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.

Data on death rates for suicide in the United States, by age, sex, race, and Hispanic origin. Data are from Health, United States. SOURCE: National Center for Health Statistics, National Vital Statistics System, Mortality File. Search, visualize, and download these and other estimates from over 150 health topics with the NCHS Data Query System (DQS), available from: https://www.cdc.gov/nchs/dataquery/index.htm.

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.

DQS Death rates for suicide, by sex, race, Hispanic origin, and age: United States from CDC WONDER

  Description

Data on death rates for suicide in the United States, by age, sex, race, and Hispanic origin. Data are from Health, United States. SOURCE: National Center for Health Statistics, National Vital Statistics System, Mortality File. Search, visualize, and download these and other estimates from over 120 health topics with the NCHS Data Query System (DQS), available… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/dqs-death-rates-for-suicide-by-sex-race-hispanic-o.

Age-adjusted rate of suicide deaths for Santa Clara County residents. The data are provided for the total county population and by sex and race/ethnicity. Data trends are presented from 2007 to 2016. Source: Santa Clara County Public Health Department, VRBIS, 2007-2016. Data as of 05/26/2017; U.S. Census Bureau, 2010 Census.METADATA:Notes (String): Lists table title, notes and sourceYear (String): Year of death Category (String): Lists the category representing the data: Santa Clara County is for total population, sex: Male and Female, race/ethnicity: African American, Asian/Pacific Islander, Latino and White (non-Hispanic White only) and Asian/Pacific Islander subgroups: Asian Indian, Chinese. Filipino, Korean and Vietnamese.Age adjusted rate per 100,000 people (Numeric): The Tenth Revision of the International Classification of Diseases codes (ICD-10) are used for coding causes of death. Age-adjusted rate is calculated using 2000 U.S. Standard Population. Suicide rate is number of suicide deaths in a year per 100,000 people in the same time period.

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.

This dataset describes drug poisoning deaths at the county level by selected demographic characteristics and includes age-adjusted death rates for drug poisoning from 1999 to 2015. 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 (1). 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. Estimate does not meet standards of reliability or precision. Death rates are flagged as “Unreliable” in the chart when the rate is calculated with a numerator of 20 or less. 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” (2). 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. Smoothed county age-adjusted death rates (deaths per 100,000 population) were obtained according to methods described elsewhere (3–5). Briefly, two-stage hierarchical models were used to generate empirical Bayes estimates of county age-adjusted death rates due to drug poisoning for each year during 1999–2015. These annual county-level estimates “borrow strength” across counties to generate stable estimates of death rates where data are sparse due to small population size (3,5). Estimates are unavailable for Broomfield County, Colo., and Denali County, Alaska, before 2003 (6,7). Additionally, Bedford City, Virginia was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. County boundaries are consistent with the vintage 2005-2007 bridged-race population file geographies (6).

This dataset tracks the updates made on the dataset "Death rates for suicide, by sex, race, Hispanic origin, and age: United States" as a repository for previous versions of the data and metadata.

The Youth Risk Behavior Surveillance System (YRBSS) is a set of surveys that monitor priority health risk behaviors and experiences that contribute markedly to the leading causes of death, disability, and social problems among youth of grade 9 -12 in the United States. The surveys are administered every other year and it is maintained by the Centers for Disease Control and Prevention (CDC). A total of 107 questionnaire are asked. Some of the health-related behaviors and experiences monitored are: * Student demographics: sex, sexual identity, race and ethnicity, and grade * Youth health behaviors and conditions: sexual, injury and violence, bullying, diet and physical activity, obesity, and mental health, suicide attempt * Substance use behaviors: electronic vapor product and tobacco product use, alcohol use, and other drug use * Student experiences: parental monitoring, school connectedness, unstable housing, and exposure to community violence The dataset is used by a group of graduate students from Texas State University for 2025 TXST Open Datathon. The main YRBSS dataset includes data of multiple years, various states, district. For analyzing demographic variations associated with suicide, the 1991–2023 combined district dataset (https://www.cdc.gov/yrbs/files/sadc_2023/HS/sadc_2023_district.dat) is used, which offers a broad historical perspective on trends across different groups. To examine the preventive measures and develop a predictive model for suicide risk, the 2023 dataset (https://www.cdc.gov/yrbs/files/2023/XXH2023_YRBS_Data.zip) was used, ensuring the inclusion of the most recent behavioral and attributes. Please review the 2023 YRBS Data User's Guide by CDC for further information.

This dataset tracks the updates made on the dataset "DEV DQS Death rates for suicide, by sex, race, Hispanic origin, and age: United States from CDC WONDER" as a repository for previous versions of the data and metadata.

Extracted in machine readable form from the AIHW General Record of Incidence of Mortality (GRIM) books.

GRIM books are Excel workbooks that contain national level, historical and recent deaths data for specific causes of death. The tables present age- and sex-specific counts and rates by cause of death, along with other summary measures.

GRIM books are available for all causes of death combined and 55 other cause of death groupings. They span different years for different causes of death, depending on the data available. GRIM books for some causes of death start at 1907 and they are the only national electronic tabulations of deaths data by cause registered before 1964. Data from 1964 onwards are sourced from the AIHW National Mortality Database. They include mortality data up to 2023.

For more information, please see Deaths data at AIHW or contact us at deaths@aihw.gov.au.

Also available on data.gov.au are the AIHW Mortality Over Regions and Time (MORT) books.

This dataset provides model-based provisional estimates of the weekly numbers of drug overdose, suicide, and transportation-related deaths using “nowcasting” methods to account for the normal lag between the occurrence and reporting of these deaths. Estimates less than 10 are suppressed. These early model-based provisional estimates were generated using a multi-stage hierarchical Bayesian modeling process to generate smoothed estimates of the weekly numbers of death, accounting for reporting lags. These estimates are based on several assumptions about how the reporting lags have changed in recent months across different jurisdictions, and the resulting estimates differ from other sources of provisional mortality data. For now, these estimates should be considered highly uncertain until further evaluations can be done to determine the validity of these assumptions about timeliness. The true patterns in reporting lags will not be known until data are finalized, typically 11–12 months after the end of the calendar year. Importantly, these estimates are not a replacement for monthly provisional drug overdose death counts, or quarterly provisional mortality estimates. For more detail about the nowcasting methods and models, see:

Rossen LM, Hedegaard H, Warner M, Ahmad FB, Sutton PD. Early provisional estimates of drug overdose, suicide, and transportation-related deaths: Nowcasting methods to account for reporting lags. Vital Statistics Rapid Release; no 11. Hyattsville, MD: National Center for Health Statistics. February 2021. DOI: https://doi.org/10.15620/ cdc:101132

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 from 1999 to 2015. 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 (1). 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. Estimate does not meet standards of reliability or precision. Death rates are flagged as “Unreliable” in the chart when the rate is calculated with a numerator of 20 or less. 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” (2). 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. Smoothed county age-adjusted death rates (deaths per 100,000 population) were obtained according to methods described elsewhere (3–5). Briefly, two-stage hierarchical models were used to generate empirical Bayes estimates of county age-adjusted death rates due to drug poisoning for each year during 1999–2015. These annual county-level estimates “borrow strength” across counties to generate stable estimates of death rates where data are sparse due to small population size (3,5). Estimates are unavailable for Broomfield County, Colo., and Denali County, Alaska, before 2003 (6,7). Additionally, Bedford City, Virginia was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. County boundaries are consistent with the vintage 2005-2007 bridged-race population file geographies (6).

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 (1). 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 2011–2016 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” (2). 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. Drug poisoning death rates may be underestimated in those instances.

REFERENCES 1. National Center for Health Statistics. National Vital Statistics System: Mortality data. Available from: http://www.cdc.gov/nchs/deaths.htm.

1. CDC. CDC Wonder: Underlying cause of death 1999–2016. Available from: http://wonder.cdc.gov/wonder/help/ucd.html.

This file contains death counts and death rates for drug overdose, suicide, homicide and firearm injuries at the United States national level (additional datasets exist for other levels of geography). The data is grouped by 3 different time periods including monthly, yearly, and trailing twelve months. Please see data dictionary for intents and mechanisms included in each measure.

Analysis of ‘NCHS - Drug Poisoning Mortality by State: United States’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/0d869bf1-96bb-413e-b39f-0754c5014832 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

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 from 1999 to 2015.

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 (1). 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.

Estimate does not meet standards of reliability or precision. Death rates are flagged as “Unreliable” in the chart when the rate is calculated with a numerator of 20 or less.

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” (2). 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.

Smoothed county age-adjusted death rates (deaths per 100,000 population) were obtained according to methods described elsewhere (3–5). Briefly, two-stage hierarchical models were used to generate empirical Bayes estimates of county age-adjusted death rates due to drug poisoning for each year during 1999–2015. These annual county-level estimates “borrow strength” across counties to generate stable estimates of death rates where data are sparse due to small population size (3,5). Estimates are unavailable for Broomfield County, Colo., and Denali County, Alaska, before 2003 (6,7). Additionally, Bedford City, Virginia was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. County boundaries are consistent with the vintage 2005-2007 bridged-race population file geographies (6).

--- Original source retains full ownership of the source dataset ---

Analysis of ‘NCHS - Drug Poisoning Mortality by State: United States’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/e469e38a-aa81-4bf9-9218-7fbed56cb5a5 on 27 January 2022.

--- Dataset description provided by original source is as follows ---

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 from 1999 to 2015.

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 (1). 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.

Estimate does not meet standards of reliability or precision. Death rates are flagged as “Unreliable” in the chart when the rate is calculated with a numerator of 20 or less.

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” (2). 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.

Smoothed county age-adjusted death rates (deaths per 100,000 population) were obtained according to methods described elsewhere (3–5). Briefly, two-stage hierarchical models were used to generate empirical Bayes estimates of county age-adjusted death rates due to drug poisoning for each year during 1999–2015. These annual county-level estimates “borrow strength” across counties to generate stable estimates of death rates where data are sparse due to small population size (3,5). Estimates are unavailable for Broomfield County, Colo., and Denali County, Alaska, before 2003 (6,7). Additionally, Bedford City, Virginia was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. County boundaries are consistent with the vintage 2005-2007 bridged-race population file geographies (6).

--- Original source retains full ownership of the source dataset ---

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.

Detailed listing of all U.S. Military Active Duty deaths for 2009

Analysis of ‘NCHS - Drug Poisoning Mortality by County: United States’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/0b942a9a-5646-4df4-831d-3a49001145a9 on 12 February 2022.

--- Dataset description provided by original source is as follows ---

This dataset describes drug poisoning deaths at the county level by selected demographic characteristics and includes age-adjusted death rates for drug poisoning from 1999 to 2015.

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 (1). 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.

Estimate does not meet standards of reliability or precision. Death rates are flagged as “Unreliable” in the chart when the rate is calculated with a numerator of 20 or less.

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” (2). 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.

Smoothed county age-adjusted death rates (deaths per 100,000 population) were obtained according to methods described elsewhere (3–5). Briefly, two-stage hierarchical models were used to generate empirical Bayes estimates of county age-adjusted death rates due to drug poisoning for each year during 1999–2015. These annual county-level estimates “borrow strength” across counties to generate stable estimates of death rates where data are sparse due to small population size (3,5). Estimates are unavailable for Broomfield County, Colo., and Denali County, Alaska, before 2003 (6,7). Additionally, Bedford City, Virginia was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. County boundaries are consistent with the vintage 2005-2007 bridged-race population file geographies (6).

--- Original source retains full ownership of the source dataset ---