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.

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.

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 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 Potential gain in life expectancy by gender after elimination of a specific cause of death in urban India

2020 ◽  
Vol 7 (5) ◽  
pp. 1848
Author(s):  
Bal Kishan Gulati ◽  
Damodar Sahu ◽  
Anil Kumar ◽  
M. V. Vardhana Rao
Keyword(s):  
Life Expectancy ◽  
Life Table ◽  
Cause Of Death ◽  
Metabolic Diseases ◽  
Circulatory System ◽  
Average Life Span ◽  
Maximum Gain ◽  
Life Expectancy At Birth ◽  
Potential Gain ◽  
Urban India

Background: Life expectancy is a statistical measure to depict average life span a person is expected to live at a given age under given age-specific mortality rates. Cause-elimination life table measures potential gain in life expectancy after elimination of a specific disease. The present study aims to estimate potential gain in life expectancy by gender in urban India after complete and partial elimination of ten leading causes of deaths using secondary data of medical certification of cause of death (MCCD) for the year 2015.Methods: Life table method was used for estimating potential gain after eliminating diseases to the tune of 25%, 50%, 75% and 100%.Results: Maximum gain in life expectancy at birth estimated from complete elimination of diseases of the circulatory system (11.1 years in males versus 13.1 years in females); followed by certain infectious and parasitic diseases (2.2  versus 2.1 years); diseases of the respiratory system (2.2 versus 2.1); injury, poisoning and certain other consequences of external causes (1.1 versus 0.7); neoplasms (0.9 versus 1.0); endocrine, nutritional and metabolic diseases (0.8 versus 0.9); diseases of the digestive system (0.8 versus 0.4); diseases of the genitourinary system (0.6 versus 0.6); diseases of the nervous system (0.4 versus 0.4); and diseases of blood & blood forming organs and certain disorders involving the immune mechanism (0.2 versus 0.3 years).Conclusions: Elimination of the circulatory diseases resulted into maximum gain in life expectancy. These findings may have implications in setting up health goals, allocating resources and launching tailor-made health programmes.

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.

scholarly journals Life Table Analysis of a Small Sample of Santal Population Living in a Rural Locality of West Bengal, India

2014 ◽  
Vol 77 (2) ◽  
pp. 233-248
Author(s):  
Arupendra Mozumdar ◽  
Bhubon Mohan Das ◽  
Subrata K. Roy
Keyword(s):  
Life Expectancy ◽  
Life Table ◽  
West Bengal ◽  
Small Sample ◽  
Optimum Number ◽  
Small Populations ◽  
Marginal Populations ◽  
Acceptable Error ◽  
Closed Population ◽  
Life Expectancy At Birth

Abstract Life table calculation of small populations, especially of marginal populations, is difficult due to a small number of death records and lack of a systematic birth and death registry. The present study aimed to calculate a life table of a small sample of Santal population from Beliatore area of the Bankura district, West Bengal, India, using the recall method. The data on birth and death events were collected using house-to-house interviewing and cross-checking the data with reference to the significant events of the area and the family. The life table was calculated from age specific death rate of a closed population retrospectively estimated for 10 years. The calculated life expectancy at birth of the study population was 63.9 years with a standard error of 3.15 years. The finding agrees with the life expectancy of the other larger populations of the region, although calculated using conventional methods. The method needs to be evaluated to get the optimum number of death events required for calculating the life table with an acceptable error level. The study will be helpful for comparisons of overall health status of small populations with respect to time and space.

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.

Chapter 8: Examination of the Model Life Table Series

1973 ◽  
Vol 27 ◽  
pp. 42-47
Author(s):  
Kenneth M. Weiss
Keyword(s):  
Life Expectancy ◽  
Life Table ◽  
Life Tables ◽  
Model Life Table ◽  
Comparative Data ◽  
Raw Data ◽  
Human Mortality ◽  
Comprehensive Study

The model life tables should be compared to various data to illustrate their applicability. The comparative data should be independent of the populations used in the construction of the tables so that they can serve as controls for the models.Russell (1958) carried out a comprehensive study of human mortality in late ancient and medieval times. The life table material in his work derives from ungraduated and unsmoothed raw data in the Corpus Inscriptionum Latinarum which lists tombstone inscriptions from ancient Roman areas. These data, together with some medieval British life expectancies also from Russell, are summarized in Tables 13 through 15. The mortality and life expectancy values closely approximate in range and pattern the values in our model life table series.

scholarly journals Imbalance in Life Table: Effect of Infant Mortality on Lower Life Expectancy at Birth

2013 ◽  
Vol 5 (3) ◽  
pp. 479-488 ◽  
Author(s):  
A. M. Fazle Rabbi
Keyword(s):  
Developing Countries ◽  
Infant Mortality ◽  
Life Expectancy ◽  
Life Table ◽  
Surveillance System ◽  
Mortality Rates ◽  
Demographic Surveillance System ◽  
Infant Mortality Rate ◽  
Life Expectancy At Birth ◽  
Infant And Child Mortality

Life expectancy at birth is a well-known demographic measure of population longevity. Rationally, life expectancy at birth should be higher than life expectancy at any particular age. However, historically, lower life expectancy at birth is observed than that of age one, which diminishes the feature of life expectancy at birth as a prominent indicator of longevity. High infant and child mortality rates result in lower values of life expectancy at birth than at older ages. This imbalance in life table disappears only when the crossover occurs and it happens when the inverse of the infant mortality becomes equal to the life expectancy at age one. For Matlab Health and Demographic surveillance system of Bangladesh, life expectancy at age one is still higher than life expectancy at birth. Required infant mortality rate to achieve crossover suggests further decline in infant mortality for Matlab HDSS to attain crossover of life expectancy at birth and age one. Keywords: Life expectancies; Developing countries; Imbalance; Life table.  © 2013 JSR Publications. ISSN: 2070-0237 (Print); 2070-0245 (Online). All rights reserved.  doi: http://dx.doi.org/10.3329/jsr.v5i3.14105 J. Sci. Res. 5 (3), 479-488 (2013)

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.

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