Risk Factors for Chronic Obstructive Pulmonary Disease in a

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Risk Factors for Chronic Obstructive Pulmonary Disease
in a European Cohort of Young Adults
Roberto de Marco1, Simone Accordini1, Alessandro Marcon1, Isa Cerveri2, Josep M. Antó3–6, Thorarinn Gislason7,
Joachim Heinrich8, Christer Janson9, Deborah Jarvis10, Nino Kuenzli11,12, Bénédicte Leynaert13, Jordi Sunyer3–6,
Cecilie Svanes14,15, Matthias Wjst16, and Peter Burney10; for the European Community Respiratory Health Survey (ECRHS)
1
Unit of Epidemiology and Medical Statistics, Department of Public Health and Community Medicine, University of Verona, Verona, Italy; 2IRCCS
San Matteo Hospital Foundation, University of Pavia, Pavia, Italy; 3Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain;
4
Universitat Pompeu Fabra, Barcelona, Spain; 5Municipal Institute of Medical Research (IMIM-Hospital del Mar), Barcelona, Spain; 6CIBER
Epidemiologı́a y Salud Pública (CIBERESP), Barcelona, Spain; 7Department of Respiratory Medicine and Sleep, Landspitali University Hospital and
Faculty of Medicine, University of Iceland, Reykjavik, Iceland; 8Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for
Environmental Health, Neuherberg, Munich, Germany; 9Department of Medical Sciences: Respiratory Medicine and Allergology, Uppsala
University, Akademiska sjukhuset, Uppsala, Sweden; 10Respiratory Epidemiology and Public Health Group, National Heart and Lung Institute,
Imperial College, London, United Kingdom; 11Swiss Tropical and Public Health Institute (SwissTPH), Basel, Switzerland; 12University of Basel, Basel,
Switzerland; 13INSERM, U700-Epidemiology, Faculté Paris Diderot, Paris VII, Paris, France; 14Bergen Respiratory Research Group, Institute of
Medicine, University of Bergen, Bergen, Norway; 15Department of Occupational Medicine, Haukeland University Hospital, Bergen, Norway;
16
Comprehensive Pneumology Center (CPC), Institute of Lung Biology and Disease (iLBD), Helmholtz Zentrum Muenchen, German Research
Center for Environmental Health (GmbH), Munich, Germany
Rationale: Few studies have investigated the factors associated with
the early inception of chronic obstructive pulmonary disease (COPD).
Objectives: We investigated COPD risk factors in an international cohort
of young adults using different spirometric definitions of the disease.
Methods: We studied 4,636 subjects without asthma who had prebronchodilator FEV1/FVC measured in the European Community Respiratory Health Survey both in 1991 to 1993 (when they were 20–44 yr old)
and in 1999 to 2002. COPD was defined according to the Global
Initiative for Chronic Obstructive Lung Disease fixed cut-off criterion
(FEV1/FVC , 0.70), and two criteria based on the Quanjer and LuftiBus
reference equations (FEV1/FVC less than lower limit of normal). COPD
determinants were studied using two-level Poisson regression models.
Measurements and Main Results: COPD incidence ranged from 1.85
(lower limit of normal [Quanjer]) to 2.88 (Global Initiative for Chronic
Obstructive Lung Disease) cases/1,000/yr. Although about half of the
cases had smoked less than 20 pack-years, smoking was the main risk
factor for COPD, and it accounted for 29 to 39% of the new cases
during the follow-up. Airway hyperresponsiveness was the second
strongest risk factor (15–17% of new cases). Other determinants
were respiratory infections in childhood and a family history of
asthma, whereas the role of sex, age, and of being underweight
largely depended on the definition of COPD used.
Conclusions: COPD may start early in life. Smoking prevention should be
given the highest priority to reduce COPD occurrence. Airway hyperresponsiveness, a family history of asthma, and respiratory infections
in childhood are other important determinants of COPD. We suggest
the need for a definition of COPD that is not exclusively based on
spirometry.
Keywords: bronchial hyperreactivity; chronic obstructive pulmonary
disease; epidemiology; reference values; risk factors
(Received in original form July 21, 2010; accepted in final form October 8, 2010)
Supported by the European Commission, as part of their Quality of Life program.
The funding organization had no role in the design of the study; the collection,
analysis, and interpretation of the data; and the decision to approve publication
of the finished manuscript.
Correspondence and requests for reprints should be addressed to Roberto de
Marco, Ph.D., Unit of Epidemiology and Medical Statistics, Department of Public
Health and Community Medicine, University of Verona, Istituti Biologici II, Strada
Le Grazie 8, 37134 Verona, Italy. E-mail: [email protected]
This article has an online supplement, which is accessible from this issue’s table of
contents at www.atsjournals.org
Am J Respir Crit Care Med Vol 183. pp 891–897, 2011
Originally Published in Press as DOI: 10.1164/rccm.201007-1125OC on October 8, 2010
Internet address: www.atsjournals.org
AT A GLANCE COMMENTARY
Scientific Knowledge on the Subject
The main risk factor for chronic obstructive pulmonary
disease (COPD) is active smoking. As it is generally considered to be a disease of the elderly, there is limited data on
the incidence of COPD and its risk factors in young
populations.
What This Study Adds to the Field
Besides cigarette smoke, the main risk factors for COPD
among young adults are airway hyperresponsiveness, a family history of asthma, and respiratory infections in childhood. The role of sex, age, and body mass index on the risk
of developing COPD largely depends on the spirometric
definition of the disease used.
Chronic obstructive pulmonary disease (COPD) is expected to
become the third leading cause of death by 2020 (1). It is
characterized by progressive airflow obstruction and the destruction of lung parenchyma. Tobacco smoking is the main
cause of COPD and it is also the main determinant of a poor
outcome in those who have the disease (2, 3). Other factors may
influence the risk of developing COPD. The host factors that
seem to play a major role are age (4), a previous history of
asthma (5), genes (6), and early respiratory infections (7).
Among environmental determinants, occupational exposures
(8) and exposure to biomass smoke (9) are primary risk factors.
The role of sex, socioeconomic status (10), and body mass index
(BMI) on the risk of developing COPD is still open to debate.
The current knowledge about the causes of COPD is
generally based on data coming from the elderly population
in whom the disease is frequent. However, the risk factors for
the early inception of COPD are not well known, because only
a few surveys have addressed young populations (11). Furthermore, no studies have investigated to what extent the identification of the risk factors of COPD depends on the criteria used
to define the disease.
The aims of the present analysis were: (1) to assess the main
risk factors of COPD incidence in an international European
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AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE
cohort of young adults, and (2) to evaluate whether the identification of the risk factors may depend on the definition used for
COPD.
For these purposes, the data from the European Community
Respiratory Health Survey (ECRHS) were used. Some of the
results of this study have been previously reported in the form
of an abstract (12).
METHODS
Design of the Study
The ECRHS I is an international multicenter study on respiratory
diseases, performed in 1991 to 1993 on random samples of young adults
(20–44 yr) from the general population (13). Each participant was sent
a brief screening questionnaire (stage 1), and from those who
responded a random sample was selected to undergo a more detailed
clinical examination (stage 2). The ECRHS II is a follow-up study of
the participants in the ECRHS I stage 2, performed between 1999 and
2002, who underwent the same clinical examination as in the first
survey (the full protocol is available at www.ecrhs.org) (14).
Ethical approval was obtained for each center from the appropriate
ethics committee and written consent was obtained from each participant.
Subjects and Definitions
A total of 9,511 subjects from 24 centers in 10 European countries
participated in the ECRHS I stage 2 (1991–1993: baseline), had valid
lung function measurements (prebronchodilator values of FEV1 and
FVC) at baseline according to the American Thoracic Society criterion
for reproducibility (15), and did not report having had asthma during
lifetime as defined by a positive answer to the question ‘‘Have you ever
had asthma?’’ (see Figure E1 in the online supplement). Of these
individuals, 6,019 (63.3%) attended the second survey. After excluding
the subjects with no valid spirometry and the subjects who reported
asthma during the follow-up, the cohort consisted of 4,636 subjects.
The maximum FEV1 and FVC from at least two of up to five
technically satisfactory maneuvers were considered in each survey.
Incident COPD cases were defined according to the following three
‘‘modified’’ (in the sense that post-bronchodilator spirometry was not
performed and prebronchodilator lung function measurements were
used instead) diagnostic criteria: (1) Global Initiative for Chronic
Obstructive Lung Disease (GOLD) (16), if they had a prebronchodilator FEV1/FVC ratio less than 0.7 at follow-up (but not at baseline);
(2) lower limit of normal (LLN) (Quanjer); and (3) LLN (LuftiBus), if
they had a prebronchodilator FEV1/FVC ratio less than or equal to the
LLN at follow-up (but not at baseline), where the LLN was computed
using the Quanjer and colleagues (17) or the LuftiBus (18) equations,
respectively. The latter were used because they represent the most
recent reference equations obtained in a large sample of the European
population. Moreover, among the published European reference
equations, the Quanjer and LuftiBus equations represent the extremes
of the expected FEV1/FVC values (18).
Accordingly, 112 (GOLD), 116 (LLN [Quanjer]), and 205 (LLN
[LuftiBus]) subjects with COPD at baseline (‘‘prevalent cases’’) were
excluded from the corresponding incidence analysis.
The potential determinants considered in the analysis (listed in
Table 2) are fully described in the online data supplement.
VOL 183
2011
the variance [21]). The models had a dummy indicator of the occurrence
of COPD as the dependent variable, a random-intercept term at level 2,
and all the predictor variables as fixed effects. The PAFs were computed
using the aflogit routine, after the estimation of Poisson regression
models with standard errors adjusted for intracenter correlation,
considering only the predictors with statistically significant IRRs at
the multivariable analysis.
The statistical analysis was performed using STATA software,
release 10 (StataCorp, College Station, TX).
Sensitivity Analysis
Due to the lack of post-bronchodilator lung function measurements,
some subjects with asthma could have been misclassified as COPD.
Therefore, the main analyses (IRRs) were repeated after the exclusion
of all the subjects who had reported having had ‘‘wheezing or whistling
in the chest at any time in the last 12 months’’ at baseline.
RESULTS
Classification and Main Characteristics of the Studied Sample
The median length of the follow-up was 9.0 (range: 6.7–11.4)
years among the 4,425 subjects with no airflow obstruction at
baseline according to all the three criteria. A total of 122
subjects developed COPD according to at least one of the three
diagnostic criteria during the follow-up. The three criteria
agreed in classifying 42 subjects as affected by COPD (corresponding to 34.4% of the subjects with COPD according to at
least one of the criteria) and 4,303 subjects as individuals with
normal lung function (Figure 1). Regardless of the definition
used, the subjects with COPD were characterized by a higher
percentage of ever smokers (from 72.6 to 80.0%, depending
on the definition used for COPD), of individuals with airway
hyperresponsiveness (AHR) (from 19.6 to 23.0%), with respiratory infections in childhood (from 14.6 to 17.3%), and with
parental asthma (from 16.7 to 17.3%) compared with normal
subjects (Table E1). The distribution of age and sex varied
considerably according to the diagnostic criteria.
None of the new cases of COPD had a FEV1 less than 50%
predicted, whereas 12.8% (GOLD), 21.3% (LLN [Quanjer])
and 16.7% (LLN [LuftiBus]) had FEV1 greater than or equal to
50% predicted and less than 80% predicted. With respect to
subjects with normal lung function, COPD cases (with any
definition) had a poorer lung function both at baseline and at
follow-up, and a steeper decline in FEV1 (Table E2).
Incidence of COPD
The incidence of COPD ranged from 1.85 (LLN [Quanjer]) to
2.88 (GOLD) cases/1,000/yr (Table 1). The GOLD-COPD
Statistical Analysis
The analysis was performed separately for each COPD criterion
(GOLD, LLN [Quanjer], and LLN [LuftiBus]). Incidence rates of
COPD were estimated as the ratio between the number of new cases
and the number of person-years at risk (per 1,000), which were
considered to be equal to the length of the follow-up for each member
of the cohort who was COPD-free at baseline. Exact 95% confidence
intervals were computed using the Poisson distribution.
The association of each predictor with the incidence of COPD was
estimated by the incidence rate ratio (IRR) and the populationattributable fraction (PAF) (19). The IRRs were computed using
two-level random-intercept Poisson regression models (20) (level 1
units [subjects] nested into level 2 units [ECRHS centers]) with robust
standard errors (obtained by the Huber/White/sandwich estimator of
Figure 1. Incident cases of chronic obstructive pulmonary disease
according to the three spirometric criteria among the 4,425 subjects
who had normal lung function according to all the definitions at
baseline. GOLD 5 Global Initiative for Chronic Obstructive Lung
Disease; LLN 5 lower limit of normal.
de Marco, Accordini, Marcon, et al.: COPD in Young Adults
893
TABLE 1. NINE-YEAR INCIDENCE OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE AS DEFINED
BY THE THREE SPIROMETRIC CRITERIA
GOLD
LLN (Quanjer)
LLN (LuftiBus)
No. of Subjects at Risk
Person-Years
No. of Cases
Incidence Rate (cases/1,000/yr)
(95% CI)*
4,524
4,520
4,431
40,625
40,592
39,774
117
75
96
2.88 (2.38, 3.45)
1.85 (1.45, 2.32)
2.41 (1.95, 2.95)
Definition of abbreviations: CI 5 confidence interval; GOLD 5 Global Initiative for Chronic Obstructive Lung Disease; LLN 5
lower limit of normal.
* Poisson exact 95% CI.
incidence was higher in males than in females, even if the
difference did not reach statistical significance, whereas the
opposite occurred for both the LLN-COPD incidence rates
(Figure 2A). A strong positive association was found between
age and GOLD COPD incidence (P , 0.001), whereas no age
trend was observed for the LLN incidence rates (Figure 2B).
Risk Factors for COPD
Active smoking at baseline or during the follow-up, AHR, the
occurrence of respiratory infections in childhood, and a family
history of asthma significantly increased the risk of the occurrence of COPD regardless of the definition used (Table 2). The
association of BMI and past smoking with the incidence of
COPD varied according to the definition used. In particular, the
risk of developing COPD was significantly increased only when
the GOLD definition was used for underweight subjects (vs.
normal subjects) and for former smokers (vs. nonsmokers). Low
socioeconomic class, environmental tobacco smoke (ETS), bio-
mass and occupational exposures, and IgE sensitization were
not associated with the incidence of COPD.
PAF
Smoking explained the higher percentage of new COPD cases
in our cohort (Table 3). In fact, the PAF ranged from 29 to
39%, according to the definition used. AHR, a family history of
asthma, and respiratory infection in childhood also accounted
for a relevant percentage of incident cases (about 15, 10, and
8%, respectively).
Sensitivity Analysis
The previous results were confirmed (data not shown) when the
main analyses were repeated considering only the subjects who
did not report wheezing at baseline (3,835, 3,832, and 3,764
when the incidence of COPD was defined according to the
GOLD, LLN [Quanjer], and LLN [LuftiBus] definition, respectively).
DISCUSSION
The main results of our study of an international cohort of
young adults point out that:
1. Cigarette smoke is the main cause of COPD also in young
people.
2. The same host factors that increase the risk of asthma, such
as a family history of asthma, the presence of AHR, and the
occurrence of respiratory infections in childhood, play an
important role in the inception of COPD in young adults.
3. The role of sex, age, former smoking, and BMI largely
depends on the criterion used to define COPD.
Tobacco Smoke Exposure and COPD Incidence
in Young Adults
Figure 2. Nine-year incidence of COPD as defined by the three
spirometric criteria, according to (A) sex, and (B) age. GOLD 5 Global
Initiative for Chronic Obstructive Lung Disease; LLN 5 lower limit of
normal.
Tobacco smoke is the major risk factor for COPD (2), and the
population-attributable risk of smoking for COPD has been
estimated in the range of 50 to 70% (22). The mechanisms
responsible for the fact that some smokers develop COPD and
others do not are not completely understood (23).
Young adults are a segment of the population in whom
COPD may be caused by factors other than smoking, due to the
relatively low cumulative exposure to tobacco smoke. In our
cohort, however, about three out of four new COPD cases were
ever smokers, and the PAF for tobacco smoking was more than
double with respect to other potential causes. These findings
point out that cigarette smoke is the most important risk factor
for COPD also among young adults, and that smoking prevention could reduce the incidence of COPD in the young
population by 29 to 39%.
It is believed that COPD occurs after 20 to 25 pack-years of
exposure. In our cohort, about half of the incident cases of
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AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE
VOL 183
2011
TABLE 2. MUTUALLY ADJUSTED INCIDENCE RATE RATIOS FOR THE ASSOCIATION BETWEEN EACH
POTENTIAL PREDICTOR AND THE INCIDENCE OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE
AS DEFINED BY THE THREE SPIROMETRIC CRITERIA
IRR (95% CI)
Female
Age (> 35 vs. , 35 yr)
BMI (vs. normal)
Underweight
Overweight/obese
Low socioeconomic class
Smoking habits (vs. nonsmoker)
Quitter/sustained quitter
Persistent smoker/new smoker/restarter
ETS
Biomass exposure
Occupational exposures
AHR
IgE sensitization
Respiratory infections in childhood
Family history of asthma
GOLD
LLN (Quanjer)
LLN (LuftiBus)
0.53 (0.32, 0.86)*
2.24 (1.48, 3.39)†
0.95 (0.52, 1.75)
1.25 (0.65, 2.39)
1.68 (0.99, 2.86)
0.92 (0.53, 1.60)
3.55 (1.59, 7.93)*
0.62 (0.42, 0.91)*
1.02 (0.56, 1.83)
2.35 (0.72, 7.64)
0.78 (0.30, 2.00)
0.63 (0.27, 1.50)
1.14 (0.31, 4.22)
1.03 (0.55, 1.94)
0.83 (0.45, 1.54)
2.08
2.61
1.08
1.17
1.01
3.97
0.69
1.88
1.95
1.69
2.42
1.09
1.25
1.02
3.89
0.86
1.97
2.24
1.30
2.43
1.10
0.95
1.19
3.39
1.11
2.23
2.09
(1.34,
(1.62,
(0.71,
(0.69,
(0.69,
(2.07,
(0.44,
(1.02,
(1.25,
3.21)*
4.20)†
1.66)
1.97)
1.47)
7.65)†
1.10)
3.46)*
3.04)*
(0.92,
(1.35,
(0.68,
(0.57,
(0.59,
(1.78,
(0.46,
(0.86,
(1.12,
3.10)
4.33)*
1.76)
2.74)
1.77)
8.53)†
1.60)
4.54)
4.48)*
(0.81,
(1.25,
(0.62,
(0.53,
(0.86,
(1.72,
(0.68,
(1.64,
(1.26,
2.09)
4.73)*
1.93)
1.70)
1.66)
6.70)†
1.79)
3.04)†
3.47)*
Definition of abbreviations: AHR 5 airway hyperresponsiveness; BMI 5 body mass index; CI 5 confidence interval; ETS 5
environmental tobacco smoke; GOLD 5 Global Initiative for Chronic Obstructive Lung Disease; IRR 5 incidence rate ratio; LLN 5
lower limit of normal.
For a detailed description of the covariates, see the online data supplement.
* P , 0.05.
†
P , 0.001.
COPD had smoked less than 20 pack-years. Thus, the association observed between smoking and the incidence of COPD is
more likely to reflect an early interaction of the tobacco
exposure with some genetic or immunologic host characteristics, rather than the effect of the cumulative exposure to
cigarette smoke per se. (24)
The risk of developing COPD has been reported to be higher
in former smokers than in nonsmokers years after they quit
(25). Our data seem to confirm this finding. However, the extent
of the risk of developing the disease in this group of young
subjects and its statistical significance strongly depended on the
criterion used to define the disease. It is likely that these
discrepancies reflect differences in specificity and sensitivity of
the three definitions used (3, 26).
Factors That Increase the Risk of Asthma Also Increase the
Risk of COPD
The Dutch hypothesis (27) postulated that both asthma and
COPD share common origins with differences in the phenotypic
presentation related to the disease evolution or to the interaction between endogenous and exogenous factors. The results
of our analysis clearly show that well-known risk factors for
asthma, such as AHR, familiarity, and respiratory infection in
childhood, are relevant risk factors also for COPD. The proportion of new cases of COPD due to each of these factors
ranges from 8% (respiratory infections) to 15% (AHR).
AHR is a cardinal feature of asthma (28). In agreement with
previous studies (29), we found that hyperresponsive subjects
without asthma had about a fourfold greater risk of developing
COPD compared with subjects who were not hyperresponsive.
Subjects having at least one parent affected by asthma had
a double risk of developing COPD in adulthood, with respect to
subjects without any familiar history of asthma. These findings
agree with recent studies showing that several genes increase
the susceptibility to both asthma and COPD and document the
existence of a common genetic background (6, 30, 31).
The occurrence of respiratory infection early in life is one of
the strongest risk factors for the development of asthma (32).
Our results showed that also the risk of developing COPD is
doubled in subjects who had respiratory infections in their
childhood. Respiratory infections in infancy are largely due to
viruses (33). Virus infections may lead to permanent changes in
TABLE 3. MUTUALLY ADJUSTED POPULATION-ATTRIBUTABLE FRACTIONS FOR THE ASSOCIATION
BETWEEN EACH POTENTIAL PREDICTOR AND THE INCIDENCE OF CHRONIC OBSTRUCTIVE
PULMONARY DISEASE AS DEFINED BY THE THREE SPIROMETRIC CRITERIA
PAF (95% CI)*
GOLD
kg/m2)
Underweight (BMI , 18.5
Ever smoking
AHR
Respiratory infections in childhood
Family history of asthma
0.04
0.39
0.15
0.06
0.09
(0.00,
(0.15,
(0.06,
(0.00,
(0.02,
LLN (Quanjer)
0.07)
0.56)
0.22)
0.13)
0.16)
0.04
0.38
0.17
0.09
0.11
(0.00,
(0.12,
(0.04,
(0.00,
(0.00,
0.11)
0.56)
0.29)
0.20)
0.22)
LLN (LuftiBus)
0.01
0.29
0.15
0.08
0.10
(0.00,
(0.01,
(0.03,
(0.03,
(0.01,
0.05)
0.50)
0.25)
0.12)
0.19)
Definition of abbreviations: AHR 5 airway hyperresponsiveness; BMI 5 body mass index; CI 5 confidence interval; GOLD 5
Global Initiative for Chronic Obstructive Lung Disease; LLN 5 lower limit of normal; PAF 5 population-attributable fraction.
Also adjusted for sex and age. 0.00: negative values truncated to zero.
* 95% CI calculated on log(12PAF) scale.
de Marco, Accordini, Marcon, et al.: COPD in Young Adults
the airways (34). Some viruses may persist as a latent infection
in the airways (35), increasing the susceptibility to COPD.
Are Sex, Age, and BMI Associated with the Risk of Developing
COPD in Young Adults?
Our findings indicate that the answer to this question depends on
the definition. When the GOLD COPD criterion was used, male,
underweight, and older subjects had a significantly increased risk
of developing COPD. When a sex-age–based definition was used
(LLN criteria), the age, sex, and BMI associations with COPD
lost their statistical significance, and sex and age even showed
a reverse association.
COPD prevalence is higher in subjects older than 40 years of
age compared with those younger than 40 years, regardless of
the diagnostic criteria used (16). However, an increasing pattern
of prevalence with age does not imply a similar trend in
incidence. Unfortunately, very few studies on COPD incidence
are available. All longitudinal studies in northern Europe found
that incidence of COPD increased with age, but almost all of
them used the GOLD as a diagnostic criterion, and the age
range investigated was much wider than ours (36–40).
The role of sex in determining COPD risk remains unclear
(16). In the past, most studies showed that COPD prevalence
and mortality were greater among men than women. More
recent studies showed that the sex difference in COPD prevalence tends to disappear (41, 42). Regarding COPD incidence, most (36–38) but not all (39) studies found a higher risk
in men than in women. Our results suggest that part of the
contrasting findings in literature may be due to methodological
differences.
An association between COPD prevalence and low BMI has
been reported in several studies (43), but it is not clear whether
a low BMI precedes or follows the onset of the disease. Our
longitudinal study points out that subjects with BMI less than
18.5 kg/m2 had a threefold risk of developing the disease
compared with subjects with a normal weight. However, the
association was weaker when LLN diagnostic criteria were
used.
To sum up, we have shown that the role of age, sex, and low
BMI on the development of COPD differs according to the
definition of the disease. The discrepancy in the relative risk
estimates when different diagnostic criteria are used is hard to
interpret. The LLN criterion might lack specificity in young
populations, leading to the underestimation of the associations
between the disease and risk factors. On the contrary, the GOLD
criterion may produce false-positive associations in the age range
(20–54 yr) studied because it does not consider the physiological
decline in FEV1/FVC. Whatever the truth is, we may empirically
conclude that, because of the contrasting results, aging, sex, and
low BMI play only a minor role in the early development of
COPD.
Environmental Exposure, Socioeconomic Class, and the Risk
of Developing COPD
Previous studies (8, 9) found an association between ETS, occupational and biomass exposures, socioeconomic class, and the
incidence of COPD. However, we were not able to confirm
these findings. The young age of our cohort could have implied
a relatively low cumulative exposure to environmental factors.
Furthermore, these factors have been measured using simple
questions during a clinical interview, and exposures could have
thus been misclassified. Moreover, due to the relatively low
number of subjects with COPD in young adults, the power of
our study might not have been enough to detect small effects
(e.g., ETS).
895
Air pollution was not considered among the environmental
determinants because we had previously shown that crosscommunity background monitor data do not accurately characterize the individual exposure (44).
COPD Incidence and the Performance of Different
Diagnostic Criteria
As expected, in our study, COPD incidence (as measured
according to the GOLD criterion) was slightly lower than the
incidence measured in other older populations in Europe (36,
38, 40).
The agreement between the GOLD and the two LLN
definitions in identifying subjects affected by COPD was
relatively poor. In fact, only 34.4% were simultaneously diagnosed as having COPD by all three criteria. The variation
between the two LLN definitions was similar to the variation
found between the GOLD and the LLN (LuftiBus). Despite
their differences, all the definitions agreed in identifying the risk
factors that have a major impact on the population. When the
diagnostic criteria disagreed, the estimates of the strength of the
association between potential risk factors and the incidence of
COPD showed a wide variation not only between the GOLD
and the LLN criteria but also within the two LLN criteria. This
finding points out that the choice of the reference equations for
calculating the LLN may introduce a relevant source of
variation and suggests the need for a definition of COPD that
is not exclusively based on spirometric tests (26).
Limitations and Strengths of the Study
The main limitation of our study is the use of prebronchodilator
spirometric values for defining COPD. As a consequence, subjects with asthma with fully reversible obstruction could have
been falsely classified as having COPD. To minimize this
potential bias, all the subjects who reported asthma at baseline
or during the follow-up were excluded. Moreover, when the
main analyses were restricted to the subgroup of individuals
who did not report current wheezing at baseline, the associations between the incidence of COPD and the main risk factors
were confirmed. Due to the lack of post-bronchodilator measurements, we cannot rule out that some cases of undiagnosed
asthma with transient airflow obstruction at the end of the
follow-up could have been erroneously classified as COPD.
However, as the probability for a subject with asthma to report
neither the label of asthma nor wheezing in the last year is very
low, it is extremely likely that the misclassification bias, if present,
could have affected our results only to a minor extent.
Other limitations are the relatively small number of subjects
with incident COPD (which is a consequence of the young age of
the population studied), which did not make it possible to
evaluate sex-stratified associations, as well as the lack of information on other chronic lung conditions. As in other longitudinal
studies, the participation rate was low in some centers, and hence
a potential selection bias could be present. However, our findings
were confirmed when the four centers with the lowest participation rate (, 50%) were excluded (data not shown). The main
strengths are the population-based prospective nature of our
study and its highly standardized multicenter international
framework.
Conclusions
COPD is a considerable problem for young adults and the most
important risk factor for developing COPD is cigarette smoke.
Smoking prevention should be given the highest priority to
reduce the occurrence of the disease. AHR, a family history of
896
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE
asthma, and respiratory infections in childhood are other important determinants of the occurrence of the disease. The variation
in incidence estimates and in the identification of risk factors due
to different diagnostic criteria of COPD suggests the need for an
epidemiological definition of the disease that is not exclusively
based on spirometry.
Author Disclosure: R.d.M. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript. S.A. does not have
a financial relationship with a commercial entity that has an interest in the subject
of this manuscript. A.M. does not have a financial relationship with a commercial
entity that has an interest in the subject of this manuscript. I.C. does not have
a financial relationship with a commercial entity that has an interest in the subject
of this manuscript. J.M.A. does not have a financial relationship with a commercial
entity that has an interest in the subject of this manuscript. T.G. is employed by
the National Institutes of Health. J.H. does not have a financial relationship with
a commercial entity that has an interest in the subject of this manuscript. C.J.
received lecture fees from GlaxoSmithKline (GSK), AstraZeneca, Merck Sharp &
Dohme, Boehringer Ingelheim (BI), and Pfizer, and received grant support from
GSK. D.J. received lecture fees from GSK. N.K. does not have a financial
relationship with a commercial entity that has an interest in the subject of this
manuscript. B.L. received lecture fees from GSK. J.S. does not have a financial
relationship with a commercial entity that has an interest in the subject of this
manuscript. C.S. does not have a financial relationship with a commercial entity
that has an interest in the subject of this manuscript. M.W. does not have
a financial relationship with a commercial entity that has an interest in the subject
of this manuscript. P.B. received lecture fees from various unknown entities,
Pfizer, and BI.
Acknowledgment: The authors thank the ECRHS Co-ordinating Center (London),
the Project Management Group, and the Study Group for their assistance. For a list
of the principal participants in ECRHS, see the online supplement.
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