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Evidence for a limit
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Evidence for a limit to human lifespan
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This study, published in Nature in 2016 by Xiao Do This study, published in Nature in 2016 by Xiao Dong, Brandon Milholland, and Jan Vijg, investigates whether there is a natural upper limit to the human lifespan. Despite significant increases in average human life expectancy over the past century, the authors provide strong demographic evidence suggesting that maximum human lifespan is fixed and subject to natural constraints, with limited improvement beyond a certain age threshold.
Background and Context
Life expectancy vs. maximum lifespan: Life expectancy has increased substantially since the 19th century, largely due to reduced early-life mortality and improved healthcare. However, maximum lifespan, defined as the age of the longest-lived individuals within a species, is generally considered a stable biological characteristic.
The oldest verified human was Jeanne Calment, who lived to 122 years, setting the recognized upper bound.
While animal studies show lifespan can be extended via genetics or pharmaceuticals, evidence on human maximum lifespan flexibility has been inconclusive.
Some previous research, such as studies from Sweden, suggested maximum lifespan was increasing during the 19th and early 20th centuries, challenging the notion of a fixed limit.
Key Findings
Trends in Life Expectancy and Late-Life Survival
Average life expectancy at birth has continually increased globally, especially in developed nations (e.g., France).
Gains in survival have shifted from early-life mortality reductions to improvements in late-life mortality, with more individuals reaching very old ages (70+).
However, the rate of improvement in survival declines sharply after around 100 years of age.
The age showing the greatest gains in survival over time increased during the 20th century but appears to have plateaued since around 1980.
This plateau is seen in 88% of 41 countries studied, indicating a potential biological constraint on lifespan extension beyond a certain point.
Maximum Reported Age at Death (MRAD) Analysis
Using data from the International Database on Longevity (IDL) and the Gerontological Research Group (GRG), the authors analyzed the maximum ages of supercentenarians (110+ years old) in countries with the largest datasets (France, Japan, UK, US).
The maximum reported age at death increased steadily between the 1970s and early 1990s but plateaued around the mid-1990s, near the time Jeanne Calment died (1997).
Linear regression divided into two periods (1968–1994 and 1995 onward) showed:
Pre-1995: MRAD increased by approximately 0.12–0.15 years per year.
Post-1995: No significant increase; a slight, non-significant decline occurred.
The MRAD has stabilized around 114.9 years (95% CI: 113.1–116.7).
The probability of exceeding 125 years in any given year is less than 1 in 10,000, according to a Poisson distribution model.
Additional Statistical Evidence
Analysis of the top five highest reported ages at death per year (not just the maximum) shows similar plateauing trends.
The annual average age at death among supercentenarians has not increased since 1968.
These consistent patterns across multiple metrics and datasets strengthen the evidence for a natural ceiling on human lifespan.
Biological Interpretation and Implications
The idea that aging is a programmed biological event evolved to cause death has been widely discredited.
Instead, limits to lifespan are likely an inadvertent consequence of genetic programs optimized for early life functions (development, growth, reproduction).
Species-specific longevity assurance systems encoded in the genome counteract genetic and cellular imperfections, maintaining lifespan within limits.
Extending human lifespan beyond these natural limits would likely require interventions beyond improving healthspan, potentially involving genetic or pharmacological modifications.
While current research explores such possibilities, the complexity of genetic determinants of lifespan suggests substantial biological constraints.
Timeline Table: Key Chronological Events and Findings
Period Event/Observation
1860s–1990s Maximum reported age at death in Sweden rose from ~101 to ~108 years, suggesting possible increase
1900 onwards Life expectancy at birth increased markedly globally, especially in developed countries
1970s–early 1990s Maximum reported age at death (MRAD) increased steadily in France, Japan, UK, and US
Mid-1990s (around 1995) MRAD plateaued at ~114.9 years; no further significant increase observed
1997 Death of Jeanne Calment, oldest verified human at 122 years
1980s onwards Age with greatest gains in survival plateaued, indicating diminishing improvements at oldest ages
Quantitative Data Summary
Metric Value/Trend Source/Data
Jeanne Calment’s age at death 122 years Oldest verified human
Maximum reported age at death (MRAD) plateau ~114.9 years (95% CI: 113.1–116.7) IDL, GRG databases
MRAD increase rate (pre-1995) +0.12 to +0.15 years/year Linear regression
MRAD increase rate (post-1995) Slight, non-significant decrease Linear regression
Probability of exceeding 125 years in a year <1 in 10,000 Poisson distribution model
Percentage of countries showing plateau in survival gains at oldest ages 88% 41 countries analyzed
Key Insights
Human maximum lifespan appears to be fixed and constrained, despite past increases in average lifespan.
Improvements in survival rates slow and plateau beyond approximately 100 years of age.
The world record for age at death has not significantly increased since the late 1990s.
The phenomenon is consistent across multiple countries and independent datasets.
Biological aging limits are likely an outcome of genetic programming optimized for early life, with longevity assured by species-specific genomic systems.
Substantial extension of maximum human lifespan would require overcoming complex genetic and biological constraints.
Conclusions
This comprehensive demographic analysis provides strong evidence for a natural limit to human lifespan, with little increase in maximum age at death over recent decades despite ongoing increases in average life expectancy. The data challenge optimistic views that human longevity can be indefinitely extended by current health improvements alone. Instead, future lifespan extension may depend on breakthroughs that directly target the underlying biological and genetic determinants of aging.
References to Core Concepts and Methods
Use of Human Mortality Database for survival and life expectancy trends.
Analysis of supercentenarian data from the International Database on Longevity (IDL) and Gerontological Research Group (GRG).
Application of linear regression and Poisson distribution modeling to maximum age at death data.
Consideration of species-specific genetic longevity assurance systems and aging biology literature.
Comparison to historical theories of lifespan limits (Fries 1980; Olshansky et al. 1990).
Keywords
Maximum lifespan
Life expectancy
Supercentenarians
Late-life mortality
Longevity limit
Jeanne Calment
Genetic constraints
Aging biology
Mortality trends
Demographic analysis
FAQ
Q: Has maximum human lifespan increased in recent decades?
A: No. Analysis shows the maximum reported age at death plateaued in the mid-1990s around 115 years.
Q: How does life expectancy differ from maximum lifespan?
A: Life expectancy is the average age people live to in a population, which has increased due to reduced early mortality. Maximum lifespan is the oldest age reached by individuals, which appears fixed.
Q: Is there evidence for biological constraints on human lifespan?
A: Yes. Data suggest species-specific genetic programs and longevity assurance systems impose natural upper limits.
Q: Could future interventions extend maximum lifespan?
A: Potentially, but such extensions require overcoming complex genetic and biological factors beyond current health improvements.
This summary synthesizes the core findings and implications of the study, strictly based on the provided content, reflecting a nuanced understanding of the limits to human lifespan suggested by recent demographic evidence.
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nyuieybh-2436
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ESSENTIAL STEPS TO HEALTH
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ESSENTIAL STEPS TO HEALTHY AGING
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Kansas State University Agricultural Experiment St Kansas State University Agricultural Experiment Station and Cooperative Extension Service
Author: Erin Yelland, Ph.D., Extension Specialist, Adult Development and Aging
Program Overview
The Essential Steps to Healthy Aging is a structured educational program designed to motivate and empower participants to adopt healthy lifestyle behaviors that foster optimal aging. Developed by Kansas State University’s Cooperative Extension Service, this program highlights that aging is inevitable, but how individuals care for themselves physically, mentally, and emotionally throughout life significantly influences the quality of their later years. The program promotes the idea that healthy lifestyle changes can positively impact well-being at any age.
Core Concept
Aging well is a lifelong process influenced by daily choices. Research on centenarians (people aged 100 and over) shows that adopting certain healthy behaviors contributes to longevity and improved quality of life. The program introduces 12 essential steps to maintain health and enhance successful aging.
The 12 Essential Steps to Healthy Aging
Step Number Essential Healthy Behavior
1 Maintain a positive attitude
2 Eat healthfully
3 Engage in regular physical activity
4 Exercise your brain
5 Engage in social activity
6 Practice lifelong learning
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The Multiomics Blueprint
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The Multiomics Blueprint of Extreme Human Lifespan
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This study presents a comprehensive multiomics ana This study presents a comprehensive multiomics analysis of an extraordinary human subject, M116, the world’s oldest verified living person from January 2023 until her death in August 2024 at the age of 117 years and 168 days. Born in 1907 in San Francisco to Spanish parents, M116 spent most of her life in Spain. Despite surpassing the average female life expectancy in Catalonia by over 30 years, she maintained an overall good health profile until her final months. The research aimed to dissect the molecular and cellular factors contributing to her extreme longevity by integrating genomic, epigenomic, transcriptomic, proteomic, metabolomic, and microbiomic data derived primarily from blood, saliva, urine, and stool samples.
Key Insights and Findings
Longevity is multifactorial, with no single genetic or molecular determinant but rather a complex interplay of rare genetic variants, preserved molecular functions, and adaptive physiological traits.
Extreme age and poor health are decoupled; M116 exhibited biological markers of advanced age alongside molecular features indicative of healthy aging.
Molecular assessments reveal preserved and robust biological functions that likely contributed to her extended lifespan.
Genomic Landscape
Telomere Length:
M116 exhibited extremely short telomeres (~8 kb), shorter than all healthy volunteers studied, with 40% of her telomeres below the 20th percentile.
This suggests telomere attrition acts more as a biological aging clock rather than a predictor of age-associated diseases in this context.
The short telomeres may have contributed to cancer resistance by limiting malignant cell replication.
Structural Variants (SVs):
Ten rare SVs identified via Optical Genome Mapping, including a large 3.3 Mb deletion on chromosome 4 and a 93.5 kb deletion on chromosome 17.
These SVs may play unknown roles but were not associated with detrimental gross chromosomal alterations.
Rare Genetic Variants:
Whole Genome Sequencing identified ~3.8 million SNVs; after filtering, 91,666 variants of interest (VOI) affecting 25,146 genes were analyzed.
Seven homozygous rare variants unique to M116 were found in genes linked to immune function, cognitive retention, longevity, pulmonary function, neuroprotection, and DNA repair (e.g., DSCAML1, MAP4K3, TSPYL4, NT5DC1, PCDHA cluster, TIMELESS).
Functional enrichment highlighted pathways involving:
Immune system regulation (e.g., T cell differentiation, response to pathogens, antigen receptor signaling)
Neuroprotection and brain health
Cardioprotection and heart development
Cholesterol metabolism and insulin signaling
Mitochondrial function and oxidative phosphorylation
Mitochondrial function assays showed robust mitochondrial membrane potential and superoxide ion levels in M116’s PBMCs, surpassing those in younger controls, indicating preserved mitochondrial health.
Burden Tests:
Identified genes with significantly higher rare variant load related to neuroprotection and longevity (e.g., EPHA2, MAL, CLU, HAPLN4).
No single gene or pathway explained longevity; rather, multiple pathways acted synergistically.
Blood Cellular and Molecular Characteristics
Clonal Hematopoiesis of Indeterminate Potential (CHIP):
M116 harbored CHIP-associated mutations: one in SF3B1 (RNA splicing factor) and two in TET2 (DNA demethylase) with variant allele frequency >2%.
Despite this, she did not develop malignancies or cardiovascular disease, suggesting CHIP presence does not necessarily translate to disease.
Single-cell RNA Sequencing (scRNA-seq) of PBMCs:
Identified a diverse immune cell repertoire including naive and memory B cells, NK cells, monocytes, and T cell subpopulations.
Notably, M116 exhibited an expanded population of age-associated B cells (ABCs), expressing markers SOX5 and FCRL2, a feature unique compared to other supercentenarians.
The T cell compartment was dominated by effector and memory cytotoxic T cells, consistent with prior observations in supercentenarians.
Metabolomic and Proteomic Profiles
Metabolomics (1H-NMR Analysis):
Compared with 6,022 Spanish individuals, M116’s plasma showed:
Extremely efficient lipid metabolism:
Very low VLDL-cholesterol and triglycerides
Very high HDL-cholesterol (“good cholesterol”)
High numbers of medium and large HDL and LDL particles, indicating effective lipoprotein maturation.
Low levels of lipid biomarkers associated with poor health (saturated fatty acids, esterified cholesterol, linoleic acid, acetone).
High free cholesterol levels linked to good health and survival.
Low glycoproteins A and B, suggesting a low systemic inflammatory state (“anti-inflammaging”).
Cardiovascular risk-associated metabolites supported excellent cardiovascular health.
Some amino acid levels (glycine, histidine, valine, leucine) were low, and lactate and creatinine were high, consistent with very advanced chronological age and imminent mortality.
Proteomics of Extracellular Vesicles (ECVs):
Compared to younger post-menopausal women, 231 proteins were differentially expressed.
GO enrichment revealed eight functional clusters: coagulation, immune system, lipid metabolism, apoptosis, protein processing, detoxification, cellular adhesion, and mRNA regulation.
Proteomic signatures indicated:
Increased complement activation and B cell immunity
Enhanced lipid/cholesterol transport and lipoprotein remodeling
Elevated oxidative stress response and detoxification mechanisms
The most elevated protein was serum amyloid A-1 (SAA1), linked to Alzheimer’s disease, yet M116 showed no neurodegeneration.
Gut Microbiome Composition
16S rDNA sequencing compared M116’s stool microbiome to 445 healthy controls (61-91 years old).
M116’s microbiome showed:
Higher alpha diversity (Shannon index 6.78 vs. 3.05 controls), indicating richer microbial diversity.
Distinct beta diversity, clearly separating her microbiome from controls.
Markedly elevated Actinobacteriota phylum, primarily due to Bifidobacteriaceae family and Bifidobacterium genus, which typically decline with age but are elevated in centenarians.
Bifidobacterium is associated with anti-inflammatory effects, production of short-chain fatty acids, and conjugated linoleic acid, linking to her efficient lipid metabolism.
Lower relative abundance of pro-inflammatory genera such as Clostridium and phyla Proteobacteria and Verrucomicrobiota, associated with frailty and inflammation in older adults.
Diet likely influenced microbiome composition; M116 consumed a Mediterranean diet and daily yogurts containing Streptococcus thermophilus and Lactobacillus delbrueckii, which promote Bifidobacterium growth.
Epigenetic and Biological Age Analysis
DNA Methylation Profiling (Infinium MethylationEPIC BeadChip):
Identified 69 CpG sites with differential methylation (β-value difference >50%) compared to controls aged 21-78 years.
Majority (68%) showed hypomethylation, consistent with known aging-associated DNA methylation changes.
Differential CpGs were more often outside CpG islands and enriched in gene bodies or regulatory regions.
Hypomethylation correlated with altered expression of genes involved in:
Vascular stemness (EGFL7)
Body mass index regulation (ADCY3)
Macular degeneration (PLEKHA1)
Bone turnover (VASN)
Repetitive DNA Elements:
Unlike typical age-associated global hypomethylation, M116 retained hypermethylation in repetitive elements (LINE-1, ALU, ERV), suggesting preserved genomic stability.
Epigenetic Clocks:
Six different DNA methylation-based epigenetic clocks and an independent rDNA methylation clock (using Whole Genome Bisulfite Sequencing) consistently estimated M116’s biological age to be significantly younger than her chronological age (~117 years).
This indicates a decelerated epigenetic aging process in M116’s cells, which may contribute to her longevity.
Integration and Conclusions
Coexistence of Advanced Age Biomarkers and Healthy Aging Traits:
M116 simultaneously exhibited biological signatures indicative of very old age (short telomeres, CHIP mutations, aged B cell populations) and preserved healthy molecular and functional profiles (genetic variants protective against diseases, efficient lipid metabolism, anti-inflammatory gut microbiome, epigenome stability, robust mitochondrial function).
Decoupling of Aging and Disease:
These findings challenge the assumption that aging and disease are inseparably linked, showing that extreme longevity can occur with a healthy functional tissue environment despite advanced biological age markers.
Multidimensional and Multifactorial Basis of Longevity:
The supercentenarian’s extended lifespan likely resulted from the synergistic effects of rare genetic variants, favorable epigenetic patterns, preserved mitochondrial and immune function, healthy metabolism, and a beneficial microbiome, rather than any single factor.
Potential Implications:
Understanding the interplay of these factors could open avenues for promoting healthy aging and preventing age-related diseases in the general population.
Timeline and Demographics of M116
Event Date / Age Notes
Birth March 4, 1907 San Francisco, USA
Moved to Spain 1915 (age 8) Following father’s death
Lived in elderly residence 2001 - 2024 Olot, Catalonia, Spain
COVID-19 Infection Not specified Survived
Death August 19, 2024 (age 117y, 168d) While sleeping, no major neurodegeneration or cancer recorded
Summary Table of Key Molecular Features in M116
Feature Status in M116 Interpretation/Significance
Telomere length Extremely short (~8 kb) Aging clock marker; may limit cancer risk
Structural variants 10 rare SVs, including large deletions Unknown effect; no gross chromosomal abnormalities
Rare homozygous variants 7 unique variants in longevity/immune-related genes Suggest combined genetic contribution to longevity
CHIP mutations Present (SF3B1, TET2 mutations) No malignancy or cardiovascular disease
Mitochondrial function Robust membrane potential & superoxide levels Preserved energy metabolism
Immune cell composition Expanded ABCs, enriched cytotoxic T cells Unique immune profile linked to longevity
Lipid metabolism Very efficient (high HDL, low VLDL) Cardiovascular protection
Inflammation Low glycoproteins A & B levels Reduced inflammaging
Gut microbiome High Bifidobacterium abundance Anti-inflammatory, supports metabolism
DNA methylation Predominantly hypomethylated CpGs with preserved methylation in repeats Epigenetic stability and decelerated aging
Biological age (epigenetic clocks) Significantly younger than chronological age Indicative of healthy aging
Proteomic profile Upregulated immune and lipid metabolism proteins; elevated SAA1 Protective mechanisms with unexplained elevated SAA1
Keywords
Supercentenarian, Extreme Longevity, Multiomics, Telomere Attrition, Rare Genetic Variants, Clonal Hematopoiesis (CHIP), Immune Cell Profiling, Mitochondrial Function, Metabolomics, Proteomics, Gut Microbiome, DNA Methylation, Epigenetic Clock, Biological Age, Inflammaging, Lipid Metabolism
Conclusion
This landmark study of M116 provides the first extensive multiomics blueprint of extreme human lifespan, revealing that exceptional longevity arises from a balance of advanced biological aging markers coupled with preserved and enhanced molecular functions across multiple systems. The results underscore the importance of immune competence, metabolic health, epigenetic stability, and microbiome composition in sustaining health during extreme aging, offering valuable insights into the biological underpinnings of healthy human longevity.
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Inconvenient Truths About
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Inconvenient Truths About Human Longevity
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This review article, “Inconvenient Truths About Hu This review article, “Inconvenient Truths About Human Longevity” by S. Jay Olshansky and Bruce A. Carnes, published in the Journals of Gerontology: Medical Sciences (2019), critically examines the ongoing scientific and public debate about the limits of human longevity, the feasibility of radical life extension, and the future priorities of medicine and public health regarding aging. It argues that while advances in public health and medicine have substantially increased life expectancy over the past two centuries, biological constraints impose practical limits on human longevity, and predictions of near-future radical life extension are unsupported by empirical evidence.
Key Insights and Arguments
Historical Gains in Longevity:
Initial life expectancy gains were driven by public health improvements reducing early-age mortality (infant and child deaths).
Recent gains are largely due to reductions in mortality at middle and older ages, achieved through medical technology.
The dramatic rise in life expectancy during the 20th century cannot be linearly extrapolated into the future due to shifting mortality dynamics.
Debate on Limits to Longevity:
Two opposing views dominate the debate:
Unlimited longevity potential based on mathematical extrapolations of declining death rates.
Biologically based limits to lifespan, currently being approached.
Proponents of unlimited longevity often rely on purely mathematical models that ignore biological realities, leading to unrealistic predictions akin to Zeno’s Paradox (infinite division without reaching zero).
Critique of Mathematical Extrapolations:
Analogies such as world record running times illustrate the fallacy of linear extrapolation: records improved steadily until plateauing, indicating biological limits on human performance.
Similarly, mortality improvements have decelerated and are unlikely to continue improving at historic rates indefinitely.
Three Independent Lines of Evidence Supporting Longevity Limits:
Entropy in the Life Table: As life expectancy rises, it becomes mathematically harder to increase further because most deaths occur within a narrow old age window with high mortality rates.
Comparative Mortality Studies: Scaling mortality schedules of humans against other mammals (mice, dogs) suggests a natural lifespan limit around 85 years for humans.
Evolutionary Biology: Biological “warranty periods” related to reproduction and survival support a median lifespan limit in the mid to upper 80s.
Empirical Data on Life Expectancy Trends:
Life expectancy gains in developed nations have decelerated or plateaued near 85 years, consistent with theoretical limits.
Table below summarizes U.S. life expectancy improvements by decade:
Decade Life Expectancy at Birth (years) Annual Average Improvement (years)
1990 75.40 —
2000 76.84 0.142
2010 78.81 0.197
2016 78.91 0.017
The data show that the predicted 0.2 years per annum improvement has not been consistently met, with recent years showing a sharp slowdown.
Problems with Radical Life Extension Claims:
Predictions of cohort life expectancy at birth reaching or exceeding 100 years for babies born since 2000 are unsupported by observed mortality trends.
Claims of “actuarial escape velocity” (mortality rates falling faster than aging progresses) lack empirical or biological evidence.
These exaggerated forecasts divert resources and funding away from realistic aging research.
Biological Mechanisms and Aging:
Aging is an unintended consequence of accumulated damage and imperfect repair mechanisms driven by genetic programs optimized for reproduction, not longevity.
Humans cannot biologically exceed certain limits because of genetic and physiological constraints.
Unlike lifespan or physical performance (e.g., running speed), aging is a complex biological process that limits survival and function.
The Future Focus: Health Span over Life Span
Rather than pursuing life extension as the primary goal, public health and medicine should prioritize extending the health span—the period of life spent in good health.
This approach aims to compress morbidity, reducing the time individuals spend suffering from age-related diseases and disabilities.
Advances in aging biology (geroscience) hold promise for improving health span even if life expectancy gains are modest.
Risks of Disease-Focused Treatment Alone:
Treating individual aging-related diseases separately may increase survival but also leads to greater prevalence and severity of chronic illnesses in very
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Extreme longevity may be
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Extreme longevity may be the rule
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This study by Breed et al. (2024) investigates the This study by Breed et al. (2024) investigates the longevity of Balaenid whales, focusing on the southern right whale (SRW, Eubalaena australis) and the North Atlantic right whale (NARW, Eubalaena glacialis). By analyzing over 40 years of mark-recapture data, the authors estimate life spans and survival patterns, revealing that extreme longevity (exceeding 130 years) is likely the norm rather than the exception in Balaenid whales, challenging previously accepted maximum life spans of 70–75 years. The study also highlights the impact of anthropogenic factors, particularly industrial whaling, on the significantly reduced life span of the endangered NARW.
Key Findings
Southern right whales (SRWs) have a median life span of approximately 73.4 years, with 10% of individuals surviving beyond 131.8 years.
North Atlantic right whales (NARWs) have a median life span of only 22.3 years, with 10% living past 47.2 years—considerably shorter than SRWs.
The reduced NARW life span is attributed to anthropogenic mortality factors, including ship strikes and entanglements, not intrinsic biological differences.
The study uses survival function modeling, bypassing traditional aging methods that rely on lethal sampling and growth layer counts, which tend to underestimate longevity.
Evidence from other whales, especially bowhead whales, supports the hypothesis that extreme longevity is widespread among Balaenids and possibly other large cetaceans.
Background and Context
Early longevity estimates in whales, such as blue and fin whales, came from counting annual growth layers in ear plugs, revealing ages up to 110–114 years.
Bowhead whales have been documented to live over 150 years, with some individuals estimated at 211 years based on aspartic acid racemization (AAR) and corroborating archaeological evidence (e.g., embedded antique harpoon tips).
Longevity estimates from traditional methods are biased low due to:
Difficulty in counting growth layers in very old whales due to tissue remodeling.
Removal of older age classes from populations by industrial whaling.
The need for lethal sampling to obtain age data, which is rarely possible in protected species.
The relation between body size and longevity supports the potential for extreme longevity in large whales, although bowhead whales exceed predictions from terrestrial mammal models.
Methodology
Data Sources:
SRW mark-recapture data from South Africa (1979–2021), including 2476 unique females, of which 139 had known birth years.
NARW mark-recapture data from the North Atlantic (1974–2020), including 328 unique females, of which 205 had known birth years.
Survival Models:
Ten parametric survival models were fitted, including Gompertz, Weibull, Logistic, and Exponential mortality functions with adjustments (Makeham and bathtub).
Models were fit using Bayesian inference with the R package BaSTA, which accounts for left truncation (unknown birth years) and right censoring (individuals surviving past the study period).
Model selection was based on Deviance Information Criterion (DIC).
Validation:
Simulated datasets, generated from fitted model parameters, were used to test for bias and accuracy.
Models accurately recovered survival parameters with minimal bias.
Estimating Reproductive Output:
The total number of calves produced by females was estimated by integrating survival curves and applying calving intervals ranging from 3 to 7 years.
Results
Parameter Southern Right Whale (SRW) North Atlantic Right Whale (NARW)
Median life span (years) 73.4 (95% CI [60.0, 88.3]) 22.3 (95% CI [19.7, 25.1])
10% survive past (years) 131.8 (95% CI [110.9, 159.3]) 47.2 (95% CI [43.0, 53.3])
Annual mortality hazard (age 5) ~0.5% 2.56%
Maximum life span potential >130 years Shortened due to anthropogenic factors
**SRW survival best fits an unmodified Gompertz model; NARW fits a Gompertz model with
Smart Summary
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rmekmkeu-3073
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xevyo
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Exploring Human Longevity
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Exploring Human Longevity
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This research paper investigates the impact of cli This research paper investigates the impact of climate on human life expectancy and longevity, analyzing economic and mortality data from 172 countries to establish whether living in colder climates correlates with longer life spans. By controlling for factors such as income, education, sanitation, healthcare, ethnicity, and diet, the authors aimed to isolate climate as a variable influencing longevity. The study reveals that individuals residing in colder regions tend to live longer than those in warmer climates, with an average increase in life expectancy of approximately 2.22 years attributable solely to climate differences.
Key Concepts and Definitions
Term Definition Source
Life Expectancy The average number of years a newborn is expected to live, assuming current age-specific mortality rates remain constant. United Nations Population Division
Life Span / Longevity The maximum number of years a person can live, based on the longest documented individual (122 years for humans). News Medical Life Sciences
Blue Zones Five global regions where people live significantly longer than average, characterized by healthy lifestyles and warm climates. National Geographic
Free Radical Theory A theory suggesting that aging results from cellular damage caused by reactive oxidative species (ROS), potentially slowed by cold. Antioxidants & Redox Signaling (Gladyshev)
Historical and Global Trends in Life Expectancy
Neolithic and Bronze Age: Average life expectancy was approximately 36 years, with hunter-gatherers living longer than early farmers.
Late medieval English aristocrats: Life expectancy reached around 64 years, comparable to modern averages.
19th to mid-20th century: Significant increases in life expectancy due to improvements in sanitation, education, housing, antibiotics, agriculture (Green Revolution), and reductions in infectious diseases such as HIV/AIDS, TB, and malaria.
2000 to 2016: Global average life expectancy increased by 5.5 years, the fastest rise since the 1950s (WHO).
Future projections: Life expectancy will continue to rise globally but at a slower pace, with Africa seeing the most substantial increases, while Northern America, Europe, and Latin America expect more gradual improvements.
Research Objectives and Methodology
Objective: To quantify the effect of climate on life expectancy while controlling for socio-economic factors such as income, healthcare access, education, sanitation, ethnicity, and diet.
Data sources: United Nations World Economic Situation and Prospects 2019, United Nations World Mortality Report 2019.
Country classification:
Four income groups: high, upper-middle, lower-middle, and low income.
Climate groups: “mainly warm” (tropical, subtropical, Mediterranean, savanna, equatorial) and “mainly cold” (temperate, continental, oceanic, maritime, highland).
Statistical analysis: ANOVA (Analysis of Variance) was used to determine the statistical significance of climate on life expectancy across and within groups.
Climate Classification and Geographic Distribution
Warm climate regions constitute about 66.2% of the world.
Cold climate regions constitute approximately 33.8% of the world.
Some large countries with diverse climates (e.g., USA, China) were classified based on majority regional climate.
Quantitative Results
Income Group Mean Life Expectancy (Warm Climate) Mean Life Expectancy (Cold Climate) Difference (Years) SD Warm Climate SD Cold Climate
High income Not specified Not specified Not specified Not specified Not specified
Upper-middle income Not specified Not specified Not specified Not specified Not specified
Lower-middle income Almost equal Slightly higher (by 0.237 years) 0.2372 Higher Lower
Low income Not specified Higher by 5.91 years 5.9099 Higher Lower
Overall average: Living in colder climates prolongs life expectancy by approximately 2.2163 years across all income groups.
Standard deviation: Greater variability in life expectancy was observed in warmer climates, indicating uneven health outcomes.
Regional Life Expectancy Insights
Region Climate Type Mean Life Expectancy (Years)
Southern Europe Cold 82.3
Western Europe Cold 81.9
Northern Europe Cold 81.2
Western Africa Warm 57.9
Middle Africa Warm 59.9
Southern Africa Warm 63.8
Colder regions generally show higher life expectancy.
Warmer regions, especially in Africa, tend to have lower life expectancy.
Statistical Significance (ANOVA Results)
Parameter Value Interpretation
F-value 49.88 Large value indicates significant differences between groups
p-value 0.00 (less than 0.05) Strong evidence against the null hypothesis (no effect of climate)
Variance between groups More than double variance within groups Climate significantly affects life expectancy
Theoretical Perspectives on Climate and Longevity
Warm climate argument: Some studies suggest higher mortality in colder months; e.g., 13% more deaths in winter than summer in the U.S. (Professor F. Ellis, Yale).
Cold climate argument: Supported by the free radical theory, colder temperatures may slow metabolic reactions, reducing reactive oxidative species (ROS) and cellular damage, thereby slowing aging.
Experimental evidence from animals (worms, mice) shows lifespan extension under colder conditions, with genetic pathways triggered by cold exposure.
Impact of Climate Change on Longevity
Rising global temperatures pose risks to human health and longevity, including:
Increased frequency of extreme weather events (heatwaves, floods, droughts).
Increased spread of infectious diseases.
Negative impacts on agriculture reducing food security and nutritional quality.
Air pollution exacerbating respiratory diseases.
Studies show a 1°C increase in temperature raises elderly death rates by 2.8% to 4.0%.
Projected effects include malnutrition, increased disease burden, and infrastructure stress, all threatening to reduce life expectancy.
Limitations and Considerations
Genetic factors: Approximately one-third of life expectancy variation is attributed to genetics (genes like APOE, FOXO3, CETP).
Climate classification biases: Countries with multiple climate zones were classified according to majority, potentially oversimplifying climate impacts.
Lifestyle factors: Blue zones with warm climates show exceptional longevity due to diet, exercise, and stress management, illustrating that climate is not the sole determinant.
Migration and localized data: Studies on migrants support climate’s role in longevity independent of genetics and lifestyle.
Practical Implications and Recommendations
While individuals cannot relocate easily to colder climates, practices such as cold showers and cryotherapy might induce genetic responses linked to longevity.
This study emphasizes the urgent need to address climate change mitigation to prevent adverse effects on human health and lifespan.
Calls for further research into:
The genetic mechanisms influenced by climate.
The potential of cryonics and cold exposure therapies to extend longevity.
More granular studies factoring lifestyle, genetics, and microclimates.
Conclusion
Colder climates are consistently associated with longer human life expectancy, with an average increase of about 2.2 years across income levels.
Climate change and global warming threaten to reduce life expectancy globally through multiple pathways.
While genetics and lifestyle factors play critical roles, climate remains a significant environmental determinant of longevity.
The study advocates for urgent global climate action and further research into climate-genetics interactions to better understand and protect human health.
Keywords
Life expectancy
Longevity
Climate impact
Cold climate
Warm climate
Climate change
Income groups
Free radical theory
Blue zones
Public health
References
Selected key references from the original content:
United Nations Population Division (Life Expectancy definitions)
World Health Organization (Life Expectancy data, Climate Effects)
National Geographic (Blue Zones)
American Journal of Physical Anthropology (Historical life expectancy)
Studies on genetic impact of temperature on longevity (University of Michigan, Scripps Research Institute)
Stanford University and MIT migration study on location and mortality
This summary strictly reflects the content and data presented in the source document without fabrication or unsupported extrapolations.
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dutcyoah-2300
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xevyo
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Extreme longevity
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Extreme longevity in proteinaceous deep-sea corals
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This study investigates the extreme longevity, gro This study investigates the extreme longevity, growth rates, and ecological significance of two proteinaceous deep-sea coral species, Gerardia sp. and Leiopathes sp., found in deep waters around Hawai’i and other global locations. Using radiocarbon dating and stable isotope analyses, the research reveals that these corals exhibit remarkably slow growth and lifespans extending thousands of years, far surpassing previous estimates. These findings have profound implications for deep-sea coral ecology, conservation, and fisheries management.
Key Insights
Deep-sea corals Gerardia sp. and Leiopathes sp. grow exceptionally slowly, with radial growth rates ranging from 4 to 85 µm per year.
Individual colonies can live for hundreds to several thousand years, with the oldest Gerardia specimen aged at 2,742 years and the oldest Leiopathes specimen at 4,265 years, making Leiopathes the oldest known skeletal accreting marine organism.
The corals feed primarily on freshly exported particulate organic matter (POM) from surface waters, as indicated by stable carbon (δ13C) and nitrogen (δ15N) isotope data.
Radiocarbon analyses confirm the skeletal carbon originates from modern surface-water carbon sources, indicating minimal incorporation of old, “14C-free” carbon into the skeleton.
These slow growth rates and extreme longevities imply that deep-sea coral habitats are vulnerable to damage and slow to recover, challenging assumptions about their renewability.
Deep-sea coral communities are critical habitat hotspots for various fish and invertebrates, contributing to deep-sea biodiversity and ecosystem complexity.
Human impacts such as commercial harvesting for jewelry, deep-water fishing, and bottom trawling pose significant threats to these fragile ecosystems.
The study emphasizes the need for international, ecosystem-based conservation strategies and suggests current fisheries management frameworks may underestimate the vulnerability of these corals.
Background and Context
Deep-sea corals colonize hard substrates on seamounts and continental margins at depths of 300 to 3,000 meters worldwide. These corals form complex habitats that support high biodiversity and serve as important ecological refuges and feeding grounds for various marine species, including commercially valuable fish and endangered marine mammals like the Hawaiian monk seal.
Prior estimates of deep-sea coral longevity were inconsistent, ranging from decades (based on amino acid racemization and growth-band counts) to over a thousand years (based on radiocarbon dating). This study clarifies these discrepancies by:
Applying high-resolution radiocarbon dating to both living and subfossil coral specimens.
Using stable isotope analysis to identify coral carbon sources and trophic levels.
Comparing radiocarbon signatures in coral tissues and skeletons with surface-water carbon histories.
Methods Overview
Samples of Gerardia and Leiopathes were collected from several deep-sea coral beds around Hawai’i (Makapuu, Lanikai, Keahole Point, and Cross Seamount) using the NOAA/Hawaiian Undersea Research Laboratory’s Pisces submersibles.
Coral skeletons were sectioned radially, and microtome slicing was used to obtain thin layers (~100 µm) for precise radiocarbon analysis.
Radiocarbon (14C) ages were calibrated to calendar years using established reservoir age corrections.
Stable isotope analyses (δ13C and δ15N) were conducted on dried polyp tissues to determine trophic level and carbon sources.
Growth rates were calculated from radiocarbon profiles and bomb-pulse 14C signatures (the increase in atmospheric 14C from nuclear testing in the 1950s-60s).
Detailed Findings
Growth Rates and Longevity
Species Radial Growth Rate (µm/year) Maximum Individual Longevity (years)
Gerardia sp. Average 36 ± 20 (range 11-85) Up to 2,742
Leiopathes sp. Approximately 5 Up to 4,265
Gerardia growth rates vary widely but average around 36 µm/year.
Leiopathes grows more slowly (~5 µm/year) but lives longer.
Some Leiopathes specimens show faster initial growth (~13 µm/year) that slows with age.
Carbon Sources and Trophic Ecology
δ13C values for living polyp tissues of both species average around –19.3‰ (Gerardia) and –19.7‰ (Leiopathes), consistent with marine particulate organic carbon.
δ15N values are enriched relative to surface POM, averaging 8.3‰ (Gerardia) and 9.3‰ (Leiopathes), indicating they are low-order consumers, feeding primarily on freshly exported surface-derived POM.
Proteinaceous skeleton δ13C is slightly enriched (~3‰) compared to tissues, likely due to lipid exclusion in skeletal formation.
Radiocarbon profiles of coral skeletons closely match surface-water 14C histories, including bomb-pulse signals, confirming rapid transport of surface carbon to depth and minimal incorporation of old sedimentary carbon.
Ecological and Conservation Implications
The extreme longevity and slow growth of these corals imply that population recovery from physical disturbance (e.g., fishing gear, harvesting) takes centuries to millennia.
Deep-sea coral beds function as keystone habitats, enhancing biodiversity and providing essential fish habitat, including for endangered species.
Physical disturbances like bottom trawling, line entanglement, and coral harvesting for jewelry threaten these corals and their associated communities.
Existing fisheries management may overestimate sustainable harvest limits, especially for Gerardia, due to underestimating longevity and growth rates.
The United States Magnuson-Stevens Fishery Conservation and Management Act (MSA) recognizes deep-sea corals as “essential fish habitat,” but enforcement and protection vary.
The study advocates for international, ecosystem-based management approaches that consider both surface ocean changes (e.g., climate change, ocean acidification) and deep-sea impacts.
The longevity data suggest that damage to these corals should not be considered temporary on human timescales, underscoring the need for precautionary management.
Timeline Table: Key Chronological Events (Related to Coral Growth and Study)
Event/Measurement Description
~4,265 years ago (calibrated 14C age) Oldest Leiopathes specimen basal attachment age
~2,742 years ago (calibrated 14C age) Oldest Gerardia specimen age
1957 Reference year for bomb-pulse 14C calibration in radiocarbon dating
2004 Sample collection year from Hawai’ian deep-sea coral beds
2006/2007 Magnuson-Stevens Act reauthorization increasing protection for deep-sea coral habitats
Present (2008-2009) Publication and review of this study
Quantitative Data Summary: Isotopic Composition of Coral Tissues and POM
Parameter Gerardia sp. (n=10) Leiopathes sp. (n=2) Hawaiian POM at 150 m (Station ALOHA)
δ13C (‰) –19.3 ± 0.8 –19.7 ± 0.3 –21 ± 1
δ15N (‰) 8.3 ± 0.3 9.3 ± 0.6 2 to 4 (range)
C:N Ratio 3.3 ± 0.3 5.1 ± 0.1 Not specified
Core Concepts
Radiocarbon dating (14C) enables precise age determination of coral skeletons by comparing measured 14C levels to known atmospheric and oceanic 14C histories.
Bomb-pulse 14C is a distinct marker from nuclear testing that provides a temporal reference point for recent growth.
Stable isotope ratios (δ13C and δ15N) provide insights into trophic ecology and carbon sources.
Radial growth rates measure the increase in coral skeleton thickness per year, reflecting growth speed.
Longevity estimates derive from radiocarbon age calibrations of inner and outer skeletal layers.
Deep-sea coral beds are ecosystem engineers, forming complex habitats critical for marine biodiversity.
Conservation challenges arise due to very slow growth and extreme longevity, combined with anthropogenic threats.
Conclusions
Gerardia and Leiopathes deep-sea corals exhibit unprecedented longevity, with lifespans of up to 2,700 and 4,200 years, respectively.
Their slow radial growth rates and feeding on freshly exported surface POM indicate a close ecological coupling between surface ocean productivity and deep-sea benthic communities.
The longevity and slow recovery rates imply that damage to deep-sea coral beds is effectively irreversible on human timescales, demanding precautionary and stringent management.
These species serve as critical habitat-formers in the deep sea, supporting diverse marine life and contributing to ecosystem complexity.
There is an urgent need for international, ecosystem-based conservation strategies to protect these unique and vulnerable communities from fishing impacts, harvesting, and environmental changes.
Current fisheries management frameworks may inadequately reflect the nonrenewable nature of these coral populations and require revision based on these findings.
Keywords
Deep-sea corals
Gerardia sp.
Leiopathes sp.
Radiocarbon dating
Longevity
Radial growth rate
Stable isotopes (δ13C, δ15N)
Particulate organic matter (POM)
Deep-sea biodiversity
Conservation
Fisheries management
Magnuson-Stevens Act
Bomb-pulse 14C
Proteinaceous skeleton
References to Note (from source)
Radiocarbon dating and longevity studies (Roark et al., 2006; Druffel et al., 1995)
Stable isotope methodology and trophic level assessment (DeNiro & Epstein, 1981; Rau, 1982)
Fisheries and habitat conservation frameworks (Magnuson-Stevens Act, 2006/2007 reauthorization)
Ecological significance of deep-sea corals (Freiwald et al., 2004; Parrish et al., 2002)
This comprehensive analysis underscores the exceptional longevity and ecological importance of proteinaceous deep-sea corals, highlighting the need for improved management and protection policies given their vulnerability and slow recovery potential.
Smart Summary
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Extension of longevity
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Extension of longevity in Drosophila mojavensis by
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Summary
The study by Starmer, Heed, and Rockwood- Summary
The study by Starmer, Heed, and Rockwood-Slusser (1977) investigates the extension of longevity in Drosophila mojavensis when exposed to environmental ethanol and explores the genetic and ecological factors underlying this phenomenon. The authors focus on differences between subraces of D. mojavensis, emphasizing the role of alcohol dehydrogenase (ADH) isozyme polymorphisms, environmental heterogeneity of host plants, and related genetic elements.
Core Findings
Longevity Increase by Ethanol Exposure: Adult D. mojavensis flies, which breed and feed on necrotic cacti, show a significant increase in longevity when exposed to atmospheric ethanol. This longevity extension is:
Diet-independent (i.e., does not depend on yeast ingestion).
Accompanied by retention of mature ovarioles and eggs in females, indicating not just longer life but maintained reproductive potential.
Subrace Differences: Longevity increases differ among strains from different geographic regions:
Flies from Arizona and Sonora, Mexico (subrace BI) exhibit the greatest increase in longevity.
Flies from Baja California, Mexico (subrace BII) show the least increase.
Genetic Correlations:
The longevity response correlates with the frequency of alleles at the alcohol dehydrogenase locus (Adh).
Adh-S allele (slow electrophoretic form) is prevalent in Arizona and Sonora populations; its enzyme product is more heat- and pH-tolerant.
Adh-F allele (fast electrophoretic form) predominates in Baja California populations; its enzyme product is heat- and pH-sensitive but shows higher activity with isopropanol as substrate.
Modifier genes, including those associated with chromosomal inversions on the second chromosome (housing the octanol dehydrogenase locus), may also influence longevity response.
Environmental Heterogeneity: Differences in longevity and allele frequencies correspond to the distinct physical and chemical environments of the host cacti:
Arizona-Sonora flies breed on organpipe cactus (Lemaireocereus thurberi), which exhibits extreme temperature and pH variability.
Baja California flies breed on agria cactus (Machaerocereus gummosus), which shows moderate temperature and pH but contains relatively high concentrations of isopropanol.
The interaction between substrate alcohol content, temperature, and pH likely maintains the polymorphism at the ADH locus and influences evolutionary adaptations.
Experimental Design and Key Results
Experimental Setup
Flies were exposed to various concentrations of atmospheric ethanol (0.0% to 8.0% vol/vol) in sealed vials containing cotton soaked with ethanol solutions.
Longevity was measured as the lifespan of adult flies exposed to ethanol vapors, and data were log-transformed (ln[hr]) for statistical analysis.
Different strains from Baja California, Sonora, and Arizona were tested, alongside analysis of ADH allele frequencies and chromosomal inversions.
Axenic (microbe-free) strains were used to test the effect of yeast ingestion on longevity.
Summary of Key Experiments
Experiment Purpose Main Result
1 (Ethanol dose response) Test longevity response of D. mojavensis adults to ethanol vapors at different concentrations Longevity increased significantly at 1.0%, 2.0%, and 4.0% ethanol; highest female longevity observed in 4.0% ethanol group, with retention of mature eggs
2 (Yeast dependence) Assess whether longevity increase depends on live yeast ingestion Longevity increase occurred regardless of yeast treatment; live yeasts (Candida krusei or Kloeckera apiculata) not essential for enhanced longevity
3 (Subrace and sex differences) Compare longevity response among strains from different regions and sexes Females from Arizona-Sonora (subrace BI) showed significantly greater relative longevity increase than Baja California (subrace BII); males showed less pronounced differences
4 (Isozyme stability tests) Measure heat and pH stability of ADH-F and ADH-S isozymes ADH-F enzyme less stable at high temperature (45°C) and acidic pH compared to ADH-S; ADH-F activity reduced after 7-11 minutes heat exposure
Quantitative Data Highlights
Longevity Response to Ethanol Concentrations (Experiment 1)
Ethanol Concentration (%) Effect on Longevity
0.0 (Control) Baseline
0.5 No significant increase
1.0 Significant increase
2.0 Significant increase (highest relative longevity)
4.0 Significant increase
8.0 No increase (toxicity likely)
Analysis of Variance (Table 1 and Table 3)
Source of Variation Significance (p-value) Effect Description
Ethanol treatment p < 0.001 Strong effect on longevity
Yeast treatment Not significant No strong effect on longevity
Interaction (Ethanol x Yeast) p < 0.05 Minor effects, but overall yeast not required
Subrace p < 0.001 Significant effect on relative longevity
Sex Not significant Sex alone not significant, but sex x subrace interaction significant
Subrace x Sex interaction p < 0.001 Males and females respond differently across subraces
Ethanol treatment (dose) p < 0.01 Different doses produce varying longevity effects
Correlation Coefficients (Longevity Response vs. Genetic Factors)
Genetic Factor Correlation with Longevity Response at 2.0% Ethanol Correlation at 4.0% Ethanol
Frequency of Adh-F allele -0.633 (negative correlation) -0.554 (negative correlation)
Frequency of ST chromosomal arrangement (3rd chromosome) -0.131 (non-significant) 0.004 (non-significant)
Frequency of LP chromosomal arrangement (2nd chromosome) -0.694 (negative correlation) -0.713 (negative correlation)
Ecological and Genetic Interpretations
The Adh-S allele product is more heat- and pH-tolerant, which suits the variable, extreme environment of the organpipe cactus in Arizona and Sonora.
The Adh-F allele product is less stable under heat and acidic conditions but metabolizes isopropanol effectively, aligning with the chemical environment of Baja California’s agria cactus.
The distribution of Adh alleles matches the physical and chemical characteristics of the host cactus substrates, suggesting natural selection shapes the genetic polymorphism at the ADH locus.
The presence of isopropanol in agria cactus tissues may favor the Adh-F allele, as its enzyme shows higher activity with isopropanol.
The second chromosome inversion frequency correlates with longevity response, implicating the octanol dehydrogenase locus and potential modifier genes in ethanol tolerance.
Biological Significance and Implications
The study supports the hypothesis that environmental ethanol serves as a selective agent influencing longevity and allele frequencies in desert-adapted Drosophila.
The increased longevity and maintained reproductive capacity in ethanol vapor suggest a fitness advantage and physiological adaptation.
Findings align with broader research on **genetic polymorphisms in Dros
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xevyo
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Family matters
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Family matters in unravelling human longevity
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Human life expectancy has doubled over the past 20 Human life expectancy has doubled over the past 200 years in industrialized countries, yet the period spent in good physical and cognitive health remains relatively short. A significant proportion of elderly individuals suffer from multiple chronic diseases; for instance, 70% of 65-year-olds and 90% of 85-year-olds have at least one disease, averaging four diseases per person. In contrast, a small subset of individuals achieves exceptional longevity without typical age-related diseases such as hypertension, cancer, or type 2 diabetes. Understanding these individuals is crucial because they likely possess gene-environment interactions that promote longevity, disease resistance, and healthy aging.
Key Insights on Longevity Research
Most knowledge on aging mechanisms is derived from animal models, which identified nine hallmarks of aging and implicated glucose and fat metabolism pathways in longevity.
Human longevity is far more complex due to heterogeneity in genomes, lifestyles, environments, and social factors.
Genetic factors contribute approximately 25% to lifespan variation, with a stronger influence observed in long-lived individuals as indicated by familial clustering.
Despite extensive genetic research, only two genes—APOE and FOXO3A—have been consistently associated with longevity.
The lack of a consistent definition of heritable longevity complicates genetic studies, often mixing sporadic long-lived cases with those from long-lived families.
The increase in centenarians (e.g., from 1 in 10,000 to 2 in 10,000 in the US between 1994 and 2012) reflects the presence of sporadically long-lived individuals, which confounds genetic analyses.
Challenges in Genetic Longevity Studies
Genome Wide Association Studies (GWAS) face difficulties because controls (average-lived individuals) might later become long-lived, blurring case-control distinctions.
Recent findings emphasize the importance of rare and structural genetic variants alongside common single nucleotide polymorphisms (SNPs).
Socio-behavioral and environmental factors (lifestyle, socio-economic status, social networks, living environment) significantly influence aging but are rarely integrated into genetic studies.
There is limited knowledge about how these non-genetic factors cluster within long-lived families.
Advances Through Family-Based Research
Two recent studies using large family tree databases—the Utah Population Database (UPDB), LINKing System for historical family reconstruction (LINKS), and Historical Sample of the Netherlands Long Lives (HSN-LL)—demonstrated that:
Longevity is transmitted across generations only if ≥30% of ancestors belong to the top 10% longest-lived of their birth cohort, and the individual themselves is in the top 10% longest-lived.
Approximately 27% of individuals with at least one long-lived parent did not show exceptional survival, indicating sporadic longevity.
To address this, the Longevity Relatives Count (LRC) score was developed to identify genetically enriched long-lived individuals, improving case selection for genetic studies and reducing sporadic longevity inclusion.
Opportunities and Recommendations
Increasing availability of population-wide family tree data (e.g., Netherlands’ civil certificate linkage, Denmark’s initiatives) enables broader analysis of long-lived families rather than individuals alone.
Integrating gene-environment (G x E) interactions by combining genetic data with genealogical, socio-behavioral, and environmental information is essential to unravel mechanisms of longevity.
Epidemiological studies should:
Recruit members from heritable longevity families.
Collect comprehensive molecular, socio-behavioral, and environmental data.
Include analyses of rare and structural genetic variants in addition to common SNPs.
Cohorts like the UK Biobank can improve the distinction between cases and controls by incorporating the LRC score based on ancestral survival data.
Conclusion
The success of genetic studies on human longevity depends on:
Applying precise, consistent definitions of heritable longevity.
Utilizing family-based approaches and large-scale genealogical data.
Incorporating non-genetic covariates such as socio-behavioral and environmental factors.
Studying interactions between genes and environment to gain comprehensive mechanistic insights into healthy aging and longevity.
Quantitative Data Table
Parameter Statistic/Description
Increase in centenarians From 1 in 10,000 (1994) to 2 in 10,000 (2012)
% of 65-year-olds with ≥1 disease 70%
% of 85-year-olds with ≥1 disease 90%
Average number of diseases in elderly 4
Genetic contribution to lifespan ~25% overall, higher in long-lived families
Ancestor longevity threshold for heritability ≥30% ancestors in top 10% longest-lived cohort
Proportion with survival similar to general population despite long-lived parent 27%
Keywords
Human longevity
Healthy aging
Gene-environment interaction (G x E)
Genetic variation
Familial clustering
Longevity Relatives Count (LRC) score
Genome Wide Association Studies (GWAS)
Rare and structural variants
Socio-behavioral factors
Epidemiological studies
Population-wide family tree databases
References
References are based on the original source and include studies on aging, longevity genetics, and epidemiological family databases....
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qpiqhaml-4104
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How not to die ?
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How not to die?
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This PDF is a summary-style medical-nutritional gu This PDF is a summary-style medical-nutritional guide based on Dr. Michael Greger’s bestselling book How Not to Die. It presents the scientific evidence showing how specific foods and lifestyle choices can prevent, treat, and even reverse the leading causes of death. The document is structured around the idea that diet is the strongest tool humans have to improve longevity, reduce disease risk, and strengthen the body’s natural defenses.
At its core, the PDF explains:
Most premature deaths are preventable through daily nutritional and lifestyle changes—especially a whole-food, plant-based diet.
🩺 1. Focus on Preventing the Top Killers
The PDF highlights how dietary patterns influence mortality from diseases such as:
Cardiovascular disease
High blood pressure
Cancer
Diabetes
Respiratory illnesses
Kidney disease
Neurological decline
How not to die - Michael Greger
The message is consistent: nutrition is medicine.
🌱 2. The Power of Whole Plant Foods
The document promotes a diet centered on:
Vegetables
Fruits
Legumes (beans, lentils)
Whole grains
Nuts & seeds
Herbs & spices
These foods contain fiber, antioxidants, phytonutrients, and anti-inflammatory compounds that protect against disease and support longevity.
How not to die - Michael Greger
🍇 3. “Daily Dozen” Longevity Checklist
Dr. Greger’s famous Daily Dozen appears in the text—a list of 12 food groups and habits to include every day.
These typically include:
Beans
Berries
Cruciferous vegetables
Greens
Whole grains
Nuts and seeds
Fruits
Spices (especially turmeric)
Water
Exercise
How not to die - Michael Greger
The Daily Dozen provides a simple, actionable structure for eating to extend lifespan.
❤️ 4. How Diet Reverses Disease
Key mechanisms highlighted:
✔ Reducing inflammation
Plant foods contain anti-inflammatory compounds that lower chronic disease risk.
✔ Improving endothelial (blood vessel) function
Essential for reversing heart disease.
✔ Reducing oxidative stress
Antioxidants in plants help prevent cellular damage and aging.
✔ Balancing blood sugar
Whole foods stabilize insulin and reduce diabetes risk.
✔ Supporting gut microbiome health
Fiber-rich foods promote healthy bacteria that protect longevity.
How not to die - Michael Greger
🚫 5. Foods and Habits Linked to Higher Mortality
The PDF warns against:
Processed meats
Excessive salt
Refined sugar
Ultra-processed foods
Sedentary lifestyle
Smoking
High intake of animal fats
How not to die - Michael Greger
These factors contribute significantly to premature death.
🧪 6. Evidence-Based Approach
Dr. Greger’s work is built on:
Peer-reviewed medical research
Epidemiological data
Clinical trials
Meta-analyses
The PDF reflects this, presenting diet as a scientifically grounded intervention—not a fad or trend.
How not to die - Michael Greger
👨⚕️ 7. Lifestyle as Medicine
Beyond nutrition, the document includes advice on:
Regular physical activity
Stress reduction
Adequate sleep
Social connection
These lifestyle pillars combine with diet to produce a powerful longevity effect.
How not to die - Michael Greger
⭐ Overall Summary
This PDF provides a clear, impactful overview of Dr. Michael Greger’s message: Most deaths from chronic diseases are preventable, and the most effective path to long life is a whole-food, plant-based diet combined with healthy daily habits. The document explains the foods that protect against disease, the biological mechanisms involved, and the lifestyle changes proven to extend lifespan.
How not to die - Michael Greger
If you want, I can also provide:
✅ A 5-line ultra-short summary
✅ A one-paragraph version
✅ A bullet-point cheat sheet
✅ Urdu/Hindi translation
Just tell me!...
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oconmngi-2383
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fast living
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fast living slow aging
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“The human body is not built for an unlimited life “The human body is not built for an unlimited lifespan. Yet there are many ways in which we can improve and prolong our health. ‘Fast Living, Slow Ageing’ is all about embracing those opportunities.” Robin Holliday, author of ‘Understanding Ageing’ and ‘Ageing: The Paradox of Life’
“Today in Australia, we eat too much and move too little. But it is our future that will carry the cost. Our current ‘fast’ lifestyles will have their greatest impact on our prospects for healthy ageing. This book highlights many of the opportunities we all have to make a diference to our outlook, at a personal and social level.” Professor Stephen Leeder, AO, Director of the Menzies Centre for Health Policy, which leads policy analysis of healthcare
“Healthy ageing can’t be found in a single supplement, diet or lifestyle change. It takes an integrated approach across a number of key areas that complement to slowly build and maintain our health. ‘Fast Living, Slow Ageing’ shows how it is possible to practically develop these kind of holistic techniques and take control of our future.” Professor Marc Cohen, MBBS (Hons), PhD (TCM), PhD (Elec Eng), BMed Sci (Hons), FAMAC, FICAE, Professor, founder of www.thebigwell.com “SLOW is about discovering that everything we do has a knock-on efect, that even our smallest choices can reshape the big picture. Understanding this can help us live more healthily, more fully and maybe even longer too.” Carl Honoré, author of ‘In Praise of Slow’
“We all know about the dangers of fast food. But food is not the only fast thing that is ruining our lives. Slow ageing is about inding important connections in the diet and lifestyle choices we make every day and embracing the possibilities for making real changes - to our own lives - in our own way.” Sally Errey, best-selling author of the cookbook ‘Staying Alive!’ “Ageing is a complex process with many diferent factors combining to determine health and longevity. To slow ageing optimally, we also need to combine a range of lifestyle changes, supplements and other activities. This practical book steers us through the many opportunities we have to change our futures for the better.” Prof Brian J Morris, PhD, DSc, Professor of Molecular Medical Sciences, Basic & Clinical Genomics Laboratory, University of Sydney
‘Fast Living, Slow Ageing’ delivers a combination of well researched strategies from both Western medicine and complementary therapies to enhance your wellness.” Dr Danika Fietz, MBBS, BN (Hons), GP Registrar
“Forget the plastic surgeons, Botox and makeovers! ‘Slow ageing’ is really about the practical choices we make every day to stay healthy, it and vital, to look great and to feel great today and in the years ahead.” Dr David Tye, GP, Kingston Family Clinic, South Brighton, SA
“We all hope that growing old will be part of our lives, although we don’t really want to think about it. In fact, ‘old’ is almost a dirty word in lots of people’s minds! ‘Fast Living, Slow Ageing’ takes you down the path of doing something about how you age, while at the same time providing you with choices and igniting an awareness to start now and take control of how you can age with grace.” Ms Robyn Ewart, businesswoman, mum and household manager
TESTIMONIALS
• 4
FAST LIVING SLOW AGEING
“Ageing is a natural and beautiful process which, all too often, we accelerate through unhealt...
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Genetic Determinants
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Genetic Determinants of Human Longevity
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Thestudyof APOE anditsisoformshasspreadinallthestu Thestudyof APOE anditsisoformshasspreadinallthestudiesaboutthegeneticsofhuman longevityandthisisoneofthefirstgenesthatemergedincandidate-genestudiesandingenome-wide analysisindifferenthumanpopulations.Thepleiotropicrolesofthisgeneaswellasthepatternof variabilityacrossdifferenthumangroupsprovideaninterestingperspectiveontheanalysisofthe evolutionaryrelationshipbetweenhumangenetics,environmentalvariables,andtheattainmentof extremelongevityasahealthyphenotype.Inthepresentreview,thefollowingtopicswillbediscussed
Serena Dato obtained a Ph.D. in Molecular Bio-Pathology in 2004. Since September 2006, she has been an Assistant Professor in Genetics at the Department of Cell Biology of the University of Calabria, where she carries out research at the Genetics Laboratory. From the beginnning, her research interests have focused on the study of human longevity and in particular on the development of experimental designs and new analytical approaches for the study of the genetic component of longevity. With her group, she developed an algorithm for integrating demographic data into genetics, which enabled the application of a genetic-demographic analysis to crosssectional samples. She was involved in several recruitment campaigns for the collection of data and DNA samples from old and oldest-old people in her region, both nonagenarian and centenarian families. She has several international collaborations with groups involved in her research field in Europe and the USA. Since 2008, she has been actively collaborating with the research group of Prof. K. Christensen at the Aging Research Center of the Institute of Epidemiology of Southern Denmark University, where she spent a year as a visiting researcher in 2008. Up to now, her work has led to forty-eight scientific papers in peer reviewed journals, two book chapters and presentations at scientific conferences.
Mette Sørensen has been active within ageing research since 2006, with work ranging from functional molecular biological studies to genetic epidemiology and bioinformatics. She obtained a Ph.D. in genetic epidemiology of human longevity in 2012 and was appointed Associate Professor at the University of Southern Denmark in March 2019. Her main research interest is in the mechanisms of ageing, age-related diseases and longevity, with an emphasis on genetic and epigenetic variation. Her work is characterized by a high degree of international collaboration and interdisciplinarity. The work has, per September 2019, led to thirty-one scientific papers in peer reviewed journal, as well as popular science communications, presentations at scientific conferences, media appearances, and an independent postdoctoral grant from the Danish Research Council in 2013.
Giuseppina Rose is Associate Professor in Genetics at the University of Calabria. She graduated from the University of Calabria School of Natural Science in 1983 and served as a Research Assistant there from 1992–1999. In 1994 she achieved a Ph.D. in Biochemistry and Molecular Biology at
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Mortality Assumptions
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Mortality Assumptions and Longevity Risk
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This report is a clear, authoritative examination This report is a clear, authoritative examination of how mortality assumptions—the predictions actuaries make about how long people will live—directly shape the financial security, pricing, risk exposure, and solvency of life insurance companies and pension plans. As life expectancy continues to rise unpredictably, the paper explains why longevity risk—the risk that people live longer than expected—is now one of the most serious and complex challenges in actuarial science.
Its central message:
Even small errors in mortality assumptions can create massive financial consequences.
When people live longer than anticipated, insurers and pension funds must pay out benefits for many more years, straining reserves, capital, and long-term sustainability.
🧩 Core Themes & Insights
1. Mortality Assumptions Are Foundational
Mortality assumptions influence:
annuity pricing
pension liabilities
life insurance reserves
regulatory capital requirements
asset–liability management
They are used to determine how much money must be set aside today to pay benefits decades into the future.
2. Longevity Risk: People Live Longer Than Expected
Longevity risk arises from:
ongoing medical advances
healthier lifestyles
improved survival at older ages
cohort effects (younger generations aging differently)
This creates systematic risk—it affects entire populations, not just individuals. Because it is long-term and highly uncertain, it is extremely difficult to hedge.
3. Why Mortality Forecasting Is Difficult
The report highlights key sources of uncertainty:
unpredictable improvements in disease treatment
variability in long-term mortality trends
differences in male vs. female mortality improvement
cohort effects (e.g., baby boom generation)
socioeconomic and geographic differences
Traditional deterministic life tables struggle to capture these dynamic changes.
4. Stochastic Mortality Models Are Essential
The paper emphasizes the growing use of:
Lee–Carter models
CBD (Cairns–Blake–Dowd) models
Multi-factor and cohort mortality models
These models incorporate randomness and allow actuaries to estimate:
future mortality paths
probability distributions
“best estimate” and adverse scenarios
This is crucial for capital planning and solvency regulation.
5. Financial Implications of Longevity Risk
When mortality improves faster than assumed:
annuity liabilities increase
pension funding gaps widen
life insurers face reduced profits
capital requirements rise
The paper explains how regulatory frameworks (e.g., Solvency II, RBC) require insurers to hold additional capital to protect against longevity shocks.
6. Tools to Manage Longevity Risk
To control exposure, companies use:
A. Longevity swaps
Transfer the risk that annuitants live longer to reinsurers or capital markets.
B. Longevity bonds and mortality-linked securities
Spread demographic risks to investors.
C. Reinsurance
Offload part of the longevity exposure.
D. Natural hedging
Balance life insurance (mortality risk) with annuities (longevity risk).
E. Scenario testing & stress testing
Evaluate the financial impact if life expectancy rises 2–5 years faster than expected.
7. Global Perspective
Countries with rapid aging—Japan, the UK, Western Europe, China—are most exposed. Regulators encourage:
more robust mortality modeling
transparent risk disclosures
dynamic assumption-setting
stronger capital buffers
The report stresses that companies must continually update assumptions as new mortality data emerge.
🧭 Overall Conclusion
The paper concludes that accurate mortality assumptions are essential for financial stability in life insurance and pensions. As longevity continues to improve unpredictably, longevity risk becomes one of the most significant threats to solvency. Insurers must adopt:
advanced mortality models
strong risk-transfer mechanisms
dynamic assumption frameworks
robust capital strategies
Longevity is a gift for individuals—but a major quantitative, financial, and strategic challenge for institutions responsible for lifetime benefits....
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Aging and aging-related
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Aging and aging-related disease
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Aging is a gradual and irreversible pathophysiolog Aging is a gradual and irreversible pathophysiological process. It presents with declines in tissue and cell functions and significant increases in the risks of various aging-related diseases, including neurodegenerative diseases, cardiovascular diseases, metabolic diseases, musculoskeletal diseases, and immune system diseases. Although the development of modern medicine has promoted human health and greatly extended life expectancy, with the aging of society, a variety of chronic diseases have gradually become the most important causes of disability and death in elderly individuals. Current research on aging focuses on elucidating how various endogenous and exogenous stresses (such as genomic instability, telomere dysfunction, epigenetic alterations, loss of proteostasis, compromise of autophagy, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, altered intercellular communication, deregulated nutrient sensing) participate in the regulation of aging. Furthermore, thorough research on the pathogenesis of aging to identify interventions that promote health and longevity (such as caloric restriction, microbiota transplantation, and nutritional intervention) and clinical treatment methods for aging-related diseases (depletion of senescent cells, stem cell therapy, antioxidative and anti-inflammatory treatments, and hormone replacement therapy) could decrease the incidence and development of aging-related diseases and in turn promote healthy aging and longevity...
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Leaving No One Behind
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Leaving No One Behind In An Ageing World
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“Leaving No One Behind in an Ageing World” is the “Leaving No One Behind in an Ageing World” is the United Nations World Social Report 2023, a comprehensive and authoritative analysis of global population ageing. It explores how the world is undergoing a permanent demographic shift toward older populations—and what must be done to ensure all people can age with dignity, health, and economic security.
It explains that population ageing is not a crisis, but a global success story—the result of longer lifespans, improvements in health, education, gender equality, and reduced fertility. However, it also warns that inequality, poverty, weak care systems, and inadequate policies risk leaving millions of older persons behind.
The report provides data, trends, challenges, and policy recommendations across five major chapters.
📌 Main Themes of the Report
1. A Rapidly Ageing World
By 2050, the number of people aged 65+ will more than double—from 761 million to 1.6 billion.
The population aged 80+ will almost triple to 459 million.
Ageing is happening everywhere, but fastest in:
Northern Africa & Western Asia
Sub-Saharan Africa
Eastern & South-Eastern Asia
The world’s oldest countries are shifting from Europe to Asia.
The report highlights how societies of tomorrow will be younger in fewer places, older almost everywhere.
2. Living Longer, Healthier Lives
Rising longevity is a major human achievement.
Premature deaths have fallen.
People live more years in good health.
But gaps remain:
Women live longer but often face more unhealthy years.
Poorer populations have shorter and less healthy lives.
COVID-19 disrupted progress in life expectancy.
Healthy ageing requires lifelong investment in education, nutrition, healthcare, safety, and environments.
3. What Ageing Means for Economies
The report rejects the idea that older populations are “burdens.”
Key points:
Population ageing affects labour, consumption, taxes, pensions, and long-term care.
With good policies, ageing can bring:
Increased productivity
A stronger labour force via women and older workers
Two “demographic dividends,” if countries invest early
Many older people contribute economically through:
Paid work
Volunteering
Childcare for families
Financial support to younger generations
However, ageing challenges include:
Rising pension and healthcare costs
A shrinking workforce
Inequitable labour markets
Lower savings among future generations
4. Ageing, Poverty, and Inequality
The report stresses that ageing does not create inequality—inequality throughout life creates unequal ageing.
Key findings:
Older persons are more likely to be poor than working-age people, especially in developing countries.
Inequalities accumulate across life:
Poor childhood conditions
Unequal education
Employment insecurity
Gender discrimination
Women face far greater risks due to:
Lower lifetime earnings
Informal/unpaid caregiving roles
Longer lifespans
Higher risk of widowhood
Future generations of older people may be more unequal than today, unless countries act now.
5. A Global Crisis of Care
Demand for long-term care is skyrocketing as populations age, especially above age 80.
Problems:
Most countries are not prepared.
Care systems are underfunded.
Care jobs are low-paid and mostly done by women.
Families—especially daughters—bear the unpaid burden.
COVID-19 exposed deep weaknesses in care facilities.
Solutions recommended:
Build integrated long-term care systems.
Professionalize and protect care workers.
Ensure quality standards and monitoring.
Support “ageing in place” (staying at home).
Reduce reliance on informal unpaid care.
🌍 What “Leaving No One Behind” Means
The report shows that ageing affects:
Health systems
Education
Labour markets
Taxes
Pensions
Social protection
Gender equality
Migration
Long-term care
It argues that ageing must become a central policy priority at national and global levels.
🏛️ Key Policy Recommendations
A. Start Early—Lifelong Interventions
Equal access to quality education
Lifelong learning
Healthy environments
Decent work
Fair labour markets
Support for women, caregivers, and informal workers
B. Strengthen Social Protection & Pensions
Universal pensions or tax-funded basic benefits
Avoid shifting financial risks to individuals
Expand coverage of retirees in informal economies
Use fair and progressive tax systems
C. Build Strong Long-Term Care Systems
Public funding
Trained and protected care workers
Home- and community-based care options
Better regulation, monitoring, and accountability
D. Promote Intergenerational Equity
Address income, education, and health gaps early in life
Encourage solidarity between generations
Prepare youth now to become healthy, secure older adults later
✨ Perfect Summary Statement
The PDF is a global roadmap for managing population ageing in a way that protects rights, reduces inequality, improves health, strengthens economies, and ensures that no person—young or old—is left behind in a rapidly ageing world....
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Promoting Active Ageing
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Promoting Active Ageing
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“Promoting Active Ageing in Southeast Asia” is a c “Promoting Active Ageing in Southeast Asia” is a comprehensive OECD/ERIA report that examines how ASEAN countries can support healthy, productive, and secure ageing as their populations grow older at unprecedented speed. The report highlights that Southeast Asia is ageing twice as fast as OECD nations, while still facing high levels of informal employment, limited social protection, and gender inequality—making ageing a major economic and social challenge.
Core Purpose
The report identifies what policies ASEAN member states must adopt to ensure:
Older people can remain healthy,
Continue to participate socially and economically, and
Avoid income insecurity in old age.
🧩 What the Report Covers
1. Demographic & Economic Realities
Fertility has dropped across all countries; life expectancy continues to rise.
The old-age to working-age ratio will surge in the next 30 years.
Working-age populations will decrease sharply in Singapore, Thailand, and Vietnam, while still growing in Cambodia, Laos, and the Philippines.
Public expenditure is low, leaving governments with limited capacity to fund pensions or healthcare.
2. Key Barriers to Active Ageing
High informality (up to 90% in some countries): keeps workers outside formal pensions, healthcare, and protections.
Gender inequalities in work, caregiving, and legal rights compound poverty risks for older women.
Low healthcare spending, shortages of medical staff, and rural access gaps.
Limited pension adequacy, low coverage, and low retirement ages.
🧭 Major Policy Recommendations
A. Reduce Labour Market Informality
Lower the cost of formalisation for low-income workers.
Strengthen labour law enforcement and improve business registration processes.
Relax overly strict product/labour market regulations.
B. Reduce Gender Inequality in Old Age
Integrate gender perspectives into all policy design.
Reform discriminatory family and inheritance laws.
Promote financial education and career equality for women.
C. Ensure Inclusive Healthcare Access
Increase public health funding.
Improve efficiency through generics, preventive care, and technology.
Expand health insurance coverage to all.
Use telemedicine and incentives to serve rural areas.
D. Strengthen Old-Age Social Protection
Increase first-tier (basic) pensions.
Raise retirement ages where needed and link them to life expectancy.
Reform PAYG pensions to ensure sustainability.
Make pension systems easier to understand and join.
E. Support Social Participation of Older Adults
Build age-friendly infrastructure (benches, safe crossings, accessible paths).
Create community programs that encourage interaction and prevent isolation.
🧠 Why This Matters
By 2050, ASEAN countries will face dramatic demographic shifts. Without rapid and coordinated policy reforms, millions of older people risk:
Poor health
Lack of income
Social isolation
Inadequate care
This report serves as a strategic blueprint for building healthy, productive, and resilient ageing societies in Southeast Asia....
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Promoting Active Ageing
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Promoting Active Ageing
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“Promoting Active Ageing in Southeast Asia” is a c “Promoting Active Ageing in Southeast Asia” is a comprehensive OECD/ERIA report that examines how ASEAN countries can support healthy, productive, and secure ageing as their populations grow older at unprecedented speed. The report highlights that Southeast Asia is ageing twice as fast as OECD nations, while still facing high levels of informal employment, limited social protection, and gender inequality—making ageing a major economic and social challenge.
Core Purpose
The report identifies what policies ASEAN member states must adopt to ensure:
Older people can remain healthy,
Continue to participate socially and economically, and
Avoid income insecurity in old age.
🧩 What the Report Covers
1. Demographic & Economic Realities
Fertility has dropped across all countries; life expectancy continues to rise.
The old-age to working-age ratio will surge in the next 30 years.
Working-age populations will decrease sharply in Singapore, Thailand, and Vietnam, while still growing in Cambodia, Laos, and the Philippines.
Public expenditure is low, leaving governments with limited capacity to fund pensions or healthcare.
2. Key Barriers to Active Ageing
High informality (up to 90% in some countries): keeps workers outside formal pensions, healthcare, and protections.
Gender inequalities in work, caregiving, and legal rights compound poverty risks for older women.
Low healthcare spending, shortages of medical staff, and rural access gaps.
Limited pension adequacy, low coverage, and low retirement ages.
🧭 Major Policy Recommendations
A. Reduce Labour Market Informality
Lower the cost of formalisation for low-income workers.
Strengthen labour law enforcement and improve business registration processes.
Relax overly strict product/labour market regulations.
B. Reduce Gender Inequality in Old Age
Integrate gender perspectives into all policy design.
Reform discriminatory family and inheritance laws.
Promote financial education and career equality for women.
C. Ensure Inclusive Healthcare Access
Increase public health funding.
Improve efficiency through generics, preventive care, and technology.
Expand health insurance coverage to all.
Use telemedicine and incentives to serve rural areas.
D. Strengthen Old-Age Social Protection
Increase first-tier (basic) pensions.
Raise retirement ages where needed and link them to life expectancy.
Reform PAYG pensions to ensure sustainability.
Make pension systems easier to understand and join.
E. Support Social Participation of Older Adults
Build age-friendly infrastructure (benches, safe crossings, accessible paths).
Create community programs that encourage interaction and prevent isolation.
🧠 Why This Matters
By 2050, ASEAN countries will face dramatic demographic shifts. Without rapid and coordinated policy reforms, millions of older people risk:
Poor health
Lack of income
Social isolation
Inadequate care
This report serves as a strategic blueprint for building healthy, productive, and resilient ageing societies in Southeast Asia....
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A New Map of Life
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A New Map of Life
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Longevity is not a synonym of old age. The increas Longevity is not a synonym of old age. The increase in life expectancy shapes lives from childhood to old age across different domains. Among those, the nature of work will undergo profound changes from skill development and the role of retirement to the intrinsic meaning of work. To put the striking potential of a 100 year life into a historical prospective it is useful to start from how technological and demographic development shaped the organization and the definition of work in the past. This longer view can more thoughtfully explore how different the nature of work has been, from working hours to the parallelism between work, employment and task-assignment.
Throughout history the role of work has been intertwined with social and technological change. Societies developed from hunter-gather to sedentary farmers, and they transitioned from the agricultural to the industrial revolution. The latter transformed a millennial long practice of self-employed farmers and artisans, working mostly for self-subsistence, without official working hours, relying on daylight and seasonality at an unchosen job from childhood until death, into employees working 10-16 hours per day for 311 days a year, mostlyindoorsfromyouthtoretirement. Thisdrastictransformationignitedfastshiftsofworkorganization not only in the pursue of higher productivity and technological advancement, but also of social wellbeing.
Among the first changes was the abandonment of unsustainable working conditions, such as day working hours, which sharply converged toward the eight hours day tendency between the 1910s and the 1940s, see Figure 1 (Huberman and Minns 2007; Feenstra, Inklaar, and Timmer 2015; Charlie Giattino and Roser 2013). Although beneficial for the workers, this reduction worried intellectuals, such as the economist John Maynard Keynes, who wrote: “How will we all keep busy when we only have to work 15 hours a week?” (Keynes 1930). Keynes predicted people’s work to become barely necessary given the level of productivity the economy would reach over the next century: “permanent problem would be how to occupy the leisure,
1
whichscienceandcompoundinterestwillhavewonforhim. [...] Afearfulproblemfortheordinaryperson” (p. 328). For a while, Keynes seemed right since the average workweek dropped from 47 hours in 1930 to slightly less than 39 by 1970. However, after declining for more than a century, the average U.S. work week has been stagnant for four decades, at approximately eight hours per day.1
Figure 1: Average working hours per worker over a full year. Before 1950 the data corresponds only to full-time production workers(non-agricultural activities). Starting 1950 estimates cover total hours worked in the economy as measured from primarily National Accounts data. Source: Charlie Giattino and Roser (2013). Data Sources: Huberman and Minns (2007) and Feenstra, Inklaar, and Timmer (2015).
Technological change did not make work obsolete, but changed the tasks and the proportion of labor force involved in a particular job. In the last seventy years, for example, the number of people employed in the agricultural sector dropped by one third (from almost 6 million to 2 million), while the productivity tripled. Feeding or delivering calves is still part of ranchers’ days, but activities like racking and analyzing genetic traits of livestock and estimating crop yields are a big part of managing and sustaining the ranch operations. In addition, the business and administration activity like bookkeeping, logistics, market pricing, employee supervision became part of the job due to the increase in average farm size from 200 to 450 acres. Another exampleistheeffectoftheautomatedtellermachine(ATM)onbanktellers, whosenumbergrewfromabout a quarter of a million to a half a million in the 45 years since the introduction of ATMs, see Figure 2 (Bessen 2016). ATM allowed banks to operate branch offices at lower cost, which prompted them to open many 1Despite the settling, differences in the number of hours worked between the low and the high skilled widened in the last fifty years. Men without a high school degree experienced an average reduction of eight working hours a week, while college graduates faced an increase of six hours a week. Similarly, female graduates work 11 hours a week more than those who did not complete high school (Dolton 2017). Overall, American full-time employees work on average 41.5 hours per week, and about 11.1% of employees work over 50 hours per week, which is much higher than countries with a comparable level of productivity like Switzerland, where 0.4% of employees work over 50 hours per week (Feenstra, Inklaar, and Timmer 2015) and part time work is commonplace...
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Future-Proofing the life
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Future-Proofing the Longevity
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This document is published by the World Economic F This document is published by the World Economic Forum as a contribution to a project, insight area or interaction. The findings, interpretations and conclusions expressed herein are the result of a collaborative process facilitated and endorsed by the World Economic Forum but whose results do not necessarily represent the views of the World Economic Forum, nor the entirety of its Members, Partners or other stakeholders. In this paper, many areas of innovation have been highlighted with the potential to support the longevity economy transition. The fact that a particular company or product is highlighted in this paper does not represent an endorsement or recommendation on behalf of the World
Haleh Nazeri Lead, Longevity Economy, World Economic Forum
Graham Pearce Senior Partner, Global Defined Benefit Segment Leader, Mercer
The world appears increasingly fragmented, but one universal reality connects us all – ageing. Across the world, people are living longer than past generations, in some cases by up to 20 years. This longevity shift, coupled with declining birth rates, is reshaping economies, workforces and financial systems, with profound implications for individuals, businesses and governments alike.
As countries transform, the systems that underpin them must also evolve. Today’s reality includes a widening gap between healthspan and lifespan, the emergence of a multigenerational workforce with five generations working side by side, and the need for stronger intergenerational collaboration.
One of the most important topics to consider during this demographic transition is the economic implications of longer lives. This paper highlights five key trends that will influence and shape the financial resilience of institutions, governments
and individuals in the years ahead. It also showcases innovative solutions that are already being implemented by countries, businesses and organizations to prepare for the future.
While the challenges are significant, they also present an opportunity to develop systems that are more inclusive, equitable, resilient and sustainable for the long term. This is a chance to strengthen pension systems and social protections, not only for those who have traditionally benefited, but also for those who were left out of social contracts the first time.
We are grateful to our multistake holder consortium of leaders across business, the public sector, civil society and academia for their contributions, inputs and collaboration on this report. We look forward to seeing how others will continue to build on these innovative ideas to future-proof the longevity economy for a brighter and more ...
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Live Longer
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How to live longer ?
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How to Live Longer is a comprehensive, science-bas How to Live Longer is a comprehensive, science-based lifestyle guide that translates decades of longevity research into simple daily actions that anyone can apply. Designed as a practical handbook rather than an academic review, it organizes the most powerful, evidence-supported habits into six core pillars of healthy aging:
Stay Active
Eat Wisely
Manage Stress
Sleep Well
Build Social Connection
Maintain Mental Stimulation
These pillars form a “longevity lifestyle,” emphasizing that small, consistent actions—especially in midlife—produce large benefits in later years.
The eBook integrates insights from real-world longevity hotspots such as Blue Zones (Okinawa, Sardinia, Nicoya, Ikaria, Loma Linda), modern public-health science, and behavioral psychology to show how daily routines shape health trajectories across the lifespan.
🔍 Core Pillars & Science-Backed Practices
1. Staying Active
Activity is the single strongest predictor of how well someone ages.
The guide recommends:
Strength training
Frequent walking
Active living (taking stairs, chores, gardening)
Stretching for mobility
Regular physical activity improves the heart, brain, metabolism, muscle strength, mood, and overall vitality.
2. Eating Wisely
A longevity-focused diet emphasizes:
Mostly plant-based meals
Fruits, vegetables, whole grains, legumes
Nuts and seeds daily
Healthy fats (olive oil, omega-3s)
Smaller portions and mindful eating
The guide highlights traditional dietary patterns of Blue Zones, especially Mediterranean and Okinawan models, which are strongly linked to long life and reduced chronic disease.
3. Managing Stress
Chronic stress accelerates aging, inflammation, and disease.
The eBook recommends:
Mindfulness and meditation
Breathing exercises
Yoga
Time in nature
Hobby-based relaxation
Scheduling downtime
These practices help regulate emotional well-being, improve resilience, and support healthier biological aging.
4. Good Quality Sleep
Sleep is described as a longevity multiplier, with profound effects on immune health, metabolic balance, brain function, and emotional stability.
The guide includes:
Consistent sleep schedules
Dark, cool sleeping environments
Reducing caffeine, alcohol, and screens before bed
5. Social Connection
Loneliness is a major risk factor for early mortality, comparable to smoking and inactivity.
The eBook emphasizes:
Strong family bonds
Friendships
Community involvement
Purposeful living (“ikigai”)
This reflects consistent findings from longevity populations worldwide.
6. Staying Mentally Active
Lifelong learning, mental stimulation, and cognitively engaging activities help preserve brain function.
Recommendations include:
Reading
Learning new skills
Puzzles or games
Creative pursuits
These habits strengthen cognitive reserve and support healthier aging.
💡 Overall Insight
The eBook argues that longevity is not about extreme interventions—it is about consistent, realistic, enjoyable habits grounded in strong science. It blends public-health evidence with lifestyle medicine, emphasizing that aging well is achievable for anyone, regardless of genetics.
Across all chapters, the tone remains practical: longevity is built through everyday choices, not expensive biohacking.
🧭 In Summary
How to Live Longer is a practical, evidence-driven handbook that shows how daily movement, nutritious eating, stress control, quality sleep, social belonging, and lifelong learning combine to support longer, healthier, more fulfilling lives....
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financial impact
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financial impact of longevity and risk
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e economic and fiscal effects of an aging society e economic and fiscal effects of an aging society have been extensively studied and are generally recognized by policymakers, but the financial consequences associated with the risk that people live longer than expected—longevity risk—has received less attention.1 Unanticipated increases in the average human life span can result from misjudging the continuing upward trend in life expectancy, introducing small forecasting errors that compound over time to become potentially significant. This has happened in the past. There is also risk of a sudden large increase in longevity as a result of, for example, an unanticipated medical breakthrough. Although longevity advancements increase the productive life span and welfare of millions of individuals, they also represent potential costs when they reach retirement. More attention to this issue is warranted now from the financial viewpoint; since longevity risk exposure is large, it adds to the already massive costs of aging populations expected in the decades ahead, fiscal balance sheets of many of the affected countries are weak, and effective mitigation measures will take years to bear fruit. The large costs of aging are being recognized, including a belated catchup to the currently expected increases in average human life spans. The costs of longevity risk—unexpected increases in life spans—are not well appreciated, but are of similar magnitude. This chapter presents estimates that suggest that if everyone lives three years longer than now expected—the average underestimation of longevity in the past—the present discounted value of the additional living expenses of everyone during those additional years of life amounts to between 25 and 50 percent of 2010 GDP. On a global scale, that increase amounts to tens of trillions of U.S. dollars, boosting the already recognized costs of aging substantially. Threats to financial stability from longevity risk derive from at least two major sources. One is the
Note: This chapter was written by S. Erik Oppers (team leader), Ken Chikada, Frank Eich, Patrick Imam, John Kiff, Michael Kisser, Mauricio Soto, and Tao Sun. Research support was provided by Yoon Sook Kim. 1See, for example, IMF (2011a).
threats to fiscal sustainability as a result of large longevity exposures of governments, which, if realized, could push up debttoGDP ratios more than 50 percentage points in some countries. A second factor is possible threats to the solvency of private financial and corporate institutions exposed to longevity risk; for example, corporate pension plans in the United States could see their liabilities rise by some 9 percent, a shortfall that would require many multiples of typical yearly contributions to address. Longevity risk threatens to undermine fiscal sustainability in the coming years and decades, complicating the longerterm consolidation efforts in response to the current fiscal difficulties.2 Much of the risk borne by governments (that is, current and future taxpayers) is through public pension plans, social security schemes, and the threat that private pension plans and individuals will have insufficient resources to provide for unexpectedly lengthy retirements. Most private pension systems in the advanced economies are currently underfunded and longevity risk alongside low interest rates further threatens their financial health. A threepronged approach should be taken to address longevity risk, with measures implemented as soon as feasible to avoid a need for much larger adjustments later. Measures to be taken include: (i) acknowledging government exposure to longevity risk and implementing measures to ensure that it does not threaten medium and longterm fiscal sustainability; (ii) risk sharing between governments, private pension providers, and individuals, partly through increased individual financial buffers for retirement, pension system reform, and sustainable oldage safety nets; and (iii) transferring longevity risk in capital markets to those that can better bear it. An important part of reform will be to link retirement ages to advances in longevity. If undertaken now, these mitigation measures can be implemented in a gradual and sustainable way. Delays would increase risks to financial and fiscal stability, potentially requiring much larger and disruptive measures in the future.
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Extreme Human Lifespan
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Extreme Human Lifespan
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The indexed individual, from now on termed M116, w The indexed individual, from now on termed M116, was the world's oldest verified living person from January 17th 2023 until her passing on August 19th 2024, reaching the age of 117 years and 168 days (https://www.supercentenarian.com/records.html). She was a Caucasian woman born on March 4th 1907 in San Francisco, USA, from Spanish parents and settled in Spain since she was 8. A timeline of her life events and her genealogical tree are shown in Supplementary Fig. 1a-b. Although centenarians are becoming more common in the demographics of human populations, the so-called supercentenarians (over 110 years old) are still a rarity. In Catalonia, the historic nation where M116 lived, the lifeexpectancy for women is 86 years, so she exceeded the average by more than 30 years (https://www.idescat.cat). In a similar manner to premature aging syndromes, such as Hutchinson-Gilford Progeria and Werner syndrome, which can provide relevant clues about the mechanisms of aging, the study of supercentenarians might also shed light on the pathways involved in lifespan. To unfold the biological properties exhibited by such a remarkable human being, we developed a comprehensive multiomics analysis of her genomic, transcriptomic, metabolomic, proteomic, microbiomic and epigenomic landscapes in different tissues, as depicted in Fig. 1a, comparing the results with those observed in non-supercentenarian populations. The picture that emerges from our study shows that extremely advanced age and poor health are not intrinsically linked and that both processes can be distinguished and dissected at the molecular level.
RESULTS AND DISCUSSION Samples from the subject were obtained from four different sources: total peripheral blood, saliva, urine and stool at different times. Most of the analyses were performed in the blood material at the time point of 116 years and 74 days, unless otherwise specifically indicated (Data set 1). The simple karyotype of the supercentenarian did not show any gross chromosomal alteration (Supplementary Fig. 1c). Since many reports indicate the involvement of telomeres in aging and lifespan1, we interrogated the telomere length of the M116 individual using High-Throughput Quantitative Fluorescence In Situ Hybridization (HT-Q-FISH) analysis2. Illustrative confocal images with DAPI staining and the telomeric probe (TTAGGG) for M116 and two control samples are shown in Fig. 1b. Strikingly, we observed that the supercentenarian exhibited the shortest mean telomere length among all healthy volunteers3 with a value of barely 8 kb (Fig. 1c). Even more noticeably, the M116 individual displayed a 40% of short telomeres below the 20th percentile of all the studied samples (Fig. 1c). Thus, the observed far reach longevity of our case occurred in the chromosomal context of extremely short telomeres. Interestingly, because the M116 individual presented an overall good health status, it is tempting to speculate that, in this ...
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AGEING IN ASIA
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AGEING IN ASIA AND THE PACIFIC
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as a whole. This highlights the need for countries as a whole. This highlights the need for countries with relatively low proportion of older persons to also put in place appropriate policies and interventions to address their specific rights and needs, and to prepare for ageing societies in the future.
An increase in the proportion and number of the oldest old (persons over the age of 80 years)
The oldest old person, the number of people aged 80 years or over, in the region is also showing a dramatic upward trend. The proportion of the oldest old in the region in the total population 2016 was 1.5 per cent of the population amounting to 68 million people, which is 53 per cent of the global population over 80 years old. This proportion is expected to rise to 5 per cent of the population totaling 258 million people by 2050. Asia
Pacific would have 59 per cent of the world population over 80 years of age compared to 53 per cent at present. This has serious implications for provision of appropriate health care and long term care, as well as income security.
The causes…
The drastic increase in the pace of ageing in the region can be attributed to two key factors, declining fertility rates and increasing life expectancies.
Rapidly declining fertility: The most precipitous declines in the region’s fertility have been in the South and SouthWest, and South-East Asia subregions, with the fertility rates falling by 50 per cent in a span of 40 years. ...
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Happy People Live Longer
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Happy People Live Longer
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This comprehensive review demonstrates that subjec This comprehensive review demonstrates that subjective well-being (SWB)—including happiness, life satisfaction, optimism, and positive emotions—plays a causal and measurable role in promoting better health, stronger physiological functioning, and longer life. Drawing on seven converging lines of evidence from longitudinal human studies, laboratory experiments, physiological research, animal studies, natural experiments, and intervention trials, the authors present one of the most rigorous and multidimensional examinations of the happiness–health connection.
The review shows that individuals who experience higher levels of SWB not only report better health but live significantly longer, even when controlling for baseline health status, socioeconomic factors, and lifestyle. Positive emotions predict reduced mortality, lower risk of cardiovascular disease, stronger immune function, and improved resilience to stress. In contrast, chronic negative emotions—such as depression, anxiety, and hostility—are linked to inflammation, impaired immunity, hypertension, atherosclerosis, and accelerated aging.
The document organizes evidence into seven major categories:
1. Long-term Prospective Studies
Large-scale, decades-long studies consistently show that SWB predicts longevity in healthy populations and sometimes improves survival in diseased populations. Optimists and individuals with high positive affect live longer than pessimists and those with low affect.
2. Naturalistic Physiological Studies
Everyday positive emotions correlate with lower cortisol, reduced blood pressure, healthier cardiovascular responses, and lower inflammation. Negative emotions produce harmful biological patterns such as elevated cytokines and delayed wound healing.
3. Experimental Mood Induction Studies
When researchers induce positive or negative emotions in controlled settings, they observe immediate changes in cardiovascular activity, immune function, stress hormones, and healing responses—confirming direct causal pathways.
4. Animal Research
Studies on monkeys, pigs, hamsters, and rodents show that stress compromises immunity, accelerates disease processes, and shortens lifespan, while positive social environments and reward-based experiences promote health and healing.
5. Quasi-experimental Studies of Real-world Events
Major emotional events—earthquakes, wars, bereavement—produce measurable spikes in mortality and biological stress markers, revealing how emotional states influence health at the population level.
6. Interventions That Improve SWB
Meditation, relaxation training, social support enhancement, and hostility-reduction interventions lead to measurable improvements in immune function, blood pressure, wound healing, and in some cases, longer survival.
7. Studies on Quality of Life and Pain
Positive emotions reduce pain sensitivity, accelerate functional recovery, and improve daily functioning among people with chronic illnesses.
Key Conclusion
Across diverse methods and populations, the evidence forms a compelling causal model:
**Happiness is not just an outcome of good health—
it is a contributor to it.**
SWB influences the immune, cardiovascular, endocrine, and inflammatory systems, shaping vulnerability or resilience to disease. While happiness cannot cure all illnesses, especially severe or rapidly progressing diseases, it profoundly improves health trajectories in both healthy and clinical populations.
In Essence
This document is a landmark synthesis demonstrating that happy people truly live longer, and that fostering subjective well-being is not merely a psychological luxury but a powerful public health priority with far-reaching implications for prevention, aging, and holistic healthcare.
If you'd like, I can also create:
✅ A shorter description
✅ An academic abstract
✅ A graphical diagram summarizing the pathways
✅ A bullet-point executive overview
Just tell me!...
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foot prints in the sand
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foot prints in the sand
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Stephen Treaster1,2, David Karasik3,4*† and Matthe Stephen Treaster1,2, David Karasik3,4*† and Matthew P. Harris1,2†
1 Department of Orthopaedics, Boston Children’s Hospital, Boston, MA, United States, 2 Department of Genetics, Harvard Medical School, Boston, MA, United States, 3 Azrieli Faculty of Medicine, Bar-Ilan University, Ramat Gan, Israel, 4 Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, United States
With the modern quality, quantity, and availability of genomic sequencing across species, as well as across the expanse of human populations, we can screen for shared signatures underlying longevity and lifespan. Knowledge of these mechanisms would be medically invaluable in combating aging and age-related diseases. The diversity of longevities across vertebrates is an opportunity to look for patterns of genetic variation that may signal how this life history property is regulated, and ultimately how it can be modulated. Variation in human longevity provides a unique window to look for cases of extreme lifespan within a population, as well as associations across populations for factors that influence capacity to live longer. Current large cohort studies support the use of population level analyses to identify key factors associating with human lifespan. These studies are powerful in concept, but have demonstrated limited ability to resolve signals from background variation. In parallel, the expanding catalog of sequencing and annotation from diverse species, some of which have evolved longevities well past a human lifespan, provides independent cases to look at the genomic signatures of longevity. Recent comparative genomic work has shown promise in finding shared mechanisms associating with longevity among distantly related vertebrate groups. Given the genetic constraints between vertebrates, we posit that a combination of approaches, of parallel meta-analysis of human longevity along with refined analysis of other vertebrate clades having exceptional longevity, will aid in resolving key regulators
of enhanced lifespan that have proven to be elusive when analyzed in isolation....
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vwitogci-0660
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Developmental Diet Alters
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Developmental Diet Alters the Fecundity–Longevity
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Drosophila melanogaster David H. Collins, PhD,*, D Drosophila melanogaster David H. Collins, PhD,*, David C. Prince, PhD, Jenny L. Donelan, MSc, Tracey Chapman, PhD , and Andrew F. G. Bourke, PhD School of Biological Sciences, University of East Anglia, Norwich, UK. *Address correspondence to: David H. Collins, PhD. E-mail: David.Collins@uea.ac.uk Decision Editor: Gustavo Duque, MD, PhD (Biological Sciences Section)
Abstract The standard evolutionary theory of aging predicts a negative relationship (trade-off) between fecundity and longevity. However, in principle, the fecundity–longevity relationship can become positive in populations in which individuals have unequal resources. Positive fecundity–longevity relationships also occur in queens of eusocial insects such as ants and bees. Developmental diet is likely to be central to determining trade-offs as it affects key fitness traits, but its exact role remains uncertain. For example, in Drosophila melanogaster, changes in adult diet can affect fecundity, longevity, and gene expression throughout life, but it is unknown how changes in developmental (larval) diet affect fecundity–longevity relationships and gene expression in adults. Using D. melanogaster, we tested the hypothesis that varying developmental diets alters the directionality of fecundity–longevity relationships in adults, and characterized associated gene expression changes. We reared larvae on low (20%), medium (100%), and high (120%) yeast diets, and transferred adult females to a common diet. We measured fecundity and longevity of individual adult females and profiled gene expression changes with age. Adult females raised on different larval diets exhibited fecundity–longevity relationships that varied from significantly positive to significantly negative, despite minimal differences in mean lifetime fertility or longevity. Treatments also differed in age-related gene expression, including for aging-related genes. Hence, the sign of fecundity–longevity relationships in adult insects can be altered and even reversed by changes in larval diet quality. By extension, larval diet differences may represent a key mechanistic factor underpinning positive fecundity–longevity relationships observed in species such as eusocial insects. Keywords: Aging, Eusociality, Life history, mRNA-seq, Nutrition
The standard evolutionary theory of aging predicts that, as individuals grow older, selection for increased survivorship declines with age (1). Therefore, individuals experience the age-related decrease in performance and survivorship that defines aging (senescence) (2). Additionally, given finite resources, individuals should optimize relative investment between reproduction and somatic maintenance (3). This causes tradeoffs between reproduction and longevity (4,5) with elevated reproduction often incurring costs to longevity (the costs of reproduction) (6). Such trade-offs and costs are evident in the negative fecundity–longevity relationships observed in many species. Although a negative fecundity–longevity relationship is typical, fecundity and longevity can become uncoupled (7) and some species or populations may exhibit positive fecundity– longevity relationships (4). This can occur for several reasons. First, in Drosophila melanogaster, mutations can increase longevity without apparent reproductive costs (8–11), particularly mutations in the conserved insulin/insulin-like growth factor signaling and target of rapamycin network (IIS-TOR).
This network regulates nutrient sensitivity and is an important component of aging across diverse taxa (2,12). Second, fecundity and longevity can become uncoupled when there is asymmetric resourcing between individuals (13,14). Within a population, well-resourced individuals may have higher fecundity and longevity than poorly resourced individuals, reversing the usual negative fecundity–longevity relationship. However, because costs of reproduction are not abolished even in well-resourced individuals (13,14), a within-individual trade-off between fecundity and longevity remains present. Third, fecundity and longevity can become uncoupled within and between the castes of eusocial insects (15–18), that is, species such as ants, bees, wasps, and termites with a longlived reproductive caste (queens or kings) and a short-lived non- or less reproductive caste (workers) (19–21). In some species, queens appear to have escaped costs of reproduction completely (22–25). This may have been achieved through rewiring the IIS-TOR network (12,26), which forms part of the TOR/IIS-juvenile hormone-lifespan and fecundity (TI-JLiFe) network hypothesized to underpin aging and longevity in eusocial insects by Korb et al....
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Genetics of human longevi
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Genetics of human longevity
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Abstract. Smulders L, Deelen J. Genetics of human Abstract. Smulders L, Deelen J. Genetics of human longevity: From variants to genes to pathways. J Intern Med. 2024;295:416–35.
The current increase in lifespan without an equivalent increase in healthspan poses a grave challenge to the healthcare system and a severe burden on society. However, some individuals seem to be able to live a long and healthy life without the occurrence of major debilitating chronic diseases, and part of this trait seems to be hidden in their genome. In this review, we discuss the findings from studies on the genetic component of human longevity and the main challenges accompanying these studies. We subsequently focus on results from genetic studies in model organismsandcomparativegenomicapproachesto highlight the most important conserved longevity
associated pathways. By combining the results from studies using these different approaches, we conclude that only five main pathways have been consistently linked to longevity, namely (1) insulin/insulin-like growth factor 1 signalling, (2) DNA-damage response and repair, (3) immune function, (4) cholesterol metabolism and (5) telomere maintenance. As our current approaches to study the relevance of these pathways in humans are limited, we suggest that future studies on the genetics of human longevity should focus on the identification and functional characterization of rare genetic variants in genes involved in these pathways.
Keywords: genetics, longevity, longevity-associated pathways, rare genetic variants, functional characterization...
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A mathematical model
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A mathematical model to estimate the seasonal
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Yasuhiro Yamada1,3, Toshiro Yamada 2,4 & Kazu Yasuhiro Yamada1,3, Toshiro Yamada 2,4 & Kazuko Yamada2,4
The longevity of a honeybee colony is far more significant than the lifespan of an individual honeybee, a social insect. the longevity of a honeybee colony is integral to the fate of the colony. We have proposed a new mathematical model to estimate the apparent longevity defined in the upper limit of an integral equation. the apparent longevity can be determined only from the numbers of adult bees and capped brood. By applying the mathematical model to a honeybee colony in Japan, seasonal changes in apparent longevity were estimated in three long-term field experiments. Three apparent longevities showed very similar season-changes to one another, increasing from early autumn, reaching a maximum at the end of overwintering and falling approximately plumb down after overwintering. The influence of measurement errors in the numbers of adult bees and capped brood on the apparent longevity was investigated.
A lifespan of an animal, which is the period of time while an individual is alive, is an important index to evaluate individual activities. In the colony composed of eusocial insects such as honeybees (Apis mellifera) which exhibit age-polyethism, the lifespan of each individual cannot always give an assessment as to the activities of a colony but the longevity of colony could give it more appropriately. The longevity of a colony will have greater significance than the lifespan of each individual of the colony. The life of colony diversely depends on the inborn lifespan of an individual, the labor division distribution ratio of each honeybee performing a particular duty, the natural environment such as the weather, the amount of food, pests and pathogens, the environmental pollution due to pesticides and so on. The honeybee length of life has been observed or estimated before in the four seasons, which have a distinct bimodal distribution in temperature zones. According to previous papers, honeybees live for 2–4 weeks1 and 30–40 days2 in spring, for 1–2 weeks1, 25–30 days2 and 15–38 days3 in summer, for 2–4 weeks1 and 50–60 days2 in autumn, and for 150–200 days3, 253 days2, 270 days4, 304 days5 6–8 months6 and 150–200 days3 in winter, where it has been estimated that the difference of life length among seasons may come from the brood-rearing load imposed on honeybees1 and may mainly come from foraging and brood-rearing activity2. Incidentally, the lifetime of the queen seems to be three to four years (maximum observed nine years). The average length of life of worker bees in laboratory cages was observed to range from 30.5 to 45.5 days7. The study on the influence of altitude on the lifespan of the honeybee has found that the lifespans are 138 days at an altitude of 970 m and 73 days at an altitude of 200 m, respectively8. Many papers have discussed what factors affect the length of life (lifespan, longevity, life expectancy) on a honeybee colony as follows: Proper nutrition may increase the length of life in a honeybee colony. Honeybees taking beebread or diets with date palm pollen (the best source for hypopharyngeal gland development) showed the longest fifty percent lethal time (LT50)9. The examination for the effect of various fat proteins on honeybee longevity have shown that honeybees fed diets of red gum pollen have the longest lifespan but those fed invert sugar have the shortest lifespan10. In the discussion on nutrition-related risks to honey bee colonies such as starvation, monoculture, genetically modified crops and pesticides in pollen and sugar, protein nutrient strongly affects brood production and larval starvation (alone and or in combination with other stresses) can weaken colonies11. And protein content in
1Department of Applied Physics, Graduate School of Engineering, University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo, 113-8656, Japan. 2Graduate School of Natural Science & Technology, Kanazawa University, Kakuma-machi, Kanazawa, 920-1192, Japan. 3Present address: Department of Physics, Osaka University, 1-1 Machikaneyama, Toyonaka, Osaka, 560-0043, Japan. 4Present address: 2-10-15, Teraji, Kanazawa, Ishikawa, 921-8178, Japan. correspondence and requests for materials should be addressed to t.Y. (email: yamatoshikazu0501@yahoo.co.jp)
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jybvxsag-3546
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xevyo
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/home/sid/tuning/finetune/backend/output/xevyo-bas /home/sid/tuning/finetune/backend/output/xevyo-base-v1/merged_fp16_hf...
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Health Status and Empiric
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Health Status and Empirical Model of Longevity
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This research paper by Hugo Benítez-Silva and Huan This research paper by Hugo Benítez-Silva and Huan Ni develops one of the most detailed and rigorous empirical models explaining how health status and health changes shape people’s expectations of how long they will live. It uses panel data from the U.S. Health and Retirement Study (HRS), a large longitudinal survey of older adults.
🌟 Core Purpose of the Study
The paper investigates:
How do different measures of health—especially changes in health—affect people’s expected longevity (their subjective probability of living to age 75)?
It challenges the common assumption that simply using “current health status” or lagged health is enough to measure health dynamics. Instead, the authors argue that:
➡ Self-reported health changes (e.g., “much worse,” “better”)
are more accurate and meaningful than
➡ Computed health changes (differences between two reported health statuses).
📌 Key Concepts
1. Health Dynamics Matter
Health is not static—people experience:
gradual aging
chronic disease progression
sudden health shocks
effects of lifestyle and medical interventions
These dynamic elements shape how people assess their future survival.
Health Status and Empirical Mod…
2. Why Self-Reported Health Status Is Imperfect
The paper identifies three major problems with simply using self-rated health categories:
Health Status and Empirical Mod…
a. Cut-point shifts
People’s interpretation of “good” or “very good” health can change over time.
b. Gray areas
Some individuals cannot clearly categorize their health, leading to arbitrary reports.
c. Peer/reference effects
People compare themselves with different reference groups as they age.
These issues mean self-rated health alone doesn’t capture true health changes.
📌 3. Two Measures of Health Change
The authors compare:
A. Self-Reported Health Change (Preferred)
Direct question:
“Compared to last time, is your health better, same, worse?”
Advantages:
captures subtle changes
less affected by shifting cut-points
aligns more closely with subjective survival expectations
B. Computed Health Change (Problematic)
This is calculated mathematically as:
Health score (t+1) − Health score (t)
Problems:
inconsistent with self-reports in 38% of cases
loses information when health changes but does not cross a discrete category
introduces potential measurement error
Health Status and Empirical Mod…
🧠 Why This Matters
Expected longevity influences:
savings behavior
retirement timing
annuity purchases
life insurance decisions
health care usage
Health Status and Empirical Mod…
If researchers use bad measures of health, they may misinterpret how people plan for the future.
📊 Data and Methodology
Uses six waves of the HRS (1992–2003)
Sample: 9,000+ individuals, 24,000+ observations
Controls for:
chronic conditions (heart disease, cancer, diabetes)
ADLs/IADLs
socioeconomic variables
parental longevity
demographic factors
unobserved heterogeneity
Health Status and Empirical Mod…
The model is treated like a production function of longevity, following economic theories of health investment under uncertainty.
📈 Major Findings
✔ 1. Self-reported health changes strongly predict expected longevity
People who report worsening health show large drops in survival expectations.
Health Status and Empirical Mod…
✔ 2. Computed health changes frequently misrepresent true health dynamics
38% are inconsistent
15% lose meaningful health-change information
Health Status and Empirical Mod…
✔ 3. Self-reported changes have effects similar in magnitude to current health levels
This means:
Health trajectory matters as much as current health.
Health Status and Empirical Mod…
✔ 4. Health change measures are crucial for accurate modeling
Failing to include dynamic health measures causes:
biased estimates
misinterpretation of longevity expectations
🏁 Conclusion
This paper makes a major contribution by demonstrating that:
To understand how people form expectations about their own longevity, you must measure health as a dynamic process—not just a static snapshot.
The authors recommend that future empirical models, especially those using large panel surveys like the HRS, should:
✔ prioritize self-reported health changes
✔ treat computed changes with caution
✔ incorporate dynamics of health in survival models
These insights improve research in aging, retirement economics, health policy, and behavioral modeling.
Health Status and Empirical Mod…
If you want, I can also create:
📌 A diagram/flowchart of the model
📌 A one-paragraph brief summary
📌 A bullet-point version
📌 A presentation slide style explanation
Just tell me!...
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fnakzpii-4028
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xevyo
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/home/sid/tuning/finetune/backend/output/xevyo-bas /home/sid/tuning/finetune/backend/output/xevyo-base-v1/merged_fp16_hf...
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Global and National
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Global and National Declines in Life
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Period life expectancy at birth [life expecta
Period life expectancy at birth [life expectancy thereafter] is the most-frequently used indicator
of mortality conditions. More broadly, life expectancy is commonly taken as a marker of human
progress, for instance in aggregate indices such as the Human Development Index (United
Nations Development Programme 2020). The United Nations (UN) regularly updates and makes
available life expectancy estimates for every country, various country aggregates and the world
for every year since 1950 (Gerland, Raftery, Ševčíková et al. 2014), providing a 70-year
benchmark for assessing the direction and magnitude of mortality changes....
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{"input_type": "file", "source {"input_type": "file", "source": "/home/sid/tuning/finetune/backend/output/fnakzpii-4028/data/document.pdf", "num_examples": 36, "bad_lines": 0}...
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oaedizhh-8535
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xevyo
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/home/sid/tuning/finetune/backend/output/xevyo-bas /home/sid/tuning/finetune/backend/output/xevyo-base-v1/merged_fp16_hf...
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Global and National
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Global and National Declines in Life
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xevyo-base-v1
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Period life expectancy at birth [life expecta
Period life expectancy at birth [life expectancy thereafter] is the most-frequently used indicator
of mortality conditions. More broadly, life expectancy is commonly taken as a marker of human
progress, for instance in aggregate indices such as the Human Development Index (United
Nations Development Programme 2020). The United Nations (UN) regularly updates and makes
available life expectancy estimates for every country, various country aggregates and the world
for every year since 1950 (Gerland, Raftery, Ševčíková et al. 2014), providing a 70-year
benchmark for assessing the direction and magnitude of mortality changes....
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{"input_type": "file", "source {"input_type": "file", "source": "/home/sid/tuning/finetune/backend/output/oaedizhh-8535/data/document.pdf", "num_examples": 6, "bad_lines": 0}...
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fioqwmlo-9810
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xevyo
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/home/sid/tuning/finetune/backend/output/xevyo-bas /home/sid/tuning/finetune/backend/output/xevyo-base-v1/merged_fp16_hf...
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Grandmothers
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Grandmothers and the Evolution of Human Longevity
Grandmothers and the Evolution of Human Longevity
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“Grandmothers and the Evolution of Human Longevity “Grandmothers and the Evolution of Human Longevity”**
This PDF is a scholarly research article that presents and explains the Grandmother Hypothesis—one of the most influential evolutionary theories for why humans live so long after reproduction. The paper argues that human longevity evolved largely because ancestral grandmothers played a crucial role in helping raise their grandchildren, thereby increasing family survival and passing on genes that favored longer life.
The article combines anthropology, evolutionary biology, and demographic modeling to show that grandmothering behavior dramatically enhanced reproductive success and survival in early human societies, creating evolutionary pressure for extended lifespan.
👵 1. Core Idea: The Grandmother Hypothesis
The central argument is:
Human females live long past menopause because grandmothers helped feed, protect, and support their grandchildren, allowing mothers to reproduce more frequently.
This cooperative childcare increased survival rates and promoted the evolution of long life, especially among women.
Healthy Ageing
🧬 2. Evolutionary Background
The article explains key evolutionary facts:
Humans are unique among primates because females experience decades of post-reproductive life.
In other great apes, females rarely outlive their fertility.
Human children are unusually dependent for many years; mothers benefit greatly from help.
Grandmothers filled this gap, making longevity advantageous in evolutionary terms.
Healthy Ageing
🍂 3. Why Grandmothers Increased Survival
The study shows how ancestral grandmothers:
⭐ Provided extra food
Especially gathered foods like tubers and plant resources.
⭐ Allowed mothers to wean earlier
Mothers could have more babies sooner, increasing reproductive success.
⭐ Improved child survival
Grandmother assistance reduced infant and child mortality.
⭐ Increased group resilience
More caregivers meant better protection and food access.
These survival advantages favored genes that supported prolonged life.
Healthy Ageing
📊 4. Mathematical & Demographic Modeling
The PDF includes modeling to demonstrate:
How grandmother involvement changes fertility patterns
How increased juvenile survival leads to higher population growth
How longevity becomes advantageous over generations
Models show that adding grandmother support significantly increases life expectancy in evolutionary simulations.
Healthy Ageing
👶 5. Human Childhood and Weaning
Human children:
Develop slowly
Need long-term nutritional and social support
Rely on help beyond their mother
Early weaning—made possible by grandmother help—creates shorter birth intervals, boosting the reproductive output of mothers and promoting genetic selection for long-lived helpers (grandmothers).
Healthy Ageing
🧠 6. Implications for Human Evolution
The article argues that grandmothering helped shape:
✔ Human social structure
Cooperative families and multigenerational groups.
✔ Human biology
Long lifespan, menopause, slower childhood development.
✔ Human culture
Shared caregiving, food-sharing traditions, teaching, and cooperation.
Healthy Ageing
Grandmothers became essential to early human success.
🧓 7. Menopause and Post-Reproductive Lifespan
One major question in evolution is: Why does menopause exist?
The article explains that:
Natural selection usually favors continued reproduction.
But in humans, the benefits of supporting grandchildren outweigh late-life reproduction.
This shift created evolutionary support for long post-reproductive life.
Healthy Ageing
⭐ Overall Summary
This PDF provides a clear and compelling explanation of how grandmothering behavior shaped human evolution, helping produce our unusually long life spans. It argues that grandmothers increased survival, supported early weaning, and boosted reproduction in early humans, leading natural selection to favor individuals—especially females—who lived well past their reproductive years. The article blends anthropology, biology, and mathematical modeling to show that the evolution of human longevity is inseparable from the evolutionary importance of grandmothers....
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7b2a2799-a74e-4dd4-93a8-4bbabe61ca47
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8684964a-bab1-4235-93a8-5fd5e24a1d0a
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vtciomis-0967
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xevyo
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/home/sid/tuning/finetune/backend/output/xevyo-bas /home/sid/tuning/finetune/backend/output/xevyo-base-v1/merged_fp16_hf...
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Diet-dependent entropic a
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Diet-dependent entropic assessment of athletes’
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Cennet Yildiz1, Melek Ece Öngel2 , Bayram Yilmaz3 Cennet Yildiz1, Melek Ece Öngel2 , Bayram Yilmaz3 and Mustafa Özilgen1* 1Department of Food Engineering, Yeditepe University, Kayısdagi, Atasehir, Istanbul 34755, Turkey 2Nutrition and Dietetics Department, Yeditepe University, Kayısdagi, Atasehir, Istanbul 34755, Turkey 3Faculty of Medicine, Department of Physiology, Yeditepe University, Istanbul, Turkey
(Received 29 July 2021 – Final revision received 26 August 2021 – Accepted 26 August 2021)
Journal of Nutritional Science (2021), vol. 10, e83, page 1 of 8 doi:10.1017/jns.2021.78
Abstract Life expectancies of the athletes depend on the sports they are doing. The entropic age concept, which was found successful in the previous nutrition studies, will be employed to assess the relation between the athletes’ longevity and nutrition. Depending on their caloric needs, diets are designed for each group of athletes based on the most recent guidelines while they are pursuing their careers and for the post-retirement period, and then the metabolic entropy generation was worked out for each group. Their expected lifespans, based on attaining the lifespan entropy limit, were calculated. Thermodynamic assessment appeared to be in agreement with the observations. There may be a significant improvement in the athletes’ longevity if theyshift to a retirement diet after the age of 50. The expected average longevity for male athletes was 56 years for cyclists, 66 years for weightlifters, 75 years for rugby players and 92 years for golfers. If they should start consuming the retirement diet after 50 years of age, the longevity of the cyclists may increase for 7 years, and those of weightlifters, rugby players and golfers may increase for 22, 30 and 8 years, respectively.
Key words: Athletes’ diet: Athletes’ longevity: Entropic age: Lifespan entropy
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lgpknhne-0430
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xevyo
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Analysis of trends
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Analysis of trends in human longevity by new model
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Byung Mook Weon
LG.Philips Displays, 184, Gongda Byung Mook Weon
LG.Philips Displays, 184, Gongdan1-dong, Gumi-city, GyungBuk, 730-702, South Korea
Abstract
Trends in human longevity are puzzling, especially when considering the limits of
human longevity. Partially, the conflicting assertions are based upon demographic
evidence and the interpretation of survival and mortality curves using the Gompertz
model and the Weibull model; these models are sometimes considered to be incomplete
in describing the entire curves. In this paper a new model is proposed to take the place
of the traditional models. We directly analysed the rectangularity (the parts of the curves
being shaped like a rectangle) of survival curves for 17 countries and for 1876-2001 in
Switzerland (it being one of the longest-lived countries) with a new model. This model
is derived from the Weibull survival function and is simply described by two parameters,
in which the shape parameter indicates ‘rectangularity’ and characteristic life indicates
the duration for survival to be ‘exp(-1) % 79.3 6≈ ’. The shape parameter is essentially a
function of age and it distinguishes humans from technical devices. We find that
although characteristic life has increased up to the present time, the slope of the shape
parameter for middle age has been saturated in recent decades and that the
rectangularity above characteristic life has been suppressed, suggesting there are
ultimate limits to human longevity. The new model and subsequent findings will
contribute greatly to the interpretation and comprehension of our knowledge on the
human ageing processes.
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qglgsrnv-4016
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xevyo
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/home/sid/tuning/finetune/backend/output/xevyo-bas /home/sid/tuning/finetune/backend/output/xevyo-base-v1/merged_fp16_hf...
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American Longevity:
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American Longevity: Past, Present, and Future
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Samuel Preston is Frederick J. Warren Professor of Samuel Preston is Frederick J. Warren Professor of Demography at the University of Pennsylvania and Director of its Population Studies Center. A 1968 Ph.D. in Economics from Princeton University, he has also been a faculty member at the University of California, Berkeley, and the Universi ty of Washington. He is past president of the Population Association of America and is a member of the National Academy of Sciences, where he chaired the Committee on Population.
The Policy Brief series is a collection of essays on current public policy issues in aging, health, income security, metropolitan studies and related research done by or on behalf of the Center for Policy Research at the Maxwell School of Citizenship and Public Affairs.
Single copies of this publication may be obtained at no cost from the Center for Policy Research, Maxwell School, 426 Eggers Hall, Syracuse, NY 13244-1090.
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AFAR American aging research
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Researchers believe that your longevity, that is, Researchers believe that your longevity, that is, the duration of your life, may rely on your having longevity assurance genes. Genes are the bits of DNA that determine an organism’s physical characteristics and drive a whole range of physiological processes. Longevity assurance genes are variations (called alleles) of certain genes that may allow you to live longer (and perhaps more healthily) than other people who inherit other versions of that gene.
WHY ARE LONGEVITY ASSURANCE GENES IMPORTANT?
If scientists could identify longevity genes in humans, in theory, they might also be able to develop ways to manipulate those genes to enable people to live much longer than they do today. Slowing the
aging process would also likely delay the appearance of agerelated diseases such as cancer, diabetes, and Alzheimer’s disease and therefore make people
healthier as well.
Most longevity assurance genes that have already been identified in lower organisms such as yeast, worms, and fruit flies act to increase lifespan and grant resistance to harmful environmental stress. For example, scientists have identified single gene variantions in roundworms that can extend lifespans by 40 to 100 percent. These genes also allow worms to withstand often fatal temperature extremes, excessive levels of toxic free radicals (cellular waste products), or damage due to ultraviolet light.
Some of the longevity assurance genes in lower organisms have similar counterparts among human or mammalian genes, which scientists are now studying. While researchers have not yet found genes that predispose us to greater longevity, some have identified single human gene variants that seem to have a protective effect against certain age-related diseases and are associated with long life. For example, inheriting one version of a gene for a particular protein called apolipoprotein E (Apo E) may decrease a
person’s risk of developing heart
disease and Alzheimer’s disease.
Identification of genes that prevent or delay crippling diseases at old age may help us find novel strategies for assuring a healthier, longer life, and enhancing the quality of life in the elderly.
Researchers believe that your longevity may rely on your having longevity assurance genes.
Infoaging Guide to Longevity | 3
HOW MUCH OF LONGEVITY IS GENETICALLY DETERMINED?
By some estimates, we humans have about 25,000 genes. But only a small fraction of those affect the length of our lives. It is hard to imagine that so few genes can be responsible for such a complex phenomenon as longevity. In looking at personality, psychologists ask how much is nature, that is, inherited, and how much is nurture, which means resulting from external influences. Similar questions exist about the heritability of lifespan. In other words, just how much of longevity is
genetically determined and how much it is mediated by external influences, such as smoking, diet, lifestyle, stress, and occupational exposures?
Studies do show that long-lived parents have long-lived children. Studies of adoptees confirm that their expected lifespans correlate more strongly to those of their birth parents than those of their adoptive parents. One study of twins reared apart suggests about a 30 percent role for heredity in lifespan, while another says the influence is even smaller.
Some scientists estimate the maximal lifespan of a human to be approximately 120 years, a full 50 years longer than the Biblical three score and ten (Psalms 90:10). The people who have actually achieved that maximum can be counted on one hand—or one finger. Mme. Jeanne Calment of France was 122 years old at her death in 1997. But although few challengers to her record exist, we are seeing more and more members of our society reach 100. In fact, in the United States today, there are more than 60,000 centenarians, and their ranks are projected to grow to nearly 1 million
by 2050. Much of this growth will be due to the convergence of the large aging Boomer demographic and improvements in health and medicine.
Most people who get to 100 do so by avoidance. They shun tobacco and excess alcohol, the sun and pollutants, sloth, bad diets, anger, and isolation. Still, many of us may know at least one smoking, drinking, sunburnt, lazy,
cantankerous recluse who has lived to 100—and wondered how he or she did it.
More and more, scientists are finding that part of the explanation lies in our genes. The siblings of centenarians have a four times greater probability of surviving to age 90 than do siblings of people who have an average life expectancy. When it comes to living 100 years, the probability is 17 times greater in male siblings of centenarians and eight times greater in female siblings of centenarians than the average lifespan of their birth cohort.
On the flip side, we humans carry a number of genes that are deleterious to our health and longevity. These genes increase our risk for heart disease and cancer, as well as age-related but harmless symptoms such as gray hair and wrinkles. Though we cannot change our genetic pedigrees, perhaps if we know what unhelpful genes we carry, we can take steps, such as ridding ourselves of bad health habits and adopting good ones, that can overcome the disadvantages our genes confer and live as long as those people with good genes.
WHAT WE HAVE LEARNED FROM LOWER ORGANISMS
Our understanding of genes and aging has exploded in recent years, due in large part to groundbreaking work done in simpler
organisms. By studying the effect of genetic modification on lifespan in laboratory organisms, researchers now provide fundamental insights into basic mechanisms of aging.
These include:
• Yeast
• Worms
• Fruit Flies
• Mice
Yeast Researchers have identified more than 100 genes in baker’s yeast (Saccharomyces cerevisiae) that are associated with increased longevity, and even more provocatively, have found human versions of many of these genes. Further study is ongoing.
As with all other organisms tested, researchers have reported that restricting the amount of calories available to yeast, either through reducing the sugar or amino acid content of the culture medium, can increase lifespan. Caloric
restriction does not extend lifespan in yeast strains lacking one of the longevity assurance genes, SIR2. This result has been shown in multiple organisms from yeast to flies, and even in mice. The SIR2 protein is the founding member of the sirtuin family involved in
genomic stability, metabolism, stress resistance, and aging. Researchers have found that
overexpression of Sir2 extends lifespan, ...
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Determinants of longevity
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Determinants of longevity
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K. CHRISTENSENa & J. W. VAUPELb From abOdense K. CHRISTENSENa & J. W. VAUPELb From abOdense University Medical School, Odense, Denmark; bSanford Institute, Duke University, Durham, NC, USA; and aThe Danish Epidemiology Science Centre, The Steno Institute of Public Health, Department of Epidemiology and Social Medicine, Aarhus University Hospital, Aarhus, Denmark
Abstract. Christensen K, Vaupel JW (Odense University Medical School, Odense, Denmark; Sanford Institute, Duke University, Durham, NC, USA; and The Danish Epidemiology Science Centre, The Steno Institute of Public Health, Department of Epidemiology and Social Medicine, Aarhus University Hospital, Aarhus, Denmark). Determinants of longevity: genetic, environmental and medical factors (Review). J Intern Med 1996; 240: 333–41.
This review focuses on the determinants of longevity in the industrialized world, with emphasis on results from recently established data bases. Strong evidence is now available that demonstrates that in developed
Introduction
The determinants of longevity might be expected to be well understood. The duration of life has captured the attention of many people for thousands of years; an enormous array of vital-statistics data are available for many centuries. Life-span is easily measured compared with other health phenomena, and in many countries data are available on whole populations and not just study samples. Knowledge concerning determinants of human longevity, however, is still sparse, and much of the little that is known has been learned in recent years. This review
countries the maximum lifespan as well as the mean lifespan have increased substantially over the past century. There is no evidence of a genetically determined lifespan of around 85 years. On the contrary, the biggest absolute improvement in survival in recent decades has occurred amongst 80 year-olds. Approximately one-quarter of the variation in lifespan in developed countries can be attributed to genetic factors. The influence of both genetic and environmental factors on longevity can potentially be modified by medical treatment, behavioural changes and environmental improvements.
Keywords: centenarians, life expectancy, lifespan, mortality.
focuses on genetic, environmental and medical factors as determinants of longevity in developed countries and discusses alternative paradigms concerning human longevity.
How should longevity be measured?
Longevity can be studied in numerous ways; key questions include the following. How long can a human live? What is the average length of life? Are the maximum and average lengths of life approaching limits? Why do some individuals live longer than others? In addressing these questions, it is useful to
# 1996 Blackwell Science Ltd 333
334 K. CHRISTENSEN & J. W. VAUPEL
study the maximum lifespan actually achieved in various populations, the mean lifespan, and the variation in lifespan. Estimating the maximum lifespan of human beings is simply a matter of finding a well-documented case report of a person who lived longer than other welldocumented cases. The assessment of mean lifespan in an actual population requires that the study population is followed from birth to extinction. An alternative approach is to calculate age-specific death rates at some point in time for a population, and then use these death rates to determine how long people would live on average in a hypothetical population in which these death rates prevailed over the course of the people’s lives. This second kind of mean lifespan is generally known as life expectancy. The life expectancy of the Swedish population in 1996 is the average lifespan that would be achieved by the 1996 birth cohort if Swedish mortality rates at each age remained at 1996 levels for the entire future life of this cohort. Assessment of determinants of life expectancy and variation in lifespan amongst individuals rely on demographic comparisons of different populations and on such traditional epidemiological designs as follow-up studies of exposed or treated versus nonexposed or nontreated individuals. Designs from genetic epidemiology – such as twin, adoption and other family studies – are useful in estimating the relative importance of genes and environment for the variation in longevity.
Determinants of extreme longevity
Numerous extreme long-livers have been reported in various mountainous regions, including Georgia, Kashmir, and Vilcabamba. In most Western countries, including the Scandinavian countries, exceptional lifespans have also been reported. Examples are Drachenberg, a Danish–Norwegian sailor who died in 1772 and who claimed that he was born in 1626, and Jon Anderson, from Sweden, who claimed to be 147 years old when he died in 1729. There is noconvincingdocumentationfortheseextremelonglivers. When it has been possible to evaluate such reports, they have proven to be very improbable [1, 2]. In countries, like Denmark and Sweden, with a long tradition of censuses and vital statistics, remarkable and sudden declines in the number of
extreme long-livers occur with the introduction of more rigorous checking of information on age of death, as the result of laws requiring birth certificates, the development of church registers and the establishment of statistical bureaus [3, 4]. This suggests that early extreme long-livers were probably just cases of age exaggeration. Today (March 1996), the oldest reported welldocumented maximum lifespan for females is 121 years [5] and for males 113 years [6]. Both these persons are still alive. Analyses of reliable cases of long-livers show that longevity records have been repeatedly broken over past decades [3, 6]; this suggests that even longer human lifespans may occur in the future. There has been surprisingly little success in identifying factors associated with extreme longevity. A variety of centenarian studies have been conducted during the last half century. As reviewed by Segerberg [7], most of the earlier studies were based on highly selected samples of individuals, without rigorous validation of the ages of reputed centenarians. During the last decade several more comprehensive, less selected centenarian studies have been carried out in Hungary [8], France [9], Finland [10] and Denmark [11]. A few specific genetic factors have been found to be associated with extreme longevity. Takata et al. [12] found a significantly lower frequency of HLA-DRw9 amongst centenarians than in an adult control group in Japan, as well as a significantly higher frequency of HLA-DR1. The HLA-antigens amongst the Japanese centenarians are negatively associated with the presence of autoimmune diseases in the Japanese population, which suggests that the association with these genetic markers is mediated through a lower incidence of diseases. More recently, both a French study [13] and a Finnish study [14] found a low prevalence of the e4 allele of apolipoprotein E amongst centenarians. The e4 allele has consistently been shown to be a risk factor both for coronary heart disease and for Alzheimer’s dementia. In the French study [13], it was also found that centenarians had an increased prevalence of the DDgenotype of angiotensin-converting enzyme (ACE) compared with adult controls. This result is contrary to what was expected as the DD-genotype of ACE has been reported to be associated with myocardial infarction. Only a few genetic association studies concerning extreme longevity have been published...
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Inconvenient Truths About
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Inconvenient Truths About Human Longevity
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S. Jay Olshansky, PhD1,* and Bruce A. Carnes, PhD2 S. Jay Olshansky, PhD1,* and Bruce A. Carnes, PhD2
1University of Illinois at Chicago, Division of Epidemiology and Biostatistics. 2University of Oklahoma. *Address correspondence to: S. Jay Olshansky, PhD, University of Illinois at Chicago. E-mail: sjayo@uic.edu
Received: February 2, 2019; Editorial Decision Date: April 3, 2019
Decision Editor: Anne Newman, MD, MPH
Abstract The rise in human longevity is one of humanity’s crowning achievements. Although advances in public health beginning in the 19th century initiated the rise in life expectancy, recent gains have been achieved by reducing death rates at middle and older ages. A debate about the future course of life expectancy has been ongoing for the last quarter century. Some suggest that historical trends in longevity will continue and radical life extension is either visible on the near horizon or it has already arrived; whereas others suggest there are biologically based limits to duration of life, and those limits are being approached now. In “inconvenient truths about human longevity” we lay out the line of reasoning and evidence for why there are limits to human longevity; why predictions of radical life extension are unlikely to be forthcoming; why health extension should supplant life extension as the primary goal of medicine and public health; and why promoting advances in aging biology may allow humanity to break through biological barriers that influence both life span and health span, allowing for a welcome extension of the period of healthy life, a compression of morbidity, but only a marginal further increase in life expectancy.
Keywords: Longevity, Public Health, Life Expectancy....
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A Longevity Agenda
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A Longevity Agenda for Singapore
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Over the last 60 years, life expectancy in Singapo Over the last 60 years, life expectancy in Singapore has increased by nearly 20 years to reach 85 – one of the highest in the world. That’s an extraordinary achievement that is taken for granted and that too often leads to a conversation about the costs of an ageing society. Those costs and concerns are very real, but a deeper more fundamental set of questions need to be answered.
If we are living this much longer, then how do we – individuals, companies and governments – respond to make the most of this extra time? How do we restructure our lives to make sure that as many people as possible, live as long as possible, in as healthy and fulfilled ways as possible?
This note draws on the findings from a high-level conference, sponsored by Rockefeller Foundation and Prudential Singapore, to map out what a global longevity agenda looks like, and to raise awareness around the world – at a government, corporate and individual level – on how we need to seize the benefits of this wonderful human achievement of longer lives.
It also looks at the measures that Singapore has taken to adjust to longer lives. Reassuringly, Singapore leads the world along many dimensions that have to do with ageing, and also longevity. However, there is much that needs to be done. Framing policies around longevity and ‘all of life’ and not just ageing and ‘end of life’ is needed if Singapore is to collectively maximise the gains available.
A Longevity Agenda For Singapore I 2
Executive Summary
• Singapore is undergoing a rapid demographic transition which will see the average age of its society
increase as the proportion of its older citizens increases.
• An ageing society creates many challenges. However, at the same time, with the number of older
people increasing, Singapore is benefitting from a longevity dividend.
• On average, Singaporeans are living for longer and in better health. In other words, how we are
ageing is changing – it is not just about there being more senior people. Exploiting this opportunity
to seize these positive advantages is the longevity agenda.
• A new-born in Singapore today, faces the prospect of living on average one of the longest lives in
human history, and so needs to prepare for his or her future differently.
• At an individual level, Singaporeans are already behaving differently – in terms of marriage, families,
work and education. Many are acting as social pioneers as they try to create a new map of life.
• To support individuals as they adapt to longer lives, Singapore needs to create a new map of life
that enables as many people as possible to live as long as possible and as healthily and as fulfilled as
possible.
• Achieving this will also ensure that not only the individual, but also the economy will benefit.
• Singapore is at the international frontier of best practice in terms of adjusting to an ageing society. It
also leads the way with many longevity measures.
• Further entrenching social change and experimentation, and creating a positive narrative around
longer, healthier lives; in particular, extending policies away from a sole focus on the old and towards the whole course of life are some key priorities ahead of us. ...
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Gene Expression Biomarker
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Gene Expression Biomarkers and Longevity
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Chronological age, a count of how many orbits of t Chronological age, a count of how many orbits of the sun an individual has made as a passenger of planet earth, is a useful but limited proxy of aging processes. Some individuals die of age related diseases in their sixties, while others live to double that age. As a result, a great deal of effort has been put into identifying biomarkers that reflect the underlying biological changes involved in aging. These markers would provide insights into what processes were involved, provide measures of how much biological aging had occurred and provide an outcome measure for monitoring the effects of interventions to slow ageing processes. Our DNA sequence is the fixed reference template from which all our proteins are produced. With the sequencing of the human genome we now have an accurate reference library of gene sequences. The recent development of a new generation of high throughput array technology makes it relatively inexpensive to simultaneously measure a large number of base sequences in DNA (or RNA, the molecule of gene expression). In the last decade, array technologies have supported great progress in identifying common DNA sequence differences (SNPs) that confer risks for age related diseases, and similar approaches are being used to identify variants associated with exceptional longevity [1]. A striking feature of the findings is that the majority of common disease-associated variants are located not in the protein coding sequences of genes, but in regions of the genome that do not produce proteins. This indicates that they may be involved in the regulation of nearby genes, or in the processing of their messages. While DNA holds the static reference sequences for life, an elaborate regulatory system influences whether and in what abundance gene transcripts and proteins are produced. The relative abundance of each tran
script is a good guide to the demand for each protein product in cells (see section 2 below). Thus, by examining gene expression patterns or signatures associated with aging or age related traits we can peer into the underlying production processes at a fundamental level. This approach has already proved successful in clinical applications, for example using gene signatures to classify cancer subtypes [2]. In aging research, recent work conducted in the InCHIANTI cohort has identified gene-expression signatures in peripheral leucocytes linked to several aging phenotypes, including low muscle strength, cognitive impairment, and chronological age itself. In the sections that follow we provide a brief introduction to the underlying processes involved in gene expression, and summarize key work in laboratory models of aging. We then provide an overview of recent work in humans, thus far mostly from studies of circulating white cells.
2 Introducing gene expression
Since the early 1900s a huge worldwide research effort has lead to the discovery and widespread use of genetic science (see the NIH website [3] for a comprehensive review of the history of the subject, and a more detailed description of the transfer of genetic information). The human genome contains the information needed to create every protein used by cells. The information in the DNA is transcribed into an intermediate molecule known as the messenger RNA (mRNA), which is then translated into the sequence of aminoacids (proteins) which ultimately determine the structural and functional characteristics of cells, tissues and organisms (see figure 1 for a summary of the process). RNA is both an intermediate to proteins and a regulatory molecule; therefore the transcriptome (the RNA ∗Address correspondence to Prof. David Melzer, Epidemiology and Public Health Group, Medical School, University of Exeter, Exeter EX1 2LU, UK. E-mail: D.Melzer@exeter.ac.uk
1
2 INTRODUCING GENE EXPRESSION
Figure 1: Representation of the transcription and translation processes from DNA to RNA to Protein — DNA makes RNA makes Protein. This is the central dogma of molecular biology, and describes the transfer of information from DNA (made of four bases; Adenine, Guanine, Cytosine and Thymine) to RNA to Protein (made of up to 20 different amino acids). Machinery known as RNA polymerase carries out transcription, where a single strand of RNA is created that is complementary to the DNA (i.e. the sequence is the same, but inverted although in RNA thymine (T) is replaced by uracil (U)). Not all RNA molecules are messenger RNA (mRNA) molecules: RNA can have regulatory functions (e.g. micro RNAs), and or can be functional themselves, for example in translation transfer RNA (tRNA) molecules have an amino acid bound to one end (the individual components of proteins) and at the other bind to a specific sequence of RNA (a codon again, this is complementary to this original sequence) for instance in the figure a tRNA carrying methionine (Met) can bind to the sequence of RNA, and the ribosome (also in part made of RNA) attaches the amino acids together to form a protein.
production of a particular cell, or sample of cells, at a given time) is of particular interest in determining the underlying molecular mechanisms behind specific traits and phenotypes. Genes are also regulated at the posttranscriptional level, by non-coding RNAs or by posttranslational modifications to the encoded proteins. Transcription is a responsive process (many factors regulate transcription and translation in response to specific intra and extra-cellular signals), and thus the amount of RNA produced varies over time and between cell types and tissues. In addition to the gene and RNA transcript sequences that will determine the final protein sequence (so called exons) there are also intervening sections (the introns) that are removed by a process known as mRNA splicing. While it was once assumed that each gene produced only one protein, it is now
clear that up to 90% of our genes can produce different versions of their protein through varying the number of exons included in the protein, a process called alternative splicing. Alteration in the functional properties of the protein can be introduced by varying which exons are included in the transcript, giving rise to different isoforms of the same gene. Many RNA regulatory factors govern this process, and variations to the DNA sequence can affect the binding of these factors (which can be thousands of base pairs from the gene itself) and alter when, where and for how long a particular transcript is produced. The amount of mRNA produced for a protein is not necessarily directly related to the amount of protein produced or present, as other regulatory processes are involved. The amount of mRNA is broadly indicative of...
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ofksvfmq-2726
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xevyo
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Life Expectancy
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Life Expectancy and Economic Growth
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Life expectancy does not affect all countries the Life expectancy does not affect all countries the same way.
Its impact depends on whether a country is before or after the demographic transition.
The demographic transition is the historical shift from:
High mortality & high fertility → Low mortality & low fertility
This shift completely changes how population, education, and income respond to improved life expectancy.
🧠 CORE IDEA (The Big Discovery)
Life expectancy can both increase and decrease economic growth — depending on the stage of development.
⭐ Before the demographic transition (pre-transitional countries):
Lower mortality → population grows faster
Fertility remains high
Little investment in education
Result: Population growth reduces per-capita income
📉 Life expectancy hurts economic growth in early-stage countries
Life Expectancy and Economic Gr…
⭐ After the demographic transition (post-transitional countries):
Lower mortality → population growth slows down
Families invest more in education (human capital rises)
Economic productivity increases
Result: Per-capita income grows faster
📈 Life expectancy boosts economic growth in advanced-stage countries
Life Expectancy and Economic Gr…
🔥 Ultimate Insight
Improving life expectancy is actually a trigger for the demographic transition itself.
This means:
When life expectancy becomes high enough, a country begins shifting from high fertility to low fertility.
This shift is what unlocks sustained long-run economic growth.
📌 The paper finds strong evidence:
Higher life expectancy significantly increases the probability of undergoing the demographic transition.
Life Expectancy and Economic Gr…
📊 How It Works – Mechanism Explained
1. Pre-Transition Phase (Low Development)
Mortality falls, people live longer
But fertility stays high → population explodes
More people sharing limited land/capital → income per capita drops
Education gains are small
Life Expectancy and Economic Gr…
2. Transition Phase (Around 1970 for many countries)
Fertility begins to fall
Population growth slows
Human capital investment begins to rise
Life Expectancy and Economic Gr…
3. Post-Transition Phase (High Development)
Longer lives → people invest more in education
Human capital grows
Smaller families → more resources per child
Income per capita increases strongly
Life Expectancy and Economic Gr…
🔍 Evidence From the Paper
Based on data from 47 countries (1940–2000):
✔ In pre-transitional countries:
Life expectancy increase → higher population, lower income per capita
Life Expectancy and Economic Gr…
✔ In post-transitional countries:
Life expectancy increase → lower population growth, higher income per capita, higher education levels
Life Expectancy and Economic Gr…
✔ By 2000:
Life expectancy had strong positive effects on schooling in all countries
Life Expectancy and Economic Gr…
🧩 Why Earlier Research Was Conflicting
Previous studies found:
Sometimes life expectancy increases GDP
Sometimes it decreases it
This paper explains why:
👉 The effect depends on whether the country has undergone the demographic transition.
If you mix pre- and post-transition countries, the results get confused.
Life Expectancy and Economic Gr…
🏁 Perfect One-Sentence Summary
Improvements in life expectancy can slow economic growth in early-stage countries by accelerating population growth but strongly boost growth in advanced countries by reducing fertility, raising education, and triggering the demographic transition....
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Genetics of extreme human
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Genetics of extreme human longevity to guide drug
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Zhengdong D. Zhang 1 ✉, Sofiya Milman1,2, Jhih-R Zhengdong D. Zhang 1 ✉, Sofiya Milman1,2, Jhih-Rong Lin1, Shayne Wierbowski3, Haiyuan Yu3, Nir Barzilai1,2, Vera Gorbunova4, Warren C. Ladiges5, Laura J. Niedernhofer6, Yousin Suh 1,7, Paul D. Robbins 6 and Jan Vijg1,8
Ageing is the greatest risk factor for most common chronic human diseases, and it therefore is a logical target for developing interventions to prevent, mitigate or reverse multiple age-related morbidities. Over the past two decades, genetic and pharmacologic interventions targeting conserved pathways of growth and metabolism have consistently led to substantial extension of the lifespan and healthspan in model organisms as diverse as nematodes, flies and mice. Recent genetic analysis of long-lived individuals is revealing common and rare variants enriched in these same conserved pathways that significantly correlate with longevity. In this Perspective, we summarize recent insights into the genetics of extreme human longevity and propose the use of this rare phenotype to identify genetic variants as molecular targets for gaining insight into the physiology of healthy ageing and the development of new therapies to extend the human healthspan...
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dvrazzun-9083
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/home/sid/tuning/finetune/backend/output/xevyo-bas /home/sid/tuning/finetune/backend/output/xevyo-base-v1/merged_fp16_hf...
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From Life Span to Health
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From Life Span to Health Span: Declaring “Victory”
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S. Jay Olshansky
School of Public Health, Univers S. Jay Olshansky
School of Public Health, University of Illinois at Chicago, Chicago, Illinois 60612, USA Correspondence: sjayo@uic.edu
Adifficultdilemmahaspresenteditselfinthecurrentera.Modernmedicineandadvancesin the medical sciences are tightly focused on a quest to find ways to extend life—without considering either the consequences of success or the best way to pursue it. From the perspectiveofphysicianstreatingtheirpatients,itmakessensetohelpthemovercomeimmediate healthchallenges,butfurtherlifeextensioninincreasinglymoreagedbodieswillexposethe savedpopulationtoanelevatedriskofevenmoredisablinghealthconditionsassociatedwith aging. Extended survival brought forth by innovations designed to treat diseases will likely push more people into a“ red zone”a later phase in life when the risk of frailty and disability risesexponentially.Theinescapableconclusionfromtheseobservationsisthatlifeextension should no longer be the primary goal of medicine when applied to long-lived populations. The principal outcome and most important metric of success should be the extension of health span, and the technological advances described herein that are most likely to make the extension of healthy life possible.
ON THE ORIGIN OF LIFE SPAN How long people live as individuals, the expected duration of life of people of any age base do current death rates in a national population, and the demographic aging of national populations (e.g., proportion of the population aged 65 and older), are simple metrics that are colloquially understood as reflective of health and longevity. Someone that lives for 100 years had a lifespan of a century ,and a life expectancy at birth of 80 years for men in the United States means that male babies born today will live to an average of 80 years if death rates at all ages today prevail throughout the life of the cohort. When life expectancy rises or declines, that is inter pretend
as an improvement or worsening of public health. These demographic and statistical metrics are reflective measurement tools only—they disclose little about why they change or vary, they reveal nothing about why they exist at all, and theyare indirect and imprecise measures of the health of a population. Understandingwhythereisaspecies-specific life span to begin with and what forces influence its presence ,level ,and the dynamics of variation and change (collectively referred to her “life span determination”) is critical to comprehending why the topic
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599ab3a3-c70a-4ba3-aec0-5660dee3f783
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jofodeku-7336
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xevyo
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/home/sid/tuning/finetune/backend/output/xevyo-bas /home/sid/tuning/finetune/backend/output/xevyo-base-v1/merged_fp16_hf...
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Exploring Human Longevity
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Exploring Human Longevity
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Riya Kewalani, Insiya Sajjad Hussain Saifudeen Du Riya Kewalani, Insiya Sajjad Hussain Saifudeen Dubai Gem Private School, Oud Metha Road, Dubai, PO Box 989, United Arab Emirates; riya.insiya@gmail.com
ABSTRACT: This research aims to investigate whether climate has an impact on life expectancy. In analyzing economic data from 172 countries that are publicly available from the United Nations World Economic Situation and Prospects 2019, as well as classifying all countries from different regions into hot or cold climate categories, the authors were able to single out income, education, sanitation, healthcare, ethnicity, and diet as constant factors to objectively quantify life expectancy. By measuring life expectancies as indicated by the climate, a comprehensible correlation can be built of whether the climate plays a vital role in prolonging human life expectancy and which type of climate would best support human life. Information gathered and analyzed from examination focused on the contention that human life expectancy can be increased living in colder regions. According to the research, an individual is likely to live an extra 2.2163 years in colder regions solely based on the country’s income status and climate, while completely ruling out genetics. KEYWORDS: Earth and Environmental Sciences; Life expectancy; Climate Science; Longevity; Income groups.
To better understand the study, it is crucial to understand the difference between life span, life expectancy, and longevity. According to the United Nations Population Division, life expectancy at birth is defined as “the average number of years that a newborn could expect to live if he or she were to pass through life subject to the age-specific mortality rates of a given period.” ¹ When addressing the life expectancy of a country, it refers to the mean life span of the populace in that country. This factual normal is determined dependent on a populace in general, including the individuals who die during labor, soon after labor, during puberty or adulthood, the individuals who die in war, and the individuals who live well into mature age. On the other hand, according to News Medical Life Sciences, life span refers to “the maximum number of years that a person can expect to live based on the greatest number of years anyone from the same data set has lived.” ² Taking humans as the model, the oldest recorded age attained by any living individual is 122 years, thereby implicating that human beings have a lifespan of at least 122 years. Life span is also known as longevity. As life expectancy has been extended, factors that affect it have been substantially debated. Consensus on factors that influence life expectancy include gender, ethnicity, pollution, climate change, literacy rate, healthcare access, and income level. Other changeable lifestyle factors also have an impact on life expectancy, including but not limited to, exercise, alcohol, smoking and diet. Nevertheless, life expectancy has for the most part continuously increased over time. The authors’ study aims to quantify and study the factors that affect human life expectancy. According to the American Journal of Physical Anthropology, Neolithic and Bronze Age data collected suggests life expectancy was an average of 36 years for both men and women. ³ Hunter-gatherers had a higher life expectancy than farmers as agriculture was not common yet and
people would resort to hunting and foraging food for survival. From then, life expectancy has been shown to be an upward trend, with most studies suggesting that by the late medieval English era, life expectancy of an aristocrat could be as much as 64 years; a figure that closely resembles the life expectancy of many populations around the world today. The increase in life expectancy is attributed to the advancements made in sanitation, education, and lodging during the nineteenth and mid-twentieth centuries, causing a consistent decrease in early and midlife mortality. Additionally, great progress made in numerous regions of well-being and health, such as the discovery of antibiotics, the green revolution that increased agricultural production, the enhancement of maternal and child survival, and mortality from infectious diseases, particularly human immunodeficiency virus (HIV)/ AIDS, tuberculosis (TB), malaria, and neglected tropical diseases (NTDs), has declined. According to the World Health Organization (WHO), global average life expectancy has increased by 5.5 years between 2000 and 2016, which has been notably the fastest increase since the 1950s.⁴ As per the United Nations World Population Prospects, life expectancy will continue to display an upward trend in all regions of the world. However, the average life expectancy isn’t predicted to grow exponentially as it has these past few decades. Projected increases in life expectancy in Northern America, Europe and Latin American and the Caribbean are expected to become more gradual and stagnant, while projections for Africa continue at a much higher rate compared to the rest of the world. Asia is expected to match the global average by the year 2050. Differences in life expectancy across regions of the world are estimated to persist even into the future due to the differences in group incomes, however, income disparity between regions is forecasted to diminish significantly by 2050 ...
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New map of Life
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New Map Of life
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The New Map of Life is a visionary blueprint for r The New Map of Life is a visionary blueprint for redesigning society to support lives that routinely reach 100 years with purpose, health, and opportunity. Instead of treating longer life as a crisis, the report reframes longevity as a profound achievement—and argues that success depends on rebuilding our social, economic, educational, and health systems for a world where centenarian life becomes normal.
The central idea:
We must redesign life’s stages—not extend old age.
This means improving childhood, work, education, health, communities, and inequality across the entire lifespan so that the extra decades are healthy and meaningful, not marked by disease or decline.
The report proposes eight foundational principles for a society built for longevity, supported by research in economics, psychology, public health, education, urban design, and social sciences.
🧭 Core Themes & Insights
1. Longevity Requires a New Life Course
The traditional model—education → work → retirement—breaks down in a 100-year society.
Instead, life must be flexible, with:
multiple careers
lifelong learning
extended midlife productivity
later, healthier transitions into older age
The report emphasizes fluid, nonlinear life paths that enable reinvention and continuous growth.
2. Healthspan Must Match Lifespan
A 100-year life is only valuable if the added decades are lived in good health.
The report calls for:
early-life investment in nutrition, physical activity, and stress reduction
prevention-centered healthcare
reduction of chronic disease
redesign of environments to promote active living
mental health support across all ages
The goal: compress morbidity, not extend frailty.
3. Learning Should Last a Lifetime
Education must shift from “front-loaded” to “lifelong.”
Key reforms include:
universal childhood support
multi-stage college or education “returns” at midlife
employer-supported learning sabbaticals
continual skill renewal in a changing economy
Learning becomes a lifelong asset for resilience, income stability, and cognitive health.
4. Work Must Become Age-Diverse, Flexible, and Purpose-Centered
With longer lives, people will work 50–60 years, but not continuously in the same way.
The report calls for:
flexible work arrangements
age-diverse teams
midlife career transitions
phased retirement options
redesigned job benefits not tied to single employers
Work must support health, meaning, and social connection—not just income.
5. Families and Communities Must Be Reinforced
Longevity increases the importance of:
strong social connections
multigenerational living options
community infrastructure
walkability
safe, accessible transportation
Healthy aging is deeply social, not individual.
6. Financial Security Must Stretch Across 100 Years
Traditional retirement models are unsustainable. The report recommends:
portable benefits
new savings models
flexible retirement ages
risk pooling
more equitable wealth-building opportunities
Financial systems must adapt to careers with multiple transitions.
7. Inequality Is the Biggest Threat to a Long-Lived Society
Longevity is currently unequally distributed—wealth, race, gender, and geography shape life expectancy.
The report insists that:
early childhood investment
improved education quality
access to preventive healthcare
better working conditions
are essential to ensure everyone benefits from longevity.
Longevity can only be a public good if it’s accessible to all.
🏙️ What a Longevity-Ready Society Looks Like
The report paints a picture of societies where:
cities are age-integrated and walkable
workplaces welcome people at 20, 40, 60, and 80
education is continuous
healthcare aggressively prevents disease
caregiving is supported, shared, and respected
retirement is flexible, not binary
purpose and connection last across the lifespan
It’s a future where longer life means better life, not longer decline.
🎯 Overall Conclusion
The New Map of Life reimagines everything—from childhood to education, work, health, retirement, community design, and public policy—for a world in which living to 100 is common. It argues that longevity is not a burden, but a once-in-human-history opportunity—if societies redesign their systems to support health, purpose, financial security, and social connection across all decades of life.
The message is transformative:
We don’t need to add years to life—we need to add life to years....
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xevyo
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/home/sid/tuning/finetune/backend/output/xevyo-bas /home/sid/tuning/finetune/backend/output/xevyo-base-v1/merged_fp16_hf...
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Genetic longevity
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Genetic Longevity
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Markus Valge, Richard Meitern and Peeter Hõrak*
D Markus Valge, Richard Meitern and Peeter Hõrak*
Department of Zoology, University of Tartu, Tartu, Estonia
Life-history traits (traits directly related to survival and reproduction) co-evolve and materialize through physiology and behavior. Accordingly, lifespan can be hypothesized as a potentially informative marker of life-history speed that subsumes the impact of diverse morphometric and behavioral traits. We examined associations between parental longevity and various anthropometric traits in a sample of 4,000–11,000 Estonian children in the middle of the 20th century. The offspring phenotype was used as a proxy measure of parental genotype, so that covariation between offspring traits and parental longevity (defined as belonging to the 90th percentile of lifespan) could be used to characterize the aggregation between longevity and anthropometric traits. We predicted that larger linear dimensions of offspring associate with increased parental longevity and that testosterone-dependent traits associate with reduced paternal longevity. Twelve of 16 offspring traits were associated with mothers’ longevity, while three traits (rate of sexual maturation of daughters and grip strength and lung capacity of sons) robustly predicted fathers’ longevity. Contrary to predictions, mothers of children with small bodily dimensions lived longer, and paternal longevity was not linearly associated with their children’s body size (or testosterone-related traits). Our study thus failed to find evidence that high somatic investment into brain and body growth clusters with a long lifespan across generations, and/or that such associations can be detected on the basis of inter-generational phenotypic correlations.
KEYWORDS
anthropometric traits, body size, inter-generational study, longevity, obesity, sex difference
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8684964a-bab1-4235-93a8-5fd5e24a1d0a
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arrmgvhy-3290
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xevyo
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/home/sid/tuning/finetune/backend/output/xevyo-bas /home/sid/tuning/finetune/backend/output/xevyo-base-v1/merged_fp16_hf...
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Has the Rate of Human Age
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Has the Rate of Human Aging Already Been Modified
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This paper investigates whether the biological rat This paper investigates whether the biological rate of human aging has changed over the past century, or whether improvements in survival and life expectancy result mostly from reducing early-life and midlife mortality rather than slowing aging itself.
The study uses historical mortality data and aging-rate models to determine if humans age more slowly today or if we simply live longer before aging starts dominating mortality.
🔍 Core Question
Has aging itself slowed down, or do we just survive long enough to reach old age more often?
📊 Methods Used
The study examines:
Mortality curves over time (e.g., 1900–present)
The Gompertz function, which mathematically describes how mortality risk doubles with age
Changes in:
Initial mortality rate (IMR)
Rate of aging (Gompertz slope)
Data comes from:
Historical life tables
Cross-country mortality records
Comparisons of birth cohorts over time
The focus is on whether the slope of mortality increase with age has changed — this slope is considered a direct indicator of the rate of aging.
🧠 Key Findings (Perfect Summary)
1. Human aging rate appears largely unchanged
The study finds no strong evidence that the rate at which mortality increases with age (the Gompertz slope) has slowed.
This means humans likely age at the same biological speed as they did 100 years ago.
2. What has changed is the starting point of aging
Early-life and midlife mortality have dropped dramatically due to sanitation, medicine, nutrition, and public health.
As a result, more people reach old age, giving the impression that aging has slowed.
But aging itself (measured by mortality acceleration) has remained stable.
3. Modern longevity gains are driven by shifting the mortality curve
Rather than flattening the curve (slower aging), society has:
Pushed the curve downward (lower mortality at all ages)
Delayed the onset of chronic disease
Improved survival after age 60
These factors extend lifespan without changing the underlying biological aging rate.
4. Even in recent decades, aging rate shows stability
Improvements after 1970 came from:
Cardiovascular improvements
Medical interventions
Smoking decline
But studies consistently show the rate of mortality acceleration remains constant.
🧬 Overall Interpretation
Human aging — measured as the exponential rise in mortality risk with age — has not slowed.
Instead, society has become better at preventing early death, allowing more people to reach advanced ages.
In short:
❗ We live longer not because we age slower, but because we avoid dying earlier.
📌 One-Sentence Perfect Summary
The paper concludes that although human life expectancy has increased dramatically, the biological rate of aging has remained essentially unchanged, and modern longevity gains are due to reduced mortality before and during old age rather than slower aging itself.
If you want, I can also provide:
A diagram or flowchart
A 5-line summary
A student-friendly explanation
A PDF or PowerPoint version
Just tell me!...
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8e8ca1b4-de7c-4d60-a85d-3996892921e1
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8684964a-bab1-4235-93a8-5fd5e24a1d0a
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bqgaiyvm-8168
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xevyo
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/home/sid/tuning/finetune/backend/output/xevyo-bas /home/sid/tuning/finetune/backend/output/xevyo-base-v1/merged_fp16_hf...
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The Four Keys
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The Four Keys to Longevity
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Famous comedian George Burns was once quoted as sa Famous comedian George Burns was once quoted as saying, “If you live to be one hundred, you’ve got it made. Very few people die past that age”. By 2050, it is estimated that there will be more than one million centenarians living in the u.S.1 For most people, planning for retirement or their later years is focused mostly on finances and how they will spend their time. However, ensuring they spend those years in good health is something that many overlook. The times are certainly changing, with medical advances and technological breakthroughs, planning for retirement and living longer needs to be more holistic.
In 1970, average life expectancy at birth in the United States was 71 years. In 2014, it is 79 years; and by 2050, the U.S. Census Bureau projects that average life expectancy will be 84 years.2 Today, according to the National Institute on Aging, there are over 40 million people in the United States aged 65 or older, accounting for about 13 percent of the total population. In 1900, there were just 3.1 million older Americans, or about 4.1% of the population.3 The vast majority of baby boomers—those born between 1946 and 1964—are on a quest to improve their odds of living longer than previous generations. They not only want to live longer, they want to live healthily, happily and more financially secure than ever before. Although there is no magic potion to ensure a long and healthy life, there are some notable accounts of individuals, families, and even whole communities that have defied the aging odds.
The holy grail of longevity In one such amazing story, Stamatis Moraitis, a Greek veteran of World War II, narrates how he was diagnosed with lung cancer in the 1960s
while living in the United States.4 He decided to forgo chemotherapy, and instead returned to his birthplace, Ikaria, the island where “people forget to die”. Moraitis abandoned his western diet and lifestyle and embraced the traditional island culture. His American doctors had told Moraitis he had only nine months to live, yet after moving to Ikaria he was still living— cancer free—45 years after his original diagnosis. According to the story, he never had chemotherapy, took drugs or sought therapy of any sort. All he did was move home to Ikaria and embrace the local lifestyle. He claimed he even outlived his U.S. physicians who, decades earlier, had predicted his imminent death as the only plausible outcome of his devastating diagnosis. Moraitis is not alone when it comes to longevity on the island of Ikaria. In fact, University of Athens researchers have concluded that people on Ikaria are reaching the age of 90 at two-and-a-half times the rate of their American counterparts.5 Stark differences in their lifestyle are apparent, even to a casual observer. ...
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8684964a-bab1-4235-93a8-5fd5e24a1d0a
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dxnygstl-3313
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xevyo
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/home/sid/tuning/finetune/backend/output/xevyo-bas /home/sid/tuning/finetune/backend/output/xevyo-base-v1/merged_fp16_hf...
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Healthy Living Guide
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Healthy Living Guide
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This PDF is a polished, reader-friendly, research- This PDF is a polished, reader-friendly, research-backed wellness guide created to help people improve their overall health in the years 2020–2021. Designed as a practical lifestyle companion, it presents clear, evidence-based advice on nutrition, physical activity, weight management, mental well-being, and maintaining healthy habits during challenging times—especially the COVID-19 pandemic.
It combines scientific recommendations, simple tools, checklists, and motivational strategies into an accessible format that supports long-term healthy living.
🔶 1. Purpose of the Guide
The document aims to help readers:
Understand the core principles of healthy living
Build habits that support long-term physical and emotional well-being
Adapt their lifestyle to pandemic-era challenges
Apply simple, realistic changes to diet, movement, and daily routines
It brings together the most up-to-date public health and nutrition research into a single, user-friendly resource.
🔶 2. Key Themes Covered
The guide addresses the essential pillars of health:
⭐ Healthy Eating
Emphasizes fruits, vegetables, whole grains, nuts, legumes, and healthy fats
Highlights the importance of high-quality food choices
Encourages limiting sugar, sodium, and processed foods
Offers practical meal planning and grocery tips
⭐ Healthy Weight
Explains the relationship between calorie intake, energy balance, and metabolism
Provides strategies for weight loss and weight maintenance
Introduces mindful eating and portion awareness
⭐ Healthy Movement
Encourages daily physical activity, not just structured exercise
Outlines benefits for cardiovascular health, muscle strength, mobility, and mood
Suggests ways to stay active at home
⭐ Mental and Emotional Well-Being
Provides guidance for reducing stress and supporting resilience
Highlights the role of sleep, social connection, and relaxation techniques
Offers coping strategies for pandemic-related anxiety
⭐ COVID-19 and Healthy Living
Explains how the pandemic influenced lifestyle patterns
Encourages maintaining routines for immunity and mental health
Offers science-based recommendations for safety and preventive care
🔶 3. Practical Tools Included
The guide contains numerous supportive features:
Healthy plate diagrams
Food quality rankings
Movement breaks and activity suggestions
Goal-setting templates
Simple recipes and snack ideas
Checklists for building healthy routines
These tools make it easy for readers to turn concepts into action.
🔶 4. Tone and Design
The document is:
Encouraging, positive, and supportive
Richly illustrated with colorful visuals
Organized into short, readable sections
Designed for both beginners and advanced health-conscious individuals
🔶 5. Core Message
The central idea of the guide is that healthy living is achievable through small, consistent, everyday decisions—not extreme diets or intense workout programs. It promotes balance, quality nutrition, regular movement, and mental well-being as the foundations of a long and healthy life.
⭐ Perfect One-Sentence Summary
This PDF is a clear, science-based, and practical guide that teaches readers how to improve their diet, activity levels, weight, and mental well-being—especially during the COVID-19 era—through simple, sustainable healthy living strategies....
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8684964a-bab1-4235-93a8-5fd5e24a1d0a
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aygvnaxq-2918
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xevyo
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Impact of rapamycin life
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Impact of rapamycin on longevity
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This document is a comprehensive scientific review This document is a comprehensive scientific review exploring how rapamycin influences aging and longevity across biological systems. It explains, in clear mechanistic detail, how rapamycin inhibits the mTOR pathway, a central regulator of growth, metabolism, and cellular aging.
The paper summarizes:
1. Why Aging Happens
It describes aging as the gradual accumulation of cellular and molecular damage, leading to reduced function, increased disease risk, and ultimately death.
2. The Role of mTOR in Aging
mTOR is a nutrient-sensing pathway that controls growth, metabolism, protein synthesis, autophagy, and mitochondrial function.
Overactivation of mTOR accelerates aging.
Rapamycin inhibits mTORC1 and indirectly mTORC2, creating conditions that slow aging at the cellular, tissue, and organ level.
3. Rapamycin as a Longevity Drug
The review highlights extensive evidence from yeast, worms, flies, and mice, showing that rapamycin:
Extends lifespan
Improves healthspan
Reduces age-related diseases
4. Key Anti-Aging Mechanisms of Rapamycin
The document details multiple biological pathways influenced by rapamycin:
Protein Homeostasis
Improves fidelity of protein translation
Reduces toxic misfolded protein accumulation
Suppresses harmful senescence-associated secretory phenotype (SASP)
Autophagy Activation
Encourages the removal of damaged organelles and proteins
Protects against neurodegeneration, heart aging, liver aging, and metabolic decline
Mitochondrial Protection
Enhances function and reduces oxidative stress
Immune Rejuvenation
Balances inflammatory signaling
Reduces age-related immune dysfunction
5. Organ-Specific Benefits
The paper includes a detailed table summarizing preclinical evidence showing rapamycin’s benefits in:
Cardiovascular system
Nervous system
Liver
Kidneys
Muscles
Reproductive organs
Respiratory system
Gastrointestinal tract
These benefits involve improvements in:
Autophagy
Stem cell activity
Inflammation
Oxidative stress
Mitochondrial health
6. Limitations & Challenges
While promising, rapamycin has:
Metabolic side effects
Immune-related risks
Dose-timing challenges
Proper therapeutic regimens are required before safe widespread human use.
In Summary
This document provides an up-to-date, detailed, and scientific overview of how rapamycin may slow aging and extend lifespan by targeting mTOR signaling. It integrates molecular biology, animal research, and clinical considerations to outline rapamycin’s potential as one of the most powerful known geroprotective drugs....
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