scholarly journals Monitoring life expectancy levels during the COVID-19 pandemic: Example of the unequal impact in Spanish regions

2020 ◽  
Author(s):  
Sergi Trias-Llimós ◽  
Tim Riffe ◽  
Usama Bilal
Keyword(s):  
Life Expectancy ◽  
Count Data ◽  
Age Groups ◽  
Balearic Islands ◽  
Health Impacts ◽  
List Type ◽  
National Statistics ◽  
Spanish Regions ◽  
The Impact ◽  
Death Count

AbstractBackgroundTo provide an interpretable summary of the impact on mortality of the COVID-19 pandemic we estimate weekly and annual life expectancies at birth in Spain and its regions.MethodsWe used daily death count data from the Spanish MoMo, and death counts from 2018, and population on 1 July, 2019 by region (CCAA), age groups, and sex from the Spanish National Statistics Institute. We estimated weekly and annual (2019 and 2020*, the shifted annual calendar period up to June 14th 2020) life expectancies at birth as well as their differences with respect to 2019.ResultsWeekly life expectancies at birth in Spain were lower in weeks 11-20, 2020 compared to the same weeks in 2019. This drop in weekly life expectancy was especially strong in weeks 13 and 14 (March 23rd to April 5th), with national declines ranging between 6.1 and 7.6 years and maximum regional weekly declines of up to 15 years in Madrid. Annual life expectancy differences between 2019 and 2020 also reflected an overall drop in annual life expectancy of 0.8 years for both men and women. These drops ranged between 0 years in several regions (e.g. Canary and Balearic Islands) to 2.7 years among men in Madrid.ConclusionsLife expectancy is an easy to interpret measure for understanding the heterogeneity of mortality patterns across Spanish regions. Weekly and annual life expectancy are sensitive useful indicators for understanding disparities and communicating the gravity of the situation because differences are expressed in intuitive year units.Key messages-Weekly and annual updated life expectancy are valuable indicators of the health impacts of the pandemic in populations.-The impact of the COVID-19 pandemic in Spain has been severe and highly heterogeneous, with weekly life expectancy falls of up to 15 years in Madrid, and with annual life expectancy falls ranging between 0 and 2.7 years.-Our results for Spain provide important insights into the magnitude of the pandemic in mortality levels across regions and are easy to interpret and compare.

scholarly journals Monitoring life expectancy levels during the COVID-19 pandemic: Example of the unequal impact of the first wave on Spanish regions

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0241952 ◽  
Author(s):  
Sergi Trias-Llimós ◽  
Tim Riffe ◽  
Usama Bilal
Keyword(s):  
Life Expectancy ◽  
Count Data ◽  
Age Groups ◽  
Balearic Islands ◽  
Calendar Period ◽  
Men And Women ◽  
National Statistics ◽  
Spanish Regions ◽  
The Impact ◽  
Death Count

Background To provide an interpretable summary of the impact on mortality of the COVID-19 pandemic we estimate weekly and annual life expectancies at birth in Spain and its regions. Methods We used daily death count data from the Spanish Daily Mortality Monitoring System (MoMo), and death counts from 2018, and population on July 1st, 2019 by region (CCAA), age groups, and sex from the Spanish National Statistics Institute. We estimated weekly and annual (2019 and 2020*, the shifted annual calendar period up to 5 July 2020) life expectancies at birth as well as their differences with respect to 2019. Results Weekly life expectancies at birth in Spain were lower in weeks 11–20, 2020 compared to the same weeks in 2019. This drop in weekly life expectancy was especially strong in weeks 13 and 14 (March 23rd to April 5th), with national declines ranging between 6.1 and 7.6 years and maximum regional weekly declines of up to 15 years in Madrid. Annual life expectancy differences between 2019 and 2020 also reflected an overall drop in annual life expectancy of 0.9 years for both men and women. These drops ranged between 0 years in several regions (e.g. Canary and Balearic Islands) to 2.8 years among men in Madrid. Conclusions Life expectancy is an easy to interpret measure for understanding the heterogeneity of mortality patterns across Spanish regions. Weekly and annual life expectancy are sensitive and useful indicators for understanding disparities and communicating the gravity of the situation because differences are expressed in intuitive year units.

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 Time use and social mixing during and around festive periods: Potential changes in the age distribution of COVID-19 cases from increased intergenerational interactions

2020 ◽  
Author(s):  
Edwin van Leeuwen ◽  
Frank G. Sandmann ◽  
Rosalind M. Eggo ◽  
Peter J. White ◽  
Keyword(s):  
Time Use ◽  
Reproduction Number ◽  
Age Distribution ◽  
Age Groups ◽  
List Type ◽  
Relative Incidence ◽  
Holiday Period ◽  
Social Mixing ◽  
Intergenerational Interactions ◽  
The Impact

AbstractRationaleAmid the ongoing coronavirus disease 2019 (COVID-19) pandemic in which many countries have adopted physical distancing measures, tiered restrictions, and episodic “lockdowns,” the impact of potentially increased social mixing during festive holidays on the age distribution of new COVID-19 cases remains unclear.ObjectiveWe aimed to gain insights into possible changes in the age distribution of COVID-19 cases in the UK after temporarily increased intergenerational interactions in late December 2020.MethodWe modelled changes in time use and social mixing based on age-stratified contact rates using historical nationally-representative surveys and up-to-date Google mobility data from four weeks before and after the festive period. We explored changes in the effective reproduction number and the age distribution of cases, in four scenarios: (1) “normal”: time use and contact patterns as observed historically, (2) “pre-lockdown”: patterns as seen before the lockdown in November 2020, (3) “lockdown”: patterns restricted as in November 2020, and (4) “festive break”: similar to 3 but with social visits over the holiday period as in 1.ResultsAcross ages, the estimated Reff decreases during the festive break in scenarios 1-3 and returns to pre-holiday levels in scenarios 2-3, while remaining relatively stable in scenario 4. Relative incidence is likely to decrease in children aged 0-15 but increase in other ages. Changes in age distribution were large during the holidays, and are likely to start before the holidays for individuals aged 16-24 years in scenarios 1-3.ConclusionsOur modelling findings suggest that increased contacts during the festive period may shift the age distribution of COVID-19 cases from children towards adults. Given that COVID-19-related hospitalisations and deaths rise by age, more intergenerational mixing risks an increased burden in the period following the holidays.HighlightsHome visits are associated with increased intergenerational mixing.The effective reproduction number is likely to remain stable or even reduce slightly due to a reduction in contacts at work and school.Relative incidence is likely to become lower in children, but higher in theolder (more vulnerable) age groups around the holiday period, which could lead to increased health care burden.

scholarly journals Can We Make Time for Physical Activity? Simulating Effects of Daily Physical Activity on Mortality

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Geoff Rowe ◽  
Mark S. Tremblay ◽  
Douglas G. Manuel
Keyword(s):  
Physical Activity ◽  
Life Expectancy ◽  
Screen Time ◽  
Activity Patterns ◽  
Age Groups ◽  
Time Profiles ◽  
Metabolic Equivalents ◽  
Canadian Population ◽  
The Impact ◽  
Sample Time

Background. The link between physical activity and health outcomes is well established, yet levels of physical activity remain low. This study quantifies effects on mortality of the substitution of low activity episodes by higher activity alternatives using time-use data. Methods. Sample time profiles are representative of the Canadian population (n=19,597). Activity time and mortality are linked using metabolic equivalents(METs). Mortality risk is determined by peak daily METs and hours spent sedentary. The impact of altering activity patterns is assessed using simulated life expectancy. Results. If all leisure screen time was replaced with an equal amount of time spent going for a walk, an increase in life expectancy of about 2.5 years (95% CI, 1.4 to 3.8) would be expected. No other activity category would have as large as an effect. Conclusions. Reducing leisure screen time has a large effect, because seniors particularly have a large potential for mortality reduction and watch more television than other age groups. The general problem of inactivity cannot be solved simply by reallocating time to more active pursuits, because daily activity patterns can be heterogeneous or fragmented and activities may be nondiscretionary (e.g., work or childcare).

scholarly journals Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis

2021 ◽  
pp. jech-2020-215505
Author(s):  
Jose Manuel Aburto ◽  
Ridhi Kashyap ◽  
Jonas Schöley ◽  
Colin Angus ◽  
John Ermisch ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Excess Mortality ◽  
Prediction Interval ◽  
Age Groups ◽  
Population Level ◽  
England And Wales ◽  
Life Expectancy At Birth ◽  
Using Data ◽  
The Impact ◽  
Excess Deaths

BackgroundDeaths directly linked to COVID-19 infection may be misclassified, and the pandemic may have indirectly affected other causes of death. To overcome these measurement challenges, we estimate the impact of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality from week 10 of 2020, when the first COVID-19 death was registered, to week 47 ending 20 November 2020 in England and Wales through an analysis of excess mortality.MethodsWe estimated age and sex-specific excess mortality risk and deaths above a baseline adjusted for seasonality with a systematic comparison of four different models using data from the Office for National Statistics. We additionally provide estimates of life expectancy at birth and lifespan inequality defined as the SD in age at death.ResultsThere have been 57 419 (95% prediction interval: 54 197, 60 752) excess deaths in the first 47 weeks of 2020, 55% of which occurred in men. Excess deaths increased sharply with age and men experienced elevated risks of death in all age groups. Life expectancy at birth dropped 0.9 and 1.2 years for women and men relative to the 2019 levels, respectively. Lifespan inequality also fell over the same period by 5 months for both sexes.ConclusionQuantifying excess deaths and their impact on life expectancy at birth provide a more comprehensive picture of the burden of COVID-19 on mortality. Whether mortality will return to—or even fall below—the baseline level remains to be seen as the pandemic continues to unfold and diverse interventions are put in place.

scholarly journals Estimating the burden of COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: A population-level analysis

2020 ◽  
Author(s):  
José Manuel Aburto ◽  
Ridhi Kashyap ◽  
Jonas Schöley ◽  
Colin Angus ◽  
John Ermisch ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Population Health ◽  
Mortality Risk ◽  
Excess Mortality ◽  
England And Wales ◽  
National Statistics ◽  
Life Expectancy At Birth ◽  
The Impact ◽  
Age And Sex ◽  
Excess Deaths

AbstractBackgroundDeaths directly linked to COVID-19 infection may be misclassified, and the pandemic may have indirectly affected other causes of death. To overcome these measurement challenges, we estimate the impact of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality from week 10, when the first COVID-19 death was registered, to week 47 ending November 20, 2020 in England and Wales through an analysis of excess mortality.MethodsWe estimated age and sex-specific excess mortality risk and deaths above a baseline adjusted for seasonality with a systematic comparison of four different models using data from the Office for National Statistics. We additionally provide estimates of life expectancy at birth and lifespan inequality defined as the standard deviation in age at death.ResultsThere have been 57,419 (95% Prediction Interval: 54,197, 60,752) excess deaths in the first 47 weeks of 2020, 55% of which occurred in men. Excess deaths increased sharply with age and men experienced elevated risks of death in all age groups. Life expectancy at birth dropped 0.9 and 1.2 years for females and males relative to the 2019 levels, respectively. Lifespan inequality also fell over the same period by five months for both sexes.ConclusionQuantifying excess deaths and their impact on life expectancy at birth provides a more comprehensive picture of the burden of COVID-19 on mortality. Whether mortality will return to -or even fall below-the baseline level remains to be seen as the pandemic continues to unfold and diverse interventions are put in place.Summary boxesWhat is already known on this topicCOVID-19 related deaths may be misclassified thereby inaccurately estimating the full impact of the pandemic on mortality. The pandemic may also have indirect effects on other causes due to changed behaviours, as well as the social and economic consequences resulting from its management. Excess mortality, the difference between observed deaths and what would have been expected in the absence of the pandemic, is a useful metric to quantify the overall impact of the pandemic on mortality and population health. Life expectancy at birth and lifespan inequality assess the cumulative impact of the pandemic on population health.What this study addsWe examine death registration data from the Office for National Statistics from 2010 to week 47 (ending on November 20) in 2020 to quantify the impact of the COVID-19 pandemic on mortality in England and Wales thus far. We estimate excess mortality risk by age and sex, and quantify the impact of excess mortality risk on excess deaths, life expectancy and lifespan inequality. During weeks 10 through 47 of 2020, elevated mortality rates resulted in 57,419 additional deaths compared with baseline mortality. Life expectancy at birth for females and males over the 47 weeks of 2020 was 82.6 and 78.7 years, with 0.9 and 1.2 years of life lost relative to the year 2019. Lifespan inequality, a measure of the spread or variation in ages at death, declined due to the increase of mortality at older ages.

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 Excess Deaths associated with the COVID-19 Pandemic in Ukraine in 2020

2021 ◽  
Author(s):  
Neil K. Mehta ◽  
Ihor Honchar ◽  
Olena Doroshenko ◽  
Igor Brovchenko ◽  
Khrystyna Pak ◽  
...  
Keyword(s):  
Excess Mortality ◽  
Age Groups ◽  
European Countries ◽  
List Type ◽  
Younger Age ◽  
Influenza Activity ◽  
Expected Mortality ◽  
The Impact ◽  
Excess Deaths

AbstractCOVID-19 related mortality has been understudied in Ukraine. As part of a World Bank project, we estimated excess mortality in Ukraine during 2020. Data on all deaths registered in government-controlled Ukraine from 2016-2020 (N=2,946,505) were utilized. We predicted deaths in 2020 by five-year age groups, sex, and month and calculated the number of deaths that deviated from expected levels (excess deaths). We compared excess deaths with the number of recorded COVID-19 deaths on death certificates and with published estimates for 30 European countries. We estimated 38,095 excess deaths in 2020 (6% of all deaths). Death rates were above expected levels in February and from June-December and lower in January and March-May. From June-December, we estimated 52,124 excess deaths with a peak in November (16,891 deaths). COVID-19 recorded deaths were approximately one-third of excess deaths in June-December (18,959 vs. 52,124). Higher than expected mortality was detected for all age groups 40-44 years and above and for those ages 0-4, 15-19, and 20-24. Ukraine’s excess mortality was about average compared to 30 other European countries. Excess deaths may be attributed directly to SARS-COV2 infection or indirectly to death causes associated with social and economic upheavals resulting in from the pandemic. Lower than expected mortality during the early part of 2020 is consistent with low influenza activity and reductions in deaths from restricted movement. Further studies are required to examine the causes of death that have contributed to positive excess mortality, particularly among younger aged groups.Key MessagesUkraine has experienced sizeable changes in its recent demography and the impact of the COVID-19 pandemic on the country’s aggregate mortality patterns is understudiedBased on recent death trends, we found that Ukraine experienced lower than expected mortality during the early part of 2020 and consistently higher than expected mortality from June-December with peak levels occurring in NovemberPositive excess mortality was observed for all age groups beginning at ages 40-44 as well as some younger age groups.

scholarly journals Smoking as the main factor of preventable mortality in Serbia

Stanovnistvo ◽  
2017 ◽  
Vol 55 (1) ◽  
pp. 87-106 ◽  
Author(s):  
Ivan Marinkovic
Keyword(s):  
Mortality Rate ◽  
Life Expectancy ◽  
Age Groups ◽  
Total Mortality ◽  
Mortality Factor ◽  
Absolute Difference ◽  
Mortality Pattern ◽  
Female Population ◽  
The Impact ◽  
Related Mortality

The use of tobacco in Serbia has for many years been one of the most frequent risk factors affecting disease development. Although its impact is often neglected and the effects on health minimised, reviewing the existing literature and calculating the tobacco consumption impact on the mortality of the population in Serbia (using the Peto-Lopez method) show a clear link between smoking and health of the population. Serbian population is heavily burdened with the negative effects of tobacco on health, especially men. At the beginning of the second decade of the 21st century, mortality from the illness or cause of death associated with smoking was at about 17% of the total mortality. In men, it is estimated that even a quarter of the total mortality is associated with smoking. In the female population, the share of smokers is considerably lower, and consequently the mortality from this factor is lower, about 9% of the total mortality. Of all major disease groups, tumours are most affected by smoking. The share of tobaccorelated mortality in neoplasms is high and accounts for 30% (43% in men and 14% in women). In cardiovascular diseases, the impact of smoking is much smaller and about 6,000 deaths per year are associated with the use of tobacco. Since the early 1990s, the number of smoking-attributable death has been growing. Relatively, the share of men has not changed, but for 20 years of analysis the share of women has significantly increased from 5% to 9%. In all age groups, the share of smoking-related mortality has increased in the female population, especially in the 45-69 age range where mortality has been doubled. Surveys on the health of the Serbian population also confirm the trend of increasing the share of women smokers in the population, especially in the categories of young people. Men in Serbia (35-69 years of age) have the highest smoking-attributable death rate in Europe. As much as 44% of total deaths in that age are directly related to smoking. Besides Hungary, where mortality in men is also relatively high (42%), other countries have significantly lower shares. Observed at the level of the entire continent, countries of the Balkan Peninsula (and their neighbours) have the highest shares of smoking-attributable death. Women in Serbia have a moderately high share of 9% and are among the ten most vulnerable countries in Europe. The biggest difference in smoking-related mortality by gender is observed in the Pyrenees Peninsula and in the eastern and south-eastern parts of Europe. These are also the countries with the largest absolute difference in the mortality rate of men and women, thus confirming the hypothesis that tobacco smoke, as a single mortality factor, plays the most important role in establishing a different gender mortality pattern. A high percentage of smokers in the total population limits the growth of life expectancy and affects the difference in gender mortality rate. If a certain mortality factor potentially affects the life expectancy of up to three years for men in Serbia, as shown in the paper, then it is especially important to pay attention to measures of prevention and awareness of the population regarding this issue. Moreover, it is particularly important to recognise the consequences of passive smoking the youth and children are exposed to, since in Serbia there is a great deal of tolerance for smoking indoors.

scholarly journals Understanding the Increase in Life Expectancy in Hong Kong: Contributions of Changes in Age- and Cause-Specific Mortality

2019 ◽  
Vol 16 (11) ◽  
pp. 1959 ◽  
Author(s):  
Yan Zheng ◽  
Qingsong Chang ◽  
Paul Siu Fai Yip
Keyword(s):  
Hong Kong ◽  
Life Expectancy ◽  
Age Groups ◽  
Limited Attention ◽  
Malignant Neoplasms ◽  
Negative Contribution ◽  
Younger Age ◽  
Males And Females ◽  
The Impact ◽  
Circulatory Diseases

To assess the mechanism responsible for the improvement in life expectancy in Hong Kong over the past several decades, Arriaga’s decomposition method was applied to quantify the influence of the age structure and the leading causes of death on the increase in life expectancy in Hong Kong from 1986 to 2015. Our results showed that, during the observed period, the major contribution to the improvement in life expectancy in Hong Kong was attributable to the older population for both males and females. Contributions of malignant neoplasms in the period of 1986–1995, 1996–2005 and 2006–2015 were 0.613, 0.279 and 0.887 years in males and 0.391, 0.312 and 0.226 years in females, respectively. For circulatory diseases, the corresponding figures were 1.452, 0.202 and 0.832 years in males and 0.675, 0.192 and 1.069 years in females, with the largest contribution also shifting to older ages. However, these positive contributions were partly offset by the negative contribution of pneumonia, especially among those at advanced ages. Furthermore, although the impact was limited, attention should also be paid to the prevalence of some chronic diseases among the younger age groups in recent years.

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