In 2022, some 76.6 percent of suicides among males in the United States were among white males. This statistic depicts the distribution of suicide deaths in the United States in 2022, by race/ethnicity and gender.

In 2021, there were around 28 suicides per 100,000 white males in the United States, while there were 43 suicides per 100,000 males among American Indians or Alaska Natives. This statistic illustrates the male suicide rate in the United States from 2019 to 2021, by race and ethnicity.

In 2021, there were around seven suicides per 100,000 white females in the United States, while there were almost ** suicides per 100,000 females among American Indians or Alaska Natives. This statistic illustrates the female suicide rate in the United States from 2019 to 2021, by race and ethnicity.

In 2022, there were around **** suicides per 100,000 white individuals in the United States, while there were **** suicides per 100,000 individuals among Native Indians or Alaska Natives. This statistic illustrates the suicide rate in the United States in 2023, by race and ethnicity.

In 2019, *** people of Asian or Pacific Islander origin died by suicide using a firearm in the United States. In that same year, ****** White people died by suicide involving a firearm in the United States.

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.

ABSTRACT BACKGROUND: Suicide is one of the leading causes of death worldwide, accounting for one million deaths annually. Greater understanding of the causal risk factors is needed, especially in large urban centers. OBJECTIVE: To ascertain the epidemiological profile and temporal trend of suicides over two decades and correlate prevalence with social indicators. DESIGN AND SETTING: Descriptive population-based longitudinal retrospective study conducted in the city of São Paulo, Brazil. METHODS: A temporal trend series for suicide mortality in this city was constructed based on data from the Ministry of Health’s mortality notification system, covering 2000-2017. It was analyzed using classic demographic variables relating to social factors. RESULTS: Suicide rates were high throughout this period, increasing from 4.6/100,000 inhabitants in the 2000s to 4.9/100,000 in 2017 (mean: 4.7/100,000). The increase in mortality was mainly due to increased male suicide, which went from 6.0/100,000 to the current 8.0/100,000. Other higher coefficients corresponded to social risk factors, such as being a young adult (25-44 years old), being more educated (eight years of schooling) and having white ethnicity (67.2%). Suicide was also twice as likely to occur at home (47.8%). CONCLUSION: High suicide rates were seen over the period 2000-2017, especially among young adults and males. High schooling levels and white ethnicity were risk factors. The home environment is the crucial arena for preventive action. One special aspect of primary prevention is the internet and especially social media, which provides a multitude of information for suicide prevention.

Dataset Description

This dataset provides comprehensive information on the death rates for suicide in the United States, segmented by sex, race, Hispanic origin, and age, spanning from 1950 to 2020. The data is sourced from reputable public health records and aims to offer valuable insights into the demographic factors associated with suicide rates over an extensive period.

Columns Overview

1. INDICATOR: This column indicates that the dataset pertains to "Death rates for suicide." It remains constant throughout the dataset.
2. UNIT: Specifies the unit of measurement, which is "Deaths per 100,000 resident population, age-adjusted." This standardization allows for consistent comparison across different demographic groups.
3. UNIT_NUM: A numerical representation of the unit, where 1 corresponds to the unit described above. This is primarily useful for data processing.
4. STUB_NAME: Represents the broad category of the population, such as "Total" (all populations), "Male," "Female," and different racial and ethnic groups (e.g., "White, non-Hispanic," "Black, non-Hispanic").
5. STUB_NAME_NUM: A numerical representation of the STUB_NAME column, facilitating easier data manipulation.
6. STUB_LABEL: Provides a detailed description of the population category, giving a more specific breakdown of the demographic groups.
7. STUB_LABEL_NUM: A numerical representation of the STUB_LABEL column.
8. YEAR: The year the data corresponds to, ranging from 1950 to 2020. This allows for time-series analysis of suicide rates.
9. YEAR_NUM: A numerical representation of the year, useful for chronological data analysis.
10. AGE: The age category of the population, such as "All ages," "Under 1 year," "1-4 years," etc. This breakdown helps in understanding the impact of age on suicide rates.
11. AGE_NUM: A numerical representation of the AGE column, aiding in numerical analysis.
12. ESTIMATE: The estimated suicide rate for the specified demographic group in the given year, expressed in deaths per 100,000 resident population.
13. FLAG: Additional notes or flags about the data, which may include indications of data quality or other relevant information. This column helps in identifying potential issues or special considerations in the data.

Dataset Highlights

• Longitudinal Data: Covers an extensive period from 1950 to 2020, allowing for a detailed analysis of trends and changes in suicide rates over time.
• Demographic Breakdown: Provides insights into how suicide rates vary by sex, race, Hispanic origin, and age, highlighting potential disparities and areas for targeted intervention.
• Public Health Relevance: This dataset is crucial for public health officials, researchers, and policymakers to understand and address the factors contributing to suicide in various demographic groups.

Potential Analyses

1. Trend Analysis: Examine how suicide rates have changed over the decades for different demographic groups.
2. Demographic Disparities: Identify which groups are most affected by suicide and how these disparities have evolved.
3. Age-Specific Rates: Analyze suicide rates across different age groups to identify vulnerable populations.
4. Impact of Societal Changes: Correlate changes in suicide rates with significant societal events or policy changes.

Usage Recommendations

• Visualizations: Create line charts, bar graphs, and heatmaps to visualize trends and disparities in suicide rates.
• Statistical Analysis: Use regression models to identify factors significantly associated with changes in suicide rates.
• Public Health Policy: Leverage insights from the data to inform and evaluate public health interventions aimed at reducing suicide rates.

Among men in the United States, those aged 75 years and older have the highest death rate from suicide among all age groups. In 2022, the suicide death rate among men aged 75 years and older was 43.9 per 100,000 population. In comparison, the death rate from suicide among men aged 25 to 44 years was 29.6 per 100,000. Suicide is a significant problem in the United States, with rates increasing over the past decade. Suicide among men In the United States, the suicide rate among men is almost four times higher than that of women. In 2022, the rate of suicide among U.S. men was 23 per 100,000 population, the highest rate recorded over the past 70 years. Firearms account for the vast majority of suicide deaths among men, accounting for around 60 percent of male suicides in 2021. The reasons why U.S. men have higher rates of suicide than women are complex and not fully understood, but may have to do with the more violent means by which men carry out suicide and the stigma around seeking help for mental health issues. Suicide among women Although the suicide rate among women in the U.S. is significantly lower than that of men, the rate of suicide among women has increased over the past couple of decades. Among women, those aged 45 to 64 years have the highest death rates due to suicide, followed by women 25 to 44 years old. Interestingly, the share of women reporting serious thoughts of suicide in the past year is higher than that of men, with around 5.5 percent of U.S. women reporting such thoughts in 2023. Similarly to men, firearms account for most suicide deaths among women, however suffocation and poisoning account for a significant share of suicides among women. In 2021, around 35 percent of suicides among women were carried out by firearms, while suffocation and poisoning each accounted for around 28 percent of suicide deaths.

Methods of suicide/self-inflicted injuries for Santa Clara County residents. The methods of injury for suicide deaths are provided for the total county population and by race/ethnicity. Data for emergency department utilization and hospital discharges are summarized only for total county population. Data are presented for pooled years combined. Missing data are not included in the analysis. Source: Santa Clara County Public Health Department, VRBIS, 2007-2016. Data as of 05/26/2017; Office of Statewide Planning and Development, 2007-2014 Emergency Department Data; Office of Statewide Planning and Development, 2007-2014 Patient Discharge Data.METADATA:Notes (String): Lists table title, notes and sourceYear (String): Year of eventData element (String): Lists data represents deaths, hospital discharges or emergency department visitsCategory (String): Lists the category representing the data. Suicide death data are presented as: Santa Clara County is for total population, sex: Male and Female, and race/ethnicity: African American, Asian/Pacific Islander, Latino and White (non-Hispanic White only). Suicide attempt/ideation data are presented as: Santa Clara County is for total population.Means of injury (String): Methods are categorized as: Poisoning, Suffocation, Firearms, Fall, Cut/pierce, Fire/flame and other.Percentage (Numeric): Percentage

Suicide rates per 100,000 person years (October 1, 2007- December 31, 2018).

Yearly citation counts for the publication titled "Microglia of Prefrontal White Matter in Suicide".

Age-specific suicide rates and rate ratios.

Considered suicide in the past 12 months (high school only) by sex, race/ethnicity, and grade, California Healthy Kids Survey, 2015-16METADATA:Notes (String): Lists table title, sourceYear (String): Year of surveyCategory (String): Lists the category representing the data: Santa Clara County is for total surveyed population, sex: Male and Female, race/ethnicity: African American, Asian/Pacific Islander, Latino and White (non-Hispanic White only) and grade level (9th, 11th, or non-traditional).Percent (Numeric): Percentage of high school students who considered suicide in the past 12 months

Age-adjusted suicide rates (per 100,000 per year) by ethnicity and gender, as well as relative risks of suicide comparing Arab ethnicity to non-ethnic whites aged 10 and older in Michigan, 1990–2007.

Dataset Card for "vibhorag101/suicide_prediction_dataset_phr"

The dataset is sourced from Reddit and is available on Kaggle. The dataset contains text with binary labels for suicide or non-suicide.
The dataset was cleaned and following steps were applied Converted to lowercase Removed numbers and special characters. Removed URLs, Emojis and accented characters. Removed any word contractions. Remove any extra white spaces and any extra spaces after a single space. Removed any… See the full description on the dataset page: https://huggingface.co/datasets/fioriclass/suicide_prediction_dataset_phr.

The suicide rate among females in the United States is highest for those aged 45 to 64 years and lowest among girls aged 10 to 14 and elderly women 75 and over. Although the suicide rate among women remains over three times lower than that of men, rates of suicide among women have gradually increased over the past couple decades. Suicide among women in the United States In 2021, there were around six suicide deaths per 100,000 women in the United States. In comparison, the rate of suicide among women in the year 2000 was about four per 100,000. Suicide rates among women are by far the highest among American Indians or Alaska Natives and lowest among Hispanic and Black or African American women. Although firearms are involved in the highest share of suicide deaths among both men and women, they account for a much smaller share among women. In 2020, the firearm suicide rate among women was 1.8 per 100,000 population, while the rates of suicide for suffocation and poisoning were 1.7 and 1.5 per 100,000, respectively. Suicidal ideation among women Although not everyone who experiences suicidal ideation, or suicidal thoughts, will attempt suicide, suicidal thoughts are a risk factor for suicide. In 2022, just over five percent of women in the United States reported having serious thoughts of suicide in the past year. Suicidal thoughts are more common among women than men even though men have much higher rates of death from suicide than women. This is because men are more likely to use more lethal methods of suicide such as firearms. Women who suffer from substance use disorder are significantly more likely to have serious thoughts of suicide than women without substance use disorder.

ABSTRACT Objective: Identify in literature the social determinants of health related to suicide in the elderly, according to the model proposed by Dahlgren and Whitehead. Method: Integrative review of articles indexed in the databases BDENF, CINAHL, LILACS, and MEDLINE, with the following main descriptors: aged, suicide, social determinants of health, and risk factors. Primary studies were included which addressed social determinants of health and suicide in the elderly. Results: From the 19 articles analyzed, three categories emerged: proximal social determinants of health (male gender, mental disorders, physical illnesses, white race, 70-74 years old); intermediate social determinants of health (substance abuse, use of alcohol or psychotropic drugs, marital status, marital, social, and family problems, violence, previous suicide attempt, history of admission to psychiatric service); and distal social determinants of health (schooling, economic issues, sanitation, stressful events). Conclusion: Proximal determinants have more effects on suicide. Intermediate determinants are composed mainly of changeable factors. Distal determinants showed lesser associations.

In contrast to the model-minority myth, which conceptualizes Asian American youth as more educationally successful, respectful of teachers, hardworking, and cooperative that other ethnic minority youth (Chang and Sue, 2003), research has demonstrated that Asian American youth are at an increased risk for depression and suicide than their White or Black counterparts (Sen, 2004). Specifically, Asian American females aged 15-24 have the highest rate of completed suicides (14.1%) compared to other racial and ethnic groups (e.g., White 9.3%, Black 3.3%, and Hispanic 7.4%). Asian males of the same age group have the second highest rate of suicide deaths (12.7%) compared to other racial/ethnic group males (e.g., White 17.5%, Black 6.7%, and Hispanic 10%) (CDC 2008). In addition to these specific mental health problems, these youth face additional culturally-specific concerns, including racial discrimination (Lee et al., 2009). Despite such needs, Asian Americans underutilize traditional mental health services (Abe-Kim et al., 2007). Compared to youth (aged 18 or younger) from other racial or ethnic groups, Asian American youth are less likely than White, Black, or Hispanic children to actually receive mental health care (Ku and Matani, 2000). Additionally, research has demonstrated that Asian American youth also tend to underutilize mental health services in school settings (Amaral, Geierstanger, Soleimanpour, and Brindis, 2011; Anyon, Ong, and Whitaker, 2014; Walker, Kerns, Lyon, Bruns, and Cosgrove, 2010), despite the delivery of mental health services in schools seemingly overcoming certain structural barriers to seeking and obtaining mental health services, including transportation, insurance coverage, and cost (Cauce et al., 2002). Using exploratory focus groups, this qualitative study sought to explore perceptions of barriers to seeking school-based mental health services among first- and second-generation Asian youth of immigrant origin (33 participants in 7 focus groups). The specific research questions were: What are the sources of stress that may contribute to mental health concerns among Asian and Asian American youth, and what are their perceptions of barriers to mental health service use?

Sample characteristics overall and by component.