Identification of risk factors for 15-year mortality among community-dwelling older people using Cox regression and a genetic algorithm.
BACKGROUND
Previous research has identified various risk factors for mortality in older people, but has considered a limited number of the variables available for analysis. The aim of this study was to use a genetic algorithm combined with Cox regression (CoRGA) to examine all the variables to identify risk factors for 15-year mortality.


METHODS
Data were obtained from a nationally representative sample of 1,042 community-dwelling people aged 65+. Data on cognitive impairment, physical health, physical activity, psychological well-being, social engagement, and physical capability resulted in 460 independent variables for analysis. Outcome was time from 1985 interview to death or censorship on February 29, 2000. CoRGA was used to selected combinations of 1, 2, 4, 8, 12, and 16 variables as potential risk factors for 15-year mortality.


RESULTS
CoRGA selected age in all six models; variables relating to handgrip strength were selected in five models; variables relating to reported chest pain were selected in four models; and pain in joints causing difficulty in carrying bags and self-rated activity compared to peers were both selected in three models. Other variables selected by CoRGA included time since last visited the dentist and optician, use of hypnotic drugs, and number of prescribed drugs being taken.


CONCLUSIONS
CoRGA confirmed current risk factors for long-term mortality among older people and identified new risk factors. Age was confirmed as the most important predictor of mortality in older people. Handgrip strength is an important marker of frailty in predicting mortality. Self-rated activity is an important predictor of long-term mortality.
Ahmad
Rabiah
R
Health Informatics Research Group, Department of Information Studies, and Department of Information Studies, The University of Sheffield, Sheffield S1 4DP, U.K.
Bath
Peter A
PA
D000368:Aged; D000375:Aging; D000465:Algorithms; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D009026:Mortality / Q000639:trends*; D016016:Proportional Hazards Models; D012111:Residence Characteristics; D012307:Risk Factors; D006113:United Kingdom / Q000453:epidemiology