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Karimjee K, Harron RC, Piercy RJ, Daley MA. A standardised approach to quantifying activity in domestic dogs. ROYAL SOCIETY OPEN SCIENCE 2024; 11:240119. [PMID: 39021771 PMCID: PMC11251761 DOI: 10.1098/rsos.240119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Accepted: 05/17/2024] [Indexed: 07/20/2024]
Abstract
Objective assessment of activity via accelerometry can provide valuable insights into dog health and welfare. Common activity metrics involve using acceleration cut-points to group data into intensity categories and reporting the time spent in each category. Lack of consistency and transparency in cut-point derivation makes it difficult to compare findings between studies. We present an alternative metric for use in dogs: the acceleration threshold (as a fraction of standard gravity, 1 g = 9.81 m/s2) above which the animal's X most active minutes are accumulated (MXACC) over a 24-hour period. We report M2ACC, M30ACC and M60ACC data from a colony of healthy beagles (n = 6) aged 3-13 months. To ensure that reference values are applicable across a wider dog population, we incorporated labelled data from beagles and volunteer pet dogs (n = 16) of a variety of ages and breeds. The dogs' normal activity patterns were recorded at 200 Hz for 24 hours using collar-based Axivity-AX3 accelerometers. We calculated acceleration vector magnitude and MXACC metrics. Using labelled data from both beagles and pet dogs, we characterize the range of acceleration outputs exhibited enabling meaningful interpretation of MXACC. These metrics will help standardize measurement of canine activity and serve as outcome measures for veterinary and translational research.
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Affiliation(s)
- Kamila Karimjee
- Comparative Neuromuscular Diseases Laboratory, Department of Clinical Science and Services, Royal Veterinary College, London NW1 0TU, UK
- Structure and Motion Laboratory, Department of Comparative Biological Sciences, Royal Veterinary College, Hawkshead Lane, Hatfield AL9 7TA, UK
| | - Rachel C. M. Harron
- Comparative Neuromuscular Diseases Laboratory, Department of Clinical Science and Services, Royal Veterinary College, London NW1 0TU, UK
| | - Richard J. Piercy
- Comparative Neuromuscular Diseases Laboratory, Department of Clinical Science and Services, Royal Veterinary College, London NW1 0TU, UK
| | - Monica A. Daley
- Neuromechanics Laboratory, Department of Ecology and Evolutionary Biology, University of California, Irvine, CA 92697, USA
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Fairclough SJ, Rowlands AV, Del Pozo Cruz B, Crotti M, Foweather L, Graves LEF, Hurter L, Jones O, MacDonald M, McCann DA, Miller C, Noonan RJ, Owen MB, Rudd JR, Taylor SL, Tyler R, Boddy LM. Reference values for wrist-worn accelerometer physical activity metrics in England children and adolescents. Int J Behav Nutr Phys Act 2023; 20:35. [PMID: 36964597 PMCID: PMC10039565 DOI: 10.1186/s12966-023-01435-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 03/10/2023] [Indexed: 03/26/2023] Open
Abstract
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.
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Affiliation(s)
- Stuart J Fairclough
- Movement Behaviours, Nutrition, Health, & Wellbeing Research Group, and Department of Sport & Physical Activity, Edge Hill University, Ormskirk, UK
| | - Alex V Rowlands
- Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, UK
- National Institute for Health Research (NIHR) Leicester Biomedical Research Centre (BRC), University Hospitals of Leicester NHS Trust and the University of Leicester, Leicester, UK
| | - Borja Del Pozo Cruz
- Faculty of Education, University of Cádiz, Cádiz, Spain
- Biomedical Research and Innovation Institute of Cádiz (IMiBICA) Resarch Unit, Puerta del Mar University Hospital, University of Cádiz, Cádiz, Spain
- Department of Sports Science and Clinical Biomechanics, Centre for Active and Healthy Ageing, University of Southern Denmark, Odense, Denmark
| | - Matteo Crotti
- Research Centre for Sport, Exercise, and Life Sciences, Coventry University, Coventry, UK
| | - Lawrence Foweather
- The Physical Activity Exchange, Research Institute of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK
| | - Lee E F Graves
- The Physical Activity Exchange, Research Institute of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK
| | - Liezel Hurter
- The Physical Activity Exchange, Research Institute of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK
| | - Owen Jones
- The Physical Activity Exchange, Research Institute of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK
| | - Mhairi MacDonald
- Movement Behaviours, Nutrition, Health, & Wellbeing Research Group, and Department of Sport & Physical Activity, Edge Hill University, Ormskirk, UK
| | - Deborah A McCann
- The Physical Activity Exchange, Research Institute of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK
| | - Caitlin Miller
- Movement Behaviours, Nutrition, Health, & Wellbeing Research Group, and Department of Sport & Physical Activity, Edge Hill University, Ormskirk, UK
| | - Robert J Noonan
- Faculty of Health and Wellbeing, University of Bolton, Bolton, UK
| | - Michael B Owen
- Department of Applied Health and Social Care and Social Work, Faculty of Health, Social Care and Medicine, Edge Hill University, Ormskirk, UK
| | - James R Rudd
- Norwegian School of Sport Sciences, Oslo, Norway
| | - Sarah L Taylor
- The Physical Activity Exchange, Research Institute of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK
| | - Richard Tyler
- Movement Behaviours, Nutrition, Health, & Wellbeing Research Group, and Department of Sport & Physical Activity, Edge Hill University, Ormskirk, UK
| | - Lynne M Boddy
- The Physical Activity Exchange, Research Institute of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK.
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Backes A, Gupta T, Schmitz S, Fagherazzi G, van Hees V, Malisoux L. Advanced analytical methods to assess physical activity behavior using accelerometer time series: A scoping review. Scand J Med Sci Sports 2021; 32:18-44. [PMID: 34695249 PMCID: PMC9298329 DOI: 10.1111/sms.14085] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 10/12/2021] [Accepted: 10/18/2021] [Indexed: 11/29/2022]
Abstract
Physical activity (PA) is a complex human behavior, which implies that multiple dimensions need to be taken into account in order to reveal a complete picture of the PA behavior profile of an individual. This scoping review aimed to map advanced analytical methods and their summary variables, hereinafter referred to as wearable‐specific indicators of PA behavior (WIPAB), used to assess PA behavior. The strengths and limitations of those indicators as well as potential associations with certain health‐related factors were also investigated. Three databases (MEDLINE, Embase, and Web of Science) were screened for articles published in English between January 2010 and April 2020. Articles, which assessed the PA behavior, gathered objective measures of PA using tri‐axial accelerometers, and investigated WIPAB, were selected. All studies reporting WIPAB in the context of PA monitoring were synthesized and presented in four summary tables: study characteristics, details of the WIPAB, strengths, and limitations, and measures of association between those indicators and health‐related factors. In total, 7247 records were identified, of which 24 articles were included after assessing titles, abstracts, and full texts. Thirteen WIPAB were identified, which can be classified into three different categories specifically focusing on (1) the activity intensity distribution, (2) activity accumulation, and (3) the temporal correlation and regularity of the acceleration signal. Only five of the thirteen WIPAB identified in this review have been used in the literature so far to investigate the relationship between PA behavior and health, while they may provide useful additional information to the conventional PA variables.
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Affiliation(s)
- Anne Backes
- Physical Activity, Sport and Health Research Group, Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Tripti Gupta
- Physical Activity, Sport and Health Research Group, Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Susanne Schmitz
- Competence Center for Methodology and Statistics, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Guy Fagherazzi
- Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Vincent van Hees
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Accelting, Almere, The Netherlands
| | - Laurent Malisoux
- Physical Activity, Sport and Health Research Group, Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg
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Dygrýn J, Medrano M, Molina-Garcia P, Rubín L, Jakubec L, Janda D, Gába A. Associations of novel 24-h accelerometer-derived metrics with adiposity in children and adolescents. Environ Health Prev Med 2021; 26:66. [PMID: 34118885 PMCID: PMC8199825 DOI: 10.1186/s12199-021-00987-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 06/01/2021] [Indexed: 12/14/2022] Open
Abstract
Background Further research is required to explore the associations between 24-h movement behaviours and health outcomes in the paediatric population. Therefore, this study aimed to examine the associations between novel data-driven 24-h activity metrics and adiposity among children and adolescents. Methods The sample included 382 children (8–13 years) and 338 adolescents (14–18 years). The average acceleration (AvAcc) of activity, intensity gradient (IG), and metrics representing the initial acceleration for the most active time periods of the 24-h cycle were calculated from raw acceleration data. Adiposity measures included body mass index z-score, fat mass percentage (FM%), and visceral adipose tissue (VAT). Data analysis was performed using multiple linear regression adjusted for wear time, sex, maternal education level, and maternal overweight and obesity. Results Children demonstrated higher values in all 24-h activity metrics than did adolescents (p < 0.001 for all). For children, the initial acceleration for the most active 2, 5, 15, and 30 min of the 24-h cycle were negatively associated with FM% (p ≤ 0.043 for all) and VAT (p <0.001 for all), respectively. For adolescents, the IG was negatively associated with FM% (p = 0.002) and VAT (p = 0.007). Moreover, initial acceleration for the most active 2, 5, 15, 30, 60, and 120 min were associated with FM% (p ≤ 0.007 for all) and with VAT (p ≤ 0.023 for all). Conclusions The intensity distribution of activity and initial acceleration for the most active 2, 5, 15, 30, 60, and 120 min within the 24-h cycle are beneficial for the prevention of excess adiposity in the paediatric population.
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Affiliation(s)
- Jan Dygrýn
- Faculty of Physical Culture, Palacký University Olomouc, třída Míru 117, 771 11, Olomouc, Czech Republic
| | - María Medrano
- Faculty of Physical Culture, Palacký University Olomouc, třída Míru 117, 771 11, Olomouc, Czech Republic
| | - Pablo Molina-Garcia
- Faculty of Physical Culture, Palacký University Olomouc, třída Míru 117, 771 11, Olomouc, Czech Republic
| | - Lukáš Rubín
- Faculty of Physical Culture, Palacký University Olomouc, třída Míru 117, 771 11, Olomouc, Czech Republic.,Faculty of Science, Humanities and Education, Technical University of Liberec, Liberec, Czech Republic
| | - Lukáš Jakubec
- Faculty of Physical Culture, Palacký University Olomouc, třída Míru 117, 771 11, Olomouc, Czech Republic
| | - David Janda
- Faculty of Physical Culture, Palacký University Olomouc, třída Míru 117, 771 11, Olomouc, Czech Republic
| | - Aleš Gába
- Faculty of Physical Culture, Palacký University Olomouc, třída Míru 117, 771 11, Olomouc, Czech Republic.
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Fairclough SJ, Tyler R, Dainty JR, Dumuid D, Richardson C, Shepstone L, Atkin AJ. Cross-sectional associations between 24-hour activity behaviours and mental health indicators in children and adolescents: A compositional data analysis. J Sports Sci 2021; 39:1602-1614. [PMID: 33615990 DOI: 10.1080/02640414.2021.1890351] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
We examined associations between youth 24-hour activity behaviour compositions and mental health. Data were collected from 359 participants (aged 9-13 years). Activity behaviours (sleep, sedentary time (ST), light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA)) were assessed using wrist-worn accelerometers. Questionnaires and a computerized cognitive test battery assessed mental health outcomes. Linear mixed models examined associations between activity behaviour compositions and mental health. Post-hoc analyses modelled the influence of reallocating fixed durations of time between activity behaviours on mental health. ST was associated with worse internalizing problems (all participants; p< 0.05) and poorer prosocial behaviour (primary school participants only; p< 0.05), relative to the other activity behaviours. LPA was associated with worse cognitive test scores among primary school participants; p< 0.05). For all participants, reallocating time to ST from sleep and MVPA was associated with higher internalizing problems. Among primary school participants, reallocating time to ST from any other behaviour was associated with poorer prosocial behaviour, and reallocating time to LPA from any other behaviour was associated with lower executive function. Children's mental health may be promoted by schools integrating opportunities for MVPA throughout the day. Our results provide further evidence for the influence of daily activity behaviours on youth mental health.
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Affiliation(s)
- Stuart J Fairclough
- Health Research Institute and Movement Behaviours, Health, and Wellbeing Research Group, and Department of Sport and Physical Activity, Edge Hill University, Ormskirk, UK
| | - Richard Tyler
- Health Research Institute and Movement Behaviours, Health, and Wellbeing Research Group, and Department of Sport and Physical Activity, Edge Hill University, Ormskirk, UK
| | - Jack R Dainty
- School of Health Sciences, Faculty of Medicine and Health Sciences, University of East Anglia, Norwich, UK
| | - Dorothea Dumuid
- Alliance for Research in Exercise, Nutrition and Activity, Allied Health & Human Performance, University of South Australia, Adelaide, South Australia
| | | | - Lee Shepstone
- Norwich Medical School, Faculty of Medicine and Health Sciences, University of East Anglia, Norwich, UK
| | - Andrew J Atkin
- School of Health Sciences, Faculty of Medicine and Health Sciences, University of East Anglia, Norwich, UK
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Crotti M, Rudd JR, Roberts S, Boddy LM, Fitton Davies K, O’Callaghan L, Utesch T, Foweather L. Effect of Linear and Nonlinear Pedagogy Physical Education Interventions on Children's Physical Activity: A Cluster Randomized Controlled Trial (SAMPLE-PE). CHILDREN-BASEL 2021; 8:children8010049. [PMID: 33467568 PMCID: PMC7830495 DOI: 10.3390/children8010049] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 01/08/2021] [Accepted: 01/13/2021] [Indexed: 01/21/2023]
Abstract
Background: School-based interventions are a key opportunity to improve children’s physical activity (PA); however, there is lack of evidence about how pedagogical approaches to motor learning in physical education (PE) might affect PA in children. Therefore, this study aimed to assess how different pedagogical approaches in PE might affect children’s PA. Methods: Participants (n = 360, 5–6 years) from 12 primary schools within the SAMPLE-PE randomized controlled trial were randomly allocated to either Linear Pedagogy (LP: n = 3) or Nonlinear Pedagogy (NP: n = 3) interventions, where schools received a 15-week PE intervention delivered by trained coaches, or to a control group (n = 6), where schools followed usual practice. ActiGraph GT9X accelerometers were used to assess PA metrics (moderate-to-vigorous PA, mean raw acceleration and lowest acceleration over the most active hour and half hour) over whole and segmented weeks at baseline, immediately post-intervention and 6 months follow-up. Intention to treat analysis employing multilevel modelling was used to assess intervention effects. Results: LP and NP interventions did not significantly affect children’s PA levels compared to the control group. Conclusion: PE interventions based on LP and NP alone might not be effective in improving habitual PA in children.
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Affiliation(s)
- Matteo Crotti
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool L2 2QP, UK; (M.C.); (J.R.R.); (S.R.); (L.M.B.); or (K.F.D.); (L.O.)
| | - James R. Rudd
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool L2 2QP, UK; (M.C.); (J.R.R.); (S.R.); (L.M.B.); or (K.F.D.); (L.O.)
| | - Simon Roberts
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool L2 2QP, UK; (M.C.); (J.R.R.); (S.R.); (L.M.B.); or (K.F.D.); (L.O.)
| | - Lynne M. Boddy
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool L2 2QP, UK; (M.C.); (J.R.R.); (S.R.); (L.M.B.); or (K.F.D.); (L.O.)
| | - Katie Fitton Davies
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool L2 2QP, UK; (M.C.); (J.R.R.); (S.R.); (L.M.B.); or (K.F.D.); (L.O.)
- Centre of Sport, Exercise and Life Sciences, Coventry University, Coventry CV1 5FB, UK
| | - Laura O’Callaghan
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool L2 2QP, UK; (M.C.); (J.R.R.); (S.R.); (L.M.B.); or (K.F.D.); (L.O.)
| | - Till Utesch
- Department of Pedagogical Assessment and Potential Development, Institute of Educational Sciences, University of Münster, 48149 Münster, Germany;
| | - Lawrence Foweather
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool L2 2QP, UK; (M.C.); (J.R.R.); (S.R.); (L.M.B.); or (K.F.D.); (L.O.)
- Correspondence:
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Rowlands AV, Dawkins NP, Maylor B, Edwardson CL, Fairclough SJ, Davies MJ, Harrington DM, Khunti K, Yates T. Enhancing the value of accelerometer-assessed physical activity: meaningful visual comparisons of data-driven translational accelerometer metrics. SPORTS MEDICINE - OPEN 2019; 5:47. [PMID: 31808014 PMCID: PMC6895365 DOI: 10.1186/s40798-019-0225-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Accepted: 11/13/2019] [Indexed: 02/02/2023]
Abstract
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.
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Affiliation(s)
- Alex V Rowlands
- Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, LE5 4PW, UK.
- NIHR Leicester Biomedical Research Centre, Leicester, UK.
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Sansom Institute for Health Research, Division of Health Sciences, University of South Australia, Adelaide, Australia.
| | - Nathan P Dawkins
- Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Ben Maylor
- Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Charlotte L Edwardson
- Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Stuart J Fairclough
- Movement Behaviours, Health, and Wellbeing Research Group, Department of Sport and Physical Activity, Edge Hill University, Ormskirk, UK
| | - Melanie J Davies
- Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Deirdre M Harrington
- Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Kamlesh Khunti
- Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, LE5 4PW, UK
- NIHR Collaboration for Leadership in Applied Health Research and Care East Midlands, Leicester General Hospital, Leicester, UK
| | - Tom Yates
- Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
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