Your browser doesn't support javascript.
loading
Reference values for wrist-worn accelerometer physical activity metrics in England children and adolescents.
Fairclough, Stuart J; Rowlands, Alex V; Del Pozo Cruz, Borja; Crotti, Matteo; Foweather, Lawrence; Graves, Lee E F; Hurter, Liezel; Jones, Owen; MacDonald, Mhairi; McCann, Deborah A; Miller, Caitlin; Noonan, Robert J; Owen, Michael B; Rudd, James R; Taylor, Sarah L; Tyler, Richard; Boddy, Lynne M.
  • Fairclough SJ; Movement Behaviours, Nutrition, Health, & Wellbeing Research Group, and Department of Sport & Physical Activity, Edge Hill University, Ormskirk, UK.
  • Rowlands AV; Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, UK.
  • Del Pozo Cruz B; National Institute for Health Research (NIHR) Leicester Biomedical Research Centre (BRC), University Hospitals of Leicester NHS Trust and the University of Leicester, Leicester, UK.
  • Crotti M; Faculty of Education, University of Cádiz, Cádiz, Spain.
  • Foweather L; Biomedical Research and Innovation Institute of Cádiz (IMiBICA) Resarch Unit, Puerta del Mar University Hospital, University of Cádiz, Cádiz, Spain.
  • Graves LEF; Department of Sports Science and Clinical Biomechanics, Centre for Active and Healthy Ageing, University of Southern Denmark, Odense, Denmark.
  • Hurter L; Research Centre for Sport, Exercise, and Life Sciences, Coventry University, Coventry, UK.
  • Jones O; The Physical Activity Exchange, Research Institute of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK.
  • MacDonald M; The Physical Activity Exchange, Research Institute of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK.
  • McCann DA; The Physical Activity Exchange, Research Institute of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK.
  • Miller C; The Physical Activity Exchange, Research Institute of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK.
  • Noonan RJ; Movement Behaviours, Nutrition, Health, & Wellbeing Research Group, and Department of Sport & Physical Activity, Edge Hill University, Ormskirk, UK.
  • Owen MB; The Physical Activity Exchange, Research Institute of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK.
  • Rudd JR; Movement Behaviours, Nutrition, Health, & Wellbeing Research Group, and Department of Sport & Physical Activity, Edge Hill University, Ormskirk, UK.
  • Taylor SL; Faculty of Health and Wellbeing, University of Bolton, Bolton, UK.
  • Tyler R; Department of Applied Health and Social Care and Social Work, Faculty of Health, Social Care and Medicine, Edge Hill University, Ormskirk, UK.
  • Boddy LM; Norwegian School of Sport Sciences, Oslo, Norway.
Int J Behav Nutr Phys Act ; 20(1): 35, 2023 03 25.
Article en En | MEDLINE | ID: mdl-36964597
BACKGROUND: Over the last decade use of raw acceleration metrics to assess physical activity has increased. Metrics such as Euclidean Norm Minus One (ENMO), and Mean Amplitude Deviation (MAD) can be used to generate metrics which describe physical activity volume (average acceleration), intensity distribution (intensity gradient), and intensity of the most active periods (MX metrics) of the day. Presently, relatively little comparative data for these metrics exists in youth. To address this need, this study presents age- and sex-specific reference percentile values in England youth and compares physical activity volume and intensity profiles by age and sex. METHODS: Wrist-worn accelerometer data from 10 studies involving youth aged 5 to 15 y were pooled. Weekday and weekend waking hours were first calculated for youth in school Years (Y) 1&2, Y4&5, Y6&7, and Y8&9 to determine waking hours durations by age-groups and day types. A valid waking hours day was defined as accelerometer wear for ≥ 600 min·d-1 and participants with ≥ 3 valid weekdays and ≥ 1 valid weekend day were included. Mean ENMO- and MAD-generated average acceleration, intensity gradient, and MX metrics were calculated and summarised as weighted week averages. Sex-specific smoothed percentile curves were generated for each metric using Generalized Additive Models for Location Scale and Shape. Linear mixed models examined age and sex differences. RESULTS: The analytical sample included 1250 participants. Physical activity peaked between ages 6.5-10.5 y, depending on metric. For all metrics the highest activity levels occurred in less active participants (3rd-50th percentile) and girls, 0.5 to 1.5 y earlier than more active peers, and boys, respectively. Irrespective of metric, boys were more active than girls (p < .001) and physical activity was lowest in the Y8&9 group, particularly when compared to the Y1&2 group (p < .001). CONCLUSIONS: Percentile reference values for average acceleration, intensity gradient, and MX metrics have utility in describing age- and sex-specific values for physical activity volume and intensity in youth. There is a need to generate nationally-representative wrist-acceleration population-referenced norms for these metrics to further facilitate health-related physical activity research and promotion.
Asunto(s)
Palabras clave

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Muñeca / Acelerometría Límite: Adolescent / Child / Female / Humans / Male País como asunto: Europa Idioma: En Año: 2023 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Muñeca / Acelerometría Límite: Adolescent / Child / Female / Humans / Male País como asunto: Europa Idioma: En Año: 2023 Tipo del documento: Article