Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Original Article
  • Published:

Joint associations of physical activity and sedentary behaviors with body mass index: results from a time use survey of US adults

Abstract

Objective:

Obesity risk is negatively associated with physical activity and positively associated with time spent in sedentary behaviors. Yet, it is not known how different combinations of sedentary and active behavior are associated with body mass index (BMI). This study examined the interaction between time spent in physical activity and sedentary behavior on BMI in US adults.

Design:

Cross-sectional, data from the 2006 American Time Use Survey.

Subjects:

10 984 non-underweight adults (aged 21 + years).

Measurement:

A phone interview assessed all activities performed in the past 24 h, height, weight, health status, and other sociodemographic characteristics. Time spent in (1) moderate-to-vigorous leisure-time physical activity (MVPA), (2) active transportation (walking, biking), (3) sedentary leisure activities (TV/movie watching, computer use, playing games, reading), and (4) sedentary transportation (motorized vehicles) was determined from activity coding. BMI was calculated.

Results:

After adjusting for age, gender, education level, race/ethnicity, and health status, sample-weighted linear regressions found significant interactions for leisure MVPA × TV/movies, leisure MVPA × playing games, active transportation × sedentary transportation, and active transportation × reading (Ps<0.0001). For example, the group of adults watching <60 min per day of TV/movies and engaging in 60 min per day of leisure MVPA had lower average BMI compared to the group watching <60 min per day of TV/movies and reporting <60 min per day of leisure MVPA (P<0.0001). In contrast, for adults watching 189 min per day of TV/movies, there was not a significant difference in BMI by time spent in leisure MVPA.

Conclusion:

Data from a US time use survey indicate that the strength of the association between certain types of sedentary behavior and BMI varies according to time spent in certain types of physical activity and vice versa.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1
Figure 2
Figure 3
Figure 4

Similar content being viewed by others

References

  1. Hu G, Lindström J, Valle TT, Eriksson JG, Jousilahti P, Silventoinen K et al. Physical activity, body mass index, and risk of type 2 diabetes in patients with normal or impaired glucose regulation. Arch Intern Med 2004; 164: 892–896.

    Article  PubMed  Google Scholar 

  2. Wolin KY, Colditz GA . Can weight loss prevent cancer? Br J Cancer 2008; 99: 995–999.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Phillips LK, Prins JB . The link between abdominal obesity and the metabolic syndrome. Curr Hypertens Rep 200; 10: 156–164.

    Article  Google Scholar 

  4. Zhang C, Rexrode KM, van Dam RM, Li TY, Hu FB . Abdominal obesity and the risk of all-cause, cardiovascular, and cancer mortality: sixteen years of follow-up in US women. Circulation 2008; 117: 1658–1667.

    Article  PubMed  Google Scholar 

  5. CDC. State-specific prevalence of obesity among adults—United States, 2007. MMWR 2008; 57: 765–768.

    Google Scholar 

  6. CDC. State-specific prevalence of obesity among adults—United States, 2005. MMWR 2006; 55: 985–988.

    Google Scholar 

  7. Mokdad AH, Serdula MK, Dietz WH, Bowman BA, Marks JS, Koplan JP . The spread of the obesity epidemic in the United States, 1991–1998. JAMA 1999; 282: 1519–1522.

    Article  CAS  PubMed  Google Scholar 

  8. Flegal KM, Carroll MD, Ogden CL, Johnson CL . Prevalence and trends in obesity among US adults, 1999–2000. JAMA 2002; 288: 1723–1727.

    Article  PubMed  Google Scholar 

  9. Healy GN, Wijndaele K, Dunstan DW, Shaw JE, Salmon J, Zimmet PZ et al. Objectively measured sedentary time, physical activity, and metabolic risk: the Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Diabetes Care 2008; 31: 369–371.

    Article  PubMed  Google Scholar 

  10. Hu FB . Sedentary lifestyle and risk of obesity and type 2 diabetes. Lipids 2003; 38: 103–108. Review.

    Article  CAS  PubMed  Google Scholar 

  11. Bowman SA . Television-viewing characteristics of adults: correlations to eating practices and overweight and health status. Prev Chronic Dis 2006; 3: A38. [E-pub 2006 March 15].

    PubMed  PubMed Central  Google Scholar 

  12. Thomson M, Spence JC, Raine K, Laing L . The association of television viewing with snacking behavior and body weight of young adults. Am J Health Promot 2008; 22: 329–335.

    Article  PubMed  Google Scholar 

  13. Ching PL, Willett WC, Rimm EB, Colditz GA, Gortmaker SL, Stampfer MJ . Activity level and risk of overweight in male health professionals. Am J Public Health 1996; 86: 25–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Frank LD, Andresen MA, Schmid TL . Obesity relationships with community design, physical activity, and time spent in cars. Am J Prev Med 2004; 27: 87–96.

    Article  PubMed  Google Scholar 

  15. Lopez-Zetina J, Lee H, Friis R . The link between obesity and the built environment. Evidence from an ecological analysis of obesity and vehicle miles of travel in California. Health Place 2006; 12: 656–664.

    Article  PubMed  Google Scholar 

  16. 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.

    Article  PubMed  Google Scholar 

  17. Gutiérrez-Fisac JL, Guallar-Castillón P, Díez-Gañán L, López García E, Banegas Banegas JR, Rodríguez Artalejo F . Work-related physical activity is not associated with body mass index and obesity. Obes Res 2002; 10: 270–276.

    Article  PubMed  Google Scholar 

  18. Kaleta D, Makowiec-Dabrowska T, Jegier A . Occupational and leisure-time energy expenditure and body mass index. Int J Occup Med Environ Health 2007; 20: 9–16.

    PubMed  Google Scholar 

  19. Lindström M . Means of transportation to work and overweight and obesity: a population-based study in southern Sweden. Prev Med 2008; 46: 22–28.

    Article  PubMed  Google Scholar 

  20. Cleland VJ, Schmidt MD, Dwyer T, Venn AJ . Television viewing and abdominal obesity in young adults: is the association mediated by food and beverage consumption during viewing time or reduced leisure-time physical activity? Am J Clin Nutr 2008; 87: 1148–1155.

    Article  CAS  PubMed  Google Scholar 

  21. Dunstan DW, Salmon J, Owen N, Armstrong T, Zimmet PZ, Welborn TA et al. Associations of TV viewing and physical activity with the metabolic syndrome in Australian adults. Diabetologia 2005; 48: 2254–2261.

    Article  CAS  PubMed  Google Scholar 

  22. Jakes RW, Day NE, Khaw KT, Luben R, Oakes S, Welch A et al. Television viewing and low participation in vigorous recreation are independently associated with obesity and markers of cardiovascular disease risk: EPIC-Norfolk population-based study. Eur J Clin Nutr 2003; 57: 1089–1096.

    Article  CAS  PubMed  Google Scholar 

  23. Tucker LA, Bagwell M . Television viewing and obesity in adult females. Am J Public Health 1991; 81: 908–911.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Chang PC, Li TC, Wu MT, Liu CS, Li CI, Chen CC et al. Association between television viewing and the risk of metabolic syndrome in a community-based population. BMC Public Health 2008; 8: 193.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Dunstan DW, Salmon J, Owen N, Armstrong T, Zimmet PZ, Welborn TA et al. Physical activity and television viewing in relation to risk of undiagnosed abnormal glucose metabolism in adults. Diabetes Care 2004; 27: 2603–2609.

    Article  PubMed  Google Scholar 

  26. Salmon J, Bauman A, Crawford D, Timperio A, Owen N . The association between television viewing and overweight among Australian adults participating in varying levels of leisure-time physical activity. Int J Obes Relat Metab Disord 2000; 24: 600–606.

    Article  CAS  PubMed  Google Scholar 

  27. Sugiyama T, Healy GN, Dunstan DW, Salmon J, Owen N . Joint associations of multiple leisure-time sedentary behaviours and physical activity with obesity in Australian adults. Int J Behav Nutr Phys Act 2008; 5: 35.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Hamrick K . Eating and Health Module User’s Guide. Administrative Publication No. AP-028. 2008. http://www.ers.usda.gov/Publications/AP/AP028/AP028.pdf (accessed 10 September, 2009).

  29. Shelley KJ . Developing the American Time Use Survey activity classification system. Mon Labor Rev 2005; 128: 3–15.

    Google Scholar 

  30. Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ et al. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc 2000; 32: S498–S504.

    Article  CAS  PubMed  Google Scholar 

  31. Tudor-Locke C, Washington TL, Ainsworth BE, Troiano R . Linking the American Time Use Survey (ATUS) and the compendium of physical activities: methods and rationale. J Phy Act Health 2009; 6: 347–353.

    Article  Google Scholar 

  32. Pate RR, Pratt M, Blair SN, Haskell WL, Macera CA, Bouchard C et al. Physical activity and public health: a recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA 1995; 273: 402–407.

    Article  CAS  PubMed  Google Scholar 

  33. US Department of Health and Human Services, US Department of Agriculture. Dietary Guidelines for Americans, 2005. US Department of Health and Human Services, US Department of Agriculture: Washington, DC, 2005.

  34. US Bureau of Labor Statistics and US Census Bureau. Current Population Survey Design and Methodology. Technical Paper 66. US Department of Labor, US Department of Commerce: Washington, DC, 2006, pp 14-1–14-3.

  35. RTI International. SUDAAN User's Manual, Release 9.0. Research Triangle Institute: Research Triangle Park, NC, 2004.

  36. Korn EL, Graubard BI . Analysis of Health Surveys. Wiley: New York, 1999.

    Book  Google Scholar 

  37. Parsons TJ, Power C, Manor O . Longitudinal physical activity and diet patterns in the 1958 British Birth Cohort. Med Sci Sports Exerc 2006; 38: 547–554.

    Article  PubMed  Google Scholar 

  38. Weuve J, Kang JH, Manson JE, Breteler MM, Ware JH, Grodstein F . Physical activity, including walking, and cognitive function in older women. JAMA 2004; 292: 1454–1461.

    Article  CAS  PubMed  Google Scholar 

  39. Shephard RJ . Curricular physical activity and academic performance. Ped Exerc Sci 1997; 9: 113–126.

    Article  Google Scholar 

  40. Rhodes RE, Smith NE . Personality correlates of physical activity: a review and meta-analysis. Br J Sports Med 2006; 40: 958–965.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Costa PT, McCrae RR . NEO Personality Inventory Professional Manual. Psychological Assessment Resources: Odessa, FL, 1992.

    Google Scholar 

  42. Salgado JF . The five factor model of personality and job performance in the European community. J App Psych 1997; 82: 30–43.

    Article  CAS  Google Scholar 

  43. 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.

    Article  CAS  PubMed  Google Scholar 

  44. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Hamilton MT, Hamilton DG, Zderic TW . Exercise physiology versus inactivity physiology: an essential concept for understanding lipoprotein lipase regulation. Exerc Sport Sci Rev 2004; 32: 161–166.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Jacobs DR, Ainsworth BE, Hartman TJ, Leon AS . A simultaneous evaluation of 10 commonly used physical activity questionnaires. Med Sci Sports Exerc 1993; 25: 81–91.

    Article  PubMed  Google Scholar 

  47. Brown WJ, Miller YD, Miller R . Sitting time and work patterns as indicators of overweight and obesity in Australian adults. Int J Obes Relat Metab Disord 2003; 27: 1340–1346.

    Article  CAS  PubMed  Google Scholar 

  48. Wang Y, Beydoun MA, Liang L, Caballero B, Kumanyika SK . Will all Americans become overweight or obese? Estimating the progression and cost of the US obesity epidemic. Obesity 2008; 16: 2323–2330.

    Article  PubMed  Google Scholar 

  49. Juster FT . Time, Goods, and Well-Being. Institute for Social Research, The University of Michigan: Ann Arbor, MI, 1985.

    Google Scholar 

  50. Krueger A . Validating the American Time Use Survey: does anybody really know what they were doing yesterday? Accessed at: http://www.irs.princeton.edu/admin/pdfs/AK_VALidating%20the%20American%20Time%20Use%20Survey.pdf on 25 May 2009.

  51. Tu S . Measuring farm women's time spent on unpaid work: diary versus stylized estimates. Accessed at: http://isi.cbs.nl/iamamember/CD2/pdf/606.PDF on 27 May 2009.

  52. Converse JM, Presser S . Survey Questions: Handcrafting the Standardized Questionnaire. Sage: Newbury Park, CA, 1989.

    Google Scholar 

  53. United States Department of Agriculture. Economic research service. Eating and Health Module (ATUS): 2007 current findings. Accessed at: http://www.ers.usda.gov/Data/ATUS/2007/2007current.htm on 10 June 2009.

Download references

Acknowledgements

We thank Karen Hamrick, PhD of the Economic Research Service at the US Department of Agriculture and the ATUS staff at the US Bureau of Labor and Statistics for their assistance with this project. The first author was supported by the Cancer Prevention Fellowship Program, Office of the Director, National Cancer Institute, National Institutes of Health during the preparation of this paper. She is now in the Department of Preventive Medicine at the University of Southern California. The views and opinions expressed in this paper are those of the authors and not necessarily those of the Department of Health and Human Services, the National Institutes of Health, or the National Cancer Institute.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to G F Dunton.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Dunton, G., Berrigan, D., Ballard-Barbash, R. et al. Joint associations of physical activity and sedentary behaviors with body mass index: results from a time use survey of US adults. Int J Obes 33, 1427–1436 (2009). https://doi.org/10.1038/ijo.2009.174

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ijo.2009.174

Keywords

This article is cited by

Search

Quick links