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Asthma and Air Pollution: Associations Between
 Asthma Emergency Department Visits, PM 2.5
  Levels, and Temperature Inversions in Utah



           Presented November 16, 2010
            Utah Department of Health
            Canon Building, Room 125
Inversion Definition

•Occurs during winter months when normal conditions (cool
air above, warm air below) are inverted

•Pollutants become trapped
within cold air near valley
floor
•Primary winter pollutant is
particulate matter (PM)



Source: Utah Department of Environmental Quality,
http://www.cleanair.utah.gov/about_inversions.htm accessed March 2010
Salt Lake Valley During Inversion




Source: Accessed at http://www.cleanair.utah.gov/about_inversions.htm
on March 10, 2010. Photo credit: Tom Smart, Deseret Morning News
Analysis Objectives

 Understand changes in PM2.5 levels during
  temperature inversions and implications for people
  with asthma
 Assess odds for emergency department (ED) visits
  for asthma associated with temperature inversions
 Assess odds for ED visits for asthma associated with
  increases in ambient PM2.5
Partner Collaboration

 Utah Asthma Program
 Utah Department of Environmental Quality
 National Weather Service
 UDOH Environmental Epidemiology Program
 UDOH Environmental Public Health Tracking
  Network
 UDOH Office of Health Care Statistics
Study Methods and Criteria
Inversion Criteria

 Criteria for identification
   Based on daily soundings in Salt Lake Valley

   Morning and afternoon inversion

 Identified inversion days
   Dec 2006-Feb 2007: 35 days (38.9%)

   Dec 2007-2008: 10 days (11.1%)
Data Used

 Daily emergency department encounter data1
 Air pollutant data (PM2.5, ozone, NO2, SO2, CO, PM10) 2
   PM2.5 daily 24-hour average used
   PM2.5 measured from nearest monitor to residence

 Daily temperature and humidity data3
 Identified inversion days (winters 2006-2007 and 2007-
  2008)4
 Data Sources:
 1. Provided by UDOH Office of Health Care Statistics
 2. Accessed from EPA website http://www.epa.gov/airexplorer/ during March 2010
 3. Accessed from Utah Mesowest website http://mesowest.utah.edu/index.html
 during March 2010
 4. Provided by National Weather Service in Salt Lake City, UT
Study Design

 Area of study
   Salt Lake County

   Highest population density

 Time-stratified case-crossover design
   Cases serve as their own controls

   Odds based on exposure on case vs. control days

   Day of week and personal characteristics controlled for in
    design
   Seasonal effects minimized
Analysis Methods

 Descriptive statistics
 Conditional logistic regression
   Outcome of interest: ED visit with primary diagnosis of
    asthma
   Exposure variables: inversion, day of inversion, air
    quality index (AQI), inversion or AQI with<=3 days lag
    time
   Covariates adjusted for in final model: NO2, SO2, ozone,
    temperature
Results
Average PM 2.5 levels for
                                   Inversion vs. Non-inversion Days

                             50
                             45                 37.4
Average Daily PM 2.5 Level




                             40
                             35
       (ug/m3 LC)




                             30
                             25
                                                                                   13.1
                             20
                             15
                             10
                              5
                             0
                                         Inversion (n=45)                Non-inversion (n=135)

                              Data Source: http://www.epa.gov/airexplorer/ accessed March 2010.
Distribution of PM 2.5 Levels on Non-inversion Days



          45



          40



          35



          30



          25
Percent




          20



          15



          10



          5



          0
               4   12   20   28     36      44   52   60   68
                                  dailypm
Distribution of PM 2.5 Levels on Inversion Days


          35




          30




          25




          20
Percent




          15




          10




          5




          0
               6     18     30     42      54   66    78
                                 dailypm
Average PM 2.5 Levels by Day of Inversion,
                                   Winters 2006-2007 and 2007-2008

                             90.0
                                                                                          53.1
                             80.0
Average Daily PM 2.5 Level




                             70.0
                             60.0
                                                                          37.7
        (ug/m3)




                             50.0
                                                         33.7
                             40.0
                             30.0
                             20.0       13.1
                             10.0
                              0.0
                                    Non-inversion   1-2 Day (n=27)   3-4 Day (n=12)   5-7 Day (n=6)
                                      (n=135)
             Data Sources:
             Identified inversion days: National Weather Service
             Daily PM 2.5 Levels: http://www.epa.gov/airexplorer/ accessed March 2010.
Odds Ratio (OR)

 Definition: Ratio of the odds of an event (ED visit)
 occurring in exposed group compared to the odds of
 event occurring in non-exposed group

 Interpretation: OR higher than “1” indicates higher
 likelihood of event (can be used to approximate risk)
Odds of Asthma ED Visit on Inversion
                   vs. Non-inversion Day


          Exposure Variable                    Odds Ratio
                                               (95% CI)*
No Inversion                                    Reference


Inversion: no lag                                  1.09
                                               (0.92-1.28)
Inversion: 1 day lag                              1.00
                                               (0.85-1.17)

Inversion: 2 day lag                               1.01
                                               (0.84-1.22)

Inversion: 3 day lag                               1.07
                                               (0.90-1.27)

*Adjusted for temperature, NO2, SO2, and O3.
Odds of Asthma ED Visit Based on Number of Days of
              Continuous Inversion Exposure


          Exposure Variable                     Odds Ratio
                                                (95% CI)*



Non-inversion Day                                Reference



1-2 day                                            1.03
                                                (0.85-1.25)

3-4 day                                            1.09
                                                (0.84-1.41)

5-7 day                                             1.42
                                                (1.02-1.96)

* Adjusted for temperature, NO2, SO2, and O3.
AQI and Corresponding PM 2.5 Levels

     AQI                PM 2.5                     Health Advisory
                   (micrograms/m3)

     Good                0-15.4          None.
     0-50
   Moderate             15.5-35.4        Unusually sensitive people should
   51 to 100                             consider reducing prolonged or heavy
                                         exertion.
 Unhealthy for          35.5-55.4        People with heart or lung disease, older
Sensitive Groups                         adults, and children should reduce
   101 to 150                            prolonged or heavy exertion.
   Unhealthy           55.5-150.4        People with heart or lung disease, older
   151 to 200                            adults, and children should avoid
                                         prolonged or heavy exertion. Everyone
                                         else should reduce prolonged or heavy
                                         exertion.
* Current 24-hour PM2.5 standard is 35 micrograms/m3
Odds of Asthma ED Visit
                       Based on Air Quality Index


      AQI              No lag        1 Day Lag     2 Day Lag     3 Day Lag
                     (95% CI)*       (95% CI)*     (95% CI)*     (95% CI)*

Good                 Reference        Reference    Reference     Reference
(PM 0-15.4)
Moderate                1.02            0.98          1.04          0.90
(PM 15.5-35.4)       (0.88-1.18)     (0.86-1.13)   (0.90-1.21)   (0.77-1.05)

Unhealthy for           1.08            0.96           0.87         0.88
Sensitive Groups     (0.88-1.33)     (0.79-1.19)   (0.70-1.09)   (0.71-1.09)
(PM 35.5-55.4)



Unhealthy                1.10            1.14         0.87           1.21
(PM >55.4)           (0.80-1.50)     (0.85-1.54)   (0.61-1.23)   (0.92-1.59)
 * Adjusted for temperature, NO2, SO2, and O3.
Other Findings

 Data suggestive of possible interaction between
  PM2.5 and inversions – insufficient data to be
  conclusive
 Similar findings when using any (rather than just
  primary) diagnosis of asthma as outcome
Conclusions

 On average, PM2.5 reaches levels that are unhealthy
  for sensitive groups during inversions lasting 3-4
  days or longer
 No association between ED visits for asthma and
  PM2.5, including up to 3 days after exposure
 Odds of primary ED visit for asthma are 42% higher
  during days 5-7 of a prolonged inversion, compared
  to a non-inversion day
Limitations

 24-hour averages of ambient PM2.5 used to measure
  exposure – individual exposure unknown
 Health effects outside of ED visits unknown
 Insufficient data to explore interactions between
  PM2.5 and inversions
Implications for Public Health

 Improved understanding of inversions and PM2.5
 People with asthma should take extra precautions during
 inversions, particularly prolonged ones
    Regularly check ambient PM2.5 levels
    Avoid or limit exposure to asthma triggers (e.g. exercise indoors)
    Asthma medication use
    Discuss personal steps to control asthma with physician
Available Air Quality Resources

 School recess guidance1
 Air quality websites2
 Red air day alerts
 Air quality tutorials3



  1. Available on the Utah Asthma Program website, at
     http://www.health.utah.gov/asthma/air%20quality/pm25.html.
  2. Hourly air quality updates available at (http://www.airquality.utah.gov/)
  3. Currently being developed by the Utah Asthma Program and the Department of
     Environmental Quality. Anticipated release in December 2010.
Related studies

 Avery CL, Mills KT, Williams R, McGraw KA, Poole C, Smith RL et al. 2010.
    Estimating error in using residential outdoor PM2.5 concentrations as proxies
    for personal exposures: a meta-analysis. Environ Health Perspect 118:673-678.
   Babin S, Burkom HS, Holtry RS, Tabernero NR, Stokes LD, Davies-Cole JO et
    al. 2007. Pediatric patient asthma-related emergency department visits and
    admissions in Washington, DC, from 2001-2004, and associations with air
    quality, socio-economic status and age group. Environmental Health 6:9.
   Bateson TF, Schwartz J. 1999. Control for seasonal variation and time trend in
    case-crossover studies of acute effects of environmental exposures.
    Epidemiology 10:539–544.
   Bateson TF, Schwartz J. 2004. Who is sensitive to the effects of particulate air
    pollution on mortality? A case-crossover analysis of effect modifiers.
    Epidemiology 15:143–149.
   Carracedo-Martínez E, Taracido M, Tobias A, Saez M, Figueiras A. 2010. Case-
    crossover analysis of air pollution health effects: a systematic review of
    methodology and application. Environ Health Perspect; doi:
    10.1289/ehp.0901485 [Online 31 March 2010].
Related Studies (cont.)

 Delfino RJ, Staimer N, Tjoa T, Gillen D, Kleinman MT, Sioutas C, et al. 2008.
    Personal and ambient air pollution exposures and lung function decrements in
    children with asthma. Environ Health Perspect 116:550-558.
   Figueiras A, Carracedo-Martinez E, Saez M, Taracido M. 2005. Analysis of
    case-crossover designs using longitudinal approaches: a simulation study.
    Epidemiology 16:239-246.
   Fung KY, Krewski D, Chen Y, Burnett R, Cakmak S. 2003. Comparison of time
    series and case-crossover analyses of air pollution and hospital admission data.
    Int J Epidemiol 32:1064-1070.
   Jaakkola JJ. 2003. Case-crossover design in air pollution epidemiology. Eur
    Respir J Suppl 40:81s-85s.
   Janes H, Sheppard L, Lumley T. 2005. Case–crossover analyses of air pollution
    exposure data referent selection strategies and their implications for bias.
    Epidemiology 16:717–726.
   Koenig JQ, Mar TF, Allen RW, Jansen K, Lumley T, Sullivan JH, et al. 2005.
    Pulmonary effects of indoor- and outdoor-generated particles in children with
    asthma. Environ Health Perspect 113:499-503.
Related Studies (cont.)

 Kunzli N, Schindler C. 2005. A call for reporting the relevant exposure term in
    air pollution case-crossover studies. J Epidemiol Community Health 59:527–
    530.
   Levy D, Lumley T, Sheppard L, Kaufman J, Checkoway H. 2001. Referent
    selection in case-crossover analyses of acute health effects of air pollution.
    Epidemiology 12:186-192.
   Lewis TC, Robins TG, Dvonch JT, Keeler GJ, Yip FY, Mentz GB, et al. 2005. Air
    pollution-associated changes in lung function among asthmatic children in
    Detroit. Environ Health Perspect 113:1068-1075.
   Lumley T, Levy D. 2000. Bias in the case-crossover design implications for
    studies of air pollution. Environmetrics 11:689 –704.
   Maclure M. 1991. The case-crossover design: a method for studying transient
    effects on the risk of acute events. Am J Epidemiol 133:144-153.
   Maclure M, Mittleman MA. 2000. Should we use a case-crossover design?
    Annu Rev Public Health 21:193–221.
Related Studies (cont.)

 Mittleman MA. 2005. Optimal referent selection strategies in case-crossover
    studies: a settled issue. Epidemiology 16:715-716.
   Norris G, YoungPong SN, Koenig JQ, Larson TV, Sheppard L, Stout JW. 1999.
    An association between fine particles and emergency department visits for
    children in Seattle. Environ Health Perspect 107:489-493.
   Wallace J, Nair P, Kanaroglou P. 2010. Atmospheric remote sensing to detect
    effects of temperature inversions on sputum cell counts in airway diseases.
    Environmental Research 110:624-632.
   Wallace J, Kanaroglou P. 2009. The effect of temperature inversions on
    ground-level nitrogen dioxide (NO2) and fine particulate matter (PM2.5) using
    temperature profiles from the atmospheric infrared sounder (AIRS). Science of
    the Total Environment 407:5085-5095.
   Wang HC, Yousef E. 2007. Air quality and pediatric asthma-related
    emergencies. Journal of Asthma 44:839-841.

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Asthma and Air Pollution

  • 1. Asthma and Air Pollution: Associations Between Asthma Emergency Department Visits, PM 2.5 Levels, and Temperature Inversions in Utah Presented November 16, 2010 Utah Department of Health Canon Building, Room 125
  • 2. Inversion Definition •Occurs during winter months when normal conditions (cool air above, warm air below) are inverted •Pollutants become trapped within cold air near valley floor •Primary winter pollutant is particulate matter (PM) Source: Utah Department of Environmental Quality, http://www.cleanair.utah.gov/about_inversions.htm accessed March 2010
  • 3. Salt Lake Valley During Inversion Source: Accessed at http://www.cleanair.utah.gov/about_inversions.htm on March 10, 2010. Photo credit: Tom Smart, Deseret Morning News
  • 4. Analysis Objectives  Understand changes in PM2.5 levels during temperature inversions and implications for people with asthma  Assess odds for emergency department (ED) visits for asthma associated with temperature inversions  Assess odds for ED visits for asthma associated with increases in ambient PM2.5
  • 5. Partner Collaboration  Utah Asthma Program  Utah Department of Environmental Quality  National Weather Service  UDOH Environmental Epidemiology Program  UDOH Environmental Public Health Tracking Network  UDOH Office of Health Care Statistics
  • 6. Study Methods and Criteria
  • 7. Inversion Criteria  Criteria for identification  Based on daily soundings in Salt Lake Valley  Morning and afternoon inversion  Identified inversion days  Dec 2006-Feb 2007: 35 days (38.9%)  Dec 2007-2008: 10 days (11.1%)
  • 8. Data Used  Daily emergency department encounter data1  Air pollutant data (PM2.5, ozone, NO2, SO2, CO, PM10) 2  PM2.5 daily 24-hour average used  PM2.5 measured from nearest monitor to residence  Daily temperature and humidity data3  Identified inversion days (winters 2006-2007 and 2007- 2008)4 Data Sources: 1. Provided by UDOH Office of Health Care Statistics 2. Accessed from EPA website http://www.epa.gov/airexplorer/ during March 2010 3. Accessed from Utah Mesowest website http://mesowest.utah.edu/index.html during March 2010 4. Provided by National Weather Service in Salt Lake City, UT
  • 9. Study Design  Area of study  Salt Lake County  Highest population density  Time-stratified case-crossover design  Cases serve as their own controls  Odds based on exposure on case vs. control days  Day of week and personal characteristics controlled for in design  Seasonal effects minimized
  • 10. Analysis Methods  Descriptive statistics  Conditional logistic regression  Outcome of interest: ED visit with primary diagnosis of asthma  Exposure variables: inversion, day of inversion, air quality index (AQI), inversion or AQI with<=3 days lag time  Covariates adjusted for in final model: NO2, SO2, ozone, temperature
  • 12. Average PM 2.5 levels for Inversion vs. Non-inversion Days 50 45 37.4 Average Daily PM 2.5 Level 40 35 (ug/m3 LC) 30 25 13.1 20 15 10 5 0 Inversion (n=45) Non-inversion (n=135) Data Source: http://www.epa.gov/airexplorer/ accessed March 2010.
  • 13. Distribution of PM 2.5 Levels on Non-inversion Days 45 40 35 30 25 Percent 20 15 10 5 0 4 12 20 28 36 44 52 60 68 dailypm
  • 14. Distribution of PM 2.5 Levels on Inversion Days 35 30 25 20 Percent 15 10 5 0 6 18 30 42 54 66 78 dailypm
  • 15. Average PM 2.5 Levels by Day of Inversion, Winters 2006-2007 and 2007-2008 90.0 53.1 80.0 Average Daily PM 2.5 Level 70.0 60.0 37.7 (ug/m3) 50.0 33.7 40.0 30.0 20.0 13.1 10.0 0.0 Non-inversion 1-2 Day (n=27) 3-4 Day (n=12) 5-7 Day (n=6) (n=135) Data Sources: Identified inversion days: National Weather Service Daily PM 2.5 Levels: http://www.epa.gov/airexplorer/ accessed March 2010.
  • 16. Odds Ratio (OR)  Definition: Ratio of the odds of an event (ED visit) occurring in exposed group compared to the odds of event occurring in non-exposed group  Interpretation: OR higher than “1” indicates higher likelihood of event (can be used to approximate risk)
  • 17. Odds of Asthma ED Visit on Inversion vs. Non-inversion Day Exposure Variable Odds Ratio (95% CI)* No Inversion Reference Inversion: no lag 1.09 (0.92-1.28) Inversion: 1 day lag 1.00 (0.85-1.17) Inversion: 2 day lag 1.01 (0.84-1.22) Inversion: 3 day lag 1.07 (0.90-1.27) *Adjusted for temperature, NO2, SO2, and O3.
  • 18. Odds of Asthma ED Visit Based on Number of Days of Continuous Inversion Exposure Exposure Variable Odds Ratio (95% CI)* Non-inversion Day Reference 1-2 day 1.03 (0.85-1.25) 3-4 day 1.09 (0.84-1.41) 5-7 day 1.42 (1.02-1.96) * Adjusted for temperature, NO2, SO2, and O3.
  • 19. AQI and Corresponding PM 2.5 Levels AQI PM 2.5 Health Advisory (micrograms/m3) Good 0-15.4 None. 0-50 Moderate 15.5-35.4 Unusually sensitive people should 51 to 100 consider reducing prolonged or heavy exertion. Unhealthy for 35.5-55.4 People with heart or lung disease, older Sensitive Groups adults, and children should reduce 101 to 150 prolonged or heavy exertion. Unhealthy 55.5-150.4 People with heart or lung disease, older 151 to 200 adults, and children should avoid prolonged or heavy exertion. Everyone else should reduce prolonged or heavy exertion. * Current 24-hour PM2.5 standard is 35 micrograms/m3
  • 20. Odds of Asthma ED Visit Based on Air Quality Index AQI No lag 1 Day Lag 2 Day Lag 3 Day Lag (95% CI)* (95% CI)* (95% CI)* (95% CI)* Good Reference Reference Reference Reference (PM 0-15.4) Moderate 1.02 0.98 1.04 0.90 (PM 15.5-35.4) (0.88-1.18) (0.86-1.13) (0.90-1.21) (0.77-1.05) Unhealthy for 1.08 0.96 0.87 0.88 Sensitive Groups (0.88-1.33) (0.79-1.19) (0.70-1.09) (0.71-1.09) (PM 35.5-55.4) Unhealthy 1.10 1.14 0.87 1.21 (PM >55.4) (0.80-1.50) (0.85-1.54) (0.61-1.23) (0.92-1.59) * Adjusted for temperature, NO2, SO2, and O3.
  • 21. Other Findings  Data suggestive of possible interaction between PM2.5 and inversions – insufficient data to be conclusive  Similar findings when using any (rather than just primary) diagnosis of asthma as outcome
  • 22. Conclusions  On average, PM2.5 reaches levels that are unhealthy for sensitive groups during inversions lasting 3-4 days or longer  No association between ED visits for asthma and PM2.5, including up to 3 days after exposure  Odds of primary ED visit for asthma are 42% higher during days 5-7 of a prolonged inversion, compared to a non-inversion day
  • 23. Limitations  24-hour averages of ambient PM2.5 used to measure exposure – individual exposure unknown  Health effects outside of ED visits unknown  Insufficient data to explore interactions between PM2.5 and inversions
  • 24. Implications for Public Health  Improved understanding of inversions and PM2.5  People with asthma should take extra precautions during inversions, particularly prolonged ones  Regularly check ambient PM2.5 levels  Avoid or limit exposure to asthma triggers (e.g. exercise indoors)  Asthma medication use  Discuss personal steps to control asthma with physician
  • 25. Available Air Quality Resources  School recess guidance1  Air quality websites2  Red air day alerts  Air quality tutorials3 1. Available on the Utah Asthma Program website, at http://www.health.utah.gov/asthma/air%20quality/pm25.html. 2. Hourly air quality updates available at (http://www.airquality.utah.gov/) 3. Currently being developed by the Utah Asthma Program and the Department of Environmental Quality. Anticipated release in December 2010.
  • 26. Related studies  Avery CL, Mills KT, Williams R, McGraw KA, Poole C, Smith RL et al. 2010. Estimating error in using residential outdoor PM2.5 concentrations as proxies for personal exposures: a meta-analysis. Environ Health Perspect 118:673-678.  Babin S, Burkom HS, Holtry RS, Tabernero NR, Stokes LD, Davies-Cole JO et al. 2007. Pediatric patient asthma-related emergency department visits and admissions in Washington, DC, from 2001-2004, and associations with air quality, socio-economic status and age group. Environmental Health 6:9.  Bateson TF, Schwartz J. 1999. Control for seasonal variation and time trend in case-crossover studies of acute effects of environmental exposures. Epidemiology 10:539–544.  Bateson TF, Schwartz J. 2004. Who is sensitive to the effects of particulate air pollution on mortality? A case-crossover analysis of effect modifiers. Epidemiology 15:143–149.  Carracedo-Martínez E, Taracido M, Tobias A, Saez M, Figueiras A. 2010. Case- crossover analysis of air pollution health effects: a systematic review of methodology and application. Environ Health Perspect; doi: 10.1289/ehp.0901485 [Online 31 March 2010].
  • 27. Related Studies (cont.)  Delfino RJ, Staimer N, Tjoa T, Gillen D, Kleinman MT, Sioutas C, et al. 2008. Personal and ambient air pollution exposures and lung function decrements in children with asthma. Environ Health Perspect 116:550-558.  Figueiras A, Carracedo-Martinez E, Saez M, Taracido M. 2005. Analysis of case-crossover designs using longitudinal approaches: a simulation study. Epidemiology 16:239-246.  Fung KY, Krewski D, Chen Y, Burnett R, Cakmak S. 2003. Comparison of time series and case-crossover analyses of air pollution and hospital admission data. Int J Epidemiol 32:1064-1070.  Jaakkola JJ. 2003. Case-crossover design in air pollution epidemiology. Eur Respir J Suppl 40:81s-85s.  Janes H, Sheppard L, Lumley T. 2005. Case–crossover analyses of air pollution exposure data referent selection strategies and their implications for bias. Epidemiology 16:717–726.  Koenig JQ, Mar TF, Allen RW, Jansen K, Lumley T, Sullivan JH, et al. 2005. Pulmonary effects of indoor- and outdoor-generated particles in children with asthma. Environ Health Perspect 113:499-503.
  • 28. Related Studies (cont.)  Kunzli N, Schindler C. 2005. A call for reporting the relevant exposure term in air pollution case-crossover studies. J Epidemiol Community Health 59:527– 530.  Levy D, Lumley T, Sheppard L, Kaufman J, Checkoway H. 2001. Referent selection in case-crossover analyses of acute health effects of air pollution. Epidemiology 12:186-192.  Lewis TC, Robins TG, Dvonch JT, Keeler GJ, Yip FY, Mentz GB, et al. 2005. Air pollution-associated changes in lung function among asthmatic children in Detroit. Environ Health Perspect 113:1068-1075.  Lumley T, Levy D. 2000. Bias in the case-crossover design implications for studies of air pollution. Environmetrics 11:689 –704.  Maclure M. 1991. The case-crossover design: a method for studying transient effects on the risk of acute events. Am J Epidemiol 133:144-153.  Maclure M, Mittleman MA. 2000. Should we use a case-crossover design? Annu Rev Public Health 21:193–221.
  • 29. Related Studies (cont.)  Mittleman MA. 2005. Optimal referent selection strategies in case-crossover studies: a settled issue. Epidemiology 16:715-716.  Norris G, YoungPong SN, Koenig JQ, Larson TV, Sheppard L, Stout JW. 1999. An association between fine particles and emergency department visits for children in Seattle. Environ Health Perspect 107:489-493.  Wallace J, Nair P, Kanaroglou P. 2010. Atmospheric remote sensing to detect effects of temperature inversions on sputum cell counts in airway diseases. Environmental Research 110:624-632.  Wallace J, Kanaroglou P. 2009. The effect of temperature inversions on ground-level nitrogen dioxide (NO2) and fine particulate matter (PM2.5) using temperature profiles from the atmospheric infrared sounder (AIRS). Science of the Total Environment 407:5085-5095.  Wang HC, Yousef E. 2007. Air quality and pediatric asthma-related emergencies. Journal of Asthma 44:839-841.