# Presentation: 142392

## Measuring the Impact of the AQI on Behavior and Health Outcomes

- P.O. Box 12194  ·  3040 Cornwallis Road  ·  Research Triangle Park, NC  27709Phone: 919-541-8053  ·  Fax: 919-541-6683  ·  carolm@rti.org  ·  www.rti.org
- RTI International is a trade name of Research Triangle Institute.

*Presented at *
**Quality of Air Means Quality of Life: **
**2006 National Air Quality Conferences**
*Presented by **	***Carol Mansfield**
**Senior Economist, RTI International**

## Overview

- Why study the impact of the AQI on behavior and health outcomes?
- What are different impacts we might study?
- Planning for the National-Scale Activity Survey (N-SAS)
- “Do Parents Respond to Ozone Alerts?” RTI study funded by an EPA STAR grant

## Twelve-year-old Justin Turnage’s asthma flared up again this year, and his doctors say ozone is the likely culprit.  Now his mother hopes that board games and music lessons will keep her son indoors on ozone alert days.  
“Summer is going to be very hard for him,” she said. 
(Raleigh News & Observer, May 1, 2001)

***“******Summer is going to be very hard for him,” she said. ***
- (*Raleigh* *News & Observer*, May 1, 2001)

## Why study the impact of the AQI on behavior?

**Program design and outreach**
- Identify vulnerable populations that are unaware of or do not understand the recommendations in the AQI message.
- Compare awareness and understanding in communities with different advisory messages (e.g., today is a “red day” verus “ozone alert day”).

## Why study the impact of the AQI on behavior?

**Improve economic analysis of air quality benefits**
- Capture *full *economic benefits of air quality improvements, including protective activities in response to air pollution
- Develop new measures of the dollar value the public places on the benefits related to improved air quality
- Evaluate data sources – compare self-reported data on behavioral changes with data from diary studies.

## Why study the impact of the AQI on behavior?

**Improve exposure modeling and human health (risk) assessment**
- Identify populations in which exposure misclassification might be a problem.
- Calibrate existing epidemiological studies or better explain heterogeneity across locations.
- Enhance studies linking health effects to air pollution and the development of concentration-response functions

## Why study the impact of the AQI on behavior?

**Accountability initiatives **
- The Clean Air Act Advisory Committee recommended that EPA
- “study effects of AQI advisories on exposure-reduction behaviors and whether behaviors lead to health benefits”  as one way to evaluate the impact of AQI advisories

## What impacts should we study?

**Awareness:  **Of a specific warning system and the air pollution problem the warning system addresses.
**Knowledge of outcomes:  **Short-term recall of warnings and air pollution events, knowledge of long term trends, health effects
**Understanding the messages:  **Do people remember the message and know how to use the information?
**Perceived risk: **Do warnings alter perceptions about places or activities?

## What impacts should we study?

**Changes in behavior  **
**Short-term** **responses** (daily, weekly) – reduce outdoor time, less strenuous activities, increase medication use, drive less
**Longer-term changes** (permanent) – change job, residence, activities
**Non-traditional changes**: new membership in nonprofit groups, voluntary activity, political activity
**Changes in health outcomes**

## Stages of the Precautionary Adoption Process Model 

| Unaware of Issue | Never heard of the AQI, precautionary actions |
| --- | --- |
| Unengaged by Issue | Never thought about changing planned activities because of AQI or air pollution |
| Deciding about Acting | Undecided about changing planned activities because of air pollution |
| Decided Not to Act | Decided not to change planned activities because of air pollution |
| Decided to Act | Decided to change planned activities because of air pollution |
| Acting | Changing planned activities because of air pollution |
| Maintenance | Continues to check air pollution levels and modifies actions accordingly |

## National Scale Activity Survey N-SAS  

- OAQPS designing a nationally representative survey to measure awareness, knowledge, risk perceptions, reported behavior
- Data on geographic location, distance to highways and other sources
- Paired with detailed activity diary studies and exposure information in specific cities

## N-SAS

- Opportunities for collaboration
- With other EPA offices and with local and state air quality regulators
- Modules covering regionally specific topics or issues excluded from the basic national survey
- Modules designed to fit with national survey, leverage resources by administering together
- Talk to Susan Stone or            Zachary  Pekar (OAQPS)!

## N-SAS: Possible topics

**Factual questions about air quality**
- Air quality on that day or over specific time period
- Acute and long-term health effects
- How air quality varies with season and time of day
**Awareness of air quality warning systems and messages**
- Names of advisory systems, sources of information
- Sensitive populations and recommended behavior
- Reported use of AQI warnings in short- and long-term decision making
**Demonstrated ability to use information**
- Questions requiring judgments based on advisory information

## N-SAS: Possible topics

**Reported actions in response to warnings**
- Short-term (day-to-day) actions, including actions that reduce the level of pollution in the city
- Long-term responses over season or year: permanent changes to activity patterns, moving, changing jobs
**Benefit measures**
- Estimate individuals’ values for air quality improvements, reduced morbidity, increased opportunities for outdoor time
- Estimate the value of public programs to provide better air quality information
- Help interpret dose-response studies and functions

## N-SAS: Possible topics

**Health status of individual and/or family**
- Including chronic conditions that affect behavior related to exposure (e.g., obesity), but are not otherwise related to air quality
**Characterization of individual and household situation**
- Work/leisure time, flexibility in work time, care giving responsibility, insurance status
- Time horizon for choices (e.g., plan to move, retire)
**Sociodemographic characteristics**

## N-SAS: Possible topics

**Other factors related to PM and ozone exposure **
- Housing attributes, neighborhood, indoor sources, sources at job site or school
**Activity profiles**
- Location of activity (indoors/outdoors)
- Level of exertion
- Location of activities within their city or county (either categories such as work/home or specific locations on a map)
- Daily symptoms and medication use

## N-SAS: Possible topics

**Questions from other national or regional surveys**
- Coordinating with other surveys (e.g., NHIS, NHANES, MEPS)
- Ask the same questions to compare results across studies
- Ask questions that help understand results from other surveys
- Jointly estimate data from your survey and the national survey

## Evidence on Awareness from RTI/KN Health and Aging Survey

- Nationally representative, web-TV based panel (Knowledge Networks), N=6,300
- 33% had heard of the color-based alert system
- 54% correctly reported that their county had experienced a code orange day during that summer
- On ozone alert days,
- 57% spent less time outdoors
- 56% reported driving less
- 48% reported engaging in both activities
- 44% of respondents reported making neither behavioral adjustment.

## Factors Affecting Awareness from RTI/KN Survey

- More likely to be aware
- Older adults
- Females
- African-Americans and Whites
- More educated
- Better overall health
- Employed full time or students, homemakers or retired persons
- Higher ozone in current summer
- History of higher ozone

## Factors Affecting Reported Behavior from RTI/KN Survey

- More likely to report staying indoors or reducing outdoor time if
- Older
- Female
- Not white
- Households with income less than $75,000
- Fair or poor health status
- In county with at least 1 purple day in current summer

## Factors Affecting Reported Behavior from RTI/KN Survey

- More likely to report driving less or not at all if
- Female
- Households with income less than $75,000
- Not white
- Good, fair or poor health status
- In county with at least 1 purple day in current summer

## Evidence on Behavior Change

**Neidell (2005, 2004, 2002), Columbia University**
**A decline in attendance by 3% to 11% at a selection of outdoor events in California could be attributed to smog alerts.**
**Negative, significant relationship between health advisories (proxies for avoidance behavior) and hospitalizations. **
**For children, but not adults, smog alerts lead to a decrease in asthma hospital admissions, avoidance behavior may lead to bias in estimates of the biological effect of ozone on health. **
**Families of high socioeconomic status display particularly strong patterns of avoidance behavior.**

## RTI STAR Grant Research Questions

- What determines parents’ awareness of ozone alerts?
- Do parents change their child’s behavior on high ozone days?
- Do families with asthmatic children behave differently?

## Survey Methodology 

- Sample frame: Drawn from the Harris Interactive Online marketing panel (self-selected panel)
- Inclusion criteria:
- 35 highest ozone MSA’s
- Child 2 to 12 years old
- One stay-at-home parent to supervise child during July/August 2002

## Survey

- Sample sizes
- 506 households child free from chronic disease
- 473 households with child with asthma
- Web-based surveys
- Able to send survey by email link on specific days
- Close survey after 48 hours for data quality

## Activity Diary Design

- Timing
- Target 3 red + 3 green days in July-September
- Child’s daytime activities
- Activity type
- Duration
- Level of activity
- Indoor/outdoor, home/away
- Daily symptoms, medicine use
- Asthma status over last week

## Response Rates

- 979 (95%) of those who qualified based on screening survey took baseline survey
- 768 (79%) of these respondents completed 2,844 usable diaries
- 469 (48%) responded to the debriefing survey

## Awareness of Alert Systems

| Type of Warning System  | Percent of Households |
| --- | --- |
| Colors that represent the level of air pollution | 54% |
| Ozone Action Day | 20% |
| Air Pollution Watch | 24% |
| Ozone Watch | 24% |
| Smog Alert/Ozone Alert | 48% |
| Other | 3% |

## Pattern of AQI Use

| Frequency Description | Percent of Households |
| --- | --- |
| I look for the air pollution forecast myself every day or almost every day | 18% |
| I look for the air pollution forecast myself some days | 13% |
| I do not check the forecast, but I pay attention when I see air pollution information | 49% |
| I rarely or never pay attention to air pollution | 18% |
| Other |   2% |

## Slide 30

| Activity | Percent of Households |
| --- | --- |
| I spend less time outdoors | 55% |
| I have my child spend less time outdoors | 69% |
| I do less strenuous activities | 30% |
| I have my child do less strenuous activities | 39% |
| I drive my car less | 22% |
| I don’t do anything differently | 23% |

## Diary-Level Summary Statistics (N=2,844)

|  | Mean  | Std Dev |
| --- | --- | --- |
| Totally Outdoor Hours 
(if outdoors>0) | 1.52 | 1.49 |
| Spent Time Totally Outdoors | 48% | 50 |
| Code Red Days | 27% | 0.44 |
| Code Orange Days | 13% | 0.33 |

## Awareness and Reported Behavior

## Determinants of Parents’ Ozone Forecast Monitoring

- Parents of asthmatics more likely to report checking AQI forecast frequently
- More serious asthma = more frequent checking
- More children = less frequent checking
- White parent = less frequent checking

## Summary of results on time outdoors

- Evidence that
- Air pollution sensitive asthmatics reduce time outdoors on code red days (based on daily diaries)
- 30+ minute reduction in time outdoors on Code Red day relative to non-Code Red day

## Air Pollution Sensitive vs. Not Air Pollution Sensitive Asthmatics

## Next Steps for N-SAS

- Input on survey design
- Topics
- Questions
- Sample
- Survey pretesting