title: Do groups of women aged 50 to 75 match the national average mammography rate?
abstract: BACKGROUND
  As mammography rates increase, an important question is how closely groups of women match or do not match the national-level, average screening percentage.
  
  
  OBJECTIVE
  This study employed a classification-tree methodology to combine individual risk factors from multiple logistic regression, in order to more comprehensively define groups of women less (or more) likely to be screened.
  
  
  METHODS
  This report was a secondary data analysis drawing on data from the 1992 National Health Interview Survey, Cancer Control Supplement (NHIS-CCS).
  
  
  METHODS
  Analyses examined mammography status of women aged 50-75 (n = 1,727).
  
  
  METHODS
  The dependent variable was having a screening mammogram in the past 2 years. Multiple logistic regression (SUDAAN) was conducted first to select significant correlates of screening. A classification-tree analysis (CHAID subroutine of SPSS) was then used to combine the significant correlates into exclusive and exhaustive subgroups.
  
  
  RESULTS
  A total of 13 subgroups were identified, of which only six approximated the overall population screening rate. The lowest screening occurred in small clusters of women, which, when added together, formed a larger percentage of the population who were not screened within the past 2 years.
  
  
  CONCLUSIONS
  Efforts to increase mammography may face the challenge of identifying relatively small pockets of women and addressing their individual barriers. Further work should be done to find efficient ways to combine individual risk factors into groups at risk for not being screened.
authors.affiliation: Department of Community Health, Brown University, Providence, RI, 02912, USA.
authors.forename: W
authors.initials: W
authors.lastname: Rakowski
authors.forename: M A
authors.initials: MA
authors.lastname: Clark
mesh_terms: D000368:Aged; D001943:Breast Neoplasms / Q000517:prevention & control; D003663:Decision Trees; D005260:Female; D006801:Humans; D016015:Logistic Models; D008327:Mammography / Q000706:statistics & numerical data*; D008403:Mass Screening / Q000706:statistics & numerical data*; D008875:Middle Aged; D012307:Risk Factors; D012959:Socioeconomic Factors; D014481:United States; D016387:Women's Health