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Occupational Medicine Advance Access originally published online on October 17, 2006
Occupational Medicine 2007 57(1):50-56; doi:10.1093/occmed/kql109
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© The Author 2006. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Occupational titles as risk factors for Parkinson's disease

Smita Dick, Sean Semple, Finlay Dick and Anthony Seaton

Department of Environmental and Occupational Medicine, University of Aberdeen Medical School, Foresterhill, Aberdeen, UK

Correspondence to: Finlay Dick, Department of Environmental and Occupational Medicine, University of Aberdeen Medical School, Foresterhill, Aberdeen, UK. Tel: +44 1224 558191; e-mail: f.dick{at}abdn.ac.uk


   Abstract
Top
 Abstract
Introduction
 Methods
 Results
 Discussion
 Conflicts of interest
 References
 
Background Job title or employment sector may be associated with Parkinson's disease (PD).

Methods In a case–control study, in four European centres, lifetime occupational histories were coded using modified International Standard Industrial Classification (ISIC) and Dictionary of Occupational Titles (DOT). We employed multiple logistic regression analyses adjusting for age, gender, smoking and family history of PD.

Results A total of 649 cases and 1587 controls were recruited. Scottish data showed a non-significant increased risk for agriculture (DOT: OR 1.32, 95% CI 0.81–2.16; ISIC: OR 1.30, 95% CI 0.84–2.02) and reduced risk for ‘transport and communication’ (ISIC: OR 0.60, 95% CI 0.37–0.97). Subsequent four-centre analyses showed reduced risk for processing occupations (DOT: OR 0.69, 95% CI 0.5–0.95). An association with pesticide exposure, found using detailed exposure assessment, was not apparent using job classification.

Conclusions In contrast to retrospective exposure assessment, job or industrial sector is a weak indicator of toxic exposures such that true associations may be missed.

Keywords      Job coding; occupational titles; Parkinson's disease


   Introduction
Top
 Abstract
 Introduction
Methods
 Results
 Discussion
 Conflicts of interest
 References
 
Idiopathic Parkinson's disease (PD) is the second commonest neurodegenerative disorder after Alzheimer's disease and is believed to be of multi-factorial aetiology. Environmental factors such as pesticides have been associated with an increased risk of developing PD in some studies [1]. Exposure to these and other toxic agents may occur through work and so occupations and occupational exposures have been studied as risk factors for PD in a number of studies [2–7]. Both job title and industry of work are studied as markers of exposure to agents used in the workplace.

Tsui et al. [8] investigated the associations between occupation and PD in a case–control study set in Vancouver, Canada. They found that PD was positively associated with employment in teaching or health care. Information on the occupations of the cases was obtained from them or their family members but job data on the controls were drawn from the 1991 Canadian census. The reliability of proxy data had been questioned in some previous studies [9,10]. This Canadian study had its origins in the observation that both teachers and health care workers appeared to be over-represented among PD sufferers attending the Movement Disorders Clinic at the University of British Columbia Hospital, Vancouver. The authors hypothesized that their observation might be due to a link between high exposure to respiratory infections in these occupations and PD. An alternative explanation of this finding is that these groups may have better access to health care than the general population, so confounding the association. One criticism of this study is that information on occupation was limited and did not include all jobs held during a working lifetime.

Semchuk et al. [2] found a link between grain farming and PD in a population-based case–control study set in Alberta, Canada. The risk of developing PD after 16–25 years of field crop and grain farming was not significant but became significant when this was extended to 35 years employment. This suggests an exposure–response relationship and highlights the advantage of using lifetime occupational histories over recording the current or last job.

Tuchsen and Jensen [11] in a large Danish cohort study showed a significantly increased risk of first hospital admissions for PD among agriculture and horticulture workers. They coded all occupations using the Danish ‘Employment Classification Module’, which provides information on occupational classification and industrial sector. An increased risk was also observed for self-employed women in laundry and dry-cleaning, occupations associated with solvent exposures. This large well-designed study provides further evidence of an association between agricultural employment and PD.

In their US mortality study, Schulte et al. [12] observed occupational clustering for work in agriculture and death due to neurological conditions including PD. They found an excess of PD among pesticide applicators, farmers and graders and sorters of agricultural products. This study recorded the occupation as stated on the death certificate but this may have been the longest held, the most prestigious or the most recent occupation. Problems such as misclassification and over-reporting have been encountered while using occupational data derived from death certificates [13,14].

Frigerio et al. [15] undertook a case–control study of occupation preceding development of PD in Olmsted County, MN, USA, using occupational data from (i) medical records review and (ii) telephone interviews. Proxy telephone interviews were employed for two-thirds of cases and half of controls. This study found an increased risk of PD among physicians (based on nine cases and one control who had worked as doctors) but found no evidence of an increased risk either among other health care workers or among teachers, librarians and counsellors.

Only two studies have attempted to classify occupations held during the lifetime and then determined the risk of developing PD using similar systems of job classification.

The first carried out by Kirkey et al. [16] was a population-based case–control study set in Detroit, MI, USA. This study found a non-significant increased risk for work in agriculture and PD. In contrast, they found that those classified as ever having been employed in a service occupation showed a decreased risk. Kirkey et al. [16] coded all the jobs held for 6 months or longer using the Dictionary of Occupational Titles (DOT) system for occupational categories and the Standard Industrial Classification system for industrial categories. Interviewers coded the jobs and an industrial hygienist reviewed the coding.

The second study set in South Korea [17] found that ever having worked in agriculture, hunting and forestry was associated with an increased risk of PD, whereas employment in the manufacturing and transportation sectors was negatively associated with PD. The authors used the Korean national coding systems for industry and occupational classification. The occupational title classification system used was similar to the DOT system but the Korean industry classification system differed from the industrial classification system used by Kirkey et al. [16].

There is limited evidence that workers in a number of occupations or industry sectors may be at increased risk of PD when compared with the general population [16,17]. We wished to explore within a large, multi-centre study whether occupation is associated with PD. Initially, we examined the occupational data gathered in one centre (Scotland), and subsequently sought to replicate these findings across all four participating centres (Scotland, Sweden, Italy and Romania).


   Methods
Top
 Abstract
 Introduction
 Methods
Results
 Discussion
 Conflicts of interest
 References
 
We carried out a multi-centre study of the genetic, environmental and occupational risk factors for parkinsonism and PD (the Geoparkinson study). The study was carried out in four centres across Europe, northern Scotland (Grampian region and Easter Ross), south-eastern Sweden (Östergötland and Jönköping), northern Italy (Emilia-Romagna region) and eastern Romania (metropolitan Bucharest). We have previously described the exposure estimation methods used in this study [18] and we shall report associations with these more detailed estimates in a later paper.

Each centre aimed to recruit 200 prevalent cases of parkinsonism or PD and 400 age- and gender-balanced controls. We recruited twice as many controls as cases to increase the statistical power of the study as there was insufficient project time to recruit more cases of a disease that presents relatively infrequently to hospital. An interviewer-administered questionnaire sought demographic details and a lifetime occupational history [18]. All interviewers were trained in the administration of the questionnaire to minimize inter-interviewer bias. Owing to the nature of PD, it was not possible to blind interviewers as to their interviewees' disease status. Cases were classified as having parkinsonism or PD using the UK Parkinson's Disease Society Brain Bank clinical diagnostic criteria [19]. In two centres (Italy and Sweden), a neurologist reviewed all cases against these diagnostic criteria prior to recruitment. Owing to resource limitations in the other two centres, patients were classified following a review of the patient's hospital medical records. We excluded cases with dementia, drug-induced parkinsonism or cerebrovascular parkinsonism and controls with dementia, parkinsonism or PD. Controls were age and gender balanced with the cases and were drawn from the same geographical areas as the cases. The controls were recruited from a random sample of the community (Sweden), a mixture of community controls (drawn from general practitioner patient lists) and Orthopaedic, Geriatric and Respiratory out-patient clinics (Scotland), anticoagulant clinics (Italy) and geriatric hospital in-patients (Romania). The study protocol received ethical approval from each centre's research ethics committee and all participants gave written informed consent.

The occupational history formed part of the study questionnaire. The job titles and industry codes for each subject were recorded for any job held for >6 months. The industry codes were based on the modified version of the International Standard Industrial Classification (ISIC) [20]. The ISIC was modified to give nine categories based on industry of work (see Table 1). This was done for ease of job classification by the interviewers across the four centres.


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  		Table 1 Multiple logistic regression analyses for ever having worked in DOT and ISIC occupational categoriesa and risk of PD for Scottish data

 
All jobs were recoded by a single assessor (S.D.) blind to disease status using the ‘DOT’ [21]. Although the jobs were coded up to the third digit of the nine-digit DOT coding (i.e. one of the 564 three-digit occupational groups of the DOT), for the purposes of this analysis, the jobs were classified into one of the nine one-digit occupational categories as shown in Table 1. The DOT classification groups jobs into the nine categories based on their similarities. A nine-digit occupational code is unique to each job with the first digit representing the occupational category.

It is important to note that for the DOT system the category is allocated based on occupational title, whereas in the modified ISIC system the category depends on the industry of work. Some of the nine categories in the DOT and the modified ISIC sound similar (e.g. agriculture, fishery, forestry and related occupations and agriculture, hunting, forestry and fishing) but overlap is not complete. For example, (i) working as a ‘teacher’ in a school will be classified under the DOT category ‘professional, technical and managerial’ (Code 0), and under the modified ISIC category ‘public administration, education and health’ (Code 8) and (ii) for an agricultural machinery engineer, the occupational title would be classified as engineer—professional, technical and managerial category under DOT but the industrial sector would be agriculture under ISIC. Industrial sector thus tends to mask the likely exposures of subsidiary, maintenance or associated jobs.

A validation exercise was carried out for the DOT coding of the Scottish questionnaires. An occupational physician and an occupational hygienist independently coded 5% of all Scottish questionnaires blind both to disease status and to the original assessor's job coding. In addition, the primary assessor recoded 5% of all Scottish questionnaires blind to initial coding.

The Statistical Package for the Social Sciences (SPSS version 12.0, SPSS Inc. Chicago, IL, USA) was used for all statistical analyses. Logistic regression analyses were carried out to determine the risk associated with work in an occupational category and the development of PD. Subsequently, multiple logistic regression analyses were carried out, adjusting for age, gender, smoking history (ever/never) and first-degree family history of PD. A Mann–Whitney U-test was carried out to assess the relationship between the years of employment in an industry (ISIC) or occupational category (DOT) and the risk of developing PD.


   Results
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 Abstract
 Introduction
 Methods
 Results
Discussion
 Conflicts of interest
 References
 
Recruitment was carried out from June 2000 to July 2002. The total number of people recruited from all four centres was 781 cases and 1587 controls with an overall response rate of 64% (77% for cases and 59% for controls). In all, work histories were available for job coding from 649 cases and 1587 controls. A total number of 7214 jobs were coded.

The quality assurance (QA) exercise showed adequate inter-rater agreement with all three coders agreeing on 82.2% of codes (n = 145 total jobs coded for the inter- and intra-rater QA system) and good intra-rater agreement at 95.9%. There was disagreement over similar DOT categories (Code 1 ‘professional technical and managerial’ and Code 2 ‘clerical and sales’), where the main assessor coded the jobs as Code 1 but the other two assessors coded the jobs as Code 2. The results presented here are for PD cases only (n = 649) versus controls.

The analyses were carried out initially using only the Scottish data (n = 590). The total number of jobs reported by the Scottish participants was 2915 [median 5, inter-quartile range (IQR) 3–6]. The highest number of jobs in the DOT classification was held in the ‘clerical and sales’ category, whereas in the modified ISIC, the category ‘distribution, hotels and restaurants’ had the most jobs. Multiple logistic regression analyses of the Scottish data (Table 1) showed a marginally non-significantly increased odds ratio (OR) for ‘ever worked’ in agriculture for both systems of classification and a significantly reduced risk by ISIC for ever working in the ‘transport and communication’ category. Work in the transport and communication category for the modified ISIC showed a significantly reduced risk of developing PD.

The analyses were repeated for the multi-centre study including Scotland, with data on 6790 jobs (median number of jobs 2, IQR 1–4). Within the DOT system of classification, the highest number of jobs was held in the ‘clerical and sales’ category followed closely by the ‘professional, technical and managerial’ and ‘service’ categories. For the modified ISIC, the highest number of jobs was held in the ‘manufacturing’ category followed by public administration and health, with the fewest jobs in the ‘extraction, energy and water supply’ category.

Logistic regression analyses showed no significant increase in OR for any job category in either system of classification (see Table 2). Regression analyses adjusting for age, gender, ever smoking and first-degree family history of PD showed that work in the ‘processing’ occupations category for the DOT classification was associated with a significantly reduced risk of developing PD.


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  		Table 2 Multiple logistic regression analyses for ever worked in occupational and industrial categoriesa and risk of developing PD for four-country data

 
A Mann–Whitney U-test was carried out to determine whether there was a significant difference between the cases and controls for the number of years worked in each category. Cases had worked for longer in the modified ISIC category of ‘agriculture, hunting, forestry and fishing’, but the results were not statistically significant (see Table 3).


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  		Table 3 A comparison of years worked by study participants between the DOT and modified ISIC occupational categories across all four countries

 

   Discussion
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
Conflicts of interest
 References
 
This study is the largest case–control study to date to assess the relationship between work in a particular occupational or industrial category and the risk of developing PD. Results for the Scottish arm of the study showed the highest risk to be associated with work in agriculture, although this was not statistically significant. The four-country Geoparkinson study data also showed a marginal, non-significantly increased OR for the agriculture category. This finding is similar to that reported by Kirkey et al. [16]. However, unlike Kirkey et al. [16] and Park et al. [17], we observed no association for work in the service sector for either the Scottish data or the four-country data.

The Scottish results showed a reduced risk for work in the transport category of the industry classification on multiple logistic regression analysis after adjusting for age, gender, smoking and family history of PD. A similar association has recently been reported in a South Korean study [17] with workers in transport being at reduced risk of developing PD. Smoking has been shown to be protective against PD in a number of studies [22,23]. An exposure–response relationship has been shown between the number of cigarettes smoked and reduced risk of PD [24]. In addition, an increased risk of PD has been found with increasing years since stopping smoking [25]. The significantly reduced ORs for the transport category of the modified ISIC coding for the Scottish data may reflect the high prevalence of smoking in occupational drivers [26]. The transport category of the modified ISIC coding had the second highest number of smokers, the majority of whom were controls. This negative association between transport and PD was not observed in the analysis of data from all four centres. For the four-centre data, the significantly reduced risk of developing PD observed for work in the processing occupations (DOT) is difficult to explain and may be a chance occurrence. Similar results were not obtained for the Scottish data.

Strengths of this study include our use of self-reported lifetime occupational histories as opposed to those obtained from proxy respondents or from death certificates. These occupational histories also aided in the categorization of the jobs under a particular industry or occupational title. We carried out a validation of our coding of jobs using the DOT classification and have shown satisfactory agreement both between and within raters. Mannetje and Kromhout [27] in their review on different coding systems have previously reported agreement rates between 75 and 97% for one-digit occupational coding using the DOT.

As in the study by Kirkey et al. [16], we recorded occupational histories including all jobs held for a period of 6 months or more. Although we used a slightly different system for the industry classification from that used by Kirkey et al. [16], the occupational title classification was similar. This allows comparisons to be drawn between our findings and those of Kirkey et al. [16]. The study by Park et al. [17] is not directly comparable as they used the Korean national classification systems for industry and occupational titles.

Except for work in the processing category, we did not find significant associations between occupational or industrial categories and the risk of developing PD. This may reflect the limitations of the classification systems when applied to a large multi-centre data set. The percentage of participants who had ever worked in agriculture varied across the four centres. Within the modified ISIC data, agriculture was a large employer in Italy (33%) in comparison to Romania (6%). The small percentage of people reporting agricultural employment in Romania may be a reflection of the urban location of the University Hospital Colentina in metropolitan Bucharest. The probability of exposure within the same occupational or industrial categories may differ between countries. In part, this may reflect work practices and health and safety regulations in the four countries. Increased job mobility in certain centres (Scotland) may increase the possibility of exposure. The Scottish participants had held 43% of all the jobs reported across the four centres and this is reflected in the difference between the median number of jobs in Scotland and the four centres combined. The fewest job changes were observed in Romania and this may be a consequence of the country's communist era. As opposed to the differences observed for total number of jobs, there was very little variation for total years of work between the four centres.

These results contrast with those we have derived from the use of detailed exposure histories in the same study (Dick FD, De Palma G, Ahmadi A, Scott NW, Prescott G, Bennett J, Semple S, Dick S, Counsell C, Mozzoni P, Haites N, Bezzina Wettinger S, Mutti A, Otelea M, Seaton A, Söderkvist P and Felice A, unpublished data) which have identified work with pesticides as a risk factor for PD and this, to some extent, is reflected in the occupational coding analyses. Work in an occupational category is a crude marker of exposure and the use of occupational or industrial coding systems to identify jobs or industries that are risk factors for PD is clearly limited. For example, although DOT Category 8 ‘structural work’ includes job titles such as painter, it also includes stonemasons. The aggregation of occupations with very different exposures may obscure associations. Similar difficulties arise with the use of classification schemes where jobs are categorized based on industry sector. Although these approaches may sometimes identify industries or occupations at increased risk of PD, any such association is likely to be attenuated because of exposure misclassification [28].

A more efficient approach than occupational coding is retrospective exposure estimation as used in the Geoparkinson study [18] where baseline exposure estimates were modified using information from exposure-specific questionnaires. Using this technique, we found that pesticide exposures were a risk factor for developing PD (Dick FD, De Palma G, Ahmadi A, Scott NW, Prescott G, Bennett J, Semple S, Dick S, Counsell C, Mozzoni P, Haites N, Bezzina Wettinger S, Mutti A, Otelea M, Seaton A, Söderkvist P and Felice A, unpublished data) and were able to show an exposure–response relationship.


   Conflicts of interest
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Conflicts of interest
References
 
None declared.


   Acknowledgements
 
This study was funded by the European Union as part of the Fifth Framework programme, project number QLK4-CT-1999-01133 and we gratefully acknowledge their support for this project.

Membership of the Geoparkinson study group:

Scotland: Dick FD, Seaton A, Haites N, Osborne A, Grant F, Semple SE, Cherrie JW, Dick S, Adiakpan N, Sutherland S, Prescott GJ, Scott NW, Bennett JE, Counsell CE, Coleman R, Primrose W, Srivastava P. Italy: Mutti A, De Palma G, Mozzoni P, Scotti E, Buzio L, Calzetti S, Montanari A, Negrotti A, Scaglioni A, Manotti C. Sweden: Söderkvist P, Ahmadi A, Axelson O, Fall P-A, Georgsson E, Hällsten A-L, Molbaek A, Schippert Å, Dizdar N, Tondel M. Romania: Otelea M, Luparu R, Tinischi M. Malta: Bezzina Wettinger S, Scerri C, Borg J, Cassar K, Cassar W, Galdies R, Vella NR, Mifsud VA, Aquilina J, Galea Debono A, Felice A.


   References
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Conflicts of interest
 References
 

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