Current marijuana use among U.S. adults in 2023 was highest in Vermont, where around 26.67 percent of adults reported using marijuana within the past year. In recent years, a number of U.S. states, including Colorado and California, have legalized the sale of marijuana for recreational use. In 2023, around 133 million people in the United States reported that they had used marijuana at least once in their lifetime. Consumer behavior Starting around 2013, the majority of U.S. adults now say they are in favor of legalizing marijuana in the United States. The share of adults who were in favor of legalization has continued to increase over the years. As of 2021, about 68 percent of U.S. adults aged 18 and older were in favor of legalization. Legal sales of marijuana reached 16.5 billion U.S. dollars in 2021, and are expected to increase to around 37 billion dollars by the year 2026. COVID-19 impact on marijuana use The COVID-19 pandemic and resulting lockdowns led to fears of an increase in substance abuse in many parts of the world. In March 2020, around 40 percent of millennials who used cannabis in the past year reported that they planned to increase their marijuana use during the COVID-19 pandemic. This rise in usage was reflected in sales early in the pandemic. In California for example, sales of marijuana on March 16, 2020 increased 159 percent compared to the same day in 2019.

The data represents individuals arrested with a marijuana charge, regardless of whether there was a more serious secondary charge. If an arrestee was charged with multiple marijuana charges, the arrest is only counted once under the more serious charge type (Manufacture/Cultivation > Distribution > Possession with Intent to Distribute > Possession > Public Consumption). The category of “Manufacture or Cultivation” was added in the 2019 data and for future years, but is not utilized in prior years.MPD collects race and ethnicity data according to the United States Census Bureau standards (https://www.census.gov/topics/population/race/about.html). Hispanic, which was previously categorized under the Race field prior to August 2015, is now captured under Ethnicity. All records prior to August 2015 have been updated to “Unknown (Race), Hispanic (Ethnicity).” Data on race and ethnicity prior to November 9, 2018 was based on officer observation; on and after November 9, 2018, the data is based on the arrestee’s response.MPD cannot release exact addresses to the general public unless proof of ownership or subpoena is submitted. The GeoX and GeoY values represent the block location (approximately 232 ft. radius) as of the date of the arrest. Due to the Department’s redistricting efforts in 2012 and 2019, data may not be comparable in some years.Arrestee age is calculated based on the number of days between the self-reported or verified date of birth (DOB) of the arrestee and the date of the arrest; DOB data may not be accurate if self-reported or if the arrestee refused to provide it.Due to the sensitive nature of juvenile data and to protect the arrestee’s confidentiality, any arrest records for defendants under the age of 18 have been coded as “NA” for the following fields:• Arrest Hour• CCN• Age• Offense Location Block GeoX/Y• Defendant Race• Defendant Ethnicity• Defendant Sex• Arrest Location Block Address• Arrest Location Block GeoX/YThis data may not match other marijuana data requests that may have included all law enforcement agencies in the District, or only the most serious charge. Figures are subject to change due to record sealing, expungements, and data quality audits.

This report contains results from the latest survey of secondary school pupils in England in years 7 to 11 (mostly aged 11 to 15), focusing on smoking, drinking and drug use. It covers a range of topics including prevalence, habits, attitudes, and wellbeing. This survey is usually run every two years, however, due to the impact that the Covid pandemic had on school opening and attendance, it was not possible to run the survey as initially planned in 2020; instead it was delivered in the 2021 school year. In 2021 additional questions were also included relating to the impact of Covid. They covered how pupil's took part in school learning in the last school year (September 2020 to July 2021), and how often pupil's met other people outside of school and home. Results of analysis covering these questions have been presented within parts of the report and associated data tables. It includes this summary report showing key findings, excel tables with more detailed outcomes, technical appendices and a data quality statement. An anonymised record level file of the underlying data on which users can carry out their own analysis will be made available via the UK Data Service later in 2022 (see link below).

Abstract Tobacco use is a Public Health issue, and the release of its use in the prison system is controversial. Its prevalence in this population is high, including in women’s prisons. The objective of this article is to estimate tobacco use prevalence in women deprived of liberty and its associated factors. Cross-sectional study with 259 participants who answered a questionnaire in a prison in the Brazilian Midwest. The dependent variable was tobacco use, and the independent variables were sociodemographic, life history, legal status, and use of other drugs. Descriptive and bivariate analyses were performed, using prevalence ratios through the Chi-square test and Poisson regression in the multivariate analysis. Tobacco use prevalence was 86.87%. In the final model, the variables: age group, from 18-39 years (PR 1.33; 95%CI 1.10-1.61), alcohol use (PR 1.26; 95%CI 1.00-1.59), marijuana use (PR 1.16; 95%CI 1.03-1.30), and interaction between prison time and cocaine use (PR 1.05; 95%CI 1.00-1.11) remained associated with tobacco use. Tobacco use prevalence was high. The age group 18-39 years, alcohol and marijuana use and interaction between imprisonment length of 36 months or more and cocaine use were associated with tobacco use.

Background. Whilst cannabis commercialization is occurring rapidly guided by highly individualistic public narratives, evidence that all congenital anomalies (CA) increase alongside cannabis use in Canada, a link with 21 CA’s in Hawaii, and rising CA’s in Colorado indicate that transgenerational effects can be significant and impact public health. It was therefore important to study Northern New South Wales (NNSW) a known cannabis use centre.

Methods. Design: Cohort. 2008-2015. Setting: NNSW and Queensland (QLD), Australia. Participants. Whole populations. Exposures. Tobacco, Risky Alcohol, Annual cannabis. Source: National Drug Strategy Household Surveys 2010, 2013. Main Outcomes. CA Rates. NNSW-QLD comparisons. Geospatial and causal regression.

Results. Cardiovascular, respiratory and gastrointestinal anomalies rose with falling tobacco and alcohol but rising cannabis use rates across Queensland. Maternal age NNSW-QLD was not different (2008-2015: 4,265/22,084 v. 96,473/490,514 >35 years, Chi.Sq.=1.687, P=0.194). A higher rate of NNSW cannabis-related than cannabis-unrelated defects occurred (prevalence ratio (PR)=2.13, 95%C.I. 1.80-2.52, P=3.24x10-19). CA’s rose more potently with rising cannabis than with rising tobacco or alcohol use. Exomphalos and gastroschisis had the highest NNSW:QLD PR (6.29(2.94-13.48) and 5.85(3.54-9.67)) and attributable fraction in the exposed (84.11%(65.95-92.58%) and 82.91%(71.75-89.66%), P=2.83x10-8 and P=5.62x10-15). In multivariable geospatial models cannabis was significantly linked with cardiovascular (atrial septal defect, ventricular septal defect, tetralogy of Fallot, patent ductus arteriosus), genetic (chromosomal defects, Downs syndrome), gastrointestinal (small intestinal atresia), body wall (gastroschisis, diaphragmatic hernia) and other (hypospadias) (AVTPCDSGDH) CA’s. In linear modelling cannabis use was significantly linked with anal stenosis, congenital hydrocephalus and Turner syndrome (ACT) and was significantly linked in borderline significant models (model P<0.1) with microtia, microphthalmia, and transposition of the great vessels. In robust and mixed effects inverse probability weighted multivariable regression cannabis was related to 18defects. E-Values in spatial models were generally >1.3 ranging up to 3.8x1030 making uncontrolled confounding unlikley.

Conclusions. These results suggest that population level CA’s react more strongly to small rises in cannabis use than tobacco or alcohol; cardiovascular, chromosomal, body wall and gastrointestinal CA’s rise significantly with small increases in cannabis use; and that cannabis is a bivariate correlate of AVTPCDSGDH and ACT anomalies and is robust to adjustment for other substances.

Browse state-level percentage estimates based on the 2021-2022 National Surveys on Drug Use and Health (NSDUH). The 37 tables include estimates for 35 measures of substance use and mental health, by age group, along with 95% confidence intervals. The percentages are based on small area estimation (SAE) methods, in which state-level NSDUH data are combined with other data from smaller geographies. The combined data are used to create modeled state estimates of the civilian, noninstitutionalized population ages 12 and older, or adults 18 and older for mental health measures. Each table covers a single measure by state, region, and age group.The indicators are presented in the following 37 tables:Drug use and Perceived RiskIllicit Drug Use in the Past MonthMarijuana Use in the Past YearMarijuana Use in the Past MonthPerceptions of Great Risk from Smoking Marijuana Once a MonthFirst Use of Marijuana in the Past Year (among those at risk for initiation)Illicit Drug Use Other than Marijuana in the Past MonthCocaine Use in the Past YearPerceptions of Great Risk from using Cocaine Once a MonthHeroin Use in the Past YearPerceptions of Great Risk from Trying Heroin Once or TwiceHallucinogen Use in the Past YearMethamphetamine Use in the Past YearPrescription Pain Reliever Misuse in the Past YearOpioid Misuse in the Past YearAlcoholAlcohol Use in the Past MonthBinge Alcohol Use in the Past MonthPerceptions of Great Risk from Having Five or More Drinks of an Alcoholic Beverage Once or Twice a WeekAlcohol Use, Binge Alcohol Use in the Past Month, and Perceptions of Great Risk from Having Five or More Drinks of an Alcoholic Beverage Once or Twice a Week (among people aged 12 to 20)TobaccoTobacco Product Use in the Past MonthCigarette Use in the Past MonthPerceptions of Great Risk from Smoking One or More Packs of Cigarettes per DaySubstance Use DisordersSubstance Use Disorder in the Past YearAlcohol Use Disorder in the Past YearAlcohol Use Disorder in the Past Year (among people aged 12 to 20)Drug Use Disorder in the Past YearPain Reliever Use Disorder in the Past YearOpioid Use Disorder in the Past YearSubstance Use TreatmentReceived Substance Use Treatment in the Past YearClassified as Needing Substance Use Treatment in the Past YearDid Not Receive Substance Use Treatment in the Past Year among those Classified as Needing Substance Use TreatmentMental IllnessAny Mental Illness in the Past YearSerious Mental Illness in the Past YearReceived Mental Health Treatment in the Past YearMajor Depressive Episode in the Past YearSuicidalityHad Serious Thoughts of Suicide in the Past YearMade Any Suicide Plans in the Past YearAttempted Suicide in the Past YearThe tables are available in an Excel spreadsheet, a PDF file, or as a zip file of 37 CSV text files.

Data for cities, communities, and City of Los Angeles Council Districts were generated using a small area estimation method which combined the survey data with population benchmark data (2022 population estimates for Los Angeles County) and neighborhood characteristics data (e.g., U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates). This indicator is based on self-report and includes adults who used any form of marijuana at least one time in the past month.Among federally prohibited drugs and substances, marijuana is the most commonly used. In early 2018, marijuana became legal for recreational sale and consumption in California. Using marijuana at any age can lead to negative health consequences, which include psychological conditions such as depression or anxiety; brain damage affecting memory, attention, and learning ability; lung and cardiovascular system damage; harm to developing fetuses or infants; and increased risk for motor vehicle crashes. Marijuana use has long been associated with the use of other substances, including alcohol, tobacco, and prescription and illicit narcotics. Cities and communities should take an active role in educating residents, particularly youth, pregnant persons, and other vulnerable groups, about the potential risks of marijuana use and adopt policies that regulate and ensure safe marijuana retail activity.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

Attitude towards drugs. Topics: Preferred contact for information about illicit drugs and drug use in general; information sources for information about the effects and risks of drug use of illicit drugs; consumption of new psychoactive substances (‘legal highs’) that imitate the effects of illicit drugs, in the last year; purchase of new substances by a friend, from a specialised shop, from the Internet or from a drug dealer; circumstances of use (alone, with friends, during a party or an event or during normal daily activities); information sources for information about the effects and risks of the use of new substances; assessment of the risk to a person’s health using cannabis, ecstasy, alcohol, cocaine, and new substances that imitate the effects of illicit drugs, once or twice and regularly; most effective ways for public authorities to reduce drugs problems (information and prevention campaigns, treatment and rehabilitation of drug users, tough measures against drug dealers and traffickers, as well as drug users, legalize drugs, reduction of poverty and unemployment, more leisure activities for young people); demand for (continued) banning or a legal regulation of the following substances (cannabis, tobacco, ecstasy, heroin, alcohol, cocaine); appropriate way to handle new psychoactive substances (introduce regulation, ban them only if they pose a risk to health, ban them under any circumstance, do nothing); possibility to obtain selected substances within 24 hours (cannabis, alcohol, cocaine, ecstasy, tobacco, heroin, new psychoactive substances); respondent has used cannabis. Demography: age; sex; highest education level; occupation and professional position of the main wage earner in the household (only full time students); occupation and professional position of the respondent; region; type of community; own a mobile phone and fixed (landline) phone in the household; number of persons aged 15 years and older in the household (household size). Einstellung zu Drogen. Themen: Präferierte Ansprechpartner für Informationen über illegale Drogen und Drogenkonsum; Informationsquellen für Informationen zu Auswirkungen und Risiken des Drogenkonsums; Konsum ´neuer psychoaktiver Substanzen (NPS)´ (´Legal Highs´), die die Wirkung illegaler Drogen imitieren, in den letzten zwölf Monaten; Kauf der neuen synthetischen Drogen von einem Freund, in einem Spezialgeschäft, im Internet bzw. von einem Drogendealer; Konsumsituation (allein, mit Freunden, während einer Party oder Veranstaltung bzw. im Alltag); Informationsquellen für erhaltene Informationen zu Auswirkungen und Risiken des Konsums neuer synthetischer Drogen; Einschätzung des Gesundheitsrisikos jeweils beim ein- oder zweimaligen Konsum und beim regelmäßigen Konsum von Cannabis, Ecstasy, Alkohol, Kokain sowie von neuen synthetischen Drogen, die die Wirkung illegaler Drogen imitieren; effektivste staatliche Maßnahmen zur Reduzierung der Drogenproblematik (Kampagnen zur Information und Vorbeugung, Behandlung und Rehabilitation von Drogenkonsumenten, strenge Maßnahmen gegen Drogendealer und Drogenhändler bzw. gegen Drogenkonsumenten, Drogen legalisieren, Reduzierung von Armut und Arbeitslosigkeit mehr Freizeitangebote für Jugendliche); Forderung nach einem (weiteren) Verbot oder einer gesetzlichen Regelung des Konsums ausgewählter Substanzen (Cannabis, Tabak, Ecstasy, Heroin, Alkohol, Kokain); geeigneter Umgang mit legalen neuen psychoaktiven Substanzen (Regulierung einführen, Verbot nur bei Gesundheitsrisiko, generelles Verbot, nichts tun); Beschaffungsmöglichkeit ausgewählter Substanzen innerhalb von 24 Stunden (Cannabis, Alkohol, Kokain, Ecstasy, Tabak, Heroin, neue psychoaktive Substanzen); Cannabiskonsum. Demographie: Alter; Geschlecht; höchster Bildungsabschluss; Beschäftigungsstatus und berufliche Stellung des Haupteinkommensbeziehers im Haushalt (falls Befragter Schüler oder Student); Beschäftigungsstatus und berufliche Stellung des Befragten; Region; Urbanisierungsgrad des Wohnortes; Mobiltelefonbesitz; Festnetztelefon im Haushalt; Anzahl der Personen im Haushalt ab 15 Jahren (Haushaltsgröße).

Contains a set of data tables for each part of the Smoking, Drinking and Drug Use among Young People in England, 2021 report

We have acquired a new tobacco-weed dataset using a Mavic Mini drone. Eight fields of tobacco crop are captured in Mardan, Khyber Pakhtunkhwa, Pakistan. At different growth stages these eight fields are captured at crop age of 15 to 40 days approximately. Data is captured at 1920×1080-pixel resolution. Dataset is captured at an average altitude of 4 meters with ground sampling distance of 0.1 cm/pixel.

Find Details in attached Research papers

Citation Request: if you use these datasets in your research or projects by any means, please cite following publications.

1) Patch-wise weeds coarse segmentation mask from aerial imagery of sesame crop (Published in Computers and Electronics in Agriculture 2022, HEC Recognized W category, Impact factor 6.757, Q1) 2) Towards automated weed detection through two-stage semantic segmentation of tobacco and weed pixels in aerial Imagery (Published in Smart Agricultural Technology (A companion journal of Computers and Electronics in Agriculture)) 3) A Patch-Image Based Classification Approach for Detection of Weeds in Sugar Beet Crop (Published in IEEE Access, Impact factor 3.1, Q1)

Acknowledgement Request This work is funded by the Higher Education Commission of Pakistan and the National center for Robotics and Automation (DF-1009–31). Please Acknowledge.

Steps to Access Mendeley datasets 1. Click on the link 2. The link with ask you to sign in or register with institutional email. 3. Use your institutional/organization email to register and then sign in. 4. Once sign in, dataset will be visible in compressed folders 5. Download and unzip/umcompress folder 6. Use dataset in your research as you see fit (folders contains original images, and their labeled groundtruths, along with binary vegetation masks. In groundtruths background have label value of 0, crop have label 1 and weeds have label of 2. maskref subfolders shows labelled data for visualization)

Find More datasets and published articles in Related Links

Einstellung zu Drogen. Themen: Präferierte Ansprechpartner für Informationen über illegale Drogen und Drogenkonsum; Informationsquellen für Informationen zu Auswirkungen und Risiken des Drogenkonsums; Konsum ´neuer psychoaktiver Substanzen (NPS)´ (´Legal Highs´), die die Wirkung illegaler Drogen imitieren, in den letzten zwölf Monaten; Kauf der neuen synthetischen Drogen von einem Freund, in einem Spezialgeschäft, im Internet bzw. von einem Drogendealer; Konsumsituation (allein, mit Freunden, während einer Party oder Veranstaltung bzw. im Alltag); Informationsquellen für erhaltene Informationen zu Auswirkungen und Risiken des Konsums neuer synthetischer Drogen; Einschätzung des Gesundheitsrisikos jeweils beim ein- oder zweimaligen Konsum und beim regelmäßigen Konsum von Cannabis, Ecstasy, Alkohol, Kokain sowie von neuen synthetischen Drogen, die die Wirkung illegaler Drogen imitieren; effektivste staatliche Maßnahmen zur Reduzierung der Drogenproblematik (Kampagnen zur Information und Vorbeugung, Behandlung und Rehabilitation von Drogenkonsumenten, strenge Maßnahmen gegen Drogendealer und Drogenhändler bzw. gegen Drogenkonsumenten, Drogen legalisieren, Reduzierung von Armut und Arbeitslosigkeit mehr Freizeitangebote für Jugendliche); Forderung nach einem (weiteren) Verbot oder einer gesetzlichen Regelung des Konsums ausgewählter Substanzen (Cannabis, Tabak, Ecstasy, Heroin, Alkohol, Kokain); geeigneter Umgang mit legalen neuen psychoaktiven Substanzen (Regulierung einführen, Verbot nur bei Gesundheitsrisiko, generelles Verbot, nichts tun); Beschaffungsmöglichkeit ausgewählter Substanzen innerhalb von 24 Stunden (Cannabis, Alkohol, Kokain, Ecstasy, Tabak, Heroin, neue psychoaktive Substanzen); Cannabiskonsum. Demographie: Alter; Geschlecht; höchster Bildungsabschluss; Beschäftigungsstatus und berufliche Stellung des Haupteinkommensbeziehers im Haushalt (falls Befragter Schüler oder Student); Beschäftigungsstatus und berufliche Stellung des Befragten; Region; Urbanisierungsgrad des Wohnortes; Mobiltelefonbesitz; Festnetztelefon im Haushalt; Anzahl der Personen im Haushalt ab 15 Jahren (Haushaltsgröße). Attitude towards drugs. Topics: Preferred contact for information about illicit drugs and drug use in general; information sources for information about the effects and risks of drug use of illicit drugs; consumption of new psychoactive substances (‘legal highs’) that imitate the effects of illicit drugs, in the last year; purchase of new substances by a friend, from a specialised shop, from the Internet or from a drug dealer; circumstances of use (alone, with friends, during a party or an event or during normal daily activities); information sources for information about the effects and risks of the use of new substances; assessment of the risk to a person’s health using cannabis, ecstasy, alcohol, cocaine, and new substances that imitate the effects of illicit drugs, once or twice and regularly; most effective ways for public authorities to reduce drugs problems (information and prevention campaigns, treatment and rehabilitation of drug users, tough measures against drug dealers and traffickers, as well as drug users, legalize drugs, reduction of poverty and unemployment, more leisure activities for young people); demand for (continued) banning or a legal regulation of the following substances (cannabis, tobacco, ecstasy, heroin, alcohol, cocaine); appropriate way to handle new psychoactive substances (introduce regulation, ban them only if they pose a risk to health, ban them under any circumstance, do nothing); possibility to obtain selected substances within 24 hours (cannabis, alcohol, cocaine, ecstasy, tobacco, heroin, new psychoactive substances); respondent has used cannabis. Demography: age; sex; highest education level; occupation and professional position of the main wage earner in the household (only full time students); occupation and professional position of the respondent; region; type of community; own a mobile phone and fixed (landline) phone in the household; number of persons aged 15 years and older in the household (household size). Telephone interview: CATI Bevölkerung der jeweiligen Nationalitäten der 28 Mitgliedsstaaten der EU, wohnhaft in den jeweiligen Mitgliedsstaaten im Alter zwischen 15 und 24 Jahren Die Umfrage umfast die nationale Bevölkerung der Bürger (in diesen Ländern) sowie die Bevölkerung der Bürger aller Mitgliedstaaten der Europäischen Union, die Bewohner dieser Länder sind und über ausreichende Kenntnisse der Landessprachen verfügen, um den Fragebogen zu beantworten. Population of the respective nationalities of the European Union Member States, resident in each of the 28 Member States and aged between 15 and 24 years old. The survey covers the national population of citizens (in these countries) as well as the population of citizens of all the European Union Member States that are residents in these countries and have a sufficient command of the national languages to answer the questionnaire.

BackgroundLittle is known about whether people who use both tobacco and cannabis (co-use) are more or less likely to have mental health disorders than single substance users or non-users. We aimed to examine associations between use of tobacco and/or cannabis with anxiety and depression.MethodsWe analyzed data from the COVID-19 Citizen Science Study, a digital cohort study, collected via online surveys during 2020–2022 from a convenience sample of 53,843 US adults (≥ 18 years old) nationwide. Past 30-day use of tobacco and cannabis was self-reported at baseline and categorized into four exclusive patterns: tobacco-only use, cannabis-only use, co-use of both substances, and non-use. Anxiety and depression were repeatedly measured in monthly surveys. To account for multiple assessments of mental health outcomes within a participant, we used Generalized Estimating Equations to examine associations between the patterns of tobacco and cannabis use with each outcome.ResultsIn the total sample (mean age 51.0 years old, 67.9% female), 4.9% reported tobacco-only use, 6.9% cannabis-only use, 1.6% co-use, and 86.6% non-use. Proportions of reporting anxiety and depression were highest for the co-use group (26.5% and 28.3%, respectively) and lowest for the non-use group (10.6% and 11.2%, respectively). Compared to non-use, the adjusted odds of mental health disorders were highest for co-use (Anxiety: OR = 1.89, 95%CI = 1.64–2.18; Depression: OR = 1.77, 95%CI = 1.46–2.16), followed by cannabis-only use, and tobacco-only use. Compared to tobacco-only use, co-use (OR = 1.35, 95%CI = 1.08–1.69) and cannabis-only use (OR = 1.17, 95%CI = 1.00–1.37) were associated with higher adjusted odds for anxiety, but not for depression. Daily use (vs. non-daily use) of cigarettes, e-cigarettes, and cannabis were associated with higher adjusted odds for anxiety and depression.ConclusionsUse of tobacco and/or cannabis, particularly co-use of both substances, were associated with poor mental health. Integrating mental health support with tobacco and cannabis cessation may address this co-morbidity.

This layer represents the Percent of Adults who used Marijuana 1+ days out of the past 30 days calculated from the 2014-2017 Colorado Behavioral Risk Factor Surveillance System (County or Regional Estimates) data set. These data represent the estimated prevalence of adult (Age 18+) Marijuana use for each county in Colorado. Marijuana use is defined as using marijuana or hashish 1 or more days out of the past 30 days. Regional estimates were used if there was not enough sample size to calculate a single county estimate. The estimate for each county was derived from multiple years of Colorado Behavioral Risk Factor Surveillance System data (2014-2017).

The Monitoring the Future (MTF) project is a long-term epidemiologic and etiologic study of substance use among youth and adults in the United States. It is conducted at the University of Michigan's Institute for Social Research and is funded by a series of investigator-initiated research grants from the National Institute on Drug Abuse. The MTF panel study consists of six different survey forms (five forms from 1976-1988), and each survey contains a "core" set of questions about demographics and substance use. This study contains the "core" data for these questions compiled across all survey forms and years in which they are included for the longitudinal panel participants. Each record in the core panel dataset includes the respondent's data for their base year (BY) 12th grade survey (modal age 18) and their young adult follow-up FU surveys (modal ages 19-30). The core panel dataset should be selected by all researchers. Use the linking variable available on all datasets, MTFID, to link the core dataset with all other MTF panel datasets. Here is a list of subjects included in the core dataset: Administrative variables Year of administration Survey form Survey date BY survey weight, sampling stratum and cluster FU panel analysis weights Demographics BY only #Parents in household Parent education levels Respondent's age in months Sex Race/Ethnicity Region of the country (school location) Population density/Urbanicity (school location) High school Zip Code, State and County FIPS codes (can be linked to user-provided data; results can be reported at no unit smaller than US geographical region) Absenteeism (illness, cutting, skipping class) High school program, Grades, post-high school plans FU only Pregnancy status Household type Urbanicity Absenteeism (missing work due to illness, other) Vocational/Technical education, Armed forces, College attendance College grades, attendance, Greek life BY and FU Marital status Household composition Political preference Religious attendance, importance, preference Evenings out, Dating Employment Salary/earned Income and Other Income Driving, tickets, and accidents related to alcohol and other substance use Substance use Cigarette use Alcohol use (including binge drinking (e.g. 5+ drinks in a row/2 weeks), drunkenness) Marijuana/cannabis, hashish use LSD use Hallucinogen use, other than LSD Cocaine use (including cocaine, crack, other forms) Amphetamine use Sedatives/Barbiturate use Tranquilizer use Heroin use (with and without needles) Narcotics use (other than Heroin) Inhalant use Steroid use Ice use Methamphetamine use MDMA use Vaping: nicotine, marijuana, flavoring Please see the study documentation available on the MTF Panel series page for question-specific details. More information about the MTF project can be accessed through the Monitoring the Future website. Annual reports are published by the research team, describing the data collection and trends over time.

Description

In the District of Columbia, the laws related to the recreational use and possession of marijuana have changed at two milestones: the effective dates of the Marijuana Possession Decriminalization Amendment Act of 2014 on July 17, 2014, and of Initiative 71 on February 26, 2015 (https://mpdc.dc.gov/marijuana). Due to privacy considerations, exact CCNs and arrest numbers for these arrest datasets are not provided. In lieu, hash numbers are provided for CNN which allows individuals to determine whether there are multiple arrests associated with one event. Additionally, arrest numbers can be linked directly to an individual and therefore DC government does not provide this more generally, but again as hash numbers.

This data includes arrests made by the Metropolitan Police Department (MPD). The data represents individuals arrested with a marijuana charge, regardless of whether there was a more serious secondary charge. If an arrestee was charged with multiple marijuana charges, the arrest is only counted once under the more serious charge type (Distribution > Possession with Intent to Distribute > Possession > Public Consumption).

MPD collects race and ethnicity data according to the United States Census Bureau standards (https://www.census.gov/topics/population/race/about.html). Hispanic, which was previously categorized under the Race field prior to August 2015, is now captured under Ethnicity. All records prior to August 2015 have been updated to “Unknown (Race), Hispanic (Ethnicity)”. Race and ethnicity data are based on officer observation, which may or may not be accurate.

MPD cannot release exact addresses to the general public unless proof of ownership or subpoena is submitted. The GeoX and GeoY values represent the block location (approximately 232 ft. radius) as of the date of the arrest. Due to the Department’s redistricting efforts in 2012 and 2017, data may not be comparable in some years.

Arrestee age is calculated based on the number of days between the self-reported or verified date of birth (DOB) of the arrestee and the date of the arrest; DOB data may not be accurate if self...

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
pain relievers, tranquilizers, stimulants, and sedatives. The survey
covers substance abuse treatment history and perceived need for
treatment, and includes questions from the Diagnostic and Statistical
Manual (DSM) of Mental Disorders that allow diagnostic criteria to be
applied. Respondents are also asked about personal and family income
sources and amounts, health care access and coverage, illegal
activities and arrest record, problems resulting from the use of
drugs, and needle-sharing. Questions introduced in previous NHSDA
administrations were retained in the 2001 survey, including questions
asked only of respondents aged 12 to 17. These "youth experiences"
items covered a variety of topics, such as neighborhood environment,
illegal activities, gang involvement, drug use by friends, social
support, extracurricular activities, exposure to substance abuse
prevention and education programs, and perceived adult attitudes
toward drug use and activities such as school work. Also retained were
questions on mental health and access to care, perceived risk of using
drugs, perceived availability of drugs, driving behavior and personal
behavior, and cigar smoking. Questions on the tobacco brand used most
often were introduced with the 1999 survey and have been retained
through the 2001 survey. Demographic data include gender, race, age,
ethnicity, marital status, educational level, job status, veteran
status, and current household composition. In addition, in 2001 questions on purchase of marijuana were added.This study has 1 Data Set.