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Original Article
Cardiorespiratory Fitness, Body Mass Index, and Heart
Failure Mortality in Men
Cooper Center Longitudinal Study
Stephen W. Farrell, PhD; Carrie E. Finley, MS; Nina B. Radford, MD; William L. Haskell, PhD
Background—We evaluated the individual and joint associations among cardiorespiratory fitness (CRF), body mass index,
and heart failure (HF) mortality, as well as the additive effect of an increasing number of cardiovascular risk factors on
HF mortality in fit versus unfit men.
Methods and Results—A total of 44 674 men without a history of cardiovascular disease underwent a baseline examination
between 1971 and 2010. Measures included body mass index and CRF quantified as duration of maximal treadmill
exercise testing. Participants were divided into age-specific low, moderate, and high CRF categories. Hazard ratios were
computed with Cox regression analysis. During a mean follow-up of 19.8±10.4 years, 153 HF deaths occurred. Adjusted
hazard ratios across high, moderate, and low CRF categories were 1.0, 1.63, and 3.97, respectively, whereas those of
normal, overweight, and obese body mass index categories were 1.0, 1.56, and 3.71, respectively (P for trend <0.0001
for each). When grouped into categories of fit and unfit (upper 80% and lower 20% of CRF distribution, respectively),
hazard ratios were significantly lower in fit compared with unfit men in normal and overweight body mass index strata
(P<0.002) but not in obese men. Within men matched for the same number of HF risk factors, fit men had significantly
lower HF mortality than unfit men (P≤0.02).
Conclusions—Higher baseline CRF is associated with lower HF mortality risk in men, regardless of the number of HF risk
factors present. Men should be counseled on physical activity with the goal of achieving at least a moderate level of CRF,
thereby presumably decreasing their risk of HF mortality. (Circ Heart Fail. 2013;6:898-905.)
Key Words: body mass index
■
heart failure
H
eart failure (HF) is a common cause of mortality in older
US adults, accounting for 292 214 deaths where HF is
listed as a primary or secondary cause and for 58 933 deaths
where it is listed as the underlying cause of death.1 For individuals aged ≥65 years, HF is the most frequent cause of hospitalization, and it is estimated that 6 million Americans are
living with HF. In addition to its physical and psychological
toll, HF also places a significant economic burden on the society. The estimated direct and indirect cost of HF in the United
States is $37.2 billion in 2009.1
■
physical fitness
our knowledge, there are no reported data relating an objective
measure of CRF with HF mortality. Although there has been
an important recent report on the joint exposures of multiple
adiposity measures, physical activity, and incidence of HF,14
there are no reported data on the joint exposures of CRF and
body mass index (BMI) with subsequent HF mortality. Because
overweight and obesity, as well as physical inactivity, are highly
prevalent in the US population,17,18 we think it is important to
examine these issues. Thus, the primary purpose of our investigation is to examine the individual and joint associations among
CRF, BMI, and HF mortality in a large cohort of men in the
Cooper Center Longitudinal Study (CCLS). A secondary purpose is to examine the additive effect of an increasing number
of risk factors on HF mortality in fit versus unfit men.
Clinical Perspective on p 905
Well-established risk factors for HF include age, hypertension, tobacco use, diabetes mellitus, obesity, high alcohol intake,
previous myocardial infarction, sleep apnea,2 and valve disease.3–6 Although many studies have examined the association
between physical activity and cardiovascular disease (CVD)
mortality,7–12 much less is known about the association between
physical activity and HF mortality. Studies that have examined this association relied exclusively on self-reported physical activity patterns,13–15 which are only moderately correlated
with objective measures of cardiorespiratory fitness (CRF).16 To
Methods
Study Participants and Measurements
The CCLS is an updated continuation of the Aerobics Center
Longitudinal Study (ACLS)19 and includes additional clinical variables, an expanded biobank, and mortality data collected through
2010. Participants in the present study included 44 674 men without
a personal history of CVD who completed a baseline comprehensive medical examination at the Cooper Clinic in Dallas, TX, during
Received July 30, 2012; accepted July 10, 2013.
From the Education Department (S.W.F.), and Research Department (C.E.F.), The Cooper Institute, Dallas, TX; Cardiovascular Medicine Department,
The Cooper Clinic, Dallas, TX (N.B.R.); and Department of Medicine, Stanford University, Palo Alto, CA (W.L.H.).
Correspondence to Stephen W. Farrell, PhD, The Cooper Institute, 12330 Preston Rd, Dallas, TX 75230. E-mail [email protected]
© 2013 American Heart Association, Inc.
Circ Heart Fail is available at http://circheartfailure.ahajournals.org
898
DOI: 10.1161/CIRCHEARTFAILURE.112.000088
Farrell et al Fitness, BMI, Heart Failure Mortality 899
1971–2010. All participants were US residents, and the majority
(≈90%) were white and from middle-to-upper socioeconomic strata.
After receiving written informed consent from each participant, a
clinical evaluation was performed and included an examination by a
physician, fasting blood chemistry assessment, personal and family
health history, anthropometry, resting blood pressure and ECG, and a
maximal graded treadmill exercise test. A standard physician’s scale
and stadiometer were used to measure weight and height. BMI was
calculated as weight in kilograms divided by height in meters squared.
We categorized men as normal weight (BMI, 18.5–24.9 kg/m2),
overweight (BMI, 25.0–29.9 kg/m2), or obese (BMI ≥30 kg/m2).
CRF was quantified as the duration of a maximal treadmill exercise test using a modified Balke protocol20 as described elsewhere.
Exercise duration from this protocol correlated highly (r=0.92) with
directly measured maximal oxygen uptake in men.21 All participants
were encouraged to provide a maximal effort, and those that did not
achieve ≥85% of age-predicted maximal heart rate (n=1697) were
excluded from the analyses. We felt it was important to exclude these
men to avoid CRF misclassification and because some men in this
group may have had subclinical disease, which may have prevented
them from achieving a maximal test. To standardize exercise test
performance, we computed maximal metabolic equivalent (MET; 1
MET=3.5 mL O2 uptake/kg body weight per minute) levels of CRF
based on the final treadmill speed and grade.22
Trained Cooper Clinic technicians analyzed blood chemistry using automated techniques following standardized procedures. This
laboratory participates in and meets quality control standards of the
Centers for Disease Control and Prevention Lipid Standardization
Program. The CCLS undergoes annual review and approval by the
Institutional Review Board of The Cooper Institute.
Men with previously diagnosed HF, myocardial infarction, stroke,
or cancer (n=5945), as well as men with a BMI <18.5 kg/m2 (n=82)
and men with <1 year (n=670) of follow-up, were excluded from
analyses. Following these exclusions, the resultant sample size of the
cohort was 44 674.
Mortality Surveillance
The National Death Index was used to ascertain vital status. The
National Death Index has a sensitivity of 96% and a specificity of
100% for determining deaths in the general population.23 Once we
identified possible decedents, Departments of Vital Statistics in the
appropriate states were contacted, and official copies of death certificates were requested. We compared information on the death
certificates with clinical records to confirm that the death certificate
matched the individual. A nosologist coded the underlying and contributing causes of death according to the International Classification
of Diseases, Ninth and Tenth Editions, Revised.
Statistical Analyses
We followed study participants for mortality from the date of
their baseline examination to the date of death for decedents or to
December 31, 2010, for survivors. We computed man-years of exposure as the sum of follow-up time among decedents and survivors.
There were 153 HF deaths identified during an average of 19.8±10.4
years of follow-up and 883 870 man-years of exposure. Cox proportional hazards regression analysis was used to estimate hazard ratios
(HRs) and 95% confidence intervals of HF mortality according to exposure categories. HRs were used instead of odds ratios because HRs
are used in cohort studies to express the relative effect of a variable
on the risk of an event over time. In our primary analysis, BMI was
grouped as described previously. CRF was grouped as low fit (lowest
20%), moderate fit (next 40%), and high fit (highest 40%) according to age-standardized normative data based on maximal treadmill
exercise test duration as described elsewhere.19 Multivariate analyses
included age (years), examination year, smoking status (never, past,
current), resting systolic blood pressure, BMI (where applicable),
presence of diabetes mellitus, and family history of CVD. These 7
factors will henceforth be referred to as covariables. Tests of linear
trends in mortality rates and risk estimates across exposure categories
were computed using ordinal scoring. We also examined the joint exposures of BMI and CRF with HF mortality. In these analyses, BMI
exposure groups were based on those previously described. CRF was
grouped as fit and unfit based on the upper 80% and the lower 20%
of the age-standardized CRF distribution, as previously reported in
the CCLS.24 Next, comparisons of HF mortality between fit and unfit
men were performed within groups of men, with 0, 1, or ≥2 risk factors. Finally, we examined the HRs for each of the individual HF risk
factors, with the low-risk group (normal resting blood pressure and
no personal history of hypertension, current nonsmoker, no personal
history of diabetes mellitus, BMI <30 kg/m2, fit, and no family history
of CVD) as the referent and using dichotomies for all comparisons.
We assessed interaction among exposure groups using likelihood ratio tests of nested models. All P values are 2-sided, and P<0.05 was
considered statistically significant.
Results
Of the 1486 total CVD deaths in the cohort, 153 (10.2%)
were from HF. Baseline characteristics of the overall cohort
according to vital status are presented in Table 1. On average,
decedents were significantly older (49.8 versus 43.4 years),
had higher BMI (27.8 versus 26.7 kg/m2), lower CRF (9.6 versus 11.7 METs), higher resting systolic (131.0 versus 121.6
mm Hg) and diastolic (86.5 versus 81.5 mm Hg) blood pressure, and higher total cholesterol (223.2 versus 206.9 mg/dL),
triglyceride (179.5 versus 137.5 mg/dL), and blood glucose
(111.1 versus 99.8 mg/dL) values than survivors. In addition,
decedents had a higher prevalence of smoking than survivors
(24.8% versus 17.4%), as well as a higher prevalence of diabetes mellitus (6.5% versus 1.8%) and hypertension (32.0%
versus 14.4%; P<0.01 for all comparisons).
Baseline characteristics of the cohort across CRF categories
are presented in Table 2. Other than alcohol intake and family
history of CVD, which were similar across categories of CRF,
each of the baseline characteristics was significantly associated with categories of CRF. More specifically, higher levels
of CRF were strongly associated with more favorable risk status (P for trend <0.0001 for each characteristic).
Adjusted HRs for HF mortality according to exposures
group are presented in Table 3. There was a significant inverse
trend in HF mortality across CRF categories (HRs=1.0, 1.63,
and 3.97 for high-, moderate-, and low-fit men, respectively;
P for trend <0.0001). The trend was only slightly attenuated
(P<0.0001) after adjustment for BMI (results not shown). As
also shown in Table 3, there was a significant positive trend in
HF mortality across incremental BMI categories (HRs=1.0,
1.56, and 3.71 for normal weight, overweight, and obese men,
respectively; P for trend <0.0001). The trend was only slightly
attenuated (P<0.003) after adjustment for CRF (results not
shown).
To place our findings into a more clinically relevant perspective, we jointly regressed HF mortality rates on BMI and
CRF exposures grouped according to standardized definitions
(Figure 1). HRs across incremental BMI categories of normal weight, overweight, and obese men were higher in unfit
(3.96, 3.64, and 6.11, respectively) than fit (1.0, 1.72, and
4.47, respectively) men. However, these differences reached
statistical significance in the normal weight and overweight
BMI categories only (P<0.002).
We next examined HF mortality in fit versus unfit men
within groups having none (referent) or any 1 or ≥2 risk
900 Circ Heart Fail September 2013
Table 1. Baseline Characteristics of 44 674 Men in the Cooper Center Longitudinal Study During 1971–2010
All (N=44 674)
Survivors (n=44 521)
HF Decedents (n=153)
Age, y
43.4±9.2
43.4±9.2
49.8±9.0
BMI, kg/m2
26.7±3.9
26.7±3.9
27.8±4.0
Cardiorespiratory fitness level, METs
11.6±2.4
11.7±2.4
9.6±2.0
Resting heart rate
61.2±10.7
61.2±10.7
64.0±12.0
Systolic blood pressure, mm Hg
121.6±13.0
121.6±13.0
131.0±18.2
Diastolic blood pressure, mm Hg
81.5±9.6
81.5±9.5
86.5±11.9
206.9±40.0
206.9±40.0
223.2±39.4
Cholesterol, mg/dL
HDL, mg/dL
46.2±12.0 (n missing=9137)
46.2±12.0 (n missing=9060)
41.7±11.3 (n missing=77)
LDL, mg/dL
132.4±35.3 (n missing=9978)
132.3±35.3 (n missing=9895)
147.5±35.5 (n missing=84)
137.6±113.1
137.5±112.8
99.8±16.9
99.8±16.8
111.1±33.8
8.4±10.6 (n missing=3976)
8.4±10.6 (n missing=3961)
7.8±9.2 (n missing=15)
Nonsmoker
25 495 (57.1)
25 436 (57.1)
59 (38.6)
Former smoker
11 380 (25.5)
11 324 (25.4)
56 (36.6)
Current smoker
7799 (17.5)
7761 (17.4)
38 (24.8)
Triglycerides, mg/dL
Glucose, mg/dL
Alcohol, drinks/wk
179.5±173.7
Smoking, n (%)
Personal history of diabetes mellitus, %
Personal history of hypertension, %
Family history of CVD, %
Follow-up, y
802 (1.8)
792 (1.8)
10 (6.5)
6457 (14.5)
6408 (14.4)
49 (32.0)
19 792 (44.3)
19 719 (44.3)
73 (47.7)
19.8±10.4
19.8±10.3
23.0±9.0
Unless otherwise specified, data are means±SD. BMI indicates body mass index; CVD, cardiovascular disease; HDL, high-density lipoprotein; HF, heart failure; LDL,
low-density lipoprotein; METs, 1 metabolic equivalent=3.5 mL O2 uptake/kg body weight per minute.
factors (Figure 2). Within each of these 3 groups, fit men had
significantly lower HF mortality than unfit men (P<0.02).
In Figure 3, we show the age-adjusted and examination
­year–adjusted HRs for HF mortality using each individual
HF risk factor. HRs for obese (3.29, 2.3–4.7) and unfit (3.37,
2.4–4.7) men were similar and were the highest of all risk factors examined.
Discussion
To our knowledge, this is the first study using objective measures of both CRF and BMI examining the individual and
joint associations among CRF, BMI, and HF mortality in
men, as well as examining HF mortality in fit versus unfit men
with a varying number of risk factors. CRF was strongly and
inversely associated with HF mortality. Compared with men
with high CRF, moderate-fit and low-fit men were 1.63 and
3.97× more likely to die from HF, respectively, after adjusting for potential confounding variables during an average
follow-up of 19.8 years. BMI was also independently and significantly associated with HF mortality. Importantly, mortality
rates were lower in fit than unfit men within each BMI strata,
particularly within the normal weight and overweight groups.
These findings suggest that among men with no personal history of CVD at baseline, measurement of both CRF and BMI
may be preferable to measurement of BMI only for assessing
risk of future HF mortality.
As mentioned, a moderate-to-high level of CRF did not
provide as much protection from HF mortality in obese
men compared with normal weight and overweight men. On
exploring this finding further, we determined that the average
MET level for fit–obese men (11.0±1.2) was lower than that
in fi
­t–overweight (12.0±1.7) and fit–normal weight men
(13.2±2.2; P for trend <0.0001). Thus, in the obese group, the
level of CRF in moderate- to high-fit men may not be sufficiently greater than that in unfit men to provide cardioprotective benefit in HF mortality.
An additional novel finding was the marked difference in
HF mortality between fit and unfit men with the same number
of HF risk factors. HRs for fit men with 0, any 1, or ≥2 risk
factors were substantially lower than those in unfit men with
the same number of risk factors. For example, among men
with ≥2 risk factors, HRs for fit versus unfit were 3.01 and
7.27, respectively (P=0.0002). Thus, a moderate-to-high level
of CRF seems to offer substantial protection against HF mortality, irrespective of the number of traditional HF risk factors
present. Our findings are consistent with other CCLS articles
that have shown that relative to low-fit individuals, attaining
a moderate-to-high level of CRF attenuates mortality risk in
obese individuals,25 hypertensives,26 type 2 diabetes mellitus
individuals,27 and smokers.28
We were also able to compare the relative strength of each
risk factor on HF mortality. Low CRF (unfit) and obesity
emerged as the 2 strongest risk factors, with HRs of 3.37 and
3.29, respectively (P<0.0001 for each). As previously mentioned, there are few studies in the literature that have examined the relationships among physical activity, adiposity, and
HF incidence. In a recent study of 28 842 Finnish men with a
mean follow-up of 18.4 years, Hu et al14 reported an inverse
association between physical activity and the incidence of
HF, as well as a direct association between various adiposity
measures and incidence of HF. Joint associations revealed a
Farrell et al Fitness, BMI, Heart Failure Mortality 901
Table 2. Baseline Characteristics of 44 674 Men Across Different Categories of Cardiorespiratory Fitness in the Cooper Center
Longitudinal Study During 1971–2010
Low Fitness (n=9120)
Moderate Fitness (n=17 775)
High Fitness (n=17 779)
P for Trend
Age, y
44.0±9.2
43.6±9.2
42. 9±9.1
<0.0001
BMI, kg/m2
29.7±5.1
26.9±3.2
25.0±2.6
<0.0001
Cardiorespiratory fitness level, METs
8.7±1.1
10.9±0.9
13.8±1.8
<0.0001
Resting heart rate
67.7±10.6
62.6±9.6
56.4±9.5
<0.0001
Systolic blood pressure, mm Hg
124.7±13.8
121.5±12.8
120.1±12.6
<0.0001
Diastolic blood pressure, mm Hg
84.2±9.9
81.9±9.5
79.7±9.0
<0.0001
215.9±42.1
210.0±40.1
199.1±37.3
<0.0001
HDL, mg/dL
Cholesterol, mg/dL
41.1±10.5 (n missing=2486)
44.5±11.0 (n missing=2879)
49.9±12.3 (n missing=1956)
<0.0001
LDL, mg/dL
136.9±37.5 (n missing=2790)
135.6±35.5 (n missing=3199)
127.6±33.6 (n missing=2057)
<0.0001
Triglycerides, mg/dL
184.7±157.2
144.9±109.4
105.5±71.6
<0.0001
Glucose, mg/dL
104.6±24.6
99.8±16.4
97.3±11.0
<0.0001
8.3±11.0
8.4±10.7
8.3±10.4
0.50
Nonsmoker
4215 (46.2)
9971 (56.1)
11 309 (63.6)
<0.0001
Former smoker
2272 (24.9)
4449 (25.0)
4659 (22.2)
Current smoker
2633 (28.9)
3355 (18.9)
1811 (10.2)
371 (4.1)
300 (1.7)
131 (0.7)
<0.0001
Personal history of hypertension, %
2133 (23.4)
2623 (14.8)
1701 (9.6)
<0.0001
Family history of CVD, %
3918 (43.0)
7882 (44.3)
7992 (45.0)
0.03
Follow-up, y
21.2±11.1
19.9±10.6
19.0±9.6
<0.0001
Alcohol, drinks/wk
Smoking, n (%)
Personal history of diabetes mellitus, %
Unless otherwise specified, data are means±SD. BMI indicates body mass index; CVD, cardiovascular disease; HDL, high-density lipoprotein; LDL, low-density
lipoprotein; METs, 1 metabolic equivalent=3.5 mL O2 uptake/kg body weight per minute.
protective effect of physical activity across all levels of BMI.
For 21 094 male participants in the Physicians Health Study, a
strong positive association was reported between BMI and HF
incidence, and a strong inverse association was found between
vigorous physical activity and HF incidence.13 More specifically, each 1 kg/m2 increase in BMI was associated with an
11% increase in HF incidence, and men who reported vigorous physical activity 5 to 7 days per week were 27% less
likely to develop HF compared with men who reported that
they rarely or never performed vigorous activity. Within each
category of BMI, risk of HF incidence was reduced in men
who reported vigorous physical activity. In this same study,
the effects of BMI and vigorous activity on HF mortality were
shown to be similar to their effects on HF incidence.
There are many possible mechanisms by which moderateto-high CRF may be protective against HF mortality. As early
as 1972, cross-sectional analyses by Bjorntorp showed that fit
middle-aged men had significantly lower insulin responses to
a glucose challenge than their unfit peers.29 Numerous training and prospective studies performed since that time have
shown that moderate-to-high levels of physical activity are
associated with improved insulin sensitivity,30 which in turn
Table 3. Adjusted* HRs (95% CIs) for Heart Failure Mortality Across Cardiorespiratory Fitness and BMI
Categories in 44 674 Men Who Were Followed for an Average of 19.8±10.4 Years in the Cooper Center
Longitudinal Study During 1971–2010
CRF Category
Total, n
High (Quintile 4–5)
Moderate (Quintile 2–3)
Low (Quintile) 1
9120
17 779
17 775
HF deaths, n
21
47
85
HR
1.0
1.63
3.97
1.0–2.7
2.4–6.5
Normal Weight
Overweight
Obese
18.5–24.9
25.0–29.9
≥30
16 043
21 387
7244
95% CI
BMI category, kg/m2
Total, n
HF deaths, n
38
74
41
HR
1.0
1.56
3.71
1.1–2.3
2.4–5.8
95% CI
P Trend
<0.0001
<0.0001
BMI indicates body mass index; CI, confidence intervals; CRF, cardiorespiratory fitness; HF, heart failure; and HR, hazard ratio.
*Adjusted for age, examination year, systolic blood pressure, smoking status, family history of cardiovascular disease, and diabetes mellitus.
902 Circ Heart Fail September 2013
NS
6.11
(3.5-10.7)
7.0
HR for HF Mortality
6.0
4.47
(2.1-9.4)
5.0
3.96*
(2.1-7.6)
4.0
3.64*
(2.1-6.2)
Unfit
3.0
2.0
1.0
1.72
(1.0-2.9)
Unfit
(n=1463)
1.0
Fit
(n=17,435)
Fit
(n=14,580)
Normal Weight
(18.5-24.9)
(n=3705)
Fit
(n=3539)
Unfit
(n=3952)
Overweight
(25.0-29.9)
Figure 1. Joint association of cardiorespiratory fitness and body mass index
(BMI) in men with adjusted* rates of heart
failure (HF) mortality in the Cooper Center
Longitudinal Study during 1971–2010.
*Adjusted for age, exam year, resting
systolic blood pressure, smoking status,
family history of cardiovascular disease,
and diabetes mellitus. Numbers on top of
boxes represent hazard ratios (HRs; 95%
confidence interval [CI]). NS indicates
nonsignificant.
Obese
(≥30)
BMI (kg/m2)
reduces the incidence of type 2 diabetes mellitus31 and metabolic syndrome.32 Furthermore, mortality among individuals
with type 2 diabetes mellitus33 and metabolic syndrome34 is
significantly lower across increasing levels of CRF. In both
cross-sectional35 and prospective studies, moderate-to-high
levels of CRF are shown to be associated with more favorable
blood lipid profiles,36 decreased resting blood pressure,37 and
decreased mortality among those with hypertension,26 as well
as a decreased likelihood of developing hypertension.38
In addition to exerting favorable effects on HF risk factors,
there is cross-sectional and prospective evidence that exercise
training is associated with beneficial structural and functional
changes in the myocardium. Levy et al39 found that a progressive 6-month aerobic training program significantly increased
end-diastolic volume, absolute peak filling rate, and peak early
or single peak diastolic filling rate at rest and during exercise
at all matched heart rates in younger (n=17) and older (n=14)
men. In cross-sectional analyses, Seals et al40 found that
endurance-trained older men had significantly better left ventricular (LV) systolic function than sedentary controls. More
specifically, the trained men had greater LV end-diastolic volume at rest and during peak exercise, as well as greater LV
exercise reserve (defined as the change in ejection fraction
between rest and exercise). In addition, a greater decrease
in end-systolic volume was shown in the trained men during
exercise than the controls, despite similar increases in systolic
blood pressure in the 2 groups. LV fractional shortening was
also higher during peak exercise in the trained group. Because
the LV wall thickness-to-radius ratio did not differ between
the 2 groups, these findings indicated a pattern of volumeoverload LV hypertrophy in the trained men. In a cross-sectional study comparing long-distance runners with sedentary
controls, Haskell et al41 found a >2-fold greater vasodilatory
capacity of the coronary arteries in the running group than in
7.27***
(4.1-12.8)
7.0
HR for HF Mortality
6.0
5.0
3.77**
(2.0-7.0)
4.0
3.01
(1.6-5.6)
2.54*
(1.2-5.6)
3.0
Unfit
n=4883
2.0
1.0
1.0
Unfit
Fit
n=11,236
0
n=1326
1.13
(0.6-4.7)
Unfit
n=2911
Fit
n=8888
Fit
n=15,433
Any 1
Any 2 or more
Number of Risk Factors
Figure 2. Adjusted* hazard ratios (HRs)
for heart failure (HF) mortality in fit and
unfit men based on the number of risk
factors in the Cooper Center Longitudinal
Study during 1971–2010. *Adjusted for
age and exam year. Numbers on top of
boxes represent HRs (95% confidence
interval [CI]). Risk factors include elevated
resting blood pressure (≥140/90 mm Hg)
or personal history of hypertension, current smoking, personal history of diabetes mellitus, obesity (body mass index
≥30 kg/m2), and family history of cardiovascular disease.*P=0.02 compared
with fit. **P<0.0001 compared with fit.
***P=0.0002 compared with fit.
Farrell et al Fitness, BMI, Heart Failure Mortality 903
5.0
HR for HF Mortality
4.0
3.0
2.0
3.29*
(2.3-4.7)
3.37*
(2.4-4.7)
41
85
2.39*
(1.7-3.3)
85
1.71**
(1.2 -2.5)
NS
1.72
(0.9-3.3)
1.64**
(1.2-2.3)
38
10
1.0
Hypertension
(n=14,028)
Current
Smoking
(n=7799)
Diabetes
(n=802)
73
BMI≥30 kg/m2
(n=7244)
Unfit
(n=9120)
Figure 3. Adjusted* hazard ratios (HRs)
for heart failure (HF) mortality in men
based on the presence of individual risk
factors in the Cooper Center Longitudinal
Study during 1971–2010. *Adjusted for
age and exam year. All comparisons are
dichotomies with the referent category
being the group who does not have the
risk factor. Numbers on top of boxes represent HRs (95% confidence interval [CI]).
Numbers in boxes represent HF deaths.
*P<0.0001. **P<0.005. BMI indicates
body mass index; CVD, cardiovascular
disease; and NS, nonsignificant.
Family History
of CVD
(n=19,792)
Heart Failure Risk Factor
controls during nitroglycerin administration. More recently,
greater coronary vasodilation in response to nitroglycerin was
shown in a more representative population (physically active
older individuals versus less active older individuals). Both
daily volume and intensity of activity were significantly correlated to vasodilation.42 These findings remained significant
after adjustment for several potential confounders. Fujimoto
et al43 examined the effects of a 1-year progressive jogging program on myocardial function in 9 sedentary men and women
with a mean age of 70 years. After training, volume-overload
LV hypertrophy was shown. Although aerobic power, total
aortic compliance, and arterial elastance were significantly
improved by training, there was no change in LV stiffness. The
authors speculated that the lack of improvement in LV stiffness
may have been because of either the age at which the exercise
program was initiated or an insufficient duration of training.
An important point to consider when interpreting the joint
associations of CRF and BMI with HF mortality is the method
in which CRF was grouped for this analysis. Currently, there
is no widely accepted method of defining CRF levels for use
in clinical or public health research. In the CCLS, we standardized the definition of low fitness (unfit) according to the
bottom 20% of the age-standardized distribution of maximal
exercise duration within the overall CCLS population, with
individuals in the remaining 80% of the distribution considered to be fit.19 By our definition, it would thus seem that even
modest levels of CRF are associated with lower risk of HF
mortality. For example, a 50- to 59-year-old man would need
to achieve a maximal MET level of ≥8.9 to qualify for the
fit category. This is equivalent to covering ≈1.2 miles in the
Cooper 12-minute run-walk test44 or achieving a treadmill
time of ≈8.5 minutes on a standard Bruce treadmill test.22 This
level of CRF can be achieved by many, perhaps even most,
apparently healthy adults through moderate amounts and
intensities of aerobic physical activity such as brisk walking.45
Among the strengths of the current study are a large and
well-characterized cohort of men, the use of objective measures for CRF and BMI, and an extensive follow-up. Although
BMI is a proxy measure of body fatness, it was significantly
correlated with percent body fat in the subset of the cohort
for whom percent body fat was measured (n=39 971; r=0.68;
data not shown). To decrease the possibility that pre-existing
disease was present at baseline, men with a BMI <18.5 kg/m2,
those who were not able to achieve ≥85% of predicted maximal
heart rate, and men with <1 year of follow-up were excluded
from analyses. Restricting our analyses to men with ≥3 years of
follow-up (n=42 764) did not materially change the strength or
patterns of these associations (data not shown), making us more
confident that subclinical HF was not a cause of low CRF and
subsequent greater HF mortality in the low-fit group. We were
also able to adjust for a large number of potentially confounding variables in the multivariate analyses.
This study has limitations. The cohort consists of only men
who are primarily white and from middle-to-upper socioeconomic strata; therefore, our findings must be cautiously
interpreted when generalizing to other populations. This
same limitation strengthens the internal validity of our findings by reducing potential confounding by these variables.
Furthermore, median levels of CRF in CCLS men are similar to median values obtained on a representative sample of
US men.46 We also point out that the overall prevalence of
metabolic syndrome among men in the CCLS cohort between
1979 and 2010 is ≈25%, which is similar to the prevalence
that has been reported among NHANES (National Health and
Nutrition Examination Survey) men in recent years.47 These
findings suggest that Cooper Clinic men have similar risk profiles compared with other US men.
Using CRF and BMI exposures as categorical rather than
continuous variables could also be viewed as a potential limitation. We chose the latter approach because we feel that the use
of clinically established cut points is more understandable and
useful for healthcare professionals. Because a relatively large
number of decedents in the cohort did not have a waist circumference measurement (n=78), we were unable to evaluate the
effects of central adiposity on mortality risk. We are reporting only baseline data on adiposity exposures and CRF. It is
904 Circ Heart Fail September 2013
possible that changes in these exposures may have occurred
during the follow-up period, which in turn may have influenced our results. An additional limitation includes the absence
of more extensive information on smoking habits, such as
number of pack-years. The relatively low number of obese
men (n=7244; 16%) in the cohort may have limited our ability
to detect a significant difference in mortality between fit and
unfit obese men. Because the Cooper Clinic did not begin to
measure high-density lipoprotein and low-density lipoprotein
cholesterol until 1978, we have missing data for these variables
in Table 1. We do not have information regarding the presence
or absence of sleep apnea in the cohort. Because high alcohol
intake (>21 drinks/week) was not significantly associated with
HF mortality in our cohort and because a substantial number of
men (n=7952) had missing data for the alcohol intake question,
we did not include this variable in our multivariate analyses.
However, by including men in the analyses who were missing
the alcohol intake variable, we were able to increase our number of HF deaths. Finally, we were unable to evaluate medication use or dietary factors in this cohort.
In summary, the inverse relationship between baseline CRF
and HF mortality in men is quite strong and is materially unaffected by adjustment for BMI and other potential confounders.
Within each category of BMI, HF mortality was lower in fit
compared with unfit men. Irrespective of the number of risk
factors present, fit men had substantially lower HF mortality
than unfit men. When examining the individual strength of
each risk factor on HF mortality, low CRF (unfit) and obesity functioned as the strongest risk factors. Regardless of the
number of HF risk factors present, clinicians are encouraged to
counsel their male patients to increase their levels of physical
activity with the goal of achieving at least a moderate level of
CRF, thereby presumably decreasing their risk of HF mortality.
Acknowledgments
We thank Kenneth H. Cooper, MD, MPH, for establishing the Cooper
Center Longitudinal Study, The Cooper Institute for data management, and Melba Morrow for editorial assistance.
Disclosures
None.
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CLINICAL PERSPECTIVE
To our knowledge, there are no reported data relating an objective measure of cardiorespiratory fitness with subsequent heart
failure (HF) mortality. In this article, we report on 44 674 apparently healthy men who underwent a baseline examination at
the Cooper Clinic between 1971 and 2010. Cardiorespiratory fitness was measured via a maximal treadmill stress test. Participants were followed for ≈20 years, during which there were 153 deaths from HF. Adjusted hazard ratios across high, moderate, and low cardiorespiratory fitness categories were 1.0, 1.63, and 3.97, respectively, showing for the first time that baseline
cardiorespiratory fitness is an important determinant of subsequent HF mortality. In addition, HF mortality rates were lower
in fit than in unfit men within each body mass index strata, particularly within the normal weight and overweight groups. An
additional novel finding in our data was the marked difference in HF mortality between fit and unfit men with the same number
of traditional HF risk factors. Importantly, the level of fitness at which the risk of HF mortality is lower seems to be modest.
Thus, patients who can meet current public health guidelines for physical activity (≥150 minutes per week of moderate intensity aerobic exercise) are likely to be at substantially lower risk with regard to future HF mortality. This is especially true if
they are also able to control other HF risk factors such as obesity, hypertension, smoking, and diabetes mellitus.