scholarly journals Geographical variation in life expectancy at birth in England and Wales is largely explained by deprivation

2005 ◽  
Vol 59 (2) ◽  
pp. 115-120 ◽  
Author(s):  
L. M Woods
Keyword(s):  
Life Expectancy ◽  
Geographical Variation ◽  
England And Wales ◽  
Life Expectancy At Birth

scholarly journals Why has mortality in England and Wales been increasing? An iterative demographic analysis

2017 ◽  
Vol 110 (4) ◽  
pp. 153-162 ◽  
Author(s):  
Lucinda Hiam ◽  
Danny Dorling ◽  
Dominic Harrison ◽  
Martin McKee
Keyword(s):  
Life Expectancy ◽  
Social Care ◽  
Demographic Analysis ◽  
England And Wales ◽  
Life Expectancy At Birth ◽  
Health And Social Care ◽  
Diagnosis Of Dementia ◽  
Small Decline ◽  
Post War

Objectives To understand why mortality increased in England and Wales in 2015. Design Iterative demographic analysis. Setting England and Wales Participants Population of England and Wales. Main outcome measures Causes and ages at death contributing to life expectancy changes between 2013 and 2015. Results The long-term decline in age-standardised mortality in England and Wales was reversed in 2011. Although there was a small fall in mortality rates between 2013 and 2014, in 2015 we then saw one of the largest increases in deaths in the post-war period. Nonetheless, mortality in 2015 was higher than in any year since 2008. A small decline in life expectancy at birth between 2013 and 2015 was not significant but declines in life expectancy at ages over 60 were. The largest contributors to the observed changes in life expectancy were in those aged over 85 years, with dementias making the greatest contributions in both sexes. However, changes in coding practices and diagnosis of dementia demands caution in interpreting this finding. Conclusions The long-term decline in mortality in England and Wales has reversed, with approximately 30,000 extra deaths compared to what would be expected if the average age-specific death rates in 2006–2014 had continued. These excess deaths are largely in the older population, who are most dependent on health and social care. The major contributor, based on reported causes of death, was dementia but caution was advised in this interpretation. The role of the health and social care system is explored in an accompanying paper.

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 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 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.

Abstract P165: Future Burden of Morbidity and Disability in England and Wales: A Modelling Study

Circulation ◽  
2016 ◽  
Vol 133 (suppl_1) ◽  
Author(s):  
Maria Guzman Castillo ◽  
Sara Ahmadi-Abhari ◽  
Piotr Bandosz ◽  
Martin Shipley ◽  
Simon Capewell ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Similar Degree ◽  
Health States ◽  
England And Wales ◽  
Incidence Trends ◽  
Dementia Incidence ◽  
Incidence And Mortality ◽  
The Future ◽  
Future Burden ◽  
Disability Prevalence

Background: Cardiovascular disease (CVD) and dementia have profound impacts on the morbidity and disability burden in older people. Uncertainty remains regarding the future incidence of these conditions. We forecast future levels of morbidity and disability in England and Wales up to 2040 under two scenarios regarding CVD and dementia future trends. Methods: We developed a probabilistic Markov model (IMPACT-BAM) which follows the transitions of the England and Wales population into health states characterised by the presence or absence of CVD, dementia and disability to 2040. Data sources include national health registers (ONS) and cohort studies (HSE, Whitehall II and ELSA). Modelled CVD and Non-CVD mortality and prevalence trends for disability and morbidity were used to estimate trends in life expectancy (LE), morbidity-free life expectancy (MFLE) and disability-free life expectancy (DFLE). We assumed that CVD incidence and mortality will continue their current trends and modelled two scenarios: Scenario A assumes constant dementia incidence, a common assumption when projecting future burden of dementia; Scenario B assumes 2% annual decline in dementia incidence, as suggested in UK population-based cohorts. Results: In 2011, LE at age 65 was 18.4 years for men and 21.0 years for women. In Scenario A, LE at 65 in 2040 will increase to 26.7 and 24.8 years in men and women. DFLE at 65 will increase (by 5.5 years in men and 2.8 years in women, to 21.7 and 20.7 years respectively). MFLE at 65 will increase slightly (by 1.5 years in men and 1.4 in women, to 10.7 and 13.2 years respectively). Disability prevalence would increase by 3.1% to 14.4% ( 1,081,483 of 7,510,299) in men and decrease slightly (by 0.6% to 14% (1,214,754 of 8,676,813)) in women. In Scenario B, LE at 65 in 2040 will increase to a similar degree as in Scenario A, but DFLE and MFLE will increase faster (DFLE: by 7.5 years in men and 4.6 in women, to 23.7 and 22.5 years respectively; MFLE: by 4.5 years for both genders to 13.8 years in men and 16.3 in women). Disability prevalence will slightly increase (by 0.8% to 12.1% (908,746 of 7,510,299)) in men and decrease by 3.0% to 11.4% (989,157 of 8,676,813) in women. Conclusions: The future disability burden crucially depends on assumptions about future dementia incidence trends. If the dementia incidence continues unchanged, the duration of morbidity and disability will be prolonged. However, if dementia incidence decreases (as suggested in the UK and mirroring CVD declines) we could live more years in good health, with morbidity compressed into a shorter period before death.

A VARIED PATTERN OF CHANGE OF THE SEX DIFFERENTIAL IN SURVIVAL IN THE G7 COUNTRIES

2005 ◽  
Vol 38 (3) ◽  
pp. 391-401 ◽  
Author(s):  
FRANK TROVATO ◽  
NILS B. HEYEN
Keyword(s):  
Sex Differences ◽  
Life Expectancy ◽  
Point Of View ◽  
Industrialized Countries ◽  
Circulatory Disease ◽  
G7 Countries ◽  
Death Rates ◽  
The United Kingdom ◽  
Life Expectancy At Birth ◽  
The Difference

Over the course of the 20th century the sex differential in life expectancy at birth in the industrialized countries has widened considerably in favour of women. Starting in the early 1970s, the beginning of a reversal in the long-term pattern of this differential has been noted in some high-income countries. This study documents a sustained pattern of narrowing of this measure into the later part of the 1990s for six of the populations that comprise the G7 countries: Canada, France, Germany, Italy, England and Wales (as representative of the United Kingdom) and USA. For Japan, a persistence of widening sex differences in survival is noted. The sex differences in life expectancy are decomposed over roughly three decades (early 1970s to late 1990s) from the point of view of four major cause-of-death categories: circulatory diseases, cancers, accidents/violence/suicide, and ‘other’ (residual) causes. In the six countries where the sex gap has narrowed, this has resulted primarily from reduced sex differences in circulatory disease mortality, and secondarily from reduced differences in male and female death rates due to accidents, violence and suicide combined. In some of the countries sex differentials in cancer mortality have been converging lately, and this has also contributed to a narrowing of the difference in life expectancy. In Japan, males have been less successful in reducing their survival disadvantage in relation to Japanese women with regard to circulatory disease and cancer; and in the case of accidents/violence/suicide, male death rates increased during the 1990s. These trends explain the divergent pattern of the sex difference in life expectation in Japan as compared with the other G7 nations.

scholarly journals Potential gain in life expectancy by gender after elimination of a specific cause of death in urban India

2020 ◽  
Vol 7 (5) ◽  
pp. 1848
Author(s):  
Bal Kishan Gulati ◽  
Damodar Sahu ◽  
Anil Kumar ◽  
M. V. Vardhana Rao
Keyword(s):  
Life Expectancy ◽  
Life Table ◽  
Cause Of Death ◽  
Metabolic Diseases ◽  
Circulatory System ◽  
Average Life Span ◽  
Maximum Gain ◽  
Life Expectancy At Birth ◽  
Potential Gain ◽  
Urban India

Background: Life expectancy is a statistical measure to depict average life span a person is expected to live at a given age under given age-specific mortality rates. Cause-elimination life table measures potential gain in life expectancy after elimination of a specific disease. The present study aims to estimate potential gain in life expectancy by gender in urban India after complete and partial elimination of ten leading causes of deaths using secondary data of medical certification of cause of death (MCCD) for the year 2015.Methods: Life table method was used for estimating potential gain after eliminating diseases to the tune of 25%, 50%, 75% and 100%.Results: Maximum gain in life expectancy at birth estimated from complete elimination of diseases of the circulatory system (11.1 years in males versus 13.1 years in females); followed by certain infectious and parasitic diseases (2.2  versus 2.1 years); diseases of the respiratory system (2.2 versus 2.1); injury, poisoning and certain other consequences of external causes (1.1 versus 0.7); neoplasms (0.9 versus 1.0); endocrine, nutritional and metabolic diseases (0.8 versus 0.9); diseases of the digestive system (0.8 versus 0.4); diseases of the genitourinary system (0.6 versus 0.6); diseases of the nervous system (0.4 versus 0.4); and diseases of blood & blood forming organs and certain disorders involving the immune mechanism (0.2 versus 0.3 years).Conclusions: Elimination of the circulatory diseases resulted into maximum gain in life expectancy. These findings may have implications in setting up health goals, allocating resources and launching tailor-made health programmes.

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