scholarly journals Credible Regression Approaches to Forecast Mortality for Populations with Limited Data

Risks ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 27 ◽  
Author(s):  
Apostolos Bozikas ◽  
Georgios Pitselis
Keyword(s):  
Mortality Rates ◽  
Random Coefficients ◽  
Mortality Data ◽  
Extrapolation Methods ◽  
Limited Data ◽  
Regression Approach ◽  
Specific Mortality

In this paper, we propose a credible regression approach with random coefficients to model and forecast the mortality dynamics of a given population with limited data. Age-specific mortality rates are modelled and extrapolation methods are utilized to estimate future mortality rates. The results on Greek mortality data indicate that credibility regression contributed to more accurate forecasts than those produced from the Lee–Carter and Cairns–Blake–Dowd models. An application on pricing insurance-related products is also provided.

scholarly journals Stroke Mortality Trends in the Population of Klaipėda From 1994 to 2008

Medicina ◽  
2011 ◽  
Vol 47 (9) ◽  
pp. 512 ◽  
Author(s):  
Henrikas Kazlauskas ◽  
Nijolė Raškauskienė ◽  
Rima Radžiuvienė ◽  
Vinsas Janušonis
Keyword(s):  
Mortality Rate ◽  
Mortality Rates ◽  
Mortality Data ◽  
World Population ◽  
Stroke Mortality ◽  
Middle Aged ◽  
Elderly Men ◽  
Men And Women ◽  
Specific Mortality ◽  
Permanent Residents

The objective of the study was to evaluate the trends in stroke mortality in the population of Klaipėda aged 35–79 years from 1994 to 2008. Material and Methods. Mortality data on all permanent residents of Klaipėda aged 35–79 years who died from stroke in 1994–2008 were gathered for the study. All death certificates of permanent residents of Klaipėda aged 35–79 years who died during 1994–2008 were examined in this study. The International Classification of Diseases (ICD-9 codes 430–436, and ICD-10 codes I60–I64) was used. Sex-specific mortality rates were standardized according to the Segi’s world population; all the mortality rates were calculated per 100 000 population per year. Trends in stroke mortality were estimated using log-linear regression models. Sex-specific mortality rates and trends were calculated for 3 age groups (35–79, 35–64, and 65–79 years). Results. During the entire study period (1994–2008), a marked decline in stroke mortality with a clear slowdown after 2002 was observed. The average annual percent changes in mortality rates for men and women aged 35–79 years were –4.6% (P=0.041) and –6.5% (P=0.002), respectively. From 1994 to 2002, the stroke mortality rate decreased consistently among both Klaipėda men and women aged 35–64 years (20.4% per year, P=0.002, and 14.7% per year, P=0.006, respectively) and in the elderly population aged 65–79 years (13.8% per year, P=0.005; and 12% per year, P=0.019). During 2003–2008, stroke mortality increased by 16.3% per year in middle-aged men (35–64 years), whereas among women (aged 35–64 and 65–79 years) and elderly men (aged 65–79 years), the age-adjusted mortality rate remained relatively unchanged. Conclusions. Among both men and women, the mortality rates from stroke sharply declined between 1994 and 2008 with a clear slowdown in the decline after 2002. Stroke mortality increased significantly among middle-aged men from 2003, while it remained without significant changes among women of the same age and both elderly men and women.

scholarly journals Differential privacy in the 2020 Census will distort COVID-19 rates

2020 ◽  
Author(s):  
Mathew Hauer ◽  
Alexis R Santos-Lozada
Keyword(s):  
Differential Privacy ◽  
The United States ◽  
Mortality Rates ◽  
Census Bureau ◽  
Mortality Data ◽  
Policy Makers ◽  
Specific Mortality ◽  
Population Sizes ◽  
Us Census ◽  
Population Counts

Scientists and policy makers rely on accurate population and mortality data to inform efforts regarding the coronavirus disease 2019 (COVID-19) pandemic, with age-specific mortality rates of high importance due to the concentration of COVID-19 deaths at older ages. Population counts – the principal denominators for calculating age-specific mortality rates – will be subject to noise infusion in the United States with the 2020 Census via a disclosure avoidance system based on differential privacy. Using COVID-19 mortality curves from the CDC, we show that differential privacy will introduce substantial distortion in COVID-19 mortality rates – sometimes causing mortality rates to exceed 100\% -- hindering our ability to understand the pandemic. This distortion is particularly large for population groupings with fewer than 1000 persons – 40\% of all county-level age-sex groupings and 60\% of race groupings. The US Census Bureau should consider a larger privacy budget and data users should consider pooling data to increase population sizes to minimize differential privacy’s distortion.

scholarly journals Comparing the COVID-19 pandemic in space and over time in Europe, using numbers of deaths, crude rates and adjusted mortality trend ratios

2020 ◽  
Author(s):  
Valentina Gallo ◽  
Paolo Chiodini ◽  
Dario Bruzzese ◽  
Elias Kondilis ◽  
Daniel Howdon ◽  
...  
Keyword(s):  
Total Mortality ◽  
Reference Population ◽  
Mortality Rates ◽  
Mortality Data ◽  
Mortality Trend ◽  
Cumulative Mortality ◽  
Crude Mortality ◽  
Specific Mortality ◽  
Over Time ◽  
Age And Sex

Background Since COVID19 was declared a pandemic, attempts have been made to monitor trends over time and to compare countries and regions. Insufficient testing for COVID19 underestimates the incidence and inflates the case/fatality proportion. Given the age and sex distribution of morbidity and mortality from COVID19, the underlying sex and age distribution of a population needs to be accounted for. The aim of this paper is to present a method for monitoring trends of COVID19 using adjusted mortality trend ratios (AMTR). Methods Age and sex mortality distribution of a reference population composed of the first 14,086 fatalities which occurred before the end of March and were reported in Europe by some countries were used to calculate age and sex specific mortality rates per 1,000,000 population. These were applied to each country population to calculate the expected deaths. Adjusted Mortality Trend Ratios (AMTRs) with 95% confidence intervals (C.I.) were calculated for selected European countries from 17/03/2020 to 22/06/2020 by dividing observed cumulative mortality, by expected mortality times the crude mortality of the reference population. These estimated the sex and age adjusted mortality for COVID19 per million population in each country. Results The cumulative mortality from COVID19, the crude mortality rates, and the AMTRs were calculated for each country and compared. United Kingdom, Italy, France and Spain registered the highest mortality in Europe. On 22/06/2020 in Europe the total mortality rate from COVID-19 was 352 per 1,000,000 inhabitants; and it was highest in Belgium (850 per 1,000,000 inhabitants) followed by Spain, UK, Italy, Sweden and France. When accounting for the underlying age and sex structure of each country, Belgium remained the single country experiencing the highest AMTR of 929 per million inhabitants on 22/06/2020; however Ireland (which had a CMR in line with the total European population) emerged as having experienced a much more important impact of COVID19 mortality with an AMTR of 550/million on 22/06/2020, higher than Sweden and Italy. Conclusions In understanding and managing the pandemic of COVID19, comparable international data is a priority. Our methods allow a fair comparison of mortality in space and over time. The authors urge the WHO, given the absence of age and sex-specific mortality data for direct standardisation, to adopt this method to estimate the comparative mortality from COVID19 pandemic worldwide.

scholarly journals Mortality rates in people with intellectual disabilities

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Rachael Williams ◽  
Jessie Oyinlola ◽  
Pauline Heslop ◽  
Gyles Glover
Keyword(s):  
Life Expectancy ◽  
Mortality Rates ◽  
Practice Research ◽  
Mortality Data ◽  
Clinical Practice Research Datalink ◽  
Crude Mortality ◽  
Specific Mortality ◽  
Standardised Mortality Ratios ◽  
People With Intellectual Disabilities ◽  
Read Codes

ABSTRACTObjectivesA growing body of evidence highlights a disparity in mortality rates for people with intellectual disability (ID) compared with the general population. However, national data for England is lacking. The objective of this study was to provide evidence on mortality rates in people with ID. ApproachPatients registered for at least a day during 01/04/10-31/03/14 at a GP practice contributing to the Clinical Practice Research Datalink (CPRD) and consenting to linkage were included. Patients with ID were identified via Read codes. Date and cause of death were identified using linked Office of National Statistics mortality data. Crude mortality rates, life expectancy and indirectly age/sex standardised mortality ratios (SMR) were calculated with 95% confidence intervals (CI), overall, by ICD10 chapter, for frequently occurring causes, and those classified as avoidable. Results11 million person-years were included (0.5% for patients with ID) and 98,035 deaths occurred (0.7% in patients with ID). The mortality rate for patients with ID was 11.2 per 1,000 population, 1.3 times the rate for those without ID, with an associated SMR of 3.2 (95% CI 2.93.4). Life expectancy was 65.5 years (95% CI 61.969.2)for patients with ID and 85.3 years for those without (95% CI 85.285.4). Mortality rates were higher in patients with ID in all age/sex groups, with larger differences for younger ages. Patients with ID had higher cause-specific mortality rates across all ICD10 chapters, with highest SMRs for congenital malformations (72.9, 95% CI 55.194.7), nervous system diseases (9.8, 95% CI 7.812.1) and mental disorders (5.4, 95% CI 3.97.3). Circulatory deaths were the most frequent, with ischaemic heart disease (SMR 2.2, 95% CI 1.62.8) and cerebrovascular disease (SMR 3.3, 95% CI 2.34.5) most prominent. A higher proportion of deaths were classified as avoidable for patients with ID (44.7%, 95% CI 41.048.5%) compared to those without (21.0%, 95% CI 20.721.3). ConclusionNational English data confirm that patients with ID have higher mortality rates than those without. Mortality rates for patients with ID were higher across all age/sex groups and causes, with almost half of deaths classified as avoidable.

scholarly journals Differential Privacy in the 2020 Census Will Distort COVID-19 Rates

2021 ◽  
Vol 7 ◽  
pp. 237802312199401
Author(s):  
Mathew E. Hauer ◽  
Alexis R. Santos-Lozada
Keyword(s):  
Differential Privacy ◽  
The United States ◽  
Mortality Rates ◽  
Census Bureau ◽  
Mortality Data ◽  
County Level ◽  
Specific Mortality ◽  
Population Counts ◽  
Privacy Budget ◽  
The U.S

Scholars rely on accurate population and mortality data to inform efforts regarding the coronavirus disease 2019 (COVID-19) pandemic, with age-specific mortality rates of high importance because of the concentration of COVID-19 deaths at older ages. Population counts, the principal denominators for calculating age-specific mortality rates, will be subject to noise infusion in the United States with the 2020 census through a disclosure avoidance system based on differential privacy. Using empirical COVID-19 mortality curves, the authors show that differential privacy will introduce substantial distortion in COVID-19 mortality rates, sometimes causing mortality rates to exceed 100 percent, hindering our ability to understand the pandemic. This distortion is particularly large for population groupings with fewer than 1,000 persons: 40 percent of all county-level age-sex groupings and 60 percent of race groupings. The U.S. Census Bureau should consider a larger privacy budget, and data users should consider pooling data to minimize differential privacy’s distortion.

scholarly journals Primary malignant brain tumor-related mortality in the Belgrade population

2003 ◽  
Vol 60 (5) ◽  
pp. 565-568
Author(s):  
Tatjana Pekmezovic ◽  
Mirjana Jarebinski ◽  
Darija Kisic ◽  
Milen Pavlovic ◽  
Marina Nikitovic ◽  
...  
Keyword(s):  
Linear Trend ◽  
Population Data ◽  
Mortality Rates ◽  
Mortality Data ◽  
World Population ◽  
Age Group ◽  
Test Results ◽  
Female Population ◽  
Specific Mortality ◽  
Related Mortality

Background. The aim of this investigation was the analysis of primary malignant brain tumors (PMBT)-related mortality in the Belgrade population during the period 1983?2000. Methods. Mortality data (based on death records) for the period observed, as well as population data, were obtained from the unpublished material of the Municipal Institute of Statistics, Belgrade. The data analysis was adjusted to specific and standardized mortality rates and linear trend, using the world population as a standard. Regression coefficient was determined by Fisher?s test. Results. During the period 1983?2000, in the Belgrade population standardized mortality rates from PMBT were 6.29/100 000 (95%CI-confidence interval 5.33?7.24) for males, 4.50/100 000 (95%CI 3.84?5.17) for females, and 5.91/100 000 (95%CI 5.20?6.63) for total population. The age-specific mortality rates increased with age up to the age group 65?74, with the highest value of 21.21/100 000 (95%CI 16.03?26.39), and decreased in persons of 75 and more years of age. Conclusion. Mortality rates from PMBT in Belgrade had slightly increasing tendency in male (5.725+0.0592x, p=0.545), and decreasing tendency in female population (y=4.703-0.0213x, p=0.756), while statistically significant increasing mortality rate was registered only in the age group 65?74 (y=435+1.7707x, p=0.0001).

Comments on “Cancer Mortality near OAK Ridge, Tennessee”

1995 ◽  
Vol 25 (2) ◽  
pp. 333-344 ◽  
Author(s):  
Charles McRae Sharpe
Keyword(s):  
Cancer Mortality ◽  
Recent Article ◽  
Health Department ◽  
Mortality Rates ◽  
Mortality Data ◽  
White Population ◽  
Health Statistics ◽  
Oak Ridge ◽  
Specific Mortality ◽  
Radiation Contamination

A recent article by Joseph Mangano concluded that changes in cancer mortality near Oak Ridge (Anderson County) in Tennessee over a 40-year period (1950–1989) suggest an increase in cancer deaths linked to radiation contamination. These conclusions are not supported by available, representative data. In his analysis, Mangano selected for comparison two three-year periods (1950–1952 and 1987–1989) that are not representative of the entire 40 years. An analysis by decade of the 42-year period from 1950 to 1991, using U.S. mortality rates from the National Center for Health Statistics and Tennessee mortality rates from the NCHS and the Tennessee Health Department, shows that the relation between expected and actual cancer deaths for the white population of Anderson County does not differ from that for the State of Tennessee. In addition, changes in methods of reporting death statistics during the 40-year period invalidate any attempt to compare current cause-specific mortality data (such as cancer deaths) with data from the 1950s. Relevant comparisons that can be made for the period 1970–1991 again show that cancer deaths for whites in Anderson County have been statistically equivalent to the expected rates.

Mortality Rates as a Quality Indicator: A Simple Answer to a Complex Question

1988 ◽  
Vol 9 (7) ◽  
pp. 330-332 ◽  
Author(s):  
William B. Crede ◽  
Walter J. Hierholzer
Keyword(s):  
Health Care ◽  
Performance Indicator ◽  
Care Delivery ◽  
Mortality Rates ◽  
Current Data ◽  
Face Validity ◽  
Mortality Data ◽  
Specific Mortality ◽  
Health Care Delivery Systems

As the consumers and regulators of health care have become more concerned with quality of delivered services, interest has focused on hospital- and physician-specific mortality rates as an index of quality. Mortality rates have several characteristics that promote their use as a performance indicator. The numerator, death, is generally (but perhaps incorrectly) accepted as an adverse outcome of health care. Death is thought to be easily measured, and is recorded in several locations, including the medical record abstract and death certificates, where the information is accessible without provider consent. The denominator, persons or patients, is also available from several public sources. The desirability of mortality data is further enhanced by the wide variety of statistical methods to manipulate and compare rates and proportions. The conceptual validity of mortality rates as reflecting quality is supported by a long tradition of using mortality rates at the “macro” level to compare the quality of national health care delivery systems (eg, infant mortality rates) and at the “micro” level to compare the outcome of different therapies (eg, thrombolytics for acute myocardial infarction). However, despite face validity, ease of measurement, and widespread acceptance in other areas, hospital-specific mortality rates, as calculated from current data sources, have a variety of potential problems.This article will explore the clinical, administrative, and information-based difficulties in using mortality rates as an indicator of the quality of medical care delivered by specific hospitals or physicians.

scholarly journals Cause-specific mortality by occupational skill level in Canada: a 16-year follow-up study

2013 ◽  
Vol 33 (4) ◽  
pp. 195-203 ◽  
Author(s):  
M Tjepkema ◽  
R Wilkins ◽  
A Long
Keyword(s):  
Causes Of Death ◽  
Mortality Rates ◽  
Skill Level ◽  
Mortality Data ◽  
Excessive Alcohol Consumption ◽  
Skill Levels ◽  
Specific Mortality ◽  
Rate Ratios ◽  
Occupational Skill

Introduction Mortality data by occupation are not routinely available in Canada, so we analyzed census-linked data to examine cause-specific mortality rates across groups of occupations ranked by skill level. Methods A 15% sample of 1991 Canadian Census respondents aged 25 years or older was previously linked to 16 years of mortality data (1991–2006). The current analysis is based on 2.3 million people aged 25 to 64 years at cohort inception, among whom there were 164 332 deaths during the follow-up period. Occupations coded according to the National Occupation Classification were grouped into five skill levels. Age-standardized mortality rates (ASMRs), rate ratios (RRs), rate differences (RDs) and excess mortality were calculated by occupational skill level for various causes of death. Results ASMRs were clearly graded by skill level: they were highest among those employed in unskilled jobs (and those without an occupation) and lowest for those in professional occupations. All-cause RRs for men were 1.16, 1.40, 1.63 and 1.83 with decreasing occupational skill level compared with professionals. For women the gradient was less steep: 1.23, 1.24, 1.32 and 1.53. This gradient was present for most causes of death. Rate ratios comparing lowest to highest skill levels were greater than 2 for HIV/AIDS, diabetes mellitus, suicide and cancer of the cervix as well as for causes of death associated with tobacco use and excessive alcohol consumption. Conclusion Mortality gradients by occupational skill level were evident for most causes of death. These results provide detailed cause-specific baseline indicators not previously available for Canada.

scholarly journals Covid-19 and excess mortality rates not comparable across countries

2021 ◽  
Author(s):  
Gabrielle E Kelly ◽  
Stefano Petti ◽  
Norman Noah
Keyword(s):  
Excess Mortality ◽  
Spatial Clustering ◽  
Mortality Rates ◽  
Mortality Data ◽  
Published Data ◽  
Death Rates ◽  
Government Response ◽  
Health Measures ◽  
Specific Mortality ◽  
Excess Deaths

Abstract: Evidence that more people in some countries and fewer in others are dying because of the pandemic, than is reflected by reported Covid-19 mortality rates, is derived from mortality data. Worldwide, mortality data is used to estimate the full extent of the effects of the Covid-19 pandemic, both direct and indirect; the possible short fall in the number of cases reported to the WHO; and to suggest explanations for differences between countries. Excess mortality data is largely varying across countries and is not directly proportional to Covid-19 mortality. Using publicly available databases, deaths attributed to Covid-19 in 2020 and all deaths for the years 2015-2020 were tabulated for 36 countries together with economic, health, demographic, and government response stringency index variables. Residual death rates in 2020 were calculated as excess deaths minus death rates due to Covid-19 where excess deaths were observed deaths in 2020 minus the average for 2015-2019. For about half the countries, residual deaths were negative and for half, positive. The absolute rates in some countries were double those in others. In a regression analysis, the stringency index (p=0.026) was positively associated with residual mortality. There was no evidence of spatial clustering of residual mortality. The results show that published data on mortality from Covid-19 cannot be directly comparable across countries, likely due to differences in Covid-19 death reporting. In addition, the unprecedented public health measures implemented to control the pandemic may have produced either increased or reduced excess deaths due to other diseases. Further data on cause-specific mortality is required to determine the extent to which residual mortality represents non-Covid-19 deaths and to explain differences between countries.

Sign in / Sign up

Export Citation Format

Share Document