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Schools play a critical role in helping children lead active, healthy lives. Recess, PE classes, after-school programs, and walking or biking to and from school all have the potential to get kids moving. Research shows that kids who move more aren’t just healthier, they also tend to do better academically, behave better in class and miss fewer days of school.  Unfortunately, many schools do not offer enough opportunities for children to be active. Policy-makers, teachers and parents can use research on the benefits of school physical activity to advocate for programs and policies that help children be active before, during and after school.

Download our Schools-related Resources Sheet for the best evidence available about a variety of school-based strategies for promoting physical activity.

You can also view and download our The Role of Schools in Promoting Physical Activity infographic.

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The Impact of Physical Environment and Policy Characteristics on Physical Activity Levels of Children Attending After-school Programs

Date: 
03/11/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.

Abstract: 

Background and Purpose
Afterschool programs (3 pm – 6 pm, ASP’s) are seen as an important setting to combat children’s physical inactivity.(1, 2) In recent years, evidence supporting the role of the physical environment and policy-level characteristics on children’s physical activity level has emerged.(3, 4) However, the extent to which ASP’s physical environment and policy characteristics impact the physical activity level of children attending is unknown.

Objectives
The purpose of this paper is to evaluate the influence of program physical environment and policy characteristics on the physical activity levels of children attending a diverse range of ASP’s.

Methods
Twenty afterschool programs across South Carolina serving 1,700 children (5-12 years old) took part in a healthy eating and physical activity intervention. Baseline information for physical activity is presented. Policy-level characteristics were evaluated for the presence of 11 supportive physical activity policy items (i.e. the presence of written policy to promote physical activity, child feedback, screen time, types of physical activity, allocating time for physical activity in the schedule, staff training to promote physical activity and quality of that training, providing activities that appeals to both girls and boys, curriculum and evaluation) using the Healthy Afterschool Program Index-Physical Activity (HAPI-PA).(5) The total score of the HAPI-PA is presented as a continuous measure (0-25) with higher scores indicating a more supportive environment of physical activity. The physical environment was defined as the size of physical activity space used by the ASP’s and was determined by the program site director and direct observation. Used indoor physical activity area (ft2) was measured using a measuring wheel at each of the 20 ’s. Estimates of the outdoor spatial area (acre) used for physical activity at each of the ASP’s in the study was calculated using Geographical Information Systems software (GIS).

Physical activity was measured using ActiGraph accelerometers (Shalimar, FL) during four non-consecutive days (Monday through Thursday) in the Spring of 2013. Children were fitted with the accelerometers upon arrival at the ASP’s and removed prior to program departure.  Cut-point thresholds associated with Moderate-to-vigorous physical activity (MVPA) (Evenson cut-points) (6) were used to distil physical activity intensity and sedentary behavior (Matthews cut-points) (7) using 5-seconds epoch intervals. Accelerometer data was included in the analysis if total daily attendance (accelerometer wear-time) was equal to or greater than 55 minutes. The association between the presence of an environmental features and time spent in MVPA and sedentary behavior was calculated using a mixed model regression accounting for multiple measurement days nested within child nested within afterschool program.

Results
The size of the physical activity space used was significantly associated with a change in the amount of time both boys and girls spent in MVPA and sedentary behavior, after adjusting for age, race, BMI, percentage of population (neighborhood) in poverty, time spent in the program, total HAPI-PA score, and scheduled physical activity time. Specifically for every 1000 ft2 of used indoor activity space, a decrease of 2.0 minutes (95%CI -3.9  - -6.5) and 2.1 minutes (95%CI -3.8 - -3.0) of MVPA and an increase of 5.5 minutes (95%CI 2.2-8.7) and 6.5 minutes (95%CI 3.1-9.1) of sedentary behavior was observed among boys and girls, respectively. For every 1 acre of outdoor space used for physical activity, boys and girls showed an increase of 2.5 minutes (95%CI 1.6-3.4) and 1.60 minutes (95%CI 0.8-2.4) of MVPA and a decrease of 3.8 minutes (95%CI -5.4 - -2.3) and 2.5 minutes (95%CI -4.0 - -1.1) of sedentary behavior. No other associations were observed.

Conclusions
Despite the importance of policy characteristics, the mere presences of these characteristics were unrelated to the physical activity levels of children attending ASP’s. Although the size of used outdoor physical activity space was related to higher levels of MVPA, while the amount of used indoor space was associated with lower levels of MVPA, for both boys and girls, the observed change in minutes of MVPA was small.

Implications for Practice and Policy
The findings of this study have two important implications for improving physical activity of children attending ASP’s. First, our results suggest that in the absence of support systems aimed at assisting ASP’s with implementation of physical activity polices, supportive policy characteristics are ineffective in increasing the amount of MVPA accumulated by children attending ASP’s. Second, our findings suggest that although the change in the amount of MVPA accumulated while at the ASP’s was significantly associated with the size of used physical activity space, the magnitude of change in the amount of MVPA accumulated was relatively small for every one unit of increases in the size of physical activity space. Taken together, these findings suggest other more modifiable ASP’s characteristics, such as the skills staff have for creating activity-friendly environments, may be more influential to increasing MVPA than policy or physical environmental characteristics.

References

  1. Beets MW, Beighle A, Erwin HE, Huberty JL. After-school program impact on physical activity and fitness: a meta-analysis. Am J Prev Med 2009;36(6):527-37.
  2. Pate RR, O’Neill JR. After-school interventions to increase physical activity among youth. British Journal of Sports Medicine 2009;43(1):14-18.
  3. Bower JK, Hales DP, Tate DF, Rubin DA, Benjamin SE, Ward DS. The childcare environment and children's physical activity. Am J Prev Med 2008;34(1):23-9.
  4. Sallis JF, Glanz K. The role of built environments in physical activity, eating, and obesity in childhood. The future of children 2006;16(1):89-108.
  5. Ajja R, Beets MW, Huberty J, Kaczynski AT, Ward DS. The healthy afterschool activity and nutrition documentation instrument. Am J Prev Med 2012;43(3):263-71.
  6. Evenson KR, Catellier DJ, Gill K, Ondrak KS, McMurray RG. Calibration of two objective measures of physical activity for children. J Sports Sci 2008;26(14):1557-65.
  7. Matthews CE, Chen KY, Freedson PS, Buchowski MS, Beech BM, Pate RR, et al. Amount of time spent in sedentary behaviors in the United States, 2003-2004. American Journal of Epidemiology 2008 167(7):875-81.

 

Support / Funding Source
1R01HL112787-01A1

Authors: 
Rahma Ajja, MPT, MPH, Morgan Clennin, MPH, Michael Beets, PhD, Daria Winnicka, BA, Falon Tilley, MS, Glenn Weaver, PhD, & Jessica Chandler, MS
Location by State: 

Association of After-school Programs Contextual Characteristics and Children’s Moderate-to-Vigorous Physical Activity and Time Spent Sedentary

Date: 
03/11/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.

Abstract: 

Background and Purpose
Nationwide, a majority of youth fail to meet current physical activity (PA) recommendations, making physical inactivity among youth an important public health concern (1). While past research has identified several settings (i.e. schools, home, neighborhood, etc.) that impact youth PA levels (2-3), the afterschool environment has recently emerged as an influential setting with the potential to substantially impact youth PA levels (4).  With an estimated 8 million youth (age 5-18 years old) attending ASP in the United States, these programs represent an ideal setting to promote PA among a diverse group of children (5). However, very little is known about ASPs characteristics associated with children’s MVPA and time spent sedentary. The purpose of the current study was to examine the relationship between ASP contextual factors, specifically size of indoor and outdoor play space, type of activity (free play vs. organized PA), program length, and MVPA and time spent sedentary among children attending a diverse sample of ASPs.

Objectives
To examine the association of the ASP contextual characteristics and their relationship with MVPA and time spent sedentary while attending an ASP.

Methods
Twenty ASPs across the South Carolina were selected to evaluate the impact of program contextual factors on children’s PA levels. A total of 1,302 children (5-12yrs, 53% boys) wore accelerometers for 4 non-consecutive days while attending the ASPs. The physical size of the indoor and outdoor play space ASP used each day were measured via a measuring wheel (indoor) and GIS (outdoor), and inventoried via direct observation. The type of activity was evaluated via direct observation using the System for Observing Staff Promotion of Activity and Nutrition and classified as a ratio of free-play (e.g., children released to play on playground and open green spaces) to organized (e.g., adult-led structured games) activity offerings based on the percentage of observational scans during physical activity time either indoors or outdoors. Time allocated for PA opportunities was determined from each ASPs’ daily schedule. PA and sedentary behavior were measured using accelerometers (ActiGraph GT3X models) (6-7). Time (min/d) spent in MVPA and sedentary indoors and outdoors was estimated using built-in light sensors (Lux values) (8). The analysis was conducted only on children attending the ASP for at least 60 minutes on a given day. Children’s MVPA and time spent sedentary (min/d) during indoor and outdoor opportunities were evaluated separately in relation to size of the play space, type of activity provided, and amount of time allocated for PA using mixed model regressions.

Results
Girls and boys accumulated an average of 18.1 and 24.2min of MVPA/d. When comparing indoor and outdoor MVPA, approximately equal portions of activity were accumulated in each activity location. Girls obtained 9.0min of indoor MVPA/d (49.7%) and 9.1mins of outdoor MVPA/d (51.3%), while boys accumulated 12.4min of indoor MVPA/d (51.3%) and 11.8min of outdoor MVPA/d (49.7%). Regarding outdoor MVPA, each additional acre of play space was associated with a 2.8 and 1.5 min/d increase in outdoor MVPA for boys and girls, respectively, and a 2.1 min/d increase in outdoor sedentary behavior for boys. A higher free-play to organized activities ratio was associated with a 3.5 and 3.0 min/d increase in outdoor MVPA for boys and girls, respectively. Examining indoor activity levels, a higher ratio of free-play to organized activities was associated with a 2.4 min/d increase in indoor MVPA for boys. Time spent sedentary indoors increased by 0.5 and 0.7 min/d with each additional increase in 1,000ft2 of indoor activity space for boys and girls, respectively, while a higher free-play to organized activities ratio was associated with a 5.5 and 8.3 min/d increase in indoor sedentary behavior for girls. Length of time allocated for PA during the ASP was unrelated to MVPA and time spent sedentary.

Conclusions
These findings suggest limited influence of the physical size of play space on children’s MVPA and sedentary behaviors during an ASP and that modifiable programmatic structure, in the form of the type of activity opportunities provided (free-play vs. organized games) was related to both MVPA and time spent sedentary. These are important findings, in that increasing physical play space is not a feasible or realistic strategy for ASPs. Conversely, more children were physically active indoors with the presence of more organized activities, yet this was related to a decrease in MVPA. Thus, future studies should develop effective strategies to increase PA levels by taking into account indoor and outdoor play opportunities.

Implications for Practice and Policy
While the ASP play space was associated with children’s PA, the impact of this was minimal. Additional contextual factors impacting ASP youth PA, such as programming high quality PA experiences, are likely to lead to greater improvements in MVPA and reductions in sedentary behaviors. Policies, therefore, should target the PA programming to ensure children are afforded opportunities to be physically active while attending as ASP.

References

  1. Troiano RP, Berrigan D, Dodd KW, Masse LC, Tilert T, McDowell M. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc. 2008; 40(1): 181-188.
  2. Davison KK, Lawson CT. Do attributes in the physical environment influence children's physical activity? A review of the literature. International Journal of Behavioral Nutrition and Physical Activity. 2006; 3(19).
  3. Ferreira I, et al. Environmental correlates of physical activity in youth – a review and update. Obesity Reviews. 2007; 8(2):129-154.
  4. Sallis JF, McKenzie TL. Physical education's role in public health. Res Q Exerc Sport. 1991; 62: 124–137.
  5. Afterschool Alliance. America After 3 pm: A Household Survey on Afterschool in America; 2009.
  6. Matthews, CE, Chen KY, et al. Amount of time spent in sedentary behaviors in the United States, 2003-2004. American Journal of Epidemiology. 2008; 167(7): 875-881.
  7. Evenson, KR, Catellier DJ, et al. Calibration of two objective measures of physical activity for children. J Sports Sci. 2008;26(14): 1557-1565.
  8. Flynn JI, Coe DP, Larsen CA, Rider BC, Conger SA, Bassett DR Jr. Detecting Indoor and Outdoor Environments Using the ActiGraph GT3X?+ Light Sensor in Children. Med Sci Sports Exerc. 2013.

 

Support / Funding Source
NIH: 1R01HL112787

Authors: 
Morgan Clennin, MPH, Rahma Ajja, MPH, Robert Weaver, PhD, & Michael Beets, PhD
Location by State: 
Study Type: 

School Gardens and Physical Activity: A Randomized Controlled Trial of Low-Income Elementary Schools

Date: 
03/11/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.nn

Abstract: 

Background and Purpose
Recently, school gardens have begun to move from niche to norm as a strategy to promote public health (Severson, 2010; Otterman, 2010).  However, despite growing interest, few studies have examined the effects of gardens on children’s health or health behaviors.  Evidence suggests that gardens may positively influence children’s diet-related outcomes such as vegetable consumption, vegetable knowledge (Morris, Briggs & Zidenberg-Cherr, 2002), willingness to taste vegetables (Morris, Neustadter & Zidenberg-Cherr, 2001; Morris, Briggs & Zidenberg-Cherr, 2002) but studies of gardens’ effects on children’s physical activity (PA) are virtually nonexistent.

Despite the dearth of research examining school gardens and PA, the influence of school gardens on children’s PA merits study for four reasons.  First, preliminary evidence suggests that school gardens have the potential to influence PA (Hermann et al., 2006) and gardening has been linked to PA among adults (Twiss et al., 2003). Second, we know that time spent outdoors is a positive and consistent predictor of PA among children (Ferreira, van der Horst, Wendel-Vox, van Lenthe & Brug, 2006; Sallis, Prochaska & Taylor, 2000).  Thus, one strategy to increase PA is to increase time outdoors, enhance children’s desire to be outdoors, and thereby compete with the “draw” of indoor activities such as TV and computers.  A third argument for gardening as a means to increase PA is that there may be carry-over effects from one context to another — in this case, from school to home.  After participating in a community gardening program in San Bernardino, California, the number of students who gardened at home increased by 20% (Twiss et al., 2003).  A fourth argument for gardening as a strategy to increase youth PA concerns the initiation of long-term health-related habits. Children and youth in this country are not achieving recommended levels of PA (Pate, Freedson, Sallis et al. 2002).  Among children ages 6-11, only 42% achieve the recommended 1 hour of PA per day (Troiano et al, 2007).  Consistent with the life course perspective, empirical evidence suggests that life-long habits, including those related to food and PA (DiNubile, 1993), are established early (Elder 1998; Wethington, 2005).  Introducing children to gardening may help to shift them from a life course trajectory of sedentary activities toward a positive trajectory of gardening and healthy habits.

Objectives
The objectives of this study are to examine:

  1. the effects of school gardens on children’s time spent outdoors and physical activity levels during the school day
  2. the effects of school gardens on children’s general activity and sedentary behavior patterns over time
  3. among children in the intervention group, differences in activity and movement patterns while participating in an outdoor, garden-based lesson compared to while participating in an indoor, classroom lesson.

 

Methods
In a randomized controlled trial, this 2-year study examined the effects of a school garden intervention on elementary school children's time spent outdoors and physical activity.  Eight low-income New York State schools were randomly assigned to receive school gardens or to serve as wait-list control schools that received gardens at the end of the data collection period. Physical activity was operationalized with three measures.  Actigraph GT3X+ accelerometers worn during the school day for three days at each of four waves of data collection indicated children's levels of vigorous, moderate, and light physical activity as well as sedentary activity.  Lux measures from the accelerometers provided a measure of children's time spent outdoors.  The GEMS Activity Questionnaire (GAQ) (Treuth et al., 2003) documented changes in overall physical activity behaviors over the 2-year period.  Lastly, the PARAGON direct observation measure (Myers & Wells, under review) was used to characterize the postures and movement associated with indoor versus outdoor learning.

Results
Lux readings from the accelerometers indicate that children in the garden intervention group showed an increase in the amount of time spent outdoors during the school day.  In addition, accelerometry results indicate the intervention group increased proportion of time spent in moderate physical activity (MPA) and moderate to vigorous physical activity (MVPA) compared to pre-garden baseline and to the non-garden control group.  Results from the GAQ suggest that over time, children in the garden intervention are less sedentary in their overall activities than the control group children.  Lastly, direct observation data suggest that while participating in a garden-based outdoor lesson, children engage in less sitting and in more walking and standing than while participating in an indoor lesson in the classroom.

Conclusions
School gardens appear to be a potent intervention to increase children’s time spent outdoors as well as the proportion of time spent in MVPA during the school day.  Gardens may also contribute to reduction of overall sedentary activities.  Lessons delivered in the garden are associated with more movement than are indoor lessons.

Implications for Practice and Policy
This study provides evidence that school gardens should move from niche to norm in schools throughout the United States, as another strategy in our toolkit to increase physical activity.

References

  1. DiNubile, N. (1993). Youth fitness—Problems and solutions. PrevMed 22:589–594.
  2. Elder, G.H. (1998). The life course and human development. Chapter 16. In: W. Damon and R.M. Lerner (Eds.) Handbook of Child Psychology. Vol1: Theoretical Models of Human Development. NY: J. Wiley & Sons, Inc.
  3. Ferreira, I., et al. (2006). Environmental correlates of physical activity in youth -- a review and update. Obesity Reviews, 8, 129-154.
  4. Hermann, J.R., et al. (2006).  After-school gardening improves children’s reported vegetable intake and physical activity. JNEB, 38: 201-202. 
  5. Morris, J.L., et al., (2002). Development and evaluation of a garden-enhanced nutrition education curriculum for elementary schoolchildren. Journal Child Nutrition Management, 2 (Fall 2002).
  6. Morris, J. L., et al.(2001). First-grade gardeners more likely to taste vegetables. California Agriculture, 55(1), 43-46.
  7. Myers, E.M. & Wells ,N.M. (under review).  Children’s physical activity while gardening.
  8. Otterman, S. (2010.  Turning Asphalt into Edible Education.  NYT, October 19, 2010.
  9. Pate, R.R., et al. (2002).  Compliance with physical activity guidelines: prevalence in a population of children and youth.  Annals of Epidemiology, 12, 303-308
  10. Sallis, J. F., et al. (2000). A review of correlates of physical activity of children and adolescents. MSSE, 32(5), 963-975.
  11. Severson, K. (2010).  School adds weeding to reading and writing.  NYT, January 19, 2010, p. D3. 
  12. Treuth, M.S., et al. (2003).  Validity and reliability of activity measures in African-American Girls for GEMS.  MSSE, 35 (3), 532 – 539.
  13. Troiano, R.P., et al. (2008).  Physical activity in the United States measured by accelerometer.  MSSE, 40 (1), 181-188.
  14. Trost, S.G., et al.(1998). Validity of the computer science and application (CSA) activity monitor in children.  MSSE, 1998, 30 (4), 629-633.
  15. Twiss, J., et al (2003).  Community Gardens AJPH, 93 (9), 1435-1438.
  16. Wethington, E. (2005). An overview of the life course perspective: Implications for health and nutrition. JNEB, 37 (3), 115-120.

 

Support / Funding Source
This research was supported by The Robert Wood Johnson Foundation through its Active Living Research Program (ALR); The U.S. Department of Agriculture, Food & Nutrition Service (FNS), People’s Garden pilot program; The Atkinson Center for a Sustainable Future.

Authors: 
Nancy Wells, PhD, Beth Myers, MPH, & Charles Henderson, MS
Location by State: 

Effects of Short Bouts of Structured Physical Activity on Preschooler's during Preschool-day Physical Activity Level

Date: 
03/11/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.

Abstract: 

Background and Purpose
The preschool years (2.9–5 years) have been identified as a critical time to intervene on physical activity (PA), since children begin to form their PA habits during this time frame (1). To date, most of PA studies have focused on changing the outdoor play environment and have rarely focused on changing the PA level during the classroom setting. Additionally, most studies do not take into account the intermittent nature of preschoolers play patterns (2). A recent review of the literature indicates that the duration of most PA interventions in preschoolers ranges between 30 - 45 minutes per session (3). There is research that suggests that these long duration PA interventions may not be effective for young children. Within a 30-minute recess period, most children tend to accumulate the majority of their moderate-to-vigorous PA (MVPA) during the first 10 minutes of play, with the remaining 20 minute spent in sedentary to light intensity activities (4). The longer children participate in a given game or activity (structured or unstructured), the less activity they accumulate during the entire period of the activity (4). Shorter bouts in PA (e.g. <= 10 minutes in duration per session) have been shown to be a successful strategy for improving children’s PA, body weight, and academic performance (5-7). The majority of these studies have been in elementary school age children. The intermittent nature of preschoolers’ play patterns suggests that short bouts of activity implemented during the preschool day may be beneficial to PA levels.

Objectives
This study examined the effects of short bouts of structured PA (SBS-PA) implemented within the classroom setting as part of designated gross-motor playtime on during-school PA in preschoolers.

Methods
The Short bouTs of Exercise for Preschoolers (STEP) study was a six-month cluster-randomized study. Ten preschool centers serving low-income families were randomized to receive the SBS-PA (n=5) intervention or continue to follow their usual preschool center gross motor playtime activities (unstructured PA (UPA), n=5). Preschool centers were stratified by school size. Although all children within a preschool were exposed to the assigned study condition (SBS-PA or UPA), children within each preschool center were separately recruited to participate in study-related PA assessments. Children were not eligible to participate in PA assessments if they had a condition limiting their participation in MVPA, a condition limiting participation in other portions of the assessment, or if their parent/guardian was unable to read, understand, or complete the informed consent.

The Tutti Fruitti Instant Recess (TFIR) intervention was adapted for preschoolers from the Instant Recess® (IR) program originally designed for adults (11,12).  TFIR is 10-minute PA routines that are designed to engage participates in MVPA by engaging major muscle groups in the upper and lower body. TFIR routines, which are available on DVD, are set to music and designed to be led by teachers (who are watching the video); preschool students follow the teachers rather than watching the video. For the current study, teachers were instructed to implement TFIR during the first 10 minutes of their usual 30-minute gross motor playtime.  For the remaining 20 minutes students engaged in unstructured play. Sixteen TFIR DVDs were rotated weekly throughout the 6-month study; each video was viewed for a total of three weeks during the course of the study. The UPA consisted of traditional long bouts (30?minutes) of unstructured gross motor playtime with typical play equipment. SBS-PA and UPA teachers were asked to repeat their assigned intervention during the morning and afternoon gross motor playtimes, five days/week for six months. Children’s PA was assessed with accelerometers (Actigraph) and direct observation (Observational System for Recording Physical Activity in Children-Preschool Version (OSRAC-P)).

Results
Data was collected in 291 participants (SBS-PA, n=141; UPA, n=150). Participants were 4.1±0.8 years of age with BMI percentile of 68.5 ± 26.7. Study fidelity data indicated that classroom teachers only partially implemented the study as designed. Approximately, 95% of SBS-PA classroom teachers implemented the TFIR DVDs during the first 10 minutes of gross motor playtime. However, only 49% of the SBS-PA classroom implemented the 20-minute gross motor (free playtime) portion of the intervention following TFIR. When gross motor time was implemented it lasted for less than 20 minutes. Compared to baseline, intervals spent in light activity significantly increased in SBS-PA group but did not change in the UPA group. In the SBS-PA group, percent of intervals spent in MVPA increased from baseline to 3-months then decreased at 6-months to baseline values. In the UPA group, percent of intervals in MVPA decreased between baseline and 3-months then increased back to baseline values at 6-months. Significant group by visit interaction was observed for percent time spent in total preschool day MVPA.

Conclusions
The implementation of short bouts of PA can potentially improve preschoolers PA during their classroom setting.

Implications for Practice and Policy
Preschool PA policies needs to be set taking into account the intermittent nature of preschoolers’ play patterns.

References

  1. Ward DS. Physical Activity in Young Children: The Role of Child Care. Med Sci Sports Exerc. 2010.
  2. Oliver M, Schofield GM, Kolt GS. Physical activity in preschoolers: understanding prevalence and measurement issues. Sports Med. 2007; 37: 1045-70.
  3. Ward DS, Vaughn A, McWilliams C, Hales D. Interventions for Increasing Physical Activity at Child Care. Med Sci Sports Exerc. 2010.
  4. McKenzie TL, Sallis J, Elder J, Berry C, Hoy P, Nader P, et al. Physical activity levels and prompts in young children at recess: a two-year study of a bi-ethnic sample. Research Quarterly for Exercise and Sport. 1997; 68: 195-202.
  5. Hollar D, Messiah SE, Lopez-Mitnik G, Hollar TL, Almon M, Agatston AS. Effect of a two-year obesity prevention intervention on percentile changes in body mass index and academic performance in low-income elementary school children. Am J Public Health. 2010; 100: 646-53.
  6. Donnelly JE, Greene JL, Gibson CA, Smith BK, Washburn RA, Sullivan DK, et al. Physical Activity Across the Curriculum (PAAC): a randomized controlled trial to promote physical activity and diminish overweight and obesity in elementary school children. Prev Med. 2009; 49: 336-41.
  7. Mahar MT, Murphy SK, Rowe DA, Golden J, Shields AT, Raedeke TD. Effects of a classroom-based program on physical activity and on-task behavior. Med Sci Sports Exerc. 2006; 38: 2086-94.
  8. Whitt-Glover MC, Ham SA, Yancey AK. Instant Recess(R): a practical tool for increasing physical activity during the school day. Prog Community Health Partnersh. 2011; 5: 289-97.
  9. Yancey AK, McCarthy WJ, Taylor WC, Merlo A, Gewa C, Weber MD, et al. The Los Angeles Lift Off: a sociocultural environmental change intervention to integrate physical activity into the workplace. Prev Med. 2004; 38: 848-56.

 

Support / Funding Source
This work was supported by Robert Wood Johnson Foundation, Active Living Research Grant # 68509.

Authors: 
Sofiya Alhassan, PhD, Ogechi Nwaokelemeh, MS, Cory Greever, MS, & Melicia Whitt-Glover, PhD
Location by State: 
Population: 

After-school Shared Use of Public School Facilities for Physical Activity in North Carolina

Date: 
03/11/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.

Abstract: 

Background and Purpose
Partnerships between schools and other community agencies to share facilities can create new opportunities for afterschool physical activity (PA)[1]. Recently, national organizations (e.g., Institute of Medicine, the American Heart Association, Healthy People 2020, and the CDC) have identified shared use of school facilities as a priority strategy to increase accessible opportunities for physical activity.  However, little is known about the current status of shared use across a large sample of public schools.  Furthermore, while prior studies have identified potential barriers that prevent community organizations from accessing school facilities [1, 2] much of this research  relied on  surveys of a cross-section of school administrators or studies of  single school districts.

Objectives
The purpose of this study was to a) survey all public schools in a State to determine the current status of shared use in public schools at all levels (elementary, middle, high); and b) examine the common characteristics of school shared use and its barriers.

Methods
A survey instrument was designed from previous research on shared use of school facilities for physical activity [1]. The instrument was piloted with 9 public school administrators in a large urban school district.  The final questionnaire included 22 items related to shared use, the specific facilities shared by schools, the type of agreements (formal vs. informal), and common barriers to shared use.  All public elementary, middle, and high schools (N=2,359) in North Carolina were surveyed  for the study.  Each school principal received a pre-survey email from the North Carolina Department of Public Instruction informing them of the forthcoming survey, its importance, and included a request to participate.  The survey was distributed by administering an electronic questionnaire through email.  Respondents received two reminder emails to complete the survey during the first month of the survey being activated.

Results
Responses yielded 1230 useable surveys (52.1% response rate).  88.8% of respondents (n=1092) indicated that school facilities were used by outside/non-school groups or individuals.  The five most commonly shared school facilities were gyms (71.3%), cafeterias (47.1%), baseball/softball fields (34.9%), open spaces (29.7%), and classrooms (26.8%).  The most frequently shared facilities at the 694 elementary schools were the gym (68.2%), cafeteria (45.1%), playground (32.4%), and open space (31.6%).  Middle schools (n=244) were most likely to share the gym (80.3%), baseball/softball field (50.8%), cafeteria (44.3%), and football field (44.3%) and High schools (n=244) shared the gym (71.3%), cafeteria (54.5%), football field (48.8%), and baseball/softball field (43.1%).  Overall, formal written agreements for shared use were more common across all school types and facilities.  When shared used occurred, the percentage of formal written agreements for each school type were 57.5% for elementary schools, 63.9% for middle schools, and 59.6% for high schools. Formal written agreements were more common when schools shared use of gyms (73.8%), football fields (68.7%), baseball/softball fields (65.2%), and soccer fields (63.5%).  An informal or no agreement for shared use was most common with school playgrounds (65.9%), and track (64.9%).  For schools that did not share use of their school facilities (n=135) the most frequent reasons were no outside groups had ever asked to use school facilities (46.3%), followed by availability of facilities (12.0%), design of school facilities (10.9%), facility maintenance responsibilities and costs (10.3%), and liability concerns (9.1%).

Conclusions
Three key findings emerge from the study results.   First, the percent of public schools in North Carolina that indicated they currently allow outside/non-school groups or organizations to use their facilities (88.7%) was much higher that previously reported.  Lee et al., [3] reported that only 59% of schools in a national survey shared school facilities and Spengler et al., [2] found that 69% of responding schools  shared facilities. Second, although shared use of indoor facilities and athletic fields was governed more frequently by formal written agreements, shared use of school playgrounds and track facilities was more frequently permitted with only informal or no agreement for community use. Third, unlike previous research that cites concerns related to increased liability and facility maintenance and operating costs as the most frequent barriers to shared use, we found  that liability and costs were less frequently reported than  lack of community interest in using school facilities and school administrators not knowing where to start.

Implications for Practice and Policy
Findings may be an indication that schools are becoming more accommodating to shared use partnerships.  However, more research on the nature of shared use and types of programs and activities that occur is needed.  Community organizations seeking to use indoor school facilities or athletic fields should be prepared to complete a formal written use agreement.  Finally, a school history of low or no shared use may not be an indication of a school’s unwillingness to allow community use of their facilities.  Preconceived notions that schools are unwilling to share their facilities may be preventing community organizations from initiating contact with school administrators.

References

  1. Kanters, M.A., et al., Shared use of school facilities with community organizations and afterschool physical activity program participation: A cost-benefit assessment. Journal of School Health, in press.
  2. Spengler, J.O., D.P. Connaughton, and J.E. Maddock, Liability concens and shared use of school recreational facilities in underserved communities. Am J Prev Med, 2011. 41(4): p. 415-420.
  3. Lee, S.M., et al., Physicla education and physical activity: Results from the school health policies and programs study 2006. Journal of School Health, 2007. 77: p. 435-463.

 

Support / Funding Source
Funding for this work was made possible by FOA CDC-RFA-DP11-1115PPHF11 from the Centers for Disease Control and Prevention (CDC). The views expressed in written materials do not necessarily reflect the official policies of the DHHS.

Authors: 
Michael Kanters, PhD, Jason Bocarro, PhD, Troy Carlton, MBA, Renee Moore, PhD, & Myron Floyd, PhD
Location by State: 
Study Type: 

The Pros and Cons of the Influence of Joint Use Agreements and Adolescent Physical Activity and Sedentary Behavior

Date: 
03/11/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.

Abstract: 

Background and Purpose
Significant disparities in physical activity and sedentariness are observed across demographic factors, including race/ethnicity and gender. Only 25 percent of urban minority youth achieve the daily PA recommendation, and only 48 percent of boys and 35 percent of girls (aged 6-11) obtain 60 minutes of daily PA, with rates declining to 12 percent of boys and just over 3 percent of girls by ages 12-15. The recent Institute of Medicine report, “Accelerating the Progress in Obesity Prevention” has recommended making schools a focal point for obesity prevention. This focus includes increasing physical activity opportunities before, during and after school hours. As part of this strategy there has been a call to increase joint use or shared use agreements between local communities and school districts.  Many communities, especially those with populations at high risk for obesity, lack recreational facilities and the implementation of joint use agreements is one possible policy solution to provide access to recreational space in these park poor neighborhoods. Research examining the impact of joint use agreements (JUA) on physical activity is limited, but studies show that children with access to existing/renovated school recreational facilities outside of regular school hours are more likely to be active. However, policy strategies are needed to not only increase physical activity, but decrease sedentary activity among youth. Most school districts have JUAs that address recreational use of school facilities, but most of these policies contain vague language or limit the types of shared use and facilities that are available to the public during non-school hours and most assign priority use to school-affiliated groups.

Objectives
The presentation will examine whether stronger, or more specific JUAs are associated with increased physical activity, as well as decreased sedentary behavior in a national sample of adolescents. To our knowledge, this will be the first national study to examine the association between stronger joint use agreements and adolescent activity behavior.

Methods
In 2010 and 2011 data on daily physical activity, sports participation (both school and non-school-based/sponsored), and sedentary behavior (T.V., computer, internet, and other electronic media use) were taken from annual cross-sectional nationally representative samples of 8th, 10th and 12th grade public school students in the US. A total sample of 311 school enrollment zones and 35,000 students were included in the analysis. Two JUA scales were constructed using information obtained from hard copies of corresponding school district JUAs and associated JU-related policies. The scales included provision specifying: 1) what groups had access to school facilities; 2) when they could use the facilities; and, 3) what facilities could be used. The first scale gave priority for facility use to school-based programs and the second one to community organizations (e.g., park and recreation departments, YMCAs, etc.). Multivariate analyses were conducted, controlling for youth and community demographic and socioeconomic characteristics and clustering at the school level. Analyses were also conducted controlling for participation in school-sponsored intramural and extramural sports, as well as the availability of park and recreation department-sponsored and private instructional school physical activity opportunities.

Results
Preliminary results showed more specific JUAs, giving priority to either schools or community organizations, were associated with decreased sedentary behavior in adolescents (OR 0.869, CI 0.78, 0.96).  JUAs were also associated with an increase in the odds of black adolescents moving from being physically active for at least one hour daily 3 days a week to 4 days a week (OR 1.45, CI 1.15, 1.81). Finally, JUAs specifying that community (vs. school) organizations had priority use of facilities outside school hours were negatively associated with school-based sports participation among females students (OR 0.89, CI 0.82, 0.98), even after controlling for school and community-based availability of physical activity opportunities.

Conclusions
This study provides some of the first initial evidence of the association between joint use policies and adolescent physical activity and sedentary behavior.  Results suggest that JUAs can have a positive impact on reducing sedentary behavior and increasing physical activity in certain sub-populations. However, results of this study also suggest that specific provisions in the JUAs could have unintended negative consequences on physical activity opportunities for females; a vulnerable group that has lower levels of physical activity than males, and is in need of creative community-wide strategies to increase activity and reduce sedentary behavior. One possible explanation for these results may be that when community groups have priority use of school facilities, a substitution effect occurs with fewer school-sponsored female sports opportunities being offered.

Implications for Practice and Policy
Results suggest more research is needed to determine the impact, and potential harmful effects more specific JUA provisions may have on vulnerable sub-populations of youth.

Support / Funding Source
The Robert Wood Johnson Foundation and the National Institute of Child Health and Human Development.

Authors: 
Sandy Slater, PhD, Jamie Chriqui, PhD, Frank Chaloupka, PhD, & Lloyd Johnston, PhD
Location by State: 
Study Type: 

Impacts of Objective and Perceived Distance on Walking-to-School Behaviors and Roles of Other Built Environmental Attributes in these Relationships

Date: 
03/11/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.

Abstract: 

Background and Purpose
Walking to school is being promoted as a sustainable and healthy mode of school transportation. Relevant studies have identified distance as the most important barrier, which was captured through either objective (e.g., Geographic Information Systems [GIS]) or subjective measures (e.g., parental report). Perception of distance may be influenced by not only the objective distance but also other built environmental attributes such as pedestrian infrastructure, road characteristics (e.g., traffic volume and speed), safety, and visual quality. Discrepancies have been reported between the objective and perceived distance for general walking behaviors. However, to our knowledge, no previous studies on walking to school have included both objective and perceived distance measures in their analyses. Consideration of both measures can facilitate the understanding of the complex factors influencing walking-to-school behaviors. Relevant results can inform school and community development, as well as promotion of walking-to-school behaviors.

Objectives
This study examined the direct role of objective distance and the mediating role of perceived distance on walking-to/from-school behaviors among elementary school children. It also explored how other built environmental attributes influenced walking to/from school directly and indirectly (through influencing perceived distance).

Methods
The data came from a parental survey of 6,383 elementary school children in 22 diverse neighborhoods in Austin, Texas. It includes information on students’ school travel modes, personal and social factors, and home-to-school travel environment. Perceived distance was captured as a binary variable by asking parents whether they considered the distance to be close enough for their child to walk to school. GIS was used to geocode students’ homes and schools, and to calculate the objective home-to-school distance based on the shortest route. Structural equation models (SEM) were estimated to predict walking to/from school using personal, social, and built environmental factors, including both direct and indirect impacts of distance and other built environmental characteristics.

Results
Among personal and social factors, parental education, car ownership, and availability of school bus service were negative correlates of walking to/from school, while the number of children in household was a positive correlate. For physical environmental factors, perceived distance was a significant mediator between objective distance and walking to/from school. After including perceived distance in the model, the objective distance no longer had a significant direct impact. Instead, it showed an indirect impact, by influencing the perceived distance, which in turn influenced walking to/from school. Perceived distance was influenced by not only the objective distance, but also other built environmental factors, including (1) sidewalk availability and quality, (2) overall walkability (a latent factor captured by convenience of walking to school, maintenance, tree shade, quietness, nice things to see, street lighting, and school zone enforcement), and (3) presence of certain land uses and facilities (busy roads, parks/playgrounds, convenience stores, bakery/café/restaurant, and bus stops) en route to school. Some of these environmental factors (sidewalk availability and quality, overall walkability, and presence of parks/playgrounds and bus stops) did not show direct impacts on walking to/from school, despite their indirect impacts.

Conclusions
These findings revealed (1) the importance of considering perceived distance as a mediator for the impact of objective built environment on walking to/from school, and (2) the significant impacts of not only objective distance but also other environmental factors on perceived distance. Without considering perceived distance, the impact of non-distance environmental factors may be underestimated.

Implications for Practice and Policy
Although distance is the strongest barrier to walking to school, shortening home-to-school distance is going to take long-term efforts in school planning and community development. Meanwhile, improving other aspects of built environments such as pedestrian infrastructure and overall walkability can be more immediate strategies, and may help increase the distance threshold perceived as walkable.

Support / Funding Source
This project is supported by a grant from the Robert Wood Johnson Foundation Active Living Research Program.

Authors: 
Xuemei Zhu, PhD, Chanam Lee, PhD, Chia-Yuan Yu, PhD Candidate, & James Varni, PhD
Location by State: 

Parental Safety Concerns and Active School Commute: Correlates Across Multiple Domains in the Home-to-School Journey

Date: 
03/11/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.

Abstract: 

Background and Purpose
The growing attention on walking to school (WTS), particularly in developed countries, is grounded in the recognition of the importance of physical activity among children who are adopting increasingly sedentary lifestyles [1].  Physical activity has both a positive, direct effect on children’s health and an indirect effect through its role in healthy weight maintenance or weight loss among the overweight [2].  The effect of physical activity on adiposity makes it an essential component in combating the childhood obesity epidemic, and recent studies have documented a positive relationship between WTS and other forms of physical activity [3, 4].

Despite its potential health benefits, rates of WTS have plummeted over the last four decades in the U.S. [5]. Several reasons for this sharp drop have been identified. Two of the most frequently reported barriers to WTS are long distance [6] and safety concerns [7]. Addressing the distance barrier is an important but difficult one, as it requires multi-faceted environmental interventions involving policy changes in land use, school siting, attendance zone, etc. [8]. On the other hand, more readily implementable environmental changes have the potential to address the safety barriers that are related to WTS. While safety concerns are hypothesized barriers to WTS, current research offers little in terms of exploring/explaining the mechanisms through which safety concerns might impact WTS [9].  Therefore, there is need for more focused empirical inquiries into the relationship between these two phenomena.

Objectives
To contribute to the growing yet limited body of literature on safety and WTS, we examined the relationships between WTS and specific measures of road safety (traffic- or pedestrian-related safety concerns) and personal safety (crime-related safety concerns) in a sample of schoolchildren selected from elementary schools across the state of Texas in the U.S. We assessed the associations across multiple environments (home, en-route and school environments) in the home-to-school journey. We also examined the relationships between selected covariates and WTS.

Methods
This cross-sectional analysis examined data from the Texas Childhood Obesity Prevention Policy Evaluation (T-COPPE) project, an evaluation of state-wide obesity prevention policy interventions. All study data were from the survey (n=827) of parents with 4th grade students attending 81 elementary schools across the state of Texas, and living within two miles from their children's schools. Using established and validated survey items, traffic safety and personal safety concerns were captured separately for the three spatial domains: (1) home, (2) en-route to school, and (3) school environments. Parents reported the mode of transportation to and from the school for their children, and answered questions on other potential covariates. Data analysis involved three steps. First, we assessed the relationships between potential covariates and WTS using chi-square tests. Secondly, we examined the relationship between each safety concern variable and WTS, using logistic regression models that produced unadjusted odds ratios. Thirdly, a series of multivariable regression models, controlling for the selected covariates, were performed to examine the association between each safety concern and WTS, independent of the influence of the covariates. All regression results were organized separately into the three spatial domains.

Results
Overall, 18% of parents reported that their child walked to school on most days of the week. For traffic safety, students were more likely to walk to school if their parent reported favorable perceptions about the following items in the home environment: higher sidewalk availability, well-maintained sidewalks and safe road crossings. For the en-route to school environment, the odds of WTS were higher for those who reported "no problem" with each one of the following: traffic speed, amount of traffic, sidewalks/pathways, intersection/crossing safety, and crossing guards, when compared to those that reported "always a problem". For personal safety in the en-route to school environment, the odds of WTS were lower when parents reported concerns about stray or dangerous animals, and availability of others with whom to walk. For the school environment, two traffic-safety variables including sidewalk availability and trees along streets near school were positively associated with WTS, and none of the crime-safety variables were significant.

Conclusions
Findings offered insights into the specific issues that drive safety concerns for elementary school children’s WTS behaviors. The observed associations between more favorable perceptions of safety and WTS provide further justification for practical intervention strategies (e.g., sidewalks, traffic calming devices, crossing guards, stray animal controls) to reduce WTS barriers that can potentially bring long-term physical activity and health benefits to school-aged children.

Implications for Practice and Policy
Public health practitioners, other professionals, and policymakers can: advocate for more sidewalks and traffic calming devices through Safe Routes to School programs, working with neighborhood associations and city government; advocate for additional transportation funds to be dedicated to bike lanes, sidewalks and other environmental changes that encourage bicycling and walking to school; educate school area residents about proper handling of their pets outdoor; and encourage schools to help parents identify safe walking/bicycling routes to and from school.

References

  1. Nelson MC, Neumark-Stzainer D, Hannan PJ, Sirard JR, Story M: Longitudinal and secular trends in physical activity and sedentary behavior during adolescence. Pediatrics 2006, 118:e1627-e1634.
  2. Janssen I, LeBlanc AG: Systematic review of the health benefits of physical activity and fitness in school-aged children and youth. International Journal of Behavioral Nutrition and Physical Activity 2010, 7:40.
  3. Southward EF, Page AS, Wheeler BW, Cooper AR: Contribution of the School Journey to Daily Physical Activity in Children Aged 11–12 Years. American journal of preventive medicine 2012, 43:201-204.
  4. Dollman J, Lewis NR: Active transport to school as part of a broader habit of walking and cycling among South Australian youth. Pediatric exercise science 2007, 19:436.
  5. McDonald NC, Brown AL, Marchetti LM, Pedroso MS: US School Travel, 2009:: An Assessment of Trends. American journal of preventive medicine 2011, 41:146-151.
  6. McDonald NC: Children's mode choice for the school trip: the role of distance and school location in walking to school. Transportation 2008, 35:23-35.
  7. Alton D, Adab P, Roberts L, Barrett T: Relationship between walking levels and perceptions of the local neighbourhood environment. Archives of disease in childhood 2007, 92:29-33.
  8. Lee C, Zhu X, Yoon J, Varni JW: Beyond Distance: Children’s School Travel Mode Choice. Annals of Behavioral Medicine 2013, 45:55-67.
  9. Davison KK, Werder JL, Lawson CT: Peer Reviewed: Children's Active Commuting to School: Current Knowledge and Future Directions. Preventing chronic disease 2008, 5.

 

Support / Funding Source
This study was funded by the Robert Wood Johnson Foundation (Grant ID: 64635) and contributions from The Michael and Susan Dell Foundation, The University of Texas School of Public Health, the Texas A&M Health Science Center (TAMHSC).

Authors: 
Abiodun Oluyomi, PhD, Chanam Lee, PhD, Eileen Nehme, MPH, Diane Dowdy, PhD, Marcia Ory, PhD, Deanna Hoelscher, PhD, & Liza Creel, MPH
Location by State: 
Study Type: 

Quantifying the Full Costs of School Transportation

Date: 
03/11/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.

Abstract: 

Background and Purpose
In the United States, $21.7 billion is spent annually on busing elementary and secondary students to and from school. This amounts to 4.2% of the total funds spent on public education in grades K-12 (U.S. Department of Education, 2011). Declining state and local revenues have made it imperative for school districts to manage transport costs, thereby preserving funding for classroom activities without sacrificing students ability to get to school. Students living within one mile of school are ten times more likely to walk or bike to school than those living more than a mile away (McDonald, et al. 2011). Yet school districts and municipalities regularly make decisions about where to site new schools and make investments in existing schools without fully understanding the impact of these decisions on overall transportation costs. Thus, the fact that current school location optimization algorithms only consider the cost of busing children to school is significant. This approach fails to recognize opportunities to locate schools in places that maximize active transportation potential and to consider tradeoffs between land values and transport costs.

The goal of this study is to document the full cost of getting children to school and develop a decision support tool to help transportation and school planners minimize transport costs when siting or improving schools. The multi-modal transportation costs are being rigorously studied at elementary schools in Florida and North Carolina. The variation in costs will be analyzed in relation to the school’s location type and its proximity to students. This will allow the researchers to develop a pilot decision support tool to estimate transportation costs of potential school sites.

This study will provide the first published evidence regarding the full cost of school transportation across all modes and including upfront and ongoing costs. This quantification will allow researchers and practitioners to consider how school site selection, investment in pedestrian and bicycle infrastructure near the school, and local residential development patterns impact costs. A better understanding of these costs will allow practitioners to economically justify siting decisions which consider the viability of active school transportation.

Description
The individual capital and operations cost items for each primary mode of transportation—automobile, school bus, bike, and walking—were identified to allow for the consistent collection of data between states and school districts. Eight public elementary schools were selected from Florida representing urban and suburban environments both in areas with high and low densities of student populations. The same criteria were used to select 12 schools in North Carolina, with the addition of four schools representing rural environments. School districts, published reports, and professionals associated with the design and planning of the study schools will be consulted to gather cost and other relevant information. A school site visit was conducted to determine the travel mode split at each study school. Based on these results, the researchers will develop a pilot decision support tool which will assist transportation and school planners in determining estimated transport costs by mode for proposed school locations.

Lessons Learned
Data collection is currently ongoing. Preliminary findings suggest that schools located in higher density areas have lower school transportation costs and higher active transportation mode shares. The pedestrian infrastructure around schools is another important factor in assessing the likelihood of transport at a school.

Conclusions and Implications
We anticipate documenting variation in school transportation costs in aggregate and by mode based on school location. We hypothesize that schools located in more developed areas will have lower transport costs due to a more compact distribution of students. However, we expect to find schools with more students living nearby have lower transport costs than schools located on parcels away from residential areas. Such a finding would have important implications for practitioners. In general, land at the periphery of communities away from residential development is cheaper. This research will give planners a way to assess tradeoffs between land values and transport costs and potentially justify school siting decisions that incorporate a location’s suitability for active transport.

Next Steps
By the time of the conference, analysis of the costs of school transportation data will be complete.  The decision support tool will be in development.

References

  1. McDonald, Noreen C., Austin L. Brown, Lauren M. Marchetti, Margo S. Pedroso. 2011. U.S. School Travel, 2009: An Assessment of Trends. American Journal of Preventive Medicine 41 (2): http://dx.doi.org/10.1016/j.amepre.2011.04.006.
  2. U.S. Department of Education, National Center for Education Statistics. Table 2: Current expenditures for public elementary and secondary education, by function, subfunction, and state or jurisdiction: Fiscal year 2009. 2011 [cited February 13, 2013]. Available from http://nces.ed.gov/pubs2011/expenditures/tables.asp.

 

Support / Funding Source
This research is being conducted with funding from the Southeastern Transportation, Research, Innovation, Development and Education Center (STRIDE) and Active Living Research.

 

Authors: 
Noreen McDonald, PhD, Ruth Steiner, PhD, Mathew Palmer, MCP, & Benjamin Lytle, BA
Location by State: 

Participatory Action Research to Improve Physical Education in San Francisco Public Schools

Date: 
03/11/2014
Description: 

Presentation at the 2014 Active Living Research Annual Conference.

Abstract: 

Background and Purpose
The Institute of Medicine recently identified physical education (PE) as an optimal strategy to improve current youth physical activity levels, as PE provides an ideal opportunity for all students to be physically active.(1-3) In California, education policy requires that elementary students receive 200 minutes of scheduled PE every 10 days.(4) However research in California has shown suboptimal compliance with PE policy and has demonstrated that disparities exist, with schools in non-compliant districts having a significantly greater proportion of students who qualify for free or reduced-price meals.(5) To our knowledge, no research has identified best practices for ensuring compliance with state PE mandates.  Strategic alliances, based on the strengths of collective action, represent groups of organizations voluntarily collaborating to address problems that are too large or complex for any one organization to solve independently.(6) Utilizing local resources and harnessing collective interest, we formed a strategic alliance (between the school district, Department of Public Health (DPH), and a research university) in order to assess local PE practices in the San Francisco Unified School District (SFUSD).  The primary goal of the alliance was to improve adherence to state PE policy mandates. Analyzing the process by which strategic alliances facilitate change, as well as the barriers and facilitators that impact such change, may help improve community health.

Objectives
To detail the alliance’s actions to improve PE; to describe the impressions of those efforts on district- and school-level (systems-level) change in PE; and to identify lessons learned that could aid future alliances in achieving greater PE policy compliance.

Methods
Semi-structured interviews with 7 alliance members, 20 principals, and 50 teachers in 20 randomly selected elementary schools, 3 years post-alliance formation.  All interviews were audio recorded, transcribed, and coded using a combination of the constant comparative method (to generate new grounded theories from the data) and a thematic analysis approach to segment, categorize, and link aspects of the data based on pre-determined theories, before final interpretation of the data.(7)

Results
Interviewees reported district-level increases in priority and funding for PE post-alliance’s actions. Collecting and disseminating local data contributed to the alliance’s achievements. Alliance members, principals, and teachers discussed the critical role funding plays in PE implementation and identified insufficient funding as a barrier to successful PE implementation. Interviewees described a lack of significant changes in rules and regulations regarding PE at the district-level.  All of the alliance partners cited the clear identification of common goals and trust between SFUSD, the DPH, and the university as keys to the alliance’s achievements; differences in communication styles and differing opinions on best methods for disseminating data were identified as challenges.

Conclusions
Increasing PE will benefit children’s health, but creating change within a school district is complicated.  Alliances may be a way to increase compliance with health policy; bringing together multiple partners with differing perspectives but shared interests may support action from multiple directions. Local data can be useful in clarifying and promoting discussions at a district level, yet school-level change may take longer to occur and may necessitate formally increasing accountability for PE at the district or state level. Future research should focus on methods to realistically and cost-effectively increase PE policy compliance, thereby increasing access to regular physical activity for youth.

Implications for Practice and Policy
School-level changes in PE policy compliance may be linked to district- or state-level accountability measures and may take longer to implement than district-level change. Further research on increasing PE policy compliance at the school-level is needed, and could include examining efforts increase the academic priority for PE by making it a core competency with common assessments, or including PE minute compliance as part of state-wide school success measures (like California’s Academic Performance Index score, which measures the academic performance and growth of schools).

References

  1. Institute of Medicine. Educating the Student Body: Taking Physical Activity and Physical Education to School. Concensus Report. May 2013.
  2. Trudeau F, Shephard RJ. Contribution of school programmes to physical activity levels and attitudes in children and adults. Sports Med. 2005;35(2):89-105.
  3. Madsen K, Gosliner W, Woodward-Lopez G, Crawford P. Physical activity opportunities associated with fitness and weight status among adolescents in low-income communities Arch Pediatr Adolesc Med. 2009;163(11):1014-1021.
  4. California State Board of Education Policy # 99-03. Education Code Section 51210. June 1999. Available at: http://www.cde.ca.gov/be/ms/po/policy99-03-june1999.asp.
  5. Sanchez-Vaznaugh EV, Sanchez BN, Rosas LG, Baek J, Egerter S. Physical Education Policy Compliance and Children's Physical Fitness. American journal of preventive medicine. May 2012;42(5):452-459.
  6. Wohlstetter P, Smith J, Mallory CL. Strategic alliances in action: toward a theory of evolution. The Policy Studies Jouranl. 2005;33(3):419-442.
  7. Grbich C. Qualitative data analysis : an introduction. London ; Thousand Oaks, Calif.: SAGE Publications; 2007.

 

Support / Funding Source
California Obesity Prevention Program and the SFUSD Public Education Enrichment Fund.

Authors: 
Hannah Thompson, MPH, Robin Haguewood, MPH, Nicole Tantoco, BA, & Kristine Madsen, MD, MPH
Location by State: 

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