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 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 Influenza-attributable deaths, Canada 1990–1999

2007 ◽  
Vol 135 (7) ◽  
pp. 1109-1116 ◽  
Author(s):  
D. L. SCHANZER ◽  
T. W. S. TAM ◽  
J. M. LANGLEY ◽  
B. T. WINCHESTER
Keyword(s):  
Excess Mortality ◽  
Influenza Season ◽  
Vital Statistics ◽  
Attributable Mortality ◽  
Mortality Data ◽  
Poisson Regression Model ◽  
Severe Influenza ◽  
All Cause Mortality ◽  
Specific Mortality ◽  
The Impact

SUMMARYThe number of deaths attributable to influenza is believed to be considerably higher than the number certified by vital statistics registration as due to influenza. Weekly mortality data for Canada from the 1989/1990 to the 1998/1999 influenza seasons were analysed by cause of death, age group, and place of death to estimate the impact of influenza on mortality. A Poisson regression model was found to accurately predict all-cause, as well as cause-specific mortality, as a function of influenza-certified deaths, after controlling for seasonality, and trend. Influenza-attributable deaths were calculated as predicted less baseline-predicted deaths. In summary, throughout the 1990s there were on average just under 4000 deaths attributable to influenza annually (for an influenza-attributable mortality rate of 13/100 000 persons), varying from no detectable excess mortality for the 1990/1991 influenza season, to 6000–8000 influenza-attributable deaths for the more severe influenza seasons of 1997/1998 and 1998/1999. On average, 8% (95% CI 7–10) of influenza-attributable deaths were certified as influenza, although this percentage varied from 4% to 12% from year to year. Only 15% of the influenza-attributable deaths were certified as pneumonia, and for all respiratory causes, 40%. Deaths were distributed over most causes. The weekly pattern of influenza-certified deaths was a good predictor of excess all-cause mortality.

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 Impact of Different Estimation Methods on Obesity-Attributable Mortality Levels and Trends: The Case of The Netherlands

2018 ◽  
Vol 15 (10) ◽  
pp. 2146 ◽  
Author(s):  
Nikoletta Vidra ◽  
Maarten Bijlsma ◽  
Fanny Janssen
Keyword(s):  
The Netherlands ◽  
Estimation Methods ◽  
Attributable Mortality ◽  
Mortality Data ◽  
Weighted Sum ◽  
Weighted Sum Method ◽  
Relative Risks ◽  
Specific Mortality ◽  
Comparative Risk ◽  
The Impact

The available methodologies to estimate the obesity-attributable mortality fraction (OAMF) affect the levels found and hamper the construction of time series. Our aim was to assess the impact of using different techniques to estimate the levels and the trends in obesity-attributable mortality for The Netherlands between 1981 to 2013. Using Body Mass Index (BMI), all-cause and cause-specific mortality data, and worldwide and European relative risks (RRs), we estimated OAMFs using three all-cause approaches (partially adjusted, weighted sum, and the two combined) and one cause-of-death approach (Comparative Risk Assessment; CRA). We adjusted the CRA approach to purely capture obesity (BMI ≥ 30 kg/m2). The different approaches led to a range of estimates. The weighted sum method using worldwide RRs generated the lowest (0.9%) while the adjusted CRA approach using 2013 RRs generated the highest estimate (1.5%). Using European-specific RRs instead of worldwide RRs resulted in higher estimates. Most of the approaches revealed an increasing OAMF over the period 1981 to 2013 especially from 1993 onwards except for the adjusted CRA approach among women. Estimates of OAMF levels and trends differed depending on the method applied. Given the limited available data, we recommend using the weighted-sum method to compare obesity-attributable mortality across European countries over time.

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.

scholarly journals Social inequalities in heat-attributable mortality in the city of Turin, northwest of Italy: a time series analysis from 1982 to 2018

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Marta Ellena ◽  
Joan Ballester ◽  
Paola Mercogliano ◽  
Elisa Ferracin ◽  
Giuliana Barbato ◽  
...  
Keyword(s):  
Time Series ◽  
Marital Status ◽  
Mortality Risk ◽  
Educational Level ◽  
Social Inequalities ◽  
Attributable Mortality ◽  
Mortality Data ◽  
All Cause Mortality ◽  
Summer Temperatures ◽  
The City

Abstract Background Understanding context specific heat-health risks in urban areas is important, especially given anticipated severe increases in summer temperatures due to climate change effects. We investigate social inequalities in the association between daily temperatures and mortality in summer in the city of Turin for the period 1982–2018 among different social and demographic groups such as sex, age, educational level, marital status and household occupants. Methods Mortality data are represented by individual all-cause mortality counts for the summer months between 1982 and 2018. Socioeconomic level and daily mean temperature were assigned to each deceased. A time series Poisson regression with distributed lag non-linear models was fitted to capture the complex nonlinear dependency between daily mortality and temperature in summer. The mortality risk due to heat is represented by the Relative Risk (RR) at the 99th percentile of daily summer temperatures for each population subgroup. Results All-cause mortality risk is higher among women (1.88; 95% CI = 1.77, 2.00) and the elderly (2.13; 95% CI = 1.94, 2.33). With regard to education, the highest significant effects for men is observed among higher education levels (1.66; 95% CI = 1.38, 1.99), while risks for women is higher for the lower educational level (1.93; 95% CI = 1.79, 2.08). Results on marital status highlighted a stronger association for widower in men (1.66; 95% CI = 1.38, 2.00) and for separated and divorced in women (2.11; 95% CI = 1.51, 2.94). The risk ratio of household occupants reveals a stronger association for men who lived alone (1.61; 95% CI = 1.39, 1.86), while for women results are almost equivalent between alone and not alone groups. Conclusions The associations between heat and mortality is unequal across different aspects of social vulnerability, and, inter alia, factors influencing the population vulnerability to temperatures can be related to demographic, social, and economic aspects. A number of issues are identified and recommendations for the prioritisation of further research are provided. A better knowledge of these effect modifiers is needed to identify the axes of social inequality across the most vulnerable population sub-groups.

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