Recent mortality in Britain: a review of trends and explanations

2021 ◽  
Author(s):  
Michael Murphy
Keyword(s):  
Life Expectancy ◽  
Excess Mortality ◽  
Seasonal Influenza ◽  
Dominant Role ◽  
Good Health ◽  
Healthy Life ◽  
Life Expectancy At Birth ◽  
Percentage Improvement ◽  
Health And Social Care

Abstract The annual percentage improvement in standardised mortality rates in the period 2011–19 was the lowest for 70 years, whereas the 2001–10 value was the highest since records began in 1841. A similar slowdown occurred from around 2011 in most European Union countries, although this was generally less severe than in Britain. Life expectancy at birth actually fell in USA for three successive years in period 2014–17. The downturn in Britain since 2011 was wide-ranging, affecting young and old, women and men and the more and the less advantaged to a broadly similar extent. Year-to-year variation in mortality increased mainly due to increased volatility in winter excess mortality from 2011, but all seasons showed lower rates of improvement in underlying longer-term trends. Mortality had started to improve at the end of the decade and the 2019 value was the lowest-ever value in Britain. Two main explanations for these trends have been advanced: UK Government post-2008 austerity policies, especially in the health and social care sectors, and the role of seasonal influenza. However, the evidence for a dominant role for either of these is weak. Longer-term overall trends have been determined principally by trends in cardiovascular rather than non-cardiovascular causes of death, although recent changes in discovery and coding of dementias makes it difficult to draw firm conclusions. Healthy life expectancy trends are also affected by changes in data and methods, but the proportion of life spent in good health for both women and men over age 65 has increased slightly since 2010.

scholarly journals The Adoption of Smoking and Its Effect on the Mortality Gender Gap in Netherlands: A Historical Perspective

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Fanny Janssen ◽  
Frans van Poppel
Keyword(s):  
Life Expectancy ◽  
Sex Difference ◽  
Gender Gap ◽  
Cancer Mortality ◽  
Historical Perspective ◽  
Excess Mortality ◽  
Attributable Mortality ◽  
Life Expectancy At Birth ◽  
Specific Mortality

We examine in depth the effect of differences in the smoking adoption patterns of men and women on the mortality gender gap in Netherlands, employing a historical perspective. Using an indirect estimation technique based on observed lung cancer mortality from 1931 to 2012, we estimated lifetime smoking prevalence and smoking-attributable mortality. We decomposed the sex difference in life expectancy at birth into smoking-related and nonsmoking-related overall and cause-specific mortality. The smoking epidemic in Netherlands, which started among men born around 1850 and among women from birth cohort 1900 onwards, contributed substantially to the increasing sex difference in life expectancy at birth from 1931 (1.3 years) to 1982 (6.7 years), the subsequent decline to 3.7 years in 2012, and the high excess mortality among Dutch men born between 1895 and 1910. Smoking-related cancer mortality contributed most to the increase in the sex difference, whereas smoking-related cardiovascular disease mortality was mainly responsible for the decline from 1983 onwards. Examining nonsmoking-related (cause-specific) mortality shed new light on the mortality gender gap and revealed the important role of smoking-related cancers, the continuation of excess mortality among women aged 40–50, and a smaller role of biological factors in the sex difference than was previously estimated.

scholarly journals Changing Educational Gradients in Life Expectancy With and Without Disease Among U.S. Older Adults From 2000 to 2010

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 505-505
Author(s):  
Matthew Farina ◽  
Phillip Cantu ◽  
Mark Hayward
Keyword(s):  
Older Adults ◽  
Life Expectancy ◽  
Chronic Diseases ◽  
Population Aging ◽  
Good Health ◽  
Vital Statistics ◽  
Healthy Life Expectancy ◽  
Healthy Life ◽  
Education Group ◽  
Education Groups

Abstract Recent research has documented increasing education inequality in life expectancy among U.S. adults; however, much is unknown about other health status changes. The objective of study is to assess how healthy and unhealthy life expectancies, as classified by common chronic diseases, has changed for older adults across education groups. Data come from the Health and Retirement Study and National Vital Statistics. We created prevalence-based life tables using the Sullivan method to assess sex-specific life expectancies for stroke, heart disease, cancer, and arthritis by education group. In general, unhealthy life expectancy increased with each condition across education groups. However, the increases in unhealthy life expectancy varied greatly. While stroke increased by half a year across education groups, life expectancy with diabetes increased by 3 to 4 years. In contrast, the evidence for healthy life expectancy provides mixed results. Across chronic diseases, healthy life expectancy decreased by 1 to 3 years for respondents without a 4-year degree. Conversely, healthy life expectancy increased for the college educated by .5 to 3 years. While previous research shows increases in life expectancy for the most educated, trends in life expectancy with chronic conditions is less positive: not all additional years are in lived in good health. In addition to documenting life expectancy changes across education groups, research assessing health of older adults should consider the changing inequality across a variety of health conditions, which will have broad implications for population aging and policy intervention.

scholarly journals Healthy life expectancy in Brazil: applying the Sullivan method

2005 ◽  
Vol 21 (suppl 1) ◽  
pp. S7-S18 ◽  
Author(s):  
Dalia Elena Romero ◽  
Iúri da Costa Leite ◽  
Célia Landmann Szwarcwald
Keyword(s):  
Life Expectancy ◽  
Functional Limitation ◽  
Good Health ◽  
World Health ◽  
Healthy Life Expectancy ◽  
State Of Health ◽  
World Health Survey ◽  
Healthy Life ◽  
Mortality And Morbidity ◽  
Sullivan Method

The objective of this study is to present the method proposed by Sullivan and to estimate the healthy life expectancy using different measures of state of health, based on information from the World Health Survey carried out in Brazil in 2003. By combining information on mortality and morbidity into a unique indicator, simple to calculate and easy to interpret, the Sullivan method is currently the one most commonly used for estimating healthy life expectancy. The results show higher number of healthy years lost if there is a long-term disease or disability that limits daily activities, regardless of the difficulty in performing such activities or the severity of the functional limitations. The two measures of healthy life expectancy adjusted by the severity of functional limitation show results very similar to estimates based on the perception of state of health, especially in advanced age. It was also observed, for all measures used, that the proportion of healthy years lost increases significantly with age and that, although females have higher life expectancy than males, they live proportionally less years in good health.

The influence of health on economic growth from the perspective of sustainable development: a case of OECD countries

2020 ◽  
Vol 16 (3) ◽  
pp. 181-194 ◽  
Author(s):  
Seda Yıldırım ◽  
Durmus Cagri Yildirim ◽  
Hande Calıskan
Keyword(s):  
Economic Growth ◽  
Cluster Analysis ◽  
Sustainable Development ◽  
Health Status ◽  
Life Expectancy ◽  
Oecd Countries ◽  
Content Type ◽  
Life Expectancy At Birth ◽  
Lower Health

PurposeThis study aims to explain the role of health on economic growth for OECD countries in the context of sustainable development. Accordingly, the study investigates the relationship between health and economic growth in OECD countries.Design/methodology/approachThis study employed cluster analysis and econometric methods. By cluster analysis, 12 OECD countries (France, Germany, Finland, Slovenia, Belgium, Portugal, Estonia, Czech Republic, Hungary, South Korea, Poland and Slovakia) were classified into two clusters as high and low health status through health indicators. For panel threshold analysis, the data included growth rates, life expectancy at birth, export rates, population data, fixed capital investments, inflation and foreign direct investment for the period of 1999–2016.FindingsThe study determined two main clusters as countries with high health status (level) and low health status (level), but there was no threshold effect in clusters. It was concluded that an increase in the life expectancy at birth of countries with higher health status had no significant impact on economic growth. However, the increase in the life expectancy at birth of countries with lower health status influenced economic growth positively.Research limitations/implicationsThis study used data that including period of 1999–2016 for OECD countries. In addition, the study used cluster analysis to determine health status of countries, and then panel threshold analysis was preferred to explain significant relations.Originality/valueThis study showed that the role of health on economic growth can change toward country groups as higher and lower health status. It was proved that higher life expectancy can influence economic growth positively in countries with worse or low health status. In this context, developing countries, which try to achieve sustainable development, should improve their health status to achieve economic and social development at the same time.

Sex differences in healthy life expectancy from self-perceived assessments of health in the City of São Paulo, Brazil

2008 ◽  
Vol 28 (1) ◽  
pp. 35-48 ◽  
Author(s):  
MIRELA CASTRO SANTOS CAMARGOS ◽  
CARLA JORGE MACHADO ◽  
ROBERTO NASCIMENTO RODRIGUES
Keyword(s):  
Life Expectancy ◽  
Multivariate Analyses ◽  
Perceived Health ◽  
Good Health ◽  
Sao Paulo ◽  
Healthy Life Expectancy ◽  
São Paulo ◽  
Healthy Life ◽  
Healthy State ◽  
The City

ABSTRACTWhether life is spent in good health or disability has a critical influence on the use of health-care services. It is also known that average healthy life expectancy differs by sex. This paper reports estimations of healthy and unhealthy life expectancy in old age using self-reported health assessments for the City of São Paulo, Brazil in 2000–01. The data derived from the Health, Well-being and Aging in Latin America and the Caribbean Project (SABE), and from population censuses and mortality statistics. Sullivan's estimation method was used. It combines the age-specific schedule of the current probabilities of death with the prevalence of self-perceived ‘poor’ and ‘good’ health. The paper also reports multivariate analyses of the factors associated with variations by age group and sex in self-perceived health. The findings revealed that, at all ages, women live longer than men and for more years in a healthy state. Among men, those aged 60, 65 and 70 years were expected to live a higher percentage of their remaining life than women in a healthy state, but among those aged 75, 80 and 85 years, the opposite held. Among women, the percentage of remaining years that were unhealthy did not increase as age increased, which differs from previous findings. The multivariate analyses showed that with increasing age, for women the number of chronic diseases decreased but dependency increased, and for men the opposite held. This finding indicated that the percentage of life spent in poor self-perceived health more accurately predicts mortality in men than women.

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 Gender difference in trends in healthy life expectancy in 2005-2012 for adults aged 50 years and older in South Africa

2019 ◽  
Vol 4 (2) ◽  
pp. 12 ◽  
Author(s):  
Witness Chirinda ◽  
Yasuhiko Saito ◽  
Danan Gu ◽  
Nompumelelo Zungu
Keyword(s):  
South Africa ◽  
Life Expectancy ◽  
Older People ◽  
Good Health ◽  
Gender Disparities ◽  
Healthy Life Expectancy ◽  
Cross Sectional ◽  
Healthy Life ◽  
Fiscal Planning ◽  
Using Data

Data characterizing older people’s life expectancy by good or poor health isimportant for policy and fiscal planning. This study aims to examine trends and investigategender differences in healthy life expectancy (HLE) for older people in South Africa for theperiod 2005–2012. Using data from three repeated cross-sectional surveys conducted in 2005,2008, and 2012, we applied a self-rated health measure to estimating HLE. The Sullivanmethod was used in the calculations. We found that unhealthy life expectancy decreased overthe period, while HLE and the proportion of life spent in good health increased more thantotal life expectancy in the same period. Gender disparities were evident: Women had higherlife expectancy than men, yet they spent a greater proportion of their lifetime in poor health.We concluded that HLE of older people in South Africa has improved over the period underinvestigation.

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