Demographic Trends and Health Outcomes in the U.S

Inequalities,Risk Factors and Access to Care

By Data Society [source]

About this dataset

This dataset contains key demographic, health status indicators and leading cause of death data to help us understand the current trends and health outcomes in communities across the United States. By looking at this data, it can be seen how different states, counties and populations have changed over time. With this data we can analyze levels of national health services use such as vaccination rates or mammography rates; review leading causes of death to create public policy initiatives; as well as identify risk factors for specific conditions that may be associated with certain populations or regions. The information from these files includes State FIPS Code, County FIPS Code, CHSI County Name, CHSI State Name, CHSI State Abbreviation, Influenza B (FluB) report count & expected cases rate per 100K population , Hepatitis A (HepA) Report Count & expected cases rate per 100K population , Hepatitis B (HepB) Report Count & expected cases rate per 100K population , Measles (Meas) Report Count & expected cases rate per 100K population , Pertussis(Pert) Report Count & expected case rate per 100K population , CRS report count & expected case rate per 100K population , Syphilis report count and expected case rate per 100k popuation. We also look at measures related to preventive care services such as Pap smear screen among women aged 18-64 years old check lower/upper confidence intervals seperately ; Mammogram checks among women aged 40-64 years old specified lower/upper conifence intervals separetly ; Colonosopy/ Proctoscpushy among men aged 50+ measured in lower/upper limits ; Pneumonia Vaccination amongst 65+ with loewr/upper confidence level detail Additionally we have some interesting trend indicating variables like measures of birth adn death which includes general fertility ratye ; Teen Birth Rate by Mother's age group etc Summary Measures covers mortality trend following life expectancy by sex&age categories Vressionable populations access info gives us insight into disablilty ratio + access to envtiromental issues due to poor quality housing facilities Finally Risk Factors cover speicfic hoslitic condtiions suchs asthma diagnosis prevelance cancer diabetes alcholic abuse smoking trends All these information give a good understanding on Healthy People 2020 target setings demograpihcally speaking hence will aid is generating more evience backed policies

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What the Dataset Contains

This dataset contains valuable information about public health relevant to each county in the United States, broken down into 9 indicator domains: Demographics, Leading Causes of Death, Summary Measures of Health, Measures of Birth and Death Rates, Relative Health Importance, Vulnerable Populations and Environmental Health Conditions, Preventive Services Use Data from BRFSS Survey System Data , Risk Factors and Access to Care/Health Insurance Coverage & State Developed Types of Measurements such as CRS with Multiple Categories Identified for Each Type . The data includes indicators such as percentages or rates for influenza (FLU), hepatitis (HepA/B), measles(MEAS) pertussis(PERT), syphilis(Syphilis) , cervical cancer (CI_Min_Pap_Smear - CI_Max\Pap \Smear), breast cancer (CI\Min Mammogram - CI \Max \Mammogram ) proctoscopy (CI Min Proctoscopy - CI Max Proctoscopy ), pneumococcal vaccinations (Ci min Pneumo Vax - Ci max Pneumo Vax )and flu vaccinations (Ci min Flu Vac - Ci Max Flu Vac). Additionally , it provides information on leading causes of death at both county levels & national level including age-adjusted mortality rates due to suicide among teens aged between 15-19 yrs per 100000 population etc.. Furthermore , summary measures such as age adjusted percentage who consider their physical health fair or poor are provided; vulnerable populations related indicators like relative importance score for disabled adults ; preventive service use related ones ranging from self reported vaccination coverage among men40-64 yrs old against hepatitis B virus etc...

Getting Started With The Dataset

To get started with exploring this dataset first your need to understand what each column in the table represents: State FIPS Code identifies a unique identifier used by various US government agencies which denote states . County FIPS code denotes counties wi...

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.

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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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.

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

The Youth Risk Behavior Surveillance System (YRBSS) monitors 6 types of health-risk behaviors that contribute to the leading causes of death and disability among youth and adults, including: behaviors that contribute to unintentional injuries and violence; sexual behaviors that contribute to unintended pregnancy and sexually transmitted diseases (STDs), including HIV infection; alcohol and other drug use; tobacco use; unhealthy dietary behaviors; inadequate physical activity. YRBSS also measures the prevalence of obesity and asthma among youth and young adults. YRBSS includes a national school-based survey conducted by CDC and state, territorial, tribal, and local surveys conducted by state, territorial, and local education and health agencies and tribal governments.

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

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.

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)

IntroductionSuicide is the leading cause of death among Korean adolescents. Suicide has been found to be associated with body mass index (BMI), height, and subjective body image among adults, but investigations of these associations among adolescents are limited. Thus, we aimed to examine to what extent suicide ideation is associated with height, BMI, and subjective body image among Korean adolescents.MethodsThis study examined the data of 6,261 adolescents, selected from a nationally representative survey. The participants were divided into subgroups by sex, suicide ideation, and subjective body image. Logistic regression analyses were performed to examine the association of suicide ideation with height, BMI, and subjective body image.ResultsThe proportion of perceived obesity was high in the total sample; the height Z-score was lower for the group with suicide ideation than the group without suicide ideation; the height Z-scores were also lower for female participants with suicide ideation than those female participants without suicide ideation. The proportions of depressed mood, suicide ideation, and suicide attempts were higher among the total sample and female participants with perceived obesity than among those with a normal body image. On logistic regression, perceived obesity was positively associated with suicide ideation even after adjusting for age, height Z-score, weight Z-score, and depressed mood, whereas height Z-score was negatively associated with suicide ideation. These relationships were more prominent among female participants than among male participants.ConclusionLow height and perceived obesity, not real obesity, are associated with suicide ideation among Korean adolescents. These findings indicate that the need for an integrated approach to growth, body image, and suicide in adolescents is warranted.

Content

The Youth Risk Behavior Surveillance System (YRBSS) monitors six types of health-risk behaviors that contribute to the leading causes of death and disability among youth and adults. This file contains state-level results for 13 tobacco-use variables by sex and grade for 2013.

Context

This is a dataset hosted by the Centers for Disease Control and Prevention. The organization has an open data platform found here and they update their information according the amount of data that is brought in. Explore CDC Data using Kaggle and all of the data sources available through the CDC organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.

Cover photo by Riley McCullough on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

The Youth Risk Behavior Surveillance System (YRBSS) monitors six categories of health-related behaviors that contribute to the leading causes of death and disability among youth and adults, including behaviors that contribute to unintentional injuries and violence; sexual behaviors related to unintended pregnancy and sexually transmitted diseases, including HIV infection; alcohol and other drug use; tobacco use; unhealthy dietary behaviors; and inadequate physical activity. YRBSS also measures the prevalence of obesity and asthma and other health-related behaviors plus sexual identity and sex of sexual contacts. YRBSS includes a national school-based survey conducted by CDC and state, territorial, tribal, and local surveys conducted by state, territorial, and local education and health agencies and tribal governments.

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

A quarter of the global human population is estimated to be latently infected by Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB). TB remains the global leading cause of death by a single pathogen and ranks among the top-10 causes of overall global mortality. Current immunodiagnostic tests cannot discriminate between latent, active and past TB, nor predict progression of latent infection to active disease. The only registered TB vaccine, Bacillus Calmette-Guérin (BCG), does not adequately prevent pulmonary TB in adolescents and adults, thus permitting continued TB-transmission. Several Mtb proteins, mostly discovered through IFN-γ centered approaches, have been proposed as targets for new TB-diagnostic tests or -vaccines. Recently, however, we identified novel Mtb antigens capable of eliciting multiple cytokines, including antigens that did not induce IFN-γ but several other cytokines. These antigens had been selected based on high Mtb gene-expression in the lung in vivo, and have been termed in vivo expressed (IVE-TB) antigens. Here, we extend and validate our previous findings in an independent Southern European cohort, consisting of adults and adolescents with either LTBI or TB. Our results confirm that responses to IVE-TB antigens, and also DosR-regulon and Rpf stage-specific Mtb antigens are marked by multiple cytokines, including strong responses, such as for TNF-α, in the absence of detectable IFN-γ production. Except for TNF-α, the magnitude of those responses were significantly higher in LTBI subjects. Additional unbiased analyses of high dimensional flow-cytometry data revealed that TNF-α+ cells responding to Mtb antigens comprised 17 highly heterogeneous cell types. Among these 17 TNF-α+ cells clusters identified, those with CD8+TEMRA or CD8+CD4+ phenotypes, defined by the expression of multiple intracellular markers, were the most prominent in adult LTBI, while CD14+ TNF-α+ myeloid-like clusters were mostly abundant in adolescent LTBI. Our findings, although limited to a small cohort, stress the importance of assessing broader immune responses than IFN-γ alone in Mtb antigen discovery as well as the importance of screening individuals of different age groups. In addition, our results provide proof of concept showing how unbiased multidimensional multiparametric cell subset analysis can identify unanticipated blood cell subsets that could play a role in the immune response against Mtb.

The Youth Risk Behavior Surveillance System (YRBSS) monitors six types of health-risk behaviors that contribute to the leading causes of death and disability among youth and adults. This file contains state-level results for 13 tobacco-use variables by sex and grade for 2013.

Abstract The objective of this article is to analyze the detention of youth offenders involved in the juvenile justice system in the State of Rio Grande do Sul (FASE-RS), the reason for detention, and mortality among former young offenders. We conducted an observational study with youth offenders discharged from facilities run by FASE-RS in Porto Alegre between 2002 and 2012 (n = 8,290). We collected the following information: date of discharge, offence committed, skin color, gender, and duration of detention. The data was crosschecked with data from the state’s Mortality Information System to identify deaths among former young offenders up to December 2014. The predominant offences were crimes against property and drug-related crimes. The large majority of youth detained for drug-related offences were admitted for offences related to drug trafficking. There was a seven-fold increase in drug-related offences over the period. Death was associated (p3). The sample’s mortality rate was high and the main cause of death was homicide. The findings suggest that young offenders face high levels of psychosocial vulnerability. There was an association between minor crimes and high rates of mortality among former young offenders.

Analysis of ‘YRBS State Tobacco Variables 2013 - v2’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/a8953f2c-072e-4ce3-ac8a-389fa807e14c on 30 September 2021.

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

The Youth Risk Behavior Surveillance System (YRBSS) monitors six types of health-risk behaviors that contribute to the leading causes of death and disability among youth and adults. This file contains state-level results for 13 tobacco-use variables by sex and grade for 2013.

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

Firearms are the leading cause of death for minors in the United States and US gun culture is often discussed as a reason behind the prevalence of school shootings. Yet, few studies systematically analyze if there is a connection between the two: Do school shooters show a distinct gun culture? This article studies gun culture in action in school shootings. It studies if school shooters show distinct meanings and practices around firearms prior to the shooting, as well as patterns in access to firearms. To do so, I analyze a full sample of US school shootings. Relying on publicly available court, police, and media data, I combine qualitative in-depth analyses with cross-case comparisons and descriptive statistics. Findings suggest most school shooters come from a social setting in which firearms are a crucial leisure activity and hold meanings of affection, friendship, and bonding. These meanings translate into practices: all school shooters had easy access to the firearms they used for the shooting. Findings contribute to research on firearms and youth violence, public health, as well as the sociology of culture.

BackgroundA personalised approach to the treatment of acute myeloid leukemia (AML) in children and adolescents, as well as the development of supportive therapies, has significantly improved survival. Despite this, some patients still die before starting treatment or in an early phase of therapy before achieving remission. The study analysed the frequency, clinical features and risk factors for early deaths (ED) and treatment related deaths (TRD) of children and adolescents with AML.MethodsFrom January 2005 to November 2023, 646 children with AML treated in the centers of the Polish Pediatric Leukemia and Lymphoma Study Group according to three subsequent therapeutic protocols were evaluated: AML-BFM 2004 Interim (385 children), AML-BFM 2012 Registry (131 children) and AML-BFM 2019 (130 children).ResultsOut of 646 children, early death occurred in 30 children, including 15 girls. The median age was 10.7 years (1 day to 18 years). More than half of the patients (53%) were diagnosed with acute myelomonocytic leukemia (M5) and 13% with acute promyelocytic leukemia (M3). The ED rate for the three consecutive AML-BFM protocols was 4.9% vs. 5.3% vs. 3.1%, respectively. In 19 patients, death occurred before the 15th day of treatment, in 11 between the 15th and 42nd day. The most common cause of death before the 15th day (ED15) was leukostasis and bleeding, whereas between the 15th and 42nd day (ED15-42), infections, mainly bacterial sepsis. A significant association was found between ED15 and high leukocyte count (>10 × 109/L), M3 leukemia (p < 0.001), and ED15-42 and age <1 year (p = 0.029). In the univariate analysis only initial high leukocyte count >100 × 109/L, was a significant predictor of early death. The overall TRD for the entire study period was 3.4%. The main cause of death were infections, mainly bacterial sepsis (10 children out of 22, 45.4%).ConclusionsHyperleukocytosis remains significant factor of early mortality in patients with AML, despite the introduction of various cytoreductive methods. Infections are still the main cause of treatment related deaths. A more individualized approach by using new targeted drugs may be the therapeutic option of choice in the future.