scholarly journals Do Different Models Induce Changes in Mortality Indicators? That Is a Key Question for Extending the Lee-Carter Model

2021 ◽  
Vol 18 (4) ◽  
pp. 2204
Author(s):  
Ana Debón ◽  
Steven Haberman ◽  
Francisco Montes ◽  
Edoardo Otranto
Keyword(s):  
Historical Data ◽  
Mortality Rates ◽  
Parametric Model ◽  
Mortality Data ◽  
Block Bootstrap ◽  
Functional Anova ◽  
Model Block ◽  
The Usa ◽  
Data Constraints ◽  
Carter Model

The parametric model introduced by Lee and Carter in 1992 for modeling mortality rates in the USA was a seminal development in forecasting life expectancies and has been widely used since then. Different extensions of this model, using different hypotheses about the data, constraints on the parameters, and appropriate methods have led to improvements in the model’s fit to historical data and the model’s forecasting of the future. This paper’s main objective is to evaluate if differences between models are reflected in different mortality indicators’ forecasts. To this end, nine sets of indicator predictions were generated by crossing three models and three block-bootstrap samples with each of size fifty. Later the predicted mortality indicators were compared using functional ANOVA. Models and block bootstrap procedures are applied to Spanish mortality data. Results show model, block-bootstrap, and interaction effects for all mortality indicators. Although it was not our main objective, it is essential to point out that the sample effect should not be present since they must be realizations of the same population, and therefore the procedure should lead to samples that do not influence the results. Regarding significant model effect, it follows that, although the addition of terms improves the adjustment of probabilities and translates into an effect on mortality indicators, the model’s predictions must be checked in terms of their probabilities and the mortality indicators of interest.

scholarly journals Mortality Forecasting: How Far Back Should We Look in Time?

Risks ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 22 ◽  
Author(s):  
Han Li ◽  
Colin O’Hare
Keyword(s):  
Predictive Power ◽  
Historical Data ◽  
Mortality Rates ◽  
Point Of View ◽  
Mortality Data ◽  
Male Mortality ◽  
Historical Information ◽  
Mortality Forecasting ◽  
Mortality Models ◽  
Forecasting Performance

Extrapolative methods are one of the most commonly-adopted forecasting approaches in the literature on projecting future mortality rates. It can be argued that there are two types of mortality models using this approach. The first extracts patterns in age, time and cohort dimensions either in a deterministic fashion or a stochastic fashion. The second uses non-parametric smoothing techniques to model mortality and thus has no explicit constraints placed on the model. We argue that from a forecasting point of view, the main difference between the two types of models is whether they treat recent and historical information equally in the projection process. In this paper, we compare the forecasting performance of the two types of models using Great Britain male mortality data from 1950–2016. We also conduct a robustness test to see how sensitive the forecasts are to the changes in the length of historical data used to calibrate the models. The main conclusion from the study is that more recent information should be given more weight in the forecasting process as it has greater predictive power over historical information.

scholarly journals Recent adverse mortality trends in Scotland: comparison with other high-income countries

2019 ◽  
Author(s):  
Lynda Fenton ◽  
Jon Minton ◽  
Julie Ramsay ◽  
Maria Kaye-Bardgett ◽  
Colin Fischbacher ◽  
...  
Keyword(s):  
Northern Ireland ◽  
Life Expectancy ◽  
Mortality Rates ◽  
Recent Change ◽  
High Income ◽  
Mortality Data ◽  
List Type ◽  
Segmented Regression ◽  
Mortality Trends ◽  
The Usa

AbstractObjectiveGains in life expectancy have faltered in several high-income countries in recent years. We aim to compare life expectancy trends in Scotland to those seen internationally, and to assess the timing of any recent changes in mortality trends for Scotland.SettingAustria, Croatia, Czech Republic, Denmark, England & Wales, Estonia, France, Germany, Hungary, Iceland, Israel, Japan, Korea, Latvia, Lithuania, Netherlands, Northern Ireland, Poland, Scotland, Slovakia, Spain, Sweden, Switzerland, USA.MethodsWe used life expectancy data from the Human Mortality Database (HMD) to calculate the mean annual life expectancy change for 24 high-income countries over five-year periods from 1992 to 2016, and the change for Scotland for five-year periods from 1857 to 2016. One- and two-break segmented regression models were applied to mortality data from National Records of Scotland (NRS) to identify turning points in age-standardised mortality trends between 1990 and 2018.ResultsIn 2012-2016 life expectancies in Scotland increased by 2.5 weeks/year for females and 4.5 weeks/year for males, the smallest gains of any period since the early 1970s. The improvements in life expectancy in 2012-2016 were smallest among females (<2.0 weeks/year) in Northern Ireland, Iceland, England & Wales and the USA and among males (<5.0 weeks/year) in Iceland, USA, England & Wales and Scotland. Japan, Korea, and countries of Eastern Europe have seen substantial gains in the same period. The best estimate of when mortality rates changed to a slower rate of improvement in Scotland was the year to 2012 Q4 for males and the year to 2014 Q2 for females.ConclusionLife expectancy improvement has stalled across many, but not all, high income countries. The recent change in the mortality trend in Scotland occurred within the period 2012-2014. Further research is required to understand these trends, but governments must also take timely action on plausible contributors.Strengths and limitations of this studyThe use of five-year time periods for comparison of life expectancy changes reduces the influence of year-to-year variation on observations.Examining long-term trends addresses concerns that recent life expectancy stalling may be over-emphasised due to notably large gains in the immediately preceding period.The international comparison was limited to the 24 high-income countries for which data were readily available for the relevant period.Analysis of trend data will always be sensitive to the period selected, however segmented regression of the full period of mortality rates available offers an objective method of identifying the timing of a change in trend.

scholarly journals Forecasting Hungarian mortality rates using the Lee-Carter method

2007 ◽  
Vol 57 (1) ◽  
pp. 21-34 ◽  
Author(s):  
S. Baran ◽  
J. Gáll ◽  
M. Ispány ◽  
G. Pap
Keyword(s):  
Mortality Rates ◽  
Mortality Data ◽  
Good Prediction ◽  
Data Set ◽  
Men And Women ◽  
Carter Model

A modified version of the popular Lee-Carter method (Lee-Carter 1992) is applied to forecast mortality rates in Hungary for the period 2004–2040 on the basis of mortality data between 1949 and 2003 both for men and women. Another case is also considered based on a restricted data set corresponding to the period 1989–2003. The model fitted to the data of the period 1949–2003 forecasts increasing mortality rates for men between ages 45 and 55, pointing out that the Lee-Carter method is hardly applicable for countries where mortality rates exhibit trends as peculiar as in Hungary. However, models fitted to the data for the last 15 years both for men and women forecast decreasing trends similarly to the case of countries where the method was successfully applied. Hence one gets a better fit in this way, however, further concerns suggest that the Lee-Carter model, which is celebrated and widely used in actuarial practice, does not necessarily give sufficiently good prediction.

scholarly journals Hybrid of the Lee-Carter Model with Maximum Overlap Discrete Wavelet Transform Filters in Forecasting Mortality Rates

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2295
Author(s):  
Nurul Aityqah Yaacob ◽  
Jamil J. Jaber ◽  
Dharini Pathmanathan ◽  
Sadam Alwadi ◽  
Ibrahim Mohamed
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Arima Model ◽  
Mortality Rates ◽  
Percentage Error ◽  
Mortality Data ◽  
Discrete Wavelet ◽  
Death Rates ◽  
Wavelet Filters ◽  
Carter Model

This study implements various, maximum overlap, discrete wavelet transform filters to model and forecast the time-dependent mortality index of the Lee-Carter model. The choice of appropriate wavelet filters is essential in effectively capturing the dynamics in a period. This cannot be accomplished by using the ARIMA model alone. In this paper, the ARIMA model is enhanced with the integration of various maximal overlap discrete wavelet transform filters such as the least asymmetric, best-localized, and Coiflet filters. These models are then applied to the mortality data of Australia, England, France, Japan, and USA. The accuracy of the projecting log of death rates of the MODWT-ARIMA model with the aforementioned wavelet filters are assessed using mean absolute error, mean absolute percentage error, and mean absolute scaled error. The MODWT-ARIMA (5,1,0) model with the BL14 filter gives the best fit to the log of death rates data for males, females, and total population, for all five countries studied. Implementing the MODWT leads towards improvement in the performance of the standard framework of the LC model in forecasting mortality rates.

scholarly journals Racial inequality in the annual risk of Tuberculosis infection in the United States, 1910–1933

2017 ◽  
Vol 145 (9) ◽  
pp. 1797-1804 ◽  
Author(s):  
J. L. ZELNER ◽  
C. MULLER ◽  
J. J. FEIGENBAUM
Keyword(s):  
African Americans ◽  
Racial Inequality ◽  
The United States ◽  
Mortality Rates ◽  
Mortality Data ◽  
Pulmonary Tb ◽  
The Us ◽  
Northern Cities ◽  
The Usa ◽  
Annual Risk

SUMMARYTuberculosis (TB) mortality rates in the USA fell rapidly from 1910 to 1933. However, during this period, racial disparities in TB mortality in the nation's expanding cities grew. Because of long delays between infection and disease, TB mortality is a poor indicator of short-term changes in transmission. We estimated the annual risk of TB infection (ARTI) in 11 large US cities to understand whether rising inequality in mortality reflected rising inequality in ARTI using city-level TB mortality data compiled by the US Department of Commerce from 1910 to 1933. We estimated ARTI for African-Americans and whites using pediatric extrapulmonary TB mortality data for African-Americans and whites in our panel of cities. We also estimated age-adjusted pulmonary TB mortality rates for these cities. We find that the ratio of ARTI for African-Americans vs. whites increased from 2·1 (95% CI = 1·7, 2·4) in 1910 to 4·2 (95% CI = 3·4, 5·2) in 1933. This change mirrored the increasing inequality in age-adjusted pulmonary TB mortality during this period. These findings may reflect the combined effects of migration, inequality in access to care, increasing population density, and racial residential segregation in northern cities during this period.

Viewpoint: Paradoxical excess mortality in the PLATO trial should be independently verified

2011 ◽  
Vol 105 (05) ◽  
pp. 752-759 ◽  
Author(s):  
Victor Serebruany
Keyword(s):  
Excess Mortality ◽  
High Volume ◽  
Mortality Rates ◽  
Mortality Data ◽  
Self Monitoring ◽  
Death Rates ◽  
Coronary Syndrome ◽  
High Death ◽  
The Usa ◽  
One Year

SummaryThe PLATO trial revealed excess all-cause (4.5%) and vascular (4.0%) mortality after experimental pyrimidine, ticagrelor, and even higher death rates (5.9% and 5.1%, respectively) after clopidogrel, which have never been seen in any previous acute coronary syndrome (ACS) trial. The Food and Drug Administration (FDA) conducted, and recently released the ticagrelor review outlining some paradoxical mortality patterns in PLATO, including the existence of alive patient, who initially was reported dead. The drug was recently approved in Europe, but repeatedly delayed in the USA. The objective of this viewpoint article was to evaluate extremely high death rates in PLATO by scrutinising FDA-released evidence, and comparing mortality patterns in recent ACS trials. These data were first presented as the analytical report submitted to the FDA on October 26, 2010. The available evidence suggest that mortality rates in PLATO, so as death benefit of ticagrelor over clopidogrel are extreme, despite incomplete follow-up, short duration of the trial, frequent preloading with clopidogrel, and gross mismatch between conventional average myocardial infarction rates but disproportionally frequent vascular fatalities, and heavily imbalanced sepsis-related deaths. In contrast to the overall PLATO results, the deaths rates in the USA were much lower (3.2% vs. 3.8%) not only favouring clopidogrel, but more importanly matching very well with identical rates in TRITON (3.2%), and one-year ACUITY (3.6%-3.9%) fatalities. Since the «play of chance» cannot explain these discrepancies due to excess death rates in both PLATO arms, and considering that study sponsor self-monitored sites in most countries, but not in the USA, the mortality data are questionable, and should be independently virified. It was concluded that excess mortality rates and delayed timing of the benefit onset in PLATO do not match with any recent ACS trial, and do not look natural. Reevaluation of the survival, especially driven from the several high-volume sponsor monitored sites in Eastern Europe may reveal discrepancies between those reported in PLATO and actual vital records. Future practice of self monitoring in pivotal indication-seeking clinical trials should be completely banned.

Inequalities and Impact of Socioeconomic-Cultural Factors in Suicide Rates Across Italy

Crisis ◽  
2011 ◽  
Vol 32 (4) ◽  
pp. 178-185 ◽  
Author(s):  
Maurizio Pompili ◽  
Marco Innamorati ◽  
Monica Vichi ◽  
Maria Masocco ◽  
Nicola Vanacore ◽  
...  
Keyword(s):  
Suicide Rate ◽  
Age Groups ◽  
Premature Death ◽  
Mortality Rates ◽  
Mortality Data ◽  
Italian Population ◽  
Comprehensive Overview ◽  
Suicide Rates ◽  
Younger Age ◽  
Age And Sex

Background: Suicide is a major cause of premature death in Italy and occurs at different rates in the various regions. Aims: The aim of the present study was to provide a comprehensive overview of suicide in the Italian population aged 15 years and older for the years 1980–2006. Methods: Mortality data were extracted from the Italian Mortality Database. Results: Mortality rates for suicide in Italy reached a peak in 1985 and declined thereafter. The different patterns observed by age and sex indicated that the decrease in the suicide rate in Italy was initially the result of declining rates in those aged 45+ while, from 1997 on, the decrease was attributable principally to a reduction in suicide rates among the younger age groups. It was found that socioeconomic factors underlined major differences in the suicide rate across regions. Conclusions: The present study confirmed that suicide is a multifaceted phenomenon that may be determined by an array of factors. Suicide prevention should, therefore, be targeted to identifiable high-risk sociocultural groups in each country.

scholarly journals Mortality beyond emergency threshold in a silent crisis– results from a population-based mortality survey in Ouaka prefecture, Central African Republic, 2020

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Eve Robinson ◽  
Lawrence Lee ◽  
Leslie F. Roberts ◽  
Aurelie Poelhekke ◽  
Xavier Charles ◽  
...  
Keyword(s):  
Central African Republic ◽  
Causes Of Death ◽  
Maternal Mortality Ratio ◽  
Mortality Rates ◽  
Population Based ◽  
Access To Healthcare ◽  
Mortality Data ◽  
Humanitarian Emergency ◽  
The World ◽  
Mortality Survey

Abstract Background The Central African Republic (CAR) suffers a protracted conflict and has the second lowest human development index in the world. Available mortality estimates vary and differ in methodology. We undertook a retrospective mortality study in the Ouaka prefecture to obtain reliable mortality data. Methods We conducted a population-based two-stage cluster survey from 9 March to 9 April, 2020 in Ouaka prefecture. We aimed to include 64 clusters of 12 households for a required sample size of 3636 persons. We assigned clusters to communes proportional to population size and then used systematic random sampling to identify cluster starting points from a dataset of buildings in each commune. In addition to the mortality survey questions, we included an open question on challenges faced by the household. Results We completed 50 clusters with 591 participating households including 4000 household members on the interview day. The median household size was 7 (interquartile range (IQR): 4—9). The median age was 12 (IQR: 5—27). The birth rate was 59.0/1000 population (95% confidence interval (95%-CI): 51.7—67.4). The crude and under-five mortality rates (CMR & U5MR) were 1.33 (95%-CI: 1.09—1.61) and 1.87 (95%-CI: 1.37–2.54) deaths/10,000 persons/day, respectively. The most common specified causes of death were malaria/fever (16.0%; 95%-CI: 11.0–22.7), violence (13.2%; 95%-CI: 6.3–25.5), diarrhoea/vomiting (10.6%; 95%-CI: 6.2–17.5), and respiratory infections (8.4%; 95%-CI: 4.6–14.8). The maternal mortality ratio (MMR) was 2525/100,000 live births (95%-CI: 825—5794). Challenges reported by households included health problems and access to healthcare, high number of deaths, lack of potable water, insufficient means of subsistence, food insecurity and violence. Conclusions The CMR, U5MR and MMR exceed previous estimates, and the CMR exceeds the humanitarian emergency threshold. Violence is a major threat to life, and to physical and mental wellbeing. Other causes of death speak to poor living conditions and poor access to healthcare and preventive measures, corroborated by the challenges reported by households. Many areas of CAR face similar challenges to Ouaka. If these results were generalisable across CAR, the country would suffer one of the highest mortality rates in the world, a reminder that the longstanding “silent crisis” continues.

scholarly journals Outcomes for Children and Adolescents With Cancer: Challenges for the Twenty-First Century

2010 ◽  
Vol 28 (15) ◽  
pp. 2625-2634 ◽  
Author(s):  
Malcolm A. Smith ◽  
Nita L. Seibel ◽  
Sean F. Altekruse ◽  
Lynn A.G. Ries ◽  
Danielle L. Melbert ◽  
...  
Keyword(s):  
United States ◽  
Childhood Cancer ◽  
Cancer Mortality ◽  
Lymphoblastic Leukemia ◽  
The United States ◽  
Mortality Rates ◽  
Mortality Data ◽  
Childhood Cancers ◽  
Essential Information ◽  
The Impact

Purpose This report provides an overview of current childhood cancer statistics to facilitate analysis of the impact of past research discoveries on outcome and provide essential information for prioritizing future research directions. Methods Incidence and survival data for childhood cancers came from the Surveillance, Epidemiology, and End Results 9 (SEER 9) registries, and mortality data were based on deaths in the United States that were reported by states to the Centers for Disease Control and Prevention by underlying cause. Results Childhood cancer incidence rates increased significantly from 1975 through 2006, with increasing rates for acute lymphoblastic leukemia being most notable. Childhood cancer mortality rates declined by more than 50% between 1975 and 2006. For leukemias and lymphomas, significantly decreasing mortality rates were observed throughout the 32-year period, though the rate of decline slowed somewhat after 1998. For remaining childhood cancers, significantly decreasing mortality rates were observed from 1975 to 1996, with stable rates from 1996 through 2006. Increased survival rates were observed for all categories of childhood cancers studied, with the extent and temporal pace of the increases varying by diagnosis. Conclusion When 1975 age-specific death rates for children are used as a baseline, approximately 38,000 childhood malignant cancer deaths were averted in the United States from 1975 through 2006 as a result of more effective treatments identified and applied during this period. Continued success in reducing childhood cancer mortality will require new treatment paradigms building on an increased understanding of the molecular processes that promote growth and survival of specific childhood cancers.

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