Because of the important role that survival expectations play in individual decision making, we investigate the extent to which individual responses to survival probability questions are informative about actual mortality. In contrast to earlier studies, which relied on the Health and Retirement Study (HRS) of US individuals aged 50 and over, we combine household survey data on subjective survival probabilities with administrative data on actual mortality for Dutch respondents aged 25 and over. Our main finding is that in our sample, individual life expectancies (measured as subjective survival probabilities) do predict actual mortality even when we control for a large set of health indicators. Our results further suggest that, on average, women underestimate their remaining life duration, whereas men tend to predict their survival chances more realistically. Both sexes, however, tend to overestimate the age gradient in mortality risk and underestimate the health risks of smoking.
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http://dx.doi.org/10.1007/s10680-017-9411-y | DOI Listing |
Diagnostics (Basel)
February 2025
Department of Trauma Surgery, Gachon University Gil Medical Center, Incheon 21565, Republic of Korea.
The Geriatric Trauma Outcome Score (GTOS) is used to predict in-hospital mortality in geriatric patients with trauma. However, its applicability to elderly patients with multiple traumas and severe traumatic brain injury (TBI) remains poorly understood. This study aimed to evaluate the predictive accuracy of the GTOS in elderly patients with multiple traumas and TBI and assess its performance in patients with mild and severe TBI.
View Article and Find Full Text PDFBackground: There were 2227 drug-related deaths in Germany in 2023, corresponding to a rise of 12% over the previous year and a doubling over the course of a decade. Approximately 60% of these deaths were related to opioid consumption. In this narrative review, we discuss whether take-home naloxone (THN) might lower the mortality of persons with opioid dependency.
View Article and Find Full Text PDFFront Artif Intell
February 2025
Department of Surgery, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia.
Heart disease is a leading cause of mortality worldwide, making accurate early detection essential for effective treatment and management. This study introduces a novel hybrid machine-learning approach that combines transfer learning using the VGG16 convolutional neural network (CNN) with various machine-learning classifiers for heart disease detection. A conditional tabular generative adversarial network (CTGAN) was employed to generate synthetic data samples from actual datasets; these were evaluated using statistical metrics, correlation analysis, and domain expert assessments to ensure the quality of the synthetic datasets.
View Article and Find Full Text PDFJ Endocr Soc
March 2025
Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0QQ, UK.
Purpose: People with resistance to thyroid hormone due to defective thyroid receptor β (RTHβ) exhibit adverse cardiovascular outcomes and premature mortality. Whether this reflects increased global cardiovascular disease (CVD) risk or hyperthyroxinemia-associated effects on cardiac rhythm and contractility is unknown. We determined CVD risk and plasma N-terminal pro-B-type natriuretic peptide (NT-proBNP) concentrations as a marker of reduced cardiac function in 99 individuals (mean age 41 years, 37% males) with RTHβ.
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