Changes in educational differentials in old-age mortality in Finland and Sweden between 1971-1975 and 1996-2000

The majority of the studies on developed countries confirm that socioeconomic mortality inequalities have been persisting or even widening. It has also been suggested that inequalities have been becoming increasingly important for old ages. The vast majority of the findings on mortality differentials rely on life table or aggregated mortality measures. However, conventional mean lifespan (life expectancy) hides important characteristics of the distribution of lifespan. Modal age at death and measures of disparity provide additional important insights on longevity, especially when focusing on mortality and survival at old ages. In this paper, using high quality census-linked data and both conventional life expectancy and distribution of life span measures, we systematically assess the direction and magnitude of changes in mortality differences at old ages in Sweden and Finland over the period 1971 to 2000. We found that educational gap in life expectancy at age 65 increased in both countries. Although the results suggest that life expectancy gap was largely explained by differential mortality due to cardiovascular system diseases, the role of other causes of death (especially cancers) has also increased. The educational gap in the modal age at death for Swedish males and Finnish females decreased, whereas it remained at the same level or slightly increased for Finnish males and Swedish females. Life span disparity was initially lower in low education groups, but eventually became higher than in high education group

Divergent trends in lifespan variation during mortality crises.

BACKGROUND: Lifespan variation has been attracting attention as a measure of population health and mortality. Several studies have highlighted its strong inverse relationship with life expectancy during periods of steady mortality decline, but this association weakens, and even reverses, when mortality does not improve equally over age. To date no study has comprehensively explored the behaviour of lifespan variation when mortality increases significantly. OBJECTIVE: We investigate lifespan variation trends around various mortality crises, focusing on agespecific contributions and sex differences. METHODS: Drawing data from the Human Mortality Database and Meslé and Vallin’s Ukrainian lifetables, we analyse five European epidemics and famines across three centuries. We use six measures of lifespan variation and adopt the linear integral method of decomposition. RESULTS: During these crises, relative lifespan variation increases, while absolute variation declines, and subsequently both quickly revert to pre-crisis levels. We show that mortality at older ages leads to a temporary increase in absolute - but not relative - variation. The lifespan variation of females is less affected than that of males, because of differences in the impact of infant and child mortality. CONCLUSIONS: Even when infant mortality is high, mortality at older ages can influence lifespan variation. Our results also underscore the sex differences in the vulnerability of young individuals in periods of extreme mortality. CONTRIBUTION: By underlining different trends of lifespan variation by sex and indicator, we offer new insight into the consequences of mortality crises. Contrary to what is often asserted, we show that the choice of lifespan variation indicator is not always inconsequential

Understanding Health Deterioration and the Dynamic Relationship between Physical Ability and Cognition among a Cohort of Danish Nonagenarians

This study aims to determine how demographics, socioeconomic characteristics, and lifestyle affect physical and cognitive health transitions among nonagenarians, whether these transitions follow the same patterns, and how each dimension affects the transitions of the other. We applied a multistate model for panel data to 2262 individuals over a 2-year follow-up period from the 1905 Danish Cohort survey. Within two years from baseline, the transition probability from good to bad physical health—ability to stand up from a chair—was higher than dying directly (29% vs. 25%), while this was not observed for cognition (24% vs. 27%) evaluated with Mini-Mental State Examination—a score lower than 24 indicates poor cognitive health. Probability of dying either from bad physical or cognitive health condition was 50%. Health transitions were associated with sex, education, living alone, body mass index, and physical activity. Physical and cognitive indicators were associated with deterioration of cognitive and physical status, respectively, and with survivorship from a bad health condition. We conclude that physical and cognitive health deteriorated differently among nonagenarians, even if they were related to similar sociodemographic and lifestyle characteristics and resulted dynamically related with each other

Analysing contributions of ages and causes of death to gender gap in life expectancy using functional data analysis

Il lavoro consiste in un’applicazione dell’analisi dei dati funzionali (FDA) a dati demografici: si analizza il contributo delle età e cause di morte alle differenze di genere nella speranza di vita in 14 paesi europei ed extraeuropei nel periodo compreso tra il 1998 e il 2016. I dati sui decessi per causa provengono dallo Human Cause of Death Database (HCD), mentre le tavole di mortalità sono tratte dallo Human Mortality Database (HMD). L'analisi consente di individuare due componenti principali che colgono gran parte della variabilità e che descrivono rispettivamente le differenze nei contributi causa-specifici e nei contributi età-specifici tra i paesi. Nel tempo, si osserva un aumento dei contributi più rilevanti soprattutto intorno all'età modale ed uno spostamento degli stessi verso l'età avanzata.The work consists of application of functional data analysis (FDA) to demographic data: it analyses the contribution of ages and causes of death to gender gap in life expectancy in 14 European and non-European countries between 1998 and 2016. Causes-of-death data and life tables were retrieved from the Human Causes-of-Death Database (HCD) and from the Human Mortality Database (HMD). Our analysis allows to identify two main components that capture most of the variability and which describe differences in cause-specific and in age-specific contributions among countries, respectively. Over time, an increase in the most relevant contributions is observed, especially around the modal age and a shift of the contributions towards older age