title: Bladder cancer clusters in Florida: identifying populations at risk.
abstract: OBJECTIVE
  Modifiable risk factors for bladder cancer have been identified, ie tobacco and chemical exposure. We identified high risk bladder cancer areas and risk factors associated with bladder cancer clusters in Florida using individual and area based data.
  
  
  METHODS
  Spatial modeling was applied to 23,266 early and advanced bladder cancer cases diagnosed between 1998 and 2002 in Florida to identify areas of excess bladder cancer risk. Multivariable regression was used to determine whether sociodemographic indicators, smoking history and proximity to known arsenic contaminated drinking water well sites were associated with bladder cancer diagnosis in a specific area (cluster).
  
  
  RESULTS
  A total of 25 clusters were found to have a higher than expected bladder cancer rate, including 13 and 12 of early and late stage disease, respectively. Urban white patients were more likely to live in an advanced bladder cancer cluster. Advanced bladder cancer cluster membership was associated with living in close proximity to known arsenic contaminated drinking water wells.
  
  
  CONCLUSIONS
  There are multiple areas of early and late stage bladder cancer clusters in Florida. Individuals in an advanced bladder cancer cluster tended to live close to arsenic contaminated wells. Increased evaluation of potentially contaminated well water is warranted in these high risk areas. Targeted bladder cancer public awareness campaigns, smoking cessation support and potentially targeted screening should also be considered in communities at increased risk for bladder cancer. Our analytical approach can also be used by others to systematically identify communities at high risk for bladder and other cancers.
authors.affiliation: Division of Urology, Columbia University, Mount Sinai Medical Center, Miami Beach, Florida 33140, USA. alan.nieder@columbia.edu
authors.forename: Alan M
authors.initials: AM
authors.lastname: Nieder
authors.forename: Jill A
authors.initials: JA
authors.lastname: MacKinnon
authors.forename: Lora E
authors.initials: LE
authors.lastname: Fleming
authors.forename: Greg
authors.initials: G
authors.lastname: Kearney
authors.forename: Jennifer J
authors.initials: JJ
authors.lastname: Hu
authors.forename: Recinda L
authors.initials: RL
authors.lastname: Sherman
authors.forename: Youjie
authors.initials: Y
authors.lastname: Huang
authors.forename: David J
authors.initials: DJ
authors.lastname: Lee
mesh_terms: D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D001151:Arsenic / Q000009:adverse effects; D015984:Causality; D016000:Cluster Analysis; D015897:Comorbidity; D003710:Demography; D055088:Early Detection of Cancer; D004787:Environmental Pollution / Q000009:adverse effects / Q000706:statistics & numerical data*; D005260:Female; D005431:Florida / Q000453:epidemiology; D006801:Humans; D016015:Logistic Models; D008297:Male; D008403:Mass Screening; D008875:Middle Aged; D015999:Multivariate Analysis; D009367:Neoplasm Staging; D011336:Probability; D011379:Prognosis; D012042:Registries; D012189:Retrospective Studies; D012307:Risk Factors; D017678:Sex Distribution; D012907:Smoking / Q000009:adverse effects / Q000453:epidemiology*; D016019:Survival Analysis; D001749:Urinary Bladder Neoplasms / Q000175:diagnosis* / Q000453:epidemiology*; D055815:Young Adult
chemical_list: D001151:Arsenic