In 2023, the leading cause of death among young adults in the United States aged 20 to 24 was accidents or unintentional injuries. At that time, there were 42.1 deaths per 100,000 population among those aged 20 to 24 years due to accidents. Suicide was the second leading cause of death among adults in this age group, with 17.3 deaths 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.

As of 2023, the third leading cause of death among teenagers aged 15 to 19 years in the United States was intentional self-harm or suicide, contributing to around 17 percent of deaths among this age group. The leading cause of death at that time was unintentional injuries, contributing to around 38.6 percent of deaths, while 20.7 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 2023, New Mexico had the highest rate of suicides among U.S. teenagers, with around 28 deaths per 100,000 teenagers, followed by Idaho with a rate of 22.5 per 100,000. The states with the lowest death rates among adolescents are New Jersey and New York. 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.

Abstract Mortality indicators for Brazilians aged between 10 and 24 years old were analyzed. Data were obtained from the Global Burden of Disease (GBD) 2019 Study, and absolute numbers, proportion of deaths and specific mortality rates from 1990 to 2019 were analyzed, according to age group (10 to 14, 15 to 19 and 20 to 24 years), sex and causes of death for Brazil, regions and Brazilian states. There was a reduction of 11.8% in the mortality rates of individuals aged between 10 and 24 years in the investigated period. In 2019, there were 13,459 deaths among women, corresponding to a reduction of 30.8% in the period. Among men there were 39,362 deaths, a reduction of only 6.2%. There was an increase in mortality rates in the North and Northeast and a reduction in the Southeast and South states. In 2019, the leading cause of death among women was traffic injuries, followed by interpersonal violence, maternal deaths and suicide. For men, interpersonal violence was the leading cause of death, especially in the Northeast, followed by traffic injuries, suicide and drowning. Police executions moved from 77th to 6th place. This study revealed inequalities in the mortality of adolescents and young adults according to sex, causes of death, regions and Brazilian states.

Content

Age-adjusted Death Rates for Selected Major Causes of Death: United States, 1900-2013

Age adjusting rates

is a way to make fairer comparisons between groups with different age distributions. For example, a county having a higher percentage of elderly people may have a higher rate of death or hospitalization than a county with a younger population, merely because the elderly are more likely to die or be hospitalized. (The same distortion can happen when comparing races, genders, or time periods.) Age adjustment can make the different groups more comparable. A "standard" population distribution is used to adjust death and hospitalization rates. The age-adjusted rates are rates that would have existed if the population under study had the same age distribution as the "standard" population. Therefore, they are summary measures adjusted for differences in age distributions.

Acknowledgements

Scrap data from data.gov

In 2022, the leading cause of death among people aged 10 to 24 years old in South Korea was suicide, resulting in approximately **** 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.

BackgroundPatients with atrial fibrillation are known to have a high risk of mortality. There is a paucity of population-based studies about the impact of atrial fibrillation on the mortality risk stratified by age, sex, and detailed causes of death.MethodsA total of 15,411 patients with atrial fibrillation from the Korean National Health Insurance Service-National Sample Cohort were enrolled, and causes of death were identified according to codes of the 10th revision of the International Classification of Diseases.ResultsFrom 2002 to 2013, a total of 4,479 (29%) deaths were confirmed, and the crude mortality rate for all-cause death was 63.3 per 1,000 patient-years. Patients with atrial fibrillation had a 3.7-fold increased risk of all-cause death compared with the general population. The standardized mortality ratio for all-cause death was the highest in young patients and decreased with increasing age (standardized mortality ratio 21.93, 95% confidence interval 7.60–26.26 in patients aged <20 years; standardized mortality ratio 2.77, 95% confidence interval 2.63–2.91 in patients aged ≥80 years). Women with atrial fibrillation exhibited a greater excess mortality risk than men (standardized mortality ratio 3.81, 95% confidence interval 3.65–3.98 in women; standardized mortality ratio 3.35, 95% confidence interval 3.21–3.48 in men). Cardiovascular disease was the leading cause of death (38.5%), and cerebral infarction was the most common specific disease. Patients with atrial fibrillation had an about 5 times increased risk of death due to cardiovascular disease compared with the general population.ConclusionsPatients with atrial fibrillation had a 4 times increased risk of mortality compared with the general population. However, the impact of atrial fibrillation on mortality decreased with age and in men. Cerebral infarction was the most common cause of death, and more attention should be paid to reducing the risk of stroke.

Registered leading causes of death by age, sex and country, UK, 2001 to 2018

BackgroundGlobal and regional projections of mortality and burden of disease by cause for the years 2000, 2010, and 2030 were published by Murray and Lopez in 1996 as part of the Global Burden of Disease project. These projections, which are based on 1990 data, continue to be widely quoted, although they are substantially outdated; in particular, they substantially underestimated the spread of HIV/AIDS. To address the widespread demand for information on likely future trends in global health, and thereby to support international health policy and priority setting, we have prepared new projections of mortality and burden of disease to 2030 starting from World Health Organization estimates of mortality and burden of disease for 2002. This paper describes the methods, assumptions, input data, and results. Methods and FindingsRelatively simple models were used to project future health trends under three scenarios—baseline, optimistic, and pessimistic—based largely on projections of economic and social development, and using the historically observed relationships of these with cause-specific mortality rates. Data inputs have been updated to take account of the greater availability of death registration data and the latest available projections for HIV/AIDS, income, human capital, tobacco smoking, body mass index, and other inputs. In all three scenarios there is a dramatic shift in the distribution of deaths from younger to older ages and from communicable, maternal, perinatal, and nutritional causes to noncommunicable disease causes. The risk of death for children younger than 5 y is projected to fall by nearly 50% in the baseline scenario between 2002 and 2030. The proportion of deaths due to noncommunicable disease is projected to rise from 59% in 2002 to 69% in 2030. Global HIV/AIDS deaths are projected to rise from 2.8 million in 2002 to 6.5 million in 2030 under the baseline scenario, which assumes coverage with antiretroviral drugs reaches 80% by 2012. Under the optimistic scenario, which also assumes increased prevention activity, HIV/AIDS deaths are projected to drop to 3.7 million in 2030. Total tobacco-attributable deaths are projected to rise from 5.4 million in 2005 to 6.4 million in 2015 and 8.3 million in 2030 under our baseline scenario. Tobacco is projected to kill 50% more people in 2015 than HIV/AIDS, and to be responsible for 10% of all deaths globally. The three leading causes of burden of disease in 2030 are projected to include HIV/AIDS, unipolar depressive disorders, and ischaemic heart disease in the baseline and pessimistic scenarios. Road traffic accidents are the fourth leading cause in the baseline scenario, and the third leading cause ahead of ischaemic heart disease in the optimistic scenario. Under the baseline scenario, HIV/AIDS becomes the leading cause of burden of disease in middle- and low-income countries by 2015. ConclusionsThese projections represent a set of three visions of the future for population health, based on certain explicit assumptions. Despite the wide uncertainty ranges around future projections, they enable us to appreciate better the implications for health and health policy of currently observed trends, and the likely impact of fairly certain future trends, such as the ageing of the population, the continued spread of HIV/AIDS in many regions, and the continuation of the epidemiological transition in developing countries. The results depend strongly on the assumption that future mortality trends in poor countries will have a relationship to economic and social development similar to those that have occurred in the higher-income countries.

Abstract

Explore global statistics on a subject that claims 800,000 lives each year.

About this dataset

Context

Suicide is a major cause of death in the world, claiming around 800,000 lives each year. It is ranked as the 14th leading cause of death worldwide as of 2017 and on average men are twice as likely to fall victim to it. It also one of the leading causes of death on young people and older people are at a higher risk as well. Source

Notes

This dataset contains data from 200+ countries on the topic of suicide and mental health infrastructure. It was created by extracting the latest data from WHO and combining it into a single dataset. Variables available range from Country, Sex, Mental health infrastructure and personnel and finally Suicide Rate (amount of suicides per 100k people). Note that the suicide rate is age-standardized, as to not bias comparisons between countries with different age compositions.

How to use

• Explore Suicide rates and their associated trends, as well as the effects of infrastructure and personnel on the suicide rates.
• Forecast suicide rates

Acknowledgements

If you use this dataset in your research, please credit the authors.

Citation

@misc{Global Health Observatory data repository, title={Mental Health}, url={https://apps.who.int/gho/data/node.main.MENTALHEALTH?lang=en}, journal={WHO} }

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CC BY NC SA IGO 3.0

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Introductionour objective was to analyze the trends in the leading causes of death among the pediatric population aged 1–19 years in Mexico and the United States (US) from 2000 to 2022. Methods. Data for Mexico were sourced from the National Institute of Statistics and Geography (INEGI), while the US data were extracted from the Centers for Disease Control and Prevention’s Wide-ranging Online Data for Epidemiologic Research (CDC-WONDER) databases.ResultsHomicide has been the leading cause of death since 2017 in Mexico and since 2019 in US youths aged 1–19. In Mexico, it reached 6.5 deaths per 100,000 people in 2022. Despite the overall pediatric mortality decline from 2000 to 2022 in both countries, the pediatric homicide rate has increased by 93.3 and 35.8% In Mexico and the US, respectively, and suicide by 86.6 and 36.9%. In both countries, death by firearm-related injuries had risen in a parallel sense. In the US, deaths by drug overdose and poisoning have increased by 314.8%.ConclusionDespite advancements in infant healthcare over the past two decades in Mexico, there remains a significant gap in the provision of healthcare services to the adolescent population. Addressing issues related to violence, mental health, and substance abuse through targeted public policies is imperative for both Mexico and the US, especially given their shared border region.

To: State, territorial, tribal, and local policymakers and administrators of agencies and programs focused on child, youth, and family health and well-being

Dear Colleagues,

Thank you for your work to support children, youth, and families. Populations served by Administration for Children and Families (ACF)-funded programs — including victims of trafficking or violence, those who are unhoused, and young people and families involved in the child welfare system — are often at particularly high risk for substance use and overdose. A variety of efforts are underway at the federal, state, and local levels to reduce overdose deaths. These efforts focus on stopping drugs from entering communities, providing life-saving resources, and preventing drug use before it starts. Initiatives across the country are already saving lives: the overdose death rate has declined over the past year but remains too high at 32.6 per 100,000 individuals.

Fentanyl, a powerful synthetic opioid, raises the risk of overdose deaths because even a tiny amount can be deadly. Young people are particularly at risk for fentanyl exposure, driven in part by widespread availability of counterfeit pills containing fentanyl that are marketed to youth through social media. While overdose deaths among teens have recently begun to decline, there were 6,696 deaths among adolescents and young adults in 2022 (the latest year with data available)[1], making unintentional drug overdose the second leading cause of death for youth ages 15—19 and the first leading cause of death among young adults ages 20-24.[2]

Often these deaths happen with others nearby and can be prevented when opioid overdose reversal medications, like naloxone, are administered in time. CDC’s State Unintentional Drug Overdose Reporting System dashboard shows that in all 30 jurisdictions with available data, 64.7% of drug overdose deaths had at least one potential opportunity for intervention.[3] Naloxone rapidly reverses an overdose and should be given to any person who shows signs of an opioid overdose or when an overdose is suspected. It can be given as a nasal spray. Studies show that naloxone administration reduces death rates and does not cause harm if used on a person who is not overdosing on opioids. States have different policies and regulations regarding naloxone distribution and administration. Forty-nine states and the District of Columbia have Good Samaritan laws protecting bystanders who aid at the scene of an overdose.[4]

ACF grant recipients and partners can play a critical role in reducing overdose deaths by taking the following actions:

Stop Overdose Now

(U.S. Centers for Disease Control and Prevention)

Integrating Harm Reduction Strategies into Services and Supports for Young Adults Experiencing Homelessness (PDF) (ACF)

Thank you for your dedication and partnership. If you have any questions, please contact your local public health department or state behavioral health agency. Together, we can meaningfully reduce overdose deaths in every community.

/s/

Meg Sullivan

Principal Deputy Assistant Secretary

[1] Products - Data Briefs - Number 491 - March 2024

[2] WISQARS Leading Causes of Death Visualization Tool

[3] SUDORS Dashboard: Fatal Drug Overdose Data | Overdose Prevention | CDC

[4] Based on 2024 report from the Legislative Analysis and Public Policy Association

(PDF). Note that the state of Kansas adopted protections as well following the publication of this report.

Metadata-only record linking to the original dataset. Open original dataset below.

Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve.

The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj.

The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 .

The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 .

The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed.

COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken down by race and ethnicity. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the COVID-19 update.

The following data show the number of COVID-19 cases and associated deaths per 100,000 population by race and ethnicity. Crude rates represent the total cases or deaths per 100,000 people. Age-adjusted rates consider the age of the person at diagnosis or death when estimating the rate and use a standardized population to provide a fair comparison between population groups with different age distributions. Age-adjustment is important in Connecticut as the median age of among the non-Hispanic white population is 47 years, whereas it is 34 years among non-Hispanic blacks, and 29 years among Hispanics. Because most non-Hispanic white residents who died were over 75 years of age, the age-adjusted rates are lower than the unadjusted rates. In contrast, Hispanic residents who died tend to be younger than 75 years of age which results in higher age-adjusted rates.

The population data used to calculate rates is based on the CT DPH population statistics for 2019, which is available online here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Population-Statistics. Prior to 5/10/2021, the population estimates from 2018 were used.

Rates are standardized to the 2000 US Millions Standard population (data available here: https://seer.cancer.gov/stdpopulations/). Standardization was done using 19 age groups (0, 1-4, 5-9, 10-14, ..., 80-84, 85 years and older). More information about direct standardization for age adjustment is available here: https://www.cdc.gov/nchs/data/statnt/statnt06rv.pdf

Categories are mutually exclusive. The category “multiracial” includes people who answered ‘yes’ to more than one race category. Counts may not add up to total case counts as data on race and ethnicity may be missing. Age adjusted rates calculated only for groups with more than 20 deaths. Abbreviation: NH=Non-Hispanic.

Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical examiner) using their best clinical judgment. Additionally, all COVID-19 deaths, including suspected or related, are required to be reported to OCME. On April 4, 2020, CT DPH and OCME released a joint memo to providers and facilities within Connecticut providing guidelines for certifying deaths due to COVID-19 that were consistent with the CDC’s guidelines and a reminder of the required reporting to OCME.25,26 As of July 1, 2021, OCME had reviewed every case reported and performed additional investigation on about one-third of reported deaths to better ascertain if COVID-19 did or did not cause or contribute to the death. Some of these investigations resulted in the OCME performing postmortem swabs for PCR testing on individuals whose deaths were suspected to be due to COVID-19, but antemortem diagnosis was unable to be made.31 The OCME issued or re-issued about 10% of COVID-19 death certificates and, when appropriate, removed COVID-19 from the death certificate. For standardization and tabulation of mortality statistics, written cause of death statements made by the certifiers on death certificates are sent to the National Center for Health Statistics (NCHS) at the CDC which assigns cause of death codes according to the International Causes of Disease 10th Revision (ICD-10) classification system.25,26 COVID-19 deaths in this report are defined as those for which the death certificate has an ICD-10 code of U07.1 as either a primary (underlying) or a contributing cause of death. More information on COVID-19 mortality can be found at the following link: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Mortality/Mortality-Statistics

Data are subject to future revision as reporting changes.

Starting in July 2020, this dataset will be updated every weekday.

Additional notes: A delay in the data pull schedule occurred on 06/23/2020. Data from 06/22/2020 was processed on 06/23/2020 at 3:30 PM. The normal data cycle resumed with the data for 06/23/2020.

A network outage on 05/19/2020 resulted in a change in the data pull schedule. Data from 5/19/2020 was processed on 05/20/2020 at 12:00 PM. Data from 5/20/2020 was processed on 5/20/2020 8:30 PM. The normal data cycle resumed on 05/20/2020 with the 8:30 PM data pull. As a result of the network outage, the timestamp on the datasets on the Open Data Portal differ from the timestamp in DPH's daily PDF reports.

Starting 5/10/2021, the date field will represent the date this data was updated on data.ct.gov. Previously the date the data was pulled by DPH was listed, which typically coincided with the date before the data was published on data.ct.gov. This change was made to standardize the COVID-19 data sets on data.ct.gov.

BackgroundOver 75% of the annual estimated 9.5 million deaths in India occur in the home, and the large majority of these do not have a certified cause. India and other developing countries urgently need reliable quantification of the causes of death. They also need better epidemiological evidence about the relevance of physical (such as blood pressure and obesity), behavioral (such as smoking, alcohol, HIV-1 risk taking, and immunization history), and biological (such as blood lipids and gene polymorphisms) measurements to the development of disease in individuals or disease rates in populations. We report here on the rationale, design, and implementation of the world's largest prospective study of the causes and correlates of mortality. Methods and FindingsWe will monitor nearly 14 million people in 2.4 million nationally representative Indian households (6.3 million people in 1.1 million households in the 1998–2003 sample frame and 7.6 million people in 1.3 million households in the 2004–2014 sample frame) for vital status and, if dead, the causes of death through a well-validated verbal autopsy (VA) instrument. About 300,000 deaths from 1998–2003 and some 700,000 deaths from 2004–2014 are expected; of these about 850,000 will be coded by two physicians to provide causes of death by gender, age, socioeconomic status, and geographical region. Pilot studies will evaluate the addition of physical and biological measurements, specifically dried blood spots. Preliminary results from over 35,000 deaths suggest that VA can ascertain the leading causes of death, reduce the misclassification of causes, and derive the probable underlying cause of death when it has not been reported. VA yields broad classification of the underlying causes in about 90% of deaths before age 70. In old age, however, the proportion of classifiable deaths is lower. By tracking underlying demographic denominators, the study permits quantification of absolute mortality rates. Household case-control, proportional mortality, and nested case-control methods permit quantification of risk factors. ConclusionsThis study will reliably document not only the underlying cause of child and adult deaths but also key risk factors (behavioral, physical, environmental, and eventually, genetic). It offers a globally replicable model for reliably estimating cause-specific mortality using VA and strengthens India's flagship mortality monitoring system. Despite the misclassification that is still expected, the new cause-of-death data will be substantially better than that available previously.

NOTE. RRfem, Relative risk for females compared with males; CI, confidence interval; χ2, chi-squared.aStatistics presented exclude deaths with undetermined cause (n = 174); of 238 NCD deaths, 13 ‘other’ NCDs are excluded from main cause of death analysis.bCD, communicable diseases (HIV, TB, malaria, other common infections).cHIV/TB is the combination of all deaths diagnosed with either TB or HIV as the cause of death.dSignificantly higher proportion of deaths in males, inverse RRmales presented [in brackets].

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

EMSIndicators:The number of individual patients administered naloxone by EMSThe number of naloxone administrations by EMSThe rate of EMS calls involving naloxone administrations per 10,000 residentsData Source:The Vermont Statewide Incident Reporting Network (SIREN) is a comprehensive electronic prehospital patient care data collection, analysis, and reporting system. EMS reporting serves several important functions, including legal documentation, quality improvement initiatives, billing, and evaluation of individual and agency performance measures.Law Enforcement Indicators:The Number of law enforcement responses to accidental opioid-related non-fatal overdosesData Source:The Drug Monitoring Initiative (DMI) was established by the Vermont Intelligence Center (VIC) in an effort to combat the opioid epidemic in Vermont. It serves as a repository of drug data for Vermont and manages overdose and seizure databases. Notes:Overdose data provided in this dashboard are derived from multiple sources and should be considered preliminary and therefore subject to change. Overdoses included are those that Vermont law enforcement responded to. Law enforcement personnel do not respond to every overdose, and therefore, the numbers in this report are not representative of all overdoses in the state. The overdoses included are limited to those that are suspected to have been caused, at least in part, by opioids. Inclusion is based on law enforcement's perception and representation in Records Management Systems (RMS). All Vermont law enforcement agencies are represented, with the exception of Norwich Police Department, Hartford Police Department, and Windsor Police Department, due to RMS access. Questions regarding this dataset can be directed to the Vermont Intelligence Center at dps.vicdrugs@vermont.gov.Overdoses Indicators:The number of accidental and undetermined opioid-related deathsThe number of accidental and undetermined opioid-related deaths with cocaine involvementThe percent of accidental and undetermined opioid-related deaths with cocaine involvementThe rate of accidental and undetermined opioid-related deathsThe rate of heroin nonfatal overdose per 10,000 ED visitsThe rate of opioid nonfatal overdose per 10,000 ED visitsThe rate of stimulant nonfatal overdose per 10,000 ED visitsData Source:Vermont requires towns to report all births, marriages, and deaths. These records, particularly birth and death records are used to study and monitor the health of a population. Deaths are reported via the Electronic Death Registration System. Vermont publishes annual Vital Statistics reports.The Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) captures and analyzes recent Emergency Department visit data for trends and signals of abnormal activity that may indicate the occurrence of significant public health events.Population Health Indicators:The percent of adolescents in grades 6-8 who used marijuana in the past 30 daysThe percent of adolescents in grades 9-12 who used marijuana in the past 30 daysThe percent of adolescents in grades 9-12 who drank any alcohol in the past 30 daysThe percent of adolescents in grades 9-12 who binge drank in the past 30 daysThe percent of adolescents in grades 9-12 who misused any prescription medications in the past 30 daysThe percent of adults who consumed alcohol in the past 30 daysThe percent of adults who binge drank in the past 30 daysThe percent of adults who used marijuana in the past 30 daysData Sources:The Vermont Youth Risk Behavior Survey (YRBS) is part of a national school-based surveillance system conducted by the Centers for Disease Control and Prevention (CDC). The YRBS monitors health risk behaviors that contribute to the leading causes of death and disability among youth and young adults.The Behavioral Risk Factor Surveillance System (BRFSS) is a telephone survey conducted annually among adults 18 and older. The Vermont BRFSS is completed by the Vermont Department of Health in collaboration with the Centers for Disease Control and Prevention (CDC).Notes:Prevalence estimates and trends for the 2021 Vermont YRBS were likely impacted by significant factors unique to 2021, including the COVID-19 pandemic and the delay of the survey administration period resulting in a younger population completing the survey. Students who participated in the 2021 YRBS may have had a different educational and social experience compared to previous participants. Disruptions, including remote learning, lack of social interactions, and extracurricular activities, are likely reflected in the survey results. As a result, no trend data is included in the 2021 report and caution should be used when interpreting and comparing the 2021 results to other years.The Vermont Department of Health (VDH) seeks to promote destigmatizing and equitable language. While the VDH uses the term "cannabis" to reflect updated terminology, the data sources referenced in this data brief use the term "marijuana" to refer to cannabis. Prescription Drugs Indicators:The average daily MMEThe average day's supplyThe average day's supply for opioid analgesic prescriptionsThe number of prescriptionsThe percent of the population receiving at least one prescriptionThe percent of prescriptionsThe proportion of opioid analgesic prescriptionsThe rate of prescriptions per 100 residentsData Source:The Vermont Prescription Monitoring System (VPMS) is an electronic data system that collects information on Schedule II-IV controlled substance prescriptions dispensed by pharmacies. VPMS proactively safeguards public health and safety while supporting the appropriate use of controlled substances. The program helps healthcare providers improve patient care. VPMS data is also a health statistics tool that is used to monitor statewide trends in the dispensing of prescriptions.Treatment Indicators:The number of times a new substance use disorder is diagnosed (Medicaid recipients index events)The number of times substance use disorder treatment is started within 14 days of diagnosis (Medicaid recipients initiation events)The number of times two or more treatment services are provided within 34 days of starting treatment (Medicaid recipients engagement events)The percent of times substance use disorder treatment is started within 14 days of diagnosis (Medicaid recipients initiation rate)The percent of times two or more treatment services are provided within 34 days of starting treatment (Medicaid recipients engagement rate)The MOUD treatment rate per 10,000 peopleThe number of people who received MOUD treatmentData Source:Vermont Medicaid ClaimsThe Vermont Prescription Monitoring System (VPMS)Substance Abuse Treatment Information System (SATIS)

This table contains the number of deaths in the population of the Netherlands by underlying cause of death (short list), sex and age-group (at time of death).

Since 2013 Statistics Netherlands is using Iris software for automatic coding for cause of death. This improved the international comparison of the data. The change in coding did cause a considerable shift in the statistic. Since 2013 the (yearly) ICD-10 updates are applied.

Data available from: 1950

Status of the figures: The figures up until 2023 are final, the figures of 2024 are provisional.

Changes as of July 3rd 2025: The provisional figures for 2024 have been added.

When will new figures be published? The aim is to publish the final figures of 2024 in the fourth quarter of 2025.

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

Belgian National Burden of Disease Study

Estimates of the burden of disease

Causes of death

Our estimates are based on the official causes of death database compiled by Statbel. We first map the ICD-10 codes of the underlying causes of death to the Global Burden of Disease cause list, consisting of 131 unique causes of deaths. Next, we perform a probabilistic redistribution of ill-defined deaths to specific causes, to obtain a specific cause of death for each deceased person.

Years of Life Lost

In addition to counting the number of deaths, we also calculate Years of Life Lost (YLLs) as a measure of premature mortality. YLLs correspond to the life expectancy at the age of death, and therefore give a higher weight to deaths occurring at younger ages. We calculate YLLs using the Global Burden of Disease reference life table, which represents the theoretical maximum number of years that people can expect to live.

Prevalence

Our estimates are based on the GBD cause list for morbidity by IHME. We first select for each of the 38 causes, the most suitable local data source as described in the protocol. Next, we calculate the prevalence by year, region, age, and sex, to obtain a prevalence for each of the included diseases.

Years Lived with Disability

In addition to calculating the number of prevalent cases, we also calculate Years Lived with Disability (YLDs) as a measure of morbidity. YLDs are calculated as the product of the number of prevalent cases with the disability weight (DW), averaged over the different health states of the disease. The DWs reflect the relative reduction in quality of life, on a scale from 0 (perfect health) to 1 (death). We calculate YLDs using the Global Burden of Disease DWs.

Disability-Adjusted Life Years

Disability-Adjusted Life Years (DALYs) are a measure of overall disease burden, representing the healthy life years lost due to morbidity and mortality. DALYs are calculated as the sum of YLLs and YLDs for each of the considered diseases.