Alcohol use disorders among Slovak and Czech university students: A closer look at tobacco use, cannabis use and socio-demographic characteristics

International Journal of Environmental Research and Public Health Article Alcohol Use Disorders among Slovak and Czech University Students: A Closer Look at Tobacco Use, Cannabis Use and Socio-Demographic Characteristics Beata Gavurova 1,* , Viera Ivankova 2and Martin Rigelsky 3   Citation: Gavurova, B.; Ivankova, V.; Rigelsky, M. Alcohol Use Disorders among Slovak and Czech University Students: A Closer Look at Tobacco Use, Cannabis Use and Socio-Demographic Characteristics. Int. J. Environ. Res. Public Health 2021, 18, 11565. https://doi.org/10.3390/ ijerph182111565 Academic Editor: Styliani (Stella) Vlachou Received: 2 October 2021 Accepted: 2 November 2021 Published: 3 November 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1Center for Applied Economic Research, Faculty of Management and Economics, Tomas Bata University in Zlín, Mostní5139, 760 00 Zlín, Czech Republic 2Faculty of Mining, Ecology, Process Control and Geotechnologies, Technical University of Košice, Letná9, 042 00 Košice, Slovakia; [email protected] 3Faculty of Management, University of Prešov in Prešov, Konštantínova 16, 080 01 Prešov, Slovakia; [email protected] *Correspondence: gavur[email protected] Abstract: The main objective of the research was to examine the associations between problematic alcohol use, tobacco use and cannabis use among Czech and Slovak university students during the early COVID-19 pandemic. The research sample consisted of 1422 participants from the Czech Republic (CZ) and 1677 from the Slovak Republic (SK). The analyses included university students who drank alcohol in the past year (CZ: 1323 (93%); SK: 1526 (91%)). Regarding the analysed measures, the Alcohol Use Disorders Identification Test (AUDIT) and its subscales, the Glover-Nilsson Smoking Behavioral Questionnaire (GN-SBQ) and the Cannabis Abuse Screening Test (CAST) were selected to identify substance-related behaviour. Age, gender and residence were included in the analyses as socio-demographic variables. Correlation and regression analyses were used to achieve the main objective of the research. The main results revealed that the use of tobacco and cannabis were positively associated with alcohol use disorders among Czech and Slovak university students. Additionally, males were more likely to report alcohol use disorders. In the Czech Republic, it was found that students living in dormitories were characterized by a lower AUDIT score. The opposite situation was found in the Slovak Republic. Czech and Slovak policy-makers are encouraged to develop alcohol use prevention programs for university students in line with these findings. Keywords: alcohol dependence; tobacco; cannabis; marijuana; smoking; COVID-19 pandemic; young adults; substance use; socio-demographic 1. Introduction Young people, especially university students, are a population group at risk of unhealthy and harmful behaviours in terms of the use of addictive substances such as alcohol, tobacco or cannabis [ 1 – 3 ]. The vulnerability of this population group is evidenced by a considerable prevalence of dependence to alcohol, tobacco and illicit drugs [ 4 ]. All these facts are the result of a new stage of life focused more on their personality, as they are curious and want to fit into the team, experience sensation and build their own social identity [5,6]. The combined use of addictive substances in the university environment is not an exceptional phenomenon either [ 7 ]. According to Nasui et al. [ 8 ], both male and female university drinkers engaged in other risky behaviours correlated with drinking. These patterns of behaviour have many consequences, whether it is a threat to health and life [ 9 ], reduced academic performance, missed classes and lower grades, memory blackouts, changes in brain function, lingering cognitive deficits, sexual assaults [ 10 ], but also poor mental health [ 11 ] or social problems [ 12 ]. Regarding determinants, it is well known that Int. J. Environ. Res. Public Health 2021,18, 11565. https://doi.org/10.3390/ijerph182111565 https://www.mdpi.com/journal/ijerph Int. J. Environ. Res. Public Health 2021,18, 11565 2 of 16 the male gender characteristic is a significant factor associated with increased alcohol use [ 13 , 14 ] and is therefore considered a predictor of alcohol use disorders [ 15 , 16 ]. This justifies respecting gender differences in research. In addition to gender characteristics, there are many other possible determinants of problematic alcohol use such as living away from parents’ home during semesters [ 1 , 17 ], parent attachment [ 18 ], smoking [ 15 ], mental health problems and satisfaction with life [ 19 , 20 ], or age of alcohol consumption onset [ 21 ]. The need to constantly monitor this problem is underlined by the fact that university students who suffer from problematic alcohol use with the risk of dependence are also characterized by the use of other addictive substances, such as tobacco, cannabis or cocaine [ 22 ]. All these factors can contribute to higher levels of alcohol use, which is an undesirable phenomenon in society. Thus, factors such as residence, age, gender, living conditions, smoking, or illicit substance use should be included in research into alcohol use disorders among university students. It is true that the COVID-19 pandemic is an unknown situation, and more pressure can be expected in students’ lives. Young adults face various impulses of risky behaviour during the pandemic [ 23 – 25 ]. Thus, in the context of the pandemic, increased attention should be paid to the psychological distress that is associated with heavy drinking and a high-risk level of drug use among university students [ 26 ]. Jackson et al. [ 27 ] examined COVID-19-related changes in drinking among university student drinkers that were attributable to changes in context, particularly a shift away from heavy drinking with peers to lighter drinking with family. Their results revealed that reduced social opportunities and/or settings, limited access to alcohol, and reasons related to health and self-discipline were reflected in decreased alcohol use. On the other hand, increased alcohol use was attributed to greater opportunity (more time) and boredom and, to a lesser extent, to a lower perceived risk of harm and to cope with distress. As a result, poor mental health, as well as alcohol abuse, can be observed among university students [ 28 ]. All these facts indicate that substance use behaviour should be monitored, especially in a critical situation such as the COVID-19 pandemic. All the above-mentioned findings indicate that alcohol use affects many dimensions in university students’ lives and is therefore a serious burden. In this regard, increased research attention should be paid to each region. Jia et al. [ 29 ] emphasized the need to investigate drug use among students also in terms of geographical differences, which may have strong links to socio-economic and demographic characteristics of the regions. This allows the design of successful interventions tailored to a geographical region with unique characteristics. As for the Czech Republic and the Slovak Republic, these countries share not only a common Central European space, but also a common history, culture, priorities, values and interests to strengthen the stability of society. This fact can also be applied in the field of addictology [ 30 ]. The Czech Republic and the Slovak Republic formed one unit, but were divided. On the other hand, each country behaves as an individual living organism, the core of which is a reflection of their own social needs and principles. For these reasons, their examination is warranted [ 31 ]. A previous study suggested potential differences in alcohol-related problems between individual regions of the countries of the former Czechoslovakia [ 32 ]. However, it was Nuevo et al. [ 33 ] who emphasized considerable differences in alcohol use between these two countries, which were politically gathered in the recent past. The Slovak Republic dominated in heavy drinkers. In this context, the abuse of addictive substances, including alcohol, was also considered a more relevant problem in the Slovak Republic compared to the Czech Republic in a sample of the general population [ 34 ]. In the pre-pandemic period, significant differences were also confirmed among university students from four countries, including the Czech Republic and the Slovak Republic [35]. Despite the fact that problematic alcohol use among students and its determinants is a well-researched issue in the world, the Czech Republic and the Slovak Republic are countries that have long overlooked and neglected this problem. Insufficiency can be seen not only in the research area, but also at the level of management of health policies targeted Int. J. Environ. Res. Public Health 2021,18, 11565 3 of 16 at a specific group of the population such as students, resulting in insufficient evidencebased interventions in the university environment. In other words, the application of research findings in practice is minimal in this region. Understanding the situation is particularly important in the current pandemic period for the development of successful strategies and programs aimed at reducing alcohol use among students, who are seen as the driving force of the economy in the future, but also as potential consumers of social support and health care. These facts reinforce the importance of the findings offered by the presented study, especially in the geographical region of the Czech Republic and the Slovak Republic. Without substantiated evidence, it is not possible to design and implement student-targeted programs that are lacking in the countries. On this basis, the objective of the presented research was to examine the associations between problematic alcohol use, tobacco use and cannabis use among Czech and Slovak university students during the early COVID-19 pandemic. The study provides a valuable platform for information on problematic alcohol use accompanied by tobacco use, cannabis use and other characteristics of individuals, facilitating public health leaders’ decision-making. 2. Materials and Methods 2.1. Research Questions This study provides a deeper insight into the issue of alcohol use disorders among university students and brings evidence from the Czech Republic and the Slovak Republic during the early COVID-19 pandemic. In the research, emphasis was placed on tobacco use, cannabis use and several socio-demographic characteristics. Based on the main aim, three research questions were formulated: RQ 1: What are the differences in alcohol use disorders between Slovak and Czech university students? RQ 2: What is the comorbidity between tobacco use, cannabis use, and alcohol use disorders among Czech and Slovak university students? RQ 3: What are the associations of alcohol use disorders with tobacco use, cannabis use, age, male gender, and residency? 2.2. Research Sample and Data Collection Process The participants involved in the presented research were Czech and Slovak university students. The research sample was formed on the basis of quota sampling with a focus on all Czech and Slovak universities. The purpose was to cover all universities, as well as all fields of study, with at least 30 observations. Prior to data collection, universities in both countries were mapped, including their number and their approximate size according to the number of students and fields of study. The ambition was to include every field of study, which succeeded. In this way, data was collected from 80% of universities. This fact makes the presented research unique, as such a large sample has not yet been studied in the examined region. The data collection was performed using an online questionnaire distributed during the first wave of COVID-19 in 2020. The questionnaire was distributed through university representatives (rectors, vice-rectors, deans, vice-deans, university teachers and lecturers) and administrative staff who were asked to share it with students. At the same time, delegates of the student council for higher education were contacted with a request to distribute the questionnaire among students. Finally, students were addressed directly on social networks in student groups. The whole survey was conducted in both languages; thus, the participants were provided with the questionnaire in Czech and Slovak. After removing irrelevant responses, the sample consisted of 1422 participants from the Czech Republic and 1677 from the Slovak Republic, with the data collection taking place during the first wave of the COVID-19 pandemic in 2020. When excluding responses, the criteria included disagreement with participation in the research, incorrect answer in the control item (one million has six zeros, while a numerical expression was also given), Int. J. Environ. Res. Public Health 2021,18, 11565 4 of 16 other than Slovak or Czech nationality, or study in another country. Table 1shows the frequency of selected identifiers in the research sample. Table 1. Research sample identifiers. Frequency CZ SK N%N% Field of study: Education 277 19.5 80 4.8 Humanities and arts 101 7.1 78 4.7 Social, economic and legal sciences 665 46.8 671 40.0 Natural science 50 3.5 73 4.4 Design, technology, production and communications 93 6.5 164 9.8 Agricultural and veterinary sciences 67 4.7 53 3.2 Health service 54 3.8 180 10.7 Services (tourism, sports, security, transport, logistics, . . . ) 69 4.9 240 14.3 Informatics, mathematics, information and communication technologies 46 3.2 138 8.2 Form of study: Full-time 1041 73.2 1550 92.4 Part-time 381 26.8 127 7.6 Degree of study: Bachelor’s 658 46.3 1140 68.0 Master’s/Engineering 380 26.7 428 25.5 Combined (Bachelor’s and Master’s/Engineering) 50 3.5 41 2.4 Doctoral 334 23.5 68 4.1 Gender: Male 349 24.5 606 36.1 Female 1073 75.5 1071 63.9 Residence—university: Dormitory 243 17.1 702 41.9 Private accommodation 287 20.2 139 8.3 With family 202 14.2 68 4.1 With a friend 40 2.8 30 1.8 At home 650 45.7 738 44.0 Residence—home: Countryside 457 32.1 823 49.1 City with up to 10,000 inhabitants 254 17.9 198 11.8 City of 10,001 to 100,000 inhabitants 459 32.3 525 31.3 City of 100,001 to 1,000,000 inhabitants 169 11.9 119 7.1 City with over 1,000,001 inhabitants 83 5.8 12 0.7 Note: N—number, CZ—Czech Republic, SK—Slovak Republic. As can be seen from Table 1, the research sample from the Slovak Republic was slightly more balanced than the research sample from the Czech Republic. Despite this fact, the total research sample could be considered sufficiently reliable for analytical processes. The identifiers included in the regression analysis were converted to the dichotomous scale described in the given part of the analytical process. Table 1indicates that the most frequent form of study was the full-time form of study, which is a common form in the university environment in the examined region. Additionally, the research sample consisted mainly of participants studying a bachelor’s degree, which could be due to the fact that not every field of study continues with a master’s/engineering degree. Female students dominated over male students, and the most common residence type was living at home. Dormitory living was more frequent in the Slovak sample than in the Czech one. A considerable proportion of the participants lived in the countryside and in cities with 10,001 to 100,000 inhabitants. 2.3. Governance and Ethics The research was approved by the ethics committee of the General University Hospital in Prague as individual research (Ref. 915/20 S–IV). At the beginning of the questionnaire, Int. J. Environ. Res. Public Health 2021,18, 11565 5 of 16 all important information on research and processing of personal data was provided. The survey was completely anonymous and personal data was protected. All participants involved in this research confirmed informed consent in the questionnaire. All aspects in this research were conducted with respect to the seventh revision of the World Medical Association Declaration of Helsinki [ 36 ] and the second revision of the Farmington Consensus [37]. 2.4. Research Instruments and Variables The analyses used in this research included variables identifying a participant’s attitude to substance use at a particular time. In this way, the analyses included a variable determining whether participants drank alcohol in the past year (CZ: No = 84 (5.9%), Yes = 1323 (93%), blank = 15 (1.1%); SK: No = 151 (9%), Yes = 1526 (91%)). Accordingly, the research sample consisted of 1323 Czech participants and 1526 Slovak participants. Subsequently, this research sample was the basis for a variable determining whether participants smoked tobacco in the last three months (CZ: No = 873 (66%), Yes = 450 (34%); SK: No = 1102 (72.2%), Yes = 424 (27.8%)) and for a variable determining whether they smoked cannabis in the past year (CZ: No = 1047 (79.1%), Yes = 276 (20.9%); SK: No = 1226 (80.3%), Yes = 300 (19.7%)). The analyses included three indicators of substance use, namely alcohol, tobacco and cannabis. The Alcohol Use Disorders Identification Test (AUDIT) [ 38 ] was used to identify alcohol use. The AUDIT measure was developed to detect problematic alcohol use and its intensity. This brief tool consists of 3 domains (hazardous alcohol use, alcohol use with dependence symptoms, harmful alcohol use) and of 10 items. The AUDIT items are scored from 0 to 4, and the total score is the sum of the individual items. The higher the total score, the higher the level of risk of alcohol use disorder. The risk levels are identified as follows (Zone—recommended intervention): (i) low risk without potential alcohol use disorder (Zone I—alcohol education), (ii) mild risk (Zone II—simple advice), (iii) moderate risk (Zone III—simple advice plus brief counselling and continued monitoring), and (iv) moderate/severe risk (zone IV—referral to specialist for diagnostic evaluation and treatment). The AUDIT measure is commonly used in the professional and scientific community. This is evidenced by several studies, in which this tool was used also in a sample of university students [ 39 , 40 ]. In the Slovak Republic, its reliability was verified by Janovskáet al. [41]. The Glover-Nilsson Smoking Behavioral Questionnaire (GN-SBQ) [ 42 ] was used to identify tobacco use. This simple 11-item questionnaire was able to assess behavioural dependence; in other words, to identify aspects of smoking dependence that are behavioural in nature. The GN-SBQ measure is commonly used by physicians, health care providers, and tobacco interventionists. The following answers were provided to GN-SBQ items: (0) not at all, (1) somewhat, (2) moderately so, (3) very much so, and (4) extremely so. This measure provides a total score, and the higher the total score, the higher the dependence. Based on the total score, dependence is identified at the following levels: mild (<12), moderate (12–22), strong (23–33), and very strong (>33). Thus, high scores in the GN-SBQ measure indicate the need for greater emphasis by physicians on behavioural management. The Cannabis Abuse Screening Test (CAST) [ 43 , 44 ] was used to identify cannabis use. The CAST measure provides psychometric properties for assessing problematic forms of cannabis use among young people and for identifying patterns of cannabis use leading to negative social or health consequences for individuals. This short measure consists of six items. The CAST items offered the following answers: (0) never, (1) rarely, (2) from time to time, (3) fairly often, (4) very often. 2.5. Statistical Analysis The following statistical methods were used to achieve the main objective of this research. Descriptive analysis was used to present the basic statistical characteristics of alcohol-related variables (mean, median, variance (Var), standard deviation (St. Dev.), Int. J. Environ. Res. Public Health 2021,18, 11565 6 of 16 interquartile range (IQR), minimum (Min), maximum (Max)). The significance of differences between countries with respect to data characteristics was investigated using the nonparametric Mann–Whitney U test. Due to the nature of the data, Spearman’s correlation coefficient ( ρ ) was used to assess the relationships. Two regression models were used to evaluate the effects, namely the ordinary least squares (OLS) model and the negative binomial generalized linear model (NB) model [ 45 ]. Significant heteroscedasticity occurred in the OLS models; therefore, a robust estimation based on the HC3 estimator was preferred. Analytical calculations were performed using the programming language R version 4.0.2 (RStudio, Inc., Boston, MA, USA), nickname: Taking off Again [46]. 3. Results This section presents the results of a descriptive analysis in order to offer a closer look at selected variables and point out a current situation in the examined issue. This section is also devoted to the examination of the relationships between alcohol use disorders and tobacco use, cannabis use and selected socio-demographic characteristics of the participants. This made it possible to map the situation in the region, where this problem has been overlooked for a long time and a deeper insight into the issue was lacking. In addition, the results help to point out the comorbidity and the association between substance use among Czech and Slovak university students during the early COVID-19 pandemic. Table 2shows the results of the descriptive analysis of the total AUDIT score and its individual subscales. With a focus on the statistical measures of the central tendency for AUDIT Total, AUDIT Hazardous Alcohol Use and AUDIT Dependence Symptoms, it was possible to observe the fact that Czech participants dominated over Slovak participants. Hazardous alcohol use and dependent alcohol use indicate a risk of mild and moderate/severe alcohol-related disorders. In terms of AUDIT Harmful Alcohol Use, the opposite situation was found, i.e., a higher mean score was identified for Slovak participants. Regarding the mean values of the total AUDIT score, it could be stated that Czech and Slovak students reported a low risk of alcohol use disorder during the early COVID-19 pandemic. However, it should be noted that the scores were almost on the threshold between low and mild risk. Table 2. Descriptive statistics of selected alcohol-related variables. AUDIT Total AUDIT Hazardous Alcohol Use AUDIT Dependence Symptoms AUDIT Harmful Alcohol Use ALL CZ SK ALL CZ SK ALL CZ SK ALL CZ SK Mean 6.08 6.12 6.05 3.58 3.64 3.52 0.59 0.63 0.55 1.92 1.85 1.98 Median 5.00 5.00 5.00 3.00 4.00 3.00 0.00 0.00 0.00 1.00 1.00 1.00 Var 21.85 20.30 23.21 4.15 3.60 4.61 1.36 1.30 1.42 5.85 5.33 6.30 St. Dev. 4.67 4.51 4.82 2.04 1.90 2.15 1.17 1.14 1.19 2.42 2.31 2.51 IQR 5.00 5.00 5.00 3.00 3.00 3.00 1.00 1.00 1.00 3.00 3.00 3.00 Min 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Max 30.00 28.00 30.00 12.00 11.00 12.00 10.00 8.00 10.00 16.00 13.00 16.00 Note: AUDIT—Alcohol Use Disorders Identification Test, CZ—Czech Republic, SK—Slovak Republic, Var—variance, St. Dev.—standard deviation, IQR—interquartile range, Min—minimum, Max—maximum. The nonparametric Mann–Whitney test of differences was applied to these data, while significant differences were revealed only in AUDIT Hazardous Alcohol Use (statistic: 951,900, p-value: 0.008) and in AUDIT Dependence Symptoms (statistic: 944,764, p-value: <0.001). Table 3shows the descriptive analysis results of GN-SBQ and CAST measures, in general as well as for individual countries. The values of the central tendency measures were higher in the Slovak Republic, especially in the case of GN-SBQ. Based on the mean values of the total GN-SBQ score, a moderate smoking dependence in behavioural nature was found in both countries during the first wave of the COVID-19 pandemic. However, the moderate level of dependence ranged from 12 to 22, and therefore it could be stated that the Czech participants reported an almost threshold value between mild and moderate Int. J. Environ. Res. Public Health 2021,18, 11565 7 of 16 dependence. By focusing on the median of the total CAST scores, the measured values did not indicate a high risk of cannabis abuse among university students in both countries during the early COVID-19 pandemic. Table 3. Descriptive statistics of selected variables related to tobacco and cannabis. GN-SBQ CAST ALL CZ SK ALL CZ SK Mean 13.15 12.21 14.17 3.58 3.56 3.60 Median 13.00 12.00 14.50 2.00 2.00 2.00 Var 66.83 76.23 55.09 17.20 16.63 17.94 St. Dev. 8.17 8.7. 7.42 4.15 4.07 4.24 IQR 13.00 13.00 11.00 5.00 5.00 5.00 Min 0.00 0.00 0.00 0.00 0.00 0.00 Max 41.00 41.00 31.00 22.00 18.00 22.00 Note: GN-SBQ—Glover-Nilsson Smoking Behavioral Questionnaire, CAST—Cannabis Abuse Screening Test, CZ—Czech Republic, SK—Slovak Republic, Var—variance, St. Dev.—standard deviation, IQR—interquartile range, Min—minimum, Max—maximum. Regarding the data on tobacco and cannabis use, the nonparametric Mann–Whitney test of differences did not show any significant differences between countries. The following analytical procedures are devoted to the relationships between problematic alcohol use and tobacco and cannabis use. Thus, the analyses included the AUDIT measure and its subscales, but also the GN-SBQ measure and the CAST measure. Table 4shows the results of the correlation analysis between the investigated variables related to addictive substances. The first column ( ρ ) provides the rate of correlation, the second column (Sig.) shows a p-value and the third column (N) offers information on the number of observations. At this point, it should be noted that the analysis included data on participants who smoked tobacco in the last three months (GN-SBQ) and also drank alcohol in the past year, as well as data on participants who smoked cannabis (CAST) and also drank alcohol in the past year. In general, there were more significant correlations in the Slovak Republic than in the Czech Republic. The rate of correlations could be considered as low to medium. Table 4. Correlation analysis. Spearman ρ CZ SK ρSig. N ρSig. N The Glover-Nilsson Smoking Behavioral Questionnaire (GN-SBQ) AUDIT Total 0.098 0.038 450 0.242 <0.001 424 AUDIT Hazardous Alcohol Use 0.091 0.053 450 0.159 0.001 424 AUDIT Dependence Symptoms 0.070 0.137 450 0.179 <0.001 424 AUDIT Harmful Alcohol Use 0.100 0.035 450 0.229 <0.001 424 Cannabis Abuse Screening Test (CAST) AUDIT Total 0.143 0.017 276 0.243 <0.001 300 AUDIT Hazardous Alcohol Use 0.109 0.072 276 0.145 0.012 300 AUDIT Dependence Symptoms 0.075 0.214 276 0.176 0.002 300 AUDIT Harmful Alcohol Use 0.145 0.016 276 0.265 <0.001 300 Note: AUDIT—Alcohol Use Disorders Identification Test, CZ—Czech Republic, SK—Slovak Republic, ρ —correlation rate, Sig.—significance, N—number. The alcohol-related variables presented above were dependent variables in the regression analysis. Independent variables were represented by variables such as Smoking (tobacco smokers in the last three months = 1, tobacco non-smokers = 0), Cannabis (cannabis smokers in the past year = 1, cannabis non-smokers = 0), Age (CZ: mean = 24.7, median = 23, standard deviation = 6.08; SK: mean = 23.36, median = 22, standard deviation = 4.24), Male Int. J. Environ. Res. Public Health 2021,18, 11565 8 of 16 (males = 1, females = 0), Countryside (countryside = 1, city = 0), Dormitory (dormitory = 1, other than dormitory = 0). In the following part of the analytical procedure, the results of regression models (the OLS model and the NB model) were presented for individual countries. Before using the regression models, the assumptions of the application of the models were first evaluated, predominantly for the OLS model. A multicollinearity was tested by the variance inflation factor (VIF) method, while the highest value was measured for Cannabis (VIF: CZ = 1.09; SK = 1.11). The constancy of variability of the residues was tested using the Breusch–Pagan test, and significant heteroscedasticity was found in all analysed cases. On this basis, the HC3estimator was used to estimate the coefficients of the OLS model. Table 5presents the results of the OLS and NB regression models, confirming the significant associations of the AUDIT indicators with selected variables (Smoking, Cannabis, Age, Male, Countryside, Dormitory). In the analysed cases of Smoking and Cannabis, a significant positive association was found in all AUDIT indicators in the Czech Republic, as well as in the Slovak Republic. This finding points to the fact that the use of tobacco and cannabis was positively associated with problematic alcohol use among Czech and Slovak university students during the early COVID-19 pandemic. In terms of Age, significant negative associations could be observed. For Czech university students, Age was significantly and negatively associated with AUDIT Total,AUDIT Hazardous Alcohol Use and AUDIT Harmful Alcohol Use. In contrast, only one significant negative association was found in Slovak university students, namely between Age and AUDIT Hazardous Alcohol Use.Male showed a positive and significant coefficient in all of the analysed cases. Thus, a male gender was positively associated with problematic alcohol use in the Czech Republic, as well as in the Slovak Republic, during the first wave of the COVID-19 pandemic. In contrast, no effect at the significance level of α < 0.05 was found for Countryside. The only discrepancy between the examined countries in terms of direction of associations was observed in Dormitory. This variable showed a negative association with AUDIT Total and AUDIT Harmful Alcohol Use in the Czech Republic. On the other hand, a significant positive association with all AUDIT indicators was identified in the Slovak Republic. Table 5. Regression analysis. DV AUDIT Total AUDIT Hazardous Alcohol Use AUDIT Dependence Symptoms AUDIT Harmful Alcohol Use Model OLS NB OLS NB OLS NB OLS NB CZ Intercept 5.43 †1.73 †3.37 †1.23 †0.37 *** −0.88 †5.43 †0.59 † Smoking 2.47 †0.39 †1.01 †0.26 †0.54 †0.82 †2.47 †0.49 † Cannabis 2.44 †0.34 †0.79 †0.19 †0.47 †0.59 †2.44 †0.52 † Age −0.04 ** −0.01 *** −0.02 *** −0.01 ** <0.001 −0.01 −0.04 ** −0.02 ** Male 1.62 †0.24 †1.04 †0.26 †0.16 ** 0.26 ** 1.62 †0.22 *** Countryside 0.38 0.05 0.1 0.02 0.04 0.08 0.38 0.11 Dormitory −0.7 *** −0.12 ** −0.19 −0.05 −0.1 −0.22 −0.7 *** −0.23 ** R20.197 −0.201 −0.11 −0.124 − R2Adjusted 0.194 −0.198 −0.106 −0.12 − Nagelkerke −0.2 −0.178 −0.112 −0.11 AIC −6974.4 −5114.9 −2733 −4747.5 SK Intercept 4.06 †1.5 †2.88 †1.09 †−0.08 −1.57 †4.06 †0.33 Smoking 3.12 †0.48 †1.31 †0.34 †0.53 †0.83 †3.12 †0.6 † Cannabis 3.01 †0.4 †1.09 †0.26 †0.45 †0.61 †3.01 †0.59 † Age −0.02 −0.01 −0.02 ** −0.01 ** 0.01 0.01 −0.02 −0.01 Male 1.82 †0.3 †1.05 †0.29 †0.28 †0.44 †1.82 †0.26 † Countryside −0.11 −0.04 0.06 0.01 −0.02 −0.12 −0.11 −0.11 * Dormitory 1.09 †0.19 †0.41 †0.11 †0.21 †0.42 †1.09 †0.28 † Int. J. Environ. Res. Public Health 2021,18, 11565 9 of 16 Table 5. Cont. DV AUDIT Total AUDIT Hazardous Alcohol Use AUDIT Dependence Symptoms AUDIT Harmful Alcohol Use Model OLS NB OLS NB OLS NB OLS NB R20.246 −0.228 −0.104 −0.162 − R2Adjusted 0.243 −0.225 −0.1 −0.158 − Nagelkerke −0.254 −0.226 −0.108 −0.141 AIC −8036.8 −6092.3 −2822.5 −5570.3 Note: *—p-value < 0.1; **—p-value < 0.05; ***—p-value < 0.01; †—p-value < 0.001. 4. Discussion 4.1. Problematic Alcohol Use in the Czech Republic and the Slovak Republic Based on the main results of the difference analysis, significant differences in problematic alcohol use were found between the examined countries in domains such as AUDIT Hazardous Alcohol Use and AUDIT Dependence Symptoms. This finding clarifies the answer to the research question 1 (RQ1) and encourages further investigation after the pandemic. A higher value was measured in the Czech Republic. Regarding the pre-pandemic period, very similar results were identified by Kalina et al. [ 35 ], who examined data from 2016 and found that Czech university students reported the highest mean AUDIT scores in terms of hazardous alcohol use and alcohol use with dependence symptoms compared to university students from the Slovak Republic, Hungary and Lithuania. On the other hand, this finding contradicts the evidence revealed by Nuevo et al. [ 33 ] and Slachtováet al. [ 34 ], who considered the Slovak Republic to be a country with greater alcohol-related problems. The discrepancy may have been due to the fact that the presented research was aimed only at university students. In explaining the results of this study, it can be assumed that Czech and Slovak students may have had different restrictions and educational conditions during the first wave of the COVID-19 pandemic. This could lead to different drinking opportunities and behaviours among students in these two countries. In general, the mean value of the total AUDIT score was 6.12 in the Czech Republic and 6.05 in the Slovak Republic, indicating a low level of risk (Zone I—alcohol education). Although this value does not represent a potential alcohol use disorder, it should be emphasized that the limit value between Zone I and Zone II with a mild risk of alcohol use disorder is 7. Thus, this unhealthy pattern should be monitored among Czech and Slovak university students. Tóthová[ 47 ] found similar results among Slovak university students in the pre-pandemic period, while most students were included in Zone I. The results of this study are consistent with the results of Kalina et al. [ 35 ], who measured very similar values in all individual AUDIT domains based on pre-pandemic data. This indicates that Czech and Slovak university students did not change their drinking during the pandemic. The explanation can be found in the fact that, despite bars, pubs, cafes, clubs and restaurants were closed, individuals could still drink alcohol from the store [ 48 , 49 ]. At the same time, off-premises alcohol use may not be apparent in the short time since the onset of the pandemic [49]. 4.2. Tobacco and Cannabis Use in the Czech Republic and the Slovak Republic When assessing tobacco use measured by the GN-SBQ score, the participants from both countries reported higher values (CZ: 12.21, SK: 14.17), which could be included in the second level of behavioural dependence, reflecting the prevalence of smoking in Central and Eastern Europe from the pre-pandemic period [ 50 , 51 ]. As this was a mean value, attention should be paid to this smoking-related indicator. Regardless of the pandemic period, a moderate smoking dependence found in both countries indicates the need for greater emphasis by physicians on behavioural management in the university environment. 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