Articles

Association between change in daily ambulatory activity
and cardiovascular events in people with impaired glucose
tolerance (NAVIGATOR trial): a cohort analysis
Thomas Yates, Steven M Haﬀner, Phillip J Schulte, Laine Thomas, Kim M Huﬀman, Connie W Bales, Robert M Caliﬀ, Rury R Holman,
John J V McMurray, M Angelyn Bethel, Jaakko Tuomilehto, Melanie J Davies, William E Kraus

Summary
Background The extent to which change in physical activity can modify the risk of cardiovascular disease in individuals
at high cardiovascular risk is uncertain. We investigated whether baseline and change in objectively-assessed
ambulatory activity is associated with the risk of a cardiovascular event in individuals at high cardiovascular risk with
impaired glucose tolerance.
Methods We assessed prospective data from the NAVIGATOR trial involving 9306 individuals with impaired glucose
tolerance who were recruited in 40 countries between January, 2002, and January, 2004. Participants also either had
existing cardiovascular disease (if age ≥50 years) or at least one additional cardiovascular risk factor (if age ≥55 years).
Participants were followed-up for cardiovascular events (deﬁned as cardiovascular mortality, non-fatal stroke, or
myocardial infarction) for 6 years on average and had ambulatory activity assessed by pedometer at baseline
and 12 months. Adjusted Cox proportional hazard models quantiﬁed the association of baseline and change inambulatory activity (from baseline to 12 months) with the risk of a subsequent cardiovascular event, after adjustment
for each other and potential confounding variables. This study is registered with ClinicalTrials.gov NCT00097786.
Findings During 45 211 person-years follow-up, 531 cardiovascular events occurred. Baseline ambulatory activity(hazard ratio [HR] per 2000 steps per day 0·90, 95% CI 0·84–0·96) and change in ambulatory activity (0·92,
0·86–0·99) were inversely associated with the risk of a cardiovascular event. Results for change in ambulatory activity
were unaﬀected when also adjusted for changes in body-mass index and other potential confounding variables
at 12 months.
Interpretation In individuals at high cardiovascular risk with impaired glucose tolerance, both baseline levels of daily
ambulatory activity and change in ambulatory activity display a graded inverse association with the subsequent risk ofa cardiovascular event.
Funding Novartis Pharmaceuticals.

Introduction
Clinical trials have shown that lifestyle interventions
can eﬀectively reduce the risk of developing
type 2 diabetes in high-risk individuals with impaired
glucose tolerance,1,2 and detailed modelling analyses
have shown them to be highly cost-eﬀective in theprevention of type 2 diabetes.3,4 Consequently, lifestylechanges form the cornerstone of diabetes prevention
initiatives that have been translated into routine clinicalpractice.5,6 However, whether changes to lifestyle factors
aﬀect the risk of cardiovascular disease in individuals
with impaired glucose tolerance is unclear, sinceprevious diabetes prevention trials were not designed,
and consequently lack suﬃcient power, to assess thisoutcome. This is an important limitation, since cardiovascular disease is the most deleterious consequence ofdysglycaemia and the primary cause of death in thosewith type 2 diabetes.7
Observational studies have consistently shown thathigher levels of physical activity or cardiorespiratoryﬁtness are associated with a lower risk of cardiovascular
www.thelancet.com Vol 383 March 22, 2014

morbidity and mortality.8–11 However, this evidence has
been limited by several factors. Physical activity is
usually assessed by self-reported questionnaires, which
are known to have poor validity, particularly
when assessing habitual or total physical activity
levels.12 Alternatively, cardiorespiratory ﬁtness, evenwhen measured objectively, is aﬀected by factors
beyond physical activity, including genetic makeup,
which also aﬀect survival.13 Along with limitations
around measurement, the extent to which change inphysical activity can act to ameliorate the risk ofcardiovascular disease in individuals already displaying
impaired glucose tolerance and other cardiovascularrisk factors is also unknown.
The NAVIGATOR trial provides the ﬁrst detailed
opportunity in an international pharmacotherapy trial
to investigate whether change in objectively-assessed
ambulatory activity is associated with a lower risk of a
cardiovascular event independently of randomised
therapy allocation, other lifestyle factors, or body-massindex.

Lancet 2014; 383: 1059–66
Published Online
December 20, 2013
http://dx.doi.org/10.1016/
S0140-6736(13)62061-9
See Comment page 1022
NIHR Leicester-LoughboroughDiet, Lifestyle, and Physical
Activity Biomedical Research
Unit, Leicester, UK (T Yates PhD,M J Davies MD); Leicester
Diabetes Centre, College ofMedicine, Biological Sciences
and Psychology, University ofLeicester, Leicester, UK (T Yates,
M J Davies); Shavano Park, USA(S M Haﬀner MD); Duke ClinicalResearch Institute, Duke
University School of Medicine,
Durham, NC, USA(P J Schulte PhD, L Thomas PhD,K M Huﬀman MD, C W Bales PhD,R M Caliﬀ MD, W E Kraus MD);
Durham VA Medical Center,
Durham, NC, USA (C W Bales);Diabetes Trials Unit, Universityof Oxford, Oxford, UK(M A Bethel, MD,
R R Holman MD); British Heart
Foundation Glasgow
Cardiovascular ResearchCentre, University of Glasgow,
Glasgow, UK(J J V McMurray MD); Centre for
Vascular Prevention, Danube
University Krems, Krems,
Austria (J Tuomilehto MD);South Ostrobothnia Central
Hospital, Seinajoki, Finland(J Tuomilehto); and King
Abdulaziz University, Jeddah,
Saudi Arabia (J Tuomilehto)
Correspondence to
Dr Thomas Yates, Leicester
Diabetes Centre, Leicester
General Hospital,
Leicester LE5 4PW, UK
ty20@le.ac.uk

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Methods
Study design and population
We analysed prospective data from NAVIGATOR(Nateglinide and Valsartan in Impaired Glucose Tolerance
Outcomes Research),14–16 a multicentre, randomised,
placebo controlled, 2 × 2 factorial trial designed toinvestigate whether nateglinide (meglitinide analogue) or
valsartan (angiotensin II receptor antagonist) reduce therisk of cardiovascular events in individuals with impaired
glucose tolerance and either existing cardiovasculardisease (if 50 years or older) or with at least one additional
cardiovascular risk factor (if 55 years of age or older).
Details of the cardiovascular risk and inclusion criteria
have been listed elsewhere.14 Participants were recruitedfrom 806 centres in 40 diﬀerent countries. 42 149 patientswere screened for inclusion. 32 843 patients were subsequently excluded, mainly because they did not meet the
protocol-deﬁned criteria for impaired glucose tolerance,leaving 9306 patients who were enrolled in the study
between January, 2002, and January, 2004, and randomised [1:1:1:1] to one of the four treatment combinations.
Participants were followed up for an average of 6 years.

Procedures
At baseline, all individuals underwent a detailed clinicalassessment, including: oral glucose tolerance test (fasting
and 2 h post-challenge glucose) and measurement oflipid proﬁle (triglycerides, total cholesterol, and HDL and
LDL cholesterol), renal function (urine albumin,creatinine, and sodium), blood and pulse pressure,electrocardiograph, bodyweight, and height. A detailed
medical history was also recorded, including previous
cardiovascular disease and concomitant diseases orconditions, smoking history, and medication status.
Biochemical and anthropometric measures wererepeated every year (apart from lipid factors which were
only measured universally at 3 years onwards). All
outcomes were assessed using the same standard
operating procedures across sites.
All randomisation groups participated in a lifestyle
modiﬁcation programme that was designed to help
participants achieve and maintain a 5% weight loss, reduce
the amount of saturated and total fats in their diet, andincrease their physical activity to 150 min a week. Personnel
within each study site were trained to administer the
programme and provided materials to participants at eachclinic visit within the ﬁrst 12 months (at 0·5, 1, 3, 6,
and 12 months), with additional reinforcement undertaken
through interim telephone contacts.
Habitual ambulatory activity was objectively assessedusing a pedometer. Research-grade pedometers(Accusplit, San Jose, CA, USA), which assess purposefulsteps taken through a horizontal, spring-suspended leverarm which moves up and down with each step, weredispatched to all NAVIGATOR study centres. 2 weeks
after the initial baseline clinical measurements,
participants were ﬁtted with a pedometer and instructed1060

to wear it during waking hours for 7 consecutive days.
Participants were given a log book and instructed to write
down their daily step count at the end of each day.
Participants then returned their step log to the study
team. Ambulatory activity levels were reassessed using
the same criteria at 12 months.
Dietary behaviour was measured by a six-item
questionnaire assessing whether participants included
fruit and vegetables in their diet on a daily basis andwhether they actively limited the amount of total fat,saturated fat, sugar, salt, and alcohol (to two drinks per
day or fewer) in their diet.
For the purposes of this study, a single cardiovascularcomposite of time to death from cardiovascular causes ornon-fatal myocardial infarction or non-fatal stroke wasused. An independent committee, who were blinded to
study allocation and ambulatory activity level, adjudicated
all putative cardiovascular events.15,16

Statistical analysis
Ambulatory activity was measured as the average numberof steps taken per day (total summed pedometer counts
divided by the number days that data were captured).
Change in ambulatory activity was calculated by subtracting average pedometers counts at 12 months fromthose at baseline. To remove potentially spurious data,baseline pedometer counts were truncated at 20 000 steps
per day, representing roughly the 99th percentile. Change
results were truncated at plus or minus 10 000 steps perday (ie, those with daily pedometer values outside theseranges were limited to these upper levels); roughly
equivalent to the ﬁrst and 99th percentile. Those reporting
an average of zero steps per day at baseline (n=343)
or 12 months (n=547) were counted as missing.
Biochemical, anthropometric, and behaviouralvariables are reported by category of change inambulatory activity (more than 1500 step per day
decrease, 0–1500 step per day decrease, 1–1500 step per
day increase, or more than 1500 step per day increase),
which were approximate to quartiles of change. Continuous variables are reported as median (IQR);
categorical variables are reported by proportion.
Cox proportional hazard models were used to estimate
the association between change in ambulatory activity
and the risk of a subsequent cardiovascular event.
Therefore, follow-up for cardiovascular events was
initiated from a landmark at the 12-month visit andcontinued until a cardiovascular outcome or censoring
for mortality, loss to follow up, or study completion.
Baseline pedometer counts and change in pedometercounts were entered into the same model. Model 1 wasadjusted for randomised treatment, body-mass index,
and baseline demographic, biochemical, and clinicalfactors found to signiﬁcantly aﬀect the risk of subsequentcardiovascular events in the NAVIGATOR cohort.17 We
also tested whether individual dietary behaviours andmedication (antihypertensive, aspirin, lipid-lowering)www.thelancet.com Vol 383 March 22, 2014

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status at baseline, factors not previously considered,17 wererelated to cardiovascular events and should therefore be
included in the model. These additional factors were
included in the full model, and a backward selection
process was used to determine association with theoutcome at the level of p=0·05; only antihypertensive
medication status was selected and consequently
included as a covariate in model 1.
Model 2 was adjusted for the same covariates, as well
as change in body-mass index between baseline
and 12 months to investigate the extent to which any
observed association was explained by change tobodyweight status. Model 3 was adjusted for the same
variables as model 2; additionally, backward selection
was again used to assess whether changes to healthstatus and behaviour between baseline and 12 months
were further associated with the cardiovascular event rateand hence potentially confounding results. Occurrenceof unstable angina between baseline and 12 months andchanges between baseline and 12 months in systolicblood pressure, 2 h glucose, estimated glomerular
ﬁltration rate, albumin/creatinine ratio, antihypertensive
use, aspirin use, lipid-lowering agent use (actual lipid
values were not measured at 12 months), and dietary
responses were assessed. Estimated glomerular ﬁltration
rate at 12 months (representing change given baseline
levels were already included) and the occurrence of
unstable angina during the ﬁrst 12 months were further
selected and included in model 3.
To make use of the complete NAVIGATOR cohort,multiple imputation was used. Missing pedometer or
covariate values at baseline or 12 months were imputed
using Markov Chain Monte Carlo and regression
methods. 25% of the cohort had missing pedometer dataat baseline and 45% had missing data at 12 months; lessthan 3% of data were missing for other covariates. Finalestimates reﬂect the combined analysis over ﬁve imputed
datasets and account for the reduction in information
due to missing data. Linearity assumptions and proportional hazards assumptions were checked. No violations
were applicable.
We also undertook interaction analysis to assess
whether associations between change in ambulatory
activity and cardiovascular events were modiﬁed bybaseline level of ambulatory activity, previous history of
cardiovascular disease (myocardial infarction, unstableangina, other forms of coronary heart disease, congestive heart failure, percutaneous coronary intervention,
coronary artery bypass graft surgery, or stroke), sex,
region (Asian vs other), and age.
Adjusted event rates at 5 years were used to show the
relation between change in ambulatory activity andcardiovascular events, using the average covariate value
for adjustment covariates. Adjusted survival curves,using the corrected group prognosis method, wereplotted by quartiles of change. Analysis was two-sided;
p<0·05 was considered signiﬁcant for main eﬀects andwww.thelancet.com Vol 383 March 22, 2014

p<0·1 was considered signiﬁcant for interactions.
Statistical analyses were done with SAS (version 9.2).
To investigate whether imputation aﬀected the results,
the above analysis was repeated for the subset ofparticipants with complete data. Hazard ratios werecompared with those generated from the full
NAVIGATOR cohort. In addition, sensitivity analysis wasundertaken to investigate whether results were aﬀected if
those with a non-fatal cardiovascular event occurring inthe ﬁrst 12 months or those classiﬁed as smokers atbaseline were excluded from the analysis.

Role of the funding source
The NAVIGATOR study was sponsored by Novartis
Pharmaceuticals and was designed by an academic
executive committee in collaboration with the sponsor.
All statistical analyses were done independently bystatisticians at the Duke Clinical Research Institute(Durham, NC, USA). The sponsor of the study had norole in study design, data collection, data analysis, datainterpretation, or writing of the report. The corresponding author had full access to all the data in the
study and had ﬁnal responsibility for the decision tosubmit for publication.

Results
Follow-up data for cardiovascular events were available
for 9018 participants over an average of 5 years after
the 12-month landmark; characteristics including thosewith imputed data, are given in the appendix. Comparedto patients with complete pedometer data at baseline
and 12 months, those with missing pedometer data
across at least one timepoint were more likely to befrom Europe (55·0% [2568 of 4673] for missing data
vs 50·8% [2209 of 4345] for complete data) or North
America (25·4% [1189 of 4673] vs 19·5% [846 of 4345]), a
smoker (11·4% [535 of 4673] vs 10·0% [434 of 4345]), andwere less likely to have a previous history of congestive heart failure (26·5% [1238 of 4673] vs 29·9%[1298 of 4345]). There was no diﬀerence in bloodpressure or other biochemical risk factors, including
lipid and glucose parameters.
The baseline characteristics of those with both baseline
and 12-month data are displayed by category of change intable 1. Baseline levels of ambulatory activity were highest
in those with the greatest decrease in activity at 12 months.
In the cohort as a whole, average pedometer levels weresimilar at baseline (median 5892 [IQR 735–8739]) andfollow-up (6320 [3988–8978]); however, there was substantial inter-individual variation in change (truncatedrange –10 000 to 10 000 steps per day). In total, there
were 531 cardiovascular events during 45 211 personyears of follow-up.
Table 2 shows the hazard ratios for the association of
baseline ambulatory activity and change in ambulatory
activity with cardiovascular events. After adjustment foreach other and measured confounding variables, both

See Online for appendix

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Category 1 (decreaseof more than 1500
steps per day) N=1099

Category 2 (decrease
between 1 and 1500 steps
per day) N=1068

Category 3 (increase
between 0 and 1499 steps
per day) N=1097

Category 4 (increaseof at least 1500 steps
per day) N=1081

Overall N=4345

Characteristics
Age, years

63 (58–68)

64 (58–69)

64 (58–69)

62 (58–68)

63 (58–68)

Women

538 (49·0%)576 (53·9%)569 (51·9%)551 (51·0%)2234 (51·4%)

RegionAsia

129 (11·7%)

70 (6·6%)

74 (6·7%)

91 (8·4%)364 (8·4%)

Europe559 (50·9%)550 (51·5%)562 (51·2%)538 (49·8%)2209 (50·8%)

Latin America

211 (19·2%)

173 (16·2%)

174 (15·9%)221 (20·4%)779 (17·9%)North America

174 (15·8%)238 (22·3%)242 (22·1%)

192 (17·8%)846 (19·5%)

Other

26 (2·4%)

37 (3·5%)

45 (4·1%)

39 (3·6%)147 (3·4%)White

836 (76·1%)

881 (82·5%)906 (82·6%)889 (82·2%)3512 (80·8%)Black

16/ (1·5%)

17 (1·6%)18 (1·6%)

13 (1·2%)

64 (1·5%)

Oriental

136 (12·4%)

75 (7·0%)75 (6·8%)

98 (9·1%)384 (8·8%)

Race

Other
Current smoker

111 (10·1%)

95 (8·9%)98 (8·9%)81 (7·5%)385 (8·9%)105 (9·6%)100 (9·4%)120 (10·9%)109 (10·1%)

434 (10·0%)

Clinical history
Congestive heart failure

40 (3·6%)

48 (4·5%)

42 (3·8%)42 (3·9%)172 (4·0%)Coronary heart disease*298 (27·1%)354 (33·1%)

315 (28·7%)331 (30·6%)1298 (29·9%)364 (8·4%)

Cerebrovascular disease†

92 (8·4%)

85 (8·0%)92 (8·4%)

95 (8·8%)

Pulmonary disease‡

9 (0·8%)19 (1·8%)

9 (0·8%)7 (0·6%)44 (1·0%)

Peripheral artery disease§22 (2·0%)44 (4·1%)

37 (3·4%)30 (2·8%)133 (3·1%)

Chronic obstructive pulmonary disease51 (4·6%)

45 (4·2%)

60 (5·5%)

48 (4·4%)204 (4·7%)

Hypertension

888 (80·8%)850 (79·6%)878 (80·0%)871 (80·6%)3487 (80·3%)

Family history of premature coronary heart disease

162 (14·7%)

176 (16·5%)

174 (15·9%)162 (15·0%)674 (15·5%)

Family history of diabetes

398 (36·2%)392 (36·7%)400 (36·5%)379 (35·1%)

1569 (36·1%)

Clinical features
Body-mass index, kg/m²

28·8 (26·1–32·4)

29·6 (26·7–33·4)

29·6 (26·7–33·1)

29·5 (26·8–32·9)

29·4 (26·6–33·0)

Systolic blood pressure, mm Hg

140 (129–150)

140 (128–150)

140 (129–150)

140 (129–150)

140 (129–150)

Diastolic blood pressure, mm Hg

82 (77–90)

82 (76–90)

82 (76–90)

82 (77–90)

82 (76–90)

Pulse pressure, mm Hg

55 (48–65)

56 (48–65)

56 (48–65)

57 (48–65)

56 (48–65)

Atrial ﬁbrillation or ﬂutter

29 (2·6%)

45 (4·2%)

41 (3·7%)

46 (4·3%)

161 (3·7%)

Laboratory variables
Fasting glucose, mmol/L

6·1 (5·7–6·5)

6·1 (5·7–6·5)

6·1 (5·7–6·4)

6·1 (5·7–6·4)

6·1 (5·7–6·4)

2 h glucose, mmol/L

9·1 (8·4–9·9)

9·1 (8·4–9·9)

9·0 (8·3–9·9)

9·0 (8·3–9·9)

9·0 (8·4–9·9)Total cholesterol, mmol/L

5·39 (4·67–6·15)

5·33 (4·65–6·05)

5·33 (4·69–6·04)

5·40 (4·75–6·13)

5·36 (4·68–6·10)

HDL cholesterol, mmol/L

1·24 (1·06–1·48)

1·23 (1·03–1·47)

1·26 (1·03–1·48)

1·20 (1·01–1·45)

1·24 (1·03–1·47)

LDL cholesterol, mmol/L

3·27 (2·68–3·91)

3·18 (2·56–3·82)

3·15 (2·56–3·86)

3·27 (2·63–3·96)

3·23 (2·61–3·89)

Triglycerides, mmol/L

1·64 (1·20–2·26)

1·68 (1·24–2·37)

1·70 (1·20–2·42)

1·74 (1·24–2·43)

1·69 (1·22–2·36)

Haemoglobin, g/L

146 (138–155)

146 (138–154)

147 (139–155)

146 (138–155)

146 (138–155)

eGRF, mL/min/1·73m²

82·5 (70·5–95·0)

78·2 (68·0–89·9)79·4 (68·4–90·7)

78·7 (67·9–91·9)

79·9 (68·8–92·1)

Urine albumin/creatinine ratio, mg/mmol

0·78 (0·50–1·58)

0·77 (0·49–1·60)

0·79 (0·50–1·47)

0·76 (0·49–1·55)

Sodium, mmol/L

142 (141–144)

0·77 (0·50–1·54)142 (141–144)

142 (141–144)

142 (141–144)

142 (141–144)

Lipid lowering agent

394 (35·9%)449 (42·1%)422 (38·5%)372 (34·4%)1637 (37·7%)

Antihypertensives779 (70·9%)769 (72·1%)781 (71·3%)763 (70·6%)3092 (71·2%)

Aspirin

366 (33·3%)391 (36·6%)401 (36·6%)394 (36·4%)1552 (35·7%)

Clinically insigniﬁcant abnormality

384 (35·5%)402 (38·2%)416 (38·7%)377 (35·3%)1579 (36·9%)

Clinically signiﬁcant abnormality

164 (15·2%)

182 (17·3%)

163 (15·1%)

189 (17·7%)698 (16·3%)810 (74·1%)

757 (71·2%)762 (70·1%)

756 (70·5%)

Medications

Electrocardiogram

Dietary behaviour
Limited total fat

3085 (71·5%)(Continues on next page)1062

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Category 3 (increase
between 0 and 1499 steps
per day) N=1097

Category 4 (increase ofat least 1500 steps perday) N=1081

Overall N=4345

788 (74·1%)787 (72·4%)785 (73·2%)3178 (73·6%)902 (84·9%)918 (84·5%)

911 (84·9%)3650 (84·6%)757 (71·2%)775 (71·3%)785 (73·2%)3129 (72·5%)Category 1 (decrease of
more than 1500 steps
per day) N=1099

Category 2 (decrease
between 1 and 1500 steps
per day) N=1068

Limited saturated fat

818 (74·8%)

Included fruit/vegetable every day

919 (84·1%)

Limited sugar

812 (74·3%)(Continued from previous page)

Limited salt

801 (73·3%)712 (67·0%)748 (68·9%)701 (65·3%)2962 (68·6%)

Limited alcohol (≤2 drinks/day)

963 (88·5%)925 (87·3%)934 (86·1%)

910 (85·0%)3732 (86·7%)9325 (6687–11887)

5778 (3766–8167)

5338 (3386–7806)

5156 (3212–7612)

6245 (4065–9157)

Pedometer
Baseline pedometer countContinuous variables are median (IQR). Categorical variables are n (%). *Myocardial infarction, angina, positive stress test, or coronary revascularisation. †Stroke, transient ischaemic attack. ‡Pulmonary embolism
or deep venous thrombosis. §Limb or foot amputation, intermittent claudication, limb arterial bypass procedure.

Table 1: Baseline patient characteristics by category of change in ambulatory activity level from baseline to 12 month follow-up, reported for the subset of participants with complete
baseline and follow-up databaseline ambulatory activity and change in ambulatory
activity between baseline and 12 months were signiﬁcantly and inversely associated with the risk ofa cardiovascular event. Speciﬁcally, at baseline,
each 2000 step per day increment in ambulatory activity
was associated with a 10% lower cardiovascular event
rate. For change, each 2000 step increase or decrease indaily ambulatory activity from baseline to 12 months was
associated with an additional 8% lower or higher
cardiovascular event rate, respectively. Results were
unaﬀected when further adjusted for change in bodymass index, change in estimated glomerular ﬁltration
rate, and the occurrence of unstable angina between
baseline and 12 months.
Interaction analysis revealed results for change inambulatory activity were not modiﬁed by baseline value(p=0·58), indicating that for each given unit of increasein ambulatory activity, there were similar eﬀects on
cardiovascular risk irrespective of where participants
started at baseline. Furthermore, results were not
modiﬁed by a previous history of cardiovascular disease(p=0·62), sex (p=0·66), age (p=0·14), or region(p=0·72 for Asia vs other). However, the small sample
size from the Asia region resulted in a wide CI for theestimated hazard ratio ([HR] 0·97; 95% CI 0·73–1·28),
therefore the p value for region should be interpretedwith caution.
The ﬁgure shows adjusted estimates of the cardiovascular event rate by change in ambulatory activity as acontinuous variable, bounded by the 5th and 95th
percentile. The adjusted survival estimates representing
the risk of a cardiovascular event by quartile of change inambulatory activity are shown in the appendix.
Results were unaﬀected (less than 3% diﬀerence inhazard ratios) when analyses were repeated on thesubsample with complete pedometer and covariate data(appendix); however, signiﬁcance levels were increased
because of the reduced sample size (HR 0·90; 95% CI
0·81–1·01; p=0·0606 per 2000 steps a day change forthe fully adjusted model). The hazard ratios werewww.thelancet.com Vol 383 March 22, 2014

HR

95% CIp

Model 1Baseline ambulatory activity (2000 step per day increment)*

0·90

0·84–0·96

0·0014

Change in ambulatory activity from baseline to 12 months(per 2000 step per day diﬀerence in change)*

0·92

0·86–0·99

0·0271Model 2
Baseline ambulatory activity (2000 step per day increment)*

0·90

0·84–0·96

0·0017

Change in ambulatory activity from baseline to 12 months(per 2000 step per day diﬀerence in change)*

0·92

0·86–0·99

0·0321Model 3Baseline ambulatory activity (2000 step per day increment)*

0·90

0·84–0·96

0·0021

Change in ambulatory activity from baseline to 12 months(per 2000 step per day diﬀerence in change)*

0·92

0·86–0·99

0·0349*Baseline ambulatory activity and change in ambulatory activity were included in the same model. Model 1: adjusted for
randomised treatment group and the following variables at baseline: body-mass index, age, region (North America,
Europe, Asia, Latin America, other), sex, current smoker status, coronary heart disease composite (previous myocardial
infarction, angina, positive stress test, or coronary revascularisation), cerebrovascular composite (stroke, transientischaemic attack), signiﬁcant abnormal electrocardiogram, insigniﬁcant abnormal ECG, albumin/creatinine ratio,
pulmonary composite (pulmonary embolism or deep venous thrombosis), peripheral artery disease composite (limb orfoot amputation, intermittent claudication, limb arterial bypass procedure), congestive heart failure, chronic obstructive
pulmonary disease, pulse pressure, temporary atrial ﬁbrillation or ﬂutter, sodium, estimated glomerular ﬁltration rate(eGFR), haemoglobin, LDL-cholesterol, and antihypertensive medication use. Model 2: adjusted for the above variables
plus change in body-mass index from baseline to 12-months. Model 3: adjusted for the above variables plus change inbody-mass index, the occurrence of unstable angina between baseline and 12 months and change in eGFR between
baseline and 12 months.

Table 2: Association of baseline and change in daily ambulatory activity with cardiovascular events(composite of cardiovascular mortality, stroke, or myocardial infarction)

similarly unaﬀected if those with a non-fatal cardiovascular event occurring within the ﬁrst 12 months(n=93) or those classiﬁed as smokers at baseline (n=969)
were excluded (appendix).

Discussion
Both baseline ambulatory activity and change inambulatory activity over 12 months were associatedindependently with the risk of a cardiovascular event in
the ensuing 5 years. Speciﬁcally, every 2000 step per day
increment in ambulatory activity at baseline (roughly
equivalent to 20 min a day of moderately-paced walking
activity18) was associated with a 10% lower risk of a1063

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0·08

95% confidence bound (adjusted for model 1)

Estimated 5-year event rate

0·06

0·04

0·02

0
–6000

–4000
–2000
0
2000
4000
Change in ambulatory activity (steps per day)

6000

Figure: Relation between change in ambulatory activity and adjusted 5-year
cardiovascular event rates

Panel: Research in context
Systematic review
We searched PubMed, Medline, and Google Scholar with the search terms “physicalactivity”, “exercise”, “mortality”, and “cardiovascular”. We were unable to identify any
studies that examined the association between objectively assessed physical activity andcardiovascular events. Recent studies have reported meta-analyses of observational
studies looking at the eﬀect of self-reported physical activity and non-vigorous physicalactivity on the risk of cardiovascular disease and mortality.8–10 However, because of thenature of the self-reported instruments used within the included studies, the reviews
were unable to adequately quantify the amount of physical activity needed to gain
speciﬁc beneﬁts. Moreover, the association between change in physical activity andcardiovascular disease has not been investigated in high-risk adults.
Interpretation
In this study involving adults at high risk of type 2 diabetes and cardiovascular disease, every
2000 step per day increment in ambulatory activity at baseline was associated with a 10%
lower risk of a cardiovascular event and each 2000 step per day change from baseline to
12 months was associated with an additional 8% diﬀerence in the cardiovascular event rate.
Results for change remained consistent across men and women, region, age, and baseline
level of activity.

cardiovascular event. Moreover, each 2000 step per daychange from baseline to 12 months was associatedwith an additional 8% diﬀerence in the cardiovascular
event rate. This diﬀerence was unaﬀected when further
adjusted for change in body-mass index and otherpotential confounding factors at 12 months. Results were
not modiﬁed by sex, age, level of baseline activity, or preexisting cardiovascular disease. To our knowledge, this is
the ﬁrst study to investigate the association between daily
ambulatory activity and cardiovascular events in at-risk
adults (panel).
Walking is known to be the most common andpreferred choice of physical activity,19–21 and behaviourchange programmes aimed at increasing total daily
1064

ambulatory activity through pedometer use have beenhighly eﬀective across a broad range of groups, including
those with impaired glucose tolerance.22,23 However, theeﬀect of changing overall daily ambulatory activity levels
on cardiovascular events has not been elucidated bycontrolled intervention studies. This observational study
therefore extends previous research by suggesting thatbaseline ambulatory activity and change in ambulatory
activity are both important and independent determinantsof future cardiovascular disease in high-risk adults.
Moreover, the lack of an interaction between the association of baseline and change in ambulatory activity
with future cardiovascular events suggests that therelative beneﬁt of increased ambulatory activity, ordeleterious eﬀect of decreased ambulatory activity,
remains consistent irrespective of the starting level.
These ﬁndings support both the promotion of increased
ambulatory activity, and the avoidance of decreased
ambulatory activity irrespective of the starting level, as
important targets in the prevention of chronic disease.
The relation between change in ambulatory activity
and cardiovascular events remained signiﬁcant after
adjustment for both baseline body-mass index andchange in body-mass index. Previous smaller observational studies using objective measures of ambulatory
activity or total physical activity have provided equivocal
evidence on whether the relation between physicalactivity and cardiometabolic risk factors are mediatedthrough adiposity.24–27 By contrast, large observational
studies that have shown a strong inverse dose-response
relation between objectively assessed cardiorespiratoryﬁtness and cardiovascular events after adjustment forbody-mass index.28,29 However, cardiorespiratory ﬁtness isdetermined by multiple factors, not just physical activity.
Our study therefore provides novel evidence for the
cardioprotective role of daily ambulatory activity,
independent of bodyweight status. This observational
ﬁnding is strengthened by several biological mechanismsthat have consistently been linked to increased physicalactivity, including improved lipid metabolism, change in
low-density lipoprotein particle size, increased tissue
plasminogen activator activity, and decreased coronary
artery calcium.30
This study has several strengths. First, the analysis was
adjusted for a comprehensive list of possible confounding
variables, both at baseline and 12 months, shown to berelated to cardiovascular events in this cohort. Second,
the sample comprised a large international population
with impaired glucose tolerance and at high cardiovascular risk, making the results broadly generalisable todiabetes and cardiovascular disease prevention programmes globally. Third, the large study cohort wasrecruited over a relatively short time frame (2 years),
minimising the possibility of temporal factors aﬀecting
the results. Finally, in the absence of randomised
controlled trials assessing the eﬀect of physical activity
on morbidity or mortality outcomes, this study represents
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Articles

an advance in quantifying the impact of daily ambulatory
activity on cardiovascular events in a high-risk population.
The main limitation was the large amount of missing
pedometer data at baseline and 12 months. This wasaddressed using rigorous multiple imputation techniques which allowed use of adjustment variables fromthe full dataset. Sensitivity analysis also revealed no
meaningful diﬀerence between estimates generated
from the complete case dataset. Nonetheless, imputation
might not completely account for missing data, which
potentially limits generalisability. Limitations also exist
in the use of pedometers; participants were not blind topedometer output and were asked to record their daily
ambulatory activity in a log book and physical activity
intensity, mode, and wear-time were not assessed. Manyof these limitations could have aﬀected recorded levelsof ambulatory activity. For example, higher ambulatory
activity might indicate greater measurement reactivity
due to self-recording daily step counts or better compliance to the measurement protocol through greater
wear time. This would act to increase inter-individual or
intra-individual variation as well as introducing thepossibility that characteristics related to pedometer use
beyond total ambulatory activity were confounding theresults. Furthermore, cardiorespiratory ﬁtness was notassessed; however, other studies have shown thatchanges in habitual physical activity and cardiorespiratory ﬁtness are weakly correlated and independently associated with metabolic health.25 In view of thehigh-risk nature of the cohort, the results are also not
generalisable to the general population. Finally, becauseof the observational design, we were unable to establish
causation between ambulatory activity and cardiovascular disease. Unmeasured or imprecisely measured
lifestyle or related factors could have acted to confoundassociations. Similarly, the design cannot fully negate
the possibility of reverse causation. However, the gradedassociation between change in ambulatory activity andcardiovascular risk, the fact that the analysis wascontrolled for a comprehensive list of possible confounding variables, and biological plausibility all provide
indirect support for the importance of physical activity
in the promotion of long-term cardiovascular health.
This study provides novel evidence that both the overalllevel of daily ambulatory activity and change inambulatory activity over 12 months display a gradedinverse association with the risk of cardiovascular diseasein high-risk individuals with impaired glucose tolerance,even after adjustment for multiple confounding variables
and body-mass index. In the absence of randomised
controlled studies assessing the eﬀect of physical activity
on morbidity or mortality outcomes, our ﬁndings
strengthen the evidence underpinning the importance ofphysical activity in the promotion of cardiovascular
health and have important implications for public healthrecommendations and the prevention of chronic disease.
Implications extend to the importance of preventing a
www.thelancet.com Vol 383 March 22, 2014

decline in physical activity levels in middle-aged andelderly populations.
Contributors
SMH, WEK, TY, LT, KMH, CWB, JT, and MJD were responsible for the
study concept and design. LT and PJS had access to all the data andundertook the statistical analysis. TY drafted the manuscript. All authors
contributed to the content and critical revision of the manuscript.
Conﬂicts of interest
SMH is a member of the NAVIGATOR executive committee. CWB is paid
an honorarium for her role as the Editor of the Journal of Nutrition in
Geriatrics and Gerontology and as a contributing editor to the Duke
Health Newsletter. RMC has received consulting fees from Bayer,
Bristol-Myers Squibb, CV Sight LLC, DSI-Lilly, Gambro, theHeart.org,
Janssen, Kowa, Novartis, Pﬁzer, Regeneron, and Roche, and his institution
has received research grants from Bristol-Myers Squibb, Novartis,
Amylin, Merck, Schering-Plough, Scios, Johnson & Johnson, and Eli Lilly.
RRH has received research support from Amylin, Bayer, Merck, andNovartis; attended advisory boards with Amylin, Lilly, Merck, Novartis,
and Novo Nordisk; and given lectures supported by Bayer, Lilly, Merck,and Novo Nordisk. MAB has received research support from Novartis andBayer, and her department has received research funding from Merck,
Amylin, Lilly, and BMS. JT has received research support from
AstraZeneca, Merck Sharp & Dohme, Novartis, and Servier, and has acted
as a consultant, advisory board member, or speaker for Novartis, Novo
Nordisk, Sanoﬁ-Aventis, Lilly, Merck Serono, and Merck Sharp & Dohme.
MJD has acted as a consultant, advisory board member, and speaker forNovartis, Novo Nordisk, Sanoﬁ-Aventis, Lilly, Merck Sharp & Dohme,
Boehringer Ingelheim, and Roche, and her department has received
research grants from Novartis, Novo Nordisk, Sanoﬁ-Aventis, Lilly, Pﬁzer,
Merck Sharp & Dohme, Johnson & Johnson, and GlaxoSmithKline.
The other authors declare that they have no conﬂicts of interest.
Acknowledgments
TY and MD are supported by the NIHR Leicester-Loughborough Diet,
Lifestyle, and Physical Activity Biomedical Research Unit, Leicester, UK.
References
1
Tuomilehto J, Lindström J, Eriksson JG, et al, and the Finnish
Diabetes Prevention Study Group. Prevention of type 2 diabetes
mellitus by changes in lifestyle among subjects with impaired
glucose tolerance. N Engl J Med 2001; 344: 1343–50.
2Knowler WC, Barrett-Connor E, Fowler SE, et al, and the Diabetes
Prevention Program Research Group. Reduction in the incidence oftype 2 diabetes with lifestyle intervention or metformin.
N Engl J Med 2002; 346: 393–403.
3
Gillies CL, Lambert PC, Abrams KR, et al. Diﬀerent strategies forscreening and prevention of type 2 diabetes in adults: costeﬀectiveness analysis. BMJ 2008; 336: 1180–85.
4Herman WH, Hoerger TJ, Brandle M, et al, and the Diabetes
Prevention Program Research Group. The cost-eﬀectiveness oflifestyle modiﬁcation or metformin in preventing type 2 diabetes inadults with impaired glucose tolerance. Ann Intern Med 2005;
142: 323–32.
5
Ali MK, Echouﬀo-Tcheugui J, Williamson DF. How eﬀective werelifestyle interventions in real-world settings that were modeled on
the Diabetes Prevention Program? Health Aﬀ (Millwood) 2012;
31: 67–75.
6
Schwarz PE, Greaves CJ, Lindström J, Yates T, Davies MJ.
Nonpharmacological interventions for the prevention oftype 2 diabetes mellitus. Nat Rev Endocrinol 2012; 8: 363–73.
7
van Dieren S, Beulens JW, van der Schouw YT, Grobbee DE, Neal B.
The global burden of diabetes and its complications: an emerging
pandemic. Eur J Cardiovasc Prev Rehabil 2010; 17 (suppl 1): S3–8.
8
Li J, Siegrist J. Physical activity and risk of cardiovasculardisease–a meta-analysis of prospective cohort studies.
Int J Environ Res Public Health 2012; 9: 391–407.
9
Woodcock J, Franco OH, Orsini N, Roberts I. Non-vigorous physicalactivity and all-cause mortality: systematic review and meta-analysis
of cohort studies. Int J Epidemiol 2011; 40: 121–38.
10 Samitz G, Egger M, Zwahlen M. Domains of physical activity andall-cause mortality: systematic review and dose-response
meta-analysis of cohort studies. Int J Epidemiol 2011; 40: 1382–400.

1065

Articles

11

12
13

14

15

16

17

18

19

20

21

1066

Kodama S, Saito K, Tanaka S, et al. Cardiorespiratory ﬁtness as aquantitative predictor of all-cause mortality and cardiovascular
events in healthy men and women: a meta-analysis. JAMA 2009;
301: 2024–35.
Shephard RJ. Limits to the measurement of habitual physicalactivity by questionnaires. Br J Sports Med 2003; 37: 197–206.
Laukkanen JA, Laaksonen D, Lakka TA, et al. Determinants ofcardiorespiratory ﬁtness in men aged 42 to 60 years with andwithout cardiovascular disease. Am J Cardiol 2009; 103: 1598–604.
Caliﬀ RM, Boolell M, Haﬀner SM, et al, and the NAVIGATOR Study
Group. Prevention of diabetes and cardiovascular disease in patientswith impaired glucose tolerance: rationale and design of the
Nateglinide And Valsartan in Impaired Glucose Tolerance Outcomes
Research (NAVIGATOR) Trial. Am Heart J 2008; 156: 623–32.
Holman RR, Haﬀner SM, McMurray JJ, et al, and the NAVIGATOR
Study Group. Eﬀect of nateglinide on the incidence of diabetes andcardiovascular events. N Engl J Med 2010; 362: 1463–76.
McMurray JJ, Holman RR, Haﬀner SM, et al, and the NAVIGATOR
Study Group. Eﬀect of valsartan on the incidence of diabetes andcardiovascular events. N Engl J Med 2010; 362: 1477–90.
Preiss D, Thomas LE, Sun JL, et al. Predictors of cardiovascular
events in a contemporary population with impaired glucose
tolerance: an observational analysis of the Nateglinide and Valsartan
in Impaired Glucose Tolerance Outcomes Research (NAVIGATOR)
trial. BMJ Open 2012; 30: e001925.
Tudor-Locke C, Bassett DR Jr. How many steps/day are enough?
Preliminary pedometer indices for public health. Sports Med 2004;
34: 1–8.
Crespo CJ, Keteyian SJ, Heath GW, Sempos CT. Leisure-time physicalactivity among US adults. Results from the Third National Health andNutrition Examination Survey. Arch Intern Med 1996; 156: 93–98.
NHS Information Centre. Health survey for England—2008:
physical activity and ﬁtness. http://www.hscic.gov.uk/catalogue/
PUB00430 (accessed Nov 20, 2013).
Laaksonen DE, Lindström J, Lakka TA, et al, and the Finnish
diabetes prevention study. Physical activity in the prevention oftype 2 diabetes: the Finnish diabetes prevention study.
Diabetes 2005; 54: 158–65.

22

23

24

25

26

27

28

29

30

Yates T, Davies M, Gorely T, Bull F, Khunti K. Eﬀectiveness of apragmatic education program designed to promote walking activity
in individuals with impaired glucose tolerance: a randomized
controlled trial. Diabetes Care 2009; 32: 1404–10.
Bravata DM, Smith-Spangler C, Sundaram V, et al. Using
pedometers to increase physical activity and improve health:a systematic review. JAMA 2007; 298: 2296–304.
Helmerhorst HJ, Wijndaele K, Brage S, Wareham NJ, Ekelund U.
Objectively measured sedentary time may predict insulin resistanceindependent of moderate- and vigorous-intensity physical activity.
Diabetes 2009; 58: 1776–79.
Ekelund U, Franks PW, Sharp S, Brage S, Wareham NJ. Increase inphysical activity energy expenditure is associated with reduced
metabolic risk independent of change in fatness and ﬁtness.
Diabetes Care 2007; 30: 2101–06.
Dwyer T, Ponsonby AL, Ukoumunne OC, et al. Association ofchange in daily step count over ﬁve years with insulin sensitivity
and adiposity: population based cohort study. BMJ 2011; 342: c7249.
Fretts AM, Howard BV, McKnight B, et al. Modest levels of physicalactivity are associated with a lower incidence of diabetes in a
population with a high rate of obesity: the strong heart family study.
Diabetes Care 2012; 35: 1743–45.
Laukkanen JA, Rauramaa R, Salonen JT, Kurl S. The predictive
value of cardiorespiratory ﬁtness combined with coronary risk
evaluation and the risk of cardiovascular and all-cause death.
J Intern Med 2007; 262: 263–72.
Stevens J, Cai J, Evenson KR, Thomas R. Fitness and fatness as
predictors of mortality from all causes and from cardiovasculardisease in men and women in the lipid research clinics study.
Am J Epidemiol 2002; 156: 832–41.
Ahmed HM, Blaha MJ, Nasir K, Rivera JJ, Blumenthal RS. Eﬀects
of physical activity on cardiovascular disease. Am J Cardiol 2012;
109: 288–95.

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