Journal of Physical Activity and Health, 2015, 12, 1128 -1132 http://dx.doi.org/10.1123/jpah.2014-0259 © 2015 Human Kinetics, Inc.
ORIGINAL RESEARCH
Activity Behaviors of University Staff in the Workplace: A Pilot Study Marie-Louise Bird, Cecilia Shing, Casey Mainsbridge, Dean Cooley, and Scott Pedersen Background: Sedentary behavior is related to metabolic syndrome and might have implications for the long-term health of workers in a low activity environment. The primary aim of this pilot study was to determine activity levels of adults working at a University during work hours. A secondary aim was to determine the relationship between actual and perceived activity levels. Methods: Activity levels of university staff (n = 15, male = 7, age = 53 ± 7 years, BMI = 26.5 ± 2.5kg·m2) were monitored over 5 consecutive workdays using SenseWear accelerometers, then participants completed a questionnaire of their perception of workplace sedentary time. Results: Each participant spent 71.5 ± 13.1% (358 ± 78 min) of their workday being sedentary (< 1.5 METs), 15.6 ± 9.0% involved in light activity (1.5–3 METs), 11.7 ± 10.0% in moderate activity (3–5 METs), and 1.1 ± 1.3% in vigorous activity (> 5 METs) (P < .0001). The mean difference between actual (SenseWear < 1.5 METs) and perceived sitting time was –2 ± 32%; however, perceived sedentary time was reported with a range of under-to-over estimation of –75% to 51%. Conclusion: This pilot study identifies long periods of low metabolic activity during the workday and poor perception of individual sedentary time. Interventions to reduce sedentary time in the workplace may be necessary to ensure that the work environment does not adversely affect long-term health. Keywords: accelerometry, ergonomics, physical activity, sedentary
Sedentary behavior is commonly defined as situations where metabolic activity is less than 1.5 METS1 and this behavior, which incorporates sitting, is an independent risk factor for adverse health outcomes in adults.2 Prolonged time spent sitting has been shown to have important metabolic consequences, and may adversely influence cholesterol, triglycerides, fasting plasma glucose, resting blood pressure, and leptin levels, which are all biomarkers of obesity, cardiovascular disease, and other chronic diseases.3–5 It appears that it takes only 4 hours of cumulative sitting per day to negatively affect these variables.6 As well as an increase in chronic metabolic health disease, time spent sitting is independently associated with total mortality, regardless of physical activity level.7,8 Importantly, a range of studies indicate that increases in one-off sessions of physical activity do not counteract the negative effects of prolonged sitting.9,10 Breaks in sitting time have been shown to have positive metabolic health benefits.11 The Australia workforce is aging due to an increase in retirement age, ability to access superannuation, longevity, and societal trends. By 2041, nearly one-fifth of Australia’s population will be aged over 65.12 In 2010, 71% of Australians aged between 55 to 59 were participating in the workforce.13 Although there is no definition for what constitutes “older workers,” older workers have higher rates of chronic disease risk and rather than work in highly active employment choose more sedentary type work roles such as management or administration.14,15 In recent years, Hugo16–18 has highlighted the fact that the age profile of the academic workforce in Australia is notably weighted to the ‘retirement end’ of the spectrum. This large and growing occupational workforce is employed in largely sedentary type work. Research into occupational sedentary behavior has revealed those
Bird ([email protected]) and Shing are with the School of Health Sciences, University of Tasmania, Launceston, Tasmania, Australia. Mainsbridge, Cooley, and Pedersen are with the Faculty of Education, University of Tasmania, Launceston, Tasmania, Australia. 1128
desk-based workers and those who sit for prolonged periods are potentially vulnerable this occupational hazard.19,20 For example, Australian desk-based workers who work fulltime sit on average for 6.5 hours per day at work, and if all of the day is taken into account, the figure exceeds 7.5 hours per day. Given the confluence of factors including the advent of technology in the workplace, the changing roles of university academics and an aging workforce, it is possible that university staff might be exposed to an occupational health risk. The extent of this problem is difficult to quantify, because of a lack of data specific to this workforce. To date there is limited literature that has investigated occupational energy expenditure in a university workplace. Demographic data of Australian Universities has indicated a secular trend of increasing mean age of staff, which may have health implications for individuals with low levels of energy expenditure in the workplace. Thus the primary aim of this study was to determine activity and energy expenditure levels of adults at a University during work hours. A secondary aim was to determine the relationship between actual and perceived activity levels.
Methods Participants were volunteers recruited by flyers displayed at the University of Tasmania and via e-mail information sheets sent by administration staff to employees (academic and professional staff). Participants were included if they worked full days at the University. No health exclusion criteria were applied. Participants attended at The School of Human Life Sciences Laboratory for 2 appointments lasting 20 minutes each. Demographic data (age, height, weight) and the type of position held at the university (academic or professional staff) were recorded at the initial appointment. At that time participants completed a question indicating whether they met the current World Health Organization (WHO) guidelines for physical activity. These basic guidelines include both aerobic and resistance exercise parameters.
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Specifically that adults aged 18 to 64 should do at least 150 minutes of moderate-intensity aerobic physical activity throughout the week or do at least 75 minutes vigorous intensity aerobic physical activity throughout the week or an equivalent combination of moderate and vigorous intensity activity and strength training on 2 days a week.21 At the first appointment participants where loaned a SenseWear activity monitor (BodyMedia, PA, USA) with instructions that it was to be worn over the midtriceps area of the left arm as per manufacturer instructions. This monitor is a triaxial accelerometer with capacity to determine skin and ambient temperature and skin bioimpedance to determine metabolic rate which it records continuously as METs. The SenseWear provides a valid measure of total energy expenditure at rest22 and during low levels of physical activity23 and is reliable with a reported between session correlation of r = .96.24 Participants were requested to wear the monitor from when they arrived at work until when they left work on 5 consecutive working days, and record any planned or scheduled physical activity during their day in a logbook. Participants were instructed to continue with usual behavior and not alter their activity levels for the duration of the study. At the second appointment participants returned the monitoring device and also completed an Occupational Sitting and Physical Activity Questionnaire (OSPAQ), which asks participants to self-report in percentages how much they sit, stand, walk, and perform heavy labor during a typical workday.25 The OSPAQ reliability and validity is similar to other established occupational PA questionnaires.26 The study was approved by the institutional research ethics committee and all participants provided written informed consent (HREC number H13049) before any data collection.
Statistical Analysis The energy expenditure data were categorized as sedentary (5.0 METs). Data were also grouped to identify periods of continuous sedentary time longer than 30 minutes, 45 minutes, or 60 minutes. Using the Shapiro-Wilk normality test data were first tested for normality. Data for blocks of continuous sitting time and total work day time were normally distributed. Data for time and percentage of work day spent in each energy expenditure category, differences between academic and professional staff for those meeting and not meeting the WHO guidelines for each category of energy expenditure and perceived sedentary time (OSPAQ) were not normally distributed. To determine if there was a difference in work time (min) or percentage of work day spent in each activity category data were analyzed using a Kruskal-Wallis one-way ANOVA (GraphPad PRISM, version 5.04). When there was a significant main effect Dunn’s multiple comparison test was used to determine which means differed. Differences in blocks of continuous sedentary time for 30 minutes or longer, 45 minutes or longer, and 60 minutes or longer were determined using a parametric one-way ANOVA with a bonferroni post hoc. Differences between academic and professional
staff and those meeting and not meeting the WHO guidelines for each category of energy expenditure were determined with Mann Whitney U. Where relevant effect size (d) was calculated from the difference in group means divided by the pooled standard deviation and interpreted according to Cohen where 0.2 represents a small effect size, 0.5 represents a medium effect size and 0.8 represents a large effect size.27 The level of agreement between percentage of workday spent sitting (OSPAQ) and sedentary ( .05), while the percentage spent in vigorous activity was significantly less than moderate (2.9–5.0 METs; P < .05) and light (1.5–2.9 METs; P < .001). The time (min) spent in each activity category (sedentary to vigorous) mirrored the percentage of workday findings (H = 50.44, df = 3, P < .0001) (Table 1). There was a significant main effect of average blocks per day spent sedentary for periods longer than 60 minutes, longer than 45 minutes and longer 30 minutes (F = 14.57, df = 2, P = .049). The number of blocks spent sedentary for longer than 60 minutes (mean ± SD: 0.79 ± 0.73) was significantly less than those spent sedentary for 30 minutes or longer (2.9 ± 1.4, P < .0001). Sedentary blocks of 30 minutes or longer were significantly greater than blocks of sedentary for 45 minutes or longer (1.4 ± 1.0, P < .01). Participants reported, via OSPAQ, engaging in sedentary behavior for 70% (range 20%–90%) of their work time, which was similar to the reported 70% time spent in sedentary activity ( .51). There were small to moderate differences between academic staff and professional staff for the percentage work time spent in sedentary activity (68.1, 57.8%–83.5% and 74.0, 67.0%–84.0%, respectively; d = 0.48), light activity (10.4, 8.5%–26.8% and 12, 9.9%–20.6%, respectively; d = 0.17), moderate activity (8.0, 6.7%–18.7% and 6.8, 4.6%–15.3%, respectively; d = 0.41) and vigorous (0.7, 0.1%–2.1% and 0.4, 0.2%–1.2%, respectively; d = 0.58).
Discussion This pilot study indicates that university staff are largely sedentary in their workday, spending approximately 6 hours per day in activities that expend 5.0 METs) during the workday, time spent in other MET categories (sedentary, light and moderate) were similar. Thus, active people might still be at risk for chronic diseases associated with sedentary behavior during the workday. This conclusion is supported by previous research, which has found that the adverse health effects of sedentary behavior are independent of meeting recommended physical activity guidelines.9,12,38,39 With increasing life expectancy in industrialized countries and concurrently more years at work in sedentary jobs, future health implications of these workplace behaviors may become more apparent than they are at present. The traditional age of 55 years as retirement has been impacted on by changes to legislation and policy to encourage older adults to stay in the workforce longer both in Australia and internationally,40 forcing many older Australian to stay within the workforce for up to 10 years longer than they would have planned when they started their careers. The average age of our cohort was 53 years and the impact of more than another decade of occupational sedentary behavior may have huge consequences for the health of our aging workforce if current sedentary behaviors are not addressed. While our sample was representative of only a small portion of the university workforce, our preliminary findings provide further justification for investigating sedentary workplace behavior in the university cohort. Longitudinal studies are required to provide more evidence on the longer term implications of highdose sedentary behavior and changes in workplace tasks, and the positive effects of interventions to try to reduce them. This pilot
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study gives a snapshot of current physical activity levels that may provide important baseline data from which to monitor changes in university workplace practice. These proposed workplace changes may be the result of positive purposeful interventions including workplace strategies to improve activity and employee health, or detrimental changes that my follow increases in online, flexible learning delivery and less face-to-face teaching.
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Conclusions This is the first study to examine occupational levels of physical activity in a university population that includes both professional and academic staff, not just desk-based office workers. This pilot study identifies long periods of low metabolic activity during the workday in university staff that are not traditionally considered ‘office workers.’ As well it identifies that perceptions of time spent in sedentary behavior is poor. Interventions to reduce sedentary time in the workplace might be necessary to ensure that the work environment does not adversely affect long-term health, especially in the context of an increasing anticipated length of working life and increasing use of technology in the workplace
References 1. Pate RR, O’neill JR, Lobelo F. The evolving definition of “sedentary”. Exerc Sport Sci Rev. 2008;36:173–178. PubMed doi:10.1097/ JES.0b013e3181877d1a 2. Thorp AA, Owen N, Neuhaus M, Dunstan DW. Sedentary behaviors and subsequent health outcomes in adults: a systematic review of longitudinal studies, 1996-2011. Am J Prev Med. 2011;41:207–215. PubMed doi:10.1016/j.amepre.2011.05.004 3. Bey L, Hamilton MT. Suppression of skeletal muscle lipoprotein lipase activity during physical inactivity: a molecular reason to maintain daily low-intensity activity. J Physiol. 2003;551:673–682. PubMed doi:10.1113/jphysiol.2003.045591 4. Ekblom-Bak E, Hellenius ML, Ekblom B. Are we facing a new paradigm of inactivity physiology? Br J Sports Med. 2010;44:834–835. PubMed doi:10.1136/bjsm.2009.067702 5. Hamilton MT, Hamilton DG, Zderic TW. Role of low energy expenditure and sitting in obesity, metabolic syndrome, type 2 diabetes, and cardiovascular disease. Diabetes. 2007;56:2655–2667. PubMed doi:10.2337/db07-0882 6. Dunstan DW, Barr ELM, Healy GN, et al. Television viewing time and mortality: The Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Circulation. 2010;121:384–391. PubMed doi:10.1161/ CIRCULATIONAHA.109.894824 7. Koster A, Caserotti P, Patel KV, et al. Association of sedentary time with mortality independent of moderate to vigorous physical activity. Plos One. 2012;7(6). 8. Owen N, Bauman A, Brown W. Too much sitting: a novel and important predictor of chronic disease risk? Br J Sports Med. 2009;43:81–83. PubMed 9. Katzmarzyk PT, Church TS, Craig CL, Bouchard C. Sitting time and mortality from all causes, cardiovascular disease, and cancer. Med Sci Sports Exerc. 2009;41:998–1005. PubMed doi:10.1249/ MSS.0b013e3181930355 10. Matthews CE, George SM, Moore SC, et al. Amount of time spent in sedentary behaviors and cause-specific mortality in US adults. Am J Clin Nutr. 2012;95:437–445. PubMed doi:10.3945/ajcn.111. 019620 11. Healy G, Dunstan D, Salmon J, et al. Breaks in sedentary time: beneficial associations with metabolic risk. Diabetes Care. 2008;31:661–666. PubMed doi:10.2337/dc07-2046 12. Australian Bureau of Statistics. 6105.0 – Australian social trends, September 2010. Available at: http://www.abs.gov.au/AUSSTATS/
[email protected]/0/97999E77DB6843A1CA2577F80010DD40?opendocu ment. Accessed March 20, 2010). 13. Australian Bureau of Statistics. 6238.0 - Retirement and retirement intentions, Australia, July 2010. Available at: http://www.abs.gov.au/ ausstats/[email protected]/mf/6238.0. Accessed April 10, 2012. 14. Grosch JW, Pansky GS. Safety and health issues for an aging workforce in aging and work: issues and implications in a changing landscape. Baltimore, MD: Johns Hopkins University Press; 2010. 15. Burgmann L. Discussion paper; Engaging and retaining Older Workers. Australian Institute of Management NSW & ACT Training Centre Limited; 2013. 16. Hugo G. Demographic trends in Australia’s academic workforce. J High Educ Policy Manage. 2005b;27:327–343. doi:10.1080/13600800500283627 17. Hugo G. Some emerging demographic issues on Australia’s teaching academic workforce. High Educ Policy. 2005c;18:207–230. doi:10.1057/palgrave.hep.8300084 18. Hugo G. The demographic outlook for Australian universities’ academic staff. CHASS occasional paper no. 6. Adelaide Council for Humanities, Arts and Social Science, 2008. 19. Straker L, Mathiassen SE. Increased physical work loads in modern work—a necessity for better health and performance? Ergonomics. 2009;52:1215–1225. PubMed doi:10.1080/00140130903039101 20. Toomingas A, Forsman M, Mathiassen SE, Heiden M, Nilsson T. Variation between seated and standing/walking postures among male and female call centre operators. BMC Public Health. 2012;12:154. PubMed 21. American College of Sports Medicine [Online]. Available at http:// exerciseismedicine.org.au/wp-content/uploads/2011/07/PA-guidelines-under65.pdf. Accessed September 20, 2013]. 22. Malavolti M, Pietrobelli A, Dugoni M, et al. A new device for measuring resting energy expenditure (REE) in healthy subjects. Nutr Metab Cardiovasc Dis. 2007;17:338–343. PubMed doi:10.1016/j. numecd.2005.12.009 23. St-Onge M, Mignault D, Allison DB, Rabasa-Lhoret R. Evaluation of a portable device to measure daily energy expenditure in free-living adults. Am J Clin Nutr. 2007;85:742–749. PubMed 24. Reeve MD, Pumpa, KL, Ball, N. Accuracy of the SenseWear Armband Mini and the BodyMedia FIT in resistance training. J Sci Med Sport. 2013;pii:S1440-2440(13)00194-1. 25. Chau JY, Van Der Ploeg HP, Dunn S, Kurko J, Bauman AE. Validity of the Occupational Sitting and Physical Activity Questionnaire. Med Sci Sports Exerc. 2012;44:118–125. PubMed doi:10.1249/ MSS.0b013e3182251060 26. Reis JP, Dubose KD, Ainsworth BE, Macera CA, Yore MM. Reliability and validity of the occupational physical activity questionnaire. Med Sci Sports Exerc. 2005;37:2075–2083. PubMed doi:10.1249/01. mss.0000179103.20821.00 27. Cohen J. Statistical power analysis for the behavioral sciences. Mahwah, NJ: Lawrence Erlbaum; 1988. 28. Thorp AA, Healy GN, Winkler E, et al. Prolonged sedentary time and physical activity in workplace and non-work contexts: a cross-sectional study of office, customer service and call centre employees. Int J Behav Nutr Phy. 2012;9: doi:10.1186/1479-5868-9-128. PubMed 29. Australian Bureau of Statistics. Australian Health Survey: Physical Activity, 2011-12. Australia. Available online at: http://www.abs.gov. au/ausstats/[email protected]/Lookup/4364.0.55.004main+features12011-12. Accessed 2013. 30. Mork PJ, Westgaard RH. The influence of body posture, arm movement, and work stress on trapezius activity during computer work. Eur J Appl Physiol. 2007;101:445–456. PubMed doi:10.1007/s00421-0070518-4 31. Kirk MA, Rhodes RE. Occupation correlates of adults’ participation in leisure-time physical activity: a systematic review. Am J Prev Med. 2011;40:476–485. PubMed doi:10.1016/j.amepre.2010.12.015 32. Kirk MA, Rhodes RE. Physical activity status of academic professors during their early career transition: an application of the theory of planned behavior. Psychol Health Med. 2012;17:551–564. PubMed doi:10.1080/13548506.2011.647700
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to office based workers. BMC Pub Health. 2014:762. Available at: http://www.biomedcentral.com/1471-2458/14/762. 38. Healy GN, Dunstan DW, Shaw JE, Zimmet PZ, Owen N. Objectively measured sedentary time and light-intensity physical activity are independently associated with components of the metabolic syndrome: the AusDiab study. Diabetologia. 2007;50:S67–S68. 39. Hamilton MT, Healy GN, Dunstan DW, Zderic TW, Owen N. Too little exercise and too much sitting: inactivity physiology and the need for new recommendations on sedentary behaviour. Curr Cardiovasc Risk Rep. 2008;2:292–298. PubMed doi:10.1007/s12170-008-0054-8 40. Duval R. The retirement effects of old-age pension and early retirement schemes in OECD countries. Organisation for Economic Cooperation and Development economics department working papers no. 370, 2003.
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33. Healy GN, Dunstan DW, Salmon J, et al. Breaks in sedentary time—beneficial associations with metabolic risk. Diabetes Care. 2008;31:661–666. PubMed doi:10.2337/dc07-2046 34. Mccrady-Spitzer SK, Levine JA. Nonexercise activity thermogenesis: a way forward to treat the worldwide obesity epidemic. Surg Obes Relat Dis. 2012;8:501–506. PubMed doi:10.1016/j.soard.2012.08.001 35. Chau J. Evidence module: workplace physical activity and nutrition interventions. Physical Activity Nutrition and Obesity Research Group. 2009;I-32. 36. Pedersen SJ, Cooley PD, Mainsbridge CP. An e-health intervention designed to increase workday energy expenditure by reducing prolonged occupational sitting habits. Work. 2014;49(2):289–95. PubMed 37. Jancey J, Tye M, McGann S, Blackford K, Lee AH. Application of the Occupational Sitting and Physical Activity Questionnaire (OSPAQ)
JPAH Vol. 12, No. 8, 2015
ORIGINAL RESEARCH
Activity Behaviors of University Staff in the Workplace: A Pilot Study Marie-Louise Bird, Cecilia Shing, Casey Mainsbridge, Dean Cooley, and Scott Pedersen Background: Sedentary behavior is related to metabolic syndrome and might have implications for the long-term health of workers in a low activity environment. The primary aim of this pilot study was to determine activity levels of adults working at a University during work hours. A secondary aim was to determine the relationship between actual and perceived activity levels. Methods: Activity levels of university staff (n = 15, male = 7, age = 53 ± 7 years, BMI = 26.5 ± 2.5kg·m2) were monitored over 5 consecutive workdays using SenseWear accelerometers, then participants completed a questionnaire of their perception of workplace sedentary time. Results: Each participant spent 71.5 ± 13.1% (358 ± 78 min) of their workday being sedentary (< 1.5 METs), 15.6 ± 9.0% involved in light activity (1.5–3 METs), 11.7 ± 10.0% in moderate activity (3–5 METs), and 1.1 ± 1.3% in vigorous activity (> 5 METs) (P < .0001). The mean difference between actual (SenseWear < 1.5 METs) and perceived sitting time was –2 ± 32%; however, perceived sedentary time was reported with a range of under-to-over estimation of –75% to 51%. Conclusion: This pilot study identifies long periods of low metabolic activity during the workday and poor perception of individual sedentary time. Interventions to reduce sedentary time in the workplace may be necessary to ensure that the work environment does not adversely affect long-term health. Keywords: accelerometry, ergonomics, physical activity, sedentary
Sedentary behavior is commonly defined as situations where metabolic activity is less than 1.5 METS1 and this behavior, which incorporates sitting, is an independent risk factor for adverse health outcomes in adults.2 Prolonged time spent sitting has been shown to have important metabolic consequences, and may adversely influence cholesterol, triglycerides, fasting plasma glucose, resting blood pressure, and leptin levels, which are all biomarkers of obesity, cardiovascular disease, and other chronic diseases.3–5 It appears that it takes only 4 hours of cumulative sitting per day to negatively affect these variables.6 As well as an increase in chronic metabolic health disease, time spent sitting is independently associated with total mortality, regardless of physical activity level.7,8 Importantly, a range of studies indicate that increases in one-off sessions of physical activity do not counteract the negative effects of prolonged sitting.9,10 Breaks in sitting time have been shown to have positive metabolic health benefits.11 The Australia workforce is aging due to an increase in retirement age, ability to access superannuation, longevity, and societal trends. By 2041, nearly one-fifth of Australia’s population will be aged over 65.12 In 2010, 71% of Australians aged between 55 to 59 were participating in the workforce.13 Although there is no definition for what constitutes “older workers,” older workers have higher rates of chronic disease risk and rather than work in highly active employment choose more sedentary type work roles such as management or administration.14,15 In recent years, Hugo16–18 has highlighted the fact that the age profile of the academic workforce in Australia is notably weighted to the ‘retirement end’ of the spectrum. This large and growing occupational workforce is employed in largely sedentary type work. Research into occupational sedentary behavior has revealed those
Bird ([email protected]) and Shing are with the School of Health Sciences, University of Tasmania, Launceston, Tasmania, Australia. Mainsbridge, Cooley, and Pedersen are with the Faculty of Education, University of Tasmania, Launceston, Tasmania, Australia. 1128
desk-based workers and those who sit for prolonged periods are potentially vulnerable this occupational hazard.19,20 For example, Australian desk-based workers who work fulltime sit on average for 6.5 hours per day at work, and if all of the day is taken into account, the figure exceeds 7.5 hours per day. Given the confluence of factors including the advent of technology in the workplace, the changing roles of university academics and an aging workforce, it is possible that university staff might be exposed to an occupational health risk. The extent of this problem is difficult to quantify, because of a lack of data specific to this workforce. To date there is limited literature that has investigated occupational energy expenditure in a university workplace. Demographic data of Australian Universities has indicated a secular trend of increasing mean age of staff, which may have health implications for individuals with low levels of energy expenditure in the workplace. Thus the primary aim of this study was to determine activity and energy expenditure levels of adults at a University during work hours. A secondary aim was to determine the relationship between actual and perceived activity levels.
Methods Participants were volunteers recruited by flyers displayed at the University of Tasmania and via e-mail information sheets sent by administration staff to employees (academic and professional staff). Participants were included if they worked full days at the University. No health exclusion criteria were applied. Participants attended at The School of Human Life Sciences Laboratory for 2 appointments lasting 20 minutes each. Demographic data (age, height, weight) and the type of position held at the university (academic or professional staff) were recorded at the initial appointment. At that time participants completed a question indicating whether they met the current World Health Organization (WHO) guidelines for physical activity. These basic guidelines include both aerobic and resistance exercise parameters.
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Specifically that adults aged 18 to 64 should do at least 150 minutes of moderate-intensity aerobic physical activity throughout the week or do at least 75 minutes vigorous intensity aerobic physical activity throughout the week or an equivalent combination of moderate and vigorous intensity activity and strength training on 2 days a week.21 At the first appointment participants where loaned a SenseWear activity monitor (BodyMedia, PA, USA) with instructions that it was to be worn over the midtriceps area of the left arm as per manufacturer instructions. This monitor is a triaxial accelerometer with capacity to determine skin and ambient temperature and skin bioimpedance to determine metabolic rate which it records continuously as METs. The SenseWear provides a valid measure of total energy expenditure at rest22 and during low levels of physical activity23 and is reliable with a reported between session correlation of r = .96.24 Participants were requested to wear the monitor from when they arrived at work until when they left work on 5 consecutive working days, and record any planned or scheduled physical activity during their day in a logbook. Participants were instructed to continue with usual behavior and not alter their activity levels for the duration of the study. At the second appointment participants returned the monitoring device and also completed an Occupational Sitting and Physical Activity Questionnaire (OSPAQ), which asks participants to self-report in percentages how much they sit, stand, walk, and perform heavy labor during a typical workday.25 The OSPAQ reliability and validity is similar to other established occupational PA questionnaires.26 The study was approved by the institutional research ethics committee and all participants provided written informed consent (HREC number H13049) before any data collection.
Statistical Analysis The energy expenditure data were categorized as sedentary (5.0 METs). Data were also grouped to identify periods of continuous sedentary time longer than 30 minutes, 45 minutes, or 60 minutes. Using the Shapiro-Wilk normality test data were first tested for normality. Data for blocks of continuous sitting time and total work day time were normally distributed. Data for time and percentage of work day spent in each energy expenditure category, differences between academic and professional staff for those meeting and not meeting the WHO guidelines for each category of energy expenditure and perceived sedentary time (OSPAQ) were not normally distributed. To determine if there was a difference in work time (min) or percentage of work day spent in each activity category data were analyzed using a Kruskal-Wallis one-way ANOVA (GraphPad PRISM, version 5.04). When there was a significant main effect Dunn’s multiple comparison test was used to determine which means differed. Differences in blocks of continuous sedentary time for 30 minutes or longer, 45 minutes or longer, and 60 minutes or longer were determined using a parametric one-way ANOVA with a bonferroni post hoc. Differences between academic and professional
staff and those meeting and not meeting the WHO guidelines for each category of energy expenditure were determined with Mann Whitney U. Where relevant effect size (d) was calculated from the difference in group means divided by the pooled standard deviation and interpreted according to Cohen where 0.2 represents a small effect size, 0.5 represents a medium effect size and 0.8 represents a large effect size.27 The level of agreement between percentage of workday spent sitting (OSPAQ) and sedentary ( .05), while the percentage spent in vigorous activity was significantly less than moderate (2.9–5.0 METs; P < .05) and light (1.5–2.9 METs; P < .001). The time (min) spent in each activity category (sedentary to vigorous) mirrored the percentage of workday findings (H = 50.44, df = 3, P < .0001) (Table 1). There was a significant main effect of average blocks per day spent sedentary for periods longer than 60 minutes, longer than 45 minutes and longer 30 minutes (F = 14.57, df = 2, P = .049). The number of blocks spent sedentary for longer than 60 minutes (mean ± SD: 0.79 ± 0.73) was significantly less than those spent sedentary for 30 minutes or longer (2.9 ± 1.4, P < .0001). Sedentary blocks of 30 minutes or longer were significantly greater than blocks of sedentary for 45 minutes or longer (1.4 ± 1.0, P < .01). Participants reported, via OSPAQ, engaging in sedentary behavior for 70% (range 20%–90%) of their work time, which was similar to the reported 70% time spent in sedentary activity ( .51). There were small to moderate differences between academic staff and professional staff for the percentage work time spent in sedentary activity (68.1, 57.8%–83.5% and 74.0, 67.0%–84.0%, respectively; d = 0.48), light activity (10.4, 8.5%–26.8% and 12, 9.9%–20.6%, respectively; d = 0.17), moderate activity (8.0, 6.7%–18.7% and 6.8, 4.6%–15.3%, respectively; d = 0.41) and vigorous (0.7, 0.1%–2.1% and 0.4, 0.2%–1.2%, respectively; d = 0.58).
Discussion This pilot study indicates that university staff are largely sedentary in their workday, spending approximately 6 hours per day in activities that expend 5.0 METs) during the workday, time spent in other MET categories (sedentary, light and moderate) were similar. Thus, active people might still be at risk for chronic diseases associated with sedentary behavior during the workday. This conclusion is supported by previous research, which has found that the adverse health effects of sedentary behavior are independent of meeting recommended physical activity guidelines.9,12,38,39 With increasing life expectancy in industrialized countries and concurrently more years at work in sedentary jobs, future health implications of these workplace behaviors may become more apparent than they are at present. The traditional age of 55 years as retirement has been impacted on by changes to legislation and policy to encourage older adults to stay in the workforce longer both in Australia and internationally,40 forcing many older Australian to stay within the workforce for up to 10 years longer than they would have planned when they started their careers. The average age of our cohort was 53 years and the impact of more than another decade of occupational sedentary behavior may have huge consequences for the health of our aging workforce if current sedentary behaviors are not addressed. While our sample was representative of only a small portion of the university workforce, our preliminary findings provide further justification for investigating sedentary workplace behavior in the university cohort. Longitudinal studies are required to provide more evidence on the longer term implications of highdose sedentary behavior and changes in workplace tasks, and the positive effects of interventions to try to reduce them. This pilot
JPAH Vol. 12, No. 8, 2015
Workplace Sedentary Behavior 1131
study gives a snapshot of current physical activity levels that may provide important baseline data from which to monitor changes in university workplace practice. These proposed workplace changes may be the result of positive purposeful interventions including workplace strategies to improve activity and employee health, or detrimental changes that my follow increases in online, flexible learning delivery and less face-to-face teaching.
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Conclusions This is the first study to examine occupational levels of physical activity in a university population that includes both professional and academic staff, not just desk-based office workers. This pilot study identifies long periods of low metabolic activity during the workday in university staff that are not traditionally considered ‘office workers.’ As well it identifies that perceptions of time spent in sedentary behavior is poor. Interventions to reduce sedentary time in the workplace might be necessary to ensure that the work environment does not adversely affect long-term health, especially in the context of an increasing anticipated length of working life and increasing use of technology in the workplace
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