“Just the Facts”…Leveraging Research to Promote Active Living in Army Communities
James Sallis, PhDSan Diego State Universitywww.drjamessallis.sdsu.edu
For Army MWR ConferenceLouisville, KY 1/26/10
Goals for this Talk
• You leave with new ideas, based on research, to promote physical activity on your base to enhance MWR.
• You are prepared to identify new partners to help you achieve your mission.
• Take lots of notes.
3Four50.com
• Oxford Health Alliance's key message: • 3 risk factors –
– tobacco use, poor diet, lack of physical activity
• Contribute to Four chronic diseases – – heart disease, type 2 diabetes, lung disease
and some cancers
• Which, in turn, contribute to more than 50 per cent of deaths in the world
Deaths (thousands) attributable to individual risk factors in both sexes
0 50 100 150 200 250 300 350 400 450 500
Low dietary polyunsaturated fatty acids
Low intake of fruits and vegetables
Alcohol use
High dietary trans fatty acids
Low dietary omega-3 fatty acids
High dietary salt
High LDL cholesterol
High blood glucose
Physical inactivity
Overweight-obesity (high BMI)
High blood pressure
Tobacco smoking
Danaei G et al, PLoS Medicine, 2009
49%
35%
10%
3.4%
10%5.4%
0%
20%
40%
60%
6-11 12-15 16-19
Age
Percentage of youth ages 6-19 meeting 60 min/day physical activity guidelines.
Based on accelerometers. NHANES 2003-4
Males
Females
Troiano, MSSE 2007
What is being done to improve PA?
• Minor investment in programs• Guided by theories that emphasize
psychological & social influences• Primary goals are education and
behavior change skills training targeting individuals
• Fragmented, poorly coordinated, poorly funded approaches
Psychosocial Models of Health Behavior
IndividualBiologicalPsychologicalSkills
Social/Cultural
How is it working?
Source: Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance System
Will individual interventions ever be sufficient?
Interventions based on psychosocial theories can be effective
But not sufficientReach is limitedEffects are modestMaintenance is rare
Programs are not designed to change the root causes of current behavioral patterns
Physical Activity Transition
Changing work practices
Increasing sedentary
An Ecological Model of Health Behavior
IndividualBiologicalPsychologicalBehavioral Skills
Social/Cultural
Physical Environment
Policy Context
Key Points from Ecological Models
• Interventions that work at all levels likely to be most effective
• Individual interventions will not work well when environments are not supportive
• Environment and policy changes likely to have most widespread and longest-lasting impacts
• First, create activity-friendly environments. Then motivate & educate people to be active
Occupational
Household
Transportation
Leisure
Domains of Activity: The SLOTH ModelSleep
Physical Activity Settings & Experts
• Neighborhood
• Transportation facilities
• Recreation facilities
• Schools & workplaces
• Planners
• Transport engineers & planners
• Park & rec, landscape architects
• Educators, architects
Comm DesignDestinations Home
Elements of An Active Living Community
“Walkable”: Mixed use, connected, dense
Not “walkable”
street connectivity and mixed land use
The Neighborhood Quality of Life (NQLS) Study: The Link Between
Neighborhood Design and Physical Activity
James SallisBrian Saelens
Lawrence FrankAnd team
Results published March 2009 in Social Science and Medicine
NQLS Neighborhood Categories
Walkability
Soc
ioec
onom
ic S
tatu
s Low High
Hig
hLo
w 4 per city
4 per city 4 per city
4 per city
Accelerometer-based MVPA Min/day in Walkability-by-Income Quadrants
28.5
33.4
29.0
35.7
0
5
10
15
20
25
30
35
40
MV
PA
min
ute
s p
er d
ay(M
ea
n *
)
Low Income High Income
Low Walk
High Walk
Walkability: p =.0002
Income: p =.36
Walkability X Income: p =.57
* Adjusted for neighborhood clustering, gender, age, education, ethnicity, # motor vehicles/adult in household, site, marital status, number of people in household, and length of time at current address.
Percent Overweight or Obese (BMI>25) in Walkability-by-Income Quadrants
63.156.8
60.4
48.2
0
10
20
30
40
50
60
70
% O
verw
eig
ht
or
Ob
ese
Low Income High Income
Low Walk
High Walk
Walkability: p =.007
Income: p =.081
Walkability X Income: p =.26
* Adjusted for neighborhood clustering, gender, age, education, ethnicity, # motor vehicles/adult in household, site, marital status, number of people in household, and length of time at current address.
Youth ages 5 to 18 years who live in mixed-use neighborhoods walk more for transportation
9% of children had walking trip over two days
18% of children had walking trip over two days
0%
5%
10%
15%
20%
No mixed land use Mixed land use
Frank, Kerr, et al., Am J of Health Promotion, 2007
Walkable neighborhoods encourage more walking in older adults
•Older women who live within walking distance of trails, parks or stores recorded significantly higher pedometer readings than women who did not. The more destinations that were close by, the more they walked.
Photo: Michael Ronkin, ODOT
King, W., Am. J. of Public Health 2003
Comm DesignDestinations Home
Park & Rec
Elements of An Active Living Community
People with access to parks & recreationFacilities are more likely to be active
A national study of US adolescents (N=20,745)* found a greater number of physical activity facilities is directly related to physical activity and inversely related to risk of overweight
Gordon-Larsen et al, Pediatrics, 2006http://www.pediatrics.org/cgi/content/full/117/2/417
*using Add Health data
0.5
0.75
1
1.25
1.5
One Two Three Four Five Six Seven
Number of facilities per block group
Od
ds
rati
o
Odds of having 5 or more bouts of MVPA
Odds of being overweight
1.26
.68
Referent
People are Most Active on Tracks and Walking Paths
0
50
100
150
200
250
300
Track
Sidew
alk
Gymnas
ium
Mul
ti-pu
rpos
e fie
ld
Playg
roun
d
Outdo
or Bas
ketb
all
Lawn
Baseb
all
Senio
r Cen
ter
Ave
rag
e N
um
ber
of
Par
k U
sers Sedentary Walking, Moderate & Vigorous
Cohen. RAND
Change in Number of Skate Park Users
0
500
1000
1500
2000
# of
Par
k U
sers
RemodeledSkate Park
ComparisonSkate Park
Baseline
Follow-up
Cohen. RAND
Use of 10 Renovated & Control Parks Declined
6449
8801
3459
870436
4717
3387
6142
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
Children Teens Adults Seniors
# o
f P
ark
Use
rs
Baseline Follow-up
Baseline: Avg of 2000 persons observed per parkFollow-up: Avg of 1500 persons observed per park
Number of Organized Activities Declined
2727
4
35
5
1 0
9
0
5
10
15
20
25
30
35
40
Gymnasium OutdoorBasketball
Court
Multi-purpose
Field
BaseballField
# o
f O
rga
niz
ed
Ac
tiv
ite
s Baseline Follow-up
Cohen. RAND
Lessons from Park Renovation Studies
• Improving physical structures alone may not be enough to change physical activity
• Programs and events may be needed to help park users make use of physical changes
• Probably need more attention to outreach
Cohen. RAND
Percent of 8-14 year-olds meeting 60 min/day of MVPA during sports practice
0
5
10
15
20
25
30
35
Soccer Baseball
Boys
Girls
Comm DesignDestinations Home
Park & RecSchool & Preschool
Elements of An Active Living Community
What PE is—too oftenWhat PE is—too often
What PE What PE shouldshould be be
PE classes in lower income schools spend less time being active. Yancey. www.calendow.org
Percent (%) of time in MVPA, by percent % of students eligible for Free and Reduced Price Lunch (FRPL)
43%
34%
0%
10%
20%
30%
40%
50%
0-74% 75-100%
Percent (%) of students eligible for FRPL
Pe
rce
nt
(%)
of
PE
tim
e in
MV
PA
All Kids Should Be Active in PE(50% of class time)
And Learn Skills
Evidence-based PE is Available
• Early Childhood/preschool
• • Elementary schools
• Middle schools
• High schools
• SPARK
• SPARK• CATCH
• M-SPAN (SPARK)• TAAG
• LEAP• SPARK
SPARK Effects on PE Class Time & Observed Physical Activity
SPARK Outcomes• PE specialists>trained classroom teachers>
controls• Improved quality of PE instruction• Increased physical activity in PE• Improved cardiorespiratory & muscle
fitness• Improved sports skills• Positive impact on academic achievement• Students enjoyed SPARK lessons• 1.3 million kids a day getting active with
SPARK
Elementary students' on-task classroom behavior improves with physical activity breaks
breaks withno physical activity
-3%
physical activity breaks,
students overall
8%
physical activity breaks, off-task
students
20%
-5%
0%
5%
10%
15%
20%
25%
Pe
rce
nt
imp
rov
em
en
t in
on
-ta
sk
be
ha
vio
r
Mahar, Murphy, et al., Medicine and Science in Sports and Exercise, 2006
School Environment Interventions
• Stratton et al. from the UK conducted several studies showing simple markings on elementary playgrounds increases PA about 18 min/day
• Verstraete from• Belgium showed• Equipment at• Recess increased• PA
After School Programs
• Primary time for youth to be active
• Key issues– Transportation access– Cost– Quality of program & leadership– Amount of activity provided
• SPARK Active Recreation Program
Before After
Lois Brink, U Colorado Denver
Comm DesignDestinations Home
Park & Rec
School & Preschool
Elements of An Active Living Community
Designed for active travel
Not designed for active travel
Activity-Friendly Transportation SystemsComplete Streets
Source: NPTS 1977, 1990 and NHTS 2001 for children 5-15
Walking to School as Percent of School Trips (Children 5-15)
20.2
16.6
12.5
0
5
10
15
20
25
1977 1990 2001
More parents report children walking or biking to school after Safe Routes to Schools project completion
10.9%
20.6%19%
3.1%
12%
28.6%
11.6%
15.6%13.7%
6.7%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
JuanCabrillo
Murrieta Sheldon Valley WestRandall
Glenoaks Jasper Mt.Vernon
CesarChavez
Newman
% c
ha
ng
e in
wa
lkin
g o
r b
ikin
g t
o s
ch
oo
l
Boarnet, Anderson, Day, et al, Am J Prev Med, 2005
Adolescents in Melbourne, Australia (N=188) are more likely to increase active commuting (walking and biking) to school if their parents are satisfied with the number of traffic lights and pedestrian crossings in their neighborhood
0.4
2.4
1 1
0
0.5
1
1.5
2
2.5
3
No traffic lights orcrossings
Adequatenumber ofcrossingsL
ikel
iho
od
of
incr
easi
ng
wal
kin
g o
r b
ikin
g t
o s
cho
ol
(Od
ds
rati
o)
Referent
Hume et al, AJPM, 2009
Where do people bicycle? The role of infrastructure in determining bicycling behavior
Jennifer Dill, Ph.D. Center for Transportation Studies
•
Distribution of recorded bicycle travel by facility type, compared to network mileage (based on 166 adult cyclists in Portland, OR). Location of travel assessed by GPS.
% of all bicycle travel (miles)
% of network
Roads without bicycle infrastructure 51 92
Primary roads/highways, no bicycle lanes 4 4
Secondary roads, no bicycle lanes 19 13
Minor streets, no bicycle lanes 27 63
Driveways, alleys, unimproved roads 2 12
Bicycle Infrastructure 49 8Primary roads/highway, with bicycle lanes 9 3
Secondary roads, with bicycle lanes 14 2
Minor streets, with bicycle lanes 3 1
Bicycle/multi-use paths 14 2
Bicycle boulevards 9 <1
N (miles) 7,479 10,564
Dill, JPHP, 2009
Promoting CyclingII - IV
Plan communities with schools, parks, public spaces, transit stops and commercial districts located as focal points within convenient walking distances of neighborhoods.
Walkable Neighborhood PlanningWalkable Neighborhood Planning
Create activity-friendly neighborhoods, towns, and military bases.
A model for military bases Linenger. Am J Prev Med. 1991
• Environmental changes on a Naval base– Bike paths along roadways– Extend hours for rec facilities– Regular athletic & PA events on base– Running & biking clubs organized– Women’s fitness center opened– Healthy foods more visible– Recognition for improved fitness– Newspaper listed top performers– Fitness testing with feedback
• Significant fitness improvements in 1 year
Resources at www.activelivingresearch.org
Next Steps• Assess conditions on your base
– Places– Policies– Programs
• What interventions could have the biggest and longest-lasting impact?
• What interventions could serve both military and civilian residents & workers?
• Gather the right partners & resources• Develop & implement a plan• Evaluate it!
More of this
Less of thisVision for The Future
www.drjamessallis.sdsu.edu www.activelivingresearch.org
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