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.

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;

This dataset contains suicide death counts by region, race or ethnicity, sex, and age group. For more information, check out: http://www.health.ny.gov/statistics/vital_statistics/.

Age-adjustment mortality rates are rates of deaths that are computed using a statistical method to create a metric based on the true death rate so that it can be compared over time for a single population (i.e. comparing 2006-2008 to 2010-2012), as well as enable comparisons across different populations with possibly different age distributions in their populations (i.e. comparing Hispanic residents to Asian residents).
Age adjustment methods applied to Montgomery County rates are consistent with US Centers for Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS) as well as Maryland Department of Health and Mental Hygiene’s Vital Statistics Administration (DHMH VSA). PHS Planning and Epidemiology receives an annual data file of Montgomery County resident deaths registered with Maryland Department of Health and Mental Hygiene’s Vital Statistics Administration (DHMH VSA).
Using SAS analytic software, MCDHHS standardizes, aggregates, and calculates age-adjusted rates for each of the leading causes of death category consistent with state and national methods and by subgroups based on age, gender, race, and ethnicity combinations. Data are released in compliance with Data Use Agreements between DHMH VSA and MCDHHS. This dataset will be updated Annually.

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.

This dataset provides comprehensive information on the total number of suicides in Mexico from 1990 to 2023, categorized by sex and state.The dataset adheres to the government methodology by using the year of registration and the state of residence of the deceased as key variables. It includes the following data points:The total male and female populations.Suicide counts for males and females.Suicide rates for each sex.Data SourcesSuicide Data: Extracted from the INEGI database of registered deaths.Source: INEGI - Microdata on DeathsPopulation Data: Sourced from Mexican government population projections for 2020-2070.Source: Gob.mx - Population ProjectionsThis dataset is a valuable resource for understanding trends in suicide across Mexico and offers insights into differences by sex and state-level demographics.

This dataset contains data about obesity, suicides and unemployment segregated by Country. The sources of data are wikipedia tables as updated on 11/04/2022. More information can be found in project's github: https://github.com/martinsanc/wikipedia_scraper

Países (List of countries by population (United Nations) - Wikipedia)

Country

UN continental region

UN statistical subregion

Population 1 July 2018

Population 1 July 2019

Change

Desempleo (List of countries by unemployment rate - Wikipedia)

Unemployment Rate

Sourcedate of information

Suicidios (List of countries by suicide rate - Wikipedia)

All

Male

Female

Tasa de obesidad por país (List of countries by suicide rate - Wikipedia)

Rank

Obesity rate

This dataset tracks the updates made on the dataset "Vital Statistics Suicide Deaths by Age-Group, Race/Ethnicity, Resident Region, and Gender: Beginning 2003" as a repository for previous versions of the data and metadata.

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 rather than unverifiable accident, neglect or abuse. The population denominators for rates are age 10 and over. Low numbers may result in zero values or missing data.

Data source: Office for Health Improvement and Disparities (OHID), Public Health Outcomes Framework (PHOF) indicator 41001 (E10). This data is updated annually.

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 rather than unverifiable accident, neglect or abuse. The population denominators for rates are age 10 and over. Low numbers may result in zero values or missing data. Data source: Office for Health Improvement and Disparities (OHID), Public Health Outcomes Framework (PHOF) indicator 41001 (E10). This data is updated annually.

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.

Historical chart and dataset showing Russia suicide rate by year from 2000 to 2021.

ObjectiveThe number of suicides in Japan has remained high for many years. To effectively resolve this problem, firm understanding of the statistical data is required. Using a large quantity of wide-ranging data on Japanese citizens, the purpose of this study was to analyze the geographical clustering properties of suicides and how suicide rates have evolved over time, and to observe detailed patterns and trends in a variety of geographic regions.MethodsUsing adjacency data from 2008, the spatial and temporal/spatial clustering structure of geographic statistics on suicides were clarified. Echelon scans were performed to identify regions with the highest-likelihood ratio of suicide as the most likely suicide clusters.ResultsIn contrast to results obtained using temporal/spatial analysis, the results of a period-by-period breakdown of evolving suicide rates demonstrated that suicides among men increased particularly rapidly during 1988–1992, 1993–1997, and 1998–2002 in certain cluster regions located near major metropolitan areas. For women, results identified cluster regions near major metropolitan areas in 1993–1997, 1998–2002, and 2003–2007.ConclusionsFor both men and women, the cluster regions identified are located primarily near major metropolitan areas, such as greater Tokyo and Osaka.

ABSTRACT Objective To identify patterns of suicide trends registered in Portugal, taking into account a set of socio-economic and demographic variables between the years 2007 and 2014 in order to obtain an overview of this scourge in Portugal. Methods Using data from the National Institute of Statistics (INE) and the Death Certificate Information System (SICO), suicide was analyzed according to the category of ICD10 (International Classification of Diseases), the incidence by gender, age group and region. Results The most affected to suicide are men (54,8%), over 75 years old (30.9%) and occurs in the more rural areas of the interior of the country that are more deprived of materials. The highest suicide mortality is found in the Alentejo region (12,8%). Conclusion Mortality due to suicide continues to grow in Portugal and varies according to gender, age is highest in the Central and South regions. A strategy of follow-up and prevention in the field of social action and health care is required, with important regional variations and greater vigilance on the illegal trade in firearms and pesticides.

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

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.

The dataset contains year, state and gender wise data on the number of farmer suicides which have happened in India. The different categories of farmer suicides data covered in the dataset include number of agricultural labourers, farmers or cultivators - both those who do farming on their own lands and on leased lands, and others who are engaged in the farming sector.

Notes: 1. The Farmer Suicides data published by National Crime Records Bureau (NCRB) is the compiled data of the same data that NCRB receives from respective States or Union Territories every year. 2. Farmer Suicides data is not published during the years 2009 to 2011 3. Prior to 2014, the NCRB had published farmers suicides data by single category of information, namely 'Total Suicides in the Farming Sector'. From 2014, the same data is published by additional categorization such as number of suicides of agricultural labourers, farmers or cultivators who cultivate on their own lands or on the leased lands, etc. 4. The NCRB defines - a. 'Farmer/Cultivator' as those whose profession is farming and include those who cultivate on their own land as well as those who cultivate on leased land/other's land with or without the assistance of agricultural labourers. b. 'Agricultural labourer' as those who primarily work in farming sector (agriculture/horticulture) whose main source of income is from agriculture labour activities.

This group of datasets describe the suicides in Scotland for the period 1982-2009. There are 4 separate datasets: All Suicides/Male Suicides/Female Suicides/All Suicide Rate (expressed per 100,000 people). The data is broken down into Local Authority Areas making it easier to investigate any spatial disparity in the suicide figures. A couple of points are worth noting are that it is unclear if the suicide data shows all suicides or just those of Adults. A recent Scottish Government report(http://www.scotland.gov.uk/Publications/2007/03/01145422/20) used deaths of people over 15 years old. Differences in the rates between this data and the results presented in the Scottish Government report may also be due to different population datasets being used. Suicide data sources form the Scottish Public Health Observatory (http://www.scotpho.org.uk/home/Healthwell-beinganddisease/suicide/suicide_data/suicide_la.asp) and the population data used to calculate the rates was sourced from ShareGeo Open (http://hdl.handle.net/10672/95) which uses mid-year estimates downloaded from Nomis (www.nomisweb.co.uk/. Datasets were joined to Local Authority (district, unitary authority and borough) boundaries downloaded from Ordnance Survey OpenData Boundary Line dataset. All spatial analysis was carried out in ArcGIS. GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2011-01-13 and migrated to Edinburgh DataShare on 2017-02-21.

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.