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 (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 *** Physical activity in children *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

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 Promoting physical activity *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

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 Objective

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 Methods – 1 * * Van Sluijs et al., BMC Publ Health 2008

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: cpm) and vigorous PA (VPA: ≥4000cpm) separate for weekdays and weekends Exposure variables (baseline) Methods – 2

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

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

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

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 Discussion

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 Conclusion

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.