scholarly journals At-a-glance - The impact of poisoning-related mortality on life expectancy at birth in Canada, 2000 to 2016

2019 ◽  
Vol 39 (2) ◽  
pp. 56-60 ◽  
Author(s):  
Heather Orpana ◽  
Justin J. Lang ◽  
Diana George ◽  
Jessica Halverson
Keyword(s):  
Life Expectancy ◽  
The United States ◽  
Mortality Data ◽  
Opioid Overdose ◽  
Age Group ◽  
Life Expectancy At Birth ◽  
Current Trends ◽  
National Mortality ◽  
The Impact ◽  
Related Mortality

Increases in opioid-related mortality have contributed to declines in life expectancy at birth in the United States and British Columbia. Canadian national mortality data from 2000 to 2016 were analyzed to determine the contribution of poisoning-related mortality to changes in life expectancy at birth by age group and sex. From 2000 to 2016, life expectancy at birth increased by almost three years; however, mortality due to unintentional poisonings, including those involving opioids, curbed this increase by 0.16 years. Although a national decrease in life expectancy at birth has not been observed in Canada during this period, current trends suggest that the national opioid overdose crisis will continue to attenuate gains to life expectancy.

scholarly journals How have changes in death by cause and age group contributed to the recent stalling of life expectancy gains in Scotland? Comparative decomposition analysis of mortality data, 2000–2002 to 2015–2017

BMJ Open ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. e036529
Author(s):  
Julie Ramsay ◽  
Jon Minton ◽  
Colin Fischbacher ◽  
Lynda Fenton ◽  
Maria Kaye-Bardgett ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Cause Of Death ◽  
Age Groups ◽  
Decomposition Analysis ◽  
Future Research ◽  
Mortality Data ◽  
Age Group ◽  
Mortality Trends ◽  
Life Expectancy At Birth ◽  
The Impact

ObjectiveAnnual gains in life expectancy in Scotland were slower in recent years than in the previous two decades. This analysis investigates how deaths in different age groups and from different causes have contributed to annual average change in life expectancy across two time periods: 2000–2002 to 2012–2014 and 2012–2014 to 2015–2017.SettingScotland.MethodsLife expectancy at birth was calculated from death and population counts, disaggregated by 5 year age group and by underlying cause of death. Arriaga’s method of life expectancy decomposition was applied to produce estimates of the contribution of different age groups and underlying causes to changes in life expectancy at birth for the two periods.ResultsAnnualised gains in life expectancy between 2012–2014 and 2015–2017 were markedly smaller than in the earlier period. Almost all age groups saw worsening mortality trends, which deteriorated for most cause of death groups between 2012–2014 and 2015–2017. In particular, the previously observed substantial life expectancy gains due to reductions in mortality from circulatory causes, which most benefited those aged 55–84 years, more than halved. Mortality rates for those aged 30–54 years and 90+ years worsened, due in large part to increases in drug-related deaths, and dementia and Alzheimer’s disease, respectively.ConclusionFuture research should seek to explain the changes in mortality trends for all age groups and causes. More investigation is required to establish to what extent shortcomings in the social security system and public services may be contributing to the adverse trends and preventing mitigation of the impact of other contributing factors, such as influenza outbreaks.

scholarly journals How have changes in death by cause and age group contributed to the recent stalling of life expectancy gains in Scotland? Comparative decomposition analysis of mortality data, 2000-02 to 2015-17

2019 ◽  
Author(s):  
Julie Ramsay ◽  
Jonathan Minton ◽  
Colin Fischbacher ◽  
Lynda Fenton ◽  
Maria Kaye-Bardgett ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Cause Of Death ◽  
Age Groups ◽  
Decomposition Analysis ◽  
Mortality Data ◽  
Age Group ◽  
Contributing Factors ◽  
Mortality Trends ◽  
Life Expectancy At Birth ◽  
The Impact

BackgroundAnnual gains in life expectancy in Scotland were slower in recent years than in the previous two decades. This analysis investigates how deaths in different age groups and from different causes have contributed to annual average change in life expectancy across two time periods: 2000-02 to 2012-14 and 2012-14 to 2015-17. MethodsLife expectancy at birth was calculated from death and population counts, disaggregated by five-year age-group and by underlying cause of death. Arriaga’s method of life expectancy decomposition was applied to produce estimates of the contribution of different age-groups and underlying causes to changes in life expectancy at birth for the two periods.FindingsAverage annual life expectancy gains between 2012-14 to 2015-17 were markedly smaller than in the earlier period. Almost all age-groups saw worsening mortality trends, which deteriorated for most cause of death groups between 2012-14 and 2015-17. In particular, the previously observed substantial life expectancy gains due to reductions in mortality from circulatory causes, which most benefited those aged 55-84 years, more than halved. Mortality rates for those aged 30-54 years and 90+ years worsened, due in large part to increases in drug-related deaths, and dementia and Alzheimer’s disease respectively. InterpretationFuture research should seek to explain the changes in mortality trends for all age-groups and causes. More investigation is required to establish to what extent shortcomings in the social security system and public services may be contributing to the adverse trends and preventing mitigation of the impact of other contributing factors, such as influenza outbreaks.

scholarly journals The decomposition of life expectancy for age and cause of death in Tuscany, Italy

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
N Nante ◽  
L Kundisova ◽  
F Gori ◽  
A Martini ◽  
F Battisti ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Causes Of Death ◽  
National Level ◽  
Age Groups ◽  
Resistant Bacteria ◽  
Mortality Data ◽  
Life Expectancy At Birth ◽  
Icd 10 ◽  
Reduction Of Mortality ◽  
The Impact

Abstract Introduction Changing of life expectancy at birth (LE) over time reflects variations of mortality rates of a certain population. Italy is amongst the countries with the highest LE, Tuscany ranks fifth at the national level. The aim of the present work was to evaluate the impact of various causes of death in different age groups on the change in LE in the Tuscany region (Italy) during period 1987-2015. Material and methods Mortality data relative to residents that died during the period between 1987/1989 and 2013/2015 were provided by the Tuscan Regional Mortality Registry. The causes of death taken into consideration were cardiovascular (CVS), respiratory (RESP) and infective (INF) diseases and cancer (TUM). The decomposition of LE gain was realized with software Epidat, using the Pollard’s method. Results The overall LE gain during the period between two three-years periods was 6.7 years for males, with a major gain between 65-89, and 4.5 years for females, mainly improved between 75-89, <1 year for both sexes. The major gain (2.6 years) was attributable to the reduction of mortality for CVS, followed by TUM (1.76 in males and 0.83 in females) and RESP (0.4 in males; 0.1 in females). The major loss of years of LE was attributable to INF (-0.15 in females; -0.07 in males) and lung cancer in females (-0.13), for which the opposite result was observed for males (gain of 0.62 years of LE). Conclusions During the study period (1987-2015) the gain in LE was major for males. To the reduction of mortality for CVS have contributed to the tempestuous treatment of acute CVS events and secondary CVS prevention. For TUM the result is attributable to the adherence of population to oncologic screening programmes. The excess of mortality for INF that lead to the loss of LE can be attributed to the passage from ICD-9 to ICD-10 in 2003 (higher sensibility of ICD-10) and to the diffusion of multi-drug resistant bacteria, which lead to elevated mortality in these years. Key messages The gain in LE during the period the 1987-2015 was higher in males. The major contribution to gain in LE was due to a reduction of mortality for CVS diseases.

scholarly journals Black and White Differences in Life Expectancy in 4 US States, 1969-2013

2019 ◽  
Vol 134 (6) ◽  
pp. 634-642 ◽  
Author(s):  
Jay S. Kaufman ◽  
Corinne A. Riddell ◽  
Sam Harper
Keyword(s):  
New York ◽  
Life Expectancy ◽  
Racial Differences ◽  
State Level ◽  
Decomposition Methods ◽  
The United States ◽  
Future Research ◽  
Age Group ◽  
Life Expectancy At Birth ◽  
Racial Gap

Objectives: Racial differences in mortality in the United States have narrowed and vary by time and place. The objectives of our study were to (1) examine the gap in life expectancy between white and black persons (hereinafter, racial gap in life expectancy) in 4 states (California, Georgia, Illinois, and New York) and (2) estimate trends in the contribution of major causes of death (CODs) to the racial gap in life expectancy by age group. Methods: We extracted data on the number of deaths and population sizes for 1969-2013 by state, sex, race, age group, and 6 major CODs. We used a Bayesian time-series model to smooth and impute mortality rates and decomposition methods to estimate trends in sex- and age-specific contributions of CODs to the racial gap in life expectancy. Results: The racial gap in life expectancy at birth decreased in all 4 states, especially among men in New York (from 8.8 to 1.1 years) and women in Georgia (from 8.0 to 1.7 years). Although few deaths occurred among persons aged 1-39, racial differences in mortality at these ages (mostly from injuries and infant mortality) contributed to the racial gap in life expectancy, especially among men in California (1.0 year of the 4.3-year difference in 2013) and Illinois (1.9 years of the 6.7-year difference in 2013). Cardiovascular deaths contributed most to the racial gap in life expectancy for adults aged 40-64, but contributions decreased among women aged 40-64, especially in Georgia (from 2.8 to 0.5 years). The contribution of cancer deaths to inequality increased in California and Illinois, whereas New York had the greatest reductions in inequality attributable to cancer deaths (from 0.6 to 0.2 years among men and from 0.2 to 0 years among women). Conclusions: Future research should identify policy innovations and economic changes at the state level to better understand New York’s success, which may help other states emulate its performance.

Assessing the Impact of Person-level Matching Algorithms to Identify Risk of Fatal Opioid Overdose Across Disparate Datasets: Retrospective Analysis (Preprint)

2020 ◽  
Author(s):  
Lindsey Ferris ◽  
Jonathan P. Weiner ◽  
Brendan Saloner ◽  
Hadi Kharrazi
Keyword(s):  
Public Health ◽  
Risk Factors ◽  
At Risk ◽  
Area Under The Curve ◽  
The United States ◽  
Risk Indicators ◽  
Mortality Data ◽  
Opioid Overdose ◽  
Fatal Overdose ◽  
The Impact

BACKGROUND The opioid epidemic in the United States has precipitated a need for public health agencies to better understand risk factors associated with fatal overdoses. Matching person-level information stored in public health, medical, and human services datasets can enhance the understanding of opioid overdose risk factors and interventions. A major impediment to using datasets from separate agencies, has been the lack of a cross-organization unique identifier. Although different matching techniques that leverage patient demographic information can be used, the impact of using a particular matching approach is not well understood. OBJECTIVE This study compares the impact of using probabilistic versus deterministic matching algorithms to link disparate datasets together for identifying persons at risk of a fatal overdose. METHODS This study used statewide prescription drug monitoring program (PDMP), arrest, and mortality data matched at the person-level using a probabilistic and two deterministic matching algorithms. Impact of matching was assessed by comparing the prevalence of key risk indicators, the outcome, and performance of a multivariate logistic regression for fatal overdose using the combined datasets. RESULTS The probabilistically matched population had the highest degree of matching within the PDMP data and with arrest and mortality data, resulting in the highest prevalence of high-risk indicators and the outcome. Model performance using area under the curve (AUC) was comparable across the algorithms (probabilistic: 0.847; deterministic-basic: 0.854; deterministic+zip: 0.826), but demonstrated tradeoffs between sensitivity and specificity. CONCLUSIONS The probabilistic algorithm was more successful in linking patients with PDMP data with death and arrest data, resulting in a larger at-risk population. However, deterministic-basic matching may be a suitable option for understanding high-level risk based on the model’s area under the curve (0.854). The clinical use case should be considered when selecting a matching approach, as probabilistic algorithms can be more resource-intensive and costly to maintain compared with deterministic algorithms.

scholarly journals Covid-19 Will Reduce US Life Expectancy at Birth by More Than One Year in 2020

2020 ◽  
Author(s):  
Patrick Heuveline
Keyword(s):  
World War Ii ◽  
Life Expectancy ◽  
Opioid Overdose ◽  
Cumulative Number ◽  
Life Expectancy At Birth ◽  
Johns Hopkins University ◽  
Causes Of Mortality ◽  
One Year ◽  
The Impact ◽  
The U.S

AbstractOn December 3rd, 2020, the cumulative number of U.S. Covid-19 deaths tallied by Johns Hopkins University (JHU) online dashboard reached 275,000, surpassing the number at which life table calculations show Covid-19 mortality will lower the U.S. life expectancy at birth (LEB) for 2020 by one full year. Such an impact on the U.S. LEB is unprecedented since the end of World War II. With additional deaths by the year end, the reduction in 2020 LEB induced by Covid-19 deaths will inexorably exceed one year. Factoring the expected continuation of secular gains against other causes of mortality, the U.S. LEB should still drop by more than a full year between 2019 and 2020. By comparison, the opioid-overdose crisis led to a decline in U.S. LEB averaging .1 year annually, from 78.9 years in 2014 to 78.6 years in 2017. At its peak, the HIV epidemic reduced the U.S. LEB by .3 year in a single year, from 75.8 years in 1992 to 75.5 years in 1993. As of now, the US LEB is expected to fall back to the level it first reached in 2010. In other words, the impact of Covid-19 on U.S. mortality can be expected to cancel a decade of gains against all other causes of mortality combined.

scholarly journals The impact of mortality for infectious diseases on life expectancy at birth in Tuscany, Italy

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
L Kundisova ◽  
N Nante ◽  
A Martini ◽  
F Battisti ◽  
L Giovannetti ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Infectious Diseases ◽  
Antimicrobial Therapy ◽  
Geographic Area ◽  
Mortality Data ◽  
Epidemiologic Transition ◽  
Geographical Differences ◽  
Life Expectancy At Birth ◽  
Hospital Infection Control ◽  
The Impact

Abstract Introduction The epidemiologic transition describes the reduction of mortality for infectious diseases (ID), followed by an increase in prevalence of non-communicable diseases. During recent years the situation has changed; an increase in mortality for sepsis was observed. Italy is amongst the countries with the highest prevalence of microorganisms resistant to antimicrobial therapy in Europe. The aim of the present work was to evaluate the impact of mortality for ID on life expectancy (LE) in the Tuscany region(Italy). Methods Mortality data relative to residents that died during the period 2000/2002- 2013/2015 were provided by the Tuscan Regional Mortality Registry. At first the analysis was performed for whole territory, then for geographic area (Nord-Est:NE, Centrum:C, South-East:SE). The analysis was realized with software Epidat,using the Pollard's method of decomposition of variations in LE for age and cause of death. Results The overall gain in LE was 2.9 years for males and 2.6 years for females. The increase in mortality for ID was responsible for the loss of 0.11 years of LE for males vs. 0.16 years for females. The loss was observed in males aged 45-89, for females from 69 years onwards, with the highest loss between 79-89 years. After analysis for area, geographical differences emerged, for both males and females the highest loss of LE was observed for NE (-0.23 years vs.-0.19), followed by C (-0.15 years vs. -0.16) and SE (-0.12 vs. -0.11). Conclusions The result can be partially explained by the transition from ICD-9 to ICD-10 (in 2010), which improved the sensitivity of codification, but also by diffusion of pathogens resistant to antimicrobial therapy. The highest impact of ID was observed in elderly, probably due to the existence of predisposing clinical condition. The ID deserve major attention; the programmes of hospital infection control and antimicrobial stewardship have to be potentiated in order to contain the phenomenon. Key messages During the study period an increase in mortality for infectious diseases comported the loss in terms of LE years. The growing diffusion of microorganisms resistent to antimicrobial therapy could have contributed to the higher mortality rates observed during the last period.

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.

On the Uses of Disinformation to Legitimize the Revival of the Cold War: Health in the U.S.S.R.

1982 ◽  
Vol 12 (3) ◽  
pp. 481-496 ◽  
Author(s):  
Albert Szymanski
Keyword(s):  
Child Care ◽  
Soviet Union ◽  
Infant Mortality ◽  
Life Expectancy ◽  
Public Health Education ◽  
The United States ◽  
Mortality Data ◽  
The Soviet Union ◽  
Employment Of Women ◽  
Child Care Facilities

During the 1970s the Soviet Union experienced rising infant mortality rates and a corresponding levelling off of earlier increases in life expectancy. Several Western critics have misrepresented or exaggerated these statistics, suggesting that these trends indicate a general breakdown in the Soviet health care system as well as the failure of the Soviet form of socialism. This paper examines life expectancy and infant mortality data by Soviet republic, showing that rates are not uniform throughout the U.S.S.R. and in many cases compare favorably with those in Western European countries and the United States. It is suggested that the infant mortality problem in the U.S.S.R. is a temporary negative consequence of rapid progress in the areas of industrialization, employment of women, and socialization of child care. It is concluded that improvements in public health education, the quality of child care facilities, and the manufacture and distribution of infant formula will contribute to the rapid resolution of this problem.

Abstract 257: Urban Teaching and Non-Teaching Hospitals Outcomes: Myocardial Infarction

2017 ◽  
Vol 10 (suppl_3) ◽  
Author(s):  
Priscilla O Okunji ◽  
Johnnie Daniel
Keyword(s):  
Myocardial Infarction ◽  
Mortality Rate ◽  
Income Group ◽  
The United States ◽  
Teaching Hospitals ◽  
Age Difference ◽  
Age Group ◽  
Urban Teaching ◽  
Significant Difference ◽  
The Impact

Background: Patients with myocardial infarction reportedly have different outcomes on discharge according to hospital characteristics. In the present study, we evaluated the differences between urban teaching hospitals (UTH) and non-teaching hospitals (NTH), discharged in 2012. We also investigated on the outcomes. Methods: Sample of 117,808 subjects diagnosed with myocardial infarction were extracted from a nationwide inpatient stay dataset using the International Classification Data, ICD 9 code 41000 in the United States, according to hospital location, size, and teaching status. Results: The analysis of the data showed that more whites were admitted to both teaching and non teaching hospitals with more males (~24%) admitted than their female counterparts. However, blacks were admitted more (~15%) in urban teaching hospitals than medium urban non teaching hospitals. Age difference was noted as well, while age group (60-79 years) were admitted more in UTH, inversely urban non-teaching hospitals admitted more older (80 years or older) age group. A significant difference (~28%) was observed in both hospital categories with UTH admitting more patients of $1.00 - $38,999.00 income group than other income categories. In addition, it was observed that patients with MI stayed more (~5%) for 14 or more days, and charged more especially for income group of $80,000 or above in UTH than NTH. No significant difference was found in the mortality rate for both hospital categories. Conclusion: The overall outcomes showed that the mortality rate between urban teaching and non-teaching hospitals were non significant, though the inpatients MI stayed longer and were charged more in UTH than NTH. The authors call for the study to be replicated with a higher level of statistical measures to ascertain the impact of the variables on the outcomes for a more validated result.

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