scholarly journals The Role of Smoking in Country Differences in Life Expectancy Across Europe, 1985–2014

2020 ◽  
Author(s):  
Fanny Janssen
Keyword(s):  
Life Expectancy ◽  
Weighted Average ◽  
European Countries ◽  
Attributable Mortality ◽  
Mortality Data ◽  
Relative Contribution ◽  
Life Expectancy At Birth ◽  
Long Run ◽  
Country Differences

Abstract Introduction Smoking contributes substantially to mortality levels and trends. Its role in country differences in mortality has, however, hardly been quantified. The current study formally assesses the—so far unknown—changing contribution of smoking to country differences in life expectancy at birth (e0) across Europe. Methods Using all-cause mortality data and indirectly estimated smoking-attributable mortality rates by age and sex for 30 European countries from 1985 to 2014, the differences in e0 between each individual European country and the weighted average were decomposed into a smoking- and a nonsmoking-related part. Results In 2014, e0 ranged from 70.8 years in Russia to 83.1 years in Switzerland. Men exhibited larger country differences than women (variance of 21.9 and 7.0 years, respectively). Country differences in e0 increased up to 2005 and declined thereafter. Among men, the average contribution of smoking to the country differences in e0 was highest around 1990 (47%) and declined to 35% in 2014. Among women, the average relative contribution of smoking declined from 1991 to 2011, and smoking resulted in smaller differences with the average e0 level in the majority of European countries. For both sexes combined, the contribution of smoking to country differences in e0 was higher than 20% throughout the period. Conclusions Smoking contributed substantially to the country differences in e0 in Europe, their increases up to 1991, and their decreases since 2005, especially among men. Policies that discourage smoking can help to reduce inequalities in mortality levels across Europe in the long run. Implications Smoking contributes substantially to country differences in life expectancy at birth (e0) in Europe, particularly among men, for whom the contribution was highest around 1990 (47%) and declined to 35% in 2014. In line with the anticipated progression of the smoking epidemic, the differences between European countries in e0 due to smoking are expected to further decline among men, but to increase among women. The role of smoking in mortality convergence since 2005 illustrates that smoking policies can help to reduce inequalities in life expectancy levels across Europe, particularly when they target smoking in countries with low e0.

scholarly journals Changing contribution of smoking to the sex differences in life expectancy in Europe, 1950–2014

2020 ◽  
Vol 35 (9) ◽  
pp. 835-841
Author(s):  
Fanny Janssen
Keyword(s):  
Sex Differences ◽  
Life Expectancy ◽  
Sex Difference ◽  
Western Europe ◽  
Decomposition Analysis ◽  
European Countries ◽  
Attributable Mortality ◽  
Mortality Data ◽  
Life Expectancy At Birth ◽  
Related Part

Abstract This article provides a detailed and overarching illustration of the contribution of smoking to sex differences in life expectancy at birth (e0) in Europe, focusing on changes over time and differences between both European countries and European regions. For this purpose, the sex difference in e0 for 31 European countries over the 1950–2014 period was decomposed into a smoking- and a non-smoking-related part, using all-cause mortality data and indirectly estimated smoking-attributable mortality rates by age and sex, and a formal decomposition analysis. It was found that smoking-attributable mortality contributed, on average, 3 years (43.5%) to the 7-year life expectancy difference between women and men in 2014. This contribution, was largest in 1995, at 5.2 out of 9.0 years, and subsequently declined in parallel with the average sex difference in life expectancy. The average contribution of smoking-attributable mortality was especially large in North-Western Europe around 1975; in Southern Europe around 1985; and in Eastern Europe around 1990–1995, when smoking-attributable mortality reached maximum levels among men, but was still low among women. The observed parallel decline from 1995 onwards in the sex differences in e0 and the absolute contribution of smoking to this sex difference suggests that this recent decline in the sex difference in e0 can be almost fully explained by historical changes in sex differences in smoking, and, consequently, smoking-attributable mortality. In line with the progression of the smoking epidemic, the sex differences in life expectancy in Europe are expected to further decline in the future.

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 Impact of obesity on life expectancy among different European countries: secondary analysis of population-level data over the 1975–2012 period

BMJ Open ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. e028086 ◽  
Author(s):  
Nikoletta Vidra ◽  
Sergi Trias-Llimós ◽  
Fanny Janssen
Keyword(s):  
Life Expectancy ◽  
Secondary Analysis ◽  
Population Level ◽  
European Countries ◽  
Attributable Mortality ◽  
Mortality Data ◽  
Weighted Sum Method ◽  
All Cause Mortality ◽  
The Usa ◽  
The Impact

ObjectiveThis study assesses the impact of obesity on life expectancy for 26 European national populations and the USA over the 1975–2012 period.DesignSecondary analysis of population-level obesity and mortality data.SettingEuropean countries, namely Austria, Belarus, Belgium, the Czech Republic, Denmark, Estonia, Finland, France, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, the Netherlands, Norway, Poland, Portugal, the Russian Federation, Slovakia, Spain, Sweden, Switzerland, Ukraine and the UK; and the USA.ParticipantsNational populations aged 18–100 years, by sex.MeasurementsUsing data by age and sex, we calculated obesity-attributable mortality by multiplying all-cause mortality (Human Mortality Database) with obesity-attributable mortality fractions (OAMFs). OAMFs were obtained by applying the weighted sum method to obesity prevalence data (non-communicable diseases (NCD) Risk Factor Collaboration) and European relative risks (Dynamic Modeling for Health Impact Assessment (DYNAMO- HIA)). We estimated potential gains in life expectancy (PGLE) at birth by eliminating obesity-attributable mortality from all-cause mortality using associated single-decrement life tables.ResultsIn the 26 European countries in 2012, PGLE due to obesity ranged from 0.86 to 1.67 years among men, and from 0.66 to 1.54 years among women. In all countries, PGLE increased over time, with an average annual increase of 2.68% among men and 1.33% among women. Among women in Denmark, Switzerland, and Central and Eastern European countries, the increase in PGLE levelled off after 1995. Without obesity, the average increase in life expectancy between 1975 and 2012 would have been 0.78 years higher among men and 0.30 years higher among women.ConclusionsObesity was proven to have an impact on both life expectancy levels and trends in Europe. The differences found in this impact between countries and the sexes can be linked to contextual factors, as well as to differences in people’s ability and capacity to adopt healthier lifestyles.

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 Health Status of Old Age Population in Bulgaria

2016 ◽  
Vol 2 (4) ◽  
pp. 126
Author(s):  
Mariana Mourgova
Keyword(s):  
Health Status ◽  
Life Expectancy ◽  
European Countries ◽  
Healthy Life Expectancy ◽  
Mortality Data ◽  
Healthy Life ◽  
Healthy Life Years ◽  
Demographic Indicators ◽  
Life Years ◽  
Different Levels

This article examines the health status of the population in Bulgaria at age 65 by gender during the period 2006-2014. The health status is examined by some of the most frequently used demographic indicators, namely life expectancy, based on mortality data and healthy life years and healthy life expectancy, based on mortality, life expectancy and self-perceived health. The main results show that despite of the observed increase in life expectancy at age 65 in Bulgaria during the period it is the lowest compared to other European countries. The share for both men and women reported their health status as without limitations in respect to daily activities decline, while those reported their health status as good increase. These contradictory facts reflect on the measures of health status. Thus, the trend in healthy life years for both sexes decline over the period, whereas the trend in healthy life expectancy increases. Compared with the other European countries, the expected number of years without limitations in Bulgaria is among the largest, while the healthy life expectancy is the lowest. These differences could be explained by the different levels in mortality and the nature of the measures of health status themselves.

scholarly journals Health Status of Old Age Population in Bulgaria

2016 ◽  
Vol 6 (1) ◽  
pp. 126
Author(s):  
Mariana Mourgova
Keyword(s):  
Health Status ◽  
Life Expectancy ◽  
European Countries ◽  
Healthy Life Expectancy ◽  
Mortality Data ◽  
Healthy Life ◽  
Healthy Life Years ◽  
Demographic Indicators ◽  
Life Years ◽  
Different Levels

This article examines the health status of the population in Bulgaria at age 65 by gender during the period 2006-2014. The health status is examined by some of the most frequently used demographic indicators, namely life expectancy, based on mortality data and healthy life years and healthy life expectancy, based on mortality, life expectancy and self-perceived health. The main results show that despite of the observed increase in life expectancy at age 65 in Bulgaria during the period it is the lowest compared to other European countries. The share for both men and women reported their health status as without limitations in respect to daily activities decline, while those reported their health status as good increase. These contradictory facts reflect on the measures of health status. Thus, the trend in healthy life years for both sexes decline over the period, whereas the trend in healthy life expectancy increases. Compared with the other European countries, the expected number of years without limitations in Bulgaria is among the largest, while the healthy life expectancy is the lowest. These differences could be explained by the different levels in mortality and the nature of the measures of health status themselves.

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.

scholarly journals Narrowing sex differences in life expectancy: regional variations, 1971-1991

2001 ◽  
Vol 28 (1) ◽  
pp. 89 ◽  
Author(s):  
Frank Trovato ◽  
N. M. Lalu
Keyword(s):  
Sex Differences ◽  
Life Expectancy ◽  
Gender Gap ◽  
Prince Edward Island ◽  
Causes Of Death ◽  
Average Length ◽  
Decomposition Analysis ◽  
Relative Contribution ◽  
Life Expectancy At Birth ◽  
Length Of Life

A number of industrialized nations have recently experienced some degrees of constriction in their long-standing sex differentials in life expectancy at birth. In this study we examine this phenomenon in the context of Canada’s regions between 1971 and 1991: Atlantic (Newfoundland, Nova Scotia, New Brunswick, Prince Edward Island); Quebec, Ontario, and the West (Manitoba, Saskatchewan, Alberta, British Columbia, Yukon and Northwest Territories). Decomposition analysis based on multiple decrement life tables is applied to address three questions: (1) Are there regional differentials in the degree of narrowing in the sex gap in life expectancy? (2) What is the relative contribution of major causes of death to observed sex differences in average length of life within and across regions? (3) How do the contributions of cause-of-death components vary across regions to either widen or narrow the sex gap in survival? It is shown that the magnitude of the sex gap is not uniform across the regions, though the differences are not large. The most important contributors to a narrowing of the sex gap in life expectancy are heart disease and external types of mortality (i.e., accidents, violence, and suicide), followed by lung cancer and other types of chronic conditions. In substantive terms these results indicate that over time men have been making sufficient gains in these causes of death as to narrow some of the gender gap in overall survival. Regions show similarity in these effects.

scholarly journals When The Last Tree Dies, The Last Man Dies: Do Forests Hold The Key To Survival In Ghana? A Critical Analysis Using The Bootstrapped Rolling Window Granger Causality Test Approach

2022 ◽  
Author(s):  
Michael Kaku Minlah ◽  
Xibao Zhang ◽  
Philipine Nelly Ganyoh ◽  
Ayesha Bibi
Keyword(s):  
Life Expectancy ◽  
Causal Relationship ◽  
Granger Causality ◽  
Human Life ◽  
Granger Causality Test ◽  
Causality Test ◽  
Vector Borne Diseases ◽  
Long Run ◽  
Rolling Window

Abstract This paper investigates the role of forests in the life expectancy of people in Ghana. We test whether the extinction of forests will inevitably lead to extinction of people in Ghana. We first examined the causal relationship between life expectancy and deforestation using the full sample bootstrap Granger causality test approach and find causality to run from deforestation to life expectancy with no feedback from life expectancy to deforestation. Testing for parameter stability, we found the short run and long run parameters of the estimated Vector Auto Regressive models to be unstable. A time-varying approach, the rolling window bootstrapped Granger causality test was then employed to investigate the causal relationship between life expectancy and deforestation. The results showed that deforestation has a negative effect on life expectancy, confirming the widely accepted saying that the health of forests is inextricably linked to the health of mankind. The empirical results further show that, on trend higher life expectancy increases the rate of deforestation in Ghana. Highlighting the importance of the role of forests in influencing life expectancy in Ghana, we recommend awareness creation on the role of forests in supporting human life and also extensive afforestation programs to reduce the rate of deforestation in Ghana. This, we believe, will reduce the spread of vector borne diseases such as malaria and reduce the surge in respiratory diseases which shorten the life span of Ghanaians.JEL codesQ23, Q50, Q53, Q58, Q58

Investment in Physical, Human Capital, Economic Growth and Life Expectancy in Bangladesh

2018 ◽  
Vol 19 (2) ◽  
pp. 251-269 ◽  
Author(s):  
Biswajit Maitra
Keyword(s):  
Health Care ◽  
Human Capital ◽  
Life Expectancy ◽  
Public Investment ◽  
Decisive Role ◽  
Physical Capital ◽  
Wald Test ◽  
Ardl Model ◽  
Long Run

This article studies the efficacy of the public investment in human capital and physical capital to raise income in Bangladesh over the period 1980–2016. This article also assesses whether the investment in human capital and income have raised life expectancy of the country. The Johansen cointegration test identifies a long-run relation of income with investment on education, health care and physical capital. The error correction mechanism (ECM) based on the cointegrating relation followed by the Wald test of Granger causality has found that these investments have caused income to rise with some lag periods. Robustness of these findings is confirmed by involving an autoregressive distributed lag (ARDL) model of cointegration followed by its ECM representation. On the other hand, the Johansen and ARDL methods of cointegration followed by their ECMs have also found a long-run relation of life expectancy with the investment in education, health care and income. A decisive role of the investment in health care and income on life expectancy is observed, while an unusual negative role of the investment in education is also found. However, positive value of the long-run coefficients of the education and health-care investments of the ECM-ARDL model indicate some long-run favourable impact of these investments on life expectancy in Bangladesh. JEL: I26, I15, C32

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