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Original article
Cross-shift and longitudinal changes in FEV1 among wood dust exposed workers
  1. Gitte Højbjerg Jacobsen1,2,
  2. Vivi Schlünssen1,
  3. Inger Schaumburg3,
  4. Torben Sigsgaard1
  1. 1Department of Public Health, Section of Environmental and Occupational Medicine, Aarhus University, Aarhus, Denmark
  2. 2Department of Occupational Medicine, Herning Hospital, Herning, Denmark
  3. 3Neuro Centre, Aarhus University Hospital, Aarhus, Denmark
  1. Correspondence to Dr Gitte Højbjerg Jacobsen, Department of Occupational Medicine, Herning Hospital, Gl. Landevej 61, 7400 Herning, Denmark. gitte.jacobsen{at}dadlnet.dk

Abstract

Objectives Acute lung function (LF) changes might predict an accelerated decline in LF. In this study, we investigated the association between cross-shift and longitudinal changes in forced expiratory volume in 1 s (FEV1) among woodworkers in a 6-year follow-up study.

Methods 817 woodworkers and 136 controls participated with cross-shift changes of FEV1 at baseline and FEV1 and forced vital capacity at follow-up. Height and weight were measured and questionnaire information on respiratory symptoms, employment and smoking habits was collected. Wood dust exposure was assessed from 3572 personal dust measurements at baseline and follow-up. Cumulative wood dust exposure was assessed by a study-specific job exposure matrix and exposure time.

Results The median (range) of inhalable dust at baseline and cumulative wood dust exposure was 1.0 (0.2–9.8) mg/m3 and 3.8 (0–7.1) mg year/m3, respectively. Mean (SD) for %ΔFEV1/workday and ΔFEV1/year was 0.2 (6.0)%, and −29.1 (41.8) ml. Linear regression models adjusting for smoking, age, height and weight change showed no association between cross-shift and annual change in FEV1 among woodworkers or controls. Including different exposure estimates, atopy or cross-shift change dichotomised or as quartiles did not change the results.

Conclusions This study among workers exposed to low levels of wood dust does not support an association between acute LF changes and accelerated LF decline.

  • Cross-shift lung function changes
  • occupational

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What this paper adds

  • Studies have associated wood dust to both acute cross-shift changes and accelerated decline in lung function (LF).

  • Furthermore, studies among workers exposed to organic dust have suggested cross-shift changes in lung forced expiratory volume in 1 s to be predictive of accelerated decline in LF.

  • Cross-shift changes in LF do not predict an accelerated decline in LF.

  • Cross-shift change in LF cannot be used to predict longitudinal changes in LF among woodworkers.

Introduction

Exposure to wood dust is common in the European Union, where approximately 3.6 million are occupationally exposed.1 Occupational exposure to wood dust has long been associated with respiratory symptoms, including asthma, chronic bronchitis, bronchial hyper-reactivity,2 cross-shift decline in forced expiratory volume in 1 s (FEV1)3–5 and decreased lung function (LF).6–10 Most studies have been cross-sectional, and no studies have previously studied the effect of cross-shift changes in LF on longitudinal changes among workers exposed to dry wood dust.

An accelerated decline in LF when exposed to wood dust could theoretically be caused by repeated cross-shift declines in FEV1 maintaining an increased level of airway responsiveness.11

If an accelerated decline in LF could be predicted from cross-shift changes this could be used to monitor the effect of changes in the work environment.

In this cohort, we have previously reported a dose–response relationship between wood dust exposure and cross-shift decline in FEV1 among woodworkers, and for female workers a dose–response relationship between cumulative wood dust exposure and longitudinal decline in LF.5 ,10

An association between cross-shift decline in LF indices and subsequent decline in LF has been studied in other industries comprising grain workers,12 ,13 wood trimmers,14 textile workers15–18 and swine confinement workers,19 related to exposure to grain dust, cotton dust,15–18 mold spores14 and endotoxins.18 ,19

The aim of the present study was to investigate a possible relationship between acute cross-shift change in LF and accelerated decline in LF in a population of woodworkers and controls in order to elucidate whether cross-shift changes could predict chronic LF changes.

Materials and methods

Study population

The baseline study population was identified in a cross-sectional study performed between 1997 and 1998 which is described elsewhere.20 In brief, 86 factories situated in Viborg County with more than four employees were identified. All factories with more than 20 employees were asked to participate (45 of 48 accepted), and additionally a random sample of factories with 5–20 employees (9 of 38) was drawn. A total of 54 factories participated in the study. The study population comprised dayshift workers employed in the woodworking departments, assembly departments and stock departments of these factories. Control workers were selected from three factories in the same area (two producing refrigerators and one producing hearing aids) where only mechanical assembly was performed.

A total of 1.301 woodworkers and 215 controls returned a questionnaire and participated with valid cross-shift LF tests at baseline and were defined as the baseline population for follow-up. Or alternatively: A total of 1.301 woodworkers and 215 controls participated with a questionnaire and a valid cross-shift LF at baseline and were defined as the baseline population at follow-up. Follow-up took place from 2003 to 2005. Visits to 52 furniture factories (38 participated at baseline) and three control factories resulted initially in contact with 635 persons from the exposed group and 120 controls. The remaining subjects were contacted by letter and invited to a follow-up examination. In total, 817 woodworkers (63%) and 136 controls (63%) participated at follow-up. A flowchart of the study is shown in figure 1.

Figure 1

Flowchart of study population.

All participants gave informed consent, and the protocol has been approved by the Ethics Committee for Viborg County, Denmark.

Exposure assessment

Personal dust samplings were carried out at baseline and follow-up with passive dust monitors described earlier.21 ,22 In summary, the method is based on measuring light extinction before and after sampling on transparent sticky foils, reported as dust covered foil area and converted to equivalent inhalable dust by linear regression models based on earlier and actual calibration measurements.21–23 In order to calculate cumulative wood dust exposure in the follow-up period, job exposure matrices based on factory size and task were constructed at baseline and at follow-up. The groupings were based on random effect analyses, where grouping by task and factory size achieved the greatest contrast between the groups.5 ,24

A modified British Medical Research Council questionnaire,25 including key The European Community Respiratory Health Survey questions on asthma,26 with additional questions on allergy, coughing, asthma, rhinitis, smoking and occupational history including work tasks was distributed at baseline and follow-up.20

Individual cumulative exposure was estimated from the exposure level at baseline for half the period (until 2001) and the exposure level at follow-up for the remaining period.

Smokers were defined as current smokers and ex-smokers, who stopped smoking less than 2 years prior to the baseline.

Measurements of LF

Pulmonary function testing was performed using a dry spirometer (Vitalograph, Buckingham, UK) according to European Respiratory Society guidelines for standardisation of spirometry.27 The same spirometer was used for all measurements at baseline and follow-up. All measurements were conducted by the same research group of three individuals. FEV1, forced vital capacity (FVC), height and weight were measured. At baseline 98.4% and at follow-up 99.7% was acceptable and included in the analyses. At baseline, preshift and cross-shift values were measured at the workplace, and 297 subjects had an additional LF at a later clinical examination at the hospital. At follow-up, preshift values were measured at factories and the remaining part of the cohort, not working at one of the factories, were invited to a LF test. A total of 69 subjects had an additional LF test at a later clinical examination at the hospital.

The highest FVC and FEV1 at baseline were used to calculate percentage of pred. (predicted) values at baseline. As a reference, we used the Danish standards for age 30 years and above supplied by the Danish Society of Lung Physicians,28 and a Danish reference material among healthy, non-smoking farming students29 for the group between 15 and 29 years.

Percentage cross-shift change in FEV1 at baseline was calculated as FEV1 postshift minus FEV1 preshift divided by FEV1 preshift.

During follow-up, change in FEV1 was calculated as FEV1 max at follow-up minus FEV1 max at baseline and reported as change per year. The same procedure was followed for FVC.

Blood sampling was performed on a subpopulation at follow-up. Atopic status was available for 625 woodworkers and 108 controls and was defined as a positive phadiatop (specific immunoglobulin E to any one of 12 common allergens).30

Analysis

When data were normally distributed, mean±SD is reported, otherwise the median (range) is reported. Univariate analyses and analyses stratified by sex and smoking were undertaken for categorical variables using χ2 test. For continuous variables, independent-sample t tests or the Mann–Whitney U-test was used. In further analyses, association between cross-shift changes in FEV1 and longitudinal changes in FEV1 and FVC were analysed using multiple linear regression models adjusting for potential confounders (smoking, age, sex, height, weight gain and atopy). In analyses adjusting for smoking, smoking was expressed as pack-years in the follow-up period. For smokers the median follow-up time was 6.3 years; therefore, 7 pack-years were chosen as the cut-off point between light and heavy smokers.

When data on a variable were missing in an analysis, the observation with missing data was excluded, which led to a varied number of subjects across variables.

Unless otherwise stated, a significance level of 5% was used.

Results

Participants versus non-participants

A flowchart of the study is shown in figure 1. At baseline, participants were slightly older compared with non-participants for woodworkers (39.0±12.2 vs 36.3±12.2 years; p<0.001) and for controls (38.9±9.7 vs 35.7±10.5 years; p=0.02). More non-participants were smokers at baseline compared with participants for woodworkers (49.3% vs 40.7%; p=0.001) and for controls (54.1% vs 45.9%; p=0.06). Non-participants tended to have lower LF expressed as FEV1% pred. (97.5% vs 99.0%; p=0.02) compared with participants for the total cohort (97.4% vs 98.8%; p=0.06), for woodworkers and (97.9 vs 100.5; p=0.14) for controls. No differences were revealed for cross-shift changes in FEV1 and when analyses were repeated stratified on smoking no differences in LF were revealed between participants and non-participants. In addition, non-participants tended to report at least one respiratory symptom at baseline more often than participants, significant for woodworkers (48.1% vs 40.9%; p=0.02), but similar for controls (49.3% vs 38.5%; p=0.14). No differences were observed for chronic bronchitis or self-reported asthma. No significant difference in baseline wood dust exposure was revealed between participants and non-participants.

A higher percentage of both woodworkers and controls contacted at the factories participated compared with workers invited by letter (figure 1).

Analyses for differences between participating woodworkers invited outside the factories compared with woodworkers at the factories revealed the former to have a significantly higher percentage of hay fever (16.7% vs 11.4%) and any respiratory symptom (47.0% vs 38.0%), including wheeze (20.5% vs 13.2%) at baseline, but revealed no differences in other respiratory symptoms (self-reported asthma, daily coughing and chronic bronchitis), smoking habits or LF expressed as FEV1% pred. or percentage cross-shift change in FEV1 at baseline.

A greater percentage of controls contacted outside the factories versus controls at the factories reported bronchitis at baseline (23.3% vs 4.4%) and lower FEV1% pred. at baseline (99.1% vs 101.6%) along with a higher percentage of smokers (65.6% vs 44%; p=0.03). No differences in other respiratory symptoms, hay fever or percentage cross-shift change in FEV1 were found.

Demographics of participants

Fewer woodworkers were female subjects compared with controls, and woodworkers tended to smoke less. Among the female woodworkers significantly fewer heavy-smokers (>7 pack-years during follow-up) were found compared with controls workers and female compared with male woodworkers had lower (p<0.01) median of cumulative wood dust exposure. No significant differences were found in baseline symptoms or atopy between exposed workers and controls or between male and female subjects, although male subjects tended to be more atopic than female subjects (table 1).

Table 1

Demographic characteristics of the cohort

Lung function

Table 2 summarises cross-shift and longitudinal changes in FEV1 and FVC stratified by sex and smoking. No significant differences were seen between woodworkers and controls of either sex. Smokers tended to have a greater cross-shift increase in FEV1 and a greater longitudinal change in FEV1 and FVC, significant for male subjects. For all workers, longitudinal changes in FEV1 were negative with mean (SD) of −29.1 (41.8) ml/year and mean cross-shift changes in FEV1 were positive (mean 0.70±212 ml). A total of 11.3% had a cross-shift change of more than 5%, with no differences between exposed and controls, male and female subjects, or smokers and non-smokers.

Table 2

Changes in lung function of woodworkers and reference workers at baseline and follow-up stratified by sex and smoking

We found no correlation between cross-shift and longitudinal changes in FEV1. The correlation coefficient was −0.06, R2 0.004, p=0.07.

Table 3 presents the results of multiple linear regression analysis for the association between relative cross-shift change in FEV1 and absolute longitudinal change in LF stratified by sex and adjusted for smoking, age, height, weight gain and cumulative wood dust exposure. For female subjects, no association was revealed, but a borderline association was found for male subjects. For female subjects, a negative association between cumulative wood dust exposure and annual change in FEV1 was revealed; the regression coefficient was −2.95 ml/year. As expected, smoking was related to decline in LF, most pronounced for heavy smokers, where significant negative regression coefficients were found in all strata.

Table 3

Multiple linear regression models on longitudinal changes in LF stratified by sex including cross-shift changes in FEV1, cumulative wood dust exposure and smoking as independent variables

Further regression analyses for the association between relative cross-shift FEV1 change and longitudinal change in LFs were performed including different estimates on wood dust exposure (exposure status at baseline, log baseline exposure, quartiles of baseline exposure and quartiles of cumulative exposure) as well as analyses including atopy at follow-up for the subgroup of workers where atopic status was available. In addition, analyses including cross-shift decline as a dichotomous variable (±5% decline; <5% decline) and as quartiles of cross-shift decline were performed as well as analyses on relative longitudinal annual LF changes. None of the additional analyses changed the results substantially. For female workers, the analyses including quartiles of cumulative exposure revealed a negative association between the highest level of cumulative wood dust exposure above 4.76 mg year/m3 and longitudinal changes in FEV1 (not shown). For male subjects, a tendency of positive associations between relative cross-shift change and longitudinal change in FEV1 was found across all analyses.

Table 4 presents the regression analyses stratified on wood dust exposure, smoking and atopy for the association between relative cross-shift change in FEV1 and annual changes in FEV1 and FVC. The results from table 3 were confirmed, and no significant associations were revealed in any of the analyses.

Table 4

Association between longitudinal changes in LF and cross-shift change in FEV1 stratified by wood dust exposure, smoking, atopic status and place of participation adjusted for confounders in linear regression analyses

In order to investigate the influence on participation on the factories as opposed to participation outside the factories, regression analyses were repeated including place of participation. Analyses stratified on participation place showed similar non-significant regression coefficients for relative cross-shift change in FEV1 on longitudinal changes (table 4), but when the participation place was included in the model, a negative association between participation at the factory and longitudinal LF changes were seen. For annual change in FEV1 the regression coefficient was −12.9 ml/year (p<0.001) and for annual change in FVC it was −13.6 ml/year (p<0.001).

Discussion

To the authors’ knowledge, the present study is the first study in the dry wood industry that investigates the possible association between cross-shift change in FEV1 and subsequent longitudinal decline in LF.

In contrast to previous studies among workers exposed to organic dust including wood dust, the results from this study in a cohort of workers exposed to relatively low concentration of wood dust do not support cross-shift changes in FEV1 to be predictive of an accelerated decline in LF. In the wood industry, only a small study has been performed by Dahlqvist and Ulfvarson. In a 27-month follow-up study of 15 wood trimmers compared with 26 sawmill workers they measured cross-week changes in FEV1 and viable mould spores, but not wood dust or endotoxin exposure. They found a correlation between cross-week and longitudinal changes in FEV1 for non-smoking wood trimmers.14

The association between acute and chronic LF changes has been most intensely studied in the textile industry. More results have been published from a 20-year follow-up study of 418 cotton workers and 417 silk workers from Shanghai textile mills. In the initial 5-year follow-up survey, the authors reported a cross-shift decline in FEV1 of more than 5% to be strongly predictive of a subsequent 5-year decline in FEV1 among cotton workers.15 The mean change in FEV1 was negative for cotton workers as well as for silk workers, and a total of 23.6% of cotton workers versus 13.2% of silk workers had a cross-shift decline of more than 5% as opposed to 11.3% in our study. The difference in cross-shift changes between cotton workers and silk workers was confirmed in further follow-ups of the cohort at approximately 5-year intervals. In addition, they reported that cotton dust was associated with an extra 10 ml/year in cotton workers, but not among silk workers, and that individuals with two or more cross-shift drops had significantly larger annual decline in FEV1.18

Another 5-year follow-up study of cotton workers with different work shifts in the USA reported a negative association between a 200 ml cross-shift drop and longitudinal change in FEV1 of 11.2, −34.6 and −35.4 ml/year for shifts 1, 2 and 3, respectively.17

In addition, a 2.5-year follow-up study of 587 Canadian grain workers and 111 civic workers reported annual decline in LF to be correlated to cross-week and cross-shift changes in LF at baseline.13 This was confirmed in a 6-year follow-up study of 267 Canadian grain workers, especially among current and ex-smokers.12 ,31

In a 5-year follow-up study of 98 swine confinement workers with mean cross-shift changes in FEV1 of −160 ml and an annual change of −54 ml, the authors reported baseline cross-shift change in FEV1 and endotoxin exposure along with smoking and age as significant determinants of annual change in FEV1.19

The current study is well powered compared with earlier studies on, for example, wood trimmers,14 grain workers12 ,13 and farmers19 with the number of participants between 30 and 270, supporting our negative finding to be true. Though, an alternative reason for the negative results in this study may be the relatively small changes in cross-shift FEV1. In accordance with other studies,17 the overall cross-shift change of dayshift workers in this study was positive due to the circadian rhythm. It cannot be ruled out that a greater cross-shift decline in FEV1 at higher wood dust exposures than found in the Danish Furniture industry could influence the change in longitudinal LF indices in the same way as found among workers exposed to cotton dust and to dust and endotoxins in swine confinements.

In addition, endotoxin or other markers of microbial exposure may be of significance when considering the association between acute and chronic LF changes. Biohazards such as endotoxins and moulds in organic dust have been associated to both cross-shift decline in LF indices and an accelerated decline in FEV1. A suspected high level of endotoxin is a common feature in industries, where an association between cross-shift and longitudinal change in FEV1 has been reported.13 ,15 ,17–19 Exposure to endotoxin and moulds among woodworkers have mainly been studied for workers exposed to fresh wood, but two studies have reported endotoxin levels of importance for health effects among workers in the dry wood industry.4 ,32

In order to evaluate possible effects of endotoxins in the present study, 29 measurements of endotoxin were performed on wood dust measurements from three factories participating in the study using the kinetic limulus amoebocyte test. We found very low levels of endotoxins with median (range) of 0.9 (0.3–6.3) EU/m3 (unpublished data), substantially lower than the health-based recommended exposure limit of 90 EU/m3 proposed by the Dutch Expert Committee on Occupational Safety.33

We have no theoretical explanation for the borderline significant association between an increasing FEV1 during the day and a subsequent lower longitudinal decline in FEV1 for male subjects. The results are probably random, but may be partly due to the data not being sufficiently adjusted for smoking. In addition, one could speculate that non-work related allergens might influence some workers with increased bronchial lability to have a steeper increase in FEV1 during the working hours and at the same time result in a greater decline in longitudinal LFs; however, we find no evidence for this lability to be related to wood dust exposure.

The overall participation rate in the follow-up study was 63%, which may have caused selection bias. The dropout analyses showed a higher drop-out rate for both woodworkers and controls not employed at the factories (figure 1). This may contribute to a healthy workers selection in the cohort, as individuals who experience respiratory symptoms might be more prone to leave the industry. Non-participants were slightly younger, smoked more, and tended to have more respiratory symptoms and lower objective measures of LF at baseline compared with participants. The analyses for disparities between subjects invited outside the factories as opposed to subjects invited from the factories revealed a tendency for the former to have a higher percentage of baseline respiratory symptoms and among controls more smokers and lower objective measures of LF. However, while the longitudinal declines in LFs were higher among workers at the factories, no differences were found in baseline cross-shift changes in LF. Including the place of participation in the analyses for change in longitudinal LFs did not change the size or the direction of the influence of cross-shift changes in FEV1. The analyses were stratified or adjusted for sex and other relevant confounders including smoking. Therefore, it is unlikely that selection bias had a major influence on the result.

In conclusion, our study among workers exposed to low levels of dry wood dust does not support an association between acute and chronic decline in LF.

References

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Footnotes

  • Funding This work has been funded by the Danish Work Environment Foundation, grant number 2002–23, the Danish Medical Research Council, grant numbers 22-02-0328 and 271-05-0570 and The Danish Health Insurance Fund, grant numbers 2002B133 and 2005B051.

  • Competing interests None.

  • Ethics approval Ethics approval was provided by the Ethics Committee for Viborg County, Denmark.

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

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