The Use of Alcohol, Tobacco, Illegal Drugs and Medicines
An estimate of consumption and substance-related disorders in Germany
; ; ; ;
Background: Prevalence estimates of the use of tobacco, alcohol, illegal drugs, and psychoactive medications and of substance-related disorders enable an assessment of the effects of substance use on health and society.
Methods: The data used for this study were derived from the 2018 Epidemiological Survey of Substance Abuse (Epidemiologischer Suchtsurvey, ESA). The sample of the German adult population comprised 9267 persons aged 18 to 64 (response rate, 42%). Population estimates were obtained by extrapolation to a total resident population of 51 544 494 people.
Results: In the 30 days prior to the survey, 71.6% of the respondents (corresponding to 36.9 million persons in the population) had consumed alcohol, and 28.0% (14.4 million) had consumed tobacco. 4.0% reported having used e-cigarettes, and 0.8% reported having used heat-not-burn products. Among illegal drugs, cannabis was the most commonly used, with a 12-month prevalence of 7.1% (3.7 million), followed by amphetamines (1.2%; 619 000). The prevalence of the use of analgesics without a prescription (31.4%) was markedly higher than that of the use of prescribed analgesics (17.5%, 26.0 million); however, analgesics were taken daily less commonly than other types of medication. 13.5% of the sample (7.0 million) had at least one dependence diagnosis (12-month prevalence).
Conclusion: Substance use and the consumption of psychoactive medications are widespread in the German population. Substance-related disorders are a major burden to society, with legal substances causing greater burden than illegal substances.
Substance use is associated with a multitude of health and social effects. The results of the Global Burden of Disease Study clearly demonstrate that alcohol and tobacco use are among the main risk factors worldwide for premature mortality and life years lost due to disease and disability (1, 2). In 2015, every third person in Western Europe reported at least one episode of heavy drinking (≥ 60 g ethanol) in the preceding 30 days, every fifth person smoked tobacco daily, and 7% of respondents stated that they had consumed cannabis in the previous 12 months (3). Prevalence rates for the use of other illegal drugs such as amphetamines (0.6%), cocaine (1.1%), and opioids (0.4%) were much lower (3).
The consumption of psychoactive substances is associated with an increased risk for substance disorders. The number of individuals with a substance-related dependence per 100 000 people was estimated to be 881 for alcohol and 425 for cannabis in Western Europe in 2015. The number of deaths caused by substance use was reported to be 78 for tobacco, 19 for alcohol, and seven for illegal drugs per 100 000 people in the population (3).
The Epidemiological Survey of Substance Abuse (Epidemiologischer Suchtsurvey, ESA) yields population-representative data on the prevalence of legal and illegal substance use, hazardous forms of use, as well as substance-related disorders according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). Projected prevalence estimates for various indicators of use make it possible to quantify the current burden caused by substance use and substance-related disorders.
Study design and sample
The 2018 ESA study population is made up of German-speaking individuals aged between 18 and 64 years living in private households in Germany. The sample was drawn in a two-stage selection process. In a first step, 254 municipalities (sample points) were randomly selected. In a second step, addresses were drawn from the respective population registers using a systematic random selection. Data was collected by means of written and online questionnaires or telephone interviews (mixed-method design). The adjusted sample included 9267 individuals (response rate = 41.6%). See the eMethods section for a detailed description of the methods used (mode effects, non-response analyses).
Tobacco, e-products, and heat-not-burn products
Prevalence estimates for the use of traditional tobacco products, such as cigarettes, cigars, cigarillos, and pipes, water pipes (hookahs), e-cigarettes, e-hookahs, e-pipes, e-cigars, and heat-not-burn products (tobacco heaters), are based on the preceding 30 days (4). Daily cigarette consumption is defined as daily use of at least one cigarette and heavy cigarette consumption as daily use of at least 20 cigarettes (30-day prevalence).
Prevalence estimates of alcohol consumption in the preceding 30 days were made using a beverage-specific quantity–frequency index. Episodic heavy drinking was defined as the consumption of five or more glasses of alcohol (approximately 70 g pure alcohol) on at least one day in the preceding 30 days. The daily consumption of more than 12 g (women) and 24 g (men) of pure alcohol was defined as the threshold for hazardous alcohol consumption (5, 6).
The 12-month prevalence for the use of illegal drugs was assessed for cannabis (hashish, marijuana), amphetamine and methamphetamine, ecstasy, LSD, heroin, other opiates, cocaine/crack cocaine, hallucinogenic mushrooms, and new psychoactive substances (NPS).
The prevalence values for the use of medicines in the preceding 30 days, as well as their daily use, were recorded for analgesics, hypnotics or sedatives, analeptics, anorectics, antidepressants, and neuroleptics. Respondents allocated each medication they had taken to one of the categories in a list of the most common types of preparations.
Abuse and dependence were recorded as substance-related disorders according to DSM-IV (7) criteria for the use of alcohol, cannabis, cocaine, amphetamine, analgesics, as well as hypnotics and sedatives. The items in the Munich Composite International Diagnostic Interview (M-CIDI) were used for the purposes of classification. Dependence is the only diagnosis defined for tobacco.
Descriptive data on substance use in the form of prevalence estimates with 95% confidence intervals are presented separately for the total population, as well as for men and women. In order to align the data with the distribution of the adult German population, all analyses were weighted (according to age, sex, education level, federal state, and municipality size class). The population size of 51 544 494 people (26 149 029 men; 25 395 465 women) as of 31.12.2017 was used for simple projections by extrapolation to the resident population aged between 18 and 64 years (10). Due to the complex sample design, standard errors were estimated using Taylor series (e1). All analyses were performed using Stata 14.1 (Stata Corp LP; College Station, TX, USA).
Tobacco, e-products, and heat-not-burn products
The prevalence of use of traditional tobacco products within the preceding 30 days was 23.3% (12.0 million individuals) and the prevalence of daily tobacco use was 15.1% (7.8 million individuals) (Table 1). Of the tobacco users, 23.4% (2.8 million) reported smoking more than 20 cigarettes a day. The prevalence of water pipe smoking was 4.2% (2.2 million individuals). In all, 4.0% (2.1 million individuals) reported using e-cigarettes and 0.8% (412 000 individuals) heat-not-burn products. Higher prevalence rates were seen among men compared to women across all three product categories.
A total of 71.6% of respondents (36.9 million individuals) stated that they had consumed alcohol in the preceding 30 days (Table 2). Of those that had consumed alcohol, 34.5% reported at least one episode of heavy drinking, with the prevalence for men (42.8%) being higher compared to women (24.6%). The prevalence of alcohol use in hazardous quantities was 18.1%, whereby there was no statistically significant difference between the prevalence among men (16.7%) and that among women (19.7%).
With a 12-month prevalence of 7.1% (3.7 million individuals), cannabis was the most frequently used illegal drug, followed by amphetamine at 1.2% (619 000 individuals) (Table 3). The use of cocaine/crack cocaine and ecstasy was each reported by 1.1% of respondents. Methamphetamine had the lowest prevalence at 0.2%. Sex differences in substance use were largely not statistically significant—only for cannabis and illegal drugs in general was consumption higher among men compared to women.
In the 30 days prior to the survey, prescription (17.5%; 9.0 million) as well as over-the-counter analgesics (31.4%; 16.2 million individuals) were the most commonly used medicines, with significantly higher prevalence rates among women than among men (Table 4). Antidepressants were the second most frequently used prescription medicines at 4.1% (2.1 million individuals). Of the over-the-counter medicines, hypnotics and sedatives (2.0%; 1.0 million individuals) were the second most commonly used. If prescribed by a physician, women took antidepressants significantly more frequently than men. The percentages for the daily use of prescription antidepressants (87.7%) and neuroleptic agents (78.0%) were the highest. The daily use of non-prescription medications was significantly lower.
With a 12-month prevalence of 8.6% (4.4 million individuals), tobacco dependence as defined in DSM-IV was the most common substance-related disorder, followed by analgesic (3.2%; 1.6 million individuals) and alcohol dependence (3.1%; 1.6 million individuals) (Table 5). The prevalence rates for dependence on illegal drugs as well as hypnotics/sedatives were both under 1.0%. The percentage for analgesic abuse was highest at 7.6%, followed by alcohol abuse at 2.8%. With the exception of analgesic dependence (men: 2.7%; women: 3.6%), substance-related disorders were more common in men compared to women.
In all, 13.5% of respondents exhibited at least one of the dependence disorders shown in Table 5, which corresponds to 7.0 million 18- to 64-year-olds in the population. Excluding tobacco dependence, 6.7% of respondents, or 3.5 million individuals, qualified for a dependence disorder (data not shown).
With 14.4 million current smokers, tobacco use is widespread in Germany. As such, the percentage of current smokers in Germany is significantly higher compared to Belgium, the Netherlands, Great Britain, Ireland, Denmark, Sweden, and Finland, with a prevalence that holds a mid-position among European Union countries (11). Tobacco use is associated with significant risks for cancer as well as cardiovascular, respiratory, and vascular diseases (12, 13, e2). The total number of tobacco-related deaths in Germany in 2013 was estimated at 121 000, with more deaths among men (85 000) compared to women (36 000) (12). Based on the 2018 ESA data, one can assume that 4.4 million of 18- to 64-year-olds in Germany are tobacco-dependent.
Although the use of electronic inhalation products has increased in Germany (14–16), the prevalence rates for e-cigarette and heat-not-burn product use are still low at 4.0% and 0.8%, respectively. The DEBRA study reported similar rates for e-cigarette use (17, 18). Since the aerosol produced by e-cigarettes contains fewer harmful substances than the smoke from traditional tobacco cigarettes, e-cigarette use is associated with fewer health risks for smokers (19). However, studies on the long-term health effects of e-cigarettes are still lacking. E-cigarettes are often used for smoking cessation and are therefore primarily used by smokers (14, 18, 20, e3). An analysis of ESA data from 2015 showed that 11% of smokers were able to quit with the help of e-cigarettes (14). However, a number of studies suggest that the use of e-cigarettes increases the risk among former smokers and non-smokers, in particular adolescents, of (re-)starting the use of traditional combustible tobacco products (19, 21, e4, e5).
In international comparisons, Germany is one of the high-consumption countries with a pro capita consumption of 10.7 liters of pure alcohol (3), which leads to high alcohol-related morbidity and mortality (22). While heavy alcohol consumption increases the long-term risk for a number of non-communicable diseases, e.g., cardiovascular diseases and cancer (23), episodic heavy drinking is a risk factor for acute effects such as falls or traffic accidents, as well as irreversible damage to the brain and nervous system (24–26). Moreover, third parties may suffer injury, e.g., due to alcohol consumption during pregnancy or as a result of traffic accidents. For example, the annual number of children born with fetal alcohol spectrum disorders (FASD) in Germany is estimated to be 12 650, and 45.1% of all third-party deaths in traffic accidents (e.g., pedestrians) can be causally attributed to alcohol consumption (27). The present study revealed approximately 3.1% of respondents to be alcohol-dependent, which corresponds to 1.6 million individuals in the population. The annual economic cost of alcohol consumption in Germany is estimated at 26.7 billion Euro, compared to the far lower tax revenues from the alcohol tax of 3.2 billion Euro (28, 29, e6).
In an international comparison, the 12-month prevalence of cannabis use in Germany of 7.1% is in line with the total European average (30). Cannabis dependence was found in 0.6% of study participants. Prescription of cannabis medication by physicans was legalized in Germany in 2017. Against the backdrop of the current political debate on regulation, a recent study emphasizes the fact that the health risks of cannabis consumption should not be underestimated (31). For example, there is a link between cannabis use and the development of anxiety disorders and depression, and there is also an increased risk for the re-emergence of bipolar symptoms (e7, e8). Furthermore, the marked increase in the concentration of tetrahydrocannabinol (THC) in recent years is accompanied by incalculable health risks (32).
At 1.2%, the prevalence of amphetamine use in Germany was more than twice the European total (0.5%) (30). Interestingly, the prevalence for new psychoactive substances (NPS) (0.9%) is higher than for methamphetamine (0.2%). A regional comparison also shows that methamphetamine use was statistically significantly more widespread in Saxony, Thuringia, and Bavaria in 2015 compared to other German federal states, whereas NPS use was almost evenly distributed across federal states (33). The higher methamphetamine prevalence in the regions close to the Czech Republic has been confirmed by recent wastewater analyses. Compared to other cities investigated in the study, Dresden has the highest inhabitant-specific load (34).
In order for medicines to confer a therapeutic benefit, they need to be used as prescribed and not over a long time period (35, 36). This applies not only to addictive analgesics, but also to over-the-counter non-opioid analgesics, for instance. Incorrect use over a longer period of time (≥ 15 days/month) can cause medication-overuse headache and promote the use of further painkillers, thereby in turn increasing the likelihood for developing medication abuse or dependence (36). Projections put the number of analgesic-dependent 18- to 64-year-olds at 1.6 million. Analyses using the ESA data from 2015, which make a distinction between opioid and non-opioid analgesics, estimated the prevalence of opioid analgesic use disorders according to DSM-V at 1% and the percentage of all mental disorders caused by analgesics at 12% (37). According to the available evidence, the majority of analgesic dependence disorders can be attributed to non-opioid analgesics that were obtained either by private prescriptions or as pharmacy-only medications. This share can be explained by the high prevalence of use combined with the psychological dependence potential of non-opioid analgesics (36). The prevalence of hypnotic/sedative use (30 days) in the population is much lower than that for analgesics, which is reflected in the lower prevalence of dependence disorders.
The vast majority of antidepressants and neuroleptic agents used were prescribed by a physician (population prevalence). The clearly low figures for the daily use of almost all medicines not prescribed by a physician suggests that abuse of these medication groups, with the exception of analgesics, is rare. With regard to analgesics, the high concordance between the population estimate on daily use (1.9 million individuals) and the estimate on analgesic dependence (1.6 million individuals) clearly demonstrates the high dependence potential of these medications.
By virtue of its multi-method design, complex sample, and suitable sample size, the 2018 Epidemiological Survey of Substance Abuse yields reliable, population-representative data on the general adult population aged 18–64 years. Biases may be caused by the systematic non-participation of certain user groups (38). For example, non-responders who filled in the non-response-questionnaire more often exhibited problematic consumption patterns, such as episodic heavy drinking, compared to study participants, but had a lower prevalence for overall consumption (eMethods). Therefore, consumption prevalence is likely to be overestimated and the prevalence of problematic consumption patterns underestimated. Limitations also arise from the fact that the responses of those questioned differ according to the survey method used, and that the estimates are based on self-reported information (38, 39, e9). When interpreting the results, one must bear in mind that the present study design precluded the possibility of reaching population groups such as homeless individuals or prison inmates in whom higher prevalence rates for substance use and substance-related disorders are assumed (40). Consequently, the fact that certain subgroups are inaccessible increases the underestimation of reported prevalence rates on substance use with increasing subgroup marginalization.
In summary, the results of this study indicate that substance use and hazardous consumption patterns are widespread in the general German population and that substance-related disorders, particularly due to legal substances such as tobacco and alcohol, as well as over-the-counter analgesics, represent a considerable burden on society.
The 2018 Epidemiological Survey of Substance Abuse (ESA) was funded by the German Federal Ministry of Health (Bundesministerium für Gesundheit, BMG) (ref: ZMVI1–2517DSM200). Funding is not subject to conditions.
Conflict of interest statement
The authors state that they have no conflicts of interest.
Manuscript submitted on 3 April 2019, revised version accepted on 24 June 2019.
Translated from the original German by Christine Rye.
Dipl.-Soz., B. Sc. Psych. Josefine Atzendorf
IFT Institut für Therapieforschung
80804 München, Germany
Cite this as:
Atzendorf J, Rauschert C, Seitz NN, Lochbühler K, Kraus L:
The use of alcohol, tobacco, illegal drugs and medicines—an estimate of consumption and substance-related disorders in Germany. Dtsch Arztebl Int 2019; 116: 577–84. DOI: 10.3238/arztebl.2019.0577
For eReferences please refer to:
eMethods Section, eTables:
Department of Public Health Sciences, Centre for Social Research on Alcohol and Drugs, Stockholm University, Stockholm, Schweden: Prof. Dr. phil. Ludwig Kraus
Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Ungarn:
Prof. Dr. phil. Ludwig Kraus
|1.||GBD 2017 Risk Factors Collaborators: Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018; 392: 1923–94 CrossRef|
|2.||GBD 2015 Risk Factors Collaborators: Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the global burden of disease study 2015. Lancet 2016; 388: 1659–724 CrossRef|
|3.||Peacock A, Leung J, Larney S, et al.: Global statistics on alcohol, tobacco and illicit drug use: 2017 status report. Addiction 2018; 113: 1905–26 CrossRef MEDLINE|
|4.||World Health Organization: Guidelines for controlling and monitoring the tobacco epidemic. Geneva: WHO Press 1998.|
|5.||Burger M, Bronstrup A, Pietrzik K: Derivation of tolerable upper alcohol intake levels in Germany: a systematic review of risks and benefits of moderate alcohol consumption. Prev Med 2004; 39: 111–27 CrossRef MEDLINE|
|6.||Seitz HK, Bühringer G, Mann K: Grenzwerte für den Konsum alkoholischer Getränke. In: Deutsche Hauptstelle für Suchtfragen, (ed.): Jahrbuch Sucht 2008. Geesthacht: Neuland 2008; 205–8.|
|7.||American Psychiatric Association: DSM-IV Diagnostic and statistical manual of mental disorders. Washington, DC: American Psychiatric Association 1994.|
|8.||Wittchen HU: Reliability and validity studies of the WHO-Composite International Diagnostic Interview (CIDI): a critical review. J Psychiatr Res 1994; 28: 57–84 CrossRef|
|9.||Wittchen HU, Beloch E, Garczynski E, et al.: Münchener Composite International Diagnostic Interview (M-CIDI), paper-pencil 2.2, 2/95. München: Max-Planck-Institut für Psychiatrie, Klinisches Institut 1995.|
|10.||Statistisches Bundesamt: Fortschreibung des Bevölkerungsstandes Deutschland. Ergebnisse auf Grundlage des Zensus 2011. www.destatis.de/DE/ZahlenFakten/GesellschaftStaat/Bevoelkerung/Bevoelkerungsstand/Bevoelkerungsstand.html 2019. (last accessed on 10 Januray 2019).|
|11.||European Union: Special Eurobarometer 458 “Attitudes of Europeans towards tobacco and electronic cigarettes”. http://data.europa.eu/euodp/en/data/dataset/S2146_87_1_458_ENG Directorate-General for Communication 2017 (last accessed on 19 July 2019).|
|12.||Mons U, Kahnert S: Neuberechnung der tabakattributablen Mortalität – Nationale und regionale Daten für Deutschland. Gesundheitswesen 2019; 8: 24–33 CrossRef MEDLINE|
|13.||U.S. Department of Health and Human Services: The health consequences of smoking: a report of the surgeon general. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health 2004.|
|14.||Atzendorf J, Gomes de Matos E, Kröger C, Kraus L, Piontek D: Die Nutzung von E-Zigaretten in der deutschen Bevölkerung – Ergebnisse des Epidemiologischen Suchtsurvey 2015. Das Gesundheitswesen 2019; 81: 137–43 CrossRef MEDLINE|
|15.||Orth B, Merkel C: Rauchen bei Jugendlichen und jungen Erwachsenen in Deutschland. Ergebnisse des Alkoholsurveys 2016 und Trends. BZgA-Forschungsbericht. Köln: Bundeszentrale für gesundheitliche Aufklärung 2018.|
|16.||Orth B, Merkel C: Der Rückgang des Zigarettenkonsums Jugendlicher und junger Erwachsener in Deutschland und die zunehmende Bedeutung von Wasserpfeifen, E-Zigaretten und E-Shishas. Bundesgesundheitsblatt 2018; 61: 1377–87 CrossRef MEDLINE|
|17.||Kotz D, Kastaun S: E-Zigaretten und Tabakerhitzer: repräsentative Daten zu Konsumverhalten und assoziierten Faktoren in der deutschen Bevölkerung (die DEBRA-Studie). Bundesgesundheitsblatt 2018; 61: 1407–14 CrossRef MEDLINE|
|18.||Kotz D, Böckmann M, Kastaun S: The use of tobacco, e-cigarettes, and methods to quit smoking in Germany—a representative study using 6 waves of data over 12 months (the DEBRA study). Dtsch Arztebl Int 2018; 115: 235–42 VOLLTEXT|
|19.||National Academies of Sciences, Engineering, and Medicine: Public health consequences of e-cigarettes. Washington, DC: The National Academies Press 2018. www.doi.org/10.17226/24952 (last accessed on 13 March 2019).|
|20.||Rahman MA, Hann N, Wilson A, Mnatzaganian G, Worrall-Carter L: E-cigarettes and smoking cessation: evidence from a systematic review and meta-analysis. PLoS One 2015; 10: e0122544 CrossRef MEDLINEPubMed Central|
|21.||Dutra LM, Glantz SA: Electronic cigarettes and conventional cigarette use among U.S. adolescents: a cross-sectional study. JAMA Pediatr 2014; 168: 610–7. Erratum in: JAMA Pediatr 2014; 168: 684 CrossRef MEDLINE PubMed Central|
|22.||Kraus L, Pabst A, Piontek D, et al.: Temporal changes in alcohol-related morbidity and mortality in Germany. Eur Addict Res 2015; 21: 262–72 CrossRef MEDLINE|
|23.||GBD 2016 Alcohol Collaborators: Alcohol use and burden for 195 countries and territories, 1990–2016: a systematic analysis for the global burden of disease study 2016. Lancet 2018; 392: 1015–35 CrossRef|
|24.||Järvenpää T, Rinne JO, Koskenvuo M, Räihä I, Kaprio J: Binge drinking in midlife and dementia risk. Epidemiology 2005; 16: 766–71 CrossRef|
|25.||Valencia-Martín JL, Galán I, Rodríguez-Artalejo F: The joint association of average volume of alcohol and binge drinking with hazardous driving behaviour and traffic crashes. Addiction 2008; 103: 749–57 CrossRef MEDLINE|
|26.||Mundt MP, Zakletskaia LI, Fleming FM: Extreme college drinking and alcohol-related injury risk. Alcohol Clin Exp Res 2009; 33: 1532–8 CrossRef MEDLINE PubMed Central|
|27.||Kraus L, Seitz NN, Shield KD, Gmel G, Rehm J: Quantifying harms to others due to alcohol consumption in Germany: a register-based study. BMC Medicine 2019; 17: 1–9 CrossRef MEDLINE PubMed Central|
|28.||Gaertner B, Freyer-Adam J, Meyer C, John U: Alkohol – Zahlen und Fakten zum Konsum. In: Deutsche Hauptstelle für Suchtfragen (ed.): Jahrbuch Sucht 2015. Lengerich: Pabst Science Publishers 2015; 39–71.|
|29.||Adams M, Effertz T: Volkswirtschaftliche Kosten des Alkohol- und Tabakkonsums. In: Singer MV, Batra A, Mann K (eds.): Alkohol und Tabak. Grundlagen und Folgeerkrankungen. Stuttgart: Georg Thieme Verlag KG 2011: 57–62.|
|30.||European Monitoring Centre for Drugs and Drug Addiction (EMCDDA): European Drug Report 2018. Trends and developments. Luxembourg: Publications Office of the European Union 2018.www.emcdda.europa.eu/publications/edr/trends-developments/2018_en (last accessed on 19 July 2019).|
|31.||Schneider M, Friemel CM, von Keller R, et al.: Cannabiskonsum zum Freizeitgebrauch. In: Hoch E, Friemel CM, Schneider M (eds.): Cannabis: Potenzial und Risiko. Eine wissenschaftliche Bestandsaufnahme. Berlin: Springer 2018: 65–264 CrossRef PubMed Central|
|32.||Chandra S, Radwan MM, Majumdar CG, Church JC, Freeman TP, ElSohly MA: New trends in cannabis potency in USA and Europe during the last decade (2008–2017). Eur Arch Psychiatry Clin Neurosci 2019; 269: 5–15 CrossRef MEDLINE|
|33.||Gomes de Matos E, Hannemann TV, Atzendorf J, Kraus L, Piontek D: The consumption of new psychoactive substances and methamphetamine—analysis of data from 6 German federal states. Dtsch Arztebl Int 2018; 115: 49–55 VOLLTEXT|
|34.||European Monitoring Center for Drugs and Drug Addiction (EMCDDA): Wastewater analysis and drugs—a European multi-city study. www.emcdda.europa.eu/topics/pods/waste-water-analysis (last accessed on 29 March 2019).|
|35.||Glaeske G: Medikamente 2016 – Psychotrope und andere Arzneimittel mit Missbrauchs- und Abhängigkeitspotenzial. In: Deutsche Hauptstelle für Suchtfragen e. V. (DHS) (ed.): Jahrbuch Sucht 18. Lengerich: Pabst Science Publishers 2018: 85–104.|
|36.||Soyka M: Medikamentenabhängigkeit: Entstehungsbedingungen – Klinik – Therapie. Stuttgart: Schattauer 2016.|
|37.||Aydin D: Konsumstörungen im Zusammenhang mit opioidhaltigen und nicht opioidhaltigen Schmerzmitteln – Prävalenz in der Bevölkerung und prädiktive Effekte (Bachelorarbeit). FernUniversität in Hagen 2018.|
|38.||Piontek D, Kraus L, Gomes de Matos E, Atzendorf J: Der Epidemiologische Suchtsurvey 2015: Studiendesign und Methodik. Sucht 2016; 62: 259–69 CrossRef|
|39.||Gorber SC, Schofield-Hurwitz S, Hardt J, Levasseur G, Tremblay M: The accuracy of self-reported smoking: a systematic review of the relationship between self-reported and cotinine-assessed smoking status. Nicotine Tob Res 2009; 11: 12–24 CrossRef MEDLINE|
|40.||Fazel S, Khosla V, Doll H, Geddes J: The prevalence of mental disorders among the homeless in western countries: systematic review and meta-regression analysis. PLOS Medicine 2008; 5: e225 CrossRef MEDLINE PubMed Central|
|e1.||Heeringa SG, West BT, Berglund PA: Applied survey data analysis. 2nd ed. Boca Raton, FL: CRC Press 2017.|
|e2.||International Agency for Research on Cancer. Working Group on the Evaluation of Carcinogenic Risks to Humans: Tobacco smoke and involuntary smoking. IARC monographs on the evaluation of carcinogenic risks to humans, Vol. 83. Lyon, France 2004. https://monographs.iarc.fr/wp-content/uploads/2018/06/mono83.pdf. (last accessed on 19 July 2019).|
|e3.||Pearson JL, Richardson A, Niaura RS, Vallone DM, Abrams DB: E-cigarette awareness, use, and harm perceptions in US adults. Am J Public Health 2012; 102: 1758–66 CrossRef MEDLINE PubMed Central|
|e4.||Morgenstern M, Nies A, Goecke M, Hanewinkel R: E-cigarettes and the use of conventional cigarettes—a cohort study in 10th grade students in Germany. Dtsch Arztebl Int 2018; 115: 243–8 VOLLTEXT|
|e5.||Schneider S, Diehl K: Vaping as a catalyst for smoking? An initial model on the initiation of electronic cigarette use and the transition to tobacco smoking among adolescents. Nicotine Tob Res 2016; 18: 647–53 CrossRef MEDLINE|
|e6.||Effertz T: Die volkswirtschaftlichen Kosten gefährlichen Konsums. Eine theoretische und empirische Analyse für Deutschland am Beispiel Alkohol, Tabak und Adipositas. Frankfurt am Main: Peter Lang 2015 CrossRef PubMed Central|
|e7.||Hoch E, Schneider M, von Keller R, et al.: Wirksamkeit, Verträglichkeit und Sicherheit von medizinischem Cannabis. In: Hoch E, Friemel CM, Schneider M (eds.): Cannabis: Potenzial und Risiko. Eine wissenschaftliche Bestandsaufnahme. Berlin: Springer 2018; 265–426 CrossRef|
|e8.||Hoch E, Niemann D, von Keller R, et al.: How effective and safe is medical cannabis as a treatment of mental disorders? A systematic review. Eur Arch Psychiatry Clin Neurosci 2019; 1: 1–19 CrossRef CrossRef MEDLINE|
|e9.||Stockwell T, Zhao J, Greenfield T, Li J, Livingston M, Meng Y: Estimating under- and over-reporting of drinking in national surveys of alcohol consumption: identification of consistent biases across four English-speaking countries. Addiction 2016; 111: 1203–13 CrossRef MEDLINE PubMed Central|
|e10.||Statistisches Bundesamt: Demographische Standards Ausgabe 2010. In: Statistisches Bundesamt, (ed.): Statistik und Wissenschaft. Wiesbaden 2010.|
|e11.||Keller S: Zur Validität des Transtheoretischen Modells – Eine Untersuchung zur Veränderung des Ernährungsverhaltens. Marburg 1998. http://archiv. ub. unimarburg.de/ diss/z1998/ 0303/ html/ frame. htm (last accessed on 19 July 2019).|
|e12.||Wittchen HU, Beloch E, Garczynski E, et al.: Münchener Composite International Diagnostic Interview (M-CIDI), paper-pencil 2.2, 2/95. München: Max-Planck-Institut für Psychiatrie, Klinisches Institut 1995.|
|e13.||Bühringer G, Augustin R, Bergmann E, et al.: Alkoholkonsum und alkoholbezogene Störungen in Deutschland. Schriftenreihe des Bundesministeriums für Gesundheit.. Bd. 128. (ed). Baden-Baden: Nomos 2000.|
|e14.||Burger M, Bronstrup A, Pietrzik K: Derivation of tolerable upper alcohol intake levels in Germany: a systematic review of risks and benefits of moderate alcohol consumption. Prev Med 2004; 39: 111–27 CrossRef MEDLINE|
|e15.||Seitz HK, Bühringer G, Mann K: Grenzwerte für den Konsum alkoholischer Getränke. In: Deutsche Hauptstelle für Suchtfragen (ed): Jahrbuch Sucht 2008. Geesthacht: Neuland 2008: 205–8.|
|e16.||Lachner G, Wittchen HU, Perkonigg A, et al.: Structure, content and reliability of the Munich-Composite International Diagnostic Interview (M-CIDI) substance use sections. Eur Addict Res 1998; 4: 28–41 CrossRef MEDLINE|
|e17.||Saß H, Wittchen HU, Zaudig M, Houben I: Diagnostische Kriterien DSM-IV. Göttingen: Hogrefe 1998.|
|e18.||Gabler S, Hoffmeyer-Zlotnik J, Krebs D: Gewichtung in der Umfragepraxis. Opladen: Westdeutscher Verlag 1994 CrossRef|
|e19.||Little RJ, Lewitzky S, Heeringa S, Lepkowski J, Kessler RC: Assessment of weighting methodology for the National Comorbidity Survey. Am J Epidemiol 1997; 146: 439–49 CrossRef MEDLINE|
|e20.||Gelman A, Carlin J: Poststratification and weighting adjustments. In: Groves RM, Eltinge JL, Little RJA, (eds.): Survey nonresponse. New York: John Wiley and Sons 2002; 289–303.|
|e21.||Bundesamt S: Fortschreibung des Bevölkerungsstandes Deutschland. Ergebnisse auf Grundlage des Zensus 2011. www.destatis.de/DE/ZahlenFakten/GesellschaftStaat/Bevoelkerung/Bevoelkerungs stand/Bevoelkerungsstand.html2019 (last accessed on 10 January 2019).|
|e22.||Kamtsiuris P, Lange M, Hoffmann R, et al.: Die erste Welle der Studie zur Gesundheit Erwachsener in Deutschland (DEGS1). Stichprobendesign, Response, Gewichtung und Repräsentativität, Bundesgesundheitsblatt 2013; 56: 620–30 CrossRef PubMed Central|