Physiological and psychosocial occupational exposures and intermediate health outcomes in
the general population
Faruque, Md Omar
DOI:10.33612/diss.154938193
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Publication date: 2021
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Faruque, M. O. (2021). Physiological and psychosocial occupational exposures and intermediate health outcomes in the general population. University of Groningen. https://doi.org/10.33612/diss.154938193
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Chapter 7
Summary, general discussion, and future perspectives
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SUMMARY
In chapter 1, we described different types of occupational exposures (i.e.
physiological and psychosocial exposures) and advanced methods (i.e. Job exposure matrix: JEM) to measure these exposures. We further introduced our study outcomes that include lung function, inflammatory biomarkers, blood pressure, and sickness absence. Additionally, we introduced our study population, i.e. the large-scale population-based Lifelines Cohort Study. Finally, we provided the aim of the thesis, the specific research questions, and the outline of the thesis.
In chapter 2, we investigated the cross-sectional association between
occupational exposures estimated with ALOHA+ JEM and sickness absence, the mediating role of respiratory symptoms, and whether genetic susceptibility to sickness absence upon occupational exposures exists in the population-based Lifelines Cohort Study. In this first study of its kind, we found that exposures to gases/fumes, solvents, and metals were associated with a higher prevalence of long-term sickness absence. In addition, chronic cough and chronic phlegm mediated the association between gases/fumes exposure and long-term sickness absence. Furthermore, several candidate single nucleotide polymorphisms (SNPs) modified the association between exposures and sickness absence.
In chapter 3, we examined the association between occupational exposures
(estimated with the ALOHA+JEM) and lung function level and annual lung function decline in the population-based Lifelines Cohort Study. Consistent with previous studies, the study showed that exposure to biological dust, mineral dust, gases/fumes, insecticides, fungicides, and aromatic solvents was associated with a lower lung function level. The effects were larger in males compared to females and in smokers compared to non-smokers. In the longitudinal analyses, exposure to biological dust was associated with a faster
annual decline of FEV1. However, exposure to mineral dust and gases/fumes
was associated with a slower annual decline of FEV1/FVC.
In chapter 4, we explored the association between occupational exposures
(allergens, reactive chemicals, pesticides, and micro-organisms), estimated with the Asthma specific JEM, and levels of and changes in inflammatory biomarkers (C reactive protein (CRP), eosinophils, and neutrophils). In this study, we found a significant cross-sectional association between exposure to allergens, reactive chemicals, and micro-organisms, and a lower CRP level. Exposure to allergens, reactive chemicals, pesticides, and micro-organisms was associated with lower
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neutrophil counts. No association between occupational exposures and
eosinophil counts was found. In the longitudinal analyses, no association between occupational exposures and changes in inflammatory biomarkers was found.
In chapter 5, we investigated the longitudinal association between occupational
exposures (estimated with the ALOHA+JEM) and the risk to develop respiratory symptoms (chronic cough, chronic sputum, chronic bronchitis) and airway obstruction in the Lifelines Cohort Study. High exposure to biological dust at baseline was associated with a higher risk to develop chronic cough and chronic bronchitis after a median follow-up of 4.5 years. High exposure to pesticides was associated with a higher risk to develop chronic cough, chronic sputum, chronic bronchitis, and airway obstruction. The associations between biological dust and the development of respiratory symptoms disappeared after adjustment for co-exposures while pesticides exposure remained significantly associated with respiratory outcomes.
In chapter 6, we assessed the cross-sectional association between
psychosocial work factors (estimated with job strain, effort-reward imbalance (ERI), and emotional demands JEMs) and blood pressure in the Lifelines Cohort Study. We further investigated whether the associations differed between males and females. We found that higher job strain was associated with a higher systolic blood pressure (SBP) and a higher diastolic blood pressure (DBP), and with a higher prevalence of hypertension (defined as SBP ≥140 mm Hg or DBP ≥90 mm Hg or self-reported use of antihypertensive medication). Higher ERI was associated with a higher DBP, but not with higher SBP or the prevalence of hypertension. Contrary to our expectation, higher emotional demands were associated with a lower SBP and a lower prevalence of hypertension.
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GENERAL DISCUSSION
In this thesis, in a large general working population from the Lifelines Cohort Study, occupational exposures were associated with a lower level of lung function and a higher risk to develop respiratory symptoms and airway obstruction (Table 1). In addition, several of the investigated occupational exposures were associated with a higher prevalence of sickness absence, especially with long-term sickness absence. Furthermore, occupational exposures were associated with a lower level of inflammatory biomarkers. High job strain was associated with a higher systolic blood pressure (SBP), a higher diastolic blood pressure (DBP), and a higher prevalence of hypertension, while high effort-reward imbalance (ERI) was associated with a higher DBP.
PHYSIOLOGICAL EXPOSURES AND HEALTH OUTCOMES Biological dust
We found that occupational exposure to biological dust was consistently associated
with lung function impairment (which is indicated by a lower level of FEV1,
FEV1/FVC, and FEF25-75 at baseline) and a faster FEV1 decline during follow-up. In
addition, exposure to biological dust was associated with a higher risk to develop respiratory symptoms (chronic cough and chronic bronchitis). However, this association disappeared when we adjusted for co-exposures. In these multi-exposure analyses, only the effect of pesticides multi-exposure remained significant. We observed that all the workers, who were exposed to pesticides (e.g. crop growers, gardeners, animal producers, and laborers in agriculture and forestry) were also exposed to biological dust, but not all biological dust exposed workers were exposed to pesticides (e.g. fiber preparers, weavers, knitters, and paper-making plants operators). We examined the association between exposure to biological dust and the development of respiratory symptoms among these subjects who were exposed only to biological dust but not to pesticides. The analyses showed no significant association between biological dust exposure and the development of respiratory symptoms.
161 O cc up at io na l ex po su re s Lu ng fu nc tio n le ve l Lu ng fu nc tio n de cl in e In ci de nc e of R S In ci de nc e of A O Si ck ne ss ab se nc e In fla m m at or y bi om ar ke rs B lo od p re ss ur e FE V- 1 FE V- / 1 FV C † FE F -25 -7 5 FE V- 1 FE V- / 1 FV C † FE F -25 -7 5 C hr . co ug h C hr . ph le gm C hr . br on ch iti s FE V1 / FV C ‡ An y SA LT SA C R P Eo s. N eu . SB P D BP H TN B io lo gi ca l d us t Lo w e xp os ur e ↓ ↓ — — — — — — H ig h ex po su re ↓ ↓ ↓ ↓ ↑ ↑ ↓ — — — — — — M in er al d us t Lo w e xp os ur e ↓ ↓ ↓ ↑ ↓ — — — — — — H ig h ex po su re ↑ — — — — — — G as es a nd fu m es Lo w e xp os ur e ↓ ↓ — — — — — — H ig h ex po su re ↓ ↑ ↑ — — — — — — Pe st ic id es ϴ Lo w e xp os ur e — — — — — — ↓ — — — — — — H ig h ex po su re — — — — — — ↑ ↑ ↑ ↑ — — — — — — In se ct ic id es Lo w e xp os ur e ↓ ↓ ↓ — — — — — — — — — — — — H ig h ex po su re — — — — — — — — — — — — H er bi ci de s Lo w e xp os ur e — — — — — — — — — — — — H ig h ex po su re ↑ — — — — — — — — — — — — Fu ng ic id es Lo w e xp os ur e ↓ ↓ ↓ — — — — — — — — — — — — H ig h ex po su re — — — — — — — — — — — — So lv en ts Lo w e xp os ur e — — — — — — ↑ ↑ — — — — — — H ig h ex po su re — — — — — — — — — — — — Ar om at ic so lv en ts Lo w e xp os ur e ↓ — — — — — — — — — — — — H ig h ex po su re ↓ — — — — — — — — — — — — C hl or in at ed so lv en ts Lo w e xp os ur e — — — — — — — — — — — — H ig h ex po su re — — — — — — — — — — — — O th er s ol ve nt s Lo w e xp os ur e ↑ ↓ — — — — — — — — — — — — H ig h ex po su re — — — — — — — — — — — — M et al s Lo w e xp os ur e ↑ — — — — — — H ig h ex po su re ↑ ↑ — — — — — — Al le rg en s — — — — — — — — — — — — ↓ ↓ — — — R ea ct iv e ch em ic al s — — — — — — — — — — — — ↓ ↓ — — — Pe st ic id es ⊗ — — — — — — — — — — — — ↓ — — — M ic ro -o rg an is m s — — — — — — — — — — — — ↓ ↓ — — — Jo b st ra in — — — — — — — — — — — — — — — ↑ ↑ ↑ Ef fo rt -r ew ar d im ba la nc e — — — — — — — — — — — — — — — ↑ Em ot io na l de m an ds — — — — — — — — — — — — — — — ↓ ↓ R S= R es pi ra to ry s ym pt om s; A O =A irw ay o bs tru ct io n; F EV 1 =F or ce d ex pi ra to ry v ol um e in o ne s ec on d; F VC = Fo rc ed v ita l ca pa ci ty ; FE F 25 -7 5 =f or ce d ex pi ra to ry f lo w , m id ex pi ra to ry p ha se ;; C hr =C hr on ic ;;L T( SA )= Lo ng -te rm si ck ne ss ab se nc e; C R P= C re ac tiv e pr ot ei n; Eo s= Eo si no ph il; N eu =N eu tro ph il; SB P= Sy st ol ic bl oo d pr es su re ; D BP =D ia st ol ic bl oo d pr es su re ; H TN =H yp er te ns io n; † =C on ve nt io na l; ‡= Lo w er li m it of n or m al ; ϴ =A LO H A+ jo b ex po su re m at rix ; ⊗ = O cc up at io na l a st hm a-sp ec ifi c jo b ex po su re m at rix. Ta bl e 1: S um m ar y of a ss oc ia tio ns b et w ee n oc cu pa tio na l e xp os ur es a nd in te rm ed ia te h ea lth o ut co m es in th is th es is .
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Thus, we assume that the association between exposure to biological dust and respiratory outcomes was confounded by exposure to pesticides. Interestingly, most previous population-based studies that reported that exposure to biological dust was associated with lung function impairment, did not adjust their analyses for co-exposures (1–3). Therefore, the health effect of biological dust in those studies might not be independent of concurrent other occupational exposures (i.e. pesticides). Importantly, by the time of writing our paper on the association between occupational exposures and lung function level and decline (Chapter 3) we also did not perform a exposure analysis. Now we have performed the co-exposures analyses and found no independent effect of exposure to biological dust on lung function impairment, indicating that indeed the effect of biological dust exposure is confounded by other exposures (i.e. pesticides).
In the occupational asthma-specific job-exposure matrix (OAsJEM), there is no specific category for exposure to biological dust. However, the OAsJEM contains two biological exposure components, i.e. allergens (animals, flour, house dust mites, storage mites, plant mites, enzymes, latex, and fish) and micro-organisms (moulds and endotoxin). Counterintuitively, we found an inverse association between exposure to biological dust (based on these 2 components in the OAsJEM) and inflammatory biomarkers at baseline and no association at follow-up. The disappearance of the association between exposure to biological dust and lung function impairment and the development of respiratory outcomes after adjustment for co-exposures and an inverse association with any sickness absence thus indicate that biological dust might not be an independent occupational harmful agent in our study population.
Pesticides
In this thesis, we found that exposure to pesticides and its components (insecticides and fungicides) was consistently associated with a lower lung function level and a higher risk to develop respiratory symptoms. These findings are in line with our earlier studies (4–6) and recent systematic literature reviews in which the deleterious effect of pesticides exposure on respiratory health was discussed (7,8). In the general population-based Vlagtwedde-Vlaardingen study, we observed the deleterious effects of pesticides exposure on lung function decline after 25 years of follow-up (1965-1989). In the European Union, the guidelines on pesticides were first legislated in 1979. In the 70s and 80s, dinitrophenoles (DNOC, Dinoseb, Dinoterb), dithiocarbamates (Thiram, Maneb), and chlormequat were the most used pesticides in the Netherlands. Many of these (i.e. DNOC, Dinoseb, and Thiram) were recognized as dangerous for health and subsequently were banned in the ‘90s. Yet, in this thesis which investigated subjects from 2006 to 2017, we
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found that pesticides exposure still negatively affects respiratory health in our study population. The pesticides that are allowed to be used under the current legislation are still toxic enough to impair lung function. In addition, current policies and legislation on pesticides may still not be adequate to protect the workers from the adverse health effects of pesticides. We have to bear in mind that our older study subjects might have been exposed to pesticides long ago when strict regulations on pesticides application were not implemented. The effects we observe now are thus not only because of current exposure but also because of previous exposure to the more toxic pesticides.
Workers such as crop growers, gardeners, animal producers, and laborers in agriculture and forestry are exposed to pesticides and its components routinely in their workplace. Although the proportion of the global population involved in agriculture decreased over the years (44% in 1991 compared to 28% in 2018), still about 1 billion people work in agriculture. In developed countries such as the Netherlands, strict occupational safety and health guidelines have been implemented to protect workers. In addition, the percentage exposed in the Netherlands is presumably lower than globally, because the number of people engaged in agriculture is rather low. Despite this we still found a pronounced adverse effect of pesticides exposure on respiratory health among workers. In line, previous studies conducted in developing countries like India (9,10), Pakistan (11,12), Iran (13,14), Ethiopia (15,16), Sri Lanka (17), and Costa Rica (18) have shown a deleterious effect of pesticides on respiratory health.
Pesticides exposure may also pose health risks to subjects living near the pesticides spraying fields. Previous studies reported that subjects living near these fields had a higher prevalence of a wide range of negative health outcomes, such as birth-related outcomes (preterm birth, fetal growth restriction, and neural tube defects) (19–21), childhood cancers (e.g., leukemia and lymphomas) (22,23), cognitive impairments (e.g., autism spectrum disorders, diminished intelligence quotient (IQ)) (24,25) and Parkinson’s disease (26). Recently, in the Netherlands, the concentration of pesticides in the open air and the house dust was higher in residents closer to the pesticides spraying fields (27). In addition, the pesticides concentration in urine in neighbors living close to these fields was twice as high as in the control group (27). Future research should therefore also focus on respiratory health in subjects living near the pesticides spraying fields and should also investigate the vulnerable groups such as babies, children, and the elderly. There is growing evidence that pesticides are immunotoxic. Pesticides can impair the immune function either by decreasing immunocompetence (also known as immunosuppression) or by inappropriate immunostimulation which results in hypersensitivity and autoimmunity (28). In this thesis, we found an inverse
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association between occupational exposure to pesticides (based on insecticides, herbicides, and fungicides in the OAsJEM) and the level of neutrophils in the blood. This pesticides induced immunosuppression is supported by previous studies (29– 31). The mechanisms behind this pesticides induced immunosuppression may be immunotoxicity or endocrine disruption.
Mineral dust
We found that low exposure to mineral dust was significantly associated with lung function impairment, whereas high exposure to mineral dust was not (Chapter 3). In addition, exposure to mineral dust was not associated with the development of respiratory symptoms or airway obstruction (Chapter 6). We observed that in our study population, of the subjects that had low exposure to mineral dust, the largest group were helpers and cleaners (22.1%) followed by home-based care workers (11.0%), dairy and livestock producers (9.5%), and heavy truck and lorry drivers (7.2%). Of those with high exposure to mineral dust, 17.6% are freight handlers, 13.4% are welding related workers, 11.8% are gardeners, horticulture and nursery growers, 10% are building frame and related trade workers, and 8.8% are agricultural or industrial machinery mechanics.
Previous general population-based studies found that occupational exposure to mineral dust (estimated with the ALOHA+ JEM) was associated with a higher incidence of phlegm and COPD (3,32). In these studies, mineral dust was dichotomized into no exposure and any exposure , so we cannot see the difference in the effect between low and high exposure. Other studies specifically investigated mineral dust exposure in subjects who were engaged in mining, quarrying, or construction (e.g. quartz and asbestos exposure). These studies reported a strong association between occupational exposure to mineral dust and lung function impairment and respiratory diseases (33–37). In our study, approximately 21% of the active workers were exposed to mineral dust, and of these only 77 (0.09%) workers were construction workers and none of them were miners. This is a very low percentage of subjects in mining, quarrying, or construction industries which might explain the non-significant association we found between high exposure to mineral dust and lung function and respiratory symptoms.
Gases/fumes, solvents, and metals
We found lower lung function levels upon exposure to gases/fumes and aromatic solvents in the cross-sectional analyses but not in the longitudinal analyses. We might not have seen any effects of gases/fumes and aromatic solvents on change of lung function due to the relatively short (a median of 4.,5 years) follow-up period. Our hypothesis that in our study the follow-up period might have been too short to
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actually observe effects on lung function, is confirmed by observations of the European Community Respiratory Health Survey (ECRHS), in which significant deleterious effects of exposure to gases/fumes were shown after 20 years (38), but not yet after 9 years of follow up (39).
Exposures to gases/fumes, solvents, and metals were associated with a higher prevalence of sickness absence. Interestingly, in the co-exposures analyses, only the effect of metals remained, the effect of solvents disappeared, and the gases/fumes became protective. Metal fumes are components of gases/fumes and 91% of metals exposed subjects were also exposed to solvents. Thus, we assume that the significant associations of solvents and gases/fumes with sickness absence were confounded by metals exposure.
Exposure to metals was associated with a higher prevalence of sickness absence, but the association was not mediated by respiratory symptoms. In addition, metals exposure was not associated with lung function impairment. These findings suggest that in the Lifelines Cohort Study, metals-exposed subjects took sick leave due to symptoms or diseases other than respiratory problems. The aerodynamic diameter of metals fumes is ≤ 2 µm (40). The air particles with a diameter of ≤ 5 µm enter the deepest part of the small airways and alveoli (41). After that, it dissolves in the blood vessels of the alveoli, and subsequently, enters the main circulatory system, and may exert a deleterious effect on different organs (e.g. kidney and brain). In line, we hypothesized that most of the metals particles have entered into the circulatory system and little debris remained in the small airways to impair respiratory health. Previous studies reported that exposure to metals fumes was associated with a broad spectrum of diseases, such as keratosis, cardiovascular disease, diabetes mellitus, cancer, multiple sclerosis, Parkinson's disease, Alzheimer's disease, muscular dystrophy, liver disease, and renal dysfunction (42). Thus, we speculate that metals exposure might lead to the above-mentioned diseases, which might force workers to take sick leave. Workers, such as welders, braziers, flame-cutters, toolmakers, and metal melters are at high risk of having various negative health effects from metals exposure at the workplace.
Healthy worker effect (HWE)
In some studies, we found counterintuitive or no significant findings. A possible explanation for these unexpected findings is the “Healthy worker effect” (HWE). The HWE is a well-known important potential confounding factor in occupational epidemiology. The HWE occurs when healthy workers (who are more resilient or less susceptible to any particular exposure in a specific job) are more likely to get employment or remain employed (43). This phenomenon occurs in two phases of employment (44). In the first phase, the HWE occurs during the hiring of workers
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because some industries recruit only workers who meet certain health criteria and some workers will only apply for jobs without specific exposures. For example, a garment factory would recruit only candidates who are not sensitive to fibers or strong odors of clothes. In the second phase, after recruitment, some workers will appear to be sensitive to the exposure, and become sick. In this phase, the unhealthy workers may opt to terminate the employment or may switch to a job with less exposure. For example, the exposure (e.g. pesticides) that produces acute symptoms (e.g. cough or sneezing) would force the workers to stop the job or switch to a job with no such exposure. As a result, only the workers who did not experience negative health effects from these exposures stayed in their job. Therefore, we assume that HWE may partially cause our unexpected or null findings.
PSYCHOSOCIAL EXPOSURES AND HEALTH OUTCOMES
Apart from physiological occupational exposures (e.g. airborne exposures), it is important to study psychosocial occupational exposures because these may also adversely affect workers’ health and wellbeing. According to the International Labour Organization, psychosocial work factors (hazards) refer to “interactions between and among work environment, job content, organizational conditions and workers’ capacities, needs, culture, and personal extra-job considerations that may, through perceptions and experience, influence health, work performance, and job satisfaction (45).” An optimal balance between work environment and human factors (i.e. workers’ capacities, needs, and expectations) is preferred. A negative interaction between work conditions and human factors may result in emotional disturbances, behavioral problems, biochemical and neurohormonal changes (46). In turn, these changes may increase the risk of mental and physical illness among workers.
Workers experience various psychosocial work factors, like high job strain, effort-reward imbalance (ERI), and high emotional demands at their workplace, which may induce stress (47). The job demand-control model refers to a balance between job demands or workload and workers’ control or autonomy over it (48). Workers may experience stress at the workplace if they perceive a high workload in terms of work intensity and deadlines and have little or no choice to decide when and how to perform their tasks (48). A high ERI is present when the workers’ perceived job efforts do not match with their perceived rewards (e.g., income, promotion, or appreciation), and this imbalance may result in stress (49). Workers further may experience stress in tasks where sustained emotional efforts are required (e.g. dealing with patients with a terminal illness or aggressive customers) (47,50). In
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turn, high stress at work may lead to a broad spectrum of health impairments that include mental and behavioral disorders such as exhaustion, burnout, anxiety, and depression, as well as other physical impairments such as cardiovascular disease and musculoskeletal disorders (46).
Therefore, we hypothesized that high job strain, high ERI, and high emotional demands at the workplace may increase the risk of high blood pressure through stress. In line with our expectations, we found that high job strain and high ERI was associated with a higher blood pressure and a higher prevalence of hypertension in a large general working population. Counterintuitively, we observed that high emotional demands at work were associated with lower levels of DBP and a lower prevalence of hypertension. This unexpected finding is interesting since we hypothesized that high emotional demands may induce stress which could lead to a higher blood pressure. Our study is the first of this kind where we examined the association between emotional demands and blood pressure in a large working population. Previous studies showed a myriad of negative health outcomes (depression, psychological distress, long-term sickness absence, diabetes, sleep disorders, and arthritis) (51–55) induced by emotional demands at the workplace. One explanation of our unexpected findings could be that jobs with high emotional demands may also induce positive emotions. In our study, in the top quartile of the emotional demands, 47.6% of subjects are engaged in ’rewarding’ occupations: nurses, care workers (e.g. taking care of children, impaired old people, and disabled people; assist medical, nursing, midwifery, and dental professionals), and social work associate professionals (e.g. guide people to find and use resources to overcome difficulties and achieve particular goals). For example, social workers would feel positive when someone would overcome his/her difficulties by following their advice.
Another explanation for this association between high emotional demands and low blood pressure could be that subjects who are exposed to high emotional demands at the workplace might have coped with or have adapted to the situation. For example, a nurse who encounters dying patients regularly may adapt to the situation in the long run. More studies are warranted to understand the association and its cellular and molecular underlying pathways.
Recently, 13 work factors were identified as potential psychosocial risk factors for workers’ health based on extensive scientific evidence: psychological support, organizational culture, clear leadership and expectations, civility and respect, psychological competencies and requirements, growth and development, recognition and reward, involvement and influence, workload management, engagement, balance, psychological protection, and protection of physical safety
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(56). In this thesis, we looked at some of them (i.e. recognition and reward, involvement and influence, workload) and found that they were associated with higher blood pressure. Our current knowledge on how workers perceive and adapt to various psychosocial factors and through which biological route these factors exert their effect is limited. With the ever-changing nature of the work, workers may also change themselves to cope or adapt to the dynamics of work. Thus, theory-driven psychosocial work factors may show unexpected health effects from time to time.
GENDER AND GENETIC MAKE-UP AS POTENTIAL MODIFIERS
In occupational epidemiology, it is important to identify vulnerable groups that are more susceptible to any exposure in developing diseases and to apply preventive measures accordingly to reduce exposure-related morbidity and mortality.
Due to biological and socially constructed differences, males and females may have differences in experiencing occupational exposures and resulting health outcomes. In the Lifelines Cohort Study, we observed that overall a higher proportion of males was exposed to dust, pesticides, aromatic solvents, chlorinated solvents, and metals while a higher proportion of females was exposed to biological dust and other solvents. Usually, dirty blue-collar jobs, e.g. farming, welding, heavy truck and lorry driving, and construction are performed more often by males than females.
Dust, pesticides, and solvents enter the body predominantly through inhalation and may impair lung function. We found that males had a relatively greater lung function impairment compared to females upon exposures to biological dust, mineral dust, gases/fumes, insecticides, fungicides, and other solvents. We hypothesized that in dirty blue-collar jobs (i.e. farming, welding, and construction) males might have experienced a higher dose of exposures than females which resulted in greater lung function impairment among males compared to females. With the same level of occupational exposures, not all the workers experience the same negative health outcomes (e.g. respiratory symptoms). Genetic make-up may play a role in the differential susceptibility to these exposures. Therefore, we hypothesized that the association between occupational exposures and sickness absence might be different in workers with different genetic make-up. Indeed, in the candidate gene-based approach, we found that having certain genetic markers diminished or aggravated the effects of particular occupational exposures regarding sickness absence. With such knowledge, workers (with a particular genetic make-up) could draw up their working plans more pragmatically: avoid jobs
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with problematic exposures. In addition, this information may also enable policymakers and occupational epidemiologists to make targeted interventions.
JOB EXPOSURE MATRIX (JEM) FOR MEASURING OCCUPATIONAL EXPOSURES
The best way to estimate individual occupational exposure is by quantitative measuring of hazardous agents either externally (concentrations in the air or on the skin) or internally (concentrations in the body tissues or excreta). However, in the general working population, it is nearly impossible to reach all the subjects and to collect data on such a real quantitative level. In addition, quantitative measuring of occupational exposure in the general working population requires substantial cost and effort. Thus, proxy measures are commonly used in estimating occupational exposure.
Estimating occupational exposure based on self-reported exposure is less expensive than quantitatively measuring occupational exposure, but it is subject to reporting and/or recall bias (57). In this thesis, we estimated occupational exposures using JEMs. Once a JEM is constructed, it is an efficient tool to estimate occupational exposure in the general population since it links workers' self-reported job titles to the occupational exposures, assessed by experts. A drawback of JEMs is that they assume homogeneity of exposure within workers in the same job. However, not all workers perform the same activities and tasks in a job. For example, in a dairy farm, some of the workers are in contact with animals most of the day (milking, feeding, etc) while others are more involved in the administration of the farm and only seldom have contact with animals. Hence, the intensity of exposure to biological dust will vary among the workers, whereas in estimating occupational exposure using a JEM, the same proxy exposure value is used for all subjects in the same job, and the true exposure values of each subject will vary randomly around this proxy. Although this error (known as “Berkson error”) leads to no or little bias in the regression coefficients, precision can be lost due to a wider confidence interval (58). Another pitfall of the use of a JEM is that it does not assess exposure at the individual chemical or biological level.
Apart from using JEMs in research, they can also be used in public health (59). In a recent study, a biomechanical JEM performed fairly well in predicting the received financial compensation for work-related disorders (60) and would improve the existing expert-based system. In addition, a JEM can also be used as a screening tool for detecting occupational exposures (e.g. silica, asbestos, and wood dust) among workers (61–63). For example, in a very recent study conducted among
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patients with lung cancer or mesothelioma, a JEM identified the previous occupational exposure to asbestos and silica accurately which suggests its potential to be applied as a screening tool for occupational exposures.
FUTURE PERSPECTIVES
In our cross-sectional analyses, we have shown that occupational exposures were associated with sickness absence, especially long-term sickness absence and blood pressure. As the findings are limited to one point of time (at baseline), they provide merely an idea about the association but we cannot say if these exposures caused sickness absence or affected blood pressure. Prospective longitudinal studies should investigate if occupational exposures really are causing sickness absence and changes in blood pressure and the underlying causal mechanisms. They should also focus on changes in the occupational exposures and covariates between baseline and follow-up in the analyses.
Thus far, not many research has incorporated life course principles (such as timing, duration, and context) in investigating the health impact of psychosocial work factors. In addition, with the continued development of workplace design (e.g. remote work, telework, and virtual teams), technological job displacement (e.g. artificial intelligence and robotics), and work arrangements (e.g. alternative work arrangement including contractors and on-call workers), new psychosocial work factors may evolve or are already present (64). Future studies should embrace the life course principles and ever-changing dynamics of the workplace, the work, and the workforce to examine the association between stress-induced by psychosocial work factors and the health consequences.
In addition, future studies should consider the details of job history to determine the exposure-disease relationship (65). For example, the total duration of exposure or cumulative exposure is a reliable metric for determining the exposure-disease relationship of chronic diseases. For acute conditions such as asthma exacerbations, peak exposure would be a preferable metric. Additionally, for many diseases, the timing of exposure (sensitive period) is very important, because it provides a period during which an occupational exposure can cause or prevent disease (66).
JEM construction and development is still ongoing. Incorporating exposure assessment in terms of geographical location, exposure variability resulting from differential regional and cultural work habits, and time periods in the existing JEMs will improve the use of JEMs (67). For example, applying JEMs to different study populations in different countries will increase the statistical power substantially,
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and will allow us to study exposure-disease association for rare diseases, or low prevalent exposure, or both. Further improvement of the use of the JEM could be achieved by an automatic job coding system (67). Manual coding is very cumbersome, requiring substantial cost and time, and is often not feasible in a large-scale setting. So far studies found a moderate agreement (50%) between automatic coding and manual coding (68,69). Therefore, more rigorous work is required to achieve a comprehensive automatic coding system, enabling us to code jobs more accurately in the general population with a myriad of job titles and in an unbiased manner.
Finally, even though a JEM is an efficient tool to estimate occupational exposure in the general population, it provides only a proxy estimate. The JEMs used in this thesis do not incorporate chemical-specific quantitative measurements. To identify the toxic levels of the occupational exposures and subsequently, to set the toxic exposures threshold levels, the focus should be directed to incorporate specific chemicals in quantitative measurements. Such a JEM will produce an exposure-response relationship and enable us to set the threshold limit of a hazardous agent in the workplace.
In this thesis, we found that several occupational exposures (i.e. pesticides, jobs strain, and ERI) were associated with adverse health outcomes. As we identified potential harmful occupational exposures, we now further need to focus on reviewing the adequacy and effectiveness of the existing preventive and monitoring systems and formulating and tailoring further preventive measures. In doing so, a hierarchy of control measures can be adopted and applied, starting from a reduction or elimination of hazards in the workplace into a substitution by alternative materials, tools, or machines till engineering of control measures and administrative measures (70).
172
CONCLUSION
In this large general working population-based thesis, we observed that pesticides is the most potent occupational exposure that may impair lung function and may increase the risk to develop respiratory symptoms and airway obstruction. Metals exposure may increase the prevalence of sickness absence among workers. Experiencing high job strain and high effort-reward imbalance in the workplace may increase blood pressure. Future studies should consider to include a detailed job history to detect the health effects of occupational exposures over the life course. In addition, future research should focus on the causal associations between occupational exposures and health effects through genetic and epigenetic analyses. The results of these future studies may point towards future preventive and therapeutic measures. Targeted preventive measures should be implemented to protect workers from exposure to pesticides and its components, metals, job strain, and effort-reward imbalance to ensure healthy working lives.
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