Skip to main content
SpringerLink
Log in

Deviation between self-reported and measured occupational physical activity levels in office employees: effects of age and body composition

  • Original Article
  • Published:
International Archives of Occupational and Environmental Health Aims and scope Submit manuscript

Abstract

Objectives

Whether occupational physical activity (PA) will be assessed via questionnaires or accelerometry depends on available resources. Although self-reported data collection seems feasible and inexpensive, obtained information could be biased by demographic determinants. Thus, we aimed at comparing self-reported and objectively measured occupational sitting, standing, and walking times adjusted for socio-demographic variables.

Methods

Thirty-eight office employees (eight males, 30 females, age 40.8 ± 11.4 years, BMI 23.9 ± 4.2 kg/m2) supplied with height-adjustable working desks were asked to report sitting, standing, and walking times using the Occupational Sitting and Physical Activity Questionnaire during one working week. The ActiGraph wGT3X-BT was used to objectively measure occupational PA during the same week. Subjectively and objectively measured data were compared computing the intra-class correlation coefficients, paired t tests and Bland–Altman plots. Furthermore, repeated-measurement ANOVAs for measurement (subjective vs. objective) and socio-demographic variables were calculated.

Results

Self-reported data yielded a significant underestimation of standing time (13.3 vs. 17.9 %) and an overestimation of walking time (12.7 vs. 5.0 %). Significant interaction effects of age and measurement of standing time (F = 6.0, p = .02, η 2 p  = .14) and BMI group and measurement of walking time were found (F = 3.7, p = .04, η 2 p  = .17). Older employees (>39 years) underestimated their standing time, while underweight workers (BMI < 20 kg/m2) overestimated their walking time.

Conclusions

Self-reported PA data differ from objective data. Demographic variables (age, BMI) affect the amount of self-reported misjudging of PA. In order to improve the validity of self-reported data, a correction formula for the economic assessment of PA by subjective measures is needed, considering age and BMI.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Adams SA, Matthews CE, Ebbeling CB, Moore CG, Cunningham JE, Fulton J, Hebert JR (2005) The effect of social desirability and social approval on self-reports of physical activity. Am J Epidemiol 161:389–398. doi:10.1093/aje/kwi054

    Article  Google Scholar 

  • Ainsworth BE, Richardson MT, Jacobs DR Jr, Leon AS, Sternfeld B (1999) Accuracy of recall of occupational physical activity by questionnaire. J Clin Epidemiol 52:219–227

    Article  CAS  Google Scholar 

  • Ainsworth BE, Caspersen CJ, Matthews CE, Masse LC, Baranowski T, Zhu W (2012) Recommendations to improve the accuracy of estimates of physical activity derived from self report. J Phys Act Health 9(Suppl 1):S76–S84

    Google Scholar 

  • Baecke JA, Burema J, Frijters JE (1982) A short questionnaire for the measurement of habitual physical activity in epidemiological studies. Am J Clin Nutr 36:936–942

    CAS  Google Scholar 

  • Baty D, Buckle PW, Stubbs DA (1986) Posture recording by direct observation, questionnaire assessment and instrumentation, a comparison based on a recent field study. In: Corlett NWJ, Manenica I (eds) The ergonomics of working postures: models, methods and cases. Taylor & Francis, London, pp 283–292

    Google Scholar 

  • Bernstein MS, Morabia A, Sloutskis D (1999) Definition and prevalence of sedentarism in an urban population. Am J Public Health 89:862–867

    Article  CAS  Google Scholar 

  • Blair SN (2009) Physical inactivity: the biggest public health problem of the 21st century. Br J Sports Med 43:1–2

    Google Scholar 

  • Blair SN, Brodney S (1999) Effects of physical inactivity and obesity on morbidity and mortality: current evidence and research issues. Med Sci Sports Exerc 31:S646–S662

    Article  CAS  Google Scholar 

  • Brown HE, Ryde GC, Gilson ND, Burton NW, Brown WJ (2013) Objectively measured sedentary behavior and physical activity in office employees relationships with presenteeism. J Occup Environ Med 55:945–953. doi:10.1097/Jom.0b013e31829178bf

    Article  Google Scholar 

  • Castillo-Retamal M, Hinckson EA (2011) Measuring physical activity and sedentary behaviour at work: a review. Work 40:345–357. doi:10.3233/WOR-2011-1246

    Google Scholar 

  • Chau JY, Van Der Ploeg HP, Dunn S, Kurko J, Bauman AE (2012) Validity of the occupational sitting and physical activity questionnaire. Med Sci Sports Exerc 44:118–125. doi:10.1249/MSS.0b013e3182251060

    Article  Google Scholar 

  • Chau JY et al (2013) Daily sitting time and all-cause mortality: a meta-analysis. Plos One 8:e80000. doi:10.1371/journal.pone.0080000

    Article  Google Scholar 

  • Choi L, Liu Z, Matthews CE, Buchowski MS (2011) Validation of accelerometer wear and nonwear time classification algorithm. Med Sci Sports Exerc 43:357–364. doi:10.1249/MSS.0b013e3181ed61a3

    Article  Google Scholar 

  • Clemes SA, Houdmont J, Munir F, Wilson K, Kerr R, Addley K (2015) Descriptive epidemiology of domain-specific sitting in working adults: the Stormont Study. J Public Health. doi:10.1093/pubmed/fdu114

    Google Scholar 

  • Cohen J (1988) Statistical power analysis for the behavioral sciences. Erlbaum, Hillsdale

    Google Scholar 

  • Cohen A, Baker J, Ardern CI (2015) Association between body mass index, physical activity, and health-related quality of life in Canadian adults. J Aging Phys Act. doi:10.1123/japa.2014-0169

    Google Scholar 

  • Craig CL et al (2003) International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 35:1381–1395. doi:10.1249/01.MSS.0000078924.61453.FB

    Article  Google Scholar 

  • De Cocker K, Duncan MJ, Short C, van Uffelen JG, Vandelanotte C (2014) Understanding occupational sitting: prevalence, correlates and moderating effects in Australian employees. Prev Med 67:288–294. doi:10.1016/j.ypmed.2014.07.031

    Article  Google Scholar 

  • Ditchen DM, Ellegast RP, Hartmann B, Rieger MA (2013) Validity of self-reports of knee-straining activities at work: a field study with 6-month follow-up. Int Arch Occup Environ Health 86:233–243. doi:10.1007/s00420-012-0758-4

    Article  Google Scholar 

  • Durante R, Ainsworth BE (1996) The recall of physical activity: using a cognitive model of the question-answering process. Med Sci Sports Exerc 28:1282–1291

    Article  CAS  Google Scholar 

  • Ellert U, Brettschneider AK, Wiegand S, Kurth BM (2014) Applying a correction procedure to the prevalence estimates of overweight and obesity in the German part of the HBSC study. BMC Res Notes 7:181. doi:10.1186/1756-0500-7-181

    Article  Google Scholar 

  • Fleiss JL (1986) The design and analysis of clinical experiments. Wiley, New York

    Google Scholar 

  • Grunseit AC, Chau JYY, van der Ploeg HP, Bauman A (2013) “Thinking on your feet”: a qualitative evaluation of sit-stand desks in an Australian workplace. BMC Public Health. doi:10.1186/1471-2458-13-365

    Google Scholar 

  • Hamilton MT, Hamilton DG, Zderic TW (2007) Role of low energy expenditure and sitting in obesity, metabolic syndrome, type 2 diabetes, and cardiovascular disease. Diabetes 56:2655–2667. doi:10.2337/db07-0882

    Article  CAS  Google Scholar 

  • Heinrich J, Blatter BM, Bongers PM (2004) A comparison of methods for the assessment of postural load and duration of computer use. Occup Environ Med 61:1027–1031

  • Ijmker S, Huysmans MA, van der Beek AJ, Knol DL, van Mechelen W, Bongers PM, Blatter BM (2011) Software-recorded and self-reported duration of computer use in relation to the onset of severe arm-wrist-hand pain and neck-shoulder pain. Occup Environ Med 68:502–509. doi:10.1136/oem.2010.056267

    Article  Google Scholar 

  • Jancey J, Tye M, McGann S, Blackford K, Lee AH (2014) Application of the Occupational Sitting and Physical Activity Questionnaire (OSPAQ) to office based workers. BMC Public Health 14:762. doi:10.1186/1471-2458-14-762

    Article  Google Scholar 

  • Kao MC, Jarosz R, Goldin M, Patel A, Smuck M (2014) Determinants of physical activity in America: a first characterization of physical activity profile using the National Health and Nutrition Examination Survey (NHANES). PM&R 6:882–892. doi:10.1016/j.pmrj.2014.03.004

    Article  Google Scholar 

  • Koeneman MA, Verheijden MW, Chinapaw MJ, Hopman-Rock M (2011) Determinants of physical activity and exercise in healthy older adults: a systematic review. Int J Behav Nutr Phys Act 8:142. doi:10.1186/1479-5868-8-142

    Article  Google Scholar 

  • Kurth BM, Ellert U (2010) Estimated and measured BMI and self-perceived body image of adolescents in Germany: Part 1—general implications for correcting prevalence estimations of overweight and obesity. Obes Facts 3:181–190. doi:10.1159/000314638

    Article  Google Scholar 

  • Laperrière E, Messing K, Couture V, Stock S (2005) Validation of questions on working posture among those who stand during most of the work day. Int J Ind Ergon 35:371–378. doi:10.1016/j.ergon.2004.10.006

    Article  Google Scholar 

  • Li J, Siegrist J (2012) Physical activity and risk of cardiovascular disease—a meta-analysis of prospective cohort studies. Int J Environ Res Public Health 9:391–407. doi:10.3390/ijerph9020391

    Article  Google Scholar 

  • Park DC, Polk TA, Mikels JA, Taylor SF, Marshuetz C (2001) Cerebral aging: integration of brain and behavioral models of cognitive function. Dialogues Clin Neurosci 3:151–165

    CAS  Google Scholar 

  • Plotnikoff RC, Prodaniuk TR, Fein AJ, Milton L (2005) Development of an ecological assessment tool for a workplace physical activity program standard. Health Promot Pract 6:453–463. doi:10.1177/1524839904263730

    Article  Google Scholar 

  • Prince SA, Adamo KB, Hamel ME, Hardt J, Connor Gorber S, Tremblay M (2008) A comparison of direct versus self-report measures for assessing physical activity in adults: a systematic review. Int J Behav Nutr Phys Act 5:56. doi:10.1186/1479-5868-5-56

    Article  Google Scholar 

  • Sanchez A, Grandes G, Ortega Sanchez-Pinilla R, Torcal J, Montoya I, Group P (2014) Predictors of long-term change of a physical activity promotion programme in primary care. BMC Public Health 14:108. doi:10.1186/1471-2458-14-108

    Article  Google Scholar 

  • Shrestha N, Ijaz S, Kukkonen-Harjula KT, Kumar S, Nwankwo CP (2015) Workplace interventions for reducing sitting at work. Cochrane Database Syst Rev 1:CD010912. doi:10.1002/14651858.CD010912.pub2

    Google Scholar 

  • Skotte J, Korshoj M, Kristiansen J, Hanisch C, Holtermann A (2014) Detection of physical activity types using triaxial accelerometers. J Phys Act Health 11:76–84. doi:10.1123/jpah.2011-0347

    Article  Google Scholar 

  • Smith MJ, Conway FT, Karsh BT (1999) Occupational stress in human computer interaction. Ind Health 37:157–173

    Article  CAS  Google Scholar 

  • Steeves JA, Bowles HR, McClain JJ, Dodd KW, Brychta RJ, Wang J, Chen KY (2015) Ability of thigh-worn ActiGraph and activPAL monitors to classify posture and motion. Med Sci Sports Exerc 47:952–959. doi:10.1249/MSS.0000000000000497

    Article  Google Scholar 

  • Thorp AA, Healy GN, Winkler E, Clark BK, Gardiner PA, Owen N, Dunstan DW (2012) 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 Phys Act 9:128. doi:10.1186/1479-5868-9-128

    Article  Google Scholar 

  • Tikkanen O et al (2013) Muscle activity and inactivity periods during normal daily life. PLoS ONE 8:e52228. doi:10.1371/journal.pone.0052228

    Article  CAS  Google Scholar 

  • Troiano RP, Berrigan D, Dodd KW, Masse LC, Tilert T, McDowell M (2008) Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc 40:181–188. doi:10.1249/mss.0b013e31815a51b3

    Article  Google Scholar 

  • Tudor-Locke C, Leonardi C, Johnson WD, Katzmarzyk PT (2011) Time spent in physical activity and sedentary behaviors on the working day the American time use survey. J Occup Environ Med 53:1382–1387. doi:10.1097/Jom.0b013e31823c1402

    Article  Google Scholar 

  • van Sluijs E, Griffin S, van Poppel M (2007) A cross-sectional study of awareness of physical activity: associations with personal, behavioral and psychosocial factors. Int J Behav Nutr Phys Act 4:53

    Article  Google Scholar 

  • van Uffelen JG et al (2010) Occupational sitting and health risks: a systematic review. Am J Prev Med 39:379–388. doi:10.1016/j.amepre.2010.05.024

    Article  Google Scholar 

  • Wallmann-Sperlich B, Bucksch J, Hansen S, Schantz P, Froboese I (2013) Sitting time in Germany: an analysis of socio-demographic and environmental correlates. BMC Public Health. doi:10.1186/1471-2458-13-196

    Google Scholar 

  • Watkinson C, van Sluijs EM, Sutton S, Hardeman W, Corder K, Griffin SJ (2010) Overestimation of physical activity level is associated with lower BMI: a cross-sectional analysis. Int J Behav Nutr Phys Act 7:68. doi:10.1186/1479-5868-7-68

    Article  Google Scholar 

Download references

Acknowledgments

We appreciate the encouragement of the Swiss health insurance (EGK Gesundheitskasse) for their infrastructural and institutional support. We are also grateful for participants’ commitment and compliance during the testing and intervention period. Special thanks to Christoph Moor for his study assistance with the ActiGraph measures.

Author information

Authors and Affiliations

  1. Institute of Psychosocial Medicine and Psychotherapy, University Hospital, Friedrich-Schiller-University Jena, Stoystr. 3, 07740, Jena, Germany

    Katharina Wick & Susanne Schwager

  2. Department of Sport, Exercise and Health University of Basel, Birsstrasse 320, 4052, Basel, Switzerland

    Oliver Faude, Lukas Zahner & Lars Donath

Authors
  1. Katharina Wick
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Oliver Faude
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Susanne Schwager
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lukas Zahner
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Lars Donath
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Katharina Wick.

Ethics declarations

Conflict of interest

None.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wick, K., Faude, O., Schwager, S. et al. Deviation between self-reported and measured occupational physical activity levels in office employees: effects of age and body composition. Int Arch Occup Environ Health 89, 575–582 (2016). https://doi.org/10.1007/s00420-015-1095-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00420-015-1095-1

Keywords

Search

Navigation