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1.
SSM Popul Health ; 18: 101118, 2022 Jun.
Article in English | MEDLINE | ID: mdl-35573866

ABSTRACT

Excess mortality has been used to measure the impact of COVID-19 over time and across countries. But what baseline should be chosen? We propose two novel approaches: an alternative retrospective baseline derived from the lowest weekly death rates achieved in previous years and a within-year baseline based on the average of the 13 lowest weekly death rates within the same year. These baselines express normative levels of the lowest feasible target death rates. The excess death rates calculated from these baselines are not distorted by past mortality peaks and do not treat non-pandemic winter mortality excesses as inevitable. We obtained weekly series for 35 industrialized countries from the Human Mortality Database for 2000-2020. Observed, baseline and excess mortalities were measured by age-standardized death rates. We assessed weekly and annual excess death rates driven by the COVID-19 pandemic in 2020 and those related to seasonal respiratory infections in earlier years. There was a distinct geographic pattern with high excess death rates in Eastern Europe followed by parts of the UK, and countries of Southern and Western Europe. Some Asia-Pacific and Scandinavian countries experienced lower excess mortality. In 2020 and earlier years, the alternative retrospective and the within-year excess mortality figures were higher than estimates based on conventional metrics. While the latter were typically negative or close to zero in years without extraordinary epidemics, the alternative estimates were substantial. Cumulation of this "usual" excess over 2-3 years results in human losses comparable to those caused by COVID-19. Challenging the view that non-pandemic seasonal winter mortality is inevitable would focus attention on reducing premature mortality in many countries. As SARS-CoV-2 is unlikely to be the last respiratory pathogen with the potential to cause a pandemic, such measures would also strengthen global resilience in the face of similar threats in the future.

2.
Eur J Popul ; 38(1): 37-58, 2022 Mar.
Article in English | MEDLINE | ID: mdl-35370528

ABSTRACT

While cohabitation and non-marital childbearing have been increasing in Russia since 1990, the share of marital first births that are conceived prior to marriage has changed very little since the Soviet era. The prior findings on the stability of trends in premarital conceptions in Russia have been contradictory and inconclusive. This study aims to extend the existing empirical evidence on premarital conceptions in Russia and to contribute to the discussion on the persistence of marriage as the preferred partnership context for parenthood. We focus on births that occurred within the first two years of marriage, and compare the childbearing patterns of Russian women who married in different historical periods. For our investigation of fertility among marital cohorts who married during the Soviet era (1960-1991), we use individual-level data from the 1994 microcensus. For our examination of fertility among more recent marital cohorts (2000, 2011, and 2016), we draw on data from birth records in civil registers. We also use relevant complementary data sources. Our findings show that there has been a marked shift in the relationship between conception and marriage in Russia. Increasingly, conceptions have been occurring before marriage, and in the most recent marital cohorts, the level of premarital first conceptions has even surpassed the level of marital first conceptions. The average interval between conception and entry into marriage has also been lengthening. We describe this unique pattern of childbearing and discuss some potential explanations for the ongoing association between marriage and childbearing in Russia. Supplementary Information: The online version contains supplementary material available at 10.1007/s10680-021-09600-5.

3.
Eur J Public Health ; 32(1): 21-23, 2022 02 01.
Article in English | MEDLINE | ID: mdl-34009332

ABSTRACT

This article addresses two unresolved methodological issues related to prior research on Russia that was based on census-unlinked data and did not account for the substantial increase in the share of death records with missing information on education. The study uses a proportional mortality analysis method relying on a case-control framework, together with a plausible imputation-based solution for the redistribution of the unknown education on death records. The new results suggest that high levels of inequality persist, but they do not support recent findings indicating that the educational gap in life expectancy has substantially widened.


Subject(s)
Life Expectancy , Mortality , Case-Control Studies , Educational Status , Health Status Disparities , Humans , Russia/epidemiology
4.
Lancet Public Health ; 4(4): e181-e188, 2019 04.
Article in English | MEDLINE | ID: mdl-30954143

ABSTRACT

BACKGROUND: Since 2005, Russia has made substantial progress, experiencing an almost doubling of per-capita gross domestic product by purchasing power parity (GDP [PPP]) to US$24 800 and witnessing a 6-year increase in life expectancy, reaching 71·4 years by 2015. Even greater gains in GDP (PPP) were seen for Moscow, the Russian capital, reaching $43 000 in 2015 and with a life expectancy of 75·5 years. We aimed to investigate whether mortality levels now seen in Russia are consistent with what would be expected given this new level of per-capita wealth. METHODS: We used per-capita GDP (PPP) and life expectancy from 61 countries in 2014-15, plus those of Russia as a whole and its capital Moscow, to construct a Preston curve expressing the relationship between mortality and national wealth and to examine the positions of Russia and other populations relative to this curve. We adjusted life expectancy values for Moscow for underestimation of mortality at older ages. For comparison, we constructed another Preston curve based on the same set of countries for the year 2005. We used the stepwise replacement algorithm to decompose mortality differences between Russia or Moscow and comparator countries with similar incomes into age and cause-of-death components. FINDINGS: Life expectancy in 2015 for both Russia and Moscow lay below the Preston-curve-based expectations by 6·5 years and 4·9 years, respectively. In 2015, Russia had a lower per-capita income than 36 of the comparator countries but lower life expectancy than 60 comparator countries. However, the gaps between the observed and the Preston-expected life expectancy values for Russia have diminished by about 25% since 2005, when the life expectancy gap was 8·9 years for Russia and 6·6 years for Moscow. When compared with countries with similar level of income, the largest part of the life expectancy deficit was produced by working-age mortality from external causes for Russia and cardiovascular disease at older ages for Moscow. INTERPRETATION: Given the economic wealth of Russia, its life expectancy could be substantially higher. Sustaining the progress seen over the past decade depends on the ability of the Russian Government and society to devote adequate resources to people's health. FUNDING: This work was partly funded through the International Project on Cardiovascular Disease in Russia supported by a Wellcome Trust Strategic Award (100217) and was supported by the Russian Academic Excellence Project 5-100.


Subject(s)
Gross Domestic Product/trends , Life Expectancy/trends , Cross-Sectional Studies , Humans , Russia
5.
Demography ; 54(4): 1579-1602, 2017 08.
Article in English | MEDLINE | ID: mdl-28755276

ABSTRACT

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.


Subject(s)
Life Expectancy/trends , Models, Statistical , Mortality/trends , England , Humans , United States , Wales
6.
PLoS One ; 12(4): e0175837, 2017.
Article in English | MEDLINE | ID: mdl-28410398

ABSTRACT

OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.


Subject(s)
Life Expectancy , Adolescent , Adult , Aged , Aged, 80 and over , Cohort Studies , Databases, Factual , Female , Humans , Life Tables , Male , Middle Aged , Prisoners/statistics & numerical data , Retrospective Studies , Sex Factors , Young Adult
8.
PLoS One ; 10(9): e0138021, 2015.
Article in English | MEDLINE | ID: mdl-26376439

ABSTRACT

BACKGROUND AND AIM: Harmful alcohol consumption has long been recognized as being the major determinant of male premature mortality in the European countries of the former USSR. Our focus here is on Belarus and Russia, two Slavic countries which continue to suffer enormously from the burden of the harmful consumption of alcohol. However, after a long period of deterioration, mortality trends in these countries have been improving over the past decade. We aim to investigate to what extent the recent declines in adult mortality in Belarus and Russia are attributable to the anti-alcohol measures introduced in these two countries in the 2000s. DATA AND METHODS: We rely on the detailed cause-specific mortality series for the period 1980-2013. Our analysis focuses on the male population, and considers only a limited number of causes of death which we label as being alcohol-related: accidental poisoning by alcohol, liver cirrhosis, ischemic heart diseases, stroke, transportation accidents, and other external causes. For each of these causes we computed age-standardized death rates. The life table decomposition method was used to determine the age groups and the causes of death responsible for changes in life expectancy over time. CONCLUSION: Our results do not lead us to conclude that the schedule of anti-alcohol measures corresponds to the schedule of mortality changes. The continuous reduction in adult male mortality seen in Belarus and Russia cannot be fully explained by the anti-alcohol policies implemented in these countries, although these policies likely contributed to the large mortality reductions observed in Belarus and Russia in 2005-2006 and in Belarus in 2012. Thus, the effects of these policies appear to have been modest. We argue that the anti-alcohol measures implemented in Belarus and Russia simply coincided with fluctuations in alcohol-related mortality which originated in the past. If these trends had not been underway already, these huge mortality effects would not have occurred.


Subject(s)
Alcoholism/mortality , Mortality/trends , Adolescent , Adult , Aged , Child , Child, Preschool , Humans , Infant , Infant, Newborn , Life Expectancy , Male , Middle Aged , Republic of Belarus/epidemiology , Russia/epidemiology , Socioeconomic Factors , Survival Rate , Young Adult
9.
Arch Gerontol Geriatr ; 55(2): 231-7, 2012.
Article in English | MEDLINE | ID: mdl-21955584

ABSTRACT

The goal of this study is to estimate the prevalence of MetS, together with its components and correlates, among elderly Russians. Our population-based sample included randomly selected residents of Moscow aged 55 and older: 955 women with an average age of 67.6, and 833 men with an average age of 68.9. MetS was defined according to National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATPIII). The prevalence of MetS was found to be 41.7% in women and 26.8% in men. It tended to decrease with age in men, but not in women. MetS was inversely related to education in women, but not in men. The most prevalent individual components of MetS were as follows: hypertension (64.4%), abdominal obesity (55%), and decreased high density lipoprotein cholesterol (HDL C) (46%) for women; and hypertension (71%) and fasting hyperglycemia (35.2%) for men. An elevated level of triglycerides (TG) was the rarest MetS component, affecting 23.5% of women and 22.1% of men. The higher female prevalence of MetS was attributable to abdominal obesity. MetS was found to be associated with markers of insulin resistance (IR), low-grade inflammation, and insufficient fibrinolysis. Although the metabolic burden is an important contributor to high levels of ill-health and cardiovascular mortality among elderly Russians (especially women), it does not explain why cardiovascular mortality is much higher in Russia than in other industrialized countries.


Subject(s)
Metabolic Syndrome/epidemiology , Aged , Aged, 80 and over , Biomarkers/blood , Cardiovascular Diseases/mortality , Cholesterol, HDL/blood , Educational Status , Fasting/blood , Female , Humans , Hyperglycemia/blood , Hyperglycemia/epidemiology , Hyperlipidemias/blood , Hyperlipidemias/epidemiology , Hypertension/epidemiology , Inflammation/blood , Inflammation/epidemiology , Insulin Resistance/physiology , Male , Middle Aged , Moscow/epidemiology , Obesity, Abdominal/epidemiology , Prevalence
10.
Popul Dev Rev ; 37(3): 419-34, 2011.
Article in English | MEDLINE | ID: mdl-22167810

ABSTRACT

We analyze trends in best-practice life expectancy among female cohorts born from 1870 to 1950. Cohorts experience declining rather than constant death rates, and cohort life expectancy usually exceeds period life expectancy. Unobserved mortality rates in non-extinct cohorts are estimated using the Lee-Carter model for mortality in 1960­2008. Best-practice cohort and period life expectancies increased nearly linearly. Across cohorts born from 1870 to 1920 the annual increase in cohort length of life was 0.43 years. Across calendar years from 1870 to 2008, the annual increase was 0.28 years. Cohort life expectancy increased from 53.7 years in the 1870 cohort to 83.8 years in the 1950 cohort. The corresponding cohort/period longevity gap increased from 1.2 to 10.3 years. Among younger cohorts, survival to advanced ages is substantially higher than could have been anticipated by period mortality regimes when these cohorts were young or middle-aged. A large proportion of the additional expected years of life are being lived at ages 65 and older. This substantially changes the balance between the stages of the life cycle.


Subject(s)
Life Expectancy , Mortality , Population Dynamics , Practice Guidelines as Topic , Women , Cohort Effect , History, 19th Century , History, 20th Century , History, 21st Century , Life Expectancy/ethnology , Life Expectancy/history , Mortality/ethnology , Mortality/history , Population Dynamics/history , Women/education , Women/history , Women/psychology , Women's Health/ethnology , Women's Health/history
11.
Popul Stud (Camb) ; 65(3): 319-34, 2011 Nov.
Article in English | MEDLINE | ID: mdl-21919630

ABSTRACT

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.


Subject(s)
Laboratory Personnel/statistics & numerical data , Life Expectancy/trends , Longevity , Academies and Institutes , Adult , Age Distribution , Aged , Demography , Female , Humans , Intelligence , Male , Middle Aged , Mortality , Russia , Socioeconomic Factors , United States
12.
Demography ; 48(1): 211-39, 2011 Feb.
Article in English | MEDLINE | ID: mdl-21359621

ABSTRACT

Patterns of diversity in age at death are examined using e (†), a dispersion measure that equals the average expected lifetime lost at death. We apply two methods for decomposing differences in e (†). The first method estimates the contributions of average levels of mortality and mortality age structures. The second (and newly developed) method returns components produced by differences between age- and cause-specific mortality rates. The United States is close to England and Wales in mean life expectancy but has higher life expectancy losses and lacks mortality compression. The difference is determined by mortality age structures, whereas the role of mortality levels is minor. This is related to excess mortality at ages under 65 from various causes in the United States. Regression on 17 country-series suggests that e (†) correlates with income inequality across countries but not across time. This result can be attributed to dissimilarity between the age- and cause-of-death structures of temporal mortality reduction and intercountry mortality variation. It also suggests that factors affecting overall mortality decrease differ from those responsible for excess lifetime losses in the United States compared with other countries. The latter can be related to weaknesses of health system and other factors resulting in premature death from heart diseases, amenable causes, accidents and violence.


Subject(s)
Cause of Death/trends , Life Expectancy/trends , Mortality, Premature/trends , Adolescent , Adult , Age Distribution , Aged , Aged, 80 and over , Child , Child, Preschool , Developed Countries/statistics & numerical data , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Socioeconomic Factors , United States/epidemiology , Young Adult
13.
Soc Sci Med ; 64(7): 1392-406, 2007 Apr.
Article in English | MEDLINE | ID: mdl-17196723

ABSTRACT

Earlier studies have found large and increasing with time differences in mortality by education and marital status in post-Soviet countries. Their results are based on independent tabulations of population and deaths counts (unlinked data). The present study provides the first census-linked estimates of group-specific mortality and the first comparison between census-linked and unlinked mortality estimates for a post-Soviet country. The study is based on a data set linking 140,000 deaths occurring in 2001-2004 in Lithuania with the population census of 2001. The same socio-demographic information about the deceased is available from both the census and death records. Cross-tabulations and Poisson regressions are used to compare linked and unlinked data. Linked and unlinked estimates of life expectancies and mortality rate ratios are calculated with standard life table techniques and Poisson regressions. For the two socio-demographic variables under study, the values from the death records partly differ from those from the census records. The deviations are especially significant for education, with 72-73%, 66-67%, and 82-84% matching for higher education, secondary education, and lower education, respectively. For marital status, deviations are less frequent. For education and marital status, unlinked estimates tend to overstate mortality in disadvantaged groups and they understate mortality in advantaged groups. The differences in inter-group life expectancy and the mortality rate ratios thus are significantly overestimated in the unlinked data. Socio-demographic differences in mortality previously observed in Lithuania and possibly other post-Soviet countries are overestimated. The growth in inequalities over the 1990s is real but might be overstated. The results of this study confirm the existence of large and widening health inequalities but call for better data.


Subject(s)
Life Expectancy/trends , Marital Status , Mortality/trends , Adult , Aged , Aged, 80 and over , Censuses , Data Interpretation, Statistical , Educational Status , Female , Humans , Lithuania/epidemiology , Male , Marital Status/statistics & numerical data , Middle Aged , Social Class
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