Association between ambient air Association between ambient air

pullution and the hospital emergency pullution and the hospital emergency

room visits for respiratory diseases: room visits for respiratory diseases:

a casea case--crossover studycrossover study

Chang Su, Yuming Guo, Xiaochuan PanChang Su, Yuming Guo, Xiaochuan Pan

Department of Occupational and Environmental Department of Occupational and Environmental

Health, School of Public Health, Peking Health, School of Public Health, Peking

University, Beijing100191, ChinaUniversity, Beijing100191, China

BackgroundBackground�� PopulationPopulation--based studies of air pollution have shown an based studies of air pollution have shown an

association with respiratory morbidity and mortality.association with respiratory morbidity and mortality.

�� PMPM1010, SO, SO22 and NOand NO22 have been associated with increased have been associated with increased

hospital visits and admissions:hospital visits and admissions:

�� Pneumonia, COPD exacerbation, asthmaPneumonia, COPD exacerbation, asthma

�� To date, the majority of research on To date, the majority of research on air pollutionair pollution and and hospital hospital

emergency room visitsemergency room visits has been conducted in developed has been conducted in developed

countries, and a limited number of studies have evaluated in countries, and a limited number of studies have evaluated in

the developing countries.the developing countries.

ObjectiveObjective

�� To explore the the association between ambient To explore the the association between ambient

air pollution(PMair pollution(PM1010, SO, SO22 and NOand NO22 ) and the ) and the

hospital emergency room visits for the hospital emergency room visits for the

respiratory diseases in Beijing, China. respiratory diseases in Beijing, China.

Methods: data collectionMethods: data collection

AA Hospital Emergency Hospital Emergency

Room Visits Room Visits

BB

CC

Air Pollutants Air Pollutants

Weather Condition Weather Condition

Data of daily average Data of daily average

temperature and relative temperature and relative

humidity were collected from humidity were collected from

the Institute of Atmospheric the Institute of Atmospheric

Physics where is about 2 km Physics where is about 2 km

away from the Peking University away from the Peking University

Third Hospital.Third Hospital.

We collected the data of We collected the data of

daily emergency room daily emergency room

visits of visits of respiratory respiratory

disease fromdisease from June 1, June 1,

2004 to December 31, 2004 to December 31,

20052005 from Peking from Peking

University Third University Third Hospital. Hospital.

Based on ICDBased on ICD--10 10

dignostic codes(J00dignostic codes(J00--J99).J99).

DataData of PMof PM1010,, SOSO22 and NOand NO22 were were

collected from Beijing Municipal collected from Beijing Municipal

Environmental Monitoring Center.Environmental Monitoring Center.

Study areaStudy area

Methods: data analysisMethods: data analysis

�� The main intention of this study is to compare each subjectThe main intention of this study is to compare each subject’’s exposure s exposure

experienced just before hospital visit with that at other times experienced just before hospital visit with that at other times when the subject when the subject

was not hospitalized. was not hospitalized.

�� The conditional logistic regression model was used in our study The conditional logistic regression model was used in our study to analyze to analyze

different exposures between the case time and the control time.different exposures between the case time and the control time.

�� Control:Control:

�� unidirectional control sampling approch: one week beforeunidirectional control sampling approch: one week before

�� bibi--directional control sampling approch: one week before and afterdirectional control sampling approch: one week before and after

Case-crossover design

Advantages of caseAdvantages of case--crossover designcrossover design

Confounding Confounding

factorsfactors

ageagesexsex

smokingsmoking

harm habitsharm habits

nutrition conditionsnutrition conditions

seasonal confoundingseasonal confounding

Steps of caseSteps of case--crossover designcrossover design

�� ToTo assess the effect of air assess the effect of air

pollution up to lags of pollution up to lags of fivefive days. days.

�� Model construction:Model construction:

SingleSingle--pollutant modelpollutant model

MultipleMultiple--pollutantspollutants modelmodel

�� PM10PM10

�� SO2SO2

�� NO2NO2

�� TheThe relevant data of air relevant data of air

temperature and humidity temperature and humidity

werewere put into the model to put into the model to

controlcontrol their effect. their effect.

distributed lag modeldistributed lag model

define the hazard perioddefine the hazard period

Single/multipleSingle/multiple pollutants modelpollutants model

ResultsResults

AA

BB

CC

DD

Air pollution and weather Air pollution and weather

conditioncondition

Hospital emergency room visitsHospital emergency room visits

SpearmanSpearman correlation analysis correlation analysis

Association of daily hospital Association of daily hospital

emergency room visits for emergency room visits for respiratoryrespiratory

diseases and air pollutants diseases and air pollutants

Summary of air pollutants and weather Summary of air pollutants and weather

condition during study periodcondition during study period

13.4113.41±±±±±±±±11.0011.00

49.1549.15±±±±±±±±20.1020.10

101.27101.27±±±±±±±±1.02 1.02

14.9014.90±±±±±±±±9.89 9.89

32.1032.10

92.0092.00

103.68103.68

7575

--8.508.50

10.0010.00

98.8898.88

00

23.2023.20

67.0067.00

102.06 102.06

1919

15.4015.40

49.0049.00

101.26 101.26

1212

3.503.50

31.7531.75

100.52 100.52

88

Weather conditionWeather condition

Temperature (Temperature (℃℃℃℃℃℃℃℃))

Relative humidity Relative humidity (%)(%)

Atmospheric pressure(pa)Atmospheric pressure(pa)

Emergency room visitsEmergency room visits

52.6252.62±±±±±±±±51.6951.69

68.6668.66±±±±±±±±25.9325.93

145.34145.34±±±±±±±±90.30 90.30

280.00280.00

214.40214.40

573.00573.00

5.715.71

17.6017.60

10.0010.00

66.0066.00

80.0080.00

189.14189.14

32.7132.71

64.0064.00

128.57128.57

18.0018.00

52.8052.80

76.0076.00

Air pollution Air pollution

SOSO22 ((μμμμμμμμg/mg/m33))

NONO22 ((μμμμμμμμg/mg/m33))

PMPM1010((μμμμμμμμg/mg/m33))

757550502525Mean Mean ±±±±±±±± SDSDMaximumMaximumMinimumMinimum

Frequency distributionFrequency distribution

Total number of ER visits for respiratory disease: 10894

Spearman correlation analysis for air pollutants Spearman correlation analysis for air pollutants

and weather data between the study periodand weather data between the study period

1.0001.000

RelativeRelative

humidity (%)humidity (%)

--0.383*0.383*1.0001.000

AtmosphericAtmospheric

pressure(pa)pressure(pa)

0.395*0.395*--0.855*0.855*1.0001.000

Temperature Temperature

((℃℃℃℃℃℃℃℃))

0.293*0.293*--0.194*0.194*0.133*0.133*1.0001.000PM10PM10

0.307*0.307*--0.0180.018--0.0190.0190.741*0.741*1.0001.000NO2NO2

--0.286*0.286*0.577*0.577*--0.717*0.717*0.349*0.349*0.480*0.480*1.0001.000SO2SO2

Relative Relative

humidity (%)humidity (%)

AtmosphericAtmospheric

pressure(pa)pressure(pa)

Temperature Temperature

((℃℃℃℃℃℃℃℃))PM10PM10NO2NO2SO2SO2

* * (P<0.05)

Association of daily ER visits for respiratory diseases Association of daily ER visits for respiratory diseases

and air pollutants at different Lagsand air pollutants at different Lags

Single pollutants modelSingle pollutants model-- association of daily ER visits for association of daily ER visits for

respiratory diseases and air pollutantsrespiratory diseases and air pollutants

1.011(1.0001.011(1.000--1.023) *1.023) *1.033(1.0191.033(1.019--1.047) *1.047) *NONO2 2 (( lag 2)lag 2)

1.012(1.0051.012(1.005--1.019) *1.019) *1.017(1.0101.017(1.010--1.025) *1.025) *SOSO2 2 (( lag 0)lag 0)

1.004(1.0011.004(1.001--1.008) *1.008) *1.011(1.0081.011(1.008--1.015) *1.015) *PMPM10 10 (( lag 0)lag 0)

bibi--directional control directional control

approchapproch

Unidirectional control Unidirectional control

approchapproch

OR (95%CI)OR (95%CI)

PollutantsPollutants

* * (P<0.05)

Multiple pollutants modelMultiple pollutants model-- association of daily ER visits for association of daily ER visits for

respiratory diseases and air pollutantsrespiratory diseases and air pollutants

1.0121.012(1.001(1.001--1.021.0222) *) *1.001(0.9831.001(0.983--1.009)1.009)+ + PMPM1010 and SOand SO

22

1.0121.012(1.002(1.002--1.022) *1.022) *1.005(0.9921.005(0.992--1.017)1.017)+ SO+ SO22

1.010(1.0001.010(1.000--1.021) *1.021) *0.997(0.9840.997(0.984--1.010)1.010)+PM+PM2.52.5

Lag Lag 22Lag Lag 22NONO22

1.011(1.0031.011(1.003--1.018)*1.018)*1.010(1.0011.010(1.001--1.018) *1.018) *+ + PMPM1010 and NOand NO

22

1.012(1.0051.012(1.005--1.019)*1.019)*1.017(1.0091.017(1.009--1.025) *1.025) *+ NO+ NO22

1.010(1.0021.010(1.002--1.017)1.017)1.009(1.0011.009(1.001--1.018) *1.018) *+ + PMPM1010

Lag 0Lag 0Lag 0Lag 0SOSO22

1.002(0.9881.002(0.988--1.005)1.005)1.010(1.0051.010(1.005--1.014) *1.014) *+SO+SO2 2 and NOand NO

22

1.004(1.0001.004(1.000--1.009) *1.009) *1.012(1.0081.012(1.008--1.016) *1.016) *+ NO+ NO22

1.002(0.9981.002(0.998--1.006)1.006)1.009(1.0051.009(1.005--1.014) *1.014) *+ SO+ SO22

Lag 0Lag 0Lag 0Lag 0PMPM1010

bibi--directional control directional control

approchapproch

Unidirectional control Unidirectional control

approchapproch

OR (95%CI)OR (95%CI)

PollutantsPollutants

* * (P<0.05)

DisussionDisussion

�� A transient increase in ambient PM10, SO2 and NO2 was associatedA transient increase in ambient PM10, SO2 and NO2 was associated

with an increased risk of hospital emergency room visits for totwith an increased risk of hospital emergency room visits for total al

respiratory diseases.respiratory diseases.

�� After controlling the influence of two pollutants, the risk effeAfter controlling the influence of two pollutants, the risk effect of the ct of the

other one air pollutant on the hospital emergency room visits foother one air pollutant on the hospital emergency room visits for total r total

respiratory diseases decreased. It indicates that the effect of respiratory diseases decreased. It indicates that the effect of the three the three

air pollutants has interaction on the related health effects.air pollutants has interaction on the related health effects.

�� The results of uThe results of unidirectional control sampling approch are differ from nidirectional control sampling approch are differ from

bibi--directional control approch. There would be bias about the timedirectional control approch. There would be bias about the time

trends of exposure in the trends of exposure in the uunidirectional control approch, the results of nidirectional control approch, the results of

bibi--directional control approch are more reliable.directional control approch are more reliable.

DiscussionDiscussion

Limitations and further studyLimitations and further study

�� Limitations: Limitations:

We used ambient monitoring data to represent the individual We used ambient monitoring data to represent the individual exposures to air exposures to air

pollutants. Our assessment of weather conditions was collected epollutants. Our assessment of weather conditions was collected entirely from ntirely from

only one monitoring only one monitoring station.station. It is possible that this type of error may introduce It is possible that this type of error may introduce

bias to our results. bias to our results.

�� Further study: Further study:

Classify the visits into different sex group, age group; anaClassify the visits into different sex group, age group; analyze the influence of lyze the influence of

season.season.

Thank You !Thank You !