- Title
- Predicting Mortality from Standard and Nontraditional Biomarkers
- Author(s)
- Noreen Goldman Noreen Goldman (Princeton University)
- Cassio M. Turra Cassio Turra (Princeton University)
- Dana A. Glei Dana Glei (University of California, Berkeley)
- Christopher L. Seplaki Christopher Seplaki (Johns Hopkins University)
- Yu-Hsuan Lin Yu-Hsuan Lin (Bureau of Health Promotion, Ministry of Health, Taiwan)
- Abstract
- Few studies focus on preclinical warning signs associated with mortality. In this paper, we investigate associations between all-cause mortality and two clusters of biological risk factors: 1) standard clinical measures related to cardiovascular disease and metabolic function; and 2) nontraditional measures pertaining to hypothalamic-pituitary-adrenal axis activity, sympathetic nervous system activity and inflammatory response. Data come from the 2000 Social Environment and Biomarkers of Aging Study, a national sample of Taiwanese ages 54 and older: 1497 persons were interviewed in their homes and 1023 participated in a hospital examination. The analysis is based on 927 respondents with complete information. Logistic regression models describe the association between biomarkers and the three-year probability of dying. Although both groups of biomarkers are significantly associated with mortality, a model with nontraditional biomarkers has better explanatory and discriminatory power than one with clinical measures. The association between the nontraditional measures and mortality remains strong after adjustment for the clinical markers, suggesting that the physiological effects of the nontraditional biomarkers are broader than those captured by the cardiovascular and metabolic system measures included here. Nontraditional markers are likely to provide early warning signs of deteriorating health and function beyond what can be learned from conventional markers. Our findings are consistent with recent studies that 1) demonstrate the importance of neuroendocrine and immune system markers for survival, and 2) indicate that standard clinical variables are less predictive of mortality in older than in younger populations.
- Creation Date
- 2006-01
- Section URL ID
- OPR
- Paper Number
- opr0601.pdf
- URL
- https://web.archive.org/web/20150906193417/http://opr.princeton.edu/papers/opr0601.pdf
- File Function
- Jel
- J19
- Keyword(s)
- biomarkers; mortality; aging; Taiwan
- Suppress
- false
- Series
- 11