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.

This dataset combines historical county-level data from the Community Health Assessment Tool (CHAT) with last year's suicide rate data from the Pierce County Medical Examiners' database (MEDIS). The purpose of this combined dataset is to provide the most up-to-date information on suicide rates in Pierce County with historical data for comparing Pierce County to other neighboring counties.

United States US: Suicide Mortality Rate: Male data was reported at 23.600 NA in 2016. This records an increase from the previous number of 23.000 NA for 2015. United States US: Suicide Mortality Rate: Male data is updated yearly, averaging 20.700 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 23.600 NA in 2016 and a record low of 17.900 NA in 2000. United States US: Suicide Mortality Rate: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.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;

United States US: Suicide Mortality Rate: per 100,000 Population data was reported at 15.300 Number in 2016. This records an increase from the previous number of 15.000 Number for 2015. United States US: Suicide Mortality Rate: per 100,000 Population data is updated yearly, averaging 13.200 Number from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 15.300 Number in 2016 and a record low of 11.300 Number in 2000. United States US: Suicide Mortality Rate: per 100,000 Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: 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;

United States US: Suicide Mortality Rate: Female data was reported at 7.200 NA in 2016. This records an increase from the previous number of 7.100 NA for 2015. United States US: Suicide Mortality Rate: Female data is updated yearly, averaging 5.900 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 7.200 NA in 2016 and a record low of 4.900 NA in 2000. United States US: Suicide Mortality Rate: Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.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 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.

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.

This report provides information regarding suicide mortality for the years 2001–2014. It incorporates the most recent mortality data from the VA/Department of Defense (DoD) Joint Suicide Data Repository and includes information for deaths from suicide among all known Veterans of U.S. military service. Data for the Joint VA/DoD Suicide Data Repository were obtained from the National Center for Health Statistics’ National Death Index through collaboration with the DoD, the CDC, and the VA/DoD Joint Suicide Data Repository initiative. Data available from the National Death Index include reports of mortality submitted from vital statistics systems in all 50 U.S. states, New York City, Washington D.C., Puerto Rico, and the U.S. Virgin Islands.

State-level firearm suicide proxy (FSS) for household gun ownership 1949-2023. Unlike most gun prevalence measures that are representative at the national or regional level, this proxy represents household gun ownership trends at the state level and is not reliant on self-reported data that are prone to social desirability bias. This extended proxy represents the longest-ranging dataset of state-level gun ownership rates to date. This dataset also includes historic data on firearm homicide and homicide counts and rates per 100,000 residents.

THIS DATASET WAS LAST UPDATED AT 2:10 AM EASTERN ON JUNE 29

OVERVIEW

2019 had the most mass killings since at least the 1970s, according to the Associated Press/USA TODAY/Northeastern University Mass Killings Database.

In all, there were 45 mass killings, defined as when four or more people are killed excluding the perpetrator. Of those, 33 were mass shootings . This summer was especially violent, with three high-profile public mass shootings occurring in the span of just four weeks, leaving 38 killed and 66 injured.

A total of 229 people died in mass killings in 2019.

The AP's analysis found that more than 50% of the incidents were family annihilations, which is similar to prior years. Although they are far less common, the 9 public mass shootings during the year were the most deadly type of mass murder, resulting in 73 people's deaths, not including the assailants.

One-third of the offenders died at the scene of the killing or soon after, half from suicides.

About this Dataset

The Associated Press/USA TODAY/Northeastern University Mass Killings database tracks all U.S. homicides since 2006 involving four or more people killed (not including the offender) over a short period of time (24 hours) regardless of weapon, location, victim-offender relationship or motive. The database includes information on these and other characteristics concerning the incidents, offenders, and victims.

The AP/USA TODAY/Northeastern database represents the most complete tracking of mass murders by the above definition currently available. Other efforts, such as the Gun Violence Archive or Everytown for Gun Safety may include events that do not meet our criteria, but a review of these sites and others indicates that this database contains every event that matches the definition, including some not tracked by other organizations.

This data will be updated periodically and can be used as an ongoing resource to help cover these events.

Using this Dataset

To get basic counts of incidents of mass killings and mass shootings by year nationwide, use these queries:

Mass killings by year

Mass shootings by year

To get these counts just for your state:

Filter killings by state

Definition of "mass murder"

Mass murder is defined as the intentional killing of four or more victims by any means within a 24-hour period, excluding the deaths of unborn children and the offender(s). The standard of four or more dead was initially set by the FBI.

This definition does not exclude cases based on method (e.g., shootings only), type or motivation (e.g., public only), victim-offender relationship (e.g., strangers only), or number of locations (e.g., one). The time frame of 24 hours was chosen to eliminate conflation with spree killers, who kill multiple victims in quick succession in different locations or incidents, and to satisfy the traditional requirement of occurring in a “single incident.”

Offenders who commit mass murder during a spree (before or after committing additional homicides) are included in the database, and all victims within seven days of the mass murder are included in the victim count. Negligent homicides related to driving under the influence or accidental fires are excluded due to the lack of offender intent. Only incidents occurring within the 50 states and Washington D.C. are considered.

Methodology

Project researchers first identified potential incidents using the Federal Bureau of Investigation’s Supplementary Homicide Reports (SHR). Homicide incidents in the SHR were flagged as potential mass murder cases if four or more victims were reported on the same record, and the type of death was murder or non-negligent manslaughter.

Cases were subsequently verified utilizing media accounts, court documents, academic journal articles, books, and local law enforcement records obtained through Freedom of Information Act (FOIA) requests. Each data point was corroborated by multiple sources, which were compiled into a single document to assess the quality of information.

In case(s) of contradiction among sources, official law enforcement or court records were used, when available, followed by the most recent media or academic source.

Case information was subsequently compared with every other known mass murder database to ensure reliability and validity. Incidents listed in the SHR that could not be independently verified were excluded from the database.

Project researchers also conducted extensive searches for incidents not reported in the SHR during the time period, utilizing internet search engines, Lexis-Nexis, and Newspapers.com. Search terms include: [number] dead, [number] killed, [number] slain, [number] murdered, [number] homicide, mass murder, mass shooting, massacre, rampage, family killing, familicide, and arson murder. Offender, victim, and location names were also directly searched when available.

This project started at USA TODAY in 2012.

Contacts

Contact AP Data Editor Justin Myers with questions, suggestions or comments about this dataset at jmyers@ap.org. The Northeastern University researcher working with AP and USA TODAY is Professor James Alan Fox, who can be reached at j.fox@northeastern.edu or 617-416-4400.

Over *** thousand deaths due to suicides were recorded in India in 2022. Furthermore, majority of suicides were reported in the state of Tamil Nadu, followed by Rajasthan. The number of suicides that year had increased from the previous year. Some of the causes for suicides in the country were due to professional problems, abuse, violence, family problems, financial loss, sense of isolation and mental disorders. Depressive disorders and suicide As of 2015, over ****** million people worldwide suffered from some kind of depressive disorder. Furthermore, over ** percent of the total population in India suffer from different forms of mental disorders as of 2017. There exists a positive correlation between the number of suicide mortality rates and people with select mental disorders as opposed to those without. Risk factors for mental disorders Every ******* person in India suffers from some form of mental disorder. Today, depressive disorders are regarded as the leading contributor not only to disease burden and morbidity worldwide, but even suicide if not addressed. In 2022, the leading cause for suicide deaths in India was due to family problems. The second leading cause was due to illness. Some of the risk factors, relative to developing mental disorders including depressive and anxiety disorders, include bullying victimization, poverty, unemployment, childhood sexual abuse and intimate partner violence.

description:

This dataset describes drug poisoning deaths at the U.S. and state level by selected demographic characteristics, and includes age-adjusted death rates for drug poisoning. Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD 10). Drug-poisoning deaths are defined as having ICD 10 underlying cause-of-death codes X40 X44 (unintentional), X60 X64 (suicide), X85 (homicide), or Y10 Y14 (undetermined intent).

Estimates are based on the National Vital Statistics System multiple cause-of-death mortality files. Age-adjusted death rates (deaths per 100,000 U.S. standard population for 2000) are calculated using the direct method. Populations used for computing death rates for 2011 2015 are postcensal estimates based on the 2010 U.S. census. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Death rates for some states and years may be low due to a high number of unresolved pending cases or misclassification of ICD 10 codes for unintentional poisoning as R99, Other ill-defined and unspecified causes of mortality. For example, this issue is known to affect New Jersey in 2009 and West Virginia in 2005 and 2009 but also may affect other years and other states. Estimates should be interpreted with caution.

This dataset describes drug poisoning deaths at the U.S. and state level by selected demographic characteristics, and includes age-adjusted death rates for drug poisoning. Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD 10). Drug-poisoning deaths are defined as having ICD 10 underlying cause-of-death codes X40 X44 (unintentional), X60 X64 (suicide), X85 (homicide), or Y10 Y14 (undetermined intent).

Estimates are based on the National Vital Statistics System multiple cause-of-death mortality files. Age-adjusted death rates (deaths per 100,000 U.S. standard population for 2000) are calculated using the direct method. Populations used for computing death rates for 2011 2015 are postcensal estimates based on the 2010 U.S. census. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Death rates for some states and years may be low due to a high number of unresolved pending cases or misclassification of ICD 10 codes for unintentional poisoning as R99, Other ill-defined and unspecified causes of mortality. For example, this issue is known to affect New Jersey in 2009 and West Virginia in 2005 and 2009 but also may affect other years and other states. Estimates should be interpreted with caution.

In 2023, South Korea's suicide rate reached **** deaths per 100,000 people, nearly double that of two decades ago. South Korea has the highest suicide rate among the member countries of the Organization for Economic Co-operation and Development (OECD).Mental health in South KoreaIn South Korea, mental illnesses such as depression and anxiety, along with financial hardships, have been identified as significant contributing factors leading individuals to attempt suicide. According to a survey, nearly half of the respondents reported experiencing severe stress, making it the most commonly reported type of mental health problem that year. Additionally, suicide is increasingly recognized not only as an individual health problem in South Korea but also as a complex social issue that arises, among other factors, from the country's rapid economic development. Suicide prevention In response to the escalating suicide rates, the government introduced its first suicide prevention program in 2004. Since then, several measures have been implemented to address this pressing issue. For instance, Seoul City initiated the "Bridge of Life" project on the Mapo Bridge, a well-known site for suicide attempts. The primary goal of the project was to provide comfort to individuals contemplating suicide by projecting uplifting messages and images on the bridge. In 2021, however, it was decided to remove the messages and slogans due to their limited impact. If you are having suicidal thoughts or you know someone who is, it is essential to seek help. Many countries have suicide crisis or prevention lines that offer free advice and support in such situations. If you live in the United States, you can reach the Suicide & Crisis Lifeline by simply calling *** to receive free and confidential support 24/7. If you live in South Korea, you can call the suicide prevention hotline ***.

BackgroundThe rise of depression, anxiety, and suicide rates has led to increased demand for telemedicine-based mental health screening and remote patient monitoring (RPM) solutions to alleviate the burden on, and enhance the efficiency of, mental health practitioners. Multimodal dialog systems (MDS) that conduct on-demand, structured interviews offer a scalable and cost-effective solution to address this need.ObjectiveThis study evaluates the feasibility of a cloud based MDS agent, Tina, for mental state characterization in participants with depression, anxiety, and suicide risk.MethodSixty-eight participants were recruited through an online health registry and completed 73 sessions, with 15 (20.6%), 21 (28.8%), and 26 (35.6%) sessions screening positive for depression, anxiety, and suicide risk, respectively using conventional screening instruments. Participants then interacted with Tina as they completed a structured interview designed to elicit calibrated, open-ended responses regarding the participants' feelings and emotional state. Simultaneously, the platform streamed their speech and video recordings in real-time to a HIPAA-compliant cloud server, to compute speech, language, and facial movement-based biomarkers. After their sessions, participants completed user experience surveys. Machine learning models were developed using extracted features and evaluated with the area under the receiver operating characteristic curve (AUC).ResultsFor both depression and suicide risk, affected individuals tended to have a higher percent pause time, while those positive for anxiety showed reduced lip movement relative to healthy controls. In terms of single-modality classification models, speech features performed best for depression (AUC = 0.64; 95% CI = 0.51–0.78), facial features for anxiety (AUC = 0.57; 95% CI = 0.43–0.71), and text features for suicide risk (AUC = 0.65; 95% CI = 0.52–0.78). Best overall performance was achieved by decision fusion of all models in identifying suicide risk (AUC = 0.76; 95% CI = 0.65–0.87). Participants reported the experience comfortable and shared their feelings.ConclusionMDS is a feasible, useful, effective, and interpretable solution for RPM in real-world clinical depression, anxiety, and suicidal populations. Facial information is more informative for anxiety classification, while speech and language are more discriminative of depression and suicidality markers. In general, combining speech, language, and facial information improved model performance on all classification tasks.

BackgroundMental health conditions and psychiatric disorders are among the leading causes of illness, disability, and death among young people around the globe. In the United States, teen suicide has increased by about 30% in the last decade. Raising awareness of warning signs and promoting access to mental health resources can help reduce suicide rates for at-risk youth. However, death by suicide remains a taboo topic for public discourse and societal intervention. An unconventional approach to address taboo topics in society is the use of popular media.MethodWe conducted a quantitative content analysis of mainstream news reporting on the controversial Netflix series 13 Reasons Why Season 1. Using a combination of top-down and bottom-up search strategies, our final sample consisted of 97 articles published between March 31 and May 31, 2017, from 16 media outlets in 3,150 sentences. We systematically examined the news framing in these articles in terms of content and valence, the salience of health/social issue related frames, and their compliance with the WHO guidelines.ResultsNearly a third of the content directly addressed issues of our interest: 61.6% was about suicide and 38.4% was about depression, bullying, sexual assault, and other related health/social issues; it was more negative (42.8%) than positive (17.4%). The criticism focused on the risk of suicide contagion, glamorizing teen suicide, and the portrayal of parents and educators as indifferent and incompetent. The praise was about the show raising awareness of real and difficult issues young people struggle with in their everyday life and serving as a conversation starter to spur meaningful discussions. Our evaluation of WHO guideline compliance for reporting on suicide yielded mixed results. Although we found recommended practices across all major categories, they were minimal and could be improved.ConclusionDespite their well intentions and best efforts, the 13 Reasons Why production team missed several critical opportunities to be better prepared and more effective in creating social impact entertainment and fostering difficult dialogs. There is an urgent need to train news reporters about established health communication guidelines and promote best practices in media reporting on sensitive topics such as suicide.

Medium/Small metropolitan counties: Model performance comparison.

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

ABSTRACT Objective To describe the epidemiological profile and analyze the time trend of suicide mortality among adolescents (10-19 years old) from the Brazilian Northeast, from 2001 to 2015. Methods This is an observational study, which took place in the Northeast region, Brazil. The study period was from 2001 to 2015. Deaths from intentional self-harm (X60 to X84). exogenous poisoning of undetermined intent (Y10 to Y19) and intentional self-harm (Y87.0) were considered, according to the 10th Review of the International Classification of Diseases (ICD-10), for adolescents aged 10 to 19 years. The variables analyzed were: sex, age group, race / color, specific ICD, state of residence and suicide mortality rate/100,000 inhabitants. Results There were 3,194 deaths due to suicide in the age group studied, with a male predominance (62.1%; n = 1,984), age group 15 to 19 years (84.8%; n = 2,707), race/brown color (65.4%; n = 2,090); between 4 and 7 years of schooling (31.7%; n = 1,011) and at CID X70 (47.8%; n = 1,528). The time trend of mortality was increasing from 2001 to 2015 (APC: 2.4%; p < 0.01), with higher rates in males. There was an increasing trend in the suicide rate, among men, throughout the period (AAPC: 2.9%; p < 0.01). In women, a decreasing trend was identified as of 2004 (APC: -2.2%; p < 0.01). Conclusion The epidemiological profile was characterized by male gender, age group 15-19 years, color/brown race and average schooling. The trend showed a growth pattern in males and a decline in females. It is recommended that public policies are aimed at the adolescent population.

The sixteen states participating in the NVDRS (of the CDC) are Alaska, Colorado, Georgia, Kentucky, Maryland, Massachusetts, New Jersey, New Mexico, North Carolina, Oklahoma, Oregon, Rhode Island, South Carolina, Utah, Virginia, and Wisconsin. Note the higher suicide incidence rates for the years 2008, 2009 and 2010 [3]. The data is available up to 12/2013, but recorded as of 10/2016, due to reporting lags. The last row in Table 3 also shows the percentage of suicides triggered by financial problems affecting the agent. Information similar to Table 2 shows the occurrence of murder-suicides as a joint event and can be found in the supporting information S2 Table.

Number of deaths and age-specific mortality rates for selected grouped causes, by age group and sex, 2000 to most recent year.