Abstract
Objective: To estimate the prevalence of parkinsonism in welders in Alabama and to compare this prevalence with that in a general population sample.
Methods: The authors screened 1,423 welders from Alabama who were referred for medical–legal evaluation for Parkinson disease (PD). Standardized videotaped assessments using the Unified Parkinson’s Disease Rating Scale motor subsection 3 (UPDRS3) were obtained. Patients provided information regarding exposure to welding fumes and job titles. Job titles were matched with Department of Labor Standard Occupational Codes (SOCs). Diagnoses were assigned based on quantitative criteria for the diagnosis of PD using two thresholds for diagnosis. With use of the number of active welders in this screening with parkinsonism as the numerator and the age-adjusted number of welders in each SOC as the denominator, the prevalence of parkinsonism in Alabama welders was estimated using conservative assumptions and compared with general population data from Copiah County, MS.
Results: With use of conservative and liberal case definitions of parkinsonism, the estimated prevalence of parkinsonism among active male welders age 40 to 69 statewide was 977 to 1,336 cases/100,000 population. The prevalence of parkinsonism was higher among welders vs age-standardized data for the general population (prevalence ratio = 10.19, 95% CI 4.43 to 23.43).
Conclusion: The estimated prevalence of parkinsonism was higher within a sample of male Alabama welders vs the general population of male residents of Copiah County, MS.
A variety of occupational and environmental exposures are associated with the development of Parkinson disease (PD). Epidemiologic studies implicate well water,1 pesticides and herbicides,2 rural residence,1 exposure to metals (manganese and iron),3 employment in the steel/alloy industry,4 employment in the wood/pulp industry,5 and farming6 as etiologic risk factors for PD. Specific occupations have also been implicated as risk factors for PD. An occupation case-control study found an increased risk of PD in carpenters (odds ratio [OR] = 3.9), cabinet makers (OR = 11), and cleaners (OR = 6.7) compared with a population-based control group.7 A population-based survey of PD in British Columbia found an association between PD and working in an orchard (adjusted OR = 2.30) or planer mill (adjusted OR = 4.97),8 suggesting that industrial chemicals, including pesticides and herbicides, could be etiologic agents. Another non-population-based case-control study in the same region found that occupational categories including forestry, logging, mining, and working in oil/gas fields had an OR of 3.79 vs other occupations studied.9 A non-population-based case-control study in the Emilia–Romagna region of Italy found that occupational exposure to “industrial chemicals” was a risk factor for PD (OR = 2.13).10 Occupational exposure to magnetic fields may be a risk factor for PD.11 A death certificate (population-based) case-control study in Colorado utilizing a tiered exposure matrix found an adjusted OR of 1.76 for PD for subjects exposed to magnetic fields. Occupations included in this study were electronic technicians and engineers, repairers of electronic equipment, telephone and telephone line installers and repairers, electric power installers and repairers, supervisors of electricians and power transmission installers, power plant operators, motion picture projectionists, broadcast equipment operators, and electricians.11 These authors also found that welders were overrepresented in PD deaths.11
In a specialty clinic–based case-control study of 15 career welders compared with consecutively ascertained and age-matched control subjects with PD, welders with PD were clinically identical to the control groups except for a significantly younger age at onset (46 vs 63 years), and 6-[18F]fluorodopa PET was consistent with idiopathic PD.12 Although this study suggested that welding may accelerate the onset of disease, the prevalence of parkinsonism in welders is unknown.
Methods.
This study was approved by the Washington University School of Medicine Human Studies Committee.
Subjects.
All patients evaluated were referred for medical screening for PD by an attorney. The majority of individuals acknowledged one or more PD symptoms and identified welding as their primary occupation, although not all subjects had symptoms nor did all subjects weld. A total of 1,950 patients were evaluated using video screening between August 2002 and March 2003. This report details the results of a subgroup of 1,423 patients residing in Alabama. Rigidity was assessed by a fellowship-trained movement disorders specialist in a pseudo-random group of 112 subjects as well as any subject with tremor identified by the videographer. A research assistant chose subjects for rigidity testing and the complete Unified Parkinson’s Disease Rating Scale motor subsection 3 (UPDRS3) by taking every nth subject, where n = an integer between 5 and 10 chosen on each day of screening. Forty-eight of the 112 pseudo-randomly selected subjects had a complete UPDRS3 performed by the “in-person” examiner. Patients provided medical history and work history (including hours–days–years, percentage welding indoors/outdoors, percentage use of respirator) and answered a PD screening questionnaire.13
Video protocol.
All patients underwent a standardized video examination that consisted of the UPDRS314 except for rigidity. Four occupational therapists and two physical therapists underwent 3 hours of training to administer the UPDRS3. Before videographers were permitted to videotape patients, 10 videotaped exams had to be approved by the research staff and in-person examiner. To ensure high-quality videotapes, the in-person rater performed the UPDRS3 on the 48 pseudo-randomly chosen subjects at the videotape session. These videos were rated by the video raters and the scores compared with those found by the in-person rater. The intraclass correlation between these independent ratings was 0.88. A unique identifier (no names) was included in the videotape. Digital pictures with the patients’ name provided backup for identification. During video rating sessions, a movement disorders specialist or research coordinator circulated between rooms to verify that video quality was sufficient.
Video diagnosis.
Video raters’ examinations were validated by rating videotapes of 10 patients with parkinsonism (nonwelders) and comparing these ratings with the in-person examiner’s video ratings on the same patients. Ratings on the test set of 10 subjects with parkinsonism demonstrated good reliability between the in-person examiner and the video raters (intraclass corre-lation = 0.85). All 10 subjects were rerated from the same tape at least 1 month later, and the individual intraclass correlations were 0.87 to 0.98 between the raters’ initial and repeat scores, demonstrating stability in the ratings over time.
The welder patients were rated by one of two fellowship-trained movement disorders experts using the UPDRS3, allowing for 0.5-point increments in limb scores. Raters were told that the subjects represented both welders and nonwelders, although they were aware that the majority of the subjects screened were welders. Raters had no knowledge of patient histories or specific exposure or occupational status. When available, the in-person examiner’s rigidity scores were added to the remainder of the UPDRS3. Patients were assigned diagnoses based on two sets of clinical criteria with different thresholds for diagnosis of parkinsonism (conservative and liberal criteria). These criteria were based on previously reported criteria,15,16 with the more stringent requirement of a “quantitative threshold” that must be reached to diagnose the cardinal features. As only a minority of subjects had rigidity testing, rigidity was a criterion in a small proportion of subjects.
Conservative criteria were as follows:
Definite PD.
Three of the following: rest tremor, rigidity, bradykinesia, postural instability; or two of the following: asymmetric rest tremor, asymmetric rigidity, asymmetric bradykinesia, postural instability.
Probable PD.
Two of the following: rest tremor, rigidity, bradykinesia, or postural instability; or one of the following asymmetric features: rest tremor, bradykinesia, or rigidity. (For both definite PD and probable PD, bradykinesia must be >1.5 in at least two limb ratings on the UPDRS3. Rigidity must be >1 in at least one limb on UPDRS3 rating. Postural instability is defined as >2 on UPDRS3.)
Exclusionary criteria. Stroke contralateral to side with most prominent bradykinesia; treatment with neuroleptic or other relevant dopamine receptor blocker or depleter.
Liberal criteria were as follows:
Definite PD.
Three of the following: rest tremor, rigidity, bradykinesia, postural instability; or two of the following: asymmetric rest tremor, asymmetric rigidity, asymmetric bradykinesia, postural instability.
Probable PD.
Two of the following: rest tremor, rigidity, bradykinesia, or postural instability; or one of the following asymmetric features: rest tremor, bradykinesia, or rigidity. (For both definite PD and probable PD, bradykinesia must be >1 in at least two limb ratings on the UPDRS3. Rigidity must be ≥1 in at least one limb on UPDRS3 rating. Postural instability is defined as ≥1 on UPDRS3 rating.)
Exclusionary criteria. Same as above.
Criteria were validated in a pseudo-randomly chosen subgroup of 48. We compared the agreement of the “quantitative criteria” with the diagnosis of parkinsonism by either video reviewer or in-person examiner. Specificity of these criteria compared with in-person examination was 91 to 100% and sensitivity was 56%.17
Any subject believed to be malingering by one of the raters was excluded from analyses. Features consistent with malingering included atypical gait disorders and tremor that consistently resolved when subjects were not being tested.
Comparison population.
We compared our prevalence of parkinsonism with the prevalence of parkinsonism in Copiah County, MS.18 This study was chosen as the reference population as the methods used by the authors were the most similar to our methods and the population was geographically similar to our sample. In the Copiah County study, subjects were screened by a door-to-door screening questionnaire followed by in-person examination of possible PD cases. The Copiah County study defined definite PD as two or more cardinal signs: rest tremor, bradykinesia, rigidity, “parkinsonian gait or posture,” retropulsion, masked facies, or micrographia. Possible PD was defined as one cardinal sign and the “equivocal presence” of one or more other cardinal signs. In the Copiah County study, parkinsonism included possible and definite PD cases. In addition to the published reports,18,19 we obtained additional data on the age- and gender-specific prevalence of parkinsonism from the authors of the Copiah County study. The number of cases of parkinsonism in men in the Copiah County deciles were as follows: 40 to 49 (no cases), 50 to 59 (one case), 60 to 69 (five cases) (D. Anderson, PhD, personal communication).
Prevalence of parkinsonism among welders.
Our screening study measured the prevalence of parkinsonism among a referral population of welders recruited for legal purposes. We used these data to estimate the population prevalence of parkinsonism among male welders in the state of Alabama through several steps. Most importantly, we made the assumption that our screening captured all cases of parkinsonism among Alabama welders; that is, that the numerator for estimates of prevalence was the number of cases we detected in our screened referral population. This is a highly conservative assumption that is likely to underestimate the prevalence of parkinsonism among welders by assuming that the cases detected in our screening represent all cases of parkinsonism among the total population of welders in Alabama.
To obtain a denominator, we obtained estimates of the number of welders in Alabama using the Department of Labor Standard Occupational Code (SOC) statistics from 2000, which list the total number of active welders in each of several SOCs.20 Our screened welders self-identified their occupational title for our classification, in a manner identical to the approach used by the Department of Labor. If a subject listed more than one job title, the first title was chosen as the current job title. Use of the SOCs results in an estimate of the total number of active welders in the state. As our reference population was restricted to subjects older than 40 and most workers are younger than 70, we then adjusted the numbers given by the SOCs to reflect the age distribution of interest. The Department of Labor’s SOCs do not provide information on age distribution of welders. We thus obtained the age distribution of active members of the International Brotherhood of Boilermakers in Alabama (M. Racic, L. Beauchamp, and P. Dumler, personal communication). We made the assumption that the age distribution of boilermakers, welders, and welders helpers in Alabama was the same as the age distribution of the Boilermakers Union and applied this age distribution to the total numbers of workers reported in the SOCs for these three groups. This provided an estimate of the number of workers in each of these three groups for three age strata: 40 to 49, 50 to 59, and 60 to 69 years. The prevalence of parkinsonism among each of three groups of welders was calculated using these denominators.
Data analysis.
All statistics were performed using SPSS v11.5 (Chicago, IL) and Excel X for Macintosh. Owing to the low number of female welders screened, we restricted analyses to male welders only. The prevalence of parkinsonism in the Copiah County study was estimated for men in each of three age strata (40 to 49, 50 to 59, 60 to 69 years), using original study data obtained from the author. The prevalence of parkinsonism in boilermakers, welders, and welder helpers was estimated using the numerator (numbers of cases detected in the screened population) and denominator (estimate of number of welders in each age stratum in the state) described above. We then used direct standardization to provide age-standardized prevalence estimates for Copiah County and Alabama welders, allowing the calculation of age-adjusted prevalence ratios. Ninety-five percent CIs for prevalence ratios were calculated using the normal approximation.21
All means for the sample are expressed as means ± SD. For univariate and bivariate logistic regression analysis, the dependent variable was the diagnostic class and the independent variables were input sequentially to determine the independent and dependent effects. Analysis of variance was used to test for a relationship between exposure and diagnostic category. For the purpose of this study, “normal” subjects were defined as those with a UPDRS3 score of <1.
Results.
Clinical and demographic features.
The mean level of education in the sample was 11.8 years (SD = 2.0). There were 95% men and 5% women in the sample (table 1). Although this sample commonly described symptoms of PD, the mean UPDRS3 score was only 6.4. With use of the “liberal criteria” for diagnosis of PD, 148 subjects had a diagnosis of definite PD(10.4%), 185 subjects had a diagnosis of probable PD (13.0%), and 929 (65.3%) were unclassified. With use of the conservative criteria, 82 subjects had a diagnosis of definite PD (5.8%), 180 subjects had a diagnosis of probable PD (12.6%), and 1,000 (70%) were unclassified. Only 126 subjects were normal (UPDRS3 score of <1). Common clinical features in those unclassified patients included isolated bradykinesia (UPDRS3 > 1 in at least one limb) (96%), isolated postural/action tremor (UPDRS3 postural tremor score > 1 in one limb) (6.7%), and bradykinesia with postural instability (19%).
Table 1 Demographic and clinical features of all Alabama welders screened
Prevalence.
We calculated age-adjusted prevalence ratios to compare the prevalence of PD in active welders in the age deciles 40 to 49, 50 to 59, and 60 to 69 years with the prevalence of PD in Copiah County, MS.18 We estimated the prevalence of parkinsonism in workers in the SOCs for “Welders, Cutters, Solderers, and Brazers,” “Boilermakers,” and “Welder Helpers” because these categories represented the majority of subjects screened. The estimated prevalences of parkinsonism for these categories for both the liberal and the conservative criteria are shown in table 2. Boilermakers, welders, and welder helpers all demonstrated a higher age-standardized prevalence of parkinsonism than the general population assessed in the Copiah County study (table 3).
Table 2 Estimated prevalence of parkinsonism in a sample of active male welders in Alabama
Table 3 Age-standardized prevalence ratios for parkinsonism, comparing male Alabama welders with a general male population in Copiah County, Mississippi18
Relationship between exposure and parkinsonism.
To investigate the relationship between welding exposure and parkinsonism, we performed univariate and bivariate logistic regression analysis to examine the relationship between the total number of welding hours and the diagnosis of parkinsonism using different diagnostic criteria. In univariate logistic regression analysis, higher exposure was associated with the diagnosis of parkinsonism using the conservative (OR = 1.025, 95% CI 0.942 to 1.116) and liberal (OR = 1.015, 95% CI 0.934 to 1.103) criteria. However, when age was included in the regression equation, only age remained associated with definite PD (p < 0.0001) using both sets of criteria. Age was modestly correlated with exposure (r = 0.297, p < 0.001). There was no significant correlation between UPDRS3 score and welding hours for the entire sample or in the active welders (table 4).
Table 4 Mean exposure hours by age category
Discussion.
We found that the estimated prevalence of parkinsonism was higher in a sample of male Alabama welders than the general population of male residents of Copiah County, MS. We believe that this is a highly conservative estimate of the prevalence of parkinsonism in welders. Our diagnostic criteria did not classify mild degrees of bradykinesia or rigidity as parkinsonism, making our criteria more conservative than other reports.18 Our quantitative thresholds for diagnosis maximized specificity with some loss of sensitivity.17 We assessed rigidity only in those with tremor or in a randomly selected group. Although videographers often had experience with neurologic patients, we provided only brief training to recognize tremor, possibly reducing our diagnostic sensitivity. Most importantly, we screened only 12% of the active welders in three Alabama SOCs and assumed in the prevalence calculation that we had identified all welders with parkinsonism in the state. It is highly unlikely that every active welder with parkinsonism in Alabama participated in this screening.
Our analysis excluded a large percentage of subjects with mild bradykinesia and postural tremor that could not be classified as parkinsonian but could be consistent with manganese exposure. Many studies document the neurotoxic effects of manganese on the CNS, similar to the clinical features seen in a large majority of the welders we screened.22–24 The Occupational Safety and Health Administration has a permissible exposure limit ceiling for manganese of 5 mg/m3.25 A cross-sectional epidemiologic study of workers exposed in a manganese oxide– and salt–producing plant found that workers exposed to low levels of manganese (approximately 1 mg/m3) had slower simple reaction times on a standardized reaction time test and more hand tremor as measured by a standardized hand steadiness assessment.23,26 Manganese-exposed foundry workers in Sweden (mean manganese exposure 0.18 to 0.41 mg/m3) demonstrated slower reaction time, reduced finger-tapping speed, reduced tapping endurance, and diadochokinesis.24,27,28 Others have found an exposure-dependent increase in blood and urine manganese levels and slowing of finger tapping in workers in a ferroalloy plant exposed to chronic low-level manganese. Even nonoccupational blood elevations in manganese also are associated with an exposure-related slowing of motor tasks and difficulty with pointing tasks consistent with tremor.29 Although many of the subjects in these studies had been exposed to manganese for many years, none had longitudinal follow-up to determine the natural course of these physiologic differences. The finding that low-level manganese exposure may be associated with parkinsonian signs similar to many of our patients implies that manganese cannot be excluded as the etiologic agent in our patients with parkinsonism and nondiagnostic motor abnormalities.
We found a strong association between age and diagnosis of parkinsonism in the 40- to 64-year range. The association of parkinsonism with age in our younger study population may support our previous study in which we found an earlier age at onset for career welders with PD compared with a control group.12 We speculate that welding exposure either increases the prevalence of PD at all ages or may shift the distribution of PD to a younger age. Determining the prevalence in a population-based sample of active and retired welders could clarify this relationship. Of course, this speculation is contingent on applying our methodology to a population-based control group to determine the specificity of our findings.
There are several limitations of this study. First, these findings should be confirmed by applying the same screening techniques to a control population. Movement disorders specialists may be more sensitive to parkinsonian findings than examiners in previous epidemiologic studies.18 Epidemiologic studies that involved direct examination by physicians for screening have found higher prevalence rates18 than studies that prescreened subjects with questionnaires30 or medical record review.31 Reviewer bias may be a concern as our video reviewers knew that many of the subjects were welders, although the reviewers did not know the welding exposure of individuals. This bias could overestimate the prevalence of parkinsonism in active welders in Alabama. Although we attempted to age standardize our prevalence ratios, the Department of Labor statistics are not age stratified. Our “proxy” age stratification based on union age data may not reflect accurately the true age distribution in active Alabama workers, producing either an over- or an underestimate of the true prevalence. Finally, we developed rigorous clinical criteria that resembled the Copiah County clinical criteria.18 We used clearly defined clinical signs for both “definite PD” and “probable PD.” As the Copiah County criteria for possible PD included “the equivocal presence of one or more other cardinal signs,” we were not able to completely overlap our criteria. However, the relative risks minimally changed if our clinically probable category required at least two cardinal PD signs, a more stringent criterion than in Copiah County. This preliminary work warrants a follow-up population-based epidemiology study, given the public health implications of a potential increased risk of parkinsonism in 1.5 million welding-exposed workers in the United States.32
Acknowledgment
The authors thank Dr. Dallas Anderson for providing raw data from the Copiah County study and the International Brotherhood of Boilermakers for providing data on age distribution their workers.
Footnotes
-
Supported by NIH grants K23NS43351 and NS41509, the Greater St. Louis Chapter of the American Parkinson’s Disease Association, and the Welder Health Fund.
The Welder Health Fund was created by Gulf States Trial Attorneys to support medical–legal screening of welders for Parkinson disease. No author has taken any money personally related to this research.
Received April 7, 2004. Accepted in final form September 30, 2004.
References
Letters: Rapid online correspondence
- Prevalence of parkinsonism and relationship to exposure in a large sample of Alabama welders
- Reply to Cox
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