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 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.

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.

Road accidents were the leading causes of death among young adults across India between 2017 and 2019. It accounted to 18.4 percent of the deaths. Suicide was another main cause of death among young adults with the age of 15 to 29 years, with a 17.4 percent share during the same time period.

This graph illustrates the distribution of young people and children who died in France in 2014, by age and cause of death. That year, about 60 percent of people being between 15 and 14 years old died from external causes such as accidents or suicide.

In the United States in 2021, the death rate was highest among those aged 85 and over, with about 17,190.5 men and 14,914.5 women per 100,000 of the population passing away. For all ages, the death rate was at 1,118.2 per 100,000 of the population for males, and 970.8 per 100,000 of the population for women. The death rate Death rates generally are counted as the number of deaths per 1,000 or 100,000 of the population and include both deaths of natural and unnatural causes. The death rate in the United States had pretty much held steady since 1990 until it started to increase over the last decade, with the highest death rates recorded in recent years. While the birth rate in the United States has been decreasing, it is still currently higher than the death rate. Causes of death There are a myriad number of causes of death in the United States, but the most recent data shows the top three leading causes of death to be heart disease, cancers, and accidents. Heart disease was also the leading cause of death worldwide.

Number of deaths and mortality rates, by age group, sex, and place of residence, 1991 to most recent year.

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.

In 2022, the leading cause of death among people aged 10 to 24 years old in South Korea was suicide, resulting in approximately 10.7 deaths per 100,000 population. Suicide has been the primary cause of death among people aged 10 to 24 in South Korea for the past few years.

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

TABLE III. Deaths in 122 U.S. cities - 2015122 Cities Mortality Reporting System ��� Each week, the vital statistics offices of 122 cities across the United States report the total number of death certificates processed and the number of those for which pneumonia or influenza was listed as the underlying or contributing cause of death by age group (Under 28 days, 28 days ���1 year, 1-14 years, 15-24 years, 25-44 years, 45-64 years, 65-74 years, 75-84 years, and ��� 85 years).FOOTNOTE:U: Unavailable -: No reported cases * Mortality data in this table are voluntarily reported from 122 cities in the United States, most of which have populations of 100,000 or more. A death is reported by the place of its occurrence and by the week that the death certificate was filed. Fetal deaths are not included. ** Totals include unknown ages. *** Partial counts for this city.

Provisional counts of the number of deaths registered in England and Wales, by age, sex, region and Index of Multiple Deprivation (IMD), in the latest weeks for which data are available.

This dataset, released November 2018, contains children and youth health statistics based on Children fully immunised at 1 year of age, 2 years of age and 5 years of age, 2017; HPV vaccine coverage: females aged 15 years in mid-2015, who received Dose 3 of the vaccine by 2017; HPV vaccine coverage: males aged 15 years in mid-2015, who received Dose 3 of the vaccine by 2017; HPV vaccine coverage: females aged 15 years in mid-2017, who received Dose 3 of the vaccine by 2018; HPV vaccine coverage: males aged 15 years in mid-2017, who received Dose 3 of the vaccine by 2018; Infant deaths, 2011 to 2015; Child mortality: Deaths of children aged 1 to 4 years, 2011 to 2015; Youth mortality: Deaths of persons aged 15 to 24 years, 2011 to 2015. The data is by Primary Health Network (PHN) 2017 geographic boundaries based on the 2016 Australian Statistical Geography Standard (ASGS).

There are 31 PHNs set up by the Australian Government. Each network is controlled by a board of medical professionals and advised by a clinical council and community advisory committee. The boundaries of the PHNs closely align with the Local Hospital Networks where possible.

For more information please see the data source notes on the data.

Source: Compiled by PHIDU based on data provided by the Australian Childhood Immunisation Register, MedicareAustralia, 2017; the National HPV Vaccination Program Register (NHVPR), February 2018 and November 2018; the ABS Census Estimated Resident Population (ERP) 2015 and 2017; and deaths data based on the 2011 to 2015 Cause of Death Unit Record Files supplied by the Australian Coordinating Registry and the Victorian Department of Justice, on behalf of the Registries of Births, Deaths and Marriages and the National Coronial Information System.

AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

This dataset, released March 2018, contains children and youth health statistics based on Children fully immunised at 1 year of age, 2 years of age and 5 years of age, 2015; HPV vaccine coverage: females aged 15 years in mid-2015, who received Dose 3 of the vaccine by 2017; HPV vaccine coverage: males aged 15 years in mid-2015, who received Dose 3 of the vaccine by 2017; Infant deaths, 2010 to 2014; Child mortality: Deaths of children aged 1 to 4 years, 2010 to 2014; Youth mortality: Deaths of persons aged 15 to 24 years, 2010 to 2014. The data is by Primary Health Network (PHN) 2017 geographic boundaries based on the 2016 Australian Statistical Geography Standard (ASGS).

There are 31 PHNs set up by the Australian Government. Each network is controlled by a board of medical professionals and advised by a clinical council and community advisory committee. The boundaries of the PHNs closely align with the Local Hospital Networks where possible.

For more information please see the data source notes on the data.

Source: Compiled by PHIDU based on data provided by the Australian Childhood Immunisation Register, MedicareAustralia, 2015; the National HPV Vaccination Program Register (NHVPR), February 2018; the ABS Census Estimated Resident Population (ERP) 2015; and deaths data based on the 2011 to 2015 Cause of Death Unit Record Files supplied by the Australian Coordinating Registry and the Victorian Department of Justice, on behalf of the Registries of Births, Deaths and Marriages and the National Coronial Information System.

AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

Abstract

The Kagera Health and Development Survey was conducted for the research project on “The Economic Impact of Fatal Adult Illness due to AIDS and Other Causes”, Mead Over (Principal Investigator, World Bank), Martha Ainsworth (Co-investigator, World Bank), and Godlike Koda, George Lwihula, Phare Mujinja, and Innocent Semali (Co-investigators, University of Dar es Salaam).

The primary objective of the Kagera Health and Development Survey (KHDS) was to estimate the economic impact of the death of prime-age adults on surviving household members. This impact was primarily measured as the difference in well-being between households with and without the death of a prime-age adult (15-50), over time. An additional hypothesis was that households in communities with high mortality rates might be less successful in coping with a prime-age adult death. Thus, the research design called for collecting extensive socioeconomic information from households with and without adult deaths in communities with high and low adult mortality rates. Data collected by the KHDS can be used to estimate the "direct costs” of illness and mortality in terms of out-of-pocket expenditures, the "indirect costs" in terms of foregone earnings of the patient, and the "coping costs” in terms of changes in the well-being of other household members and in the allocation on of time and resources within the household as these events unfold.

The KHDS was an economic survey. It did not attempt to measure knowledge, attitudes, behaviors or practices related to HIV infection or AIDS in households or communities. It also did not collect blood samples or attempt to measure HIV seroprevalence; this would have substantially affected the costs and complexity of the research and possibly the willingness of households to participate. Information on the cause of death in the KHDS household survey is based on the reports of surviving household members; the researchers maintained that household coping will respond to the perceived cause of death, irrespective of whether the deceased actually died of AIDS. Lastly, the KHDS did not attempt to measure the psycho-social impact of HIV infection or AIDS deaths.

OVERVIEW OF THE RESEARCH DESIGN

The research design called for a longitudinal survey of a sample of households, some of which would experience an adult death and some of which would not, some of them drawn from communities with high adult mortality rates, and some drawn from low-mortality communities.

The sampling frame for the survey was based on the 1988 Tanzania Census, which also provided information on adult death rates by ward within Kagera region. While it was possible to determine which communities had relatively high and low adult death rates from the census data, two additional problems arose that led to the decision for a stratified sample of households based on multiple criteria:

• First, despite the high rates of HIV infection in Kagera and the large number of deaths over time due to AIDS, the death of a prime-age adult is still a relatively rare event over a short time period. This meant that a very large sample would have had to be selected in order to ensure that the survey could interview enough families suffering our about to suffer the death of a prime-age adult.

• Second, HIV prevalence and adult mortality rates in Kagera were geographically concentrated and thus strongly correlated with different climates and cropping patterns. The highest rural HIV infection rates were in the northeast (10% in Bukoba Rural and Muleba districts and 24% in the town of Bukoba), where tree crops (bananas, coffee) were predominant, while the lowest rates were in the south and west (0.4% in Ngara and Biharamulo districts), where perennial crops and livestock are more common (Killewo and others 1990). A survey design stratified only on mortality rates might confound the effects of high mortality with different agricultural, soil, and rainfall patterns. Thus, the sample of households was selected from a stratified random sample of communities from the 1988 census (stratified on agroclimatic zone and adult mortality rate). Within communities, the household sample was stratified according to the anticipated risk of each household of suffering a prime-age adult death. Households were classified as “high-risk” or “low-risk”, based on information obtained from a house-to-house enumeration of all selected communities.

One additional concern was that the high mortality of households might lead to attrition from the sample that is systematically related to household coping. For example, if out-migration is an important coping behavior, then the most severely affected households might leave the sample and the analysis of the remaining households would understate the economic impact of adult deaths. For this reason, at the conclusion of the fieldwork, interviewers attempted to locate and interview all of the individuals who were members of households that dropped out of the longitudinal survey between the first and last interviews, and who were still resident in the region. Individuals were given a specially designed “follow-up questionnaire” that included much of the individual information collected in the household questionnaire, plus information on the reason for leaving the sample and the characteristics of the household were they were now residing.

The final longitudinal household survey followed 816 households at 6-7 month intervals, over a 24-month period from 1991-94. The 816 households were selected from 51 “clusters” of 16 households each located in 49 villages or urban areas representing four economic zones of all districts in Kagera region and, within each zone, representing areas with both high and low adult mortality.

Because household coping behavior is conditioned on local prices, services, and available programs, the KHDS also collected data from the communities from which households were drawn, local markets, the nearest source of modern medical care, and all of the primary schools in the community. This information was collected longitudinally, with the exception of a questionnaire for traditional healers, which was administered only once. While households were drawn from a stratified random sample of households, the health facilities, schools, markets and healers interviewed represent those closest to each community and thus are not random samples that are statistically representative of Kagera facilities.

The panel survey was conducted in a total of five waves.

• Wave 1 September 1991 - May 1992
• Wave 2 April 1992 - November 1992
• Wave 3 November 1992 - May 1993
• Wave 4 June 1993 - January 1994
• Wave 5 - 2004

Geographic coverage

Kagera region of Tanzania

Analysis unit

• Households
• Individuals
• Community

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE DESIGN AND SELECTION

Qualitative studies of small samples of households can point to hypotheses about the ways in which fatal adult illness affects households. However, policymakers need to know which households are suffering the most, the size of the impact, the extent to which they suffer more than other households in a poor country, and the potential costs and effects of assistance programs. For this purpose, the sample of households must be representative of the population, a random sample for which the probability of selecting each household from the whole population is known.

The KHDS used a random sample that was stratified geographically and according to several measures of adult mortality risk. This strategy allowed the team to ensure an adequate number of households with an adult death in the sample while retaining the ability to extrapolate the results to the entire population. The results from the household survey show that stratification of the sample on mortality risk at both the community and household level proved to be worthwhile. Among the 816 households in the original sample that began the survey in the first passage, 91 had an adult death in the course of the survey—more than three times the expected number (25) had the households been drawn at random with no stratification. The 816 households that began the survey in the first passage were observed, on average, for 1.6 years, generating a total of 1,322.7 years of observation. The average probability of an adult death per household per year, according to the 1988 Tanzania Census, is 0.0188. Thus, the expected number of deaths from a random sample of 816 households observed for 1.6 years is 25. Because households were added to the sample to compensate for attrition, a total of 918 households were eventually interviewed at least once. Between the first and last interview, 102 of these households had an adult death, compared to 27 households that would have been expected to have a death from from a non-stratified sample.

A. THE TWO-STAGE STRATIFIED RANDOM SAMPLING PROCEDURE

The KHDS household sample was drawn in two stages, with stratification based on geography in the first stage and mortality risk in both stages.

1. First Stage: Selection of communities and clusters

In the first stage of selecting the sample, the 550 primary sampling units (PSUs) in Kagera region were classified according to eight strata defined over four agronomic zones and, within each zone, the level of adult mortality (high and low). A PSU is a geographical area delineated by the 1988 Tanzanian Census that usually corresponds to a community or, in the case of a town, to a neighborhood. Clusters of households were drawn randomly from the PSUs in each stratum, with a probability of selection proportional to the size of the PSU.

a) Classification of communities by sampling stratum

The four agronomic zones are: - Tree Crop

This dataset, released July 2018, contains children and youth health statistics based on Children fully immunised at 1 year of age, 2 years of age and 5 years of age, 2015; HPV vaccine coverage: females aged 15 years in mid-2015, who received Dose 3 of the vaccine by 2017; HPV vaccine coverage: males aged 15 years in mid-2015, who received Dose 3 of the vaccine by 2017; Infant deaths, 2011 to 2015; Child mortality: Deaths of children aged 1 to 4 years, 2011 to 2015; Youth mortality: Deaths of persons aged 15 to 24 years, 2011 to 2015. The data is by Primary Health Network (PHN) 2017 geographic boundaries based on the 2016 Australian Statistical Geography Standard (ASGS).

There are 31 PHNs set up by the Australian Government. Each network is controlled by a board of medical professionals and advised by a clinical council and community advisory committee. The boundaries of the PHNs closely align with the Local Hospital Networks where possible.

For more information please see the data source notes on the data.

Source: Compiled by PHIDU based on data provided by the Australian Childhood Immunisation Register, MedicareAustralia, 2015; the National HPV Vaccination Program Register (NHVPR), February 2018; the ABS Census Estimated Resident Population (ERP) 2015; and deaths data based on the 2011 to 2015 Cause of Death Unit Record Files supplied by the Australian Coordinating Registry and the Victorian Department of Justice, on behalf of the Registries of Births, Deaths and Marriages and the National Coronial Information System.

AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

Since the 1950s, the suicide rate in the United States has been significantly higher among men than women. In 2022, the suicide rate among men was almost four times higher than that of women. However, the rate of suicide for both men and women has increased gradually over the past couple of decades. Facts on suicide in the United States In 2022, the rate of suicide death in the United States was around 14 per 100,000 population. The suicide rate in the U.S. has generally increased since the year 2000, with the highest rates ever recorded in the years 2018 and 2022. In the United States, death rates from suicide are highest among those aged 45 to 64 years and lowest among younger adults aged 15 to 24. The states with the highest rates of suicide are Montana, Alaska, and Wyoming, while New Jersey and Massachusetts have the lowest rates. Suicide among men In 2023, around 4.5 percent of men in the United States reported having serious thoughts of suicide in the past year. Although this rate is lower than that of women, men still have a higher rate of suicide death than women. One reason for this may have to do with the method of suicide. Although firearms account for the largest share of suicide deaths among both men and women, firearms account for almost 60 percent of all suicides among men and just 35 percent among women. Suffocation and poisoning are the other most common methods of suicide among women, with the chances of surviving a suicide attempt from these methods being much higher than surviving an attempt by firearm. The age group with the highest rate of suicide death among men is by far those aged 75 years and over.

The indicator measures the standardised death rate of tuberculosis, HIV and hepatitis (International Classification of Diseases (ICD) codes A15-A19_B90, B15-B19_B942 and B20-B24). The rate is calculated by dividing the number of people dying due to selected communicable diseases by the total population. Data on causes of death (COD) refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. The data are presented as standardised death rates, meaning they are adjusted to a standard age distribution in order to measure death rates independently of different age structures of populations. This approach improves comparability over time and between countries. The standardised death rates used here are calculated on the basis of the standard European population referring to the residents of the countries.

Find data on deaths of Massachusetts residents. Information is obtained from death certificates received by the Registry of Vital Records and Statistics.

Abstract

Noncommunicable diseases are the top cause of deaths. In 2008, more than 36 million people worldwide died of such diseases. Ninety per cent of those lived in low-income and middle-income countries.WHO Maps Noncommunicable Disease Trends in All Countries The STEPS Noncommunicable Disease Risk Factor Survey, part of the STEPwise approach to surveillance (STEPS) Adult Risk Factor Surveillance project by the World Health Organization (WHO), is a survey methodology to help countries begin to develop their own surveillance system to monitor and fight against noncommunicable diseases. The methodology prescribes three steps—questionnaire, physical measurements, and biochemical measurements. The steps consist of core items, core variables, and optional modules. Core topics covered by most surveys are demographics, health status, and health behaviors. These provide data on socioeconomic risk factors and metabolic, nutritional, and lifestyle risk factors. Details may differ from country to country and from year to year.

The Federated States of Micronesia (Chuuk) NCD STEPS survey provides the baseline assessment of the risk factors of noncommunicable diseases (NCDs) and their associated risk factors among Chuuk Islanders. The key objectives of the NCD STEPS survey were: - To document the prevalence and magnitude of key NCDs among adults - To document the prevalence and magnitude of major modifiable risk factors for NCDs including tobacco use, betel nut use, harmful use of alcohol, poor eating patterns, physical inactivity, obesity, high blood pressure, raised blood glucose and cholesterol levels - To compare NCDs and their risk factors across different age groups and between men and women.

Geographic coverage

The State of Chuuk, FSM

Analysis unit

Household Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The STEPS guidelines require a minimum sample size of 2000 participants, with at least 300 participants in each of 10 age-gender categories. The study randomly selected and invited 3,000 Chuuk Islanders aged 15-64 years to participate in the survey.The sample size was 2,831, and the sample comprised 2,034 people in the age group 25-64 and 797 people in the age group 15-24. Thirty precent of the sample aged 25-64 was randomly selected to participate in STEP 3 .

Mode of data collection

Face-to-face [f2f]

Research instrument

With the technical assistance of the FSM Census Office, the FSM (Chuuk) STEPS survey followed a sequential three-step process as follows : Step 1: A questionnaire-based (interview) survey on tobacco use, betel nut use, alcohol drinking, fruit and vegetable consumption, and physical activity. Step 2: Physiological measures of blood pressure, height, weight, hip and waist circumference. Step 3: Biochemical measures of fasting blood glucose, total cholesterol and triglycerides.

Similar to other STEPS surveys conducted in the Pacific region, the Chuuk survey collected core information across all three steps. STEPS standardized survey methodology was followed. This approach ensures that Chuuk has available populationwide and representative data for between-country comparisons as well as within-country comparisons. In future surveys, Chuuk could add more questions or measurements to the core questions, depending on local needs. A copy of the questionnaire used in the FSM (Chuuk) STEP Survey is provided as related materials.

Cleaning operations

Data entry was conducted by the survey staff at the Ministry of Health office using the EpiData software configured for double data entry function. With support from the Division of Pacific Technical Support, WPRO/WHO Office in Suva, WHO Office in Geneva performed final data cleaning, data weighting, and analysis. Data analyses were conducted using the EpiInfo 2002 Version 3.5.1. The Division of Pacific Technical Support, WPRO/WHO Office in Suva compiled the whole Data Book.

Response rate

A total of 2,831 individuals participated (response rate of 94.4%)

Data appraisal

Submitted questionnaires were checked randomly by staff to assess overall quality of data collection and completeness.