中国老年人口健康预期寿命差异的分解研究

健康预期寿命是反映人群健康长寿的重要指标,健康预期寿命差异反映了一个国家或地区的健康不平等状况。利用多状态生命表分析了中国老年人口健康预期寿命在过去十余年间的趋势与变动,并通过夏普利值分解法测算了人口社会学等11类因素对老年人口健康预期寿命差异的具体贡献值。得到以下四项重要研究结论:第一,从2005年到2018年,中国老年人口健康预期寿命差异的程度略有增加,女性、农村群体相比对应群体差距始终较高;泰尔指数分解发现,组内不平等(而非组间不平等)是造成上述差异的主要原因;老年人口健康预期寿命的性别差异呈现出高龄老人缩小而低龄老人扩大的趋势。第二,婚姻状况是健康预期寿命变动最重要的影响因素,但影响程度呈现逐年下降趋势,反之,受教育程度的影响在逐年上升;进一步将11类影响因素归类后发现:"个体特征"是最重要的影响因素,"经济因素"和"行为因素"的重要性次之,"环境因素"的影响最小。第三,上述影响因素对中国老年人口健康预期寿命的影响总体呈上升趋势,分城乡、分性别后依然呈现出相同的特征。最后,各因素在不同城乡、性别、婚姻状态的群体中的影响存在异质性。     

Social inequalities in disability-free life expectancy in the french male population, 1980–1991

We calculate aggregate indicators of population health for occupational groups to gauge changes in health disparities during the 1980-1991 period. The study is based on the experiences of French adult men in three major occupational classes: managers, manual workers, and an intermediary occupational group. Life table models show that managers have longer life expectancy and disability-free life expectancy (DFLE) than manual workers, and a shorter life expectancy with disability. The concurrent increases in life expectancy and DFLE during the period maintained the occupational disparities in health; the years lived with disability, however, declined for all groups, as for the entire French population.     

The Contribution of Health Care and Other Interventions to Black–White Disparities in Life Expectancy, 1980–2007

Black–white mortality disparities remain sizable in the United States. In this study, we use the concept of avoidable/amenable mortality to estimate cause-of-death contributions to the difference in life expectancy between whites and blacks by gender in the United States in 1980, 1993, and 2007. We begin with a review of the concept of “avoidable mortality” and results of prior studies using this cause-of-death classification. We then present the results of our empirical analyses. We classified causes of death as amenable to medical care, sensitive to public health policies and health behaviors, ischemic heart disease, suicide, HIV/AIDS, and all other causes combined. We used vital statistics data on deaths and Census Bureau population estimates and standard demographic decomposition techniques. In 2007, causes of death amenable to medical care continued to account for close to 2 years of the racial difference in life expectancy among men (2.08) and women (1.85). Causes amenable to public health interventions made a larger contribution to the racial difference in life expectancy among men (1.17 years) than women (0.08 years). The contribution of HIV/AIDS substantially widened the racial difference among both men (1.08 years) and women (0.42 years) in 1993, but its contribution declined over time. Despite progress observed over the time period studied, a substantial portion of black–white disparities in mortality could be reduced given more equitable access to medical care and health interventions.     

Longevity and Lifespan Variation by Educational Attainment in Spain: 1960–2015

For a long time, studies of socioeconomic gradients in health have limited their attention to between-group comparisons. Yet, ignoring the differences that might exist within groups and focusing on group-specific life expectancy levels and trends alone, one might arrive at overly simplistic conclusions. Using data from the Spanish Encuesta Sociodemográfica and recently released mortality files by the Spanish Statistical Office (INE), this is the first study to simultaneously document (1) the gradient in life expectancy by educational attainment groups, and (2) the inequality in age-at-death distributions within and across those groups for the period between 1960 and 2015 in Spain. Our findings suggest that life expectancy has been increasing for all education groups but particularly among the highly educated. We observe diverging trends in life expectancy, with the differences between the low- and highly educated becoming increasingly large, particularly among men. Concomitantly with increasing disparities across groups, length-of-life inequality has decreased for the population as a whole and for most education groups, and the contribution of the between-group component of inequality to overall inequality has been extremely small. Even if between-group inequality has increased over time, its contribution has been too small to have sizable effects on overall inequality. In addition, our results suggest that education expansion and declining within-group variability might have been the main drivers of overall lifespan inequality reductions. Nevertheless, the diverging trends in longevity and lifespan inequality across education groups represent an important phenomenon whose underlying causes and potential implications should be investigated in detail.     

Global patterns of healthy life expectancy for older women

This paper focuses on patterns of healthy life expectancy for older women around the globe in the year 2000, and on the determinants of differences in disease and injury for older ages. Our study uses data from the World Health Organization for women and men in 191 countries. These data include a summary measure of population health, healthy life expectancy (HALE), which measures the number of years of life expected to be lived in good health, and a complementary measure of the loss of health (disability-adjusted life years or DALYs) due to a comprehensive set of disease and injury causes. We examine two topics in detail: (1) cross-national patterns of female-male differences in healthy life expectancy at age 60; and (2) identification of the major injury and disability causes of disability in women at older ages. Globally, the male-female gap is lower for HALE than for total life expectancy. The sex gap is highest for Russia (10.0 years) and lowest in North Africa and the Middle East, where males and females have similar levels of healthy life expectancy, and in some cases, females have lower levels of healthy life expectancy. We discuss the implications of the findings for international health policy.     

Global Patterns of Healthy Life Expectancy for Older Women

SUMMARY

This paper focuses on patterns of healthy life expectancy for older women around the globe in the year 2000, and on the determinants of differences in disease and injury for older ages. Our study uses data from the World Health Organization for women and men in 191 countries. These data include a summary measure of population health, healthy life expectancy (HALE), which measures the number of years of life expected to be lived in good health, and a complementary measure of the loss of health (disability-adjusted life years or DALYs) due to a comprehensive set of disease and injury causes. We examine two topics in detail: (1) cross-national patterns of female-male differences in healthy life expectancy at age 60; and (2) identification of the major injury and disability causes of disability in women at older ages. Globally, the male-female gap is lower for HALE than for total life expectancy. The sex gap is highest for Russia (10.0 years) and lowest in North Africa and the Middle East, where males and females have similar levels of healthy life expectancy, and in some cases, females have lower levels of healthy life expectancy. We discuss the implications of the findings for international health policy.     

Black-White Disparities in Life Expectancy: How Much Can the Standard SES Variables Explain?

This article quantifies the extent to which socioeconomic and demographic characteristics can account for black-white disparities in life expectancy in the United States. Although many studies have investigated the linkages between race, socioeconomic status, and mortality, this article is the first to measure how much of the life expectancy gap remains after differences in mortality are purged of the compositional differences in socioeconomic characteristics between blacks and whites. The decomposition is facilitated by a reweighting technique that creates counterfactual estimation samples in which the distribution of income, education, employment and occupation, marital status, and other theoretically relevant variables among blacks is made to match the distribution of these variables among whites. For males, 80% of the black-white gap in life expectancy at age 1 can be accounted for by differences in socioeconomic and demographic characteristics. For females, 70% percent of the gap is accounted for. Labor force participation, occupation, and (among women only) marital status have almost no additional power to explain the black-white disparity in life expectancy after precise measures for income and education are controlled for.     

Forecasting differences in life expectancy by education

Forecasts of life expectancy (LE) have fuelled debates about the sustainability and dependability of pension and healthcare systems. Of relevance to these debates are inequalities in LE by education. In this paper, we present a method of forecasting LE for different educational groups within a population. As a basic framework we use the Li–Lee model that was developed to forecast mortality coherently for different groups. We adapted this model to distinguish between overall, sex-specific, and education-specific trends in mortality, and extrapolated these time trends in a flexible manner. We illustrate our method for the population aged 65 and over in the Netherlands, using several data sources and spanning different periods. The results suggest that LE is likely to increase for all educational groups, but that differences in LE between educational groups will widen. Sensitivity analyses illustrate the advantages of our proposed method.     

Testing the relationship between income inequality and life expectancy: a simple correction for the aggregation effect when using aggregated data

In this paper, we show a simple correction for the aggregation effect when testing the relationship between income inequality and life expectancy using aggregated data. While there is evidence for a negative correlation between income inequality and a population’s average life expectancy, it is not clear whether this is due to an aggregation effect based on a non-linear relationship between income and life expectancy or to income inequality being a health hazard in itself. The proposed correction method is general and independent of measures of income inequality, functional form assumptions of the health production function, and assumptions on the income distribution. We apply it to data from the Human Development Report and find that the relationship between income inequality and life expectancy can be explained entirely by the aggregation effect. Hence, there is no evidence that income inequality itself is a health hazard.     

Recent perspectives on active life expectancy for older women

This article provides a critical review of recent active life expectancy literature, describing trends of special interest to women. We review findings from leading perspectives used to study life expectancy and active life expectancy, including gender, racial and socioeconomic differences, disease-specific effects, and biodemography. We examine three competing theories of population health that frame active life expectancy research-compression of morbidity, expansion of morbidity, and dynamic equilibrium-concluding there is support for both the compression of morbidity and dynamic equilibrium theories. Policy implications for women include a greater understanding of the role of education and racial and ethnic diversity in active life trends, and an increased public policy emphasis on prevention and treatment of chronic disease, together with adoption of more healthy lifestyles.     

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.     

Is 60 the New 50? Examining Changes in Biological Age Over the Past Two Decades

Increasing life expectancy has been interpreted as improving health of a population. However, mortality is not always a reliable proxy for the pace of aging and could instead reflect achievement in keeping ailing people alive. Using data from NHANES III (1988–1994) and NHANES IV (2007–2010), we examined how biological age, relative to chronological age, changed in the United States between 1988 and 2010, while estimating the contribution of changes in modifiable health behaviors. Results suggest that biological age is lower for more recent periods; however, the degree of improvement varied across age and sex groups. Overall, older adults experienced the greatest improvement or decreases in biological age. Males, especially those in the youngest and oldest groups, experienced greater declines in biological age than females. These differences were partially explained by age- and sex-specific changes in behaviors, such as smoking, obesity, and medication use. Slowing the pace of aging, along with increasing life expectancy, has important social and economic implications; thus, identifying modifiable risk factors that contribute to cohort differences in health and aging is essential.     

Inequality, Wealth and Health: Is Decreasing Income Inequality the Key to Create Healthier Societies?

The idea that the level of stratification of societies contributes to the well-being of their members is gaining popularity. We contribute to this debate by investigating whether reducing inequalities in the income distribution of societies is a strategy for improving population health, especially appropriate for those countries that have reached the limits of economic growth. We test this idea on a dataset covering 140 countries and 2360 country-year observation between 1987 and 2008 and formulate hypotheses separately for countries with different level of economic development. We indeed found that countries with higher levels of income inequality also have lower levels of life expectancy (our measure of population health), and this result was consistent both in cross-sectional and longitudinal analyses. However, the relationship was found only among low- and middle-developed countries. In the group of high-developed countries, the relationship between income inequality and life expectancy was non-significant, which contradicts the literature. Expectations on the relationship between a country’s wealth and health were confirmed: economic growth does contribute to improving population health, but this effect is weaker in more economically developed countries. These results imply that a decrease in a country’s income inequality parallel with an increase in its wealth can help to improve health in economically lesser-developed countries, but not in high-developed countries.     

Losses of Expected Lifetime in the United States and Other Developed Countries: Methods and Empirical Analyses

Patterns of diversity in age at death are examined using e ^†, a dispersion measure that equals the average expected lifetime lost at death. We apply two methods for decomposing differences in e ^†. The first method estimates the contributions of average levels of mortality and mortality age structures. The second (and newly developed) method returns components produced by differences between age- and cause-specific mortality rates. The United States is close to England and Wales in mean life expectancy but has higher life expectancy losses and lacks mortality compression. The difference is determined by mortality age structures, whereas the role of mortality levels is minor. This is related to excess mortality at ages under 65 from various causes in the United States. Regression on 17 country-series suggests that e ^† correlates with income inequality across countries but not across time. This result can be attributed to dissimilarity between the age- and cause-of-death structures of temporal mortality reduction and intercountry mortality variation. It also suggests that factors affecting overall mortality decrease differ from those responsible for excess lifetime losses in the United States compared with other countries. The latter can be related to weaknesses of health system and other factors resulting in premature death from heart diseases, amenable causes, accidents and violence.     

Recent Perspectives on Active Life Expectancy for Older Women

SUMMARY

This article provides a critical review of recent active life expectancy literature, describing trends of special interest to women. We review findings from leading perspectives used to study life expectancy and active life expectancy, including gender, racial and socioeconomic differences, disease-specific effects, and biodemography. We examine three competing theories of population health that frame active life expectancy research—compression of morbidity, expansion of morbidity, and dynamic equilibrium—concluding there is support for both the compression of morbidity and dynamic equilibrium theories. Policy implications for women include a greater understanding of the role of education and racial and ethnic diversity in active life trends, and an increased public policy emphasis on prevention and treatment of chronic disease, together with adoption of more healthy lifestyles.     

中国高龄老人健康预期寿命研究

用隶属等级 (GradeofMembership ,GOM)模型将反映 1998年被访高龄老人不同健康维度的 5 0个变量进行综合得到健康、比较健康、功能受限、体弱多病、极度虚弱五个纯类。用这五个纯类将高龄老人预期寿命进行了分析     

The Cause-Deleted Index: Estimating Cause of Death Contributions to Mortality

Causes underlying mortality disparities are often determined by causal decomposition. This method is based on the decomposition of differences in mortality or life expectancy into parameters representing the contribution of underlying causes. It quantifies disparities as differences in mortality rates and does not account for the fact that many underprivileged groups are more likely to die from nearly all causes. Results are driven by the frequency of cause of death. Alternatively, the cause deleted index quantifies the role of underlying causes in mortality disparities as the change in the relative risk of dying that is related to deleting a specific cause. The consistency between the methods in estimating cause of death contributions is analyzed using 2000 U.S. mortality data and simulated mortality profiles. The two methods often produce divergent results because causal decomposition relies on the prevalence of causes of death.     

分年龄组死亡率变动对人均期望寿命影响的实验研究 ——以甘肃省为例

人均期望寿命是分析、评价人口健康状况,衡量社会经济发展及医疗卫生服务水平的重要指标。从2014年开始人均期望寿命的提高被纳入卫生计生系统考核内容,受到各级政府的重视。为了有效地甄别和评价政策实施对人均期望寿命提高的贡献程度,需要精确地估计和判断各年龄组死亡率变动对人均期望寿命提高的影响。在实践中,针对某一年龄组或某一特定人群死亡率的变动以及相关政策实施对人均期望寿命的影响鲜有较为精确的定量解答或快速有效的估算办法。本研究通过数据实验方法和计算机辅助计算建立一套可以较为精确地估算某一区域内某一年龄组死亡率变动对人均期望寿命影响的计算方法和结果集,利用这种方法可以开展不同类型、不同区域内人口死亡率变动对人均期望寿命影响的快速估算。利用估算结果可以对区域内政策实施效果进行较为科学的评估或评价。文章以中国2010年人口普查数据中甘肃省各年龄组分性别死亡率数据为基础对上述研究进行实证分析和验证。     

Differences in life expectancy by education and occupation in Italy, 1980-94: indirect estimates from maternal and paternal orphanhood

In the present study, we use the modified orphanhood method to analyse mortality differences by socio-economic status in Italy. This technique permits the indirect estimation of adult mortality from survey-based information on parents' survival in developed populations and helps to overcome several limitations of conventional studies on mortality differences by social class. We estimate a time series of life tables by education and occupation and analyse the differences in life expectancy by socio-economic status along with their changes between 1980-84, 1985-89, and 1990-94. Whereas mortality differences between the highest social class and the other socio-economic status groups increased among men, they decreased among women. We speculate about the reasons for these sex-specific trends and evaluate the application of indirect estimation techniques to the populations of developed countries.