Validity of objective methods for measuring sedentary behaviour in older adults: a systematic review

Kristiann C Heesch, Robert L Hill, Nicolas Aguilar-Farias, Jannique G Z van Uffelen, Toby Pavey, Kristiann C Heesch, Robert L Hill, Nicolas Aguilar-Farias, Jannique G Z van Uffelen, Toby Pavey

Abstract

Background: The evidence showing the ill health effects of prolonged sedentary behaviour (SB) is growing. Most studies of SB in older adults have relied on self-report measures of SB. However, SB is difficult for older adults to recall and objective measures that combine accelerometry with inclinometry are now available for more accurately assessing SB. The aim of this systematic review was to assess the validity and reliability of these accelerometers for the assessment of SB in older adults.

Methods: EMBASE, PubMed and EBSCOhost databases were searched for articles published up to December 13, 2017. Articles were eligible if they: a) described reliability, calibration or validation studies of SB measurement in healthy, community-dwelling individuals, b) were published in English, Portuguese or Spanish, and c) were published or in press as journal articles in peer-reviewed journals.

Results: The review identified 15 studies in 17 papers. Of the included studies, 11 assessed the ActiGraph accelerometer. Of these, three examined reliability only, seven (in eight papers) examined validity only and one (in two papers) examined both. The strongest evidence from the studies reviewed is from studies that assessed the validity of the ActiGraph. These studies indicate that analysis of the data using 60-s epochs and a vertical magnitude cut-point < 200 cpm or using 30- or 60-s epochs with a machine learning algorithm provides the most valid estimates of SB. Non-wear algorithms of 90+ consecutive zeros is also suggested for the ActiGraph.

Conclusions: Few studies have examined the reliability and validity of accelerometers for measuring SB in older adults. Studies to date suggest that the criteria researchers use for classifying an epoch as sedentary instead of as non-wear time (e.g., the non-wear algorithm used) may need to be different for older adults than for younger adults. The required number of hours and days of wear for valid estimates of SB in older adults was not clear from studies to date. More older-adult-specific validation studies of accelerometers are needed, to inform future guidelines on the appropriate criteria to use for analysis of data from different accelerometer brands.

Trial registration: PROSPERO ID# CRD42017080754 registered December 12, 2017.

Keywords: Accelerometer; Measurement; Older adults; Sedentary time; Sitting.

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The authors declare that they have no competing interests.

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Figures

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PRISM flow chart

References

    1. Tremblay MS, Aubert S, Barnes JD, Saunders TJ, Carson V, Latimer-Cheung AE, Chastin SFM, Altenburg TM, Chinapaw MJM. Sedentary behavior research network (SBRN) – terminology consensus project process and outcome. Int J Behav Nutr Phys Act. 2017;14:75. doi: 10.1186/s12966-017-0525-8.
    1. Hamer Mark, Coombs Ngaire, Stamatakis Emmanuel. Associations between objectively assessed and self-reported sedentary time with mental health in adults: an analysis of data from the Health Survey for England. BMJ Open. 2014;4(3):e004580. doi: 10.1136/bmjopen-2013-004580.
    1. Copeland JL, Ashe MC, Biddle SJH, Brown WJ, Buman MP, Chastin S, et al. Sedentary time in older men and women: a critical review of measurement, associations with health, and interventions. Br J Sports Med. 2017;51:1539. doi: 10.1136/bjsports-2016-097210.
    1. Biswas A, Oh PI, Faulkner GE, Bajaj RR, Silver MA, Mitchell MS, Alter DA. Sedentary time and its association with risk for disease incidence, mortality, and hospitalization in adults: a systematic review and meta-analysis. Ann Intern Med. 2015;162:123–132. doi: 10.7326/M14-1651.
    1. Biswas A, Alter DA. Sedentary time and risk for mortality. Ann Intern Med. 2015;162:875–876. doi: 10.7326/L15-5060-2.
    1. Grunseit AC, Chau JY, Rangul V, Turid Lingaas H, Bauman A. Patterns of sitting and mortality in the Nord-Trondelag Health Study (HUNT). Int J Behav Nutr Phys Act. 2017;14:8.
    1. Matthews CE, Moore SC, George SM, Sampson J, Bowles HR. Improving self-reports of active and sedentary behaviors in large epidemiologic studies. Exerc Sport Sci Rev. 2012;40:118–126.
    1. Pavey TG, Peeters GG, Brown WJ. Sitting-time and 9-year all-cause mortality in older women. Br J Sports Med. 2015;49:95–99. doi: 10.1136/bjsports-2012-091676.
    1. de Rezende LFM, Rey-López JP, Matsudo VKR, Luiz OC. Sedentary behavior and health outcomes among older adults: a systematic review. BMC Public Health. 2014;14:333. doi: 10.1186/1471-2458-14-333.
    1. Harrington DM, Barreira TV, Staiano AE, Katzmarzyk PT. The descriptive epidemiology of sitting among US adults, NHANES 2009/2010. J Sci Med Sport. 2014;17:371–375. doi: 10.1016/j.jsams.2013.07.017.
    1. Matthews CE, Chen KY, Freedson PS, Buchowski MS, Beech BM, Pate RR, et al. Amount of time spent in sedentary behaviors in the United States, 2003-2004. Am J Epidemiol. 2008;167:875. doi: 10.1093/aje/kwm390.
    1. Davis MG, Fox KR, Hillsdon M, Coulson JC, Sharp DJ, Stathi A, et al. Getting out and about in older adults: the nature of daily trips and their association with objectively assessed physical activity. Int J Behav Nutr Phys Act. 2011;8:116. doi: 10.1186/1479-5868-8-116.
    1. Copeland JL, Clarke J, Dogra S. Objectively measured and self-reported sedentary time in older Canadians. Prev Med Rep. 2015;2:90–95. doi: 10.1016/j.pmedr.2015.01.003.
    1. Dogra S, Ashe MC, Biddle SJH, Brown WJ, Buman MP, Chastin S, et al. Sedentary time in older men and women: an international consensus statement and research priorities. Br J Sports Med. 2017;51:1526. doi: 10.1136/bjsports-2016-097209.
    1. Harvey JA, Chastin SFM, Skelton DA. Prevalence of sedentary behavior in older adults: a systematic review. Int J Environ Res Pub Health. 2013;10:6645–6661. doi: 10.3390/ijerph10126645.
    1. Atkin AJ, Gorely T, Clemes SA, Yates T, Edwardson C, Brage S, et al. Methods of measurement in epidemiology: sedentary behaviour. Int J Epidemiol. 2012;41:1460–1471. doi: 10.1093/ije/dys118.
    1. Aguilar-Farias N, Brown WJ, Peeters GM. ActiGraph GT3X+ cut-points for identifying sedentary behaviour in older adults in free-living environments. J Sci Med Sport. 2014;17:293–299. doi: 10.1016/j.jsams.2013.07.002.
    1. Gorman E, Hanson HM, Yang PH, Khan KM, Liu-Ambrose T, Ashe MC. Accelerometry analysis of physical activity and sedentary behavior in older adults: a systematic review and data analysis. Eur Rev Aging Phys Act. 2014;11:35–49. doi: 10.1007/s11556-013-0132-x.
    1. Tudor-Locke C, Camhi SM, Troiano RP. A catalog of rules, variables, and definitions applied to accelerometer data in the National Health and Nutrition Examination Survey, 2003–2006. Prev Chronic Dis. 2012;9:E113.
    1. Moher D, Liberati A, Tetzlaff J, Altman DG, Group TP Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097. doi: 10.1371/journal.pmed.1000097.
    1. Sallis JF, Saelens BE. Assessment of physical activity by self-report: status, limitations, and future directions. Res Q Exerc Sport. 2000;71:S1–S4. doi: 10.1080/02701367.2000.11082780.
    1. Kelly P, Fitzsimons C, Baker G. Should we reframe how we think about physical activity and sedentary behaviour measurement? Validity and reliability reconsidered. Int J Behav Nutr Phys Act. 2016;13:32. doi: 10.1186/s12966-016-0351-4.
    1. Zweig MH, Campbell G. Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clin Chem. 1993;39:561–577.
    1. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;1:307–310. doi: 10.1016/S0140-6736(86)90837-8.
    1. Bourke AK, Ihlen EA, Van de Ven P, Nelson J, Helbostad JL. Video analysis validation of a real-time physical activity detection algorithm based on a single waist mounted tri-axial accelerometer sensor. Conf Proc IEEE Eng Med Biol Soc. 2016;2016:4881–4884.
    1. Chudyk AM, McAllister MM, Cheung HK, McKay HA, Ashe MC. Are we missing the sitting? Agreement between accelerometer non-wear time validation methods used with older adults’ data. Cogent Med. 2017;4:1313505. doi: 10.1080/2331205X.2017.1313505.
    1. Keadle SK, Shiroma EJ, Kamada M, Matthews CE, Harris TB, Lee IM. Reproducibility of accelerometer-assessed physical activity and sedentary time. Am J Prev Med. 2017;52:541–548. doi: 10.1016/j.amepre.2016.11.010.
    1. Keadle SK, Shiroma EJ, Freedson PS, Lee IM. Impact of accelerometer data processing decisions on the sample size, wear time and physical activity level of a large cohort study. BMC Public Health. 2014;14:1210. doi: 10.1186/1471-2458-14-1210.
    1. Koster A, Shiroma EJ, Caserotti P, Matthews CE, Chen KY, Glynn NW, et al. Comparison of sedentary estimates between activPAL and hip- and wrist-worn ActiGraph. Med Sci Sports Exerc. 2016;48:1514–1522. doi: 10.1249/MSS.0000000000000924.
    1. Rosenberg D, Godbole S, Ellis K, Di C, Lacroix A, Natarajan L, et al. Classifiers for accelerometer-measured behaviors in older women. Med Sci Sports Exerc. 2017;49:610–616. doi: 10.1249/MSS.0000000000001121.
    1. Sasaki JE, Hickey AM, Staudenmayer JW, John D, Kent JA, Freedson PS. Performance of activity classification algorithms in free-living older adults. Med Sci Sports Exerc. 2016;48:941–950. doi: 10.1249/MSS.0000000000000844.
    1. Wanner M, Martin BW, Meier F, Probst-Hensch N, Kriemler S. Effects of filter choice in GT3X accelerometer assessments of free-living activity. Med Sci Sports Exerc. 2013;45:170–177. doi: 10.1249/MSS.0b013e31826c2cf1.
    1. Evenson KR, Wen F, Herring AH, Di C, LaMonte MJ, Tinker LF, et al. Calibrating physical activity intensity for hip-worn accelerometry in women age 60 to 91 years: the Women's Health Initiative OPACH calibration study. Prev Med Rep. 2015;2:750–756. doi: 10.1016/j.pmedr.2015.08.021.
    1. Bai J, Di C, Xiao L, Evenson KR, LaCroix AZ, Crainiceanu CM, et al. An activity index for raw accelerometry data and its comparison with other activity metrics. PLoS One. 2016;11:e0160644. doi: 10.1371/journal.pone.0160644.
    1. Hart TL, Swartz AM, Cashin SE, Strath SJ. How many days of monitoring predict physical activity and sedentary behaviour in older adults. Int J Behav Nutr Phys Act. 2011;8:62. doi: 10.1186/1479-5868-8-62.
    1. Kocherginsky M, Huisingh-Scheetz M, Dale W, Lauderdale DS, Waite L. Measuring physical activity with hip accelerometry among U.S. older adults: How many days are enough? PLoS One. 2017;12:e0170082. doi: 10.1371/journal.pone.0170082.
    1. Hutto B, Howard VJ, Blair SN, Colabianchi N, Vena JE, Rhodes D, et al. Identifying accelerometer nonwear and wear time in older adults. Int J Behav Nutr Phys Act. 2013;10:120. doi: 10.1186/1479-5868-10-120.
    1. Klenk J, Buchele G, Lindemann U, Kaufmann S, Peter R, Laszlo R, et al. Concurrent validity of activPAL and activPAL3 accelerometers in older adults. J Aging Phys Act. 2016;24:444–450. doi: 10.1123/japa.2015-0178.
    1. Wullems JA, Verschueren SMP, Degens H, Morse CI, Onambélé GL. Performance of thigh-mounted triaxial accelerometer algorithms in objective quantification of sedentary behaviour and physical activity in older adults. PLoS One. 2017;12:e0188215. doi: 10.1371/journal.pone.0188215.
    1. Landry GJ, Falck RS, Beets MW, Liu-Ambrose T. Measuring physical activity in older adults: calibrating cut-points for the MotionWatch 8. Front Aging Neurosci. 2015;7:165.
    1. Choi L, Ward SC, Schnelle JF, Buchowski MS. Assessment of wear/nonwear time classification algorithms for triaxial accelerometer. Med Sci Sports Exerc. 2012;44:2009–2016. doi: 10.1249/MSS.0b013e318258cb36.
    1. Sirard John R., Forsyth Ann, Oakes J. Michael, Schmitz Kathryn H. Accelerometer Test-Retest Reliability by Data Processing Algorithms: Results from the Twin Cities Walking Study. Journal of Physical Activity and Health. 2011;8(5):668–674. doi: 10.1123/jpah.8.5.668.
    1. Pavey TG, Gomersall SR, Clark BK, Brown WJ. The validity of the GENEActiv wrist-worn accelerometer for measuring adult sedentary time in free living. J Sci Med Sport. 2016;19:395–399. doi: 10.1016/j.jsams.2015.04.007.
    1. Freedson PS, John D. Comment on “estimating activity and sedentary behavior from an accelerometer on the hip and wrist”. Med Sci Sports Exerc. 2013;45:962. doi: 10.1249/MSS.0b013e31827f024d.
    1. Kozey-Keadle S, Libertine A, Lyden K, Staudenmayer J, Freedson PS. Validation of wearable monitors for assessing sedentary behavior. Med Sci Sports Exerc. 2011;43:1561–1567. doi: 10.1249/MSS.0b013e31820ce174.
    1. Clarke-Cornwell AM, Farragher TM, Cook PA, Granat MH. Empirically derived cut-points for sedentary behaviour: are we sitting differently? Physiol Meas. 2016;37:1669–1685. doi: 10.1088/0967-3334/37/10/1669.
    1. Peterson NE, Sirard JR, Kulbok PA, DeBoer MD, Erickson JM. Validation of accelerometer thresholds and inclinometry for measurement of sedentary behavior in young adult university students. Res Nurs Health. 2015;38:492–499. doi: 10.1002/nur.21694.
    1. Johannsen DL, DeLany JP, Frisard MI, Welsch MA, Rowley CK, Fang X, et al. Physical activity in aging: comparison among young, aged, and nonagenarian individuals. J Appl Physiol. 2008;105:495–501. doi: 10.1152/japplphysiol.90450.2008.
    1. Strath SJ, Pfeiffer KA, Whitt-Glover MC. Accelerometer use with children, older adults, and adults with functional limitations. Med Sci Sports Exerc. 2012;44:S77. doi: 10.1249/MSS.0b013e3182399eb1.
    1. Evenson KR, Terry JW., Jr Assessment of differing definitions of accelerometer nonwear time. Res Q Exerc Sport. 2009;80:355–362. doi: 10.1080/02701367.2009.10599570.
    1. Trost SG, Loprinzi PD, Moore R, Pfeiffer KA. Comparison of accelerometer cut points for predicting activity intensity in youth. Med Sci Sports Exerc. 2011;43:1360–1368. doi: 10.1249/MSS.0b013e318206476e.
    1. Freedson P, Bowles HR, Troiano R, Haskell W. Assessment of physical activity using wearable monitors: recommendations for monitor calibration and use in the field. Med Sci Sports Exerc. 2012;44:S1. doi: 10.1249/MSS.0b013e3182399b7e.
    1. Pavey TG, Gilson ND, Gomersall SR, Clark B, Trost SG. Field evaluation of a random forest activity classifier for wrist-worn accelerometer data. J Sci Med Sport. 2017;20:75–80. doi: 10.1016/j.jsams.2016.06.003.
    1. Lyden K, Keadle SK, Staudenmayer J, Freedson PS. A method to estimate free-living active and sedentary behavior from an accelerometer. Med Sci Sports Exerc. 2014;46:386–397. doi: 10.1249/MSS.0b013e3182a42a2d.
    1. Rowlands AV, Olds TS, Hillsdon M, Pulsford R, Hurst TL, Eston RG, et al. Assessing sedentary behavior with the GENEActiv: introducing the sedentary sphere. Med Sci Sports Exerc. 2014;46:1235–1247. doi: 10.1249/MSS.0000000000000224.
    1. Rowlands AV, Yates T, Olds TS, Davies M, Khunti K, Edwardson CL. Sedentary sphere: wrist-worn accelerometer-brand independent posture classification. Med Sci Sports Exerc. 2016;48:748–754. doi: 10.1249/MSS.0000000000000813.
    1. Lyden K, Kozey Keadle SL, Staudenmayer JW, Freedson PS. Validity of two wearable monitors to estimate breaks from sedentary time. Med Sci Sports Exerc. 2012;44:2243–2252. doi: 10.1249/MSS.0b013e318260c477.
    1. Lyden K, Keadle SK, Staudenmayer J, Freedson PS. The activPAL™ accurately classifies activity intensity categories in healthy adults. Med Sci Sports Exerc. 2017;49:1022–1028. doi: 10.1249/MSS.0000000000001177.
    1. Ryde GC, Gilson ND, Suppini A, Brown WJ. Validation of a novel, objective measure of occupational sitting. J Occup Health. 2012;54:383–386. doi: 10.1539/joh.12-0091-BR.
    1. Steeves JA, Bowles HR, McClain JJ, Dodd KW, Brychta RJ, Wang J, et al. Ability of thigh-worn ActiGraph and activPAL monitors to classify posture and motion. Med Sci Sports Exerc. 2015;47:952–959. doi: 10.1249/MSS.0000000000000497.
    1. Choi L, Liu Z, Matthews CE, Buchowski MS. Validation of accelerometer wear and nonwear time classification algorithm. Med Sci Sports Exerc. 2011;43:357–364. doi: 10.1249/MSS.0b013e3181ed61a3.
    1. Troiano RP, Berrigan D, Dodd KW, Masse LC, Tilert T, McDowell M. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc. 2008;40:181–188. doi: 10.1249/mss.0b013e31815a51b3.
    1. JOHN DINESH, FREEDSON PATTY. ActiGraph and Actical Physical Activity Monitors. Medicine & Science in Sports & Exercise. 2012;44:S86–S89. doi: 10.1249/MSS.0b013e3182399f5e.

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