Transcript Models and Frameworks - University of California, San Diego

“Just the Facts”…Leveraging
Research to Promote Active
Living in Army Communities
James Sallis, PhD
San Diego State University
www.drjamessallis.sdsu.edu
For Army MWR Conference
Louisville, 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
Tobacco smoking
High blood pressure
Overweight-obesity (high BMI)
Physical inactivity
High blood glucose
High LDL cholesterol
High dietary salt
Low dietary omega-3 fatty acids
High dietary trans fatty acids
Alcohol use
Low intake of fruits and vegetables
Low dietary polyunsaturated fatty acids
0
Danaei G et al, PLoS Medicine, 2009
50
100 150 200
250 300 350 400
450 500
Percentage of youth ages 6-19 meeting 60 min/day
physical activity guidelines.
Based on accelerometers. NHANES 2003-4
60%
49%
40%
35%
20%
10%
10%
3.4%
5.4%
0%
6-11
Troiano, MSSE 2007
12-15
Age
16-19
Males
Females
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
Social/Cultural
Individual
Biological
Psychological
Skills
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 sufficient
Reach is limited
Effects are modest
Maintenance 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
Policy Context
Physical Environment
Social/Cultural
Individual
Biological
Psychological
Behavioral Skills
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
Domains of Activity:
The SLOTH Model
Sleep
Leisure
Occupational
Transportation
Household
Physical Activity Settings & Experts
• Neighborhood
• Transportation
facilities
• Recreation facilities
• Schools & workplaces
• Planners
• Transport engineers
& planners
• Park & rec, landscape
architects
• Educators, architects
Elements of An Active Living
Community
Comm Design
Destinations
Home
“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 Sallis
Brian Saelens
Lawrence Frank
And team
Results published March 2009 in Social Science and Medicine
NQLS Neighborhood Categories
Walkability
Low
High
4 per city
4 per city
4 per city
4 per city
Accelerometer-based MVPA Min/day
in Walkability-by-Income Quadrants
Walkability: p =.0002
Income: p =.36
Walkability X Income: p =.57
35
35.7
30
(Mean *)
MVPA minutes per day
40
25
33.4
28.5
Low Walk
High Walk
29.0
20
15
10
5
0
Low Income
High Income
* 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
Walkability: p =.007
Income: p =.081
Walkability X Income: p =.26
% Overweight or Obese
70
60
63.1
50
56.8
Low Walk
High Walk
60.4
48.2
40
30
20
10
0
Low Income
High Income
* 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
20%
9% of children had walking
trip over two days
15%
18% of children had walking
trip over two days
10%
5%
0%
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
Elements of An Active Living
Community
Comm Design
Destinations
Home
Park & Rec
People with access to parks & recreation
Facilities 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
1.5
Odds ratio
Odds of having 5 or more
bouts of MVPA
1.26
1.25
Referent
1
Odds of being
overweight
0.75
.68
0.5
One
*using Add Health data
Two
Three
Four
Five
Six
Number of facilities per block group
Gordon-Larsen et al, Pediatrics, 2006
http://www.pediatrics.org/cgi/content/full/117/2/417
Seven
Cohen. RAND
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Pl
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M
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Average Number of Park Users
People are Most Active on
Tracks and Walking Paths
Walking, Moderate & Vigorous
250
200
150
100
50
0
Change in Number of Skate Park Users
# of Park Users
2000
1500
1000
Baseline
Follow-up
500
0
Remodeled
Skate Park
Cohen. RAND
Comparison
Skate Park
Use of 10 Renovated
& Control Parks Declined
10000
Baseline
9000
Follow-up
8801
# of Park Users
8000
7000
6449
6142
6000
5000
4717
4000
3459 3387
3000
2000
870
1000
436
0
Children
Teens
Adults
Seniors
Baseline: Avg of 2000 persons observed per park
Follow-up: Avg of 1500 persons observed per park
Number of Organized Activities Declined
# of Organized Activites
40
35
35
30
Baseline
Follow-up
27
27
25
20
15
9
10
5
5
4
1
0
0
Gymnasium
Cohen. RAND
Outdoor
Basketball
Court
Multipurpose
Field
Baseball
Field
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
35
30
25
20
Boys
15
Girls
10
5
0
Soccer
Baseball
Elements of An Active Living
Community
Comm Design
Destinations
School & Preschool
Home
Park & Rec
What PE is—too often
What PE should be
PE classes in lower income schools
spend less time being active.
Yancey. www.calendow.org
P e r c e n t (%) o f tim e in M V P A,
b y p e r c e n t % o f s tu d e n ts e lig ib le fo r
P er c ent (% ) of P E tim e i n M V P A
F r e e a n d R e d u c e d P r ic e Lu n c h (F R P L)
50%
40%
43%
30%
34%
20%
10%
0%
0 -7 4 %
7 5 -1 0 0 %
P e r c e nt (%) of s tude nts e ligible for FRP L
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
• LEAP
• SPARK
SPARK
• SPARK
• CATCH
M-SPAN (SPARK)
TAAG
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
Percent improvement in on-task behavior
25%
physical activity
breaks, off-task
students
20%
15%
physical activity
breaks,
students overall
10%
20%
8%
5%
breaks with
no physical activity
0%
-3%
-5%
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
Lois Brink, U Colorado Denver
Before
After
Elements of An Active Living
Community
Comm Design
Destinations
Home
School & Preschool
Park & Rec
Designed for active travel
Not designed for active travel
Activity-Friendly Transportation Systems
Complete Streets
Walking to School as Percent of
School Trips (Children 5-15)
25
20.2
20
16.6
15
12.5
10
5
0
1977
1990
Source: NPTS 1977, 1990 and NHTS 2001 for children 5-15
2001
More parents report children walking or biking to school after
Safe Routes to Schools project completion
% change in walking or biking to school
50%
45%
40%
35%
28.6%
30%
25%
19%
20%
20.6%
15.6%
13.7%
15%
10%
11.6%
12%
10.9%
6.7%
3.1%
5%
0%
Juan
Cabrillo
Murrieta Sheldon
Valley
West
Glenoaks Jasper
Randall
Boarnet, Anderson, Day, et al, Am J Prev Med, 2005
Mt.
Vernon
Cesar
Chavez
Newman
Likelihood of increasing walking or biking to school
(Odds ratio)
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
3
Referent
2.4
2.5
2
1.5
1
1
No traffic lights or
crossings
Adequate
number of
crossings
1
0.5
0.4
0
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
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
49
8
Primary 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
7,479
10,564
Roads without bicycle infrastructure
Bicycle Infrastructure
•
N (miles)
Dill, JPHP, 2009
II - IV
Promoting Cycling
Create activity-friendly neighborhoods, towns,
and military bases.
Plan communities with schools,
parks, public spaces, transit
stops and commercial districts
located as focal points within
convenient walking distances
of neighborhoods.
Walkable Neighborhood Planning
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!
Vision for
The Future
Less of this
More of this
www.drjamessallis.sdsu.edu
www.activelivingresearch.org