scholarly journals The Linear Link: Deriving Age-Specific Death Rates from Life Expectancy

Risks ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 109
Author(s):  
Marius Pascariu ◽  
Ugofilippo Basellini ◽  
José Aburto ◽  
Vladimir Canudas-Romo
Keyword(s):  
Life Expectancy ◽  
R Package ◽  
Value Of Life ◽  
Life Tables ◽  
Human Longevity ◽  
Death Rates ◽  
New Model ◽  
Life Expectancy At Birth ◽  
Age Patterns ◽  
Full Life

The prediction of human longevity levels in the future by direct forecasting of life expectancy offers numerous advantages, compared to methods based on extrapolation of age-specific death rates. However, the reconstruction of accurate life tables starting from a given level of life expectancy at birth, or any other age, is not straightforward. Model life tables have been extensively used for estimating age patterns of mortality in poor-data countries. We propose a new model inspired by indirect estimation techniques applied in demography, which can be used to estimate full life tables at any point in time, based on a given value of life expectancy at birth. Our model relies on the existing high correlations between levels of life expectancy and death rates across ages. The methods presented in this paper are implemented in a publicly available R package.

A VARIED PATTERN OF CHANGE OF THE SEX DIFFERENTIAL IN SURVIVAL IN THE G7 COUNTRIES

2005 ◽  
Vol 38 (3) ◽  
pp. 391-401 ◽  
Author(s):  
FRANK TROVATO ◽  
NILS B. HEYEN
Keyword(s):  
Sex Differences ◽  
Life Expectancy ◽  
Point Of View ◽  
Industrialized Countries ◽  
Circulatory Disease ◽  
G7 Countries ◽  
Death Rates ◽  
The United Kingdom ◽  
Life Expectancy At Birth ◽  
The Difference

Over the course of the 20th century the sex differential in life expectancy at birth in the industrialized countries has widened considerably in favour of women. Starting in the early 1970s, the beginning of a reversal in the long-term pattern of this differential has been noted in some high-income countries. This study documents a sustained pattern of narrowing of this measure into the later part of the 1990s for six of the populations that comprise the G7 countries: Canada, France, Germany, Italy, England and Wales (as representative of the United Kingdom) and USA. For Japan, a persistence of widening sex differences in survival is noted. The sex differences in life expectancy are decomposed over roughly three decades (early 1970s to late 1990s) from the point of view of four major cause-of-death categories: circulatory diseases, cancers, accidents/violence/suicide, and ‘other’ (residual) causes. In the six countries where the sex gap has narrowed, this has resulted primarily from reduced sex differences in circulatory disease mortality, and secondarily from reduced differences in male and female death rates due to accidents, violence and suicide combined. In some of the countries sex differentials in cancer mortality have been converging lately, and this has also contributed to a narrowing of the difference in life expectancy. In Japan, males have been less successful in reducing their survival disadvantage in relation to Japanese women with regard to circulatory disease and cancer; and in the case of accidents/violence/suicide, male death rates increased during the 1990s. These trends explain the divergent pattern of the sex difference in life expectation in Japan as compared with the other G7 nations.

scholarly journals Life Expectancy in Germany Based on the 2011 Census: Was the Healthy Migrant Effect Merely an Artefact?

2016 ◽  
Vol 41 (2) ◽  
Author(s):  
Felix Zur Nieden ◽  
Bettina Sommer
Keyword(s):  
Life Expectancy ◽  
Life Table ◽  
Census Data ◽  
Population Data ◽  
Life Tables ◽  
German Population ◽  
Healthy Migrant Effect ◽  
Foreign Population ◽  
Life Expectancy At Birth ◽  
Do So

The Federal Statistical Office’s 2010/12 general life table is the first to provide results on life expectancy based on census data for reunified Germany. This article therefore examines the question of how the revisions of the population figures from the 2011 census affected the measured life expectancy. To do so, we analysed both the official life tables based on the old intercensal population updates before the census and those based on the population data from the 2011 census. The method used to calculate the census-adjusted 2010/12 general life table was also transferred to separate life tables drawn up for the German and the foreign population. In this way, findings on the so-called “healthy migrant effect” can be discussed, ruling out possible errors in the intercensal population updates. These errors had previously been cited as the main causes for a distinctly longer life expectancy among the foreign population compared with the German population. As expected, a census-based calculation for the total population and for the German population resulted in only minor revisions to the life expectancy figures. The use of the census results does, however, distinctly alter the life expectancy of foreign women and men. An advantage of over 5 years in life expectancy at birth, measured on the basis of the old population data, needs to be revised to about 2.9 years for men and 2.1 years for women based on the 2011 census. The healthy migrant effect therefore cannot be traced back solely to data artefacts from the old intercensal population updates – even with revised data, the foreign population shows marked survival advantages.

scholarly journals Demographic perspectives on the rise of longevity

2021 ◽  
Vol 118 (9) ◽  
pp. e2019536118
Author(s):  
James W. Vaupel ◽  
Francisco Villavicencio ◽  
Marie-Pier Bergeron-Boucher
Keyword(s):  
Life Expectancy ◽  
Demographic Data ◽  
Human Longevity ◽  
Considerable Uncertainty ◽  
Political Consequences ◽  
The Past ◽  
Life Expectancy At Birth ◽  
Estimate Life Expectancy ◽  
Substantial Progress ◽  
Length Of Life

This article reviews some key strands of demographic research on past trends in human longevity and explores possible future trends in life expectancy at birth. Demographic data on age-specific mortality are used to estimate life expectancy, and validated data on exceptional life spans are used to study the maximum length of life. In the countries doing best each year, life expectancy started to increase around 1840 at a pace of almost 2.5 y per decade. This trend has continued until the present. Contrary to classical evolutionary theories of senescence and contrary to the predictions of many experts, the frontier of survival is advancing to higher ages. Furthermore, individual life spans are becoming more equal, reducing inequalities, with octogenarians and nonagenarians accounting for most deaths in countries with the highest life expectancy. If the current pace of progress in life expectancy continues, most children born this millennium will celebrate their 100th birthday. Considerable uncertainty, however, clouds forecasts: Life expectancy and maximum life span might increase very little if at all, or longevity might rise much faster than in the past. Substantial progress has been made over the past three decades in deepening understanding of how long humans have lived and how long they might live. The social, economic, health, cultural, and political consequences of further increases in longevity are so significant that the development of more powerful methods of forecasting is a priority.

Analysis of Mortality Data due to Infectious Diseases: Life Table Methods Complementary to Direct Rates

1988 ◽  
Vol 27 (03) ◽  
pp. 137-141
Author(s):  
M. A. A. Moussa ◽  
M. M. Khogali ◽  
T. N. Sugathan
Keyword(s):  
Life Expectancy ◽  
Infectious Diseases ◽  
Life Table ◽  
Census Data ◽  
Total Mortality ◽  
Life Tables ◽  
Mortality Data ◽  
Men And Women ◽  
Male And Female ◽  
Life Expectancy At Birth

SummaryLife table methods are employed complementary to standard rates to analyse Kuwaiti mortality data due to infectious diseases. The procedure comprises total mortality, multiple-decrement, cause—elimination and cause—delay life tables. To improve reliability of estimated age-specific death rates, the numerator was based on the three-year average of deaths (1981-83), while the denominator was the mid 1982 population projected from the 1980 and 1985 population censuses. To overcome the difficulty of age heaping, both mortality and census data were graduated using the natural cubic spline approach. Proportional mortality was maximum in intestinal infectious diseases particularly in the rural Jahra Governorate. Infectious diseases caused 29.4 and 37.1% of male and female deaths respectively in infancy and early childhood. The male and female life expectancy at birth were 67 and 72 years, respectively.The multiple-decrement life tables showed that 3,346 men and 2,986 women out of the birth cohort (100,000) will ultimately die from infectious diseases. The average number of years lost due to infectious diseases were 0.75 years in both men and women. Relating this loss to the affected (saved) subpopulation only, large gains in life expectancy occur (22.3 and 25.2 years in men and women respectively).

scholarly journals Life expectancy at birth and life disparity: an assessment of sex differentials in mortality in India

2016 ◽  
Vol 2 ◽  
Author(s):  
Akansha Singh ◽  
Laishram Ladusingh
Keyword(s):  
Life Expectancy ◽  
Rural Areas ◽  
Urban Areas ◽  
Average Length ◽  
Adult Mortality ◽  
Life Tables ◽  
Life Expectancy At Birth ◽  
Replacement Algorithm ◽  
Sex Differentials ◽  
Length Of Life

This study aims to examine the sex differentials in life expectancy at birth and life disparity, and to estimate the age-specific contribution of the differences for India and its major states. Life dispari-ty measures the variation in the distribution of deaths, and life expectancy at birth measures the average length of life. Complete life tables generated from death rates and abridged life tables of the Sample Reg-istration System in India from 1970–1975 to 2006–2010 were used to fulfill the research goals. Stepwise replacement algorithm was used for the decomposition of sex differences in life expectancy at birth and in life disparity. The results indicate that the increase in life expectancy at birth and decline in life disparity was higher for females. The sex differential was more prominent in urban areas than in rural areas. A ma-jority of the states in India experienced changes in the direction and magnitude of sex differentials in life expectancy at birth and life disparity from 1970–1975 to 2006–2010. The sex differentials in life expec-tancy at birth and life disparity in 1970–1975 were primarily attributed to child mortality, whereas the sex differentials in recent decades were attributed to adult mortality.

scholarly journals Abridged Life Tables for Registered Indians in Canada, 1976-1980 to 1996-2000

2004 ◽  
Vol 31 (2) ◽  
pp. 197
Author(s):  
Ravi V. P. Verma ◽  
Margaret Michalowski ◽  
R. Pierre Gauvin
Keyword(s):  
Life Expectancy ◽  
Regional Variation ◽  
Life Tables ◽  
Eastern Region ◽  
Confidence Limits ◽  
East Atlantic ◽  
Life Expectancy At Birth ◽  
Canadian Population ◽  
Males And Females ◽  
Government Of Canada

This paper presents the analyses of the new estimates of abridged life tables comprising life expectancy at birth, and their estimates of variance and confidence limits by males and females for Registered Indians in Canada and two broad regions (East: Atlantic, Quebec, Ontario, and Manitoba; and West: Saskatchewan, Alberta, British Columbia, Yukon and Northwest Territories) for the periods, 1976-80, 1981-1985, 1986-1990, 1991-1995 and 1996-2000. The life tables were constructed using the Chiang Method based on the adjusted data on deaths and population by age and sex from the Indian Registry, maintained by the Department of Indian Affairs and Northern Development, Government of Canada. The data on the register are subjected to late reported and non reported vital events. At the Canada level, life expectancy at birth for Registered Indian males was 59.9 years in 1976-1980, rising to 68.3 years in 1996-2000. For females, the life expectancy at birth was relatively higher, 66.6 years in 1976-80, and 74.5 years in 1996-2000. The recent life expectancies at birth for Registered Indians are comparable to those observed for the total Canadian male and female populations during the period 1960-1962 at 68.4 and 74.3 years. In 1999, life expectancy at birth for the total Canadian population was reported to be 76.3 years for males and 81.7 years for females. The life expectancy at birth for the Registered Indians in the Eastern region was higher than for those in the Western region. The pattern of regional variation in life expectancy at birth for this population seems to be the reverse of the regional variation for the total Canadian population.

scholarly journals A precise measure of the impact of the first wave of Covid-19 on life expectancy. Regional differentials in Switzerland

2020 ◽  
Author(s):  
Philippe Wanner
Keyword(s):  
Life Expectancy ◽  
Sharp Decrease ◽  
Life Tables ◽  
Average Life ◽  
Average Life Expectancy ◽  
Life Expectancy At Birth ◽  
Precise Measure ◽  
The One ◽  
Health Situation ◽  
The Impact

AbstractBased on publicly available data supplied by the Swiss Federal Statistical Office (FSO), we calculated life tables by sex and by week for seven major regions of Switzerland in 2020, up to October 26th. These life tables provide information on the trends of life expectancy at birth and at the age of 65 years during the first wave of the coronavirus disease 2019 (COVID-19) epidemic.The results show a strong cyclical decrease in life expectancy, particularly in Ticino, where this variable has decreased by almost 6 years compared to the 2019 life expectancy, and in the Lake Geneva region. The other regions of Switzerland observed more modest decreases during the first wave, generally not exceeding a 2-year reduction. This decrease can be explained to some extent by seasonal variations in this indicator.In conclusion, the very sharp decrease in the average lifespan observed in the two regions mentioned above suggests that the first wave of the epidemic had a significant impact. It also reflects an unfavourable health situation. The life expectancy at the age of 65 years observed at the end of March 2020 in Ticino corresponded to the average life expectancy observed in Switzerland forty years ago.The calculated indicators have the advantage of accounting for the age structures of the respective populations. They therefore demonstrate their usefulness in monitoring during a pandemic, such as the one occurring currently.

scholarly journals A new model for estimating district life expectancy at birth in India, with special reference to Assam state

2014 ◽  
Vol 41 (1-2) ◽  
pp. 180
Author(s):  
Rajan Sarma ◽  
Labananda Choudhury
Keyword(s):  
Life Expectancy ◽  
South Asian ◽  
Census Data ◽  
Life Tables ◽  
Important Indicator ◽  
Registration System ◽  
Life Expectancy At Birth ◽  
Sample Registration System ◽  
Using Data ◽  
The Relationship

Life expectancy at birth (e0) is considered as an important indicator of the mortality level of a population. In India, direct estimation of e0 is not possible due to incomplete death registration. The Sample Registration System (SRS) of India provides information on e0 only for the 16 major states. Estimates of e0 for the districts are not available. Using data from the Coale-Demeny West model life tables, United Nations South Asian model life tables, and SRS life tables of India and its major states, the paper shows that the relationship between life expectancy at age one (e0) and the probability of surviving to age one (l1) is linear, and the relationship between e0 and l1 is quadratic. From the quadratic relationship between e0 and l1, an attempt is made to estimate e0 for some selected districts of India for 2001 and 2010, using estimated l1 from 2001 census data and Annual Health Survey (2010–11) data.

scholarly journals The life table paradox: has Brazil already overcome it?

2021 ◽  
Vol 38 ◽  
pp. 1-23
Author(s):  
Filipe Costa de Souza
Keyword(s):  
Infant Mortality ◽  
Life Expectancy ◽  
Life Table ◽  
National Level ◽  
Decomposition Analysis ◽  
Life Tables ◽  
Total Change ◽  
Life Expectancy At Birth ◽  
The Difference ◽  
Over Time

Ideally, life expectancy should be a decreasing function of age. When this fact is not observed, this situation is known as the life table paradox. This paper investigated the timing (and health metrics at the time) in which Brazil and its Federation Units (FU) overcame (or are expected to overcome) this paradox. The data were gathered from the Brazilian Institute of Geography and Statistics and contained 3,416 sex-specific abridged life tables, from 2000 to 2060. At national level, females and males overcame the paradox in 2016 and 2018, respectively. However, when the FU were examined separately, much heterogeneity was observed. Through the decomposition analysis of the change over time in the difference between life expectancy at birth and at age one, we found that Brazil and most of its FU are expected to have both changes declining over time and the total change is expected to be decreasing and greater than zero. Nevertheless, for some Northeastern states the total change is expected to pass from a positive to a negative value; and for two Northern states the total change is expected to be neither decreasing nor increasing. In a public planning perspective, we understand that achieving balancing in the life tables is a goal to be pursued, especially because having an imbalanced table means that life expectancy at birth is still strongly influenced by high levels of infant mortality. Therefore, this knowledge could help planners to properly define strategies to accelerate the balancing process and revert unequal scenarios.

scholarly journals On Mathematical Equalities and Inequalities in the Life Table: Something Old and Something New

2021 ◽  
Author(s):  
David A. Swanson ◽  
Lucky M. Tedrow
Keyword(s):  
Life Expectancy ◽  
Life Table ◽  
Life Tables ◽  
Entire Population ◽  
Maximum Lifespan ◽  
Life Expectancy At Birth ◽  
Inequality Theorem ◽  
New Inequalities

AbstractThis paper discusses known mathematical equalities and inequalities found within life tables and proceeds to identify two new inequalities. The first (theorem 1) is that at any given age x, the sum of mean years lived and mean years remaining exceeds life expectancy at birth when age is greater than zero and less than the maximum lifespan. The second inequality (theorem 2) applies to the entire population and shows that the sum of mean years lived and mean years remaining exceeds life expectancy at birth. Illustrations of the two inequalities are provided as well as a discussion.

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