29 research outputs found
Relation of the Weibull Shape Parameter with the Healthy Life Years Lost Estimates: Analytic Derivation and Estimation from an Extended Life Table
Matsushita et al (1992) have done an interesting finding. They observed that
the shape parameter of the Weibull model presented systematic changes over time
and age when applied to mortality data for males and females in Japan. They
have also estimated that this parameter was smaller in the 1891-1898 data in
Japan compared to the 1980 mortality data and they presented an illustrative
figure for females where the values of the shape parameter are illustrated on
the diagram close to the corresponding survival curves. However, they have not
provided an analytical explanation of this behavior of the shape parameter of
the Weibull model. The cumulative hazard of this model can express the additive
process of applying a force in a material for enough time before cracking. To
pass to the human data, the Weibull model and the cumulative hazard can express
the additive process which disabilities and diseases cause the human organism
during the life span leading to healthy life years lost. In this paper we
further analytically derive a more general model of survival-mortality in which
we estimate a parameter related to the Healthy Life Years Lost (HLYL) and
leading to the Weibull model and the corresponding shape parameter as a
specific case. We have also demonstrated that the results found for the general
HLYL parameter we have proposed provides results similar to those provided by
the World Health Organization for the Healthy Life Expectancy (HALE) and the
corresponding HLYL estimates. An analytic derivation of the mathematical
formulas is presented along with an easy to apply Excel program. This program
is an extension of the classical life table including four more columns to
estimate the cumulative mortality, the average mortality, the person life years
lost and finally the HLYL parameter bx. The latest versions of this program
appear in the Demographics2019 websit
Chaos in Simple Rotation-Translation Models
The chaotic properties of simple two-dimensional rotation-translation models
are explored and simulated. The models are given in difference equation forms,
while the corresponding differential equations systems are studied and the
resulting trajectories in the plane are explored and illustrated in the
computer experiments done. Characteristic patterns, egg-shaped forms and
central chaotic bulges are present when particles are introduced in the
rotating system. The resulting forms and chaotic attractors mainly depend on
the form of the nonlinear function expressing the rotation angle. Several cases
are studied corresponding to a central force rotation system.Comment: 18 pages, 28 figure
Properties of a Stochastic Model for Life Table Data: Exploring Life Expectancy Limits
In this paper we explore the life expectancy limits by based on the
stochastic modeling of mortality and applying the first exit or hitting time
theory of a stochastic process. The main assumption is that the health state or
the "vitality", according to Strehler and Mildvan, of an individual is a
stochastic variable and thus it was introduced and applied a first exit time
density function to mortality data. The model is used to estimate the
development of mortality rates in the late stages of the human life span, to
make better fitting to population mortality data including the infant
mortality, to compare it with the classical Gompertz curve, and to make
comparisons between the Carey med-fly data and the population mortality data
estimating the health state or "vitality" functions. Furthermore, we apply the
model to the life table data of Italy, France, USA, Canada, Sweden, Norway and
Japan, and we analyze the characteristic parameters of the model and make
forecasts.Comment: 9 pages, 2 figure
A Quantitative Method for Estimating the Human Development Stages by Based on the Health State Function Theory and the Resulting Deterioration Process
The Health State Function theory is applied to find a quantitative estimate
of the Human Development Stages by defining and calculating the specific age
groups and subgroups. Early and late adolescence stages, first, second and
third stages of adult development are estimated along with the early, middle
and old age groups and subgroups. We briefly present the first exit time theory
used to find the health state function of a population and then we give the
details of the new theoretical approach with the appropriate applications to
support and validate the theoretical assumptions. Our approach is useful for
people working in several scientific fields and especially in medicine,
biology, anthropology, psychology, gerontology, probability and statistics. The
results are connected with the speed and acceleration of the deterioration of
the human organism during age as a consequence of the changes in the first,
second and third differences of the Health State Function and of the
Deterioration Function.
Keywords: Human development stages, Deterioration, Deterioration function,
Human Mortality Database, HMD, World Health Organization, WHO, Quantitative
methods, Health State Function, Erikson's stages of psychosocial development,
Piaget method, Sullivan method, Disability stages, Light disability, Moderate
disability, Severe disability stage, Old ages, Critical ages.Comment: 19 pages, 9 figures, 8 table
A Method for Estimating the Total Loss of Healthy Life Years: Applications and Comparisons in UK and Scotland
We propose a method of estimating the Total Loss of Healthy Life Years based
on the first exit time theory for a stochastic process, the resulting Health
State Function and the Deterioration Function estimated as the curvature of the
health state function. We have done many applications in UK and Scotland and
Sweden supporting our theory. Furthermore it was proven that both the WHO and
EU estimates of the healthy life expectancy can result from our method. The WHO
system takes into account the severe and moderate causes in estimating the loss
of healthy life years; instead the EU system calculates the total loss of
healthy life years. For both cases our methodology provides both estimators
from only death and population data. The advantages of our method are
straightforward. We do not need survey data to make the calculations. The
resulting estimates should be used to test and improve the existing survey
based methodologies. While the WHO and EU systems tend to approach each other
differences continue to appear based on the methodology of the related surveys
and the analysis of data. Two main schools are working to these directions one
based on USA the Institute for Health Metrics and Evaluation (IHME) headed by
Christopher J.L. Murray and contributors in all over the world and the European
Health and Life Expectancy Information System (EHLEIS) with Jean-Marie Robine
and a team from the EU member states. Keywords: Deterioration, Loss of healthy
years, HALE, DALE, World Health Organization, WHO, European Union, EU, EHEMU,
IHME, EHLEIS, Healthy life expectancy, Life expectancy.Comment: 15 pages, 8 figures, 4 table
Modeling the Health Expenditure in Japan, 2011. A Healthy Life Years Lost Methodology
The Healthy Life Years Lost Methodology (HLYL) is introduced to model and
estimate the Health Expenditure in Japan in 2011. The HLYL theory and
estimation methods are presented in our books in the Springer Series on
Demographic Methods and Population Analysis vol. 45 and 46 titled: Exploring
the Health State of a Population by Dynamic Modeling Methods and Demography and
Health Issues: Population Aging, Mortality and Data Analysis. Special
applications appear in Chapters of these books as in The Health-Mortality
Approach in Estimating the Healthy Life Years Lost Compared to the Global
Burden of Disease Studies and Applications in World, USA and Japan and in
Estimation of the Healthy Life Expectancy in Italy Through a Simple Model Based
on Mortality Rate by Skiadas and Arezzo. Here further to present the main part
of the methodology with more details and illustrations, we develop and extend a
life table important to estimate the healthy life years lost along with the
fitting to the health expenditure in the related case. The application results
are quite promising and important to support decision makers and health
agencies with a powerful tool to improve the health expenditure allocation and
the future predictions.Comment: 9 pages, 7 figure
The Health State Function, the Force of Mortality and other Characteristics resulting from the First Exit Time Theory applied to Life Table Data
In this paper we summarize the main parts of the first exit time theory
developed in connection to the life table data and the resulting theoretical
and applied issues. Several new tools arise from the development of this theory
and especially the Health State Function and some important characteristics of
this function. Special attention has being done in the presentation of the
health state function along with the well established theory for the Force of
Mortality and the related applications as are the life tables and the
estimation of life expectancies. A main part of this work is the formulation of
the appropriate non-linear analysis program including a model which provides an
almost perfect fit to life table data. This model, proposed in 1995 is now
expanded as to include the mortality excess for the age group from 15-30 years.
A version of the program is given in Excel and provided at the website:
http://www.cmsim.netComment: 20 pages, 12 figure
Estimating the Healthy Life Expectancy from the Health State Function of a Population in Connection to the Life Expectancy at Birth
Following our previous works on the health state of a population and the
related health state function we proceed in developing a method to estimate the
Healthy Life Expectancy in connection to the relative impact of the Mortality
Area in the health state function graph. The resulting tools are applied to the
data sets for 1990, 2000 and 2009 for the Countries of the World Health
Organization (WHO). The application is done in the Excel Chart and it is ready
to be used for other time periods. The results are compared with the estimates
presented in the WHO report for 2000 showing a good relationship between the
estimates of the two methods. However, our proposed method, not based on
collection of data for diseases and other causes affecting a healthy life, is
more flexible. We can estimate the healthy life years from various time periods
when information related to diseases is missing. Keywords: Health state
function, Healthy life expectancy, Deterioration, Loss of healthy years, HALE,
DALE, World Health Organization, WHOComment: 17 pages, 8 figures, 4 table
Direct Healthy Life Expectancy Estimates from Life Tables with a Sullivan Extension. Bridging the Gap Between HALE and Eurostat Estimates
The analytic derivation of a more general model of survival-mortality and the
estimation of a parameter bx related to the Healthy Life Years Lost (HLYL) is
followed with the formulation of a computer program providing results similar
to those of the World Health Organization for the Healthy Life Expectancy
(HALE) and the corresponding HLYL estimates. This program is an extension of
the classical life table including more columns to estimate the cumulative
mortality, the average mortality, the person life years lost and finally the
HLYL parameter bx. Evenmore, a further extension of the Excel program based on
the Sullivan method provides estimates of the Healthy Life Expectancy at every
year of the lifespan for five different types of estimates that are the Direct,
WHO, Eurostat, Equal and Other. Estimates for several countries are presented.
It is also presented a methodology and a program to bridge the gap between the
World Health Organization (HALE) and Eurostat (HLE) healthy life expectancy
estimates. The latest version of this program (SKI-6) appear in the
Demographics2020 website.Comment: 14 pages, 10 figures, 2 tables. arXiv admin note: substantial text
overlap with arXiv:1904.1012
Verifying the HALE measures of the Global Burden of Disease Study: Quantitative Methods Proposed
To verify the Global Burden of Disease Study and the provided healthy life
expectancy (HALE) estimates from the World Health Organization (WHO) we propose
a very simple model based on the mortality {\mu}x of a population provided in a
classical life table and a mortality diagram. We use the abridged life tables
provided by WHO. Our estimates are compared with the HALE estimates for the
World territories and the WHO countries. Even more we have developed the
related simple program in Excel which provides immediately the Life Expectancy,
the Loss of Healthy Life Years and the Healthy Life Expectancy estimate. We
also apply the health state function theory to have more estimates and
comparisons. The results suggest improved WHO estimates in recent years for the
majority of the cases. Keywords: Health state function, Healthy life
expectancy, Mortality Diagram, Loss of healthy years, LHLY, HALE, DALE, World
Health Organization, WHO, Global burden of Disease, Health status.Comment: 29 pages, 9 figures, 6 Tables (3 Tables with full estimated figures