Skip to main content

What Matters Most for Predicting Survival? A Multinational Population-Based Cohort Study

Author(s): Goldman, Noreen; Glei, Dana A; Weinstein, Maxine

Download
To refer to this page use: http://arks.princeton.edu/ark:/88435/pr1bg6z
Full metadata record
DC FieldValueLanguage
dc.contributor.authorGoldman, Noreen-
dc.contributor.authorGlei, Dana A-
dc.contributor.authorWeinstein, Maxine-
dc.date.accessioned2016-10-17T14:14:08Z-
dc.date.available2016-10-17T14:14:08Z-
dc.date.issued2016-07-19en_US
dc.identifier.citationGoldman, Noreen, Glei, Dana A, Weinstein, Maxine. "What Matters Most for Predicting Survival? A Multinational Population-Based Cohort Study" PLOS ONE, (7), 11, e0159273 - e0159273, doi:10.1371/journal.pone.0159273en_US
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr1bg6z-
dc.description.abstractDespite myriad efforts among social scientists, epidemiologists, and clinicians to identify variables with strong linkages to mortality, few researchers have evaluated statistically the relative strength of a comprehensive set of predictors of survival. Here, we determine the strongest predictors of five-year mortality in four national, prospective studies of older adults. We analyze nationally representative surveys of older adults in four countries with similar levels of life expectancy: England (n = 6113, ages 52+), the US (n = 2023, ages 50+), Costa Rica (n = 2694, ages 60+), and Taiwan (n = 1032, ages 53+). Each survey includes a broad set of demographic, social, health, and biological variables that have been shown previously to predict mortality. We rank 57 predictors, 25 of which are available in all four countries, net of age and sex. We use the area under the receiver operating characteristic curve and assess robustness with additional discrimination measures. We demonstrate consistent findings across four countries with different cultural traditions, levels of economic development, and epidemiological transitions. Self-reported measures of instrumental activities of daily living limitations, mobility limitations, and overall self-assessed health are among the top predictors in all four samples. C-reactive protein, additional inflammatory markers, homocysteine, serum albumin, three performance assessments (gait speed, grip strength, and chair stands), and exercise frequency also discriminate well between decedents and survivors when these measures are available. We identify several promising candidates that could improve mortality prediction for both population-based and clinical populations. Better prognostic tools are likely to provide researchers with new insights into the behavioral and biological pathways that underlie social stratification in health and may allow physicians to have more informed discussions with patients about end-of-life treatment and priorities.en_US
dc.format.extente0159273 - e0159273en_US
dc.relation.ispartofPLOS ONEen_US
dc.rightsThis is the publisher’s version of the article (version of record). All rights reserved to the publisher. Please refer to the publisher's site for terms of use.en_US
dc.titleWhat Matters Most for Predicting Survival? A Multinational Population-Based Cohort Studyen_US
dc.typeJournal Articleen_US
dc.identifier.doidoi:10.1371/journal.pone.0159273-
dc.date.eissued2016-07-19en_US
dc.identifier.eissn1932-6203-

Files in This Item:
File Description SizeFormat 
OAWhatMattersMost.PDF1.29 MBAdobe PDFView/Download


Items in OAR@Princeton are protected by copyright, with all rights reserved, unless otherwise indicated.