Developing Analytic Forecasting Methodologies for Health Impact Assessment

1. Developing Analytic Forecasting Methodologies for Health Impact Assessment Rajiv Bhatia, MD, MPH San Francisco Department of Public Health

2. Presentation Overview • The Distinction Among Assessment of Existing Conditions vs. Monitoring vs. Forecasting • Three Examples: • Existing Forecasting Method • New Method Based on Existing Research • New Method Based on New Research • Implications for Alaska HIA Rajiv Bhatia Alaska Health Impact Assessment Training 2008

3. Example 1: Assessment and Mitigation of Roadway Air Pollution Impacts on Sensitive Uses • State and National air quality standards concern limited pollutants • Regional monitoring does not capture intra-urban variation in exposure • Regulations limit tailpipe emissions per mile but not vehicle intensity • Local agencies do not regulate air quality land use conflicts related to high volume roadways Rajiv Bhatia Alaska Health Impact Assessment Training 2008

4. Available Health Effects Assessment Methods For Air Quality Assessment • Dose response functions can associate area-level air quality exposures with health effects • Air quality dispersion models and other techniques can assess roadway related air quality exposure based on: • Vehicle Flow, Speed • Emissions • Meteorology • Relationship between Facilities and Sensitive Receptors Rajiv Bhatia Alaska Health Impact Assessment Training 2008

5. Estimating Mortality Impacts From Exposure to PM2.5 based on CARB CR Functions Mortality = R0• [exp(-*∆PM2.5 -1) ] • P • R0 = Baseline Mortality Rate •  = Coefficient Derived from Relative Risk • P = Affected Population Rajiv Bhatia Alaska Health Impact Assessment Training 2008

6. Spatial Extent of Vehicle PM2.5 All Vehicle Sources using CAL3QHCR—West Oakland, CA Rajiv Bhatia Alaska Health Impact Assessment Training 2008

7. Applications • Location of Sensitive Uses • Transportation System Planning • Indoor Air Quality Ventilation Standards Rajiv Bhatia Alaska Health Impact Assessment Training 2008

8. Example 2: Quantifying the Health Benefits of a Living Wage • Few analyses health benefits of labor policies Plausible relationship meditated through material needs • Consistent association among high quality epidemiologic studies on income and health looking at multiple health outcomes Rajiv Bhatia Alaska Health Impact Assessment Training 2008

9. Data Required For Impact Analysis • The baseline income of the population targeted by the living wage • The estimated income gains of workers benefiting from the new wage • A dose response function between income and health outcomes Rajiv Bhatia Alaska Health Impact Assessment Training 2008

10. Inclusion Criteria For Studies Providing Dose-Response Relationships • English language peer reviewed literature 1990-1998 • Studies of income and mortality, hospitalizations, or health status indicators • Subjects representative of the U.S. general population • Income measured at the household, family or individual level • Longitudinal design • Statistical adjustment for age and gender year of income ascertainment provided • Income applied as a continuous variable Rajiv Bhatia Alaska Health Impact Assessment Training 2008

11. Estimated Health Effects Due To Living Wage Income Gains For Workers With A Current Family Income of $20,000 Rajiv Bhatia Alaska Health Impact Assessment Training 2008

12. Example 3: Area-level Model of Pedestrian Vehicle Collisions • Transportation Analyses in EIA provides little analysis of Pedestrian Safety Impacts: • Vehicle-pedestrian injuries and fatalities are preventable. • Key area-level environmental determinants of collisions include: • Traffic volumes • Traffic speed • Pedestrian activity Rajiv Bhatia Alaska Health Impact Assessment Training 2008

13. Vehicle-pedestrian injury collisions: San Francisco, California census tracts (2001–2005) An Environmental Approach: Evident area-level patterns – correlate with the freeway network, concentrations of streets with heavy arterial traffic, pedestrian activity centers (e.g., downtown, Golden Gate Park). Rajiv Bhatia Alaska Health Impact Assessment Training 2008

14. Built Environment : street and land use characteristics Vehicle - Pedestrian Collisions Population Characteristics : ( Number ): number of residents and workers , pedestrian injury socio - demographic characteristics and death Travel Behaviors : walking , public transit , private vehicle use Model development framework How do transportation, land use, and population factors predict change in pedestrian injury collisions in San Francisco census tracts? Rajiv Bhatia Alaska Health Impact Assessment Training 2008

15. Vehicle-Pedestrian Injury Collision Model • Publicly available data (SWITRS, U.S. Census, SF Planning, SF MTA) • Traffic Volume, Street Characteristics – SF DPH/UC Berkeley • Continuous, census-tract level variables • Multivariate, linear regression model – predicts the natural log of vehicle-pedestrian injury collisions: ln(PIC) = b0 + ∑biXi Rajiv Bhatia Alaska Health Impact Assessment Training 2008

16. Vehicle-Pedestrian Injury Collision Final Model Variables • Traffic volume (+) • Arterial streets (+) • Neighborhood commercial zoning (+) • Employees (+) • Residents (+) • Land area (-) • Below poverty level (+) • Age 65 and over (-) Rajiv Bhatia Alaska Health Impact Assessment Training 2008

17. Final Ordinary Least Squares Regression Model Vehicle-Pedestrian Injury Collisions: San Francisco, California, 2001-2005 (n=175 census tracts) a Excludes grade-separated street segments inaccessible to pedestrians. Rajiv Bhatia Alaska Health Impact Assessment Training 2008

18. Comparing the Simple Bivariate Model to Our Multivariate Model Approach Holding all covariates constant (as above), the model is equivalent to a power function with β=0.753. Rajiv Bhatia Alaska Health Impact Assessment Training 2008

19. Vehicle-Pedestrian Injury Collision Model: Eastern Neighborhoods Plans EIR Analysis a Areas defined based on SF Planning boundaries, and census tracts used for the Eastern Neighborhoods Rezoning Socioeconomic Impacts analysis. b Census Tract, Aggregate Traffic Volumes. c Based on the Air Quality Chapter, Eastern Neighborhoods Pre-draft Environmental Impact Report, 2007. d Population increases based on increased population and housing units projected in Rezoning Option B, detailed in the draft Eastern Neighborhoods Rezoning and Community Plans, Environmental Setting and Impacts, April 2007. Rajiv Bhatia Alaska Health Impact Assessment Training 2008

20. Vehicle-Pedestrian Injury Collision Model: Eastern Neighborhoods Plans EIR Analysis Predicted % change in pedestrian injury collisions based on estimated changesin resident population and traffic volume. 20% 21% 15% 24% Rajiv Bhatia Alaska Health Impact Assessment Training 2008

21. Vehicle-Pedestrian Injury Collision Model: Application • Land Use Development • Transportation Facilities Planning and Funding • Congestion Pricing and other Transportation Policy Rajiv Bhatia Alaska Health Impact Assessment Training 2008

22. A General Approach to Predicting Health Effects Using Epidemiological Research • Develop Clear Analytic Objectives • Literature Review • Develop study criteria and data needs • Identify Sources • Establish Adequacy of Existing Reviews • Evaluate studies • Formal summary and documentation of review • Make qualitative inferences on health effects • If appropriate and feasible, quantify effects • Select or generate a summary effect measure • Estimate Baseline and Changes to “Exposure” • Predict Health Impacts (PAR, Forecasting) • Qualify certainty of assessment & predictions Rajiv Bhatia Alaska Health Impact Assessment Training 2008

23. Developing Forecasting Methods for Alaskan HIA • Some environmental - health relationships may be generalizable from general population studies • HIA forecasting methods in Alaska probably requires new research environmental-health relationships • Data collection and monitoring will support long term research efforts Rajiv Bhatia Alaska Health Impact Assessment Training 2008