Predictors of mortality in 2,249 nonagenarians--the Danish 1905-Cohort Survey.
OBJECTIVE
: To elucidate whether well-known predictions of mortality are reduced or even reversed, or whether mortality is a stochastic process in the oldest old.


METHODS
: A multidimensional survey of the Danish 1905 cohort conducted in 1998 with follow-up of vital status after 15 months.


METHODS
: Denmark.


METHODS
: All Danes born in 1905, irrespective of physical and mental status were approached. Two thousand two hundred sixty-two persons of 3,600 participated in this survey.


METHODS
: Professional interviewers collected data concerning sociodemographic factors, smoking, alcohol consumption, body mass index, physical and cognitive performance, and health during a visit at the participant's residency. Cox regression models were used to evaluate predictors of mortality.


RESULTS
: Five hundred seventy-nine (25.7%) of the 2,249 participants eligible for the analysis died during the 15 months follow-up. Multivariate analyses showed that marital status, education, smoking, obesity, consumption of alcohol, and number of self-reported diseases were not associated with mortality. Disability and cognitive impairment were significant risk factors in men and women. In addition poor self-rated health was associated with an increase in mortality in women.


CONCLUSIONS
: In the oldest old, several known predictors of mortality, such as sociodemographic factors, smoking, and obesity, have lost their importance, but a high disability level, poor physical and cognitive performance, and self-rated health (women only), predict mortality, which shows that mortality in the oldest old is not a stochastic process.
D000203:Activities of Daily Living; D000368:Aged; D000369:Aged, 80 and over / Q000706:statistics & numerical data*; D015331:Cohort Studies; D003718:Denmark / Q000453:epidemiology; D005260:Female; D015577:Geriatric Assessment; D006801:Humans; D007407:Interviews as Topic; D008297:Male; D009026:Mortality / Q000639:trends*; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D012307:Risk Factors