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Abstract
Objectives Chronic bronchitis (CB) is an important chronic obstructive pulmonary disease (COPD)-related phenotype, with distinct clinical features and prognostic implications. Occupational exposures have been previously associated with increased risk of CB but few studies have examined this association prospectively using objective exposure assessment. We examined the effect of occupational exposures on CB incidence in the European Community Respiratory Health Survey.
Methods Population samples aged 20–44 were randomly selected in 1991–1993, and followed up twice over 20 years. Participants without chronic cough or phlegm at baseline were analysed. Coded job histories during follow-up were linked to the ALOHA Job Exposure Matrix, generating occupational exposure estimates to 12 categories of chemical agents. Their association with CB incidence over both follow-ups was examined with Poisson models using generalised estimating equations.
Results 8794 participants fulfilled the inclusion criteria, contributing 13 185 observations. Only participants exposed to metals had a higher incidence of CB (relative risk (RR) 1.70, 95% CI 1.16 to 2.50) compared with non-exposed to metals. Mineral dust exposure increased the incidence of chronic phlegm (RR 1.72, 95% CI 1.43 to 2.06). Incidence of chronic phlegm was increased in men exposed to gases/fumes and to solvents and in women exposed to pesticides.
Conclusions Occupational exposures are associated with chronic phlegm and CB, and the evidence is strongest for metals and mineral dust exposure. The observed differences between men and women warrant further investigation.
- epidemiology
- respiratory
- longitudinal studies
- retrospective exposure assessment
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Key messages
What is already known about this subject?
Chronic bronchitis is an important chronic obstructive pulmonary disease (COPD)-related outcome, and certain occupational exposures have been previously associated with its prevalence.
What are the new findings?
This study provides strong prospective evidence for an association between occupational exposures, particularly metals and mineral dust exposure, and chronic bronchitis incidence.
How might this impact on policy or clinical practice in the foreseeable future?
Occupation may be associated with COPD and with particular COPD phenotypes.
Occupation needs to be taken into account in the clinical evaluation of patients with COPD.
Introduction
Chronic bronchitis (CB) has been defined as the presence of cough and sputum production for at least 3 months in 2 consecutive years. CB is common in patients with chronic obstructive pulmonary disease (COPD).1 COPD is a leading cause of mortality and morbidity worldwide,2 and is characterised by largely persistent airflow limitation, respiratory symptoms and frequent symptom exacerbations.3 Tobacco smoking is the primary risk factor for COPD, although a number of other environmental factors have been identified,4 including occupational exposures.5 CB is one of the validated COPD-related clinical phenotypes with distinct clinical features.6
CB is also seen in persons without airflow limitation, especially among smokers.7 Besides its detrimental impact on quality of life,8 CB is important because it has been associated with more frequent exacerbations, accelerated lung function decline, increased incidence of COPD and increased all-cause mortality,7 9–11 even among those without airflow limitation.12
Although occupation is currently considered an established risk factor for COPD,13 few studies have specifically examined the association between CB and certain occupational exposures,14 particularly dusts and fumes, and most such studies have been cross sectional.5 The European Community Respiratory Health Survey (ECRHS) is a large multicentre population-based longitudinal study that includes detailed information on occupation and respiratory outcomes, and can therefore provide strong prospective evidence. An earlier analysis in this cohort, which enrolled adults of fairly young age, did not show an association of occupational exposures with the incidence of CB, but only with chronic phlegm for mineral dust and gas/fume exposure.15 Now the ECRHS has accumulated 20 years of follow-up, allowing a relative ageing of the study population. Furthermore, we recently demonstrated an association between occupational exposures (biological dust, gases/fumes and pesticides) and COPD incidence within a subset of the ECRHS cohort.16 Following up from that analysis, our objective was to examine the effect of a variety of occupational exposures on CB incidence in the ECRHS.
Methods
ECRHS study overview
The aims and methods of the ECRHS have been described before.17 In brief, the study began in 1991–1993 and enrolled random general population samples aged 20–44 years in 55 centres from 23 countries. A first follow-up visit was performed between 1998 and 2002 (ECRHS II) and a second between 2010 and 2012 (ECRHS III). At baseline and at both follow-ups participants completed a detailed questionnaire via face-to-face interview and underwent a clinical examination, spirometry and other measurements.
Outcome definition, study population and spirometry
At each study visit participants were asked, ‘Do you usually cough during the day, or at night, in the winter?’ followed by ‘Do you cough like this on most days for as much as three months each year?’; a positive response to both questions was defined as chronic cough. Participants were also asked, ‘Do you usually bring up any phlegm from your chest during the day, or at night, in the winter?’ followed by ‘Do you bring up phlegm like this on most days for as much as three months each year?’; a positive response to both questions was defined as chronic phlegm. CB was defined as the presence of both chronic cough and chronic phlegm, that is, a positive response to all four questions above.
CB was the main outcome of the study, but chronic cough and chronic phlegm were also separately examined as secondary outcomes. Chronic phlegm (which implies coughing up the sputum) can be regarded as a more sensitive outcome that is still related to CB. Chronic cough (without phlegm), on the other hand, is much less specific and can be also indicative of other respiratory disorders, such as asthma or interstitial lung disease. The study population included all participants who had neither chronic cough nor chronic phlegm at baseline (ECRHS I) and were followed at least once, that is, at ECRHS II and/or ECRHS III.
Forced spirometry testing during follow-up was performed according to the American Thoracic Society/European Respiratory Society standards for reproducibility, keeping the maximum forced volume capacity (FVC) and forced expiratory volume in 1 s (FEV1) per participant. No bronchodilator was administered. For each participant, the presence of airflow limitation was defined as an FEV1/FVC ratio under the lower limit of normal (LLN) for age, height and gender according to the Global Lung Function Initiative 2012 equations.18 Furthermore, the severity of airflow limitation was graded according to the Global Initiative for Chronic Obstructive Lung Disease classification categories as follows: normal (FEV1/FVC≥LLN); stage I (FEV1/FVC<LLN, FEV1≥80% predicted); stage II (FEV1/FVC<LLN, 50%≤FEV1<80% predicted); stages III–IV (FEV1/FVC<LLN, FEV1<50% predicted).
Occupational exposure assessment
At both follow-up interviews, participants were asked to provide a detailed list of their occupations and industries from jobs held since the previous study visit. Jobs performed for at least 8 hours/week for at least 3 months were included. Each such employment was recorded in free text and subsequently coded in the International Classification of Occupations 88 (ISCO-88) by trained local coders in each country. Occupational exposures were assessed by linking the ISCO-88 occupational codes to the semiquantitative ALOHA(+) Job Exposure Matrix (JEM), a general-purpose JEM that has been used in many similar occupational epidemiology studies.19 20 For every job code, the ALOHA(+) JEM assigns three levels of exposure (none, low, high) to 10 categories of agents (biological dusts, mineral dusts, gases/fumes, herbicides, insecticides, fungicides, aromatic solvents, chlorinated solvents, other solvents and metals) and two composites of the above (all pesticides and vapours/gases/dusts/fumes (VGDF)).
Data analysis
Associations between the three outcomes (CB, chronic cough, chronic phlegm) and occupational exposures were examined in Poisson regression models fitted using generalised estimating equations (GEE) with an exchangeable working correlation matrix.21 Such GEE models provide population-averaged relative risk (RR) effect estimates over the follow-up visits of a longitudinal study, accounting for the correlation between multiple observations from the same study participant.22 In addition, GEE implicitly accounts for the nested clustering structure by study centre and by country. All models were adjusted for age, sex, lifetime smoking pack-years, current smoking, socioeconomic status (SES), current asthma and severity of airflow limitation at follow-up. We also included quadratic terms for age and lifetime smoking pack-years in order to account for potential non-linear relationships between these important covariates and CB incidence.23 SES was defined according to the participants' age of completion of formal education, and classified into three categories: high (>19 years), middle (16–19 years), low (<16 years). Current asthma was defined as a positive response to either of the following three questions: ‘Have you had an attack of asthma in the last 12 months?’, ‘Are you currently taking any medicines for asthma?’ and ‘Have you been woken by an attack of shortness of breath at any time in the last 12 months?’.
For each of the 12 ALOHA(+) exposures one model was fit, comparing any exposure (to the respective agent) to no exposure (to that agent). Stratified effects by sex and by smoking status (ever smokers vs never smokers) were obtained by including appropriate interaction terms in the models, and dose–response was examined by including separate terms for only low and for ever high exposure (to each agent). Four sensitivity analyses were performed: one without adjustment for severity of airflow limitation, one excluding all incident asthma cases, another both excluding incident asthma cases and without adjustment for severity of airflow limitation and another without adjustment for SES. Comparisons between models were performed using the quasilikelihood information criterion (QIC) statistic24; between two models fitted on the same data set, the one with the lower QIC is the best supported by the data. To address missingness with respect to covariates, we used multiple imputation with chained equations25; 50 imputed data sets were created, with models fit on each one and the results pooled. For details on the multiple imputation procedure and comparison with the corresponding complete case analyses, see the online supplementary materials. All analyses were performed with the R statistical environment, V.3.4.2,26 using packages ‘geepack’, ‘mice’ and ‘QICpack’.
Supplemental material
Results
Figure 1 illustrates the flow of ECRHS participants into our final study sample; in total 8794 participants fulfilled the selection criteria and were included in the analysis, originating from 30 study centres in 15 countries (Australia, Belgium, Denmark, Estonia, France, Germany, Iceland, Italy, Norway, Spain, Sweden, Switzerland, UK and the USA). Median age at baseline was 34.3 years. Of those participants, 4515 participated in both follow-up visits, 3361 only in ECRHS II and 918 only in ECRHS III. The descriptive characteristics of the study population are summarised in table 1. A total of 116 participants (1.5%) had CB at the ECRHS II, and the percentage increased to 2.1% at the ECRHS III (p=0.014). Approximately half of all participants were ever smokers, and across both follow-ups smokers were more likely to report CB (129/5845, 2.2%) than never smokers (63/5266, 1.2%, p<0.001). The proportion of participants with any occupational exposure since baseline (ECRHS I) ranged from 1.5% (to herbicides at ECRHS II) up to 40.5% (to gases/fumes at ECRHS III). Substantial correlations between individual exposures were noted, particularly within the pesticide and solvent categories (figure 2). A number of participants had missing covariate information, especially as regards spirometry and smoking status information, particularly at ECRHS III (table 1). Therefore, multiple imputation was performed; pooled results are presented below unless otherwise noted.
Flow chart of European Community Respiratory Health Survey (ECRHS) participants into the study population, and reasons for exclusion.
Correlation map (Spearman’s rho) between occupational exposures in the study population (n=13 185 observations).
Characteristics of the study population, n=8794 participants without cough or phlegm at baseline (ECRHS I)
Table 2 summarises the results from the main, fully adjusted GEE model for the three outcomes of interest (CB, chronic cough and chronic phlegm). Any exposure to metals, as compared with no metal exposure, resulted in an increased incidence of CB (RR 1.70, 95% CI 1.16 to 2.50); less pronounced increased risks were also observed for exposure to mineral dust (RR 1.35, 95% CI 0.99 to 1.83) and chlorinated solvents (RR 1.21, 95% CI 0.81 to 1.81). To put this in perspective, these effects are similar or greater than the adjusted effects of 10 pack-years of smoking (table 2). Neither exclusion of incident asthma cases from the analysis, omitting adjustment for severity of airway obstruction, nor omitting adjustment for SES did meaningfully impact these results (online supplementary table 1). In the models with separate terms for only low and ever high exposure, there was no strong evidence (on the basis of a lower QIC compared with the main models) for a dose–response effect of any exposure on CB incidence (online supplementary table 2). Similarly, no significant differences were found by gender or by smoking status (online supplementary table 3), although metal exposure appeared to have a stronger effect on CB incidence among never smokers (RR 2.45, 95% CI 1.23 to 4.91) than among ever smokers (RR 1.51, 95% CI 0.97 to 2.36).
Associations between (A) occupational exposures and 10 pack-years of smoking, and (B) incidence of CB, chronic cough and chronic phlegm. n=8794 participants without cough or phlegm at baseline (ECRHS I) followed up at ECRHS II and/or III (n=13 185 observations)
Associations were generally weaker for chronic cough (table 2) and only exposure to metals showed an effect on incidence (RR 1.29, 95% CI 1.02 to 1.64), which was not substantially modified by intensity of exposure, gender or by smoking status, and was similar in all three sensitivity analyses.
With respect to chronic phlegm we observed increased incidence for exposure to metals, aromatic and chlorinated solvents, mineral dust, gases and fumes and VGDF (table 2). Exclusion of incident asthma cases or omitting adjustment for airway obstruction did not materially change the results (online supplementary table 1). Moreover, there was evidence (lower QIC) for effect modification by gender (table 3); a significant effect on chronic phlegm incidence was observed only in men for gases and fumes (RR 1.51, 95% CI 1.20 to 1.91), VGDF (RR 1.63, 95% CI 1.29 to 2.06) and also for other solvents (RR 1.27, 95% CI 1.00 to 1.62). On the other hand, women exposed to insecticides and fungicides had higher incidence of chronic phlegm (RR 2.10, 95% CI 1.10 to 4.01 and RR 2.03, 95% CI 1.03 to 4.02, respectively), which was not the case for men. No effect modification was observed by smoking status for any of the 12 ALOHA(+) exposures. However, we observed evidence of an exposure–response relationship between VGDF exposure and chronic phlegm; any high exposure to VGDF resulted in an RR of 1.55 (95% CI 1.25 to 1.91) compared with no exposure, while only low exposure to VGDF showed a lower risk (RR 1.20, 95% CI 1.02 to 1.41).
Associations between occupational exposures and incidence of chronic phlegm, stratified by gender. n=8794 participants without cough or phlegm at baseline (ECRHS I) followed up at ECRHS II and/or III (n=13 185 observations)
Discussion
This is the first study to use CB as outcome, and estimate incidence rather than its prevalence, in a prospective fashion. Several important associations were found for CB and chronic phlegm, and, to a lesser extent, for chronic cough.
Our study is the first large prospective population-based study to clearly show that occupational exposure to metals increases the incidence of CB. Only one smaller population-based study has recently associated exposure to metals with fixed airflow obstruction,27 and an industry-based study linked metals to deterioration in lung function.28 Occupations involving exposure to metals in our study cohort included jobs such as motor vehicle mechanics, other machinery engineers and technicians, plumbers and pipe fitters. The mechanisms via which metal exposure may be associated with CB symptoms are not clear. Metals are a heterogeneous category of exposures, which have been linked with various forms of pulmonary toxicity.29 For one metal in particular, vanadium (present in steel and in fossil fuels), there is both occupational epidemiologic and experimental evidence of an association with bronchitis.30 31
Many workers in these occupations were also exposed to mineral dust, which also showed a trend towards increased CB incidence, especially with incident asthma cases omitted from analysis. Other frequent jobs with mineral dust exposure but without metal exposure included truck and lorry drivers (low probability and high intensity), and helpers/cleaners in offices, hotels and other establishments (high probability and low intensity), the latter jobs frequently performed by women. A number of population-based studies have associated dust exposure in general with CB symptoms,5 but only one cross-sectional study has done so specifically for mineral dust, showing an even higher risk in ever smokers.32 Our study adds substantially to the evidence base for this association. In addition, we did not find an interaction of mineral dust exposure (or any other exposure) with smoking, nor with sex, for the outcome of CB symptoms.
We also examined chronic cough and chronic phlegm separately, two outcomes that are less specific than CB; this particularly applies to chronic cough, for which no association was found in this study with occupational exposures other than metals. However, we found many interesting associations with chronic phlegm as outcome, which were very similar to those observed in a recent cross-sectional study from the Netherlands that used the same JEM to assign exposure and the same outcome definitions as our study.33 Moreover, we found that the effects were different for men and women; although mineral dust exposure increased the incidence of chronic phlegm in both men and women, metals, gases/fumes and solvents had this effect only among men. In addition, we found increased chronic phlegm incidence only among women exposed to insecticides and fungicides; although the numbers of exposed cases were small, this finding deserves further attention as pesticides have recently been associated with accelerated lung function decline20 and airway obstruction.34 Chronic phlegm is the key presenting symptom of CB and there is an active interest in its exact role in the pathogenesis and progression of COPD.35 There is recent evidence that chronic phlegm may represent an early developmental phase of COPD particularly among smokers,10 for some COPD cases.36 As a result, the association of occupational exposures with this outcome is important and may represent a pathway through which occupation mediates its effects on COPD risk.
It is of particular interest to compare these findings about CB with our recently published analysis on occupational exposures and spirometry-defined COPD incidence in the ECRHS.16 That analysis used a narrower subset of the cohort (3343 participants with complete follow-up between ECRHS I and III) and found an association with COPD incidence for biological dust, gases/fumes and pesticides, but not for metals or mineral dust exposure. In contrast, we found here no association with CB or chronic phlegm for biological dust, and associations with chronic phlegm only for gases/fumes and pesticides (the latter only among women). These differences may indicate that the effects of occupational exposures are complex, and mediated by different pathogenetic mechanisms that are currently poorly understood,37 resulting in variable effects on COPD and CB incidence. It is also a reminder that these are associated but distinct entities; an individual can have COPD without ever having CB, and not all patients with CB will end up with COPD.37
The prevalence of chronic respiratory symptoms, including CB, is higher among patients with COPD.38 The severity of airflow limitation may be associated, if only weakly, with CB symptoms.38 39 Therefore, we decided in advance to adjust our analyses for the severity of airflow limitation; however, it was found to not substantially affect the relationship between CB and occupational exposures. Exclusion of incident asthma cases resulted in slightly higher effect estimates for both mineral dust and metal exposure, particularly with CB as outcome. Exclusion of participants with asthma essentially increases the specificity of the study questions for the ascertainment of CB, thereby reducing non-differential misclassification of outcome which might bias estimates towards the null.
The strengths of the current study include the prospective design, long follow-up of 20 years (one of the longest to date) and large population size. Job histories were collected for the entire follow-up period, which for many participants represented most of their working life to date; therefore, occupational exposures could be assessed for a variety of agents, and in an objective way using a JEM rather than self-reported, which could be more vulnerable to recall and/or reporting bias. We were able to control for multiple important confounders for CB, including smoking and lifetime smoking pack-years, and also SES and current asthma. We also accounted for non-linear relationships of CB with age and smoking pack-years, in order to reduce residual confounding as far as possible. Multiple imputation was employed to effectively handle missing covariates, which can be a problem in any large population-based study. In addition, the multicentre and multicountry design increases the generalisability of our findings.
On the other hand, the study has certain limitations. The incidence of CB in our cohort was very low (around 2%) compared with other studies, and lower than the reported prevalence of 3.4%–22% for the general population, thereby diminishing the study power to detect associations; there are multiple possible reasons for this, including the relatively young age of the cohort, the exclusion of participants with cough or phlegm at baseline and, potentially, the ‘healthy worker effect’ due to both lower recruitment and/or higher dropout among participants with occupationally exposed jobs. The proportion of occupationally exposed women was much lower than men, as in most occupational epidemiology studies, making inference about effects in women more difficult. Future studies need to try and recruit more women, in order to assess potential effect modification by gender. In addition, although the study population was one of the largest to date, it was still insufficient to do subgroup analyses or to reliably assess heterogeneity across study centres and countries. Finally, the use of a JEM tailored for general population studies cannot prevent a certain degree of exposure misclassification, since not all individuals in the same occupation will have been similarly exposed. As a consequence, this might have resulted in somewhat attenuated, but not biased, risk estimates.
In conclusion, this study provides strong prospective evidence about the association of particular occupational exposures (metals, mineral dust, pesticides in women) with CB and chronic phlegm, thus highlighting their potential role in the pathogenesis and clinical presentation of COPD. This should be viewed in the wider context of the environmental and lifestyle exposures associated with COPD. Future research should investigate the differences observed between men and women. Still, these findings highlight the need to avoid these exposures in the relevant occupations or control them via appropriate protective measures, as well as the need to take occupation into consideration when assessing individual patients for their COPD risk.
Acknowledgments
This work is dedicated to the memory of our colleague Dr Michael Burr, in recognition of his contributions to the ECRHS study.
References
Footnotes
Contributors Study idea and design: TL, MK, JPZ, HK, JMA, KT, DJ. Data collection: MK, HK, AEC, JMA, HB, JW, JH, DN, IU, JMM, JAG, APV, CRS, IP, PD, BL, SV, TG, OS, MH, BF, DN, AJM, NPH, GB, RJ, KT, TS, VS, MO, PDB, JW, RB, ASB, RV, DJ, JPZ. Data analysis: TL, JPZ. Data interpretation: all authors. Initial manuscript draft: TL, MK, JPZ. Critical revision of the manuscript for important intellectual content: all authors. Final approval of the manuscript for publication: all authors.
Funding Financial support for ECRHS I for the local centres included in this study: Australia: Asthma Foundation of Victoria, Allen and Hanbury’s, Belgium: Belgian Science Policy Office, National Fund for Scientific Research, Estonia: Estonian Science Foundation, grant number 1088, France: Ministère de la Santé, Glaxo France, Insitut Pneumologique d’Aquitaine, Contrat de Plan Etat-Région Languedoc-Rousillon, CNMATS, CNMRT (90MR/10, 91AF/6), Ministre delegué de la santé, RNSP, France; GSF, Germany: Bundesminister für Forschung und Technologie, Italy: Ministero dell’Università e della Ricerca Scientifica e Tecnologica, CNR, Regione Veneto grant RSF number 381/05.93, Norway: Norwegian Research Council project number 101422/310, Spain: Fondo de Investigación Sanitaria (91/0016-060-05/E, 92/0319 and 93/0393), Hospital General de Albacete, Hospital General Juan Ramón Jiménez, Dirección Regional de Salud Pública (Consejería de Sanidad del Principado de Asturias), CIRIT (1997 SGR 00079) and Servicio Andaluz de Salud; Sweden: The Swedish Medical Research Council, the Swedish Heart Lung Foundation, the Swedish Association Against Asthma and Allergy; Switzerland: Swiss National Science Foundation grant 4026-28099; UK: National Asthma Campaign, British Lung Foundation, Department of Health, South Thames Regional Health Authority, USA: US Department of Health, Education and Welfare Public Health Service (grant number 2 S07 RR05521-28). Financial support for ECRHS II for the local centres included in this study: Australia: National Health and Medical Research Council, Belgium: Antwerp: Fund for Scientific Research (grant code G.0402.00), University of Antwerp, Flemish Health Ministry; Estonia: Tartu Estonian Science Foundation grant number 4350, France: (All) Programme Hospitalier de Recherche Clinique–Direction de la Recherche Clinique (DRC) de Grenoble 2000 number 2610, Ministry of Health, Ministère de l’Emploi et de la Solidarité, Direction Génerale de la Santé, Centre Hospitalier Universitaire (CHU) de Grenoble, Bordeaux: Institut Pneumologique d’Aquitaine; Grenoble: Comite des Maladies Respiratoires de l’Isere Montpellier: Aventis (France), Direction Regionale des Affaires Sanitaires et Sociales Languedoc-Roussillon; Paris: Union Chimique Belge- Pharma (France), Aventis (France), Glaxo France, Germany: Erfurt GSF–National Research Centre for Environment and Health, Deutsche Forschungsgemeinschaft (grant code FR1526/1-1). Hamburg: GSF–National Research Centre for Environment and Health, Deutsche Forschungsgemeinschaft (grant code MA 711/4-1). Iceland: Reykjavik, Icelandic Research Council, Icelandic University Hospital Fund; Italy: Pavia GlaxoSmithKline Italy, Italian Ministry of University and Scientific and Technological Research (MURST), Local University Funding for Research 1998 and 1999; Turin: Azienda Sanitaria Locale 4 Regione Piemonte (Italy), Azienda Ospedaliera Centro Traumatologico Ospedaliero/Centro Traumatologico Ortopedico–Istituto Clinico Ortopedico Regina Maria Adelaide Regione Piemonte Verona: Ministero dell’Universita e della Ricerca Scientifica (MURST), Glaxo Wellcome, Norway: Bergen: Norwegian Research Council, Norwegian Asthma and Allergy Association, Glaxo Wellcome, Norway Research Fund; Spain: Fondo de Investigacion Santarias (grant codes 97/0035-01, 99/0034-01 and 99/0034 02), Hospital Universitario de Albacete, Consejeria de Sanidad; Barcelona: Sociedad Espanola de Neumologıa y Cirugıa Toracica, Public Health Service (grant code R01 HL62633-01), Fondo de Investigaciones Santarias (grant codes 97/0035-01, 99/0034-01 and 99/0034-02), Consell Interdepartamentalde Recerca i Innovacio Tecnologica (grant code 1999SGR 00241), Instituto de Salud Carlos III; Red de Centros de Epidemiologıa y Salud Publica, C03/09, Redde Basesmoleculares y fisiologicas de las Enfermedades Respiratorias, C03/011 and Red de Grupos Infancia y Medio Ambiente G03/176; Huelva: Fondo de Investigaciones Santarias (grant codes 97/0035-01, 99/0034-01 and 99/0034-02); Galdakao: Basque Health Department Oviedo: Fondo de Investigaciones Sanitaria (97/0035-02, 97/0035, 99/0034-01, 99/0034-02, 99/0034-04, 99/0034-06, 99/350, 99/0034–07), European Commission (EU-PEAL PL01237), Generalitat de Catalunya (CIRIT 1999 SGR 00214), Hospital Universitario de Albacete, Sociedad Española de Neumología y Cirugía Torácica (SEPAR R01 HL62633-01), Red de Centros de Epidemiología y Salud Pública (C03/09), Red de Bases moleculares y fisiológicas de las Enfermedades Respiratorias (C03/011) and Red de Grupos Infancia y Medio Ambiente (G03/176; 97/0035-01, 99/0034-01 and 99/0034-02); Sweden: Göteborg , Umea, Uppsala: Swedish Heart Lung Foundation, Swedish Foundation for Health Care Sciences and Allergy Research, Swedish Asthma and Allergy Foundation, Swedish Cancer and Allergy Foundation, Swedish Council for Working Life and Social Research (FAS), Switzerland: Basel Swiss National Science Foundation, Swiss Federal Office for Education and Science, Swiss National Accident Insurance Fund; UK: Ipswich and Norwich: Asthma UK (formerly known as National Asthma Campaign). USA: Portland: American Lung Association of Oregon, Northwest Health Foundation, Collins Foundation, Merck Pharmaceutical. Financial support for ECRHS III for the local centres included in this study: Australia: National Health and Medical Research Council, Belgium: Antwerp South, Antwerp City: Research Foundation Flanders (FWO), grant code G.0.410.08.N.10 (both sites), Estonia: Tartu-SF0180060s09 from the Estonian Ministry of Education. France: (All) Ministère de la Santé. Programme Hospitalier de Recherche Clinique (PHRC), National 2010. Bordeaux: INSERM U897, Université Bordeaux Segalen, Grenoble: Comite Scientifique AGIRadom 2011. Paris: Agence Nationale de la Santé, Région Ile de France, domaine d’intérêt majeur (DIM). Germany: Erfurt: German Research Foundation HE 3294/10-1 Hamburg: German Research Foundation MA 711/6-1, NO 262/7-1 Iceland: Reykjavik, The Landspitali University Hospital Research Fund, University of Iceland Research Fund, ResMed Foundation, California, USA, Orkuveita Reykjavikur (geothermal plant), Vegagerðin (the Icelandic Road Administration, ICERA). Italy: All Italian centres were funded by the Italian Ministry of Health, Chiesi Farmaceutici. In addition, Verona was funded by Cariverona Foundation, Education Ministry (MIUR). Norway: Norwegian Research Council grant number 214123, Western Norway Regional Health Authorities grant number 911631, Bergen Medical Research Foundation. Spain: Fondo de Investigación Sanitaria (PS09/02457, PS09/00716 09/01511, PS09/02185, PS09/03190), Servicio Andaluz de Salud, Sociedad Española de Neumología y Cirurgía Torácica (SEPAR 1001/2010); Sweden: All centres were funded by the Swedish Heart and Lung Foundation, the Swedish Asthma and Allergy Association, the Swedish Association Against Lung and Heart Disease. Fondo de Investigación Sanitaria (PS09/02457). Barcelona: Fondo de Investigación Sanitaria (FIS PS09/00716). Galdakao: Fondo de Investigación Sanitaria (FIS 09/01511). Huelva: Fondo de Investigación Sanitaria (FIS PS09/02185) and Servicio Andaluz de Salud Oviedo: Fondo de Investigación Sanitaria (FIS PS09/03190). Sweden: All centres were funded by the Swedish Heart and Lung Foundation, the Swedish Asthma and Allergy Association, the Swedish Association Against Lung and Heart Disease. Swedish Research Council for Health, Working Life and Welfare (FORTE). Göteborg : Also received further funding from the Swedish Council for Working Life and Social Research. Umea also received funding from Vasterbotten Country Council ALF grant. Switzerland: The Swiss National Science Foundation (grant numbers 33CSCO-134276/1, 33CSCO-108796, 3247BO-104283, 3247BO-104288, 3247BO-104284, 3247-065896, 3100-059302, 3200-052720, 3200-042532, 4026-028099). The Federal Office for Forest, Environment and Landscape, The Federal Office of Public Health, The Federal Office of Roads and Transport, the Canton’s Government of Aargan, Basel-Stadt, Basel-Land, Geneva, Luzern, Ticino, Valais and Zürich, the Swiss Lung League, the Canton’s Lung League of Basel Stadt/ Basel, Landschaft, Geneva, Ticino, Valais and Zurich, SUVA, Freiwillige Akademische Gesellschaft, UBS Wealth Foundation, Talecris Biotherapeutics, Abbott Diagnostics, European Commission 018996 (GABRIEL), Wellcome Trust WT 084703MA, UK: Medical Research Council (grant number 92091). Support also provided by the National Institute for Health Research through the Primary Care Research Network. The coordination of the ECRHS 3 was funded through the Medical Research Council (grant number 92091). ISGlobal is a member of the CERCA Programme/Generalitat de Catalunya.
Competing interests DJ reports grants from European Commission during the conduct of the study. VS reports grants from the Wood Dust Foundation (Project No 444508795) during the conduct of the study. IP reports non-financial support and other from Novartis, personal fees and other from Astra Zeneca, non-financial support and other from Chiesi, outside the submitted work. PD reports personal fees from ALK, Stallergènes Greer, Chiesi, Thermo Fisher Scientific, Ménarini, Bausch&Lomb and Mylan, outside the submitted work. RJ reports grants from Estonian Research Council (personal research grant number 562) during the conduct of the study, personal fees and non-financial support from GSK, personal fees from Novartis and Boehringer, outside the submitted work.
Ethics approval Ethical approval for each centre was obtained from their respective competent bodies, and written informed consent was obtained from all participants.
Provenance and peer review Not commissioned; externally peer reviewed.
Patient consent for publication Not required.