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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.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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