Adiposity, fitness, health-related quality of life and the reallocation of time between children's school day activity behaviours: A compositional data analysis

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Abstract

Sedentary time (ST), light (LPA), and moderate-to-vigorous physical activity (MVPA) constitute the range of school day activity behaviours. This study investigated whether the composition of school activity behaviours was associated with health indicators, and the predicted changes in health when time was reallocated between activity behaviours. Accelerometers were worn for 7-days between October and December 2010 by 318 UK children aged 10–11, to provide estimates of school day ST, LPA, and MVPA. BMI z-scores and percent waist-to-height ratio were calculated as indicators of adiposity. Cardiorespiratory fitness (CRF) was assessed using the 20-m shuttle run test. The PedsQL™ questionnaire was completed to assess psychosocial and physical health-related quality of life (HRQL). Log-ratio multiple linear regression models predicted health indicators for the mean school day activity composition, and for new compositions where fixed durations of time were reallocated from one activity behaviour to another, while the remaining behaviours were unchanged. The school day activity composition significantly predicted adiposity and CRF ( p = 0.04–0.002), but not HRQL. Replacing MVPA with ST or LPA around the mean activity composition predicted higher adiposity and lower CRF. When ST or LPA were substituted with MVPA, the relationships with adiposity and CRF were asymmetrical with favourable, but smaller predicted changes in adiposity and CRF than when MVPA was replaced. Predicted changes in HRQL were negligible. The school day activity composition significantly predicted adiposity and CRF but not HRQL. Reallocating time from ST and LPA to MVPA is advocated through comprehensive school physical activity promotion approaches.

Trial registration

ISRCTN03863885.

Highlights

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First study to report school day activity compositions and health indicators
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School day activity composition predicted adiposity and cardiorespiratory fitness.
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School day activity composition did not predict health-related quality of life.
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Predicted changes in health were greatest when MVPA was replaced by other behaviours.

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Most cited references 43

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Validation of wearable monitors for assessing sedentary behavior.

Sarah Kozey-Keadle, Amanda Libertine, Kate Lyden … (2011)

A primary barrier to elucidating the association between sedentary behavior (SB) and health outcomes is the lack of valid monitors to assess SB in a free-living environment. The purpose of this study was to examine the validity of commercially available monitors to assess SB. Twenty overweight (mean ± SD: body mass index = 33.7 ± 5.7 kg·m(-2)) inactive, office workers age 46.5 ± 10.7 yr were directly observed for two 6-h periods while wearing an activPAL (AP) and an ActiGraph GT3X (AG). During the second observation, participants were instructed to reduce sitting time. We assessed the validity of the commonly used cut point of 100 counts per minute (AG100) and several additional AG cut points for defining SB. We used direct observation (DO) using focal sampling with duration coding to record either sedentary (sitting/lying) or nonsedentary behavior. The accuracy and precision of the monitors and the sensitivity of the monitors to detect reductions in sitting time were assessed using mixed-model repeated-measures analyses. On average, the AP and the AG100 underestimated sitting time by 2.8% and 4.9%, respectively. The correlation between the AP and DO was R2 = 0.94, and the AG100 and DO sedentary minutes was R2 = 0.39. Only the AP was able to detect reductions in sitting time. The AG 150-counts-per-minute threshold demonstrated the lowest bias (1.8%) of the AG cut points. The AP was more precise and more sensitive to reductions in sitting time than the AG, and thus, studies designed to assess SB should consider using the AP. When the AG monitor is used, 150 counts per minute may be the most appropriate cut point to define SB.

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Andrew Atkin, Trish Gorely, Stacy Clemes … (2012)

Research examining sedentary behaviour as a potentially independent risk factor for chronic disease morbidity and mortality has expanded rapidly in recent years. We present a narrative overview of the sedentary behaviour measurement literature. Subjective and objective methods of measuring sedentary behaviour suitable for use in population-based research with children and adults are examined. The validity and reliability of each method is considered, gaps in the literature specific to each method identified and potential future directions discussed. To date, subjective approaches to sedentary behaviour measurement, e.g. questionnaires, have focused predominantly on TV viewing or other screen-based behaviours. Typically, such measures demonstrate moderate reliability but slight to moderate validity. Accelerometry is increasingly being used for sedentary behaviour assessments; this approach overcomes some of the limitations of subjective methods, but detection of specific postures and postural changes by this method is somewhat limited. Instruments developed specifically for the assessment of body posture have demonstrated good reliability and validity in the limited research conducted to date. Miniaturization of monitoring devices, interoperability between measurement and communication technologies and advanced analytical approaches are potential avenues for future developments in this field. High-quality measurement is essential in all elements of sedentary behaviour epidemiology, from determining associations with health outcomes to the development and evaluation of behaviour change interventions. Sedentary behaviour measurement remains relatively under-developed, although new instruments, both objective and subjective, show considerable promise and warrant further testing.

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The PedsQL 4.0 as a school population health measure: feasibility, reliability, and validity.

James Varni, Tasha Burwinkle, Michael Seid (2006)

The application of health-related quality of life (HRQOL) as a school population health measure may facilitate risk assessment and resource allocation, the tracking of student health at the school and district level, the identification of health disparities among schoolchildren, and the determination of health outcomes from interventions and policy decisions at the school, district, and county level. To determine the feasibility, reliability, and validity of the 23-item PedsQL 4.0 (Pediatric Quality of Life Inventory) Generic Core Scales as a school population health measure for children and adolescents. Survey conducted in 304 classes at 18 elementary schools, 4 middle schools, and 3 high schools within a large metropolitan school district. The PedsQL 4.0 Generic Core Scales (Physical, Emotional, Social, School Functioning) were completed by 2437 children ages 8-18 and 4227 parents of children ages 5-18. The PedsQL 4.0 evidenced minimal missing responses, achieved excellent reliability for the Total Scale Score (alpha = 0.89 child, 0.92, parent report), and distinguished between healthy children and children with chronic health conditions. The PedsQL 4.0 was related to indicators of socioeconomic status (SES) at the school and district level. The PedsQL School Functioning Scale was significantly correlated with standardized achievement scores based on the Stanford 9. The results demonstrate the feasibility, reliability and validity of the PedsQL 4.0 Generic Core Scales as a school population health measure. The implications of measuring HRQOL in schoolchildren at the school, district, and county level for identifying and ameliorating health disparities are discussed.

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Author and article information

Contributors

Stuart J. Fairclough

Dorothea Dumuid

Kelly A. Mackintosh

Genevieve Stone

Rebecca Dagger

Gareth Stratton

Ian Davies

Lynne M. Boddy

Journal

Journal ID (nlm-ta): Prev Med Rep

Journal ID (iso-abbrev): Prev Med Rep

Title: Preventive Medicine Reports

Publisher: Elsevier

ISSN (Electronic): 2211-3355

Publication date PMC-release: 24 July 2018

Publication date Collection: September 2018

Publication date (Electronic): 24 July 2018

Volume: 11

Pages: 254-261

Affiliations

[a ]Movement Behaviours, Health and Wellbeing Research Group, Department of Sport and Physical Activity, Edge Hill University, St Helens Road, Ormskirk, Lancashire, UK

[b ]Department of Physical Education and Sports Science, University of Limerick, Limerick, Ireland

[c ]Alliance for Research in Exercise Nutrition and Activity (ARENA), Sansom Institute, School of Health Sciences, University of South Australia, Adelaide, Australia

[d ]Research Centre in Applied Sports, Technology Exercise and Medicine, College of Engineering, Swansea University, Swansea, Wales, UK

[e ]Faculty of Health and Social Care, Edge Hill University, St Helens Road, Ormskirk, Lancashire, UK

[f ]Department of Health Sciences, Liverpool Hope University, Hope Park, Liverpool, Merseyside, UK

[g ]School of Sport Studies, Leisure and Nutrition, Liverpool John Moores University, IM Marsh, Liverpool, Merseyside, UK

[h ]Physical Activity Exchange, Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, Merseyside, UK

Author notes

[* ]Corresponding author at: Movement Behaviours, Health and Wellbeing Research Group, Department of Sport and Physical Activity, Edge Hill University, St Helens Road, Ormskirk, Lancashire, UK. stuart.fairclough@ 123456edgehill.ac.uk

Article

Publisher ID: S2211-3355(18)30124-4

DOI: 10.1016/j.pmedr.2018.07.011

PMC ID: 6080199

PubMed ID: 30109170

SO-VID: db049d22-e1c3-49ca-a716-d0972574a82f

License:

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

History

Date received : 16 April 2018

Date revision received : 22 June 2018

Date accepted : 21 July 2018

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Adiposity, fitness, health-related quality of life and the reallocation of time between children's school day activity behaviours: A compositional data analysis

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Chinese Journal of School Health

Most cited references 43

Validation of wearable monitors for assessing sedentary behavior.

Methods of Measurement in epidemiology: sedentary Behaviour.

The PedsQL 4.0 as a school population health measure: feasibility, reliability, and validity.

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Cited by 22

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