Falling Short of Highest Life Expectancy: How Many Americans Might Have Been Alive in the Twentieth Century?

Life expectancy at birth in the United States during the twentieth century was lower than in many other highly developed countries. We investigate how this mortality disadvantage in the last 100 years translates into the number of hypothetical lives lost and their sex and age structure. We estimate the hypothetical US population if it had experienced in each decade since 1900 the mortality level of the country with the then highest life expectancy and compare the results to the actual figures in 2000. By 2000, the number of additional people who could have been alive had the mortality levels in the United States been as low as those in countries with the highest life expectancy was 66 million. This number is distributed equally between males and females. Suboptimal mortality at reproductive ages is crucial for the cumulative effect of potential lives lost, resulting from premature deaths of women who could still become first‐time mothers or bear additional children. Out of the 66 million additional persons who could have been alive in 2000, 45 million are attributable to those indirect deaths. Although the differences in the composition of the population by sex and age under the two mortality regimes are minor, the majority of people who might have been alive—54 million—were of working age or younger.     

Bayesian Estimation of Age-Specific Mortality and Life Expectancy for Small Areas With Defective Vital Records

High sampling variability complicates estimation of demographic rates in small areas. In addition, many countries have imperfect vital registration systems, with coverage quality that varies significantly between regions. We develop a Bayesian regression model for small-area mortality schedules that simultaneously addresses the problems of small local samples and underreporting of deaths. We combine a relational model for mortality schedules with probabilistic prior information on death registration coverage derived from demographic estimation techniques, such as Death Distribution Methods, and from field audits by public health experts. We test the model on small-area data from Brazil. Incorporating external estimates of vital registration coverage though priors improves small-area mortality estimates by accounting for underregistration and automatically producing measures of uncertainty. Bayesian estimates show that when mortality levels in small areas are compared, noise often dominates signal. Differences in local point estimates of life expectancy are often small relative to uncertainty, even for relatively large areas in a populous country like Brazil.     

Understanding the age and cause drivers of recent longevity trends in Australia

Longevity continues to increase in Australia. The period 1979–2011 saw increases in life expectancy at birth of 6.9 years to 84.7 years for females, and 9.5 years to 80.2 years for males. A decomposition analysis reveals that the majority of the increase, particularly for females, is attributable to mortality improvement at older ages, and that gains are being made at increasingly older ages over time. Improvements in circulatory disease mortality account for a very significant component of life expectancy gains over the period—75 % for females and 60 % for males—with land transport accidents, congenital and perinatal mortality, and neoplasms also making significant positive contributions. Dementia and Alzheimer’s disease, and lung neoplasms for females, have had a negative impact. Females currently outlive males by 4.5 years on average, with ischaemic heart disease and prostate and other neoplasms the important positive contributors to this differential, and breast cancer having a negative effect. With 93 % of females and 88 % of males now surviving to age 65 in Australia, continued life expectancy improvements will depend to a large extent on success in delaying death at the older ages.     

The Legacy of the Great Recession in Italy: A Wider Geographical,Gender, and Generational Gap in Working Life Expectancy

Under the pressure of population aging the Italian pension system has undergone reforms to increase labor force participation and retirement age, and, thus, the length of working life. However, how the duration of working life has developed in recent years is not well understood. This paper is the first to analyze trends in working life expectancy in Italy. We use data from a nationally representative longitudinal sample of 880,000 individuals from 2003 to 2013 and estimate working life expectancy by gender, occupational category, and region of residence using a Markov chain approach. We document large and increasing heterogeneity in the length of working life. From 2003–2004 to 2012–2013, working life expectancy for men declined from 35.2 to 27.2 years and for women from 34.7 to 23.7 years, increasing the gender gap to 3.5 years. Both young and old were hit, as roughly half of the decline was attributable to ages below 40, half above 40. Working life expectancy declined for all occupational groups, but those in manual occupations lost most, 8.5 years (men) and 10.5 years (women). The North–South economic gradient widened such that men living in the North were expected to work 8 years longer than women living in the South. The fraction of working life of total life expectancy at age 15 declined to record lows at 40% for men and 34% for women in 2012–2013. Policies aiming at increasing total population working life expectancy need to take into consideration the socio-demographic disparities highlighted by our results.

     

How Long Do We Live?

Period life expectancy is calculated from age‐specific death rates using life table methods that are among the oldest and most widely employed tools of demography. These methods are rarely questioned, much less criticized. Yet changing age patterns of adult mortality in countries with high life expectancy provide a basis for questioning the conventional use of life tables. This article argues that when the mean age at death is rising, period life expectancy at birth as conventionally calculated overestimates life expectancy. Estimates of this upward bias, ranging from 1.6 years for the United States and Sweden to 3.3 years for Japan for 1980–95, are presented. A similar bias in the opposite direction occurs when mean age at death is falling. These biases can also distort trends in life expectancy as conventionally calculated and may affect projected future trends in period life expectation, particularly in the short run.     

Anatomy of a Municipal Triumph: New York City's Upsurge in Life Expectancy

Over the period 1990–2010, the increase in life expectancy for males in New York City was 6.0 years greater than for males in the United States. The female relative gain was 3.9 years. Male relative gains were larger because of extremely rapid reductions in mortality from HIV/AIDS and homicide, declines that reflect effective municipal policies and programs. Declines in drug‐ and alcohol‐related deaths also played a significant role in New York City's advance, but every major cause of death contributed to its relative improvement. By 2010, New York City had a life expectancy that was 1.9 years greater than that of the US. This difference is attributable to the high representation of immigrants in New York's population. Immigrants to New York City, and to the United States, have life expectancies that are among the highest in the world. The fact that 38 percent of New York's population consists of immigrants, compared to only 14 percent in the United States, accounts for New York's exceptional standing in life expectancy in 2010. In fact, US‐born New Yorkers have a life expectancy below that of the United States itself.     

Trends in senescent life expectancy

The distinction between senescent and non-senescent mortality proves to be very valuable for describing and analysing age patterns of death rates. Unfortunately, standard methods for estimating these mortality components are lacking. The first part of this paper discusses alternative methods for estimating background and senescent mortality among adults and proposes a simple approach based on death rates by causes of death. The second part examines trends in senescent life expectancy (i.e., the life expectancy implied by senescent mortality) and compares them with trends in conventional longevity indicators between 1960 and 2000 in a group of 17 developed countries with low mortality. Senescent life expectancy for females rises at an average rate of 1.54 years per decade between 1960 and 2000 in these countries. The shape of the distribution of senescent deaths by age remains relatively invariant while the entire distribution shifts over time to higher ages as longevity rises.     

The Association Between Individual Income and Remaining Life Expectancy at the Age of 65 in the Netherlands

This article quantifies the association between individual income and remaining life expectancy at the statutory retirement age (65) in the Netherlands. For this purpose, we estimate a mortality risk model using a large administrative data set that covers the 1996–2007 period. Besides age and marital status, the model includes as covariates individual and spouse’s income as well as a random individual specific effect. It thus allows for dynamic selection based on both observed and unobserved characteristics. We find that conditional on marital status, individual income is about equally strong and negatively associated with mortality risk for men and women and that spouse’s income is only weakly associated with mortality risk for women. For both men and women, we quantify remaining life expectancy at age 65 for low-income individuals as approximately 2.5 years less than that for high-income individuals.     

Recent trends in mortality in Australia—an analysis of the causes of death through the application of life table techniques

The paper examines the post-1971 reduction in Australian mortality in light of data on causes of death. Multiple-decrement life tables for eleven leading causes of death by sex are calculated and the incidence of each cause of death is presented in terms of the values of the life table functions. The study found that in the overall decline in mortality over the last 20 years significant changes occurred in the contribution of the various causes to total mortality. Among the three leading causes of death, heart disease, malignant neoplasms (cancer), and cerebrovascular disease (stroke), mortality rates due to neoplasms increased and those of the other two causes decreased. The sex-age-cause-specific incidence of mortality changed and the median age at death increased for all causes except for deaths due to motor-vehicle accidents for both sexes and suicide for males. The paper also deciphers the gains in the expectation of life at birth over various time periods and the sex-differentials in the expectation of life at birth at a point in time in terms of the contributions made by the various sex-age-cause-specific mortality rates.     

Causes of death contributing to changes in life expectancy in New York City between 1983 and 1992

Recent changes in life expectancy among race and sex groups in New York City were evaluated by analyzing the relative effects of different causes of death in 1983 and 1992, a period in which life expectancy at birth declined by 1.1 years among white males, remained unchanged among black males, and increased 1.2 years among white and black females. Heart disease was found to be the leading cause of death making positive contributions to changes in life expectancy regardless of race or sex, and HIV/AIDS was the leading negative contributor. Overall, deaths from infectious diseases and external causes are becoming more important compared to degenerative conditions in explaining trends in life expectancy in New York City. Past improvements in survival due to reductions in infant deaths are being reversed due to an increase in deaths from preventable causes such as violence and AIDS. Future gains in longevity may require a greater emphasis on policies and programs emphasizing conflict resolution and HIV prevention.     

中国各地区人口预期寿命及地理分布分析

平均预期寿命是世界公认的衡量人类进步的标准。本文以生命表为基础,主要依据我国第六次人口普查资料,计算各省市区的预期寿命并进行相关分析,计算结果表明,2010年中国人口平均预期寿命为78.17岁,男75.86岁,女80.68岁,已进入发达国家行列。预期寿命与婴儿死亡率呈负相关r＝-0.789,与人均国民总收入呈正相关r＝0.604。预期寿命女性比男性长4～7岁,符合一般规律。影响男性寿命低于女性的原因很多,本文重点讨论了遗传因素和生活方式的影响,并对预期寿命的地理分布进行分析。     

How Change in Age-specific Mortality Affects Life Expectancy

At current mortality rates, life expectancy is most responsive to change in mortality rates at older ages. Mathematical formulae that describe the linkage between change in age-specific mortality rates and change in life expectancy reveal why. These formulae also shed light on how past progress against mortality has been translated into increases in life expectancy – and on the impact that future progress may have. Furthermore, the mathematics can be adapted to study the effect of mortality change in heterogeneous populations in which those who did at some age would, if saved, enjoy a different life expectancy than those who live.     

Modeling Quality-Adjusted Life Expectancy Loss Resulting from Tobacco use in the United States

Purpose  To describe the development of a model for estimating the effects of tobacco use upon Quality Adjusted Life Years (QALYs) and to estimate the impact of tobacco use on health outcomes for the United States (US) population using the model. Method  We obtained estimates of tobacco consumption from 6 years of the National Health Interview Survey (NHIS). In addition, NHIS data were used to impute the Quality of Well-Being (QWB) Scale using a new methodology known as QWBX1. The QWB places health status on a continuum ranging from death (0.0) to full functioning without symptoms (1.0). The method allows the adjustment of life expectancy for reduced quality of life associated with health conditions. NHIS data were matched to the National Death Index for 14,464 deaths occurring by December 31, 1997. The analysis is limited to adults between the ages of 18 and 70 years. Results  Quality of Well-Being scores were broken down by age and for six smoking categories: (1) non-smokers, (2) those who smoke 1–10 cigarettes per day, (3) 11–20 cigarettes per day, (4) 21–30 cigarettes per day, and (5) 31–40 cigarettes per day, and (6) 40 or greater cigarettes per day. There was a systematic relationship between current tobacco use and health-related quality of life at each point along the age spectrum and there was a clear and systematic separation of quality-adjusted life expectancy by number of cigarettes smoked per day. Teenagers who continue to smoke loose 3.5 QALYs between ages 18 and 70 in comparison to non-smokers. A greater portion in the loss in QALE is attributable to quality of life than to shorten life expectancy. Conclusions  The overall goal of Healthy People 2010 is to increase Years of Healthy Life (or QALE) in the United States. Each year, tobacco use results in hundreds of thousands of quality-adjusted life years lost. Combined models of morbidity and mortality incorporating a range of tobacco consumption levels are required to best represent the impact of tobacco use. Supported by a Grant 11RT-0243 from the Californian Tobacco Related Disease Research Program (TRDRP)     

Potential support ratios: Cohort versus period perspectives

The ‘prospective potential support ratio’ has been proposed by researchers as a measure that accurately quantifies the burden of ageing, by identifying the fraction of a population that has passed a certain measure of longevity, for example, 17?years of life expectancy. Nevertheless, the prospective potential support ratio usually focuses on the current mortality schedule, or period life expectancy. Instead, in this paper we look at the actual mortality experienced by cohorts in a population, using cohort life tables. We analyse differences between the two perspectives using mortality models, historical data, and forecasted data. Cohort life expectancy takes future mortality improvements into account, unlike period life expectancy, leading to a higher prospective potential support ratio. Our results indicate that using cohort instead of period life expectancy returns around 0.5 extra younger people per older person among the analysed countries. We discuss the policy implications implied by our cohort measures.     

The Contribution of Drug Overdose to Educational Gradients in Life Expectancy in the United States, 1992–2011

Since the mid-1990s, the United States has witnessed a dramatic rise in drug overdose mortality. Educational gradients in life expectancy widened over the same period, and drug overdose likely plays a role in this widening, particularly for non-Hispanic whites. The contemporary drug epidemic is distinctive in terms of its scope, the nature of the substances involved, and its geographic patterning, which influence how it impacts different education groups. I use vital statistics and National Health Interview Survey data to examine the contribution of drug overdose to educational gradients in life expectancy from 1992–2011. I find that over this period, years of life lost due to drug overdose increased for all education groups and for both males and females. The contribution of drug overdose to educational gradients in life expectancy has increased over time and is greater for non-Hispanic whites than for the population as a whole. Drug overdose accounts for a sizable proportion of the increases in educational gradients in life expectancy, particularly at the prime adult ages (ages 30–60), where it accounts for 25 % to 100 % of the widening in educational gradients between 1992 and 2011. Drug overdose mortality has increased more rapidly for females than for males, leading to a gender convergence. These findings shed light on the processes driving recent changes in educational gradients in life expectancy and suggest that effective measures to address the drug overdose epidemic should take into account its differential burden across education groups.     

Changing Life Expectancy and Health Expectancy Among Russian Adults: Results from the Past 20 Years

The decade following the collapse of the Soviet Union was characterized by wide fluctuations in Russian mortality rates, but since the early 2000s, life expectancy has improved progressively. Recent upturns in longevity have promoted policy debates over extending the retirement age in the country. However, whether observed gains in life expectancy are accompanied by improving health remains to be addressed. Using data from the 1994–2014 Russian Longitudinal Monitoring Survey of the Higher School of Economics, this study investigates trends over 20 years in healthy life expectancy (HLE) and illness-free life expectancy (IFLE) for men and women at adult ages. Analyses using the Sullivan method show that men and women at adult ages have experienced large increases in health expectancies during the post-Soviet period. Increases in HLE exceeded increases in total life expectancy for both genders. Further, health expectancies have evolved over time through cycles of increases and decreases, just like life expectancy. These results suggest increases in good-quality years among men and women at working ages, offering support for changing the official retirement age. The extent of the change in the retirement age, however, needs to be carefully considered, given that, despite recent improvements, the health expectancy of the Russian population still remains low.     

Changing mortality patterns that led life expectancy in Japan to surpass Sweden’s: 1972–1982

Between 1972 and 1982, Japan caught up to and then surpassed Sweden as the country with the longest life expectancy. The contributions of different causes of death and age groups to life expectancy changes in males during this time period are examined in detail for these two countries. Even though cerebrovascular disease mortality rates remained lower in Sweden over the entire interval, the rapid gain made by Japan relative to Sweden for this cause of death was a prime factor in Japan's ending the period with a higher life expectancy. Important contributions to life expectancy improvement in Japan came from declining mortality rates in those aged 55 and older.     

Steep increase in best-practice cohort life expectancy

We analyze trends in best-practice life expectancy among female cohorts born from 1870 to 1950. Cohorts experience declining rather than constant death rates, and cohort life expectancy usually exceeds period life expectancy. Unobserved mortality rates in non-extinct cohorts are estimated using the Lee-Carter model for mortality in 1960–2008. Best-practice cohort and period life expectancies increased nearly linearly. Across cohorts born from 1870 to 1920 the annual increase in cohort length of life was 0.43 years. Across calendar years from 1870 to 2008, the annual increase was 0.28 years. Cohort life expectancy increased from 53.7 years in the 1870 cohort to 83.8 years in the 1950 cohort. The corresponding cohort/period longevity gap increased from 1.2 to 10.3 years. Among younger cohorts, survival to advanced ages is substantially higher than could have been anticipated by period mortality regimes when these cohorts were young or middle-aged. A large proportion of the additional expected years of life are being lived at ages 65 and older. This substantially changes the balance between the stages of the life cycle.     

Estimating Indigenous life expectancy: pitfalls with consequences

The methods used by the Australian Bureau of Statistics (ABS) to estimate life expectancies of Aboriginal and Torres Strait Islander peoples in 2009 have been controversial and require critical and sensitive analysis. The introduction by ABS of the direct method for estimating Indigenous life expectancies, based on estimated deaths and populations, has been generally welcomed. But the way this method has been applied and, in particular, death estimates used by the ABS, warrant scrutiny. These estimates were based on a first ever linkage between Indigenous deaths and census records following the 2006 census. Census-based identification was used in place of identification in the death registrations, rather than as a supplementary data source. The various national, state and regional life expectancy estimates published may have been biased upwards by this process. Because the impact of the methodology varies across Australia, regional differentials reported appear substantial but are not soundly based. The questionable ABS results are highlighted and discussed. Analysis based on more comprehensive linkage of death records in New South Wales over 5?years suggests that the ABS methods have understated Indigenous deaths and so overstated life expectancy. The effect of an alternative ABS approach is also discussed. ABS estimates published in 2009 are not necessarily definitive and may well overestimate Aboriginal and Torres Strait Islander life expectancy and underestimate the life expectancy gap. Estimates should be based on accurate estimates of deaths and population. Consultation and a thorough review are essential before the next round of estimates following the findings of the 2011 population census. Closing the Gap commitments focus on eliminating the life expectancy gap between Aboriginal and Torres Strait Islander peoples and other Australians. Life expectancy estimates need to be based on methods and data that are well understood and broadly supported. The alternative is unproductive debate about statistics rather than the range of policies and resourcing issues needed to improve Indigenous health.     

Differences in Life Expectancy and Disability Free Life Expectancy in Italy. A Challenge to Health Systems

Background Measures of health expectancy such as Disability Free Life Expectancy are used to evaluate and compare regional/national health statuses. These indicators are useful for understanding changes in the health status and defining health policies and decisions on the provision of services because provide useful information on possible areas needing interventions and burden of care to health systems. Methods Two databases have been used for the analysis: the Italian Health Interview Survey and the European Community Household Panel. The data were analyzed by gender and geographic area. DFLE was calculated by the Sullivan method. Results In 2005 in Italy women have a longer life expectancy than men: 84 and 78 years, respectively. But if we consider life without disability in Italy the male disadvantage reduces: men live 85% of their years without disability, women only 75%. Geographic differences do exist because Disability Free Life Expectancy is longer in Northern and in Central regions; shorter in the South. At a European level similar data can be found: on average women live longer but they have a longer time of life with disability. Conclusion In Italy women live longer but have a worse quality of health than men; in the South there is a worse quality of health. Similar findings can be identified at a European level. The Italian situation with the highest percentage of DFLE at 65 out of the total LE at 65 and one of the longest LE witnesses ageing is not necessarily associated to a worsening of health.