Periodicities (repeating patterns) are observed in many human behaviors. Their strength may capture untapped patterns that incorporate sleep, sedentary, and active behaviors into a single metric indicative of better health. We present a framework to detect periodicities from longitudinal wrist-worn accelerometry data. GENEActiv accelerometer data were collected from 20 participants (17 men, 3 women, aged 35–65) continuously for 64.4±26.2 (range: 13.9 to 102.0) consecutive days. Cardiometabolic risk biomarkers and health-related quality of life metrics were assessed at baseline. Periodograms were constructed to determine patterns emergent from the accelerometer data. Periodicity strength was calculated using circular autocorrelations for time-lagged windows. The most notable periodicity was at 24 h, indicating a circadian rest-activity cycle; however, its strength varied significantly across participants. Periodicity strength was most consistently associated with LDL-cholesterol (r’s = 0.40–0.79, P’s < 0.05) and triglycerides (r’s = 0.68–0.86, P’s < 0.05) but also associated with hs-CRP and health-related quality of life, even after adjusting for demographics and self-rated physical activity and insomnia symptoms. Our framework demonstrates a new method for characterizing behavior patterns longitudinally which captures relationships between 24 h accelerometry data and health outcomes.
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- Behavioral Periodicity Detection From 24 h Wrist Accelerometry and Associations With Cardiometabolic Risk and Health-Related Quality of Life
- Buman, Matthew (Author)
- Hu, Feiyan (Author)
- Newman, Eamonn (Author)
- Smeaton, Alan F. (Author)
- Epstein, Dana R. (Author)
- College of Health Solutions (Contributor)
- Digital object identifier: 10.1155/2016/4856506
- Identifier TypeInternational standard serial numberIdentifier Value2314-6133
- Identifier TypeInternational standard serial numberIdentifier Value2314-6141
- The article is published at https://www.hindawi.com/journals/bmri/2016/4856506/, opens in a new window
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Buman, M. P., Hu, F., Newman, E., Smeaton, A. F., & Epstein, D. R. (2016). Behavioral Periodicity Detection from 24 h Wrist Accelerometry and Associations with Cardiometabolic Risk and Health-Related Quality of Life. BioMed Research International, 2016, 1-9. doi:10.1155/2016/4856506