Historical Lifespan Patterns

How it works

Benefits

Comparisons

Background

Other

Highlighted claims

• Among U.S.-born people surviving past age 10, median lifespan around 1650 was about 62 years for both males and females. — Data Mining of Online Genealogy Datasets for Revealing Lifespan Patterns in Human Population
• Average lifespan for U.S.-born females increased sharply from 1850 to 1900. — Data Mining of Online Genealogy Datasets for Revealing Lifespan Patterns in Human Population
• Higher p increases survival after senescence, making death occur later even when senescence begins earlier. — Cellular senescence in the Penna model of aging
• Maximum lifespan remains fixed at l_max + M for populations with the same M. — Cellular senescence in the Penna model of aging
• The WikiTree lifespan distributions showed high infant and child mortality and peaks around ages 70 to 80. — Data Mining of Online Genealogy Datasets for Revealing Lifespan Patterns in Human Population
• Historical trends showed fewer early deaths and increasing lifespans over time. — Data Mining of Online Genealogy Datasets for Revealing Lifespan Patterns in Human Population
• The observed lifespan pattern resembled prior genealogy and national-statistics lifespan graphs, supporting the plausibility of the WikiTree data. — Data Mining of Online Genealogy Datasets for Revealing Lifespan Patterns in Human Population
• Higher p produces younger populations in terms of senescence onset. — Cellular senescence in the Penna model of aging
• The senescent Penna model shows a greater probability of living to higher ages but not an increase in mean lifespan for higher p. — Cellular senescence in the Penna model of aging
• Increasing M moves senescence onset earlier while allowing longer post-senescence survival. — Cellular senescence in the Penna model of aging