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Physical activity of physiotherapists in Germany: a cross-sectional study


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AimWe aimed to quantify the work-related physical activity of physiotherapists in Germany.Subjects and methodsWe included working physiotherapists aged between 18 and 65 years in Germany. We excluded physiotherapists working less than 20 h a week. We measured our primary outcome, work-related physical activity, by the average number of steps taken daily during work, standardized on an 8-h working day. We controlled the main outcome for potential confounders, such as working hours per week, age, weekday, and clinical setting (outpatient vs. inpatient), by multivariate linear regression analysis. We used R statistics for all statistical analyses.ResultsWe included 35 participants (7 outpatient and 28 inpatient), with a median age category of 20–29 years. Our participants had a mean work-related physical activity of 6614 steps (95% confidence interval, CI [6118; 7111]) per workday. Higher age, outpatient clinical setting, and working full time were associated with lower step count, but these associations were not statistically significant.Conclusions The work-related physical activity of physiotherapists in Germany is comparable with results from other countries and can be regarded as ‘low’. Our result, however, might be affected by volunteer bias and gender effects. Further research should identify high-risk groups in the profession for cost-effective prevention.
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Physical activity of physiotherapists in Germany: a cross-sectional
Bernhard Elsner
&Daniel Völker
&Mario Heinzmann
&Vera Rähmer
&Joachim Kugler
&Jan Mehrholz
Received: 16 January 2020 /Accepted: 8 March 2020
#The Author(s) 2020
Aim We aimed to quantify the work-related physical activity of physiotherapists in Germany.
Subjects and methods We included working physiotherapists aged between 18 and 65 years in Germany. We excluded phys-
iotherapists working less than 20 h a week. We measured our primary outcome, work-related physical activity, by the average
number of steps taken daily during work, standardized on an 8-h working day. We controlled the main outcome for potential
confounders, such as working hours per week, age, weekday, and clinical setting (outpatient vs. inpatient), by multivariate linear
regression analysis. We used R statistics for all statistical analyses.
Results We included 35 participants (7 outpatient and 28 inpatient), with a median age category of 2029 years. Our participants
had a mean work-related physical activity of 6614 steps (95% confidence interval, CI [6118; 7111]) per workday. Higher age,
outpatient clinical setting, and working full time were associated with lower step count, but these associations were not statis-
tically significant.
Conclusions The work-related physical activity of physiotherapists in Germany is comparable with results from other countries
and can be regarded as low. Our result, however, might be affected by volunteer bias and gender effects. Further research should
identify high-risk groups in the profession for cost-effective prevention.
Keywords Physiotherapy .Physical activity .Occupational health .Cross-sectional study
Physical inactivity is one of the major risk factors for devel-
oping chronic, non-communicable diseases (Guthold et al.
2018; Martin et al. 2006). This risk factor can easily be
avoided by physical activity (Ekelund et al. 2016; Rütten
and Pfeifer 2016). In Germany, every second employee states
to work in the majority of the time in a sitting or standing
position (Finger et al. 2017). In the literature, work-related
physical activity is regarded as health promoting (Abu-Omar
and Rutten 2008; Samitz et al. 2011; Sofi et al. 2007), al-
though not to the same extent as leisure-time-related physical
activity (Sofi et al. 2007). Despite this, an overall increase of
work-related physical activity seems to be a suitable approach
in order to prevent non-communicable chronic diseases
(Goldgruber and Ahrens 2010; Wilke et al. 2012).
An essential approach for achieving higher amounts of
work-related physical activity is a workplace-related ap-
proach, which should consist of: (1) a concrete supply of pre-
ventive measures, (2) the redesign of work-related processes,
and (3) the creation of activity-promoting infrastructure at
work (Rütten and Pfeifer 2016).
The creation of activity-promoting infrastructure at work
can also be beneficial for medical personnel; for example, it
was shown that cardiologists only walked between 5000 and
6000 steps per working day (Abd et al. 2012), instead of the
recommended amount of 10,000 to 12,000 steps per day
(Rütten and Pfeifer 2016). In the German healthcare system,
there are approximately 197,000 physiotherapists
(Statistisches Bundesamt 2019). According to the World
Confederation of Physical Therapy (WCPT), physiotherapists
Electronic supplementary material The online version of this article
( contains supplementary
material, which is available to authorized users.
*Bernhard Elsner
SRH University of Applied Health Sciences, Campus Gera,
Gera, Germany
Professorship of Public Health, Medical Faculty Carl Gustav Carus,
Dresden University of Technology, Fetscherstr. 74,
01307 Dresden, Germany
/ Published online: 18 March 2020
Journal of Public Health: From Theory to Practice (2021) 29:1339–1342
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explicitly cover the areas prevention and health promotion
and, amongst others, it is their core responsibility to motivate
people to participate in physical activity (WCPT 2017).
However, until now, it is unclear how active physiotherapists
in Germany are and if there is actually a need for primary
prevention in the physiotherapy profession.
The primary aim of our study was to quantify the work-
related physical activity in physiotherapists in Germany.
Materials and methods
This explorative study was a cross-sectional study and was
conducted in January 2018. It involved a convenience sample
among physiotherapists in Berlin and Gera. Inclusion criteria
were: (1) working clinically in an outpatient or inpatient set-
ting and (2) working more than 20 h per week. Exclusion
criteria was working less than 20 h per week.
Our primary outcome was the mean number of steps
walked per workday (continuous). We recorded the data on
five consecutive days with a pedometer (Omron Walking
Style IV, Omron, Kyoto, Japan), standardized on an 8-h work-
ing day. We choosepedometers because these are valid assess-
ments to estimate physical activity and the measurement on
five consecutive days is reliable (Kang et al. 2009a; Tudor-
Locke et al. 2002).
Our primary outcome, work-related physical activity, was
analyzed by a multivariate linear regression model, controlled
for working hours per week, age, weekday, and setting (out-
patient vs. inpatient) (Bolker et al. 2009). The predictive per-
formance of the model was estimated by cross validation (k=
2) and R
. In case of multicollinearity, the corresponding var-
iable was excluded from analysis (James et al. 2013). All
statistical analyses have been conducted with the software R
statistics (R Core Team 2012). The level of significance αwas
set to 0.05.
Overall, 35 physiotherapists participated in the study. Their
characteristics can be found in Table 1.
Primary outcome
The mean number of steps walked during an 8-h working day
was 6614 (95% confidence interval, CI [6118; 7111]). A
boxplot of the distribution of the number of steps walked over
the age of the participants can be found in Fig. 1.
The number of steps walked during an 8-h working day
depending on the setting (outpatient vs. inpatient) can be
found in Fig. 2. The number of steps (mean (standard devia-
tion, SD)) walked in an outpatient setting was 6393 (2195)
and in an inpatient setting, it was 6670 (1242). There was no
statistically significant difference between the two settings
(mean difference, MD = 277 steps; t=0.32044, p=0.76,
95% CI [2316; 1763].
The number of steps walked per 8-h working day (mean
(SD)) varied slightly between weekdays: Monday 6157
(1697), Tuesday 5827 (1768), Wednesday 6570 (1971),
Thursday 6364 (1665), and for Friday 5801 (1771). A boxplot
over the distributions can be found in Fig. 3.
The analysis of the dependent variable (number of steps
walked during an 8-h working day) by multivariate linear
regression (n= 34) with the prediction variables age, working
time (hours per week), and professional setting (outpatient vs.
inpatient) yielded no statistically significant difference
(adjusted R
in the test data = 0.09; Table 2). The independent
variable weekday was removed from the model due to
Table 1 Characteristics
of the participants No. (%)
Age (years)
1719 1 (3)
2029 20 (57)
3039 9 (26)
4049 4 (11)
5059 1 (3)
6067 0
Outpatient 7 (20)
Inpatient 28 (80)
Working time
Full-time (40 h/week) 29 (83)
Part-time (<40 h/week) 6 (17)
17−20 20−29 30−39 40−49 50−59
5000 7000 9000
Boxplot of steps walked by age
e cate
ory in years
Number of steps during an 8−hour working day
Fig. 1 Number of steps walked during a standardized 8-h working day by
age category (n=35)
1340 J Public Health (Berl.): From Theory to Practice (2021) 29:1339–1342
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Our results suggest that physiotherapists in Germany walk
about (mean (SD)) 6500 (1600) steps on a representative 8-h
working day. Although the differences were not statistically
significant, the number of steps walked seems to be decreased
with higher age and increased in physiotherapists working in
an inpatient clinic compared to an outpatient setting.
The results of this study are in line with Abd et al. (2012), who
showed that cardiologists and cardiac surgeons achieved a sim-
ilar level of physical activity of 5000 to 6000 steps per day (Abd
et al. 2012). According to the pedometer index of Tudor-Locke
and Bassett (2004), the work-related physical activity of physio-
therapists in Germany should be classified as low active
(Tudor-Locke and Bassett 2004). In a multicenter cross-
sectional survey, which measured work-related physical activity
among American physiotherapists by accelerometers, there were
similar results in this regard (Brewer et al. 2016). However, the
recommended optimum of physical activity by guidelines was
not achieved: the mean (SD) number of steps walked during
work in an outpatient setting was 3195 (1333) steps and in inpa-
tient setting, it was 4475 (1465) (Brewer et al. 2016). Our results
showed that physiotherapists in Germany walk more steps during
work than their colleagues in the United States and that working
in an inpatient setting was associated with a higher level of phys-
ical activity. The latter could be explained by different work
organization procedures in inpatient settings (e.g., working on a
single hospital ward vs. working among different wards), which
could have resulted in longer distances to be walked in order to
see a patient. There are also indications that longer working time
was associated with a lower step count. This could be explained
by a possibly higher compression of work in the schedule of part-
time workers, thus resulting in a higher relative physical activity.
The results show that physiotherapists in Germany are suit-
able candidates for individualized health promotion programs by
promoting physical activity (Ziesche and Köppel 2017), which
should: (1) be implemented after assessing the employeesde-
mands, (2) be close to the workplace, (3) have a responsible key
person, and (4) have a marketing platform (Wollesen et al. 2017).
A limitation of this cross-sectional study is that volunteer
bias may have occurred and rather physically active therapists
voluntarily participated in the study, which may overestimate
the real amount of work-related physical activity in physio-
therapists in Germany. Essential covariates like the age of the
participants, clinical setting, and weekday have been con-
trolled and taken into account in the analysis. It should also
be taken into account that only the surveillance of physical
activity with pedometers can raise the physical activity by up
to 2000 steps per day, which may also result in an overestima-
tion of physical activity (Kang et al. 2009b).
One could also argue that the analysis did not control for
gender effects. In the published literature, it was shown that
women in general have a lower mean work-related physical
activity than men (Finger et al. 2017). Since this might rather
be a self-selection effect between different professions, we
discarded this analysis.
Another limitation is the small sample size of this study, so
future studies should recruit more participants, control for
gender-specific effects, and include other professional settings
Table 2 Analysis of the predictors age, clinical setting, and working
time on the primary outcome, work-related physical activity (numbers of
steps walked during an 8-h working day). Multivariate linear model with
cross-validation applied on the test data (n=34).Adjusted R
= 0.09
βcoefficient Standard error t-Value p-Value
(Intercept) 9926.6 1775 5.592 <0.0001
Age 120.06 521.23 0.230 0.82
Setting 107.28 783.89 0.137 0.89
Working time 81.82 40.11 2.040 0.06
Outpatient Inpatient
5000 7000 9000
Boxplot of steps walked by clinical setting
Clinical settin
Number of steps during an 8−hour working day
Fig. 2 Number of steps walked during a standardized 8-h working day by
clinical setting (n=35)
Mon Tue Wed Thur Fri
2000 4000 6000 8000
Boxplot of steps walked by weekday
Number of steps during an 8−hour working day
Fig. 3 Number of steps walked during a standardized 8-h working day by
weekday (n=35)
1341J Public Health (Berl.): From Theory to Practice (2021) 29:1339–1342
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of physiotherapists (like working in schools/universities), as
well as physiotherapists working over weekends.
The work-related physical activity of physiotherapists in
Germany can be regarded as low activeand is comparable
to those of physiotherapists and other medical professions in
other industrialized countries.
Contributions of authors Conceptualization: Author 2, Author 3, Author
4, Author 1; Methodology: Author 1; Formal analysis and investigation:
Author 1; Writing - original draft preparation: Author 1; Writing - review
and editing: Author 6, Author 5; Funding acquisition: Author 1, Author 2,
Author 3, Author 4; Supervision: Author 5, Author 6.
Funding Information Open Access funding provided by Projekt DEAL. We
would like to thank the Anschubfinanzierung of the SRH University of
Applied Health Sciences for supporting the acquisition of the pedometers.
Compliance with ethical standards
Informed consent was obtained from all individual participants included in
the study. The approval of the local ethics committee was given (1422-0515).
All testing was ethically harmless and the measures used are internationally
certified and are standard outcome measures for physical activity. The eval-
uation was carried out in accordance with the 2013 Helsinki Declaration.
Conflict of interest The authors declare that they have no conflict of interest.
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Abd TT, Kobylivker A, Perry A, Miller Iii J, Sperling L (2012) Work-
related physical activity among cardiovascular specialists. Clin
Cardiol 35:7882.
Abu-Omar K, Rutten A (2008) Relation of leisure time, occupational, domes-
tic, and commuting physical activity to health indicators in Europe. Prev
Med 47:319323.
Bolker BM, Brooks ME, Clark CJ, Geange SW, Poulsen JR, Stevens
MHH, White J-SS (2009) Generalized linear mixed models: a prac-
tical guide forecology and evolution. Trends Ecol Evol 24:127135.
Brewer W, Ogbazi R, Ohl D, Daniels J, Ortiz A (2016) A comparison of
work-related physical activity levels between inpatient and outpa-
tient physical therapists: an observational cohort trial. BMC Res
Notes 9:313.
Ekelund U, Steene-Johannessen J, Brown WJ et al (2016) Does physical
activity attenuate, or even eliminate, the detrimental association of
sitting time with mortality? A harmonised meta-analysis of data
from more than 1 million men and women. Lancet 388:1302
Finger JD, Mensink GBM, Lange C, Manz K (2017) Arbeitsbezogene
körperliche Aktivität bei Erwachsenen in Deutschland. J Health
Monit 2:29-36.
Goldgruber J, Ahrens D (2010) Effectiveness of workplace health pro-
motion and primary prevention interventions: a review. J Public
Health 18:7588.
Guthold R, Stevens GA, Riley LM, Bull FC (2018) Worldwide trends in
insufficient physical activity from 2001 to 2016: a pooled analysis of
358 population-based surveys with 1.9 million participants. Lancet Glob
Health 6:e1077e1086.
James G, Witten D, Hastie T, Tibshirani R (2013) An introduction to
statistical learning: with applications in R. Springer, New York
Kang M, Bassett DR, Barreira TV et al (2009a) How many days are enough?
A study of 365 days of pedometer monitoring. Res Q Exerc Sport 80:
Kang M, Marshall SJ, Barreira TV, Lee JO (2009b) Effect of pedometer-
based physical activity interventions: a meta-analysis. Res Q Exerc
Sport 80:648655.
Martin BW, Kahlmeier S, Racioppi F et al (2006) Evidence-based phys-
ical activity promotion - HEPA Europe, the European Network for
the Promotion of Health-Enhancing Physical Activity. J Public
Health 14:5357.
R Core Team (2012) R: a language and environment for statistical com-
puting. R Foundation for Statistical Computing, Vienna, Austria
Rütten A, Pfeifer K (eds) (2016) Nationale Empfehlungen für Bewegung
und Bewegungsförderung. FAU Erlangen-Nürnberg, Nürnberg
Samitz G, Egger M, Zwahlen M (2011) Domains of physical activity and
all-cause mortality: systematic review and doseresponse meta-
analysis of cohort studies. Int J Epidemiol 40:13821400. https://
Sofi F, Capalbo A, Marcucci R (2007) Leisure time but not occupational
physical activity significantly affects cardiovascular risk factors in
an adult population. Eur J Clin Invest 37:947953.
Statistisches Bundesamt (2019) Statistisches Bundesamt Deutschland -
GENESIS Online-Ergebnis - 23621-0002. https://www-genesis. Accessed 12 Nov 2019
Tudor-Locke C, Bassett DR Jr (2004) How many steps/day are enough?
Preliminary pedometer indices for public health. Sports Med 34:1
Tudor-Locke C, Williams JE, Reis JP, Pluto D (2002) Utility of pedom-
eters for assessing physical activity: convergent validity. Sports Med
Wilke C, Krämer K, Biallas B, Froböse I (2012) Lebensqualität und
körperliche Aktivität im betrieblichen Kontext. Präv Gesundheitsf
Wollesen B, Menzel J, Drögemüller R, Hartwig C, Mattes K (2017) The
effects of a workplace health promotion program in small and
middle-sized companies: a prepost analysis. J Public Health 25:
World Confederation of Physical Therapy (WCPT) (2017) Policy state-
ment: description of physical therapy.
ps-descriptionPT. Accessed 12 Nov 2019
Ziesche S, Köppel M (2017) Wirkung der Aktivität am Arbeitsplatz auf
die Freizeitaktivität. Präv Gesundheitsf 12:2226.
Publishersnote Springer Nature remains neutral with regard to jurisdic-
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Full-text available
Background: Insufficient physical activity is a leading risk factor for non-communicable diseases, and has a negative effect on mental health and quality of life. We describe levels of insufficient physical activity across countries, and estimate global and regional trends. Methods: We pooled data from population-based surveys reporting the prevalence of insufficient physical activity, which included physical activity at work, at home, for transport, and during leisure time (ie, not doing at least 150 min of moderate-intensity, or 75 min of vigorous-intensity physical activity per week, or any equivalent combination of the two). We used regression models to adjust survey data to a standard definition and age groups. We estimated time trends using multilevel mixed-effects modelling. Findings: We included data from 358 surveys across 168 countries, including 1·9 million participants. Global age-standardised prevalence of insufficient physical activity was 27·5% (95% uncertainty interval 25·0-32·2) in 2016, with a difference between sexes of more than 8 percentage points (23·4%, 21·1-30·7, in men vs 31·7%, 28·6-39·0, in women). Between 2001, and 2016, levels of insufficient activity were stable (28·5%, 23·9-33·9, in 2001; change not significant). The highest levels in 2016, were in women in Latin America and the Caribbean (43·7%, 42·9-46·5), south Asia (43·0%, 29·6-74·9), and high-income Western countries (42·3%, 39·1-45·4), whereas the lowest levels were in men from Oceania (12·3%, 11·2-17·7), east and southeast Asia (17·6%, 15·7-23·9), and sub-Saharan Africa (17·9%, 15·1-20·5). Prevalence in 2016 was more than twice as high in high-income countries (36·8%, 35·0-38·0) as in low-income countries (16·2%, 14·2-17·9), and insufficient activity has increased in high-income countries over time (31·6%, 27·1-37·2, in 2001). Interpretation: If current trends continue, the 2025 global physical activity target (a 10% relative reduction in insufficient physical activity) will not be met. Policies to increase population levels of physical activity need to be prioritised and scaled up urgently. Funding: None.
Full-text available
AimEmployees have to deal with work-related problems like a sedentary work style or musculoskeletal disorders. Moreover, psychological factors like time pressure can lead to the inability to work. The Fit for Business-program started in order to provide health promotion interventions for small and middle-sized companies. This study analyzed data concerning the infrastructure, activity levels and critical factors of success to increase physical activity levels. Subject and methodsA total of N = 342 employees filled out standardized questionnaires about the infrastructure needed for health promotion, their workload, their physical and mental well-being, their resources and their health-related behavior. Statistical pre–post analysis included chi2-tests and multivariate tests. Qualitative interviews identified factors necessary for a successful implementation. ResultsThere were differences concerning employees’ specific health conditions and infrastructures established for health promotion. The number of physically active employees increased significantly (p = 0.015, Z = –3.67). This increase in sporting activity was due to participation in sports in fitness centers (+16.5 %, p < 0.001, Z = 5.217), company sports (+8.7 %, p = 0.002, Z = –3.024) and sports clubs (+6.4 %, p = 0.048, Z = –1.976). Moreover, when the specific needs of the employees were considered, the number of people involved in several kinds of sports increased. Conclusions The implementation of health promotion programs in small and middle-sized companies is successful if the following factors are considered: a responsible key person or a linkage group and a marketing platform for the programs (e.g. a trail course) exists, an assessment of the employees’ demands for health promotion takes place and the interventions are geographically close to the company and compatible with working hours. Additionally, there might be a relationship between the company-specific infrastructure for health promotion and resulting workloads or physical complaints.
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Background Physical therapists (PTs) work in a variety of healthcare settings with varied levels of physical activity demands placed on them. The purpose of this study is to compare the physical activity (PA) levels between PTs in inpatient versus outpatient environments for one work week using a cross-sectional design. Methods Sixty-one PTs (30 inpatient, 31 outpatient) wore a tri-axial accelerometer and inclinometer for one work-week. The number steps-per-day, PA intensities, energy expenditures and postural positions adopted during the work day were recorded. ResultSignificantly longer amounts of time spent sitting was found for inpatient PTs regardless of the significantly higher number of steps-per-day. Outpatient PTs had a higher number of breaks from sedentary activity with those breaks being longer than the inpatient PTs. The percentage of time spent performing moderate-vigorous PA approached significance implying more time was spent performing these types of activities for outpatient PTs. The energy expenditures between the two groups of PTs were not different. Conclusion This study compared the differences in physical activity levels between physical therapists who worked at inpatient versus outpatient environment as little is known about their activity levels. Inpatient physical therapists took more steps per day than outpatient physical therapists but the outpatient physical therapists were less sedentary and took more frequent and longer breaks from sedentary activities. The energy expenditures were similar between both types of therapists and this may be reflective of the gender and bodyweight differences between the groups that equalizes the energy expenditures. The findings of this study suggests that there are differences in the physical activity demands between inpatient and outpatient physical therapists. The results of this study may serve dual purposes: (1) employers may be able to more accurately describe the expected physical activity demands to future employees; (2) individuals tasked with preparing PTs to physically manage their work environment can outline training programs that are diverse based on the specific work environment of PTs.
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform.Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.
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 of prolonged 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 data from 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 (in metabolic equivalent of task [MET]-hours per week). We then combined data across all studies to analyse the association of 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. Compared with the referent (<4 h of sitting per day and highest quartile of physical activity [>35·5 MET-h per week]), there was no increased 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 was significantly 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 the increased 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 for work and may also inform future public health recommendations. Funding: None.