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Canadian Journal of Public Health = Revue Canadienne de Santé Publique logoLink to Canadian Journal of Public Health = Revue Canadienne de Santé Publique
. 2009 Jul 1;100(4):263–267. doi: 10.1007/BF03403944

A Classification and Regression Tree for Predicting Recurrent Falling among Community-dwelling Seniors Using Home-care Services

Bernard Simon Leclerc 18,✉, Claude Bégin 28, Élizabeth Cadieux 18, Lise Goulet 38, Jean-François Allaire 48, Julie Meloche 48, Nicole Leduc 38, Marie-Jeanne Kergoat 58
PMCID: PMC6973839  PMID: 19722338

Abstract

Objectives: A prospective, observational study was undertaken to identify risk profiles of subjects regarding the recurrence of falling among community-dwelling seniors using home-care services.

Methods: A convenience sample of 868 community-dwelling older persons, aged 65 years or older, who use home-care services offered by public community-based centres in the province of Québec. Subjects were recruited between 2002 and 2005, assessed for fall-related risk factors, and monitored for prospective falls. Data were examined by a classification and regression tree (CART) and survival analyses.

Results: Ninety-nine participants reported two falls within six months of entry to the study. Thus, the incidence of recurrent fallers was 11.4%. The tree analysis classified the population into five groups differing in risk of recurrent falling, based on history of falls in the three months prior to the initial interview, Berg balance score, type of housing, and usual alcohol consumption in the six months preceding study entry. The relative risks varied from 0.7 to 5.1. The survival analysis showed that the length of time before becoming a recurrent faller varies among risk profiles.

Conclusion: The study permitted the construction of easily interpretable risk profiles of recurrent falling. These can guide clinicians and public health practitioners to identify high-risk individuals and to decide on the appropriate intervention and follow-up.

Keywords: Accidental falls, elderly, home care services, multiple classification analysis, prognosis, public health, risk factors, risk assessment, survival analysis

Footnotes

This research is part of Leclerc’s PhD thesis in Public Health and Epidemiology, realized under the supervision of Professors Lise Goulet and Nicole Leduc, respectively from the Département de médecine sociale et préventive and the Département d’administration de la santé, Faculté de médecine, Université de Montréal, Montréal, QC, Canada.

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