CDC EPICDC EPI--AID Investigations of Health Effects Associated AID Investigations of Health Effects Associated With Forest Fire Smoke Exposure, U.S.,1999With Forest Fire Smoke Exposure, U.S.,1999--20012001

Josh Mott, NCEH, CDCJosh Mott, NCEH, CDC

EPIEPI--AID 2000AID 2000--0909EPIEPI--AID 2000AID 2000--4040EPIEPI--AID 2001AID 2001--0707

Outline of this PresentationOutline of this Presentation

1)1) Overview of Three CDC InvestigationsOverview of Three CDC Investigations

a) Hoopa Valley Indian Reservation, CA, November 1999a) Hoopa Valley Indian Reservation, CA, November 1999

b) Los Alamos National Laboratory, NM, May 2000b) Los Alamos National Laboratory, NM, May 2000

c) Bitterroot Valley, MT, November 2000c) Bitterroot Valley, MT, November 2000

2)2) Conclusions and Future DirectionsConclusions and Future Directions

Assessment of Health Effects and Evaluation of Assessment of Health Effects and Evaluation of Interventions Associated with Forest Fires,Interventions Associated with Forest Fires,

Hoopa, California, August-October 1999Hoopa, California, August-October 1999

Joshua Mott, PhD; Pamela Meyer, PhD; Eva Smith, MD;Joshua Mott, PhD; Pamela Meyer, PhD; Eva Smith, MD;David Mannino, MD; Emmett Chase MD; Stephen Redd, MDDavid Mannino, MD; Emmett Chase MD; Stephen Redd, MD

EPI-AID 2000-09EPI-AID 2000-09

Smoke from Wildand Fires in the area of theSmoke from Wildand Fires in the area of theHoopa Valley Indian Reservation 9/30/1999Hoopa Valley Indian Reservation 9/30/1999

* Hoopa

The Big-Bar Fires, Shasta-Trinity Forest, The Big-Bar Fires, Shasta-Trinity Forest, 10/31/9910/31/99

29 Miles29 Miles

Hoopa Valley Indian ReservationHoopa Valley Indian Reservation• Trinity River Valley, northern CaliforniaTrinity River Valley, northern California• 770 tribal households770 tribal households• 57% poverty57% poverty• 32% unemployment32% unemployment

Temperature Inversions and Confining TopographyTemperature Inversions and Confining Topography

Ambient Particulate Matter < 10 Microns (PMAmbient Particulate Matter < 10 Microns (PM1010), ), Hoopa Valley Indian Reservation, Hoopa Valley Indian Reservation,

September 28-October 28, 1999September 28-October 28, 1999

µg

/m3

µg

/m3

Hazardous Hazardous >> 425 425 µg/m3µg/m3 (24 hours) (24 hours)

00

100100

200200

300300

400400

500500

600600

700700

PM10, 24-hour AveragePM10, 24-hour Average

Oct. 1Oct. 1 Oct. 22Oct. 22Oct. 8Oct. 8 Oct. 15Oct. 15Sept. 28Sept. 28

Standard Standard >> 150 150 µg/m3 µg/m3 (24 hours)(24 hours)

Oct. 28Oct. 28

Time periodTime period

Average Weekly PMAverage Weekly PM1010 Levels and Number of Levels and Number of

Respiratory Visits to K’ima:w Medical Center, Respiratory Visits to K’ima:w Medical Center, By Week, August-November, 1998,1999By Week, August-November, 1998,1999

2936

2429 27

3843 46

42 40

31 32

0

50

100

150

200

250

300

350

400

2226

39 37

54 53

64 6355

87

6965

0

50

100

150

200

250

300

350

400

Pm10 (g/m3) PM10 (g/m3)

Aug. Sep. Oct. Nov.Aug. Sep. Oct. Nov.

1999199919981998

Aug. Sep. Oct. Nov.Aug. Sep. Oct. Nov.

Weekly # of respiratory visits Weekly # of respiratory visits

Number of Asthma Visits by Week of Visit and Average Weekly PM10 Levels, Hoopa, CA,

1998, 1999*

0

10

20

30

40

1 2 3 4 5 6 7 8 9 10 11

0

50

100

150

200

250

300

350

400

0

10

20

30

40

1 2 3 4 5 6 7 8 9 10 11

0

50

100

150

200

250

300

350

400

1998 1999

* Average Number of People at Hotels funded by NCIDC in 1999 Wk 9: 66; Wk 10: 444; Wk 11: 313

Number of COPD Visits by Week of Visit and Average Weekly PM10 Levels, Hoopa, CA, 1998, 1999*

0

10

20

30

1 2 3 4 5 6 7 8 9 10 11

0

50

100

150

200

250

300

350

400

0

5

10

15

20

25

30

1 2 3 4 5 6 7 8 9 10 11

0

50

100

150

200

250

300

350

400

1998 1999

* Average Number of People at Hotels funded by NCIDC in 1999 Wk 9: 66; Wk 10: 444; Wk 11: 313

Number of Visits for Headaches by Week of Visit and Average Weekly PM10 Levels, Hoopa, CA, 1998, 1999*

1 2 3 4 5 6 7 8 9 10 11

0

50

100

150

200

250

300

350

400

0

5

10

15

1 2 3 4 5 6 7 8 9 10 11

0

50

100

150

200

250

300

350

400

1998 1999

* Average Number of People at Hotels funded by NCIDC in 1999 Wk 9: 66; Wk 10: 444; Wk 11: 313

Number of Coronary Artery Disease Visits by Week of Visit and Average Weekly PM10 Levels, Hoopa, CA, 1998,

1999*

0

10

20

30

40

1 2 3 4 5 6 7 8 9 10 11

0

50

100

150

200

250

300

350

400

0

2

4

6

8

10

12

14

16

1 2 3 4 5 6 7 8 9 10 11

0

50

100

150

200

250

300

350

400

1998 1999

* Average Number of People at Hotels funded by NCIDC in 1999 Wk 9: 66; Wk 10: 444; Wk 11: 313

Selected Drugs Dispensed by KMC Pharmacy by Year, Hoopa, CA, 1998-1999

178

319

245650

106

15 22

0

50

100

150

200

250

300

350

1998 1999

Year

Un

its

Dis

pens

ed

AlbuterolAtroventAzmacortVancenase

Interventions Implemented by Tribal Council Interventions Implemented by Tribal Council and Staff of K’ima:w Medical Centerand Staff of K’ima:w Medical Center

September-October 1999September-October 1999

• Filtered and non-filtered masks Filtered and non-filtered masks

• Free hotel vouchersFree hotel vouchers

• HEPA Cleaners HEPA Cleaners

• Public service announcements (PSAs)Public service announcements (PSAs)

• Preferential Distribution of InterventionsPreferential Distribution of Interventions

CDC arrived to assist in assessment of health effects and CDC arrived to assist in assessment of health effects and evaluation of interventions – 11/08/99evaluation of interventions – 11/08/99

Objectives of the CDC InvestigationObjectives of the CDC Investigation

• To assess the health impact of the smokeTo assess the health impact of the smoke By pre-existing cardiopulmonary conditionBy pre-existing cardiopulmonary condition

• To evaluate the impact of interventionsTo evaluate the impact of interventions

MethodsMethods•Cross-sectional survey Cross-sectional survey

No pre-existing conditions, N=197No pre-existing conditions, N=197 Pre-existing conditions, N=92 Pre-existing conditions, N=92

Pre-existing conditions defined as…Pre-existing conditions defined as…

“ “one or more visits in the last year for CAD,one or more visits in the last year for CAD, asthma, COPD, or other lung disease”asthma, COPD, or other lung disease”

•N=289, 78.5% response rateN=289, 78.5% response rate

Survey questionsSurvey questions

• Measures of ExposureMeasures of Exposure

• Symptom frequency (on a scale of 1-5) Symptom frequency (on a scale of 1-5)

– BEFOREBEFORE the heavy smoke began (baseline) the heavy smoke began (baseline)

– DURINGDURING the heavy smoke (Aug. 23-Oct. 26) the heavy smoke (Aug. 23-Oct. 26)

– AFTERAFTER the heavy smoke ended (Oct. 27-Nov.15) the heavy smoke ended (Oct. 27-Nov.15)

• Dichotomous outcome variablesDichotomous outcome variables Worse from Worse from before to during the smokebefore to during the smoke Worse from Worse from before to after the smokebefore to after the smoke (post-fire symptoms)(post-fire symptoms)

• Lower respiratory symptomsLower respiratory symptoms Breathing difficultyBreathing difficulty Chest painChest pain CoughingCoughing

Outcome DefinitionOutcome Definition

Self-Reported Impact of the Heavy Smoke Self-Reported Impact of the Heavy Smoke on Lower Respiratory Symptomson Lower Respiratory Symptoms

21.3% 23.9%% still worse after the smoke% still worse after the smoke

61.9% 64.1%% worse during the smoke% worse during the smoke

No pre-existing No pre-existing conditionsconditions

Pre-existing Pre-existing conditionsconditions

Mean Number of Reported Lower Respiratory Mean Number of Reported Lower Respiratory Symptoms: Before, During, and After the SmokeSymptoms: Before, During, and After the Smoke

0.52 0.92After the smokeAfter the smoke 1.07 1.46During the smokeDuring the smoke

0.38 1.08Before the smokeBefore the smoke

No pre-existingNo pre-existing

conditioncondition

Pre-existingPre-existing

conditioncondition

Sample Participation Rates For InterventionsSample Participation Rates For Interventions Implemented by K’ima:w Medical CenterImplemented by K’ima:w Medical Center

Number Number Percent Percent ParticipatingParticipating Participating Participating

Wore a MaskWore a Mask 100/286 35%Evacuated ReservationEvacuated Reservation 140/287 48%Ran HEPA Cleaner at HomeRan HEPA Cleaner at Home 98/287 34%Recalled and Recited a PSARecalled and Recited a PSA 223/289 77%

Intervention Evaluation:Intervention Evaluation:Analysis Strategy for Confounding by SeverityAnalysis Strategy for Confounding by Severity

• Outcome of interest is Outcome of interest is post-fire symptomspost-fire symptoms

• Assessed increased participation Assessed increased participation among only those among only those who received interventionswho received interventions

• Multiple logistic regression, Multiple logistic regression, all results are adjustedall results are adjusted for: for:

Frequency of symptoms at baselineFrequency of symptoms at baseline IncomeIncome AgeAge Hours per day normally spent outsideHours per day normally spent outside

Associations Between Exposure Indices and the Associations Between Exposure Indices and the Odds of Reporting Worsening Lower Respiratory Odds of Reporting Worsening Lower Respiratory

Symptoms, Hoopa, California, 1999Symptoms, Hoopa, California, 1999

0.75-48.56 .092

1.03-1.22 .007

6.02

1.12

Home < 650 feet in altitudeHome < 650 feet in altitude

Hours per day outsideHours per day outside

0.98-1.44 .0801.19Household incomeHousehold income

0.88-3.49 .1111.75Female SexFemale Sex

0.97-2.04 .0751.40Poorer home conditionPoorer home condition

95% CI p-value 95% CI p-value aORaOR

Odds of worsening lower Odds of worsening lower

respiratory symptomsrespiratory symptoms

Effect of Duration of Mask Use Among Those Who Effect of Duration of Mask Use Among Those Who Received Filtered Masks, Hoopa, California, 1999Received Filtered Masks, Hoopa, California, 1999

0.39-6.451.5951-75% (wore a mask 8-24 hours/week)51-75% (wore a mask 8-24 hours/week)

0.33-6.341.45Top 25% (wore a mask Top 25% (wore a mask >> 25 hours/week) 25 hours/week)

95% CI95% CIaORaOR

Bottom 25% (wore mask 0-2 hours/week)Bottom 25% (wore mask 0-2 hours/week)

0.47-6.691.7826-50% (wore a mask 3-7 hours/week)26-50% (wore a mask 3-7 hours/week)

N = 100 (those who received filtered masks)N = 100 (those who received filtered masks)

Reference Group

Odds of worsening lower Odds of worsening lower respiratory symptomsrespiratory symptoms

Effect of Duration and Timing of Evacuation Effect of Duration and Timing of Evacuation Among Those Who Left the Reservation,Among Those Who Left the Reservation,

Hoopa, California, 1999Hoopa, California, 1999

Odds of worsening lower Odds of worsening lower respiratory symptomsrespiratory symptoms

0.39-3.641.20Evacuated for top 3 days of PMEvacuated for top 3 days of PM1010

Total Days Away from ReservationTotal Days Away from Reservation

95% CI95% CI aOR aOR

N = 140 (who evacuated the reservation)N = 140 (who evacuated the reservation)

0.98 0.91-1.06

0.89-1.000.95Total time HEPA Cleaner was runTotal time HEPA Cleaner was run

0.04-0.870.18Top 25% (Top 25% (>> 337 hours of use) 337 hours of use)

0.11-1.450.3951-75% (163-336 hours of use)51-75% (163-336 hours of use)

0.13-2.730.5926-50% (73-162 hours of use) 26-50% (73-162 hours of use)

Bottom 25% (0-72 hours of use)Bottom 25% (0-72 hours of use)

95% CI95% CIaORaOR

Odds of worsening lower Odds of worsening lower respiratory symptomsrespiratory symptoms

Effect of Duration of HEPA Cleaner Use Among Effect of Duration of HEPA Cleaner Use Among Those Who Received HEPA Cleaners, Those Who Received HEPA Cleaners,

Hoopa, California, 1999Hoopa, California, 1999

N = 98 (those who received HEPA filters)N = 98 (those who received HEPA filters)

Reference Group

HEPA Cleaners vs. Evacuation?HEPA Cleaners vs. Evacuation?

EvacuationEvacuation HEPA CleanersHEPA Cleaners

% participated during % participated during

three days of highest three days of highest

PMPM1010

17% 49%

Mean duration of Mean duration of participationparticipation

7.6 days 14.9 days

Of those who participated in each intervention…Of those who participated in each intervention…

Financial and Occupational Barriers Financial and Occupational Barriers to Evacuation.to Evacuation.

• 44% of the responses of those who didn’t go to a 44% of the responses of those who didn’t go to a hotel indicated occupational barriers. hotel indicated occupational barriers.

• 12% indicated economic constraints.12% indicated economic constraints.

• Those with pre-existing conditions were not lessThose with pre-existing conditions were not less likely than those without pre-existing conditionslikely than those without pre-existing conditions to work in the fire camps.to work in the fire camps.

Public Service Announcements Public Service Announcements

Remain indoors - 78.6%Remain indoors - 78.6% Wear face covering - 44.1%Wear face covering - 44.1%

Leave area temporarily - 34.5% Leave area temporarily - 34.5%

Close windows - 23.9%Close windows - 23.9%

Restrict strenuous outdoor activity - 19.4%Restrict strenuous outdoor activity - 19.4%

Use air conditioning - 9.7%Use air conditioning - 9.7%

SourceSourceRadio - 51.5% Radio - 51.5%

Doctor - 37.2%Doctor - 37.2%

Friend/family - 21.3%Friend/family - 21.3%

Employer - 17.2%Employer - 17.2%

Television - 13.9% Television - 13.9%

Newspaper - 6.7%Newspaper - 6.7%

Effect of Receiving Public Service Announcements Effect of Receiving Public Service Announcements (PSAs), Hoopa, California, 1999(PSAs), Hoopa, California, 1999

Did not recall any PSAsDid not recall any PSAs

0.01-0.220.03Recited three or more PSAsRecited three or more PSAs

0.21-1.050.47Recited one PSARecited one PSA

0.17-0.890.38Recited two PSAsRecited two PSAs

95% CI95% CIaORaOR

N = 289N = 289

Reference Group

Odds of worsening lower Odds of worsening lower respiratory symptomsrespiratory symptoms

LimitationsLimitations1.1. Observational StudyObservational Study

•• looked for dose-response effects within groupslooked for dose-response effects within groups

• • post-fire outcomespost-fire outcomes

2. No Measure of Personal Exposure2. No Measure of Personal Exposure •• Urinary methoxyphenols not validated Urinary methoxyphenols not validated

•• DNA, Hb and Albumin Adducts DNA, Hb and Albumin Adducts not yet validatednot yet validated

•• Could not use personal exposure monitorsCould not use personal exposure monitors

3. Self-report data3. Self-report data•• Uncertain correlation with more severe outcomesUncertain correlation with more severe outcomes

•• Recall biasRecall bias

•• Common reporter biasCommon reporter bias

Conclusions: Health EffectsConclusions: Health Effects

• Prioritize interventions to those with Prioritize interventions to those with pre-existing cardiopulmonary conditions pre-existing cardiopulmonary conditions

• Continue to implement programs to reduce Continue to implement programs to reduce exposure in the entire population exposure in the entire population

Conclusions: InterventionsConclusions: Interventions

• Mask Use: Mask Use: Ineffective Ineffective

• PSA’s: PSA’s: Effective, but mechanism unclearEffective, but mechanism unclear

• HEPA Cleaners: HEPA Cleaners: Effective, need validationEffective, need validation

• Evacuation: Evacuation: Ineffective, not feasibleIneffective, not feasible

Future DirectionsFuture Directions

• Validate a biomarker for wood smoke exposure. Validate a biomarker for wood smoke exposure.

• Continue to evaluate interventions using objective Continue to evaluate interventions using objective indicators of exposure and health effects.indicators of exposure and health effects.

Investigation of Exposures from the Investigation of Exposures from the Cerro Grande Fire, Los Alamos, New Cerro Grande Fire, Los Alamos, New

Mexico, May 2000Mexico, May 2000Epi-Aid 2000-40Epi-Aid 2000-40

Mitchell Wolfe, Joshua Mott, Ron Voorhees, C. Mack Sewell, Mitchell Wolfe, Joshua Mott, Ron Voorhees, C. Mack Sewell, C.M. Wood, Dan Paschal, Stephen ReddC.M. Wood, Dan Paschal, Stephen Redd

BackgroundBackgroundCerro Grande FireCerro Grande Fire

• May 4: Controlled burn by Nat’l Park Service begins in Bandelier National Monument adjacent to Los Alamos National Lab (LANL), approx 25 mi. NW of Santa Fe.

• May 5: Declared wildland fire. Continued spread.• May 10&11: 239 houses burned; 25,000 evacuated.

– Mandatory: Los Alamos, White Rock– Voluntary: Española

• May 18: 100% contained, 47,650 acres, 5% LANL property• May 18: NMDOH invited CDC to assist:

– Mitchell Wolfe, Josh Mott, and C.M. Wood departed May 18th

May 11, 2000

EspañolaLos Alamos

CDC ObjectivesCDC Objectives

1)1) Assess environmental monitoring data Assess environmental monitoring data

2)2) Assess need for human screening for Assess need for human screening for specific exposures specific exposures

3)3) Perform necessary screening Perform necessary screening

Environmental monitoring in response to the Environmental monitoring in response to the Cerro Grande FireCerro Grande Fire

• Chemicals and metals (EPA)Chemicals and metals (EPA)– 6 sites around LANL, May 12-17.6 sites around LANL, May 12-17.– VOCs, PAHs, pesticides, and metalsVOCs, PAHs, pesticides, and metals– Results: very low VOC, PAH, and metalsResults: very low VOC, PAH, and metals

• Particulate Matter (NMED, EPA)Particulate Matter (NMED, EPA)– Additional sites and intervalsAdditional sites and intervals– Española began May 13Española began May 13– Results: low except elevated PM10 on LANL May 12-13.Results: low except elevated PM10 on LANL May 12-13.

• Asbestos (NMED)Asbestos (NMED)– air/wipe samples in Los Alamos townair/wipe samples in Los Alamos town– Results: LowResults: Low

• Radionuclides (Many agencies)Radionuclides (Many agencies)– Results: Some samples contained small amounts of radioactive Results: Some samples contained small amounts of radioactive

material, mostly from natural sources, but the concentrations in the material, mostly from natural sources, but the concentrations in the samples were several orders of magnitude below any regulatory limitsamples were several orders of magnitude below any regulatory limit

Potential human exposurePotential human exposure

• 1,600 firefighters1,600 firefighters– 1,400 (88%) during May 11-15, when most of LANL burned1,400 (88%) during May 11-15, when most of LANL burned

• Several hundred National Guard, City and State PoliceSeveral hundred National Guard, City and State Police– EvacuationsEvacuations– RoadblocksRoadblocks– Traffic control, etcTraffic control, etc

• Residents of Española (pop. 9,000) and environsResidents of Española (pop. 9,000) and environs

DiscussionDiscussion• Metal levelsMetal levels

– Some elevated values, but only Ni and U above expected number Some elevated values, but only Ni and U above expected number of elevated valuesof elevated values

• Neither Ni or U associated with smoke exposure.Neither Ni or U associated with smoke exposure.• Uranium naturally-occurring Uranium naturally-occurring • History of high natural U in previous water studies in area.History of high natural U in previous water studies in area.

• No positive association of metals with smoke exposureNo positive association of metals with smoke exposure– Only exception is cadmium in National Guard, and small mean Only exception is cadmium in National Guard, and small mean

difference in exposed vs unexposeddifference in exposed vs unexposed– Some negative associations (lower mean values in exposed)Some negative associations (lower mean values in exposed)

Difficult IssuesDifficult Issues• Health effects of “elevated” valuesHealth effects of “elevated” values

• Clinical/public health interface (acute/long-term follow-upClinical/public health interface (acute/long-term follow-up))

Limitations and Future NeedsLimitations and Future Needs• Time intervalTime interval

– Because of time interval (approx 2 ½ weeks) from fire to testing, may be Because of time interval (approx 2 ½ weeks) from fire to testing, may be an assessment of background levels in populationsan assessment of background levels in populations

– Many factors influence half-life, so difficult to reconstruct dose.Many factors influence half-life, so difficult to reconstruct dose.

• Urine testingUrine testing– Spot urine performed, but not as accurate as 24-hour urineSpot urine performed, but not as accurate as 24-hour urine– Because of issues regarding distribution in the body, measuring urine Because of issues regarding distribution in the body, measuring urine

may not be as accurate a measure as serum or other fluids/tissuesmay not be as accurate a measure as serum or other fluids/tissues

• Classification of exposureClassification of exposure– No biomarker for smoke exists. Definition of exposure based on No biomarker for smoke exists. Definition of exposure based on

presence in a city, or fighting fires, on certain days. May not be specificpresence in a city, or fighting fires, on certain days. May not be specific—need a validated biomarker of exposure.—need a validated biomarker of exposure.

Respiratory and Circulatory Hospital Respiratory and Circulatory Hospital Admissions Associated with Forest Fires - Admissions Associated with Forest Fires - Montana, July-September, 1999 & 2000Montana, July-September, 1999 & 2000

Charon Gwynn, Joshua A. Mott, Todd DamrowCharon Gwynn, Joshua A. Mott, Todd DamrowDavid Mannino, Stephen ReddDavid Mannino, Stephen Redd

EPI-AID 2001-07EPI-AID 2001-07

BackgroundBackground

• Forest fires in Bitterroot Forest fires in Bitterroot Valley burned approximately Valley burned approximately 950,000 acres950,000 acres

• 24-hour PM24-hour PM1010 concentrations concentrations

reached 300reached 300g/mg/m33

• Concerns prompted a Concerns prompted a request for assistancerequest for assistance

ObjectivesObjectives

• Quantify county-level admission rates for Quantify county-level admission rates for cardio-vascular and respiratory illnesscardio-vascular and respiratory illness

• Compare admission rates based on year Compare admission rates based on year and level of exposureand level of exposure

Case DefinitionCase Definition

• Patients admitted July 1 - September 15, Patients admitted July 1 - September 15, 1999 and 2000 for:1999 and 2000 for:– cardiovascular illness (ICD9: 390-459)cardiovascular illness (ICD9: 390-459)– respiratory illness (ICD9: 460-519)respiratory illness (ICD9: 460-519)

• Residents of 4 Counties with varying Residents of 4 Counties with varying exposure levelsexposure levels

Missoula

Ravalli

Lewis&

Clark

Yellowstone

Increase in Average PM Concentration Increase in Average PM Concentration Between the 1999 & 2000 Study PeriodsBetween the 1999 & 2000 Study Periods

0

10

20

30

40

50

60

70

-2.5 1.5 5.5 9.5 13.5 17.5

1999

2000

RavalliRavalli MissoulaMissoula LewisLewis&&

ClarkClark

YellowstoneYellowstone

PMPM1010

((g/mg/m33))

MethodsMethods• Information abstracted from 2,250 medical Information abstracted from 2,250 medical

recordsrecords

• Variables collected included:Variables collected included:– Primary & secondary discharge diagnosisPrimary & secondary discharge diagnosis– Admission/discharge dateAdmission/discharge date– Demographic informationDemographic information– History of illnessHistory of illness

• 1999 & 2000 hospitalization rates calculated 1999 & 2000 hospitalization rates calculated using the 1999 Census population estimatesusing the 1999 Census population estimates

Odds Ratios for Admission in 2000 Compared Odds Ratios for Admission in 2000 Compared to 1999 for Each Exposure Levelto 1999 for Each Exposure Level

0

1

2

3

4

5

-3 2 7 12 17 22 27 32 37 42

No ExposureModerate ExposureHigh Exposure

RESPRESP COPDCOPD DYSDYSCIRCCIRC IHDIHD HFHFPNEUPNEU CVDCVDTOTALTOTAL

OROR

• Risk of admission for circulatory and respiratory Risk of admission for circulatory and respiratory illness was greater: illness was greater:

– in highly exposed area during the 2000 fire than the in highly exposed area during the 2000 fire than the

unexposed area unexposed area

– in 2000 than 1999 in smoke exposed areasin 2000 than 1999 in smoke exposed areas

• From 1999 to 2000, risk of admission generally From 1999 to 2000, risk of admission generally increased with exposure increased with exposure

• Evidence of the influence of biomass smoke Evidence of the influence of biomass smoke exposure on more severe health endpoints. exposure on more severe health endpoints.

ConclusionsConclusions

Future DirectionsFuture Directions

• Investigate temporal PM-hospital admission Investigate temporal PM-hospital admission relationshiprelationship

• Evaluate history of illnessEvaluate history of illness

• Investigate potential biomarkers of smoke Investigate potential biomarkers of smoke exposureexposure

Conclusions From Three Conclusions From Three InvestigationsInvestigations

Health EffectsHealth EffectsSmoke exposure associated with: Smoke exposure associated with:

• increased self reported symptoms (Hoopa)increased self reported symptoms (Hoopa)• increased ED visits for resp. diseases (ICD-9 460-519)increased ED visits for resp. diseases (ICD-9 460-519)• increased hospitalizations for respiratory diseases, increased hospitalizations for respiratory diseases,

COPD, IHD. COPD, IHD.– mortality?mortality?– short term health effects?short term health effects?– disease susceptibility, longer term health effects?disease susceptibility, longer term health effects?– studies of biologic plausibility?studies of biologic plausibility?

Conclusions (Cont.)Conclusions (Cont.)Indicators of Exposure Indicators of Exposure Health effects associated with: Health effects associated with:

• geographic proximity to fires/PMgeographic proximity to fires/PM• self reported hours of outdoor activityself reported hours of outdoor activity

– other indicators? (phenols, PAHs, nickel, CO)other indicators? (phenols, PAHs, nickel, CO)

Effectiveness of InterventionsEffectiveness of Interventions• HEPA Cleaner use (Hoopa and Malaysia)HEPA Cleaner use (Hoopa and Malaysia)• Recollection of PSAsRecollection of PSAs

– randomized trials?randomized trials?