Seasonal Variations in Asthma Hospital Admission in the United States

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Air Quality, Human Health, and the Economy in New
England Ongoing Research and Assessment
Cameron Wake and Thomas Lambert Institute for
the Study of Earth, Oceans and Space Tom
Kelly Office of Sustainability Programs Robert
Woodward Dept Health Management and Policy,
Economics Ross Gittell Management
Department Aicha Hassane Economics Jason
Rudokas Mathematics/Economics
NH DHHS and NH DES Concord, NH 10 Nov 2004
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Denora, Pennsylvania 29 Oct 1948
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Air Quality, Human Health, and the Economy in New
England Ongoing Research and Assessment
100 Cameron Wake - The NOAA funded AIRMAP
INHALE projects 115 Thomas Lambert - Summer 2004
Spirometry Testing 130 Jason Rudokas - Air
Quality and Indoor Worker Productivity 145
Aicha Hassane - Preliminary Analysis of
Respiratory and Cardiovascular Services at
Three Hospitals in New Hampshire 200 - 300
Discussion Joint UNH - NH DHHS- NH DES
efforts How do we collaborate to improve public
health?
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Conceptual Framework
Env Health Tracking
Vulnerability Sensitivity - Adaptation
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Portsmouth, NH Ozone Exceedance Days (8 hr ozone
gt 80 ppb)
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Portsmouth 8 hr Ozone vs Tmax 1982-2002
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AIRMAPMapping New Englands Changing Climate and
Air Qualityhttp//airmap.unh.edu
AIRMAP Atmospheric Investigation, Regional Modeli
ng, Analysis, and Prediction
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Summer 2004 ICARTT Campaign (International
Consortium for Atmospheric Research on Transport
and Transformations)
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INHALEIntegrated Human Health and Air Quality
Assessment

• Goal of INHALE project is to improve public
  health by
• Engaging a wide range of stakeholders in a
  collaborative effort to better define the link
  between broad measures of pulmonary health and
  air quality (e.g., pollution, pollen, mold,
  temperature, humidity)
• Using the results to create informed public
  policy and guide the product development of the
  NOAA air quality forecasting effort
• Determining the health care costs associated
  with air pollution events

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Economic and Public Health Research

• Quantitative economic assessment of health care
  and related costs of poor air quality in New
  England
• Examination of the potential uses of air quality
  information and forecasts

Research Objectives

• Improve understanding of relationship between air
  quality and hospital and health care operations
  and costs
• Identify beneficial applications of air quality
  information and forecasts by hospitals and
  employers of large numbers of workers

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Tip of the Iceberg
Adverse health effects that could be avoided
every year by meeting the US EPA's daily maximum
ozone standard (80 ppb 8-hr) in New York. Figure
sections not drawn to scale. From Thurston 1997.
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Summer 2004 Spirometry Testing
Thomas Lambert Institute for the Study of Earth,
Oceans and Space and Department of Earth
Sciences University of New Hampshire
NH DHHS and NH DES Concord, NH 10 Nov 2004
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INHALE - Summer 2004 Pulmonary Function Monitoring
Spirometry Twice daily
Respiratory Symptoms Once daily
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Over 60,000 Observations with 450 People in New
England
Peak Flow
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Preliminary Observations

• Pulmonary function responds over different time
  scales
• Seasonally
• Daily
• Within the day
• Over weeks

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First Second Volume (liters)
DES/DHHS
Retirement Community
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Standardized 6-Second Volume (liters)
DES/DHHS
Retirement Community
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6-Second Volume
DES/DHHS
Retirement Community
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Ozone 8 hour Maximum
Ozone ppbv
First Second Volume
DES/DHHS
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Fine Particulates µg/m3
Retirement FEV6 (liters)
DES/DHHS FEV6 (liters)
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Continuing Work

• Build models to explain the variability in
  pulmonary function
• Short term variability
• Seasonal variability
• How are allergens and respiratory symptoms
  affecting pulmonary function

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Air Quality and Indoor Worker Productivity

• Jason Rudokas, Undergraduate
• Mathematics/Economics
• University of New Hampshire

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Volunteer Employee Survey Summer of 2004

• Objective To explore how air quality effects
  employee and area resident behavior.
• Because of the exploratory nature of the inquiry,
  a broad cross-section of survey participants was
  desired.
• For example, volunteers with and without
  pre-existing respiratory, cardiovascular and
  pulmonary conditions (who might be most adversely
  affected by air quality) are desired.
• Participants of all ages, part-time and full-time
  employees, and workers in all occupations will
  also be sought.

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Employee Surveys

• The initial survey included background
  demographic questions (e.g., age, gender,
  household status and zip code of residence).
• On-going surveys.. once a week for 7 weeks, used
  to capture changes in behavior and work practices
  associated with air quality.
• Participating volunteers received (prompting)
  emails asking them to complete an on-line survey
  within 24 hours.
• On-going surveys included questions on
  day-to-day activities at work, going
  to-and-from work, and at-home.
• On-going survey will took fewer than 5 minutes to
  complete.
• All data collected in aggregate (no personal
  identifiers will be revealed) and subjected to
  the procedures, control and protocol established
  and protected by the UNH IRB.  

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The Respondent population is concentrated on the
Seacoast and Rockingham and Strafford Counties
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Survey Demographics

• Average Number of Respondents 321
• Highest Response 340 7/30/04 Week 2
• Lowest Response 302 8/26/04 Week 6
• Ratio of Men to Women remained amost constant
• 30 Men to 70 Women
• Average Age between 42 and 43
• 50 of respondents between 33-50
• Workers were from UNH,Cisco Systems, and Exeter,
  W-D and Portsmouth Hospitals

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Peaks in the Respiratory Ailments not as highly
correlated to ozone as how workers feel and
productivity. However, Week 5 peak correlated to
high ozone
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How Workers Felt at the end of the day is
correlated to Ozone
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Declines in Worker Productivity most strongly
correlated with peaks in 8-hour Ozone
concentration. Highest Concentration Surveys1, 2
5
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Next Steps for research

• Continue to explore data, test relationships and
  consider hypotheses
• Identify action strategies to reduce costs of
  poor air quality..such as
• Preventative measures
• encourage less outdoor physical activity during
  bad air days
• Allow working from home during bad air days
• Hospital staffing based on anticipated peaks in
  particular ailments related to atmospheric
  conditions..

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Preliminary Data Analysisof Three Hospitals in
New HampshireAicha Hassane, Ph.D.
StudentDepartment of EconomicsUniversity of New
HampshireNovember 10, 2004
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Goal and Objectives

• GOAL Improve our understanding of the link
  between air quality, climate, and human health.
• Specific Objective 1
• Analyze Local Hospitals respiratory and
  cardiovascular services for
• Seasonal patterns
• Variations in seasonal patterns between years
• Compare these patterns with those of Nationwide
  Inpatient Sample

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Goal and Objectives

• Specific Objective 2
• Correlate the variations in hospital use with
  weather and air quality variations
• Sources of Variations
• Seasonal patterns within each year
• Differences in seasonal patterns between years

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Hospital Data
Primary diagnosis only.
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Seasonal Variations in the Literature
Figure 3. Median weekly asthma admissions by age
group, 19861999, in Maryland. Plot of weekly
admissions for 04, 514, and 1518 year olds.
Asthma admissions increase four- to eightfold in
the fall compared to the summer (weeks
2638). From Blaisdell, C. J., S. R. Weiss, et
al. (2002). "Using seasonal variations in asthma
hospitalizations in children to predict
hospitalization frequency." J Asthma 39(7)
567-75.
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Nationwide Inpatient Sample Data

• 2000 NIS data
• 7.5 million inpatient stays
• 71,843 had a primary diagnosis of asthma
• 1,000 hospitals from 28 states.
• 2000 New England sub-sample
• 3 New England States CT, MA, ME
• 308,448 inpatients stays
• 2,915 had a primary diagnosis of asthma

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USA
New England
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Seasonality of Asthma at Local Hospitals

• Seasonality of Asthma by Year.
• Comparing 1998, 2000, and 2002
• Seasonality of Asthma by Age group
• 7 age groups 0-4 5-17 18-24 25-34
  35-5455-64 over 65.

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2000
8 days with 8hr ozone above 80 ppb
1998 and 2002
0 days with 8hr ozone above 80 ppb
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0-4
18-24
gt65
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Cardio vascular
respiratory
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Hypotheses to Explain the Summer Dips in
Respiratory Services.

• Individuals do not want to go to the hospital in
  the summer
• Children going back to school transmit colds to
  each other
• Cold temperatures may lead to an increase in
  respiratory ailments
• High pollen counts during the fall (ragweed, etc)

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Hypotheses to Explain the Summer Dips in
Respiratory Services.

• Response to cumulative effects of summer air
  pollution
• Operation of dormant forced hot air heating
  systems with cold fall weather
• Some combination of all the above hypotheses
  mentioned.

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THE END.

• Thank You
• Any questions?