This collection focuses on how changes in the legal drinking age affect the number of fatal motor vehicle accidents and crime rates. The principal investigators identified three areas of study. First, they looked at blood alcohol content of drivers involved in fatal accidents in relation to changes in the drinking age. Second, they looked at how arrest rates correlated with changes in the drinking age. Finally, they looked at the relationship between blood alcohol content and arrest rates. In this context, the investigators used the percentage of drivers killed in fatal automobile accidents who had positive blood alcohol content as an indicator of drinking in the population. Arrests were used as a measure of crime, and arrest rates per capita were used to create comparability across states and over time. Arrests for certain crimes as a proportion of all arrests were used for other analyses to compensate for trends that affect the probability of arrests in general. This collection contains three parts. Variables in the Federal Bureau of Investigation Crime Data file (Part 1) include the state and year to which the data apply, the type of crime, and the sex and age category of those arrested for crimes. A single arrest is the unit of analysis for this file. Information in the Population Data file (Part 2) includes population counts for the number of individuals within each of seven age categories, as well as the number in the total population. There is also a figure for the number of individuals covered by the reporting police agencies from which data were gathered. The individual is the unit of analysis. The Fatal Accident Data file (Part 3) includes six variables: the FIPS code for the state, year of accident, and the sex, age group, and blood alcohol content of the individual killed. The final variable in each record is a count of the number of drivers killed in fatal motor vehicle accidents for that state and year who fit into the given sex, age, and blood alcohol content grouping. A driver killed in a fatal accident is the unit of analysis.

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 had at least one drink of any alcoholic beverage (such as beer, wine, or liquor) in the past month.In the US, alcohol use is legal for those ages 21 years and older and should be avoided or used in moderation (defined as consuming two or less drinks per day for men or one or less drinks per day for women). Excessive alcohol use includes binge drinking, heavy drinking, any underage alcohol use, and any alcohol use by pregnant persons. Alcohol use is associated with numerous health, safety, and social problems, including chronic diseases, unintentional injuries, interpersonal violence, fetal alcohol spectrum disorders, alcohol use disorders, and weakened interpersonal relationships and ability to function at work, school, or home. In general, people with higher socioeconomic status (SES) report drinking more frequently and more heavily than those with lower SES; however, people with lower SES are on average more negatively affected by alcohol-related harms. It is important for cities and communities to build strategies that create environments that reduce excessive alcohol use and prevent underage drinking.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

This layer represents the Percent of Adults who Drink Heavily calculated from the 2014-2017 Colorado Behavioral Risk Factor Surveillance System (County or Regional Estimates) data set. These data represent the estimated prevalence of Heavy Drinking among adults (Age 18+) for each county in Colorado. Heavy Drinking is defined for males as having 15 or more drinks per week and for females as having 8 or more drinks per week. Heavy Drinking is calculated from the number of days alcohol was consumed in the past 30 days, and the average number of drinks consumed on those 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).

Early onset of alcohol use was associated with alcohol dependence and other health problems. Although national data include information about alcohol consumption in Thailand,(1) sufficient information about the socio-ecological context associated with alcohol consumption among adolescents in a particular community is still limited. A few studies investigating alcohol consumption among adolescents were conducted in urban and suburban areas, presenting an estimated prevalence of current alcohol consumption ranging from 10.4% to 18.6%. Nowadays, one-half of the Thai population still resides in rural areas where healthcare provider characteristics, health literacy, and socioeconomic contexts may differ from those in urban areas. Recently, a related quantitative study about the substance abuse situation in a remote rural community, Chachoengsao Province, detected that 36.8% of adolescents reported being a current alcohol drinker and indicated that alcohol drinking was associated with substance abuse in the rural community, which was considered a major health issue in the Thai rural community. Unfortunately, information regarding risk factors for alcohol consumption among adolescents in this remote rural area was not uncovered. The present study aimed to identify the prevalence and factors associated with alcohol consumption among adolescents in a remote rural area using quantitative methods. Moreover, a qualitative study will explore the socio-ecological factors affecting alcohol consumption, including family members and friends, store and accessibility, and social and environmental factors. If factors associated with alcohol consumption among adolescents are explored, appropriate strategies and practical interventions may be implemented in this population to resolve this issue in the future. The study enrolled a total of 413 adolescents. On average, young adolescents initiated alcohol consumption at age 13. The lifetime drinking prevalence among adolescents was 60.5%, while the one-year drinking prevalence was 53.0%. The prevalence of hazardous drinking among current drinkers was 42.0%. Alcohol consumption was associated with females (adjusted prevalence ratio (APR): 1.19; 95% CI: 1.01–1.41), age ≥16 years (APR: 1.28; 95% CI: 1.09–1.50), having close friends consuming alcohol (APR: 1.75; 95% CI: 1.43–2.14), night out (APR: 1.93; 95% CI: 1.53–2.45), being a current smoker (APR: 1.39; 95% CI: 1.15–1.69), and having relationship (with boyfriend/girlfriend) problems (APR: 1.18; 95% CI: 1.01–1.38). Qualitative data demonstrated that individual and environmental factors, including friends, family, social media use, and alcohol accessibility, affect alcohol use in this population. Therefore, effective strategies should be implemented across multiple levels of the socio-ecological model simultaneously to alleviate alcohol consumption and attenuate its complications.

ชื่อเจ้าของฐานข้อมูล และการติดต่อ

ร.อ. ผศ.บุญทรัพย์ ศักดิ์บุญญารัตน์ ภาควิชาเวชศาสตร์ทหารและชุมชน วิทยาลัยแพทยศาสตร์พระมงกุฎเกล้า Capt. Asst.Prof.Boonsub Sakboonyarat, MD, MPH Department of Military and Community Medicine, Phramongkutklao College of Medicine, Bangkok, Thailand E-mail Boonsub1991@pcm.ac.th

Availability of data and materials

The datasets generated or analyzed during the current study are not publicly available because the data sets contain confidential information. Thus, due to ethics restrictions concerning the data sets, they are available from the corresponding author upon reasonable request.

การขอเข้าถึง Protocol และ ข้อมูล

กดที่ ปุ่ม ร้องขอข้อมูล ที่ หน้า Protocol และ ข้อมูล

Annual data on number of alcohol-specific deaths by sex, age group and individual cause of death, UK constituent countries.

Annual data for Great Britain on teetotalism, drinking in the week before survey interview, frequent drinking and units drunk, including analysis by sex, age and socioeconomic status.

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).

Prenatal alcohol-drinking is often measured with self-report, but it is unclear whether mothers give more accurate answers when asked while pregnant or some time after their pregnancy. There is also the question of whether to measure drinking in a dichotomous or continuous fashion. We sought to examine how the timing and scale of self-reports affected the content of reports. From a sample of 576 black mothers around Cape Town, South Africa, we compared prenatal reports of prenatal drinking with 5-year retrospective reports, and dichotomous metrics (drinking or abstinent) with continuous metrics (fluid ounces of absolute alcohol drunk per day). Amounts increased over the 5-year period, whereas dichotomous measures found mothers less likely to report drinking later. All four measures were weakly associated with birth weight, birth height, child head circumference soon after birth, and child intelligence at age 5. Furthermore, neither reporting time nor the scale of measurement were consistently related to the strengths of these associations. Our results point to problems with self-report, particularly with this population, but we recommend post-birth continuous measures as the best of the group for their flexibility and their consistency with previous research.

Value-based choice and compulsion theories of addiction offer distinct explanations for the persistence of alcohol use despite harms. Choice theory argues that problematic drinkers ascribe such high value to alcohol that costs are outweighed, whereas compulsion theory argues that problematic drinkers discount costs in decision making. The current study evaluated these predictions by testing whether alcohol use disorder (AUD) symptom severity (indexed by the AUDIT) was more strongly associated with the intensity item (maximum alcohol consumption if free, indexing alcohol value) compared to the breakpoint item (maximum expenditure on a single drink, indexing sensitivity to monetary costs) of the Brief Assessment of Alcohol Demand (BAAD) questionnaire, in student (n = 579) and community (n = 120) drinkers. The community sample showed greater AUD than the student sample (p = .004). In both samples, AUD severity correlated with intensity (students, r = 0.63; community, r = 0.47), but not with breakpoint (students, r = -0.01; community, r = 0.12). Similarly, multiple regression analyses indicated that AUD severity was independently associated with intensity (student, ΔR2 < 0.20, p < .001; community, ΔR2 = 0.09, p = .001) but not breakpoint (student, ΔR2 = 0.003, p = .118; community ΔR2 = 0.01, p = .294). There was no difference between samples in the strength of these associations. The value ascribed to alcohol may play a more important role in AUD severity than discounting of alcohol-associated costs (compulsivity), and there is no apparent difference between student and community drinkers in the contribution of these two mechanisms.

Assessments: Data were collated across a number of experiments and in all cases questionnaires were delivered at baseline and followed the same order. Demographic measures (age and gender) were collected. AUD severity was assessed using the ten-item Alcohol Use Disorders Identification Test (AUDIT) (Babor et al. 2001). The AUDIT total score ranges from 0-40, and can be divided into categories: low-risk (0–7), hazardous (8–15), harmful (16–19) and possibly dependent (20–40). Cronbach’s alpha for the AUDIT was .78 in the student and .81 in the community sample. The AUDIT has two subscales, measuring alcohol consumption and alcohol-related consequences (Doyle et al. 2007). Value and cost insensitivity constructs were measured with the Brief Assessment of Alcohol Demand (BAAD) questionnaire (Owens et al. 2015). The BAAD has three items. The first item indexes intensity of demand (‘If drinks were free, how many would you have in a single session?’), with possible responses ranging from 0 to 10+ drinks in increments of 1. The second item indexes Omax (‘What is the maximum total amount you would spend on drinks for yourself in a single session?’), with responses ranging from £0 to £40 in £4 increments. The final item indexes breakpoint (‘What is the maximum you would pay for a single drink?’) with responses ranging from £0 to £20 in £2 increments.

The first aim of the fellowship was to build on my PhD research to develop a novel brief intervention for hazardous drinking young people. My proposed intervention combines a number of elements with prior evidence of efficacy in hazardous alcohol use. High-risk individuals will be provided with personalised feedback regarding the specific negative emotions which trigger their drinking (for example, anger, sadness, boredom) (Blevins and Stephens 2016) and encouraged to generate individualised alternative coping strategies (Conrod et al. 2013). Crucially, individuals will also be instructed in functional imagery training, a promising technique used to encourage adoption of adaptive behaviours in high-risk scenarios. The two pilot studies proposed in clinical populations in this project are on hold due to COVID-19 restrictions. However, development of this intervention has continued and online pilot testing in student populations is ongoing. Data will be uploaded as and when these projects are complete. Additional aims of the fellowship included: 1) To publish completed research demonstrating that a brief, 6 minute mindfulness training procedure can reduce drinking under stress in students. This research has been published in the journal Addictive Behaviours and a full dataset is uploaded here. 2) To publish research validating a novel measure of negative coping motives (the Coping Motives Checklist). This measure will be used to identify specific negative triggers to alcohol use - and to provide personalised feedback on these motives - in my proposed novel intervention. Initial data linkage and analysis is ongoing and data will be uploaded when this is finalised. 3) Validation of a measure of alcohol valuation - the Brief Assessment of Alcohol Demand (BAAD) - to be used as a brief screening tool to identify those at risk of dependence. This research has been published in Addictive Behaviours and a full dataset is uploaded here.

The Drug Abuse Warning Network (DAWN) is a nationally representative public health surveillance system that has monitored drug related emergency department (ED) visits to hospitals since the early 1970s. First administered by the Drug Enforcement Administration (DEA) and the National Institute on Drug Abuse (NIDA), the responsibility for DAWN now rests with the Substance Abuse and Mental Health Services Administration's (SAMHSA) Center for Behavioral Health Statistics and Quality (CBHSQ). Over the years, the exact survey methodology has been adjusted to improve the quality, reliability, and generalizability of the information produced by DAWN. The current approach was first fully implemented in the 2004 data collection year. DAWN relies on a longitudinal probability sample of hospitals located throughout the United States. To be eligible for selection into the DAWN sample, a hospital must be a non-Federal, short-stay, general surgical and medical hospital located in the United States, with at least one 24-hour ED. DAWN cases are identified by the systematic review of ED medical records in participating hospitals. The unit of analysis is any ED visit involving recent drug use. DAWN captures both ED visits that are directly caused by drugs and those in which drugs are a contributing factor but not the direct cause of the ED visit. The reason a patient used a drug is not part of the criteria for considering a visit to be drug-related. Therefore, all types of drug-related events are included: drug misuse or abuse, accidental drug ingestion, drug-related suicide attempts, malicious drug poisonings, and adverse reactions. DAWN does not report medications that are unrelated to the visit. The DAWN public-use dataset provides information for all types of drugs, including illegal drugs, prescription drugs, over-the-counter medications, dietary supplements, anesthetic gases, substances that have psychoactive effects when inhaled, alcohol when used in combination with other drugs (all ages), and alcohol alone (only for patients aged 20 or younger). Public-use dataset variables describe and categorize up to 22 drugs contributing to the ED visit, including toxicology confirmation and route of administration. Administrative variables specify the type of case, case disposition, categorized episode time of day, and quarter of year. Metropolitan area is included for represented metropolitan areas. Created variables include the number of unique drugs reported and case-level indicators for alcohol, non-alcohol illicit substances, any pharmaceutical, non-medical use of pharmaceuticals, and all misuse and abuse of drugs. Demographic items include age category, sex, and race/ethnicity. Complex sample design and weighting variables are included to calculate various estimates of drug-related ED visits for the Nation as a whole, as well as for specific metropolitan areas, from the ED visits classified as DAWN cases in the selected hospitals.This study has 1 Data Set.

BackgroundAccurate estimates of the impact of alcohol on overall and age-specific mortality are crucial for formulating health policies. However, different approaches to estimating alcohol-attributable mortality provide different results, and a detailed comparison of age-specific estimates is missing.MethodsUsing data on cause of death, alcohol consumption, and relative risks of mortality at different consumption levels, we compare eight estimates of sex- and age-specific alcohol-attributable mortality in France (2010) and Finland (2013): five estimates using cause-of-death approaches (with one accounting for contributory causes), and three estimates using attributable fraction (AF) approaches.ResultsAF-related approaches and the approach based on alcohol-related underlying and contributory causes of death provided estimates of alcohol-attributable mortality that were twice as high as the estimates found using underlying cause-of-death approaches in both countries and sexes. The differences across the methods were greatest among older age groups An inverse U-shape in age-specific alcohol-attributable mortality (peaking at around age 65) was observed for cause-of-death approaches, with this shape being more pronounced in Finland. AF-related approaches resulted in different estimates at older ages: i.e., mortality was found to increase with age in France; whereas in Finland mortality estimates depended on the underlying assumptions regarding the effects of alcohol consumption on cardiovascular mortality.ConclusionsWhile the most detailed approaches (i.e., the AF-related approach and the approach that includes underlying and contributory causes) are theoretically able to provide more accurate estimates of alcohol-attributable mortality, they–especially the AF approaches- depend heavily on data availability and quality. To enhance the reliability of alcohol-attributable mortality estimates, data quality for older age groups needs to be improved.

This table contains 334320 series, with data for years 2000 - 2000 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (199 items: Canada; Newfoundland and Labrador; Health and Community Services St. John's Region; Newfoundland and Labrador (Peer group H);Health and Community Services Eastern Region; Newfoundland and Labrador (Peer group D) ...), Age group (14 items: Total; 12 years and over;15-19 years;12-19 years;12-14 years ...), Sex (3 items: Both sexes; Males; Females ...), Frequency of having 5 or more drinks on one occasion (5 items: Total population for the variable population reporting drinking; Never 5 or more drinks on one occasion;5 or more drinks on one occasion; 12 or more times a year;5 or more drinks on one occasion; less than 12 times a year ...), Characteristics (8 items: Number of persons; Coefficient of variation for number of persons; High 95% confidence interval - number of persons; Low 95% confidence interval - number of persons ...).

The survey Epidemiological Survey on Substance Abuse in Germany 2018 (ESA) is a representative survey on the use and abuse of psychoactive substances among adolescents and adults aged 18 to 64 years, which has been conducted regularly nationwide since 1980. The data collection took place between March and July 2018 and was conducted by infas Institut für angewandte Sozialwissenschaft GmbH on behalf of the IFT, Institute for Therapy Research in Munich. The nationwide study was conducted in a mixed-mode design as a standardised telephone survey (CATI: Computer Assisted Telephone Interview), as a written-postal survey (PAPSI: Paper and Pencil Self Interview) and as an online survey. The study is financially supported by the Federal Ministry of Health. The survey covered 30-day, 12-month and lifetime prevalence of tobacco use (tobacco products as well as shisha, heat-not-burn products and e-cigarettes), alcohol, illicit drugs and medicines. For conventional tobacco products, alcohol, selected illicit drugs (cannabis, cocaine and amphetamines) and medications (painkillers, sleeping pills and tranquillisers), additional diagnostic criteria were recorded with the written version of the Munich Composite International Diagnostic Interview (M-CIDI) for the period of the last twelve months. Furthermore, a series of socio-demographic data, the physical and mental state of health, nutritional behaviour, mental disorders as well as modules on the main topics of children from families with addiction problems, reasons for abstinence in the field of alcohol and the perception or knowledge of the health risk posed by alcohol were recorded. Physical and mental health status: self-assessment of health status; self-assessment of mental well-being; chronic illnesses; frequency of physical problems or pain without clear explanation, anxiety attack / panic attack, frequent worries, strong fears in social situations, strong fears of public places, means of transport or shops, strong fears of various situations, e.g. use of lifts, tunnels, aeroplanes as well as severe weather, sadness or low mood, loss of interest, tiredness or lack of energy, unusually happy, over-excited or irritable, stressful traumatic events, psychiatric, psychological or psychotherapeutic treatment in the last 12 months; physical activity and diet in the last three months: frequency of physical activity (moving from place to place, recreational sports, work-related physical activity) per week; duration of physical activity; consumption of selected foods (low-fat dairy products, raw vegetables, fresh salads, herbs, fresh fruit, cereal products, herbal tea or fruit tea); illness caused by excessive alcohol consumption. 2. Medication use: type of medication use (painkillers, sleeping pills, tranquilizers, stimulants, appetite suppressants, antidepressants, neuroleptics and anabolic steroids) in the last 12 months; frequency of use of painkillers, sleeping pills, tranquilizers, stimulants, appetite suppressants, antidepressants and neuroleptics in the last 30 days and respective prescription by a physician; use of painkillers, sleeping pills or tranquilizers in the last 12 months; tendencies towards dependence: In the last 12 months, the following were asked: significant problems related to the use of painkillers, sleeping pills and tranquillisers (neglect of household and children, poor performance, injury-prone situations while under the influence of medication, unintentional injuries such as accidents or falls, legal problems, accusations from family or friends, broken relationship, financial difficulties, physically attacking or hurting someone, use in larger quantities or for longer periods than prescribed or intended by the doctor, discomfort when stopping the medication. discomfort when stopping the medication and then continuing to take the medication to avoid discomfort, higher doses required for desired effect or weakened effect, unsuccessful attempts to reduce or stop medication use, large amount of time required to obtain medication or recover from effects, restriction of activities, taking medication despite knowledge of harmful effects, craving for medication so strong that resisting or thinking otherwise was not possible. 3. Smoking: smoking status; smoking behaviour: smoked more than 100 cigarettes, cigars, cigarillos, pipes in total during lifetime; type of tobacco use (cigarettes, cigars, cigarillos, pipe); age of initiation of tobacco use; time of last tobacco use; specific number of days in the last month on which cigarettes (or cigars, cigarillos or pipes) were smoked and average number smoked per day; average daily consumption of 20 or more cigarettes (or 10 cigarillos, 7 pipes, 5 cigars) in the last 12 months; smoking behaviour in the last 12 months (had to smoke more than before to get the same effect, effect of smoking decreased, smoked much more than intended, tried unsuccessfully to cut down or quit smoking for a few days, chain smoker, gave up important activities because of smoking, continued to smoke during serious illness, smoking interfered with work, school or housework, smoked in situations where there was a high risk of injury, continued to smoke even though it made other people angry or unhappy, unable to resist strong cravings for tobacco, unable to think of anything else because of strong cravings for tobacco); physical or mental health problems in the last 12 months due to smoking; continued to smoke in spite of physical or mental health problems; health problems due to smoking cessation in the last 12 months (low mood, insomnia, irritability/annoyance, restlessness, difficulty concentrating, slow heartbeat, weight gain); started smoking again to avoid complaints; serious attempts to stop smoking in the last 12 months; successful attempt to quit smoking; ever used shisha (hookah), a Neat-Not-Burn product or an e-cigarette, e-shisha, e-pipe, e-cigar and time of last use; age at first use of e-cigarette/e-cigar/e-shisha/e-pipe and frequency of use in the last 30 days; use of e-cigarettes/e-cigars/e-shishas/e-pipes with or without nicotine. 4. Alcohol consumption: age at first glass of alcohol; alcohol consumption at least once a month; age of onset of regular alcohol consumption; alcohol excesses (binge drinking) in the past and frequency of alcohol excesses in the last 12 months; age at first alcohol excess; time of last alcohol consumption; total number of days with alcohol consumption in the last 30 days or 12 months; concrete information on the average amount of beer, wine/sparkling wine and mixed drinks containing alcohol (alcopops, long drinks, cocktails or punch) consumed in the last 30 days or 12 months. 12 months; concrete information on the average amount of beer, wine/sparkling wine, spirits and mixed drinks containing alcohol (alcopops, long drinks, cocktails or punch) consumed in the last 30 days or in the last 12 months; number of days with consumption of at least five glasses of alcohol in the last 30 days or 12 months; problems caused by alcohol in the last 30 days or 12 months; number of days with consumption of at least five glasses of alcohol in the last 30 days or 12 months. 12 months; problems caused by alcohol in the last 12 months (significant difficulties at work, school or home, situations involving risk of injury, trouble with the police, accusations from family or friends, broken relationship, financial difficulties, physically attacking or hurting someone); alcohol consumption behaviour in the last 12 months (had to drink more than before to get the same effect, effect of alcohol consumption decreased, drank much more than intended, tried unsuccessfully to drink less alcohol or to stop drinking altogether, drank a lot of alcohol over several days, been drunk or suffered from the effects of alcohol, gave up important activities because of alcohol, could not resist strong craving for alcohol, could not think of anything else because of strong craving for alcohol); symptoms after alcohol withdrawal (trembling, insomnia, anxiety, sweating, hallucinations (seizure), nausea, vomiting, urge to move, rapid heartbeat); drank alcohol to avoid such complaints; physical illnesses or mental problems related to alcohol in the last 12 months; alcohol consumption despite physical or mental problems; increased cancer incidence in the last 12 months; alcohol consumption in spite of physical or mental problems. increased cancer risk due to alcohol consumption (stomach cancer, ovarian cancer, breast cancer, mouth and oesophagus cancer, brain tumour, bowel cancer, liver cancer, bladder cancer); alcohol consumption in the last 30 days; personal reasons for abstaining from alcohol (alcohol causes people to lose control, condition of illness worsens due to alcohol, parents had an alcohol problem, family is against alcohol consumption, alcohol consumption is against my spiritual/religious attitude, I do not like the taste and/or smell of alcohol, own pregnancy or partner´s pregnancy). 5. Drug use: drug experience with cannabis (hashish, marijuana), stimulants, amphetamines, ecstasy, LSD, heroin, other opiates such as e.g. codeine, methadone, opium, morphine), cocaine, crack, sniffing substances and mushrooms as intoxicants or never tried any of these drugs before; ever used substances that imitate the effect of illegal drugs (legal highs, research chemicals, bath salts, herbal mixtures or new psychoactive substances (NPS); used such legal substances in the last 12 months; form of substances consumed (herbal mixtures for smoking, powders, crystals or tablets as well as liquids); generally tried drugs; frequency of drug use in total, in each case related to cannabis (hashish, marijuana), stimulants, amphetamines, ecstasy, LSD, heroin, other opiates, cocaine, crack cocaine, sniffing substances, mushrooms resp. Legal highs, research chemicals, bath salts, herbal mixtures, NPS; time of last use of any of the above drugs (in the

This dataset charted Finnish consumption of alcoholic beverages in terms of individual drinking occasions. The data were collected as part of the Finnish Drinking Habits Survey 2016 (main data: FSD3282). FSD's holdings also include a dataset belonging to the same study concerning abstaining from drinking during occasions where other people consumed alcohol (FSD3314). The study examined situations in which the respondents had consumed alcoholic beverages: how many centilitres they had consumed of different alcoholic drinks, where, when and with whom. The respondents could provide information on multiple drinking occasions, and the same questions were asked about each of them. The data also contain conversions made from variables in the questionnaire, e.g. conversions of consumed quantities of different drinks into pure alcohol. The questionnaire (in Finnish) describes in more detail the coefficients used in the conversions as well as the formula for calculating the respondents' estimated blood-alcohol content (per mille) during each drinking occasion. Background variables include gender, age, date and weekday of the drinking occasion as well as starting and ending times for drinking.

Abstract Objectives: to assess alcohol intake prevalence and identify associated factors among pregnant women in the municipality of Rio Grande, RS, Brazil. Methods: this was a crosssectional study which included all parturient women residing in the municipality who gave birth in 2013. Two outcomes were characterized: alcohol intake during pregnancy and excessive alcohol intake during pregnancy. In the analysis, proportions were tested using the Chisquare test, whilst Poisson regression was used in the multivariate analysis. Results: 9.4% (CI95%= 8.210.5) of the 2,685 parturient women studied reported having consumed alcohol during pregnancy, with beer being most common beverage. Following adjustment, the factors associated with alcohol intake in pregnancy were: age ≥30 years, brown skin colour, living without a partner, low schooling, tobacco smoking and illicit drug use, having had more children and late onset of prenatal care. Excessive alcohol intake was found in 12.7% (CI95%= 8.616.9) of those who reported drinking during pregnancy and the factors associated with this practice were age ≥30 years, lower schooling and illicit drug use. Conclusions: this study found high alcohol intake during the gestation period and identified women more susceptible to this practice. There is an evident need for health professionals to work on preventing and handling alcohol intake among pregnant women in the municipality

This table contains 18480 series, with data for years 1994 - 1998 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (not all combinations are available): Geography (11 items: Canada; Prince Edward Island; Nova Scotia; Newfoundland and Labrador ...), Age group (14 items: Total; 12 years and over; 15-19 years; 12-19 years; 12-14 years ...), Sex (3 items: Both sexes; Males; Females ...), Frequency of having 5 or more drinks on one occasion (5 items: Total population for the variable population reporting drinking;5 or more drinks on one occasion; 12 or more times a year;5 or more drinks on one occasion; less than 12 times a year; Never 5 or more drinks on one occasion ...), Characteristics (8 items: Number of persons; High 95% confidence interval - number of persons; Coefficient of variation for number of persons; Low 95% confidence interval - number of persons ...).

Annual data on age-standardised and age-specific alcohol-specific death rates in the UK, its constituent countries and regions of England.

Colorado County BRFSS Binge Drinking Prevalence represents the Percent of Adults who Binge Drink calculated from the 2018-2022 Colorado Behavioral Risk Factor Surveillance System (County Estimates) data set. These data represent the estimated prevalence of Binge Drinking among adults (Age 18+) for each county in Colorado. Binge Drinking is defined for males as having five or more drinks on one occasion and for females as having four or more drinks on one occasion within the past 30 days. Binge Drinking is calculated from the number of days alcohol was consumed in the past 30 days, and the average number of drinks consumed on those days. Data is suppressed if there was not enough data to calculate a reliable estimate. The estimate for each county was derived from multiple years of Colorado Behavioral Risk Factor Surveillance System data (2018-2022). This file was developed for use in activities and exercises within the Colorado Department of Public Health and Environment (CDPHE), including the Alcohol Outlet Density StoryMap. COUNTY (County Name)FULL (Full County Name)LABEL (Proper County Name)County FIPS (County FIPS Code as String)NUM FIPS (County FIPS Code as Number)CENT LAT (County Centroid Latitude)CENT LONG (County Centroid Longitude)US FIPS (Full FIPS Code)Binge Percent (County estimate for prevalence of Binge Drinking among adults Age 18+)Lower Confidence Limit (Lower 95% Confidence Interval for Binge Percent Value)Upper Confidence Limit (Upper 95% Confidence Interval for Binge Percent Value)Years (2018-2022)

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 1999 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. Demographic data include sex, race, age, ethnicity, marital status, educational level, job status, veteran status, and current household composition. This study has 1 Data Set.

Per capita alcohol consumption in the United States has increased in the past couple of decades to reach 2.51 gallons of ethanol per capita in 2021. Beer has accounted for the largest share of the alcohol market in the United States over most of the last decade, but was overtaken by spirits for the first time in 2022. Health risks Constant and excessive alcohol use has been shown to cause many health complications and increase the risk of many diseases. For example, alcohol consumption increases the risk of various types of cancer, cardiovascular disease, and liver disease. The cost of such health complications from alcohol is substantial. As of 2020, it was estimated that the health care costs alone from the abuse of alcohol in the United States were around 27 billion dollars a year. Liver cirrhosis A common health complication from the abuse of alcohol is liver cirrhosis. Cirrhosis is scarring of the liver from repeated injury. It can cause other health complications such as high blood pressure, bleeding, and infection, and can result in early death if left untreated. In 2019, there were over 24,000 alcohol-related liver cirrhosis deaths in the United States, almost double the number reported 15 years earlier.