Daily steps and all-cause mortality: a meta-analysis of 15 international cohorts

Abstract

Background:
Although 10 000 steps per day is widely promoted to have health benefits, there is little evidence to support this recommendation. We aimed to determine the association between number of steps per day and stepping rate with all-cause mortality.

Methods:
In this meta-analysis, we identified studies investigating the effect of daily step count on all-cause mortality in adults (aged ≥18 years), via a previously published systematic review and expert knowledge of the field. We asked participating study investigators to process their participant-level data following a standardised protocol. The primary outcome was all-cause mortality collected from death certificates and country registries. We analysed the dose-response association of steps per day and stepping rate with all-cause mortality. We did Cox proportional hazards regression analyses using study-specific quartiles of steps per day and calculated hazard ratios (HRs) with inverse-variance weighted random effects models.

Findings:
We identified 15 studies, of which seven were published and eight were unpublished, with study start dates between 1999 and 2018. The total sample included 47 471 adults, among whom there were 3013 deaths (10·1 per 1000 participant-years) over a median follow-up of 7·1 years ([IQR 4·3-9·9]; total sum of follow-up across studies was 297 837 person-years). Quartile median steps per day were 3553 for quartile 1, 5801 for quartile 2, 7842 for quartile 3, and 10 901 for quartile 4. Compared with the lowest quartile, the adjusted HR for all-cause mortality was 0·60 (95% CI 0·51-0·71) for quartile 2, 0·55 (0·49-0·62) for quartile 3, and 0·47 (0·39-0·57) for quartile 4. Restricted cubic splines showed progressively decreasing risk of mortality among adults aged 60 years and older with increasing number of steps per day until 6000-8000 steps per day and among adults younger than 60 years until 8000-10 000 steps per day. Adjusting for number of steps per day, comparing quartile 1 with quartile 4, the association between higher stepping rates and mortality was attenuated but remained significant for a peak of 30 min (HR 0·67 [95% CI 0·56-0·83]) and a peak of 60 min (0·67 [0·50-0·90]), but not significant for time (min per day) spent walking at 40 steps per min or faster (1·12 [0·96-1·32]) and 100 steps per min or faster (0·86 [0·58-1·28]).

Interpretation:
Taking more steps per day was associated with a progressively lower risk of all-cause mortality, up to a level that varied by age. The findings from this meta-analysis can be used to inform step guidelines for public health promotion of physical activity.

Funding:
US Centers for Disease Control and Prevention.

Full text

Articles
www.thelancet.com/public-health Vol 7 March 2022
e219
Daily steps and all-cause mortality: a meta-analysis of
15 international cohorts
Amanda E Paluch, Shivangi Bajpai, David R Bassett, Mercedes R Carnethon, Ulf Ekelund, Kelly R Evenson, Deborah A Galuska, Barbara J Jefferis,
William E Kraus, I-Min Lee, Charles E Matthews, John D Omura, Alpa V Patel, Carl F Pieper, Erika Rees-Punia, Dhayana Dallmeier, Jochen Klenk,
Peter H Whincup, Erin E Dooley, Kelley Pettee Gabriel, Priya Palta, Lisa A Pompeii, Ariel Chernofsky, Martin G Larson, Ramachandran S Vasan,
Nicole Spartano, Marcel Ballin, Peter Nordström, Anna Nordström, Sigmund A Anderssen, Bjørge H Hansen, Jennifer A Cochrane, Terence Dwyer,
Jing Wang, Luigi Ferrucci, Fangyu Liu, Jennifer Schrack, Jacek Urbanek, Pedro F Saint-Maurice, Naofumi Yamamoto, Yutaka Yoshitake,
Robert L Newton Jr, Shengping Yang, Eric J Shiroma, Janet E Fulton, on behalf of The Steps for Health Collaborative
Summary
Background Although 10 000 steps per day is widely promoted to have health benefits, there is little evidence to support
this recommendation. We aimed to determine the association between number of steps per day and stepping rate
with all-cause mortality.
Methods In this meta-analysis, we identified studies investigating the eect of daily step count on all-cause mortality
in adults (aged ≥18 years), via a previously published systematic review and expert knowledge of the field. We asked
participating study investigators to process their participant-level data following a standardised protocol. The primary
outcome was all-cause mortality collected from death certificates and country registries. We analysed the dose–
response association of steps per day and stepping rate with all-cause mortality. We did Cox proportional hazards
regression analyses using study-specific quartiles of steps per day and calculated hazard ratios (HRs) with inverse-
variance weighted random eects models.
Findings We identified 15 studies, of which seven were published and eight were unpublished, with study start dates
between 1999 and 2018. The total sample included 47 471 adults, among whom there were 3013 deaths (10·1 per
1000 participant-years) over a median follow-up of 7·1 years ([IQR 4·3–9·9]; total sum of follow-up across studies was
297 837 person-years). Quartile median steps per day were 3553 for quartile 1, 5801 for quartile 2, 7842 for quartile 3,
and 10 901 for quartile 4. Compared with the lowest quartile, the adjusted HR for all-cause mortality was 0·60 (95% CI
0·51–0·71) for quartile 2, 0·55 (0·49–0·62) for quartile 3, and 0·47 (0·39–0·57) for quartile 4. Restricted cubic splines
showed progressively decreasing risk of mortality among adults aged 60 years and older with increasing number of
steps per day until 6000–8000 steps per day and among adults younger than 60 years until 8000–10 000 steps per day.
Adjusting for number of steps per day, comparing quartile 1 with quartile 4, the association between higher stepping
rates and mortality was attenuated but remained significant for a peak of 30 min (HR 0·67 [95% CI 0·56–0·83]) and
a peak of 60 min (0·67 [0·50–0·90]), but not significant for time (min per day) spent walking at 40 steps per min or
faster (1·12 [0·96–1·32]) and 100 steps per min or faster (0·86 [0·58–1·28]).
Interpretation Taking more steps per day was associated with a progressively lower risk of all-cause mortality, up to a
level that varied by age. The findings from this meta-analysis can be used to inform step guidelines for public health
promotion of physical activity.
Funding US Centers for Disease Control and Prevention.
Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND
4.0 license.
Introduction
Physical activity can reduce morbidity and mortality due
to multiple chronic conditions, including cardiovascular
disease, type 2 diabetes, and several cancers, and is
associated with better quality of life.1,2 The number of
steps acquired per day is a simple measure of physical
activity. Monitoring daily steps is more feasible than
ever for the general public as fitness trackers and mobile
devices have become increasingly popular.3,4 Although
the goal of 10 000 steps per day is widely promoted as
being optimal for general health, it is not based on
evidence, but instead originates from a marketing
campaign in Japan.5 Expert committees from the WHO
2020 Physical Activity Guidelines and US 2018 Physical
Activity Guidelines identified a gap in research on
the dose–response association between volume and
intensity of physical activity and health outcomes,
including physical activity measured by step volume
and rate.1,2
The optimal number of steps needed to reduce the
risk of mortality might be aected by characteristics
such as age or sex. Walking volume and pace decrease
Lancet Public Health 2022;
7: e219–28
See Comment page e200
Department of Kinesiology and
Institute for Applied Life
Sciences, University of
Massachusetts Amherst,
Amherst, MA, USA
(A E Paluch PhD, S Bajpai MS);
Department Kinesiology,
Recreation, and Sport Studies,
University of Tennessee,
Knoxville, TN, USA
(Prof D R Bassett PhD);
Department of Preventive
Medicine, Northwestern
University Feinberg School of
Medicine, Chicago, IL, USA
(Prof M R Carnethon PhD);
Department of Sport Medicine,
Norwegian School of Sport
Sciences (Prof U Ekelund PhD,
Prof S A Anderssen PhD,
Prof B H Hansen PhD) and
Department of Chronic
Diseases and Ageing
(Prof U Ekelund PhD),
Norwegian Institute of Public
Health, Oslo, Norway;
Department of Epidemiology,
Gillings School of Global Public
Health, University of North
Carolina Chapel Hill, Chapel Hill,
NC, USA (Prof K R Evenson PhD);
Division of Nutrition, Physical
Activity, and Obesity, National
Center for Chronic Disease
Prevention and Health
Promotion, Centers for Disease
Control and Prevention,
Atlanta, GA, USA
(D A Galuska PhD, J D Omura MD,
J E Fulton PhD); Department of
Primary Care and Population
Health, UCL Medical School,
London, UK (B J Jefferis PhD);
Duke Molecular Physiology
Institute and Division of
Cardiology, Department of
Medicine, Duke University,
Durham, NC, USA
(Prof W E Kraus MD); Brigham
and Women’s Hospital, Harvard
Medical School, Boston MA,
USA (Prof I-M Lee ScD);

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Department of Epidemiology,
Harvard T H Chan School of
Public Health, Boston, MA
(Prof I-M Lee); Division of
Cancer Epidemiology and
Genetics, National Cancer
Institute, Rockville, MD, USA
(C E Matthews PhD,
P F Saint-Maurice PhD);
Department of Population
Science, American Cancer
Society, Atlanta, GA, USA
(A V Patel PhD,
E Rees-Punia PhD); Department
of Biostatistics and
Bioinformatics, Duke
University Medical Center,
Durham, NC (C F Pieper DrPH);
Agaplesion Bethesda Clinic,
Research Unit on Ageing, Ulm,
Germany (D Dallmeier PhD);
Department of Epidemiology
(D Dallmeier PhD,
Prof R S Vasan MD) and
Department of Biostatistics
(A Chernofsky MS,
M G Larson PhD), Boston
University School of Public
Health, Boston, MA, USA;
Institute of Epidemiology and
Medical Biometry, Ulm
University, Ulm, Germany
(Prof J Klenk PhD); Department
of Clinical Gerontology, Robert
Bosch Hospital, Stuttgart,
Germany (Prof J Klenk);
IB University of Applied Health
and Social Sciences, Stuttgart,
Germany (Prof J Klenk);
Population Health Research
Institute, St George’s,
University of London, London,
UK (Prof P H Whincup PhD);
Department of Epidemiology,
University of Alabama at
Birmingham, Birmingham, AL,
USA (E E Dooley PhD,
Prof K Pettee Gabriel PhD);
Departments of Medicine and
Epidemiology, Columbia
University Irving Medical
Center, New York, NY, USA
(P Palta PhD); Department of
Pediatrics, Center for
Epidemiology and Population
Health, Baylor College of
Medicine, Houston, TX, USA
(Prof L A Pompeii PhD);
Department of Endocrinology,
Diabetes, Nutrition and Weight
Management (N Spartano PhD)
and Department of Medicine
(Prof R S Vasan), Boston
University School of Medicine,
Boston, MA, USA; Department
of Community Medicine and
Rehabilitation, Unit of Geriatric
Medicine (M Ballin MSc,
Prof P Nordström PhD) and
Department of Public Health
and Clinical Medicine, Section
with age and might dier by sex; hence, the distribution
of steps diers in younger and older adults and by sex.6,7
Findings from large prospective studies have shown
mortality risk levels o for older women (aged ≥62 years)
at 7500 steps per day5 and among a nationally rep-
resentative sample of US and Norwegian adults (aged
≥40 years) at approximately 8000–12 000 steps per day.6
Several observational studies have shown stepping rate,
a marker of intensity, is inversely associated with
mortality; however, when adjusted for volume of steps
per day, step rate was no longer associated with
mortality.5,6,8 A meta-analysis observed a linear asso-
ciation between step volume and mortality from
seven studies, observing large heterogeneity among
studies and did not report associations by age, sex, or
stepping rate.9
Here, we aimed to complete a meta-analysis on steps per
day and mortality, addressing the limitations of previous
studies. We aimed to include a larger sample of studies
than previous meta-analyses and to collect data across age
groups and by sex to generate robust evidence to inform a
daily step count guideline. Our primary objective was to
assess the dose–response association between steps per
day and all-cause mortality and determine whether this
association varied by age and sex. A secondary objective
was to assess the association between stepping rate and
all-cause mortality. We hypothesised that a dose–response
association exists between steps per day and mortality and
that the association would dier between younger and
older adults.
Methods
Search strategy and selection criteria
This meta-analysis was completed in association with
The Steps for Health Collaborative, which is an inter-
national consortium that was formed to determine the
association between device-measured volume and rate
of steps and prospective health outcomes among adults.
Two strategies were used to identify studies for this
meta-analysis. First, we identified studies through a
systematic review of daily step count and associations
with all-cause mortality, cardiovascular disease, and
dysgly caemia, the findings of which have been published
previously.10 Briefly, we searched MEDLINE, Embase,
CINAHL, and Cochrane Library databases for pub-
lications in English from database inception to
Aug 1, 2019. Search terms were related to daily step count
measured by pedometer or accelerometer and to
mor tality, cardio vascular disease, and dysglycaemia.
Eligibility criteria included longitudinal design, adult
participants (aged ≥18 years), and non-patient popu-
lations, and that the study reported an association
between daily step counts and mortality. The previous
systematic review was registered with PROSPERO
Research in context
Evidence before this study
No evidence-based public health guidelines exist that
recommend a specific number of steps per day for health
benefits. We previously published a systematic review of the
literature of daily steps and associations with all-cause
mortality, cardiovascular disease, and dysglycaemia. Findings
from prospective studies show mortality risk plateaus for older
women (aged ≥62 years) at 7500 steps per day and among
nationally representative samples of US and Norwegian adults
at approximately 8000–12 000 steps per day. Observational
studies have shown that stepping rate, a marker of intensity,
is inversely associated with mortality; however, when adjusted
for volume of steps per day, stepping rate is no longer
significantly associated with mortality. A meta-analysis that
used the effect estimates directly reported by seven
publications found a linear association between step volume
and mortality, observing large heterogeneity among studies
and did not report associations by age, sex, or stepping rate.
The Steps for Health Collaborative is an international
consortium formed to determine the prospective association
between device-measured step volume and rate with health
outcomes, including mortality.
Added value of this study
This meta-analysis of 15 prospective cohort studies from Asia,
Australia, Europe, and North America (including 47 471 adults
and 3013 deaths) provides evidence-based thresholds for the
optimum number of steps per day associated with reduced risk
of all-cause mortality. Each cohort study completed a
standardised statistical analysis created by The Steps for Health
Collaborative and these results were then meta-analysed.
Compared with adults in the lowest steps per day quartile,
adults in the highest steps per day quartile had a
40% to 53% lower risk of mortality. Taking more steps per day
was associated with a progressively lower risk of all-cause
mortality, up to a level that was similar by sex but varied by age.
There was progressively lower risk of mortality among adults
aged 60 years and older until about 6000–8000 steps per day
and among adults younger than 60 years until about
8000–10 000 steps per day. We found inconsistent evidence
that step intensity was associated with risk of mortality beyond
total volume of steps.
Implications of all the available evidence
Number of daily steps is a simple and feasible measure for
monitoring and promoting physical activity globally as fitness
trackers and mobile devices increase in popularity. Our findings
suggest mortality benefits, particularly for older adults, can
occur at levels less than the popular reference value of
10 000 steps per day. The findings from this meta-analysis can
be used to inform step guidelines for public health promotion
of physical activity.

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of Sustainable Health (M Ballin,
A Nordström PhD), Umeå
University, Umeå, Sweden;
School of Sport Sciences, UiT
The Arctic University of
Norway, Tromsø, Norway
(A Nordström PhD);
Department of Sport Science
and Physical Education,
University of Agder, Norway
(Prof B H Hansen PhD); Menzies
Institute for Medical Research,
University of Tasmania,
Hobart, TAS, Australia
(J A Cochrane BA,
Prof T Dwyer MD); Nuffield
Department of Women’s and
Reproductive Health,
University of Oxford, Oxford,
UK (Prof T Dwyer); Murdoch
Children’s Research Institute,
Melbourne, VIC, Australia
(Prof T Dwyer, J Wang, PhD);
Intramural Research Program
(L Ferrucci PhD) and Laboratory
of Epidemiology and
Population Sciences
(E J Shiroma ScD), National
Institute on Aging, Baltimore,
MD, USA; Department of
Epidemiology (F Liu MHS,
J Schrack PhD), Center on Aging
and Health (J Schrack PhD,
J Urbanek PhD), and Division of
Geriatric Medicine and
Gerontology, Department of
Medicine (J Urbanek, PhD),
Johns Hopkins School of
Medicine, Baltimore, MD, USA;
Faculty of Collaborative
Regional Innovation, Ehime
University, Matsuyama, Ehime,
Japan (N Yamamoto PhD);
Institute for Pacific Rim
Studies, Meio University, Nago,
Okinawa, Japan
(Y Yoshitake PhD); Pennington
Biomedical Research Center,
Baton Rouge, LA, USA
(R L Newton Jr PhD, S Yang PhD)
Correspondence to:
Dr Amanda E Paluch,
Department of Kinesiology,
University of Massachusetts
Amherst, Amherst,
MA 01003, USA
apaluch@umass.edu
See Online for appendix
(CRD42020142656).10 Five studies were identified through
this systematic review, a number that was deemed too
few for a meta-analysis. Therefore, we used a second
strategy to identify additional studies for the current
meta-analysis.
Additional studies were identified through Colla-
borative members’ awareness of ongoing and unpub-
lished studies measuring steps and mortality. These
studies were also required to meet the inclusion criteria
stipulated in the previous systematic review. The
investigators of studies found to be eligible were
approached by AEP to ask whether they would participate
in this meta-analysis.
We used the Newcastle Ottawa quality assessment
scale to assess the methodological quality of each study.11
Risk of bias assessments were done inde pendently by
two reviewers (AEP and SB), and disagreements were
resolved by consensus between the two reviewers.
Individual study-level data processing
We asked the investigators of participating studies to
process their participant-level data according to a
standardised protocol developed by The Steps for Health
Collaborative to limit heterogeneity in our analyses
across studies (appendix pp 34–60). In each study,
participants wore a step counting device for 1 week,
considered baseline in this study, and then were
followed up for death from any cause. Investigators
were asked to quantify step volume as steps per day,
averaged over all days for which step data were collected.
Studies that quantified stepping rate used one or more
of four measures reported in previous studies on steps
and mortality.5,6,8 We asked the investigators of each
study to calculate peak 30 min and 60 min stepping
rates as the highest number of steps accumulated over
30 min and 60 min periods (not necessarily con-
secutively) throughout each day and as a mean over all
days. We also asked study investigators to calculate
stepping rate as the time (in min) spent walking at
40 steps per min or faster (defined as intentional
walking) and 100 steps per min or faster (defined as a
moderate rate walking pace).12 Our primary outcome
was all-cause mortality collected from death certificates
and country registries.
Individual study-level analyses
The Steps for Health Collaborative established a
standardised analytical plan for study investigators to
complete. Investigators of participating studies were
asked to categorise step volume into quartiles across the
study population and examine associations with all-cause
mortality (referenced against the lowest quartile) using
Cox proportional hazards regression (satisfying
proportional hazards assumptions) producing hazard
ratios (HRs) and 95% CIs. Investigators of participating
studies completed models for each study’s overall
sample, by age group and by sex where applicable. Age
was grouped into younger (<60 years) and older
(≥60 years) groups on the basis of WHO’s definition of
older people from the 2020 Decade of Healthy Ageing
Baseline Report.13 Investigators of participating studies
constructed two models: model 1 adjusted for age and sex
and model 2, the final model, adjusted for socio-
demographic factors, lifestyle behaviours, and health
indicators that are known to aect the association
between steps per day and all-cause mortality. Model 2
also adjusted for age, sex, race and ethnicity, education or
income, body-mass index, and study-specific covariates
for chronic disease (eg, diabetes, blood pressure, history
of cardiovascular disease or cancer, and medications),
self-rated health or functional status, accelerometer wear
time, and lifestyle factors (eg, smoking and alcohol;
appendix p 5). Investigators of participating studies were
asked to complete sensitivity analysis excluding deaths
within the first 2 years of follow-up.
For studies with stepping rate measures, we used the
same analytical approach for model 1 and model 2.
Model 3 adjusted for all covariates from model 2 plus
steps per day using the residual method in which
stepping rate was regressed on steps per day and the
resulting stepping rate residuals and steps per day were
independent variables in the model.5,14
Data analysis
We summed the total number of participants, deaths,
and person-years of follow-up across all studies. For the
total sample, we calculated median (IQR) steps per day
by quartile from the medians of each individual study.
We calculated risk dierences and 95% CIs as com-
parison quartile minus reference quartile (ie, the quartile
with the lowest number of steps per day). We assessed
dierences in median steps per day using the Wilcoxon
rank-sum test. We meta-analysed eect esti mates
using inverse-variance weighted random-eects models,
calculating pooled HRs and 95% CIs. The final adjusted
model (model 2) was the primary model. Because of the
known associations of age and sex with physical activity,1
we did a priori stratified analyses by age and sex for the
associations between mortality and steps per day. We
calculated I² heterogeneity values, which were considered
to be low (<25%), moderate (25–75%), or high (>75%).15
We assessed presence of study bias using funnel plots
comparing study HRs against SEs and Egger’s test for
funnel plot symmetry.16
We used log-transformed HRs from model 2 to generate
restricted cubic spline models using knots at the 25th,
50th, and 75th percentiles of total steps per day.17 We used
the Wald test to test for non-linearity by examining the
null hypothesis that the regression coecient of the spline
transformation was equal to zero.18 We examined model fit
using de-correlated residuals versus exposure plots and
the coecient of determination.18 We assessed age (aged
<60 years vs ≥60 years) and sex subgroup dierences in
curves using multiplicative interaction terms. We excluded

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one study19 from all spline analyses because step data were
processed with a low frequency extension filter, which
significantly inflates steps per day.20
We also did a series of sensitivity analyses. We
investigated the potential for reverse causation by
excluding participants at the study level who died within
the first 2 years of follow-up. We stratified studies by
average length of follow-up and compared those with less
than 6 years of follow-up and 6 years or longer of follow-
up.21 We compared studies stratified by publication status
(published vs unpublished). We did an analysis using the
leave-one-out approach, excluding one study at a time, to
ensure that the results were not simply due to one large
study or a study with an extreme result. Furthermore, we
used a leave one-device-out approach, in which we
excluded all studies that used a specific step-monitoring
device, to determine if the dose–response estimates of
steps were aected by any single device. We also
reanalysed our data using a fixed-eects inverse-variance
method.
p values of less than 0·05 were considered to be
statistically significant. We did meta-analyses using R
(version 4.0) and SAS (version 9.4).
Role of the funding source
The sta of the funder had no role in data collection or
data analysis, but did have a role in the study design, data
interpretation, and writing of the report.
Results
We identified 15 studies that were eligible for inclusion
in our meta-analysis (figure 1), including four studies in
Europe, one in Japan, one in Australia, eight in the USA,
and one that included data from 40 countries (table;
appendix pp 3–4). Seven studies were published5,6,8,17,23,24,26
and eight were unpublished at the time of data
compilation,19,27–33 with study start dates ranging between
1999 and 2018.
The total sample included 47 471 participants
(individual-level mean age 65·0 years [SD 12·4],
32 226 [68%] were female, and >70% were of White race
[appendix pp 6–8]), with a median study follow-up time
of 7·1 years (range 2·7–13·5 [IQR 4·3–9·9]; total sum of
follow-up across studies was 297 837 person-years). The
overall median of the median steps per day was 6495
[IQR 4273–8768]. Adults younger than 60 years had
significantly higher median steps per day (7803
[IQR 5377–10 352]) than did adults aged 60 years and
older (5649 [IQR 3686–8092]; p=0·033). A total of
3013 deaths were reported (10·1 per 1000 participant-
years). The Newcastle Ottawa quality scores were high,
ranging from 7 to 9 out of a possible 9 points (appendix
p 10).
Compared with the lowest quartile of steps per day,
higher quartiles of steps per day were associated with a
reduced risk of mortality in the overall sample (figure 2;
appendix p 13). Funnel plots had minor asymmetry for
the second and third quartile comparisons among lower
weighted studies with visual inspection (appendix p 14).
Egger’s test for symmetry suggested no evidence of study
selection bias (appendix p 14). There was a non-linear,
dose–response association between steps per day and all-
cause mortality in the spline model (pnon-linearity<0·0001).
The lowest HR was observed at approximately
7000–9000 steps per day in the overall sample (appendix
p 15).
HRs for risk of mortality by age group (<60 years and
≥60 years) are shown in figure 2 and the appendix
(pp16–17). There was a significant interaction (p=0·012)
by age group in the spline model (figure 3). The number
of daily steps at which the HR for mortality plateaus
among adults aged 60 years and older was approximately
6000–8000 steps per day and among adults younger than
60 years was approximately 8000–10 000 steps per day
(figure 3).
The HRs for mortality were similar for females and
males (figure 2; appendix pp 20–21). The interaction by
sex in the spline model was not significant (p=0·11). For
males and females, the lowest HR for mortality was seen
at approximately 7000–9000 steps per day (appendix
p23).
Seven studies reported stepping rate measures (table).
Median peak 30-min stepping rate was 64·1 steps per
min (IQR 52·9–80·5) and 60-min stepping rate was
57·5 steps per min (46·2–70·9). Median time spent
walking at a rate of 40 steps per min or faster was
51·4 min (23·3–87·4) and at 100 steps per min or faster
was 5·2 min (1·3–15·2). Higher stepping rates were
associated with lower risk of mortality without
adjustment for total steps (model 2; figure 4). The
Figure 1: Study selection
5 studies identified via previous systematic
review10 of publications up to
Aug 1, 2019, and study investigators
approached to participate
1 declined to participate
because of paucity of
personnel and resources22
12 unpublished studies identified by
members of The Steps for Health
Collaborative and study investigators
approached to participate
4 agreed to participate 11 agreed to participate
15 studies included in meta-analysis
7 published
8 unpublished
3 had study-level publications after
Aug 1, 2019
8 remain unpublished at the time of
data compliation
1 declined to participate
because of lack of
interest

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Publication Country Study entry Step-monitoring device
(wear location)
Stepping rate measures
available
Participants Mean age,
years (SD)
Female
participants
Mean
follow-up,
years
Deaths
during
follow-up
Published
British Regional Heart Study (BRHS) Jefferis et al
(2019)23
UK 2010–12 ActiGraph GT3X (waist) None 1397 78·4 (4·6) 0 4·7 240
Coronary Artery Risk Development in
Young Adults (CARDIA)
Paluch at al
(2021)8
USA 2005–06 ActiGraph 7164 (waist) Peak 30 min, peak 60 min,
time at ≥40 steps per min,
time at ≥100 steps per min
2110 45·2 (3·6) 1203 (57%) 10·2 72
National Health and Nutrition
Examination Survey (NHANES)
Saint Maurice et al
(2020)6
USA 2005–06 ActiGraph 7164 (waist) Peak 30 min, peak 60 min,
time at ≥40 steps per min,
time at ≥100 steps per min
2382 60·1 (13·3)* 1189 (50%) 10·0 507
Niigata Elderly Study (NES) Yamamoto et al
(2018)24
Japan 1999 EC-100S, YAMASA (waist) None 416 71 (0) 189 (45%) 9·8 76
Norwegian National Physical Activity
Surveillance 1 (NNPAS1)
Hansen et al
(2020)25
Norway 2008–09 ActiGraph GT1M (waist) None 3043 49·9 (14·9) 1627 (53%) 8·9 122
Tasped Pooled Cohort Study
(Tasped)
Dwyer et al
(2015)26
Australia 2000 Yamax SW-200 and
Omrom- HJ-003 and
Omron HJ-102 (waist)
None 2576 58·7 (13·2) 1350 (52%) 11·1 219
Women’s Health Study (WHS) Lee et al (2019)5USA 2011 ActiGraph GT3X (waist) Peak 30 min, peak 60 min,
time at ≥40 steps per min
16 741 72·0 (5·7) 16 741 (100%) 4·3 504
Unpublished
Activity and Function in the Elderly
in Ulm (ActiFE)
NA Germany 2009–10 activPAL (thigh) Peak 30 min, peak 60 min,
time at ≥40 steps per min,
time at ≥100 steps per min
1240 75·4 (6·5) 712 (57%) 8·2 367
Atherosclerosis Risk in Communities
Study (ARIC)
NA USA 2016–17 ActiGraph GT3X (waist) Peak 30 min, time at ≥40
steps per min
452 78·4 (4·7) 266 (59%) 2·9 25
Baltimore Longitudinal Study of
Aging (BLSA)
NA USA 2016 ActiGraph GT3X-LFE
(wrist)
Peak 30 min, peak 60 min,
time at ≥40 steps per min,
time at ≥100 steps per min
382 76·1 (8·9) 201 (53%) 2·7 22
Cancer Prevention Study-3 (CPS-3) NA USA 2015 ActiGraph GT3X (waist) None 720 52·7 (10·0) 428 (59%) 3·5 6
Framingham Heart Study (FHS) NA USA 2008–14 Actical (model number
198-0200-00; waist)
Peak 30 min, peak 60 min,
time at ≥40 steps per min,
time at ≥100 steps per min
4548 55·3 (13·9) 2444 (54%) 7·1 157
Healthy Ageing Initiative NA Sweden 2012–18 ActiGraph GT3X (waist) None 3793 70·4 (0·1) 1934 (51%) 4·3 138
Jackson Heart Study (JHS) NA USA 2000 Yamax SW-200 (waist) None 401 60·2 (9·8) 244 (61%) 13·5 87
Nateglinide and Valsartan in
Impaired Glucose Tolerance
Outcomes Research (NAVIGATOR)
NA 40 countries 2002–04 Accusplit AE120 (waist) None 7270 63·7 (6·9) 3698 (51%) 6·3 471
Data are n or n (%), unless otherwise stated. Mean data are presented with SD in parentheses. LFE=low-frequency extension. NA=not applicable. *Unweighted mean age; weighted mean age was 56·9 years (SE 0·6).
Table: Selected characteristics of included studies

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association between peak 30-min and peak 60-min rate
measures and mortality remained significant after
adjusting for steps per day (appendix pp 24–25). After
adjusting for step volume, time spent walking at 40 steps
per min or faster and at 100 steps per min or faster were
not associated with mortality, except for the first versus
second quartiles at a rate of 100 steps per min or faster
(figure 4; appendix pp 26–27).
Sensitivity analyses excluding deaths within the first
2 years of follow-up showed the association between
steps per day quartiles and mortality was attenuated
but remained significant (appendix pp 28–29). The
association between step counts and mortality was
stronger in the six studies with fewer than 6 years of
follow-up (HR 0·32 [95% CI 0·25–0·41]) than among
the nine studies with 6 years of follow-up or more
(0·57 [0·49–0·66]) when comparing the lowest and
highest quartile (appendix p 30). There was a significantly
lower HR for published (0·54 [0·42–0·68]) than
unpublished studies (0·73 [0·63–0·85]) when comparing
the first and second quartile (appendix p 31). We found
no appreciable dierences in the association between
steps per day and mortality when excluding any
one study or step-counting device (appendix p 33). When
reanalysing the data using a fixed-eects inverse-variance
method, we found no change in the results (appendix
Figure 2: Association between steps per day and all-cause mortality, in all participants, and by age and sex
Model 1 adjusted for age and sex (if applicable). Model 2 was further adjusted for device wear time, race and ethnicity (if applicable), education or income, body-mass index, plus study-specific
variables for lifestyle, chronic conditions or risk factors, and general health status. The x-axis of the plot is on the log scale.
Total
Age, years
<60
≥60
Sex
Male
Female
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
15
15
15
15
7
7
7
7
13
13
13
13
11
11
11
11
11
11
11
11
3553
5801
7842
10
901
4849
7245
8911
11
482
2841
5217
7116
10
501
3897
5943
7871
11
209
3623
5901
7880
11
217
11
858
11
877
11
877
11
859
2588
3036
3188
3356
9093
8652
8504
8335
3584
3655
3694
3838
7888
7824
7793
7645
1447/70
991
676/74
732
511/75
587
379/76
526
127/22
718
77/26
993
67/26
499
88/30
246
1241/49
878
637/47
171
467/46
351
313/45
566
739/25
681
379/27
456
272/27
731
226/28
961
691/45
420
292/46
463
201/47
008
140/46
583
1 (ref)
–65 (–72 to –58)
–79 (–86 to –72)
–90 (–97 to –83)
1 (ref)
–24 (–34 to –14)
–28 (–38 to –18)
–22 (–33 to –13)
1 (ref)
–63 (–72 to –54)
–81 (–90 to –73)
–99 (–107 to –91)
1 (ref)
–102 (–119 to –86)
–132 (–148 to –117)
–147 (–162 to –132)
1 (ref)
–50 (–58 to –43)
–62 (–69 to –55)
–69 (–76 to –62)
1·00 (ref)
0·56 (0·47 to 0·65)
0·47 (0·40 to 0·56)
0·39 (0·32 to 0·48)
1·00 (ref)
0·57 (0·47 to 0·70)
0·42 (0·28 to 0·63)
0·53 (0·38 to 0·73)
1·00 (ref)
0·56 (0·34 to 0·92)
0·45 (0·37 to 0·55)
0·35 (0·28 to 0·45)
1·00 (ref)
0·57 (0·48 to 0·69)
0·48 (0·38 to 0·61)
0·46 (0·36 to 0·58)
1·00 (ref)
0·60 (0·46 to 0·77)
0·44 (0·35 to 0·56)
0·36 (0·26 to 0·52)
1·00 (ref)
0·60 (0·51 to 0·71)
0·55 (0·49 to 0·62)
0·47 (0·39 to 0·57)
1·00 (ref)
0·59 (0·39 to 0·88)
0·51 (0·37 to 0·71)
0·60 (0·44 to 0·83)
1·00 (ref)
0·62 (0·52 to 0·73)
0·52 (0·43 to 0·62)
0·43 (0·34 to 0·53)
1·00 (ref)
0·62 (0·52 to 0·76)
0·55 (0·44 to 0·68)
0·52 (0·41 to 0·66)
1·00 (ref)
0·62 (0·47 to 0·81)
0·53 (0·41 to 0·68)
0·43 (0·31 to 0·61)
52%
12%
47%
34%
0%
0%
55%
50%
48%
43%
54%
44%
57%
34%
50%
Steps per
day
quartile
Median
steps
per day
Number
of
studies
Participants Deaths/
person-
years
Risk difference
per 1000 people
(95% CI)
Model 1 Model 2
Hazard ratio (95% CI) Heterogeneity,
I2
1·0
Hazard ratio (95% CI; model 2)
0·1
Figure 3: Dose-response association between steps per day and all-cause mortality, by age group
Thick lines indicate hazard ratio estimates, with shaded areas showing 95% CIs. Reference set at the median of the
medians in the lowest quartile group (age ≥60 years = 3000 steps per day and <60 years = 5000 steps per day).
Model is adjusted for age, accelerometer wear time, race and ethnicity (if applicable), sex (if applicable), education
or income, body-mass index, and study-specific variables for lifestyle, chronic conditions or risk factors, and
general health status. pinteraction=0·012 by age group. 14 studies included in spline analysis, excluded Baltimore
Longitudinal Study of Aging.19 The y-axis is on a log scale.
0·2
0·5
1·0
2·0
Steps per day
Hazard ratio (95% CI)
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
11000
12000
13000
14000
15000
16000
Age <60 years
Age ≥60 years

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e225
p 12). In main analyses, heterogeneity (I²) was low to
moderate, ranging from 0 to 57% across quartiles
(figure 2).
Discussion
In this meta-analysis of 15 studies, seven published and
eight unpublished, we found that taking more steps per
day was associated with progressively lower mortality
risk, with the risk plateauing for older adults (aged
≥60 years) at approximately 6000–8000 steps per day and
for younger adults (aged <60 years) at approximately
8000–10 000 steps per day. We found inconsistent
evidence that step intensity had an association with
mortality beyond total volume of steps.
Our findings add to the body of research on steps and
health by describing a curvilinear association and range
in steps per day associated with all-cause mortality. The
curvilinear association and 50–60% lower risk in the
higher steps per day quartiles than in the lowest steps
per day quartile is similar to the association and risks
observed for time spent doing moderate-to-vigorous
intensity physical activity and mortality,17 and study-
level publications on steps and mortality.5,6,8,25 The steep
early slope of the dose–response curve suggests
increasing steps might be beneficial in terms of
reducing risk of mortality, particularly among indi-
viduals who have lower step volumes. We observed a
plateau in risk reduction, which varied by age group.
Figure 4: Association between stepping rate with all-cause mortality, with and without adjustment for total step volume
Hazard ratios and 95% CIs are adjusted for age, device wear time, race and ethnicity (if applicable), sex (if applicable), education or income, body-mass index,
and study-specific variables for lifestyle, chronic conditions or risk factors, and general health status. The model with additional adjustment for step volume uses the
residual method for the rate variable. The x-axis is on a log scale.
Peak 30-min stepping rate
Not adjusting for step volume
Adjusting for step volume
Peak 60-min stepping rate
Not adjusting for step volume
Adjusting for step volume
Time (in min) per day spent at ≥40 steps per min
Not adjusting for step volume
Adjusting for step volume
Time (in min) per day spent at ≥100 steps per min
Not adjusting for step volume
Adjusting for step volume
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
7
7
7
7
7
7
7
7
6
6
6
6
6
6
6
6
7
7
7
7
7
7
7
7
5
5
5
5
5
5
5
5
836
347
248
200
564
460
336
270
6850
6851
6850
6850
6834
6835
6837
6833
6972
6965
6964
6967
6937
6948
6950
6948
2657
2679
2664
2664
2665
2666
2668
2664
6964
6962
6968
6982
6947
6948
6950
5946
841
338
224
203
511
464
375
255
842
353
232
204
330
386
418
496
548
267
156
131
201
246
388
269
0%
52%
34%
0%
26%
22%
0%
52%
56%
0%
20%
60%
0%
46%
26%
0%
0%
0%
45%
40%
44%
6%
60%
62%
1 (ref)
0·58 (0·51–0·67)
0·55 (0·42–0·72)
0·51 (0·41–0·65)
1 (ref)
0·73 (0·64–0·84)
0·66 (0·55–0·79)
0·67 (0·56–0·83)
1 (ref)
0·57 (0·50–0·66)
0·52 (0·40–0·67)
0·54 (0·40–0·72)
1 (ref)
0·74 (0·65–0·85)
0·69(0·58–0·82)
0·67 (0·50–0·90)
1 (ref)
0·58 (0·51–0·67)
0·51 (0·40–0·66)
0·53 (0·42–0·65)
1 (ref)
1·00 (0·85·1·16)
0·97 (0·83–1·14)
1·12 (0·96–1·32)
1 (ref)
0·64 (0·50–0·84)
0·62 (0·48–0·82)
0·53 (0·39–0·72)
1 (ref)
0·70 (0·56–0·87)
0·89 (0·60–1·31)
0·86 (0·58–1·28)
Quartiles Studies Deaths Participants Hazard ratio
(95% CI)
Heterogeneity,
I2
0·1 1·0
Hazard ratio (95% CI)

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We did not find that high step volumes were associated
with increased risk of mortality.34 Furthermore, in
sensitivity analyses, we found stronger associations
among studies with shorter follow-up than in those
with longer follow-up,21 suggesting that more recent
physical activity might be more important for
associations with mortality.
Contrary to the curvilinear dose response observed in
our analysis, a recent steps and mortality meta-analysis
of seven studies found a linear association for
2700–17 500 steps per day; however, this study was limited
by sparse data being available at the upper end of the
steps distribution, with only three eect estimates
provided above 12 500 steps per day.9 Because of the small
number of studies included, this meta-analysis was
unable to provide robust subgroup analyses and,
therefore, was unable to examine associations by age or
sex. Here, we included 15 studies and applied a
standardised, meta-analytical method for data synthesis
across studies, strengthening the reliability of our
findings.
We found that thresholds of steps per day were dierent
for younger and older adults because the steps per day
versus mortality spline curves varied by age group. The
curvilinear shape of the step count to mortality association
was similar for older and younger adults, but the step
volume associated with a given HR diered by age. In a
study of older women (aged ≥62 years) by Lee and
colleagues,5 the mortality risk plateaued at 7500 steps per
day.5 We observed a similar plateauing at 6000–8000 steps
per day for older individuals, and included both sexes and
a slightly wider age group to enable us to identify ranges
of steps per day for younger and older age groups, and by
sex. As age increases, mobility limitations, decreases in
aerobic capacity, and biomechanical ineciencies might
restrict the possible number of steps per day older adults
can accumulate.35,36 The association between daily steps
and all-cause mortality might start at lower step volumes
for older adults because of lower absolute step volume for
the same relative step intensity and physiological stimulus
than for younger adults. Therefore, older adults might
require a lower number of steps to gain similar
improvements in health benefits.37
We found an association between stepping rate
(cadence) and all-cause mortality with some, but not all,
rate measures.5,6 Increasing daily peak stepping rate in
any (not necessarily consecutive) 30 min or 60 min
period, independent of steps per day, was associated with
reduced mortality.12 Conversely, adjusting for step
volume, time spent walking at 40 steps per min or faster
and 100 steps per min or faster were not associated with
mortality. Peak stepping rate might better reflect fitness
levels than thresholds of time spent walking at 40 or
100 steps per min or faster, and fitness is a strong
predictor of mortality,38 which might partially explain
why peak stepping rate might be more strongly related to
mortality than the 40 and 100 steps per min thresholds.
The time threshold measures we used here were
developed in laboratory settings12,39 and might not
represent real-world patterns of walking. Peak stepping
rate variables were more normally distributed than
thresholds measures, allowing for easier detection of
dierences.12 For example, most participants spent little
time walking at 100 steps per min or faster (median
5·2 min per day [IQR 1·3–15·2]). Time spent walking at
a speed slower than 100 steps per min might be
considered for future observational studies of the
association between walking with health outcomes.
Disentangling the health associations of stepping rates
from step volume in daily life is dicult because
individuals who walk at a faster pace usually accumulate
more steps per day than those who walk at a slower pace.
Trials pre scribing dierent stepping rate groups while
maintaining the same total step volume might be needed
to fully examine the association between stepping rate
and inter mediate health outcomes (eg, hypertension or
diabetes).1 Taken together, our findings were incon clusive
when determining if step intensity has additional
mortality benefits beyond that associated with total steps.
The implications of our findings extend to health care
and public health. Steps per day is a simple and easy
to interpret measure that can enhance clinician–patient
and public health communication for monitoring and
promoting physical activity. Wearable devices that
monitor steps, such as smartphones and fitness trackers,
have substantially increased in popularity over the past
decade and this popularity is expected to continue to
increase.3,4 Many consumers rely on the number of steps
provided from these devices to monitor their physical
activity.
Our study has several limitations. The data are derived
from observational studies; therefore, causal inferences
cannot be made. We focused on all-cause mortality;
however, the associations between steps and other health
outcomes are important considerations when developing
guidelines or providing clinical advice. Although we
attempted to control for sociodemographic, lifestyle, and
health status factors in our analyses, residual confound-
ing and reverse causality might still be present. Steps
were measured at a single timepoint. 1 week of device-
measured steps has relative stability over several years,40
but does not account for changes in steps per day over
time. In this meta-analysis we used study-level data, and
although we standardised our analyses across studies,
heterogeneity in participants between studies (eg,
demographics, health status) and design (eg, step-
counting device, covariates) might not be fully accounted
for compared with in individual-level pooled meta-
analyses. We selected prespecified knots in splines,
which risks model misspecification. All included studies
were in high-income countries and participants were
volunteers primarily among White populations,
restricting generalisability of the findings. Future
research should emphasise monitoring and promoting

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e227
steps in populations at higher risk of mortality (eg, some
race and ethnicity groups, low socioeconomic status, and
individuals with or without high risk for chronic
diseases). Since the development of this meta-analysis
collaboration, to our knowledge, two studies on steps and
mortality41,42 have been published. The findings of these
two studies, which included primarily older adults, are
consistent with our results, with a greater number of
daily steps being significantly associated with a decreased
risk of all-cause mortality.
Device type, wear location, and walking speed and
duration can aect the accuracy of step estimates. Step
counts obtained from research and consumer devices are
highly correlated but can vary by 20% or more;20 therefore,
estimates of steps per day reported here might not
precisely match all devices. Stepping rate was measured
as the number of steps accumulated per min rather than
the number of steps while in motion and, therefore,
might not adequately capture short walking periods,
which are common in daily life.43 Additionally, some
devices might not detect all steps at very slow walking
speeds.44 Therefore, devices might underestimate steps
particularly among frail older adults. Most of the
participating studies used devices worn at the hip,
whereas many consumer devices are worn on the wrist
and can provide dierent estimates.20
This meta-analysis has several strengths. The par-
ticipant population was geographically diverse, and so
the associations were generated with greater precision
and relevance to a diverse population of individuals
worldwide than would be possible in individual, country-
level studies. Use of measures recorded by devices such
as step counters and accelerometers might more
accurately reflect the strength of the association between
movement and mortality than self-reported activity.45
Each study used a consistent methodological approach
to minimise heterogeneity. Unpublished studies were
invited to participate, which would have reduced
publication bias. Positive findings tend to be published
earlier and more often than negative findings;46 therefore,
if we had only relied on published evidence the estimated
pooled eect size might have been overestimated. We
found associations between daily steps and all-cause
mortality in both published and unpublished studies,
providing robust evidence for this association.
There are currently no evidence-based public health
guidelines recommending the number of steps per day
for health benefits. Our findings suggest mortality
benefits, particularly for older adults, can be seen at levels
less than the popular reference of 10 000 steps per day.
Adults taking more steps per day have a progressively
lower risk of all-cause mortality, up to a level that varies by
age. Our findings can be used to inform step guidelines
for clinical and population promotion of physical activity.
Contributors
AEP, DRB, MRC, UE, KRE, DAG, BJJ, WEK, I-ML, CEM, JDO, AVP,
CFP, ER-P, and JEF conceived and designed the study and interpreted
the data. AEP, CFP, and SB did the statistical analyses and accessed and
verified the underlying study data. AEP and JEF drafted the manuscript.
All authors acquired the data. All authors critically revised the
manuscript for intellectual content. All authors had full access to the
data in the study and had final responsibility for the decision to submit
for publication.
Declaration of interests
AEP and CFP received funding for this project from US Centers for
Disease Control and Prevention (CDC) Intergovernmental Personnel Act
Agreement. BJJ receives grant funding through the British Heart
Foundation. MRC and RSV have received grant funding through
National Heart Lung and Blood Institute, National Institutes of Health
(NIH). I-ML, KPG, and PP receive grant funding through NIH.
KRE receives grant funding through NIH, Robert Wood Johnson
Foundation, US Department of Transportation, and North Carolina
Department of Transportation; receives consulting fees from NIH;
and is on the Board of Trustees with the American College of Sports
Medicine. DD has received grant funding through German Research
Foundation, travel expenses for 10th International Meeting on Ageing,
honoraria for being an instructor at Boston University School of Public
Health, been an unpaid speaker for German Society of Epidemiology,
and been an unpaid member of the Alumni Leadership Council of
Boston University School of Public Health. JS receives grant funding
through National Institutes on Aging, NIH. All other authors declare no
competing interests.
Data sharing
Relevant meta-level data, protocol, and analytical code on which this
analysis is based are available on request to the corresponding author
(AEP). All requests will need to provide a methodologically sound
justification and will require approval from the Steps for Health
Collaborative. Requests can be made immediately after publication of
this Article, with no end date. Individual participant level data or study-
level data from any specific study included in the meta-analysis are not
available through this request.
Acknowledgments
This project was supported by an Intergovernmental Personnel Act
Agreement through the CDC. We thank all research sta for data
collection and participants of all studies for their important contributions.
We thank the Tasped investigator team; Brady Rippon for analytic
support for the Atherosclerosis Risk in Communities Study;
and H Miyazaki, from the Niigata Elderly Study. We also thank
Eric T Hyde and Katherine Hall for invaluable contributions to the Steps
for Health Collaborative. The findings and conclusions in this Article are
those of the authors and do not necessarily represent the ocial position
of the CDC or the NIH.
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