Life expectancy

We give simple upper and lower bounds on life expectancy. In a life-table population, if e(0) is the life expectancy at birth, M is the median length of life, and e(M) is the expected remaining life at age M, then (M+e(M))/2≤e(0)≤M+e(M)/2. In general, for any age x, if e(x) is the expected remaining life at age x, and ℓ(x) is the fraction of a cohort surviving to age x at least, then (x+e(x))≤l(x)≤e(0)≤x+l(x)∙e(x). For any two ages 0≤w≤x≤ω, (x-w+e(x))∙ℓ(x)/ℓ(w)≤e(w)≤x-w+e(x)∙ℓ(x)/ℓ(w) . These inequalities give bounds on e(0) without detailed knowledge of the course of mortality prior to age x, provided ℓ(x) can be estimated. Such bounds could be useful for estimating life expectancy where the input of eggs or neonates can be estimated but mortality cannot be observed before late juvenile or early adult ages.inequalities, life expectancy, life table, stationary population

A Panel Data Study of the Determinants of Life Expectancy in Low Income Countries

This study attempts to determine the impact of several socioeconomic determinants of life expectancy for 34 low income countries using ordinary least squares linear regression. Most explanatory variables were statistically significant, implying that the socioeconomic variables of interest, including government health expenditures, access to basic sanitation facilities, HIV prevalence, urbanization, education, and sex, are important measures in influencing life expectancy. Foreign aid, corruption, and undernourishment, were determined insignificant when determining life expectancy. Based on the analysis results, it has been suggested that these developing countries implement appropriate policies and programs to increase HIV education and preventative measures, increase women’s rights and labor force participation, and specifically direct foreign aid inflows, in order to increase the life expectancy of people in the country

On the correspondence between CAL and lagged cohort life expectancy

It has been established that under certain mortality assumptions, the current value of the Cross-sectional Average length of Life (CAL) is equal to the life expectancy for the cohort currently reaching its life expectancy. This correspondence is important, because the life expectancy for the cohort currently reaching its life expectancy, or lagged cohort life expectancy (LCLE), has been discussed in the tempo literature as a summary mortality measure of substantive interest. In this paper, we build on previous work by evaluating the extent to which the correspondence holds in actual populations. We also discuss the implications of the CAL-LCLE correspondence (or lack thereof) for using CAL as a measure of cohort life expectancy, and for understanding the connection between CAL, LCLE, and underlying period mortality conditions.cohort mortality, life expectancy, mortality measures, tempo effects

Life-Expectancy Disparities Among Adults With HIV in the United States and Canada: The Impact of a Reduction in Drug- and Alcohol-Related Deaths Using the Lives Saved Simulation Model.

Improvements in life expectancy among people living with human immunodeficiency virus (PLWH) receiving antiretroviral treatment in the United States and Canada might differ among key populations. Given the difference in substance use among key populations and the current opioid epidemic, drug- and alcohol-related deaths might be contributing to the disparities in life expectancy. We sought to estimate life expectancy at age 20 years in key populations (and their comparison groups) in 3 time periods (2004-2007, 2008-2011, and 2012-2015) and the potential increase in expected life expectancy with a simulated 20% reduction in drug- and alcohol-related deaths using the novel Lives Saved Simulation model. Among 92,289 PLWH, life expectancy increased in all key populations and comparison groups from 2004-2007 to 2012-2015. Disparities in survival of approximately a decade persisted among black versus white men who have sex with men and people with (vs. without) a history of injection drug use. A 20% reduction in drug- and alcohol-related mortality would have the greatest life-expectancy benefit for black men who have sex with men, white women, and people with a history of injection drug use. Our findings suggest that preventing drug- and alcohol-related deaths among PLWH could narrow disparities in life expectancy among some key populations, but other causes of death must be addressed to further narrow the disparities

Linking period and cohort life-expectancy linear increases in Gompertz proportional hazards models

In a Gompertz mortality model with constant yearly improvements at all ages, linear increases in period life expectancy correspond to linear increases in the respective cohort life expectancy. The link between the two measures can be given by a simple approximate relationship.cohort life expectancy, Gompertz mortality, Linear Shift Models, period life expectancy

The Growing Gap in Life Expectancy by Income: Recent Evidence and Implications for the Social Security Retirement Age

[Excerpt] This report provides a brief overview of the concept of life expectancy, how it is measured, and how it has changed over time in the United States. While life expectancy may be studied in a variety of contexts, this report focuses on the link between life expectancy and SES, as measured by lifetime income. In particular, this report synthesizes recent research on (1) the life expectancy gap by income and (2) the relationship between this gap and Social Security benefits. Finally, this report discusses the implications of this research for one type of Social Security reform proposal: increasing the Social Security retirement age

Life Expectancy and Economic Growth: The Role of the Demographic Transition

In this paper we investigate the causal effect of life expectancy on economic growth by explicitly accounting for the role of the demographic transition. In addition to focusing on issues of empirical identification, this paper emphasizes the role of the econometric specification. We present a simple theory of the economic and demographic transition where individuals' education and fertility decisions depend on their life expectancy. The theory predicts that before the demographic transition improvements in life expectancy primarily increase population. Improvements in life expectancy do, however, reduce population growth and foster human capital accumulation after the onset of the demographic transition. This implies that the effect of life expectancy on population, human capital and income per capita is not the same before and after the demographic transition. Moreover, a sufficiently high life expectancy is ultimately the trigger of the transition to sustained income growth. We provide evidence supporting these predictions using data on exogenous mortality reductions in the context of the epidemiological revolution.life expectancy, demographic transition, epidemiological revolution, heterogeneous treatment effects

Disease and Development: The Effect of Life Expectancy on Economic Growth

What is the effect of increasing life expectancy on economic growth? To answer this question, we exploit the international epidemiological transition, the wave of international health innovations and improvements that began in the 1940s. We obtain estimates of mortality by disease before the 1940s from the League of Nations and national public health sources. Using these data, we construct an instrument for changes in life expectancy, referred to as predicted mortality, which is based on the pre-intervention distribution of mortality from various diseases around the world and dates of global interventions. We document that predicted mortality has a large and robust effect on changes in life expectancy starting in 1940, but no effect on changes in life expectancy before the interventions. The instrumented changes in life expectancy have a large effect on population; a 1% increase in life expectancy leads to an increase in population of about 1.5%. Life expectancy has a much smaller effect on total GDP both initially and over a 40-year horizon, however. Consequently, there is no evidence that the large exogenous increase in life expectancy led to a significant increase in per capita economic growth. These results confirm that global efforts to combat poor health conditions in less developed countries can be highly effective, but also shed doubt on claims that unfavorable health conditions are the root cause of the poverty of some nations.

A Causal Analysis of Life Expectancy at Birth. Evidence from Spain

Background: From a causal point of view, there exists a set of socioeconomic indicators concerning life expectancy. The objective of this paper is to determine the indicators which exhibit a relation of causality with life expectancy at birth. Methods: Our analysis applies the Granger causality test, more specifically its version by Dumitrescu–Hurlin, starting from the information concerning life expectancy at birth and a set of socioeconomic variables corresponding to 17 Spanish regions, throughout the period 2006–2016. To do this, we used the panel data involving the information provided by the Spanish Ministry of Health, Consumer Affairs and Social Welfare (MHCSW) and the National Institute of Statistics (NIS). Results: Per capita income, and the rate of hospital beds, medical staff and nurses Granger-cause the variable “life expectancy at birth”, according to the Granger causality test applied to panel data (Dumitrescu–Hurlin’s version). Conclusions: Life expectancy at birth has become one of the main indicators able to measure the performance of a country’s health system. This analysis facilitates the identification of those factors which exhibit a unidirectional Granger-causality relationship with life expectancy at birth. Therefore, this paper provides useful information for the management of public health resources from the point of view of the maximization of social benefits