title: Smoking as a confounder in case-control studies of occupational bladder cancer in women.
abstract: BACKGROUND
  In studies in men, risk estimates on occupation and bladder cancer are distorted by about 10% when not adjusting for smoking. We examined the degree to which occupational risk estimates for bladder cancer in women are confounded by smoking, and the degree of residual confounding by inadequate control of this effect.
  
  
  METHODS
  Primary data of 11 case-control studies on occupation and bladder cancer from Denmark, France, Germany, Greece, Italy, and Spain were pooled. Information for smoking and lifetime occupational history for 700 female cases and 2,425 female controls ages 30-79 was abstracted and recoded. Logistic regression was used to calculate odds ratios (OR) by occupation, applying five models which differed in their degree of adjustment for smoking.
  
  
  RESULTS
  In major occupational groups, risk estimates were distorted by less than 10% when not adjusting for smoking. A statistically significant excess risk for bladder cancer was found in 13 specific occupations and industries. In most occupations, adjustment for smoking led the ORs towards the null value, but all statistically significant associations were maintained after adjustment. In three occupations (lathe operators, field crop workers, and wood manufacturers), a statistically significant excess risk was masked when not adjusting for smoking. In six occupations, estimates were distorted by more than 10% (-22% up to +40%). In occupations where smoking acted as a positive confounder, the proportion of confounding removed using a dichotomous smoking variable (ever/never) was around 60%. In one occupation (buyers), controlling for smoking status (ever, never) led to over-adjustment, because the percentage of smokers was high but the quantity smoked was low.
authors.affiliation: Respiratory and Environmental Health Research Unit, IMIM, Barcelona, Spain.
authors.forename: A
authors.initials: A
authors.lastname: 't Mannetje
authors.forename: M
authors.initials: M
authors.lastname: Kogevinas
authors.forename: J
authors.initials: J
authors.lastname: Chang-Claude
authors.forename: S
authors.initials: S
authors.lastname: Cordier
authors.forename: C A
authors.initials: CA
authors.lastname: González
authors.forename: M
authors.initials: M
authors.lastname: Hours
authors.forename: K H
authors.initials: KH
authors.lastname: Jöckel
authors.forename: U
authors.initials: U
authors.lastname: Bolm-Audorff
authors.forename: E
authors.initials: E
authors.lastname: Lynge
authors.forename: S
authors.initials: S
authors.lastname: Porru
authors.forename: F
authors.initials: F
authors.lastname: Donato
authors.forename: U
authors.initials: U
authors.lastname: Ranft
authors.forename: C
authors.initials: C
authors.lastname: Serra
authors.forename: A
authors.initials: A
authors.lastname: Tzonou
authors.forename: P
authors.initials: P
authors.lastname: Vineis
authors.forename: J
authors.initials: J
authors.lastname: Wahrendorf
authors.forename: P
authors.initials: P
authors.lastname: Boffetta
mesh_terms: D000328:Adult; D017677:Age Distribution; D000368:Aged; D016022:Case-Control Studies; D016001:Confidence Intervals; D015986:Confounding Factors, Epidemiologic; D005060:Europe / Q000453:epidemiology; D005260:Female; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D009784:Occupational Diseases / Q000453:epidemiology* / Q000209:etiology; D009790:Occupations / Q000145:classification / Q000706:statistics & numerical data; D016017:Odds Ratio; D012107:Research Design / Q000592:standards*; D012307:Risk Factors; D012907:Smoking / Q000009:adverse effects / Q000453:epidemiology*; D001749:Urinary Bladder Neoplasms / Q000453:epidemiology* / Q000209:etiology; D016387:Women's Health