Transcript Central European Study of Air Pollution and Respiratory Health

Does outdoor or indoor air pollution cause
more respiratory disease? Evidence from
the Central European Study on Air
Pollution and Respiratory Health
(CESAR Study).
Tony Fletcher, London School of Hygiene and Tropical
Medicine, London. UK
Brunekreef B, Houthuijs D, Fabianova E, Lebret E,
Leonardi G, Gurzau E, Nikiforov B, Rudnai P, Volf J,
Zejda J.
Central European Study of Air Pollution
and Respiratory Health
CESAR National Research Teams
Bulgaria: National Centre of Hygiene, Bojidar Nikiforov
Czech Republic: Regional Institute of Hygiene Ostrava, Jaroslav Volf
Hungary: National Institute of Public Health, Alan Pintér and Peter Rudnai
Poland: Institute of Occupational Medicine and Environmental Health, Jan Zejda
Romania: Environmental Health Center, Eugen Gurzau
Slovakia: Regional Specialized Institute of Public Health Banska Bystrica, Eleonorá
Fabiánová
United Kingdom: LSHTM, Tony Fletcher, Giovanni Leonardi and Sam
Pattenden
The Netherlands: WAU, : Bert Brunekreef and Gerard Hoek
The Netherlands: RIVM, Erik Lebret, Annelike Dusseldorp and Danny
Houthuijs
CESAR - AIMS:
Establish comparable base-line data on:
children’s respiratory health
air pollution, including PM10 and PM2.5
environment and health risk perceptions
Investigate effects on respiratory health of:
air pollution
indoor and other risks factors
Capacity building:
(epidemiological) research methods
introduction of QA/QC methods
Central European Study of Air Pollution
and Respiratory Health
European Funding for CESAR:
1994-1997
EC - PHARE Programme
1999-2000
EC - INCO Copernicus
Central European Study of Air Pollution
and Respiratory Health
Study characteristics
 Cross-sectional study among children aged 7 - 11 year in 6
countries
 Four (five) study areas per country: 25 study areas
 Selection of study areas within countries based on differences in
air pollution levels and in dominant local sources
 Participation of about 1,000 children per study area
 Current concentration of PM10 and PM2.5 measured in all study
areas
 Assessment of respiratory health endpoints and potential
confounders at individual level
CESAR Study areas
Central European Study of Air Pollution
and Respiratory Health
Methods
• 24 hour sampling, once every six days, during Nov 1995 - Oct 1996
• background sampling site
• Harvard impactors with cut-off points at 2.5 and 10 µm
• preparation and analysis in one central laboratory per country
• Questionnaire respiratory symptoms and conditions: based on items from
WHO, ISAAC and ATS in children 7 - 11 years old
• Base-line pulmonary function test (FVC and FEV1) in children age 9 - 11
• Information on risk factors and potential confounders collected by
questionnaire
Questionnaire based health endpoints
• Cough on most days for at least 3 months consecutively in the last
autumn-winter season
• Any cough symptom over life time (combination)
• Any wheeze symptom in the last 12 months (combination)
• Any wheeze symptom over lifetime (combination)
• Bronchitis doctor diagnosed, ever
• Bronchitis in last 12 months
• Asthma doctor diagnosed, ever
• Asthma attacks in last 12 months
• Medication use for a breathing trouble in last 12 months
Risk factors in model
• Age, sex
• Furniture with chipboard
• country
• Reported frequency of traffic
• current # of smokers in the
home
• use of gas range or oven for
heating in winter
• use of unvented gas, oil or
kerosene heater
• ever moisture stains or mould
in the home over lifetime of
child
passing the house
• Consumption of fruit,
vegetables and fish
• education of the mother
• occupation of the father
• Parental history of wheeze,
asthma, inhalant allergy,
eczema or hay fever
Statistical analyses
• Assessment of current annual average concentrations for PM10,
PM2.5 and coarse fraction
• Two stage regression of area-specific means/logits after adjustment
for potential individual confounders
• Random effects models at taking into account within country
correlations for estimating pollution effect
• Attributable fraction: calculation of attributable fractions from
logistic regression models
Numbers in study
•total population: 20271
•3470 (1 Country) dropped for lack of PM
data
•2899 dropped for missing values in one or
more variables in the models
•subjects used in these analyses: 13902
CESAR - 25 Study areas
Bulgaria
Sofia suburb
Sofia centre
Vratza
Assenovgrad
Poland
Thermal power station
Traffic
Chemicals,
Metallurgical
Kedzierzyn - Kozle
Kielce
Pszczyna
Swietochlowice
Czech Republic
Romania
Ostrava centre
-Vitkovice
Ostrava - Poruba
Ostrava - Radvanice
Bucharest
Ploiesti
Baja Mare
Tirgu Mures
Local heating, traffic Ostrava
Iron works, power, coke
No local sources
Iron works, coke oven
Chemical plant
Clean, recreational area
Clean area
Metallurg., coal, chemical
Traffic, local heating
Petrochemical, chemicals
Metallurgical industry
Chemical industry
Hungary
Slovakia
Cegled
Dorog
Eger
Tata
Tatabanya
Banska Bystrica suburb No local sources
Banska Bystrica centre Traffic, cement plant
Zilina
Chemical, paper factories
Bratislava
Traffic, local heating
No local sources
Local heat., power plant, pharmac.
Local heat., intense traffic, agric.
Local heating, moderate traffic
Local heating, coal/ oil power
Central European Study of Air Pollution
and Respiratory Health
Association of PM with respiratory health
outcomes
The next two slides illustrate provisional results of the
relationships between particulate pollution and adjusted
prevalence of respiratory symptoms. Detailed numerical values
will be available in a forthcoming publication
The subsequent slide illustrates the calculation of attributable
fractions for a limited number of exposure factors and one
outcome factor. Detailed results will be available in a
forthcoming publication
Cough and PM2.5 by study area
any cough symptoms ever (%)
60
C
C
P
40
S
S
S
B
S
20
H
H
H
B
P
P
C
P
C
BB
HH
0
30
40
50
PM2.5-concentration (µg/m3)
60
70
Wheeze and PM2.5 by study area
any wheeze symptoms ever (%)
50
B
40
B
B
B
30
H
S
S
S
20
10
S
30
H
H
HH
P
C
C
C
P
40
50
PM2.5-concentration (µg/m3)
P
C
60
P
70
Example of some risk factors for Wheeze:
Prevalence, Odds ratios and Attributable fractions
Variable
Level
Air pollution
29 µg/m3
67 µg/m3
Traffic intensity
None
Light
Medium
Heavy
Prev. %
OR
95%CI
5
5 - 95
1.49
1.07 -2.07
11.3
52
29
12
6
1.16
1.18
1.17
1.03 -1.31
1.03 -1.35
1.05 -1.31
3.0
1.4
0.7
Traffic
Heating with Gas Oven
Kerosene heater
Indoor combustion
sources
AFs %
5.1
No
Yes
No
Yes
96
4
96
4
1.04
0.85 -1.28
0.1
1.32
1.05 -1.67
0.8
0.9
Conclusions
• attributable fractions are a helpful indicator for interpreting these
results and could be used more widely
• parental history of respiratory illness and indicators of
socioeconomic status are important contributors to symptom
prevalence
• air pollution is more important for some symptoms than indoor
combustion sources, ETS or dampness
• the presence of chipboard furniture is very prevalent and appears
to be associated with substantial attributable fractions for some
symptoms
Central European Study of Air Pollution
and Respiratory Health