Presentation for Session VI.

Slides:



Advertisements
Similar presentations
June 23, 2003AVW International Mortality Comparisons Richard MacMinn Richard MacMinn Edmondson-Miller Chair Katie School College of Business Illinois.
Advertisements

The Demographic Transition Model (DTM) Mr Elliott SSOT.
1 POPULATION PROJECTIONS Session 6 - Introduction to population projections Ben Jarabi Population Studies & Research Institute University of Nairobi.
© Cancer Research UK 2003 Registered charity number Leukaemia The statistics in this presentation are based on the Leukaemia CancerStats report.
KNOMAD, Migration Seminar New York, April World Population Prospects: an overview of the migration component François Pelletier United Nations.
Global Population Aging
The Leslie model and the population stability: an application 3-rd International Symposium Shaping Europe 2020: socio – economic challenges Bucharest,
Life expectancies at birth (e 0 ) and at age one (e 1 ) are the same when they are equal to the inverse of the infant mortality death rate, or age- specific.
Chapter 2 Key Issue 3 Why Is Population Increasing at Different Rates in Different Countries?
Module 12: Advanced Session on using the RAP ILO, 2013.
Using Mortality to Compare the Health of Populations by James W. Vaupel Max Planck Institute for Demographic Research, Rostock, Germany, University of.
Abcd AGEING POPULATION - Burden or Benefit? Demographic Trends Adrian Gallop Edinburgh 21 January 2002.
1 Mortality Compression and Longevity Risk Jack C. Yue National Chengchi Univ. Sept. 26, 2009.
Sub-regional Workshop on Census Data Evaluation, Phnom Penh, Cambodia, November 2011 Evaluation of Census Data using Consecutive Censuses United.
Reconstruction of Populations by Age, Sex and Level of Educational Attainment for 120 Countries for Using Demographic Back-Projection Methods.
Draft version. Do not cite without permission of the authors. First World Congress on Men’s Health Vienna 2-4 November 2001 Men’s health in Central and.
The SAINT mortality model: theory and application Quant Congress USA New York, 9 July 2008 Tryk Alt+F8 og Afspil auto_open for at vise værktøjslinien til.
School of Geography FACULTY OF ENVIRONMENT ESRC Research Award RES What happens when international migrants settle? Ethnic group population.
2014-based National Population Projections Paul Vickers Office for National Statistics 2 December 2015.
Measuring the population: importance of demographic indicators for gender analysis Workshop Title Location and Date.
Length of life and the pensions of five million retired German men by Vladimir M. Shkolnikov, Rembrandt Scholz, Dmitri A. Jdanov, Michael Stegmann, and.
Standardisation Alexander Ives Public Health England, South West.
EXPOSURE TO TOBACCO SMOKE IN THE EUROPEAN UNION 2nd Working Meeting on Adult Premature Mortality in the European Union October 2006, Warsaw, Poland.
Population Pyramids. POPULATION STRUCTURE The population pyramid displays the age and sex structure of a country or given area Population in Five Year.
The swedish research barometer 2016
Unconventional Approaches to Mortality Estimation
John Jerrim UCL Institute of Education
Health Indicators.
Mortality: The Life Table Its Construction and Applications
Data Quality Issues and Adjustments in the Human Mortality Database
Population Ageing a Great Challenge for Former Eastern Europe
Human Mortality over Age, Time, Sex, and Place The First HMD Symposium
Demographic Analysis Migration: Estimation Using Residual Methods -
Demographic Analysis Age and Sex Structure The Population Pyramid as an Historical Record and a Tool for Demographic Analysis.
Workshop on Demographic Analysis
Mortality Amenable to Health Care, 2004 and 2014
A Multi-State Generalization of the HMD Methodology, Applied to Fertility by Parity in the United States, John R. Wilmoth Department of Demography.
Italy - Evidence package
Comparative Quality of Mortality Data Derived from Official Statistics, for both Historical and Contemporary Populations John Wilmoth, Danzhen You, and.
Association between GDP and old-age mortality in seven European countries, A life-course perspective F.Janssen, A.E.Kunst, J.P.Mackenbach Department.
Why is the Global Population Increasing?
Chapter 2 Key Issue 3 Why Is Population Increasing at Different Rates in Different Countries?
The lowest mortalities
Lung cancer prevalence on the rise (Nov. 2014)
POPULATION PROJECTIONS
Introduction to Population Pyramids
Census and forecast, Mexico from 1940 to 2050.
Estimating mortality from defective data
LIFE EXPECTANCY DECOMPOSITION IN SPAIN
Difference in life expectancy between sexes. Why is it reducing?
Unit 2: Population (Part V) Population pyramids
Mortality of Supercentenarians: Does It Grow with Age?
WEIGHTING SUB-POPULATIONS IN MORTALITY LONGEVITY RESEARCH: A PRACTICAL APPROACH     Adam Szulc Institute of Statistics and Demography Warsaw School of.
Key Issues Where is the world population distributed? Why is global population increasing? Why does population growth vary among regions? Why do some regions.
Mortality Patterns at Advanced Ages
Demographic Analysis and Evaluation
All-time low period fertility in Finland: tempo or quantum effect?
Demographic Analysis and Evaluation
Overview of Census Evaluation and Selected Methods Pres. 2
Age and Sex structure.
Overview of Census Evaluation through Demographic Analysis Pres. 3
NORC at The University of Chicago
Overview of Census Evaluation and Selected Methods Pres. 2
Conflicting of interest disclosure: None
NORC at The University of Chicago
Chapter 2 Key Issue 3 Why Is Population Increasing at Different Rates in Different Countries?
Sickness absence as an indicator of health?
Includes data from the Welsh Cancer Intelligence and Surveillance Unit
Mortality Patterns at Advanced Ages
Alternatives for updating AEQ analysis and prioritizing data needs
Presentation transcript:

Presentation for Session VI. Human Mortality over Age, Time, Sex, and Place. The First HMD Symposium. June 18-19, 2004. Rostock, Germany. Presentation for Session VI. Official population statistics and re-estimation of old age populations of European countries with the Human Mortality Database Dmitry Jdanov, Rembradt Scholz and Vladimir Shkolnikov Max Planck Institute for Demographic Research

Importance of precise estimates of old-age populations. Increase in absolute numbers and proportions of men and women aged 80+ and 90+ for the total population of Denmark, E&W, Finland, France, West Germany, Hungary, Netherlands, Norway, Sweden, and Switzerland. Importance of precise estimates of old-age populations. 2

HMD is an unusual database HMD is an unusual database. Population estimates at ages over 80 have to be recalculated after each update from newly obtained population at the beginning of the last available year and deaths. Following V.Kannisto we rely on the extinct cohorts method. It assumes that there is no international migration at ages over 80 and that data on deaths and ages at death are precise. The basic idea is that at old ages quality of death data is better than quality of population estimates. Extinct cohort method returns reliable estimates of survivors to old ages (Thatcher, 1992, 2001, Kannisto, 1988, 1994, Hill et al., 2000). 3

Age w B C 90 A 80 Time About tn - 15 tn tn - 10 HMD Methods Protocol: Regions for application of different procedures for re-estimating of populations on the Lexis map. A-official population estimates; w -age of extinction (about 103-105) B-extinct cohort method; tn-beginning of the last available year C-survival ratio+extinct cohort methods tn Time 80 90 w B C A Age tn - 10 About tn - 15 4

W- Age of extinction is the youngest age, such that during the last five calendar years mean death number at ages beyond this age does not exceed 1/2. For populations of modern developed countries this age is usually about 103-105 years. B: Extinct cohort method. For extinct cohorts, older than age W, there are no people alive in the last available year and their population over ages can be estimated by a diagonal summing of deaths. C: If population at the beginning of the last year is available for an open ended age interval (e.g. 90+, 95+, or 100+), we apply the survivor ratio method to estimate population by single ages over age 90. This method assumes that 5-year survival in a cohort in question is the same as the average survival of five previous cohorts. After obtaining the last year population by single age group, the extinct cohort method can be applied. 5

Illustration of the extinction rule from the HMD Methods Protocol by John Wilmoth et al. 6

Illustration of the survivor ratio method from the HMD Methods Protocol by John Wilmoth et al. 7

w- Age of extinction is the youngest age, such that during the last five calendar years mean death number at ages beyond this age does not exceed 1/2. For populations of modern developed countries this age is usually about 103-105 years. B: Extinct cohort method. For extinct cohorts, older than age w there are no people alive in the last available year and their population over ages can be estimated by a diagonal summing of deaths. C: If population at the beginning of the last year is available for an open ended age interval (e.g. 90+, 95+, or 100+), we apply the survivor ratio method to estimate population by single ages over age 90. This method assumes that 5-year survival in a cohort in question is the same as the average survival of five previous cohorts. After obtaining the last year population by single age group, the extinct cohort method can be applied. 8

Age-cohort-year-specific relative differences between the HMD and official population estimates at ages 80+ in East and West Germany. (In per cent) males males Observations: Cohort patterns of the differences. Increase with age. Census points and inter-census periods are clearly visible. Population estimates are significantly adjusted after each census. The differences decline with time. It seems that for males the differences are slightly greater than for females. females females 9

West Germany Age-standardized relative differences between the HMD and official population estimates at age 80+ in East and West Germany. females males East Germany Absolute differences 10

Not in all countries situation with death registration and availability of data on deaths at the oldest ages is as good as it is in Germany. Two types of problems: - no death counts until the highest age  procedure for splitting death; - quality of data on deaths. Artificial decline in e(80) in Sweden from 1750 to 1820 due to increasing completeness of death counts Age heaping at ages 85 and 90 in Russia before 1970. 11

Review of population data of 12 European countries.

Long-term trends in age-standardized relative difference between the HMD and the official estimates of population aged 80+. Switzerland Finland England and Wales France 13

Factors of relative difference between the HMD and the official estimates of population aged 80+ in six European countries since 1910. Coefficients from an OLS regression: B*100 / Standard Error/ p 14

Norway Sweden The Netherlands England and Wales Hungary Russia 15

The average relative difference between the HMD and the official estimates of population aged 80+. 16

Factors of relative difference between the HMD and the official estimates of population aged 80+ in six European countries: 1950-1999. Coefficients from an OLS regression: B*100 / Standard Error/ p 17