The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Accelerometer-based measures in physical activity surveillance: current practices and issues
Abstract
Objective: Self-reports of physical activity (PA) have been the mainstay of measurement in most non-communicable disease (NCD) surveillance systems. To these, other measures are added to summate to a comprehensive PA surveillance system. Recently, some national NCD surveillance systems have started using accelerometers as a measure of PA. The purpose of this paper was specifically to appraise the suitability and role of accelerometers for population-level PA surveillance. Methods: A thorough literature search was conducted to examine aspects of the generalisability, reliability, validity, comprehensiveness and between-study comparability of accelerometer estimates, and to gauge the simplicity, cost-effectiveness, adaptability and sustainability of their use in NCD surveillance. Conclusions: Accelerometer data collected in PA surveillance systems may not provide estimates that are generalisable to the target population. Accelerometer-based estimates have adequate reliability for PA surveillance, but there are still several issues associated with their validity. Accelerometer-based prevalence estimates are largely dependent on the investigators’ choice of intensity cut-off points. Maintaining standardised accelerometer data collections in long-term PA surveillance systems is difficult, which may cause discontinuity in time-trend data. The use of accelerometers does not necessarily produce useful between-study and international comparisons due to lack of standardisation of data collection and processing methods. To conclude, it appears that accelerometers still have limitations regarding generalisability, validity, comprehensiveness, simplicity, affordability, adaptability, between-study comparability and sustainability. Therefore, given the current evidence, it seems that the widespread adoption of accelerometers specifically for large-scale PA surveillance systems may be premature.
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Lee, I.-M., Shiroma, E. J., Lobelo, F., Puska, P., Blair, S. N., & Katzmarzyk, P. T. (2012) · The Lancet · doi:10.1016/s0140-6736(12)61031-9 · Cited by 8,215
Physical Activity in the United States Measured by Accelerometer
TROIANO, R. P., BERRIGAN, D., DODD, K. W., MÂSSE, L. C., TILERT, T., & MCDOWELL, M. (2008) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e31815a51b3 · Cited by 7,638
Global physical activity levels: surveillance progress, pitfalls, and prospects
Hallal, P. C., Andersen, L. B., Bull, F. C., Guthold, R., Haskell, W., & Ekelund, U. (2012) · The Lancet · doi:10.1016/s0140-6736(12)60646-1 · Cited by 5,711
Translating Social Ecological Theory into Guidelines for Community Health Promotion
Stokols, D. (1996) · American Journal of Health Promotion · doi:10.4278/0890-1171-10.4.282 · Cited by 2,763
Amount of Time Spent in Sedentary Behaviors in the United States, 2003-2004
Matthews, C. E., Chen, K. Y., Freedson, P. S., Buchowski, M. S., Beech, B. M., Pate, R. R., & Troiano, R. P. (2008) · American Journal of Epidemiology · doi:10.1093/aje/kwm390 · Cited by 2,631
Validation of Accelerometer Wear and Nonwear Time Classification Algorithm
CHOI, L., LIU, Z., MATTHEWS, C. E., & BUCHOWSKI, M. S. (2011) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e3181ed61a3 · Cited by 1,804
Limits to the measurement of habitual physical activity by questionnaires
Shephard, R. J. (2003) · British Journal of Sports Medicine · doi:10.1136/bjsm.37.3.197 · Cited by 1,694
Suñé, P., Suñé, J. M., & Montoro, J. B. (2013) · PLoS ONE · doi:10.1371/journal.pone.0054583 · Cited by 1,687
The Effect of Social Desirability and Social Approval on Self-Reports of Physical Activity
Adams, S. A. (2005) · American Journal of Epidemiology · doi:10.1093/aje/kwi054 · Cited by 1,160
Internal construct validity of the Shirom-Melamed Burnout questionnaire (SMBQ)
Lundgren-Nilsson, Å., Jonsdottir, I. H., Pallant, J., & Ahlborg, G. (2012) · BMC Public Health · doi:10.1186/1471-2458-12-1 · Cited by 626
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O’Donovan, G., Lee, I.-M., Hamer, M., & Stamatakis, E. (2017) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2016.8014 · Cited by 462
Dowd, K. P., Szeklicki, R., Minetto, M. A., Murphy, M. H., Polito, A., Ghigo, E., van der Ploeg, H., Ekelund, U., Maciaszek, J., Stemplewski, R., et al. (2018) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-017-0636-2 · Cited by 385
Workplace interventions for reducing sitting at work
Shrestha, N., Kukkonen-Harjula, K. T., Verbeek, J. H., Ijaz, S., Hermans, V., & Bhaumik, S. (2016) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd010912.pub3 · Cited by 385
Sember, V., Meh, K., Sorić, M., Starc, G., Rocha, P., & Jurak, G. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17197161 · Cited by 266
Remote Physical Activity Monitoring in Neurological Disease: A Systematic Review.
Block, V. A. J., Pitsch, E., Tahir, P., Cree, B. A. C., Allen, D. D., & Gelfand, J. M. (2016) · PLOS ONE · doi:10.1371/journal.pone.0154335 · Cited by 198
Metadata
- Authors
- Pedišić, Ž., & Bauman, A.
- Venue
- British Journal of Sports Medicine
- Publisher
- BMJ
- Published
- 2014-11-04
- Volume
- 49
- Issue
- 4
- Pages
- 219-223
- ISSN
- 0306-3674 (ISSN-L)
- 1473-0480
- OpenAlex
- W2127105414
- Cited by
- 330
- References
- 21
- FWCI
- 15.74
- Type
- journal article
- Language
- en
- Open access
- closed
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