The future of death in America

Dados Bibliográficos

ID2636616
AutoresSamir Soneji (0000-0001-8735-276X, Dartmouth Institute for Health Policy and Clinical Practice, autor correspondente), Gary King (0000-0002-5327-7631)
Ano2011
Volume25
Páginas1-38
Data de publicação2011-07-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoDemographic Research (JOURNAL)
Identificadores do periódicoISSN: 1435-9871 • E-ISSN: 2363-7064
EditoraMax Planck Institute for Demographic Research (PUBLISHER • DE)
DOI10.4054/demres.2011.25.1
PMID24696636
OpenAlexW2024315059
IdiomaEN
Citações recebidas18
Referências citadas65

Population mortality forecasts are widely used for allocating public health expenditures, setting research priorities, and evaluating the viability of public and private pensions, and health care financing systems. In part because existing methods forecast less accurately when based on more information, most forecasts are still based on simple linear extrapolations that ignore known biological risk factors and other prior information. We adapt a Bayesian hierarchical forecasting model capable of including more known health and demographic information than has previously been possible. This leads to the first age- and sex-specific forecasts of American mortality that simultaneously incorporate, in a formal statistical model, the effects of the recent rapid increase in obesity, the steady decline in tobacco consumption, and the well known patterns of smooth mortality age profiles and time trends. Formally including new information in forecasts can matter a great deal. For example, we estimate an increase in male life expectancy at birth from 76.2 years in 2010 to 79.9 years in 2030, which is 1.8 years greater than the U.S. Social Security Administration projection and 1.5 years more than U.S. Census projection. For females, we estimate more modest gains in life expectancy at birth over the next twenty years from 80.5 years to 81.9 years, which is virtually identical to the Social Security Administration projection and 2.0 years less than U.S. Census projections. We show that these patterns are also likely to greatly affect the aging American population structure. We offer an easy-to-use approach so that researchers can include other sources of information and potentially improve on our forecasts too

Geography · Sociology · Demography · Health and Conflict Studies · Health disparities and outcomes · Insurance, Mortality, Demography, Risk Management