1. Assessing the Impact of Community Policy on Physical Activity and Health with Health Impact Analysis Candace Rutt, Ph.D. Division of Nutrition and Physical Activity National Canter for Chronic Disease Prevention and Health Promotion Centers for Disease Control and Prevention

2. What is Smart Growth? Greater density Greater land-use mix
Greater connectivity
Range of housing opportunities
Strong “sense of place”
Pedestrian friendly
Numerous transportation choices
Preserve exisiting greenspace

3. How Does the Built Environment Impact Health?
Physical activity (recreation and transportation)
Social Capital
Air quality
Water quality
Mental health

4. TRB/IOM
Changing the built environment to make it more activity conducive is desirable “even in the absence of the goal of increasing physical activity because of their positive social effects on neighborhood safety, sense of community, and quality of life”

5. Health Impact Assessment (HIA)
A combination of procedures, methods, and tools by which a policy, program, or project may be judged as to its potential effects on the health of a population, and the distribution of those effects within the population (Gothenburg consensus statement, 1999)

6. Health Impact Assessment
Tool to objectively evaluate a project/policy before it is implemented
Provide recommendations to increase positive and minimize negative health outcomes
Encompasses a variety of methods and tools
Qualitative and quantitative
Community input and/or expert opinion
Has been performed extensively in Europe, Canada and other countries
Regulatory and voluntary basis

7. Potential Contributions of HIA
Bring potential health impacts to the attention of policy-makers, particularly when they are not already recognized or are otherwise unexpected
Highlight differential effects on population sub-groups

8. Using HIA for Projects vs. Policies
Projects: Physical developments (highway, rail line, park, trail, housing complex, etc)
Affect smaller population
More detailed plans
Easier to define target population, stakeholders, and perform impact estimation
Policies: Set of rules and regulations that govern activities and budget expenditures (zoning, farm subsidies, living wage law, etc.)
Affect larger population
Greater impact on public health
Health impacts may be harder to quantify

9. HIA Level of Complexity
Qualitative – describe direction but not magnitude of predicted results
Easy to predict; hard to use in cost/benefit models
Example: Build a sidewalk and people will walk more
Quantitative – describe direction and magnitude of predicted results
Difficult to obtain data; useful for cost/benefit models
Hypothetical example: Build a sidewalk and 300 people who live within 200 yards of location will walk an average of 15 extra minutes per day

10. Voluntary vs. Regulatory
Voluntary (a tool used by a health officer to inform a planning commission)
Simpler, less expensive, less litigious
Less likely to be used if not required
More politically acceptable
Regulatory (modeled on a required environmental impact statement)
More complex, more expensive, more litigious
More likely to be used if required
Less politically acceptable

11. Community Involvement in Conducting an HIA
Increases community buy-in to project
Helps identify social issues as well as health issues
Commonly used in HIAs in Europe
May add substantially to time and resources needed to conduct HIA

12. HIA efforts outside the U.S.
Extensive work for nearly a decade
Increasing interest
Usually focused on local projects
Often linked to EIA or focused on facilitating community participation
HIA efforts have been spurred by pressure on the World Bank to consider the health impacts of its projects, continuing efforts by the European Office of W.H.O. to to implement initiatives such as the Ottawa Charter and Healthy Cities, Canadian efforts to operationalize a population health approach in health planning, and in Britain by the Acheson Report on Health Disparities.
The World Bank, Canada, Australia and New Zealand have taken an EIA-based approach to HIA, while HIA in Sweden and Great Britain has taken the an approach that emphasizes community participation.

13. HIA in the U.S. To date only a handful have been completed
Voluntary basis
Very few people currently trained to complete HIAs
However, there is a lot of interest in HIA (APA, NACCHO, CDC, RWJF, FHWA, ARC, CQGRD)

14. Relationship of HIA to Environmental Impact Assessment
EIA
Regulatory
Thousands conducted each year
HIA components could logically fit within an EIA

15. Learning from EIA But EIAs… Long, complex documents
Process is time-consuming and expensive
Often litigious process
Tends to focus on projects, not policies
Tends to stop short of considering health outcomes

16. Steps in Conducting a Health Impact Assessment
Screening
Identify projects or policies for which an HIA would be useful
Scoping
Identify which health impacts should be included
Risk assessment
Identify how many and which people may be affected
Assess how they may be affected
Reporting of results to decision-makers
Create report suitable in length and depth for audience
Evaluation of impact on actual decision process

17. Screening – When to do HIA
In general, HIA is most useful
For policy-decisions outside health sector
When there are likely to be significant health impacts that are not already being considered
The HIA can be completed before key decisions are made and stakeholders are likely to use information
There are sufficient data and resources available

18. Scoping - Health Impacts to Consider in an HIA
Physical activity, obesity, CVD
Air quality, asthma, other respiratory diseases
Water quality, waterborne diseases
Food quality, food borne diseases, nutrition
Motor vehicle, pedestrian and other injuries
Accessibility for persons with disabilities
Noise
Mental health
Social capital
Social equity, environmental justice

19. Risk Assessment Logic frameworks Assessing research evidence
Qualitative vs. quantitative outcomes
Calculate estimates of morbidity and mortality
Cost-effectiveness when feasible

20. Examine Feasibility of HIA is U.S.
Received funding from RWJF to complete two case studies of HIA
Worked with UCLA to complete these case studies

21. Screening – Initial List of HIAs
General Walkability
Walk to School
Trails (recreation and transportation)
Active Commuting to Work
Worksite Interventions
Mass Transit
Zoning
Location Efficient Mortgage
Buford Highway
Beltine

22. Screening - Selection Criteria
Specific enough to create quantitative estimates
Impact physical activity
High quality data
Not overly complicated
Political interest
Target at risk populations
Foundation for other HIAs
Generalizability

23. Screening - Selecting Case Studies
Walk-to-school HIA
Natomas school district in Sacramento, CA
Buford Highway HIA
Highway redevelopment in Atlanta, GA

24. Screening - Site Selection
Sacramento was selected because:
Program already in-place, which facilitates determination of project and population parameters
Program staff interested in cooperating with research team
Minimal seasonality
Ethnically-mixed, modest income population
24% of students currently walking to school

25. Diverse Student Population in Natomas Schools
Elementary (K-5)
Middle School (6-8)
High School (9-12)
44.8%
24.7%
30.5%
Male
Female
51.8 %
48.2%
Non-Hispanic White
Black
Hispanic/Latino
Asian
27.1%
26.9%
12.5%
Total
8,636

26. Streets around the target schools

27. Scoping - Create Logic Model
Policy Proximal Intermediate Health
Impacts Impacts Outcomes
Education: safety training
Air and noise pollution
Asthma
Social norms
Obesity
walkability
Engineering: improve pedestrian facilities, traffic calming
Physical activity (long-term)
CVD risk factors
safety
Perceptions of risk
Insulin sensitivity
Enforcement: increase police presence, crossing guards
Motor vehicle use
cancers
osteoporosis
Physical activity (short-term)
Dedicated resources: walking school busses
Mental health
Injury

28. Risk Assessment
More thorough literature review of all identified proximal, intermediate, and health outcomes
Determine which health impacts will be done qualitatively versus quantitatively
Physical activity
BMI
Gather data and perform quantitative analysis

29. Risk Assessment – Baseline Data
California Department of Education enrollment statistics for Natomas Unified School District 2003, k-8th grade (
Enrollment in Natomas Unified schools
6,000
% of total enrollment in elementary grades
64.5%
TABLE 1-1: SEX DISTRIBUTION FOR EACH SCHOOL LEVEL (%)
Male
Female
total % n
Elementary
53.2%
2,060
46.8%
1,810
100.0%
3,870
Middle School
52.1%
1,110
47.9%
1,020
2,130
Total
52.8%
3,170
47.2%
2,830
California Department of Education enrollment statistics for Natomas Unified School District 2003, k-5th grade used for Elementary; 6-8th grade for Middle School (

30. Risk Assessment – Baseline Data
TABLE 1-2: PREVALENCE OF UNHEALTHY BODY COMPOSITION AND EXCESS BMI AT BASELINE
Assumed fraction of "unhealthy body composition" due to excess BMI =
95.0%
unhealthy body composition
Excess BMI (based on fraction of unhealthy body composition in the pop. due to excess BMI) %* % n
Elementary male
33.8%
32.1%
661
Elementary female
23.8%
22.6%
409
Middle school male
44.7%
42.47%
472
Middle school female
34.2%
32.5%
331
*California Dept of Ed "Fitnessgram" : 5th grade used for Elementary; 7th grade for Middle School (

31. Risk Assessment – Estimated Impact
TABLE 1-3: WALK-TO-SCHOOL PROGRAM CHARACTERISTICS
Default
Theoretical Max.
Input
Avg walk distance to school (mi)
0.6
N/A
Assumed walking speed (mi/hr)
1.8
Avg # days walked to school among those who walk to school (days/week) 3 5
% of total who walk to school at baseline:
inputs below must be >0 & ≤ max. specified at left
Elementary
24%
90%
Middle School
% increase in # walkers due to intervention:
64%
317%

32. Risk Assessment – Expected Outcomes on Physical Activity
39% of students are expected to walk after the intervention (64% increase)
Avg. of 15 min/day additional walking

33. Risk Assessment – Expected Outcomes for BMI
Change in average BMI due to increase in pa
Number of students in sub-group
Change in hours * (change in BMI/hrs. pa/day)
Participants
All students
Average all elem.
-.004
-.001
3870
Average all middle
-.015
-.002
2130
Average all males
-.009
3170
Average all females
-.020
-.003
2830
Average all overweight
-.053
-.08
1873
Total
-.014
6000
* estimates from Berkey et al, 2003

34. Increase in Daily Hours of PA by Number of Days Walked to School
0.60
0.45
Average Daily Hours of PA
0.30
0.15
0.00 1 2 3 4 5
# Days Walked to School
Number of days walked to school vs. average daily hours of physical activity among participants; Assuming 24% baseline walking, 0.6 miles one-way & 64% increase in walking due to intervention

35. Decrease in BMI (overweight) by Days Walked to School
Number of days walked to school vs. average decrease in BMI among obese participants; Assuming 24% baseline walking, 0.6 miles one-way & 64% increase in walking due to intervention

36. Increase in Daily Hours of PA by Intervention Effect

37. Traffic-related injury
Walk-to-school programs can actually decrease pedestrian injury rates:
No injuries reported in first two years of Marin County program
Orange County program reported a decrease in injury rates
Estimating changes pedestrian injury rates not feasible for small numbers/small areas

38. Air pollution: Expected Impacts
Walk-to-school programs may increase or decrease exposure to air pollution depending on
Current mode
Exposure to several pollutants x times higher inside diesel school buses than outside (Sabin, Behrentz, Winer et al., 2003)
Inhalation rates
Duration of trip
Traffic density along walking routes
Time and season
Marginal increase or decrease is probably small relative to PA-related impacts

39. Assumptions for Kids Walk
Assume a best-case scenario modeled after Marin county (different demographics)
Relationship between time spent walking and BMI from Berkey et al (2003) apply to younger children
1 year time horizon for effects
Average distance walked to school is 0.6 miles (NHTS, 2001)
Average walking speed is 1.8 miles/hour

40. Implications of Case Study
Walk-to-school programs are important, but only part of the solution of childhood obesity
HIA can either temper expectations, provide justification for termination, or provide strong support for programs/policies

41. Key Challenges of HIA Uncertainties (data, models, policy) Timeliness
Relevance to stakeholders and decision makers
Establishing the causal linkages that link health outcomes to a given policy is complicated by a lack of data, numerous steps mediating the effects, numerous, interacting effects which are not necessarily unidirectional, and a lack of consensus among experts. Progress in this area will require the work of many researchers over a long period of time.
Work on HIA is caught in a dilemma between investing sufficient resources, including time, to produce a solid analysis that expands what is known about a particular topic, but producing results quickly enough so as to have maximum benefit for policy decisions.
The strongest case for HIA is when it leads to a greater consideration of health effects of policies outside the health sector, but policy-makers’ training,responsibilities, interests and constituencies may make it difficult to advance the goals of HIA.
To date much of the work on HIA, including our own, has focused on the technical feasibility of HIA. To translate this research into practice collaborative relationships with legislators and their staffs need to be established to focus HIA on those issues where it will be most useful and to communicate the results of HIA in a way that is most usable.

42. Summary
HIA is a new and evolving science in the U.S., however it is a promising new approach to quantify health impacts of a wide variety of policies and projects
HIA provides only one piece of information (health) in complex decisions and stakeholders may have different priorities
HIA provides an outlet for health to be appropriately factored into complex decisions