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Charlotte L. Edwardson, Melanie Davies, Kamlesh Khunti, Thomas Yates and Alex V. Rowlands

Purpose: To compare steps counts recorded by consumer activity trackers when worn on the non-dominant and dominant wrist against a waist-worn pedometer during free-living. Methods: 30 participants wore six consumer wrist-worn physical activity trackers and a pedometer. On day 1, three trackers were worn on the non-dominant wrist (ND) and three on the dominant (D) wrist. On day 2 trackers were worn on the opposite wrist. On both days, a pedometer (New-Lifestyles NL-800) was worn at the waist. Mean absolute percent error (MAPE) and the Bland-Altman method assessed tracker agreement with the pedometer. Repeated measures ANOVA examined whether MAPEs were significantly different between wrist trackers (i.e., brand comparison) and between wrist location (i.e., non-dominant vs. dominant). Results: MAPEs were higher for the D wrist trackers. Five out of six trackers on the D wrist over-counted, while four out of six trackers on the ND wrist under-counted. MAPE errors were significant (p ≤ .001) between trackers but not across wrist location (p > .05). Fitbit Flex_ND, Mi Band_ND and D, Garmin Vivofit3_D and Jawbone UP24_D had a mean bias of <500 steps. 95% limits of agreement were narrowest for Mi Band_ND. Conclusions: Tracker agreement with the waist-worn pedometer varied widely but trackers on the ND wrist had better agreement. The Mi Band was the most comparable to the pedometer.

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Paddy C. Dempsey, Chuck E. Matthews, S. Ghazaleh Dashti, Aiden R. Doherty, Audrey Bergouignan, Eline H. van Roekel, David W. Dunstan, Nicholas J. Wareham, Thomas E. Yates, Katrien Wijndaele and Brigid M. Lynch

Background: Recent updates to physical activity guidelines highlight the importance of reducing sedentary time. However, at present, only general recommendations are possible (ie, “Sit less, move more”). There remains a need to investigate the strength, temporality, specificity, and dose–response nature of sedentary behavior associations with chronic disease, along with potential underlying mechanisms. Methods: Stemming from a recent research workshop organized by the Sedentary Behavior Council themed “Sedentary behaviour mechanisms—biological and behavioural pathways linking sitting to adverse health outcomes,” this paper (1) discusses existing challenges and scientific discussions within this advancing area of science, (2) highlights and discusses emerging areas of interest, and (3) points to potential future directions. Results: A brief knowledge update is provided, reflecting upon current and evolving thinking/discussions, and the rapid accumulation of new evidence linking sedentary behavior to chronic disease. Research “action points” are made at the end of each section—spanning from measurement systems and analytic methods, genetic epidemiology, causal mediation, and experimental studies to biological and behavioral determinants and mechanisms. Conclusion: A better understanding of whether and how sedentary behavior is causally related to chronic disease will allow for more meaningful conclusions in the future and assist in refining clinical and public health policies/recommendations.