Self-rated health and mortality among black and white adults: examining the dynamic evaluation thesis.
OBJECTIVE
Many studies of self-rated health show that it is a reliable predictor of mortality even when controlling for health-related variables and status characteristics. According to previous research, one reason for the consistent finding is that self-ratings of health represent judgments of health trajectories. Although self-ratings of health may be dynamic perceptions of health, relatively few studies have systematically examined this possibility.


METHODS
This study reexamines the prognostic value of self-ratings of health on mortality with data from 20 years of the National Health and Nutrition Examination Survey-I Epidemiologic Follow-up Study (N = 6,833). Special attention is given to differences between White and African Americans.


RESULTS
Results indicate that event history models of mortality with self-rated health treated as a time-dependent covariate are superior to those treating it as a baseline predictor only-the latter are likely to underestimate the effect. Moreover, self-ratings of health predict mortality for African Americans only when treated as a time-dependent covariate.


CONCLUSIONS
The results suggest that self-ratings of health are sensitive to declines in physical health, especially those associated with terminal drop. The analysis also demonstrates the importance of using dynamic models for studying the link between self-rated health and mortality if data from multiple observation points are available.
Ferraro
K F
KF
Department of Sociology and Gerontology Program, Purdue University, West Lafayette, Indiana, USA. ferraro@purdue.edu
Kelley-Moore
J A
JA
D000328:Adult; D001741:Black or African American / Q000706:statistics & numerical data*; D000368:Aged; D005260:Female; D006304:Health Status; D006801:Humans; D008297:Male; D008875:Middle Aged; D009026:Mortality; D015999:Multivariate Analysis; D016017:Odds Ratio; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D012306:Risk; D012307:Risk Factors; D014481:United States / Q000453:epidemiology; D044465:White People / Q000706:statistics & numerical data*