A summary of Special Collection 2

Special Collection 2: Determinants of Diverging Trends in Mortality is a set of papers stemming from the first seminar of the Committee on Emerging Health Threats (CEHT) of the International Union for the Scientific Study of Population (IUSSP), "Determinants of Diverging Trends of Mortality". The seminar was held in Rostock (Germany) from 19-21 June 2002. The seminar encouraged studies on adverse mortality trends and widening mortality differentials between and within countries. Thirteen contributions were submitted to the journal Demographic Research and went through peer review. They were published, along with an introduction, on 16 April 2004 as the journal’s second “special collection†of material on a common topic. This short summary of the collection has been added to Volume 10 in order to include full details of the collection in the current running volume as well. The following pages list the contributions and give direct links where readers may download the material from the Demographic Research website. A full list of all papers is also available at: http://www.demographic-research.org/special/2/.decline, mortality, mortality analysis

Regularities and peculiarities of birth schedules in industrialized countries: an analysis of FFS data

Inter-individual diversity of women according to birth numbers (quantum) and birth spacing (tempo) are important for understanding of fertility regimes. Elsewhere, we have shown that diversity with respect to fertility quantum is increasing from older to younger cohorts. The present study looks at tempo dimension by decomposing the diversity of birth schedules. The data set contains pooled FFS data from 19 industrialized countries and covers 11124 women aged 40-44 at survey. The analyses include descriptive characteristics of birth schedules, their classification by cluster analysis, and the identification of some of the underlying factors by two types of regression analyses. The first of them is a multinomial logistic regression linking types of birth schedules with characteristics of women at the time of interview. The second includes event-history analyses examining the transition to second and third conception (leading to birth), where time since previous birth is combined with the current values of the covariates. Age at first birth is a major component of inter-individual differences in birth schedules and it largely determines their clustering. Distributions of second, third, and fourth births over time since the previous births are very similar to each other. The median length of birth intervals is 3-3.5 years and 75% of births occur within 5-6 years after the previous delivery. One cluster stands out of this regularity as it is characterized by long last birth interval of about 11 years. Age distributions of fertility for women from this cluster are bimodal and their shape points at unexpectedly “renewed” fertility careers. Additional births produced by the phenomenon compose about 6% of all births. Regression analyses show that the long last birth interval is associated with new partnerships. Some influence of contraceptive failure can not be excluded, too. More in-depth research is needed to learn about the dynamic factors of birth schedules and particularly about the relationship between entering new partnerships and childbearing.Europe, age distribution, birth spacing, fertility, fertility surveys

The 2010 OSCE Kazakhstan Chairmanship: Carrot Devoured, Results Missing. EUCAM Policy Brief No. 15, April 2011

This brief looks at Kazakhstan’s chairmanship through the prism of the EU’s relations with Central Asian states and examines what lessons the EU can draw from the Kazakhstan chairmanship. The OSCE Chairmanship and the agreement to hold the 2010 OSCE Summit in Astana, despite it not having a Summit-like agenda were significant ‘carrots’ given to Kazakhstan. Did these carrots bring any results, and is there any reason to offer more such carrots to Kazakhstan or to other Central Asian states

Long-term trends in the longevity of scientific elites: evidence from the British and the Russian academies of science.

National science academies represent intellectual elites and vanguard groups in the achievement of longevity. We estimated life expectancy (LE) at age 50 of members of the British Royal Society (RS) for the years 1670-2007 and of members of the Russian Academy of Sciences (RAS) for the years 1750-2006. The longevity of academicians was higher than that of their corresponding national populations, with the gap widening from the 1950s. Since the 1980s, LE in the RS has been higher than the maximum LE among all high-income countries. In each period, LE in the RS was greater than in the RAS, although since the 1950s it has risen in parallel in the two academies. This steep increase shared by academicians in Britain and Russia suggests that general populations have the potential for a substantial increase in survival to high ages

Gini coefficient as a life table function

This paper presents a toolkit for measuring and analyzing inter-individual inequality in length of life by Gini coefficient. Gini coefficient and four other inequality measures are defined on the length-of-life distribution. Properties of these measures and their empirical testing on mortality data suggest a possibility for different judgements about the direction of changes in the degree of inequality by using different measures. A new computational procedure for the estimation of Gini coefficient from life tables is developed and tested on about four hundred real life tables. The estimates of Gini coefficient are precise enough even for abridged life tables with the final age group of 85+. New formulae have been developed for the decomposition of differences between Gini coefficients by age and cause of death. A new method for decomposition of age-components into effects of mortality and composition of population by group is developed. Temporal changes in the effects of elimination of causes of death on Gini coefficient are analyzed. Numerous empirical examples show: Lorenz curves for Sweden, Russia and Bangladesh in 1995, proportional changes in Gini coefficient and four other measures of inequality for the USA in 1950-1995 and for Russia in 1959-2000. Further shown are errors of estimates of Gini coefficient when computed from various types of mortality data of France, Japan, Sweden and the USA in 1900-95, decompositions of the USA-UK difference in life expectancies and Gini coefficients by age and cause of death in 1997. As well, effects of elimination of major causes of death in the UK in 1951-96 on Gini coefficient, age-specific effects of mortality and educational composition of the Russian population on changes in life expectancy and Gini coefficient between 1979 and 1989. Illustrated as well are variations in life expectancy and Gini coefficient across 32 countries in 1996-1999 and associated changes in life expectancy and Gini coefficient in Japan, Russia, Spain, the USA, and the UK in 1950-1999. Variations in Gini coefficient, with time and across countries, are driven by historical compression of mortality, but also by varying health and social patterns.inequality, life expectancy, mortality, variability

Algorithm for decomposition of differences between aggregate demographic measures and its application to life expectancies, healthy life expectancies, parity-progression ratios and total fertility rates

A general algorithm for the decomposition of differences between two values of an aggregate demographic measure in respect to age and other dimensions is proposed. It assumes that the aggregate measure is computed from similar matrices of discrete demographic data for two populations under comparison. The algorithm estimates the effects of replacement for each elementary cell of one matrix by respective cell of another matrix. Application of the algorithm easily leads to the known formula for the age-decomposition of differences between two life expectancies. It also allows to develop new formulae for differences between healthy life expectancies. In the latter case, each age-component is split further into effects of mortality and effects of health. The application of the algorithm enables a numerical decomposition of the differences between total fertility rates and between parity progression ratios by age of the mother and parity. Empirical examples are based on mortality data from the USA, the UK, West Germany, and Poland and on fertility data from Russia.healthy life expectancy, life expectancy, parity progression

Introduction to the Special Collection “Human Mortality over Age, Time, Sex, and Place: The 1st HMD Symposiumâ€

This introduction to the special collection “Human Mortality over Age, Time, Sex, and Place: The 1st HMD Symposium†describes the Human Mortality Database project and briefly summarizes the Special Collection articles.

Official population statistics and the Human Mortality Database estimates of populations aged 80+ in Germany and nine other European countries

A systematic comparison of the Human Mortality Database and official estimates of populations aged 80+ is presented. We consider statistical series for East and West Germany and also for Denmark, England and Wales, France, Finland, Hungary, the Netherlands, Russia, Sweden, and Switzerland. The Human Mortality Database (HMD, www.mortality.org) methodology relies on the methods of extinct and almost extinct generations. HMD estimates are precise if the quality of death data is high and the migration among the elderly is negligible. The comparisons between the HMD and the official populations are not fully appropriate for the 1990s since the HMD calculations are related to official population estimates. A significant overestimation of the male population aged 80+ and especially 90+ between the censuses of 1970 and 1987 was found in West Germany. The relative surplus of men aged 90+ increased from 5 to 20 percent, which expressed in absolute numbers indicates an increase from 2 to 10 thousand. In 1971-1987 the official death rates have fallen dramatically to implausibly low values. In 1987-88 death rates based on the official populations suddenly jumped to the HMD death rates due to the census re-estimation. In the 1990s an accelerated decrease in male death rates has resumed. Among other countries, the relative and absolute deviations from the HMD estimates were especially high in Russia, Hungary, and England and Wales. Regression analysis reveals common factors of the relative deviation from the HMD populations. The deviation tends to decrease with time, increase with age, be higher during inter-census periods than in census years, and to decrease after the introduction of population registers.age/aging, elderly, population estimates, quality of statistics, statistics

Estimates of mortality and population changes in England and Wales over the two World Wars

Almost one million soldiers from England and Wales died during the First and Second World War whilst serving in the British Armed Forces. Although many articles and books have been published that commemorate the military efforts of the British Armed Forces, data on the demographic aspects of British army losses remain fragmentary. Official population statistics on England and Wales have provided continuous series on the civilian population, including mortality and fertility over the two war periods. The combatant population and combatant mortality have not been incorporated in the official statistics, which shows large out-migration at the beginning and large in-migration towards the end of the war periods. In order to estimate the dynamics of the total population and its excess mortality, we introduce in this paper a model of population flows and mortality in times of war operations. The model can be applied to a detailed reconstruction of war losses, using various shapes of the input data. This enables us to arrive at detailed estimates of war-related losses in England and Wales during the two world wars. Our results agree with elements of data provided by prior studies.England, First World War, population estimates, Second World War, Wales

Algorithm for decomposition of differences between aggregate demographic measures and its application to life expectancies, Gini coefficients, health expectancies, parity-progression ratios and total fertility rates

A general algorithm for the decomposition of differences between two values of an aggregate demographic measure in respect to age and other dimensions is proposed. It assumes that the aggregate measure is computed from similar matrices of discrete demographic data for two populations under comparison. The algorithm estimates the effects of replacement for each elementary cell of one matrix by respective cell of another matrix. Application of the algorithm easily leads to the known formula for the age-decomposition of differences between two life expectancies. It also allows to develop new formulae for differences between Gini coefficients (measures of inter-individual variability in age at death) and differences between health expectancies. In the latter case, each age-component is split further into effects of mortality and effects of health. The application of the algorithm enables a numerical decomposition of the differences between total fertility rates and between parity progression ratios by age of the mother and parity. Empirical examples are based on mortality data from the USA, the UK, West Germany, and Poland and on fertility data from Russia.