Graphical models illustrated complex associations between variables describing human functioning

J Clin Epidemiol. 2009 Sep;62(9):922-33. doi: 10.1016/j.jclinepi.2009.01.018. Epub 2009 Jun 21.

Abstract

Objective: To examine whether graphical modeling is a potentially useful method for the study of human functioning using data collected by means of the International Classification of Functioning, Disability and Health (ICF).

Study design and setting: The applicability of the method was examined in a convenience sample of 616 patients from a cross-sectional multicentric study undergoing early postacute rehabilitation. Functioning was qualified using 115 second-level ICF categories. The modeling was carried out on a data set with imputed missing values. The least absolute shrinkage and selection operator (LASSO) for generalized linear models was used to identify conditional dependencies between the ICF categories. Bootstrap aggregating was used to enhance the accuracy and validity of model selection.

Results: The resulting graph showed highly meaningful relationships. For example, one structure centered around speaking and included three paths addressing conversation, speech functions, and mental functions of language.

Conclusion: Graphical modeling of human functioning using data collected by means of the ICF yields clinically meaningful results. The structures found may be the basis for the identification of suitable targets for rehabilitation interventions, the identification of confounders and intermediate variables, and the selection of parsimonious sets of variables for multivariate epidemiological modeling.

Publication types

  • Multicenter Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Activities of Daily Living
  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Cross-Sectional Studies
  • Disability Evaluation*
  • Female
  • Health Status Indicators*
  • Humans
  • Male
  • Middle Aged
  • Models, Statistical
  • Rehabilitation Centers
  • Rehabilitation*
  • Young Adult