Articles

Does physical activity attenuate, or even eliminate, thedetrimental association of sitting time with mortality?
A harmonised meta-analysis of data from more than
1 million men and women
Ulf Ekelund, Jostein Steene-Johannessen, Wendy J Brown, Morten Wang Fagerland, Neville Owen, Kenneth E Powell, Adrian Bauman, I-Min Lee,for the Lancet Physical Activity Series 2 Executive Committe* and the Lancet Sedentary Behaviour Working Group*

Summary
Lancet 2016; 388: 1302–10
Published Online
July 27, 2016
http://dx.doi.org/10.1016/
S0140-6736(16)30370-1
This online publication has beencorrected. The corrected version
first appeared at thelancet.com
on September 22, 2016
See Comment pages 1254,
1255, 1257, and 1258
See Articles page 1311
See Series pages 1325 and 1337
This paper forms part of the
Physical Activity 2016 Series*Members listed at the end of
the Article
Department of Sport Medicine,
Norwegian School of Sport
Sciences, Oslo, Norway(Prof U Ekelund PhD,
J Steene-Johannessen PhD,
M Wang Fagerland PhD);
Medical Research Council
Epidemiology Unit, Universityof Cambridge, Cambridge, UK(Prof U Ekelund); Centre for
Research on Exercise, Physical
Activity and Health, School of
Human Movement andNutrition Sciences, Universityof Queensland, Brisbane, QLD,
Australia (Prof W J Brown PhD);
Oslo Centre for Biostatistics
and Epidemiology, Research
Support Services, Oslo
University Hospital, Oslo,
Norway(M Wang Fagerland PhD); Baker
IDI Heart and Diabetes
Institute, and Swinburne
University of Technology,
Melbourne, VIC, Australia(Prof N Owen PhD); Atlanta, GA,
USA (K E Powell MD); School of
Public Health, Sydney
University, Sydney, NSW,
Australia (Prof A Bauman PhD);
and Division of Preventive
Medicine, Brigham and
Women’s Hospital, Harvard
Medical School, Boston, MA,
USA, and Department of

1302

Background High amounts of sedentary behaviour have been associated with increased risks of several chronic conditions
and mortality. However, it is unclear whether physical activity attenuates or even eliminates the detrimental eﬀects ofprolonged sitting. We examined the associations of sedentary behaviour and physical activity with all-cause mortality.
Methods We did a systematic review, searching six databases (PubMed, PsycINFO, Embase, Web of Science, Sport Discus,and Scopus) from database inception until October, 2015, for prospective cohort studies that had individual level exposure
and outcome data, provided data on both daily sitting or TV-viewing time and physical activity, and reported eﬀect estimates
for all-cause mortality, cardiovascular disease mortality, or breast, colon, and colorectal cancer mortality. We included datafrom 16 studies, of which 14 were identiﬁed through a systematic review and two were additional unpublished studies
where pertinent data were available. All study data were analysed according to a harmonised protocol, which categorised
reported daily sitting time and TV-viewing time into four standardised groups each, and physical activity into quartiles (inmetabolic equivalent of task [MET]-hours per week). We then combined data across all studies to analyse the associationof daily sitting time and physical activity with all-cause mortality, and estimated summary hazard ratios using Cox
regression. We repeated these analyses using TV-viewing time instead of daily sitting time.
Findings Of the 16 studies included in the meta-analysis, 13 studies provided data on sitting time and all-cause mortality.
These studies included 1 005 791 individuals who were followed up for 2–18·1 years, during which 84 609 (8·4%) died.
Compared with the referent group (ie, those sitting <4 h/day and in the most active quartile [>35·5 MET-h per week]),mortality rates during follow-up were 12–59% higher in the two lowest quartiles of physical activity (from HR=1·12,
95% CI 1·08–1·16, for the second lowest quartile of physical activity [<16 MET-h per week] and sitting <4 h/day; to
HR=1·59, 1·52–1·66, for the lowest quartile of physical activity [<2·5 MET-h per week] and sitting >8 h/day). Daily sitting
time was not associated with increased all-cause mortality in those in the most active quartile of physical activity. Comparedwith the referent (<4 h of sitting per day and highest quartile of physical activity [>35·5 MET-h per week]), there was noincreased risk of mortality during follow-up in those who sat for more than 8 h/day but who also reported >35·5 MET-h per
week of activity (HR=1·04; 95% CI 0·99–1·10). By contrast, those who sat the least (<4 h/day) and were in the lowest
activity quartile (<2·5 MET-h per week) had a signiﬁcantly increased risk of dying during follow-up (HR=1·27, 95% CI
1·22–1·31). Six studies had data on TV-viewing time (N=465 450; 43 740 deaths). Watching TV for 3 h or more per day was
associated with increased mortality regardless of physical activity, except in the most active quartile, where mortality wassigniﬁcantly increased only in people who watched TV for 5 h/day or more (HR=1·16, 1·05–1·28).
Interpretation High levels of moderate intensity physical activity (ie, about 60–75 min per day) seem to eliminate theincreased risk of death associated with high sitting time. However, this high activity level attenuates, but does not
eliminate the increased risk associated with high TV-viewing time. These results provide further evidence on the
beneﬁts of physical activity, particularly in societies where increasing numbers of people have to sit for long hours forwork and may also inform future public health recommendations.
Funding None.

Introduction
In a seminal 1953 Lancet paper, J N Morris and colleagues1
reported an increased risk of coronary heart disease in
London bus drivers compared with conductors. Since then,many observational studies have shown that lack of physicalactivity is a major risk factor for morbidity and premature
mortality.2–4 Indeed, estimates from 2012 indicated that notmeeting physical activity recommendations is responsible
for more than 5 million deaths globally each year.4
Nowadays, sedentary behaviours are highly prevalent,and data from adults in high-income countries suggest the
majority of time awake is spent being sedentary.5,6 Further,high amounts of sedentary behaviour, usually assessed asdaily sitting time or time spent viewing TV, have beenwww.thelancet.com Vol 388 September 24, 2016

Articles

Research in context
Evidence before this study
Compelling evidence from many observational studies showsthat lack of physical activity increases the risks of many
non-communicable diseases such as type 2 diabetes,
cardiovascular disease, stroke, some cancers, and premature
mortality. Sedentary behaviour, on the other hand, has emerged asa potential risk factor for many chronic conditions and mortality
during the last decade. A recent meta-analysis suggested that
prolonged TV-viewing time was associated with increased risk fortype 2 diabetes, cardiovascular disease, and all-cause mortality.
Two other meta-analyses had examined the associations of sitting
time with non-communicable disease incidence and mortality.
One of these concluded that prolonged sitting time was associatedwith increased risks of deleterious health outcomes regardless ofphysical activity level, whereas the other concluded that physicalactivity (no details on the amount of activity were provided)
seemed to attenuate the increased risk of all-cause mortality due
to high sitting. No previous systematic review had directlycompared the joint eﬀects of diﬀerent, speciﬁed levels of physicalactivity and sitting time, to investigate the associations of diﬀerent
amounts of sitting time and physical activity in relation to allcause mortality. Such information is required for the developmentof public health guidelines targeting sedentary behaviour.
We performed a systematic literature search in six databases(PubMed, PsycINFO, Embase, Web of Science, Sport Discus, andScopus) from database inception until October, 2015, following
the PRISMA guidelines. We identiﬁed 8381 articles, of whichassociated with increased risks for several chronic
conditions and mortality.7–9 A crucial question is: if one isactive enough, will this attenuate or even eliminate thedetrimental association of daily sitting time with mortality?8,9We therefore did a systematic review and meta-analysis
to examine the joint and stratiﬁed associations ofsedentary behaviour and physical activity with all-cause
mortality, using data from studies that were analysed
according to a standard protocol.

Methods
Data sources, literature search, and study selection
Following PRISMA guidelines,10 we identiﬁed 16 published11–26 studies through a systematic review ofsix databases (PubMed, PsycINFO, Embase, Web of
Science, Sport Discus, and Scopus) from database
inception until Oct 30, 2014, updating the search up to
Oct 10, 2015 (a detailed search description is provided in
the appendix). We also obtained data from two additional
studies,27,28 when the pertinent data were available but
not published. Authors or principal investigators were
contacted and asked about their willingness to participate
in a harmonised meta-analysis. One study11 did not
respond to our request to participate and one additional
study12 was excluded as it measured physical activity by
www.thelancet.com Vol 388 September 24, 201616 were identiﬁed as eligible for inclusion. We also identiﬁed two
studies in which the pertinent data were available but
unpublished. We then contacted the principal author/investigatorof these 18 studies and asked whether they were willing toreanalyse their data according to a harmonised protocol. In total,
16 studies were analysed according to a predeﬁned protocol andincluded in this harmonised meta-analyses (details on the two
excluded studies are provided in the text).

Epidemiology, Harvard
T H Chan School of Public
Health, Boston, MA, USA(Prof I-M Lee)
Correspondence to:Prof Ulf Ekelund, Department ofSports Medicine, Norwegian
School of Sports Sciences, Ullevål
Stadion, 0806, Oslo, Norway
ulf.ekelund@nih.no

Added value of this study
This is the ﬁrst meta-analysis to use a harmonised approach todirectly compare mortality between people with diﬀerent levelsof sitting time and physical activity. Examining the joint eﬀects
of these two behaviours is important, because most people
engage in both behaviours every day, so the eﬀects of bothshould be considered in public health guidelines.
Implications of all the available evidence
These results provide further evidence on the beneﬁts of physicalactivity, particularly in societies where increasing numbers ofpeople have to sit for long hours for work or transport. Ourﬁndings indicate that increased sitting time is associated withincreased all-cause mortality; however, the magnitude ofincreased risk with increased sitting time is mitigated inphysically active people. Indeed, those belonging to the mostactive quartile and who are active about 60–75 min per day ofmoderate intensity physical activity seem to have no increased
risk of mortality, even if they sit for more than 8 h a day.

accelerometry, which could not be harmonised with selfreport data. For one other study, the Women’s Health
Initiative Observational Study (WHIOS)26 investigators did
not agree to participate but data for a shorter follow-up
were publicly available.29 Thus, we analysed individual datafrom 16 studies11–25,29 according to a predeﬁned protocol andincluded these data in the harmonised meta-analyses. We
included English-language, prospective cohort studies that
had individual level exposure and outcome data, provided
data on both daily sitting or TV-viewing time and physicalactivity, and reported eﬀect estimates (hazard ratios [HRs],
odds ratios [ORs], or relative risks [RRs] with 95% CIs) for
all-cause mortality, cardiovascular disease mortality, orbreast, colon, and colorectal cancer mortality. This review
protocol is registered with the PROSPERO database.

Data extraction and harmonisation
One author (JS-J) extracted, and all other authors conﬁrmed,
the following information from each eligible study: nameof the ﬁrst author; study location; source and number ofparticipants; age of participants; number of men andwomen; years of follow-up; number of deaths from allcauses, cancer, and cardiovascular disease; and methods ofascertainment; assessment details for physical activity andsitting time; and covariates included in adjusted models.

For the study protocol see
http://www.crd.york.ac.uk/
PROSPERO/display_record.
asp?ID=CRD42015023870
See Online for appendix

1303

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To reduce heterogeneity, we ﬁrst reviewed the questionnaires used to assess sedentary behaviour and physicalactivity, then determined whether it was possible to deﬁnethese exposures using the same metric across all studies.
All but two studies13,14 asked about sitting time using an
open-ended format or categories that could be collapsed
into four or ﬁve common groups (appendix). Of theremaining two studies, one13 used ﬁve categories that wecollapsed into four by combining the two highest
categories, whereas the other study14 used only three
categories of sitting time (appendix). Data for TV-viewing
time from six studies16,20,22–25 could be combined into fourcommon groups (appendix). We reanalysed data fromeach study using predeﬁned categories of sitting time infour groups (0–<4 h/day, 4–<6 h/day, 6–8 h/day, >8 h/day)and TV-viewing time in four groups (<1 h/day, 1–2 h/day,
3–4 h/day, and >5 h/day).
Physical activity was assessed by diﬀerent validated
self-report questionnaires in all studies. To reduce
heterogeneity in the assessment of physical activity, weonly included information on walking and leisure timeand recreational physical activities (including exercise
and sports) since this information was available from allstudies (appendix). We asked each contributing study torecalculate their estimated physical activity energy
expenditure by multiplying the reported duration by theintensity, and expressing physical activity in metabolic
equivalent of task (MET)-hours per week (MET-h perweek). We used the same MET values for intensity as in
8381 records identified throughdatabase search andreviewed
7699 excluded after title review
682 records were retrieved to
endnote191 duplicates removed
491 records for abstract review
393 records excluded after
abstract review
98 records for full text review
82 excluded after full text
review
30 outcome measure
48 exposure
1 study design
3 secondary analysis
16 studies eligible for inclusion
2 studies identified throughpersonal contact

1 study did not respond toparticipation request
1 study excluded due toharmonisation issues
16 studies included in themeta-analyses

Figure 1: Study selection1304

the original publications. For those studies that simply
reported duration of speciﬁc physical activities14,19,22 weassigned the conventionally accepted intensity levels(3·3 METs for walking, 4 METs for moderate intensity
activity, 7 METs for vigorous intensity activity, and
7·2 METs for strenuous sports).30 Therefore, our estimateof physical activity reﬂects participation in moderate andvigorous intensity activity (MVPA). Due to the design ofthe questions used for assessing physical activity, it
was not possible to calculate physical activity in
MET-h per week in its continuous form in fourstudies.14,17,22,27 In these studies, we asked contributing
studies to calculate MET-h per week in three14 or
four17,22,27 categories that were assumed to reﬂect thequartiles derived from the other studies (appendix).
The median MET-h per week across studies for theupper boundary for the ﬁrst (lowest) quartile was
2·5 MET-h per week (equivalent to about 5 min ofmoderate intensity activity per day). Corresponding values
for the second and third quartiles were 16 MET-h per week
(about 25–35 min of moderate intensity activity per day)and 30 MET-h per week (about 50–65 min of moderateintensity activity per day), and the lower boundary for the
fourth (top) quartile was 35·5 MET-h per week (about
60–75 min of moderate intensity activity per day; appendix).
Examples of moderate intensity activities are brisk walking
at 5·6 km/h, and bicycling for pleasure at 16 km/h.30

Data analyses and syntheses
Using the study quality checklist proposed by Kmet andcolleagues,31 two authors (JS-J and UE) independently
assessed the studies, and any disagreements wereresolved by consensus. Studies were scored (0 for no,
1 for partial, 2 for yes) on 14 criteria.31 The sum of allscores was then divided by the highest possible score (28),
giving quality scores ranging from 0 (worst) to 1 (best).
Principal authors or investigators for all studies except
one29 reanalysed their data according to a harmonised
protocol, using minimally adjusted models (adjusted forsex and age) and in models that adjusted for the same
covariates as in their original publications. For the
WHIOS study,26 we used publicly available individuallevel data to perform the analyses.29
All studies apart from three17–19 either excluded allparticipants with major chronic diseases at baseline or
excluded deaths occurring within at least 1 year insensitivity analyses. Two of the remaining threestudies,18,19 which included older participants, provided
analyses for this meta-analysis in which they excluded
deaths within the ﬁrst 2 years. The remaining study,17which had a short follow-up period (mean 2·8 years),
analysed their data excluding those with baseline
cardiovascular disease, diabetes, and cancer. Thus, allstudies in this meta-analysis included, for the most part,
apparently healthy participants at baseline.
We ﬁrst performed joint analyses of the associations ofdaily sitting time, physical activity, and all-cause mortality,
www.thelancet.com Vol 388 September 24, 2016

Articles

Country; study name;participant characteristics

Years offollow-up

Method of case ascertainment
Mortality
outcome(s),number of cases

Variables the covariates were adjusted for

QualityAge, sex, smoking, and alcohol consumption

0·85

Sitting
Katzmarzyk Canada; Canada Fitness Survey
et al, 200913 (CFS); 17 013 men and women
aged 18–90 years

12·9 years
All-cause, 1832;(maximum) CVD, 759;cancer, 547

Canadian Mortality Database

Inoue et al,200814

Japan; Japan Public HealthCenter-based Prospective Study;
83 034 men and women aged
45–74 years

8·7 years

Death certiﬁcate provided by Ministry Age, sex, geographical area, occupation, history of
diabetes, smoking, alcohol consumption, BMI, and totalof Health, Labour, and Welfare, andenergy intake
classiﬁed using International
Classiﬁcation of Diseases

0·95

Patel et al,
20101514 years
All-cause, 19 230; National Death Index and classiﬁed
USA; American Cancer Society
using International Classiﬁcation ofCancer Prevention Study II Nutrition (maximum) CVD 6369;
Diseases
cancer, 6989
Cohort (CPS-II); 123 216 men andwomen aged 50–74 years

Age, sex, race, education, BMI, alcohol consumption,smoking status, marital status, total energy intake, andcomorbidity

0·95

All-cause, 4564;
CVD, 974;
cancer, 2044

Matthews
USA; NIH-AARP Diet and Healthet al, 201216 Study; 240 814 men and women
aged 50–71 years

8·5 years

All-cause, 17 044; Social Security Administration and
the National Death Index
CVD, 4684;
cancer, 7652

Age, sex, race, education, BMI, smoking, and diet

0·95

Van der
Ploeg et al,
201217Australia; 45 and Up Study;
222 497 men and women aged
≥45 years

2·8 years

All-cause, 5405

New South Wales Registry of Births,
Deaths, and Marriages

Age, sex, education, urban or rural residence, BMI, marital
status, smoking, self-rated health, and receiving help withdaily task for long time illness or disability

0·95

Pavey et al,
201218Australia; The AustralianLongitudinal Study on Women’s
Health; 6656 women aged
≥75 years

All-cause, 2003
9 years(maximum)
6 years(median)Australian National Death Index

Age, education, marital status, area, smoking, alcohol
consumption, BMI, number of chronic conditions, selfrated health, and assistance with daily tasks

0·90

LeónSpain; 2635 men and women aged
Munoz
≥60 years
et al, 201319

2 years

All-cause, 846

National Death Index

Age, sex, education, BMI, smoking, alcohol consumption,weight, BMI, chronic lung disease, ischaemic heartdisease, stroke, diabetes mellitus, osteomuscular disease,cancer, morbidity, health-related quality of life, mobility
limitations, and agility limitations

0·85

Kim et al,
201320USA; Multiethnic Cohort Study;
134 596 men and women aged
45–75 years

13·7 years

Age, sex, race or ethnic origin, education, smoking
All-cause, 19 143; Death certiﬁcate linked to National
history, history of diabetes or hypertension, energy
Death Index and classiﬁed using
CVD, 6535;
International Classiﬁcation of Diseases intake, and alcohol consumption
cancer, 6697

0·95Petersen
Denmark; Danish Healthet al, 201421 Examination Survey; 71 363 men
and women aged 18–99 years

5·4 years

All-cause, 1074;
CVD, 308

Danish Civil Registration system

Age, sex, educational level, smoking habits, BMI, alcohol
consumption, and hypertension

0·95

Matthews
USA; Southern Community Cohort
et al, 201422 Study; 63 308 men and women
aged 40–79 years

6·4 years

All-cause, 5007;
CVD, 1376;
cancer, 1227

Social Security Administration and
the National Death Index andclassiﬁed using International
Classiﬁcation of Diseases

Age, sex, source of enrolment, race, education, income,marital status, occupational status, comorbid conditions,alcohol intake, smoking history, BMI, and sleep duration

0·95

Jørgensen
Denmark; INTER99; 4513 men and
et al, 200327 women aged 35–66 years

7·5 years

All-cause, 112

Danish registry of causes of death

Age, sex, socioeconomic status, smoking, BMI, alcohol,
diabetes, and hypertension

0·90

Krokstad
Norway; The Nord-Trøndelag
et al, 201328 Health Study (HUNT); 40 752 men
and women aged 19–99 years

18·1 years

All-cause, 5004;
CVD, 1537;
cancer, 1536

Norwegian Causes of Death Registry
and classiﬁed using International
Classiﬁcation of Diseases

Age, sex, BMI, smoking, alcohol, blood pressure, andmedication

0·95

WHIOS29*

USA; Women’s Health Initiative;
92 234 women aged 50–79 years

10·2 years

All-cause 10 800; Hospital records, autopsy records,
death certiﬁcates, and National
CVD 3206;
Center for Health Statistics’ National
cancer 4338
Death Index

Age, race or ethnic origin, education, marital status, BMI,
smoking, alcohol consumption, number of chronic diseases,
number of falls in the past year, hormone use, depressedmood, living alone, and activities of daily living disability

0·95

DunstanAustralia; The Australian Diabetes,
et al, 201023 Obesity and Lifestyle Study;
8800 men and women aged
≥25 years

6·6 years

All-cause, 284;
CVD, 87;
and cancer, 125

Australian National Death Index andclassiﬁed using International
Classiﬁcation of Diseases

Age, sex, education, BMI, smoking (current or ex-smoker),
total energy intake, alcohol, waist circumference,
hypertension, total cholesterol, high-density lipoproteins,triglycerides, glucose tolerance, and undiagnosed andknown diabetes

0·90

Wijndaele
UK; European Prospective
et al, 201024 Investigation into Cancer andNutrition Study; 13 197 men andwomen aged 45–79 years

9·5 years

All-cause 1270;
CVD, 323;
cancer, 570

Oﬃce of National Statistics (UK) and Age, sex, education, smoking, alcohol consumption,
anti-hypertensive medication, medication forclassiﬁed using International
dyslipidaemia, baseline history of diabetes, family history
Classiﬁcation of Diseasesof CVD, and cancer

0·90

Ford et al,
2012255·8 years

All-cause, 542

National Death Index and classiﬁedusing International Classiﬁcation of
Diseases

TV viewing

USA; National Health andNutrition Examination Survey;
7350 men and women aged
≥20 years

Age, sex, race education, smoking, and Healthy Eating
Index score

0·90(Table 1 continues on next page)www.thelancet.com Vol 388 September 24, 2016

1305

Articles

Years offollow-up

Method of case ascertainment
Mortality
outcome(s),number of cases

Variables the covariates were adjusted for

Quality

Matthews
USA; NIH-AARP Diet and Healthet al, 201216 Study; 240 814 men and women
aged 50–71 years

8·5 years

All-cause, 17 044; Social Security Administration and
the National Death Index
CVD, 4684;
cancer, 7652

Age, sex, race, education, BMI, smoking, and diet

0·95

Kim et al,
20132013·7 years

Age, sex, race or ethnic origin, education, smoking
All-cause, 19 143; Death certiﬁcate linked to National
history, history of diabetes or hypertension, energy
Death Index and classiﬁed using
CVD, 6535;
International Classiﬁcation of Diseases intake, and alcohol consumption
cancer, 6697

6·4 years

All-cause, 5007;
CVD, 1376;
cancer, 1227

Country; study name;participant characteristics(Continued from previous page)

USA; Multiethnic Cohort Study;
134 596 men and women aged
45–75 years

Matthews
USA; Southern Community Cohort
et al, 201422 Study; 63 308 men and women
aged 40–79 years

Social Security Administration and
the National Death Index andclassiﬁed using International
Classiﬁcation of Diseases

Age, sex, source of enrolment, race, education, income,marital status, occupational status, comorbid conditions,alcohol consumption, smoking history, BMI, and sleep
duration

0·95

0·95

BMI=body-mass index. CVD=cardiovascular disease. HDL=high-density lipoprotein. PAR-Q=Physical Activity Readiness Questionnaire. *Data downloaded from the NHLBI Biologic Specimen and Data Repository
Information Coordinating Center (BioLINCC).

Table 1: Characteristics of studies included in the meta-analysis, data extracted from original publications

For the BioLINCC website see
https://biolincc.nhlbi.nih.gov/
home/

1306

to directly compare groups with diﬀerent amounts ofsitting time and physical activity against those who sat
the least (<4 h/day; arbitrarily chosen on the basis ofquestionnaire categories) and also those who had themost physical activity (top quartile >35·5 MET-h per
week; ie, referent). We calculated eﬀect estimates using
Cox regression analyses and presented as HRs with theirassociated 95% CIs. We estimated summary HRs acrossstudies with a ﬁxed-eﬀect inverse variance method.32 We
then repeated these analyses, but used TV-viewing time
instead of sitting time.
Next, in stratiﬁed analyses (stratiﬁcation by physicalactivity), we assessed whether the dose-response
association between sitting and mortality diﬀered
between people with diﬀerent activity levels, to address
whether physical activity modiﬁed the detrimental eﬀectof prolonged sitting. That is, we separately investigated
the association between sitting time and all-cause
mortality for each quartile of physical activity, with thosesitting the least serving as referent. We then repeatedthese analyses using TV time instead.
In secondary analyses, we repeated all analyses but
used cardiovascular disease and cancer mortality as theoutcomes. We also tested whether the HRs diﬀered
between extreme groups (ie, the group who sat the mostand also had the most activity, compared with the group
who sat the least and were least active). We performed
sensitivity analyses and separated the highest category
for sedentary time into two (8–10 h/day and >10 h/day)and repeated the analyses; we estimated the eﬀect ofeach individual study by repeating the meta-analysis for
all-cause mortality, excluding one study at a time, and we
also examined publication bias33 and heterogeneity;these ﬁndings are reported in the appendix. Finally, wereanalysed our data and estimated summary HRs acrossstudies with random-eﬀect models and the mainﬁndings were unchanged (data not shown). All metaanalyses were performed using Matlab (R2014a, The
Mathworks, Inc).

Role of the funding source
The study had no sponsors. UE, JS-J, and MWF had fullaccess to the harmonised data provided by study partners.

Results
We identiﬁed 8381 articles by searching six diﬀerent
databases. We retrieved 98 papers for full text review, of
which 16 studies11–26 were identiﬁed as eligible forinclusion (ﬁgure 1). We also obtained data from
two additional studies.27,28 We used publicly available
data29 for the follow-up of one of the studies.26 Therefore,
we analysed individual data from 16 studies13–25,27–29
according to a predeﬁned protocol and included thesedata in the harmonised meta-analyses. Quality scores
were high (≥0·85 in all studies; table 1).
Of the 16 studies included in the meta-analysis,
13 studies13–22,27–29 provided data on sitting time and all-cause
mortality. These studies included 1 005 791 individuals who
were followed up for 2–18·1 years, during which 84 609(8·4%) died, and whom we included in the meta-analysis of
the associations of sitting time and physical activity withall-cause mortality. Nine studies13–16,20–22,28–29 also had data on
cardiovascular disease mortality and eight13–16,20,22,28–29 on
cancer mortality. Three16,20,22 of the 13 studies also had dataon TV-viewing time, and with three additional studies,23–25
contributed to the meta-analysis of the joint associations ofTV-viewing time and physical activity with all-cause
mortality (N=465 450; 43 740 deaths). The number of participants and deaths refer to those provided by the individual
studies and included in the harmonised meta-analysis.
The appendix shows the summary HRs for the joint
associations of sitting time and physical activity with allcause mortality. A clear dose-response association wasobserved, with an almost curvilinear augmented risk for
all-cause mortality with increased sitting time incombination with lower levels of activity (ﬁgure 2A).
Compared with the referent group (ie, those sitting<4 h/day and in the most active quartile), mortality
during follow-up was 12–59% higher in the two lowest
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www.thelancet.com Vol 388 September 24, 2016

quartile (27%) than in the second (12%) and third (10%)
activity quartiles. In the most active quartile, there was no
signiﬁcant association between daily sitting time and allcause mortality.
A
2·0

Hazard ratio (95% CI)

1·7

1·4

1·2
1·1
1·0
0·9

8
6–

>8

h/

y
da
y
h/
da
y

y

da

da

h/

h/

<6

<4

4–

y
da
y
h/
da
y
h/

8
6–

>8

y

da

da

h/

h/

<6

<4

4–

6–

8

h/

da
y
h/
d
>8 ay
h/
da
y

y
da
h/

<6

<4

4–

<4

h/
da
4– y (re<6 f)h
6– /day
8
h/
d
>8 ay
h/
da
y

0·8

>35·5 MET-h/week

30 MET-h/week

16 MET-h/week<2·5 MET-h/week

Quartiles of physical activity

B
2·0

Hazard ratio (95% CI)

1·7

1·4

1·2
1·1
1·0

ay

y

h/
d

ay

4

h/
d

da
h/

3–

>5

y
1–
2

h/
da
<1

2h
/d
3– ay
4
h/
d
>5 ay
h/
da
y

ay
h/
d
<1

1–

ay
h/
da
>5 y
h/
da
y
4

/d

3–

1–

2h

da
y
h/
<1

h/
d

ay
1– (re2 h f)
/d
3– ay
4
h/
d
>5 ay
h/
da
y

0·9

<1

quartiles of physical activity (HR 1·12, 95% CI 1·08–1·16,
for the second lowest quartile of physical activity and<4 h/day; HR 1·59, 1·52–1·66, for the lowest quartile ofphysical activity and >8 h/day of sitting time; appendix).
However, in the third quartile of physical activity (ie, thesecond most active group), only those sitting 4 h/day ormore had higher mortality than the reference group.
Among the most active, there was no signiﬁcant relation
between amount of sitting and mortality rates, suggestingthat high physical activity eliminated the increased risk ofprolonged sitting on mortality. Indeed, this observation
was conﬁrmed in sensitivity analyses using ﬁve categories
for sitting time (appendix).
Since we did not have access to individual level datafrom all studies, we estimated whether HRs between
groups diﬀered signiﬁcantly, as described in the appendix.
Those in the most active quartile, but who also reported
the most sitting time (>8 h/day), had a signiﬁcantly lower
risk (p<0·0001) of dying during follow-up (HR 1·04,
95% CI 0·99–1·10) than did the least active who also sat
the least (<4 h/day; HR 1·27, 1·22–1·30).
We then repeated these analyses with TV-viewing time
instead of sitting time. Similar ﬁndings were observed,
although the eﬀect estimates were less precise, possibly
because of smaller sample sizes (ﬁgure 2B, appendix). In
those who watched TV for 5 h or more per day, the hazard
for all-cause mortality was markedly increased by
between 16% and 93% across activity quartiles (appendix).
Among the most active quartile, only this amount of TVviewing time (≥5 h/day) was signiﬁcantly associated withan increased hazard of mortality (HR 1·16, 95% CI
1·05–1·28). In comparison, people in the least active
quartile who watched TV for only less than 1 h/day had asigniﬁcantly higher mortality risk (HR 1·32, 1·20–1·46;
p=0·007).
In a subsample of studies with available data, we
examined mortality due to cardiovascular disease andcancer. The results for cardiovascular disease mortality
were similar to those observed for all-cause mortality(appendix). Compared with those sitting less than 4 h a
day in the most active quartile, cardiovascular diseasemortality rates were 23–74% higher in the two lowest
quartiles of physical activity (appendix). For cancer
mortality, increased hazards of between 12% and 22%
with more sitting time were observed only for people in
the least active quartile (appendix). Using TV-viewing
time instead of sitting time did not materially change theresults for cardiovascular disease, and the association
between cancer mortality and TV-viewing time was not
signiﬁcant for all levels of physical activity (appendix).
The associations between sitting time and all-cause
mortality are shown separately for individuals in four levels(quartiles) of physical activity in table 2. Among the threeleast active quartiles, increased all-cause mortality rates
were observed with increased sitting time, compared withthe referent categories (<4 h/day). The hazard of sitting
more than 8 h/day was much higher in the least active>35·5 MET-h/week

30 MET-h/week

16 MET-h/week<2·5 MET-h/week

Quartiles of physical activity

Figure 2: Meta-analyses of the joint associations of sitting time and physical activity with all-cause mortality(A) and of TV-viewing time and physical activity with all-cause mortality (B)(A) Sitting time analysis, N=1 005 791. (B) TV-viewing time analysis, N=465 450. The reference categories are thegroups with the highest levels of physical activity (>35·5 MET-h per week) in combination with <4 h/day of sitting (A)or <1h/day of TV-viewing (B). The median MET-h per week for the upper boundary for the ﬁrst (lowest) quartile was
2·5 MET-h per week (equivalent to about 5 min of moderate intensity activity per day). Corresponding values for thesecond and third quartiles were 16 MET-h per week (about 25–35 min of moderate intensity activity per day) and
30 MET-h per week (about 50–65 min of moderate intensity activity per day), and the lower boundary for the fourth(top) quartile was 35·5 MET-h per week (about 60–75 min of moderate intensity activity per day).

1307

Articles<4 h/day ofsitting time

4–<6 h/day ofsitting time

6–8 h/day ofsitting time

>8 h/day of sitting
time≤2·5 MET-h perweek

1 (ref)(N=76 212; 6646)

1·08 (1·04–1·12)(N=48 613; 5224)

1·09 (1·05–1·14)(N=66 839; 5820)

1·27 (1·22–1·32)(N=60 730; 6018)

16 MET-h per week

1 (ref)(N=77 651; 7221)

1·04 (1·00–1·07)(N=73 444; 7873)

1·06 (1·02–1·10)(N=51 263; 5322)

1·12 (1·07–1·17)(N=60 838; 5012)

30 MET-h per week

1 (ref)(N=75 365; 5387)

1·05 (1·01–1·10)(N=63 959; 5489)

1·03 (0·98–1·08)(N=48 292; 3504)

1·10 (1·04–1·16)(N=52 576; 3487)>35·5 MET-h perweek

1 (ref)(N=90 762; 6208)

1·00 (0·96–1·04)(N=65 976; 5268)

1·01 (0·97–1·06)(N=49 715; 3565)

1·04 (0·98–1·10)(N=43 856; 2717)

The reference categories are the groups with <4 h/day of sitting for all quartiles of physical activity. *Median upperboundary for Q1–3 and lower boundary for Q4 in MET-h per week. The equivalent amount of time spent in moderateintensity activity are ≈5 min/day (Q1); 25–35 min/day (Q2); 50–65 min/day (Q3); and 60–75 min/day (Q4).

Table 2: Meta-analyses of the associations between sitting time and all-cause mortality (N=1 005 791;
84 609 deaths) stratiﬁed by quartiles of physical activity*<1 h/day ofTV-viewing time

1–2 h/day ofTV-viewing time

3–4 h/day ofTV-viewing time

≥5 h/day ofTV-viewing time

≤2·5 MET-h perweek

1 (ref)
1·00 (0·94–1·08)(N=10 609; 1064) (N=33 411; 3382)

1·10 (1·02–1·18)(N=40 688; 4702)

1·44 (1·34–1·56)(N=22 779; 3533)

16 MET-h per week

1 (ref)(N=12 280; 984)

1·00 (0·93–1·08)(N=45 493; 4098)

1·08 (1·01–1·15)(N=51 917; 5576)

1·29 (1·19–1·39)(N=21 365; 2870)

30 MET-h per week

1 (ref)(N=11 232; 613)

1·08 (0·98–1·18)(N=39 807; 2589)

1·17 (1·07–1·27)(N=43 699; 3675)

1·41 (1·28–1·56)(N=17 563; 1925)>35·5 MET-h perweek

1 (ref)(N=12 478; 752)

0·96 (0·88–1·04)(N=40 642; 2738)

1·01 (0·93–1·10)(N=44 018; 3551)

1·15 (1·05–1·27)(N=17 469; 1688)

The reference categories are the groups with <1 h/day of TV viewing across quartiles of physical activity. *Median upperboundary for Q1–3 and lower boundary for Q4 in MET-h per week. The equivalent amount of time spent in moderateintensity activity are; ≈5 min/day (Q1); 25–35 min/day (Q2); 50–65 min/day (Q3); and 60–75 min/day (Q4).

Table 3: Meta-analyses of the associations between TV-viewing time, and all-cause mortality(N=465 450; 43 740 deaths) stratiﬁed by quartiles of physical activity*

We then analysed TV-viewing time instead of sitting
time, using as referent those who watched TV for lessthan 1 h/day (table 3). TV-viewing for up to 2 h/day did
not signiﬁcantly increase the risk of mortality duringfollow-up in any activity strata; however, 3 h or more per
day of TV-viewing time was associated with increased risk
among all, except for the most active quartile. In the mostactive quartile, TV-viewing time of 5 h or more per day
was associated with an increased hazard of all-cause
mortality (HR 1·15; 95% CI 1·05–1·27).

Discussion
These analyses, including data from more than 1 million
individuals, indicate that high levels of physical activity,
equivalent to 60–75 min of moderate intensity physicalactivity per day, seem to eliminate the increased mortality
risks associated with high total sitting time. Indeed,those in the highest physical activity quartile (about
60–75 min/day) who sat for more than 8 h daily had asigniﬁcantly lower risk of dying during follow-up than
did those who sat for less than 4 h in the least active
quartile (about 5 min/day). In the middle two quartiles ofphysical activity (which encompass current physicalactivity guideline levels34), the mortality risks associated1308

with increased sitting time were attenuated comparedwith those seen in the least active quartile. For TV-viewing
time, the results were similar, except that high physicalactivity attenuated, but did not eliminate the risk, in
those viewing TV for 5 h or more a day.
Our harmonised meta-analytical approach allowed us
to examine associations betweeen sedentary behaviours,
physical activity and all-cause mortality with greater
precision and a more uniform classiﬁcation of sedentary
behaviour and physical activity than has previously beenpossible. The results suggest that high levels of physicalactivity attenuate the harmful eﬀects of prolonged sitting
time. Across sitting time categories, all-cause mortality
was considerably reduced at higher levels of physicalactivity, and eliminated in those who were the most active.
These results were consistent in joint and stratiﬁed
analyses and in analyses of mortality due to cardiovasculardisease and cancer. By combining the results of a larger
number of studies, and using a harmonised approach to
reduce heterogeneity in the exposure variables, we wereable to reduce statistical uncertainty in the results andalso estimate levels of sitting time and physical activity for
informing public health policy.
The amount of physical activity in the top quartile
equated to approximately 60–75 min of moderate intensity
activity per day or more. This amount is beyond the basic
level of most physical activity recommendations for publichealth34,35 but only slightly greater than the upper amountrecommended in the Australian Physical Activity
Guidelines36 and the level recommended by the US
guidelines35 for “even greater health beneﬁts” (1 h a dayof moderate intensity activity). Notably, 60–75 min ofmoderate intensity activity is congruent with the level ofphysical activity showing maximum mortality beneﬁt in alarge meta-analysis from 2015.37 In the present study, thisamount of activity (reported by a quarter of the participants),
was required to eliminate the increased hazard associatedwith sitting for more than 8 h/day. However, even those in
the second quartile of physical activity (about 25–35 min ofmoderate intensity activity per day, which is congruent
with the basic level recommended), there were smaller
increases in mortality risks associated with high sitting
time than were seen in the least active group (about 5 min
per day), even though the risks were not completely
eliminated. In comparison with other risk factors for poor
health, the increased mortality risk (58%) in those who sat
for more than 8 h/day and were also least active, is similar
to that of smoking38 and obesity.39
If daily sitting time and TV-viewing time capture similar
aspects of sedentary behaviour, we expected broadly
similar magnitudes of associations from both exposures.
Yet the eﬀect of TV-viewing on all-cause mortality seemed
to be stronger in magnitude. This diﬀerence is congruent
with previous observations20 and might be partly due todiﬀerences in the accuracy of reporting these behaviours.
However, other explanations are also plausible. TVviewing typically occurs in the evenings (at least, for the
www.thelancet.com Vol 388 September 24, 2016

Articles

generation represented in the included studies), usually
after dinner, and prolonged postprandial sedentary time
may be particularly detrimental for glucose and lipid
metabolism.40 It is also plausible that individuals break up
their sitting time more frequently during work than whenviewing TV, and breaking up sedentary time seems to be
beneﬁcial for various cardio-metabolic risk factors.40
Another explanation for the diﬀerence observed could bethat TV-viewing might be accompanied by snacking
behaviours41 and food advertising on TV might aﬀect
eating behaviour.42 Thus, associated dietary behaviours
may explain some of the diﬀerences observed.
Our meta-analysis has several strengths. Most
important, all original study data were reanalysed in aharmonised manner. This approach substantially reduced
heterogeneity between studies for measures of sedentary
behaviour and physical activity, and allowed directinterpretation of levels of sitting time and physical activity(beyond comparing “high” vs “low”). The large sample
size allowed detailed joint analyses of the dose-response
associations among sedentary behaviours, physicalactivity, and mortality, providing precise eﬀect estimateswith narrow conﬁdence intervals. We performed subgroup
analyses to examine possible bias from any single study byreanalysing all data, excluding each study one at a time
and the results were essentially unchanged (data available
on request). Mortality ascertainment varied across studies
but all used oﬃcial national or regional registers, likely tobe high or complete. Our observation that physical activity
might eliminate the detrimental association between daily
sitting time and mortality is biologically plausible. Thereis evidence that 1 h of moderate intensity activity positively
inﬂuences postprandial lipid metabolism following 8 h ofsitting,43 and that 45 min of cycling at moderate intensity
following more than 10 h of sitting has beneﬁcial eﬀects
on glucose metabolism in type 2 diabetes.44
The study has also some limitations; ﬁrst, the majority ofstudies included participants older than 45 years and all but
one study was conducted in the USA, western Europe, orAustralia. Thus, the results may not be generalisable
beyond these populations. Second, all except two studies
combined data from men and women, which precluded
speciﬁc analyses. Third, residual confounding may exist.
A priori, we required contributing studies to control for thesame covariates included in their original publication; however, unmeasured or poorly measured confounders might
have distorted our results. Fourth, although we did not ﬁndany evidence for publication bias, we cannot rule out thatpublication bias could exist, because of the low number ofstudies in some analyses. Fifth, we attempted to minimise
bias from reverse causation (ie, illness causing individuals
to become sedentary) by including apparently healthy
participants; however, we cannot fully rule this bias out.
Sixth, all studies asked participants to self-report sedentary
behaviour and physical activity at one point in time. Thismeasure increases the chance of random measurement
error, which would attenuate true associations.
www.thelancet.com Vol 388 September 24, 2016

In conclusion, high levels of moderate intensity
physical activity (ie, about 60–75 min per day) seem toeliminate the increased risk of death associated withhigh sitting time. However, this high activity level
attenuates, but does not eliminate the increased risk
associated with high TV-viewing time. If long periods ofsitting time each day are unavoidable (eg, for work ortransport), it is important also to be physically active.
Contributors
All authors contributed to the design of the study, generated hypotheses,interpreted the data, and wrote and critically reviewed the report.
UE wrote the ﬁrst draft of the report. JS-J and UE did the literaturesearch. MWF analysed the data. MWF, JS-J, and UE had full access tostudy level data from all contributing studies.
Declaration of interests
We declare no competing interests.
Acknowledgments
UE was partly funded by the UK Medical Research Council programme
grant MC_UU_12015/3 Members of The Lancet Physical Activity Series II
steering group are: Adrian Bauman (School of Public Health, Sydney
University, Sydney, NSW, Australia), Ding Ding (Sydney School of Public
Health University of Sydney, Sydney, NSW, Australia), Ulf Ekelund(Norwegian School of Sports Sciences, Oslo, Norway and Medical ResearchCouncil Epidemiology Unit, University of Cambridge, Cambridge, UK),
Gregory Heath (Department of Health & Human Performance, Universityof Tennessee, Chattanooga, USA), Pedro C Hallal (Postgraduate
Programme in Epidemiology, Federal University of Pelotas, Pelotas, Brazil),
Harold W Kohl III (University of Texas School of Public Health, Austin,USA), I-Min Lee (Division of Preventive Medicine, Brigham and Women’s
Hospital, Harvard Medical School, Boston, MA, USA, and Department of
Epidemiology, Harvard T H Chan School of Public Health, Boston, MA,
USA), Kenneth E Powell (Atlanta, GA, USA), Michael Pratt (National
Center for Chronic Disease Prevention and Health Promotion, Emory
University, Atlanta, GA, USA), Rodrigo Reis (Prevention Research Centerin St Louis, Brown School, Washington University in St Louis, USA; Urban
Management Graduate Program, Pontiﬁcal Catholic University of Parana,
Curitiba, Brazil), and Jim Sallis (Division of Behavioural Medicine,
University of California, San Diego, CA, USA). Members of The Lancet
Sedentary Working Group are: Mette Aadahl (Department of Public Health,
Faculty of Health Sciences, University of Copenhagen, Copenhagen,Denmark), William J Blot (Department of Medicine, Vanderbilt University
Medical Center and Vanderbilt-Ingram Cancer Center, Nashville, TN,
USA), Tien Chey (Sydney School of Public Health, University of Sydney,
Sydney NSW, Australia), Anusila Deka (Epidemiology Research Program,
American Cancer Society, Atlanta, GA, USA), David Dunstan (Baker IDI
Heart and Diabetes Institute, Melbourne, VIC, Australia), Earl S Ford
(Division of Adult and Community Health, National Center for Chronic
Disease Prevention and Health Promotion, Centers for Disease Control
and Prevention, Atlanta, GA, USA), Kristine Færch (Steno Diabetes Center,
Gentofte, Denmark), Manami Inoue (Epidemiology and Prevention
Division, Research Center for Cancer Prevention and Screening, National
Cancer Center, Tokyo, Japan), Peter T Katzmarzyk (Pennington Biomedical
Research Center, Baton Rouge, LA, USA), Sarah Kozey Keadle (Nutritional
Epidemiology Branch, Division of Cancer Epidemiology and Genetics,
National Cancer Institute, Bethesda, USA), Charles E Matthews(Nutritional Epidemiology Branch, Division of Cancer Epidemiology andGenetics, National Cancer Institute, Bethesda, MD, USA), David Martinez(Preventive Medicine and Public Health School of Medicine Universidad
Autónoma de Madrid, Madrid, Spain), Alpa V Patel (Epidemiology
Research Program, American Cancer Society, Atlanta, GA, USA),
Toby Pavey (School of Human Movement and Nutrition Sciences,
The University of Queensland, Brisbane, QLD, Australia),
Christina Bjørk Petersen (National Institute of Public Health, University ofSouthern Denmark, Copenhagen, Denmark), Hidde Van Der Ploeg(Department of Public & Occupational Health, VU University Medical
Center Amsterdam, Amsterdam, Netherlands), Vegar Rangul (HUNT
Research Centre, Faculty of Health Science Nord-Troendelag University
College Levanger, Namsos, Norway), Parneet Sethi (Baker IDI Heart and1309

Articles

Diabetes Institute, Melbourne, VIC, Australia), Erik R Sund (HUNT
Research Centre, Faculty of Health Science Nord-Troendelag University
College Levanger, Namsos, Norway), Kate Westgate (MRC Epidemiology
Unit, University of Cambridge, Cambridge, UK), Katrien Wijndaele(MRC Epidemiology Unit, University of Cambridge, Cambridge, UK),
Song Yi-Park (Cancer Epidemiology Program, University of Hawaii Cancer
Center, Honululu, HI, USA). In addition to data from all the contributing
studies, this manuscript was prepared using WHIOS Research Materials
obtained from the NHLBI Biologic Specimen and Data Repository
Information Coordinating Center and does not necessarily reﬂect theopinions or views of the WHIOS or the NHLBI.
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