The combination of cardiorespiratory fitness and muscle strength, and mortality risk
European Journal of Epidemiology
The combination of cardiorespiratory fitness and muscle strength, and mortality risk
Youngwon Kim 0 1 2 3
Tom White 0 1 2 3
Katrien Wijndaele 0 1 2 3
Kate Westgate 0 1 2 3
Stephen J. Sharp 0 1 2 3
Jørn W. Helge 0 1 2 3
Nick J. Wareham 0 1 2 3
Soren Brage 0 1 2 3
0 Department of Health , Kinesiology, and Recreation , College of Health, University of Utah , 250 South 1850 East Room 204, Salt Lake City, UT 84112 , USA
1 MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science , Cambridge Biomedical Campus, Cambridge, Cambridgeshire CB2 0QQ , UK
2 & Youngwon Kim
3 Department of Biomedical Sciences, Center of Healthy Aging, University of Copenhagen , Blegdamsvej 3, 2200 N, Copenhagen , Denmark
Little is known about the combined associations of cardiorespiratory fitness (CRF) and hand grip strength (GS) with mortality in general adult populations. The purpose of this study was to compare the relative risk of mortality for CRF, GS, and their combination. In UK Biobank, a prospective cohort of [ 0.5 million adults aged 40-69 years, CRF was measured through submaximal bike tests; GS was measured using a hand-dynamometer. This analysis is based on data from 70,913 men and women (832 all-cause, 177 cardiovascular and 503 cancer deaths over 5.7-year follow-up) who provided valid CRF and GS data, and with no history of heart attack/stroke/cancer at baseline. Compared with the lowest CRF category, the hazard ratio (HR) for all-cause mortality was 0.76 [95% confidence interval (CI) 0.64-0.89] and 0.65 (95% CI 0.55-0.78) for the middle and highest CRF categories, respectively, after adjustment for confounders and GS. The highest GS category had an HR of 0.79 (95% CI 0.66-0.95) for all-cause mortality compared with the lowest, after adjustment for confounders and CRF. Similar results were found for cardiovascular and cancer mortality. The HRs for the combination of highest CRF and GS were 0.53 (95% CI 0.39-0.72) for all-cause mortality and 0.31 (95% CI 0.14-0.67) for cardiovascular mortality, compared with the reference category of lowest CRF and GS: no significant association for cancer mortality (HR 0.70; 95% CI 0.48-1.02). CRF and GS are both independent predictors of mortality. Improving both CRF and muscle strength, as opposed to either of the two alone, may be the most effective behavioral strategy to reduce all-cause and cardiovascular mortality risk.
Low cardio-respiratory fitness (CRF) is a strong predictor
of numerous health outcomes, including mortality, not only
in general adult populations [
] but also in obese [
], or diabetic  adults. Poor muscular
strength, another component of fitness, has also been
indicated as an important marker of mortality [
] as well
as adverse health outcomes such as frailty and sarcopenia
. Recent clinical trials [
] have demonstrated that
compared with improving either CRF or muscle strength
alone, improving both CRF and muscle strength
simultaneously led to more favorable changes on intermediate
cardio-metabolic risk factors and functional status; these
intermediate outcomes are important predictors for clinical
]. However, the prior clinical trials
] did not include clinical end-points, and it would, in
fact, be nearly impossible to establish clinical trials with
sufficient statistical power to do so. In contrast, large-scale
prospective observational studies can provide such
evidence. However, a few observational studies evaluating
combined impacts of CRF and muscle strength in relation
to mortality risk merely included data from highly select
populations of men (i.e. men who were either hypertensive
 or adolescent [
] at baseline). This limitation
precludes the ability to draw robust conclusions for general
adult populations of men and women. Given that current
public health guidelines [
] recommend that men and
women engage in both aerobic and muscle-strengthening
activities across the whole lifespan, it is critical from
clinical and public health standpoints to examine the
combined impacts of CRF and muscle strength for
mortality risk for a broader adult population.
The UK Biobank study is an ongoing prospective
national cohort of over half a million middle-aged UK men
and women. Data collection at baseline and
repeatassessment visit included submaximal stationary bike tests
to assess CRF as well as grip strength (GS) to evaluate
overall muscle strength [
]. This provides an
opportunity to disentangle the interplay between CRF, muscle
strength and mortality in general adult populations.
Therefore, the purpose of this study was to explore the
relative risk of mortality from all causes, cardiovascular
disease (CVD) and cancer for CRF, GS and the
combination of both.
Study design and participants
Approximately 9.2 million adults who were within \ 25
miles of one of 22 assessment centres across the UK and
registered with the National Health Service were initially
contacted for participation in the UK Biobank study.
Between 2006 and 2010,[ 500,000 participants underwent
baseline data collection which included a wide variety of
physical measurements and biological samples, as well as
questionnaires on prevalent morbidities,
socio-demographic factors, family history/early-life exposures,
lifestyle, and environmental factors. Repeated assessments of
the variables were carried out between 2012 and 2013 in a
sub-sample of over 20,000 individuals. From 2009, the
baseline protocol was extended to include submaximal
stationary bike tests to assess CRF; this was offered to
96,550 participants (79,209 from baseline; 20,218 from the
repeat-measures visit), totaling 99,427 measurements
(2877 at both time points). More details about the UK
Biobank methodology are provided elsewhere [
]; Fig. 1
provides an overview of participants included in the
present analysis. All participants signed informed written
consent prior to participation, and the UK Biobank protocol
was approved by the North West Multi-Centre Research
Prior to performing a submaximal exercise test on a
stationary bike (eBike Comfort Ergometer, General Electric,
firmware version 1.7), participants were categorized into
one of five risk categories (S1 Material in Appendix) [
The risk categorization determined allocation to an
individualized exercise protocol (S2 Material in Appendix), a
methodology aimed at increasing the number of
participants with exposure information whilst at the same time
reducing the likelihood that participants experience any
adverse medical events during the exercise test. Individuals
with ‘minimal risk’ (n = 72,715) and ‘small risk’
(n = 11,257) carried out standard bike protocols, which
consisted of (1) an initial 15-s seated-rest period, (2) a
2-min phase at constant power (30 watts for women; 40
watts for men), (3) a 4-min ramp phase with linear
increases in power from their initial constant power to their
individually assigned peak power (to 50 and 35% of
predicted maximal workload for ‘minimal’ and ‘small’ risk,
respectively), and (4) a 1-min recovery period. Individuals
with ‘medium risk’ (n = 2812) cycled at the constant
power level for 6 min. Participants were asked to cycle at
60 revolutions-per-minute (RPM) during all cycling
phases. Individuals in the ‘high’ risk (n = 11,162) category
only did a 2-min seated-rest assessment and were excluded
from this analysis, as were those ‘ineligible’ for
electrocardiograph testing (n = 1481).
Participants’ electrocardiograms were recorded at
500 Hz with a 4-lead electrocardiograph device
(CAMUSB 6.5, Cardiosoft v6.51; two electrocardiograph
electrodes on each upper limb) throughout the full test. The
electrocardiograph signal was processed using the
PhysioNet Toolkit [
] implementation of the SQRS algorithm
], which applies a digital filter to the signal and
identifies the distinctive downward slopes of QRS complexes.
The resultant inter-beat-intervals were converted to
beatsper-minute values, using ‘‘ihr’’ of the PhysioNet Toolkit
] (restricting beat-to-beat heart rate changes to
B 10 bpm), after which linear interpolation was applied to
derive heart rate at 1-s resolution. In addition, we
implemented data cleaning and quality control procedures (S3
Material in Appendix). Linear regression was performed to
predict workload from heart rate (S4 Material in
Appendix); the established linear relationship was then
extrapolated to age-predicted maximum heart rate [
] to estimate
an individual’s maximal power (watts) as an indicator of
CRF. Consolidation procedures were applied to obtain the
most robust CRF estimate (S5 Material in Appendix). To
account for differences in body size, CRF was expressed as
maximal power per fat-free mass (kg) (i.e. body mass–fat
mass), the latter measured using bio-impedance analysis
(Tanita BC-418MA). Individuals with heart rate missing for
[ 2 min (50%) during the ramp phase (n = 116) or with
maximum power of 0 (n = 156; a sign of the cycle
ergometer/ECG acquisition system malfunctioning) or
outliers with [ 20 watts/fat-free mass (n = 41) were
excluded from analyses.
GS was assessed once in each hand using a hydraulic hand
dynamometer (Jamar J00105), which can measure
isometric grip force and was calibrated by staff at the start of
each measurement day. Each participant grasped the
handle of the device in their right hand while sitting upright on
a chair with their forearm on the armrest, and whilst
maintaining a 90 angle of their elbow, squeezed the
handle as strongly as possible for about 3 s. The same
protocol was undertaken with the left hand. GS measures
have good reliability and reproducibility [
]. For the
current primary analysis, values from the two hands were
averaged if available; otherwise, the value from a single
hand was used in a small subsample (n = 204). Values of
GS (kg) were also divided by fat-free mass (kg) to account
for differences in body size.
Mortality status was ascertained by linking the Biobank
data with death records from the National Health Service
Information Centre and the Scottish Morbidity Record. For
the present analyses, we used mortality cases accrued until
February 15th 2016. Mortality from CVD and cancer were
classified according to the International Classification of
Diseases-10 codes F01 and I00-I99, and C00-D48,
respectively. The median follow-up period was 5.7 years
(interquartile range 5.6–5.9 years).
The following variables were included as covariates in the
analyses: sex, waist circumference (centimeters), ethnicity
(White, mixed, Asian/Asian British, Black/Black British,
other), smoking status (never, previous, current),
employment (unemployed, employed), Townsend Deprivation
Index (a composite score of employment, car ownership,
home ownership and household overcrowding; based on
postcode, with higher values indicating a higher degree of
deprivation), alcohol consumption (never, previously,
currently \ 3 times/week, currently C 3 times/week),
processed/red meat consumption (days/week), beta-blocker
use (yes, no), hypertension, and diabetes. Hypertension was
defined as systolic/diastolic blood pressure C 140/
90 mmHg, a physician diagnosis of hypertension, and/or
reported medication used to regulate blood pressure.
Participants were considered having diabetes if they reported a
physician diagnosis of diabetes or were taking
glucoselowering medication. Participants with a self-reported
history of heart attack, stroke or cancer were excluded,
resulting in a final sample of 70,913 participants (2005 with
repeated measures) with no missing values included in the
analyses (Fig. 1).
Sex- and age-specific categories of CRF and GS were
calculated based on tertiles of their baseline distributions to
categorize individuals into either low, medium or high
CRF/GS at both baseline and the repeated exposure
assessment (S1 Table in Appendix). Cox regression, with
age as the underlying time scale, was used to estimate
associations of CRF and GS with mortality, including the
categories of CRF and GS at both baseline and follow-up
as time-updated covariates. Models were fitted with no
adjustment (Model 1), adjustment for potential
confounders (Model 2), and further adjustment for GS in
models for CRF or for CRF in models for GS (Model 3).
Parallel sets of models were performed using standardized
variables (i.e. per 1-standard deviation increment) of CRF
and GS. Interactions of CRF or GS with sex were tested.
Joint associations of CRF and GS with mortality were
estimated using low GS/low CRF as the common reference
group; the multiplicative interaction between CRF and GS
was tested. Log–log plots provided support for the
proportional hazards assumptions. The following sensitivity
analyses were performed: (1) a random-effects
meta-analysis across the different individualized protocols to
examine the impacts of protocol assignment on fitness-mortality
associations, (2) an analysis after excluding mortality cases
occurring during the first 2 years of follow-up to address
reverse causality, and (3) an analysis with CRF and GS
both normalized for body weight to examine whether
different handling of the scaling for body size influences
mortality associations. Analyses were performed in Stata/
SE Version 14 (StataCorp LP, College Station, TX).
Table 1 summarizes characteristics of the participants
across CRF and GS categories. Individuals with greater
CRF or GS were more likely to be smokers, or alcohol
drinkers, be employed, live in less deprived areas, and have
no hypertension or diabetes at baseline. The Pearson
correlation between CRF and GS was moderate (0.55) [
Table 2 shows associations of CRF and GS with
allcause, CVD and cancer mortality. Over 379,682
personyears of follow-up, there were 832, 177 and 503 deaths
from all causes, CVD and cancer, respectively. Crude
mortality rates from all causes, CVD and cancer were
consistently lower in those with higher levels of CRF or
GS. Interactions of each exposure with sex were not
significant (p-values \ 0.05), so associations were estimated
for men and women combined. Compared with the lowest
category of CRF, the hazard ratios (HR) of all-cause
mortality were lower for the higher CRF categories (p for
trend: \ 0.0001), after adjustment for potential
confounders. Additional adjustment for GS made almost no
difference to the results. Every 1-standard deviation
increase in CRF was associated with 23% (95% CI
13–31%) lower hazard of all-cause mortality. A
metaanalysis across the different individualized protocols
(sensitivity analysis) revealed similar inverse (although
less linear) associations (S2 Table in Appendix). Analyses
using CRF estimates only from the constant phase also
found similar inverse associations (data not shown).
Compared with the lowest category of GS, the highest
category had a significant HR of 0.80 (95% CI 0.67–0.96)
Values are means (standard deviations) unless otherwise indicated. Age- and sex-specific cut-points were used to create categories of
cardiorespiratory fitness and grip strength. Note: ‘‘N’’ indicates numbers of total participants (i.e. participants who provided repeated measures are
treated as separate data cases) and ‘‘n’’ indicates numbers of unique participants
while the HR for the middle category (HR 0.88; 95% CI
0.75–1.04) was not statistically significant after adjustment
for confounders. Nonetheless, the linear trend across the
three groups was significant (p for trend: 0.014). Additional
adjustment for CRF made no meaningful differences to the
associations (p for trend: 0.010). The HR of all-cause
mortality for every 1-standard deviation increase in GS was
0.93 (95% CI 0.86–1.01), which was weaker than that for
Higher CRF was associated with lower hazards of CVD
(p for trend: 0.001) and cancer (p for trend: 0.003)
mortality, compared with the lowest category, after adjustment
for confounders and GS. The highest CRF category had
51% (95% CI 26–68%) and 28% (95% CI 10–42%) lower
P for linear trend
Per 1-SD increase in
Categories of grip
All models used age as the underlying time variable. Categories of aerobic fitness and grip strength were defined based on age and sex
specificcategories of the baseline distribution. Aerobic fitness and grip strength were both normalized by fat-free mass
Model 1: No adjustment
Model 2: Adjusted for sex, waist circumference, ethnicity (White, mixed, Asian/Asian British, Black/Black British, other), smoking status (never,
previous, current), employment (unemployed, employed), Townsend Deprivation Index, alcohol consumption (never, previous, currently
\ 3 times/week, currently C 3 times/week), processed/red meat consumption (days/week), beta-blocker use, hypertension, and diabetes
Model 3: Model 2 plus grip strength in models where cardiorespiratory fitness was the exposure, or cardiorespiratory fitness in models where grip
strength was the exposure
CVD cardiovascular disease, SD standard deviation
hazards of CVD and cancer mortality, respectively,
compared with the lowest category. CVD and cancer mortality
rates were also lower in higher categories of GS, although
the HRs were not statistically significant. Nonetheless,
associations were stronger for CVD mortality compared to
all-cause mortality. The HRs comparing CRF categories
were larger than those for GS for all three mortality
outcomes. Similar findings were identified in sensitivity
analyses where CRF and GS were both normalized for
body weight (S3 Table in Appendix), and deaths within the
first 2-years of follow-up were excluded (S4 Table in
Figure 2 shows joint associations between CRF, GS and
all-cause mortality (p for interaction: 0.187). Compared
with individuals with the lowest CRF and GS, those with
higher levels of both CRF and GS had lower hazards of
allcause mortality. The HR (compared with low GS and low
CRF) in the highest CRF but lowest GS group (HR 0.58;
95% CI 0.44–0.75) was stronger than that in the lowest
CRF but highest GS group (HR 0.71; 95% CI 0.55–0.93),
although the 95% CIs around these two estimates
overlapped. Compared with those with the lowest CRF and GS,
individuals in the highest category of CRF and GS had a
47% (95% CI 28–61%) lower hazard of all-cause mortality
and a 69% (95% CI 33–86%) lower hazard of CVD (Fig. 3;
p for interaction: 0.412): no significant association for
cancer mortality (HR 0.70; 95% CI 0.48–1.02) (Fig. 4;
p for interaction: 0.374).
consumption (never, previous, currently \ 3 times/week, currently
C 3 times/week), processed/red meat consumption (days/week),
betablocker use, hypertension, and diabetes. Age- and sex-specific
categories of aerobic fitness and grip strength were used. Aerobic
fitness and grip strength were both normalized by fat-free mass
This study is the first investigation evaluating the relative
risk of all-cause, CVD and cancer mortality for CRF,
muscle strength and the combination of both in a general
population of middle-aged and older men and women.
Higher CRF was associated with lower risks of all-cause,
CVD and cancer mortality, independent of GS and
confounders. The highest GS was associated with lower risk of
all-cause mortality compared with the lowest. Individuals
with the highest level of CRF and GS had the lowest risks
of all-cause and CVD mortality among all comparisons,
compared with the lowest level of CRF and GS. The
inverse associations were more consistent for higher CRF
categories across GS levels than for higher GS categories
across CRF levels.
Similar analyses have been reported in prior
investigations but in highly selected populations [
]. Using data
from 1506 middle-aged hypertensive men, Artero et al.
 found that compared with men in the lower 50% CRF
group and the lowest muscle strength tertile, those in the
upper 50% CRF group and the highest muscle strength
tertile had a 51% lower risk of all-cause mortality.
Similarly, a study of 1.5 million adolescent boys found that the
lowest tertiles of CRF and muscle strength during
adolescence were associated with more than twice the risk of
allcause (HR 2.01) and CVD (HR 2.63) mortality in later
adulthood, compared with the highest tertiles [
study used data of men and women aged [ 40 years with
no critical medical conditions at baseline, and therefore
provides new insights into the beneficial combined impacts
of CRF and muscle strength on mortality risk in the general
The relatively stronger mortality associations with CRF
than with GS suggest that lower CRF is a more important
risk factor for mortality than lower muscle strength. A
potential explanation for this difference is that the degree
to which grip strength represents overall muscle strength
may be lesser than the degree to which submaximal bike
tests represent cardiorespiratory fitness. However, this
finding is in line with prior research that found no
] or inconsistent [
] associations of muscle
strength (e.g., GS, sit-ups and push-ups [
]; bench press,
leg press and sit-ups [
]) with mortality when CRF (e.g.,
predicted VO2max [
]; maximal-treadmill test [
adjusted for in the analyses. Nonetheless, other studies
using data of men concluded that muscle strength (e.g.,
bench press and leg press) was a strong predictor of
mortality independent of CRF (e.g., maximal treadmill test)
]. In other studies, the combination of low CRF and
muscle strength was associated with increased risks of
developing stroke , type 2 diabetes [
events and arrhythmia [
], all of which are strong
mortality risk factors [
In addition to the evidence from observational studies,
numerous intervention studies have demonstrated the
synergistic effects of combining resistance training and
aerobic exercise on eliciting favorable changes in intermediate
health indicators. A recent 26-week randomized controlled
trial of dieting obese older adults [
] found that individuals
who received an intervention consisting of both aerobic
\ 3 times/week, currently C 3 times/week), processed/red meat
consumption (days/week), beta-blocker use, hypertension, and
diabetes. Age- and sex-specific categories of cardiorespiratory fitness
and grip strength were used. Cardiorespiratory fitness and grip
strength were both normalized by fat-free mass
and resistance exercise (3 days/week; 75–90 min each)
plus a weight-management program showed relatively
larger improvements in functional status and body
composition in comparison with individuals who, in
conjunction with a weight-management program, carried out either
aerobic (3 days/week; 60 min each) or resistance exercise
alone (3 days/week; 60 min each). Moreover, in a 9-month
randomized-controlled trial of individuals with type 2
], hemoglobin A1c levels significantly
decreased in the intervention group who undertook a
combined program of resistance training (2 days/week) and
aerobic exercise (expending 10 kcal/kg/week) compared
with the control group. Notably, this effect was not
observed in the other intervention groups who received
either resistance training (3 days/week) or aerobic exercise
(expending 12 kcal/kg/week) [
]. Similarly, in an
8-month randomized controlled trial of 196 overweight
adults aged 18–70 years [
], a combined protocol of
resistance (3 days/week) and aerobic training (running 12
miles/week) resulted in significant improvements in insulin
sensitivity, which was not achieved with either resistance
or aerobic training alone. While clinical trials are needed to
formally determine causality for the joint effects of CRF
and muscle strength on mortality risk, these would be
difficult to undertake in the general population; therefore,
for the foreseeable future, public health action has to be
informed by the combined evidence from exercise trials on
intermediate risk factors and prospective observational
epidemiological studies on clinical endpoints.
The current physical activity guidelines [
that adults do both moderate-to-vigorous intensity aerobic
physical activity for 150 min/week and
muscle-strengthening activities at least twice a week. Previous research
found that meeting the guidelines for muscle-strengthening
activities in addition to aerobic physical activity was
associated with further reductions in the risks of
] and mortality [
]. Nonetheless, fewer than
30% of UK [
] and US [
] adults meet both the aerobic
physical activity and muscle-strengthening guidelines.
Furthermore, the prevalence of meeting these guidelines
currently C 3 times/week), processed/red meat consumption (days/
week), beta-blocker use, hypertension, and diabetes. Age- and
sexspecific categories of cardiorespiratory fitness and grip strength were
used. Cardiorespiratory fitness and grip strength were both
normalized by fat-free mass
declines drastically with age [
]. Public health efforts
should, therefore, be focused on encouraging adults of all
ages to engage in both aerobic and resistance exercise to
reduce mortality risk through increased CRF and muscle
The following limitations should be considered when
interpreting the findings. First, the findings of this study
may not be generalizable to the whole UK population or
adults in other countries as no sampling strategies were
used in UK Biobank to select representative samples of
adults. Another potential selection bias may exist with the
sub-sample of individuals who performed bike tests.
However, the UK Biobank employed less rigorous pre-test
screening procedures compared with prior studies [
and those individuals who performed bike tests had
virtually identical demographic and biological characteristics
(e.g. sex ratio, GS, fat-free mass, resting pulse rate) to those
who did not perform bike tests. In addition, there is risk of
residual confounding due to the use of self-reported
information (e.g., behaviors and comorbidities). Moreover,
the findings may not be applicable to individuals with
cancer, stroke or heart attack as these prevalent medical
conditions were excluded from the present analyses.
Furthermore, we may not have full follow-up information on
individuals who migrated to other countries after
participation in baseline assessment. Another limitation is the
inability to draw firm conclusions about causal
relationships of CRF and GS with mortality due to the
observational nature of this study.
Individuals with higher CRF showed lower risks of
allcause, CVD and cancer mortality; those with higher GS
had lower all-cause mortality. All-cause and CVD
mortality risk was lowest in adults with both higher CRF and
higher. Improving both CRF and muscle strength, as
opposed to either of the two alone, may be the most
effective behavioral strategy to reduce all-cause and
cardiovascular mortality risk.
Acknowledgements This work was supported by the UK Medical
Research Council [MC_UU_12015/1 and MC_UU_12015/3], a PhD
studentship from MedImmune (to TW), and an Intermediate Basic
Science Research Fellowship of British Heart Foundation (FS/12/58/
29709 to KWi). The funders had no role in study design, data
collection and analysis, decision to publish, or preparation of the
manuscript. YK had full access to all of the data in the study and takes
responsibility for the integrity of the data and the accuracy of the data
analysis. This research has been conducted using the UK Biobank
Resource under Application Number 408. We also thank the Danish
National Health Examination Survey for sharing maximal power and
predictor data, used to individualise the UK Biobank exercise
Compliance with ethical standards
Conflict of interest The authors declare that they have no conflict of
Ethical approval All procedures performed in the UK Biobank
involving human participants were in accordance with the ethical
standards of the institutional and/or national research committee.
Open Access This article is distributed under the terms of the Creative
Commons Attribution 4.0 International License (http://creative
commons.org/licenses/by/4.0/), which permits unrestricted use,
distribution, and reproduction in any medium, provided you give
appropriate credit to the original author(s) and the source, provide a
link to the Creative Commons license, and indicate if changes were
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