People with extreme longevity represent a unique model to study the biology of aging. Unfortunately, their inclusion in research projects is challenging with the consequent lack of evidence and the need to rely on small convenience samples. Given the growing global aging population, especially in the segment of the oldest old (i.e., aged 90 and older), research in this population has become crucial. Furthermore, by studying the characteristics of extremely longeval persons, it might be possible to 1) better understand the mechanisms of aging, and 2) identify endogenous or exogenous factors contributing to a long life. The design and implementation of research activities in the oldest people need special consideration and a pragmatic approach. Possible implementable solutions and suggestions are provided from experience gained during the conduction of the FAtigue in CEnTenarians (FACET) study.
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http://dx.doi.org/10.1016/j.arr.2023.102170 | DOI Listing |
Intern Emerg Med
December 2024
Department of Clinical Sciences and Community Health, University of Milan, via Francesco Sforza 35, 20122, Milan, Italy.
We investigated the interplay of cardiovascular autonomic and inflammatory profiles in persons with extreme longevity (PEL), their direct offsprings (DO), and a group of controls matched for age and sex with the DO. Cardiac autonomic control was assessed through the heart rate variability (HRV) using spectral and symbolic analysis. The plasma concentration and gene expression of interleukin (IL)-10, IL-6, and TNF-α were quantified.
View Article and Find Full Text PDFFront Psychiatry
December 2024
Operations Management and External Communications Department, The Thirteenth People's Hospital of Chongqing, Chongqing, China.
Background: Early detection of anxiety symptoms can support early intervention and may help reduce the burden of disease in later life in the elderly with abdominal obesity, thereby increasing the chances of healthy aging. The objective of this research is to formulate and validate a predictive model that forecasts the probability of developing anxiety symptoms in elderly Chinese individuals with abdominal obesity.
Method: This research's model development and internal validation encompassed 2,427 participants from the 2017-2018 Study of the Chinese Longitudinal Healthy Longevity Survey (CLHLS).
Environ Int
December 2024
Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA; Irset Institut de Recherche en Santé, Environnement et Travail, UMR-S 1085, Inserm, University of Rennes, EHESP, Rennes, France.
Understanding effects of extreme heat across diverse settings is critical as social determinants play an important role in modifying heat-related risks. We apply a multi-scale analysis to understand spatial variation in the effects of heat across Mexico and explore factors that are explaining heterogeneity. Daily all-cause mortality was collected from the Mexican Secretary of Health and municipality-specific extreme heat events were estimated using population-weighted temperatures from 1998 to 2019 using Daymet and WorldPop datasets.
View Article and Find Full Text PDFPublic Health
December 2024
School of Public Health, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia; Bijie Institute of Shanghai University of Traditional Chinese Medicine, Bijie, China; Bijie District Center for Disease Control and Prevention, Bijie, China. Electronic address:
Objectives: We aimed to predict dyslipidemia risk in elderly Chinese adults using machine learning and dietary analysis for public health.
Study Design: This cross-sectional study includes 13,668 Chinese adults aged 65 or older from the 2018 Chinese Longitudinal Healthy Longevity Survey.
Methods: Dyslipidemia prediction was carried out using a variety of machine learning algorithms, including Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), Random Forest (RF), Gaussian Naive Bayes (GNB), Gradient Boosting Machine (GBM), Adaptive Boosting Classifier (AdaBoost), Light Gradient Boosting Machine (LGBM), and K-Nearest Neighbour (KNN), as well as conventional logistic regression (LR).
Sci Adv
December 2024
Centre for Planetary Health and Food Security, Griffith University, Nathan, QLD, Australia.
We fit ongoing 40+-year mark-recapture databases from the thriving southern right whale (SRW), , and highly endangered North Atlantic right whale (NARW), , to candidate survival models to estimate their life spans. Median life span for SRW was 73.4 years, with 10% of individuals surviving past 131.
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