title: Risk factors of falls in community-dwelling older adults: logistic regression tree analysis.
abstract: OBJECTIVE
  A novel logistic regression tree-based method was applied to identify fall risk factors and possible interaction effects of those risk factors.
  
  
  METHODS
  A nationally representative sample of American older adults aged 65 years and older (N = 9,592) in the Health and Retirement Study 2004 and 2006 modules was used. Logistic Tree with Unbiased Selection, a computer algorithm for tree-based modeling, recursively split the entire group in the data set into mutually exclusive subgroups and fit a logistic regression model in each subgroup to generate an easily interpreted tree diagram.
  
  
  RESULTS
  A subgroup of older adults with a fall history and either no activities of daily living (ADL) limitation and at least one instrumental activity of daily living or at least one ADL limitation was classified as at high risk of falling. Additionally, within each identified subgroup, the best predictor of falls varied over subgroups and was also evaluated.
  
  
  CONCLUSIONS
  Application of tree-based methods may provide useful information for intervention program design and resource allocation planning targeting subpopulations of older adults at risk of falls.
authors.affiliation: Scripps Gerontology Center, Miami University, Oxford, OH 45056, USA. yamasht@muohio.edu
authors.forename: Takashi
authors.initials: T
authors.lastname: Yamashita
authors.forename: Douglas A
authors.initials: DA
authors.lastname: Noe
authors.forename: A John
authors.initials: AJ
authors.lastname: Bailer
mesh_terms: D000058:Accidental Falls / Q000517:prevention & control / Q000706:statistics & numerical data*; D000203:Activities of Daily Living; D000368:Aged; D000369:Aged, 80 and over; D003663:Decision Trees; D005260:Female; D015577:Geriatric Assessment / Q000379:methods*; D006306:Health Surveys; D006801:Humans; D016015:Logistic Models; D008297:Male; D011237:Predictive Value of Tests; D012111:Residence Characteristics; D018570:Risk Assessment / Q000379:methods*; D012959:Socioeconomic Factors; D014481:United States