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Do accelerometer-based physical activity patterns differentially affect cardiorespiratory fitness? A growth mixture modeling approach

  • Sophie BaumannEmail author
  • Diana Guertler
  • Franziska Weymar
  • Martin Bahls
  • Marcus Dörr
  • Neeltje van den Berg
  • Ulrich John
  • Sabina Ulbricht
Article

Abstract

Findings on the association between cardiorespiratory fitness (CRF) and moderate-to-vigorous physical activity (MVPA) may be distorted if patterns of accumulated MVPA over a week exist but are ignored. Our aim was to identify MVPA patterns and to associate them to CRF. Two hundred twenty-four 40–75-year-old adults wore accelerometers for 7 days. CRF was measured by peak oxygen uptake (V′O2,peak) assessed on a cycle ergometer via standardized cardiopulmonary exercise testing. Growth mixture modeling indicated four MVPA patterns: “low/stable” (57%, Mean MVPA time (M) = 21 min day−1), “medium/stable” (20%, M = 46 min day−1), “medium/weekend high” (14%, M = 47 min day−1), and “high/weekend low” (9%, M = 71 min day−1). V′O2,peak was higher for persons with “high/weekend low” and “medium/weekend high” patterns compared to “low/stable” and “medium/stable” (p values < 0.001). The same total amount of MVPA may have greater benefit if performed on fewer days during the week but with a longer duration than if performed every day but with a lower duration.

Keywords

Oxygen uptake Aerobic capacity Motion sensor Latent class Unobserved heterogeneity Adults 

Notes

Funding

This study was funded by the Federal Ministry of Education and Research as part of the DZHK (Grant Number 81/Z540100152).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The local ethics committee approved the study (BB 002/15a).

Human and animal rights and Informed consent

All procedures followed were in accordance with ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was obtained from all patients for being included in the study.

References

  1. Aadahl, M., Kjaer, M., Kristensen, J. H., Mollerup, B., & Jorgensen, T. (2007). Self-reported physical activity compared with maximal oxygen uptake in adults. European Journal of Cardiovascular Prevention & Rehabilitation, 14, 422–428.  https://doi.org/10.1097/HJR.0b013e3280128d00 CrossRefGoogle Scholar
  2. Aadland, E., Jepsen, R., Andersen, J. R., & Anderssen, S. A. (2013). Increased physical activity improves aerobic fitness, but not functional walking capacity, in severely obese subjects participating in a lifestyle intervention. Journal of Rehabilitation Medicine, 45, 1071–1077.  https://doi.org/10.2340/16501977-1205 CrossRefGoogle Scholar
  3. Akaike, H. (1998). Information theory and an extension of the maximum likelihood principle. In E. Parzen, K. Tanabe, & G. Kitagawa (Eds.), Selected papers of Hirotugu Akaike (pp. 199–213). New York, NY: Springer.CrossRefGoogle Scholar
  4. Balady, G. J., Arena, R., Sietsema, K., Myers, J., Coke, L., Fletcher, G. F., et al. (2010). Clinician’s Guide to cardiopulmonary exercise testing in adults: A scientific statement from the American Heart Association. Circulation, 122, 191–225.  https://doi.org/10.1161/CIR.0b013e3181e52e69 CrossRefGoogle Scholar
  5. Cao, Z. B., Miyatake, N., Higuchi, M., Miyachi, M., Ishikawa-Takata, K., & Tabata, I. (2010). Predicting VO2max with an objectively measured physical activity in Japanese women. Medicine and Science in Sports and Exercise, 42, 179–186.  https://doi.org/10.1249/MSS.0b013e3181af238d CrossRefGoogle Scholar
  6. Ceaser, T. G., Fitzhugh, E. C., Thompson, D. L., & Bassett, D. R., Jr. (2013). Association of physical activity, fitness, and race: NHANES 1999-2004. Medicine and Science in Sports and Exercise, 45, 286–293.  https://doi.org/10.1249/MSS.0b013e318271689e CrossRefGoogle Scholar
  7. Dyrstad, S. M., Anderssen, S. A., Edvardsen, E., & Hansen, B. H. (2016). Cardiorespiratory fitness in groups with different physical activity levels. Scandinavian Journal of Medicine and Science in Sports, 26, 291–298.  https://doi.org/10.1111/sms.12425 CrossRefGoogle Scholar
  8. Evenson, K. R., Herring, A. H., & Wen, F. (2017). Accelerometry-assessed latent class patterns of physical activity and sedentary behavior with mortality. American Journal of Preventive Medicine, 52, 135–143.  https://doi.org/10.1016/j.amepre.2016.10.033 CrossRefGoogle Scholar
  9. Evenson, K. R., Wen, F., Metzger, J. S., & Herring, A. H. (2015). Physical activity and sedentary behavior patterns using accelerometry from a national sample of United States adults. International Journal of Behavioral Nutrition and Physical Activity, 12, 20.  https://doi.org/10.1186/s12966-015-0183-7 CrossRefGoogle Scholar
  10. Glaser, S., Ittermann, T., Schaper, C., Obst, A., Dorr, M., Spielhagen, T., et al. (2013). The Study of Health in Pomerania (SHIP) reference values for cardiopulmonary exercise testing. Pneumologie, 67, 58–63.  https://doi.org/10.1055/s-0032-1325951 Google Scholar
  11. Guertler, D., Meyer, C., Dorr, M., Braatz, J., Weymar, F., John, U., et al. (2016). Reach of individuals at risk for cardiovascular disease by proactive recruitment strategies in general practices, job centers, and health insurance. International Journal of Behavioral Medicine, 24, 153–160.  https://doi.org/10.1007/s12529-016-9584-5 CrossRefGoogle Scholar
  12. Haskell, W. L., Lee, I. M., Pate, R. R., Powell, K. E., Blair, S. N., Franklin, B. A., et al. (2007). Physical activity and public health: Updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Circulation, 116, 1081–1093.  https://doi.org/10.1161/circulationaha.107.185649 CrossRefGoogle Scholar
  13. Hebestreit, H., Kieser, S., Rudiger, S., Schenk, T., Junge, S., Hebestreit, A., et al. (2006). Physical activity is independently related to aerobic capacity in cystic fibrosis. European Respiratory Journal, 28, 734–739.  https://doi.org/10.1183/09031936.06.00128605 CrossRefGoogle Scholar
  14. Jones, N. L., Makrides, L., Hitchcock, C., Chypchar, T., & McCartney, N. (1985). Normal standards for an incremental progressive cycle ergometer test. American Review of Respiratory Disease, 131, 700–708.  https://doi.org/10.1164/arrd.1985.131.5.700 Google Scholar
  15. Jones, S. A., Wen, F., Herring, A. H., & Evenson, K. R. (2016). Correlates of US adult physical activity and sedentary behavior patterns. Journal of Science and Medicine in Sport, 19, 1020–1027.  https://doi.org/10.1016/j.jsams.2016.03.009 CrossRefGoogle Scholar
  16. Kreuter, F., & Muthén, B. (2008). Analyzing criminal trajectory profiles: Bridging multilevel and group-based approaches using growth mixture modeling. Journal of Quantitative Criminology, 24, 1–31.CrossRefGoogle Scholar
  17. Kulinski, J. P., Khera, A., Ayers, C. R., Das, S. R., de Lemos, J. A., Blair, S. N., et al. (2014). Association between cardiorespiratory fitness and accelerometer-derived physical activity and sedentary time in the general population. Mayo Clinic Proceedings, 89, 1063–1071.  https://doi.org/10.1016/j.mayocp.2014.04.019 CrossRefGoogle Scholar
  18. Lee, I. M., & Skerrett, P. J. (2001). Physical activity and all-cause mortality: What is the dose-response relation? Medicine and Science in Sports and Exercise, 33(6 Suppl), S459–S471. (discussion S493–S454).CrossRefGoogle Scholar
  19. Marschollek, M. (2013). A semi-quantitative method to denote generic physical activity phenotypes from long-term accelerometer data: The ATLAS index. PLoS ONE, 8, e63522.  https://doi.org/10.1371/journal.pone.0063522 CrossRefGoogle Scholar
  20. McHorney, C. A., Ware, J. E., Jr., & Raczek, A. E. (1993). The MOS 36-Item Short-Form Health Survey (SF-36): II. Psychometric and clinical tests of validity in measuring physical and mental health constructs. Medical Care, 31, 247–263.CrossRefGoogle Scholar
  21. Metzger, J. S., Catellier, D. J., Evenson, K. R., Treuth, M. S., Rosamond, W. D., & Siega-Riz, A. M. (2008). Patterns of objectively measured physical activity in the United States. Medicine and Science in Sports and Exercise, 40, 630–638.  https://doi.org/10.1249/MSS.0b013e3181620ebc CrossRefGoogle Scholar
  22. Motl, R. W., Sandroff, B. M., Pilutti, L. A., Klaren, R. E., Baynard, T., & Fernhall, B. (2017). Physical activity, sedentary behavior, and aerobic capacity in persons with multiple sclerosis. Journal of the Neurological Sciences, 372, 342–346.  https://doi.org/10.1016/j.jns.2016.11.070 CrossRefGoogle Scholar
  23. Mundwiler, J., Schupbach, U., Dieterle, T., Leuppi, J. D., Schmidt-Trucksass, A., Wolfer, D. P., et al. (2017). Association of occupational and leisure-time physical activity with aerobic capacity in a working population. PLoS ONE, 12, e0168683.  https://doi.org/10.1371/journal.pone.0168683 CrossRefGoogle Scholar
  24. Muthén, L. K., & Muthén, B. O. (1998–2012). Mplus user’s guide (7th edn). Los Angeles, CA: Muthén & Muthén.Google Scholar
  25. Myers, J., Arena, R., Franklin, B., Pina, I., Kraus, W. E., McInnis, K., et al. (2009). Recommendations for clinical exercise laboratories: A scientific statement from the American Heart Association. Circulation, 119, 3144–3161.  https://doi.org/10.1161/circulationaha.109.192520 CrossRefGoogle Scholar
  26. Palange, P., Ward, S. A., Carlsen, K. H., Casaburi, R., Gallagher, C. G., Gosselink, R., et al. (2007). Recommendations on the use of exercise testing in clinical practice. European Respiratory Journal, 29, 185–209.  https://doi.org/10.1183/09031936.00046906 CrossRefGoogle Scholar
  27. Pedišić, Ž., & Bauman, A. (2015). Accelerometer-based measures in physical activity surveillance: Current practices and issues. British Journal of Sports Medicine, 49, 219–223.  https://doi.org/10.1136/bjsports-2013-093407 CrossRefGoogle Scholar
  28. Ramirez-Marrero, F. A., Miles, J., Joyner, M. J., & Curry, T. B. (2014). Self-reported and objective physical activity in postgastric bypass surgery, obese and lean adults: Association with body composition and cardiorespiratory fitness. Journal of Physical Activity & Health, 11, 145–151.  https://doi.org/10.1123/jpah.2012-0048 CrossRefGoogle Scholar
  29. Ross, R., Blair, S. N., Arena, R., Church, T. S., Despres, J. P., Franklin, B. A., et al. (2016). Importance of assessing cardiorespiratory fitness in clinical practice: A case for fitness as a clinical vital sign: A scientific statement from the American Heart Association. Circulation, 134, e653–e699.  https://doi.org/10.1161/cir.0000000000000461 CrossRefGoogle Scholar
  30. Savi, D., Di Paolo, M., Simmonds, N., Onorati, P., Internullo, M., Quattrucci, S., et al. (2015). Relationship between daily physical activity and aerobic fitness in adults with cystic fibrosis. BMC Pulmonary Medicine, 15, 59.  https://doi.org/10.1186/s12890-015-0036-9 CrossRefGoogle Scholar
  31. Sclove, S. L. (1987). Application of model-selection criteria to some problems in multivariate analysis. Psychometrika, 52, 333–343.  https://doi.org/10.1007/BF02294360 CrossRefGoogle Scholar
  32. Serrano-Sanchez, J. A., Delgado-Guerra, S., Olmedillas, H., Guadalupe-Grau, A., Arteaga-Ortiz, R., Sanchis-Moysi, J., et al. (2010). Adiposity and age explain most of the association between physical activity and fitness in physically active men. PLoS ONE, 5, e13435.  https://doi.org/10.1371/journal.pone.0013435 CrossRefGoogle Scholar
  33. StataCorp. (2015). Stata statistical software: Release 14.1. College Station, TX: StataCorp LP.Google Scholar
  34. Troiano, R. P., Berrigan, D., Dodd, K. W., Masse, L. C., Tilert, T., & McDowell, M. (2008). Physical activity in the United States measured by accelerometer. Medicine and Science in Sports and Exercise, 40, 181–188.  https://doi.org/10.1249/mss.0b013e31815a51b3 CrossRefGoogle Scholar
  35. Ullrich, A., Baumann, S., Voigt, L., John, U., van den Berg, N., Dorr, M., et al. (2018). Patterns of accelerometer-based sedentary behavior and their association with cardiorespiratory fitness in adults. Scandinavian Journal of Medicine and Science in Sports, 28, 2702–2709.  https://doi.org/10.1111/sms.13289 CrossRefGoogle Scholar
  36. van den Berg, N., Ulbricht, S., Schwaneberg, T., Weitmann, K., Weymar, F., Groß, S., et al. (2017). The influence of wearing schemes and supportive telephone calls on adherence in accelerometry measurement: Results of a randomized controlled trial. Patient preference and adherence, 11, 597–602.  https://doi.org/10.2147/PPA.S129640 CrossRefGoogle Scholar
  37. Vermunt, J. K. (2010). Latent class modeling with covariates: Two improved three-step approaches. Political Analysis, 18, 450–469.  https://doi.org/10.1093/pan/mpq025 CrossRefGoogle Scholar
  38. Wang, J., & Wang, X. (2012). Structural equation modeling: Applications using Mplus. West Sussex, UK: Wiley.CrossRefGoogle Scholar
  39. Weymar, F., Braatz, J., Guertler, D., van den Berg, N., Meyer, C., John, U., et al. (2015). Characteristics associated with non-participation in 7-day accelerometry. Preventive Medicine Reports, 2, 413–418.  https://doi.org/10.1016/j.pmedr.2015.05.003 CrossRefGoogle Scholar
  40. Yu, C. A., Rouse, P. C., Veldhuijzen Van Zanten, J. J., Ntoumanis, N., Kitas, G. D., Duda, J. L., et al. (2015). Subjective and objective levels of physical activity and their association with cardiorespiratory fitness in rheumatoid arthritis patients. Arthritis Research & Therapy, 17, 59.  https://doi.org/10.1186/s13075-015-0584-7 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Institute and Policlinic for Occupational and Social Medicine, Faculty of MedicineTechnische Universität DresdenDresdenGermany
  2. 2.Institute of Social Medicine and PreventionUniversity Medicine GreifswaldGreifswaldGermany
  3. 3.German Centre for Cardiovascular Research (DZHK)GreifswaldGermany
  4. 4.Institute for Community Medicine, Section Epidemiology of Health Care and Community HealthUniversity Medicine GreifswaldGreifswaldGermany
  5. 5.Department of Internal Medicine BUniversity Medicine GreifswaldGreifswaldGermany

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