Data on drug overdose death rates, by drug type and selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for critical information about measures, definitions, and changes over time. SOURCE: NCHS, National Vital Statistics System, numerator data from annual public-use Mortality Files; denominator data from U.S. Census Bureau national population estimates; and Murphy SL, Xu JQ, Kochanek KD, Arias E, Tejada-Vera B. Deaths: Final data for 2018. National Vital Statistics Reports; vol 69 no 13. Hyattsville, MD: National Center for Health Statistics.2021. Available from: https://www.cdc.gov/nchs/products/nvsr.htm. For more information on the National Vital Statistics System, see the corresponding Appendix entry at https://www.cdc.gov/nchs/data/hus/hus19-appendix-508.pdf.

For those interested in data on student drug addiction in 2024, several sources offer valuable datasets and statistics.

1. Kaggle Dataset: Kaggle hosts a specific dataset on student drug addiction. This dataset includes various attributes related to student demographics, substance use patterns, and associated behavioral factors. It's a useful resource for data analysis and machine learning projects focused on understanding drug addiction among students【5†source】.

2. National Survey on Drug Use and Health (NSDUH): This comprehensive survey provides detailed annual data on substance use and mental health across the United States, including among students. It covers a wide range of substances and demographic details, helping to track trends and the need for treatment services【6†source】【8†source】.

3. Monitoring the Future (MTF) Survey: Conducted by the National Institute on Drug Abuse (NIDA), this survey tracks drug and alcohol use and attitudes among American adolescents. It provides annual updates and is an excellent source for understanding trends in substance use among high school and college students【7†source】.

4. Australian Institute of Health and Welfare (AIHW): For those interested in a more global perspective, the AIHW offers data from the National Drug Strategy Household Survey, which includes information on youth and young adult drug use in Australia. This can be useful for comparative studies【10†source】.

For detailed datasets and further analysis, you can explore these resources directly:

• Kaggle Student Drugs Addiction Dataset
• NSDUH Data
• Monitoring the Future
• AIHW Drug Survey

The National Household Survey on Drug Abuse (NHSDA) series measures the prevalence and correlates of drug use in the United States. The surveys are designed to provide quarterly, as well as annual, estimates. Information is provided on the use of illicit drugs, alcohol, and tobacco among members of United States households aged 12 and older. Questions include age at first use as well as lifetime, annual, and past-month usage for the following drug classes: marijuana, cocaine (and crack), hallucinogens, heroin, inhalants, alcohol, tobacco, and nonmedical use of prescription drugs, including psychotherapeutics. Respondents were also asked about personal and family income sources and amounts, substance abuse treatment history, illegal activities, problems resulting from the use of drugs, need for treatment for drug or alcohol use, criminal record, and needle-sharing. Questions on mental health and access to care, which were introduced in the 1994-B questionnaire (see NATIONAL HOUSEHOLD SURVEY ON DRUG ABUSE, 1994), were retained in this administration of the survey. Also retained was the section on risk/availability of drugs that was reintroduced in 1996, and sections on driving behavior and personal behavior were added (see NATIONAL HOUSEHOLD SURVEY ON DRUG ABUSE, 1996). The 1997 questionnaire (NATIONAL HOUSEHOLD SURVEY ON DRUG ABUSE, 1997) introduced new items that the 1998 NHSDA continued on cigar smoking, people who were present when respondents used marijuana or cocaine for the first time (if applicable), reasons for using these two drugs the first time, reasons for using these two drugs in the past year, reasons for discontinuing use of these two drugs (for lifetime but not past-year users), and reasons respondents never used these two drugs. Both the 1997 and 1998 NHSDAs had a series of questions that were asked only of respondents aged 12 to 17. These items covered a variety of topics that may be associated with substance use and related behaviors, such as exposure to substance abuse prevention and education programs, gang involvement, relationship with parents, and substance use by friends. Demographic data include sex, race, age, ethnicity, marital status, educational level, job status, income level, veteran status, and current household composition. This study has 1 Data Set.

Prescription Drug Misuse reports the prevalence of the misuse of prescription pain killers by age range.

Heroin Use reports an estimated average percent of people who consumed heroin, by age range. These data are collected by the Substance Abuse and Mental Health Services Administration (SAMHSA) as part of the National Survey on Drug Use and Health (NSDUH), Substate Region Estimates by Age Group. This survey is conducted on a representative sample of U.S. civilian, non-institutionalized people ages 12 and older. Data are available for the state of Connecticut, substate regions within Connecticut, the Northeast region of the United States, and the Total United States.

This pilot study was conducted in an attempt to better understand the jailed population in terms of the number of families at risk and the relationship between parental substance use and incarceration and its impact on the children of the incarcerated. The aim of the study was to describe the jailed population, their needs in relation to substance abuse and parenting issues, to explore children's risk factors resulting from having a parent with substance abuse and/or criminal justice involvement, and ultimately to offer a point of intervention for parents and children at risk. Participants included 229 men and 52 women aged 18 and older, who were in their first 48 hours of incarceration in the Santa Clara County Department of Corrections in August 2003 and who where voluntary participants in the National Institute of Justice's (NIJ) Arrestee Drug Abuse Monitoring (ADAM) Program (ARRESTEE DRUG ABUSE MONITORING (ADAM) PROGRAM IN THE UNITED STATES, 2003 [ICPSR 4020]). Male subjects were chosen through a random selection process, while female participants were taken from a convenience sample. The pilot study used a questionnaire completed as an addendum to the ADAM program main interview. Major types of variables included in this study are type and duration of alcohol/drug use, family history of incarceration, number and ages of children for whom the respondent was the primary caregiver, social consequences for the child due to the incarceration of the respondent, and if the child had any problems with drugs and/or alcohol.

The PATH Study was launched in 2011 to inform the Food and Drug Administration's regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). The PATH Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). The study sampled over 150,000 mailing addresses across the United States to create a national sample of people who use or do not use tobacco. 45,971 adults and youth constitute the first (baseline) wave, Wave 1, of data collected by this longitudinal cohort study. These 45,971 adults and youth along with 7,207 "shadow youth" (youth ages 9 to 11 sampled at Wave 1) make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete an interview after parental consent. At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population (CNP) at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled Primary Sampling Unit (PSU)s and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the CNP at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort. At Wave 7, a probability sample of 14,863 adults, youth, and shadow youth ages 9 to 11 was selected from the CNP at the time of Wave 7. This sample was recruited from residential addresses not selected for Wave 1 or Wave 4 in the same sampled PSUs and segments using similar within-household sampling procedures. This "second replenishment sample" was combined for estimation and analysis purposes with the Wave 7 adult and youth respondents from the Wave 4 Cohorts who were at least age 15 and in the CNP at the time of Wave 7. This combined set of Wave 7 participants, 46,169 participants in total, forms the Wave 7 Cohort. Please refer to the Restricted-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1, Wave 4, and Wave 7 Cohorts. Dataset 0002 (DS0002) contains the data from the State Design Data. This file contains 7 variables and 82,139 cases. The state identifier in the State Design file reflects the participant's state of residence at the time of selection and recruitment for the PATH Study. Dataset 1011 (DS1011) contains the data from the Wave 1 Adult Questionnaire. This data file contains 2,021 variables and 32,320 cases. Each of the cases represents a single, completed interview. Dataset 1012 (DS1012) contains the data from the Wave 1 Youth and Parent Questionnaire. This file contains 1,431 variables and 13,651 cases. Dataset 1411 (DS1411) contains the Wave 1 State Identifier data for Adults and has 5 variables and 32,320 cases. Dataset 1412 (DS1412) contains the Wave 1 State Identifier data for Youth (and Parents) and has 5 variables and 13,651 cases. The same 5 variables are in each State Identifier dataset, including PERSONID for linking the State Identifier to the questionnaire and biomarker data and 3 variables designating the state (state Federal Information Processing System (FIPS), state abbreviation, and full name of the state). The State Identifier values in these datasets represent participants' state of residence at the time of Wave 1, which is also their state of residence at the time of recruitment. Dataset 1611 (DS1611) contains the Tobacco Universal Product Code (UPC) data from Wave 1. This data file contains 32 variables and 8,601 cases. This file contains UPC values on the packages of tobacco products used or in the possession of adult respondents at the time of Wave 1. The UPC values can be used to identify and validate the specific products used by respondents and augment the analyses of the characteristics of tobacco products used

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)

According to Cognitive Market Research, The Drug Abuse Testing Market will be USD XX Billion in 2023 and is set to achieve a market size of USD XX Billion by the end of 2031 growing at a CAGR of XX% from 2024 to 2031. North America held the major market share for more than XX% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of XX % from 2024 to 2031. The Europe region is the fastest growing market with a CAGR of XX% from 2024 to 2031 and it is projected that it will grow at a CAGR of XX% in the future. Asia Pacific accounted for a market share of over XX% of the global revenue with a market size of USD XX million. Latin America had a market share for more than XX% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of XX% from 2024 to 2031. Middle East and Africa had a market share of around XX% of the global revenue and was estimated at a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of XX% from 2024 to 2031. The Drug Abuse Testing Market held the highest market revenue share in 2024.

Market Dynamics of The Drug Abuse Testing Market

Key Drivers for The Drug Abuse Testing Market

Increase in road accidents due to alcohol consumption growing the market for drug abuse testing.

The number of people killed and injured in traffic accidents, whether they occur right away or 30 days later, are the metrics used to assess these incidents. Alcohol and other substances impair reflexes, judgment, decision-making, impulse control, and motor function, which increases the risk of traffic accidents and frequently results in fatalities. The World Health Organization (WHO) estimates that between 20 and 50 million people get non-fatal injuries and 1.3 million people die in traffic accidents each year. Rising road accidents through alcohol consumption have increased drug abuse testing due to this the market is growing. For instance, according to the 2021 National Survey on Drug Use and Health (NSDUH), in 2021, around 57.8% of people aged 12 years and more used tobacco, alcohol, and illicit drugs. Further, 47.5% of them were alcohol consumers, 19.5% took tobacco, and 14.3% used illicit drugs. Additionally, it is well-known that men are more likely to consume drugs and alcohol than women. Source:(https://www.samhsa.gov/data/sites/default/files/2022-12/2021NSDUHFFRHighlights092722.pdf) For instance, in October 2023, In India, Kerala police launched a rapid drug screening system that uses saliva samples and gives results in five minutes. The hand-held device, the SoToxa Mobile Test System, has been deployed on a trial basis in Thiruvananthapuram city, and depending on its reliability and accuracy, the system will be expanded to other parts of the state as well. Over the past two days, the police have booked 11 people for narcotic abuse through a roadside drive using this device that helps in identifying those who took drugs even two days before Source:(https://www.onmanorama.com/news/kerala/2023/10/08/police-launch-new-device-detect-drug-use-in-5-minutes.html) After alcohol, marijuana is most frequently detected in the blood of drivers who have been in accidents. The mind-altering component of marijuana, delta-9-tetrahydrocannabinol (THC), which is found in blood, sometimes takes center stage during an inquiry. Furthermore, compared to when the substances are taken separately, marijuana may increase the risk of car accidents when combined with cocaine, alcohol, or benzodiazepines. Therefore, in the future, the frequency of drug misuse testing will be determined by the rising incidence of such adverse occurrences.

The increasing prevalence of drug abuse treatment drives growth in the drug abuse testing market. 

The increasing prevalence of drug abuse has led to a rising demand for drug abuse treatment, consequently driving growth in the drug abuse testing market. With a greater focus on identifying and addressing substance abuse issues, there's a corresponding need for accurate and efficient testing methods to monitor and manage treatment progress effectively. The growing consumption of illicit drugs by individuals needs to have drug abuse treatment which in turn increases the prevalence of drug abuse treatment hence it has led to drive the market growth of drug abuse testing. For instance,...

The Estonian Drug Treatment Database is a state register which is kept on the people who have started drug treatment. The Drug Treatment Database started its work on January 1, 2008.

Collection and processing of data on these people is necessary for getting an overview on occurrence of mental and behavioural disorders related to drug use, as well as for organising of relevant health services and planning of drug abuse preventive actions. Health care institutions holding a psychiatry authorization in Estonia present data to the database if they are turned to by a patient who is diagnosed with a mental and behavioural disorder due to drug use.

On the basis of the database's data, an annual overview is compiled, giving information about drug addicts who have turned to drug treatment in the previous calendar year, about the health service provided, the patients' socio-economic background, drug use and the related risk behaviour.

The data on the Drug Treatment Database are also submitted to the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) and United Nations Office on Drugs and Crime (UNODC).

The Population Assessment of Tobacco and Health (PATH) Study began originally surveying 45,971 adult and youth respondents. The PATH Study was launched in 2011 to inform Food and Drug Administration's regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). The PATH Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). The study sampled over 150,000 mailing addresses across the United States to create a national sample of people who use or do not use tobacco. 45,971 adults and youth constitute the first (baseline) wave of data collected by this longitudinal cohort study. These 45,971 adults and youth along with 7,207 "shadow youth" (youth ages 9 to 11 sampled at Wave 1) make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete an interview after parental consent. At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled Primary Sampling Unit (PSU)s and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the civilian, noninstitutionalized population at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort.Dataset 0001 (DS0001) contains the data from the Master Linkage file. This file contains 14 variables and 67,276 cases. The file provides a master list of every person's unique identification number and what type of respondent they were for each wave. At Wave 7, a probability sample of 14,863 adults, youth, and shadow youth ages 9 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 7. This sample was recruited from residential addresses not selected for Wave 1 or Wave 4 in the same sampled PSUs and segments using similar within-household sampling procedures. This second replenishment sample was combined for estimation and analysis purposes with Wave 7 adult and youth respondents from the Wave 4 Cohort who were at least age 15 and in the civilian, noninstitutionalized population at the time of Wave 7. This combined set of Wave 7 participants, 46,169 participants in total, forms the Wave 7 Cohort. Please refer to the Public-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1, Wave 4, and Wave 7 Cohorts.Dataset 1001 (DS1001) contains the data from the Wave 1 Adult Questionnaire. This data file contains 1,732 variables and 32,320 cases. Each of the cases represents a single, completed interview. Dataset 1002 (DS1002) contains the data from the Youth and Parent Questionnaire. This file contains 1,228 variables and 13,651 cases.Dataset 2001 (DS2001) contains the data from the Wave 2 Adult Questionnaire. This data file contains 2,197 variables and 28,362 cases. Of these cases, 26,447 also completed a Wave 1 Adult Questionnaire. The other 1,915 cases are "aged-up adults" having previously completed a Wave 1 Youth Questionnaire. Dataset 2002 (DS2002) contains the data from the Wave 2 Youth and Parent Questionnaire. This data file contains 1,389 variables and 12,172 cases. Of these cases, 10,081 also completed a Wave 1 Youth Questionnaire. The other 2,091 cases are "aged-up youth" having previously been sampled as "shadow youth." Dataset 3001 (DS3001) contains the data from the Wave 3 Adult Questionnaire. This data file contains 2,139 variables and 28,148 cases. Of these cases, 26,241 are continuing adults having completed a prior Adult Questionnaire. The other 1,907 cases are "aged-up adults" having previously completed a Youth Questionnaire. Dataset 3002 (DS3002) contains the data from t

The goal of this study was to test specific hypotheses illustrating the relationships among serious victimization experiences, the mental health effects of victimization, substance abuse/use, and delinquent behavior in adolescents. The study assessed familial and nonfamilial types of violence. It was designed as a telephone survey of American youth aged 12-17 living in United States households and residing with a parent or guardian. One parent or guardian in each household was interviewed briefly to establish rapport, secure permission to interview the targeted adolescent, and to ensure the collection of comparative data to examine potential nonresponse bias from households without adolescent participation. All interviews with both parents and adolescents were conducted using Computer-Assisted Telephone Interviewing (CATI) technology. From the surveys of parents and adolescents, the principal investigators created one data file by attaching the data from the parents to the records of their respective adolescents. Adolescents were asked whether violence and drug abuse were problems in their schools and communities and what types of violence they had personally witnessed. They were also asked about other stressful events in their lives, such as the loss of a family member, divorce, unemployment, moving to a new home or school, serious illness or injury, and natural disaster. Questions regarding history of sexual assault, physical assault, and harsh physical discipline elicited a description of the event and perpetrator, extent of injuries, age at abuse, whether alcohol or drugs were involved, and who was informed of the incident. Information was also gathered on the delinquent behavior of respondents and their friends, including destruction of property, assault, theft, sexual assault, and gang activity. Other questions covered history of personal and family substance use and mental health indicators, such as major depression, post-traumatic stress disorders, weight changes, sleeping disorders, and problems concentrating. Demographic information was gathered from the adolescents on age, race, gender, number of people living in household, and grade in school. Parents were asked whether they were concerned about violent crime, affordable child care, drug abuse, educational quality, gangs, and the safety of their children at school. In addition, they were questioned about their own victimization experiences and whether they discussed personal safety issues with their children. Parents also supplied demographic information on gender, marital status, number of children, employment status, education, race, and income.

The DC Metropolitan Area Drug Study (DCMADS) was
conducted in 1991, and included special analyses of homeless and
transient populations and of women delivering live births in the DC
hospitals. DCMADS was undertaken to assess the full extent of the
drug problem in one metropolitan area. The study was comprised of 16
separate studies that focused on different sub-groups, many of which
are typically not included or are underrepresented in household
surveys. The Homeless and Transient Population
study examines the prevalence of illicit drug, alcohol, and tobacco
use among members of the homeless and transient population aged 12 and
older in the Washington, DC, Metropolitan Statistical Area (DC
MSA). The sample frame included respondents from shelters, soup
kitchens and food banks, major cluster encampments, and literally
homeless people. Data from the questionnaires include history of
homelessness, living arrangements and population movement, tobacco,
drug, and alcohol use, consequences of use, treatment history, illegal
behavior and arrest, emergency room treatment and hospital stays,
physical and mental health, pregnancy, insurance, employment and
finances, and demographics. Drug specific data include age at first
use, route of administration, needle use, withdrawal symptoms,
polysubstance use, and perceived risk.This study has 1 Data Set.

A. SUMMARY This dataset includes unintentional drug overdose death rates by race/ethnicity by year. This dataset is created using data from the California Electronic Death Registration System (CA-EDRS) via the Vital Records Business Intelligence System (VRBIS). Substance-related deaths are identified by reviewing the cause of death. Deaths caused by opioids, methamphetamine, and cocaine are included. Homicides and suicides are excluded. Ethnic and racial groups with fewer than 10 events are not tallied separately for privacy reasons but are included in the “all races” total.

Unintentional drug overdose death rates are calculated by dividing the total number of overdose deaths by race/ethnicity by the total population size for that demographic group and year and then multiplying by 100,000. The total population size is based on estimates from the US Census Bureau County Population Characteristics for San Francisco, 2022 Vintage by age, sex, race, and Hispanic origin.

These data differ from the data shared in the Preliminary Unintentional Drug Overdose Death by Year dataset since this dataset uses finalized counts of overdose deaths associated with cocaine, methamphetamine, and opioids only.

B. HOW THE DATASET IS CREATED This dataset is created by copying data from the Annual Substance Use Trends in San Francisco report from the San Francisco Department of Public Health Center on Substance Use and Health.

C. UPDATE PROCESS This dataset will be updated annually, typically at the end of the year.

D. HOW TO USE THIS DATASET N/A

E. RELATED DATASETS Overdose-Related 911 Responses by Emergency Medical Services Preliminary Unintentional Drug Overdose Deaths San Francisco Department of Public Health Substance Use Services

F. CHANGE LOG

• 12/16/2024 - Updated with 2023 data. Asian/Pacific Islander race/ethnicity group was changed to Asian.
• 12/16/2024 - Past year totals by race/ethnicity were revised after obtaining accurate race/ethnicity for some decedents that were previously marked as “unknown” race/ethnicity.

This data presents provisional counts for drug overdose deaths based on a current flow of mortality data in the National Vital Statistics System. Counts for the most recent final annual data are provided for comparison. National provisional counts include deaths occurring within the 50 states and the District of Columbia as of the date specified and may not include all deaths that occurred during a given time period. Provisional counts are often incomplete and causes of death may be pending investigation resulting in an underestimate relative to final counts. To address this, methods were developed to adjust provisional counts for reporting delays by generating a set of predicted provisional counts. Several data quality metrics, including the percent completeness in overall death reporting, percentage of deaths with cause of death pending further investigation, and the percentage of drug overdose deaths with specific drugs or drug classes reported are included to aid in interpretation of provisional data as these measures are related to the accuracy of provisional counts. Reporting of the specific drugs and drug classes involved in drug overdose deaths varies by jurisdiction, and comparisons of death rates involving specific drugs across selected jurisdictions should not be made. Provisional data presented will be updated on a monthly basis as additional records are received. For more information please visit: https://www.cdc.gov/nchs/nvss/vsrr/drug-overdose-data.htm

Three crime data sources were collected and merged for this study. All three crime sources were either only reporting on the U.S. state of Kentucky (KOOL and Louisville Open Data), or filtered to only contain results for the U.S. state of Kentucky (FBI). Each data source contains unique features such as crime classifications, and unique challenges in collection and cleaning.

The United States Federal Bureau of Investigation (FBI) issues a variety of query-able crime related data on their website. This data is sourced from law enforcement agencies across the U.S. as part of their National Incident-Based Reporting System (NIBRS) and its standards. The goal of gathering, standardizing, and providing this information is to facilitate research into crime and law enforcement patterns. The information is provided as a collection of CSV files with instructions and code for importing into a SQL database. For the purposes of this research, we utilized the the crime databases for the years 2017, 2018 and 2019, containing a total of 1,939,990 unique incidents. The NIBRS_code property denotes the type of crime as assigned by the reporting agency. The human trafficking codes are 40A (Prostitution), 40B (Assisting or Promoting Prostitution), and 370 (Pornography/Obscene Material). The drug incidents were found using codes 35A (Drug/Narcotic Violations) and 35B (Drug Equipment Violations).

The Kentucky Department of Corrections, as a service to the public, provides an online lookup of people currently in its custody called Kentucky Offender Online Lookup (KOOL). This web application offers users tools to search for sets of inmates based on features such as name, crime date, crime name, race, and gender. The data that KOOL searches contains only people who are currently under supervision of the state of Kentucky (or should be under supervision in the case of escape).

The Louisville Open Data Initiative (LOD) is a program from the city of Louisville, Kentucky, U.S.A. to increase the transparency of the city government and promote technological innovation. As part of LOD, a dataset of crime reports is made available online. The records contained within the LOD dataset represent any call for police service where a police incident report was generated. This does not necessarily mean a crime was committed, as an incident report can be generated before an investigation has taken place.

The primary research objective of this study was to examine the prevalence, nature, and reporting of various types of sexual assault experienced by university students in an effort to inform the development of targeted intervention strategies. In addition, the study had two service-oriented objectives: (1) to educate students about various types of sexual assault, how they can maximize their safety, and what they can do if they or someone they know has been victimized and (2) to provide students with information about the campus and community resources that are available should they need assistance or have any concerns or questions. The study involved a Web-based survey of random samples of undergraduate students at two large public universities, one located in the South (University 1) and one located in the Midwest (University 2). Researchers drew random samples of students aged 18-25 and enrolled at least three-quarters' time at each university to participate in the study. The survey was administered in the winter of 2005-2006, and a total of 5,446 undergraduate women and 1,375 undergraduate men participated for a grand total of 6,821 respondents. Sampled students were sent an initial recruitment e-mail that described the study, provided a unique study ID number, and included a hyperlink to the study Web site. During each of the following weeks, students who had not completed the survey were sent follow-up e-mails and a hard-copy letter encouraging them to participate. The survey was administered anonymously and was designed to be completed in an average of 15 minutes. Respondents were provided with a survey completion code that, when entered with their study ID number at a separate Web site, enabled them to obtain a $10 Amazon.com gift certificate. The survey was divided into six modules. The Background Information module included survey items on demographics, school classification (year of study, year of enrollment, transfer status), residential characteristics, academic performance, and school involvement. An Alcohol and Other Drug Use module generated a number of measures of alcohol and drug use, and related substance use behaviors. A Dating module included items on sexual orientation, dating, consensual sexual activity, and dating violence. The Experiences module was developed after extensive reviews of past surveys of sexual assault and generated information on physically forced sexual assault and incapacitated sexual assault. For both physically forced and incapacitated sexual assault, information was collected on completed and attempted assaults experienced before entering college and since entering college. For male respondents, a Behaviors module asking about the perpetration of the same types of sexual assault covered in the Experiences module was included. The final module of the survey covered attitudes about sexual assault and attitudes about the survey. The data file contains 747 variables.

The PATH Study was launched in 2011 to inform the Food and Drug Administration's regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). The PATH Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). The study sampled over 150,000 mailing addresses across the United States to create a national sample of people who do and do not use tobacco. 45,971 adults and youth constitute the first (baseline) wave, Wave 1, of data collected by this longitudinal cohort study. These 45,971 adults and youth along with 7,207 "shadow youth" (youth ages 9 to 11 sampled at Wave 1) make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete an interview after parental consent. At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population (CNP) at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled Primary Sampling Units (PSUs) and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the CNP at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort.At Wave 7, a probability sample of 14,863 adults, youth, and shadow youth ages 9 to 11 was selected from the CNP at the time of Wave 7. This sample was recruited from residential addresses not selected for Wave 1 or Wave 4 in the same sampled PSUs and segments using similar within-household sampling procedures. This "second replenishment sample" was combined for estimation and analysis purposes with the Wave 7 adult and youth respondents from the Wave 4 Cohorts who were at least age 15 and in the CNP at the time of Wave 7. This combined set of Wave 7 participants, 46,169 participants in total, forms the Wave 7 Cohort.Please refer to the Public-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1, Wave 4, and Wave 7 Cohorts. Wave 4.5 was a special data collection for youth only who were aged 12 to 17 at the time of the Wave 4.5 interview. Wave 4.5 was the fourth annual follow-up wave for those who were members of the Wave 1 Cohort. For those who were sampled at Wave 4, Wave 4.5 was the first annual follow-up wave.Wave 5.5, conducted in 2020, was a special data collection for Wave 4 Cohort youth and young adults ages 13 to 19 at the time of the Wave 5.5 interview. Also in 2020, a subsample of Wave 4 Cohort adults ages 20 and older were interviewed via the PATH Study Adult Telephone Survey (PATH-ATS).Wave 7.5 was a special collection for Wave 4 and Wave 7 Cohort youth and young adults ages 12 to 22 at the time of the Wave 7.5 interview. For those who were sampled at Wave 7, Wave 7.5 was the first annual follow-up wave. Dataset 1002 (DS1002) contains the data from the Wave 4.5 Youth and Parent Questionnaire. This file contains 1,395 variables and 13,131 cases. Of these cases, 11,378 are continuing youth having completed a prior Youth Interview. The other 1,753 cases are "aged-up youth" having previously been sampled as "shadow youth." Datasets 1112, 1212, and 1222, (DS1112, DS1212, and DS1222) are data files comprising the weight variables for Wave 4.5. The "all-waves" weight file contains weights for participants in the Wave 1 Cohort who completed a Wave 4.5 Youth Interview and completed interviews (if old enough to do so) or verified their information with the study (if not old enough to be interviewed) in Waves 1, 2, 3, and 4. There are two separate files with "single wave" weights: one for the Wave 1 Cohort and one for the Wave 4 Cohort. The "single-wave" weight file for the Wave 1 Cohort contains weights for youth who completed an interview in Wave 1 an

This special topic poll, conducted April 30 to May 6, 1996, is part of a continuing series of monthly surveys that solicit public opinion on the presidency and on a range of other political and social issues. This poll sought Americans' views on the most important problems facing the United States, their local communities and their own families. Respondents rated the public schools, crime, and drug problems at the national and local levels, their level of optimism about their own future and that of the country, and the reasons they felt that way. Respondents were asked whether they were better off financially than their parents were at their age, whether they expected their own children to be better off financially than they were, and whether the American Dream was still possible for most people. Respondents then compared their expectations about life to their actual experiences in areas such as job security, financial earnings, employment benefits, job opportunities, health care benefits, retirement savings, and leisure time. A series of questions asked whether the United States was in a long-term economic and moral decline, whether the country's main problems were caused more by a lack of economic opportunity or a lack of morality, and whether the United States was still the best country in the world. Additional topics covered immigration policy and the extent to which respondents trusted the federal, state, and local governments. Demographic variables included respondents' sex, age, race, education level, marital status, household income, political party affiliation, political philosophy, voter registration and participation history, labor union membership, the presence of children in the household, whether these children attended a public school, and the employment status of respondents and their spouses. telephone interviewThe data available for download are not weighted and users will need to weight the data prior to analysis.The data collection was produced by Chilton Research Services of Radnor, PA. Original reports using these data may be found via the ABC News Polling Unit Website.According to the data collection instrument, code 3 in the variable Q909 (Education Level) included respondents who answered that they had attended a technical school.The original data file contained four records per case and was reformatted into a data file with one record per case. To protect respondent confidentiality, respondent names were removed from the data file.The CASEID variable was created for use with online analysis. The data contain a weight variable (WEIGHT) that should be used in analyzing the data. This poll consists of "standard" national representative samples of the adult population with sample balancing of sex, race, age, and education. Households were selected by random-digit dialing. Within households, the respondent selected was the adult living in the household who last had a birthday and who was at home at the time of interview. Persons aged 18 and over living in households with telephones in the contiguous 48 United States. Datasets: DS1: ABC News Listening to America Poll, May 1996

Youth data for the seventh wave of the National Youth Survey are contained in this collection. This research project, designed to gain a better understanding of both conventional and deviant types of behavior by youths, involved collecting information from a representative sample of young people in the United States. The first wave of this survey was conducted in 1976 (ICPSR 8375), the second in 1977 (ICPSR 8424), the third in 1978 (ICPSR 8506), the fourth in 1979 (ICPSR 8917), the fifth in 1980 (ICPSR 9112), and the sixth in 1983 (ICPSR 9948). For this wave, young adults were interviewed in early 1987 about events and behavior occurring in calendar year 1986, when they were 20 to 29 years of age. Data are available on the demographic and socioeconomic status of respondents, parents and friends, neighborhood problems, education, employment, skills, aspirations, encouragement, normlessness, attitudes toward deviance, exposure to delinquent peers, self-reported depression, delinquency, drug and alcohol use, victimization, pregnancy, abortion, use of mental health and outpatient services, violence by respondent and acquaintances, use of controlled drugs, and sexual activity.