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

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

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

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”

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)

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

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

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

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

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

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

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.

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)

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

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

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

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

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

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

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

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

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

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

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

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

Streets around the target schools

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

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

Risk Assessment – Baseline Data California Department of Education enrollment statistics for Natomas Unified School District 2003, k-8th grade (http://data1.cde.ca.gov/dataquest/) 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 (http://data1.cde.ca.gov/dataquest/)

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" 2002-2003: 5th grade used for Elementary; 7th grade for Middle School (http://data1.cde.ca.gov/dataquest)

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%

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

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

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

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

Increase in Daily Hours of PA by Intervention Effect

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

Air pollution: Expected Impacts Walk-to-school programs may increase or decrease exposure to air pollution depending on Current mode Exposure to several pollutants 50-400x 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

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

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

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.

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