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Study protocol: The associations between sitting at work and all-cause mortality

Simone Visbjerg Møller1, Harald Hannerz1, Andreas Holtermann1, Hidde P. van der Ploeg2

1. National Research Centre for the working Environment, Denmark.

2. Department of Public and Occupational Health, EMGO Institute for Health and Care

Research, VU University Medical Center Amsterdam, the Netherlands.

Aim

The overall aim of the study is to investigate the independent relationship between sedentary work and all-

cause mortality. The aim will be investigated by testing the following hypothesis in a general Danish

working population:

1. There is a difference in the all-cause mortality risk between employees engaged in sedentary work

and employees not engaged in sedentary work.

2. A dose-response relationship exists between time spent sitting at work and all-cause mortality risk.

Furthermore the change over time of sitting at work in Denmark will be explored.

Methods

Data sources

This study will use data from the Danish Work Environment Cohort Study (DWECS), the Danish Register of

Causes of Death and the Central Person Register. DWECS is a cohort study of the working population in

Denmark which was conducted every five years from 1990-2010. Participants were randomly drawn among

Danish residents aged 18-59 years at baseline. At the waves 1995-2010 the population was supplemented

with age and migration panels to ensure representativeness of the Danish working population. In 2005 and

2010 the main cohort was further supplemented. This study includes data from the four waves 1990-2005

when testing for differences in mortality risk and from the waves 1990-2010 when exploring changes in

sitting time in Denmark. Data was collected by telephone interviews in 1990-2000 and by either postal or

web-based questionnaires (90%) or telephone interviews (10%) in 2005, and by web-based questionnaires

in 2010 (1). Response rates vary from 90 % in 1990 to 53 % in 2010.

The Central Person Register contains information on gender, addresses and dates of birth, death and

migration for every person who is or has been an inhabitant of Denmark sometime between 1968 and

present (2).

Sedentary work

In the four included DWECS waves the respondents were asked: Does your job involve sitting? The

corresponding response categories were: Almost all of the time; app. ¾ of the time; app. ½ of the time; app.

¼ of the time; rarely; never. Table 1 illustrates the distribution of time spent sitting at work for all

respondents in the cohort older than 20 years.

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Table 1: Distribution of time spent sitting at work, DWECS 1990-2005.

1990 1995 2000 2005

N % N % N % N %

Almost all of the time 1,127 20.1 833 15.9 1,089 18.4 1,659 18.9

App. ¾ of the time 785 14.0 922 17.6 961 16.2 1,628 18.6

App. ½ of the time 917 16.4 924 17.6 1,081 18.2 1,510 17.2

App. ¼ of the time 714 12.7 810 15.5 917 15.5 1,530 17.4

Rarely 713 12.7 1,004 19.2 1,111 18.7 1,756 20.0

Never 1,352 24.1 745 14.2 767 12.9 686 7.8

TOTAL 5,608 100 5,238 100 5,926 100 8,769 100

The variable on sedentary work is combined with self-reported information on actual working hours in

main and second jobs in order to approximate actual time spent sitting at work. The total weekly working

hours have been multiplied by following coefficients corresponding to the indicated amount of sedentary

work:

Almost all of the time: 0.875

App. ¾ of the time: 0.75

App. ½ of the time: 0.5

App. ¼ of the time: 0.25

Rarely: 0.125

Never: 0

In the Danish National Health Survey work is considered sedentary if it involves at least 6 hours of sitting

per day (3;4). If this cut point is applied to the present study and the above described operationalization of

sitting hours in hypothesis 1 it would result in respondents being categorized as non-sedentary if they

indicate to sit ¾ of the time in a 37 hour work week (standard Danish work week). Furthermore there are

far more women than men working on reduced hours (5). This means that, for example, women who work

32 hours a week and indicate to sit almost all of the time at work would not be classified as sedentary (32

hours*0.875 = 28 hours a week, corresponding to 5.6 hours a day). Instead respondents are considered

exposed to sedentary work in the present study if they spent 24 hours a week or more sitting at work, as

this corresponds to ¾ of a 32 hour work week, and unexposed otherwise (hypothesis 1). Table 2 illustrates

the distribution of respondents exposed to sedentary work.

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Table 2: Distribution of employees exposed to sedentary work

(≥24 hour sitting at work a week), DWECS 1990-2005.

1990 1995 2000 2005

N % N % N % N %

Sedentary work 1795 32,0 1706 32,6 2045 34,5 3120 35,6

Non-sedentary work 3812 68,0 3529 67,4 3878 65,4 5427 61,9

Missings 1 0,0 3 0,1 3 0,1 222 2,5

I ALT 5608 100 5238 100 5926 100 8769 100

Endpoint

The endpoint of this study will be mortality from all causes and employees from DWECS will be followed-up

for deaths in the Danish Central Person Register.

Confounders

Potential confounders of the association between sedentary work and mortality are identified using the

theory of Directed Acyclic Graphs (DAGs), which is a tool to ensure relevant and appropriate adjustments in

the statistical analyses (6;7). Figure 1 illustrates the assumed causal pathway between sedentary work and

mortality based on findings in the existing scientific literature.

According to figure 1 the association between sedentary work and mortality is possibly confounded by SES,

diet, smoking, BMI and waist circumference. Light intensity physical activity is an intermediate variable on

the direct pathway linking sedentary work and mortality. Furthermore age and sex is assumed to interact

with most of the illustrated associations in figure 1.

The association between sedentary work and all-cause mortality may be strongly confounded by the

influence of socio-economic status, as white collar professions and managerial positions are far more likely

to involve sitting at work. Employees in professions involving much sitting usually have more beneficial

health behaviours due to their high social status, such as lower rates of smoking, higher intake of fruits and

vegetables as well as higher levels of moderate-to-vigorous physical activity. This might offset the negative

effects of sedentary work (8;9).

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Figure 1: Theoretical DAG for the association between sedentary work and mortality.

Sedentary work All-cause mortality

Overweight/obesity

Socio-economic status

Smoking

Diet

Light intensity PA

Sex Age Moderate-to-vigorous PA

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Operationalization of confounders

Table 3 shows the operationalization of variables in this study. Overweight or obesity is measured by BMI.

The question on leisure time physical activity is not included in the questionnaire until 2000 and the

questions differ between 2000 and 2005. However the respondents are asked which activity describes their

leisure time best, and the response category indicating physical inactivity (less than 2 hours of moderate

physical activity a week) is comparable between the two waves:

2000: Almost completely physically passive or only having light-intensity activity less than 2 hours

per week (e.g. reading, watching television, going to the cinema)

2005: Reads, watches television, goes to the cinema or other sedentary activity or only having light-

intensity physical activity less than 2 hours per week

The variables will be dichotomised to adjust for possible confounding due to differences in leisure time

physical activity.

At all four DWECS waves the respondents have indicated their smoking status as current, former or never

smoker. Socio economic status is defined according to the respondent´s term of employment and classified

into three groups of white-collar and two groups of blue-collar workers. Health status is self-rated by the

respondents and for the purpose of this study health status is dichotomised into poor (poor and very poor)

and good health (fair, good and very good).

In 2000 and 2005 the respondents have indicated how often they consume fruit and vegetables. The

variable will be dichotomised to indicate whether respondents consume fruit or vegetables at least once a

day.

Table 3: Operationalization of confounders in the statistical analyses.

Theoretical

variable

Operationalization

1990

Operationalization

1995

Operationalization

2000

Operationalization

2005

SES Job function Job function Job function Job function

Physical activity N/A N/A Physically inactive

in leisure time*

(yes/no)

Physically inactive

in leisure time*

(yes/no)

Health status Poor self-rated

health (yes/no)

Poor self-rated

health (yes/no)

Poor self-rated

health (yes/no)

Poor self-rated

health (yes/no)

Smoking status Yes/former/never Yes/former/never Yes/former/never Yes/former/never

Diet N/A N/A Consume fruit or

vegetables every

day (yes/no)

Consume fruit or

vegetables every

day (yes/no)

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BMI <25; 25-<30; ≥30 <25; 25-<30; ≥30 <25; 25-<30; ≥30 <25; 25-<30; ≥30

Age <40; 40-49;50-59;

60-69;≥70 years

<40; 40-49;50-59;

60-69; ≥ 70 years

<40; 40-49;50-59;

60-69; ≥70 years

<40; 40-49;50-59;

60-69; ≥70 years

Calender year 1991-1994;1995-1999;2000-2004;

2005-2010

1995-1999;2000-2004;

2005-2010

2000-2004; 2005-2010

2005-2010

* Difference in the formulation of questions, where it is deemed possible to make a common operationalization. N/A

The question is not available in the DWECS wave.

Study population and follow-up

People who are categorised as employees according to the DWECS-interview in 1990 (October - November)

enter the follow-up 1 January 1991 if they on that date:

are alive and live in Denmark

are at least 20 years old

have a BMI ≥ 18.5 and <50

People who have not yet entered the cohort and are categorised as employees according to the interview

in 1995 will enter the follow-up 1 January 1996, if they fulfil the above requirements on that date. The

same principle is used for entries among the interviewees of 2000 and 2005.

Each of the included persons is followed until any of the following events occur: (S)he dies, (s)he emigrates

or the study period ends (31 December 2010). Thus, respondents who resign from the labour market are

still included in the analyses, although the studied exposure ceases.

Power calculations

The above follow-up strategy on the employees in DWECS (without linkage to the exposure data) yields in

total 590 deaths. The power calculations for hypothesis 1 are given in the graph below. They are based on

the Poisson distribution, the propagation of error formulas and the central limit theorem. The overall

significance level is set to 0.05 and the hypotheses are two-tailed.

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Figure 2: Power of detecting differences in mortality rates

between workers with and without sedentary work as a

function of the rate ratio (RR), follow-up 1991-2010.

Statistical analyses

The association between sedentary work and risk of death will be analysed using multiple Poisson

regression. Since the exposure and confounder variables are measured at four waves the exposure status

might change over time. In case of a missing data point of an exposure or confounder variable at a certain

wave the most recently available information is carried forward. The carry backward method is not applied

due to the risk of reverse causality. Respondents with missing information on the exposure variable (sitting

at work or working hours) at all waves will be excluded.

According to the theory of DAG it would be sufficient to adjust the analysis for socio economic status and

stratify the analysis on age and sex. Any further adjustment will be done in additional analysis with caution

of interpretation due to the risk of overadjustment (cf. table 4, sensitivity analysis 1). However this ideal

approach is challenged by the low number of events in the follow-up period, cf. the power calculations, and

instead age and sex will be included in the model 1 as confounders (in addition to socio economic status).

The follow-up period will be 2001-2010 for analysis including variables available in the 2000 and 2005

waves only, that is, physical activity and diet, in order to reduce the risk of reverse causation and selection

bias.

All participants under the age of 40 years will be excluded in sensitivity analyses (cf. table 4, sensitivity

analyses 2 and 3) to study how the results will be influenced when eliminating cases that are likely to have

other aetiologies than those of interest.

Sick people might tend to sit more at work and have higher mortality rates, which will introduce selection

bias in this study. Excluding participants with poor self-rated health will affect the power of detecting an

association. Adjusting the analyses for self-rated health, on the other hand, might attenuate the association

of interest, since sedentary work is likely to influence all-cause mortality risk through health. We explore

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the effect of poor health by conducting additional sensitivity analyses excluding and adjusting for poor

health, respectively, operationalised as self-rated poor and very poor health (cf table 4, sensitivity analyses

4-7).

In order to detect possible biased estimates due to deaths caused by unknown diseases, cases of death that

occurred within the first 3 years of cohort entry will be excluded in an additional sensitivity analysis (cf.

table 4, sensitivity analysis 8).

Since the chosen threshold of sedentary work (≥ 24 hours a week spent sitting) is arbitrary, we introduce

two additional sensitivity analyses (Sensitivity analyses 9-10) for hypothesis 1 including the thresholds for

sedentary work of 18 and 30 hours a week spend sitting, respectively.

Table 4: Approach to statistical analysis testing associations between sedentary work and mortality risk

Hypothesis 1 Hypothesis 2 Hypothesis 2

Test Poisson Poisson Goodness of fit

Covariates included

Model 1 Follow-up 1991-2010

Age, sex, SES, calendar period

Age, sex, SES, calendar period

Age, sex, SES, calendar period

Sensitivity analysis 1 Follow-up 2001-2010

Age, sex, SES, physical activity, smoking status, diet, BMI

Age, sex, SES, physical activity, smoking status, diet, BMI

Sensitivity analysis 2 Follow-up 1991-2010

Model 1 excluding participants < 40 years

Model 1 excluding participants < 40 years

Sensitivity analysis 3 Follow-up2001-2010

Sensitivity analysis 1 excluding participants < 40 years

Sensitivity analysis 1 excluding participants < 40 years

Sensitivity analysis 4 Follow-up 1991-2010

Model 1 excluding participants with poor self-rated health at entry

Model 1 excluding participants with poor self-rated health at entry

Sensitivity analysis 5 Follow-up 2001-2010

Sensitivity analysis 1 excluding participants with poor self-rated health at entry

Sensitivity analysis 1 excluding participants with poor self-rated health at entry

Sensitivity analysis 6 Follow-up 1991-2010

Model 1 adjusting for poor self-rated health at entry

Model 1 adjusting for poor self-rated health at entry

Sensitivity analysis 7 Follow-up 2001-2010

Sensitivity analysis 1 adjusting for poor self-rated health at entry

Sensitivity analysis 1 adjusting for poor self-rated health at entry

Sensitivity analysis 8 Model 1 excluding cases of death occurring within 3 years of cohort entry

Model 1 excluding cases of death occurring within 3 years of cohort entry

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Sensitivity analysis 9 Follow up 1991-2010

Model 1 with ≥ 30 hours spent sitting at work as threshold for sedentary work

Sensitivity analysis 10 Follow up 1990-2010

Model 1 with ≥ 18 hours spent sitting at work as threshold for sedentary work

Hypothesis 1

Poisson proportional hazards regression will be used to estimate hazard ratios (HR) and corresponding 95%

confidence intervals for the mortality risk in sedentary workers (≥ 24 hours a week) compared to non-

sedentary workers. The test of hypothesis 1 is regarded statistically significant, if 1 is not contained in the

estimated 95% confidence interval of model 1.

Hypothesis 2

The continuous variable of sitting time will be included in the regression models to test whether a dose-

response relationship exists between time spent sedentary at work and the mortality risk. Furthermore chi2

Goodness of fit test will be conducted in order to confirm a possible dose-response relationship. An ordinal

scale of time spent sedentary at work will be included in this analyses, cf. table 5.

Table 5: Ordinal scale for sedentary time for the Goodness of fit test

1990 1995 2000 2005

Weekly time

spent sedentary

N % N % N % N %

0 hours 1386 24.7 769 14.7 797 13.4 697 8,2

>0 - <10 hours 1281 22.8 1660 31.7 1748 29.5 2710 31.7

10 - <20 hours 923 16.5 892 17.0 1016 17.1 1494 17.5

20 - < 30 hours 844 15.0 889 17.0 944 15.9 1435 16.8

30 - < 35 hours 827 14.7 660 13.1 461 13.6 352 14.1

35+ hours 346 6.2 365 7.4 348 10.3 278 11.2

Missings 1 0.0 3 0.1 3 0.1 222 2.5

TOTAL 5608 100 5238 100 5926 100 8769 100

The test of hypothesis 2 is regarded statistical significant if 1 is not contained in the estimated 95%

confidence interval of model 1. Furthermore the Goodness of Fit test in model 1 must be non-significant (p

> 0.05).

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In order to confirm hypothesis 2 based on the stated p-values, hypothesis 1 must be confirmed. However

hypothesis 2 will be explored even if hypothesis 1 is not confirmed, because the threshold for being

sedentary in hypothesis 1 is arbitrary and furthermore in order to study any non-linear trend for the

association between sedentary work and mortality risk.

Development in sedentary work

Sedentary work in the Danish labour force over time (1990, 1995, 2000, 2005 and 2010) will be explored

with descriptive statistics using different operationalizations for sitting time. Both the original response

categories presented in table 1 and the ordinal scale presented in table 5 will be used. Proportions of

respondents engaged in sedentary work (at least 24 hours per week spent sitting at work, in line with the

definition used for hypothesis 1) will also be calculated. Both crude and age and gender standardised

proportions will be calculated. The DWECS sample of 1990 (those with non-missing values on sitting) will be

used as the standard population. The following age categories will be used: < 30; 30-39; 40-49; ≥ 50 years.

Furthermore, the proportion of respondents engaged in sedentary work according to hypothesis 1 will be

given with 95% confidence intervals.

Discussion

This study will provide important information on sitting time at work as an independent risk factor of all-

cause mortality. The strengths in this study are that it uses a sample that is representative for the Danish

labor force, and that it contains information on many potential confounders. Furthermore information on

sedentary work and confounders are measured repeatedly during the follow-up period reducing

misclassification related to changes in exposure status. The operationalization of hours spent sedentary at

work enables the examination of doses-response association which has been a limitation in previous

studies. A few limitations must be addressed. The study does not have sufficient power to test interaction

effects of age or gender, and the analysis cannot be stratified on these parameters which may bias the

results. Also, the power in the analysis including additional confounders might be too low to detect any

differences in mortality rates between sedentary and non-sedentary workers. Furthermore the information

on physical activity and diet might be insufficient due to the dichotomization, and unmeasured

confounding from total amount of sitting might exist.

Ethical approval

According to Danish law, questionnaire and register based studies do not need approval by ethical and

scientific committees, nor informed consent. DWECS is approved by the Danish Data Protection Agency,

journal number: 2007-54-0059 and 2012-54-0042.

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Characteristics of participants regarding confounders

Table 6: Age of the participants, DWECS 1990-2005

1990 1995 2000 2005

N % N % N % N %

< 40 years 3078 54.9 2726 52.0 2826 47.7 3401 38,8

40-49 years 1570 28.0 1469 28.0 1567 26.4 2595 29,6

50-59 years 960 17.1 922 17.6 1274 21.5 2453 28,0

60-69 years 0 0.0 121 2.3 259 4,4 306 3,5

70+ 0 0.0 0 0.0 0 0.0 14 0,2

Missings 0 0.0 0 0.0 0 0.0 0 0,0

TOTAL 5608 100 5238 100 5926 100 8769 100

Table 7: Participant´s sex, DWECS 1990-2005.

1990 1995 2000 2005

N % N % N % N %

Men 2900 51.7 2753 52.6 3122 52.7 4307 49.1

Women 2708 48.4 2485 47.4 2804 47.3 4462 50.9

TOTAL 5608 100 5238 100 5926 100 8769 100

Table 8: BMI, DWECS 1990-2005.

1990 1995 2000 2005

N % N % N % N %

< 25

Normal

4006 71.4 3474 66.3 3520 59.4 4806 54.8

25- <30

Overweight

1317 23.5 1437 27.4 1888 31.9 2909 33.2

30+

Obese

260 4.6 290 5.5 457 7.7 901 10.3

Missings 25 0.4 37 0.7 61 1.0 1.7 1.7

TOTAL 5608 100 5238 100 5926 100 8769 100

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Table 9: Leisure time physical inactive

DWECS 2000 and 2005.

2000 2005

Physical inactive N % N %

Yes 895 15.1 1427 16.3

No 5015 84.6 7262 82.8

Missings 16 0.3 80 0.9

TOTAL 5926 100 8769 100

Table 10: Smoking status, DWECS 1990-2005.

1990 1995 2000 2005

N % N % N % N %

Yes 2648 47.2 2198 42.0 2190 37.0 2515 28.7

Former 1006 17.9 1078 20.6 1355 22.9 2390 27.3

Never 1954 34.8 1961 37.4 2372 40.0 3807 43.4

Missings 0 0 1 0.0 9 0.2 57 0.7

TOTAL 5608 100 5238 100 5926 100 8769 100

Table 11: High alcohol consumers, DWECS 2000 and 2005

High consumers 2000 2005

N % N %

No 5578 94.1 7369 84.0

Yes 333 5.6 1260 14.4

Missings 15 0.3 140 1.6

TOTAL 5926 100 8769 100

Table 12: Consume fruit every day, DWECS 2000 and 2005

High consumers 2000 2005

N % N %

No 1588 26.5 2019 23.0

Yes 4326 73.0 6721 76.6

Missings 12 0,2 29 0,3

TOTAL 5926 100 8769 100

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References

(1) NFA. Den Nationale Arbejdsmiljøkohorte - NAK. Det Nationale Forskningscenter for Arbejdsmiljø 2011 June 6 [cited 2013 Apr 10];Available from: URL: http://www.arbejdsmiljoforskning.dk/da/arbejdsmiljoedata/nak2005

(2) Pedersen CB. The Danish Civil Registration System. Scandinavian Journal of Public Health 2011 Jul 1;39(7 suppl):22-5.

(3) Hammer-Helmich L. Sundhedsprofil for region og kommuner 2010. Glostrup: Region Hovedstaden; 2010.

(4) Helt Poulsen I. Sundhedsprofil. Sorø: Region Sjælland; 2011. (5) Pedersen KM, Kamper-Jørgensen F. Folkesundhedsrapporten Danmark 2007. [Kbh.]: Statens Institut

for Folkesundhed; 2007. (6) Glymour MM, Greenland S. Modern epidemiology. Modern epidemiology. 3. edition ed. Philadelphia,

Pa.: Wolters Kluwer; 2008. p. 183-209. (7) Hernan MA, Hernandez-Diaz S, Werler MM, Mitchell AA. Causal Knowledge as a Prerequisite for

Confounding Evaluation: An Application to Birth Defects Epidemiology. American Journal of Epidemiology 2002 Jan 15;155(2):176-84.

(8) Stamatakis E, Chau J, Pedisic Z, Bauman A, Macniven R, Coombs N, et al. Are sitting occupations associated with increased all-cause, cancer, and cardiovascular disease mortality risk? A pooled analysis of seven british population cohorts. PLOS One 2013 Sep;8(9).

(9) Warren T, Barry V, Hooker S, Siu X, Church TS, BLAIR SN. Sedentary behaviors increase risk of cardiovascular disease mortality in men. Medicine and science in sports and exercise 2010 May;42(5).