: the ESCAPE project Martin Adam, research associate *,

Long-term exposure to air pollution and lung function in adults: the ESCAPE project
Martin Adam, research associate1,2*, Tamara Schikowski, research associate1,2,3*,
Anne Elie Carsin, research associate4*, Yutong Cai, PhD student5, Benedicte
Jacquemin, research associate4,6,7, Margaux Sanchez, PhD student6,7, Andrea
Vierkötter, research associate3, Alessandro Marcon, research associate8, Dirk Keidel,
research assistant1,2, Dorothee Sugiri, research assistant 3, Zaina Al Kanani, PhD
student5, Rachel Nadif, research associate6,7, Valérie Siroux, research associate9,10,
Rebecca Hardy, professor11, Diana Kuh, professor11, Thierry Rochat, professor12,
Pierre-Olivier Bridevaux, research associate12, Marloes Eeftens, research
associate1,2,13, Ming-Yi Tsai, research associate 1,2, Simona Villani, professor14, Harish
Chandra Phuleria, research associate1,2, Matthias Birk, research assistant15, Josef
Cyrys, research associate15,16, Marta Cirach, research assistant4, Audrey de Nazelle,
lecturer17, Mark J Nieuwenhuijsen, professor4, Bertil Forsberg, professor18, Kees de
Hoogh, research associate5, Christophe Declerq, research associate19, Roberto Bono,
professor20, Pavilio Piccioni, research associate21, Ulrich Quass, research associate22,
Joachim Heinrich, research associate15, Deborah Jarvis, professor5,23, Isabelle Pin,
research associate9,10, 24, Rob Beelen, research associate13, Gerard Hoek, professor13,
Bert Brunekreef, professor13,25, Christian Schindler, research associate1,2, Jordi
Sunyer, professor4#, Ursula Krämer, professor3#, Francine Kauffmann, professor6#,
Anna L Hansell, senior lecturer5,26#, Nino Künzli, professor1,2#, Nicole Probst-Hensch,
professor1,2#. *contributed equally; # Steering Committe of ESCAPE Work Package 4
on Respiratory Health in Adults.
Corresponding Author:
Prof. Dr. Nicole Probst-Hensch
Head Unit Chronic Disease Epidemiology
Swiss Tropical and Public Health Institute
Socinstrasse 57, P.O. Box, 4002 Basel, Switzerland
PHONE: 0041-61-284 83 78 ; EMAIL: [email protected]
1
Swiss Tropical and Public Health Institute, 4002 Basel
2
University of Basel, Switzerland;
3
Leibniz Research Institute for Environmental Medicine (IUF), 40225 Düsseldorf,
Germany
1
4
Centre for Research in Environmental Epidemiology (CREAL), 08003 Barcelona,
Spain
5
MRC-PHE Centre for Environment and Health, Dept of Epidemiology and
Biostatistics, School of Public Health, Imperial College London, W2 1PG London,
UK
6
Inserm, Centre for research in Epidemiology and Population Health (CESP), U1018,
Respiratory and Environmental Epidemiology Team, 94807, Villejuif, France
7
Univ Paris-Sud, UMRS 1018, 94807, Villejuif, France.
8
Unit of Epidemiology and Medical Statistics, Department of Public Health and
Community Medicine, University of Verona, 37134 Verona, Italy
9
Inserm U823, Environmental Epidemiology Applied to Reproduction and
Respiratory Health team, 38042 Grenoble, France;
10
Univ Joseph Fourier, 83041 Grenoble, France
11
MRC University Unit for Lifelong Health & Ageing at University College London
WC1E 6BT, UK
12
Division of Pulmonary Medicine, University Hospitals of Geneva, 1205 Geneva,
Switzerland
13
Institute for Risk Assessment Sciences, Utrecht University, 3508 TD Utrecht, The
Netherlands
14
Unit of Biostatistics and Clinical Epidemiology Department of Public Health,
Experimental and Forensic Medicine University of Pavia, 27100 Pavia, Italy.
15
Helmholtz Zentrum, München & German Research Centre for Environmental
Health, Institute of Epidemiology I, 85764 Neuherberg, Germany
16
Environmental Science Center, University Augsburg, 86150 Augsburg, Germany
17 Centre for Environmental Policy, Imperial College London, London SW7 1NA,
UK
18
Environmental and Occupational Medicine, Department of Public Health and
Clinical Medicine, Umeå University, SE-901 85 Umeå, Sweden
19
French Institute for Public Health Surveillance, 94415 Saint-Maurice, France.
20
Department of Public Health and Pediatrics, University of Turin, 10126 Turin, Italy
21
SC Pneumologia CPA ASL 4 Turin, 10154 Turin, Italy
22
Air Quality and Sustainable Nanotechnology, IUTA Institut für Energie- und
Umwelttechnik e.V., 47229 Duisburg, Germany
2
23
Department of Respiratory Epidemiology and Public Health, National Heart and
Lung Institute, Imperial College London, London SW7 2AZ, UK
24
Pédiatrie, CHU de Grenoble, 38700 La Tronche, France.
25
Julius Center for Health Sciences and Primary Care, University Medical Center
Utrecht, 3508 GA Utrecht, The Netherlands
26
Public Health and Primary Care Directorate, Imperial College Healthcare NHS
Trust, London SW7 2AZ, UK
3
Outline of Sections:
Methods

Cohorts

Exposure

Lung Function Metrics and Outcomes

Statistical models

Meta-analysis
Supplemental Table S1: Description of cohort-specific study populations.
Supplemental Table S2: Information on spirometry instruments.
Supplemental Table S3. Level of lung function and annual change of lung function
of the cohort-specific study populations.
Supplemental Table S4. The spatial variance of the applied ESCAPE LUR models.
Supplemental Table S5. Cohort-specific distribution of all exposure estimates.
Supplemental Table S6. Cohort-specific spearman correlation matrix for all home
outdoor exposures.
Supplemental Table S7. Results from meta-analyses for the cross-sectional
association between the level of lung function and NO2 exposure (standard contrast of
10 µg/m³) backextrapolated to the time point of the 2nd spirometry.
Supplemental Table S8 and Table S9. Results from meta-analyses for the crosssectional association between the level of lung function and NO2 exposure (standard
contrast of 10 µg/m³) in different subgroups.
Supplemental Table S10. Results from meta-analyses for the cross-sectional
association between the level of lung function and NO2 exposure (standard contrast of
10 µg/m³) in the restricted groups included in the sensitivity analysis.
Supplemental Figures S1a-e: Flowcharts describing the study specific ESCAPE
sampling process.
Supplemental Figure S2 and Figure S3: Forest plot displaying the center-specific
mixed linear regression models of NO2 and FVC stratified by obesity status.
4
Supplemental Figure S4 and Figure S5: Forest plot displaying the mixed linear
regression models of NO2 and FEV1 and FVC for women.
5
Methods
Cohorts
ECRHS (European Community Respiratory Health Survey)
1
was initiated in 1991-
93 as a cross-sectional study, followed up in 2001. The study included 48 centers
from 23 countries. In ECRHS I adults aged between 20 and 44 years were selected at
random from available population based registers with an oversampling of asthmatics.
The baseline (at 1st spirometry) investigation was based on 17354 subjects. The follow
up (at 2nd spirometry) had a response rate of 65.3% of the baseline sample. The main
objective of ECRHS I was to estimate the variation in the prevalence of asthma,
asthma-like symptoms, asthma sensitization and bronchial reactivity. Further, the
identification of risk factors and how these explain variation across Europe was
determined as well as the estimation of variation in the treatment for asthma in
Europe.
Wherever practically possible, 1st spirometry lung function measures (FEV1 and FVC)
were taken using the same equipment in both, ECRHS I and ECHRS II. In the
majority of centers this was a water-sealed bell spirometer (Biomedin, Padova, Italy).
Twenty-two ECRHS centers used the same spirometer in both ECRHS I and ECRHS
II, with most having updated software on the second occasion. Eighteen centers used
the Spiro Medics computerized dry-rolling seal spirometer system 2130 (Sensor
Medics, Anaheim, California, USA). The other four centers used other comparable
spirometers on both occasions. The use of different equipment did not lead to any
heterogeneity in lung function change compared with other centers 1.
EGEA (French Epidemiological study on Genetics and Environment of Asthma) 2, 3 is
a 12-year follow-up study. It combines a case-control study with a family study of
asthma cases (children or adults) conducted between 1991 and 1995 (at 1st
spirometry) in 2047 subjects from five French cities 4, 5. A follow-up (at 2nd
spirometry) of the initial cohort was conducted between 2003 and 2007. Among the
alive cohort (n = 2002), 92% (n = 1845) and 80% completed a short self-administered
questionnaire and among them 1601 had an examination (1414 with lung function
test. Spirometry devices were switched between 1st spirometry to 2nd spirometry
(Biomedin to Spirodyn).
6
NSHD (Medical Research Council’s National Survey of Health and Development)
6
consists of a socially stratified sample of all births that took place in England,
Scotland and Wales during one week in March 1946 6. The original sample of 2547
women and 2815 men have been followed up multiple times during the life course.
The main objectives since the 1999 follow-up, taken as the 1st spirometry for the
ESCAPE study, have been the measurement of physical and mental functioning, the
study of pathways to those outcomes, and study of morbidity and mortality for
multiple health outcomes.
Lung function was measured at ages 53 (1999; 1st spirometry) and 60-64 (2006-2010;
2nd spirometry) years using the Micromedical turbine electronic spirometer,
administered by a trained nurse. The protocol did not correspond to ATS criteria.
Three trials were given at 53 years, and 2 trials were given at 60-64 years. Where
three blows were recorded, the variation in FEV1 across the best two of these trials
was within 5% for 77.5% of the sample. FEV in 1 sec (FEV1) and forced vital
capacity (FVC) were measured in the standing position, without nose clips, after
instruction and under the supervision of a trained research nurse. Subjects were
excluded from subsequent analyses if the best two lung function readings differed by
more than 10% from each other and if readings were outside the normal range after
adjusting for gender and height (standardized residuals greater than 3 SD units from
the mean) 7-9
SALIA (Study on the influence of Air pollution on Lung function, Inflammation and
Aging) 10 study was initiated in 1985 as part of Environmental Health surveys, which
were an element of the Clean Air Plan initiated by the Government of North-Rhine
Westphalia in Germany. Main objective of the baseline investigations was to monitor
health effects of outdoor air pollution in the heavily polluted Ruhr Area. A
questionnaire follow-up was conducted in 2006 and in 2007 to 2009 (at 2nd
spirometry) health assessments were performed to investigate the long-term effects of
outdoor air pollution and changes in pollution on respiratory health.
The baseline investigation (at 1st spirometry) included 4756 women. The geographic
regions were chosen to represent a range of polluted areas with high traffic load and
steel and coal industries. The regions included parts of the cities of Duisburg, Essen,
Gelsenkirchen, Dortmund, Herne and Borken. Sampling included all women of
7
German nationality aged 54 to 55 residing in the selected areas (near (< 4 km) to
governmental measurement stations).
SALIA kept one device (Master Scope Jaeger), which was used for most women in
Spirometry 1 and 2. During spirometry 1, Vica test was replaced with Master Scope
Jaeger. 116 women had an investigation with both devices. From these double
measurements a regression equation was established for transforming the values
between devices. (FVCjaeger = 1.037*FVCvica – 0.01072; FEV1jaeger=0.96216*FEV1vica0.01311. During spirometry 2 Master Scope Jaeger was replaced with NDD Easy
One. 28 persons were investigated with both devices and the following transformation
equations
were
developed:
FVCJaeger
=
1.10797*FVCndd
–
0.04149;
FEV1Jaeger=1.03671*FEV1ndd+0.21955. The values used in the analysis of this paper
were all transformed to Master Scope Jaeger values. Spirometry was performed
according to the ATS/ETS recommendations. Forced expiratory volume in 1 second
(FEV1) and forced vital capacity (FVC) were measured. Between three to four
maneuvers were performed under direction of trained personnel, and the values where
the maximal FEV1 was reached were used. All measuring instruments were calibrated
prior to each testing. The technical personnel were trained and all results were
reviewed by a pulmonary physician 11.
SAPALDIA (Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in
Adults)
12
is a multi-center study that was initiated in 1991 in eight geographic areas
representing the range of environmental, meteorological and socio-demographic
conditions in Switzerland. The main aim of the study was to assess the effect of air
pollution (outdoor and indoor) on respiratory and cardiovascular health, with a special
focus on how the respiratory and cardio-vascular system interact in this regard, and on
the role of lifestyle and genetic background.
In 1991, 9'651 subjects, aged 18 to 60 years, were recruited for a detailed interview
and more than 90% of them provided valid spirometry (1st spirometry) results. The
follow-up assessment (at 2nd spirometry) was conducted in 2002 and 8'047 (83%)
participants provided health information and 6'528 persons underwent physical reexamination. SAPALDIA will contribute to the study with lung function
measurements from the baseline (at 1st spirometry) examination in 1991
(SAPALDIA1 ) and the first follow-up (at 2nd spirometry) examination in 2002
(SAPALDIA2).
8
The same spirometry protocol was used in SAPALDIA 1 and 2; identical to the
protocol in ECRHS and meeting ATS performance standards. Spirometric tests were
performed in a sitting position with nose clips. Participants performed at least three
and up to eight forced expiratory lung function maneuvers in order to obtain a
minimum of two acceptable and reproducible values. Identical spirometers were used
by each center and at both, 1st spirometry SAPALDIA1 and SAPALDIA2 2nd
spirometry examination: each center in SAPALDIA1 and SAPALDIA2 was equipped
with an identical computerized spirometer (Sensormedics 2200 SP, Bilthoven, The
Netherlands) which uses the successfully evaluated and accepted mass flow
anemometer technology. The three best results for forced vital capacity (FVC) and
forced expiratory volume in one second (FEV1), and the five-digit error code for ATS
criteria were stored on a hard disk and printed on paper, including flow-volume charts
for further documentation. The highest values for FVC and FEV1, of any accepted
trial were chosen. SAPALDIA performed detailed quality control measurements
between field workers at spirometry 1 (13 and between spirometry 1 and spirometry 2
devices (same device)
14
. Furthermore the lung function results were also compared
between Sensormedics (instrument used in SAPALDIA) and Biomedin (the
instrument in ECRHS and EGEA study centers). The quality control studies showed
no significant differences between individual technicians or teams. But they showed
that although all devices complied with the ATS standards of accurate instruments,
and all calibrations were within the required precision, lung function test results taken
under biologic conditions did differ significantly between instruments 14.
Exposure
ESCAPE exposure assessment is described in detail in an online manual
(http://www.escapeproject.eu/manuals/) and in a Lancet Online Supplement
associated with Beelen et al. 2013 15.
Air pollution monitoring campaigns were conducted between 2008 and 2011 in all
selected study areas from participating cohorts. In each area, the monitoring
campaigns consisted of three 2-week measurements of NO2 and NOx performed at 40
sites. Simultaneous measurements of PM2.5 absorbance (marker for black carbon),
PM2.5, PM10 were performed in a subsample of study areas selected for the NO2/NOX
measurement campaign, because budgetary constraints prohibited inclusion of all
study areas. PM measurements were performed at 20 sites within each study area. The
9
ESCAPE exposure assessment in all geographic sites of ESCAPE has followed a
standardized measurement protocol
16
. Measurement sites were selected to represent
the anticipated spatial variation of air pollution in the area.
Land use regression (LUR) models specific for the measurement area to explain
spatial variation of annual average concentrations as obtained from the measurement
campaigns were developed. Predictor variables on nearby traffic intensity,
population/household density and land use were derived from Geographic Information
Systems (GIS). These LUR models were developed for each cohort following a
common protocol (http://www.escapeproject.eu/manuals/) and assigned annual mean
air pollutant concentrations to the baseline residential address of each study
participant.
Pollution measurements were performed between 2008-2011, but follow-up from 1st
to 2nd spirometry in all cohorts covered earlier time periods which dated as far back as
1985. We therefore had to extrapolate predicted concentrations back in time using the
ratio between baseline and 2008-2011 periods, based on data from routine background
monitoring network site(s) in the study areas. As these background monitoring
network only provided historical data for NO2 and PM10, we restricted
backextrapolation to these two metrics. Historical data on NO2 and PM10 was not used
for the backextrapolation of additional pollution metrics, as time trends differ by
pollutant. Details and examples for the procedure of backextrapolation are provided in
the Online Supplement of the paper by Beelen et al
15
. ESCAPE NO2 and PM10
exposures were backextrapolated to the time point of the 1st and 2nd spirometry where
possible and appropriate. Backextrapolation of NO2 and PM10 exposure to the 1st
spirometry was not possible for ECRHS and EGEA, as historical data was not
available from all study areas. NO2 and PM10 exposure in NSHD and SALIA were
only backextrapolated to 1st spirometry, as the timepoints for 2nd spirometry were
sufficiently close to the time of the ESCAPE monitoring campaign (2008-2011).
In addition to pollutants derived from measurement campaigns and LUR models,
traffic intensity on the nearest road (vehicles/day) and total traffic load
(intensity*length) on all major roads within a 100 m buffer were used. These variables
were obtained using a digital road network linked with traffic intensity data in a GIS.
According data was obtained by local cohort experts in the absence of available traffic
intensity data on a European-wide scale (for detailed procedures see
10
(http://www.escapeproject.eu/manuals/). A default of 500 vehicles/day was assigned
to minor roads missing from the local road networks or to roads lacking information
on traffic intensity.
Epidemiological evidence on the association between traffic indicators and health
outcomes and their interpretation are discussed in detail in the Health Effect Institute
Report on Traffic-Related Air Pollution: A Critical Review of the Literature on
Emissions, Exposure, and Health Effects 17.
Lung Function Metrics and Outcomes
Applied spirometry instruments for pulmonary function testing in the ESCAPE
centers included in this analysis, differed by cohort and in some study areas by
assessment round (1st spirometry and 2nd spirometry) (Supplemental Table 2). As
spirometric outcome metrics we assessed FEV1 and FVC cross-sectionally (level of
lung function) and longitudinally (change in lung function) in this study. For level of
lung function, the time point of spirometry closest to the actual ESCAPE exposure
measurement provided the outcome metrics. For change in lung function we assessed
the annual lung function decline (ml/year) which was calculated as (lung function at
2nd spirometry minus lung function at 1st spirometry)/years of follow-up, thus a
negative value indicates that lung function declined during follow-up. In addition, we
calculated the percent change in lung function (%), calculated as (annual decline/lung
function at 1st spirometry*100), thus a negative percent value indicates that lung
function declined during follow-up.
Statistical models
It was a strategic decision in the ESCAPE project to aim for local analyses, following
strict and harmonized protocols, followed by meta-analysis. Privacy issues and
limited centralized resources precluded centralized analyses.
The association between lung function and air pollution was analyzed in each cohort
separately according to a common statistical protocol, codebook and STATA script
used by the local analysts. A statistical working group developed general ESCAPE
wide guidelines for the statistical analyses (www.escapeproject.eu/manuals/).
11
Consistent with other ESCAPE projects, we applied a staged modeling approach to
choose the main analytic model. Model 1 was the unadjusted crude analyses. Model
2 was a simple model with adjustment only for age, age squared, height, and sex.
Model 3 (Main Model of reference) is in particular used for all assessments of
interactions and for the sensitivity analyses and the meta-analyses. The model was
adjusted for a common set of potential confounders, which were available in all
studies in a standardized form, based on evidence from previous studies and the
assessment and quality of available data within the ESCAPE cohorts. Confounders in
the models were selected a priori based on current knowledge on determinants of
lung function and the potential association with air pollution. The Main Model does
not include variables that might be on the pathway linking air pollution with the
specific health outcome (e.g. chronic bronchitis). Thus, Model 3 included in the
cross-sectional analyses all variables of Model 2 plus BMI, highest educational level,
and smoking status and, in the longitudinal analyses, all variables of Model 2 plus
BMI, BMI change, highest educational level, smoking status at 1st spirometry and
quitting smoking during follow-up. Study-specific models with additional covariates
(e.g. packyears smoked, occupational exposures to gas / dust / fumes) were also
tested on smaller numbers of subjects, to assess sensitivity of the associations to
these additional adjustments. As results from models with these additional
adjustments did not differ materially from model 3 adjustments (or the number of
subjects on whom information on these additional variables was available, were too
few to be informative), all results presented were derived from model 3.
Meta-analysis
Cohort specific overall and stratum-specific effect estimates obtained by mixed
linear regression models were meta-analyzed. The heterogeneity of the effect
estimates between the studies was assessed using X2 test. In the absence of
heterogeneity between studies (i.e., if the p-value of heterogeneity is larger than 0.1),
fixed-effect models were used to calculate the summary effect estimates. In presence
of heterogeneity, random-effect models were used instead. In addition, the I2 statistic
for quantifying heterogeneity was calculated. We assessed the contribution from each
cohort to the overall effect estimate.
12
13
Online Supplement
Supplemental Table S1. Description of cohort-specific study populations. Characteristicsa are presented for the larger subgroup of participants included in the
analysis of NO2 and NOx, traffic indicators and for the smaller subgroup of participants included in the PM metrics analysis.
ECRHS
Cohort
EGEA
NSHD
SALIA
SAPALDIA
Ntotal=3859
Ntotal=1831
Ntotal=568
Ntotal=342
Ntotal=844
Ntotal=751
Ntotal=580
Ntotal=580
Ntotal=1764
Ntotal=729
NO population
PM population
NO population
PM population
NO population
PM population
NO population
PM population
NO population
PM population
1st spirometry
1991-1993
1991-1995
1999
1985-1994
1991-1992
2nd spirometry
2001-2002
2003-2007
2006-2010
2007-2009
2002
Characteristics
N/mean
%/SD
N/mean
%/SD
N/mean
%/SD
N/mean
%/SD
N/mean
%/SD
N/mean
%/SD
N/mean
%/SD
N/mean
%/SD
N/mean
%/SD
N/mean
%/SD
1981
51.3%
967
52.8%
303
53.3%
182
53.2%
471
55.8%
418
55.7%
580
100.0%
580
100.0%
980
55.6%
422
57.9%
43.0
7.2
43.9
7.1
53.1
11.3
53.1
10.8
63.3
1.1
63.3
1.1
73.3
3.4
73.3
3.4
53.2
11.0
53.9
10.7
BMI [kg/m ]
25.7
4.6
25.1
4.6
25.3
4.3
25.0
4.1
27.7
4.9
27.7
5.0
27.4
4.5
27.4
4.5
25.4
4.3
25.1
4.3
Height [in cm]
168.6
9.5
169.5
9.3
168.5
8.4
168.8
8.4
167.4
8.6
167.5
8.6
162.3
5.5
162.3
5.5
168.8
9.0
166.7
8.7
Exsmoker
1064
27.6%
565
30.9%
206
36.3%
123
36.0%
497
58.9%
450
59.9%
99
17.1%
99
17.1%
568
32.2%
219
30.0%
1224
31.7%
451
24.6%
81
14.3%
46
13.5%
77
9.1%
71
9.5%
18
3.1%
18
3.1%
492
27.9%
219
30.0%
7.7
12.0
7.4
12.2
5.9
10.0
5.6
9.9
9.1
12.6
9.3
12.6
2.8
8.4
2.8
8.4
10.9
17.9
11.8
19.3
3.9
10.9
2.9
10.9
1.7
8.3
1.9
8.6
0.7
2.5
0.7
2.5
0.6
6.7
0.6
6.7
3.1
6.5
3.5
6.8
1321
34.2%
627
34.2%
118
20.8%
60
17.5%
439
52.0%
394
52.5%
276
47.6%
276
47.6%
1121
63.5%
510
70.0%
1420
36.8%
707
38.6%
263
46.3%
182
53.2%
102
12.1%
82
10.9%
199
34.3%
199
34.3%
520
29.5%
172
23.6%
Female
Age
3
Current smoker
st
Pack years at 1 spirometry
b
Pack years from 1st spirometry to 2nd spirometryb
Medium educational level
High educational level
b
b
Environmental tobacco exposure at home or at work
b
676
17.5%
301
16.4%
233
41.0%
137
40.1%
168
19.9%
144
19.2%
347
59.8%
347
59.8%
119
6.7%
40
5.5%
Occupational exposure to dust/fumes or gasesb
1685
43.7%
648
35.4%
125
22.0%
59
17.3%
246
29.1%
220
29.3%
39
6.7%
39
6.7%
460
26.1%
143
19.6%
Ever asthmab,c
616
16.0%
318
17.4%
183
32.2%
119
34.8%
83
9.8%
68
9.1%
50
8.6%
50
8.6%
155
8.8%
49
6.7%
The table shows the amount of observations (N, and % of total N) for categorical variables, and the mean value (and standard deviation (SD)) in case of
continuous variables. a Characteristics refer to time point of 2nd spirometry. b Information missing on a limited number of subjects. c Asthma diagnosed by a
physician at 1st and/or at 2nd spirometry.
14
Supplemental Table S2: Information on instruments used at 1st and 2nd spirometry in ESCAPE centers included in this analysis.
Study
Study center
Year of 1st spirometry
for this paper
ECRHS
Belgium/Antwerp
1991-1992
ECRHS
France/Grenoble
1991-1993
ECRHS
France/Paris
1991-1993
ECRHS
Germany/Erfurt
1991-1992
ECRHS
Italy/Pavia
1991-1993
ECRHS
Italy/Turin
1992-1993
ECRHS
Italy/Verona
1992-1993
ECRHS
Spain/Albacete
1991-1992
ECRHS
Spain/Barcelona
1991-1992
ECRHS
Spain/Galdakoa
1991-1992
ECRHS
Spain/Huelva
1991-1993
ECRHS
Spain/Oviedo
1991-1992
ECRHS
Sweden/Umea
1991-1992
ECRHS
UK/Norwich
1990-1991
ECRHS
UK/Ipswich
1991-1992
SAPALDIA
Basel
1991/92
SAPALDIA
Geneva
1991/92
SAPALDIA
Lugano
1991/92
NSHD
UK
1999
SALIA
Ruhr Area
1985-1994
EGEA
Grenoble
1992-1995
EGEA
Lyon
1992-1995
EGEA
Marseille
1992-1995
Instrument(s) used at 1st
spirometry:
Instrument / N
Sensormedics
N=440
Biomedin spir.
N=329
Biomedin spir.
N=322
Jaeger pneum
N=254
Biomedin spir.
N=147
Biomedin spir.
N=149
Biomedin spir.
N=184
Biomedin spir.
N=338
Biomedin spir.
N=161
Biomedin spir.
N=332
Biomedin spir.
N=266
Biomedin spir.
N=230
Sensormedics
N=392
Biomedin spir.
N=245
Biomedin spir.
N=283
Sensormedics 2200
N=643
Sensormedics 2200
N=394
Sensormedics 2200
N=728
Micro Medical Plus (MS03s )
N=844
Master Scope Jaeger /
(partly VICAest 4 transformed)
N=580
Biomedin/
N=210
Jaeger pneumotach (Lyon)/
N=154
Biomedin/
N=75
Year of 2nd
spirometry for this
paper
Instrument(s) used at 2nd spirometry:
Instrument / N
Participants switching
instruments during 2nd
spirometry (N/%)
2000-2002
Jaeger pneum N=440
100%
2001-2002
Biomedin spir. N=329
0%
2000-2002
Biomedin spir. N=322
0%
2000-2001
Jaeger pneum N=254
0%
2000-2001
Biomedin spir. N=147
0%
2000-2001
Biomedin spir. N=149
0%
2000-2002
Biomedin spir. N=184
0%
1999-2001
Biomedin spir. N=338
0%
2000-2001
Biomedin spir. N=161
0%
2000-2001
Biomedin spir. N=332
0%
1999-2002
Biomedin spir. N=266
0%
2000-2001
Biomedin spir. N=230
0%
1999-2000
Sensormedics
N=392
0%
1999-2001
Biomedin spir. N=245
0%
1999-2001
Biomedin spir. N=283
0%
2002
2002
2002
2006-2010
2007-2009
2003-2006
2003-2006
2003-2006
15
Sensormedics 2200
N=643
Sensormedics 2200
N=394
Sensormedics 2200
N=728
Micro Medical Plus (MS03s)
N=844
Master Scope Jaeger /
(partly Easy One transformed)
N=580
SPIRODYN’R N=201
SPIRODYN’R
N=154
SPIRODYN’R
N=75
0%
0%
0%
0%
(0%) (after
transformation)
100%
100%
100%
EGEA
Paris
1992-1995
Biomedin/
N=143
2003-2006
16
SPIRODYN’R N=150
100%
Supplemental Table S3
Level of lung function and annual change of lung function of the cohort specific study populations. Presented are the number of observations (N), the means
and the standard deviations (sd) of level and change in FEV1 and FVC (in liters per year) during follow up for all five study populations stratified by sex,
smoking status (never vs. ever) and asthma status (never vs. ever) for the larger subgroup of participants included in the analysis of NO2, NOx and traffic
indicators, and for the smaller subgroup of participants included in the analysis of the PM metrics, respectively.
ECRHS
All
NO population
N=
Female
3859
N=
1981
Male
N=
Never smoker
1878
N=
1664
Ever smoker
N=
2195
No asthma
N=
3423
Asthma
N=
430
mean
Sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
FEV1 at 2 spirometry up [L]
3.466
0.808
2.967
0.511
3.993
0.725
3.464
0.835
3.468
0.787
3.507
0.797
3.144
0.818
FVC at 2nd spirometry [L]
4.333
0.998
3.669
0.593
5.033
0.847
4.295
1.029
4.361
0.972
4.351
0.993
4.187
1.019
change of FEV1 [l]
-0.026
0.032
-0.022
0.027
-0.030
0.035
-0.025
0.031
-0.027
0.032
-0.026
0.029
-0.024
0.047
change of FVC [l]
-0.018
0.040
-0.014
0.036
-0.022
0.044
-0.017
0.038
-0.019
0.041
-0.018
0.038
-0.015
0.051
nd
All
PM population
N=
Female
1831
Male
Never smoker
Ever smoker
No asthma
N=
967
N=
864
N=
858
N=
973
N=
1588
Asthma
N=
237
mean
Sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
3.462
0.802
2.988
0.516
3.994
0.729
3.471
0.834
3.455
0.774
3.519
0.786
3.087
0.807
FVC at 2 spirometry [L]
4.348
0.999
3.702
0.607
5.072
0.843
4.330
1.032
4.364
0.969
4.379
0.994
4.145
1.007
change of FEV1 [l]
-0.025
0.033
-0.021
0.028
-0.030
0.037
-0.024
0.032
-0.026
0.033
-0.025
0.029
-0.025
0.050
change of FVC [l]
-0.018
0.039
-0.013
0.033
-0.023
0.045
-0.017
0.036
-0.018
0.042
-0.018
0.036
-0.018
0.054
FEV1 at 2nd spirometry [L]
nd
EGEA
All
NO population
nd
FEV1 at 2 spirometry [L]
Female
Male
Never smoker
Ever smoker
No asthma
Asthma
N=
568
N=
303
N=
265
N=
282
N=
286
N=
383
N=
158
mean
Sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
3.030
0.853
2.674
0.603
3.437
0.914
2.976
0.889
3.082
0.814
3.101
0.837
2.856
0.884
nd
FVC at 2 spirometry [L]
4.001
1.013
3.477
0.688
4.602
0.993
3.889
1.060
4.113
0.954
3.985
1.010
4.051
1.029
change of FEV1 [L]
-0.028
0.031
-0.023
0.025
-0.034
0.035
-0.025
0.028
-0.032
0.032
-0.029
0.027
-0.027
0.039
change of FVC [L]
-0.015
0.037
-0.010
0.031
-0.020
0.041
-0.012
0.035
-0.018
0.038
-0.014
0.033
-0.017
0.043
All
Female
Male
Never smoker
Ever smoker
No asthma
Asthma
PM population
N=
342
N=
182
N=
160
N=
175
N=
17
167
N=
227
N=
104
mean
Sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
FEV1 at 2 spirometry [L]
3.104
0.868
2.713
0.595
3.548
0.916
3.015
0.913
3.198
0.810
3.200
0.853
2.884
0.886
FVC at 2nd spirometry [L]
4.132
1.032
3.557
0.672
4.787
0.979
3.990
1.087
4.281
0.951
4.132
1.042
4.123
1.026
change of FEV1 [L]
-0.028
0.027
-0.023
0.022
-0.033
0.031
-0.025
0.024
-0.030
0.030
-0.028
0.027
-0.027
0.030
change of FVC [L]
-0.010
0.031
-0.008
0.027
-0.013
0.036
-0.009
0.030
-0.012
0.033
-0.010
0.030
-0.012
0.034
nd
NSHD
All
NO population
nd
FEV1 at 2 spirometry [L]
Female
Male
Never smoker
Ever smoker
No asthma
Asthma
N=
844
N=
471
N=
373
N=
270
N=
574
N=
774
N=
44
mean
Sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
2.831
0.655
2.427
0.394
3.343
0.553
2.824
0.582
2.835
0.686
2.855
0.649
2.531
0.636
nd
FVC at 2 spirometry [L]
3.573
0.813
3.052
0.457
4.231
0.677
3.527
0.725
3.595
0.852
3.593
0.817
3.310
0.694
change of FEV1 [L]
-0.022
0.025
-0.021
0.020
-0.024
0.030
-0.019
0.021
-0.024
0.026
-0.022
0.025
-0.020
0.019
change of FVC [L]
-0.025
0.034
-0.024
0.030
-0.026
0.040
-0.022
0.032
-0.026
0.035
-0.025
0.035
-0.030
0.028
All
PM population
nd
FEV1 at 2 spirometry [L]
Female
Male
Never smoker
Ever smoker
No asthma
Asthma
N=
751
N=
418
N=
333
N=
230
N=
521
N=
690
N=
37
mean
Sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
2.837
0.658
2.428
0.390
3.351
0.558
2.823
0.591
2.844
0.686
2.863
0.651
2.458
0.637
nd
FVC at 2 spirometry [L]
3.583
0.817
3.055
0.451
4.246
0.677
3.535
0.734
3.604
0.850
3.608
0.818
3.190
0.674
change of FEV1 [L]
-0.022
0.025
-0.021
0.020
-0.024
0.031
-0.018
0.021
-0.024
0.027
-0.023
0.025
-0.019
0.018
change of FVC [L]
-0.024
0.035
-0.023
0.030
-0.025
0.040
-0.020
0.031
-0.025
0.036
-0.024
0.035
-0.030
0.029
SALIA
All
NO population
FEV1 at 2nd spirometry [L]
Female
Male
Never smoker
Ever smoker
No asthma
Asthma
N=
580
N=
580
N=
0
N=
459
N=
121
N=
558
N=
9
mean
Sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
2.197
0.419
2.197
0.419
NA
NA
2.208
0.406
2.153
0.463
2.203
0.418
1.957
0.619
nd
FVC at 2 spirometry [L]
2.911
0.537
2.911
0.537
NA
NA
2.911
0.534
2.913
0.550
2.913
0.539
2.891
0.664
change of FEV1 [L]
-0.020
0.014
-0.020
0.014
NA
NA
-0.019
0.014
-0.023
0.015
-0.020
0.014
-0.013
0.019
change of FVC [L]
-0.022
0.019
-0.022
0.019
NA
NA
-0.022
0.019
-0.024
0.019
-0.022
0.018
-0.010
0.032
PM population
All
Female
Male
Never smoker
Ever smoker
18
No asthma
Asthma
FEV1 at 2nd spirometry [L]
N=
580
N=
580
N=
0
N=
459
N=
121
N=
558
N=
9
mean
Sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
2.197
0.419
2.197
0.419
NA
NA
2.208
0.406
2.153
0.463
2.203
0.418
1.957
0.619
nd
FVC at 2 spirometry [L]
2.911
0.537
2.911
0.537
NA
NA
2.911
0.534
2.913
0.550
2.913
0.539
2.891
0.664
change of FEV1 [L]
-0.020
0.014
-0.020
0.014
NA
NA
-0.019
0.014
-0.023
0.015
-0.020
0.014
-0.013
0.019
change of FVC [L]
-0.022
0.019
-0.022
0.019
NA
NA
-0.022
0.019
-0.024
0.019
-0.022
0.018
-0.010
0.032
SAPALDIA
All
NO population
nd
FEV1 at 2 spirometry [L]
N=
Female
1764
Male
Never smoker
Ever smoker
No asthma
N=
980
N=
784
N=
766
N=
998
N=
1658
Asthma
N=
106
mean
Sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
3.095
0.816
2.681
0.543
3.612
0.804
3.076
0.830
3.109
0.805
3.098
0.808
3.052
0.922
nd
FVC at 2 spirometry [L]
4.083
1.015
3.499
0.625
4.813
0.935
3.981
1.022
4.161
1.004
4.080
1.012
4.124
1.072
change of FEV1 [L]
-0.033
0.030
-0.030
0.027
-0.036
0.034
-0.029
0.027
-0.036
0.032
-0.033
0.030
-0.026
0.029
change of FVC [L]
-0.022
0.041
-0.019
0.035
-0.025
0.048
-0.018
0.036
-0.025
0.045
-0.022
0.042
-0.014
0.037
All
PM population
Female
Male
Never smoker
Ever smoker
No asthma
Asthma
N=
729
N=
422
N=
307
N=
323
N=
406
N=
693
N=
36
mean
Sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
mean
sd
FEV1 at 2 spirometry [L]
2.991
0.777
2.606
0.497
3.519
0.783
2.982
0.794
2.997
0.765
2.985
0.765
3.103
0.985
FVC at 2nd spirometry [L]
3.875
0.936
3.357
0.562
4.586
0.881
3.815
0.958
3.922
0.917
3.866
0.927
4.045
1.099
change of FEV1 [L]
-0.034
0.027
-0.032
0.024
-0.036
0.031
-0.031
0.026
-0.036
0.028
-0.034
0.027
-0.025
0.028
change of FVC [L]
-0.018
0.035
-0.018
0.030
-0.019
0.041
-0.016
0.032
-0.020
0.037
-0.019
0.035
-0.006
0.036
nd
NA, indicates not applicable.
19
Supplemental Table S4
The spatial variance of the applied ESCAPE LUR models by study center.
Center/Area
R2 in
R2 cross
RMSEa
Number
cohorts validation cross
of sites
(LOOCV
validation
R2)
(µg/m3)
NOx
Umea, Region
Sweden
London/Oxford, UK
Moran’s I
(p-value)
Measured
concentration
(µg/m3)
-0.13
(0.12)
-0.009
(0.78)
-0.16
(0.06)
-0.03
(0.95)
-0.02
(0.95)
-0.06
(0.77)
-0.07
(0.76)
-0.08
(0.88)
-0.04
(0.65)
-0.04
(0.71)
0.003
(0.23)
-0.05
(0.28)
-0.05
(0.36)
-0.08
(0.46)
-0.02
(0.91)
0.02
(0.26)
0.02
(0.46
18.9 [2.3-95.9]
87%
82%
7.9
40
91%
88%
16.2
40
Netherlands/Belgium 87%
region
Ruhr area, Germany 88%
82%
11.2
80
81%
13.6
40
Erfurt, Germany
87%
84%
4.3
39
Paris, France
75%
67%
31.6
40
Grenoble, France
82%
74%
11.2
40
Lyon, France
75%
65%
22.5
40
Marseilles, France
53%
39%
31.6
40
Basel, Switzerland
61%
52%
12.0
40
Geneva, Switzerland
81%
73%
9.1
40
Lugano, Switzerland
87%
82%
7.4
42
Turin, Italy
78%
72%
17.0
40
Pavia, Italy
88%
80%
9.6
20
Verona, Italy
64%
54%
32.3
40
Barcelona, Spain
73%
65%
27.7
40
Mid-East Spain:
AlbaceteValencia, Spain
Huelva, Spain
88%
84%
11.0
38
56%
31%
11.5
24
-0.15
(0.08)
33.8 [13.3-71.3]
-0.08
(0.43)
-0.009
(0.71)
-0.143
(0.09)
-0.18
(0.08)
9.3 [1.5-35.8]
69.3 [18.8257.4]
51.8 [17.5130.8]
60.0 [26.9135.7]
28.8 [15.6-61.8]
80.3 [12.7248.3]
48.2 [6.5-116.2]
61.7 [6.5-199.2]
70.1 [11.9266.1]
53.1 [21.6-95.7]
55.9 [22.1108.6]
47.8 [21.2116.4]
101.2 [22.8101.2]
50.9 [29.5117.9]
91.8 [33.1284.4]
101.3 [21.0236.4]
42.7 [0.6-148.6]
NO2
Umea, Region
Sweden
London/Oxford, UK
87%
83%
2.8
40
89%
87%
6.6
40
Netherlands/Belgium 86%
region
Ruhr area, Germany 89%
81%
5.1
80
84%
4.3
40
20
37.9 [7.3-102.7]
30.9 [12.8-61.5]
33.2 [20.2-58.4]
Erfurt, Germany
89%
87%
2.1
39
0.01
(0.16)
-0.05
(0.71)
-0.08
(0.82)
-0.06
(0.08)
-0.06
(0.87)
-0.05
(0.45)
0.002
(0.25)
-0.04
(0.51)
-0.08
(0.10)
-0.05
(0.99)
-0.05
(0.33)
-0.03
(0.98)
0.03
(0.37)
18.6 [11.0-33.4]
Paris, France
77%
67%
11.6
40
Grenoble, France
83%
78%
4.8
40
Lyon, France
90%
72%
8.7
40
Marseilles, France
59%
46%
10.7
40
Basel, Switzerland
67%
58%
4.8
40
Geneva, Switzerland
87%
81%
3.7
40
Lugano, Switzerland
87%
82%
3.5
42
Turin, Italy
78%
70%
7.7
40
Pavia, Italy
92%
87%
3.3
20
Verona, Italy
64%
55%
10.8
40
Barcelona, Spain
75%
68%
11.6
40
Mid-East Spain:
AlbaceteValencia, Spain
Huelva, Spain
90%
87%
5.2
38
55%
31%
7.0
24
-0.14
(0.10)
21.9 [8.4-43.4]
-0.13
(0.42)
0.16
(0.28)
-0.05
(0.99)
-0.13
(0.91)
-0.13
(0.10)
-0.07
(0.70)
-0.07
(0.88)
18.6[12.1-31.2]
-0.19
(0.20)
0.02
(0.77)
-0.02
(0.64)
-0.11
(0.83)
11.2 [7.0-21.1]
39.8 [6.9-96.8]
27.2 [5.5-53.2]
35.0 [7.3-88.0]
36.1 [10.0-92.8]
31.0 [16.0-47.8]
29.3 [16.1-51.3]
28.6 [12.2-59.1]
53.3 [15.6-83.7]
25.9 [15.7-53.4]
41.6 [16.3100.1]
57.7 [13.8109.0]
26.1 [1.9-75.5]
PM10
London/Oxford, UK
90%
88%
1.5
20
Netherlands/Belgium 68%
region
Ruhr area, Germany 69%
60%
2.3
40
63%
2.0
20
Paris, France
87%
77%
3.5
20
Lugano, Switzerland
87%
80%
1.6
18
Turin, Italy
78%
69%
3.9
20
Barcelona, Spain
87%
82%
3.1
20
82%
77%
PM2.5
1.4
20
Netherlands/Belgium 67%
region
Ruhr area, Germany 88%
61%
1.2
40
79%
0.9
20
Paris, France
73%
1.8
20
London/Oxford, UK
89%
21
27.1 [21.9-37.0]
27.9 [22.5-33.6]
25.6 [16.6-52.4]
23.9 [18.5-32.4]
43.1 [31.5-57.8]
37.4 [17.8-48.5]
17.1 [12.7-21.5]
18.5 [15.5-21.6]
16.0 [11.9-30.6]
Lugano, Switzerland
83%
77%
1.1
19
Turin, Italy
71%
59%
2.0
20
Barcelona, Spain
83%
71%
2.1
20
London/Oxford, UK
PM2.5absorbance
0.2
96%
92%
Netherlands/Belgium 92%
region
Ruhr area, Germany 97%
89%
0.2
40
95%
0.1
20
Paris, France
91%
81%
0.4
20
Lugano, Switzerland
79%
71%
0.3
19
Turin, Italy
88%
81%
0.3
20
Barcelona, Spain
86%
80%
0.4
20
68%
57%
PMcoarse
1.3
20
Netherlands/Belgium 51%
region
Ruhr area, Germany 66%
38%
1.7
40
57%
1.2
20
Paris, France
81%
73%
4.6
20
Lugano, Switzerland
77%
65%
1.1
18
Turin, Italy
65%
58%
2.4
20
Barcelona, Spain
75%
70%
2.3
20
London/Oxford, UK
a
RMSE indicates Root-mean squared error
22
20
-0.12
(0.10)
-0.09
(0.45)
0.01
(0.46)
17.2 [13.7-22.5]
-0.21
(0.16)
-0.16
(0.42)
-0.02
(0.65)
-0.16
(0.97)
-0.13
(0.09)
-0.06
(0.82)
-0.01
(0.64)
1.6 [0.9-4.7]
-0.17
(0.29)
-0.08
(0.75)
-0.02
(0.73)
-0.08
(0.82)
-0.12
(0.18)
-0.10
(0.30)
-0.09
(0.61)
7.4 [4.4-10.3]
29.3 [22.7-36.3]
16.3 [8.4-24.4]
1.7 [0.9-3.0]
1.6 [1.0-2.6]
2.0 [0.8-5.1]
2.0 [1.2-3.0]
3.0 [1.6-4.2]
2.7 [0.9-4.9]
9.3 [6.4-15.0]
9.4 [7.1-12.8]
9.6 [3.9-21.8]
6.8 [3.8-9.9]
13.8 [7.5-21.5]
21.0 [9.4-26.0]
Supplemental Table S5
Distribution of all cohort-specific exposure estimates (annual averages of ambient air pollutants and traffic variables), at participants address in each cohort.
ECRHS
Exposures
N
Mean
SD
Min
P25
P50
P75
Max
IQR
3
PM2.5 [µg/m ]
1830
15.9
5.6
8.2
10.7
16.1
17.7
34.4
7.0
-5 -1
PM2.5absorbance [10 m ]
1540
2.0
0.9
0.8
1.2
1.8
2.7
5.2
1.6
3
PM10 [µg/m ]
1830
25.8
9.1
11.9
18.6
24.6
28.3
55.2
9.7
3
PM (coarse) [µg/m ]
1830
10.3
4.4
3.9
6.8
9.2
11.5
25.4
4.7
3
NO2 [µg/m ]
3859
28.9
15.4
0.0
18.8
26.5
37.5
115.5
18.7
3
NOx [µg/m ]
3859
50.5
30.4
0.0
31.5
43.0
65.9
223.1
34.5
Traffic intensity on nearest road [cars/day]
2492
4807
10878
0
500
500
6009 143156
5509
a
Traffic load on nearest major road [cars-km/day; in thousand]
2687
1.45
3.22
0
0
0
1.67
56.5
1.67
st
NO2 (backextrapolated to BL) [µg/m3]
No complete exposure backextrapolation to 1 spirometry available
3
PM10 (backextrapolated to BL) [µg/m ]
No complete exposure backextrapolation to 1st spirometry available
3
NO2 (backextrapolated to FU) [µg/m ]
3859
34.2
18.1
0.0
21.8
31.4
44.8
120.7
23.0
3
PM10 (backextrapolated to FU) [µg/m ]
1388
27.1
5.7
16.3
22.3
27.2
30.7
47.1
8.4
EGEA
Exposures
N
Mean
SD
Min
P25
P50
P75
Max
IQR
3
PM2.5 [µg/m ]
342
15.3
1.9
10.0
14.2
15.1
16.2
22.3
2.0
-5 -1
PM2.5absorbance [10 m ]
148
2.1
0.9
0.9
1.4
1.9
2.7
4.7
1.3
3
PM10 [µg/m ]
342
25.1
3.5
18.6
22.7
24.6
26.6
36.2
4.0
3
PM (coarse) [µg/m ]
342
9.4
2.4
3.9
7.5
9.5
10.8
17.1
3.3
3
NO2 [µg/m ]
568
27.4
11.8
9.3
18.5
25.2
33.1
98.5
14.7
3
NOx [µg/m ]
568
46.7
26.8
5.6
29.2
41.4
57.1
245.3
27.9
Traffic intensity on nearest road [cars/day]
568
6633
11560
0
1187 3706 7853 116863
6667
a
Traffic load on nearest major road [cars-km/day; in thousand]
568
1.37
3.56
0
0
0
1.58
41.6
1.58
3
st
NO2 (backextrapolated to BL) [µg/m ]
No complete exposure backextrapolation to 1 spirometry available
3
PM10 (backextrapolated to BL) [µg/m ]
No complete exposure backextrapolation to 1st spirometry available
NO2 (backextrapolated to FU) [µg/m3]
568
32.1
13.2
11.4
22.0
29.9
39.5
101.5
17.5
23
PM10 (backextrapolated to FU) [µg/m3]
Exposures
PM2.5 [µg/m3]
PM2.5absorbance [10-5m-1]
PM10 [µg/m3]
PM (coarse) [µg/m3]
NO2 [µg/m3]
NOx [µg/m3]
Traffic intensity on nearest road [cars/day]
Traffic load on nearest major road [cars-km/day; in thousand] a
NO2 (backextrapolated to BL) [µg/m3]
PM10 (backextrapolated to BL) [µg/m3]
NO2 (backextrapolated to FU) [µg/m3]
PM10 (backextrapolated to FU) [µg/m3]
Exposures
PM2.5 [µg/m3]
PM2.5absorbance [10-5m-1]
PM10 [µg/m3]
PM (coarse) [µg/m3]
NO2 [µg/m3]
NOx [µg/m3]
Traffic intensity on nearest road [cars/day]
Traffic load on nearest major road [cars-km/day; in thousand] a
NO2 (backextrapolated to BL) [µg/m3]
PM10 (backextrapolated to BL) [µg/m3]
NO2 (backextrapolated to FU) [µg/m3]
PM10 (backextrapolated to FU) [µg/m3]
148
27.0
4.3
19.7
23.7
26.7
29.0
37.3
5.3
NSHD
N
Mean
SD
Min
P25
P50
P75
Max
IQR
751
9.5
1.0
8.2
8.7
9.5
10.2
13.5
1.5
751
1.0
0.2
0.8
0.9
1.0
1.1
3.2
0.3
751
15.7
2.1
11.8
14.7
15.7
16.5
26.2
1.9
751
6.4
0.9
5.6
5.8
6.0
6.6
9.7
0.8
844
22.4
7.1
12.9
16.6
21.8
26.7
62.0
10.0
844
37.5
14.2
19.7
27.2
36.1
44.3
145.4
17.1
844
1239
4091
500
500
500
500
76224
0
844
0.27
0.91
0
0
0
0
10.0
0
841
26.3
8.3
14.6
20.1
25.6
31.4
70.2
11.2
748
22.0
2.8
16.4
20.7
22.0
23.3
36.4
2.6
ESCAPE exposure measurements were conducted at time of second spirometry
ESCAPE exposure measurements were conducted at time of second spirometry
SALIA
N
Mean
SD
Min
P25
P50
P75
Max
IQR
580
17.8
1.3
15.9
16.9
17.3
18.6
21.9
1.7
580
1.4
0.4
1.0
1.2
1.3
1.6
3.4
0.4
580
26.7
2.1
23.9
25.4
26.2
27.5
33.5
2.1
580
9.4
1.6
2.8
8.5
8.8
10.1
14.8
1.6
580
27.6
7.5
19.7
22.7
24.2
30.7
70.3
8.1
580
44.2
19.0
23.9
31.9
35.4
52.6
124.3
20.7
580
1642
3637
500
500
500
500
27798
0
580
0.72
2.01
0
0
0
0.32
15.8
0.32
580
36.0
11.5
20.3
27.6
33.3
41.6
84.1
14.0
580
47.7
8.0
32.2
39.2
49.8
52.8
65.1
13.6
ESCAPE exposure measurements were conducted at time of second spirometry
ESCAPE exposure measurements were conducted at time of second spirometry
24
Exposures
PM2.5 [µg/m3]
PM2.5absorbance [10-5m-1]
PM10 [µg/m3]
PM (coarse) [µg/m3]
NO2 [µg/m3]
NOx [µg/m3]
Traffic intensity on nearest road [cars/day]
Traffic load on nearest major road [cars-km/day; in thousand] a
NO2 (backextrapolated to BL) [µg/m3]
PM10 (backextrapolated to BL) [µg/m3]
NO2 (backextrapolated to FU) [µg/m3]
PM10 (backextrapolated to FU) [µg/m3]
SAPALDIA
N
Mean
729
16.8
729
1.9
729
23.2
729
6.5
1764
27.0
1764
44.8
1697
3207
1671
0.94
1762
47.7
726
46.2
1764
31.0
729
37.8
SD
1.6
0.4
2.6
1.2
6.8
14.4
5242
1.83
10.5
4.5
8.0
4.3
Min
12.4
0.9
17.6
4.3
6.9
4.0
0
0
11.5
33.8
8.2
26.9
P25
16.2
1.7
22.3
5.5
23.3
37.6
81
0
41.3
44.4
26.9
35.7
P50
16.8
2.0
23.3
6.5
27.7
45.6
779
0
48.3
45.5
31.2
38.3
P75
17.4
2.2
24.6
7.4
31.0
52.8
3957
1.42
53.6
48.4
34.8
40.0
Max
23.5
3.2
31.7
10.4
56.3
112.2
46400
18.7
96.4
61.9
64.0
53.2
IQR
1.1
0.5
2.3
1.9
7.7
15.2
3876
1.42
12.3
4.0
8.0
4.3
BL, indicates Baseline; FU, Follow-up. PM2.5: particulate matter with a diameter of 2.5 micrometers or less; PM2.5abs: absorbance of particulate matter with a
diameter of 2.5 micrometers; PM10: particulate matter with a diameter of 10 micrometers or less; PMcoarse: coarse fraction of PM2.5 to PM10; NO2: nitrogen
dioxide; NOx: nitrogen oxides. a Traffic load on nearest major road in a 100m buffer presented in thousand.
25
Supplemental Table S6. Cohort-specific spearman correlation matrix for all individually assigned markers of home outdoor exposures, by cohort.
ECRHS
PM2.5
PM2.5
absorbance
PM10
PM
coarse
NO2
NOx
Traffic
intensity
Traffic
load
NO2
(back to
BL)
PM10
(back to
BL)
NO2
(back to
FU)
PM10
(back to
FU)
N
rho
rho
rho
Rho
rho
rho
rho
rho
rho
rho
rho
rho
1830
1.00
0.80
0.86
0.70
0.80
0.63
0.56
0.52
NA
NA
0.79
0.81
1540
0.80
1.00
0.78
0.85
0.87
0.77
0.57
0.64
NA
NA
0.91
0.62
1830
0.86
0.78
1.00
0.87
0.79
0.69
0.46
0.45
NA
NA
0.77
0.96
1830
0.70
0.85
0.87
1.00
0.76
0.71
0.40
0.49
NA
NA
0.77
0.81
3859
0.80
0.87
0.79
0.76
1.00
0.91
0.53
0.53
NA
NA
0.95
0.77
3859
0.63
0.77
0.69
0.71
0.91
1.00
0.41
0.57
NA
NA
0.86
0.56
2492
0.56
0.57
0.46
0.40
0.53
0.41
1.00
0.50
NA
NA
0.51
0.50
2687
0.52
0.64
0.45
0.49
0.53
0.57
0.50
1.00
NA
NA
0.59
0.35
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
3859
0.79
0.91
0.77
0.77
0.95
0.86
0.51
0.59
NA
NA
1.00
0.69
1388
0.81
0.62
0.96
0.81
0.77
0.56
0.50
0.35
NA
NA
0.69
1.00
Exposures
3
PM2.5 [µg/m ]
PM2.5absorbance [10-5m-1]
PM10 [µg/m3]
PM (coarse) [µg/m3]
NO2 [µg/m3]
NOx [µg/m3]
Traffic intensity on nearest road [cars/day]
Traffic load on nearest major road in a 100m buffer
[cars-km/day]
NO2 (backextrapolated to BL) [µg/m3]
PM10 (backextrapolated to BL) [µg/m3]
NO2 (backextrapolated to FU) [µg/m3]
PM10 (backextrapolated to FU) [µg/m3]
EGEA
PM2.5
PM2.5
absorbance
PM10
PM
coarse
NO2
NOx
Traffic
intensity
Traffic
load
NO2
(back to
BL)
PM10
(back to
BL)
NO2
(back to
FU)
PM10
(back to
FU)
N
rho
rho
rho
Rho
rho
rho
rho
rho
rho
rho
rho
rho
342
1.00
0.57
0.70
0.47
0.64
0.64
0.37
0.49
NA
NA
0.62
0.75
148
0.57
1.00
0.18
0.75
0.81
0.68
0.36
0.82
NA
NA
0.81
0.18
342
0.70
0.18
1.00
0.54
0.62
0.63
0.38
0.36
NA
NA
0.61
1.00
342
0.47
0.75
0.54
1.00
0.71
0.56
0.05
0.47
NA
NA
0.76
0.50
568
0.64
0.81
0.62
0.71
1.00
0.94
0.36
0.54
NA
NA
0.99
0.43
568
0.64
0.68
0.63
0.56
0.94
1.00
0.42
0.52
NA
NA
0.92
0.48
Exposures
3
PM2.5 [µg/m ]
PM2.5absorbance [10-5m-1]
PM10 [µg/m3]
PM (coarse) [µg/m3]
NO2 [µg/m3]
NOx [µg/m3]
26
Traffic intensity on nearest road [cars/day]
Traffic load on nearest major road in a 100m buffer
[cars-km/day]
NO2 (backextrapolated to BL) [µg/m3]
PM10 (backextrapolated to BL) [µg/m3]
NO2 (backextrapolated to FU) [µg/m3]
PM10 (backextrapolated to FU) [µg/m3]
568
0.37
0.36
0.38
0.05
0.36
0.42
1.00
0.47
NA
NA
0.33
0.35
568
0.49
0.82
0.36
0.47
0.54
0.52
0.47
1.00
NA
NA
0.55
0.10
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
568
0.62
0.81
0.61
0.76
0.99
0.92
0.33
0.55
NA
NA
1.00
0.43
148
0.75
0.18
1.00
0.50
0.43
0.48
0.35
0.10
NA
NA
0.43
1.00
NSHD
PM2.5
PM2.5
absorbance
PM10
PM
coarse
NO2
NOx
Traffic
intensity
Traffic
load
NO2
(back to
BL)
PM10
(back to
BL)
NO2
(back to
FU)
PM10
(back to
FU)
N
rho
rho
rho
Rho
rho
rho
rho
rho
rho
rho
rho
rho
751
1.00
0.64
0.64
0.20
0.89
0.89
0.10
0.25
0.67
0.48
0.89
0.64
751
0.64
1.00
0.57
0.31
0.83
0.74
0.17
0.31
0.67
0.42
0.83
0.57
751
0.64
0.57
1.00
0.66
0.60
0.60
0.18
0.27
0.45
0.74
0.60
1.00
751
0.20
0.31
0.66
1.00
0.17
0.19
0.21
0.32
0.14
0.52
0.17
0.66
844
0.89
0.83
0.60
0.17
1.00
0.92
0.07
0.22
0.80
0.45
1.00
0.60
844
0.89
0.74
0.60
0.19
0.92
1.00
0.13
0.28
0.73
0.44
0.92
0.60
844
0.10
0.17
0.18
0.21
0.07
0.13
1.00
0.54
0.04
0.09
0.07
0.18
844
0.25
0.31
0.27
0.32
0.22
0.28
0.54
1.00
0.15
0.19
0.22
0.27
841
0.67
0.67
0.45
0.14
0.80
0.73
0.04
0.15
1.00
0.56
0.80
0.45
748
0.48
0.42
0.74
0.52
0.45
0.44
0.09
0.19
0.56
1.00
0.45
0.74
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Exposures
3
PM2.5 [µg/m ]
PM2.5absorbance [10-5m-1]
PM10 [µg/m3]
PM (coarse) [µg/m3]
NO2 [µg/m3]
NOx [µg/m3]
Traffic intensity on nearest road [cars/day]
Traffic load on nearest major road in a 100m buffer
[cars-km/day]
NO2 (backextrapolated to BL) [µg/m3]
PM10 (backextrapolated to BL) [µg/m3]
NO2 (backextrapolated to FU) [µg/m3]
PM10 (backextrapolated to FU) [µg/m3]
SALIA
PM2.5
PM2.5
absorbance
PM10
PM
coarse
NO2
NOx
Traffic
intensity
Traffic
load
NO2
(back to
BL)
PM10
(back to
BL)
NO2
(back to
FU)
PM10
(back to
FU)
N
rho
rho
rho
Rho
rho
rho
rho
rho
rho
rho
rho
rho
580
1.00
0.90
0.91
0.79
0.80
0.80
0.13
0.25
0.71
0.69
0
0
Exposures
3
PM2.5 [µg/m ]
27
PM2.5absorbance [10-5m-1]
PM10 [µg/m3]
PM (coarse) [µg/m3]
NO2 [µg/m3]
NOx [µg/m3]
Traffic intensity on nearest road [cars/day]
Traffic load on nearest major road in a 100m buffer
[cars-km/day]
NO2 (backextrapolated to BL) [µg/m3]
PM10 (backextrapolated to BL) [µg/m3]
NO2 (backextrapolated to FU) [µg/m3]
PM10 (backextrapolated to FU) [µg/m3]
580
0.90
1.00
0.93
0.83
0.88
0.83
0.23
0.48
0.81
0.76
0
0
580
0.91
0.93
1.00
0.82
0.78
0.77
0.12
0.29
0.73
0.77
0
0
580
0.79
0.83
0.82
1.00
0.74
0.73
0.12
0.27
0.70
0.68
0
0
580
0.80
0.88
0.78
0.74
1.00
0.98
0.22
0.44
0.86
0.66
0
0
580
0.80
0.83
0.77
0.73
0.98
1.00
0.23
0.32
0.85
0.64
0
0
580
0.13
0.23
0.12
0.12
0.22
0.23
1.00
0.40
0.16
0.11
0
0
580
0.25
0.48
0.29
0.27
0.44
0.32
0.40
1.00
0.35
0.26
0
0
580
0.71
0.81
0.73
0.70
0.86
0.85
0.16
0.35
1.00
0.83
0
0
580
0.69
0.76
0.77
0.68
0.66
0.64
0.11
0.26
0.83
1.00
0
0
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
SAPALDIA
PM2.5
PM2.5
absorbance
PM10
PM
coarse
NO2
NOx
Traffic
intensity
Traffic
load
NO2
(back to
BL)
PM10
(back to
BL)
NO2
(back to
FU)
PM10
(back to
FU)
N
rho
rho
rho
rho
rho
rho
rho
rho
rho
rho
rho
rho
729
1.00
0.71
0.70
0.62
0.72
0.68
0.15
0.29
0.35
0.34
0.71
0.66
729
0.71
1.00
0.67
0.79
0.74
0.74
0.09
0.15
0.43
0.35
0.75
0.64
729
0.70
0.67
1.00
0.80
0.82
0.74
0.29
0.28
0.39
0.47
0.82
0.91
729
0.62
0.79
0.80
1.00
0.84
0.77
0.25
0.12
0.46
0.40
0.85
0.75
1764
0.72
0.74
0.82
0.84
1.00
0.90
0.20
0.24
0.56
0.43
0.94
0.77
1764
0.68
0.74
0.74
0.77
0.90
1.00
0.23
0.23
0.54
0.39
0.85
0.69
1697
0.15
0.09
0.29
0.25
0.20
0.23
1.00
0.05
0.07
0.10
0.22
0.25
1671
0.29
0.15
0.28
0.12
0.24
0.23
0.05
1.00
0.13
0.16
0.26
0.25
1762
0.35
0.43
0.39
0.46
0.56
0.54
0.07
0.13
1.00
0.80
0.46
0.35
726
0.34
0.35
0.47
0.40
0.43
0.39
0.10
0.16
0.80
1.00
0.44
0.44
1764
0.71
0.75
0.82
0.85
0.94
0.85
0.22
0.26
0.46
0.44
1.00
0.78
729
0.66
0.64
0.91
0.75
0.77
0.69
0.25
0.25
0.35
0.44
0.78
1.00
Exposures
3
PM2.5 [µg/m ]
PM2.5absorbance [10-5m-1]
PM10 [µg/m3]
PM (coarse) [µg/m3]
NO2 [µg/m3]
NOx [µg/m3]
Traffic intensity on nearest road [cars/day]
Traffic load on nearest major road in a 100m buffer
[cars-km/day]
NO2 (backextrapolated to BL) [µg/m3]
PM10 (backextrapolated to BL) [µg/m3]
NO2 (backextrapolated to FU) [µg/m3]
PM10 (backextrapolated to FU) [µg/m3]
28
NA, indicates not applicable; BL, Baseline; FU, Follow-up..
29
Supplemental Table S7. Results from meta-analyses for the cross-sectional association between the level of
lung function and NO2 exposure (standard contrast of 10 µg/m³) backextrapolated to the time point of the 2nd
spirometry.
Level of lung functiona
FEV1 (in mL)
Study population
nd
NO2 (backextrapolated to 2 spirometry)
nd
PM10 (backextrapolated to 2 spirometry)
FVC (in mL)
2
Betab
95%CI
-12.84
-22.83 to -2.85
-42.84
-89.36 to 3.68
I
p-valuehet
0.0%
p=0.745
0.0%
p=0.623
a
Betab
95%CI
-13.45
-25.00 to -1.90
-71.91
-127.04 to -16.78
I2
p-valuehet
0.0%
p=0.990
0.0%
p=0.697
Level of lung function derived from 2nd spirometry. b The betas for the association between level of lung
function and exposure, are derived from the main model, adjusting for age, age squared, height, sex, BMI,
highest educational level, and smoking status at 2nd spirometry; a negative sign indicates lower lung function
with increasing exposure. d I2 and Cochran’s test for heterogeneity of effect estimates between cohorts.
30
Supplemental Table S8. Results from meta-analyses for the cross-sectional association between the level of
lung function and NO2 exposure (standard contrast of 10 µg/m³), stratified by gender, obesity, asthma status,
and smoking status.
Level of lung functiona
FEV1 (in mL)
Study population
Betab
95%CI
Females
-15.78
-28.34 to -3.23
Males
-8.16
-28.32 to 12.00
Not obese persons
-8.18
-21.01 to 4.66
Obese persons
-32.74
-58.84 to -6.65
Not Asthmatics
-11.25
-23.51 to 1.00
Asthmatics
-13.90
-37.36 to 9.56
Non smokers
-12.03
-28.13 to 4.06
Smokers
-15.01
FVC (in mL)
2d
-30.82 to 0.79
I
p-valuehet
0.0%
p=0.859
0.0%
p=0.399
12.7%
p=0.333
0.0%
p=0.907
0.0%
p=0.805
0.0%
p=0.469
0.0%
p=0.658
0.0%
p=0.920
p-valueintc
Betab
95%CI
-21.81
-36.78 to -6.85
-3.01
-26.14 to 20.13
-7.27
-22.27 to 7.73
-44.93
-74.59 to -15.27
-10.92
-25.95 to 4.11
-19.12
-47.98 to 9.73
-17.31
-36.68 to 2.06
-13.12
-31.53 to 5.29
p=0.529
p=0.098
p=0.844
p=0.796
a
I2 d
p-valuehet
0.0%
p=0.682
4.9%
p=0.368
0.0%
p=0.800
0.0%
p=0.753
0.0%
p=0.963
0.0%
p=0.866
0.0%
p=0.990
0.0%
p=0.847
p-valueintc
p=0.181
p=0.026
p=0.621
p=0.759
Level of lung function derived from 2nd spirometry. b The betas for the association between level of lung
function and exposure, are derived from the main model, adjusting for age, age squared, height, sex, BMI,
highest educational level, and smoking status at 2nd spirometry; a negative sign indicates lower lung function
with increasing exposure. c p-values of effect modification across subgroups. d I2 and Cochran’s test for
heterogeneity of effect estimates between cohorts.
31
Supplemental Table S9. Results from meta-analyses for the cross-sectional association between the level of
lung function and NO2 exposure (standard contrast of 10 µg/m³), stratified by gender and obesity.
Level of lung functiona
FEV1 (in mL)
Study population
Betab
95%CI
Not obese females
-10.44
-24.06 to 3.18
Obese females
-32.37
-60.39 to -4.36
Not obese males
-2.45
-24.18 to 19.29
Obese males
-30.30
-76.57 to 15.97
FVC (in mL)
I2 d
p-valuehet
0.0%
p=0.850
0.0%
p=0.891
32.2%
p=0.219
0.0%
p=0.997
p-valueintc
Betab
95%CI
-17.19
-33.49 to -0.90
-45.75
-77.73 to -13.77
6.05
-19.06 to 31.16
-41.42
-91.18 to 8.35
p=0.168
p=0.286
a
I2 d
p-valuehet
0.0%
p=0.794
0.0%
p=0.825
37.7%
p=0.186
0.0%
p=0.828
p-valueintc
p=0.119
p=0.095
Level of lung function derived from 2nd spirometry. b The betas for the association between level of lung
function and exposure, are derived from the main model, adjusting for age, age squared, height, sex, BMI,
highest educational level, and smoking status at 2nd spirometry; a negative sign indicates lower lung function
with increasing exposure. d I2 and Cochran’s test for heterogeneity of effect estimates between cohorts.
32
Supplemental Table S10. Results from meta-analyses for the cross-sectional association between the level
of lung function and NO2 exposure (standard contrast of 10 µg/m³), by the restricted groups included in the
sensitivity analysis.
Level of lung functiona
FEV1 (in mL)
FVC (in mL)
2d
Study population
N
Betab
95%CI
Persons not moving between 1st and 2nd
spirometry
4482
-9.14
-24.34 to 6.06
Participants aged 30+ (age at 1st spirometry)
3841
-10.81
-29.00 to 7.39
a
I
p-valuehet
0.0%,
p=0.684
0.0%,
p=0.505
Betab
95%CI
-10.71
-28.64 to 7.22
-5.89
-26.95 to 15.17
I2 d
p-valuehet
37.2%,
p=0.173
0.0%,
p=0.475
Level of lung function derived from 2nd spirometry. b The betas for the association between level of lung
function and exposure, are derived from the main model, adjusting for age, age squared, height, sex, BMI,
highest educational level, and smoking status at 2nd spirometry; a negative sign indicates lower lung function
with increasing exposure. d I2 and Cochran’s test for heterogeneity of effect estimates between cohorts.
33
Supplemental Figures S1a-e: Flowcharts describing the study specific ESCAPE sampling process
a)ECRHS, b) EGEA, c) NSHD, d)SALIA and e)SAPALDIA
Figure S1a ECRHS
Original study population BL - (POPULATION A)
Total original study population with at least baseline data (participants >=20)
N=17349
Number of death or lost at follow-up:
N=6987
Original study population BL & FU - (POPULATION B)
Total study population participating at baseline and follow-up
N=10362 (59.7% of A)
After area restriction: N=4778
Total ESCAPE study population BL & FU - (POPULATION C)
(Participants data from baseline and at follow-up living at ESCAPE sites at both surveys)
N=5584 (32.2% of A)
No complete lung function records: N=1410
ESCAPE study population with spirometry BL & FU - (POPULATION D)
ESCAPE Participants BL & FU with valid spirometry (FEV1 and FVC)
N=4174 (24.1% of A)
No complete case information: N=59
ESCAPE study population with spirometry and covariates BL & FU - (POPULATION E)
Population D with age, gender, height, smoking status, education and BMI at both surveys
N=4115 (23.7% of A)
Final study population (POPULATION F1)
Final study population (POPULATION F2)
Population E with valid NO2 measurements and
Population E with valid PM10 measurements and
complete case information
complete case information
N=3859 (22.2%)
N=1831 (10.6%)
34
Figure S1b. EGEA
Original study population BL - (POPULATION A)
Total original study population with at least baseline data (participants >=20)
N=1321
Number of death or lost at follow-up:
N=131
Original study population BL & FU - (POPULATION B)
Total study population participating at baseline and follow-up
N=1190 (90.1% of A)
After area restriction: N=470
Total ESCAPE study population BL & FU - (POPULATION C)
(Participants data from baseline and at follow-up living at ESCAPE sites at both surveys)
N=720 (54.5% of A)
No complete lung function records: N=138
ESCAPE study population with spirometry BL & FU - (POPULATION D)
ESCAPE Participants BL & FU with valid spirometry (FEV1 and FVC)
N=582 (44.1% of A)
No complete case information: N=5
ESCAPE study population with spirometry and covariates BL & FU - (POPULATION E)
Population D with age, gender, height, smoking status, education and BMI at both surveys
N=577 (43.7% of A)
Final study population (POPULATION F1)
Final study population (POPULATION F2)
Population E with valid NO2 measurements and
Population E with valid PM10 measurements and
complete case information
complete case information
N=568 (43.0%)
N=342 (25.9%)
35
Figure S1c NSHD
Original study population BL - (POPULATION A)
Total original study population with at least baseline data (participants >=20)
N=2988
Number of death or lost at follow-up:
N=879
Original study population BL & FU - (POPULATION B)
Total study population participating at baseline and follow-up
N=2109 (70.6% of A)
After area restriction: N=0
Total ESCAPE study population BL & FU - (POPULATION C)
(Participants data from baseline and at follow-up living at ESCAPE sites at both surveys)
N=2109 (70.6% of A)
No complete lung function records: N=1088
ESCAPE study population with spirometry BL & FU - (POPULATION D)
ESCAPE Participants BL & FU with valid spirometry (FEV1 and FVC)
N=1021 (34.2% of A)
No complete case information: N=146
ESCAPE study population with spirometry and covariates BL & FU - (POPULATION E)
Population D with age, gender, height, smoking status, education and BMI at both surveys
N=875 (29.3% of A)
Final study population (POPULATION F1)
Final study population (POPULATION F2)
Population E with valid NO2 measurements and
Population E with valid PM10 measurements and
complete case information
complete case information
N=844 (28.2%)
N=751 (25.1%)
36
Figure S1d SALIA
Original study population BL - (POPULATION A)
Total original study population with at least baseline data (participants >=20)
N=4756
Number of death or lost at follow-up:
N=2558
Original study population BL & FU - (POPULATION B)
Total study population participating at baseline and follow-up
N=2198 (46.2% of A)
After area restriction: N=0
Total ESCAPE study population BL & FU - (POPULATION C)
(Participants data from baseline and at follow-up living at ESCAPE sites at both surveys)
N=2198 (46.2% of A)
No complete lung function records: N=871
ESCAPE study population with spirometry BL & FU - (POPULATION D)
ESCAPE Participants BL & FU with valid spirometry (FEV1 and FVC)
N=585 (12.3% of A)
No complete case information: N=4
ESCAPE study population with spirometry and covariates BL & FU - (POPULATION E)
Population D with age, gender, height, smoking status, education and BMI at both surveys
N=581 (12.2% of A)
Final study population (POPULATION F1)
Final study population (POPULATION F2)
Population E with valid NO2 measurements and
Population E with valid PM10 measurements and
complete case information
complete case information
N=580 (12.2%)
N=580 (12.2%)
37
Figure S1e SAPALDIA
Original study population BL - (POPULATION A)
Total original study population with at least baseline data (participants >=20)
N= 9,246
Number of death or lost at follow-up:
N=1510
Original study population BL & FU - (POPULATION B)
Total study population participating at baseline and follow-up
N= 7,736 (83.67% OF A)
After area restriction: N=4804
Total ESCAPE study population BL & FU - (POPULATION C)
(Participants data from baseline and at follow-up living at ESCAPE sites at both surveys)
N=2,648 (28.64% of A)
No complete lung function records: N=871
ESCAPE study population with spirometry BL & FU - (POPULATION D)
ESCAPE Participants BL & FU with valid spirometry (FEV1 and FVC)
N=1,777 (19.22% of A)
No complete case information: N=11
ESCAPE study population with spirometry and covariates BL & FU - (POPULATION E)
Population D with age, gender, height, smoking status, education and BMI at both surveys
N=1,766 (19.10% of A)
Final study population (POPULATION F1)
Final study population (POPULATION F2)
Population E with valid NO2 measurements and
Population E with valid PM10 measurements and
complete case information
complete case information
N=1,764 (19.08%)
N=729 (7.89%)
Legend Supplemental Figures S1a-e:
38
1. Population A: Original Baseline population (Survey 1; timepoint of 1st spirometry): Total original study
population considered as baseline participants, irrespective of availability of lung function and of
ESCAPE-relevant geography.
2. Population B: Population participating at original baseline (Survey 1) AND at last Follow-up (Survey 2;
; timepoint of 2nd spirometry), irrespective of availability of lung function and of ESCAPE-relevant
geography. This is a subgroup of A
3. Population C: ESCAPE population Survey 1 & Survey 2: Baseline and Follow up participants,
irrespective of availability of lung function. This is Population B but restricted to those living in
ESCAPE sites at both surveys. (= Subgroup of B)
4. Population D: ESCAPE Population with valid spirometry: This is Population C with the additional
requirement of having valid Specific Aim outcome data, i.e. valid spirometry data for all two lung
function metrics (FEV1 and FVC) from baseline and follow-up examination. ( = Subgroup of C)
5. Population E: like D, but in addition requirement of ‘complete case’ information on main co-variables
from baseline and follow-up as defined in modeling chapter: age, sex, height, smoking status, highest
educational level and BMI. ( = Subgroup of D)
6. Population F1 & F2: like E, but in addition with a valid estimate of home outdoor NO2 (NF1) and PM10
(NF2) exposure, respectively, successfully assigned to the subjects’ records. Please not that in looking at
traffic exposure we will be looking at a subset of F1 and F2 populations only (no traffic indicator subset
will be created). We will need to be careful, therefore, in making direct comparisons between exposure
associations for NOx, PM metric derived exposures and traffic exposures
39
Supplemental Figure S2 and Figure S3
Forest plot displaying the study-specific mixed linear regression model estimatesa,b of the association of NO2 with FVC (in mL) stratified by obesity statusc.
%
FVC (not obese) by NO2
Study
ID
%
Weight
FVC (obese) by NO2
Study
ES (95% CI)
(I-V)
N
SAPALDIA
3.58 (-37.62, 44.78)
13.25
1512
ECRHS
-12.99 (-31.80, 5.83)
63.53
3279
NSHD
9.26 (-46.34, 64.86)
7.28
587
SALIA
-20.45 (-82.86, 41.96)
5.78
EGEA
9.99 (-37.05, 57.02)
10.17
I-V Subtotal (I-squared = 0.0%, p = 0.800)
-7.27 (-22.27, 7.73)
100.00
D+L Subtotal
-7.27 (-22.27, 7.73)
ID
Weight
ES (95% CI)
(I-V)
N
SAPALDIA
-122.29 (-247.50, 2.92)
5.61
252
ECRHS
-42.05 (-79.23, -4.87)
63.64
580
NSHD
-46.93 (-125.79, 31.93)
14.15
255
409
SALIA
-20.17 (-100.42, 60.08)
13.66
171
495
EGEA
-64.87 (-237.83, 108.09)
2.94
73
I-V Subtotal (I-squared = 0.0%, p = 0.753)
-44.93 (-74.59, -15.27)
100.00
D+L Subtotal
-44.93 (-74.59, -15.27)
NO2_1
NO2_1
-82.9
0
increased risk
82.9
-247
decreased risk
0
increased risk
coefficient
247
decreased risk
coefficient
NO2_1 indicates NO2 measured at time of ESCAPE. a Associations with lung function measures are presented as increments in NO2 per 10µg/m3. I-square:
variation in estimated effects attributable to heterogeneity. D+L (Der Simonian and Laird method): pooled estimate of all studies. b The mixed linear regression
models were adjusted for: age, age squared, height, sex, BMI, highest educational level, and smoking status at 2nd spirometry; negative estimates indicated
lower lung function with increasing exposure. c Obesity has been stratified as not obese “BMI<30 kg/m2” and obese “BMI>=30 kg/m2”. P-value for
heterogeneity obese vs. non-obese: 0.026 for FVC.
40
Supplemental Figure S4 and Figure S5
Forest plot displaying the study-specific mixed linear regression model estimatesa,b of the association of NO2 with FEV1 and FVC (in mL) in females.
%
FEV1 (females) by NO2
Study
ID
%
Weight
FVC (females) by NO2
Study
ES (95% CI)
(I-V)
N
SAPALDIA
-4.78 (-40.78, 31.23)
12.15
980
ECRHS
-14.01 (-29.98, 1.95)
61.83
1981
NSHD
-35.01 (-77.59, 7.56)
8.69
SALIA
-22.97 (-63.06, 17.12)
9.80
EGEA
-16.53 (-62.30, 29.25)
7.52
I-V Subtotal (I-squared = 0.0%, p = 0.859)
-15.78 (-28.34, -3.23)
100.00
D+L Subtotal
-15.78 (-28.34, -3.23)
ID
Weight
ES (95% CI)
(I-V)
N
SAPALDIA
-38.49 (-82.03, 5.06)
11.80
980
ECRHS
-14.43 (-33.66, 4.80)
60.53
1981
470
NSHD
-24.04 (-71.01, 22.92)
10.15
470
580
SALIA
-20.79 (-70.20, 28.63)
9.17
580
303
EGEA
-50.18 (-101.95, 1.60)
8.35
303
I-V Subtotal (I-squared = 0.0%, p = 0.682)
-21.81 (-36.78, -6.85)
100.00
D+L Subtotal
-21.81 (-36.78, -6.85)
NO2_1
NO2_1
-77.6
0
increased risk
77.6
-102
decreased risk
0
increased risk
102
decreased risk
coefficient
coefficient
NO2_1 indicates NO2 measured at time of ESCAPE. a Associations with lung function measures are presented as increments in NO2 per 10µg/m3. I-square:
variation in estimated effects attributable to heterogeneity. D+L (Der Simonian and Laird method): pooled estimate of all studies. b The mixed linear regression
models were adjusted for: age, age squared, height, BMI, highest educational level, and smoking status at 2nd spirometry; negative estimates indicated lower
lung function with increasing exposure.
41
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