Data on death rates for suicide, by selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for critical information about measures, definitions, and changes over time.

SOURCE: NCHS, National Vital Statistics System (NVSS); Grove RD, Hetzel AM. Vital statistics rates in the United States, 1940–1960. National Center for Health Statistics. 1968; numerator data from NVSS annual public-use Mortality Files; denominator data from U.S. Census Bureau national population estimates; and Murphy SL, Xu JQ, Kochanek KD, Arias E, Tejada-Vera B. Deaths: Final data for 2018. National Vital Statistics Reports; vol 69 no 13. Hyattsville, MD: National Center for Health Statistics. 2021. Available from: https://www.cdc.gov/nchs/products/nvsr.htm. For more information on the National Vital Statistics System, see the corresponding Appendix entry at https://www.cdc.gov/nchs/data/hus/hus19-appendix-508.pdf.

BackgroundIn Europe, men have lower rates of attempted suicide compared to women and at the same time a higher rate of completed suicides, indicating major gender differences in lethality of suicidal behaviour. The aim of this study was to analyse the extent to which these gender differences in lethality can be explained by factors such as choice of more lethal methods or lethality differences within the same suicide method or age. In addition, we explored gender differences in the intentionality of suicide attempts.Methods and FindingsMethods. Design: Epidemiological study using a combination of self-report and official data. Setting: Mental health care services in four European countries: Germany, Hungary, Ireland, and Portugal. Data basis: Completed suicides derived from official statistics for each country (767 acts, 74.4% male) and assessed suicide attempts excluding habitual intentional self-harm (8,175 acts, 43.2% male).Main Outcome Measures and Data Analysis. We collected data on suicidal acts in eight regions of four European countries participating in the EU-funded “OSPI-Europe”-project (www.ospi-europe.com). We calculated method-specific lethality using the number of completed suicides per method * 100 / (number of completed suicides per method + number of attempted suicides per method). We tested gender differences in the distribution of suicidal acts for significance by using the χ2-test for two-by-two tables. We assessed the effect sizes with phi coefficients (φ). We identified predictors of lethality with a binary logistic regression analysis. Poisson regression analysis examined the contribution of choice of methods and method-specific lethality to gender differences in the lethality of suicidal acts.Findings Main ResultsSuicidal acts (fatal and non-fatal) were 3.4 times more lethal in men than in women (lethality 13.91% (regarding 4106 suicidal acts) versus 4.05% (regarding 4836 suicidal acts)), the difference being significant for the methods hanging, jumping, moving objects, sharp objects and poisoning by substances other than drugs. Median age at time of suicidal behaviour (35–44 years) did not differ between males and females. The overall gender difference in lethality of suicidal behaviour was explained by males choosing more lethal suicide methods (odds ratio (OR) = 2.03; 95% CI = 1.65 to 2.50; p < 0.000001) and additionally, but to a lesser degree, by a higher lethality of suicidal acts for males even within the same method (OR = 1.64; 95% CI = 1.32 to 2.02; p = 0.000005). Results of a regression analysis revealed neither age nor country differences were significant predictors for gender differences in the lethality of suicidal acts. The proportion of serious suicide attempts among all non-fatal suicidal acts with known intentionality (NFSAi) was significantly higher in men (57.1%; 1,207 of 2,115 NFSAi) than in women (48.6%; 1,508 of 3,100 NFSAi) (χ2 = 35.74; p < 0.000001).Main limitations of the studyDue to restrictive data security regulations to ensure anonymity in Ireland, specific ages could not be provided because of the relatively low absolute numbers of suicide in the Irish intervention and control region. Therefore, analyses of the interaction between gender and age could only be conducted for three of the four countries. Attempted suicides were assessed for patients presenting to emergency departments or treated in hospitals. An unknown rate of attempted suicides remained undetected. This may have caused an overestimation of the lethality of certain methods. Moreover, the detection of attempted suicides and the registration of completed suicides might have differed across the four countries. Some suicides might be hidden and misclassified as undetermined deaths.ConclusionsMen more often used highly lethal methods in suicidal behaviour, but there was also a higher method-specific lethality which together explained the large gender differences in the lethality of suicidal acts. Gender differences in the lethality of suicidal acts were fairly consistent across all four European countries examined. Males and females did not differ in age at time of suicidal behaviour. Suicide attempts by males were rated as being more serious independent of the method used, with the exceptions of attempted hanging, suggesting gender differences in intentionality associated with suicidal behaviour. These findings contribute to understanding of the spectrum of reasons for gender differences in the lethality of suicidal behaviour and should inform the development of gender specific strategies for suicide prevention.

Number of suicides and suicide rates, by sex and age, in England and Wales. Information on conclusion type is provided, along with the proportion of suicides by method and the median registration delay.

India IN: Suicide Mortality Rate: Male data was reported at 17.800 NA in 2016. This records a decrease from the previous number of 18.000 NA for 2015. India IN: Suicide Mortality Rate: Male data is updated yearly, averaging 18.000 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 18.600 NA in 2000 and a record low of 17.700 NA in 2010. India IN: Suicide Mortality Rate: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Health Statistics. Suicide mortality rate is the number of suicide deaths in a year per 100,000 population. Crude suicide rate (not age-adjusted).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

In 2022, the rate of suicides among males was 16.4 per 100,000 population and among females it was 5.4 per 100,000. The rate of suicide has slightly decreased for both genders since the beginning of given time period of the statistic, although recent years has seen an increase again for both men and women. However, the rate of suicide for men has remained significantly higher than for women. Individuals seeking help for mental health issuesIn Great Britain, almost 70 percent have never visited a mental health professional, while eighteen percent consult with one at least once a year. Additionally, almost 60 percent of those with a psychiatric condition do not take any medication to control their condition. Mental health of young peopleThe COVID-19 pandemic had a huge impact of the mental health of many people, particularly young people. The share of all adults reporting to having experienced symptoms of depression doubled during the pandemic compared to before. Although for those in the age group 16 to 39 years, depression prevalence tripled. Among young people that had mental health concerns prior to the pandemic, a significant majority of those surveyed reported that their life had become worse due to the impact of the pandemic and subsequent restrictions.

This data shows deaths (of people age 10 and over) from Suicide and Undetermined Injury, numbers and rates by gender, as 3-year moving-averages.

Suicide is a significant cause of premature deaths occurring generally at younger ages than other common causes of premature mortality. It may also be seen as an indicator of underlying rates of mental ill-health.

Directly Age-Standardised Rates (DASR) are shown in the data, where numbers are sufficient, so that death rates can be directly compared between areas. The DASR calculation applies Age-specific rates to a Standard (European) population to cancel out possible effects on crude rates due to different age structures among populations, thus enabling direct comparisons of rates.

The figures in this dataset include deaths recorded as suicide (people age 10 and over) and undetermined injury (age 15 and over) as those are mostly likely also to have been caused by self-harm. The population denominators for rates are age 10 and over.

Data source: Public Health England, Public Health Outcomes Framework (PHOF) indicator 4.10. This data is updated annually.

Rate of deaths by age/gender (per 100,000 population) for people killed in crashes involving a driver with BAC =>0.08%, 2012. 2012 Source: Fatality Analysis Reporting System (FARS)Note: Blank cells indicate data are suppressed. 2014 Source: Source: National Highway Traffic Administration's (NHTSA) Fatality Analysis Reporting System (FARS), 2014 Annual Report File. Fatality rates based on fewer than 20 deaths are suppressed.

This dataset contains counts of deaths for California as a whole based on information entered on death certificates. Final counts are derived from static data and include out-of-state deaths to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all deaths that occurred during the time period. Deaths involving injuries from external or environmental forces, such as accidents, homicide and suicide, often require additional investigation that tends to delay certification of the cause and manner of death. This can result in significant under-reporting of these deaths in provisional data.

The final data tables include both deaths that occurred in California regardless of the place of residence (by occurrence) and deaths to California residents (by residence), whereas the provisional data table only includes deaths that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by age, gender, race-ethnicity, and death place type. Deaths due to all causes (ALL) and selected underlying cause of death categories are provided. See temporal coverage for more information on which combinations are available for which years.

The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.

Rate of deaths by age/gender (per 100,000 population) for people killed in crashes involving a driver with BAC =>0.08%, 2012, 2014. 2012 Source: Fatality Analysis Reporting System (FARS). 2014 Source: National Highway Traffic Administration's (NHTSA) Fatality Analysis Reporting System (FARS), 2014 Annual Report File. Note: Blank cells indicate data are suppressed. Fatality rates based on fewer than 20 deaths are suppressed.

Rate of deaths by age/gender (per 100,000 population) for people killed in crashes involving a driver with BAC =>0.08%, 2012, 2014. 2012 Source: Fatality Analysis Reporting System (FARS). 2014 Source: National Highway Traffic Administration's (NHTSA) Fatality Analysis Reporting System (FARS), 2014 Annual Report File. Note: Blank cells indicate data are suppressed. Fatality rates based on fewer than 20 deaths are suppressed.

Number of deaths occurring in the province of Alberta, by year, gender, age, and cause of death.

The dataset contains year- and gender-wise data on number of suicides which have happened in India, categorized by annual income level of suicide victims such as Less than 1 Lakh Rupees, More than 1 Lakh and Less than 5 Lakh Rupees, More than 5 Lakhs and Less than 10 Lakh Rupees, and 10 Lakhs and above

As of 2023, around 18 percent of U.S. transgender and nonbinary youth who did not have gender-affirming spaces in schools reported attempting suicide in the past year, compared to 14 percent of youth who had gender-affirming spaces in schools. The statistic illustrates the share of U.S. transgender and nonbinary youth who attempted suicide in the past year as of 2023, by gender-affirming spaces.

This dataset shows the Canadian Armed Forces (CAF) rate for suicide per 100,000 for Regular Force males. As the number of events was less than 20 in most years, rates were not calculated annually as these would not have been statistically reliable. Regular Force female rates were not calculated because female suicides were uncommon. This dataset is taken from the yearly Report on Suicide Mortality in the Canadian Armed Forces released on the Canada.ca platform at the homepage link provided down below.

English:

The data set contains 503 variables and 624 observations on suicides and suicide rates as well as on demographic, socio-structural, infrastructure and crime statistics on the canton and national level for the years 1952 to 1990. The information was recorded and processed by GDR’s Central Bureau of Statistics on a yearly basis. The statistical yearbooks of the GDR and various files of the Federal Archive were used as the sources of this data.

The demographic statistics include the population distribution by gender and age-groups, the incidence of deaths, homicides, births, stillbirths, as well as infant mortality and domestic migration rates by year and administrative district. The socio-structural information includes marriage and divorce rates, population distribution by education, employment and religious denomination, as well as the number of members and candidates of the Socialist Unity Party of Germany by year and district. The infrastructure data contains information on population density, residential housing construction and retail sales by year and administrative canton. The annual numbers of offenders of criminally liable age and convicted persons in the districts that come from the GDR crime statistics were included in the data set from the GDR crime statistics.

Missing values indicate that no information could be found for the given year or region. However, the missing information on the distribution by gender and age-groups, as well as suicide rates by age-group can be estimated using the attached do-files. A detailed description of how the missing values have been determined can be found in the document “Imputation und Standardisierung.pdf”. The do-files and the description are available in a zip file below.

Deutsch:

Dieser Datensatz umfasst 503 Variablen und 624 Beobachtungen. Er beinhaltet Informationen zu Suizidzahlen sowie demographische, sozialstrukturelle, infrastrukturelle Statistiken und Kriminalstatistiken in den Bezirken der DDR sowie des gesamten Landes von 1952 bis 1990. In der DDR war die Staatliche Zentralverwaltung für Statistik (SZS) für die Sammlung und Aufbereitung der verschiedenen Jahresstatistiken zuständig, weshalb die langen Zeitreihen größtenteils aus dem Primärbestand der SZS ermittelt und anschließend vergleichbar über die Bezirke und den Zeitverlauf berechnet wurden. Als Recherchequellen dienen die statistischen Jahrbücher der DDR sowie verschiedene Akten des Bundesarchivs.

Die demographischen Statistiken umfassen die jährlichen bezirksspezifischen Verteilungen der Geschlechter, Altersgruppen, Verstorbenen, Ermordeten, Lebendgeborenen, Totgeborenen, gestorbenen Säuglinge und Binnenmigration. Die sozialstrukturellen Informationen umfassen Angaben zu regionalen Verteilungen der Eheschließung, Ehescheidung, Bildung, Beschäftigung und Konfession sowie Statistiken über die Mitgliedschaft und Kandidatur für eine Mitgliedschaft bei der SED. Die verschiedenen infrastrukturellen Daten umfassen jährliche Statistiken der Bevölkerungsdichte, des Wohnungsbaus und des Einzelhandelsumsatzes in den Bezirken der DDR. Zudem wurden aus der Kriminalstatistik der DDR die jährliche Anzahl der strafmündigen Täter und der Verurteilten in den Bezirken in den Datensatz aufgenommen.

Missings werden in dem Datensatz ausgewiesen, wenn für bestimmte Jahre oder Regionen keine Zahlen recherchiert werden konnten bzw. die Informationen nicht erhoben wurden. Fehlende Suizidzahlen und fehlende Bevölkerungszahlen in bestimmten Altersgruppen können mittels der beigefügten Do-Files geschätzt und importiert werden. Eine ausführliche Beschreibung der Bestimmung der fehlenden Zahlen lassen sich dem Dokument „Imputation und Standardisierung.pdf“ entnehmen. Zudem ist ein unverzerrter Vergleich der Suizidraten über Regionen und Zeit nur anhand von standardisierten Suizidraten möglich. Auch dieses Vorgehen der indirekten Standardisierung ist im genannten Dokument beschrieben und kann anhand der Do-Files repliziert werden. Sie sind unten in einer Zip-Datei verfügbar.

Content

The United States Census Bureau’s International Dataset provides estimates of country populations since 1950 and projections through 2050. Specifically, the data set includes midyear population figures broken down by age and gender assignment at birth. Additionally, they provide time-series data for attributes including fertility rates, birth rates, death rates, and migration rates.

The full documentation is available here. For basic field details, please see the data dictionary.

Note: The U.S. Census Bureau provides estimates and projections for countries and areas that are recognized by the U.S. Department of State that have a population of at least 5,000.

Acknowledgements

This dataset was created by the United States Census Bureau.

Inspiration

Which countries have made the largest improvements in life expectancy? Based on current trends, how long will it take each country to catch up to today’s best performers?

Use this dataset with BigQuery

You can use Kernels to analyze, share, and discuss this data on Kaggle, but if you’re looking for real-time updates and bigger data, check out the data on BigQuery, too: https://cloud.google.com/bigquery/public-data/international-census.

This dataset contains counts of deaths for California counties based on information entered on death certificates. Final counts are derived from static data and include out-of-state deaths to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all deaths that occurred during the time period. Deaths involving injuries from external or environmental forces, such as accidents, homicide and suicide, often require additional investigation that tends to delay certification of the cause and manner of death. This can result in significant under-reporting of these deaths in provisional data.

The final data tables include both deaths that occurred in each California county regardless of the place of residence (by occurrence) and deaths to residents of each California county (by residence), whereas the provisional data table only includes deaths that occurred in each county regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by age, gender, race-ethnicity, and death place type. Deaths due to all causes (ALL) and selected underlying cause of death categories are provided. See temporal coverage for more information on which combinations are available for which years.

The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.

A database based on a random sample of the noninstitutionalized population of the United States, developed for the purpose of studying the effects of demographic and socio-economic characteristics on differentials in mortality rates. It consists of data from 26 U.S. Current Population Surveys (CPS) cohorts, annual Social and Economic Supplements, and the 1980 Census cohort, combined with death certificate information to identify mortality status and cause of death covering the time interval, 1979 to 1998. The Current Population Surveys are March Supplements selected from the time period from March 1973 to March 1998. The NLMS routinely links geographical and demographic information from Census Bureau surveys and censuses to the NLMS database, and other available sources upon request. The Census Bureau and CMS have approved the linkage protocol and data acquisition is currently underway. The plan for the NLMS is to link information on mortality to the NLMS every two years from 1998 through 2006 with research on the resulting database to continue, at least, through 2009. The NLMS will continue to incorporate data from the yearly Annual Social and Economic Supplement into the study as the data become available. Based on the expected size of the Annual Social and Economic Supplements to be conducted, the expected number of deaths to be added to the NLMS through the updating process will increase the mortality content of the study to nearly 500,000 cases out of a total number of approximately 3.3 million records. This effort would also include expanding the NLMS population base by incorporating new March Supplement Current Population Survey data into the study as they become available. Linkages to the SEER and CMS datasets are also available. Data Availability: Due to the confidential nature of the data used in the NLMS, the public use dataset consists of a reduced number of CPS cohorts with a fixed follow-up period of five years. NIA does not make the data available directly. Research access to the entire NLMS database can be obtained through the NIA program contact listed. Interested investigators should email the NIA contact and send in a one page prospectus of the proposed project. NIA will approve projects based on their relevance to NIA/BSR''s areas of emphasis. Approved projects are then assigned to NLMS statisticians at the Census Bureau who work directly with the researcher to interface with the database. A modified version of the public use data files is available also through the Census restricted Data Centers. However, since the database is quite complex, many investigators have found that the most efficient way to access it is through the Census programmers. * Dates of Study: 1973-2009 * Study Features: Longitudinal * Sample Size: ~3.3 Million Link: *ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00134

Note: Starting April 27, 2023 updates change from daily to weekly. Summary The cumulative number of confirmed COVID-19 deaths among Maryland residents by gender: Female; Male; Unknown. Description The MD COVID-19 - Confirmed Deaths by Gender Distribution data layer is a collection of the statewide confirmed and probable COVID-19 related deaths that have been reported each day by the Vital Statistics Administration by gender. A death is classified as confirmed if the person had a laboratory-confirmed positive COVID-19 test result. Some data on deaths may be unavailable due to the time lag between the death, typically reported by a hospital or other facility, and the submission of the complete death certificate. Probable deaths are available from the MD COVID-19 - Probable Deaths by Gender Distribution data layer. Terms of Use The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

Rate of deaths by age/gender (per 100,000 population) for people killed in crashes involving a driver with BAC =>0.08%, 2012, 2014. 2012 Source: Fatality Analysis Reporting System (FARS). 2014 Source: National Highway Traffic Administration's (NHTSA) Fatality Analysis Reporting System (FARS), 2014 Annual Report File. Note: Blank cells indicate data are suppressed. Fatality rates based on fewer than 20 deaths are suppressed.