The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
Methods for objective measure, quantification and analysis of sedentary behaviour and inactivity
Abstract
The purpose of this study was to develop and test a generic technique to robustly quantify the pattern of sedentary behaviour from objective records. The technique was applied to four groups of subjects: a healthy group with an active occupation (N=54), a healthy group with a sedentary occupation (N=53), a group of subjects with chronic low back pain (N=5) and a group of subjects with chronic fatigue syndrome (N=14). This study presents the first evidence that bouts of sedentary activity are power law distributed. Results showed that there was no significant difference in total sedentary time between the groups, however, the patterns of accumulation of sedentary time were significantly different for the groups. Sedentary groups accumulated their total sedentary time from a small number of longer sedentary bouts. Active groups tended to break their sedentary time into a greater number of shorter bouts. This suggests that the power law exponent alpha and the GINI index G, used to describe the pattern of accumulation of sedentary time, could be used to evaluate and quantify sedentary behaviour.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The accelerometer data were classified every minute of the day as MVPA, SB or LIPA depending on a threshold. This method is less accurate than postural allocation at distinguishing between SB and LIPA [57], therefore it is possible that these two components of the composition might not be entirely accurate and that different thresholds might lead to different results.”
Citations
Cites
Compendium of physical activities: an update of activity codes and MET intensities
AINSWORTH, B. E., HASKELL, W. L., WHITT, M. C., IRWIN, M. L., SWARTZ, A. M., STRATH, S. J., O???BRIEN, W. L., BASSETT, D. R., SCHMITZ, K. H., EMPLAINCOURT, P. O., et al. (2000) · Medicine & Science in Sports & Exercise · doi:10.1097/00005768-200009001-00009 · Cited by 8,497
Newman (2005) · doi:10.1080/00107510500052444 · Cited by 5,749
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
Fractal dynamics in physiology: Alterations with disease and aging
Goldberger, A. L., Amaral, L. A. N., Hausdorff, J. M., Ivanov, P. C., Peng, C., & Stanley, E. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.012579499 · Cited by 2,220
Hu, F. B., Li, T. Y., Colditz, G. A., Willett, W. C., & Manson, J. E. (2003) · JAMA · doi:10.1001/jama.289.14.1785 · Cited by 1,892
Hamilton, M. T., Hamilton, D. G., & Zderic, T. W. (2007) · Diabetes · doi:10.2337/db07-0882 · Cited by 1,655
Healy, G. N., Dunstan, D. W., Salmon, J., Cerin, E., Shaw, J. E., Zimmet, P. Z., & Owen, N. (2008) · Diabetes Care · doi:10.2337/dc07-2046 · Cited by 1,465
The Estimation of the Lorenz Curve and Gini Index
Gastwirth, J. L. (1972) · The Review of Economics and Statistics · doi:10.2307/1937992 · Cited by 1,153
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
Mathie, M. J., Coster, A. C. F., Lovell, N. H., & Celler, B. G. (2004) · Physiological Measurement · doi:10.1088/0967-3334/25/2/r01 · Cited by 828
Flagged first, then by citations
Research works printed but not linked: 2
- Clauset A, Shalizi C, Newman M. Power-law distribution in empirical data. SIAM Review; in press: preprint at arXiv:0706.1062v1. · arXiv
- Tigbe, 2008, Sedentary behaviour as a determinant of coronary heart disease risk, 16th European Congress on Obesity, Int J Obes, 32, S213
Cited by
Sorted by citations
Items 101–101 of 101
Longitudinal Changes in Children’s Accelerometer-derived Activity Pattern Metrics
DUNTON, G. F., YANG, C.-H., ZINK, J., DZUBUR, E., & BELCHER, B. R. (2020) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0000000000002247 · Cited by 25
Metadata
- Authors
- Chastin, S. F. M., & Granat, M. H.
- Affiliations
- Glasgow Caledonian University (GB)
- Corresponding author
- Chastin, S.F.M.
- Venue
- Gait & Posture
- Publisher
- Elsevier BV
- Published
- 2010-01
- Volume
- 31
- Issue
- 1
- Pages
- 82-86
- ISSN
- 0966-6362 (ISSN-L)
- OpenAlex
- W2031292431
- Cited by
- 323
- References
- 33
- Citations by year
- 2026: 15 · 2025: 11 · 2024: 22 · 2023: 17 · 2022: 22 · 2021: 20 · 2020: 28 · 2019: 20 · 2018: 26 · 2017: 22 · 2016: 30 · 2015: 23 · 2014: 19 · 2013: 18 · 2012: 14
- FWCI
- 6.41
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Gait & Posture (publishedVersion)
- PubMed (publishedVersion)
- ResearchOnline (Glasgow Caledonian University) (submittedVersion)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Social Sciences › Human Factors and Ergonomics › Ergonomics and Musculoskeletal Disorders
- Keywords
- sedentary behavior, physical inactivity, sedentary bouts, power-law distribution, Gini coefficient, chronic low back pain, chronic fatigue syndrome
- MeSH terms
- Adult, Analysis of Variance, Cross-Sectional Studies, Female, Humans, Male, Middle Aged, Monitoring, Physiologic, Occupations, Posture, Fatigue Syndrome, Chronic, Low Back Pain, Sedentary Behavior
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
