scholarly journals Could Historical Mortality Data Predict Mortality Due to Unexpected Events?

2021 ◽  
Vol 10 (5) ◽  
pp. 283
Author(s):  
Panagiotis Andreopoulos ◽  
Kleomenis Kalogeropoulos ◽  
Alexandra Tragaki ◽  
Nikolaos Stathopoulos
Keyword(s):  
Prediction Models ◽  
Population Aging ◽  
Mortality Data ◽  
The European Union ◽  
Unexpected Events ◽  
Probabilistic Distribution ◽  
Exogenous Factors ◽  
And Gender ◽  
Population Mortality ◽  
Aging Parameter

Research efforts focused on developing a better understanding of the evolution of mortality over time are considered to be of significant interest—not just to the demographers. Mortality can be expressed with different parameters through multiparametric prediction models. Based on the Beta Gompertz generalized Makeham (BGGM) distribution, this study aims to evaluate and map four of such parameters for 22 countries of the European Union, over the period 1960–2045. The BGGM probabilistic distribution is a multidimensional model, which can predict using the corresponding probabilistic distribution with the following parameters: infant mortality (parameter θ), population aging (parameter ξ), and individual and population mortality due to unexpected exogenous factors/events (parameters κ and λ, respectively). This work focuses on the random risk factor (λ) that can affect the entire population, regardless of age and gender, with increasing mortality depicting developments and trends, both temporally (past–present–future) and spatially (22 countries). Moreover, this study could help policymakers in the field of health provide solutions in terms of mortality. Mathematical models like BGGM can be used to achieve and highlight probable cyclical repetitions of sudden events (such as Covid-19) in different time series for different geographical areas. GIS context is used to map the spatial patterns of this estimated parameter as well as these variations during the examined period for both men and women.

Gender Differences in the Link Between Marital Status and the Risk of Cognitive Impairment: Results From the Korean Longitudinal Study of Aging

2021 ◽  
pp. 009141502110241
Author(s):  
Yujin Kim
Keyword(s):  
Cognitive Impairment ◽  
Longitudinal Study ◽  
Marital Status ◽  
Event History Analysis ◽  
Population Aging ◽  
Event History ◽  
Never Married ◽  
History Analysis ◽  
Married Men ◽  
And Gender

In the context of South Korea, characterized by increasing population aging and a changing family structure, this study examined differences in the risk of cognitive impairment by marital status and investigated whether this association differs by gender. The data were derived from the 2006–2018 Korean Longitudinal Study of Aging. The sample comprised 7,568 respondents aged 45 years or older, who contributed 30,414 person-year observations. Event history analysis was used to predict the odds of cognitive impairment by marital status and gender. Relative to their married counterparts, never-married and divorced people were the most disadvantaged in terms of cognitive health. In addition, the association between marital status and cognitive impairment was much stronger for men than for women. Further, gender-stratified analyses showed that, compared with married men, never-married men had a higher risk of cognitive impairment, but there were no significant effects of marital status for women.

scholarly journals Spatiotemporal Econometrics Models for Old Age Mortality in Europe

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1061
Author(s):  
Patricia Carracedo ◽  
Ana Debón
Keyword(s):  
Panel Data ◽  
Goodness Of Fit ◽  
Population Aging ◽  
European Population ◽  
Data Models ◽  
European Countries ◽  
Mortality Data ◽  
Panel Data Models ◽  
Estimation Of Parameters ◽  
Advantages And Disadvantages

In the past decade, panel data models using time-series observations of several geographical units have become popular due to the availability of software able to implement them. The aim of this study is an updated comparison of estimation techniques between the implementations of spatiotemporal panel data models across MATLAB and R softwares in order to fit real mortality data. The case study used concerns the male and female mortality of the aged population of European countries. Mortality is quantified with the Comparative Mortality Figure, which is the most suitable statistic for comparing mortality by sex over space when detailed specific mortality is available for each studied population. The spatial dependence between the 26 European countries and their neighbors during 1995–2012 was confirmed through the Global Moran Index and the spatiotemporal panel data models. For this reason, it can be said that mortality in European population aging not only depends on differences in the health systems, which are subject to national discretion but also on supra-national developments. Finally, we conclude that although both programs seem similar, there are some differences in the estimation of parameters and goodness of fit measures being more reliable MATLAB. These differences have been justified by detailing the advantages and disadvantages of using each of them.

scholarly journals A Two-Population Mortality Model to Assess Longevity Basis Risk

Risks ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 44
Author(s):  
Selin Özen ◽  
Şule Şahin
Keyword(s):  
Risk Reduction ◽  
Significant Risk ◽  
Reference Population ◽  
Mortality Data ◽  
Basis Risk ◽  
Mortality Model ◽  
Proposed Model ◽  
Population Mortality ◽  
Mortality Jumps ◽  
The Impact

Index-based hedging solutions are used to transfer the longevity risk to the capital markets. However, mismatches between the liability of the hedger and the hedging instrument cause longevity basis risk. Therefore, an appropriate two-population model to measure and assess longevity basis risk is required. In this paper, we aim to construct a two-population mortality model to provide an effective hedge against the basis risk. The reference population is modelled by using the Lee–Carter model with the renewal process and exponential jumps, and the dynamics of the book population are specified. The analysis based on the U.K. mortality data indicate that the proposed model for the reference population and the common age effect model for the book population provide a better fit compared to the other models considered in the paper. Different two-population models are used to investigate the impact of sampling risk on the index-based hedge, as well as to analyse the risk reduction regarding hedge effectiveness. The results show that the proposed model provides a significant risk reduction when mortality jumps and sampling risk are taken into account.

Future Costs of Long-term Care in Japan and Sweden

2017 ◽  
Vol 48 (1) ◽  
pp. 128-147 ◽  
Author(s):  
Mårten Lagergren ◽  
Noriko Kurube ◽  
Yasuhiko Saito
Keyword(s):  
Long Term Care ◽  
Population Change ◽  
Population Aging ◽  
Population Data ◽  
Epidemiological Data ◽  
The Other ◽  
Age Group ◽  
Term Care ◽  
And Gender

Population aging is expected to increase long-term care (LTC) costs in both Japan and Sweden. This study projected LTC costs for 2010 through 2040 for different assumptions of population change, LTC need by age group and gender, and LTC provided per level of need and cost in Japan and Sweden. Population data were taken from the official national forecasts. Needs projections were based on epidemiological data from the Nihon University Japanese Longitudinal Study of Aging and the Swedish Survey of Living Conditions. Data on LTC provision by need and cost were taken from nine Japanese municipalities collected by assessments in the LTC insurance system and from surveys in eight Swedish municipalities. Total initial costs were calibrated to official national figures. Two projections based on two different scenarios were made for each country from 2010 to 2040. The first scenario assumed a constant level of need for LTC by age group and gender, and the other assumed a continuation of the present LTC need trends until 2025. For Japan, this resulted in a projected cost increase of 93% for the one and 80% for the other; for Sweden it was 52% and 24%, respectively. The results reflected differences in population aging and health development.

scholarly journals Proteomic biomarker profiles and vascular dysfunction in angina with no obstructive coronary artery disease

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
A Ejupi ◽  
A Aziz ◽  
P Ong ◽  
B H Shafi ◽  
T Lange ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Prediction Model ◽  
Prediction Models ◽  
Vascular Dysfunction ◽  
Obstructive Coronary Artery Disease ◽  
Protein Biomarkers ◽  
Age And Gender ◽  
Artery Disease ◽  
And Gender

Abstract Background Coronary vascular dysfunction is a common cause of symptoms in patients with angina and no obstructed coronary arteries (ANOCA). Several endotypes have been defined but there are big gaps in our understanding of the underlying pathophysiology. Proteomic analyses may improve the understanding of the pathophysiology. Purpose Exploratory approach to 1) compare the proteomic biomarker profile across different types of vascular dysfunction in ANOCA and 2) assess the value of prediction models with protein biomarkers for vascular dysfunction in ANOCA. Methods We included 107 angina patients without previous coronary artery disease, left ventricular ejection fraction >45% and no obstructive coronary artery disease (CAD) (<50% stenosis of epicardial vessels) on coronary angiography. Three types of vascular dysfunction were assessed: 1) Vasomotor dysfunction (VMD) defined as epicardial or microvascular vasospasm on acetylcholine provocation, 2) Coronary microvascular dysfunction (CMD) defined as coronary flow velocity reserve (CFVR) ≤2.5 on echocardiography of the LAD on adenosine stimulation and 3) Reactive Hyperaemia Index (RHI) ≤1.67 as a measure of peripheral endothelial dysfunction. Blood samples were analysed for 184 protein biomarkers related to cardiovascular disease. Correlations between biomarkers and results of vascular function assessments were analysed with Pearson's correlation coefficient and visualized with volcano plots. Significantly correlated biomarkers (p<0.05) were tested in prediction models for their incremental value over age and gender with C-statistics. Results CFVR was correlated to 24 biomarkers before (figure 1a) and 2 biomarkers after adjustment for age and gender. The basic prediction model had AUC of 0.68 and was not significantly improved by adding biomarkers (figure 2a). RHI was correlated to 27 biomarkers before (figure 1b) and 10 biomarkers after adjustment for age and gender. The clinical prediction model was significantly improved (p=0.037) by adding TRAIL R2 and IL-18, in addition to age and gender, with an AUC of 84.4 (figure 2b). VMD was correlated to 14 biomarkers before (figure 1c) and 6 biomarkers after adjustment for age and gender. The prediction model was significantly improved (p=0.011) by adding HSP-27, RARRES-2 and SERPINA-12 in addition to age and gender in prediction of VMD with an AUC of 85.4 (figure 2c). Conclusion Several biomarkers were associated with vascular dysfunction in ANOCA patients with little overlap between different endotypes. We identified biomarkers that may contribute to the understanding of the underlying pathophysiology and have applications for screening. Results need to be confirmed in larger studies. FUNDunding Acknowledgement Type of funding sources: Public hospital(s). Main funding source(s): Department of Cardiology, Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Denmark.Department of Cardiology and Angiology, Robert Bosch Krankenhaus, Stuttgart, Germany

scholarly journals Policy evaluation and gender mainstreaming in the European Union: the perfect (mis)match?

2020 ◽  
Vol 3 (2) ◽  
pp. 277-294
Author(s):  
Rachel Minto ◽  
Lut Mergaert ◽  
María Bustelo
Keyword(s):  
European Union ◽  
Policy Evaluation ◽  
Research Policy ◽  
Current Approach ◽  
Gender Mainstreaming ◽  
The European Union ◽  
Implementation Phase ◽  
Better Regulation ◽  
And Gender ◽  
Social Agendas

This article assesses the ability of the European Commission’s current approach to policy evaluation to evaluate gender mainstreaming and, in turn, other cross-cutting social agendas (Articles 8–10 TFEU). Taking European Union research policy as a case study, through our analysis, we reveal mismatches between current evaluation standards adopted within the Better Regulation framework and requirements for effectively assessing progress towards cross-cutting social objectives, such as gender equality. The article concludes with a series of recommendations to overcome the identified shortcomings. Our analysis constitutes a key contribution to the development of feminist scholarship on the post-implementation phase of the policy process.

scholarly journals Cross-Temporal and Cross-National Poverty and Mortality Rates among Developed Countries

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Johan Fritzell ◽  
Olli Kangas ◽  
Jennie Bacchus Hertzman ◽  
Jenni Blomgren ◽  
Heikki Hiilamo
Keyword(s):  
Population Health ◽  
Health Indicators ◽  
Developed Countries ◽  
Mortality Data ◽  
Social Risk ◽  
Welfare Regimes ◽  
Cross Sectional ◽  
Relative Poverty ◽  
And Gender ◽  
The Relationship

A prime objective of welfare state activities is to take action to enhance population health and to decrease mortality risks. For several centuries, poverty has been seen as a key social risk factor in these respects. Consequently, the fight against poverty has historically been at the forefront of public health and social policy. The relationship between relative poverty rates and population health indicators is less self-evident, notwithstanding the obvious similarity to the debated topic of the relationship between population health and income inequality. In this study we undertake a comparative analysis of the relationship between relative poverty and mortality across 26 countries over time, with pooled cross-sectional time series analysis. We utilize data from the Luxembourg Income Study to construct age-specific poverty rates across countries and time covering the period from around 1980 to 2005, merged with data on age- and gender-specific mortality data from the Human Mortality Database. Our results suggest not only an impact of relative poverty but also clear differences by welfare regime that partly goes beyond the well-known differences in poverty rates between welfare regimes.

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