Use of wearable devices that monitor physical activity is projected to increase more than fivefold per half-decade1. We investigated how device-based physical activity energy expenditure (PAEE) and different intensity profiles were associated with all-cause mortality. We used a network harmonization approach to map dominant-wrist acceleration to PAEE in 96,476 UK Biobank participants (mean age 62 years, 56% female). We also calculated the fraction of PAEE accumulated from moderate-to-vigorous-intensity physical activity (MVPA). Over the median 3.1-year follow-up period (302,526 person-years), 732 deaths were recorded. Higher PAEE was associated with a lower hazard of all-cause mortality for a constant fraction of MVPA (for example, 21% (95% confidence interval 4–35%) lower hazard for 20 versus 15 kJ kg−1 d−1 PAEE with 10% from MVPA). Similarly, a higher MVPA fraction was associated with a lower hazard when PAEE remained constant (for example, 30% (8–47%) lower hazard when 20% versus 10% of a fixed 15 kJ kg−1 d−1 PAEE volume was from MVPA). Our results show that higher volumes of PAEE are associated with reduced mortality rates, and achieving the same volume through higher-intensity activity is associated with greater reductions than through lower-intensity activity. The linkage of device-measured activity to energy expenditure creates a framework for using wearables for personalized prevention.
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The UK Biobank data that support the findings of this study can be accessed by researchers on application (https://www.ukbiobank.ac.uk/register-apply/). Variables derived specifically for this study will be returned along with the code to the UK Biobank for future applicants to request.
Analysis code is available on request to the corresponding author.
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We are grateful to the participants of the UK Biobank study and those who collected and managed the data. This work was conducted under UK Biobank application number 20684. T.S., K.W., S.B., S.J.S., T.L., P.C.D., M.P., J.J. and N.W. are supported by the UK Medical Research Council (unit program numbers MC_UU_12015/1 and MC_UU_12015/3). P.C.D. is supported by a National Health and Medical Research Council of Australia research fellowship (no. 1142685). T.L. is supported by the Cambridge Trust and St Catharine’s College.
The authors declare no competing interests.
Peer review information Jennifer Sargent was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.
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Numbers and reasons for participant exclusions.
Change in covariates between baseline and visit 2 measurement for those in the main analysis sample that undertook both visits (n = 8,503).
Change in covariates between baseline and visit 3 measurement for those in the main analysis sample that undertook both visits (n = 15,140).
Descriptive statistics for the season of wear variable.
Scatter plot of physical activity energy expenditure versus fraction of physical activity energy expenditure from moderate-to-vigorous-intensity physical activity for the main analysis sample and the two excluded participants (n = 96,478).
Timeline of recruitment and data collection for participants in the main analyses of the present study.
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Strain, T., Wijndaele, K., Dempsey, P.C. et al. Wearable-device-measured physical activity and future health risk. Nat Med 26, 1385–1391 (2020). https://doi.org/10.1038/s41591-020-1012-3
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