Using Devices to Assess Physical Activity and Sedentary Behavior in a Large Cohort Study: The Women’s Health Study

in Journal for the Measurement of Physical Behaviour
Restricted access

Purchase article

USD  $24.95

Student 1 year subscription

USD  $37.00

1 year subscription

USD  $50.00

Student 2 year subscription

USD  $71.00

2 year subscription

USD  $93.00

In recent years, it has become feasible to use devices for assessing physical activity and sedentary behavior among large numbers of participants in epidemiologic studies, allowing for more precise assessments of these behaviors and quantification of their associations with health outcomes. Between 2011–2015, the Women’s Health Study (WHS) used the Actigraph GT3X+ device to measure physical activity and sedentary behavior over seven days, during waking hours, among 17,708 women (Mage, 72 years) living throughout the United States. Devices were sent to and returned by participants via mail. We describe here the methods used to collect and process the accelerometer data for epidemiologic data analyses. We also provide metrics that describe the quality of the accelerometer data collected, as well as expanded findings regarding previously published associations of physical activity or sedentary behavior with all-cause mortality during an average follow-up of 2.3 years (207 deaths). The WHS is one of the earliest “next generation” epidemiologic studies of physical activity, utilizing wearable devices, in which long-term follow-up of participants for various health outcomes is anticipated. It therefore serves as a useful case study in which to discuss unique challenges and issues faced.

Lee and Buring are with the Division of Preventive Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA; and also with the Dept. of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA. Shiroma is with the Laboratory of Epidemiology and Population Science, National Institute on Aging, Bethesda, MD. Evenson is with the Dept. of Epidemiology, Gillings School of Global Public Health, University of North Carolina–Chapel Hill, Chapel Hill, NC. Kamada is with the Dept. of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA; and also with the Dept. of Physical Activity Research, National Institute of Health and Nutrition, NIBIOHN, Tokyo, Japan. LaCroix is with the Dept. of Family Medicine and Public Health, University of California San Diego, San Diego, CA.

Lee (ilee@rics.bwh.harvard.edu) is corresponding author.
  • Aguilar-Farias, N., Brown, W.J., & Peeters, G.M. (2014). ActiGraph GT3X+ cut-points for identifying sedentary behaviour in older adults in free-living environments. Journal of Science and Medicine in Sport, 17(3), 293299. doi:10.1016/j.jsams.2013.07.002

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Alessa, H.B., Chomistek, A.K., Hankinson, S.E., Barnett, J.B., Rood, J., Matthews, C.E., … Tobias, D.K. (2017). Objective measures of physical activity and cardiometabolic and endocrine biomarkers. Medicine & Science in Sports & Exercise, 49(9), 18171825. PubMed ID: 28398945 doi:10.1249/MSS.0000000000001287

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bassett, D.R., Jr., Toth, L.P., LaMunion, S.R., & Crouter, S.E. (2017). Step counting: A review of measurement considerations and health-related applications. Sports Medicine, 47(7), 13031315. PubMed ID: 28005190 doi:10.1007/s40279-016-0663-1

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brocklebank, L.A., Falconer, C.L., Page, A.S., Perry, R., & Cooper, A.R. (2015). Accelerometer-measured sedentary time and cardiometabolic biomarkers: A systematic review. Preventive Medicine, 76, 92102. PubMed ID: 25913420 doi:10.1016/j.ypmed.2015.04.013

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Buman, M.P., Winkler, E.A., Kurka, J.M., Hekler, E.B., Baldwin, C.M., Owen, N., … Gardiner, P.A. (2014). Reallocating time to sleep, sedentary behaviors, or active behaviors: Associations with cardiovascular disease risk biomarkers, NHANES 2005–2006. American Journal of Epidemiology, 179(3), 323334. PubMed ID: 24318278 doi:10.1093/aje/kwt292

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chastin, S.F., Palarea-Albaladejo, J., Dontje, M.L., & Skelton, D.A. (2015). Combined effects of time spent in physical activity, sedentary behaviors and sleep on obesity and cardio-metabolic health markers: A novel compositional data analysis approach. PLoS ONE, 10(10), 0139984. PubMed ID: 26461112 doi:10.1371/journal.pone.0139984

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Choi, L., Liu, Z., Matthews, C.E., & Buchowski, M.S. (2011). Validation of accelerometer wear and nonwear time classification algorithm. Medicine & Science in Sports & Exercise, 43(2), 357364. PubMed ID: 20581716 doi:10.1249/MSS.0b013e3181ed61a3

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Choi, L., Ward, S.C., Schnelle, J.F., & Buchowski, M.S. (2012). Assessment of wear/nonwear time classification algorithms for triaxial accelerometer. Medicine & Science in Sports & Exercise, 44(10), 20092016. PubMed ID: 22525772 doi:10.1249/MSS.0b013e318258cb36

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chomistek, A.K., Shiroma, E.J., & Lee, I.M. (2016). The relationship between time of day of physical activity and obesity in older women. The Journal of Physical Activity and Health, 13(4), 416418. doi:10.1123/jpah.2015-0152

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chomistek, A.K., Yuan, C., Matthews, C.E., Troiano, R.P., Bowles, H.R., Rood, J., … Bassett, D.R., Jr. (2017). Physical activity assessment with the ActiGraph GT3X and doubly labeled water. Medicine & Science in Sports & Exercise, 49(9), 19351944. PubMed ID: 28419028 doi:10.1249/MSS.0000000000001299

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cook, N.R., Lee, I.M., Gaziano, J.M., Gordon, D., Ridker, P.M., Manson, J.E., … Buring, J.E. (2005). Low-dose aspirin in the primary prevention of cancer: The women’s health study: A randomized controlled trial. Journal of the American Medical Association, 294(1), 4755. PubMed ID: 15998890 doi:10.1001/jama.294.1.47

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Desquilbet, L., & Mariotti, F. (2010). Dose-response analyses using restricted cubic spline functions in public health research. Statistics in Medicine, 29(9), 10371057. doi:10.1002/sim.3841

    • Search Google Scholar
    • Export Citation
  • Diaz, K.M., Howard, V.J., Hutto, B., Colabianchi, N., Vena, J.E., Safford, M.M., … Hooker, S.P. (2017). Patterns of sedentary behavior and mortality in U.S. middle-aged and older adults: A national cohort study. Annals of Internal Medicine, 167(7), 465475. PubMed ID: 28892811 doi:10.7326/M17-0212

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Doherty, A., Jackson, D., Hammerla, N., Plotz, T., Olivier, P., Granat, M.H., … Wareham, N.J. (2017). Large scale population assessment of physical activity using wrist worn accelerometers: The UK Biobank study. PLoS ONE, 12(2), e0169649. PubMed ID: 28146576 doi:10.1371/journal.pone.0169649

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dohrn, I.M., Sjostrom, M., Kwak, L., Oja, P., & Hagstromer, M. (2017). Accelerometer-measured sedentary time and physical activity-A 15 year follow-up of mortality in a Swedish population-based cohort. Journal of Science and Medicine in Sport, pii, S14402440(17)31748-6. doi:10.1016/j.jsams.2017.10.035

    • Search Google Scholar
    • Export Citation
  • Ensrud, K.E., Blackwell, T.L., Cauley, J.A., Dam, T.T., Cawthon, P.M., Schousboe, J.T., … Osteoporotic Fractures in Men Study Group. (2014). Objective measures of activity level and mortality in older men. Journal of the American Geriatrics Society, 62(11), 20792087. PubMed ID: 25367147 doi:10.1111/jgs.13101

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Evenson, K., Buchner, D., & Morland, K. (2012). Objective measurement of physical activity and sedentary behavior among US adults aged 60 years or older. Preventing Chronic Disease, 9, E26. PubMed ID: 22172193

    • Search Google Scholar
    • Export Citation
  • 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(2), 135143. doi:10.1016/j.amepre.2016.10.033

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Evenson, K.R., Wen, F., & Herring, A.H. (2016). Associations of accelerometry-assessed and self-reported physical activity and sedentary behavior with all-cause and cardiovascular mortality among US adults. American Journal of Epidemiology, 184(9), 621632. PubMed ID: 27760774 doi:10.1093/aje/kww070

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Evenson, K.R., Wen, F., Herring, A.H., Di, C., LaMonte, M.J., Tinker, L.F., … Buchner, D.M. (2015). Calibrating physical activity intensity for hip-worn accelerometry in women age 60 to 91 years: The women’s health initiative OPACH calibration study. Preventive Medicine Reports, 2, 750756. doi:10.1016/j.pmedr.2015.08.021

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fishman, E.I., Steeves, J.A., Zipunnikov, V., Koster, A., Berrigan, D., Harris, T.A., & Murphy, R. (2016). Association between objectively measured physical activity and mortality in NHANES. Medicine & Science in Sports & Exercise, 48(7), 13031311. PubMed ID: 26848889 doi:10.1249/MSS.0000000000000885

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Freedson, P.S., Lyden, K., Kozey-Keadle, S., & Staudenmayer, J. (2011). Evaluation of artificial neural network algorithms for predicting METs and activity type from accelerometer data: Validation on an independent sample. Journal of Applied Physiology (1985), 111(6), 18041812. doi:10.1152/japplphysiol.00309.2011

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Howard, V.J., Rhodes, J.D., Mosher, A., Hutto, B., Stewart, M.S., Colabianchi, N., … Hooker, S.P. (2015). Obtaining accelerometer data in a national cohort of black and white adults. Medicine & Science in Sports & Exercise, 47(7), 15311537. PubMed ID: 25333247 doi:10.1249/MSS.0000000000000549

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jefferis, B.J., Parsons, T.J., Sartini, C., Ash, S., Lennon, L.T., Papacosta, O., … Whincup, P.H. (2018). Objectively measured physical activity, sedentary behaviour and all-cause mortality in older men: Does volume of activity matter more than pattern of accumulation? British Journal of Sports Medicine. doi:10.1136/bjsports-2017-098733

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • Jefferis, B.J., Sartini, C., Shiroma, E., Whincup, P.H., Wannamethee, S.G., & Lee, I.M. (2015). Duration and breaks in sedentary behaviour: Accelerometer data from 1566 community-dwelling older men (British regional heart study). British Journal of Sports Medicine, 49(24), 15911594. PubMed ID: 25232029 doi:10.1136/bjsports-2014-093514

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Keadle, S.K., Shiroma, E.J., Freedson, P.S., & Lee, I.M. (2014). Impact of accelerometer data processing decisions on the sample size, wear time and physical activity level of a large cohort study. BMC Public Health, 14, 1210. PubMed ID: 25421941 doi:10.1186/1471-2458-14-1210

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koster, A., Caserotti, P., Patel, K.V., Matthews, C.E., Berrigan, D., Van Domelen, D.R., … Harris, T.B. (2012). Association of sedentary time with mortality independent of moderate to vigorous physical activity. PLoS ONE, 7(6), e37696. PubMed ID: 22719846 doi:10.1371/journal.pone.0037696

    • Crossref
    • Search Google Scholar
    • Export Citation
  • LaMonte, M.J., Buchner, D.M., Rillamas-Sun, E., Di, C., Evenson, K.R., Bellettiere, J., … LaCroix, A.Z. (2018). Accelerometer-measured physical activity and mortality in women aged 63 to 99. Journal of the American Geriatrics Society, 66, 886894. doi:10.1111/jgs.15201

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • Lee, I.M., Cook, N.R., Gaziano, J.M., Gordon, D., Ridker, P.M., Manson, J.E., … Buring, J.E. (2005). Vitamin E in the primary prevention of cardiovascular disease and cancer: The women’s health study: A randomized controlled trial. Journal of the American Medical Association, 294(1), 5665. PubMed ID: 15998891 doi:10.1001/jama.294.1.56

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, I.M., Sesso, H.D., Oguma, Y., & Paffenbarger, R.S., Jr. (2004). The “weekend warrior” and risk of mortality. American Journal of Epidemiology, 160(7), 636641. PubMed ID: 15383407 doi:10.1093/aje/kwh274

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, I.M., & Shiroma, E.J. (2014). Using accelerometers to measure physical activity in large-scale epidemiological studies: Issues and challenges. British Journal of Sports Medicine, 48(3), 197201. PubMed ID: 24297837 doi:10.1136/bjsports-2013-093154

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, I.M., Shiroma, E.J., Evenson, K.R., Kamada, M., LaCroix, A.Z., & Buring, J.E. (2018). Accelerometer-measured physical activity and sedentary behavior in relation to all-cause mortality: The women’s health study. Circulation, 137(2), 203205. PubMed ID: 29109088 doi:10.1161/CIRCULATIONAHA.117.031300

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, I.M., Shiroma, E.J., Lobelo, F., Puska, P., Blair, S.N., Katzmarzyk, P.T., & Lancet Physical Activity Series Working Group. (2012). Effect of physical inactivity on major non-communicable diseases worldwide: An analysis of burden of disease and life expectancy. Lancet, 380(9838), 219229. PubMed ID: 22818936 doi:10.1016/S0140-6736(12)61031-9

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lollgen, H., Bockenhoff, A., & Knapp, G. (2009). Physical activity and all-cause mortality: An updated meta-analysis with different intensity categories. International Journal of Sports Science & Medicine, 30(3), 213224. doi:10.1055/s-0028-1128150

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Look Ahead Research Group, Wing, R.R., Bolin, P., Brancati, F.L., Bray, G.A., Clark, J.M., … Yanovski, S.Z. (2013). Cardiovascular effects of intensive lifestyle intervention in type 2 diabetes. The New England Journal of Medicine, 369(2), 145154. PubMed ID: 23796131 doi:10.1056/NEJMoa1212914

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Loprinzi, P.D., Loenneke, J.P., Ahmed, H.M., & Blaha, M.J. (2016). Joint effects of objectively-measured sedentary time and physical activity on all-cause mortality. Preventive Medicine, 90, 4751. PubMed ID: 27349647 doi:10.1016/j.ypmed.2016.06.026

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matthews, C.E., Keadle, S.K., Troiano, R.P., Kahle, L., Koster, A., Brychta, R., … Berrigan, D. (2016). Accelerometer-measured dose-response for physical activity, sedentary time, and mortality in US adults. The American Journal of Clinical Nutrition, 104(5), 14241432. PubMed ID: 27707702 doi:10.3945/ajcn.116.135129

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Migueles, J.H., Cadenas-Sanchez, C., Ekelund, U., Delisle Nystrom, C., Mora-Gonzalez, J., Lof, M., … 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), 18211845. PubMed ID: 28303543 doi:10.1007/s40279-017-0716-0

    • Crossref
    • Search Google Scholar
    • Export Citation
  • O’Donovan, G., Lee, I.M., Hamer, M., & Stamatakis, E. (2017). Association of “weekend warrior” and other leisure time physical activity patterns with risks for all-cause, cardiovascular disease, and cancer mortality. JAMA Internal Medicine, 177(3), 335342. doi:10.1001/jamainternmed.2016.8014

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pettee Gabriel, K., McClain, J.J., Lee, C.D., Swan, P.D., Alvar, B.A., Mitros, M.R., & Ainsworth, B.E. (2009). Evaluation of physical activity measures used in middle-aged women. Medicine & Science in Sports & Exercise, 41(7), 14031412. PubMed ID: 19516161 doi:10.1249/MSS.0b013e31819b2482

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Physical Activity Guidelines Advisory Committee. (2008). 2008 Physical activity guidelines advisory committee report. Washington, DC: Department of Health and Human Services.

    • Search Google Scholar
    • Export Citation
  • Physical Activity Guidelines Advisory Committee. (2018). 2018 Physical Activity Guidelines Advisory Committee Report. Retrieved from https://health.gov/paguidelines/second-edition/report.aspx

    • Search Google Scholar
    • Export Citation
  • Ridker, P.M., Cook, N.R., Lee, I.M., Gordon, D., Gaziano, J.M., Manson, J.E., … Buring, J.E. (2005). A randomized trial of low-dose aspirin in the primary prevention of cardiovascular disease in women. The New England Journal of Medicine, 352(13), 12931304. PubMed ID: 15753114 doi:10.1056/NEJMoa050613

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Santos-Lozano, A., Santin-Medeiros, F., Cardon, G., Torres-Luque, G., Bailon, R., Bergmeir, C., … Garatachea, N. (2013). Actigraph GT3X: Validation and determination of physical activity intensity cut points. International Journal of Sports Medicine, 34(11), 975982. doi:10.1055/s-0033-1337945

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sasaki, J.E., John, D., & Freedson, P.S. (2011). Validation and comparison of ActiGraph activity monitors. Journal of Science and Medicine in Sport, 14(5), 411416. doi:10.1016/j.jsams.2011.04.003

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schmid, D., Ricci, C., Baumeister, S.E., & Leitzmann, M.F. (2016). Replacing sedentary time with physical activity in relation to mortality. Medicine & Science in Sports & Exercise, 48(7), 13121319. PubMed ID: 26918559 doi:10.1249/MSS.0000000000000913

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schmid, D., Ricci, C., & Leitzmann, M.F. (2015). Associations of objectively assessed physical activity and sedentary time with all-cause mortality in US adults: The NHANES study. PLoS ONE, 10(3), e0119591. PubMed ID: 25768112 doi:10.1371/journal.pone.0119591

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shiroma, E.J., Kamada, M., Smith, C., Harris, T.B., & Lee, I.M. (2015). Visual inspection for determining days when accelerometer is worn: Is this valid? Medicine & Science in Sports & Exercise, 47(12), 25582562. PubMed ID: 26110697 doi:10.1249/MSS.0000000000000725

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shiroma, E.J., Sesso, H.D., Moorthy, M.V., Buring, J.E., & Lee, I.M. (2014). Do moderate-intensity and vigorous-intensity physical activities reduce mortality rates to the same extent? Journal of the American Heart Association, 3(5), e000802. PubMed ID: 25326527 doi:10.1161/JAHA.114.000802

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Staudenmayer, J., Pober, D., Crouter, S., Bassett, D., & Freedson, P. (2009). An artificial neural network to estimate physical activity energy expenditure and identify physical activity type from an accelerometer. Journal of Applied Physiology (1985), 107(4), 13001307. doi:10.1152/japplphysiol.00465.2009

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tremblay, M.S., Aubert, S., Barnes, J.D., Saunders, T.J., Carson, V., Latimer-Cheung, A.E., … SBRN Terminology Consensus Project Participants. (2017). Sedentary Behavior Research Network (SBRN) – terminology consensus project process and outcome. The International Journal of Behavioral Nutrition and Physical Activity, 14(1), 75. doi:10.1186/s12966-017-0525-8

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Troiano, R.P., McClain, J.J., Brychta, R.J., & Chen, K.Y. (2014). Evolution of accelerometer methods for physical activity research. British Journal of Sports Medicine, 48(13), 10191023. PubMed ID: 24782483 doi:10.1136/bjsports-2014-093546

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tudor-Locke, C., Camhi, S.M., & Troiano, R.P. (2012). A catalog of rules, variables, and definitions applied to accelerometer data in the National Health and Nutrition Examination Survey, 2003–2006. Preventing Chronic Disease, 9, E113. PubMed ID: 22698174

    • Search Google Scholar
    • Export Citation
  • U.S. Department of Health and Human Services. (2008). Physical activity guidelines. Retrieved from https://health.gov/paguidelines/

    • Export Citation
  • Wirth, K., Klenk, J., Brefka, S., Dallmeier, D., Faehling, K., Figuls, M.R., … SITLESS Consortium. (2016). Biomarkers associated with sedentary behaviour in older adults: A systematic review. Ageing Research Reviews. doi:10.1016/j.arr.2016.12.002

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Woodcock, J., Franco, O.H., Orsini, N., & Roberts, I. (2011). Non-vigorous physical activity and all-cause mortality: Systematic review and meta-analysis of cohort studies. International Journal of Epidemiology, 40(1), 121138. PubMed ID: 20630992 doi:10.1093/ije/dyq104

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 349 318 21
Full Text Views 8 7 0
PDF Downloads 9 8 0