Texas Childhood Obesity Prevention PolicyEvaluation (T-COPPE Project): Baseline datafrom Safe Routes to School Policy evaluationCo-Leads:Deanna Hoelscher, PhD, RD, LDMarcia G. Ory, PhD, MPH
Presentation Overview¨ Why are we doing TCOPPE? ¨ Background and rationale¨ What are we doing? ¨ Methods¨ What did we find? ¨ Results¨ What does it all mean? ¨ Discussion
The Rule of 2s¨ Two policies to evaluate ¤ Both aspects of the energy equation: activity and nutrition • Safe Routes to Schools (SRTS) • WIC ¤ Two environments • School/home environment • Grocery stores/home ¤ Two functional timelines • School year • Year round
Slide 2 of 2s¨ Two state universities in a unique and effective working relationship… ¤ The University of Texas School of Public Health ¤ Texas A&M (Health Science Center School of Rural Public Health)¨ Two rivalries……
Why Evaluating Childhood Obesity &Prevention Policies? National ¨ Robert Wood Johnson Foundation is impact… committed to reducing childhood obesity starts with by 2015 evidence of ¨ There are a number of national policies local impact identified as aimed at reducing childhood obesity (i.e., SRTS) ¨ Which of these national policies are actually shown to be effective in reducing childhood obesity? ¨ What is the impact of implementing these national policies locally?
How did we select our policies?¨ Potential for evidence of effectiveness¨ Political feasibility ¤ Potential for leadership engagement ¤ Champions identified in Texas Legislature and State Government¨ Public Acceptability ¤ Readinessand feasibility in implementation ¤ Documented history of obesity efforts during last decade
How did we select our policies? (cont.)¨ Partnership support ¤ LiveSmart Texas coalition development/support ¤ Partnership for a Healthy Texas¨ Policy sustainability
Standardized Mode of TransportationTrips to School, 1965-2005 Source: McDonald, N.C. 2007. American Journal of Preventive Medicine
Walking/Biking by Distance to School,1965-2005 Source: McDonald, N.C. 2007. American Journal of Preventive Medicine
Active Commuting to School¨ Current childhood obesity epidemic¨ Children are not meeting current recommendations for physical activity¨ One strategy to increase physical activity among children: ¤ Walking or biking to and from school (Active Commuting to School or ACS)¨ Currently, approximately less than 16% of children use ACS
Safe Routes to School Policy¨ SAFETEA-LU ¤ 2005 Federal Transportation Bill ¤ % of nation s total children K-8 to offer increased physical activity through health alternatives to bus and car school transportation ¤ Texas received about $40 million in Safe Routes to School (SRTS) funding between 2005 and 2009¨ State support for SRTS ¤ In September 2007, The Texas Transportation Commission approved $24.7 million for 244 projects in 66 communities throughout the state ¤ Supplemented by revenue from the God Bless Texas and God Bless America specialty license plates ¤ Funds administered through grant process Source: Tx DOT, 2008
Texas SRTS PolicySRTS ¨ For Texas, two major types of grants were awarded:Education ¤ Construction (Infrastructure) grants, whichEnforcement include brick and mortar type projects,Encouragement such as construction of crosswalks, sidewalks, etc.Evaluation n Schools need to have a SRTS plan in placeEngineering first ¤ Planning grants, which include a SRTS plan, which may or may not include potential infrastructure changes or implementation of the plan.
Methods ¨ PurposeMeasures: ¤ Todetermine the effects of differing• Student (4th allocation methods of fundinggrade) survey (construction versus planning grants)• Parent survey from the Texas Transportation Commission on parent attitudes &• ACS behaviors.• School Checklist ¨ Natural experiment• Campus Policy ¤ Quasi-experimental• School Audit ¨ Initial study assumptions ¤ Foractive commuting to schools (ACS), construction (infrastructure) schools > planning schools > comparison schools
MethodsBaseline ¨ Funded schools were selected for measurement based on funding type,data location (urban/rural), race/ethnicity, andcollected socioeconomic status (SES); comparisonin 2009 schools had similar characteristics but received no funding. ¨ Data were analyzed using mixed linear regression and controlled for random and fixed effects, and other independent variables.
SRTS Baseline DataSchool Survey Status Infrastructure Planning Control Total Schools Schools SchoolsMeasured Spring 2009 11 13 13 37Measured Fall 2009 14 9 21 44Total 25 22 34 81 Survey Activity Total (to date) Student Survey 3315 Parent Survey 2057 Parent/Student Survey 1653 Combination Active Transport Count 12,167 Environmental Audit 79 * * Two school environmental audits were not done due to safety concerns for the auditors
Demographic Variables by SchoolCondition (n = 81)Variable Construction Schools Planning Schools (n Comparison Schools (n = 25) = 22) (n = 34)Student Male (%) 49.9 51.9 47.5Parent race/ethnicity White (%) 19.8 30.3 24.3 Other (%) 80.2 69.7 75.7Economically 75.5 65.8 68.3disadvantaged (%)All family members 64.1 55.3 57.7born in USA (%)Mean time to school <5 m (%) 27.0 28.5 20.6 5-10 m (%) 38.5 39.3 36.2 11-20 m (%) 20.9 20.3 25.5 >20 min (%) 13.6 11.9 17.6
Baseline Rates of Active Commuting to School (ACS), n = 79 ACS in 1969 (48%)Mean % ACS *Means are signiﬁcantly diﬀerent from comparison schools (p<0.05) Ac>ve Commu>ng is 2-‐day self-‐reported walking or biking to or from school Analyses are controlled for % economically disadvantaged, % white, mean precipita>on, mean heat, mean wind speed.
Mean Active Commuting to SchoolBefore School After School Mean ACSn=79 n=79 n=7910.4% 17.1% 13.8%Analyses were conducted using Mixed Effects Linear Regression
School Environment (Rural)¨ School in rural area.¨ Only 2 segments indicated on audit tool. ¤ One was a one-lane gravel road that separated school property from a corn field.
School Environment(Urban) Planning school Planning school
Environment Comparisons¨ Construction school with gate¨ Planning School with crosswalk, sidewalks, signage
Environmental Comparisons¨ Comparison School¨ Planning School
Differences in Parent Attitudes &Behaviors by School Types at BaselineVariable Construc0on Schools Planning Schools Comparison Schools Mean (SD)* Mean (SD) Mean (SD) n = 25 n = 22 n = 34 Asking Behavior Scale 1.11 (.09) 1.29 (.10)a .98 (.08)a Parent Self-‐Eﬃcacy Scale 18.6 (.4)a 20.4 (.5)ab 18.7 (.4)b Parent Outcome 13.9 (.2) a 14.7 (.2) ab 13.7 (.2) b Expecta>ons Student Self-‐Eﬃcacy Scale 27.2 (.5) a 27.2 (.6) b 24.7 (.5) ab Arrived Walking (%) 10.5 (1.5) a 9.1 (1.7) b 4.6 (1.3) ab Arrived Biking (%) 0.5 (0.6) a 2.5 (0.6) ab 0.5 (0.5) b Arrived by School Bus (%) 16.4 (4.1) a 14.0 (4.5) b 26.9 (0 ab 3.5)TV on during evening meal 3.51 (.11) a 3.14 (.12) ab 3.58 (.09) b TV >me on weekends 4.49 (.07) 4.32 (.08) a 4.59 (.06) a School level analyses using weighted UNIANOVA
What Factors are Associated withWalking or Biking to School (Child)?Factors NOT ¨ Students who walked or biked to schoolAssociatedwith ACS: were more likely to: ¤ Have a friend who walked or biked to• Screen time school• Days PA ¤ Have self-confidence that they could walk• Safety to school• Social ¤ Feel that they could ask their parents tosupport walk or bike to school• Attitude
What Factors are Associated withWalking or Biking to School (Parent)?¨ Parents more likely to let their children commute to school: ¤ Had higher self-efficacy (self-confidence) in letting their child walk to school ¤ Perceived better walkability around their house and their child s school ¤ Were more likely to let their children walk to other places from school ¤ Reported better outcomes associated with walking to school (e.g., children would be healthier) ¤ Reported fewer barriers to commuting
Does weather influence ACS?¨ Students decrease ACS in the morning due to precipitation (marginally significant, p- value=0.099)¨ When the morning temperature was warmer, ACS was higher (p-value=0.019) ¤ Morning temperature range = 10.4-89.6 degrees Fahrenheit¨ Analysis ¤ Covariates in the Mixed Effects Linear Regression Modeling of ACS
Implications¨ Number of children walking or riding a bike to school was low¨ We need policies that promote environments that are conducive to walking and biking¨ We need safety and perception of safety
Policy Implications¨ Many parent-related variables were consistent with ACS ¤ Parents are highly motivated to participate and be engaged ¤ Parents made a point to contact both PI and Project Director to express interest and ask how else to be involved¨ Need programs that focus on parent education¨ Need programs that make neighborhoods safer (e.g., benefits of complete streets)
Conclusions¨ Significant differences were seen in ACS between planning/construction and comparison schools ¤ Outcome expectations, self-efficacy, TV ¤ Grant application process encouraged schools to collect pilot data n Smaller grants (planning grants) may be as effective in getting ACS as larger grants (construction grants) initially n Grant processèAwarenessèMore likely to engage in ACS? n More likely to have a program champion? n Planning schools had greater percentage of children who biked¨ Allocation of resources may be given to schools who are already working on SRTS ¤ How do we reach other schools?
Conclusions¨ Child behaviors associated with walking & biking to school included asking behaviors & having friends commute¨ Programs like SRTS increase walking and bike riding
Why School Audits?¨ Important role of the built environment in promoting WTS.¨ Recognition of the many micro-scale and modifiable barriers at/around schools.¨ Importance of the context-specific and detailed environmental features in changing school travel behaviorsà Lack/shortage of instruments designed to capture school environments systematically and comprehensively
Audit Components and ItemsFORMAT: Letter-size sheets with checklist, rating, closed-end choices, a nd mapping itemsCOMPONENTS: A. STREET AUDIT B. SCHOOL SITE AUDIT C. MAP AUDIT – sidewalk, bike lane, drainage ditch, buffer, tr ail, crosswalk, and bus stop § Land Uses § Street/traffic/parking conditions § Lighting , other amenities, and sigs § Unattractive items § Perceptual rating items (surveillance, maintenance, cleanliness, vis ual quality, safety and attractiveness)
Street Segment Audit• Audit info. • Segment Image - Auditor info. - Indicating each - Date, weather segment - Start/end time - North up - Street name • Perceptions• Audit Items - For objective observations • Map Audit Indic ators - If related items present, go to Map Audit(s)
School Site Audit • School Site Ima ge - Indicating School site and• Frontage property line - Maine entry - Street facing - Vehicular and pedestrian entries • On-site facilities - Physical features• Main entry - Amenities, etc. - Amenities around main entry • D/P Area - Location, types, and capacity
AnalyzingSchool Audit Data zPreliminary Results
Descriptive Findings from 79TCOPPE Schools audited across TexasStreet & Map Audit ElementsRequiring Improvements:¤ Bike lanes (98% lacked)¤ Benches and trash cans (96%)¤ Traffic calming devices (85%)¤ Unattractive items/social disorder (75% with 1+)¤ Street lights (25% lacking)¤ Sidewalk obstructions (many with poles, parked cars, mail boxes, etc.)
Descriptive Findings from 79TCOPPE Schools audited across TexasSchool Site Audit Elements Requiring Improvements:¤ Designated drop-off/pick-up area (21 lacked)¤ Adjacency to vacant/abandoned/undeveloped areas (19 schools)¤ Lack of walkway connections to school buildings (14 lacked)¤ Trails/paths within campus (73 lacked)
Frontage Street Audit Items Correlated with % WalkersVariables B Sig.Presence of sidewalks 10.996 0.001Presence of street parking 7.143 0.012Presence of vacant areas -6.999 0.022Presence of unattended/stray -8.358 0.050dogsPresence of drainage ditches -6.853 0.047Surveillance* 2.030 0.058Safety in walking* 3.033 0.013Safety in bicycling* 3.453 0.008Attractiveness in walking* 2.459 0.048Attractiveness in bicycling* 2.451 0.047 *likert-type scale item (1 being poor to 5 being excellent)
Other Street Audit Items Correlated with % WalkersVariable B Sig.Number of 4 – 10 7.090 0.055intersections* 11+ 6.194 0.064Number of street 1-3 6.854 0.037lights** 4+ 4.202 0.247Presence of street parking 4.628 0.094Presence of street calming -7.178 0.019devicesPresence of safety/child 7.943 0.006crossing signPresence of landscaped buffer 7.642 0.008Presence of drainage ditch -5.094 0.096Presence of crosswalk 6.308 0.081 * The reference category is 0-3 driveways. ** The reference category is 0 street light.
School Site Audit ItemsCorrelated with % WalkersVariable B Photograph by Yang Mi Kim Sig.Number of school bus only entry & exit -2.717 0.051Number of pedestrian only entries & exits 1.562 0.028Presence of vacant area -7.179 0.029Presence of sidewalk/walkway connection 9.234 0.016Presence of private car area -7.163 0.050Presence of basketball/tennis/volleyball court 7.147 0.006Presence of baseball/football/soccer field -6.616 0.016Presence of outdoor swimming pool 5.427 0.056Presence of bench / seating 6.411 0.019Presence of picnic table 7.604 0.015 * The reference category is none of evergreen tree.
Conclusion¨ This School Audit Instrument is a tool that can provide effective and efficient assessments of street and school site environments, focusing on those attributes related to children s active transportation to school.¨ The instrument s three components help objectively identify many easily modifiable elements, facilitating policy development toward creating safe and walkable communities.¨ With proper training, this audit can be used for education, research, intervention, and policy-support purposes.¨ The instrument can be shortened and customized, once more data are collected from diverse communities.
Multi-pronged Support andDissemination System…¨ Partnership with Texas Health Institute part of initial funding proposal with expectation of ¤ Legislative policy forums in years 1, 2, 3 and 5 of the grant ¤ Sharing activities and findings in real time¨ Support and advisement from Texas Obesity Policy Research Advisory Council (TOPRAC) whose mission is ¤ To provide health policy research, translation, evaluation, and dissemination support to TCOPPE and Live Smart Texas¨ Regular feedback to Live Smart Texas (LST) collaboration ¤ Texas coalition working collaboratively on obesity prevention efforts and the development of resources to fund it ¤ TCOPPE is LST s first major research project¨ Respond to opportunities as they arise and are appropriate
Additional opportunities…¨ Testimony to the Institute of Medicine on Childhood Obesity Prevention workshop in Texas, February 2009¨ Annual participation in the Texas Obesity Awareness Week events at the Texas Capital¨ Invited testimony to Texas legislative committees on the state of obesity in Texas¨ Development of a Strategic Communications Plan ¤ Intensive communications workshop provided by RWJF to selected individuals ¤ To provide focus and benchmarks for monitoring success and outlining timely policy forum opportunities
Conclusions¨ Close collaboration and communication with stakeholders at multiple levels¨ Dissemination throughout the project¨ Establish team of credible experts who can inform and educate legislators—the go to team¨ Policy makers knowledgeable about issue before research conclusions are made/available
It takes more than a Village todo this Texas-sized project… It takes a TEXAS-sized team… ¤ Roy Allen ¤ Jingang Miao ¤ Heather Atteberry ¤ Lisako McKyer ¤ Chester Bryant ¤ Hyung Jin Kim ¤ Arthur Castro ¤ Deb Kellstedt ¤ Yichen Cheng ¤ Tiffni Menendez ¤ Diane Dowdy ¤ Marcia Ory ¤ Sandra Evans ¤ Courtney Peterson ¤ Kyna Farmer ¤ Mike Pomeroy ¤ Selina Guerra ¤ Donna Nichols ¤ Emily Hines ¤ John Reilly ¤ Deanna Hoelscher ¤ Tina Simms ¤ Leah Kolar ¤ Carolyn Smith ¤ Pat Koym ¤ Christine Tisone ¤ Chanam Lee ¤ Suojin Wang ¤ Kris Lykins ¤ Pete Walton ¤ Jay Mendoza ¤ Jerri Ward ¤ Ann Mesaros ¤ Cheryl Brien-Warren
AcknowledgementsThis work was partially supported by three Robert WoodJohnson Foundation grants (64634, 63755, 65539).We would like to thank:n Arthur Casto for his help with the audits.n Jun Hyun Kim, Carolyn Smith, Ashley Wilson, and Chelsea Mounce for the valuable inputs during the instrument development phases.n Dr. Woosung Lee for his help with the data analyses.To request a copy of the instrument & manual, pleasecontact Diane Dowdy, PhD, TCOPPE Project Director: Dowdy@srph.tamhsc.edu
Current Stats: The Walking School Bus and ChildrensPhysical Activity Study¨ Objective: Evaluated a walking school bus program on active commute and moderate to vigorous physical activity (MVPA)¨ Intervention: Walking school bus (a group of children led by an adult to and from school ) ¤ Intervention group: n=4 schools; 70 4th graders ¤ Control group: n=4 schools; 79 4th graders ¤ 76% of total students from low-income families (<= $30,000) ¤ 91% of students Hispanic; 47% of students Black¨ Measures: self-questionnaire and accelerometry at Time 1 and Time 2¨ Results: ¤ Intervention group increased daily minutes of MVPA from 46.6 +/- 4.5 at Time 1 to 48.8 +/- 4.5 at Time 2 ¤ Control group decreased daily minutes of MVPA from 46.1 +/- 4.3 at Time 1 to 41.3 +/- 4.3 at Time 2 Source: Mendoza JA, et al. Pediatrics, 2011.
The Walking School Bus and Childrens PhysicalActivity Study: continued¨ Objectives: ¤ Evaluate the feasibility of a protocol to measure changes to children s pedestrian safety behaviors ¤ Evaluate the potential influence of the WSB program, neighborhood safety, and intersection characteristics on children s pedestrian safety behaviors at the school-level¨ Intervention group: Taught and modeled safe pedestrian behaviors during walks from trained staff members¨ Control group: Received usual information from school district about school transportation¨ Results: impact on pedestrian behaviors is unknown ¤ Child pedestrians at the intervention schools had a five- fold higher odds of crossing at the corner or crosswalk compared to pedestrians at control schools ¤ Child pedestrians at the intervention school also had five-fold lower odds of stopping at the curb versus control schools Source: Mendoza JA, et al. Health Place, 2012.
Methods¨ Baseline data collected for T-COPPE Study th¨ 4 grade students and parents were recruited through 81 schools¨ Active Transport Survey/Counts ¤ Collected in classrooms ¤ 2-day self-report ¤ Validated instrument