A Test of Paleodemographic Models

1978 ◽  
Vol 43 (4) ◽  
pp. 715-729 ◽  
Author(s):  
Roberta L. Hall
Keyword(s):  
Population Structure ◽  
Life Expectancy ◽  
Life Table ◽  
Structure Data ◽  
Age Structure ◽  
Census Data ◽  
Research Tool ◽  
Aged Sample ◽  
Demographic Processes ◽  
Archaeological Reconstruction

AbstractPaleodemography is a useful adjunct to archaeological reconstruction, but as a research tool it is relatively new and requires further study. This paper reports on a project in which the life-table method of modeling demographic processes, based on a sexed and aged sample from the community ossuary, was tested against census records of the population structure. Data were taken from cemetery headstones in a township in central Indiana, spanning the period from its first settlement by Euroamerican farmers in 1830 through 1972. Life-expectancy estimates produced from the life tables were essentially identical to those produced from federal census data. Paleodemographic models of population structure were statistically different from census tabulations but were similar in form, representing a "smoothed" estimate of age structure.

scholarly journals Population Age Structure, Complex Socio-Demographic Systems and Resilience Potential: A Spatio-Temporal, Evenness-Based Approach

2019 ◽  
Vol 11 (7) ◽  
pp. 2050 ◽  
Author(s):  
Massimo Cecchini ◽  
Sirio Cividino ◽  
Rosario Turco ◽  
Luca Salvati
Keyword(s):  
Population Structure ◽  
Age Structure ◽  
Census Data ◽  
Principal Component ◽  
System Thinking ◽  
Italian Population ◽  
Comprehensive Overview ◽  
Population Age Structure ◽  
Evenness Index ◽  
Over Time

The present study illustrates an original approach grounded on entropy theory and complex system thinking with the aim to investigate changes over time and space in population structure by age in Italy, in light of socioeconomic resilience and post-crisis recovery potential. Assuming that population structure may reflect different levels of resilience to exogenous shocks, a Pielou J evenness index was calculated on census data made available every 10 years (1861–2011) with the aim to identify compositional homogeneity (or heterogeneity) in the age structure of the Italian population. Trends over time in the Pielou J evenness index were identified using descriptive statistics, comparison with ancillary demographic indicators and multivariate exploratory techniques including principal component analysis. The empirical results allowed the identification of multiple dimensions of demographic transition in Italy, distinguishing two phases, the former encompassing a relatively long time period between 1861 and 1936, and the latter covering a shorter period between 1936 and 2011. A spatially-explicit analysis of Pielou J evenness indices applied to the population age structure of each Italian municipality at the latest survey (2017) finally provided a comprehensive overview of the demographic characteristics likely influencing the resilience potential of local districts. The empirical evidence outlined the consolidation of a coastal–inland divide as a result of the complex linkage between demographic dynamics and local background contexts.

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 Impact of Pregnancy-Related Deaths on Female Life Expectancy in Zambia: Application of Life Table Techniques to Census Data

PLoS ONE ◽  
2015 ◽  
Vol 10 (10) ◽  
pp. e0141689 ◽  
Author(s):  
Richard Banda ◽  
Ingvild Fossgard Sandøy ◽  
Knut Fylkesnes ◽  
Fanny Janssen
Keyword(s):  
Life Expectancy ◽  
Life Table ◽  
Census Data ◽  
Female Life Expectancy

Age structure, survivorship and life expectancy for future in Murree forests

2020 ◽  
Vol 53 (3) ◽  
Author(s):  
Afsheen Khan ◽  
S. Shahid Shaukat ◽  
Moinuddin Ahmed
Keyword(s):  
Life Expectancy ◽  
Age Structure

scholarly journals A Study of Aging Population and Central Provident Fund System in Macao

2018 ◽  
Vol 8 (1) ◽  
pp. 40
Author(s):  
Tang, Tang, Kai Hong
Keyword(s):  
Population Structure ◽  
Life Expectancy ◽  
Aging Population ◽  
Fertility Rate ◽  
Dependency Ratio ◽  
Special Administrative Region ◽  
Administrative Region ◽  
General Rules ◽  
The Government ◽  
Provident Fund

The world's overall fertility rate is declining while the life expectancy is increasing, the population structure is aging, the dependency ratio in Macao will steadily increase to 38.6% at the end of 2031. The median age of Macao is rising from Aged 38.1 to 45.5 during the period of 2011 to 2031. In this view, Macao becomes the aging society.In order to establish a basis for the establishment of a central provident fund system, the Macao SAR Government implemented the central savings system in 2009 through the General Rules for the Establishment and Management of Individual Accounts of the Central Savings System through Administrative Regulation No. 31/2009 to allocate funds for eligible account holders, Subsequently, the Government of the Macau Special Administrative Region (SAR) promulgated the Act "Non-mandatory Central Provident Fund System".

scholarly journals Decomposing Indigenous life expectancy gap by risk factors: a life table analysis

2013 ◽  
Vol 11 (1) ◽  
Author(s):  
Yuejen Zhao ◽  
Jo Wright ◽  
Stephen Begg ◽  
Steven Guthridge
Keyword(s):  
Risk Factors ◽  
Life Expectancy ◽  
Life Table ◽  
Life Table Analysis ◽  
Table Analysis

scholarly journals Life expectancy and disparity: an international comparison of life table data

BMJ Open ◽  
2011 ◽  
Vol 1 (1) ◽  
pp. e000128-e000128 ◽  
Author(s):  
J. W. Vaupel ◽  
Z. Zhang ◽  
A. A. van Raalte
Keyword(s):  
Life Expectancy ◽  
Life Table ◽  
International Comparison ◽  
Life Table Data ◽  
Table Data

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.

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