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Using Research to Create aLess Obesogenic World
James Sallis, PhDSan Diego State University
Active Living Researchwww.drjamessallis.sdsu.edu
Lompoc, CA Community Health SummitMarch 25, 2010
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David visits America
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Shaping the CultureThe Weight Loss Industry
• At least $20B in sales (2002)• Preying on people’s desires for quick fixes• In 2001, $100M spent on infomercials
alone• Huge increase in (completely unregulated)
dietary supplements• FTC determined over 55% of ads had
false or inadequately supported claims• Why be active or eat better when “results
are guaranteed”?
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Shaping the Culture: What are the influences? Ads as of of 2004:
• Food, beverages, candy $6.8B
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Shaping the Culture: What are the influences? Ads as of of 2004:
• Food, beverages, candy $6.8B– 5 a day (max of) $0.0003B
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Shaping the Culture: What are the influences? Ads as of of 2004:
• Food, beverages, candy $6.8B– 5 a day (max of) $0.0003B
• Automobiles $20.5B
• Movies, DVDs $5.3B
• Computers, software $2.5B
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Shaping the Culture: What are the influences? Ads as of of 2004:
• Food, beverages, candy $6.8B– 5 a day (max of) $0.0003B
• Automobiles $20.5B
• Movies, DVDs $5.3B
• Computers, software $2.5B– Sporting goods $0.5B– VERB (max of) $0.0125B
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Overview of Presentation
• How to think about the problem: Ecological models of diet and physical activity
• Research on nutrition environments
• Research on PA environments
• Getting research used in policy decisions that affect diet and PA
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What is the public health approach to improving diet and
PA?• Minor investment in programs• Guided by theories that emphasize
psychological & social influences• Primary goals are education and behavior
change skills training targeting individuals• Low reach, modest effects, poor
maintenance• Fragmented, poorly coordinated, poorly
funded approaches
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Typical Models of Health Behavior
IndividualBiologicalPsychologicalSkills
Social/Cultural
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An Ecological Model of Health Behavior
IndividualBiologicalPsychologicalSkills
Social/Cultural
Physical Environment
Policy Context
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An Alternative: Ecological Models
• Because there are multiple levels of influence, the most effective interventions should work at ALL levels
• Multi-level intervention approaches – First, create environments & policies that
make healthy choices easy– Then, educate & motivate people to make
those choices
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Promise of Built Environment Changes
• Many believe we have built a world that supports unhealthy habits– Neighborhood design requires driving– Portion size inflation– Fast food restaurants & other eating
opportunities have proliferated– Many options for sedentary entertainment
• Built environment changes – Are permanent– Affect everyone
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An Ecological Framework Depicting the Multiple Influences on What People Eat
Individual Factors
(personal)
Social Environment(networks)
Macro-level Environments
(sectors)
Physical Environments
(settings)
Home Worksites School,
Afterschool Child-care Neighborhoods
& Communities Restaurants &
fast food outlets Supermarkets Convenience &
corner stores
Access Availability Barriers Opportunitie
s
Cognitions (e.g. attitudes, preferences, knowledge, values)
Skills and behaviors Lifestyle Biological (e.g. genes,
gender, age) Demographics (e.g.
income, race/ethnicity)
Outcome expectations Motivations Self-efficacy Behavioral capability
Societal and cultural norms and values
Food and beverage industry
Food marketing and media Food and agriculture
policies Economic systems Food production &
distribution systems Government & political
structures and policies Food assistance programs Health care systems Land use and
transportation
Practices Legislative,
regulatory, or policy actions
Family Friends Peers
Role modeling Social support Social norms
Story et al., ARPH, 2007
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What do you see in your food environments?
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Research on Community Food Environments. Sallis & Glanz, Millbank Q, 2009
• African Americans ate more F&V when they lived close to supermarkets (Morland 2002)
• Living close to supermarkets related to– Better quality diet (Moore 2008)
– Lower prevalence of obesity (Morland 2006, Powell 2007)
• Most studies show there are fewer supermarkets in low-income and minority neighborhoods
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Research on Community Food Environments. Sallis & Glanz, Millbank Q, 2009
• Frequency of eating is restaurants is related to poorer diet (Satia 2004) and more weight gain (Pereira 2005)
• Higher concentration of fast food restaurants in low-income areas (Powell 2007)
• Mixed evidence on relation of fast food density to obesity (Papas 2007)
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Research on Consumer Food Environments. Sallis & Glanz, Millbank Q, 2009
• Fewer healthy food options & higher prices in food stores in low-income areas (Horowitz 2004; Glanz 2007)
• Fast food chain restaurants provide nutrition info, but not at point-of-decision (Saelens 2007; Wootan 2006)
• In a study of 217 Atlanta restaurants, less than 1/3 had any main dishes that could be identified as healthy (Saelens 2007)
• Menu calorie labeling laws are being evaluated in NYC, Seattle, and California
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Research on Rural Food Environments. Casey. Prev Med. In press.
• Survey of adults in rural MO, AR, TN
• Proximity to convenience stores, buffets, fast food was not related to obesity.
• Shopping frequently at small grocery stores was associated with obesity.
• Eating out frequently at buffets/cafeterias, fast food restaurants, and convenience stores was associated with being obese.
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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
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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
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Promoting exercise has not worked
Source: Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance System
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Occupational
Household
Transportation
Leisure
Domains of Activity: The SLOTH ModelSleep
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Walking for transport & overweight:Adults
Based on data from Based on data from the Nationwide the Nationwide Personal Personal Transportation Transportation Survey and the Survey and the Centers for Disease Centers for Disease Control and Control and Prevention.Prevention.
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Physical Activity Transition
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Changing work practices
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Increasing sedentary
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Community DesignDestinations Home
Elements of An Active Living Community
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Community DesignDestinations Home
Park & Rec
Elements of An Active Living Community
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Community DesignDestinations Home
Park & RecSchool & Worksite
Elements of An Active Living Community
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Community DesignDestinations Home
Park & Rec
School & Worksite
Elements of An Active Living Community
Transportation System
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“Walkable”: Mixed use, connected, dense
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Not “walkable” street connectivity and mixed land use
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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
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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
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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.
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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.
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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
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Neighborhood Walkability and Active Commuting to School
• 201 parents reported on children aged 4 to 17
• Active commuting to school:– 25% in hi-walkable neighborhoods– 11% in lo-walkable neighborhoods
• Parent concerns, mostly about traffic, were higher in lo-walkable neighborhoods
• Kerr, et al. MSSE, 2006
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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
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We can learn from international studies
Atlanta, USA
Ghent, Belgium
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Multiple Environmental Factors Are Needed to Support Physical
Activity: An 11-Country Study of Neighborhood Environments
James F. Sallis, USA
Heather Bowles, Australia
Barbara E. Ainsworth, USA
Adrian Bauman, Australia
Et al
Am J Prev Med. May 2009
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Associations Between Individual Environmental Characteristics and HEPA/Minimal Activity Among Respondents who Live in Cities with Population ≥ 30,000
0.6
0.8
1.0
1.2
1.4
1.6
1.8
Single FamilyHouses
Shops NearHome
T ransit StopNear Home
SidewalksP resent
Facilit ies toBicycle
Low Cost RecFacilit ies
Unsafe to Walkdue to Crime
'Agre e ' wi th Environm e ntal C haracte ristic('Disagre e ' i s re fe re nt)
Odd
s R
atio
HE
PA
/Min
imal
Act
ivit
y
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Dose Response between Number of Environmental Characteristics and HEPA/Minimal Activity
(Pooled City Sample)
0.60
1.00
1.40
1.80
2.20
2.60
3.00
1 2 3 4 5 6
Total Num be r of Environm e ntal C haracte ristics(Ze ro i s re fe re nt)
Odd
s R
atio
HE
PA
/Min
imal
ly A
ctiv
e
Sallis. Am J Prev Med. 06/09
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What are rural active living environments?
• Walkability concepts are not relevant– Except in small towns, which can be sprawling
• Casey study found PA environment was related to obesity– Less access to physical activity facilities– No safe road shoulders available– Rating the community as unpleasant
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RALA: Rural Active Living Assessment Tools
• Yousefian. Prev Med 2010 & webinar. Access via www.activelivingresearch.org
• Town-Wide assessment– 18 town characteristic questions– inventory of 15 recreational amenities
• Program and Policy assessment (20 questions)• Street Segment observations (28 questions)• Some components assess by interview of
knowledgeable leaders. Street observations require trained observers
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People with access to parks & recreationFacilities are more likely to be active
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Access to Recreation Facilities Related to MVPA & Overweight in Youth
Availability of recreational & PA facilities and relative odds of overweight and bouts of moderate and vigorous physical activity
(MVPA)
0.5
0.75
1
1.25
1.5
One Two Three Four Five Six Seven
Number of facilities per block group
GordonLarsenPediatr2006
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Recreation Facilities May Be More Important for Minorities
Percent being active with high and low recreational resources within 1 mile of home
25
30
35
40
45
50
55
Blacks & Hispanics Non-Hispanic Whites
Low recreational resources
High recreational resources
Diez-Roux2007
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Percent of census tracts without a recreational facility by race/ethnicity
38%
81%70%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
African American Hispanic White
% w
ith
no
rec
reat
ion
fac
ilit
y
Moore, Am J Prev Med, 2007
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Mean EE by Park Activity Zones (Chicago)
0.0580
0.0630
0.0680
0.0730
0.0780
0.0830
0.0880
0.0930
0.0980
En
erg
y E
xpen
dit
ure
(K
kcal
/kg
/min
)
Scheffe’spost hoc test
Chicago, F = 10.20, Chicago, F = 10.20, p p < .001< .001
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Activity-Friendly Transportation Systems
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Walkability > Driving > Obesity?The more miles a person travels by vehicle, the
more likely they are to be obese
9.5
14.3
27.08
18.05
0%
5%
10%
15%
20%
25%
30%
Q1 Q2 Q3 Q4
Quartiles of vehicle miles traveled (VMT)
Lopez Zetina 2006
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Where do people bicycle? The role of infrastructure in determining bicycling behavior
Jennifer Dill, Ph.D. Center for Transportation Studies
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Where do people bicycle in Portland, OR? Based on GPS.
Type of road % of bicycle miles
% of road miles
Without bicycle facilities
51 92
With bicycle facilities (lane, separate path, bike boulevard
49 8
Jennifer Dill. J Public Health Policy. 2008.
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Source: Pucher, Dill, and Handy, “Infrastructure, Programs, and Policies to Increase Bicycling,” Preventive Medicine, Jan 2010, Vol. 50, S.1, pp. S106-S125.
Increase in Bike Share of Trips in Cities Around the World
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What PE What PE shouldshould be be
What PE is—What PE is—too oftentoo often
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Evidence-Based PE• Strongly recommended by CDC’s
community guide• Healthy People 2010: 50% of class time in
MVPA• Improved quality of PE instruction• Increased physical activity in PE• Improved fitness• Improved sports skills• SPARK & CATCH evidence-based
programs are widely disseminated• SPARK is affecting >1 millions kids per day
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Before After
Courtesy, Lois Brink, U Colorado Denver
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Where is the field now?• IOM Childhood Obesity Report based on an
ecological model
• Transportation Research Board-IOM Panel concluded built environments related to PA
• CDC’s Community Guide recommends land use interventions
• International Obesity Task Force guided by ecological model
• WHO diet and physical activity global strategy based on policy & environmental changes
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Active Living Research:Nurturing a New
Transdisciplinary Field
www.activelivingresearch.org An Active Living Program supported by The Robert Wood Johnson Foundation and administered by San Diego State University.
www.activelivingresearch.org
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Active Living Research: 2001-2012
• Contribute to Robert Wood Johnson Foundation’s goal of reversing the childhood obesity epidemic by 2015• Focus on groups at highest risk
–African American, Latino, Native American, Asian/Pacific Islander, lower income
• Build the evidence base–We manage $27 million in research grants–Investigators from 30+ disciplines–Funded 150+ studies
• Use research to inform policy
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Resources at www.activelivingresearch.org
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Our research is being used
• I briefed the First Lady on evidence-based approaches
• President’s multi-agency Obesity Task Force is consistent with the research
• New vehicles for researchpolicy
2/9/10
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Progress closer to home
• In December 2009 I and others met with the Governor & recommended evidence-based policies for PE, after-school, and safe routes to schools
• At February 2010 health summit, Governor announced legislation for these topics and others
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But What Can I Do?Make New Friends
• Create walkable communities
• Build transport systems for peds & cyclists
• Good parks in every community
• Schools as active places for students & communities
• Planners, city council, environmentalists
• Transportation engineers, bike/walk grps
• Park dept & advocates
• Education dept, PE teachers, park dept, pediatricians
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But What Can I Do?Join with Others
• Organize an interest group or advocacy committee in your current organizations
• Combine diverse groups to develop a local or state coalition– A key to success of tobacco control
• Join advocacy groups to amplify your voice and strengthen their efforts. See www.americawalks.org
• Get professional help: advocacy, social marketing, lobbying
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But What Can I Do?Speak Up--Often
• Be a voice for physically active people and places
• Act locally– Attend planning board, city council, school
board. Talk to your friends & colleagues
• Write it down– Newspapers, elected officials, blogs
• Act globally– Advocate for national & international policies
for sustainable transportation & development
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Be An Effective Spokesperson
• Know the research & advocate for evidence-based policies
• Develop relationships with decision makers and their staff
• Recognize & celebrate good decisions
• Be Bold
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More of this
Less of thisVision for The Future
www.drjamessallis.sdsu.edu www.activelivingresearch.org