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Enhancing the value of accelerometer-assessed physical activity: meaningful visual comparisons of data-driven translational accelerometer metrics.
Rowlands, Alex V; Dawkins, Nathan P; Maylor, Ben; Edwardson, Charlotte L; Fairclough, Stuart J; Davies, Melanie J; Harrington, Deirdre M; Khunti, Kamlesh; Yates, Tom.
Afiliação
  • Rowlands AV; Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, LE5 4PW, UK. alex.rowlands@leicester.ac.uk.
  • Dawkins NP; NIHR Leicester Biomedical Research Centre, Leicester, UK. alex.rowlands@leicester.ac.uk.
  • Maylor B; Alliance for Research in Exercise, Nutrition and Activity (ARENA), Sansom Institute for Health Research, Division of Health Sciences, University of South Australia, Adelaide, Australia. alex.rowlands@leicester.ac.uk.
  • Edwardson CL; Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, LE5 4PW, UK.
  • Fairclough SJ; NIHR Leicester Biomedical Research Centre, Leicester, UK.
  • Davies MJ; Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, LE5 4PW, UK.
  • Harrington DM; NIHR Leicester Biomedical Research Centre, Leicester, UK.
  • Khunti K; Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, LE5 4PW, UK.
  • Yates T; NIHR Leicester Biomedical Research Centre, Leicester, UK.
Sports Med Open ; 5(1): 47, 2019 Dec 05.
Article em En | MEDLINE | ID: mdl-31808014
The lack of consensus on meaningful and interpretable physical activity outcomes from accelerometer data hampers comparison across studies. Cut-point analyses are simple to apply and easy to interpret but can lead to results that are not comparable. We propose that the optimal accelerometer metrics for data analysis are not the same as the optimal metrics for translation. Ideally, analytical metrics are precise continuous variables that cover the intensity spectrum, while translational metrics facilitate meaningful, public-health messages and can be described in terms of activities (e.g. brisk walking) or intensity (e.g. moderate-to-vigorous physical activity). Two analytical metrics that capture the volume and intensity of the 24-h activity profile are average acceleration (volume) and intensity gradient (intensity distribution). These allow investigation of independent, additive and interactive associations of volume and intensity of activity with health; however, they are not immediately interpretable. The MX metrics, the acceleration above which the most active X minutes are accumulated, are translational metrics that can be interpreted in terms of indicative activities. Using a range of MX metrics illustrates the intensity gradient and average acceleration (i.e. 24-h activity profile). The M120, M60, M30, M15 and M5 illustrate the most active accumulated minutes of the day, the M1/3DAY the most active accumulated 8 h of the day. We demonstrate how radar plots of MX metrics can be used to interpret and translate results from between- and within-group comparisons, provide information on meeting guidelines, assess individual activity profiles relative to percentiles and compare activity profiles between domains and/or time periods.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sports Med Open Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sports Med Open Ano de publicação: 2019 Tipo de documento: Article