Active Living: Using Research to Inform Policy and Practice James - PowerPoint PPT Presentation

Active Living: Using Research to Inform Policy and Practice James Sallis UCSD, Active Living Research http://sallis.ucsd.edu Society for Nutrition Education and Behavior. July 30, 2016

Outline • Why physical activity? • What is evidence about the role of environments and policies in active living? • Examples of effective PSE strategies • How to improve our translation of research to policy and practice www.activelivingresearch.org

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 50 100 150 200 250 300 350 400 450 500 Danaei G et al, PLoS Medicine, 2009

How Did We Become Inactive? • S leep • L eisure • O ccupation • T ransportation • H ousehold www.activelivingresearch.org

We have invested $Billions to make active transport difficult or impossible www.activelivingresearch.org

Active Transportation by Youth has Decreased Mode for Trips to School – National Personal Transportation Survey McDonald NC. Am J Prev Med 2007;32:509.

Accelerometer-based MVPA for Adolescents. From Hallal, Lancet, 2012 www.activelivingresearch.org

Obesity is strongly related to walking, cycling, and transit use! 30 60 Percent Walk, Bike,Transit 25 50 Percent of Obesity 20 40 15 30 10 20 5 10 0 0 d a y d d a s d k e y n n A a i d n n n n i n l c l i e r d r n a S a a a a a a a a n d t a l s m r t p m a l l l U a r n I e a t u e n l S s e r w a r n e r r i A u F z e F e C I e Z S t A h G i D t w w e S N e N Obesity Walk, Bike, Transit Credit: John Pucher

Elements of An Active Living Community Community Design Destinations Home Transportation System School & Worksite Park & Rec www.activelivingresearch.org

Public Health Needs to Partner Setting for PA Expertise for Policy, Practice • Planners • Neighborhood • Transport engineers & • Transportation facilities planners (sidewalks) • Park & rec, landscape • Recreation facilities architects • Educators, architects • Schools & workplaces www.activelivingresearch.org

The Neighborhood Quality of Life (NQLS) Study: The Link Between Neighborhood Design and Physical Activity 2001-2005 James Sallis, Ph.D. Brian Saelens, Ph.D. Lawrence Frank, Ph.D. And team

Accelerometer-based MVPA Min/day in Walkability-by-Income Quadrants Walkability: p =.0002 Income: p =.36 Walkability X Income: p =.57 40 35 MVPA minutes per day Low Walk 35.7 30 33.4 High Walk 25 29.0 28.5 (Mean *) 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.

Estimated Public Health Impact of Walkability • 50 minutes per week = 2+ miles per week • 2 miles per week = 100 miles per year • 100 miles per year = 10,000 kcal per year • 10,000 kcal per year = 2.9 pounds/1.3 kg • More than the average adult weight gain per year in the U.S. www.activelivingresearch.org

Percent Overweight or Obese (BMI>25) in Walkability-by-Income Quadrants Walkability: p =.007 Income: p =.081 Walkability X Income: p =.26 70 % Overweight or Obese 60 Low Walk 63.1 60.4 High Walk 50 56.8 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.

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 70 68 68.5 Low Walk 66 High Walk MVPA minutes per day 65.6 64 62 (Mean *) 61.8 60 58 58.8 56 54 52 Low Income High Income * Adjusted for gender and age

Outside Activities (except gardening) (min/wk) SNQLS (Adjusted for Time, Region, Demographics) Walkability: p < .008 I ncome: p = .04 250 200 150 100 50 0 WALK Low W High W Low W High W I NCOME High Income Low Income www.activelivingresearch.org King, Sallis, Frank, Saelens et al., 2011, Soc Sci Med, 73, 1525-1533

Body Mass Index (BMI) SNQLS (Adjusted for Time, Region, Demographics) Walkability: p = .02 28 I ncome: p < .03 27 BMI 26 25 24 WALK Low W High W Low W High W High Income Low Income I NCOME www.activelivingresearch.org King, Sallis, Frank, Saelens et al., 2011, Soc Sci Med, 73, 1525-1533

Low PA, Low N Low PA, High N High PA, Low N High PA, High N BMI in 85 th percentile 34.4% 31.6% 28.7% 27.3% BMI in 95 th percentile 18.8% 15.3% 14.4% 11.7% www.activelivingresearch.org

Atlanta, USA Ghent, Belgium We can learn from international studies

Associations Between Individual Environmental Characteristics and HEPA/Minimal Activity Among Respondents who Live in Cities with Population ≥ 30,000 1.8 1.6 HEPA/Minimal Activity 1.4 Odds Ratio 1.2 1.0 0.8 0.6 Single Family Shops Near Transit Stop Sidewalks Facilities to Low Cost Rec Unsafe to Walk Houses Home Near Home Present Bicycle Facilities due to Crime 'Agree' with Environmental Characteristic ('Disagree' is referent) 21

Dose Response between Number of Environmental Characteristics and HEPA/Minimal Activity (Pooled City Sample) 3.00 HEPA/Minimally Active 2.60 2.20 Odds Ratio 1.80 1.40 1.00 0.60 1 2 3 4 5 6 Total Number of Environmental Characteristics (Zero is referent) Sallis. Am J Prev Med. 06/09

www.ipenproject.org • Encourage environment and policy research on physical activity worldwide • Develop & encourage use of common measures and methods • Support investigators to obtain internal funding • Coordinate international studies – IPEN Adult, funded by NCI – IPEN Adolescent, funded by NHLBI • Communicate findings to decision makers www.activelivingresearch.org

Belgium, Denmark, Czech Republic, UK, Spain 12 IPEN Adult Countries

IPEN Adult: GIS Walkability Index 9 SDs

Results: Environmental Attributes + MVPA Min/Week GIS-based Environmental Single variable model Final adjusted model Variable Net residential density *** *** 1km Intersection density * NS 1km Mixed land use NS NS 1km (retail & civic) Public transit density ** * 1km Number of parks ** * 0.5km www.activelivingresearch.org

Moderate-to-vigorous physical activity Moderate-to-vigorous physical activity 80 60 Associations of environmental 55 70 variables based on 1 km buffers 50 with accelerometry-based 60 45 estimates of daily minutes of 50 moderate-to-vigorous physical 40 activity 40 35 30 30 0 20000 40000 60000 80000 0 100 200 300 400 Net residential density (1km b Intersection density (1km buf Moderate-to-vigorous physical activity Moderate-to-vigorous physical activity 60 60 55 55 50 50 45 45 40 40 35 35 30 30 0 20 40 60 80 100 0 10 20 30 40 50 Transit density (1km buffers) Number of parks (1km buffers

Comparing MVPA by Lowest & Highest Cities on Environmental Variables • Adults living in the most activity-friendly cities did 68-89 more minutes of MVPA per week compared to those in the least activity-friendly cities • Living in the most activity-friendly environments could help the average resident achieve 32-59% of the 150 minute/week physical activity guidelines www.activelivingresearch.org

Design of streetscapes matters www.activelivingresearch.org

What is the role of streetscape design? MAPS Mini • 15-item MAPS-Mini was designed for practitioners and advocates – Reduced from 120 items • Items were selected based on – Correlations with physical activity – Guidelines and recommendations – Modifiability • Evaluated for validity in 3677 children, teens, adults, older adults – 3 regions www.activelivingresearch.org

How do MAPS-Mini scores relate to active transportation? ADJUSTED MAPS Mini Score Children Adolescents Adults Seniors Commercial Segments N/A Public Parks Transit Stops Street Lights Benches Building Maintenance Absence of Graffiti Sidewalk Buffer Tree, Awning Coverage Absence of Trip Hazards Marked Crosswalk Curb Cuts Crossing Signal GRAND SCORE GRAND SCORE (for Active Transport) www.activelivingresearch.org

Dose-response of MAPS-Mini total scores and active transport Frequency for 4 age groups

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 of having 5 or more 1.26 bouts of MVPA 1.25 Odds ratio Referent 1 Odds of being 0.75 .68 overweight 0.5 One Two Three Four Five Six Seven Number of facilities per block group *using Add Health data Gordon-Larsen et al, Pediatrics, 2006 http://www.pediatrics.org/cgi/content/full/117/2/417 www.activelivingresearch.org