1. Critical perspectives on heat vulnerability assessment: case studies in Phoenix, AZ Wen-Ching Chuang, Ph.D. Arizona State University November 5, 2014 2 ND International UGEC Conference, Taipei, Taiwan

2. Theoretical framework Definition of vulnerability the degree to which a system or system component is likely to experience harm due to exposure to hazard, either perturbation or stress. 2 Exposure Sensitivity Adaptive capacity

3. Adapted from Turner et al. 2003 3 Exposure SensitivityResilience urban residents (all kinds) Heat events : frequency, magnitude, duration A framework for vulnerability analysis in sustainability science Human conditions Environmental conditions Adaptive/coping capacity heat-related health outcomes Adjustment & adaptation

4. Social Vulnerability Index (SoVI ) Social Vulnerability (SoVI) to Environmental Hazards (Cutter et al. 2003) Key concern: Socioeconomically disadvantaged populations are vulnerable to environmental hazards. Method: Principal component analysis of a set of indicating variables from the Census data

5. Indicators of SoVI Neighborhood characteristics Percent of Children living in Married Couple Families Percent of household receiving social security People per unit Percent Renters Median House Value Median Gross Rent Percent Mobile Homes Percent Unoccupied housing unit Wealth/income/(medical) resources/ Unemployment Percent Poverty Percent of Households Earning Greater than $200k annually Per capita income Hospital per capita (county level only) percent of population without health insurance (county level only) Percent Civilian Unemployment Percent of Housing Units with No car

6. Indicators of SoVI Race/ethnicity/gender Percent Asian Percent Black Percent Hispanic Percent Native American Percent Female Percent Female Headed Households Age Percent of population under 5 yrs or above 65 Median age Education/language barrier percent of population without health insurance (county level only) percent speaking English as a second language with limited English Proficiency Vulnerable workforce Percent Employment in Extractive Industries Percent employment in service industry percent female participation in labor force preexisting health condition Percent of population living in nursing and skilled-nursing facilities

9. The gap between SoVI and actual health burden in Arizona

10. Usefulness of a generic heat vulnerability index (HVI) in Phoenix 10 Reid et al. 2009 How effective is the national HVI in local application?

11. Usefulness of a generic heat vulnerability index (HVI) in Phoenix Variables: Poverty, ethnic minority, no high school diploma, age above 65, no central AC, no AC of any kind, no green space, elderly living alone, and diabetes. Methods Factor analysis that identifies major risk factors Multinomial logistic regression model that tests the accuracy of the national HVI using factor scores and heat-related hospital admissions 11

12. Usefulness of a generic heat vulnerability index (HVI) in Phoenix Factors of risk components: 12 Factors at a local scale 1: Poverty, ethnic minority and low education 2: Lack of AC and vegetation 3:Diabetes and social isolation (including elderly living alone) Factors at the national scale 1: Poverty, ethnic minority and low education and no green space 2: Social isolation (living alone and elderly living alone) 3: Lack of AC 4: Proportion of elderly/diabetes

13. 13 Usefulness of a generic heat vulnerability index (HVI) in Phoenix Results of multinomial logistic regression Factor 2 (Lack of AC ) is not significant.

14. 14 Group 1: The high-incidence neighborhoodsGroup 2: The zero-incidence neighborhoods HVI used in the national study accurately classified only about 54% of the census tracts in Phoenix. Usefulness of a generic heat vulnerability index (HVI) in Phoenix

15. Vulnerability mapping using two types of health data Heat-related emergency calls (heat 911 calls) Occurrence-based data (locations of incidents) Heat-related hospitalization data Residence-based data (home addresses of patients) 15 Challenges of vulnerability mapping

16. Geospatial analysis 16 = Highlights effected areas, produces hot-spots maps Challenges of vulnerability mapping

17. 17 (1)911 calls (locations of incidents) (2) Hospitalization (home addresses) South Mountain Challenges of vulnerability mapping

18. Conclusion 18 HVI used in a national study has flaws in predicting actual heat hospital admissions in Phoenix. Cities will need to incorporate place-based factors to increase the usefulness of vulnerability indices and mapping to decision making. Vulnerability indices are sensitive to scale, measurement, and context, using multiple datasets and different approaches could help decision makers develop effective intervention strategies.

19. Thank you