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dc.contributor.authorMigueles, Jairo H
dc.contributor.authorCadenas Sánchez, Cristina
dc.contributor.authorHenriksson, Pontus
dc.contributor.authorAcosta Manzano, Francisco Miguel
dc.contributor.authorRodríguez Ayllon, María
dc.contributor.authorEsteban Cornejo, Irene
dc.contributor.authorPlaza Florido, Abel
dc.contributor.authorGil Cosano, José Juan 
dc.contributor.authorOrtega Porcel, Francisco Bartolomé
dc.identifier.citationMigueles, J. H., Cadenas-Sanchez, C., Rowlands, A. V., Henriksson, P., Shiroma, E. J., Acosta, F. M., ... & Ekelund, U. (2019). Comparability of accelerometer signal aggregation metrics across placements and dominant wrist cut points for the assessment of physical activity in adults. Scientific Reports, 9(1), 1-12.es_ES
dc.description.abstractLarge epidemiological studies that use accelerometers for physical behavior and sleep assessment differ in the location of the accelerometer attachment and the signal aggregation metric chosen. This study aimed to assess the comparability of acceleration metrics between commonly-used body-attachment locations for 24 hours, waking and sleeping hours, and to test comparability of PA cut points between dominant and non-dominant wrist. Forty-five young adults (23 women, 18–41 years) were included and GT3X + accelerometers (ActiGraph, Pensacola, FL, USA) were placed on their right hip, dominant, and non-dominant wrist for 7 days. We derived Euclidean Norm Minus One g (ENMO), Low-pass filtered ENMO (LFENMO), Mean Amplitude Deviation (MAD) and ActiGraph activity counts over 5-second epochs from the raw accelerations. Metric values were compared using a correlation analysis, and by plotting the differences by time of the day. Cut points for the dominant wrist were derived using Lin’s concordance correlation coefficient optimization in a grid of possible thresholds, using the nondominant wrist estimates as reference. They were cross-validated in a separate sample (N = 36, 10 women, 22–30 years). Shared variances between pairs of acceleration metrics varied across sites and metric pairs (range in r2: 0.19–0.97, all p < 0.01), suggesting that some sites and metrics are associated, and others are not. We observed higher metric values in dominant vs. non-dominant wrist, thus, we developed cut points for dominant wrist based on ENMO to classify sedentary time (<50 mg), light PA (50–110 mg), moderate PA (110–440 mg) and vigorous PA (≥440 mg). Our findings suggest differences between dominant and non-dominant wrist, and we proposed new cut points to attenuate these differences. ENMO and LFENMO were the most similar metrics, and they showed good comparability with MAD. However, counts were not comparable with ENMO, LFENMO and MAD.es_ES
dc.description.sponsorshipThis study was conducted under the umbrella of the ActiveBrains and the SmarterMove projects supported by the MINECO/FEDER (DEP2013-47540, DEP2016- 79512-R, RYC-2011-09011). JHM and AP-F are supported by grants from the Spanish Ministry of Education, Culture and Sport (FPU15/02645, FPU16/02760). CC-S is supported by a grant from the Spanish Ministry of Economy and Competitiveness (BES-2014-068829). IE-C is supported by a grant from the Alicia Koplowitz Foundation and by the Spanish Ministry of Economy and Competitiveness (IJCI-2017-33642). PH is supported by a grant from the the Strategic Research Area Health Care Science, Karolinska Institutet/Umea University. AR is supported by the NIHR Leicester Biomedical Research Centre and the Collaboration for leadership in Applied Health Research and Care (CLAHRC) East Midlands. UE is supported by the Research Council of Norway (249932/F20). This study has been partially funded by the University of Granada, UGR Research and Knowledge Transfer Fund (PPIT) 2016, Excellence Actions Programme: Units of Scientific Excellence; Scientific Unit of Excellence on Exercise and Health (UCEES), and by the Regional Government of Andalusia, Regional Ministry of Economy, Knowledge, Entreprises and University and European Regional Development Fund (ERDF), ref. SOMM17/6107/UGR. In addition, funding was provided by the SAMID III network, RETICS, funded by the PN I + D + I 2017–2021 (Spain), ISCIII- Sub-Directorate General for Research Assessment and Promotion, the European Regional Development Fund (ERDF) (Ref. RD16/0022), the EXERNET Research Network on Exercise and Health in Special Populations (DEP2005-00046/ACTI) and the European Union Horizon 2020 research and innovation programme under grant agreement No 667302.es_ES
dc.publisherSpringer Naturees_ES
dc.rightsAtribución 3.0 España*
dc.titleComparability of accelerometer signal aggregation metrics across placements and dominant wrist cut points for the assessment of physical activity in adultses_ES

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Atribución 3.0 España
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