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Keywords:

  • bladder cancer;
  • occupation;
  • case-control study;
  • New Zealand

Abstract

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References

We conducted a nationwide case-control study of bladder cancer in adult New Zealanders to identify occupations that may contribute to the risk of bladder cancer in the New Zealand population. A total of 213 incident cases of bladder cancer (age 25–70 years) notified to the New Zealand Cancer Registry during 2003 and 2004, and 471 population controls, were interviewed face-to-face. The questionnaire collected demographic information and a full occupational history. The relative risks for bladder cancer associated with ever being employed in particular occupations and industries were calculated by unconditional logistic regression adjusting for age, sex, smoking and socio-economic status. Estimates were subsequently semi-Bayes adjusted to account for the large number of occupations and industries being considered. An elevated bladder cancer risk was observed for hairdressers (odds ratio (OR) 9.15 95% Confidence Interval (95%CI) 1.60–62.22), and sewing machinists (OR 3.07 95%CI 1.35–6.96). Significantly increased risks were not observed for several other occupations that have been reported in previous studies, including sales assistants (OR 1.03 95%CI 0.64–1.67), painters and paperhangers (OR 1.42 95%CI 0.56–3.60), sheet metal workers (OR 0.39, 95%CI 0.15–1.00), printing trades workers (OR 1.11 95%CI 0.41–3.05) and truck drivers (OR 1.36 95%CI 0.60–3.09), although the elevated odds ratios for painters, printers and truck drivers are consistent with excesses observed in other studies. Nonsignificantly increased risks were observed for tailors and dressmakers (OR 2.84 95%CI 0.62–13.05), rubber and plastics products machine operators (OR 2.82 95%CI 0.75–10.67), building workers (OR 2.15, 95%CI 0.68–6.73), and female market farmers and crop growers (OR 2.05 95%CI 0.72–5.83). In conclusion, this study has confirmed that hairdressers and sewing machinists are high risk occupations for bladder cancer in New Zealand, and has identified several other occupations and industries of high bladder cancer risk that merit further study. © 2007 Wiley-Liss, Inc.

Occupational exposure to a range of carcinogens remains widespread. For example, it has been estimated that 23% of the European Union workforce (or 32 million workers) is currently exposed to one or more agents in their workplace that have been classified by the International Agency for Research on Cancer (IARC) as recognized (Group 1), probable (Group 2A), or selected possible (Group 2B) occupational carcinogens.1 Similarly, Infante2 has estimated that 20 million US workers are exposed to occupational lung carcinogens, namely 12,864,000 to IARC Group 1 and a further 7,321,000 to Group 2A lung carcinogens.

A recent literature review3 concluded that workplace exposures account for 5–25% of all bladder cancer cases. Aromatic amines are currently the only agents whose association with bladder cancer has been clearly established, but other agents such as paints, dyes, metals, industrial oils/cutting fluids and polycyclic aromatic hydrocarbons (PAHs) have also been linked to increased bladder cancer risks.3 Occupational exposures to these potential bladder carcinogens occur in a number of industries including aromatic amine manufacture, dyestuff manufacture and use, rubber and cable manufacture, textile and leather works, driving occupations, and the coal, tar, aluminium, and gas industries.3

It is unlikely that New Zealand workplace conditions differ markedly from those in other developed countries in terms of their occupational cancer risk, but the type and range of industry may differ in New Zealand. In 2001, the Massey University Centre for Public Health Research and the New Zealand Department of Labor, therefore, commenced a project to evaluate occupational contributions to the development of leukemia, non-Hodgkin's lymphoma and bladder cancer.4 The controls for the 3 studies have been pooled to provide greater precision for the control exposure prevalence estimates. Here, we present findings for the bladder cancer study to identify occupations that may also contribute to the risk of bladder cancer in the New Zealand population.

Methods

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References

Potential cases in the study were all incident cases of bladder cancer, aged 25–70 years, reported to the New Zealand Cancer Registry during 2003 and 2004, a total of 381 notifications nationwide. Both the treating clinician and general practitioner (GP) of the patient were sent a letter explaining the study and asking for consent to contact the patient. For 23 (6.0%) of the notifications, either the clinician or the GP did not provide consent to contact the patient. Of the 358 remaining cases, for 80 no contact could be established by mail and a further 46 were not eligible (e.g. never worked in New Zealand, mental health problems, bladder cancer was not the primary cancer). From the 232 remaining cases, 213 (91.8%) cases were interviewed for the study. Three of these were next of kin interviews. Thus, among those eligible for the study, the response rate was ∼64%.

Controls were randomly selected from the New Zealand Electoral Roll for 2003, frequency matched by age according to the age distribution of cancer registrations for NHL, bladder cancer and leukemia in 1999. A letter of invitation was sent to 1,200 individuals, of which 100 were returned to sender and thus considered ineligible. Of the remaining 1,100, for 348 (32%) contact could not be established. Their addresses were subsequently compared to the most recent Electoral Rolls of 2005 and 2006. Of the 348 nonresponders, 20 did not appear or appeared with another address on the new Electoral Roll and were thus considered ineligible. Of the 752 for whom contact could be established, 92 were ineligible because of other reasons (e.g. never worked in New Zealand). Of the remaining 660 controls, 187 declined to participate (28%), and 473 population controls were interviewed. Thus, among those eligible for the study, the response rate in the controls was ∼48%.

A face-to-face interview was conducted at the home of the case or control by a trained interviewer with an occupational health nursing background. The questionnaire collected information on demographics, smoking and a full occupational history. Each job held since leaving school was listed, including the start year, year of termination, department and job title, and name, location and activity of employer. For each job held at least 12 months, additional information was sought, including a task description, use of machines and materials, self reported exposures, workplace ventilation and use of protective equipment. When the same job was held at 2 different time periods, a single set of additional information was obtained.

Each job was coded according to the 1999 New Zealand Standard Classification of Occupations (NZSCO 1999)5 (hereafter referred to as the occupational code) and the Australian and New Zealand Standard Industrial Classification (New Zealand use version 1996)6 (hereafter referred to as the industry code). The occupational code was based on the full job and task description, rather than on the occupational title alone, to ensure that the code covered the actual tasks of each job. The industry code was based on the activity of the employer. All coding was done blind to the case-control status of the participants.

Before the data analyses were conducted, a broad list of a priori high risk occupations was constructed, based on the international literature. To identify these, we conducted a PubMed search from 1980 onwards for English-language publications of studies that contained both of the key words ‘bladder cancer’ and ‘occupation’ or ‘occupational exposures’ and prepared summary tables of the positive findings. These were then reviewed by the OSH Cancer Panel4 which identified occupations and occupational exposures for which it was considered that there was evidence of a probable increased risk of bladder cancer. The final list included hairdressers, salespersons, horticultural workers, painters, metal workers, blacksmiths and toolmakers, mechanics, printing trades workers, tailors and dressmakers, operators in mining and mineral processing, metal processing, and chemical processing, rubber workers, textile workers, drivers, and building workers.

Unconditional logistic regression using SAS V9.1 was applied to estimate the odds ratio (OR) and its 95% confidence interval (95%CI), for ever being employed in a certain occupation/industry, compared to never being employed in that occupation/industry. ORs were calculated for all 958 occupational codes. Of these, only 229 had 10 study subjects or more that ever worked in these occupations, and only the results of these occupations were evaluated. ORs were also calculated for each industry code. Of these 684 codes only 222 contained 10 subjects or more.

ORs were adjusted for age (5 year age groups), gender, Maori ethnicity, and smoking (never, ex, ever). Cases and controls were considered current smokers if they reported to have stopped smoking less than 2 years before the interview. Logistic regression models were also adjusted for socioeconomic status, based on the New Zealand Socioeconomic index of Occupational Status (NZSEI)7 (continuous variable ranging between 20 and 90) of the longest held occupation. Whether a longer duration in a certain occupation was associated with an increased risk was studied through categorical variables for duration of each job (1–2 years, 2–10 years, more than 10 years).

Semi-Bayes adjustment

Because of the large number of occupations and industries being considered, this type of study carries the risk that some of the findings involving elevated odds ratios will be due to chance. A semi-Bayes (SB) approach was therefore applied to determine which of the findings were the most robust. The basic idea of empirical Bayes (EB) and SB adjustments for multiple associations is that the observed variation of the estimated relative risks around their geometric mean is larger than the variation of the true (but unknown) relative risks. In SB adjustments, an a priori value for the extra variation is chosen so that the true relative risks have a reasonable range of variation, and is then used to adjust the observed relative risks.8 The adjustment consists in shrinking outlying relative risks towards the overall mean (of the relative risks of all the different ‘exposures’ being considered). The larger the individual variance of the relative risks, the stronger is the shrinkage, i.e., the shrinkage is stronger for less reliable estimates based on small numbers. Typical applications in which SB adjustments are a useful alternative to traditional methods of adjustment for multiple comparisons are large occupational surveillance studies, where many relative risks are estimated with few or no a priori beliefs about which associations might be causal.8 SB estimates were calculated using R (free software for statistical computing and graphics).9 The input for SB adjustments were the maximum likelihood estimate of β (logOR), resulting from the multivariate logistic regression for each occupation and industry. The variance of the distribution of the true logOR was assumed equal to 0.25. Assuming a normal distribution of the logORs, this choice implies that the true ORs are within a 7-fold range of each other.10

For those occupations (or industries) which were not considered to be of a priori high risk for bladder cancer, estimates were shrunk towards the mean for all occupations (or industries). Similarly, for those occupations (and industries) which were considered to be of a priori high risk for bladder cancer, estimates were shrunk towards the mean for all such occupations (or industries).

The findings for all occupations and industries, both before and after SB adjustment, will be made available on web-based tables. Here, we report the findings for a priori high risk occupations and industries and for other occupations and industries that showed statistically significant elevated or decreased risks in the current analyses.

Results

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References

The study included 213 interviews with bladder cancer cases, and 473 interviews with population controls. Of these, 2 controls were excluded because of missing values in key variables, leaving 213 cases and 471 controls available for analysis (Table I). Cases were 77% male (23% female) and controls were 47% male (53% female), with a mean age of 59.9 years in cases and 59.2 in controls. Current smoking was more common in the cases (23%) than in the controls (8%) (OR 3.75, 95%CI 2.35–5.97). Ever smoking was more common in the cases (69%) than in the controls (50%) (OR 2.29, 95%CI 1.62–3.24).

Table I. Characteristics of the Study Participants
 Bladder cancer casesPopulation controls
n%n%
Total213100%471100%
Gender
 Men16554%22147%
 Women4846%25053%
Age at interview
20–502920%6213%
51–605737%13729%
61–7011040%26055%
71–173%123%
Smoking
 Never6330%23249%
 Ex9746%20042%
 Current5023%368%
NZSEI (occupational class)
 Class 1 (75–90) highest52%82%
 Class 2 (60–75)147%317%
 Class 3 (50–60)2713%5812%
 Class 4 (40–50)3717%9019%
 Class 5 (30–40)5928%17036%
 Class 6 (10–30) lowest7133%11424%

Occupational class distribution was similar for cases and controls, except for the lowest occupational class (Class 6), which had a higher frequency in the cases (33%) than in the controls (24%), whereas there was a difference in the other direction for class 5 (28% vs. 36%), and the proportions for Class 5 and 6 combined were similar in cases (61%) and controls (60%). We studied whether these differences in occupational class between cases and controls could have been a result of response-bias in the controls, i.e., that controls with lower occupational class were less likely to participate in the study. For this purpose, we compared the sex, age and occupational class distributions between the 471 participating controls and the 729 nonparticipating controls using the information available from the electoral roll. This showed that both sex and age were significant determinants of nonparticipation within the controls, with men and younger ages less likely to participate. Logistic regression showed that the lowest occupational class (Class 6) was a statistically significant determinant of nonparticipation in controls (OR = 1.8, 95%CI 1.2–2.8), adjusting for age and sex, while all other occupational classes had ORs for nonparticipation of 1.0–1.1 compared to the highest occupational class. Logistic regression models were therefore also adjusted for occupational class.

A priori high risk occupations and industries

Tables II and III list the findings for the a priori high risk occupations and industries, both adjusted for and stratified by sex.

Table II. Odds Ratios and 95% CIs for A Priori High Risk Occupations
A priori high risk occupation for bladder cancerAll (213 cases, 471 controls)Men (165 cases, 221 controls)Women (48 cases, 250 controls)
cases/ controls (n)OR95%CIcases/ controls (n)OR95%CIcases/ controls (n)OR95%CI
  1. Numbers were too small (less than 10 cases + controls) for the following a priori high risk occupations: spray painters, metal moulders, leather goods makers, wood products machine operators, leather goods assemblers.

  2. OR: odds ratio, adjusted for gender, age group, smoking status, Māori ethnicity, occupational status.

  3. 95%CI: 95% confidence interval of the odds ratio.

Hairdressers, beauty therapists and related workers
 5141-Hairdressers, beauty therapists and related workers6/64.021.05–15.362/0  4/63.990.84–18.97
 51411-Hairdresser6/39.151.60–52.222/0  4/39.951.37–72.21
Salespersons, demonstrators and models
 52-Salespersons, demonstrators and models36/1070.850.54–1.3624/301.150.63–2.1112/770.390.17–0.90
 521-Salesperson and demonstrators35/1010.910.57–1.4723/261.290.69–2.4112/750.410.18–0.92
 5211-Salesperson and demonstrators35/1010.910.57–1.4723/261.290.69–2.4112/750.410.18–0.92
 52111-Sales assistant35/941.030.64–1.6723/211.600.83–3.1012/730.420.18–0.95
Market farmers and crop growers
 611-Market farmers and crop growers18/440.920.50–1.6711/290.600.29–1.277/152.050.72–5.83
 6112-Fruit growers9/201.310.56–3.055/100.940.31–2.874/102.030.55–7.48
 6113- Gardeners and nursery growers8/180.850.35–2.026/140.700.26–1.922/41.320.19–9.05
Painters and paperhangers
 7124-Painters and paperhangers11/101.420.56–3.6010/101.280.50–3.301/0  
 71241-Painter, decorator and/or paperhanger7/61.350.42–4.397/61.410.44–4.560/0  
Metal moulders, sheet-metal and related workers
 721-Metal moulders, sheet-metal and related workers7/210.370.15–0.927/200.410.16–1.030/1  
 7212-Sheet metal workers7/190.390.15–1.007/190.430.17–1.100/0  
 72124-Fitter and welder4/80.650.18–2.324/80.690.19–2.420/0  
Blacksmiths, toolmakers and related workers
 722-Blacksmiths, toolmakers and related workers1/60.170.02–1.551/60.210.02–1.860/0  
Machinery mechanics and fitters
 723-Machinery mechanics and fitters21/231.170.60–2.2921/221.240.63–2.420/1  
 7231-Machinery mechanics and fitters21/231.170.60–2.2921/221.240.63–2.420/1  
 72311-Machinery mechanic10/81.590.57–4.4010/71.690.59–4.810/1  
 72312-Motor mechanic11/180.750.32–1.7311/180.800.35–1.850/0  
Printing trades workers
 733-Printing trades workers7/121.110.41–3.055/80.930.28–3.032/41.540.22–10.87
 7331-Printing trades workers5/81.210.36–4.144/51.080.27–4.431/31.310.10–16.84
 73317-Printing machinist4/71.310.35–4.943/41.170.24–5.701/31.310.10–16.84
Tailors and dressmakers
 743-Tailors and dressmakers5/42.840.62–13.053/0  2/41.160.16–8.47
Mining and mineral processing plant operators
 811-Mining and mineral processing plant operators3/70.540.13–2.203/70.550.14–2.230/0  
Metal-processing plant operators
 812-Metal-processing plant operators4/90.810.23–2.883/60.670.16–2.831/32.080.20–21.86
Chemical processing plant operators3/8        
 815-Chemical processing plant operators3/80.450.11–1.883/80.510.12–2.080/0  
Chemical products machine operators
 822-Chemical products machine operators3/70.500.12–2.153/50.640.14–2.880/2  
Rubber and plastics products machine operators
 823-Rubber and plastics products machine operator7/42.820.75–10.677/33.450.85–14.080/1  
Textile products machine operators
 826-Textile products machine operators17/381.930.96–3.885/32.280.51–10.1712/351.260.52–3.07
 8263-Sewing and embroidering machine operators13/242.911.31–6.502/0  11/241.960.78–4.92
 82631-Sewing machinist12/233.071.35–6.961/0  11/232.260.90–5.65
 8264-Textile bleaching, dyeing and cleaning machine operators3/100.810.19–3.543/0  0/10  
Drivers and mobile machinery operators
 83-Drivers and mobile machinery operators39/550.860.52–1.4336/520.850.50–1.433/32.480.33–18.43
 832-Motor vehicle drivers24/340.930.51–1.6922/310.880.47–1.663/32.480.33–18.43
 8321-Car, taxi and light van operators12/210.730.33–1.6011/180.750.33–1.721/30.420.03–6.77
 83211-Taxi driver3/120.500.14–1.852/100.320.07–1.531/21.130.04–35.01
 83212-Light truck or van driver9/100.860.32–2.329/91.100.40–3.030/1  
 8322-Bus drivers7/71.690.55–5.265/71.210.35–4.142/0  
 83221-Passenger coach driver7/71.690.55–5.265/71.210.35–4.142/0  
 8323-Heavy truck drivers16/131.360.60–3.0916/131.610.71–3.670/0  
 83231-Heavy truck or tanker driver16/131.360.60–3.0916/131.610.71–3.670/0  
 833-Agricultural, earthmoving and other materials-handling equipment13/190.760.35–1.6613/190.830.38–1.820/0  
 8331-Motorised farm machinery operators5/80.640.19–2.145/80.630.19–2.150/0  
 8332-Earthmoving and related machinery operators6/110.570.19–1.706/110.670.23–1.980/0  
 83325-Roading and/or paving machine operator3/90.340.08–1.393/90.400.10–1.620/0  
Building and related workers
 84-Building and related workers8/62.150.68–6.737/61.630.51–5.261/0  
 91512 – Builders laborer10/62.650.92–7.6310/62.590.90–7.440/0  
Table III. Odds Ratios and 95% CIs for A Priori High Risk Industries
A priori high risk industry for bladder cancerAll (213 cases, 471 controls)Men (165 cases, 221 controls)Women (48 cases, 250 controls)
cases/ controls (n)OR95%CIcases/ controls (n)OR95%CIcases/ controls (n)OR95%CI
  1. Numbers were too small (less than 10 cases + controls) for the following a priori high risk industries: chemical manufacturing, paint manufacturing.

  2. OR: odds ratio, adjusted for gender, age group, smoking status, Maori ethnicity, occupational status.

  3. 95%CI: 95% confidence interval of the odds ratio.

Horticulture
 A011-Horticulture and fruit growing16/321.340.69–2.609/180.810.35–1.907/143.031.06–8.65
 A0113-Vegetable growing4/81.030.29–3.713/60.790.19–3.331/21.970.16–23.81
Mining
 B-Mining14/101.690.69–4.1314/101.690.70–4.120/0  
Textile, clothing, footwear and leather manufacture
 C22-Textile, clothing, footwear and leather manufacture20/501.470.78–2.766/100.720.24–2.1814/401.560.68–3.56
 C222-Textile product manufacturing3/140.700.18–2.751/40.240.02–3.022/100.900.18–4.55
 C2221-Made-up textile product manufacturing3/71.750.41–7.451/20.910.08–10.332/51.790.31–10.41
 C224-Clothing manufacturing11/272.040.90–4.632/0  9/271.200.46–3.17
Printing
 C2412-Printing4/81.020.28–3.673/50.870.19–3.871/31.260.09–17.53
Plastic product manufacturing
 C256-Plastic product manufacturing8/82.100.72–6.187/42.670.72–9.841/40.950.09–9.66
Metal product manufacturing
 C27-Metal product manufacturing25/301.450.79–2.6522/201.510.77–2.963/101.180.29–4.88
 C271-Iron and steel manufacturing8/71.970.65–6.028/42.780.79–9.760/3  
 C274-Structural metal product manufacturing8/72.100.69–6.376/51.490.43–5.182/25.250.57–48.69
 C276-Fabricated metal product manufacturing9/101.550.58–4.137/71.310.43–3.972/32.270.31–16.37
Building construction
 E411-Building construction26/391.060.60–1.8624/360.960.54–1.722/34.000.54–29.56
 E4111-House construction14/260.840.41–1.7113/250.810.39–1.691/15.200.17–159.08
 E4113-Non-residential building construction7/120.940.35–2.567/110.930.34–2.550/1  
Painting and decorating services
 E4244-Painting and decorating services7/91.130.39–3.296/71.110.34–3.561/21.380.10–19.76
Retail trade
 G-Retail trade73/1810.930.64–1.3652/701.000.64–1.5921/1110.750.37–1.50
 G51-Food retailing25/870.760.45–1.2816/280.770.39–1.519/590.660.28–1.54
 G52-Personal and household good retailing40/941.180.74–1.8926/221.500.79–2.8314/720.780.37–1.65
 G53-Motor vehicle retailing and services24/430.860.48–1.5420/330.760.40–1.434/102.410.66–8.77
Road transport
 I61-Road transport21/231.420.72–2.7817/211.180.57–2.434/28.521.17–61.97
 I611-Road freight transport12/81.650.61–4.4712/82.030.74–5.530/0  
 I612-Road passenger transport10/151.300.55–3.066/130.730.26–2.044/28.521.17–61.97
Hairdressing and beauty salons
 Q9526-Hairdressing and beauty salons7/55.351.37–20.93/0  4/54.790.90–25.32
Hairdressers

Hairdressers had an elevated risk of bladder cancer (Odds Ratio (OR) 9.15 95% confidence interval (95%CI) 1.60–62.22).The same pattern was observed for the industrial classification of ‘hairdressing and beauty salons’ (OR 5.35, 95%CI 1.37–20.9). The association appeared to be present in both males and females, but the numbers for males were small and there were no exposed controls. However, there were no consistent patterns by duration of employment (see web tables) although the numbers were relatively small. For hairdressers, the OR was 2.87 (95% CI 0.59–13.89) in ever smokers and 9.66 (95% CI 0.62–151.42) in nonsmokers.

Salesworkers

Overall, there was little or no evidence of an increased risk in sales workers. Sales assistants had an OR of 1.03 (95%CI 0.64–1.67); there was a suggestion of an elevated risk in males (OR 1.60, 95%CI 0.83–3.10), whereas there was a significantly reduced risk in females (OR 0.42, 95%CI 0.18–0.95). There was also little evidence of an increased risk for work in the retail trade.

Market farmers and crop growers

Overall, there was no increased risk for market farmers and crop growers (OR 0.92, 95%CI 0.50–1.67), although there was a nonsignificantly elevated risk in women (OR 2.05, 95%CI 0.72–5.83). For the industrial category of ‘horticulture and fruit growing,’ there was a small elevated risk (OR 1.34, 95%CI 0.69–2.60) which was statistically significant in women (OR 3.03, 95%CI 1.06–8.65).

Tailors and dressmakers

Tailors and dressmakers had a nonsignificantly increased risk (OR 2.84, 95%CI 0.62–13.05).

Rubber workers

Rubber and plastics machine operators had a nonsignificantly increased risk (OR 2.82, 95%CI 0.75–10.67), as did work in plastic product manufacturing (OR 2.10, 95%CI 0.72–6.18).

Textile workers

Textile products machine operators had an increased risk (OR 1.93, 95%CI 0.96–3.88) which was statistically significant for sewing machinists (OR 3.07, 95%CI 1.35–6.96). There was some evidence of an association with duration of employment (see web tables), with odds ratios of 0.77 (95% CI 0.19–3.20), 2.32 (95% CI 0.90–5.96) and 4.53 (95% CI 0.90–22.90) for 1–2, 2–10, and 10+ years of employment as a textile products machine operator. The OR was 1.78 (95% CI 0.74–4.52) in ever smokers and 2.21 (95% CI 0.75–6.50) in nonsmokers. There was a nonsignificantly increased risk for clothing manufacturing (OR 2.04, 95%CI 0.90–4.63), but there was little evidence of an association with duration of employment (see web tables).

Drivers

Overall, there was little evidence of an increased risk in motor vehicle drivers (OR 0.93, 95%CI 0.51–1.69) or heavy truck drivers (OR 1.36, 95%CI 0.60–3.09), or for work in road transport (OR 1.42, 95%CI 0.72–2.78). However, the latter category showed a significantly increased risk for women (OR 8.52, 95%CI 1.17–61.97), and there was a nonsignificantly increased risk for road freight transport in men (OR 2.03, 95%CI 0.74–5.53).

Building workers

There was a nonsignificantly elevated risk in building workers (OR 2.15, 95%CI 0.68–6.73), but not for work in building construction (OR 1.06, 95%CI 0.60–1.86).

Other a priori high risk occupations

There was little evidence of an increased risk for occupations involving metal work (Table II), but there were nonsignificantly increased risks for metal product manufacturing (Table III) The a priori high risk occupations and industries of painting, mining, chemical processing and printing showed little evidence of increased risks.

Semi-Bayes adjustment of the a priori high risk occupations and industries

Ever being employed in one or more of the a priori high risk occupations (Table II) and industries (Table III) was associated with only a slight increased risk for bladder cancer (ORa priori occupation1.01 95%CI 0.69-1.48; ORa priori industry1.57 95%CI 1.07-2.32). All estimates in Tables II and III were also regressed towards these means using SB adjustment. This generally resulted in an attenuation of the ORs (see web-based tables), and only one of the ORs for the a priori high risk occupations (82631 – sewing machinist, OR 2.08 95%CI 1.00–4.35) remained statistically significant at the p < 0.05 level after SB adjustment.

Occupations and industries with an observed increased or decreased risk (p < 0.05) but not considered an a priori high risk occupation, are listed in Table IV. A number of occupations and industries showed a statistically significant decreased risk for bladder cancer, but almost all of these were no longer statistically significant after SB adjustment. Three occupations showed a statistically significant increased risk (see Table IV), in addition to the a priori high risk occupations listed in Table II, but none of these remained statistically significant after SB adjustment. Four occupations showed a statistically significant increased risk (see Table IV), in addition to the a priori high risk industries listed in Table III, but none of these remained statistically significant after SB adjustment. However, the reduced risk for work in education and the increased risks for work in manufacturing, and specifically in ‘other food manufacturing’ remained statistically significant after SB adjustment.

Table IV. Odds Ratios and 95% CIs for A Posteriori High and Low Risk (p < 0.05) Occupations and Industries (Excluding the A Priori High Risk Occupations Listed in Tables 2 and 3)
Aposteriori high and low risk occupation and industry for bladder cancercases/controls (n)Not Semi-Bayes adjustedSemi-Bayes adjusted
OR95% CIOR95% CI
  1. OR: odds ratio, adjusted for gender, age group, smoking status, Maori ethnicity, occupational status.

  2. 95%CI: 95% confidence interval of the odds ratio.

Occupations—reduced risk
 2331-Primary teaching professionals3/370.260.07–0.900.620.28–1.38
 331-Finance and sales associate professionals23/530.530.30–0.950.630.38–1.04
 4114-Secretaries3/490.280.08–0.950.630.28–1.39
 422-Client information clerks4/450.280.09–0.850.570.27–1.23
Occupations—increased risk
 12213-Production manager (manufacturing)9/62.991.01–8.861.750.83–3.68
 311-Physical science and engineering technicians13/102.771.15–6.701.760.89–3.47
 8143-Papermaking plant operators6/112.801.31–125.111.550.60–4.02
Industries—reduced risk
 K75-Services to finance and insurance1/320.080.01–0.570.620.24–1.60
 K752-Services to insurance1/240.100.01–0.800.710.28–1.79
 L77-Property services3/270.180.05–0.630.530.23–1.21
 L772-Real estate agents2/210.180.04–0.840.650.27–1.55
 N-Education23/1280.440.26–0.760.530.32–0.85
 N842-School education13/850.490.25–0.950.630.36–1.11
 N8421-Primary education5/450.340.13–0.920.620.30–1.28
 N844-Other education3/160.180.06–0.540.490.22–1.08
Industries—increased risk
 A015-Other livestock farming9/212.262.29–65.802.030.82–5.04
 C-Manufacturing132/2081.601.20–2.311.491.05–2.12
 C217-Other food manufacturing13/64.921.69–14.322.191.02–4.67
 C2179-Food manufacturing NEC8/29.171.83–46.061.950.80–4.77
 Q-Personal and other services38/681.641.02–2.651.470.95–2.28

Discussion

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References

This study of 213 incident bladder cancer cases diagnosed in New Zealand during 2003 and 2004 and 471 population controls aimed to identify occupations that entail an elevated risk for bladder cancer in New Zealand. After adjustment for age, smoking status, and socioeconomic status, this study showed that hairdressers and some textile workers remain at high risk for bladder cancer, and that several other occupations and industries including horticultural workers (females), tailors and dressmakers, and rubber workers may have an increased risk.

Before discussing the detailed study findings, the strengths and limitations of the study should be acknowledged. The study was population-based with the National Cancer Registry providing virtually complete coverage of incident cancers, and the Electoral Roll providing a near complete population register for the sampling of controls. Interviews were conducted face-to-face and involved a detailed occupational history. The main limitations of the study are the low response rates (estimated as 64% of cases and 48% of controls), and hence the relatively small number of cases interviewed. However, as noted earlier, there is little evidence of systematic response bias, apart from the particularly low response rate in the lowest occupational class in the controls, which was controlled for in the analysis. The small number of cases and controls interviewed is perhaps of greater concern, as there were a number of occupations and industries that showed elevated relative risks, consistent with previous studies, which were not statistically significant because of the small numbers involved.

Hairdressers

We found a strongly increased risk (OR 9.15) for hairdressers, and for employment in the hairdressing industry (OR 5.35). Hairdressing has been identified as a risk for bladder cancer in several previous studies.11–14 The causative agent is generally assumed to be hair dyes because of their toxicology,15 although studies of personal use of hair dyes have found only limited evidence for increased bladder cancer risks.16–19 However, the finding that permanent hair dye users that are also slow acetylators of aromatic amines are at particularly increased risk of bladder cancer adds to the evidence of a likely causal role of aromatic amines.20, 21

Textile workers

We found a significantly increased risk for sewing machinists (OR 3.07). An excess of bladder cancer has previously been reported in workers with textiles,12, 14, 22, 23 tailors, dressmakers, weavers, and upholstery workers,24, 25 and leatherworkers,26–28 but not necessarily sewing machine operators. Claude et al.24 showed an increasing trend with employment as a tailor, weaver and upholsterer, with a relative risk of 2.5 at 10+ years. The presumptive causative agent for excess bladder cancer risks in the textile industry is not known, but textile dyes are plausible candidates,29 and once again the likely causative agents are aromatic amines.

Sales workers

A large number of epidemiological studies have reported positive associations between bladder cancer and sales occupations. A recent meta-analysis30 concluded that publication bias explained most of the reported increased bladder cancer risk in men, but sales work still appeared to be associated with a small risk in women. However, the current study found little overall evidence of an increased risk; there was a nonsignificantly increased risk in men (OR 1.60), whereas there was a significantly reduced risk in women (OR 0.42). Possible causal factors include lower frequency of urination and reduced fluid intake.30

Farming

We found a nonsignificantly increased risk in women for the occupational category of ‘market farmers and crop growers’ (OR 2.05) and a significantly increased risk for the industry category of ‘horticulture and fruit growing’ (OR 3.03). An excess of bladder cancer has been shown in female field, crop and vegetable farm workers,30 gardeners31 and in workers using insecticides32, 33 and herbicides,34 but was not found in a meta-analysis of cancer among farmers.35 't Mannetje et al.25 have shown an increasing trend with years as a field, crop and vegetable farm worker, with a relative risk of 2.1 at 25+ years of exposure. They postulated that this may be related to exposure to pesticides.

Painters

An excess of bladder cancer in painters has been reported in several studies22, 24, 26, 34, 36 many showing a significant positive trend with years of employment. Relative risks at 10+ years employment were reported as 1.39,22 1.6,36 and 8.4,24 and at 20+ years 2.024 and 4.1.22 Silverman et al.36 noted that painters may have been exposed to benzidine, polychlorinated biphenyls, formaldehyde, benzene, dioxane and methylene chloride may have been the causative factors. Elevated risk for bladder cancer has also been reported among artistic painters.37, 38 However, we found no evidence of an increased risk in the current study.

Metal workers

A number of published studies have shown excess risks of bladder cancer in turners, foundry workers, sheetmetal workers, drill press operatives and blacksmiths,24, 31, 36 in workers exposed to cutting and lubricating oils,24, 39 and in machinists.1, 1, 1, 40 The associated agents are the cutting and lubricating oils.24 These sometimes contain aromatic amines as additives and N-nitrosamines can be found in the semi-synthetic and synthetic cutting fluids. Hours et al.39 found an elevated odds ratio of 2.56 (95% CI 1.2–1.4) for bladder cancer cases exposed to cutting fluids after adjusting for socioprofessional status and tobacco smoking, compared to general referents. Several studies reported relative risks for length of exposure.41 At 10 or more years of employment the relative risk was 2.4 for drill press operatives,36 2.3 for foundry workers,24 and 3.2 for female blacksmiths, toolmakers, and machine tool operators.25 We found little evidence of an increased risk for these occupations in the current study.

Drivers

A number of published studies have shown an excess of bladder cancer in truck and other drivers.22, 24, 36 Relative risks associated with 10 or more years of driving have been reported as ranging from 1.524 to 5.5.36 Increased risks have particularly been associated with exposure to diesel exhaust fumes.42, 43, 44, 45 In the current study, we found little evidence of an increased risk in truck drivers, although there was a significant association in women for employment in the road transport industry (OR 8.52).

Building workers

We found a nonsignificantly increased risk for building workers (OR 2.15) and builders' laborers (OR 2.65). Increased risks in construction workers have previous been reported by Silverman et al.36 and Porru et al.43

Conclusions

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References

This study observed a diverse list of high risk occupations for bladder cancer largely in concordance with previous studies in New Zealand and elsewhere. Most notably, bladder cancer risk was increased for hairdressers and textile workers. These are both female-dominant occupations in which the likely causative agents are aromatic amines. There were also nonsignificantly increased risks for tailors and dressmakers, rubber and plastics products machine operators, building workers, and female market farmers and crop growers.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References

Authors thank Ms. Rochelle Berry for her work on the data collection for this project. We also thank Ms. Pam Miley-Terry, Ms. Joy Stubbs, Ms. Catherine Douglas, Ms. Trish Knight, Ms. Nicky Curran, Ms. Heather Duckett, and the Department of Labor staff who conducted case and control interviews, and Jenny West, Mr. Frank Darby and Dr. Geraint Emrys for facilitating the conduct of the study. We also thank the staff of the New Zealand Cancer Registry at the New Zealand Health Information Service for collecting and making available information on cancer registrations.

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  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References
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