Article Text

Original article
Risk factors for chronic mucus hypersecretion in individuals with and without COPD: influence of smoking and job exposure on CMH
  1. Akkelies E Dijkstra1,2,
  2. Kim de Jong2,3,
  3. H Marike Boezen2,3,
  4. Hans Kromhout4,
  5. Roel Vermeulen4,
  6. Harry J M Groen1,
  7. Dirkje S Postma1,2,
  8. Judith M Vonk2,3
  1. 1Department of Pulmonology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
  2. 2University of Groningen, GRIAC research institute, Groningen, The Netherlands
  3. 3Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
  4. 4University of Utrecht, Institute for Risk Assessment Sciences, Utrecht, The Netherlands
  1. Correspondence to Judith M Vonk, University of Groningen, University Medical Center Groningen, Department of Epidemiology, Hanzeplein 1, Groningen 9700 RB, The Netherlands; J.M.Vonk{at}umcg.nl

Abstract

Background Chronic mucus hypersecretion (CMH) is highly prevalent in smokers and associated with an accelerated lung function decline and chronic obstructive pulmonary disease (COPD). Several risk factors contribute to CMH and to COPD. It is, however, unknown if risk factors for CMH are similar in persons with and without COPD.

Methods 1479 persons with and 8529 without COPD, participating in the general population-based LifeLines cohort, completed questionnaires and underwent spirometry. Occupational exposure was assessed using the ALOHA+ job exposure matrix. Analyses were performed using multiple logistic regression models.

Results In COPD, a significantly higher risk for CMH was associated with higher pack-years smoking (per 10 pack-years) (OR=1.28; 1.12 to 1.46) and environmental tobacco smoke (ETS) (OR=2.06; 1.33 to 3.19). In non-COPD; male gender (OR=1.91; 1.51 to 2.41), higher Body Mass Index (OR=1.04; 1.01 to 1.06), higher pack-years smoking (OR=1.28; 1.14 to 1.44), current smoking (OR=1.50; 1.04 to 2.18), low and high exposure to mineral dust (OR=1.39; 1.04 to 1.87 and OR=1.60; 1.02 to 2.52), high exposure to gases & fumes (OR=2.19; 1.49 to 3.22). Significant interactions were found between COPD and exposure to gases & fumes (p=0.018) and aromatic solvents (p=0.038).

Conclusions A higher risk for CMH was associated with higher pack-years smoking regardless of COPD status. However, a higher risk for CMH was associated with high occupational exposure to gases & fumes in individuals without COPD only.

  • Materials, exposures and occupational groups

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What this paper adds

  • Chronic mucus hypersecretion is common in smokers with and without chronic obstructive pulmonary disease (COPD).

  • It is not known whether risk factors for chronic mucus hypersecretion (CMH) are similar in persons with and without COPD.

  • We conclude that cigarette smoking is the predominant predictor of CMH in all individuals.

  • High occupational exposure to gases and fumes is an important determinant of CMH in people without, but not in those with COPD.

Introduction

The secretion of mucus is a normal response of epithelial cells in order to protect the airways and lung tissue against inhaled pathogens, particles and noxious chemicals. By contrast, chronic mucus hypersecretion (CMH) is abnormal. CMH is a condition of mucus overproduction defined by mucus production for at least 3 months during the last 2 years, when specific causes have been excluded.1 The prevalence of CMH in the general population varies from 3.5% to 12.7% depending on the study population and the CMH definitions used.2 ,3 In the general population, CMH is associated with an increased duration and frequency of respiratory infections, excess decline of the forced expiratory volume in 1 s (FEV1), and increased hospitalisation and mortality rates.2 ,4–6

The best studied and most important risk factor for CMH is cigarette smoking.2 ,7 Other risk factors for CMH are higher age and male gender.8 ,9 Of interest, the presence of respiratory infections in childhood is a risk factor for CMH and also for development of chronic obstructive pulmonary disease (COPD), as is smoking.7 ,10 Next to active smoking, there is evidence that exposure to maternal smoking during pregnancy (passive smoking in utero) and environmental tobacco smoke exposure (ETS) in childhood are additional risk factors for the presence of CMH in adulthood.11–15 Occupational exposures have been mentioned as risk factors for CMH in many general population-based studies, and have also been reported as risk factors for COPD in different studies.3 ,16 ,17 Additionally, CMH is present in about 30% of COPD patients where it constitutes a risk factor for increased duration and frequency of respiratory infections, hospitalisation and mortality and higher risk for exacerbations.18 ,19

The above studies show that CMH can be present in persons with and without COPD, and some risk factors for COPD overlap with those for CMH, like smoking and bacterial infections. However, not all patients with COPD have CMH and, conversely, not all individuals with CMH have COPD. We therefore investigated whether risk factors for CMH differ between persons with and without COPD. To this aim we used data of the LifeLines cohort, a general population-based study in the northern part of The Netherlands, and determined risk factors for CMH in persons with and without COPD taking into account well-known clinical, demographic and environmental factors contributing to CMH (active smoking, exposure to ETS and occupational exposures).

Methods

Study population and methods

To investigate risk factors for CMH we included patients participating in the Dutch LifeLines cohort study. The LifeLines study is a multidisciplinary prospective general population-based study among residents of the three northern provinces of The Netherlands, investigating the origins and the development of chronic diseases and multimorbidity.20 Patients were recruited via general practitioners. In the current study, we included 13 301 Caucasian adults, aged between 18 and 90 years, from the second data release of the LifeLines cohort. All participants gave written informed consent, completed questionnaires and underwent a medical examination and standardised spirometry, according to the ERS guidelines.21 In this population-based study we did not administer a bronchodilator. The exact question used to define CMH was ‘do you usually expectorate sputum during day or night in winter on the majority of days ≥3 months a year? (yes/no)’. Since it is known that the presence of asthma can cause symptoms of CMH, patients with asthma (ever having asthma confirmed by a physician) were excluded from the analyses (n=953).

ETS exposure and smoking habits

Exposure to smoke during childhood was determined by the question ‘did your mother/father smoke regularly during your childhood?’ (yes/no). Furthermore, current ETS exposure was determined by questions about regular exposure to smoke from others during the last year for at least 1 h per day (yes/no), and in case of a paid job, whether smoking was present in the workplace (yes/no). Smoking habits were defined as never smoking, ex-smoking and current smoking, and the lifetime number of pack-years smoked.

An individual was defined as being a current smoker if he/she answered ‘yes’ to the question ‘do you smoke now or have you been smoking in the last month?’ A never smoker when answered ‘no’ to the question ‘have you ever smoked for as long as a year?’, and an ex-smoker answered ‘yes’ to the question ‘have you ever smoked for as long as a year’ and ‘no’ to the question ‘do you smoke now or have you been smoking in the last month?’ and ‘yes’ to the question ‘did you currently quit smoking?’ Pack-years of smoking were calculated as the number of packs of cigarettes (1 pack=20 cigarettes) smoked per day times the number of years of smoking.

Occupational exposure

Information on employment status, job title and description of work tasks of the current job (or last held job in case of retirement) was obtained by questionnaire and coded according to the International Standard Classification of Occupations V.1988 (ISCO-88).22

Employed and unemployed persons were included in this study. The ALOHA+ job exposure matrix (JEM) was used to classify the reported jobs into no, low or high exposure to various agents (coded, respectively, 0, 1 or 2).16 If someone had two or more jobs (n=232, 2.3%), the average occupational exposure was determined by rounding the average to the nearest integer (0.5=1 and 1.5=2).

Statistical analyses

Analyses were stratified for COPD defined as FEV1/FVC <70%. Body Mass Index (BMI) was defined as weight/height2 (kg/m2). Differences in characteristics and occupational exposures between persons with and without CMH stratified by COPD were analysed using χ2 tests and twotailed unpaired Student t tests.

Characteristics significantly associated with CMH (except for the 108 occupational exposures and lung function), were included in a multivariate logistic regression model. Subsequently, each occupational exposure was included in this model one by one without taking into account other occupational exposures. The interaction effect between COPD and the other possible risk factors was tested by using a multivariate regression model including COPD × risk factor as an extra variable in the model.

Since the prevalence of exposures to herbicides and insecticides was very low in our population (1.3% vs 3.5%), we analysed all pesticides as one variable (prevalence 4.0%). Differential effects of the possible risk factors between persons with and without COPD were tested in unstratified multivariate models by including the appropriate interaction terms. In an additional analysis, retired and unemployed persons were excluded (n=1996) to assess the effect of current occupational exposure only. Finally, analyses were stratified by age, gender and smoking habits to investigate possible effect modification by these variables.

Analyses were conducted using SPSS V.19.0. A twosided p value <0.05 was considered statistically significant.

Results

From the initial LifeLines sample of 13 301 individuals, a total of 2340 was excluded because of incomplete data on CMH (n=356), lacking information on smoking habits and ETS (n=1568) and incomplete data on lung function (n=416). After exclusion of asthmatics (n=953) 100 08 individuals (75.8% of the total) remained, including 1479 (14.8%) with and 8529 without COPD.

Characteristics, ETS and smoking habits related to CMH

Table 1 presents the demographics of persons with and without CMH, stratified by COPD status. The overall prevalence of CMH was 4.2% and was significantly higher in patients with COPD (8.7%) than in persons without COPD (3.4%, p<0.001). In persons with and without COPD, the prevalence of CMH was significantly higher in males, in ever smokers and current smokers and in persons with ETS exposure; the number of pack-years smoked was also significantly higher in patients with CMH. COPD patients with CMH had significantly worse lung function than those without CMH.

Table 1

Demographic characteristics of persons with and without chronic mucus hypersecretion and association of these characteristics with chronic mucus hypersecretion (expressed as p value), stratified by COPD (n=10 008)

Table 2 and figure 1 present the results of the multivariate logistic regression analysis on the associations between risk factors and CMH, stratified by COPD, and the results of interaction analysis between risk factors and COPD.

Table 2

Interaction analysis between COPD and characteristics, ETS (by others and at work), ex- and current smoking and pack-years and multivariate logistic regression on association between chronic mucus hypersecretion and gender, BMI, ETS (by others and at work), ex- and current smoking and pack-years, stratified by COPD

Figure 1

ORs and 95% CI for multivariate analysis showing association between chronic mucus hypersecretion and gender, BMI, environmental tobacco smoke and smoking habits, stratified by chronic obstructive pulmonary disease. Pack-years per 10: the unit in the analysis is 10 pack-years so the OR is the estimate of 10 pack-years.

In patients with COPD, a higher number of pack-years and current ETS exposure were significantly associated with a higher risk for CMH. In individuals without COPD, next to a higher number of pack-years, also male gender, higher BMI and current smoking were associated with a significant higher risk for CMH. None of the investigated interactions between the risk factors and COPD was statistically significant.

Occupational exposure and risk for CMH

Table 3 presents the proportion of patients without, with low, or high exposure to occupational agents according to the ALOHA+ JEM, in patients with and without CMH, stratified by COPD. Almost 45% of the population had some occupational exposure, either low or high. Exposure to gases & fumes was the most frequent occupational exposure (40.1%). An overview of the most prevalent occupations within those exposed is given in table 1 in the supplementary file.

Table 3

Prevalence of occupational exposures, according to the ALOHA+ JEM, in persons with and without chronic mucus hypersecretion, stratified by COPD

In patients with COPD, there was no significant difference in occupational exposures between patients with and without CMH. By contrast, in patients without COPD, the prevalence of five out of the eight investigated occupational exposures was significantly different between patients with and without CMH.

Statistically significant interactions were found between COPD and high exposure to gases and fumes, and between COPD and low exposure to aromatic solvents (see online supplementary table S2). In the stratified analyses, significant associations were found particularly between low and high exposure to mineral dust and CMH, and between high exposure to gases and fumes, chlorinated solvents or heavy metals and CMH (adjusted for gender, BMI, ETS and smoking habits) in patients without COPD. Figure 2 shows the ORs and 95% CIs of occupational risk factors studied with respect to the presence of CMH, stratified by COPD. In patients with COPD, there were no significant associations between occupational exposures and CMH (see online supplementary table S2).

Figure 2

ORs and 95% CI for multivariate analysis showing association between chronic mucus hypersecretion and occupational exposures, stratified by chronic obstructive pulmonary disease (COPD). Reference is not exposed; analysis corrected for gender, Body Mass Index, environmental tobacco smoke, ex- and current smoking and pack-years. Occupational exposures were added one by one. Grey frame: significant interaction (p<0.05) between occupational exposure and COPD.

Exclusion of retired and unemployed patients to assess the effect of current occupational exposures did not change the results (results not shown).

Stratification by age, gender or smoking habits (never-smoker, ex-smoker and current smoker) did not consistently indicate effect modification by these variables of the associations between occupational exposures and CMH (see online supplementary table S3–S5).

Discussion

We report results from a large cross-sectional general population-based study, relating demographic characteristics, environmental smoke exposure, smoking habits and occupational exposures to CMH in patients with and without COPD. Patients with COPD had a higher prevalence of CMH (defined by expectoration of sputum on most days ≥3 months during the last year) (8.7%) than to those without COPD (3.4%). The risk for CMH in patients with COPD increased with higher pack-years and ETS exposure only, without any effect of occupational exposures. By contrast, risk factors for CMH in patients without COPD were male gender, higher BMI, current smoking, higher pack-years and several occupational exposures. Interestingly, the association between CMH and high occupational exposure to gases & fumes differed significantly between patients with and without COPD. Although the differences in the associations of the other occupational risk factors with CMH between patients with and without COPD failed to reach statistical significance, the observed differences in effect sizes may be important.

The commonly reported prevalence of CMH in the general population ranges from 3.5% to 12.7%.2 ,9 The prevalence of CMH was 4.2% in our study, which is in the lower range of reported prevalences. When asthmatics also were included, the prevalence was 4.8%. The prevalence of CMH in our study was comparable with the prevalence of CMH (defined in the same way), in another general population-based cohort from the northern part of The Netherlands (Vlagtwedde), also when stratified for gender, smoking habits or COPD.

It has been well established that the presence of CMH increases with the severity of airflow limitation.18 ,23 Since our population encompassed patients with relatively mild COPD according to GOLD the guidelines (80% stage 1, 20% stage 2), the relatively low prevalence of CMH in patients with COPD of 8.7% is in line with the association of CMH with the lung function level.24

We had only prebronchodilator lung function available in this population-based study, which may have affected our prevalence of COPD and especially very mild COPD. For this same reason, it is also possible that few undiagnosed asthmatics may incorrectly have been included in the COPD group. In a sensitivity analysis, we used the lower limit of normal (LLN) to define COPD.25 The results of this analysis showed that the prevalence of CMH and the directions and magnitudes of the associations remained similar (see online supplementary table S6).

In accordance with many other general population-based studies, we found that CMH is significantly more prevalent in men than in women.2 ,3 ,17 A potential reason for this difference is a tendency for women to report more dyspnoea and cough, but less phlegm symptoms than men.26

The association between pack-years smoking and CMH is in accordance with the literature but was rarely examined separately for patients with and without COPD in the general population.27 We found this association to be present in both groups. This could mean that the cigarette smoke-induced chronic inflammatory process and its associated remodelling of the airway walls, are the most important risk factors for CMH, thereby reducing the effects of other potential risk factors.

In addition to pack-years, current smoking was significantly associated with an increased CMH-risk in persons without but not in patients with COPD. Since some individuals would have quit for only a short time, this may have affected the results. Even when we excluded individuals who quit smoking for only a short period (smoking cessation <1 year, n=31) or added these 31 patients to the analysis in current smokers with COPD, current smoking was still not a significant risk factor for CMH. It is possible that the extensive and longstanding smoking history in patients with COPD has resulted in irreversible airway damage which constitutes an overwhelming important contributor to CMH, more so than the current smoking status.

Occupational exposures

The ALOHA+ JEM assigns exposures to gases and fumes as well as exposures to mineral and biological dusts. Exposure to gases and fumes includes exposures to aromatic, chlorinated and other solvents, to heavy metals and to all pesticides, which were also additionally separately allocated. Exposure to heavy metals contributes also to exposure to mineral dust. In our study, occupational exposures like mineral dust, gases and fumes, chlorinated solvents and heavy metals are significantly contributing to CMH in persons without COPD, but not at all in patients with COPD.

Online supplementary table S7 shows how this is related to findings in the literature published since 2000, reporting risk factors for CMH including occupational exposures, demographic characteristics and smoking habits in the general population. Of importance, we have not found any study in general populations that performed stratified analyses for COPD status combined with detailed information on occupational exposures (JEM), and our findings are new in this respect.

Given the low numbers of patients with COPD in the general population, results of the above mentioned studies will be driven primarily by persons without COPD. This makes the results of these population-based studies comparable to our results in persons without COPD. However, a considerable variation in the definitions used for CMH or chronic bronchitis (CB), and in definitions for (extent of) occupational exposures complicates comparisons.

Comparison of studies is further complicated by differences in age between populations, differences in habits (exposure in home caused by cooking) belonging to a continent, the registration of exposure (lifetime vs last job, self-reported vs a JEM).

Notwithstanding this, some studies have found an association between CMH and exposure to gases and fumes, and most studies have not found an association between CMH and biological dust, similar to our results.

The significant associations between CMH and low or high exposure to mineral dust, and between CMH and high exposure to heavy metals (separately) we found, were not found in other studies.

Since there are differential effects of occupational exposures on CMH in persons with and without COPD, the question arises whether the pathophysiology of CMH is different as well. This clearly needs further study into differences given the composition, tenacity, viscosity and produced volume of sputum, as well as the type and level of inflammation, the involved genes and epigenetic phenomena. Furthermore, cigarette smoke causes damage from the central to the peripheral airways. This is a slow process which is accompanied by metaplasia of goblet cells and mucus hypersecretion that is located in the larger airways and also in the small airways in a later stage, accompanied by closure of the small airways and subsequently airway obstruction. It remains to be established whether occupational exposures mainly affect the larger airways in persons without COPD, yet with similar symptoms of CMH as occurring in smoking-related COPD.

The strength of this study is that we had access to a large population, with a very wide age range and a considerable number of people with airflow limitation, which allowed us to study risk factors for CMH in people with and without COPD, separately. A limitation is the lack of information about lifetime occupational exposure since we had information about occupational exposures during the current or last job only. Symptomatic individuals might have left jobs with exposures to occupational exposures before (early) retirement. However, an additional analysis in which unemployed and retired people were excluded contradicts the possibility of selective avoidance of hazardous occupational exposures; patients with COPD had a similar or even higher prevalence of occupational exposures in their current job than persons without (19% had exposure to mineral dust in non-COPD vs 24.4% in COPD, for gases and fumes being 39.9% and 44.9%, respectively (results not shown)).

Comparison of provided reasons for unemployment in non-COPD and COPD revealed that the mean age in the COPD-group was considerably higher explaining the higher number of persons who were retired or preretired in this group. The percentage of persons who were incapable of working was comparable in both groups.

We believe that through legislation and awareness of the danger of these exposures, people are nowadays less exposed. We hypothesise that with using current or last held job, we have under, rather then over estimated the association between occupational exposures or ETS and risk for CMH. Clearly, studies including information on lifetime (cumulative) exposure are desirable to confirm the effects found.

Conclusion

We conclude that occupational exposures contribute differentially to CMH in persons with and without COPD. In patients with established COPD only the number of pack-years smoked is associated with an increased risk for CMH, and occupational exposures do not contribute. By contrast, high occupational exposure to gases and fumes (among which solvents, all pesticides and heavy metals) is an important driver of CMH in patients without airflow limitation, next to pack-years smoking.

References

Supplementary materials

  • Supplementary Data

    This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

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Footnotes

  • Collaborators LifeLines cohort study: BZ Alizadeh: Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands; RA de Boer: Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands; H M Boezen: Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands; M Bruinenberg: the LifeLines cohort study, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands; L Franke: Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands; P van der Harst: Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands; HL Hillege: Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands; Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands; MM van der Klauw: Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands; G Navis: Department of Internal Medicine, Division of Nephrology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands; J Ormel: Department of Psychiatry, University of Groningen, University Medical Center Groningen, Interdisciplinary Center of Psychopathology of Emotion Regulation (ICPE), Groningen, The Netherlands; DS Postma: Department of Pulmonology, University of Groningen, University Medical Center Groningen, Groningen The Netherlands; JGM Rosmalen: Department of Psychiatry, University of Groningen, University Medical Center Groningen, Interdisciplinary Center of Psychopathology of Emotion Regulation (ICPE), Groningen, The Netherlands; JP Slaets: University of Groningen, University Medical Center Groningen, University Center for Geriatric Medicine, Groningen, The Netherlands; H Snieder: Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands; RP Stolk: Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands; BHR Wolffenbuttel: Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands; C Wijmenga: Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.

  • Contributors AED participated in the study design, analysis and interpretation of the data, and drafting of the manuscript, tables and figures. KdJ, HMB, DSP, HJG and JMV obtained funding, determined the study design, participated in the analysis and interpretation of data, and critically supervised writing of the manuscript. HK and RV designed and provided the ALOHA+ JEM and participated in writing of the manuscript. All authors approved the final version of the manuscript.

  • Funding The LifeLines cohort study was sponsored by the Dutch ministry of Health, Welfare and Sport, the ministry of Economic Affairs, Agriculture and Innovation, the province of Groningen, the European Union (regional development fund), the Northern Netherlands Provinces (SNN), the Netherlands Organisation for Scientific Research (NWO), University Medical Center Groningen (UMCG), University of Groningen, de Nierstichting (the Dutch Kidney Foundation), and the Diabetes Fonds (the Diabetic Foundation).

  • Competing interests The University of Groningen has received money for professor Postma regarding an unrestricted educational grant for research from AstraZeneca, GSK. Fees for consultancies by professor Postma were given to the University of Groningen by AstraZeneca, Boehringer Ingelheim, Chiesi, GSK, Nycomed and TEVA. Fees for consultancies by professor Groen were given to the University of Groningen by Roche, Eli Lilly and Pfizer. Fees for consultancies by professor Kromhout were given to the University of Utrecht by the Norwegian Government.

  • Patient consent Obtained.

  • Ethics approval The Dutch Ministry of Health and the Medical Ethics Committee of the hospital approved the study protocol. Ethics approval and informed consent was obtained from all participants in all studies participating.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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