The female-male gap in life expectancy in Poland

The difference in life expectancy between the sexes in Poland started to decline only in 1991, equaling 8.4 years in 2009. In addition, with the rapid increase in male excess mortality between 1989 and 1991, the sex gap also increased. With the exception of excess mortality of male infants, the female advantage in mortality grows with age and reaches the maximum at the age of 65–70 years in 2009. The excess mortality of male infants decreased over the studied years from a contribution of over a year to the sex gap in life expectancy at birth in 1959, to less than a month in 2009. Differences in life expectancy at birth between the sexes in Poland are greater in rural than in urban areas and there is a variation between the voivodships: from 7.9 years in 2008 in the Pomorskie voivodship to 10.2 years in Lubelskie. The largest variation in the sex gap in life expectancy was that between different educational groups: and the gap decreased with the level of educational attainment. Diseases of the circulatory system are a major group of causes of death, with the highest contribution to the sex gap in life expectancy, and were the largest factor in the narrowing of the sex gap between 1991 and 2006. External causes of death were the second-largest group contributing to the sex gap in life expectancy at birth in 1991, and to the narrowing of the gap in the studied period. Over the years under study, the importance of malignant neoplasms for the phenomenon in consideration increased, but at the same time life expectancy of both sexes rose due to improvements in mortality from this group of causes. According to our estimates, smoking- and alcohol-related causes of death together explained about 50% of the total difference in life expectancy at birth between the sexes in the years 1989–2006. In this period, the sex gap in life expectancy due to these causes of death increased, which is opposite to what was reported for other developed countries

The concept of the Equivalent Lenght of Life for quantifying differences in age-at-death distributions across countries

Life expectancy, that is the mean age at death in a life table, is the most common measure used to describe and compare mortality distributions. Alternatives to life expectancy that have been proposed so far have also referred to only a single parameter of the mortality distribution. We propose to study mortality distributions by applying Silber’s concept of the Equivalent Length of Life (ELL), which enables comparisons based on up to three parameters of age-at-death distributions: life expectancy, dispersion and skewness. The method, and our decomposition, is used to study convergence/divergence of life-table age-at-death distributions across 35 developed countries of the Human Mortality Database in 1970–2010 and to assess the contribution of the three moments of the distribution to the total differences between countries and trends in the contribution. We observed a divergence of age-at-death distributions across the study countries from 1970 to 2005, followed by a convergence. Differences in life expectancies contributed the most to inequalities between the countries in life-table age-at-death distributions and the observed changes over time for both sexes. An additional important contribution resulted from the growing negative covariance between life expectancy and dispersion of ages at death, indicating that the largest increase in life expectancy occurred in the countries where variation in ages at death was lowest, especially among women. For men, including the skewness parameter resulted in lower differences between countries. The ELL and its decomposition thus have clear added value for studying differences between countries and convergence/divergence of age-at-death distributions

Visualizing Mortality Dynamics in the Lexis Diagram

The goal of this book is simple: We would like to show how mortality dynamics can be visualized in the so-called Lexis diagram. To appeal to as many potential readers as possible, we do not require any specialist knowledge. This approach may be disappointing: Demographers may have liked more information about the mathematical underpinnings of population dynamics on the Lexis surface as demonstrated, for instance, by Arthur and Vaupel in 1984. Statisticians would have probably preferred more information about the underlying smoothing methods that were used. Epidemiologists likewise might miss discussions about the etiology of diseases. Sociologists would have probably expected that our results were more embedded into theoretical frameworks...

Smoking cessation among European older adults: the contributions of marital and employment transitions by gender.

Knowledge about the potential effects of stressful events on smoking cessation is helpful for the design of health interventions. Previous studies on this topic tended to group together adults of all ages and of both genders. We investigate the contribution of marital and employment losses on smoking cessation by gender, specifically among older adults in Europe. We used panel data from waves 4 (2011) and 5 (2013) of the Survey of Health, Ageing and Retirement in Europe for 3345 male and 3115 female smokers at baseline aged 50 and over from 13 countries. The associations between marital and employment losses and smoking cessation were derived from logistic regression models for each gender, controlling for age, educational attainment, diseases incidence and country of residence. Interactions between gender and marital and employment losses were tested. Over the analysed period, 119 smokers became widowed or divorced (1.8 %), 318 became retired (4.9 %) and 100 became unemployed (1.5 %). Becoming widowed or divorced was associated with lower probability of smoking cessation among both men (OR 0.36, 95 % CI 0.14-0.94) and women (OR 0.46, 95 % CI 0.21-0.99). Transitions to unemployment and to retirement were not significantly associated with smoking cessation (OR 0.62, 95 % CI 0.25-1.49; and OR 0.68, 95 % CI 0.43-1.07, respectively). Gender differences in the association between marital and employment losses and smoking cessation were not statistically significant (p value > 0.05 for all interactions). Health interventions should take into account that male and female older adults affected by marital loss are at risk of continuing smoking

The Old-Age Healthy Dependency Ratio in Europe

The aim of this study is to answer the question of whether improvements in the health of the elderly in European countries could compensate for population ageing on the supply side of the labour market. We propose a state-of-health-specific (additive) decomposition of the old-age dependency ratio into an old-age healthy dependency ratio and an old-age unhealthy dependency ratio in order to participate in a discussion of the significance of changes in population health to compensate for the ageing of the labour force. Applying the proposed indicators to the Eurostat’s population projection for the years 2010–2050, and assuming there will be equal improvements in life expectancy and healthy life expectancy at birth, we discuss various scenarios concerning future of the European labour force. While improvements in population health are anticipated during the years 2010–2050, the growth in the number of elderly people in Europe may be expected to lead to a rise in both healthy and unhealthy dependency ratios. The healthy dependency ratio is, however, projected to make up the greater part of the old-age dependency ratio. In the European countries in 2006, the value of the old-age dependency ratio was 25. But in the year 2050, with a positive migration balance over the years 2010–2050, there would be 18 elderly people in poor health plus 34 in good health per 100 people in the current working age range of 15–64. In the scenarios developed in this study, we demonstrate that improvements in health and progress in preventing disability will not, by themselves, compensate for the ageing of the workforce. However, coupled with a positive migration balance, at the level and with the age structure assumed in the Eurostat’s population projections, these developments could ease the effect of population ageing on the supply side of the European labour market

Role of smoking in regional variation in mortality in Poland

Aims We assess the effect of smoking on regional disparities in mortality in Poland and its contribution to the change in regional disparities during the last two decades. Design, Setting and Participants We used population-level mortality data from the population registry for 379 Nomenclature of Territorial Units for Statistics (NUTS)-4 Polish regions for 1991–93 and 2008–10. Measurements The importance of smoking was assessed by smoking-attributable mortality (SAM) derived using a simplified indirect Peto-Lopez method. Regional differences in age-standardized allcause, smoking- and non-smoking-attributable mortality (NSAM) rates at ages 35 years and over were mapped, and spatial clustering (Moran’s I) and coefficients of variation (CV) were estimated. The contribution of SAM to variation in all-cause mortality was assessed by variance decomposition and compared over time. Findings In 2008–10, all-cause and SAM rates were characterized by a similar pattern of spatial clustering (Moran’s I > 0.44, P < 0.0001). For NSAM, a more random pattern with less regional clustering showed (Moran’s I = 0.34, P < 0.0001). The contribution of smoking to regional variation was substantial [54%, 95% confidence interval (CI) = 44.9, 62.5 among men; 24.9%, 95% CI = 20.9, 29.1 among women], and compared with 1991–93, 27.5 percentage points lower for men and 6.3 percentage points higher for women. Smoking contributed to the divergence between the regions in all-cause mortality between 1991–93 and 2008–10 for men [increase in CV of SAM by 2% (0, 4%)], but not for women [decrease in CV of SAM by 15% (22, 10%)]. Conclusions Differences in past smoking behaviour may largely explain the regional differences in all-cause mortality existing in 2008–10 in Poland, and its trends since 1991–1993

Terytorialne zróżnicowanie umieralności w Polsce ze względu na chorobę niedokrwienną serca, 2006–2010

Background: Spatial differences in mortality in Poland are large and remain unexplained to a large extent. Ischaemic heart disease (IHD) is a good candidate for explaining regional inequalities in mortality in Poland due to the high level of mortality from this cause and the large spatial differences. Aim: We describe the contribution of IHD to all-cause mortality in Poland in 2006–2010 on a powiat (Polish district) level and explain the differences in mortality by selected socio-economic factors. Methods: We use mortality data from the population registry at the NUTS-4 level for 2006–2010. We map age-standardised all-cause and IHD mortality rates. The contribution of IHD mortality to all-cause mortality was also assessed through variance decomposition. Correlation coefficients between age-standardised mortality rates and selected socio-economic variables were estimated for all powiats and for a group excluding large cities. Results: We demonstrated that regional differences between powiats in IHD mortality do not constitute a major factor behind regional mortality disparities in Poland. However, the spatial patterns for all-cause and IHD mortality in Polish powiats were both related to the level of urbanisation, with group of powiats characterised by the lowest IHD mortality comprising only large cities. The negative effect of large cities on the level of all-cause and IHD mortality was confirmed by the significant correlation between the socio-economic contextual variables, standing for the level of urbanisation, and IHD mortality. Conclusions: Ease of access to medical care in large cities and in particular to cardiology units is an important factor behind the levels of all-cause and IHD mortality in Poland.Wstęp: W 2010 r. różnica między najdłuższym i najkrótszym czasem trwania życia w województwach w Polsce wynosiła 2,5 roku dla kobiet i 3,6 roku dla mężczyzn. Pomimo występujących znacznych różnic terytorialnych w umieralności w Polsce, zjawisko to w dużym stopniu pozostaje niezbadane. Ze względu na dobrze rozpoznane we wcześniejszych badaniach znaczenie choroby niedokrwiennej serca (IHD) dla różnic w umieralności między krajami, między regionami w wybranych krajach, ale także między województwami, ta przyczyna zgonu jest dobrym parametrem do wytłumaczenia terytorialnych różnic w umieralności w Polsce. Cel: Celem badania była analiza wpływu IHD na terytorialne zróżnicowanie umieralności na poziomie powiatów w Polsce w latach 2006–2010 oraz wytłumaczenie zaobserwowanych różnic poprzez wybrane czynniki społeczno-ekonomiczne. Metody: W badaniu wykorzystano informacje dotyczące zgonów oraz liczby ludności na poziomie powiatów w latach 2006–2010. Terytorialne zróżnicowanie umieralności w Polsce opisano, opierając się na podstawowych statystykach dotyczących standaryzowanych współczynników zgonów ze względu na wszystkie przyczyny i standaryzowanych współczynników zgonów ze względu na IHD w powiatach. Wyznaczone współczynniki przedstawiono na mapach. Wpływ IHD na zróżnicowanie umieralności w Polsce oszacowano na podstawie dekompozycji wariancji współczynników zgonów w powiatach. Porównano też udział dużych miast w poszczególnych decylach rozkładu współczynników. Ponadto wyznaczono współczynniki korelacji między standaryzowanymi współczynnikami zgonów i wybranymi charakterystykami społeczno-ekonomicznymi dla wszystkich powiatów oraz dla grupy powiatów po wyeliminowaniu dużych miast. Wyniki: Mimo że IHD jest jedną z ważniejszych przyczyn zgonów w Polsce dla obu płci, różnice w umieralności z powodu tej choroby tylko w niewielkim stopniu były odpowiedzialne za ogólne zróżnicowanie współczynników umieralności w Polsce. Wzorzec terytorialny umieralności ze względu na IHD w Polsce wskazał na istotne różnice w poziomie umieralności ze względu na tę przyczynę między dużymi miastami i resztą powiatów. Zbliżony wzorzec terytorialny obserwowano jednocześnie dla wszystkich zgonów, które nastąpiły w latach 2006–2010. W rezultacie powiaty o najniższej umieralności ze względu na IHD (pierwszy decyl rozkładu w powiatach) stanowiły wyłącznie duże miasta. Natomiast w przypadku wszystkich przyczyn zgonów łącznie duże miasta stanowiły 70% powiatów o najniższej umieralności. Wpływ poziomu urbanizacji na umieralność ze względu na wszystkie przyczyny i ze względu na IHD potwierdzono także poprzez istotną wysoką dodatnią korelację między współczynnikami zgonów i czynnikami społeczno-ekonomicznymi uwzględnionymi w badaniu. Czynniki społeczno-ekonomiczne uwzględnione w badaniu wiązały się bezpośrednio w Polsce z poziomem urbanizacji lub sytuacją na rynku pracy w powiatach. Wyznaczone współczynniki korelacji między standaryzowanymi współczynnikami zgonów i czynnikami społeczno-ekonomicznymi po wyeliminowaniu z badanej grupy powiatów dużych miast okazały się nieistotne dla grupy czynników określających poziom urbanizacji powiatów. Ze względu na to, że wcześniejsze badania pokazały, że nie istnieją istotne różnice między obszarami miejskimi i wiejskimi w dostępie do szybkiej interwencji medycznej w przypadku zagrożenia życia, natomiast duże miasta charakteryzuje ułatwiony dostęp do specjalistycznej pomocy medycznej, uzyskany gradient umieralności interpretowano jako wynik różnic w dostępie do specjalistycznej opieki kardiologicznej, która występowała wyłącznie w dużych miastach. Wnioski: Wyniki analizy podkreśliły znaczenie różnic w dostępie do specjalistycznej opieki kardiologicznej w dużych miastach w Polsce dla terytorialnego zróżnicowania umieralności ze względu na IHD i umieralność ogółem