title: Local bladder cancer clusters in southeastern Michigan accounting for risk factors, covariates and residential mobility.
abstract: BACKGROUND
  In case control studies disease risk not explained by the significant risk factors is the unexplained risk. Considering unexplained risk for specific populations, places and times can reveal the signature of unidentified risk factors and risk factors not fully accounted for in the case-control study. This potentially can lead to new hypotheses regarding disease causation.
  
  
  METHODS
  Global, local and focused Q-statistics are applied to data from a population-based case-control study of 11 southeast Michigan counties. Analyses were conducted using both year- and age-based measures of time. The analyses were adjusted for arsenic exposure, education, smoking, family history of bladder cancer, occupational exposure to bladder cancer carcinogens, age, gender, and race.
  
  
  RESULTS
  Significant global clustering of cases was not found. Such a finding would indicate large-scale clustering of cases relative to controls through time. However, highly significant local clusters were found in Ingham County near Lansing, in Oakland County, and in the City of Jackson, Michigan. The Jackson City cluster was observed in working-ages and is thus consistent with occupational causes. The Ingham County cluster persists over time, suggesting a broad-based geographically defined exposure. Focused clusters were found for 20 industrial sites engaged in manufacturing activities associated with known or suspected bladder cancer carcinogens. Set-based tests that adjusted for multiple testing were not significant, although local clusters persisted through time and temporal trends in probability of local tests were observed.
  
  
  CONCLUSIONS
  Q analyses provide a powerful tool for unpacking unexplained disease risk from case-control studies. This is particularly useful when the effect of risk factors varies spatially, through time, or through both space and time. For bladder cancer in Michigan, the next step is to investigate causal hypotheses that may explain the excess bladder cancer risk localized to areas of Oakland and Ingham counties, and to the City of Jackson.
authors: Department of Geography, University at Buffalo, The State University of New York, Buffalo, New York, United States of America; BioMedware Inc., Ann Arbor, Michigan, United States of America.
authors: Geoffrey M
authors: GM
authors: Jacquez
authors: Department of Geography, University at Buffalo, The State University of New York, Buffalo, New York, United States of America.
authors: Chen
authors: C
authors: Shi
authors: Department of Preventive Medicine and Graduate Program in Public Health, Stony Brook University, Stony Brook, New York, United States of America.
authors: Jaymie R
authors: JR
authors: Meliker
mesh_terms: D000367:Age Factors; D001151:Arsenic / Q000009:adverse effects*; D016000:Cluster Analysis; D004522:Educational Status; D005843:Geography; D006801:Humans; D008824:Michigan / Q000453:epidemiology; D016273:Occupational Exposure / Q000706:statistics & numerical data*; D044469:Racial Groups; D012307:Risk Factors; D012737:Sex Factors; D012907:Smoking; D001749:Urinary Bladder Neoplasms / Q000453:epidemiology*
chemical_list: D001151:Arsenic