This statistic displays the share of deaths by cause in Europe. The year varies between countries, ranging from 2000 to 2015. During this period ischaemic heart disease was one of the the leading causes of death among men and women in Europe, with ** percent of men and ** percent of women dying as a result of the disease. Stroke and cardiovascular disease were also leading causes of death among individuals in Europe.

In 2013, the main causes of death in France was cancer. That year 163,602 French individuals died of cancer, regardless of gender. Diseases appear to be the leading causes of death in Europe and Western countries. Ischaemic heart diseases, as well as other circulatory system diseases kill millions of Europeans every year.

Diseases are the leading causes of death in France and worldwide

In 2018, there were more than 601,000 deaths in France. Most of them were caused by cancer and other diseases. Tumor is the leading cause of death among French men, while women seem more affected by heart diseases. In Europe in 2016, the cause of death with the greatest likelihood of death was cancer, which occurred in 265 people out of every 100,000 Europeans. Despite the development of medicine and technological progress, health issues like cancers keep being the main causes of death among the human population.

The increase of life expectancy

Even though tumors and other heart diseases are responsible for the majority of deaths in the world, it appears that medical advances in the last years and decades have a real impact on mortality rate worldwide. Between 2007 and 2017 alone, the global death rate went from 8.08 deaths per 1,000 inhabitants to 7.62. Similarly, the global child mortality rate has fallen steadily across the world since the sixties. These different factors had led to an increase of life expectancy. In 2016, the average life expectancy at birth worldwide reached 72 years, compared to 64 years in 1990.

Leading causes of death by age group and sex

Source agency: Office for National Statistics

Designation: Official Statistics not designated as National Statistics

Language: English

Alternative title: Mortality

The indicator measures the standardised death rate of homicide and injuries inflicted by another person with the intent to injure or kill by any means, including ‘late effects’ from assault (International Classification of Diseases (ICD) codes X85 to Y09 and Y87.1). It does not include deaths due to legal interventions or war (ICD codes Y35 and Y36). Data on causes of death (COD) refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. The data are presented as standardised death rates, meaning they are adjusted to a standard age distribution in order to measure death rates independently of different age structures of populations. This approach improves comparability over time and between countries. The standardised death rates used here are calculated on the basis of the standard European population referring to the residents of the countries.

The mortality rate has been stable in France since the middle of 1980s. The mortality rate varies between *** and ***** deaths per 1,000 inhabitants. Life expectancy of women in France amounted to more than 85 years in 2023, making the country one of the areas in Europe where women live the longest. A slowly increasing death rate From 2014 to 2020, the death rate in France generally remained stable, oscillating mostly between *** and *** deaths per 1,000 population. Death rate, also known as mortality rate, is the ratio between the annual number of deaths and the average total population over a given period and on a specific territory. In 2023, the population in France reached ***** million people, while in 2022, the total number of deaths in France was *******. The mortality rate in France increased slowly in recent years. In 2007, the death rate amounted to *** per thousand population, compared to *** deaths ten years later. Causes of death In 2013, the leading cause of death among French citizens was cancer. That year, ******* people died of tumors, while diseases of the circulatory system were the second most common cause of death in the country. Mortality rate because of cancer was particularly high among French males, whereas females appear to be more affected by cardiovascular disease. Studies have shown that cancer was not only the leading cause of death in France, but also in Europe. More broadly, health and diseases were among the major causes of death in European countries, even if traffic accidents killed more than ***** individuals in France in 2021.

The primary source of the data relating to the causes of death is represented by the "death card" prepared by the National Statistical Institute (Istat) which must be filled in by the attending physician or by the physician who assisted the deceased patient. This form, according to the 1990 Mortuary Police (Rpm) regulation (Presidential Decree 285/90), is in duplicate and must be sent by the Municipality of death to Istat and to the Local Health Unit of death.

The dataset, updated to the month of June 2015, contains the complete list of the deceased by sex, citizenship, age and major causes of death of those registered in the Register of the municipality of Matera and deceased in the same municipality. Also included are deaths occurring in other municipalities or abroad (transcribed acts) for which, not having documentation relating to the causes of death, they have been classified as: "OTHER UNKNOWN CAUSES ARISING FROM TRANSCRIPTED ACTS".

The table shows the standardised death rate by major causes of death worldwide, 2018 [per 100 000 inhabitants]*

This table contains figures on deaths by major primary causes of death, age (at the time of death) and gender by region in the period 1996-2005. The numbers are randomly rounded to multiples of five. The regions are composed of the municipalities. Deceased persons are shown according to the municipality of registration. Data is available for the following regions: municipality, part of the country, province, COROP area, urban region and metropolitan agglomeration. Data available 1996-2005. Status of the figures: These are final figures. Changes as of: November 5, 2009 This table has been renamed and has been discontinued. The table is followed by the new table Causes of death; short list, region. February 22, 2008 The GGD regions have been removed from the table. The figures are also no longer broken down by age group. The application of random rounding appears to lead to confusion, especially in this breakdown. When will new figures come out? This table has been discontinued.

The indicator measures the standardised death rate of chronic diseases. Chronic diseases included in the indicator are malignant neoplasms, diabetes mellitus, ischaemic heart diseases, cerebrovascular diseases, chronic lower respiratory diseases and chronic liver diseases (International Classification of Diseases (ICD) codes C00 to C97, E10 to E14, I20 to I25, I60 to I69 and J40 to J47). Death due to chronic diseases is considered premature if it occurs before the age of 65. The rate is calculated by dividing the number of people under 65 dying due to a chronic disease by the total population under 65. Data on causes of death (COD) refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. The data are presented as standardised death rates, meaning they are adjusted to a standard age distribution in order to measure death rates independently of different age structures of populations. This approach improves comparability over time and between countries. The standardised death rates used here are calculated on the basis of the standard European population referring to the residents of the countries.

This table contains death figures by major underlying causes of death (Beldo list), age and gender by region. Deceased persons are shown according to the municipality of registration. Data is available for the following regions: part of the country, province, COROP area and large municipalities. In the 2013 statistical year, Statistics Netherlands switched to using international software for the automatic coding of causes of death. This makes the figures more reproducible and internationally comparable. There are, however, once-off some significant shifts in the causes of death. Data available from: 1996 Status of the figures The figures up to and including 2021 are final, the figures for 2022 are provisional. Changes as of 28 June 2023: The provisional figures for 2022 have been added. When will new numbers come out? The aim is to publish the final figures for 2022 in the fourth quarter of 2023.

This table contains figures of deceased residents of the Netherlands by major underlying causes of death (Beldo list), age (at the time of death) and gender. In the 2013 statistical year, Statistics Netherlands switched to using international software for the automatic coding of causes of death. This makes the figures more reproducible and internationally comparable. There are, however, once-off some significant shifts in the causes of death. Data available from: 1950 Status of the figures The figures up to and including 2021 are final, the figures for 2022 are provisional. Changes as of 28 June 2023: The provisional figures for 2022 have been added. When will new numbers come out? The aim is to publish the final figures for 2022 in the fourth quarter of 2023.

BackgroundEven in low and middle income countries most deaths occur in older adults. In Europe, the effects of better education and home ownership upon mortality seem to persist into old age, but these effects may not generalise to LMICs. Reliable data on causes and determinants of mortality are lacking. Methods and FindingsThe vital status of 12,373 people aged 65 y and over was determined 3–5 y after baseline survey in sites in Latin America, India, and China. We report crude and standardised mortality rates, standardized mortality ratios comparing mortality experience with that in the United States, and estimated associations with socioeconomic factors using Cox's proportional hazards regression. Cause-specific mortality fractions were estimated using the InterVA algorithm. Crude mortality rates varied from 27.3 to 70.0 per 1,000 person-years, a 3-fold variation persisting after standardisation for demographic and economic factors. Compared with the US, mortality was much higher in urban India and rural China, much lower in Peru, Venezuela, and urban Mexico, and similar in other sites. Mortality rates were higher among men, and increased with age. Adjusting for these effects, it was found that education, occupational attainment, assets, and pension receipt were all inversely associated with mortality, and food insecurity positively associated. Mutually adjusted, only education remained protective (pooled hazard ratio 0.93, 95% CI 0.89–0.98). Most deaths occurred at home, but, except in India, most individuals received medical attention during their final illness. Chronic diseases were the main causes of death, together with tuberculosis and liver disease, with stroke the leading cause in nearly all sites. ConclusionsEducation seems to have an important latent effect on mortality into late life. However, compositional differences in socioeconomic position do not explain differences in mortality between sites. Social protection for older people, and the effectiveness of health systems in preventing and treating chronic disease, may be as important as economic and human development. Please see later in the article for the Editors' Summary

BackgroundDecades of steady improvements in life expectancy in Europe slowed down from around 2011, well before the COVID-19 pandemic, for reasons which remain disputed. We aimed to assess how changes in risk factors and cause-specific death rates in different European countries related to changes in life expectancy in those countries before and during the COVID-19 pandemic.MethodsWe used data and methods from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 to compare changes in life expectancy at birth, causes of death, and population exposure to risk factors in 16 European Economic Area countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, and Sweden) and the four UK nations (England, Northern Ireland, Scotland, and Wales) for three time periods: 1990–2011, 2011–19, and 2019–21. Changes in life expectancy and causes of death were estimated with an established life expectancy cause-specific decomposition method, and compared with summary exposure values of risk factors for the major causes of death influencing life expectancy.FindingsAll countries showed mean annual improvements in life expectancy in both 1990–2011 (overall mean 0·23 years [95% uncertainty interval [UI] 0·23 to 0·24]) and 2011–19 (overall mean 0·15 years [0·13 to 0·16]). The rate of improvement was lower in 2011–19 than in 1990–2011 in all countries except for Norway, where the mean annual increase in life expectancy rose from 0·21 years (95% UI 0·20 to 0·22) in 1990–2011 to 0·23 years (0·21 to 0·26) in 2011–19 (difference of 0·03 years). In other countries, the difference in mean annual improvement between these periods ranged from –0·01 years in Iceland (0·19 years [95% UI 0·16 to 0·21] vs 0·18 years [0·09 to 0·26]), to –0·18 years in England (0·25 years [0·24 to 0·25] vs 0·07 years [0·06 to 0·08]). In 2019–21, there was an overall decrease in mean annual life expectancy across all countries (overall mean –0·18 years [95% UI –0·22 to –0·13]), with all countries having an absolute fall in life expectancy except for Ireland, Iceland, Sweden, Norway, and Denmark, which showed marginal improvement in life expectancy, and Belgium, which showed no change in life expectancy. Across countries, the causes of death responsible for the largest improvements in life expectancy from 1990 to 2011 were cardiovascular diseases and neoplasms. Deaths from cardiovascular diseases were the primary driver of reductions in life expectancy improvements during 2011–19, and deaths from respiratory infections and other COVID-19 pandemic-related outcomes were responsible for the decreases in life expectancy during 2019–21. Deaths from cardiovascular diseases and neoplasms in 2019 were attributable to high systolic blood pressure, dietary risks, tobacco smoke, high LDL cholesterol, high BMI, occupational risks, high alcohol use, and other risks including low physical activity. Exposure to these major risk factors differed by country, with trends of increasing exposure to high BMI and decreasing exposure to tobacco smoke observed in all countries during 1990–2021.InterpretationThe countries that best maintained improvements in life expectancy after 2011 (Norway, Iceland, Belgium, Denmark, and Sweden) did so through better maintenance of reductions in mortality from cardiovascular diseases and neoplasms, underpinned by decreased exposures to major risks, possibly mitigated by government policies. The continued improvements in life expectancy in five countries during 2019–21 indicate that these countries were better prepared to withstand the COVID-19 pandemic. By contrast, countries with the greatest slowdown in life expectancy improvements after 2011 went on to have some of the largest decreases in life expectancy in 2019–21. These findings suggest that government policies that improve population health also build resilience to future shocks. Such policies include reducing population exposure to major upstream risks for cardiovascular diseases and neoplasms, such as harmful diets and low physical activity, tackling the commercial determinants of poor health, and ensuring access to affordable health services.

The indicator measures the standardised death rate of tuberculosis, HIV and hepatitis (International Classification of Diseases (ICD) codes A15-A19_B90, B15-B19_B942 and B20-B24). The rate is calculated by dividing the number of people dying due to selected communicable diseases by the total population. Data on causes of death (COD) refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. The data are presented as standardised death rates, meaning they are adjusted to a standard age distribution in order to measure death rates independently of different age structures of populations. This approach improves comparability over time and between countries. The standardised death rates used here are calculated on the basis of the standard European population referring to the residents of the countries. Copyright notice and free re-use of data on: https://ec.europa.eu/eurostat/about-us/policies/copyright

Provision of 21 documents (21 XLS files) for the period from 31.12.2001 to 31.12.2013 with the spatial reference Berlin.

This table contains the total number of deaths by age and gender for municipalities, municipal health services and the Netherlands over the period 1996-2020 (absolute and per 10,000 inhabitants). At the GGD and national level, in addition to the total number of deaths, a distinction is also made according to a number of main groups of causes of death. The regional classification of 2020 has been used for all years. The figures in this table come from the Cause of Death Statistics of Statistics Netherlands (CBS). Data available from: 1996 Status of the figures: The figures in this table are final. Changes as of 23-06-2022: None, this is a new table. When will new numbers come out? New figures are released every two years. These are published in separate tables.

This table shows the number of deaths by age and gender for municipalities, GGDs and the Netherlands total over the period 1996-2020 (absolutely and per 10,000 inhabitants). At the GGD and national level, in addition to the total number of deaths, a number of main causes of death have also been distinguished. For all years, the regional classification of 2020 has been used. The figures in this table are derived from the Death Causes Statistics of the Central Statistical Office (CBS).

Data available from: 1996

Status of the figures: The figures in this table are final.

Changes from 23-06-2022: None, this is a new table.

When are new figures coming? New figures are released every two years. These are published in separate tables.

BackgroundWhile the high prevalence of preterm births and its impact on infant mortality in the US have been widely acknowledged, recent data suggest that even full-term births in the US face substantially higher mortality risks compared to European countries with low infant mortality rates. In this paper, we use the most recent birth records in the US to more closely analyze the primary causes underlying mortality rates among full-term births.Methods and findingsLinked birth and death records for the period 2010–2012 were used to identify the state- and cause-specific burden of infant mortality among full-term infants (born at 37–42 weeks of gestation). Multivariable logistic models were used to assess the extent to which state-level differences in full-term infant mortality (FTIM) were attributable to observed differences in maternal and birth characteristics. Random effects models were used to assess the relative contribution of state-level variation to FTIM. Hypothetical mortality outcomes were computed under the assumption that all states could achieve the survival rates of the best-performing states. A total of 10,175,481 infants born full-term in the US between January 1, 2010, and December 31, 2012, were analyzed. FTIM rate (FTIMR) was 2.2 per 1,000 live births overall, and ranged between 1.29 (Connecticut, 95% CI 1.08, 1.53) and 3.77 (Mississippi, 95% CI 3.39, 4.19) at the state level. Zero states reached the rates reported in the 6 low-mortality European countries analyzed (FTIMR < 1.25), and 13 states had FTIMR > 2.75. Sudden unexpected death in infancy (SUDI) accounted for 43% of FTIM; congenital malformations and perinatal conditions accounted for 31% and 11.3% of FTIM, respectively. The largest mortality differentials between states with good and states with poor FTIMR were found for SUDI, with particularly large risk differentials for deaths due to sudden infant death syndrome (SIDS) (odds ratio [OR] 2.52, 95% CI 1.86, 3.42) and suffocation (OR 4.40, 95% CI 3.71, 5.21). Even though these mortality differences were partially explained by state-level differences in maternal education, race, and maternal health, substantial state-level variation in infant mortality remained in fully adjusted models (SIDS OR 1.45, suffocation OR 2.92). The extent to which these state differentials are due to differential antenatal care standards as well as differential access to health services could not be determined due to data limitations. Overall, our estimates suggest that infant mortality could be reduced by 4,003 deaths (95% CI 2,284, 5,587) annually if all states were to achieve the mortality levels of the best-performing state in each cause-of-death category. Key limitations of the analysis are that information on termination rates at the state level was not available, and that causes of deaths may have been coded differentially across states.ConclusionsMore than 7,000 full-term infants die in the US each year. The results presented in this paper suggest that a substantial share of these deaths may be preventable. Potential improvements seem particularly large for SUDI, where very low rates have been achieved in a few states while average mortality rates remain high in most other areas. Given the high mortality burden due to SIDS and suffocation, policy efforts to promote compliance with recommended sleeping arrangements could be an effective first step in this direction.

This table contains figures on the deceased by major primary causes of death, age (at the time of death) and gender per region in the period 1996-2005. The numbers are based on chance (select) rounded to multiples of five. The regions shall be composed from the municipalities. The deceased will be shown to the municipality of registration. Of the the following regions are available: municipality, part of the country, province, COROP area, city-west and metropolitan agglomeration.

Data available 1996-2005.

Status of the figures: These are definitive figures.

Changes by: 5 November 2009 This table has been renamed and discontinued. The table becomes followed by the new table <a href=“https://statline.cbs.nl/StatWeb/selection/?DM=SLNL&PA=80202NED”

Causes of death; short list, region.

22 February 2008 The GGD regions have been removed from the table. Also, the figures are no longer broken down by age classes. The application of a random completion appears to lead, in particular, to confusion in this division.

When are new figures coming? This table has been discontinued.