Influence of epoch length on measurement of light physical activity in the elderly: A technical analysis
Aims: To clarify how epoch lengths of accelerometers affect measurement of physical activity in elderly people. Methods: The data was based on 70 elderly people (72.6 ± 5.4 years) living in Japan between 2017 and 2018. Furthermore, we used data obtained from triaxial accelerometers that the subjects wore for more than 10 hours every day for 7 days. We evaluated light physical activity (2.9 Mets or less) and further grouped it into sedentary behaviour (SB, 1.5 Mets or less) and Light Intensity Physical Activity (LIPA, between 1.6 and 2.9 Mets). We also compared 10-second epoch lengths (ELs) to 60-second ELs (%) by Bayesian estimation. Results: In 2017 and 2018, SB at 10-second ELs was longer than at 60-second ELs (55.5 vs. 50.4% in 2017; 55.7 vs. 48.9% in 2018); however, LIPA at 10-second ELs was shorter than at 60-second ELs (35.0 vs. 42.3% in 2017; 35.0 vs. 44.5% in 2018). The Bayesian factor varied between 3.0x1012 and 3.2x1024. The robustness of the Bayesian factor was confirmed by the robustness check. Furthermore, effect sizes were between |1.68| and |3.00|. Conclusion: ELs of the accelerometer may affect measurement of physical activity in elderly people. Thus, SB at 10-second ELs may be longer than at 60-second ELs and may be the reverse for LIPA.
Ayabe, M., Kumahara, H., Morimura, K., Tanaka, H. Epoch length and the physical activity bout analysis: An accelerometry research issue. BMC Research Notes. 2013;6;20. https://doi.org/10.1186/1756-0500-6-20
Cohen, J. Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ Lawrence Erlbaum Associates. 1988.
Dawid, A.P. Posterior expectations for large observations. Biometrika. 1973;60; 664-667. https://doi.org/10.1093/biomet/60.3.664
Dencker, M., Svensson, J., EI-Naaman, B., Bugge, A., Andersen, L.B. Importance of epoch length and registration time on accelerometer measurements in younger children. J Sports Med Phys Fitness. 2012;52(2);115-121.
Gabriel, K.P., McClain, J.J., Schmid, K.K., Storti, K.L., High, R.R., Underwood, D.A., Kuller, L.H., Kriska, A.M. Issues in accelerometer methodology: the role of epoch length on estimates of physical activity and relationships with health outcomes in overweight, post-menopausal women. Int J Behav Nutr Phys Act. 2010;15(7);53. https://doi.org/10.1186/1479-5868-7-53
Gelman A. Bayesian statistics then and now. Stat Sci. 2010;25;162-165.
Gelman, A., Carlin, J.B., Stern, H.S., Dunston, D.B., Vehtari, A., Rubin, D.B. Bayesian data analysis, 3rd ed. Boca Raton Chapman & Hall/CRC. 2014.
Hoeling, J.A., Madigan, D., Rafttery, A.E., Volinsky, C.T. Bayesian model averaging: A tutorial. Stat Sci. 1999;14;382-417. https://www.jstor.org/stable/2676803
Jaynes, E.T. Bayesian methods: general background. In Justice JH ed. Maximum Entry and Bayesian Methods in Applied Statistics, 1-25. Cambridge: Cambridge University Press, 1986. https://doi.org/10.1017/cbo9780511569678.003
John, K. Bayesian estimation supersedes the t test. J Exp Psychol Gen. 2013;142; 573-603.
Maarten, M., Schönbrodt, F.D., Richard, D.M., Yuling, Y., Andrew, G., Wagenmakers, E.J. A Bayesian bird's eye view of ‘Replications of important results in social psychology. Royal Society Open Science. 2017. https://doi.org/10.1098/rsos.160426
Morey, R.D., Romeijn, J.W., Rouder, N. The philosophy of Bayes factors and the quantification of statistical evidence. J Math Psychol. 2016;72;6-18. https://doi.org/10.1016/j.jmp.2015.11.001
Michael, S.O., Jason, A.S., Greta, C.B., Ava, D.S., Glenn, K.K. How humans walk: bout duration, steps per bout, and rest duration. J Rehabilitation Research & Development. 2008;45;Issue 7. https://doi.org/10.1682/jrrd.2007.11.0197
Mâsse, L.C., Fuemmeler, B.F., Anderson, C.B., Matthews, C.E., Trost, S.G., Catellier, D.J., Treuth, M. Accelerometer data reduction: a comparison of four reduction algorithms on select outcome variables. Med Sci Sports Exerc, 2005;37;S44-54. https://doi.org/10.1249/01.mss.0000185674.09066.8a
Nilsson, A., Ekelund, U., Yngve, A., Sjöström, M. Assessing Physical Activity Among Children with Accelerometers using Different Time Sampling Intervals and Placements. Medicine & Science in Sports & Exercise. 2001;33(5);p5252. https://doi.org/10.1123/pes.14.1.87
Owari, Y., Miyatake, N., Suzuki, H. “Active Guide” Brochure Reduces Sedentary Behavior of Elderly People: A Randomized Controlled Trial. Acta Medica Okayama. 2019;73;427-432. https://doi.org/10.18926/AMO/57373
Ozechowski, T.J. Empirical Bayes MCMC estimation for modeling treatment processes, mechanisms of change, and clinical outcomes in small samples. J Consult Clin Psychol. 2014;82(5);854-67. https://doi.org/10.1037/a0035889
Pettee, N.K., Storti, K.L., Ainsworth, B.E., Kriska, A.M. Measurement of Physical Activity and Inactivity in Epidemiologic Studies. In Lee IM, ed. Epidemiological Methods in Physical Activity Studies. New York Oxford University Press. 2009;15-33. https://doi.org/10.1093/acprof:oso/9780195183009.003.0002
Ronald L. Wasserstein & Nicole A. Lazar (2016) The ASA Statement on p-Values: Context, Process, and Purpose, The American Statistician, 70:2, 129-133. https://doi.org/10.1080/00031305.2016.1154108
Rouder, J.N., Morey, R.D. A Bayer-factor meta analysis of Bem’s ESP claim. Psychon B Rev. 2011;18(4);682-689. https://doi.org/10.3758/s13423-011-0088-7
Trost, S.G., McIver, K.L., Pate, R.R. Conducting accelerometer-based activity assessments in field-based research. Med Sci Sports Exerc. 2005;37(11 Suppl);531-543. https://doi.org/10.1249/01.mss.0000185657.86065.98
Vale, S., Santos, R., Silva, P., Soares-Miranda, L., Mota, J. Preschool children physical activity measurement: importance of epoch length choice. Pediatr Exerc Sci. 2009;21(4);413-20. https://doi.org/10.1123/pes.21.4.413
Wagenmakers, E.J., Lodewyckx, T., Kuriyal, H., Grasman, R. Bayesian hypothesis testing for psychologists: A tutorial on the savage-dickey method. Cognit Psychol. 2010; 60(3);158-189. https://doi.org/10.1016/j.cogpsych.2009.12.001
Wagenmakers, E.J., Beek, T.F., Rotteveel, M., Gierholz, A., Matzke, D., Steingroever, H., Ly, A., Verhagen, J., Selker, R., Sasiadek, A., Gronau, Q.F., Love, J., Pinto, Y. Turning the hands of time again: a purely confirmatory replication study and a Bayesian analysis. Front Psychol. 2015;6;494. https://doi.org/10.3389/fpsyg.2015.00494
Copyright (c) 2018 Journal of Human Sport and Exercise
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.