How Can We Build Healthy & Active Communities?

James Sallis, PhDUniversity of California, San Diego

http://sallis.ucsd.edu

For PAPH in ArubaJune 14, 2012

Maintaining & Building Activity-Friendly Places in Aruba

SLOTH Model of Physical Activity

• Sleep

• Leisure

• Occupation

• Transportation

• Household

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

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

An Ecological Model of Health Behavior

IndividualBiologicalPsychologicalBehavioral Skills

Social/Cultural

Physical Environment

Policy Context

Different environments----Different congestion

Places for Physical Activity

• Leisure

• Occupation

• Transportation

• Household

• Parks, health clubs, sidewalks

• Workplace

• Streets, bike facilities

• Home

Comm DesignDestinations Home

Park & Rec

School & Preschool

Elements of An Active Living Community

Transportation

“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.

Multiple Pathways from Land Use to Health: Walkability Associations With Active Transportation,

Body Mass Index, and Air Quality.Frank et al. JAPA 2007

• 5% increase in walkability associated with:– 32% increase in walking for transport– ¼ point decrease in BMI (about 1.25 pounds)– 6.5% decrease in vehicle miles traveled– 5.6% decrease in oxides of nitrogen (NOx)

grams– 5.5% decrease in volatile organic compounds

(VOC) grams• County government is acting on results

Accelerometer-based MVPA Min/day in Walkability-by-Income Quadrants

Walkability: F=13.74; p =.000

Income: F=2.59; p =.108

Walkability X Income: F=.001; p =.981

* Adjusted for gender and age

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

We can learn from international studies

Atlanta, USA

Ghent, Belgium

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

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

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

Built environment correlates of physical activity behaviours in a developing city:

The case of Bogota, Colombia

Olga Lucia Sarmiento and team

Universidade de los Andes

photo: O.L. Sarmiento

Main Results• Walking for transport (30 min/day for at least 5 days/week) was positively associated with:

– Street density (POR 1.71, 95% CI 1.19-2.46)– Street connectivity (POR 2.21, 95% CI 1.40-3.49)– Bus Rapid Transit stations in the neighborhood (POR

1.71, 95% CI 1.19-3.47)

• Leisure time physical activity (30 min/day for at least 5 days/week) was positively associated with:

– Park density (POR 2.05, 95%CI 1.13-3.72)– Bus Rapid Transit stations in the neighbohood (POR

1.27, 95% CI 1.07-1.50)

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

Activity-Friendly Transportation Systems

Room for ImprovementPlan & Build for Pedestrians

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

0

5

10

15

20

25

30

Per

cen

t o

f O

bes

ity

0

10

20

30

40

50

60

Per

cen

t W

alk

, B

ike,

Tra

nsi

t

Obesity Walk, Bike, Transit

Obesity falls sharply with increased walking, cycling, and transit use!

Credit: John Pucher

Daily steps are higher among adults who commute by train instead of car

7500

9500

6000

7000

8000

9000

10000

Train Car

Commuting Mode

Ave

rag

e D

aily

Ste

ps

(ped

om

eter

)

Wener & Evans, Environment and Behavior, 2007

Neighborhood Walkability and Active Commuting to School

• 201 parents of 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

Where do people bicycle?  The role of infrastructure in determining bicycling behavior

Jennifer Dill, Ph.D. Center for Transportation Studies

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.

•The Ministry of Traffic designated Odense as Denmark’s National Cycle City 1999-2002 (186.000 citizens)

Odense – The National Cycle City of Denmark

Right-hand turn lanesII - IV

Awareness of cyclistsII - IV

•Results •1999-2003: •> 50 sub-projects• Bicycle traffic increase by 20%•Accidents involving cyclists decrease by 20%

Odense – The National Cycle City of Denmark

www.cyclecity.dk

London('03-'06)

Barcelona('05-'07)

Paris('01-'07)

Bogota('95-'07)

Minneapolis('80-'08)

Portland('90-'08)

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

1.2

0.81.0

0.81.0 1.1

1.6 1.8

2.5

3.2

4.3

6.0

Per

cen

t of

Tri

ps

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

Bogota, Colombia has invested heavily in walking, cycling, & PA events

Boulder, CO

Brisbane, Australia has invested in pedestrian facilities

*Beautiful pedestrian bridge*Walkways along the river*Pleasing aesthetics

Amsterdam is a model for being friendly to pedestrians & cyclists

TheIncredibleBicycleParkingStructure At theTrainStation

Decisions aboutClimate change andControlling chronicDisease are related

Resources from www.activelivingresearch.org