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      Correlates of intensity-specific physical activity in children aged 9–11 years: a multilevel analysis of UK data from the International Study of Childhood Obesity, Lifestyle and the Environment

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          Abstract

          Objectives

          Physical activity (PA) can provide numerous physical and psychological health gains, yet a low proportion of children in England are sufficiently active to accrue benefit. Analysing the correlates of PA from a socioecological perspective may help to identify factors that promote versus discourage PA. The purpose of the present study was to: (1) assess the relationships between a wide range of potential correlates and intensity-specific PA and (2) explore which correlates are associated with meeting government PA guidelines.

          Design, setting and participants

          Cross-sectional study on children aged 9–11 years from the South West of England (n=425; 183 males).

          Outcome measures

          A mixture of self-reported and objective measures (eg, body mass index (BMI), accelerometer-derived PA, self-reported sport participation, etc) were collected from child participants, parents and school teachers. After adjusting for covariates (ie, age, sex and accelerometer wear time), multilevel modelling techniques were employed to examine the relationships between potential correlates and light-intensity, moderate-intensity and vigorous-intensity PA, as measured with an ActiGraph GT3X+ accelerometer. Generalised linear mixed modelling was used to analyse the correlates associated with government-recommended levels of PA.

          Results

          Computer use shared a negative association whereas parent support for PA showed a positive relationship with light-intensity PA. In terms of moderate-intensity PA, computer use and BMI z-score shared a negative association whereas positive relationships were found for sport participation, active transport and for outdoor time after school. Children at schools with 25%–49% of pupils attending school sport/PA clubs did more moderate-intensity PA than those attending schools with lower participation rates. For vigorous-intensity PA, a negative relationship was observed for BMI z-score, and positive associations for self-efficacy, active transport, parent support and the presence of crossing guards on routes to school. Correlates associated with meeting the PA guidelines were BMI z-score (negative), sport participation, active transport and outdoor time after school (all positive).

          Conclusion

          Results demonstrate that factors pertaining to the individual, home and school environment may play an important role in understanding the correlates of differing PA intensities in children.

          Trial registration number

          NCT01722500.

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          Most cited references40

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          Using Multivariate Statistics

          A Practical Approach to using Multivariate Analyses Using Multivariate Statistics , 6th edition provides advanced undergraduate as well as graduate students with a timely and comprehensive introduction to today's most commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher-level mathematics. This text's practical approach focuses on the benefits and limitations of applications of a technique to a data set - when, why, and how to do it. Learning Goals Upon completing this book, readers should be able to: Learn to conduct numerous types of multivariate statistical analyses Find the best technique to use Understand Limitations to applications Learn how to use SPSS and SAS syntax and output
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            Accelerometer data reduction: a comparison of four reduction algorithms on select outcome variables.

            Accelerometers are recognized as a valid and objective tool to assess free-living physical activity. Despite the widespread use of accelerometers, there is no standardized way to process and summarize data from them, which limits our ability to compare results across studies. This paper a) reviews decision rules researchers have used in the past, b) compares the impact of using different decision rules on a common data set, and c) identifies issues to consider for accelerometer data reduction. The methods sections of studies published in 2003 and 2004 were reviewed to determine what decision rules previous researchers have used to identify wearing period, minimal wear requirement for a valid day, spurious data, number of days used to calculate the outcome variables, and extract bouts of moderate to vigorous physical activity (MVPA). For this study, four data reduction algorithms that employ different decision rules were used to analyze the same data set. The review showed that among studies that reported their decision rules, much variability was observed. Overall, the analyses suggested that using different algorithms impacted several important outcome variables. The most stringent algorithm yielded significantly lower wearing time, the lowest activity counts per minute and counts per day, and fewer minutes of MVPA per day. An exploratory sensitivity analysis revealed that the most stringent inclusion criterion had an impact on sample size and wearing time, which in turn affected many outcome variables. These findings suggest that the decision rules employed to process accelerometer data have a significant impact on important outcome variables. Until guidelines are developed, it will remain difficult to compare findings across studies.
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              What Is the Relationship between Outdoor Time and Physical Activity, Sedentary Behaviour, and Physical Fitness in Children? A Systematic Review

              The objective of this systematic review was to examine the relationship between outdoor time and: (1) physical activity, (2) cardiorespiratory fitness, (3) musculoskeletal fitness, (4) sedentary behaviour; or (5) motor skill development in children aged 3–12 years. We identified 28 relevant studies that were assessed for quality using the GRADE framework. The systematic review revealed overall positive effects of outdoor time on physical activity, sedentary behaviour, and cardiorespiratory fitness, although causality could not be assumed due to a lack of RCTs. Motor skill development was unrelated to outdoor time; however, this relationship was only examined in a single study of preschool children. No studies were found that examined associations between outdoor time and musculoskeletal fitness.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2018
                3 February 2018
                : 8
                : 2
                : e018373
                Affiliations
                [1 ] departmentDepartment for Health , Centre for Motivation and Health Behaviour Change, University of Bath , Bath, UK
                [2 ] Pennington Biomedical Research Center , Baton Rouge, Louisiana, USA
                Author notes
                [Correspondence to ] Professor Martyn Standage; M.Standage@ 123456bath.ac.uk
                Article
                bmjopen-2017-018373
                10.1136/bmjopen-2017-018373
                5829668
                29431128
                0250a0d9-e3db-4bd8-9f64-587ed6d94886
                © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

                History
                : 27 June 2017
                : 14 January 2018
                : 17 January 2018
                Funding
                Funded by: The Coca-Cola Company;
                Categories
                Public Health
                Research
                1506
                1724
                Custom metadata
                unlocked

                Medicine
                physical activity,child,correlates,multilevel analysis
                Medicine
                physical activity, child, correlates, multilevel analysis

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