The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Validation and Calibration of an Accelerometer in Preschool Children
Abstract
Objective: Obesity rates in young children are increasing, and decreased physical activity is likely to be a major contributor to this trend. Studies of physical activity in young children are limited by the lack of valid and acceptable measures. The purpose of this study was to calibrate and validate the ActiGraph accelerometer for use with 3‐ to 5‐year‐old children. Research Methods and Procedures: Thirty preschool children wore an ActiGraph accelerometer (ActiGraph, Fort Walton Beach, FL) and a Cosmed portable metabolic system (Cosmed, Rome, Italy) during a period of rest and while performing three structured physical activities in a laboratory setting. Expired respiratory gases were collected, and oxygen consumption was measured on a breath‐by‐breath basis. Accelerometer data were collected at 15‐second intervals. For cross‐validation, the same children wore the same instruments while participating in unstructured indoor and outdoor activities for 20 minutes each at their preschool. Results: In calibrating the accelerometer, the correlation between V̇o2 (ml/kg per min) and counts was r = 0.82 across all activities. The only significant variable in the prediction equation was accelerometer counts (R2 = 0.90, standard error of the estimate = 4.70). In the cross‐validation, the intraclass correlation coefficient between measured and predicted V̇o2 was R = 0.57 and the Spearman correlation coefficient was R = 0.66 (p < 0.001). Cut‐off points for moderate‐ and vigorous‐intensity physical activity were identified at 420 counts/15 s (V̇o2 = 20 mL/kg per min) and 842 counts/15 s (V̇o2 = 30 mL/kg per min), respectively. When these cutpoints were applied to the cross‐validation data, percentage agreement, kappa, and modified kappa for moderate activity were 0.69, 0.36, and 0.38, respectively. For vigorous activity, the same measures were 0.81, 0.13, and 0.62. Discussion: Accelerometer counts were highly correlated with V̇o2 in young children. Accelerometers can be appropriately used as a measure of physical activity in this population.
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Cites
Aging, body composition, and lifestyle: the Fels Longitudinal Study
Guo, S. S., Zeller, C., Chumlea, W. C., & Siervogel, R. M. (1999) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/70.3.405 · Cited by 408
Haapanen, N., Miilunpalo, S., Pasanen, M., Oja, P., & Vuori, I. (1997) · International Journal of Obesity · doi:10.1038/sj.ijo.0800403 · Cited by 174
Cited by
Calibration of two objective measures of physical activity for children
Evenson, K. R., Catellier, D. J., Gill, K., Ondrak, K. S., & McMurray, R. G. (2008) · Journal of Sports Sciences · doi:10.1080/02640410802334196 · Cited by 2,677
Practical Guide to Measuring Physical Activity
Sylvia, L. G., Bernstein, E. E., Hubbard, J. L., Keating, L., & Anderson, E. J. (2014) · Journal of the Academy of Nutrition and Dietetics · doi:10.1016/j.jand.2013.09.018 · Cited by 637
Methods of Measurement in epidemiology: Sedentary Behaviour
Atkin, A. J., Gorely, T., Clemes, S. A., Yates, T., Edwardson, C., Brage, S., Salmon, J., Marshall, S. J., & Biddle, S. J. (2012) · International Journal of Epidemiology · doi:10.1093/ije/dys118 · Cited by 518
Tandon, P. S., Zhou, C., Sallis, J. F., Cain, K. L., Frank, L. D., & Saelens, B. E. (2012) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/1479-5868-9-88 · Cited by 461
Early Childhood Obesity Prevention Policies
(2011) · doi:10.17226/13124 · Cited by 452
Metadata
- Authors
- Pate, R. R., Almeida, M. J., McIver, K. L., Pfeiffer, K. A., & Dowda, M.
- Venue
- Obesity
- Publisher
- Wiley
- Published
- 2006-11
- Volume
- 14
- Issue
- 11
- Pages
- 2000-2006
- ISSN
- 1930-7381 (ISSN-L)
- 1930-739X
- OpenAlex
- W2094436282
- Cited by
- 723
- References
- 2
- FWCI
- 4.31
- Type
- journal article
- Language
- en
- Open access
- closed
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