Order article via Infotrieve]
  11. Davos CH, Doehner W, Rauchhaus M, Cicoira M, Francis DP, Coats AJ, Clark AL, Anker SD. Body mass and survival in patients with chronic heart failure without cachexia: the importance of obesity. J Card Fail. 2003; 9: 29–35.[CrossRef][Medline] [Order article via Infotrieve]
  12. Gustafsson F, Kragelund CB, Torp-Pedersen C, Seibaek M, Burchardt H, Akkan D, Thune JJ, Kober L. Effect of obesity and being overweight on long-term mortality in congestive heart failure: influence of left ventricular systolic function. Eur Heart J. 2005; 26: 58–64.[Abstract/Free Full Text]
  13. Curtis JP, Selter JG, Wang Y, Rathore SS, Jovin IS, Jadbabaie F, Kosiborod M, Portnay EL, Sokol SI, Bader F, Krumholz HM. The obesity paradox: body mass index and outcomes in patients with heart failure. Arch Intern Med. 2005; 165: 55–61.[Abstract/Free Full Text]
  14. Alla F, Briancon S, Juilliere Y, Mertes PM, Villemot JP, Zannad F. Differential clinical prognostic classifications in dilated and ischemic advanced heart failure: the EPICAL study. Am Heart J. 2000; 139: 895–904.[Medline] [Order article via Infotrieve]
  15. Ho KK, Anderson KM, Kannel WB, Grossman W, Levy D. Survival after the onset of congestive heart failure in Framingham Heart Study subjects. Circulation. 1993; 88: 107–115.[Abstract/Free Full Text]
  16. Swedberg K, Pfeffer M, Granger C, Held P, McMurray J, Ohlin G, Olofsson B, Ostergren J, Yusuf S; CHARM-Programme Investigators. Candesartan in Heart failure: Assessment of Reduction in Mortality and morbidity (CHARM): rationale and design. J Card Fail. 1999; 5: 276–282.[CrossRef][Medline] [Order article via Infotrieve]
  17. Pfeffer MA, Swedberg K, Granger CB, Held P, McMurray JJ, Michelson EL, Olofsson B, Ostergren J, Yusuf S, Pocock S. Effects of candesartan on mortality and morbidity in patients with chronic heart failure: the CHARM-Overall programme. Lancet. 2003; 362: 759–766.[CrossRef][Medline] [Order article via Infotrieve]
  18. Obesity: Preventing and Managing the Global Epidemic: Report of a WHO Consultation on Obesity, Geneva, June 3–5, 1997. Geneva, Switzerland: World Health Organization; 1998.
  19. Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults. Bethesda, Md: National Institutes of Health; 1998. Publication NIH 98-4083.
  20. Pocock SJ, Wang D, Pfeffer MA, Yusuf S, McMurray JJ, Swedberg KB, Ostergren J, Michelson EL, Pieper KS, Granger CB. Predictors of mortality and morbidity in patients with chronic heart failure. Eur Heart J. 2006; 27: 65–75.[Abstract/Free Full Text]
  21. SAS Institute Inc. SAS/STAT User’s Guide, Version 9.1. Cary, NC: SAS Institute Inc; 2004.
  22. Lavie CJ, Milani R, Mehra MR, Ventura HO, Messerli FH. Obesity, weight reduction and survival in heart failure. J Am Coll Cardiol. 2002; 39: 1563–1564.[Free Full Text]
  23. 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: 1439–1444.[Abstract/Free Full Text]
  24. Kenchaiah S, Gaziano JM, Vasan RS. Impact of obesity on the risk of heart failure and survival after the onset of heart failure. Med Clin North Am. 2004; 88: 1273–1294.[CrossRef][Medline] [Order article via Infotrieve]
  25. Lavie CJ, Mehra MR, Milani RV. Obesity and heart failure prognosis: paradox or reverse epidemiology? Eur Heart J. 2005; 26: 5–7.[Free Full Text]
  26. Berry C, Clark AL. Catabolism in chronic heart failure. Eur Heart J. 2000; 21: 521–532.[Free Full Text]
  27. Anker SD, Rauchhaus M. Insights into the pathogenesis of chronic heart failure: immune activation and cachexia. Curr Opin Cardiol. 1999; 14: 211–216.[CrossRef][Medline] [Order article via Infotrieve]
  28. Anker SD, Negassa A, Coats AJ, Afzal R, Poole-Wilson PA, Cohn JN, Yusuf S. Prognostic importance of weight loss in chronic heart failure and the effect of treatment with angiotensin-converting-enzyme inhibitors: an observational study. Lancet. 2003; 361: 1077–1083.[CrossRef][Medline] [Order article via Infotrieve]
  29. Coats A, Anker SD, Roecker EB, Schultz MK, Staiger C, Amann-Zalan I, Shusterman N, Packer M. Prevention and reversal of cardiac cachexia in patients with severe heart failure by carvedilol: results of the COPERNICUS study. Circulation. 2001; 104 II-437.
  30. Horwich TB, Fonarow GC, Hamilton MA, MacLellan WR, Woo MA, Tillisch JH. The relationship between obesity and mortality in patients with heart failure. J Am Coll Cardiol. 2001; 38: 789–795.[Abstract/Free Full Text]
  31. Vaz M, Jennings G, Turner A, Cox H, Lambert G, Esler M. Regional sympathetic nervous activity and oxygen consumption in obese normotensive human subjects. Circulation. 1997; 96: 3423–3429.[Abstract/Free Full Text]
  32. Weber MA, Neutel JM, Smith DH. Contrasting clinical properties and exercise responses in obese and lean hypertensive patients. J Am Coll Cardiol. 2001; 37: 169–174.[Abstract/Free Full Text]
  33. Anker SD, Clark AL, Kemp M, Salsbury C, Teixeira MM, Hellewell PG, Coats AJ. Tumor necrosis factor and steroid metabolism in chronic heart failure: possible relation to muscle wasting. J Am Coll Cardiol. 1997; 30: 997–1001.[Abstract]
  34. Takahashi N, Waelput W, Guisez Y. Leptin is an endogenous protective protein against the toxicity exerted by tumor necrosis factor. J Exp Med. 1999; 189: 207–212.[Abstract/Free Full Text]
  35. Mohamed-Ali V, Goodrick S, Bulmer K, Holly JM, Yudkin JS, Coppack SW. Production of soluble tumor necrosis factor receptors by human subcutaneous adipose tissue in vivo. Am J Physiol. 1999; 277: E971–E975.[Medline] [Order article via Infotrieve]
  36. Mehra MR, Uber PA, Park MH, Scott RL, Ventura HO, Harris BC, Frohlich ED. Obesity and suppressed B-type natriuretic peptide levels in heart failure. J Am Coll Cardiol. 2004; 43: 1590–1595.[Abstract/Free Full Text]
  37. Wang TJ, Larson MG, Levy D, Benjamin EJ, Leip EP, Wilson PW, Vasan RS. Impact of obesity on plasma natriuretic peptide levels. Circulation. 2004; 109: 594–600.[Abstract/Free Full Text]
  38. Eckel RH, Krauss RM; AHA Nutrition Committee. American Heart Association call to action: obesity as a major risk factor for coronary heart disease. Circulation. 1998; 97: 2099–2100.[Free Full Text]
  39. Lauer MS, Anderson KM, Kannel WB, Levy D. The impact of obesity on left ventricular mass and geometry: the Framingham Heart Study. JAMA. 1991; 266: 231–236.[Abstract]
  40. Alpert MA, Lambert CR, Terry BE, Cohen MV, Mulekar M, Massey CV, Hashimi MW, Panayiotou H, Mukerji V. Effect of weight loss on left ventricular diastolic filling in morbid obesity. Am J Cardiol. 1995; 76: 1198–1201.[CrossRef][Medline] [Order article via Infotrieve]
  41. Alpert MA, Terry BE, Mulekar M, Cohen MV, Massey CV, Fan TM, Panayiotou H, Mukerji V. Cardiac morphology and left ventricular function in normotensive morbidly obese patients with and without congestive heart failure, and effect of weight loss. Am J Cardiol. 1997; 80: 736–740.[CrossRef][Medline] [Order article via Infotrieve]
  42. Lavie CJ, Osman AF, Milani RV, Mehra MR. Body composition and prognosis in chronic systolic heart failure: the obesity paradox. Am J Cardiol. 2003; 91: 891–894.[CrossRef][Medline] [Order article via Infotrieve]
 

CLINICAL PERSPECTIVE

In 7599 symptomatic heart failure (New York Heart Association class II to IV) patients (mean age, 65 years; 35% women) with a broad spectrum of left ventricular ejection fractions (mean, 39%) in the Candesartan in Heart failure: Assessment of Reduction in Mortality and morbidity (CHARM) clinical trials, we examined the influence of body mass index (BMI) (defined as weight in kilograms divided by the square of height in meters) on prognosis. During a median follow-up of 38 months, 1831 patients died. Lowest mortality was noted in patients with BMI between 30 and <35, and progressive increase in mortality was evident below this range (22%, 46%, and 69% increase in patients with BMI 25 to <30, 22.5 to <25, and <22.5, respectively), and a plateau or increase was observed above this range (17% increase, albeit statistically nonsignificant, among patients with BMI ≥35). Similarly, highest number of days alive out of hospital was observed in patients with BMI between 30 and 34.9 (39, 29, 19, and 12 fewer days alive out of hospital during 2 years of follow-up in patients with BMI <22.5, 22.5 to <25, 25 to <30, and ≥35, respectively). The association between BMI and mortality was similar in patients with impaired as well as preserved left ventricular ejection fraction. However, lower BMI was associated with a greater risk of death primarily in patients without edema, an indicator of fluid overload status. Lower BMI (likely a consequence of involuntary weight loss or cachexia) was linked with a greater risk of cardiovascular death and noncardiovascular death (including cancer deaths), suggesting that among patients with heart failure, low BMI is a general marker of ill health.




This article has been cited by other articles:


Home page
 HypertensionHome page
R. Harmancey, C. R. Wilson, and H. Taegtmeyer
Adaptation and Maladaptation of the Heart in Obesity
Hypertension, August 1, 2008; 52(2): 181 - 187.
[Full Text] [PDF]

Home page
 J. Am. Soc. Nephrol.Home page
T. A. Ikizler, P. Stenvinkel, and B. Lindholm
Resolved: Being Fat Is Good for Dialysis Patients: The Godzilla Effect: Pro
J. Am. Soc. Nephrol., June 1, 2008; 19(6): 1059 - 1064.
[Abstract] [Full Text] [PDF]

Home page
 Eur Heart JHome page
J. Abdulla, L. Kober, S. Z. Abildstrom, E. Christensen, W. P. T. James, and C. Torp-Pedersen
Impact of obesity as a mortality predictor in high-risk patients with myocardial infarction or chronic heart failure: a pooled analysis of five registries
Eur. Heart J., March 1, 2008; 29(5): 594 - 601.
[Abstract] [Full Text] [PDF]

Home page
 DOC NewsHome page
Heart Failure Mortality Rises With Low BMI
DOC News, October 1, 2007; 4(10): 15 - 15.
[Full Text]

Home page
 CirculationHome page
S. von Haehling, T. B. Horwich, G. C. Fonarow, and S. D. Anker
Tipping the Scale: Heart Failure, Body Mass Index, and Prognosis
Circulation, August 7, 2007; 116(6): 588 - 590.
[Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Correction
Right arrow Correction (v116,pe136)
Right arrow All Versions of this Article:
116/6/627    most recent
CIRCULATIONAHA.106.679779v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Request Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Kenchaiah, S.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Kenchaiah, S.
Right arrowPubmed/NCBI databases
*Compound via MeSH
*Substance via MeSH
Medline Plus Health Information
*Heart Failure
Related Collections
Right arrow Clinical Studies
Right arrow Epidemiology
Right arrow Congestive
Right arrow Obesity
Right arrow Risk Factors

Circulation Home | Subscriptions | Archives | Feedback | Authors | Help | AHA Journals Home | Search
Copyright © 2007 American Heart Association, Inc. All rights reserved. Unauthorized use prohibited.