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Background: The concept of "premature mortality" is at the heart of many national and global health measurement and benchmarking efforts. However, despite the intuitive appeal of its underlying concept, it is far from obvious how to best operationalise it. The previous work offers at least two basic approaches: an absolute and a relative one. The former—and far more widely used— approach sets a unique age threshold (e.g. 65 years), below which deaths are defined as premature. The relative approach derives the share of premature deaths from the country-specific age distribution of deaths in the country of interest. The biggest disadvantage of the absolute approach is that of using a unique, arbitrary threshold for different mortality patterns, while the main disadvantage of the relative approach is that its estimate of premature mortality strongly depends on how the senescent deaths distribution is defined in each country. Method: We propose to overcome some of the downsides of the existing approaches, by combining features of both, using a hierarchical model, in which senescent deaths distribution is held constant for each country as a pivotal quantity and the premature mortality distribution is allowed to vary across countries. In this way, premature mortality estimates become more comparable across countries with similar characteristics. Results: The proposed hierarchical models provide results, which appear to align with related evidence from specific countries. In particular, we find a relatively high premature mortality for the United States and Denmark. Conclusions: While our hybrid approach overcomes some of the problems of previous measures, some issues require further research, in particular the choice of the group of countries that a given country is assigned to and the choice of the benchmarks within the groups. Hence, our proposed method, combined with further study addressing these issues, could provide a valid alternative way to measure and compare premature mortality across countries. [ABSTRACT FROM AUTHOR]

OBJECTIVES: The concurrent contributions of dynamic, interrelated late-life parameters, such as body mass index (BMI), cognition, and physical functioning on mortality in the elderly are unclear, as is the influence of APOE genotype. We explored these measures in relation to 7-year mortality in long-lived Italian elderly. DESIGN: A representative, age-stratified, population sample. SETTING: The Treviso Longeva (TRELONG) Study, in Treviso, Italy. PARTICIPANTS: Three hundred eleven men and 357 women, aged 70 years and older (mean age 84 ± 8 years). MEASUREMENTS: Seven-year mortality, BMI, Mini-Mental State Examination (MMSE) score, Activities of Daily Living (ADL), APOE genotype, and a variety of clinical and survey data. RESULTS: In separate age- and sex-adjusted analyses, BMI <18.5 kg/m(2), MMSE <=24, and ADL <6, were associated with greater 7-year mortality among adults aged 70 years and older. In a multivariate model including all factors, MMSE <=24, and ADL <6 were associated with greater mortality; BMI >=30 kg/m(2) was protective. There were no interactions between BMI, MMSE, or ADL. When excluding those dying within 3 years of baseline, only an MMSE <=24 was related to mortality. APOE4 was not related to mortality. CONCLUSION: Higher MMSE score, higher ADL score, and higher BMI, independent of age, sex, and other factors, are markers for longer life among northern Italian adults aged 70 years or older. Global cognition, BMI, and physical functioning, assessed by short, simple tests are profound indicators of death within less than a decade. [ABSTRACT FROM AUTHOR]

In many countries of the world, COVID-19 pandemic has led to exceptional changes in mortality trends. Some studies have tried to quantify the effects of Covid-19 in terms of a reduction in life expectancy at birth in 2020. However, these estimates might need to be updated now that, in most countries, the mortality data for the whole year are available. We used data from the Human Mortality Database (HMD) Short-Term Mortality Fluctuations (STMF) data series to estimate life expectancy in 2020 for several countries. The changes estimated using these data and the appropriate methodology seem to be more pessimistic than those that have been proposed so far: life expectancy dropped in the Russia by 2.16 years, 1.85 in USA, and 1.27 in England and Wales. The differences among countries are substantial: many countries (e.g. Denmark, Island, Norway, New Zealand, South Korea) saw a rather limited drop in life expectancy or have even seen an increase in life expectancy., Competing Interests: The authors have declared that no competing interests exist.

This study analyzed whether there are different patterns of mortality decline among low-mortality countries by identifying the role played by all the mortality components. We implemented a cluster analysis using a functional data analysis (FDA) approach, which allowed us to consider age-specific mortality rather than summary measures, as it analyses curves rather than scalar data. Combined with a functional principal component analysis, it can identify what part of the curves is responsible for assigning one country to a specific cluster. FDA clustering was applied to the data from 32 countries in the Human Mortality Database from 1960 to 2018 to provide a comprehensive understanding of their patterns of mortality. The results show that the evolution of developed countries followed the same pattern of stages (with different timings): (1) a reduction of infant mortality, (2) an increase of premature mortality and (3) a shift and compression of deaths. Some countries were following this scheme and recovering the gap with precursors; others did not show signs of recovery. Eastern European countries were still at Stage (2), and it was not clear if and when they will enter Stage 3. All the country differences related to the different timings with which countries underwent the stages, as identified by the clusters., Competing Interests: Conflict of interestThe authors declare that they have no conflict of interest., (© The Author(s) 2021.)

Life expectancy is most commonly measured for a period (corresponding to mortality within a given year) or for a specific birth cohort. Although widely used, period and cohort life expectancy have limitations as their time-trends often show disparities and can mask the historical mortality experience of all cohorts present at a given time. The truncated cross-sectional average length of life, or TCAL, is a period measure including all available cohort mortality information, irrespective of whether all cohort members have died. It is particularly useful for comparing cohort mortality between populations. This study extends TCAL by disentangling causes of death contributions. The strength of the approach is that it allows identification of mortality differences in cohorts with members still alive, as well as identification of which ages and causes of death contribute to mortality differentials between populations. Application of the method to Japan shows that over the period 1950-2014 a major contributor to TCAL differences with other high-longevity countries was its lower cardiovascular disease mortality., (© The Author(s) 2020; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Reliable mortality forecasts are an essential component of healthcare policies in ageing societies. The Lee-Carter method and its later variants are widely accepted probabilistic approaches to mortality forecasting, due to their simplicity and the straightforward interpretation of the model parameters. This model assumes an invariant age component and linear time component for forecasting. We apply the Lee-Carter method on smoothed mortality rates obtained by LASSO-type regularization and hence adjust the time component with the observed lifespan disparity. Smoothing with LASSO produces less error during the fitting period than do spline-based smoothing techniques. As a more informative indicator of longevity, matching with lifespan disparity makes the time component more reflective of mortality improvements. The forecasts produced by the new method were more accurate during out-of-sample evaluation and provided optimistic forecasts for many low-mortality countries., Competing Interests: Conflict of interestThe authors declare that they have no competing interests., (© Springer Nature B.V. 2020.)

Premature mortality is often a neglected component of overall deaths, and the most difficult to identify. However, it is important to estimate its prevalence. Following Pearson's theory about mortality components, a definition of premature deaths and a parametric model to study its transformations are introduced. The model is a mixture of three distributions: a Half Normal for the first part of the death curve and two Skew Normals to fit the remaining pieces. One advantage of the model is the possibility of obtaining an explicit equation to compute life expectancy at birth and to break it down into mortality components. We estimated the mixture model for Sweden, France, East Germany and Czech Republic. In addition, to the well-known reduction in infant deaths, and compression and shifting trend of adult mortality, we were able to study the trend of the central part of the distribution of deaths in detail. In general, a right shift of the modal age at death for young adults is observed; in some cases, it is also accompanied by an increase in the number of deaths at these ages: in particular for France, in the last twenty years, premature mortality increases., (© The Author(s) 2020.)

A new mortality model based on a mixture distribution function is proposed. We mix a half-normal distribution with a generalization of the skew-normal distribution. As a result, we get a six-parameter distribution function that has a good fit with a wide variety of mortality patterns. This mixture model is fitted to several mortality data schedules and compared with the Siler (five-parameter) and Heligman-Pollard (eight-parameter) models. Our proposal serves as a convenient compromise between the Heligman-Pollard model (which ensures a good fit with data but is often overparameterized) and the Siler model (which is more compact but fails to capture 'accident humps').

Background: The Lee-Carter method and its later variants are widely accepted extrapolative methods for forecasting mortality and life expectancy in industrial countries due to their simplicity and availability of high quality long time series data., Objective: We compared and contrasted mortality forecasting models for higher mortality regimes that lack long time series data of good quality, which is common in several Central and Eastern European (CEE) countries., Data and Methods: We utilized seven different variants of the Lee-Carter method and coherent mortality forecasts of various CEE countries, and the Bayesian Hierarchical Model used by the United Nations to produce probabilistic forecasts. The data of nine CEE countries with comparatively higher mortality have been considered., Results: The performance of the forecasting models for the nine CEE countries was found to be lower than that observed for low-mortality countries. No model gives uniquely best performance for all the nine CEE countries. Most of the LC variants produced lower forecasts of life expectancies than current life expectancy values for Belarus, Russia, and Ukraine. A coherent mortality forecast could not overcome the limitations of single population forecasting techniques due to increasing mortality differences between these countries over the fitting period (mortality divergence). In the same context, the use of the probabilistic forecasting technique from the Bayesian framework resulted in a better forecast than some of the extrapolative methods but also produced a wider prediction interval for several countries. The more detailed analysis for Hungary indicates that a better fit of certain forecasting methods may occur in the later part of the life span rather than the whole life span., Conclusion: These findings imply the necessity of inventing a new forecasting technique for high-mortality countries., Competing Interests: Both authors declare that they have no competing interests.Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Introduction: It has been reported that elderly subjects have a compromised ability to produce melatonin nightly, and that reduced melatonin levels may be a risk factor for cancer. The purpose of this study was to evaluate the relationship between melatonin levels and chronic diseases in a cohort of elderly subjects using the Charlson comorbidity index (CCI)., Design: We performed a secondary data analysis of a longitudinal study of a representative, age-stratified, sample population., Setting: The Treviso Longeva (Trelong) study, in Treviso, Italy., Participants: A total of 114 men and 146 women, aged 77 years and older, still alive after 7 years of follow-up., Measurements: As an estimation of serum melatonin secretion levels, urinary 6-sulfatoxymelatonin (aMT6s) was assayed in the urine of 260 elderly subjects using an enzyme-linked immunosorbent assay (ELISA) kit (product 01-EK-M6S, ALPCO Immunoassays, Windham, NH). All aMT6s levels were creatinine standardized ([aMT6s]/[creatinine]), and the CCI was calculated., Results: The melatonin levels decreased with aging despite not reaching statistical significance, and the decrease was more evident in males than in females (40.5 ng vs 47.0 ng aMT6s/mg creatinine, ns). Melatonin levels were significantly lower in patients reporting insomnia (p=0.05). The CCI score was inversely correlated with the levels of melatonin (p=0.03). Melatonin levels of subjects affected by CCI pathologies were significantly lower than those of healthy subjects (p=0.03) and of subjects suffering from diseases not included in the CCI and, therefore, less severe (p=0.03)., Conclusion: Melatonin appears to be a marker of disease state and severity, as well as of sleep disorders, in the elderly. These early findings would confirm the protective role of melatonin against several chronic diseases. The benefits of this agent as a possible medication should be more thoroughly clinically tested.

Human sirtuins are seven proteins with deacetylase activity that are emerging as key modulators of basic physiological functions. Some evidence links SIRT3 to longevity in mammals. This study aimed to investigate whether variants within SIRT3 gene were associated to human longevity. We analyzed 549 genomic DNA collected during the prospective study "Treviso Longeva," including elderly over 70 years of age from the municipality of Treviso, a small city in the northeast of Italy. We genotyped SIRT3 rs3825075, rs4980329, and rs11555236 single nucleotide polymorphisms (SNPs) by real-time polymerase chain reaction allelic discrimination assay. A cross-sectional analysis performed by comparing people over and under 85 years of age did not evidence association among the SIRT3 SNPs and longevity. However, when we performed a longitudinal analysis considering mortality as a dependent variable, we observed an association of SIRT3 rs11555236 and rs4980329 with longevity in the whole population (p values corrected for potential confounders = 0.04 and 0.03, respectively). After stratification according to gender, the same SNPs were associated to female longevity only (p values corrected for potential confounders = 0.03 and 0.02, respectively). Finally, as rs11555236 was reported to be in linkage disequilibrium with a putative functional enhancer within the SIRT3 gene, we assessed whether rs11555236 genotypes correlated with a different level of SIRT3 protein in peripheral blood mononuclear cells. We found an increased level of SIRT3 in subjects homozygous for the (T) allele. We suggest that SIRT3 genetic variability might be relevant for the modulation of human longevity in the Italian population.

Background: The Multidimensional Prognostic Index (MPI) based on a comprehensive geriatric assessment has been developed to predict mortality in hospitalized elderly patients. The Treviso Dementia (TREDEM) Study is an observational prospective cohort study of 1,364 outpatients evaluated at the Cognitive Impairment Center in Treviso, Italy from 2000 to January 2010., Objective: To use the MPI in the TREDEM outpatient setting to assess the correlation of MPI with mortality and hospitalizations for acute cases that occurred after the date of assessment., Methods: MPI was consecutively applied to the last 340 of 1,364 outpatients who were evaluated at the Center from 2008 to January 2010, after the first publication of MPI index in 2008. Participants' mortality was verified by linking the cohort with Registries of Municipalities, National Register of Revenue Authorities, and Nominal Register of Causes of Death. Data about hospitalizations for acute cases that occurred within 12 months after the date of assessment were obtained from all Italian hospitals. A Cox regression method was used to investigate the effect of MPI upon mortality and hospitalizations, also considering confounder factors such as age and gender., Results: 114 men and 226 women, aged 52.1-99 years (mean age 80.4 years), were studied and had an MPI mean of 0.41. On 15 February 2013, 100 were deceased, and average hospitalizations for acute cases were 0.3, days 3.8. For MPI scores between 0 and 1, the increase in the probability of death was more than nine times (odds: 9.53 p = 0.0002) and of hospitalization was more than six times (odds: 6.50, p = 0.0079)., Conclusion: MPI discloses the risk of death and of hospitalizations for acute cases in outpatients affected by cognitive impairment.

Background: The incidence of dementia increases exponentially with age but knowledge of real disease-modifying interventions is still limited., Objectives: To describe the study design and methods of a large prospective cohort study aimed at exploring the complex underlying relationships existing among cognition, frailty, and health-related events in older persons with cognitive impairment., Design: Prospective cohort study of a representative population of outpatients attending the Treviso Cognitive Impairment Center between 2000 and 2010., Setting: The TREVISO DEMENTIA (TREDEM) Study conducted in Treviso, Italy., Participants: 490 men and 874 women, mean age 79.1 ± 7.8 years (range 40.2-100 years)., Measurements: Physiological data, biochemical parameters, clinical conditions, neuroradiological parameters (e.g., brain atrophy and cerebral vascular lesions identified by computerized tomography scans), neuropsychological assessment, and physical function markers were measured at baseline. Patients were followed-up to 10 years., Results: The final sample included in the study was predominantly composed of women and characterized by an initial physical function impairment and increased vascular risk profile. Cognitive function of the sample population showed moderate cognitive impairment (Mini Mental State Examination 20.2 ± 6.3; Clinical Dementia Rating 1.2 ± 0.7), and a prevalence of vascular dementia of 26.9%. Cortical, subcortical and hippocampus atrophy were all significantly correlated with age and cognitive function., Conclusion: Results obtained from the preliminary analyses conducted in the TREDEM study suggest that the database will support the accomplishment of important goals in understanding the nature of cognitive frailty and neurodegenerative diseases.

Background: Socio-economic inequalities in health have become a major public health concern in Europe. The measurement of health inequalities over time and across countries does, however, remain a challenge. Previous European evidence found that health inequalities have been increasing in most countries, with greatly varying degrees., Methods: The authors use the European Labour Force Survey (ELFS), with its unprecedented coverage of years and countries, as a potential complementary source for the measurement of health inequality. The ELFS provides information on sickness absence or reduced labour supply attributable to ill health. After constructing four separate and one overall health indicator, the authors compute health inequality indices for all countries and years, and analyse their trends. The authors also examine the sensitivity of the health inequality measures to different proxies of socio-economic status and., Results: Health inequalities in the working age population have been increasing for several countries, but also decreasing in about as many countries, while they remained stable in a minority of countries. These results are not too sensitive to the various proxies for socio-economic status we employ, but they are sensitive to the specific health indicator from which the inequality index is derived., Conclusions: While not without its problems, the ELFS may offer a useful additional and hitherto unexploited resource for the measurement of socio-economic inequalities in health across European countries and over time. Future research should try to understand how and why health inequality trends differ between different surveys as much as they appear to do in light of the present findings.

Background: Albumin excretion rate has been found to be associated with increased risk of mortality in several clinical settings. We assessed the relationship between urinary albumin and 7-year mortality in a cohort of patients with acute myocardial infarction (AMI)., Methods: In this prospective study, we examined 505 white patients admitted with AMI to the intensive care unit of 3 hospitals. Main end points were nonearly all-cause and cardiovascular (CV) mortality. Albumin-to-creatinine ratio (ACR) was measured by radioimmunoassay on the first, third, and seventh days after admission. Risk estimates were made using Cox proportional-hazard model and relative odds. Forty patients (7.9%) died early inhospital, and 175 (34.7%) died during the rest of the follow-up (nonearly mortality)., Results: The ACR measured on the third day predicted the occurrence of 7-year nonearly all-cause and CV mortality. Hazard ratios for ACR > or =0.97 mg/mmol were 3.0 (95% confidence limit 2.2-4.1), P < .0001, for nonearly all-cause mortality and 3.5 (95% confidence limit 2.5-5.0), P < .0001, for CV mortality. Correspondent fully adjusted hazard ratios were 1.9 (95% CI 1.4-2.6), P < .0001, and 2.2 (95% CI 1.5-3.2), P < .0001, respectively. By adding ACR to the 18-variable predictive model, ACR improved significantly both the goodness of fitting of the model for nonearly all-cause (P < .0001) and CV mortality (P < .0001) and the C-statistic value (P < .0001 and P = .002 for nonearly all-cause and CV mortality, respectively). Similar results were obtained for ACR measured on the first day or the seventh day., Conclusions: An early increase of urinary albumin in AMI is a strong independent predictor of long-term adverse clinical outcome. The ACR improved clinical prediction over and above baseline traditional multivariable risk models.