The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Physical Activity and Inactivity in an Adult Population Assessed by Accelerometry
Abstract
INTRODUCTION: Strong evidence suggests a link between physical inactivity and chronic disease prevalence in the adult population. To target the right groups for interventions in a population, accurate assessment of physical activity is important. The objective of this study was to assess the levels and pattern of physical activity and inactivity in an adult population sample using an objective method. METHODS: In total, 1114 adults (56% women, 45+/-15 yr), randomly recruited from the Swedish population across a year, used an accelerometer (Actigraph MTI) for seven consecutive days. Inactivity was defined as <100 counts per minute, and cutoff values for moderate and vigorous activity were 1952-5724 and >5724 counts per minute, respectively. Average intensity was measured as counts per minute. RESULTS: The adults were active in at least moderate-intensity activity for a median (intraquartile range) of 31 (18-47) min.d(-1). Fifty-two percent accumulated 30 min.d(-1) of at least moderate-intensity physical activity. Only 1% achieved those 30 min from three or more bouts of at least 10 min. Average intensity, moderate and vigorous physical activity was lower with higher age or body mass index (BMI). Men spent more time than women in moderate and vigorous physical activity, but there was no gender difference in average intensity. The variation in inactivity could not be explained by gender, age, or BMI. CONCLUSION: Objectively obtained estimates of physical activity yielded lower values and a different activity pattern compared with those obtained by commonly used self-reports. This highlights the need to better understand the nature and measurement issues of health-enhancing physical activity of adults.
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Calibration of the Computer Science and Applications, Inc. accelerometer
FREEDSON, P. S., MELANSON, E., & SIRARD, J. (1998) · Medicine & Science in Sports & Exercise · doi:10.1097/00005768-199805000-00021 · Cited by 3,825
Interindividual variation in posture allocation: possible role in human obesity
Levine, J. A., Lanningham-Foster, L. M., McCrady, S. K., Krizan, A. C., Olson, L. R., Kane, P. H., Jensen, M. D., & Clark, M. M. (2005) · Science · doi:10.1126/science.1106561 · Cited by 705
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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
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
Objectively Measured Sedentary Time, Physical Activity, and Metabolic Risk
Healy, G. N., Wijndaele, K., Dunstan, D. W., Shaw, J. E., Salmon, J., Zimmet, P. Z., & Owen, N. (2008) · Diabetes Care · doi:10.2337/dc07-1795 · Cited by 1,100
Progress in physical activity over the Olympic quadrennium
Sallis, J. F., Bull, F., Guthold, R., Heath, G. W., Inoue, S., Kelly, P., Oyeyemi, A. L., Perez, L. G., Richards, J., & Hallal, P. C. (2016) · The Lancet · doi:10.1016/s0140-6736(16)30581-5 · Cited by 935
Best Practices for Using Physical Activity Monitors in Population-Based Research
MATTHEWS, C. E., HAGSTRÖMER, M., POBER, D. M., & BOWLES, H. R. (2012) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e3182399e5b · Cited by 703
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Metadata
- Authors
- HAGSTRÖMER, M., OJA, P., & SJÖSTRÖM, M.
- Venue
- Medicine & Science in Sports & Exercise
- Published
- 2007-09
- Volume
- 39
- Issue
- 9
- Pages
- 1502-1508
- ISSN
- 0195-9131 (ISSN-L)
- OpenAlex
- W2076331784
- Cited by
- 397
- References
- 3
- FWCI
- 11.27
- Type
- journal article
- Language
- en
- Open access
- closed
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