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 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 Populationin 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%

24.7%

26.9%

12.5%

Total 8,636

Streets around the target schools

Scoping - Create Logic Model

Education: safety training Social norms

Physical activity (long-term)

CVD risk factors

Obesity

Asthma

Insulin sensitivity

walkability

Motor vehicle use

cancers

osteoporosis

Mental health

Air and noise pollution

Enforcement: increase police presence, crossing guards

Engineering: improve pedestrian facilities, traffic calming Perceptions

of risk

Injury

Physical activity (short-term)

safety

Policy Proximal Intermediate HealthImpacts Impacts Outcomes

Dedicated resources: walking school busses

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 % n % n

Elementary 53.2% 2,060 46.8% 1,810 100.0% 3,870

Middle School 52.1% 1,110 47.9% 1,020 100.0% 2,130

Total 52.8% 3,170 47.2% 2,830   6,000

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 0.6

Assumed walking speed (mi/hr) 1.8 N/A 1.8

Avg # days walked to school among those who walk to school (days/week) 3 5 3

% of total who walk to school at baseline:  

inputs below must be >0 & ≤ max.

specified at left

Elementary 24% 90% 24%

Middle School 24% 90% 24%

% increase in # walkers due to intervention:    

inputs below must be >0 & ≤ max.

specified at left

Elementary 64% 317% 64%

Middle School 64% 317% 64%

• 39% of students are expected to walk after the intervention (64% increase)

• Avg. of 15 min/day additional walking

Risk Assessment – Expected Outcomes on Physical Activity

Risk Assessment – Expected Outcomes for BMI

Change in average BMI due to increase in pa

Number of students in sub-groupChange 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 -.001 3170

Average all females -.020 -.003 2830

Average all overweight

-.053 -.08 1873

Total -.014 -.002 6000* estimates from Berkey et al, 2003

Increase in Daily Hours of PA by Number of 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

0.00

0.15

0.30

0.45

0.60

1 2 3 4 5

# Days Walked to School

Ave

rag

e D

aily

Ho

urs

of

PA

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

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

1 2 3 4 5

# Days Walked to School

Av

era

ge

De

cre

as

e in

BM

I

Increase in Daily Hours of PA by Intervention Effect

0.00

0.05

0.10

0.15

0.20

0.25

10% 30% 50% 70% 90% 317%

Intervention effect

Ave

rag

e D

aily

Ho

urs

of

PA

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

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

Implications of Case Study

Key Challenges of HIA

Uncertainties (data, models, policy) Timeliness Relevance to stakeholders and decision

makers

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