Agreement and equivalence of estimated physical activity behaviours, using ENMO- and counts-based processing methods, for wrist-worn accelerometers in adolescents

References

• Aadland, E., Kvalheim, O. M., Anderssen, S. A., Resaland, G., & Andersen, L. B. (2018). The multivariate physical activity signature associated with metabolic health in children. International Journal of Behavioral Nutrition and Physical Activity, 15(1), 77. https://doi.org/10.1186/s12966-018-0707-z
   PubMed Web of Science ®Google Scholar
• Aadland, E., Nilsen, A. K., Andersen, L. B., Rowlands, A. V., & Kvalheim, O. M. (2021). A comparison of analytical approaches to investigate associations for accelerometry-derived physical. Journal of Sports Sciences, 39(4), 10. https://doi.org/10.1080/02640414.2020.1824341
   PubMed Web of Science ®Google Scholar
• Altman, D. G., & Bland, J. M. (1983). Measurement in medicine: The analysis of method comparison studies. Journal of the Royal Statistical Society, 32(3), 11. https://doi.org/10.2307/2987937
   Google Scholar
• Barker, A. R., Gracia-Marco, L., Ruiz, J. R., Castillo, M. J., Aparicio-Ugarriza, R., González-Gross, M., Kafatos, A., Androutsos, O., Polito, A., Molnar, D., Widhalm, K., & Moreno, L. A. (2018). Physical activity, sedentary time, TV viewing, physical fitness and cardiovascular disease risk in adolescents: The HELENA study. International Journal of Cardiology, 254, 7. https://doi.org/10.1016/j.ijcard.2017.11.080
   Web of Science ®Google Scholar
• Biddle, S., & Asare, M. (2011). Physical activity and mental health in children and adolescents: A review of reviews. British Journal of Sports Medicine, 45(11), 886–895. https://doi.org/10.1136/bjsports-2011-090185
   PubMed Web of Science ®Google Scholar
• Bland, J. M., & Altman, D. G. (1999). Measuring agreement in method comparison studies. Statistical Methods in Medical Research, 8(2), 27. https://doi.org/10.1177/096228029900800204
   Web of Science ®Google Scholar
• Boddy, L. M., Noonan, R., Kim, Y., Rowlands, A. V., Welk, G. J., Knowles, Z. R., & Fairclough, S. J. (2018). Comparability of children’s sedentary time estimates derived from wrist worn GENEActiv and Hip worn ActiGraph accelerometer thresholds. Journal of Science and Medicine in Sport, 21(10), 16. https://doi.org/10.1016/j.jsams.2018.03.015
   PubMed Web of Science ®Google Scholar
• Buchan, D. S., & McLellan, G. (2019). Comparing physical activity estimates in children from hip-worn actigraph GT3X+ accelerometers using raw and counts based processing methods. Journal of Sports Sciences, 37(7), 10. https://doi.org/10.1080/02640414.2018.1527198
   Web of Science ®Google Scholar
• Bull, F. C., Al-Ansari, S. S., Biddle, S., Borodulin, K., Buman, M. P., Cardon, G., Carty, C., Chaput, J.-P., Chastin, S., Chou, R., Dempsey, P. C., DiPietro, L., Ekelund, U., Firth, J., Friedenreich, C. M., Garcia, L., Gichu, M., Jago, R., Katzmarzyk, P. T., … Willumsen, J. F. (2020). World health organization 2020 guidelines on physical activity and sedentary behaviour. British Journal of Sports Medicine, 54(24), 1451. https://doi.org/10.1136/bjsports-2020-102955
   PubMed Web of Science ®Google Scholar
• Cain, K. L., Sallis, J. F., Conway, T. L., Dyck, D. V., & Calhoon, L. (2013). Using accelerometers in youth physical activity studies: A review of methods. Journal of Physical Activity & Health, 10(3), 14. https://doi.org/10.1123/jpah.10.3.437
   Web of Science ®Google Scholar
• Carson, V., Ridgers, N. D., Howard, B. J., Winkler, E. A. H., Healy, G. N., Owen, N., Dunstan, D. W., Salmon, J., & Kiechl, S. (2013). Light-intensity physical activity and cardiometabolic biomarkers in US adolescents. PloS One, 8(8), 7. https://doi.org/10.1371/journal.pone.0071417
   Web of Science ®Google Scholar
• Chandler, J. L., Brazendale, K., Beets, M. W., & Mealing, B. A. (2016). Classification of physical activity intensities using a wristworn accelerometer in 8-12 year old children. Pediatric Obesity, 11(2), 8. https://doi.org/10.1111/ijpo.12033
   Web of Science ®Google Scholar
• Choi, L., Ward, S. C., Schnelle, J. F., & Buchowski, M. S. (2012). Assessment of wear/nonwear time classification algorithms for triaxial accelerometer. Medicine and Science in Sports and Exercise, 44(10), 17. https://doi.org/10.1249/MSS.0b013e318258cb36
   Web of Science ®Google Scholar
• Clevenger, K. A., Pfeiffer, K. A., & Montoye, A. H. (2020). Cross-generational comparability of raw and count-based metrics from ActiGraph GT9X and wGT3X-BT accelerometers during free-living in youth. Measurement in Physical Education and Exercise Science, 24(3), 194–204. https://doi.org/10.1080/1091367X.2020.1773827
   Web of Science ®Google Scholar
• Crouter, S., Horton, M., & Bassett, D. (2013). Validity of actigraph child-specific equations during various physical activities. Medicine and Science in Sports and Exercise, 45(7), 7. https://doi.org/10.1249/MSS.0b013e318285f03b
   Web of Science ®Google Scholar
• Datta, D. (2017). blandr: A bland-altman method comparison package for R. [RStudio]. https://doi.org/10.5281/zenodo.824514
   Google Scholar
• Dixon, P. M., Saint-Maurice, P. F., Kim, Y., Hibbing, P., Bai, Y., & Welk, G. J. (2018). A primer on the use of equivalence testing for evaluating measurement agreement. Medicine and Science in Sports and Exercise, 50(4), 18. https://doi.org/10.1249/MSS.0000000000001481
   PubMed Web of Science ®Google Scholar
• Fairclough, S. J., Noonan, R., Rowlands, A. V., Hees, V. V., Knowles, Z., & Boddy, L. M. (2016). Wear compliance and activity in children wearing wrist- and hip-mounted accelerometers. Medicine and Science in Sports and Exercise, 48(2), 9. https://doi.org/10.1249/MSS.0000000000000771
   Web of Science ®Google Scholar
• Hänggi, J. M., Phillips, L. R. S., & Rowlands, A. V. (2013). Validation of the GT3X actigraph in children and comparison with the GT1M actigraph. Journal of Science and Medicine in Sport, 16(1), 6. https://doi.org/10.1016/j.jsams.2012.05.012
   Web of Science ®Google Scholar
• Hildebrand, M., Hansen, B. H., van Hees, V. T., & Ekelund, U. (2017). Evaluation of raw acceleration sedentary thresholds in children and adults. Scandinavian Journal of Medicine & Science in Sports, 28(12), 10. https://doi.org/10.1111/sms.12795
   Web of Science ®Google Scholar
• Hildebrand, M., Hees, V. T. V., Hansen, B. H., & Ekelund, U. (2014). Age group comparability of raw accelerometer output from wrist- and hip-worn monitors. Medicine and Science in Sports and Exercise, 46(9), 9. https://doi.org/10.1249/MSS.0000000000000289
   Web of Science ®Google Scholar
• Hurter, L., Fairclough, S. J., Knowles, Z. R., Porcellato, L. A., Cooper-Ryan, A. M., & Boddy, L. M. (2018). Establishing raw acceleration thresholds to classify sedentary and stationary behaviour in children. Children, 5(12), 18. https://doi.org/10.3390/children5120172
   PubMedGoogle Scholar
• Katzmarzyk, P. T., Barreira, T. V., Broyles, S. T., Champagne, C. M., Chaput, J.-P., Fogelholm, M., Hu, G., Johnson, W. D., Kuriyan, R., Kurpad, A., Lambert, E. V., Maher, C., Maia, J., Matsudo, V., Olds, T., Onywera, V., Sarmiento, O. L., Standage, M., Tremblay, M. S., … Church, T. S. (2015). Physical activity, sedentary time, and obesity in an international sample of children. Medicine and Science in Sports and Exercise, 47(10), 8. https://doi.org/10.1249/MSS.0000000000000649
   Web of Science ®Google Scholar
• Kim, Y., Hibbing, P., Saint-Maurice, P. F., Ellingson, L., Hennessy, E., Wolff-Hughes, D., Perna, F., & Welk, G. J. (2017). Surveillance of youth physical activity and sedentary behavior with wrist accelerometry. American Journal of Preventive Medicine, 52(6), 8. https://doi.org/10.1016/j.amepre.2017.01.012
   Web of Science ®Google Scholar
• Koo, T. K., & Li, M. (2016). A guideline of selecting and reporting intraclass correlation coefficients for reliability research. Journal of Chiropractic Medicine, 15(2), 9. https://doi.org/10.1016/j.jcm.2016.02.012
   PubMedGoogle Scholar
• Lakens, D. (2017). Equivalence tests: A practical primer for t tests, correlations, and meta-analyses. Social Psychological and Personality Science, 8(4), 355–362. https://doi.org/10.1177/1948550617697177
   PubMed Web of Science ®Google Scholar
• Leppänen, M. H., Migueles, J. H., Abdollahi, A. M., Engberg, E., Ortega, F. B., & Roos, E. (2022). Comparing estimates of physical activity in children across different cut‐points and the associations with weight status. Scandinavian Journal of Medicine & Science in Sports, 32(6), 971–983. https://doi.org/10.1111/sms.14147
   PubMed Web of Science ®Google Scholar
• Leppänen, M. H., Migueles, J. H., Cadenas, C., Henriksson, P., Mora, J., Henriksson, H., Labayen, I., Löf, M., Esteban, I., & Ortega, F. B. (2020). Hip and wrist accelerometers showed consistent associations with fitness and fatness in children aged 8‐12 years. Acta Paediatrica, 109(5), 9. https://doi.org/10.1111/apa.15043
   Web of Science ®Google Scholar
• Liljequist, D., Elfving, B., Roaldsen, K. S., & Chiacchio, F. (2019). Intraclass correlation—A discussion and demonstration of basic features. PloS One, 14(7), 7. https://doi.org/10.1371/journal.pone.0219854
   Web of Science ®Google Scholar
• Looney, M. A. (2018). Assessment of interrater and intermethod agreement in the kinesiology literature. Measurement in Physical Education and Exercise Science, 22(2), 14. https://doi.org/10.1080/1091367X.2017.1395742
   Web of Science ®Google Scholar
• Migueles, J. H., Aadland, E., Andersen, L. B., Brønd, J. C., Chastin, S. F., Hansen, B. H., Konstabel, K., Kvalheim, O. M., McGregor, D. E., Rowlands, A. V., Sabia, S., van Hees, V. T., Walmsley, R., Ortega, F. B., Wolstenholme, S., & Pluim, B. M. (2021). GRANADA consensus on analytical approaches to assess associations with accelerometer-determined physical behaviours (physical activity, sedentary behaviour and sleep) in epidemiological studies. British Journal of Sports Medicine, 55(1), 9. https://doi.org/10.1136/bjsports-2020-102360
   PubMed Web of Science ®Google Scholar
• Migueles, J. H., Cadenas-Sanchez, C., Ekelund, U., Delisle Nyström, C., Mora-Gonzalez, J., Löf, M., Labayen, I., Ruiz, J. R., & Ortega, F. B. (2017). Accelerometer data collection and processing criteria to assess physical activity and other outcomes: A systematic review and practical considerations. Sports Medicine, 47(9), 1821–1845. https://doi.org/10.1007/s40279-017-0716-0
   PubMed Web of Science ®Google Scholar
• Migueles, J. H., Cadenas, C., Tudor, C., Löf, M., Esteban, I., Molina, P., Mora, J., Rodriguez, M., Garcia, E., Ekelund, U., & Ortega, F. B. (2019). Comparability of published cut‐points for the assessment of physical activity: Implications for data harmonization. Scandinavian Journal of Medicine & Science in Sports, 29(4), 9. https://doi.org/10.1123/jmpb.2018-0063
   Web of Science ®Google Scholar
• Migueles, J. H., Rowlands, A. V., Huber, F., Sabia, S., & van Hees, V. T. (2019). GGIR: A research community–driven open source R package for generating physical activity and sleep outcomes from multi-day raw accelerometer data. Journal for the Measurement of Physical Behaviour, 2(3), 10. https://doi.org/10.1123/jmpb.2018-0063
   Google Scholar
• O’Brien, M. W. (2021). Implications and recommendations for equivalence testing in measures of movement behaviors: A scoping review. Journal for the Measurement of Physical Behaviour, 4(4), 353–362. https://doi.org/10.1123/jmpb.2021-0021
   Google Scholar
• Romanzini, M., Petroski, E., Ohara, D., Dourado, A., & Reichert, F. (2014). Calibration of actigraph GT3X, actical and RT3 accelerometers in adolescents. European Journal of Sports Science, 14(1), 10. https://doi.org/10.1080/17461391.2012.732614
   Web of Science ®Google Scholar
• Rowlands, A. V. (2018). Moving forward with accelerometer-assessed physical activity: Two strategies to ensure meaningful, interpretable, and comparable measures. Pediatric Exercise Science, 30(4), 7. https://doi.org/10.1123/pes.2018-0201
   Web of Science ®Google Scholar
• Rowlands, A. V., Dawkins, N., Maylor, B., Edwardson, C. L., Fairclough, S. J., Davies, M. J., Harrington, D. M., Khunti, K., & Yates, T. (2019). Enhancing the value of accelerometer-assessed physical activity: Meaningful visual comparisons of data-driven translational accelerometer metrics. Sports Medicine-Open, 5(1), 11. https://doi.org/10.1186/s40798-019-0225-9
   PubMedGoogle Scholar
• Rowlands, A. V., Edwardson, C. L., Davies, M. J., Khunti, K., Harrington, D. M., & Yates, T. (2018). Beyond cut points: Accelerometer metrics that capture the physical activity profile. Medicine and Science in Sports and Exercise, 50(6), 10. https://doi.org/10.1249/MSS.0000000000001561
   Web of Science ®Google Scholar
• Rowlands, A. V., Mirkes, E., Yates, T., Clemes, S., Davies, M., Khunti, K., & Edwardson, C. L. (2017). Accelerometer-assessed physical activity in epidemiology: Are monitors equivalent? Medicine and Science in Sports and Exercise, 50(2), 257–265. https://doi.org/10.1249/MSS.0000000000001435
   Web of Science ®Google Scholar
• Rowlands, A. V., Yates, T., Davies, M., Khunti, K., & Edwardson, C. L. (2016). Raw accelerometer data analysis with GGIR R-package: Does accelerometer brand matter? Medicine and Science in Sports and Exercise, 48(10), 7. https://doi.org/10.1249/MSS.0000000000000978
   PubMed Web of Science ®Google Scholar
• RStudio Team (2020). RStudio: Integrated Development for R. RStudio, PBC, Boston, MA. http://www.rstudio.com/
   Google Scholar
• Troiano, R. P., McClain, J. J., Brychta, R. J., & Chen, K. Y. (2015). Evolution of accelerometer methods for physical activity research. British Journal of Sports Medicine, 48(13), 1019–1023. https://doi.org/10.1136/bjsports-2014-093546
   Web of Science ®Google Scholar
• Trost, S. G. (2020). Population-level physical activity surveillance in young people: Are accelerometer-based measures ready for prime time? International Journal of Behavioral Nutrition and Physical Activity, 17(1), 28. https://doi.org/10.1186/s12966-020-00929-4
   PubMed Web of Science ®Google Scholar
• Trost, S., Loprinzi, P., Moore, R., & Pfeiffer, K. (2011). Comparison of accelerometer cut points for predicting activity intensity in youth. Medicine and Science in Sports and Exercise, 43(7), 7. https://doi.org/10.1249/MSS.0b013e318206476e
   Web of Science ®Google Scholar
• Tudor-Locke, C., Barreira, T. V., Jr, J. M. S., Mire, E. F., Chaput, J.-P., Fogelholm, M., Hu, G., Kuriyan, R., Kurpad, A., Lambert, E. V., Maher, C., Maia, J., Matsudo, V., Olds, T., Onywera, V., Sarmiento, O. L., Standage, M., Tremblay, M. S., Zhao, P., & Katzmarzyk, P. T. (2015). Improving wear time compliance with a 24-hour waist-worn accelerometer protocol in the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE). International Journal of Behavioral Nutrition and Physical Activity, 12(11), 9. https://doi.org/10.1186/s12966-015-0172-x
   PubMed Web of Science ®Google Scholar
• van Hees, V. T., Fang, Z., Langford, J., Assah, F., Mohammad, A., da Silva, I., Trenell, M., White, T., Wareham, N., & Brage, S. (2014). Autocalibration of accelerometer data for free-living physical activity assessment using local gravity and temperature: An evaluation on four continents. Journal of Applied Physiology, 117(7), 7. https://doi.org/10.1152/japplphysiol.00421.2014
   Web of Science ®Google Scholar
• van Hees, V. T., Gorzelniak, L., Dean Leon, E., Eder, M., Pias, M., Taherian, S., Ekelund, U., Renström, F., Franks, P., Horsch, A., Brage, S., & Müller, M. (2013). Separating movement and gravity components in an acceleration signal and implications for the assessment of human daily physical activity. PloS One, 8(4), 4. https://doi.org/10.1371/journal.pone.0061691
   Web of Science ®Google Scholar