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1.
Occup Environ Med ; 65(4): 249-54, 2008 Apr.
Article in English | MEDLINE | ID: mdl-17928387

ABSTRACT

OBJECTIVES: To assess male lung cancer risks for industrial sectors in the Netherlands and to estimate the proportion of lung cancer attributed to working in specific industrial sectors. METHODS: Associations were studied among men aged 55-69 years (n = 58 279) from the prospective Netherlands Cohort Study. 1920 incident lung cancer cases were available after 11.3 years of follow-up. Based on a case-cohort design, and using Cox proportional hazards models, risks were estimated for blue collar workers in 26 industrial sectors. RESULTS: Adjustment for individual smoking habits affected risk estimates for some sectors, but adjustment for fruit/vegetables and alcohol intake did not. Adjusted for confounders, an increased risk of lung cancer was observed for employment for >/=15 years in blue collar jobs in the "electronics and optical instruments" industry (rate ratio (RR) 1.99; 95% CI 1.18 to 3.35), "construction and homebuilding business" (RR 1.64; 95% CI 1.21 to 2.22) and "railway company" (RR 2.40; 95% CI 1.00 to 5.73). The attributable fraction for working for >/=15 years in these three industries was 5%. In three other sectors there was a statistically non-significant elevated RR of >1.5. CONCLUSIONS: Male lung cancer risk is increased in several industrial sectors. Approximately 2000 lung cancer cases between 1986 and 1997 in the 55-69-year-old age group in the Netherlands may be attributable to working for >/=15 years in the three sectors with increased risk. In addition, estimates for occupational lung cancer risks for sectors may be biased if no individual information is available on smoking habits.


Subject(s)
Lung Neoplasms/epidemiology , Lung Neoplasms/etiology , Occupational Diseases/epidemiology , Occupational Diseases/etiology , Aged , Alcohol Drinking/epidemiology , Epidemiologic Methods , Feeding Behavior , Fruit , Humans , Industry , Male , Middle Aged , Netherlands/epidemiology , Occupational Exposure/adverse effects , Smoking/adverse effects , Smoking/epidemiology , Time Factors , Vegetables
3.
Carcinogenesis ; 21(2): 307-9, 2000 Feb.
Article in English | MEDLINE | ID: mdl-10657973

ABSTRACT

K-ras gene mutations (codons 12 and 13) were determined by PCR-based mutant allele-specific amplification (MASA) in tumour tissue of 185 colon cancer patients: 36% harboured mutations, of which 82% were located in codon 12. High intakes of animal protein, calcium and poultry were differently associated with codon 12 and 13 mutations: odds ratios (OR) and 95% confidence intervals (95% CI) for codon 12 versus codon 13 were 9.0 (2.0-42), 4.1 (1.4-12) and 15 (1.4-160), respectively. In case-control comparisons, high intakes of animal protein and calcium were positively associated with colon tumours harbouring codon 12 mutations [for animal protein per 17 g, OR (95% CI) = 1.5 (1.0-2.1); for calcium per 459 mg, 1.2 (0.9-1.6)], while inverse associations were observed for tumours with K-ras mutations in codon 13 [for animal protein 0.4 (0.2-1.0); for calcium 0.6 (0. 3-1.2)]. Transition and transversion mutations were not differently associated with these dietary factors. These data suggest a different dietary aetiology of colon tumours harbouring K-ras codon 12 and 13 mutations.


Subject(s)
Calcium, Dietary/adverse effects , Carcinoma/genetics , Codon/genetics , Colonic Neoplasms/genetics , DNA, Neoplasm/genetics , Dietary Proteins/adverse effects , Meat/adverse effects , Mutation , Adult , Aged , Animals , Carcinoma/etiology , Case-Control Studies , Colonic Neoplasms/etiology , DNA Adducts , DNA Mutational Analysis , Dairy Products , Dietary Fats , Feeding Behavior , Female , Fishes , Genes, ras , Humans , Male , Middle Aged , Netherlands , Odds Ratio , Polymerase Chain Reaction , Poultry , Surveys and Questionnaires
4.
Int J Cancer ; 81(5): 675-81, 1999 May 31.
Article in English | MEDLINE | ID: mdl-10328215

ABSTRACT

Epidemiological studies have suggested that dietary factors may differently affect p53-dependent and p53-independent pathways to colon cancer. Results of such studies may depend on the method used to assess p53 status. This case-control study of 185 colon-cancer cases and 259 controls examines this relation, using both immunohistochemistry and SSCP(exons 5-8)/sequencing to detect p53 abnormalities. Of 185 carcinomas analyzed using immunohistochemistry, 81 (44%) were categorized as p53 over-expression. p53 mutations were detected in 59 tumors (32%). A slight increase in risk observed for intake of saturated fat was largely due to an increased risk in cases without p53 over-expression (OR per 16.1 g/day, 1.46; 95% CI, 1.08-1.97), and no association in cases with p53 over-expression (OR, 1.07, 95% CI, 0.78-1.47). However, findings were less pronounced when cases were classified by mutation analysis (wild-type OR, 1.33; 95% CI, 1.01-1.75; mutated OR, 1.16; 95% CI, 0.81-1.65). Similar results were observed for total fat intake. For other nutrients and for vegetable and meat food groups no differences in risk for either p53 pathway were observed, independent of the laboratory technique used. Interestingly, in cases with transversion mutations in the p53 gene, an increased risk was observed for saturated fat (OR, 2.00; 95% CI, 0.97-4.14), in contrast to those with mutations at CpG sites (OR, 0.93; 95% CI, 0.55-1.57). An increase in colon-cancer risk for the p53-independent pathway due to fat intake, is more pronounced when using immunohistochemistry. However, mutation analysis is needed to study the possible association with a small group of tumors with transversion mutations.


Subject(s)
Colonic Neoplasms/genetics , Colonic Neoplasms/metabolism , Feeding Behavior , Tumor Suppressor Protein p53/biosynthesis , Tumor Suppressor Protein p53/genetics , Age Factors , Case-Control Studies , Colonic Neoplasms/epidemiology , DNA Mutational Analysis , Diet , Exons/genetics , Female , Humans , Immunohistochemistry , Male , Middle Aged , Mutation , Odds Ratio , Polymorphism, Single-Stranded Conformational , Risk Factors , Sex Factors
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