As of 2022, the third leading cause of death among teenagers aged 15 to 19 years in the United States was intentional self-harm or suicide, contributing around 17 percent of deaths among age group. The leading cause of death at that time was unintentional injuries, contributing to around 37.4 percent of deaths, while 21.8 percent of all deaths in this age group were due to assault or homicide. Cancer and heart disease, the overall leading causes of death in the United States, are also among the leading causes of death among U.S. teenagers. Adolescent suicide in the United States In 2021, around 22 percent of students in grades 9 to 12 reported that they had seriously considered attempting suicide in the past year. Female students were around twice as likely to report seriously considering suicide compared to male students. In 2022, Montana had the highest rate of suicides among U.S. teenagers with around 39 deaths per 100,000 teenagers, followed by South Dakota with a rate of 33 per 100,000. The states with the lowest death rates among adolescents are New York and New Jersey. Mental health treatment Suicidal thoughts are a clear symptom of mental health issues. Mental health issues are not rare among children and adolescents, and treatment for such issues has become increasingly accepted and accessible. In 2021, around 15 percent of boys and girls aged 5 to 17 years had received some form of mental health treatment in the past year. At that time, around 35 percent of youths aged 12 to 17 years in the United States who were receiving specialty mental health services were doing so because they had thought about killing themselves or had already tried to kill themselves.

In 2022, the leading cause of death among teenagers in the United States aged 15 to 19 was accidents or unintentional injuries. At that time, there were 4,762 deaths among teens aged 15 to 19 years due to accidents. Homicide was the second leading cause of death among teens in this age group, with 2,781 deaths.

In 2022, the leading causes of death among children and adolescents in the United States aged 10 to 14 were unintentional injuries, intentional self-harm (suicide), and cancer. That year, unintentional injuries accounted for around 25 percent of all deaths among this age group. Leading causes of death among older teens Like those aged 10 to 14 years, the leading cause of death among older teenagers in the U.S. aged 15 to 19 years is unintentional injuries. In 2022, unintentional injuries accounted for around 37 percent of all deaths among older teens. However, unlike those aged 10 to 14, the second leading cause of death among teens aged 15 to 19 is assault or homicide. Sadly, the third leading cause of death among this age group is suicide, making suicide among the leading three causes of death for both age groups. Teen suicide Suicide remains a major problem among teenagers in the United States, as reflected in the leading causes of death among this age group. It was estimated that in 2021, around 22 percent of high school students in the U.S. considered attempting suicide in the past year, with this rate twice as high for girls than for boys. The states with the highest death rates due to suicide among adolescents aged 15 to 19 years are Montana, South Dakota, and New Mexico. In 2022, the death rate from suicide among this age group in Montana was 39 per 100,000 population. In comparison, New York, the state with the lowest rate, had just five suicide deaths among those aged 15 to 19 years per 100,000 population.

Data contain vehicular fatalities, licensing, and licensure provisions of those age 16-59. The observations are at the cell level: age, sex, year, and state.

Over the last few years, gun violence in the United States has become an increasingly deadly public health crisis. In 2021, firearms were the leading cause of death for children and adolescents aged one to 19 years old for a second year in a row in the United States, with ***** deaths from firearms, which accounted for more deaths than car crashes and other diseases in that year. This is an increase from the previous year, when there were ***** deaths from firearms. Gun violence in the U.S. Along with a rise in gun-related deaths, the United States has been experiencing an overall increase in gun violence, including mass shootings, school shootings, and gun homicides. Not surprisingly, the United States has also reported in increase in gun sales, with the unit sales for firearms reaching a new high in recent years. A uniquely American problem Despite the rise of gun violence and gun-related deaths, guns remain easily accessible in the United States and gun control has become a divisive issue throughout the nation. However, gun control proponents often call attention to the uniquely American phenomenon of school shootings. Since 2018, the annual number of incidents involving firearms at K-12 schools in the U.S. reached over *** in each year, while similar incidents in other countries with strict gun laws are exceptionally rare.

Replication data for: "Are Minimum Wages a Silent Killer? New Evidence on Drunk Driving Fatalities"

ABSTRACT This article analyzes maternal deaths of adolescents in Piauí and describes the stories of those who died due to induced abortion between 2008 and 2013. The study was conducted in two stages. The first, quantitative, obtained demographic data and basic causes of deaths from the Mortality Information System. In the second, qualitative, the mothers of the adolescents were interviewed. Adolescents’ deaths accounted for 17.2% (50 cases) of total maternal deaths. The majority of the adolescents lived in inner cities (78%) and was black (70%). The causes of death were hypertensive disorders (28%), puerperal infection (16%), hemorrhage (12%), thromboembolism (12%) and abortion (10%). The use of medication occurred in all cases of abortion, with abundant bleeding and pelvic pain being the main reasons for seeking hospital care. There was delay in the diagnosis and appropriate treatment of abortion complications, which may have contributed to the death of the adolescents. Maternal deaths among adolescents were mostly caused by conditions considered preventable. The stories of young women who died of abortion complications have highlighted the need for better-qualified health care, as well as laws and public policies that protect women who decide to terminate their pregnancies.

Effective June 28, 2023, this dataset will no longer be updated. Similar data are accessible from CDC WONDER (https://wonder.cdc.gov/mcd-icd10-provisional.html).

Deaths involving coronavirus disease 2019 (COVID-19) with a focus on ages 0-18 years in the United States.

The study examined adolescent sexual assault survivors' help-seeking experiences with the legal and medical systems in two Midwestern communities that have different models of Sexual Assault Nurse Examiner (SANE)/Sexual Assault Response Team (SART) interventions. In Dataset 1 (Qualitative Victim Interviews), investigators conducted qualitative interviews with N=20 adolescent sexual assault victims 14-17 years old. From these interviews, investigators identified three distinct patterns of survivors' post-assault disclosures and their pathways to seeking help from SANE programs and the criminal justice system: voluntary (survivors' contact with the legal and medical system was by their choice), involuntary (system contact was not by choice), and situational (circumstances of the assault itself prompted involuntary disclosure). Interviews included responses that described the assault, their experience with both the SANE/SART programs and the criminal justice system, and victim and offender demographic information. In Dataset 2 (SANE Programs Quantitative Data), investigators obtained SANE program records, police and prosecutor records, and crime lab findings for a sample of N=395 (ages 13-17) adolescent sexual assault victims who sought services from the local SANE programs in two different counties. The data collected examined victim's progress through the criminal justice system. Factors that could potentially affect case progression were also examined; age of victim, relationship to offender, assault characteristics, number of assaults on victim, and evidence collected. Differences between the two different counties' programs were also examined for their effect on the case progression.

This statistic shows the annual number of people aged 12 to 20 who were victims of a violent crime from 1993 to 2021. In 1993 around **** million adolescents were victims of violent crime. In 2021, the rate had dropped to ******* adolescents.

Background: The reduction of child and adolescent deaths (defined as decedents aged 0–19 years) remains a crucial public health priority also in high-income countries such as Finland. There is evidence of a relationship between socioeconomic gradients and child mortality, but the association is considered complex and relatively poorly understood. Exploiting a Finnish dataset with nationwide coverage, the present study aimed to shed light on the sociodemographic predictors of child and adolescent mortality at the municipality level.Methods: A public database of Statistics Finland was queried for municipality-level data on sociodemographic traits and child and adolescent deaths in Finland during the years 2011–2018. The sociodemographic indicators included total population size, child and adolescent population size, sex distribution, mean age, education, unemployment, median income, population density, rurality, percentage of individuals living in their birth municipality, household size, overcrowded households, foreign language speakers, divorce rate, car ownership rate, and crime rate. The sociodemographic indicators were modeled against child and adolescent mortality by means of generalized estimating equations.Results: A total of 2,371 child and adolescent deaths occurred during the 8-year study period, yielding an average annual mortality rate of 26.7 per 100,000 individuals. Despite a fluctuating trend, the average annual decline in child and adolescent deaths was estimated to be 3% (95% confidence interval 1–5%). Of the sociodemographic indicators, population density was associated with higher child and adolescent mortality (rate ratio 1.03, 95% confidence interval 1.01–1.06), whereas the percentage of foreign language speakers was associated with lower child and adolescent mortality (0.96, 0.93–0.99).Conclusion: Densely populated areas should be the primary focus of efforts to reduce child and adolescent mortality. Of note is also the apparently protective effect of foreign language speakers for premature mortality. Future studies are welcomed to scrutinize the mediating pathways and individual-level factors behind the associations detected in this study.

Abstract (en): This project examined the role of technology use in teen dating violence and abuse, and bullying. The goal of the project was to expand knowledge about the types of abuse experiences youth have, the extent of victimization and perpetration via technology and new media (e.g., social networking sites, texting on cellular phones), and how the experience of such cyber abuse within teen dating relationships or through bullying relates to other life factors. This project carried out a multi-state study of teen dating violence and abuse, and bullying, the main component of which included a survey of youth from ten schools in five school districts in New Jersey, New York, and Pennsylvania, gathering information from 5,647 youth about their experiences. The study employed a cross-sectional, survey research design, collecting data via a paper-pencil survey. The survey targeted all youth who attended school on a single day and achieved an 84 percent response rate. The Urban Institute's Justice Policy Center examined the role of youth technology use in teen dating violence and abuse, and bullying. The goal of the study was to expand knowledge about the types of abuse experiences youth have, the extent of victimization and perpetration via technology and new media, such as social networking sites and texting on cellular phones, and how experiencing such cyber abuse within teen dating relationships or through bullying relates to other life factors. This study contributes to the knowledge base on which policy and program developers, school administrators, victim advocates, and criminal justice personnel rely on to develop evidence-based policies and strategies to address these problems. The specific questions asked in this study was in two main parts: Teen Dating Violence and Abuse : To understand the role of cyber abuse in youth dating violence and abuse. How often do youth experience dating violence and abuse victimization? ; How often do youth perpetrate dating violence and abuse? ; Does teen dating violence and abuse vary by gender, and is it reciprocal? ; Does teen dating violence and abuse vary by other subgroup status? ; Does teen dating violence and abuse happen at school? ; Do teen dating violence and abuse victims seek help? ; How often does cyber dating abuse co-occur with other types of violence and abuse, including cyber bullying? ; How does cyber dating abuse relate to other life factors? ; Bullying : To understand the role of cyber bullying in youth's lives. How often do youth experience bullying victimization? ; How often do youth perpetrate bullying? ; Does bullying vary by gender, and do bullying victims and perpetrators overlap? ; Does bullying vary by other subgroup status? ; Does bullying happen at school? ; Do bullying victims seek help? ; How often does cyber bullying co-occur with other types of violence and abuse, including cyber dating abuse? ; How does cyber bullying relate to other life factors? ; The study employed a cross-sectional survey research design to capture the prevalence of youths' experiences with teen dating violence and abuse, and bullying. Particularly in regards to cyber abuse; compared those rates across differing subgroups of youth; and examined the correlational associations between such experiences and other life factors. The study conducted a large-scale survey of 7th to 12th grade youth, using a convenience sampling of schools in the Northeastern United States. The sampling goals were : To achieve a sample size large enough to examine teen dating violence and abuse, and bullying, given that only a portion of any sample would report such experiences. ; To recruit schools that were willing to allow access to youth on a single school day to conduct a survey about sensitive topics. ; To recruit schools with populations diverse enough to yield sizable, racially/ethnically and socioeconomically diverse subgroups of youth. ; The final study sample included ten schools across five school districts located in New Jersey, New York, and Pennsylvania. The survey questions asked youth about their demographic backgrounds; technology use; experiences with dating relationships, including violence and abuse; experiences with bullying; other risky behaviors (e.g., sexual activity, substance use); psychosocial adjustment (e.g., depression, anger/hostility); family relationships; and school experiences. The surveys were conducted in classrooms and administered by school staff trained by ...

The current study used latent profile analysis to identify subgroups of victims based on victimization (self- and peer-reported) and popularity (peer-reported). This study sought to (1) verify the existence of popular victims and (2) compare victim subgroups on loneliness and self-esteem. Participants were 804 Dutch adolescents (50.2% boys, Mage = 13.65 years). Results revealed six subgroups, including a group of popular self-identified victims. Popular self-identified victims were generally less lonely than other victims, but were more lonely and had lower self-esteem than non-victims. Implications for understanding the victimization experiences of high-status youth are discussed.All information about the content of the files is described in 'read me.pdf'. This file also contains information about the recruitment, participants and data collection. Data and the syntax for the descriptive statistics and all analyses as presented in the paper are also stored.

ABSTRACT Objective Identify the clinical and epidemiological profile of adolescents and young victims of firearms wounds admitted in a leading trauma hospital in North and Northeast of Brazil. Methods Quantitative and descriptive study, from June to December/2014, in Fortaleza-CE. The sample consisted of 231 participants, 12 to 24 years old. Date collection was carried out by interview with participant. We adopted significance level of 5% (p

New Mexico was the state with the highest rate of suicidal death among adolescents in the U.S. in 2023, with around **** deaths per 100,000 adolescents. The overall suicide rate in the U.S. has increased over recent years. Suicide is more common among men than women, with rates among men almost **** times higher than among women. Risk factors Risk factors for suicide include mental disorders, such as depression, bipolar disorder, and personality disorders, as well as substance abuse. In fact, suicidal thoughts, plans to commit suicide, and suicide attempts are all more common among those with drug or alcohol dependence or abuse. In terms of suicides due to a known mental disorder, depression accounts for around ** percent of all such suicides. Methods Most suicides in the United States are carried out by firearms, however, the most common method of suicide differs from country to country. In 2022, over ****** suicides in the United States were conducted by firearms, or just over half of all suicides that year. Firearms are the most common means of suicide among both men and women in the United States, but suicide by poisoning is much more common among women than men.

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.

Data for CDC’s COVID Data Tracker site on Rates of COVID-19 Cases and Deaths by Vaccination Status. Click 'More' for important dataset description and footnotes

Dataset and data visualization details: These data were posted on October 21, 2022, archived on November 18, 2022, and revised on February 22, 2023. These data reflect cases among persons with a positive specimen collection date through September 24, 2022, and deaths among persons with a positive specimen collection date through September 3, 2022.

Vaccination status: A person vaccinated with a primary series had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after verifiably completing the primary series of an FDA-authorized or approved COVID-19 vaccine. An unvaccinated person had SARS-CoV-2 RNA or antigen detected on a respiratory specimen and has not been verified to have received COVID-19 vaccine. Excluded were partially vaccinated people who received at least one FDA-authorized vaccine dose but did not complete a primary series ≥14 days before collection of a specimen where SARS-CoV-2 RNA or antigen was detected. Additional or booster dose: A person vaccinated with a primary series and an additional or booster dose had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after receipt of an additional or booster dose of any COVID-19 vaccine on or after August 13, 2021. For people ages 18 years and older, data are graphed starting the week including September 24, 2021, when a COVID-19 booster dose was first recommended by CDC for adults 65+ years old and people in certain populations and high risk occupational and institutional settings. For people ages 12-17 years, data are graphed starting the week of December 26, 2021, 2 weeks after the first recommendation for a booster dose for adolescents ages 16-17 years. For people ages 5-11 years, data are included starting the week of June 5, 2022, 2 weeks after the first recommendation for a booster dose for children aged 5-11 years. For people ages 50 years and older, data on second booster doses are graphed starting the week including March 29, 2022, when the recommendation was made for second boosters. Vertical lines represent dates when changes occurred in U.S. policy for COVID-19 vaccination (details provided above). Reporting is by primary series vaccine type rather than additional or booster dose vaccine type. The booster dose vaccine type may be different than the primary series vaccine type. ** Because data on the immune status of cases and associated deaths are unavailable, an additional dose in an immunocompromised person cannot be distinguished from a booster dose. This is a relevant consideration because vaccines can be less effective in this group. Deaths: A COVID-19–associated death occurred in a person with a documented COVID-19 diagnosis who died; health department staff reviewed to make a determination using vital records, public health investigation, or other data sources. Rates of COVID-19 deaths by vaccination status are reported based on when the patient was tested for COVID-19, not the date they died. Deaths usually occur up to 30 days after COVID-19 diagnosis. Participating jurisdictions: Currently, these 31 health departments that regularly link their case surveillance to immunization information system data are included in these incidence rate estimates: Alabama, Arizona, Arkansas, California, Colorado, Connecticut, District of Columbia, Florida, Georgia, Idaho, Indiana, Kansas, Kentucky, Louisiana, Massachusetts, Michigan, Minnesota, Nebraska, New Jersey, New Mexico, New York, New York City (New York), North Carolina, Philadelphia (Pennsylvania), Rhode Island, South Dakota, Tennessee, Texas, Utah, Washington, and West Virginia; 30 jurisdictions also report deaths among vaccinated and unvaccinated people. These jurisdictions represent 72% of the total U.S. population and all ten of the Health and Human Services Regions. Data on cases among people who received additional or booster doses were reported from 31 jurisdictions; 30 jurisdictions also reported data on deaths among people who received one or more additional or booster dose; 28 jurisdictions reported cases among people who received two or more additional or booster doses; and 26 jurisdictions reported deaths among people who received two or more additional or booster doses. This list will be updated as more jurisdictions participate. Incidence rate estimates: Weekly age-specific incidence rates by vaccination status were calculated as the number of cases or deaths divided by the number of people vaccinated with a primary series, overall or with/without a booster dose (cumulative) or unvaccinated (obtained by subtracting the cumulative number of people vaccinated with a primary series and partially vaccinated people from the 2019 U.S. intercensal population estimates) and multiplied by 100,000. Overall incidence rates were age-standardized using the 2000 U.S. Census standard population. To estimate population counts for ages 6 months through 1 year, half of the single-year population counts for ages 0 through 1 year were used. All rates are plotted by positive specimen collection date to reflect when incident infections occurred. For the primary series analysis, age-standardized rates include ages 12 years and older from April 4, 2021 through December 4, 2021, ages 5 years and older from December 5, 2021 through July 30, 2022 and ages 6 months and older from July 31, 2022 onwards. For the booster dose analysis, age-standardized rates include ages 18 years and older from September 19, 2021 through December 25, 2021, ages 12 years and older from December 26, 2021, and ages 5 years and older from June 5, 2022 onwards. Small numbers could contribute to less precision when calculating death rates among some groups. Continuity correction: A continuity correction has been applied to the denominators by capping the percent population coverage at 95%. To do this, we assumed that at least 5% of each age group would always be unvaccinated in each jurisdiction. Adding this correction ensures that there is always a reasonable denominator for the unvaccinated population that would prevent incidence and death rates from growing unrealistically large due to potential overestimates of vaccination coverage. Incidence rate ratios (IRRs): IRRs for the past one month were calculated by dividing the average weekly incidence rates among unvaccinated people by that among people vaccinated with a primary series either overall or with a booster dose. Publications: Scobie HM, Johnson AG, Suthar AB, et al. Monitoring Incidence of COVID-19 Cases, Hospitalizations, and Deaths, by Vaccination Status — 13 U.S. Jurisdictions, April 4–July 17, 2021. MMWR Morb Mortal Wkly Rep 2021;70:1284–1290. Johnson AG, Amin AB, Ali AR, et al. COVID-19 Incidence and Death Rates Among Unvaccinated and Fully Vaccinated Adults with and Without Booster Doses During Periods of Delta and Omicron Variant Emergence — 25 U.S. Jurisdictions, April 4–December 25, 2021. MMWR Morb Mortal Wkly Rep 2022;71:132–138. Johnson AG, Linde L, Ali AR, et al. COVID-19 Incidence and Mortality Among Unvaccinated and Vaccinated Persons Aged ≥12 Years by Receipt of Bivalent Booster Doses and Time Since Vaccination — 24 U.S. Jurisdictions, October 3, 2021–December 24, 2022. MMWR Morb Mortal Wkly Rep 2023;72:145–152. Johnson AG, Linde L, Payne AB, et al. Notes from the Field: Comparison of COVID-19 Mortality Rates Among Adults Aged ≥65 Years Who Were Unvaccinated and Those Who Received a Bivalent Booster Dose Within the Preceding 6 Months — 20 U.S. Jurisdictions, September 18, 2022–April 1, 2023. MMWR Morb Mortal Wkly Rep 2023;72:667–669.

Estimated number of additional adolescent pregnancies, maternal and neonatal deaths, low birthweight births and stunted children resulting from girls dropping out of school due to the COVID-19 pandemic in six South Asian countries.

We provide data on the status of unclaimed deaths by age in Yongsan-gu, Seoul from 2018 to 2023, by male and female, in their teens, 20s, 30s, 40s, 50s, 60s, 70s, 80s, and 90s.

Data by medical encounter for the following conditions by age, race/ethnicity, and sex (gender): Congenital Anomalies Maternal Complications

Visit https://www.sandiegocounty.gov/content/sdc/hhsa/programs/phs/maternal_child_family_health_services/MCFHSstatistics.html to view MCFHS perinatal health indicators, including: Live Births Teen Births Early Prenatal Care Preterm Birth Low Birth Weight Fetal Mortality Infant Mortality Maternal Deaths

Rates per 100,000 population. Age-adjusted rates per 100,000 2000 US standard population. Blank Cells: Events less than 11 are suppressed. Starting with data year 2022, geographies with less than 20,000 population contain no age-adjusted rates and all rates based on events <20 are suppressed due to statistical instability. Rates not calculated in cases where zip code is unknown. SES: Is the median household income by Subregional Area (SRA) community. Data for SRA only.

Data sources: California Department of Public Health, Center for Health Statistics, Office of Health Information and Research, Vital Records Business Intelligence System (VRBIS), 2022. California Department of Health Care Access and Information (HCAI), Emergency Department Discharge Database and Patient Discharge Database, 2022. SANDAG Population Estimates, 2022 (v11/23). 2022 population estimates were derived from the 2020 decennial census. Comparison of rates to prior years may not be appropriate. Prepared by: County of San Diego, Health and Human Services Agency, Public Health Services, Community Health Statistics Unit, May 2024.

2022 Community Profile Data Guide and Data Dictionary Dashboard: https://public.tableau.com/app/profile/chsu/viz/2022COREDataGuideandDataDictionary/Home