HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Full Text Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Kuchibhatla, M. Articles by Fillenbaum, G. G. Search for Related Content PubMed PubMed Citation Articles by Kuchibhatla, M. Articles by Fillenbaum, G. G.

Assessing Risk Factors for Mortality in Elderly White and African American People: Implications of Alternative Analyses

^a Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC
^b Center for the Study of Aging and Human Development, Duke University Medical Center, Durham

Correspondence: Maragatha Kuchibhatla, PhD, Department of Biostatistics and Bioinformatics, Box 3003, Duke University Medical Center, Durham, NC 27710. E-mail: mnk{at}geri.duke.edu.

Decision Editor: Terrie T. Wetle, PhD

Purpose: The aim of this study was to ascertain whether the determinants of death differ as a function of type of analysis in a representative sample of older African American and White people with comparable mortality rates. Design and Methods: Participants included all African American (n = 2,261) and White (n = 1,875) people at the Duke site of the Established Populations for Epidemiological Studies of the Elderly. Baseline information used to predict mortality 12 years later included demographic, health, and functional characteristics. Mortality (55% for African American people and 54% for White people) was determined through the National Death Index. Cox proportional hazards models, logistic regression, and tree-based classification analysis were used (separately for African American and White people) to identify risk factors for mortality. Results: Risk factors for mortality were comparable, but the constellation of characteristics indicating higher risk for death differed between African American and White people. Implications: Proportional hazards and logistic regression identified risk factors in general; tree-based classification models identified the characteristics of groups at risk. The analysis used may influence the type and manner of intervention.

Key Words: Proportional hazards models • Logistic regression • Classification tree analysis • Racial differences