Poster Session on Health, mortality and longevity (3)

A notable mortality gap between East and West Germany that persisted for decades began to narrow rapidly right after the unification of the two states. Despite extensive research, the factors underlying the remarkable improvement in East Germany are still not fully understood. One of the reasons for that is a number of significant changes in the classification of causes of death as well as the changes in coding practices. These changes which happened to coincide in time with profound socioeconomic transformation of East Germany have complicated the interpretation of mortality trends and made the international comparisons difficult. In this paper, we explore the complex methodological issues related to the changes in the system of data collection and classification. Our ultimate goal is to obtain the detailed mortality series for East Germany which can be comparable across time and countries. We rely on the official mortality data and the method of a posteriori reconstruction of mortality trends. The method was successfully implemented for a number of countries including West Germany. The intended work continues this well-established research line. Its outcome is expected to contribute towards better understanding of the health changes observed in East Germany, and facilitate further research in this direction.

Population decline is common for modern Russia because of bad health, fertility decline and rapid mortality increase, especially male of working age.
The aim of our study is a critical analysis of modern methods of calculation of economic damage and the development (modification) of the optimal methodologies to assess the extent of economic losses due to mortality in the Far East Federal District, taking into account the valuation of the average life. This study is based on the concept of human capital, which considers health as one of the most important conditions for social and economic development of any territory.
Overall the Far East the total damage from the mortality of all ages increased by 2.8 times in 2003-2010, amounting to 42.7 billion of rubles or 2.4% of GRP in 2010. In Russia the growth rate of this indicator amounted to 2.6 times (in 2010 - 798 billion rubles or 2.5% of GDP). These estimates show that the mortality rate in the Far East and Russia as a whole, is associated with very significant economic losses, which couldn’t be ignored in the current circumstances, considering the low level of health, high mortality in the working age and the reduction of population.

To date, no study has satisfactorily addressed the relationship between social mobility and mortality in China’s context. The present paper examines how grandparents’ status, parents' status and individuals' status together influence the physical well-being of individuals, using the China Multi-Generational Panel Dataset-Liaoning (CMGPD-LN). A mobility-Path model is proposed to estimate effects of specific components in individual mobility course for three generations. Results show that mobility itself has effects on mortality risks. The relative effects of grandfather position, father position and individual position vary by individuals' childhood, early adulthood and late adulthood. Cumulative effects of socioeconomic circumstances over a lifetime are not obvious in the current analysis.

Demographers are still trying to find a way of modelling the relationship between mortality and age. So far the Gompertz-Makeham function was for a long time universally used for extrapolating mortality curves. But at present it is important to develop new models. This is mainly the fact that there is an improvement in mortality. More and more people live to old age. The second reason is better availability of statistical data. As a result of improving mortality of the oldest persons and better statistical data many new models have emerged. Currently, come to the fore logistic models. In this paper we will present selected logistic models and we will apply them to the data on mortality of the Czech population. The results will be compared with the methodology of the Czech Statistical Office and life expectancy obtained from the mortality tables without extrapolation.

In terms of competing risks Mixture Long-term Survival Models are widely used for the analysis of individuals may never suffer the considered cause of failure. Under condition of a cured fraction, some individuals will be treated as immune to a specific cause of failure or be defined as long-term survivors. In case of multi- or bivariate cause-specific survival data different dependence structures between variables can be suited with different copula functions. There are two main methodical aspects for the marginal distributions need to account for: first the maximum of flexibility and second the application in case of masked causes. We proposed a bivariate mixture long-term model based on the Farlie-Gumbel-Morgenstern (FGM)copula. Data simulations will be provided with SEER Breast Cancer Data, and comparing the model with different types of copulas e.g. FGM, Positive Stable, Frank and Clayton Copula. Otherwise we will discuss optional ideas for this approach in a semi-competing risk setting.

BACKGROUND The disabled elderly, who utilize more health services than their counterparts, put a heavy pressure on the health system. However, our knowledge of the disease pattern in disability burden among the Chinese elderly remains limited.

METHODS Based on a nationally representative data, we used the attribution method to obtain disability prevalence by disease and then employed the Sullivan method to produce life expectancy with disability (LED) by disease. The analyses were carried out at both disease group level and individual disease level.

RESULTS At the disease group level, ear, eye, circulatory and musculoskeletal diseases and injury and poisoning were the 5 leading causes of disability burden in terms of their contributions to disability prevalence and LED. At the individual disease level, presbycusis, cataract, cerebrovascular disease, osteoarthritis and unclassified injury totally accounted for 64% of disabilities and caused males and females aged 60 to have 3.04 and 3.76 years of LED, respectively.

CONCLUSIONS Along with the epidemiologic transition, chronic diseases have become the predominant contributor to disability burden among the elderly population in China. And, presbycusis, cataract, cerebrovascular disease, osteoarthritis and unclassified injuries should be the priorities in fighting ag

The study proposes a new way to compute confidence intervals for life expectancy estimates, based on Monte Carlo simulations. Taking into account the stochastic variability is particularly relevant for geographical areas with small population size, as the limited number - if any - of death events and/or population at risk, especially at younger ages, may cause fluctuations in the estimates of life expectancies which make it difficult to identify trends. To test its robustness, the method is applied to about 300 complete life tables of European regions computed by Eurostat, representing a variety of mortality patterns and possible issues of data quality/availability. A comparison is also made with other two stochastic methods proposed in the literature (Chiang 1984 and Silcock et al. 2001), as well as sensitivity analyses to assess the impact of different age grouping in the life table.

gamma-Gompertz frailty models indicate the heterogeneity of mortality both in male and female at advanced age in China; while female have a larger individual heterogeneity. In general, male show higher mixture mortality than female from 80 to 115 years old, however, female mortality starts to exceed male since about 96 years old controlling for their heterogeneity respectively. The married mostly elderly in male tend to have lower hazard rate by 32% compared to those without spouses. Proximity to children of male oldest of the old has a positive relationship with mortality only after controlling the health behaviors and condition variables, as the direct and indirect effect of proximity to children on mortality can be decomposed. Neither of the two family support factors affects the hazard rate in female. The gender differentials of dependence on spouses and children in term of social connections and support, selective effect of living arrangement related to health condition, role expectancy as well as health behaviors may together contribute to the above phenomenon.