Background and Purpose
Shared Use (SU) of community facilities for physical activity (PA) is not a new concept (1). However, its resurgence as an efficient and effective way to deliver recreational services comes at a time when researchers, practitioners, and policy-makers have adopted ecological frameworks to develop interventions to increase physical activity (2). Schools have been the most prominent facilities recommended because they are seen as safe, accessible places for physical activity to occur within the community (3). Despite the promise of SU as an intervention strategy, limited objective data exists about their association with facility use and physical activity and overall effectiveness.

Objectives
1. Compare facility use of physical activity settings in schools with shared use to use of physical activity settings in schools without shared use agreements (NSU); 2. Examine whether a SU policy was predictive of children and adults’ likelihood to engage in moderate and vigorous PA in school physical activity settings; 3. examine associations among program and environmental correlates and PA levels in those settings.

Methods
A survey of all middle schools within a school district resulted in schools categorized as having no/low Shared Use, Medium Shared Use, and High Shared Use (4). Four schools (2 NSU and 2 SU) were selected for in depth observations based on similar demographic/neighborhood characteristics. Data were obtained from direct observations using the System for Observing Play and Leisure in Youth (SOPLAY) (5). Between March 2010 and December 2010, 3,422 observations (1776 SU; 1646 NSU) of designated school zones were conducted by trained assessors during 3 time periods (6:30-8:30am, 2:30-4:30pm, and 5:30-7:30pm) during weekdays and weekends (8:00-10:00am, 1:00-3:00pm, and 5:00-7:00pm). Each school was observed 3 days during the week during the spring and fall and 1 day per week during the summer. Primary SOPLAY codes accounted for age, gender, and activity level (sedentary, walking, and vigorous), and type of activity. Inter-rater reliability for SOPLAY codes was almost perfect (kappa > 0.89) (6).

Individual users of school facilities and SOPLAY scans served as the units of analysis. First, binomial logistic regression was used to predict the likelihood of facility use based on shared use status at the scan level. Second, t-tests and Chi-Square tests examined associations between levels of usage and levels of physical activity and shared use status at the scan level. Finally, multinomial logistic regression was used to examine associations between individuals’ physical activity levels and predictor variables.

Results
Overall, 42,868 users (34,679 SU vs 8,189 NSU) were observed in school designated zones. In SU schools, 37.7% of the users observed were sedentary, 36.6% were moderately active, and 25.7% were engaged in vigorous activity. In non-SU schools, 36.2% of the users observed were sedentary, 40.1% were moderately active, and 23.6% were engaged in vigorous activity. The majority of users observed at schools were children (81% of overall users; 79.4% at SU schools; 86.1% at non SU schools). Among all schools, the majority of use occurred on outside athletic fields (73%) followed by gyms (16%). Shared use facilities were in use approximately 15.7% of the time periods observed, compared with only 8.9% non-shared use schools (OR = 1.91, p<.001).  An examination of user demographics based on SU revealed moderate differences in facility use among adults (OR =1.57, p<.001) and males (OR 1.18, p<.001). Regression models indicated no significant association between SU and individual levels of physical activity.

Conclusions
This study was one of the first to examine the impact of shared use of school facilities on PA levels. Several interesting findings should be noted. First, although shared use schools had significantly more users than non-SU schools, the difference in individual PA levels was negligible. Thus, shared use of schools facilities provided an opportunity for more people to be active, but did not increase levels of physical activity among users. While SU schools were nearly twice as likely to have their facilities used, that usage was only 15.7%, suggesting they are still under-utilized. Therefore, even schools with SU may have opportunities to offer more access to their facilities by encouraging their use through formal or informal shared use agreements with external community organizations. Finally, a comparison between use and the physical activity levels between users revealed that shared use seems to support male users and adult users more than females and children. This supports prior research suggesting that organized programming may encourage more girls and adults females to use public facilities (7, 8).

Implications for Practice and Policy
Policy and programming measures suggested by our data include marketing PA opportunities to nearby residents and other community organizations to maximize the percentage of time facilities are used.  To encourage greater use by women and girls, more formal programming should be a priority. The data can also be used to educate and inform citizens, school officials, and other community leaders about how shared use can promote community partnerships, organizational efficiencies and healthy communities.

References

1. Spengler, J. O., Young, S. J., & Linton, L. S. (2007). Schools as a community resource for physical activity: Legal considerations for decision makers. American Journal of Health Promotion, 21(4), 390-396.
2. Sallis, J. F., Cervero, R. B., Ascher, W., Henderson, K. A., Kraft, M. K., & Kerr, J. (2006). An ecological approach to creating active living communities. Annual Review of Public Health, 27(1), 297-322. doi: doi:10.1146/annurev.publhealth.27.021405.102100
3. Koplan, J. P., Liverman, C. T., & Kraak, V. I. (2005). Preventing childhood obesity: Health in the balance. Washington, DC: The National Academies Press.
4. Kanters, M., Bocarro, J. N., Filardo, M., Edwards, M.B., McKenzie, T.L., & Floyd, M.F. (in press). Does shared use of school facilities enhance physical activity and is it cost effective? Journal of School Health.
5. McKenzie, T. L. (2002). The use of direct observation to assess physical activity. In G. Welk (Ed.), Physical Activity Assessments for Health-related Research (pp. 179-195). Champaign, IL: Human Kinetics.
6. Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33, 159-174.
7. Bocarro, J. N., Kanters, M. A., Cerin, E., Floyd, M. F., Casper, J. M., SUu, L. J., & McKenzie, T. L. (2012). School sport policy and school-based physical activity environments and their association with observed physical activity in middle school children. Health & Place, 18(1), 31-38. doi: 10.1016/j.healthplace.2011.08.007
8. Cohen, D. A., Sehgal, A., Williamson, S., Marsh, T., Golinelli, D., & McKenzie, T. L. (2009). New Recreational Facilities for the Young and the Old in Los Angeles: Policy and Programming Implications. Journal of Public Health Policy, 30, S248-S263. doi: 10.1057/jphp.2008.45

Support / Funding Source
This research was funded by the Robert Wood Johnson Foundation, Active Living Research Round 9.