United States life tables, 2005.
ABSTRACT This report presents period life tables by age, race, and sex for the United States based on age-specific death rates in 2005. The tables presented are based on a newly revised methodology. For comparability, all life tables from the year 2000 forward have been re-estimated using the revised methodology and are presented in the "Technical Notes" section.
Data used to prepare the 2005 life tables are 2005 final mortality statistics, July 1, 2005 population estimates based on the 2000 decennial census, and 2005 Medicare data for ages 66-100. The methods used to estimate mortality for ages 0-65 were the same as those used in annual life tables from 1997 through 2004 (1). The methodology to estimate mortality for the population aged 66 and over was revised in three ways: Medicare data were used to supplement vital statistics and census data starting at age 66 rather than 85, as was done from 1997 through 2004; probabilities of death based on current Medicare data rather than rates of change of probabilities of death based on noncurrent Medicare data were used; and the smoothing and extrapolation of the probabilities of death for ages 66 and over were performed using a nonlinear least squares model rather than a linear model of the rate of change of the probabilities of death for ages 85 and over (1-3).
In 2005, the overall expectation of life at birth was 77.4 years, representing a decline of 0.1 years from life expectancy in 2004. From 2004 to 2005, life expectancy at birth remained the same for males (74.9), females (79.9), the white population (77.9), white males (75.4), white females (80.4), the black population (72.8), and black males (69.3). Life expectancy at birth increased for black females (from 76.0 to 76.1). Life expectancy estimates based on the revised methodology are slightly lower than those based on the previous methodology. For 2005, life expectancy at birth based on the revised methodology was lower by 0.4 years for the total population.
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ABSTRACT: Although recent guidelines call for expanded routine screening for HIV, resources for antiretroviral therapy (ART) are limited, and all eligible persons are not currently receiving treatment. To evaluate the effects on the U.S. HIV epidemic of expanded ART, HIV screening, or interventions to reduce risk behavior. Dynamic mathematical model of HIV transmission and disease progression and cost-effectiveness analysis. Published literature. High-risk (injection drug users and men who have sex with men) and low-risk persons aged 15 to 64 years in the United States. Twenty years and lifetime (costs and quality-adjusted life-years [QALYs]). Societal. Expanded HIV screening and counseling, treatment with ART, or both. New HIV infections, discounted costs and QALYs, and incremental cost-effectiveness ratios. One-time HIV screening of low-risk persons coupled with annual screening of high-risk persons could prevent 6.7% of a projected 1.23 million new infections and cost $22,382 per QALY gained, assuming a 20% reduction in sexual activity after screening. Expanding ART utilization to 75% of eligible persons prevents 10.3% of infections and costs $20,300 per QALY gained. A combination strategy prevents 17.3% of infections and costs $21,580 per QALY gained. With no reduction in sexual activity, expanded screening prevents 3.7% of infections. Earlier ART initiation when a CD4 count is greater than 0.350 × 10(9) cells/L prevents 20% to 28% of infections. Additional efforts to halve high-risk behavior could reduce infections by 65%. The model of disease progression and treatment was simplified, and acute HIV screening was excluded. Expanding HIV screening and treatment simultaneously offers the greatest health benefit and is cost-effective. However, even substantial expansion of HIV screening and treatment programs is not sufficient to markedly reduce the U.S. HIV epidemic without substantial reductions in risk behavior. National Institute on Drug Abuse, National Institutes of Health, and Department of Veterans Affairs.Annals of internal medicine 12/2010; 153(12):778-89. DOI:10.1059/0003-4819-153-12-201012210-00004 · 16.10 Impact Factor