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Article

Substance Use and Mental Health during the First COVID-19 Lockdown in Germany: Results of a Cross-Sectional Survey

1
German Institute for Addiction and Prevention Research, Catholic University of Applied Sciences, 52066 Aachen, Germany
2
LVR-Hospital Essen, Department of Addictive Behavior and Addiction Medicine, Medical Faculty, University of Duisburg-Essen, 47057 Essen, Germany
3
Institute of Health Research and Social Psychiatry, Catholic University of Applied Sciences, 52066 Aachen, Germany
4
Institute for Addiction Research, Frankfurt University of Applied Sciences, 60318 Frankfurt, Germany
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2022, 19(19), 12801; https://doi.org/10.3390/ijerph191912801
Submission received: 30 August 2022 / Revised: 27 September 2022 / Accepted: 29 September 2022 / Published: 6 October 2022
(This article belongs to the Section Mental Health)

Abstract

:
Background: The measures taken to contain the COVID-19 pandemic have led to significant changes in people’s daily lives. This paper examines changes in substance use during the first lockdown (March–July 2020) and investigates mental health burdens in substance users with increased consumption of alcohol, nicotine or tetrahydrocannabinol (THC) in Germany compared to users with unchanged or reduced consumption. Method: In a cross-sectional online survey, 2369 people were asked about their mental health and their substance use during the first lockdown in Germany. Results: Of the participants, 28.5% increased their alcohol use, 28.8% their use of tobacco products, and 20.6% their use of THC-containing products during the pandemic. The groups with increased alcohol, nicotine, and THC use during the first lockdown reported more depressive symptoms and anxiety. Individuals who reported increased consumption of alcohol or nicotine were also more likely to experience loneliness and have suicidal thoughts and were more often stressed due to social distancing. Conclusion: Alcohol, nicotine and THC increased in a subgroup of consumers who reported to have more mental health problems compared to individuals who did not increase their consumption. This increased substance use could, therefore, be understood as a dysfunctional strategy to cope with negative emotions during the lockdown.

1. Introduction

The global disease (COVID-19) pandemic was and is a challenge for individuals’ daily lives. To date, over 267 million people have been infected with the virus and over 5.2 million people have died from or with the disease [1].
In Germany, the virus was confirmed for the first time on 27 January 2020 [2]. On 16 March 2020, measures to contain the coronavirus were adopted by the German government. The measures to restrict contact became effective on 22 March 2020 [3]. Contact was only allowed with persons from one’s own household. Private contact with another person outside one’s household was permitted only in public spaces. Private and public parties were prohibited and violations were sanctioned. Restaurants and bars were closed except for pick-up and delivery services. Likewise, all personal care facilities had to be closed. Effective hygiene concepts were mandatory in businesses, especially those open to the public [3]. The consequences of these measures were that social contacts were limited to an absolute minimum. These comprehensive restrictions were an attempt to prevent the spread of the virus. The measures had a profound effect on the everyday life of the population.
Several studies found an impact of the COVID-19 pandemic and its myriad disruptions on mental health [4,5,6,7,8]. Risk factors for increased psychological distress such as female gender, negative affect, social disconnectedness, and poor self-rated health status were identified in various studies [9,10,11,12,13]. A systematic review finds that at least the short-term effects of the COVID-19 pandemic are associated with a general worsening of mental health regardless of country or gender [14].
Previous studies reported an association between mental health problems and use of substances such as alcohol, nicotine or other drugs [15]. Further an increase in mental distress increases substance use, particularly following disasters [16]. For changes in substance use during the COVID-19 pandemic, no clear European trend seems to emerge from the report of the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) [17]. For Great Britain, it is reported that excessive alcohol consumption has become more frequent [18]. In Belgium, slightly increased consumption of alcohol and cigarettes is reported, but no change in the use of tetrahydrocannabinol (THC) [19]. In Germany, the consumption of alcohol seems to have increased somewhat during the first lockdown [20]. Another study suggests that in particular binge drinking increased in Germany [21]. Women seem to be particularly affected by increased consumption of alcohol and nicotine [22]. A recent review reports a trend towards increased consumption of alcohol and other substances during the pandemic, which were negatively correlated with mental health [23].
One explanation for the increase in substance use during the COVID-19 pandemic might be that substances are used as a coping strategy to regulate mental distress associated with the pandemic [24,25,26,27]. However, the impact of the pandemic on substance use and mental health on nicotine, alcohol, and THC users is still not fully comprehended. Therefore, the main aim of the current study is to investigate substance use in the general population and to compare the mental health of individuals with an increase in substance use since the pandemic with individuals with unchanged or decreased substance use. For taking effective measures, health care providers (e.g., counsellors, psychotherapists, physicians) need more detailed information on the impact of the lockdown on mental health in substance users. Based on previous findings, we hypothesize that individuals with an increase in substance use will also report an increase in depression, anxiety, suicidal ideation, loneliness, and a higher burden of social distancing.

2. Material and Methods

2.1. Design and Sampling

A cross-sectional online survey collected data on drug use and mental health during the first lockdown in Germany. The data were collected from 1 June 2020 until 17 July 2020. The questionnaire format was designed using the public survey tool LimeSurvey (https://www.limesurvey.org, accessed on 3 October 2022). The survey was conducted online and advertised through many websites (German AIDS Service Organizations, German Society for Social Psychiatry, German Federation of Telephone Emergency Services, German Federation for Social Work in the Healthcare System, German Society for Social Work in Addiction Aid). Anyone who was at least 18 was invited to participate. The survey was voluntary and anonymous, and participants could withdraw from the study at any time. No compensation was paid for participation. The questionnaire was available only in German language, therefore sufficient knowledge of the German language was needed. In total, 3154 people were reached through the online survey. For this evaluation, the subset of people who gave at least their age were included (n = 2369). Given that participants were able to stop and save their data at any point of the survey and the survey software was not programmed in a “forced choice” format, data of non-completers were included on a pairwise basis, resulting in a different number of responses per analysis. Potential bias will be discussed in Section 5, “Limitations”.

2.2. Measures

The survey started with a short introduction to the questionnaire. Subsequently, socio-demographic questions, questions on substance use and questions on mental health were asked with 131 items. Substance use was surveyed by a 12-month prevalence and with questions on changes in substance use during the lockdown, for alcohol, nicotine and illegal drugs, in particular THC. To measure changes in substance use, participants reported whether their consumption decreased, increased or did not change during the lockdown. In addition, it was asked whether it has become easier or more difficult to buy illicit drugs. Mental health was surveyed with the German version of the Brief Patient Health Questionnaire (PHQ-D) [28]. We used the subscale Patient Health Questionnaire (PHQ-9) [29] to measure depressive symptoms and the Generalized Anxiety Disorder Scale-7 (GAD-7) [30] to assess anxiety disorders. The PHQ-9 scale assesses the severity of depressive symptoms with a maximum score of 27 points. GAD-7 measures symptoms of anxiety with a maximum score of 21 points. A score of 10 points or above on each of the two scales indicates at least clinical significant depressive symptoms and anxiety. The internal reliability of the PHQ-9 was with a Cronbach’s α of 0.90 excellent. Additionally, the internal reliability of the GAD-7 was excellent (Cronbach’s α = 0.91). With the 11-item De Jong Giervald Loneliness Scale we surveyed emotional and social loneliness [31]. The scale assesses loneliness on a scale of 0–11 points. The cut-off score of 3 points and above indicates significant symptoms of loneliness [31]. The internal reliability of the De Jong Giervand Loneliness Scale was with a Cronbach’s α = 0.81 good.
In addition, specific effects of the lockdown on mental health were explored. For this purpose, the subjective burden of social isolation during lockdown was surveyed by a Likert scale. We asked the question: “How much do you feel socially isolated by the social distancing measures?” (0 = not isolated at all, 6 = very isolated). The frequency of suicidal thoughts during the lockdown were asked as follows: “From the time of social distancing/social restrictions due to the Corona pandemic, how often did you think about killing yourself?” (never, rarely (once), sometimes (twice), often (3–4 times), very often (5 times or more)).

2.3. Statistical Analysis

For data analyses, IBM SPSS Statistics version 25 (https://www.ibm.com/de-de/products/spss-statistics, accessed on 3 October 2022) was used. To compare groups with increased vs. unchanged substance use, independent t-tests were used for normally distributed data. For non-normally distributed or ordinal scaled data, Mann–Whitney-U-tests were used. Chi-square tests were used to compare the distributions of categorical variables. Significance was tested at the 5% level.

3. Results

3.1. Sociodemographics

The analysis of the survey included 2369 persons (female (67.8%), male (30.9%), and diverse (1.5%)) who provided at least information on age. The respondents were fairly evenly distributed across the age groups from 25 to 64. The sample was highly educated with 51.8% holding a university degree and 35.2% having completed secondary education. Furthermore, 61.5% were employed full-time or part-time. The majority of respondents had no children (73.7%). For all sociodemographic data see Table 1.

3.2. Mental Health

Depressive symptoms above the cut-off (>10 points) were reported by 25.9% of the sample. Generalized anxiety symptoms above the cut-off for at least moderate anxiety symptoms (>10 points) were reported by 23.3%. Loneliness above the cut-off (>3 points) were reported by 23.3%. At least having suicidal thoughts once during the lockdown were reported by 38.2%. For all mental health data see Table 2.

3.3. Drug Consumption during the First Lockdown

The respondents provided information on their alcohol, nicotine and/or THC consumption during the first lockdown. Table 3 gives the sociodemographic data of persons who had consumed any of the respective substances at least once in the last 12 months. In Table 4, the consumption data have been grouped into three categories (no consumption/less consumption, constant consumption, and more consumption). During the lockdown, 28.5% reported increased alcohol consumption, 28.8.% an increased nicotine consumption, and 20.6% reported an increased THC consumption.
In addition, 15% of the respondents reported that it was more difficult to purchase THC. Data on drug purchases for THC and other illicit drugs through the course of the lockdown is presented in Table 5.

3.4. Alcohol and Mental Health

Those respondents reporting increased alcohol consumption reported more depressive symptoms (PHQ-9) (t(1044) = −6.891, p < 0.001) compared with the group with similar or less self-reported alcohol consumption. The same was observed with regard to symptoms of anxiety disorder (GAD-7) (t(1059) = −7.584, p < 0.001) and with regard to loneliness (t(1123) = −4.869, p = 0.001). The group with increased alcohol consumption also reported more significant financial losses under the COVID-19 pandemic (X2 = 9.162, p < 0.002, df = 1), more burdens of social distancing (U = 405,484.500, Z = −6.132, p < 0.001) and more suicidal thoughts during lockdown (U = 70,896.500, Z = −2.904, p < 0.004). For detailed data, see Table 6.

3.5. Nicotine and Mental Health

The group with more nicotine consumption reported more depressive symptoms (PHQ-9) than the group with similar or less nicotine consumption (t(677) = −5.816, p < 0.001). This was also found with regard to the anxiety (t(668) = −7.013, p < 0.001) and loneliness during the lockdown (t(719) = −4.146, p < 0.001). The group with increased nicotine consumption also reported more burdens of social distancing (U = 66,379.500, Z = −5.091, p < 0.001) and more suicidal thoughts during lockdown (U = 17,111.000, Z = −2.203, p < 0.001). For detailed data, see Table 7.

3.6. THC and Mental Health

The group with more THC consumption showed more symptoms of depression (PHQ-9) compared to the group with unchanged or decreased THC consumption (t(162.079) = −2.568, p < 0.006). Similarly, those with less or unchanged THC consumption reported less anxiety measured with the GAD-7 (t(265) = −2.178, p < 0.015). For detailed data, see Table 8.

4. Discussion

The first aim of the current study was to investigate the prevalence rates of substance use (i.e., alcohol, nicotine and THC) during the pandemic in the German population.
In the current study, 28.5% reported drinking more alcohol than before the lockdown. At the same time, however, 30.3% reported consuming less alcohol during the lockdown than before. Therefore, it cannot generally be stated that alcohol consumption increased during the lockdown for most consumers as the consumption pattern seems to be more complex. These results are also in line with previous findings by Manthey and colleagues showing on average lower alcohol consumption during the first lockdown in Germany, but an increase in alcohol use in vulnerable groups [21]. A study from Ireland found that 15% of their participants reported an increase in alcohol consumption whereas 66% reported a decrease [32]. Koopman and colleagues, on the other hand, reported increased alcohol consumption in the general population in Germany [33], which was also found for consumers in the United States [34]. The current and previous findings, thus, point to an increase in alcohol use in at least a subgroup of users.
With regard to nicotine consumption, 28.8% of the respondents reported an increase in nicotine consumption whereas 32.9% reported a decrease in nicotine consumption. In line with our findings, a representative study on the prevalence of tobacco smoking in the adult population in Germany found an increase in smoking prevalence from 26.5% up to 30.9% [35]. In contrast, Damerow and colleagues reported less tobacco smoking during the lockdown [36]. Interestingly, Bommele et al. found that stress during the pandemic either predicted increased or decreased smoking behavior [37]. They postulate that the differential association between stress and smoking behavior during the pandemic might result from the fear of severe illness related to COVID-19, which, in turn, might have increased the motivation to stop smoking in some individuals whereas in others the burdens related to restrictions during the lockdown might have increased smoking behavior.
Regarding THC consumption, 52.9% decreased THC use and only 20.6% increased their consumption. This is in line with a study by Merrill et al. who found that THC use decreased in the subgroup of students during the lockdown [38]. They assume that this might be related to moving from campus to the parents’ home during the lockdown. In contrast, in a survey by Werse and Kamphausen exploring THC use in frequent users, they found that most of the respondents increased their THC consumption during the lockdown [39]. In contrast, Vanderbruggen et al. found that THC use did not change during the lockdown [19]. Thus, there is no clear picture related to the impact of the pandemic on THC consumption. Nevertheless, although most studies do not report a general increase in THC consumption but rather a decrease or no change in consumption, there seems to be a small subgroup with increased THC use during the lockdown.
The second aim of the current study was to investigate differences in mental health in individuals with increased substance use compared to individuals with unchanged or decreased substance use. As already noted, in the current study, substance use did not increase for all consumers. However, a subgroup of users reported increased use of alcohol, nicotine and THC, whereas others reported a decrease or no change in substance use. Given the high burden of disease associated with alcohol, nicotine and THC consumption [40,41,42,43,44], exploring factors that might be associated with an increase in substance use is highly warranted.
For alcohol and nicotine, individuals with an increase in substance use reported more depressive symptoms, anxiety and loneliness compared to individuals with less/unchanged substance use. Furthermore, they were more likely to report suicidal thoughts and experienced higher burdens due to social isolation. This is in line with findings from Australia showing an association between depression, anxiety and stress with increased alcohol and nicotine consumption during the lockdown [45]. In the current study, THC users with an increase in THC use reported more depressive symptoms and anxiety compared to users with unchanged consumption but no differences were found with respect to loneliness, suicidal thoughts or burdens related to social isolation between these groups.
The current findings are in line with previous findings pointing to an association between substance use and mental health problems or loneliness during the COVID-19 pandemic. Vanderbruggen and colleagues found that substance use correlates with feelings of loneliness and a loss of daily structure [19]. Faris and colleagues report that in Spain increased substance use is more likely among people with more depressive symptoms [25]. In a study from Greece, a significant proportion of respondents reported using alcohol and nicotine to cope better with anxiety and depression during the COVID 19 pandemic [26]. In a survey in France, Rolland and colleagues analyzed that lower well-being and increased stress are factors that increase behaviors related to addictions such as the use of alcohol and nicotine [27]. In an Australian study, 12.3% reported using drugs to cope with stress and emotions during the pandemic [24]. A cross-sectional study from UK also found increased alcohol consumptions predicted poor mental health [46].
Thus, the current and previous findings suggest that substance use may be used as a strategy to cope with mental health burdens during the pandemic. However, as we did not investigate whether there was a change in mental health compared to the time before the lockdown and data were acquired cross-sectionally, more research and cautious interpretation in the meantime is certainly needed.

5. Limitations

Some limitations warrant cautious interpretation of the data. The current sample is not representative for the general population in Germany due to the online recruiting process via different websites. The demographic data clearly show that both women (67.3%) and persons without children in the household (73.7%) are significantly overrepresented. Especially the factor of loneliness can thus lead to a distorted picture. Furthermore, women might be more affected by the impact of the pandemic than men [22]. In addition, our sample is highly educated. In addition, elderly people are underrepresented, which could be a result of the online recruiting process.
It should also be noted that this study did not ask if there was any change in mental health compared to the time before the lockdown, which was found in previous studies during the lockdown [47,48]. With regard to substance use, the survey provides insight into the change in substance use but gives no information about the absolute amount consumed. Further, the retrospective design of this cross-sectional study might be prone to recall biases.

6. Conclusions

To sum up, alcohol, nicotine and THC use did not increase in most of the users during the lockdown. However, there are subgroups with increased substance use. We assume that people suffering from greater psychological burdens during the lockdown are more vulnerable to increase their consumption. This increased substance use could, therefore, be understood as a strategy to cope with negative emotions during the lockdown, which could lead to additional problems. It is therefore necessary to identify vulnerable groups in times of lockdowns to promote mental health, which might also positively affect substance use. Prevention strategies thus need to address specific health needs and coping mechanisms. Additionally, methods of approaching these groups should be reflected; outreach work and target-group-specific social media campaigns could help to diminish social isolation. It is conceivable both to alleviate the psychological stress and to offer and enable other ways of coping with stress through more tailored services. The Robert Koch Institute (RKI) suggests that long-term consequences for mental health follow from prolonged stress, especially if stressors are not adequately coped with [49]. This paper shows that despite small changes in substance use in the general population, the consumption of alcohol, nicotine and THC needs to be addressed to ensure that pandemic-related burdens do not have long-term negative effects on mental health and substance (ab)use. Further research is needed to identify vulnerable groups and to develop and implement appropriate interventions.

Author Contributions

Data curation, D.D., C.F., N.H. and N.S.; Formal analysis, D.D. and N.H.; Methodology, D.D. and N.H.; Resources, H.S.; Validation, D.D. and H.S.; Writing—original draft, C.F. and S.F.; Writing—review & editing, D.D., C.F., H.S., N.H., N.S. and S.F. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The studies involving human participants were reviewed and approved by Ethics Committee of the Catholic University NRW, Department Aachen, approval nr. AZ 2020-I (25.05.2020). The minimum age for participation in the survey was set at 18 years, whereby on the basis of the German guidelines.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The datasets generated and/or analyzed during the current study are not publicly available due to reasons of sensitivity but are available from the corresponding author Daniel Deimel on reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Johns Hopkins University (JHU) Coronavirus COVID-19 (2019-NCoV). Available online: https://gisanddata.maps.arcgis.com/apps/dashboards/bda7594740fd40299423467b48e9ecf6 (accessed on 8 December 2021).
  2. Merlot, J. Erste Corona-Fälle in Deutschland: Die unglückliche Reise von Patientin null. Der Spiegel, 16 May 2020. [Google Scholar]
  3. Die Bundesregierung Vereinbarung zwischen der Bundesregierung und den Regierungschefinnen und Regierungschefs der Bundesländer angesichts der Corona-Epidemie in Deutschland. Available online: https://www.bundesregierung.de/breg-de/themen/buerokratieabbau/vereinbarung-zwischen-der-bundesregierung-und-den-regierungschefinnen-und-regierungschefs-der-bundeslaender-angesichts-der-corona-epidemie-in-deutschland-1730934 (accessed on 8 December 2021).
  4. Jones, E.A.K.; Mitra, A.K.; Bhuiyan, A.R. Impact of COVID-19 on Mental Health in Adolescents: A Systematic Review. Int. J. Environ. Res. Public Health 2021, 18, 2470. [Google Scholar] [CrossRef] [PubMed]
  5. Lee, J.; Solomon, M.; Stead, T.; Kwon, B.; Ganti, L. Impact of COVID-19 on the Mental Health of US College Students. BMC Psychol. 2021, 9, 95. [Google Scholar] [CrossRef] [PubMed]
  6. Nam, S.-H.; Nam, J.-H.; Kwon, C.-Y. Comparison of the Mental Health Impact of COVID-19 on Vulnerable and Non-Vulnerable Groups: A Systematic Review and Meta-Analysis of Observational Studies. Int. J. Environ. Res. Public Health 2021, 18, 10830. [Google Scholar] [CrossRef] [PubMed]
  7. Santomauro, D.F.; Mantilla Herrera, A.M.; Shadid, J.; Zheng, P.; Ashbaugh, C.; Pigott, D.M.; Abbafati, C.; Adolph, C.; Amlag, J.O.; Aravkin, A.Y.; et al. Global Prevalence and Burden of Depressive and Anxiety Disorders in 204 Countries and Territories in 2020 Due to the COVID-19 Pandemic. Lancet 2021, 398, 1700–1712. [Google Scholar] [CrossRef]
  8. Bäuerle, A.; Teufel, M.; Musche, V.; Weismüller, B.; Kohler, H.; Hetkamp, M.; Dörrie, N.; Schweda, A.; Skoda, E.-M. Increased Generalized Anxiety, Depression and Distress during the COVID-19 Pandemic: A Cross-Sectional Study in Germany. J. Public Health 2020, 42, 672–678. [Google Scholar] [CrossRef]
  9. Galea, S.; Merchant, R.M.; Lurie, N. The Mental Health Consequences of COVID-19 and Physical Distancing: The Need for Prevention and Early Intervention. JAMA Intern. Med. 2020, 180, 817–818. [Google Scholar] [CrossRef] [Green Version]
  10. Mazza, C.; Ricci, E.; Biondi, S.; Colasanti, M.; Ferracuti, S.; Napoli, C.; Roma, P. A Nationwide Survey of Psychological Distress among Italian People during the COVID-19 Pandemic: Immediate Psychological Responses and Associated Factors. Int. J. Environ. Res. Public Health 2020, 17, 3165. [Google Scholar] [CrossRef]
  11. Wang, C.; Pan, R.; Wan, X.; Tan, Y.; Xu, L.; Ho, C.S.; Ho, R.C. Immediate Psychological Responses and Associated Factors during the Initial Stage of the 2019 Coronavirus Disease (COVID-19) Epidemic among the General Population in China. Int. J. Environ. Res. Public Health 2020, 17, 1729. [Google Scholar] [CrossRef] [Green Version]
  12. Zhao, S.Z.; Wong, J.Y.H.; Wu, Y.; Choi, E.P.H.; Wang, M.P.; Lam, T.H. Social Distancing Compliance under COVID-19 Pandemic and Mental Health Impacts: A Population-Based Study. Int. J. Environ. Res. Public Health 2020, 17, 6692. [Google Scholar] [CrossRef]
  13. McMahon, G.; Douglas, A.; Casey, K.; Ahern, E. Disruption to Well-Being Activities and Depressive Symptoms during the COVID-19 Pandemic: The Mediational Role of Social Connectedness and Rumination. J. Affect. Disord. 2022, 309, 274–281. [Google Scholar] [CrossRef]
  14. Cénat, J.M.; Blais-Rochette, C.; Kokou-Kpolou, C.K.; Noorishad, P.-G.; Mukunzi, J.N.; McIntee, S.-E.; Dalexis, R.D.; Goulet, M.-A.; Labelle, P.R. Prevalence of Symptoms of Depression, Anxiety, Insomnia, Posttraumatic Stress Disorder, and Psychological Distress among Populations Affected by the COVID-19 Pandemic: A Systematic Review and Meta-Analysis. Psychiatr. Res. 2021, 295, 113599. [Google Scholar] [CrossRef]
  15. Rodgers, B.; Korten, A.E.; Jorm, A.F.; Jacomb, P.A.; Christensen, H.; Henderson, A.S. Non-Linear Relationships in Associations of Depression and Anxiety with Alcohol Use. Psychol. Med. 2000, 30, 421–432. [Google Scholar] [CrossRef] [PubMed]
  16. Goldmann, E.; Galea, S. Mental Health Consequences of Disasters. Annu. Rev. Public Health 2014, 35, 169–183. [Google Scholar] [CrossRef] [PubMed]
  17. European Monitoring Centre for Drugs and Drug Addiction. EMCDDA Trendspotter Briefing. Impact of COVID-19 on Drug Services and Help-Seeking in Europe; European Monitoring Centre for Drugs and Drug Addiction: Lisbon, Portugal, 2020. [Google Scholar]
  18. Niedzwiedz, C.L.; Green, M.J.; Benzeval, M.; Campbell, D.; Craig, P.; Demou, E.; Leyland, A.; Pearce, A.; Thomson, R.; Whitley, E.; et al. Mental Health and Health Behaviours before and during the Initial Phase of the COVID-19 Lockdown: Longitudinal Analyses of the UK Household Longitudinal Study. J. Epidemiol. Commun. Health 2020, 75, 224–231. [Google Scholar] [CrossRef] [PubMed]
  19. Vanderbruggen, N.; Matthys, F.; Van Laere, S.; Zeeuws, D.; Santermans, L.; Van den Ameele, S.; Crunelle, C.L. Self-Reported Alcohol, Tobacco, and Cannabis Use during COVID-19 Lockdown Measures: Results from a Web-Based Survey. Eur. Addict. Res. 2020, 26, 309–315. [Google Scholar] [CrossRef]
  20. Georgiadou, E.; Hillemacher, T.; Müller, A.; Koopmann, A.; Leménager, T.; Kiefer, F. Alkohol und Rauchen: Die COVID-19-Pandemie als idealer Nährboden für Süchte. Dtsch. Ärzteblatt 2020, 117, A–1251/B–1060. [Google Scholar]
  21. Manthey, J.; Kilian, C.; Schomerus, G.; Kraus, L.; Rehm, J.; Schulte, B. Alkoholkonsum in Deutschland Und Europa Während Der SARS-CoV-2 Pandemie. SUCHT 2020, 66, 247–258. [Google Scholar] [CrossRef]
  22. Schecke, H.; Fink, M.; Bäuerle, A.; Skoda, E.-M.; Schweda, A.; Musche, V.; Dinse, H.; Weismüller, B.M.; Moradian, S.; Scherbaum, N.; et al. Changes in Substance Use and Mental Health Burden among Women during the Second Wave of COVID-19 in Germany. Int. J. Environ. Res. Public Health 2021, 18, 9728. [Google Scholar] [CrossRef]
  23. Roberts, A.; Rogers, J.; Mason, R.; Siriwardena, A.N.; Hogue, T.; Whitley, G.A.; Law, G.R. Alcohol and Other Substance Use during the COVID-19 Pandemic: A Systematic Review. Drug Alcohol Depend. 2021, 229, 109150. [Google Scholar] [CrossRef]
  24. Czeisler, M.É.; Wiley, J.F.; Facer-Childs, E.R.; Robbins, R.; Weaver, M.D.; Barger, L.K.; Czeisler, C.A.; Howard, M.E.; Rajaratnam, S.M.W. Mental Health, Substance Use, and Suicidal Ideation during a Prolonged COVID-19-Related Lockdown in a Region with Low SARS-CoV-2 Prevalence. J. Psychiatr. Res. 2021, 140, 533–544. [Google Scholar] [CrossRef]
  25. Faris, L.H.; Gabarrell-Pascuet, A.; Felez-Nobrega, M.; Cristóbal-Narváez, P.; Mortier, P.; Vilagut, G.; Olaya, B.; Alonso, J.; Haro, J.M.; López-Carrilero, R.; et al. The Association between Substance Use Disorder and Depression during the COVID-19 Lockdown in Spain and the Moderating Role of Social Support: A Cross-Sectional Study. Int. J. Ment. Health Addict. 2021. [CrossRef] [PubMed]
  26. Rantis, K.; Panagiotidis, P.; Parlapani, E.; Holeva, V.; Tsapakis, E.M.; Diakogiannis, I. Substance Use during the COVID-19 Pandemic in Greece. J. Subst. Use 2021, 27, 231–238. [Google Scholar] [CrossRef]
  27. Rolland, B.; Haesebaert, F.; Zante, E.; Benyamina, A.; Haesebaert, J.; Franck, N. Global Changes and Factors of Increase in Caloric/Salty Food Intake, Screen Use, and Substance Use during the Early COVID-19 Containment Phase in the General Population in France: Survey Study. JMIR Public Health Surveill. 2020, 6, e19630. [Google Scholar] [CrossRef] [PubMed]
  28. Gräfe, K.; Zipfel, S.; Herzog, W.; Löwe, B. Screening psychischer Störungen mit dem “Gesundheitsfragebogen für Patienten (PHQ-D)”. Diagnostica 2004, 50, 171–181. [Google Scholar] [CrossRef]
  29. Kroenke, K.; Spitzer, R.L.; Williams, J.B.W. The PHQ-9: Validity of a Brief Depression Severity Measure. J. Gen. Intern. Med. 2001, 16, 606–613. [Google Scholar] [CrossRef]
  30. Löwe, B.; Decker, O.; Müller, S.; Brähler, E.; Schellberg, D.; Herzog, W.; Herzberg, P.Y. Validation and Standardization of the Generalized Anxiety Disorder Screener (GAD-7) in the General Population. Med. Care 2008, 46, 266–274. [Google Scholar] [CrossRef]
  31. de Jong-Gierveld, J.; van Tilburg, T. Manual of the Loneliness Scale 1999; Department of Social Research Methodology, Vrije Universiteit: Amsterdam, The Netherlands, 1999; ISBN 978-90-90-12523-7. [Google Scholar]
  32. Carbia, C.; García-Cabrerizo, R.; Cryan, J.F.; Dinan, T.G. Associations between Mental Health, Alcohol Consumption and Drinking Motives during COVID-19 Second Lockdown in Ireland. Alcohol Alcohol. 2022, 57, 211–218. [Google Scholar] [CrossRef]
  33. Koopmann, A.; Georgiadou, E.; Kiefer, F.; Hillemacher, T. Did the General Population in Germany Drink More Alcohol during the COVID-19 Pandemic Lockdown? Alcohol Alcohol. 2020, 55, 698–699. [Google Scholar] [CrossRef]
  34. Barbosa, C.; Cowell, A.J.; Dowd, W.N. Alcohol Consumption in Response to the COVID-19 Pandemic in the United States. J. Addict. Med. 2021, 15, 341–344. [Google Scholar] [CrossRef]
  35. DEBRA. DEBRA study – Deutsche Befragung zum Rauchverhalten | German Study on Tobacco Use. 2021. Available online: https://www.debra-study.info/ (accessed on 24 February 2022).
  36. Damerow, S.; Rommel, A.; Prütz, F.; Beyer, A.-K.; Hapke, U.; Schienkiewitz, A.; Starker, A.; Richter, A.; Baumert, J.; Fuchs, J.; et al. Developments in the Health Situation in Germany during the Initial Stage of the COVID-19 Pandemic for Selected Indicators of GEDA 2019/2020-EHIS. J. Health Monit. 2020, 5, 3–20. [Google Scholar] [CrossRef]
  37. Bommelé, J.; Hopman, P.; Hipple Walters, B.; Geboers, C.; Croes, E.; Fong, G.; Quah, A.; Willemsen, M. The Double-Edged Relationship between COVID-19 Stress Andsmoking: Implications for Smoking Cessation. Tob. Induc. Dis. 2020, 18, 125580. [Google Scholar] [CrossRef]
  38. Merrill, J.E.; Stevens, A.K.; Jackson, K.M.; White, H.R. Changes in Cannabis Consumption among College Students during COVID-19. J. Stud. Alcohol Drugs 2022, 83, 55–63. [Google Scholar] [CrossRef] [PubMed]
  39. Werse, B.; Kamphausen, G. Cannabis und Coronavirus SARS-CoV-2—Eine Online-Kurzbefragung während der Kontaktbeschränkungen in der frühen Phase der Pandemie. Suchttherapie 2021, 22, 101–106. [Google Scholar] [CrossRef]
  40. Crippa, J.A.; Zuardi, A.W.; Martín-Santos, R.; Bhattacharyya, S.; Atakan, Z.; McGuire, P.; Fusar-Poli, P. Cannabis and Anxiety: A Critical Review of the Evidence. Hum. Psychopharmacol. 2009, 24, 515–523. [Google Scholar] [CrossRef] [PubMed]
  41. GBD 2019 Tobacco Collaborators. Spatial, Temporal, and Demographic Patterns in Prevalence of Smoking Tobacco Use and Attributable Disease Burden in 204 Countries and Territories, 1990–2019: A Systematic Analysis from the Global Burden of Disease Study 2019. Lancet 2021, 397, 2337–2360. [Google Scholar] [CrossRef]
  42. Lev-Ran, S.; Roerecke, M.; Le Foll, B.; George, T.P.; McKenzie, K.; Rehm, J. The Association between Cannabis Use and Depression: A Systematic Review and Meta-Analysis of Longitudinal Studies. Psychol. Med. 2014, 44, 797–810. [Google Scholar] [CrossRef] [PubMed]
  43. Shield, K.; Manthey, J.; Rylett, M.; Probst, C.; Wettlaufer, A.; Parry, C.D.H.; Rehm, J. National, Regional, and Global Burdens of Disease from 2000 to 2016 Attributable to Alcohol Use: A Comparative Risk Assessment Study. Lancet Public Health 2020, 5, e51–e61. [Google Scholar] [CrossRef] [Green Version]
  44. Wilson, J.; Freeman, T.P.; Mackie, C.J. Effects of Increasing Cannabis Potency on Adolescent Health. Lancet Child Adolesc. Health 2019, 3, 121–128. [Google Scholar] [CrossRef] [Green Version]
  45. Stanton, R.; To, Q.G.; Khalesi, S.; Williams, S.L.; Alley, S.J.; Thwaite, T.L.; Fenning, A.S.; Vandelanotte, C. Depression, Anxiety and Stress during COVID-19: Associations with Changes in Physical Activity, Sleep, Tobacco and Alcohol Use in Australian Adults. Int. J. Environ. Res. Public Health 2020, 17, 4065. [Google Scholar] [CrossRef]
  46. Jacob, L.; Smith, L.; Armstrong, N.C.; Yakkundi, A.; Barnett, Y.; Butler, L.; McDermott, D.T.; Koyanagi, A.; Shin, J.I.; Meyer, J.; et al. Alcohol Use and Mental Health during COVID-19 Lockdown: A Cross-Sectional Study in a Sample of UK Adults. Drug Alcohol Depend. 2021, 219, 108488. [Google Scholar] [CrossRef]
  47. Das, A.; Singh, P.; Bruckner, T.A. State Lockdown Policies, Mental Health Symptoms, and Using Substances. Addict. Behav. 2022, 124, 107084. [Google Scholar] [CrossRef] [PubMed]
  48. Khubchandani, J.; Sharma, S.; Webb, F.J.; Wiblishauser, M.J.; Bowman, S.L. Post-Lockdown Depression and Anxiety in the USA during the COVID-19 Pandemic. J. Public Health 2021, 43, 246–253. [Google Scholar] [CrossRef] [PubMed]
  49. Mauz, E.; Eicher, S.; Peitz, D.; Junker, S.; Hölling, H.; Thom, J. Psychische Gesundheit der erwachsenen Bevölkerung in Deutschland während der COVID-19-Pandemie. Ein Rapid-Review. J. Health Monit. 2021, 6, 2–65. [Google Scholar] [CrossRef] [PubMed]
Table 1. Sociodemographic data of the entire sample.
Table 1. Sociodemographic data of the entire sample.
n%
Gender Identity 2327
Female 1595 67.3
Male 732 30.9
Diverse 35 1.5
Age 2369
18–24 351 14.8
25–34 485 20.5
35–44 477 20.1
45–54 435 18.4
55–64 439 18.5
≥65 182 7.7
Education2359
University or university of applied sciences diploma 1228 51.8
Completed vocational education 285 12.0
Completion of secondary school 833 35.2
Other/none 13 0.5
Employment status2363
Full-time employed 853 36.0
Part-time employed 605 25.5
Student 418 17.6
Retired 247 10.4
Unemployed 94 4.0
Other 146 6.2
Monthly net income2284
<1000 Euros 604 25.5
1000–2000 Euros 742 31.3
2000–3000 Euros 599 25.3
More than 3000 Euros 339 14.3
Financial losses due to the Corona pandemic2360
no financial losses 1600 67.5
very small financial losses 401 16.9
significant financial losses 243 10.3
very strong financial losses 62 2.6
the income has completely disappeared 54 2.3
Children in household2354
0 1746 73.7
1 241 10.2
2 269 11.4
3 74 3.1
≥4240.9
Preexisting chronic conditions
cardiovascular diseases/hypertension 335 14.1
weakened immune system 261 11.0
high obesity 241 10.2
chronic respiratory diseases1737.3
diabetes mellitus883.7
cancer743.1
chronic liver diseases210.9
Table 2. Mental health.
Table 2. Mental health.
MMDSDMinMax>Cut-Off
Depressive Symptoms (PHQ-9) 7.165.902725.9%
Generalized Anxiety (GAD-7)6.655.302123.3%
Loneliness1.612.201123.3%
Burdens of social isolation during lockdown3.531.416--
n%
Suicidal thoughts during lockdown938
Never 580 61.8
rarely (once) 193 20.6
sometimes (2 times) 92 9.8
often (3–4 times) 31 3.3
very often (5 times or more) 42 4.5
Table 3. Sociodemographic data of persons who used alcohol, nicotine and THC in the last 12 months.
Table 3. Sociodemographic data of persons who used alcohol, nicotine and THC in the last 12 months.
Alcohol Consumption Last 12 Months
n = 2207
Nicotine Consumption
Last 12 Months
n = 920
THC Consumption
Last 12 Months
n = 478
n%n%n%
Gender Identity 2148 895 465
Female 1458 66.1 565 63.1 267 57.4
Male 659 29.8 311 34.7 180 38.7
Diverse 31 1.4 19 2.1 18 3.9
Age 2144 896 464
18–2432715.3 164 18.3 121 26.1
25–3444620.8 237 26.5 147 31.7
35–4443420.2 180 20.1 89 19.2
45–5438818.1 173 19.3 61 13.1
55–6439118.2 118 13.2 42 9.1
≥651587.4 24 2.7 4 0.9
Education2145 890 462
University or university of applied sciences diploma114553.4 405 45.5 212 45.9
Completed vocational education24911.6 116 13.0 55 11.9
Completion of secondary school74334.6 367 41.2 195 42.2
Other/none80.4 2 0.2 0 0.0
Employment status2202 918 478
Full-time employed80936.7 338 36.8 170 35.6
Part-time employed56725.7 225 24.5 107 22.4
Student40118.2 207 22.5 131 27.4
Retired 2159.8 46 5.0 16 3.3
Unemployed793.6 49 5.3 22 4.6
Other1315.9 53 5.8 32 6.7
Monthly net income2076 881 458
<1000 Euros54126.1 261 29.6 165 36.0
1000–2000 Euros67332.4 310 35.2 153 33.4
2000–3000 Euros54926.4 208 23.6 100 21.8
More than 3000 Euros31315.1 102 11.6 40 8.7
Financial losses due to the Corona pandemic2200 917 477
no financial losses148767.6 585 63.8 289 60.6
very small financial losses38117.3 164 17.9 80 16.8
significant financial losses22210.1 115 12.5 68 14.3
very strong financial losses612.8 32 3.5 18 3.8
the income has completely disappeared492.2 21 2.3 22 4.6
Preexisting chronic conditions2207 920 478
cardiovascular diseases/hypertension30013.6 108 11.7 41 8.6
weakened immune system22510.2 108 11.7 74 15.5
high obesity 214 9.7 85 9.2 37 7.7
chronic respiratory diseases 155 7.0 697.5387.9
diabetes mellitus793.6313.491.9
cancer 69 3.1 192.140.8
chronic liver diseases150.760.730.6
Table 4. Substance use during first lockdown.
Table 4. Substance use during first lockdown.
Substance Usen%
Alcohol
Alcohol use last 12 months2207 94.0
Alcohol use during lockdown2184
no consumption/less than before66130.3
unchanged90041.2
more than before62328.5
Nicotine
Nicotine use last 12 months92045.6
Nicotine use during lockdown907
no consumption/less than before29832.9
unchanged34838.4
more than before26128.8
THC
THC use last 12 months47823.5
THC use during lockdown467
no consumption/less than before24752.9
unchanged12426.6
more than before9620.6
Table 5. Drug purchase during lockdown.
Table 5. Drug purchase during lockdown.
Drug Purchase during LockdownTHC
(n = 187)
Amphetamine
(n = 28)
Methamphetamine
(n = 8)
Cocaine
(n = 29)
Ecstasy
(n = 25)
n%n%n%n%n%
Easier than before the lockdown 4 2.1 2 7.1 112.513.428.0
Same as before the lockdown 155 82.9 18 64.3 450.02379.31768.0
More difficult than before the lockdown, at a lower or the same price 19 10.2 6 21.4 225.0310.3416.0
More difficult than before the lockdown, at a higher price 9 4.8 2 7.1 112.526.928.0
Table 6. Alcohol use and mental health.
Table 6. Alcohol use and mental health.
VariableNo Increase in Alcohol Use Increase in Alcohol Use Test-Statistic
95% CI Effect size
NM (SD) NM (SD) t-testLLULp-valueCohens d
Age125843.04 (15.88) 60640.36 (13.27) 3.831.314.060.0010.19
Mental health
Depression (PHQ-9 score)12106.30 (6.63) 5618.35 (5.91) −6.89−2.63−1.470.0010.37
Anxiety (GAD-7 score)11905.81 (5.04) 5717.85 (5.39) −7.58−2.57−1.510.0010.39
Loneliness (score)12902.56 (2.42) 6233.18 (2.68) −4.87−0.87−0.370.0010.25
N% N% X2 p-valuePhi
Gender2126
Female106970.4 37561.8 16.69 0.0010.089
Male43328.5 21835.9
Diverse171.1 142.3
Monthly net income2056
<1.000 Euros38626.3 15025.5 0.49 0.921
1.000–2.000 Euros48032.7 18832.0
2.000–3.000 Euros38726.4 15826.9
More than 3.000 Euros21514.6 9215.6
Mental health
Depression (PHQ-9 ≥ 10)129828.2 53536.1 11.09 0.0010.08
Anxiety (GAD-7 ≥ 10)143621.5 57134.0 33.76 0.0010.13
Loneliness (cut-off ≥ 3)67143.1 31350.2 9.25 0.0020.07
Significant financial losses from the Corona pandemic15564.1 6217.2 9.16 0.0020.07
NMdn (IQR)MNMdn (IQR)MMann–Whitney-U p-valuer
Burdens of social distancing15583 (2)3.366234 (2)3.76405,484.50 0.0010.13
Suicidal thoughts during lockdown5771 (1)1.592751 (1)1.8170,896.50 0.0040.10
Table 7. Nicotine consumption and mental health.
Table 7. Nicotine consumption and mental health.
VariableNo Increase in Nicotine Use Increase in Nicotine Use Test-Statistic
95% CI Effect size
NM (SD) NM (SD) t-testLLULp-valueCohens d
Age45040.08 (13.92) 25437.96 (12.66) 1.990.344.190.0230.16
Mental health
Depression (PHQ-9 score)4357.24 (6.15) 24410.12 (6.28) −5.82−3.86−1.910.001−0.47
Anxiety (GAD-7 score)4286.39 (5.41) 2429.49 (5.65) −7.01−3.97−2.230.001−0.56
Loneliness (score)4602.81 (2.53) 2613.62 (2.50) −4.15−1.19−0.430.001−0.32
N% N% X2 p-valuePhi
Gender883
Female39963.5 16062.7 0.61 0.739
Male21734.6 8834.5
Diverse121.9 72.7
Monthly net income869
<1.000 Euros18129.3 7529.9 7.39 0.060
1.000–2.000 Euros22235.9 8835.1
2.000–3.000 Euros13421.7 6927.5
More than 3.000 Euros8113.1 192.2
Mental health
Depression (PHQ-9 ≥ 10)18032.4 11246.9 14.96 0.0010.14
Anxiety (GAD-7 ≥ 10)14023.2 11246.3 44.09 0.0010.23
Loneliness (cut-off ≥ 3)30246.7 16161.7 16.60 0.0010.14
Significant financial losses from the Corona pandemic325.0 218.0 3.17 0.075
NMdn (IQR)MNMdn (IQR)MMann–Whitney-U p-valuer
Burdens of social distancing6453 (3)3.442614 (2)3.9766,379.50 0.0010.17
Suicidal thoughts during lockdown2751 (1)1.671411 (1)1.9217,111.00 0.0280.11
Table 8. THC consumption and mental health.
Table 8. THC consumption and mental health.
VariableNo Increase in THC Use Increase in THC Use Test-Statistic
95% CI Effect size
NM (SD) NM (SD) t-testLLULp-valueCohens d
Age18233.86 (12.49) 9434.87 (12.70) 0.62−2.164.130.537
Mental health
Depression (PHQ-9 score)1728.42 (5.95) 9210.63 (7.00) −2.57−3.90−0.510.006−0.35
Anxiety (GAD-7 score)1797.69 (5.64) 899.31 (5.95) −2.18−3.09−0.160.015−0.28
Loneliness (score)1893.26 (2.45) 963.70 (2.43) −1.42−1.04−0.170.079
N% N% X2 p-valuePhi
Gender454
Female20958.2 5456.8 0.07 0.968
Male13637.9 3738.9
Diverse143.9 44.2
Monthly net income448
<1.000 Euros13036.7 3537.2 3.06 0.383
1.000–2.000 Euros11231.6 3739.4
2.000–3.000 Euros7922.3 1617.0
More than 3.000 Euros339.3 66.4
Mental health
Depression (PHQ-9 ≥ 10)13641.2 4451.2 2.75 0.097
Anxiety (GAD-7 ≥ 10)11432.7 3640.4 1.91 0.167
Loneliness (cut-off ≥ 3)20755.8 6163.5 1.87 0.171
Significant financial losses from the Corona pandemic287.6 1212.5 2.36 0.124
NMdn (IQR)MNMdn (IQR)MMann–Whitney-U p-valuer
Burdens of social distancing3704 (2)3.62964 (2)3.9315,520.00 0.051
Suicidal thoughts during lockdown2011 (1)1.74571 (2)1.955264.50 0.295
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Deimel, D.; Firk, C.; Stöver, H.; Hees, N.; Scherbaum, N.; Fleißner, S. Substance Use and Mental Health during the First COVID-19 Lockdown in Germany: Results of a Cross-Sectional Survey. Int. J. Environ. Res. Public Health 2022, 19, 12801. https://doi.org/10.3390/ijerph191912801

AMA Style

Deimel D, Firk C, Stöver H, Hees N, Scherbaum N, Fleißner S. Substance Use and Mental Health during the First COVID-19 Lockdown in Germany: Results of a Cross-Sectional Survey. International Journal of Environmental Research and Public Health. 2022; 19(19):12801. https://doi.org/10.3390/ijerph191912801

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Deimel, Daniel, Christine Firk, Heino Stöver, Nicolas Hees, Norbert Scherbaum, and Simon Fleißner. 2022. "Substance Use and Mental Health during the First COVID-19 Lockdown in Germany: Results of a Cross-Sectional Survey" International Journal of Environmental Research and Public Health 19, no. 19: 12801. https://doi.org/10.3390/ijerph191912801

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