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:

The inverse relationship between number of steps per day and obesity in a population-based sample – the AusDiab study

International Journal of Obesity volume 31, pages 797–804 (2007)Cite this article

Abstract

Background:

Physical activity (PA) is inversely associated with obesity but the effect has been difficult to quantify using questionnaires. In particular, the shape of the association has not yet been well described. Pedometers provide an opportunity to better characterize the association.

Methods:

Residents of households over the age of 25 years in randomly selected census districts in Tasmania were eligible to participate in the AusDiab cross-sectional survey conducted in 1999–2000. 1848 completed the AusDiab survey and 1126 of these (609 women and 517 men) wore a pedometer for 2-weekdays. Questionnaire data on recent PA, TV time and other factors were obtained. The outcomes were waist circumference (in cm) and body mass index (BMI) (kg/m2).

Results:

Increasing daily steps were associated with a decline in the obesity measures. The logarithmic nature of the associations was indicated by a sharper decline for those with lower daily steps. For example, an additional 2000 steps for those taking only 2000 steps per day was associated with a reduction of 2.8 (95% confidence interval (CI): 2.1,4.4) cm in waist circumference among men (for women; 2.2 (95% CI: 0.6, 3.9 cm)) with a baseline of only 2000, steps compared to a 0.7 (95% CI 0.3, 1.1) cm reduction (for women; 0.6 (95% CI: 0.2, 1.0)) for those already walking 10 000 steps daily. In the multivariable analysis, clearer associations were detected for PA and these obesity measures using daily step number rather than PA time by questionnaire.

Interpretation:

Pedometer measures of activity indicate that the inverse association between recent PA and obesity is logarithmic in form with the greatest impact for a given arithmetic step number increase seen at lower levels of baseline activity. The findings from this study need to be examined in prospective settings.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Similar content being viewed by others

References

  1. 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 

  2. Cameron AJ, Welborn TA, Zimmet PZ, Dunstan DW, Owen N, Salmon J et al. Overweight and obesity in Australia: the 1999–2000 Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Med J Aust 2003; 178: 427–432.

    PubMed  Google Scholar 

  3. Centers for Disease Control and Prevention (CDC). Prevalence of diabetes and impaired fasting glucose in adults–United States, 1999–2000. Morb Mortal Week Rep 2003; 52: 833–837.

  4. Dunstan DW, Zimmet PZ, Welborn TA, De Courten MP, Cameron AJ, Sicree RA et al. The rising prevalence of diabetes and impaired glucose tolerance: the Australian Diabetes, Obesity and Lifestyle Study. Diabetes Care 2002; 25: 829–834.

    Article  PubMed  Google Scholar 

  5. Fitzgerald SJ, Kriska AM, Pereira MA, de Courten MP . Associations among physical activity, television watching, and obesity in adult Pima Indians. Med Sci Sports Exerc 1997; 29: 910–915.

    Article  CAS  PubMed  Google Scholar 

  6. 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 

  7. Sallis JF, Saelens BE . Assessment of physical activity by self-report: status, limitations, and future directions. Res Q Exerc Sport 2000; 71: S1–S14.

    Article  CAS  PubMed  Google Scholar 

  8. McCormack G, Giles-Corti B, Milligan R . The test–retest reliability of habitual incidental physical activity. Aust NZ J Public Health 2003; 27: 428–433.

    Article  Google Scholar 

  9. 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 

  10. Hu FB, Leitzmann MF, Stampfer MJ, Colditz GA, Willett WC, Rimm EB . Physical activity and television watching in relation to risk for type 2 diabetes mellitus in men. Arch Intern Med 2001; 161: 1542–1548.

    Article  CAS  PubMed  Google Scholar 

  11. 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 

  12. Chan CB, Spangler E, Valcour J, Tudor-Locke C . Cross-sectional relationship of pedometer-determind ambulatory activity to indicators of health. Obes Res 2003; 11: 1563–1570.

    Article  PubMed  Google Scholar 

  13. Tudor-Locke C, Bassett DR . How many steps/day are enough? Preliminary pedometer indices for public health. Sports Med 2004; 34: 1–8.

    Article  PubMed  Google Scholar 

  14. Miyatake N, Nishikawa H, Morishita A, Kunitomi M, Wada J, Suzuki H et al. Daily walking reduces visceral adipose tissue areas and improves insulin resistance in Japanese obese subjects. Diabetes Res Clin Pract 2002; 58: 101–107.

    Article  CAS  PubMed  Google Scholar 

  15. Bassett DR, Schneider PL, Huntington GE . Physical activity in an Old Order Amish community. Med Sci Sports Exerc 2004; 36: 79–85.

    Article  PubMed  Google Scholar 

  16. Chan CB, Ryan DA, Tudor-Locke C . Health benefits of a pedometer-based physical activity intervention in sedentary workers. Prev Med 2004; 39 (6): 1215–1222.

    Article  PubMed  Google Scholar 

  17. Dunstan DW, Zimmet PZ, Welborn TA, Cameron AJ, Shaw J, de Courten M et al. The Australian diabetes, obesity and lifestyle study (AusDiab) – methods and response rates. Diabetes Res Clin Pract 2002; 57: 119–129.

    Article  PubMed  Google Scholar 

  18. Tudor-Locke CE, Myers AM . Methodological consideration for researchers and practioners using pedometers to measure physical (ambulatory) activity. Rese Quart Exerc Sport 2001; 72: 1–12.

    Article  CAS  Google Scholar 

  19. Tudor-Locke C, Burkett L, Reis JP, Ainsworth BE, Macera CA, Wilson DK . How many days of pedometer monitoring predict weekly physical activity in adults? Prev Med 2005; 40 (3): 293–298.

    Article  CAS  PubMed  Google Scholar 

  20. Australian Institute for Health and Welfare (AIHW). The Active Australia Survey: A Guide and Manual for Implementation, Analysis and Reporting. AIHW: Canberra, 2003.

  21. Timperio A, Salmon J, Bull F, Rosenberg M . Validation of Adult Physical Activity Questions for use in Australian Population Surveys. University of Western Australia: Perth, 2002.

    Google Scholar 

  22. Brown W, Trost S, Bauman A, Mummery K, Owen N . Test- Re-Test Reliability Study of Physical Activity Questions for Use in Australian Population Surveys. University of Queensland: St Lucia, 2002.

    Google Scholar 

  23. Armstrong T, Bauman A, Davies J . Physical Activity Patterns of Australian adults. Results of the 1999 National Physical Activity Survey. Australian Institute of Health and Welfare: Canberra, Australia, 2000.

    Google Scholar 

  24. Salmon J, Owen N, Crawford D, Bauman A, Sallis JF . Physical activity and sedentary behaviour: a population-based study of barriers, enjoyment, and preference. Health Psychol 2003; 22: 178–188.

    Article  PubMed  Google Scholar 

  25. Ireland P, Jolley D, Giles G, O'Dea K, Powles J, Rutishauser I et al. Development of the Melbourne FFQ: a food frequency questionnaire for use in an Australian prospective study involving an ethnically diverse cohort. Asia Pacific J Clin Nutr 1994; 3: 19–31.

    CAS  Google Scholar 

  26. SPSS Inc. SPSS Statistical Software: Release 11.0. SPSS Corp: Chicago, IL, 2003.

  27. Stata Corp. Statistical Software: Release 8.0. Stata Corporation: College Station, TX, 2003.

  28. Royston P, Ambler G, Sauerbrei W . The use of fractional polynomials to model continuous risk variables in epidemiology. Int J Epidemiol 1999; 28: 964–974.

    Article  CAS  PubMed  Google Scholar 

  29. Kleinbaum DG, Kupper LL, Mueller KE, Nazim A . Applied Regression Analysis and Other Multivariable Methods 3rd edn. Duxbury: Belmont, CA, 1998.

    Google Scholar 

  30. 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 

  31. Petersen L, Schnohr P, Sorensen TI . Longitudinal study of the long-term relation between physical activity and obesity in adults. Int J Obes Relat Metab Disord 2004; 28 (1): 105–112.

    Article  CAS  PubMed  Google Scholar 

  32. Bouchard C, Depres JP, Tremblay A . Exercise and obesity. Obesity Res 1993; 1: 133–147.

    Article  CAS  Google Scholar 

  33. Pratt M, Macera CA, Blanton C . Levels of physical activity and inactivity in children and adults in the United States: current evidence and research issues. Med Sci Sports Exerc 1999; 31: S526–S533.

    Article  CAS  PubMed  Google Scholar 

  34. Garrow JS, Summerbell CD . Meta-analysis: effect of exercise, with or without dieting, on the body composition of overweight subjects. Eur J Clin Nutr 1995; 49: 1–10.

    CAS  PubMed  Google Scholar 

  35. Ballor DL, Keesey RE . A meta-analysis of the factors affecting exercise-induced changes in body mass, fat mass and fat-free mass in males and females. Int J Obes Relat Metab Disord 1991; 15: 717–726.

    CAS  Google Scholar 

  36. Eck LH, Pascale RW, Klesges RC, Ray JA, Klesges LM . Predictors of waist circumference change in healthy young adults. Int J Obes Relat Metab Disord 1995; 19: 765–769.

    CAS  PubMed  Google Scholar 

  37. Kahn HS, Tatham LM, Rodriguez C, Calle EE, Thun MJ, Heath Jr CW . Stable behaviors associated with adults' 10-year change in body mass index and likelihood of gain at the waist. Am J Public Health 1997; 87: 747–754.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Saris WH, Blair SN, van Baak MA, Eaton SB, Davies PS, Di Pietro L et al. How much physical activity is enough to prevent unhealthy weight gain? Outcome of the IASO 1st Stock Conference and consensus statement. Obes Rev 2003; 4: 101–114.

    Article  CAS  PubMed  Google Scholar 

  39. Morrill AC, Chinn CD . The obesity epidemic in the United States. J Public Health Policy 2004; 25: 353–366.

    Article  PubMed  Google Scholar 

  40. Marshall A, Ferney S . Are pedometers a measure or motivator for physical activity? Active Living – All Together Better National Physical Activity Conference, Fremantle, Western Australia 2003.

  41. Steps to a Better Health Manual http://www.cooperinst.org/.

Download references

Acknowledgements

We are most grateful to the following for their financial support of the study: The Commonwealth Department of Health and Aged Care, Abbott Australasia Pty Ltd, Alphapharm Pty Ltd, Aventis Pharmaceutical, AstraZeneca, Bristol-Myers Squibb Pharmaccuticals, Eli Lilly (Australia) Pty Ltd, GlaxoSmithKline, Janssen-Cilag (Australia) Pty Ltd, Merck Lipha s.a., Merck Sharp & Dohme (Australia), Novartis Pharmaceutical (Australia) Pty Ltd, Novo Nordisk Pharmaceutical Pty Ltd, Pharmacia and Upjohn Pty Ltd, Pfizer Pty Ltd, Roche Diagnostics, Sanofi Synthelabo (Australia) Pty Ltd, Servier Laboratories (Australia) Pty Ltd, BioRad Laboratories Pty Ltd, HITECH Pathology Pty Ltd, the Australian Kidney Foundation, Diabetes Australia, Diabetes Australia (Northern Territory), Queensland Health, South Australian Department of Human Services, Tasmanian Department of Health and Human Services, Territory Health Services, Victorian Department of Human Services, and Health Department of Western Australia. DD is supported by a National Health and Medical Research Council (NHMRC) Post-Doctoral Research Fellowship. JS is supported by a Victorian Health Promotion Foundation Public Health Research Fellowship. A-L Ponsonby provided comments on the manuscript draft. Also, for their invaluable contribution to the field activities of AusDiab, we are enormously grateful to Annie Allman, Marita Dalton, Adam Meehan, Clare Reid, Alison Stewart, Robyn Tapp and James Dilger. The AusDiab Steering Committee consisted of Dr B Atkins, Dr S Bennett, Dr S Chadban, Professor S Colagiuri, Dr M de Courten, Dr M D'Embden, Dr D Dunstan, Professor T Dwyer, Dr D Jolley, Dr P Magnus, Professor J Mathews, Dr D McCarty, Professor K O'Dea, Dr P Phillips, Dr P Popplewell, Mr I Kemp, Professor H Taylor, Professor T Welborn and Professor P Zimmet. Role of the Funding Source: The funding source had no such involvement in study design, collection, analysis and interpretation of data, in the writing of the report and in the decision to submit the paper for publication. Contributors: Terence Dwyer, Alison Venn, Leigh Blizzard and Paul Zimmet designed and implemented the study. Jenny Cochrane contributed to study implementation. David Hosmer, Trina Hosmer and Leigh Blizzard conducted the statistical analyses. All authors contributed to the interpretation of the study findings and the writing and revision of manuscript. Terence Dwyer is the guarantor of the paper.

Author information

Authors and Affiliations

  1. Murdoch Childrens Research Institute, Royal Children's Hospital, Parkville, Melbourne, Victoria, Australia

    T Dwyer

  2. Department of Biostatistics and Epidemiology, School of Public Health, University of Massachusetts, Amherst, MA, USA

    D Hosmer & T Hosmer

  3. Menzies Research Institute, University of Tasmania, Hobart, Australia

    A J Venn, C L Blizzard, R H Granger & J A Cochrane

  4. The Cooper Institute, Dallas, TX, USA

    S N Blair

  5. International Diabetes Institute, Caulfield, Melbourne, Victoria, Australia

    J E Shaw, P Z Zimmet & D Dunstan

Authors
  1. T Dwyer
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. D Hosmer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. T Hosmer
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. A J Venn
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. C L Blizzard
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. R H Granger
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. J A Cochrane
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. S N Blair
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. J E Shaw
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. P Z Zimmet
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. D Dunstan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to T Dwyer.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Dwyer, T., Hosmer, D., Hosmer, T. et al. The inverse relationship between number of steps per day and obesity in a population-based sample – the AusDiab study. Int J Obes 31, 797–804 (2007). https://doi.org/10.1038/sj.ijo.0803472

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/sj.ijo.0803472

Keywords

This article is cited by

Search

Advanced search

Quick links