Variability in physical activity patterns as measured by the SenseWear Armband: how many days are needed?
To examine sources of variance in objectively measured physical activity and to determine the number of monitoring days needed to quantify physical activity patterns reliably, 394 Flemish adults (41.1 ± 9.9 years) were monitored during 7 days, using the SenseWear Armband. Differences between weekdays, Saturday and Sunday were examined with repeated measures ANOVA’s. Variance components were estimated for subject, weekday and residual error using data from Mondays through Fridays and used to calculate the reliability of 1–5 monitoring weekdays. Saturday was more and Sunday less active than an average weekday. Inter-individual variability was the largest source of variance (54.4–67.9%) for physical activity level (PAL), energy expenditure, inactivity, light, moderate and total physical activity. Intra-individual variability accounted for 31.8–44.8% and weekday for 0.1–1.1% of total variance. Intra-individual variability was the largest source of variance for vigorous activity in both sexes and steps in women. At least, 3 monitoring weekdays were required to achieve a reliability of 0.80 for PAL, energy expenditure, inactivity, light, moderate and total physical activity. All 5 weekdays should be monitored to reach acceptable reliability for steps. Five weekdays resulted in a reliability of 0.58–0.60 for vigorous activity. Both Saturday and Sunday and at least 3 weekdays need to be monitored to obtain reliable measures of habitual physical activity.
KeywordsInter-individual variance Intra-individual variance Reliability Objective monitoring Assessment
- Haskell WL, Lee IM, Pate RR, Powell KE, Blair SN, Franklin BA, Macera CA, Heath GW, Thompson PD, Bauman A (2007) Physical activity and public health: updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc 39:1423–1434PubMedCrossRefGoogle Scholar
- Johnson M, Baranowski T (1996) Estimating and evaluating correlation structures in repeated measures designs using the GLM and MIXED procedures. In: SAS Users Group International Proceedings (SUGI 21)Google Scholar
- Matthews CE (2002) Use of self-reports instruments to assess physical activity. In: Welk GJ (ed) Physical activity assessments for health-related research. Human Kinetics, Champaign, pp 107–123Google Scholar
- St-Onge M, Mignault D, Allison DB, Rabasa-Lhoret R (2007) Evaluation of a portable device to measure daily energy expenditure in free-living adults. Am J Clin Nutr 85:42–749Google Scholar
- Wareham NJ, Rennie KL (1998) The assessment of physical activity in individuals and populations: why try to be more precise about how physical activity is assessed? Int J Obes Relat Metab Disord 22 Suppl 2:S30-S38Google Scholar
- Warren JM, Ekelund U, Besson H, Mezzani A, Geladas N, Vanhees L (2010) Assessment of physical activity—a review of methodologies with reference to epidemiological research: a report of the exercise physiology section of the European Association of Cardiovascular Prevention and Rehabilitation. Eur J Cardiovasc Prev Rehabil 17:127–139PubMedCrossRefGoogle Scholar