title: Demographic consequences of defeating aging.
abstract: A common objection against starting a large-scale biomedical war on aging is the fear of catastrophic population consequences (overpopulation). This fear is only exacerbated by the fact that no detailed demographic projections for radical life extension scenario have been conducted so far. This study explores different demographic scenarios and population projections, in order to clarify what could be the demographic consequences of a successful biomedical war on aging. A general conclusion of this study is that population changes are surprisingly slow in their response to a dramatic life extension. For example, we applied the cohort-component method of population projections to 2005 Swedish population for several scenarios of life extension and a fertility schedule observed in 2005. Even for very long 100-year projection horizon, with the most radical life extension scenario (assuming no aging at all after age 60), the total population increases by 22% only (from 9.1 to 11.0 million). Moreover, if some members of society reject to use new anti-aging technologies for some religious or any other reasons (inconvenience, non-compliance, fear of side effects, costs, etc.), then the total population size may even decrease over time. Thus, even in the case of the most radical life extension scenario, population growth could be relatively slow and may not necessarily lead to overpopulation. Therefore, the real concerns should be placed not on the threat of catastrophic population consequences (overpopulation), but rather on such potential obstacles to a success of biomedical war on aging, as scientific, organizational, and financial limitations.
authors.affiliation: Center on Aging, NORC and The University of Chicago, Chicago, Illinois 60637, USA. gavrilov@longevity-science.org
authors.forename: Leonid A
authors.initials: LA
authors.lastname: Gavrilov
authors.forename: Natalia S
authors.initials: NS
authors.lastname: Gavrilova
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology; D003710:Demography; D005260:Female; D005544:Forecasting; D006801:Humans; D008017:Life Expectancy; D008297:Male; D008962:Models, Theoretical; D011157:Population Dynamics; D044968:Regenerative Medicine / Q000639:trends; D012727:Sex Characteristics