Health Co-Benefits of Increased Walking and Cycling in Urban by 66pgoq


									Walking, Biking, Electric Driving:
What are the Health Benefits of Sustainable
Transportation Alternatives?
Neil Maizlish, PhD, MPH, Epidemiologist
California Department of Public Health
Center for Chronic Disease Prevention and Health Promotion

Presented at the Center for Healthcare Policy and Research
UC Davis Medical Center, Sacramento

March 21, 2012                                               1
Climate Change and Public Health
• Climate change no. 1 public health threat in 21st Century
• California 12th largest greenhouse gas emitter in world
• Transportation is the largest source of GHGs in California –
  38% of total (179 MMT CO2E in 2003)
  • Personal passenger vehicles account for 30% (79% of 38%)
• How can we reduce GHG emissions in transportation?
  • Increase efficiency of vehicles and fuels
  • Reduce vehicle miles traveled (less trips, mode
    switching (SOV to mass transport), walking/bicycling
    (active transport)

                ?               ?            ?                 ?   2
Smart Strategies Solve Multiple Problems
• Strategies to reduce GHG emissions impact health
   • Do the strategies generate health co-benefits?
                                               Chronic Disease/
       GHGs                                    Obesity Epidemic

  • Do the strategies generate harms?
  • What strategies yield significant health co-benefits?
  • How do we measure this?                                       3
Groundbreaking Health Co-Benefits Research
• 2009 London Study: estimated the health impacts of alternative
  strategies for reducing carbon dioxide emissions from transport.
   • Lower carbon driving
       • Lower carbon emission motor vehicles/fuels
   • Increased active travel
       • Replacing urban car and motorcycle trips with
                                                         Dr. James Woodcock
          walking or bicycling
• Shift from 10 to 30 minutes/day of walking and bicycling:
   19% Cardiovascular Disease
   15% Diabetes
   13% Breast Cancer              =
    8% Dementia
    38% CO2 Emissions
* Woodcock J, Edwards P, Tonne C, Armstrong BG, Ashiru O, Banister D, et al. Public health benefits of   4
strategies to reduce greenhouse-gas emissions: urban land transport. The Lancet 2009;374:1930-1943.
Can the London Active Transport Model Be Adapted for Regional
Transportation Plans in California?
California Department of Public Health
• Partner with MTC (regional MPO) and
  BAAQMD to apply the London model
  (aka ITHIM) to the Bay Area
   • Test the feasibility
   • Develop a tool kit and technical resources
     to assist other MPOs apply the model to
     their geographic area

The Model Integrates Bay Area Data on Health and Travel


                       Premature Deaths
                       Years of Life Lost
                       Years Living with Disability
Active Transport and Low Carbon Driving Scenarios
                                                         Cities with high levels of walking and biking to work
1. Bay Area Benchmarks (Leading Cities)
    • Scenario: All Bay Area cities
      achieve by 2035 the walking
      and biking levels of the 2009
      Bay Area leaders (SF, Oakland,
      Palo Alto, Berkeley, Mtn. View,
      Rohnert Park, Morgan Hill)

2. Replace short car trips with active transport
    • 45% of 2006 Bay Area car trips were < 3 miles
    • 60% of car trips were < 5 mi
    • Scenario: 1/2 of trips <1.5 miles walked and 1/2 of trips 1.5 to 5 miles bicycled

3. Attaining Carbon and Physical Activity Goals (C/PAG)
    • Back cast the amount of active transport time and distance to reduce car VMT and
       increase active transport to optimum levels (no more than average commute time to
       work ~25 minutes); land use and infrastructure exist to support changes

4.    Low Carbon Driving (LCD)
     • Fuel efficiency increases, low carbon fuels and low/no emissions cars and light trucks                    7
        become more widespread, but there are no changes in physical activity or driving
Daily Active Travel Times and Distances for a Typical Resident

 BAU = Business-as-Usual
Summary of Bay Area Scenarios: Active Transport and Low Carbon Driving

   Active Transport Scenarios
    • 2-3 fold increase in walking (2.6%-4.3% of distance mode share)
    • 4-16 fold increase in bicycling (2.9%-10.7% of distance mode share)
    • Carbon reduction goal has 15% of distance mode share from active transport
    • 4%-15% decrease in car VMT

    Low Carbon Driving
    • Penetration of gas-electric hybrid vehicles and light duty diesels, increased biofuels
      usage and the penetration of electric vehicles (Pavley I&II)
       • BAU/incremental changes 16.5% decrease
       • Electrification and biofuels (9%-33.5% decrease)

Methods for Assessing Health Outcomes for Active Transport

•   Comparative Risk Assessment
       Disease Burden = Attributable Fraction × Disease Burden
                      Percent change in disease rates from BAU due
                  to shift in exposure distribution in the alternative scenario
                      RR   x
                                 Population(BAU) x RR x  Population(Alt.)x
               AF    x                                x
                                                 Population(BAU) x

    RR is the relative risk of the health outcome at the given exposure level
•   For physical activity, exposure, x, is the hours per week spent in walking and
    bicycling (and all other physical activity),
•   For air pollution, exposure, x, is the concentration of fine particulate matter
•   Burden of Disease
      Disability Adjusted Life Year, DALY, is a measure of premature mortality and
         disability based on the years of life lost, YLL (years of expected life - age at
         death) + years lived with a disability, YLD                                        10
                                 DALY = YLL + YLD
Meta-analyses for Assessing Health Outcomes for Active Transport

 • Physical Activity
    • Based on strong quantitative evidence of a link between exposure pathways
      and health outcomes, the following health outcomes were chosen:
      Condition        Studies included                Relative     Exposure (Metabolic
                                                       Risk         Equivalents)*
      Breast cancer    19 cohort studies, 29 case          0.94     each additional h/wk
                       control studies
      Cardiovascular   18 cohort studies (459,833         0.84      3 hrs walking per week (7.5
      disease          people, 19,249 cases)                        METs/wk )
      Colon cancer     15 cohorts (7873 cases)          Women:      30.1 METs/wk
                                                         Men:       30.9 METs/wk
      Depression       Cohort study (10,201 men,                    Kcal/wk
                       387 first episodes physician-        1       <1000
                       diagnosed depression)              0.83      1000-2499
                                                          0.72      2500+
      Diabetes         10 cohort studies (301,211         0.83      10 METs/wk
                       people, 9367 cases)

    * Metabolic Equivalent is amount of energy expended of a person at rest (1 MET = 1 kcal/kg/hr)
Health Impacts of Active Transport Scenarios
                         Change in disease        Change in premature
                             burden                     deaths
 Cardiovascular Dis.           6-15%                   724-1895*

      Diabetes                 6-15%                     73-189

    Depression                  2-6%                        <2

     Dementia                  3-10%                     63-218
   Breast cancer                2-5%                      15-48

   Colon Cancer                 2-6%                      17-53

Road traffic crashes          10-19%                     60-113
        * Range reflects range of physical activity in scenarios
Annual Health Benefits of Active Transport and Low Carbon Driving in
the Bay Area: Predictions from the ITHIM Model

                           Source of Health Benefit or Harm

                (Scenario 3: Active transport       Scenario 4         13
                   15% of miles traveled)
Annual Aggregate Reductions in Passenger Vehicle Greenhouse Gas Emissions
from Different Transport Scenarios

                                                                                                       2000 Baseline
                                                                                                       27.9 MMTCO2

                                 45% Reduction 2035 Goal

   # Based on car VMT*BASSTEGG emission factor
   * Per capita reduction of 26%                                                                                       14
   † Adjusted for double counting of mode choice
   BAU, Business-as-Usual; LCD, Low Carbon Driving; TD, Top Decile of Cities; ATC, Active Transport Carbon Goal
Summary of Findings
A shift in active transport from a median of 4.4 to
22 minutes/day (2% to 15% mode share):
• Disease reductions
  14% of heart disease, stroke, and diabetes
  6-7% of dementia and depression
  5% of breast and colon cancer
• Major public health impact
   • Adds about 9.5 months of life expectancy
   • $1.4 to $22 billion annual Bay Area health cost savings

Summary of Findings
• Injuries
   19% of injuries to pedestrian and bicyclists
• Physical activity accounts for almost all the health
  benefits; air pollution < 1%
• ~15% reductions in CO2 emissions
• Low carbon driving is not as important as physical activity
  for generating health co-benefits
Together, low carbon driving and active transport can
  achieve California’s carbon reduction goals and optimize
  the health of the population

                         +                =
• The Team
   • Linda Rudolph, CDPH (conceived the project), Sacramento
   • Neil Maizlish, CDPH, Richmond
   • James Woodcock, UKCRC Centre for Diet and Activity Research (CEDAR), UK
   • Sean Co, Metropolitan Transportation Commission, Oakland
   • Bart Ostro, Centre for Research in Environmental Epidemiology (CREAL), Spain
   • Amir Fanai and David Fairley, Bay Area Air Quality Management District, San Francisco
• Other Contributors
   • Caroline Rodier, Urban Land Use & Transportation Program, UC Davis
   • Dr. Phil Edwards and Dr. Zaid Chalabi, London School of Hygiene and Tropical Medicine
   • Colin Mathers, World Health Organization, Geneva
   • Other staff from MTC, UCD, CDPH, Mike Zdeb (University at Albany, NY)
• Partial funding and grant support
   • The California Endowment, Oakland
   • Kaiser Permanente – Northern California Community Benefits Programs, Oakland
   • Public Health Law and Policy, Oakland, CA
   • Public Health Institute, Oakland                                                        17
Contact Information

                     Neil Maizlish (

                                Report available at:


                                 N Maizlish – 10/24/11

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