To derive reliable demographic indicators, appropriate data on population exposures are needed. Access to such data is becoming increasingly challenging in many countries due to factors such as the growing diversity of international migration patterns and the trend towards replacing full censuses with register-based censuses. Germany represents a particularly challenging case in this respect. Before Germany implemented its first register-based census in 2011, the country had not conducted a census for more than two decades. This census revealed that the number of people living in Germany in 2011 was about 1.5 million lower than the previous official post-censal population estimates for that year indicated. It is likely that a large portion of this discrepancy had existed for quite some time prior to 2011. Due to the long inter-censal period, the Federal Statistical Office of Germany decided not to produce backward-adjusted population estimates by single-year ages and sex for the whole period. The main aim of this paper is thus to make such detailed adjusted inter-censal population estimates available. While we have to take the peculiarities of the German case into account, our evaluation of different strategies offers important insights for developing a generalised methodology to adjust inter-censal population estimates for globalised countries that face challenges in ensuring the proper registration of migration events. We discuss four alternative approaches for deriving adjusted inter-censal population estimates. The results suggest that even for a rather complicated case like Germany, a relatively simple approach seems to work reasonably well. Finally, we demonstrate to what extent the implemented adjustments affect mortality indicators. The adjusted inter-censal population estimates for Germany and its federal states are provided in the online data appendix.
The mortality of advanced-age residents of Russia has remained stable and high for several decades. However, the steady increase in life expectancy that started in the mid-2000s is largely due to decreased mortality among the elderly. The decrease in mortality among Moscow residents over age 80 was especially large during this period. We found evidence of a systematic deviation of these dynamics from the patterns observed in countries with reliable mortality statistics. Assuming that the patterns observed in these countries are applicable to Russia, we took the possible underestimation of mortality into account and corrected the life expectancy estimates for the residents of Moscow, Russia, and the Central Federal District at age 80, at retirement age, and at birth.
Russia has one of the highest rates of cardiovascular disease in the world. The International Project on Cardiovascular Disease in Russia (IPCDR) was set up to understand the reasons for this. A substantial component of this study was the Know Your Heart Study devoted to characterising the nature and causes of cardiovascular disease in Russia by conducting large cross-sectional surveys in two Russian cities Novosibirsk and Arkhangelsk. The study population was 4542 men and women aged 35-69 years recruited from the general population. Fieldwork took place between 2015-18. There were two study components: 1) a baseline interview to collect information on socio-demographic characteristics and cardiovascular risk factors, usually conducted at home, and 2) a comprehensive health check at a primary care clinic which included detailed examination of the cardiovascular system. In this paper we describe in detail the rationale for, design and conduct of these studies.
Background: Russia has the largest area of any country in the world and has one of the highest cardiovascular mortality rates. Over the past decade, the number of facilities able to perform percutaneous coronary interventions (PCIs) has increased substantially. We quantify the extent to which the constraints of geography make equitable access to this effective technology difficult to achieve. Methods: Hospitals performing PCIs in 2010 and 2015 were identified and combined with data on the population of districts throughout the country. A network analysis tool was used to calculate road-travel times to the nearest PCI facility for those aged 40+ years. Results: The number of PCI facilities increased from 144 to 260 between 2010 and 2015. Overall, the median travel time to the closest PCI facility was 48minutes in 2015, down from 73 minutes in 2010. Two-thirds of the urban population were within 60 minutes’ travel time to a PCI facility in 2015, but only one-fifth of the rural population. Creating 67 new PCI facilities in currently underserved urban districts would increase the population share within 60 minutes’ travel to 62% of the population, benefiting an additional 5.7 million people currently lacking adequate access. Conclusions: There have been considerable but uneven improvements in timely access to PCI facilities in Russia between 2010 and 2015. Russia has not achieved the level of access seen in other large countries with dispersed populations, such as Australian and Canada. However, creating a relatively small number of further PCI facilities could improve access substantially, thereby reducing inequality.
This is the 23rd issue of Annual Series of Analytical reports regularly published by the HSE Institute of Demography since 1993. The recent report conducts the detailed analysis of the current situation in Russia’s demography in the context of its long-term evolution and demographic tendencies as seen through the prism of main demographic processes, such as marriage, birth and death rates, family planning, international and internal (intra-Russian) migration, changes in population, and age structure of Russia’s population. The analysis is based on the official data of the Federal State Statistics service of Russian Federation, ministries and government agencies of Russian Federation, international organizations and national statistics services of other countries as well as local estimates (acquired by using these resources), the results of special sampling studies, and the materials of scholarly publications. The book is designed for the researchers that work in the field of demography and similar disciplines as well as decision-making employees, workers of government organizations of all levels, and instructors and students of secondary and postsecondary professional schools.
This paper aims to estimate the cancer mortality and morbidity derivatives for the Russian population given the limited access to medical and demographic data. The multiple decrement life table method also known as the population model of cancer was originally proposed by J. Duchêne and makes it possible to assess otherwise inaccessible indicators, such as the prevalence of cancer in the Russian population. Applying this model to the publicly available data on cancer mortality and morbidity, we were able to estimate the following indicators for the Russian population: average age at malignant neoplasms (MN) diagnosis, the average duration of disease, the prevalence of MN, and an average age at death from MN. We aimed to determine whether the prevalence of MN is increasing in the Russian Federation and whether this growth is occurring due to the expansion of morbidity.
It was found that the average age at cancer diagnosis, along with the average age at death from cancer, is increasing in the Russian population, with the primacy of the latter. These processes are in turn resulting in an increase of the average number of years lived with cancer, hence justifying the claim for an expansion of morbidity. This phenomenon, along with the increase in the incidence of MN, is the cause of the increase in MN prevalence in Russia.
Localizations with the highest and lowest MN prevalence were identified, as well as localizations for which the expansion of morbidity phenomenon does not occur. It was found that in Russia the general trend is for the expansion of morbidity, expressed in an increase in the number of years lived in an imperfect health condition. MN of the lip, oral cavity and oesophagus (C00 - C15) in women is the only localization for which this phenomenon is not observed. This localization is the only exception to the otherwise observed expansion of morbidity. The main limitations and drawbacks of the study are discussed in a separate section.
The collapse of the USSR, transition to market economy and structural changes in society had given start to the family and marriage transformation in Russia and post-soviet countries of Eastern Europe. Estonia is one of the examples of rapid deinstitutionalization of marriage, widespread of cohabitations and nonmarital births. At the same time, since first post-war decades Estonia accepted the Russian migrants throughout a long time. Research shows that adaptation of the Russian population in Estonia has proceeded slowly, and patterns of matrimonial behavior of the Russian migrants and their descendants in Estonia tend to be closer to base patterns of ethnical Russians observed in Russia. In this article the UN ECE ‘Generations and Gender’ Survey data were used to estimate and compare fertility behavior among the Russian and Estonian population in Estonia and Russians in Russia. Our results show the significant changes in reproductive behavior among Estonians and Russians in Estonia, but the probabilities of first births among Russians in Russia are stable across generations. The probabilities of second births were increasing from one generation to other among Estonians women, but contrary, decreased among Russians both in Estonia and Russia. The contribution of births in high-order unions to total number of births significantly sincreased both among Estonians and Russian population in Russia, as well as among Russian migrants in Estonia. At the same time, the reproductive behavior of Russians in Estonia has common features with behavior of the Russian population in Russia: the share of births in the unregistered unions is less, and length of the time interval between the first and second births in the continuous union is bigger, than for Estonians. However, there are signs of some changes in reproductive behavior among Russians in Estonia born after 1970.
The Chapter is devoted to the analysis of the current situation in the field of fertility and family planning in Russia against the background of long-term evolution of the main demographic processes. Special attention is paid to the results of the 2015 micro-census.
Based on the harmonized data of the first wave of "Generations and Gender Survey" the comparative analysis of childbearing out of marriage and partner union in Estonia, Russia and France was carried out. Two hypotheses have been formulated. The first one suggests that probability of first childbirth outside union among Russian and Estonian women is equal in generations whose first reproductive events were during the common Soviet period. The second one applies to similarity of women’s behavior concerning the first birth outside union among Estonians and French women after 1991. The obtained results have shown that in the generations of women born in the 1950s-1960s in the three countries under consideration there were no significant distinctions in risks of out-of-union first birth. However, the analysis shows that Estonians from generations of the 1930s and 1940s had significantly less chance of having a child out of union, particularly in young ages under 20 years, than French and Russian women in the same cohorts. But the chance of women born during the 1970s to give birth to a child out of union in Estonia and in Russia is much higher, then in France. The observed increase of out-of-union births among Estonian women could be due to the big flow of Russians in the 1940s-1959s, and the significant differences in contraceptive practices between native Estonian and migrant Russian women in Estonia.
Usually in rich countries life expectancy is higher than in poor countries. We checked whether this is true for the regions of Russia.
The object of the study was data for 2010, which is the year of the last population census. We used life expectancy at birth as longevity measure and the value of gross domestic product per capita in US dollars at purchasing power parity is used as the welfare measure.
The analysis is based on a comparison of regional data with the Preston curve that describes relationship between per capita GDP and life expectancy at birth. The curve was also determined for 2010 based on data from 57 countries, where population statistics are suitable for the calculation of life table.
We found that life expectancy in Russia is substantially below the level that the Preston's model predicts for Russian on the basis of the Russia’s GDP per capita. In 2010, the difference between the model and real life expectancy was 8.7 years and was the highest among the 57 countries involved in the calculation.
The dependence of life expectancy on economic situation in regions is practically nonexistent. The illusion of interdependence exists because Moscow stands out among other regions with high GDP and high life expectancy. However life expectancy in 2010 in Moscow was significantly lower than the level predicted by the Preston's model. In authors; opinion, the lack of communication is explained by the fact that in regions with high GDP, the level of economic inequality is also high. High incomes of a small part of the population can raise the average level of economic indicators in the region, but a lower mortality in a small group has little effect on life expectancy of total population.
This study proposes a new decomposition method that permits a difference in an aggregate measure at a final time point to be split into additive components corresponding to the initial differences in the event rates of the measure and differences in trends in these underlying event rates. For instance, when studying divergence in life expectancy, this method allows researchers to more easily contrast age-specific mortality trends between populations by controlling for initial age-specific mortality differences. Two approaches are assessed: (1) an additive change method that uses logic similar to cause-of-death decomposition, and (2) a contour decomposition method that extends the stepwise replacement algorithm along an age-period demographic contour. The two approaches produce similar results, but the contour method is more widely applicable. We provide a full description of the contour replacement method and examples of its application to life expectancy and lifetime disparity differences between the United States and England and Wales in the period 1980–2010.
We aimed to explore whether mortality data are consistent with the view that aging is accelerated for people with a history of incarceration compared to the general population, using data on mortality rates and life expectancy for persons in Ontario, Canada.
We obtained data from the Ontario Ministry of Community Safety and Correctional Services on all adults admitted to provincial correctional facilities in Ontario in 2000, and linked these data with death records from provincial vital statistics between January 1, 2000 and December 31, 2012. We used life table methods to calculate mortality rates and life expectancies for this cohort by sex and 5-year age group. We similarly generated population comparison rates using publicly available data for the general population of Ontario in 2006 as the midpoint of the follow up period. We compared these mortality indices between the 2000 Ontario prison cohort and the general population by age group and sex.
The difference in all-cause mortality rates between the 2000 Ontario prison cohort and the general population was greatest for younger adults, with the prison cohort experiencing rates of death that would be expected for persons at least 15 years older at ages 20 to 44 for men and ages 20 to 59 for women. Life expectancy in the 2000 Ontario prison cohort was most similar to life expectancy of persons five years older in the general population at age intervals 20 to 45 in men and 20 to 30 in women.
For most of adulthood, life expectancy and mortality rates are worse for adults with a history of incarceration than for the general population in Ontario, Canada. However, the association between mortality and incarceration status is modified by age, with the greatest relative burden of mortality experienced by younger persons with a history of incarceration and modified by sex, with worse relative mortality in women. Future research should explore the association between incarceration status and markers of aging including mortality, morbidity and physical appearance.
After several decades of negative trends and short-term fluctuations, life expectancy has been increasing in Russia since 2004. Between 2003 and 2014, the length of life rose by 6.6 years among males and by 4.6 years among females. While positive trends in life expectancy are observed in all regions of Russia, these trends are unfolding differently in different regions. First, regions entered the phase of life expectancy growth at different points in time. Second, the age- and cause-specific components of the gains in life expectancy and the number of years added vary noticeably. In this paper, we apply decomposition techniques—specifically, the stepwise replacement algorithm—to examine the age- and cause-specific components of the changes in inter-regional disparities during the current period of health improvement. The absolute inter-regional disparities in length of life, measured by the population-weighted standard deviation, decreased slightly between 2003 and 2014, from 3.3 to 3.2 years for males, and from 2.0 to 1.8 years for females. The decomposition of these small changes by ages and causes of death shows that these shifts were the result of diverse effects of mortality convergence at young and middle ages, and of mortality divergence at older ages. With respect to causes of death, the convergence is mainly attributable to external causes, while the inter-regional divergence of trends is largely determined by cardiovascular diseases. The two major cities, Moscow and Saint Petersburg, are currently pioneering mortality improvements in Russia and are making the largest contributions to the inter-regional divergence.
Since the mid-2000s, after a few decades of negative trends and fluctuations, Russia has experienced the longest and most stable period of life expectancy increasing for the entire period of observation which was determined not only by a decrease in mortality at the middle ages, but also at the old ages. This period has been marked by a very fast increase in life expectancy of Muscovites. The paper shows that the mortality at old ages in Moscow systematically deviates from the patterns observed in economically developed countries with reliable mortality statistics. We assume that experience of these countries is applicable to regions of Russia. Based on this assumption the adjusted estimates of life expectancy at old ages in Moscow and Russia were calculated, as well as effect of the underestimation of mortality over age 80 on life expectancy at birth and at the age of retirement.
This article is devoted to the study of the differences in mortality rates between population groups with different educational levels in Russia after 1979. It also assesses the contribution of changes in the mortality rates within different educational groups and the educational structure of the population to changes in the life expectancy of the entire population. This work is based on state statistics covering the breakdown of the population and the deceased by levels of education. The distribution of the population by age, sex and levels of education was calculated on the basis of the censuses of 1979, 1989 and 2002, and the micro-censuses of 1994 and 2015. Similar data on the deceased for 1979 and 1989 are contained in tables of vital statistics provided by statistical offices as annual reports. Data for 1998 and 2015, was obtained by further development of anonymous micro-data on the number of deceased collected by the Rosstat. The study showed that the change in the educational structure of the population contributed most to the increase in life expectancy of both men and women at the ages of 30 to 69 in 1979 – 2015. Another positive contribution was made by the decrease in mortality in all age groups of the population with higher education, and at the age of 50 and older in groups with secondary education as well
Significance. During the recent decades, Russia has experienced significant shifts in mortality. Considering the heterogeneity of the Russian regions, it is important to analyze how those shifts were experienced at the regional level and how they influenced the inter-regional mortality inequality.
Purpose. To evaluate how the inter-regional mortality inequality in Russia changed during the period 1989-2016; to measure contribution of different age groups and causes of death into the inter-regional mortality inequality in Russia and changes in those contributions over time.
Methods. In the current study, we used gap in life expectancy between the two groups of regions as the main measure of inter-regional inequality. The first group included regions with the highest levels of life expectancy inhabited altogether by 15% of the total Russian population. The second group included regions with the lowest levels of life expectancy, which also altogether accounted for 15% of the total Russian population. The contribution of different age groups and causes of death into the gap in life expectancy between the two groups was estimated with the stepwise replacement decomposition technique.
Results. Life expectancy inequality between regions increased substantially in the 1990s. The recent period of mortality improvements in Russia did not result in any significant changes in the inter-regional inequality. In 2016, the difference between the two 15%-groups of regions performing the best and the worst in terms of life expectancy amounted to 9.6 years in males. Mortality inequality in ages 15-39 contributed 2.6 years to this gap, in ages 40-64 – 4.2 years, and in ages over 65 – 2.9 years. In females the gap amounted to 5.3 years; 1.2 years, 2.0 years, and 2.0 years contributed by age intervals 15-39, 40-64, and 65 years and over respectively. Among the causes of death, the major contribution in inequality is attributable to external causes of death at the young and middle ages and circulatory diseases at the middle and elderly ages.
Conclusions. Decreased contribution of external causes of death in the young and middle ages, and circulatory diseases in the middle age had a positive effect on the inter-regional inequality in life expectancy after 2005 contributing to its decline. At the same time, mortality decline in the elderly contributed to divergency in life expectancy across regions. Those positive changes in the elderly mortality towards reduction, which are associated with the beginning of cardiovascular revolution in Russia, did not equally affect the Russian regions.