Reproducibility of domain-specific physical activity over two seasons in children

Eivind Aadland, Lars Bo Andersen, Ulf Ekelund, Sigmund Alfred Anderssen, Geir Kåre Resaland, Eivind Aadland, Lars Bo Andersen, Ulf Ekelund, Sigmund Alfred Anderssen, Geir Kåre Resaland

Abstract

Background: Knowledge of the reproducibility of domain-specific accelerometer-determined physical activity (PA) estimates are a prerequisite to conduct high-quality epidemiological studies. The aim of this study was to determine the reproducibility of objectively measured PA level in children during school hours, afternoon hours, weekdays, weekend days, and total leisure time over two different seasons.

Methods: Six hundred seventy six children from the Active Smarter Kids study conducted in Sogn og Fjordane, Norway, were monitored for 7 days by accelerometry (ActiGraph GT3X+) during January-February and April-May 2015. Reproducibility was estimated week-by-week using intra-class correlation (ICC) and Bland-Altman plots with 95% limits of agreement (LoA).

Results: When controlling for season, reliability (ICC) was 0.51-0.66 for a 7-day week, 0.55-0.64 for weekdays, 0.11-0.43 for weekend days, 0.57-0.63 for school hours, 0.42-0.53 for afternoon hours, and 0.42-0.61 for total leisure time. LoA across models approximated a factor of 1.3-2.5 standard deviations of the sample PA levels. 3-6 weeks of monitoring were required to achieve a reliability of 0.80 across all domains but weekend days, which required 5-32 weeks.

Conclusion: Reproducibility of PA during leisure time and weekend days were lower than for school hours and weekdays, and estimates were lower when analyzed using a week-by-week approach over different seasons compared to previous studies relying on a single short monitoring period. To avoid type 2-errors, researchers should consider increasing the monitoring period beyond a single 7-day period in future studies.

Trial registration: ClinicalTrials.gov, NCT021324947 . Registered on 7 April 2014.

Keywords: Accelerometry; Agreement; Intra-class correlation; Measurement; Reliability; Test-retest.

Conflict of interest statement

Ethics approval and consent to participate

The South-East Regional Committee for Medical Research Ethics approved the study protocol (reference number 2013/1893). We obtained written informed consent from each child’s parents or legal guardian and from the responsible school authorities prior to all testing.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

    1. Cain KL, Sallis JF, Conway TL, Van Dyck D, Calhoon L. Using accelerometers in youth physical activity studies: a review of methods. J Phys Act Health. 2013;10(3):437–450. doi: 10.1123/jpah.10.3.437.
    1. Atkin AJ, Sharp SJ, Harrison F, Brage S, Van Sluijs EMF. Seasonal variation in children's physical activity and sedentary time. Med Sci Sports Exerc. 2016;48(3):449–456. doi: 10.1249/MSS.0000000000000786.
    1. Gracia-Marco L, Ortega FB, Ruiz JR, Williams CA, Hagstromer M, Manios Y, et al. Seasonal variation in physical activity and sedentary time in different European regions. The HELENA study. J Sports Sci. 2013;31(16):1831–1840. doi: 10.1080/02640414.2013.803595.
    1. Ridgers ND, Salmon J, Timperio A. Too hot to move? Objectively assessed seasonal changes in Australian children's physical activity. Int J Behav Nutr Phys Act. 2015;12:77. 10.1186/s12966-015-0245-x.
    1. Hutcheon JA, Chiolero A, Hanley JA. Random measurement error and regression dilution bias. Br Med J. 2010;340:2289. 10.1136/bmj.c2289.
    1. Trost SG, McIver KL, Pate RR. Conducting accelerometer-based activity assessments in field-based research. Med Sci Sports Exerc. 2005;37(11):S531–SS43. doi: 10.1249/01.mss.0000185657.86065.98.
    1. Pedersen ESL, Danquah IH, Petersen CB, Tolstrup JS. Intra-individual variability in day-to-day and month-to-month measurements of physical activity and sedentary behaviour at work and in leisure-time among Danish adults. BMC Public Health. 2016;16:1222. 10.1186/s12889-016-3890-3.
    1. Jerome GJ, Young DR, Laferriere D, Chen CH, Vollmer WM. Reliability of RT3 accelerometers among overweight and obese adults. Med Sci Sports Exerc. 2009;41(1):110–114. doi: 10.1249/MSS.0b013e3181846cd8.
    1. Coleman KJ, Epstein LH. Application of generalizability theory to measurement of activity in males who are not regularly active: a preliminary report. Res Q Exerc Sport. 1998;69(1):58–63. doi: 10.1080/02701367.1998.10607667.
    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. 10.1186/1479-5868-8-62.
    1. Basterfield L, Adamson AJ, Pearce MS, Reilly JJ. Stability of habitual physical activity and sedentary behavior monitoring by accelerometry in 6-to 8-year-olds. J Phys Act Health. 2011;8(4):543–547. doi: 10.1123/jpah.8.4.543.
    1. Addy CL, Trilk JL, Dowda M, Byun W, Pate RR. Assessing preschool children's physical activity: how many days of accelerometry measurement. Pediatr Exerc Sci. 2014;26(1):103–109. doi: 10.1123/pes.2013-0021.
    1. Hinkley T, O'Connell E, Okely AD, Crawford D, Hesketh K, Salmon J. Assessing volume of accelerometry data for reliability in preschool children. Med Sci Sports Exerc. 2012;44(12):2436–2441. doi: 10.1249/MSS.0b013e3182661478.
    1. Hislop J, Law J, Rush R, Grainger A, Bulley C, Reilly JJ, et al. An investigation into the minimum accelerometry wear time for reliable estimates of habitual physical activity and definition of a standard measurement day in pre-school children. Physiol Meas. 2014;35(11):2213–2228. doi: 10.1088/0967-3334/35/11/2213.
    1. Penpraze V, Reilly JJ, MacLean CM, Montgomery C, Kelly LA, Paton JY, et al. Monitoring of physical activity in young children: how much is enough? Pediatr Exerc Sci. 2006;18(4):483–491. doi: 10.1123/pes.18.4.483.
    1. Rich C, Geraci M, Griffiths L, Sera F, Dezateux C, Cortina-Borja M. Quality control methods in accelerometer data processing: defining minimum wear time. PLoS One. 2013;8(6):67206. 10.1371/journal.pone.0067206.
    1. Murray DM, Catellier DJ, Hannan PJ, Treuth MS, Stevens J, Schmitz KH, et al. School-level intraclass correlation for physical activity in adolescent girls. Med Sci Sports Exerc. 2004;36(5):876–882. doi: 10.1249/01.MSS.0000126806.72453.1C.
    1. Treuth MS, Sherwood NE, Butte NF, McClanahan B, Obarzanek E, Zhou A, et al. Validity and reliability of activity measures in African-American girls for GEMS. Med Sci Sports Exerc. 2003;35(3):532–539. doi: 10.1249/01.MSS.0000053702.03884.3F.
    1. Trost SG, Pate RR, Freedson PS, Sallis JF, Taylor WC. Using objective physical activity measures with youth: how many days of monitoring are needed? Med Sci Sports Exerc. 2000;32(2):426–431. doi: 10.1097/00005768-200002000-00025.
    1. Chinapaw MJM, de Niet M, Verloigne M, De Bourdeaudhuij I, Brug J, Altenburg TM. From sedentary time to sedentary patterns: accelerometer data reduction decisions in youth. PLoS One. 2014;9(11):111205. 10.1371/journal.pone.0111205.
    1. Kang M, Bjornson K, Barreira TV, Ragan BG, Song K. The minimum number of days required to establish reliable physical activity estimates in children aged 2-15 years. Physiol Meas. 2014;35(11):2229–2237. doi: 10.1088/0967-3334/35/11/2229.
    1. Ojiambo R, Cuthill R, Budd H, Konstabel K, Casajus JA, Gonzalez-Aguero A, et al. Impact of methodological decisions on accelerometer outcome variables in young children. Int J Obes. 2011;35:S98–S103. doi: 10.1038/ijo.2011.40.
    1. Pate RR, Brown WH, Pfeiffer KA, Howie EK, Saunders RP, Addy CL, et al. An intervention to increase physical activity in children a randomized controlled trial with 4-year-olds in preschools. Am J Prev Med. 2016;51(1):12–22. doi: 10.1016/j.amepre.2015.12.003.
    1. Jones RA, Okely AD, Hinkley T, Batterham M, Burke C. Promoting gross motor skills and physical activity in childcare: a translational randomized controlled trial. J Sci Med Sport. 2016;19(9):744–749. doi: 10.1016/j.jsams.2015.10.006.
    1. Kriemler S, Zahner L, Schindler C, Meyer U, Hartmann T, Hebestreit H, et al. Effect of school based physical activity programme (KISS) on fitness and adiposity in primary schoolchildren: cluster randomised controlled trial. BMJ. 2010;340:c785. doi: 10.1136/bmj.c785.
    1. Resaland GK, Aadland E, Moe VF, Aadland KN, Skrede T, Stavnsbo M, et al. Effects of physical activity on schoolchildren's academic performance: the active smarter kids (ASK) cluster-randomized controlled trial. Prev Med. 2016;91:322–328. doi: 10.1016/j.ypmed.2016.09.005.
    1. Gomersall SR, Rowlands AV, English C, Maher C, Olds TS. The activitystat hypothesis the concept, the evidence and the methodologies. Sports Med. 2013;43(2):135–149. doi: 10.1007/s40279-012-0008-7.
    1. Van Cauwenberghe E, Jones RA, Hinkley T, Crawford D, Okely AD. Patterns of physical activity and sedentary behaviour in preschool children. Int J Behav Nutr Phys Act. 2012;9:138. 10.1186/1479-5868-9-138.
    1. O'Neill JR, Pfeiffer KA, Dowda M, Pate RR. In-school and out-of-school physical activity in preschool children. J Phys Act Health. 2016;13(6):606–610. doi: 10.1123/jpah.2015-0245.
    1. Nilsson A, Anderssen SA, Andersen LB, Froberg K, Riddoch C, Sardinha LB, et al. Between- and within-day variability in physical activity and inactivity in 9-and 15-year-old European children. Scand J Med Sci Sports. 2009;19(1):10–18. doi: 10.1111/j.1600-0838.2007.00762.x.
    1. De Meester F, Van Dyck D, De Bourdeaudhuij I, Deforche B, Cardon G. Changes in physical activity during the transition from primary to secondary school in Belgian children: what is the role of the school environment? BMC Public Health. 2014;14:261. 10.1186/1471-2458-14-261.
    1. Baranowski T, Masse LC, Ragan B, Welk G. How many days was that? We're still not sure, but we're asking the question better. Med Sci Sports Exerc. 2008;40(7):S544–S5S9. doi: 10.1249/MSS.0b013e31817c6651.
    1. Matthews CE, Hagstromer M, Pober DM, Bowles HR. Best practices for using physical activity monitors in population-based research. Med Sci Sports Exerc. 2012;44:S68–S76. doi: 10.1249/MSS.0b013e3182399e5b.
    1. Wickel EE, Welk GJ. Applying generalizability theory to estimate habitual activity levels. Med Sci Sports Exerc. 2010;42(8):1528–1534. doi: 10.1249/MSS.0b013e3181d107c4.
    1. Levin S, Jacobs DR, Ainsworth BE, Richardson MT, Leon AS. Intra-individual variation and estimates of usual physical activity. Ann Epidemiol. 1999;9(8):481–488. doi: 10.1016/S1047-2797(99)00022-8.
    1. Mattocks C, Leary S, Ness A, Deere K, Saunders J, Kirkby J, et al. Intraindividual variation of objectively measured physical activity in children. Med Sci Sports Exerc. 2007;39(4):622–629. doi: 10.1249/mss.0b013e318030631b.
    1. Aadland E, Johannessen K. Agreement of objectively measured physical activity and sedentary time in preschool children. Preventive Med Rep. 2015;2:635–639. doi: 10.1016/j.pmedr.2015.07.009.
    1. Aadland E, Ylvisåker E. Reliability of objectively measured sedentary time and physical activity in adults. PLoS One. 2015;10(7):1–13. doi: 10.1371/journal.pone.0133296.
    1. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;1(8476):307–310. doi: 10.1016/S0140-6736(86)90837-8.
    1. Hopkins WG. Measures of reliability in sports medicine and science. Sports Med. 2000;30(1):1–15. doi: 10.2165/00007256-200030010-00001.
    1. Weir JP. Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. J Strength Cond Res. 2005;19(1):231–240.
    1. Resaland GK, Moe VF, Aadland E, Steene-Johannessen J, Glosvik Ø, Andersen JR, et al. Active smarter kids (ASK): rationale and design of a cluster-randomized controlled trial investigating the effects of daily physical activity on children's academic performance and risk factors for non-communicable diseases. BMC Public Health. 2015;15:709. doi: 10.1186/s12889-015-2049-y.
    1. John D, Freedson P. ActiGraph and Actical physical activity monitors: a peek under the hood. Med Sci Sports Exerc. 2012;44(1 Suppl 1):S86–SS9. doi: 10.1249/MSS.0b013e3182399f5e.
    1. Esliger DW, Copeland JL, Barnes JD, Tremblay MS. Standardizing and optimizing the use of accelerometer data for free-living physical activity monitoring. J Phys Act Health. 2005;2(3):366. doi: 10.1123/jpah.2.3.366.
    1. Evenson KR, Catellier DJ, Gill K, Ondrak KS, McMurray RG. Calibration of two objective measures of physical activity for children. J Sports Sci. 2008;26(14):1557–1565. doi: 10.1080/02640410802334196.
    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(7):1360–1368. doi: 10.1249/MSS.0b013e318206476e.
    1. McGraw KO, Wong SP. Forming inferences about some intraclass correlation coefficients. Psychol Methods. 1996;1(1):30–46. doi: 10.1037/1082-989X.1.1.30.
    1. Tarp J, Andersen LB. Ostergaard L. quantification of underestimation of physical activity during cycling to school when using accelerometry. J Phys Act Health. 2015;12(5):701–707. doi: 10.1123/jpah.2013-0212.

Source: PubMed

Sponsors en medewerkers

Medische omstandigheden

Geneesmiddelinterventies

3
Abonneren