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Predictors of change in children's physical activity: potential targets for intervention

Predictors of change in children's physical activity: potential targets for intervention Esther van Sluijs , Chris Craggs, Kirsten Corder, Alison McMinn, Andy Jones, Ulf Ekelund, Simon Griffin. Physical activity in children.

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Predictors of change in children's physical activity: potential targets for intervention

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  1. Predictors of change in children's physical activity: potential targets for intervention Esther van Sluijs, Chris Craggs, Kirsten Corder, Alison McMinn, Andy Jones, Ulf Ekelund, Simon Griffin

  2. Physical activity in children • Physical activity (PA) is important for children’s current and future health* • Many children do not meet current PA guidelines of 60 minutes moderate-to-vigorous PA each day** • self-report – 60-70% • accelerometry – 0-99% • PA declines in late childhood and adolescence*** *e.g. Jansen et al, IJBNPA 2010; Telema, Obes Facts 2009; Yang et al, IJO 2009 **Ekelund et al, BJSM 2011 ***e.g. Nader et al, JAMA 2008; Jago et al, AJPM 2008; Corder al et, Ped 2010

  3. Promoting physical activity • Effects of PA promotion interventions in children have been varied* • Knowledge about factors associated with PA change will aid intervention development • current data mostly cross-sectional** • Review of prospective studies*** • only identified 46 studies • few factors studied consistently • predominant use of self- or parent-reported PA *e.g. Kriemler et al, BJSM 2011; Van Sluijs et al, BJSM 2011 **e.g. Sallis et al, MSSE 2000; Van der Horst et al, MSSE 2007 **Craggs et al, AJPM 2011

  4. Objective • To study predictors of 1-year change in PA in 10-year old children, using: • exposure variables at different levels of influence • objectively-measured PA • temporal and intensity-specific outcomes

  5. Methods – 1 • Sport, Physical activity and Eating behaviour, Environmental Determinants in Young people (SPEEDY) • Population-based sample • N=92 schools across Norfolk • sampled for environmental heterogeneity • invited all Year 5 children (aged 9-10) • Data collection at baseline (2007) • during 12-week Summer term • questionnaires and anthropometry at school measurement session • home pack including accelerometer & parent questionnaire * * Van Sluijs et al., BMC Publ Health 2008

  6. Methods – 2 • Data collection at follow-up (2008) • during 12-week Summer term • accelerometer and questionnaire sent home • Outcome variables • change in % wear time spent in moderate PA (MPA: 2000-3999cpm) and vigorous PA (VPA: ≥4000cpm) • separate for weekdays and weekends • Exposure variables (baseline)

  7. Methods – exposure variables Behavioural 1 variable Demographic & Biological 5 variables active travel age sex parental education Socio-cultural 9 variables self-efficacy barriers PA preference home in cul-de-sac availability of parks distance to green space Psychological 5 variables Environmental 8 variables family cohesiveness rules and restrictions electronic equipment

  8. ns P<0.001 P=0.012 ns Results – descriptive • 755 children provided valid data (≥3 days of 500 minutes) • 37% of SPEEDY-1 participants (N=2064) • fewer boys and those of lower SES • Both MPA and VPA decreased significantly at weekend days only Figure: Minutes spent in MPA and VPA at baseline and 1-year follow-up.

  9. NOTES: *p<0.05; **p<0.01; ***p<0.001; BMI: body mass index; HHI: Herfindahl-Hirschmann Index Results – final models • Multilevel linear regression models • Models adjusted for baseline PA, sex and school • No differences by sex

  10. Discussion • Predictors of change in PA are time- and intensity-specific • targets for interventions may vary • Few factors associated with changes on weekday • influence of school-level factors? • less change in PA on weekdays • Study has many strengths, but also some limitations: • did not assess potential complex associations • differential drop-out • multiple testing

  11. Conclusion • Interventions to prevent declines in PA in primary school children may focus on: • weekend activity • family logistical support • preventing further declines in those with higher BMI

  12. ACKNOWLEDGEMENTS Part of this work was undertaken by the Centre for Diet and Activity Research (CEDAR), a UKCRC Public Health Research Centre of Excellence. The SPEEDY study was funded by the National Prevention Research Initiative and the Medical Research Council.

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