1. education
2. school

School Wellness Policies: Promoting School Health Councils and Local Wellness Policy Implementation
Erika Profili,
1,2
BS ;
Diana Rubio,
1 University
1
BS ;
Stewart Eidel,
3
MS ;
Megan Lopes,
3
MPH ;
Lea Jaspers,
3
MS ;
Erin Penniston,
4
MSW ;
Brit Saksvig,
5
PhD ;
Maureen Black,
1
PhD ;
Erin Hager, PhD1.
of Maryland School of Medicine, 2 George Mason University, 3 Maryland State Department of Education, 4 Maryland Department of Health and Mental Hygiene, 5 University of Maryland, College Park
Background
•Written Local Wellness Policies (LWPs) are federally mandated in school systems to
enhance opportunities for healthy eating/physical activity among students1, 2 .
•Schools are encouraged to form school-level School Health Councils (SHCs) or
wellness committees to oversee LWP implementation.
•Little is known about how SHCs are operationalized or relations between having an
active SHC and LWP implementation.
Results
•Mean active SHC score 2.6 (SD=1.4, range 0-5). LWP implementation categories:
no (19.6%), low (36.0%), high (44.4%).
•26% of schools majority low-income (>75% of students eligible for Free-orReduced-Price Meals).
Methods
•2012-2013 Maryland Active Living/ Healthy Eating in Schools Wellness Polices &
Practices Survey
•Online survey on 2012-2013 activities, based on the School Nutrition Policies and
Practices Survey (Schwartz, 2011), Maryland Wellness Policy Implementation Checklist
(MSDE), SMART administrative review (USDA), Alliance for a Healthier Generation
school wellness criteria, and wording from the Healthy Hunger Free Kids Act
•Sent via e-mail to school administrators (n=1349, response rate=55%)
•Sample:
•42% had a SHC
•School-level implementation of wellness policies and practices
•17-item scale
•Cronbach’s alpha=0.923
•Scored in 3 categories-no, low, high implementation
School demographic data: provided by State Department of Education
• “Active SHC score”
•5 constructs (scored 0/1), summed, higher score=more activities
•set goals for healthy eating and physical activity
•met >4 times during 2012-2013 school year
•members include >3: administrator, PE teacher, cafeteria manager, school nurse
•members include parent and/or student
•activities publicly available (website, PTA meetings, or e-mail).
•Analysis Plan
•Chi-Square
•ANOVA (LSD post-hoc testing)
•Multi-level multinomial logistic regression (adjusting for clustering within school
systems and majority low-income student body).
Criteria: 1 point if met
Goals for healthy eating Yes
and physical activity?
How frequently did you >4x/year
meet?
At least 3 of the following:
Composition: school
Administrator, PE teacher, Nurse,
Food Service
% endorsed
66.9%
none
School-Level LWP
Implementation
low
high
χ2 (p)
61.0%
59.5%
75.4%
None versus low Implementation
Likelihood
Ratio
p-value
0.96
Majority Low-Income 1.48
Student Body
45.8%
35.6%
42.3%
52.9%
.055
46.9%
44.3%
38.4%
55.1%
.028
Parent and/or Student
31.2%
24.6%
25.9%
38.4%
.049
How public is informed
Website, newsletter, PTA meetings
71.4%
70.5%
63.4%
78.3%
.035
TOTAL SCORE
Mean=2.64, SD=1.40
Range: 0-5
2.41
2.31
3.00
F=8.984
P<0.001
Blue font indicates significance, p<.05
•Based on the chi-squared analyses schools that met more criteria were more likely to be
in the high implementation group. Each of the 5 criteria had a significant correlation to
LWP implementation. (Table 1)
•Figure 1: School-Level Implementation of Wellness Policies and Practices by Having a
School-Level SHC in Place
3.5
3
2.5
2
1.5
1
0.5
0
3.00
2.41
SHC Score
None versus high Implementation
95% C.I.
Likelihood
Ratio
p-value
95% C.I.
0.700
0.76, 1.21
1.39
0.006
1.10, 1.75
0.260
0.75, 1.21
2.05
0.039
1.04, 4.06
.017
Composition: families
Active SHC Score
Hypothesis: schools are more likely to implement wellness policies and practices
when they have an active school health council that:
• sets goals for healthy eating and physical activity
• meets at least 4 times per school year
• has at least 3 of the following on their school health council: administrator, PE
teacher, cafeteria manager, school nurse
• has a parent or student on their school health council
• inform stakeholders of activities through a website, newsletter, or PTA meetings
Table 2: SHC score based on school-level implementation with adjusting for clustering
Table 1: School-level implementation based on SHCs meeting certain criteria
Objective
To examine factors associated with having an active SHC and to determine if
having an active SHC is associated with greater school-level LWP
implementation.
Results (Continued)
2.31
• Adjusted multi-level models revealed for every one-unit increase in SHC score,
schools are 39% more likely to be in high implementation group (p=0.006). (Table 2)
•Schools without a majority low-income student body are 2.05 times more likely to be
in the high implementation group compared to the no implementation group. (Table
2)
Conclusions/Implications
•Schools with an active SHC have a higher likelihood of LWP implementation.
•Interventions that focus on the formation and maintenance of active SHCs are likely to
increase LWP implementation.
•Federal/State Departments of Education and school systems should support the
establishment of school-level school health councils to enhance implementation of
LWPs in schools.
•School systems can encourage LWP implementation in schools through promoting
school-level actions (setting goals, having SHCs meet frequently, communicating to the
community, etc.).
•Schools with majority low-income student body are less likely to implement LWPs, and
may benefit from assistance in establishing active SHCs.
References
• Child Nutrition and WIC Reauthorization Act, Pub. L. No. 108-265, § 204, 118
Stat.729, 780-781 (2004).
• Healthy, Hunger-Free Kids Act of 2010, Pub. L. No. 111-296, § 204, 124 Stat.
3183,3236-3238 (2010).
Funded by:
No
Low
High
Implementation Implementation Implementation
Based on the ANOVA analyses the mean active SHC score differed by LWP implementation
category (F=8.98, p<0.001). Schools with no and low-implementation had significantly
lower SHC scores than schools with high implementation (2.41 and 2.31 versus 3.00,
p=0.015 and p<0.001, respectively). (Figure 1)
Primary funding support: (1) Centers for Disease Control and Prevention, Cooperative Agreement #5U58DP003497; (2) Centers
for Disease Control and Prevention, Prevention Research Centers Program Cooperative Agreement #U48 DP001929 and Special
Interest Project #12-062 with the University of Maryland Prevention Research Center; (3) National Institute of Child Health and
Development K12 HD 43489. This has been prepared solely by the authors independent of the supporting agencies and may not
represent the official positions of these agencies.
Supported in part by: (1) NIA Short-Term Training Program on Aging Grant T35AG036679 to the University of Maryland School
of Medicine; (2) University of Maryland School of Medicine Summer Program in Obesity, Diabetes and Nutrition Research
Training (SPORT), NIH Grant #5 T 3 5 D K 0 9 5 7 3 7; (3) Mid-Atlantic Nutrition Obesity Research Center (NORC) Summer
Research Program, under NIH Grant #P30 DK072488.
Erika Profili
Contact Information:
[email protected]
443-421-8430