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Background. Few studies focus on "preclinical" warning signs associated with mortality. In this article, we investigate associations between all-cause mortality and two clusters of biological risk factors: (i) standard clinical measures related to cardiovascular disease and metabolic function; and (ii) nonclinical measures pertaining to hypothalamic-pituitary-adrenal axis activity, sympathetic nervous system activity, and inflammatory response. Methods. Data come from the 2000 Social Environment and Biomarkers of Aging Stud,. a national sample of Taiwanese persons aged 54 years or 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 3-year probability of dying. Results. Although both groups of biomarkers are significantly associated with mortality, the model with neuroendocrine and immune biomarkers has better explanatory and discriminatory power than the one with clinical measures. The association between these nonclinical measures and mortality remains strong after adjustment for the clinical markers, suggesting that the physiological effects of the nonclinical biomarkers are broader than those captured by the cardiovascular and metabolic system measures included here. Conclusions. Nonclinical markers are likely to provide warning signs of deteriorating health and function beyond what can be learned from conventional markers. Our findings are consistent with those of recent studies that (i) demonstrate the importance of neuroendocrine and immune system markers for survival, and (ii) indicate that standard clinical variables are less predictive of mortality in older than in younger populations. [ABSTRACT FROM AUTHOR]

Researchers have had a longstanding interest in understanding the determinants of mortality. This article examines the impact of a broad array of biological markers, together with self-reports of physical and mental health status, on the probability of dying for older adults. The estimates are derived from logistic regression models based on data from a national survey in Taiwan. The analysis confirms previous studies demonstrating the effects of clinical measures related to metabolic syndrome on mortality and identifies detrimental effects of neuroendocrine and immune-system markers. The results reveal that biomarkers provide independent explanatory power in the presence of self-reported health measures. The associations between biomarkers and mortality found here provide new avenues for projecting future mortality and elucidating differences in longevity across populations. [ABSTRACT FROM AUTHOR]

Abstract: The theory of allostatic load [McEwen, B.S., Stellar, E., 1993. Stress and the individual: mechanisms leading to disease. Arch. Intern. Med. 153, 2093–2101] describes how the cumulative experience of emotional challenges and stressful events over the life course may take a significant physiological toll on multiple interrelated systems of the body. Various summary measures of these effects have been proposed in the literature, but few studies focus on systematically evaluating them. We use data from a population-based sample of older Taiwanese to compare the explanatory power and cross-sectional predictive performance of several measures of allostatic load for diverse health outcomes. We find that choices regarding which biomarkers to include in a summary measure and how the measure is formed have modest effects across the basic prediction models we evaluate. Our findings suggest that count-based summary measures incorporating risk at both high and low tails and measures that preserve the continuous properties of the biological variables are strategies that may yield stronger predictions of a wider array of health outcomes than other measures. These fundamental insights are useful for researchers in search of empirical formulations of allostatic load and for those who are focused on the development of improved measurement strategies. [Copyright &y& Elsevier]

Natural disasters, such as earthquakes, can have deleterious consequences for physical and psychological health. In this study, we investigate variability in resilience to depressive symptoms in the aftermath of a massive earthquake that struck Taiwan in 1999. We analyze data on 1160 older individuals from a national, longitudinal survey with interviews before and after the earthquake. This survey contains extensive information on physical and cognitive function, depressive symptoms, socio-demographic characteristics and earthquake-related exposure and experiences. We estimate regression models to identify risk factors associated with the presence of depressive symptoms after the disaster, controlling for health status and the presence of depressive symptoms beforehand. We pay special attention to how socio-demographic factors moderate the psychological impact of the earthquake. Results indicate that persons of low socioeconomic status (SES), socially isolated individuals, and women reported higher levels of depressive symptoms than their respective counterparts, as did persons who experienced damage to their homes. The psychological effects of damage were strongest among those aged 54-70. The findings suggest that people who experience damage to their home during a disaster are at risk of experiencing depressive symptoms, with the elderly being more resilient than the near-elderly.

The allostatic load framework postulates that an important pathway connecting the social environment with health involves biological responses to stressful stimuli and the subsequent dysregulation of interrelated physiological systems. We formulate a new measure for cumulative physiological dysregulation using a grade of membership model estimated with biodemographic data from a national sample of older Taiwanese persons. We investigate associations between the measure and physical, psychological, and cognitive function. The results provide insights into the relationships between a set of biological profiles and various health outcomes, identify limitations of earlier approaches, and underscore next steps in the development of improved for mulations of physiological dysregulation.

We investigate how biological markers of individual responses to stressful experiences are associated with profiles of physical and mental functioning in a national sample of middle-aged and elderly Taiwanese. Data come from a population-based sample of middle-aged and elderly Taiwanese in 2000. The data combine rich biological measures with self-reported information on physical and mental health. Grade of membership methods are used to summarize functional status, and multinomial logit models provide information on the association between biological measures and function. The analysis identifies significant associations between biomarkers of stressful experience and profiles of physical and mental functioning. The estimates reveal the potential importance for health of both low and high values of biological parameters. The findings point to directions for future research regarding development of aggregate measures of cumulative dysregulation across multiple physiological systems.