Alcohol Use and Its Related Psychosocial Effects during the Prolonged...

[Full title: Alcohol Use and Its Related Psychosocial Effects during the Prolonged COVID-19 Pandemic in Japan: A Cross-Sectional Survey]

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International Journal of Environmental Research and Public Health Article Alcohol Use and Its Related Psychosocial Effects during the Prolonged COVID-19 Pandemic in Japan: A Cross-Sectional Survey Nagisa Sugaya 1 , Tetsuya Yamamoto 2, *, Naho Suzuki 3 and Chigusa Uchiumi 2 Citation: Sugaya, N.; Yamamoto, T.; Suzuki, N.; Uchiumi, C. Alcohol Use and Its Related Psychosocial Effects during the Prolonged COVID-19 Pandemic in Japan: A Cross-Sectional Survey Int. J. Environ. Res. Public Health 2021 , 18 , 13318. https:// doi.org/10.3390/ijerph 182413318 Academic Editor: Paul B. Tchounwou Received: 11 October 2021 Accepted: 11 December 2021 Published: 17 December 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/) 1 Unit of Public Health and Preventive Medicine, School of Medicine, Yokohama City University, Yokohama 236-0004, Japan; nagisa_s@yokohama-cu.ac.jp 2 Graduate School of Technology, Industrial and Social Sciences, Tokushima University, Tokushima 770-8502, Japan; uchiumi@tokushima-u.ac.jp 3 Graduate School of Sciences and Technology for Innovation, Tokushima University, Tokushima 770-8502, Japan; gypll.82@gmail.com * Correspondence: t.yamamoto@tokushima-u.ac.jp; Tel.: +81-88-656-7617 Abstract: We conducted a large-scale survey in the Japanese population, about one year after the initial declaration of the state of emergency, to investigate alcohol use under the prolonged coronavirus disease 2019 (COVID-19) pandemic and its related psychosocial and demographic characteristics The survey was conducted online between 15 and 20 June 2021. A total of 11,427 participants were included in the analysis (48.5% female, 48.82 ± 13.30 years, range = 20–90 years). Compared with females, males were more prevalent in the hazardous user and the potential alcoholism group and were less prevalent in the no alcohol-related problem group. However, the prevalence of potential alcoholism among the participants in our study was higher than that previously reported. This trend was particularly pronounced in women. The presence of potential alcoholism was related to a deteriorated psychological status, particularly depression and anxiety, and various difficulties in their daily lives due to the COVID-19 pandemic. In the future, intervention methods and systems should be developed to provide optimal assistance to people with psychological problems who are vulnerable to alcohol-related problems during the COVID-19 pandemic, while conducting further long-term follow-up studies Keywords: the coronavirus disease 2019; alcohol use; the Alcohol Use Disorders Identification Test; mental health 1. Introduction Coronavirus disease 2019 (COVID-19) has rapidly spread worldwide since its outbreak in December 2019. To deter the spread of COVID-19, many countries have imposed repeated lockdowns with restrictions on outings, service closures, and so forth. While lockdowns are expected to deter the spread of infection, they also cause psychological distress and economic damage [ 1 , 2 ]. Many studies have been conducted on alcohol use during the COVID-19 pandemic and its lockdown in many countries [ 3 , 4 ]. Alcohol use was reported to be one of the factors associated with higher odds of suicidal behavior during the COVID-19 pandemic [ 5 ]. Although some studies in Japan, India, the United States, and Czechia reported that alcohol use decreased [ 6 , 7 ] or that alcohol-related problems did not change [ 8 , 9 ] during the COVID-19 pandemic, other studies in the United States and Norway reported that alcohol use or alcohol-related problems increased [ 10 – 13 ]. Findings from eight European countries indicated that during the first months of the COVID-19 pandemic, alcohol consumption in the upper decile of drinkers increased, as did the prevalence of heavy drinkers, in contrast to the declining consumption in other groups in the sample [ 14 ]. Previous research in the United States found that participants reported drinking more alcohol due to having Int. J. Environ. Res. Public Health 2021 , 18 , 13318. https://doi.org/10.3390/ijerph 182413318 https://www.mdpi.com/journal/ijerph

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Int. J. Environ. Res. Public Health 2021 , 18 , 13318 2 of 13 more time (28%) or boredom (22%) [ 15 ]. Studies from Italy and Belgium reported that increased alcohol consumption was particularly prevalent in men [ 16 , 17 ]. Among women in Germany, 23% increased their alcohol consumption during the COVID-19 pandemic, and the presence of generalized anxiety was a significant predictor of increases in alcohol use [ 18 ]. Another study from Germany reported that consuming more alcohol during lockdown was associated with middle age, higher subjective stress due to the COVID-19 pandemic, a lower agreement with the importance of the restrictions, and consuming alcohol more than once per week before the lockdown [ 19 ]. Previous results in Norway showed that people aged 30–39 years had higher odds of increased alcohol consumption during lockdown compared to the oldest adults, and increased alcohol consumption was more frequent among people reporting economic troubles, those quarantined, and those studying or working at home [ 20 ]. A previous study estimated that there were 3 million alcohol-attributable deaths in 2016 globally, and reported that alcohol use was a major risk factor for communicable, maternal, perinatal, and nutritional diseases, non-communicable diseases, and injury deaths [ 21 ]. Therefore, it is important to understand worldwide problems of alcohol use during the COVID-19 pandemic in order to take measures to protect people’s health The Japanese government repeatedly declared a state of emergency in April 2020 While many countries were in lockdown with penalties for violations, the Japanese policy for COVID-19 differed as the government did not impose penalties and only requested people to refrain from going out, except for emergencies, and to temporarily limit certain businesses. However, the “mild lockdown” [ 22 ] in Japan affected people’s lives in many ways, causing changes in their lifestyle due to teleworking or online classes, and economic damage due to decreased income or job loss [ 23 ]. The prolonged COVID-19 pandemic and repeated declaration of states of emergency may significantly deteriorate the psychological condition of the Japanese population [ 24 ]. These long-term stressful conditions and behavioral restrictions may affect alcohol use in the Japanese population. In a recent survey in Japan, the percentage of those who drank alcohol in amounts that increased their risk of lifestyle-related diseases (women: 20 g/day or more of pure alcohol; men: 40 g/day or more) decreased between 2013 and 2018, but did not change for women [ 25 ]. A nationwide survey in Japan conducted in 2018 suggested that alcoholism was prevalent among 40,000 women and 220,000 men, of which around 80% did not seek medical care [ 25 ]. A previous study [ 6 ] on dietary patterns including alcohol use in the Japanese population was conducted during the early stages of the COVID-19 pandemic (January–May 2020), and it reported that their alcohol intake decreased. However, no previous research has investigated problematic alcohol use during the prolonged COVID-19 pandemic and its demographic and psychosocial factors in Japan using large-scale samples, to the best of our knowledge. Moreover, a survey conducted later in the pandemic, such as 1 year after, may yield different results from the previous studies described above. Thus, we conducted a large-scale survey in the Japanese population about one year after the initial declaration of the state of emergency to investigate alcohol use during the prolonged COVID-19 pandemic and its related psychosocial and demographic characteristics 2. Materials and Methods 2.1. Participants and Data Collection The survey was conducted online between 15–20 June 2021. The survey period was during the third state of the emergency. We conducted an online survey with the following inclusion criteria: (a) inhabitants living in the six prefectures (Tokyo, Aichi, Osaka, Kyoto, Hyogo, and Fukuoka) and (b) age ≥ 20 years. The exclusion criteria were (a) age < 20 years and (b) high school students. The number of participants from each prefecture was determined based on the ratio of the prefecture’s populations—Tokyo ( n = 3763; 32.9%), Aichi ( n = 1827; 16.0%), Osaka ( n = 2360; 20.6%), Kyoto ( n = 618; 54.0%), Hyogo ( n = 1516; 13.2%), and Fukuoka ( n = 1369; 12.0%).

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Int. J. Environ. Res. Public Health 2021 , 18 , 13318 3 of 13 Through Macromill.inc. (Tokyo, Japan), a global marketing research company, participants were recruited via email, and data were collected on an online platform. Participants completed the online survey after having received a link. All participants voluntarily responded to the survey anonymously and provided their informed consent online before completing the survey. Participants received a clear explanation of the survey procedure and could interrupt or terminate the survey at any time without providing a reason. The questionnaire format, excluding the default items provided by Macromill, Inc. (sex, age, occupation, annual household income, marital status, and presence of children), did not allow participants to proceed to the next page if there were items they had not answered. All participants received Macromill points for their participation, which could be exchanged for prizes or cash. Macromill points are a points-based reward system provided by Macromill Inc This study was approved by the Research Ethics Committee of the Graduate School of Social and Industrial Science and Technology, Tokushima University (acceptance number 212) and was performed per the ethical standards of the 1964 Declaration of Helsinki and its later amendments 2.2. Measurements 2.2.1. Sociodemographic Characteristics We collected sociodemographic information in participants including age, sex, employment status (employed, homemaker, student, unemployed, or other), marital status, the presence of child, and annual household income (<2.0 million JPY, 2.0–3.9 million JPY, 4.0–5.9 million JPY, 6.0–7.9 million JPY, ≥ 8.0 million JPY, or unknown) 2.2.2. Alcohol Use Alcohol use was assessed using the Japanese version of the Alcohol Use Disorders Identification Test (AUDIT) [ 26 ]. The AUDIT has 10 items across three domains: hazardous alcohol use (three items), dependence symptoms (three items), and harmful alcohol use (four items). Each item was scored from 0 to 4, 0, 2, or 4. The lowest possible score of the AUDIT was 0, and the highest possible score was 40. The likelihood and severity of hazardous drinking, harmful drinking, and alcohol dependence increased as the score increased. Persons with a score of 8 points or higher in the AUDIT were considered to have a hazardous drinking problem (hazardous user group), and those with a score of 15 points or higher were considered to have alcohol dependence (potential alcoholism group) based on the cut-off criteria of the AUDIT by the World Health Organization and in specific health guidance by the Japanese Ministry of Health, Labour and Welfare [ 27 , 28 ]. Persons with a score of 7 points or lower were defined as those without alcohol problems (no problem group). Previous research conducted in the Japanese population before the COVID-19 pandemic reported that males had higher AUDIT scores than females [ 29 ]. 2.2.3. Psychological Distress We used the Japanese version of the Kessler Psychological Distress Scale-6 (K 6) [ 30 ], which is a six-item screening instrument measuring non-specific psychological distress over the past 30 days. Each question was rated on a scale of 0 (none of the time) to 4 (all of the time), with total scores ranging from 0 to 24. Because of its high accuracy and brevity, the K 6 is considered an ideal scale for screening for mental disorders or psychological distress in population-based health surveys [ 30 – 32 ]. K 6 scores ranging from 5 to 12 were defined as mild-to-moderate psychological distress. This threshold is the optimal lower threshold cutoff point for screening for moderate psychological distress [ 33 ]. A threshold score of 13 was traditionally used in previous studies [ 31 , 34 ]. A score of ≥ 13 was defined as serious psychological distress, and a score of ≤ 4 was defined as no or low psychological distress 2.2.4. Depression Symptoms We used the Japanese version of the Patient Health Questionnaire-9 (PHQ-9) [ 35 ] to evaluate the symptoms of depression amongst the participants; the PHQ-9 comprised

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Int. J. Environ. Res. Public Health 2021 , 18 , 13318 4 of 13 nine questions. Symptoms of depression during the past four weeks were reported by the participants, with a score of 0 (not at all) to 3 (nearly every day) [ 36 ]. A score of ≥ 10 was recommended as a cutoff point to indicate that a person was more likely to have major depression 2.2.5. Anxiety We used the Japanese version of the Generalized Anxiety Disorder-7 (GAD-7) [ 37 ] to assess anxiety symptoms. Seven questions were rated on a scale of 0 (Never) to 3 (Almost every day). The total score ranged from 0 to 21 points [ 38 ]. In the evaluation of symptoms, a score of 0 to 4 points indicates no anxiety disorder, 5 to 9 indicates mild anxiety, 10 to 14 indicates moderate anxiety, and 15 to 21 indicates severe anxiety disorder. A respondent who scored 10 points or more was considered to require drug therapy 2.2.6. Loneliness We measured loneliness using the Japanese version of the UCLA Loneliness Scale Version 3 (UCLA-LS 3) [ 39 ]. The UCLA-LS 3 consists of 10 items, and each question was rated on a scale of 1 (never) to 4 (always) [ 40 ]. The total scores ranged from 10 to 40, with higher scores indicating higher levels of loneliness 2.2.7. Social Isolation We measured the social networks of the participants during the state of emergency using the Japanese version of the abbreviated Lubben Social Network Scale (LSNS-6) [ 41 ]. The LSNS-6 is a shortened version of the Lubben Social Network Scale [ 42 ] that includes six items on the network size of relatives or friends who provide emotional and instrumental support. The LSNS-6 consists of three items related to the family and friendship network each. Each question was rated on a scale of 0 (none) to 5 (nine or more) [ 43 ]. The total score ranged from 0 to 30 points, with higher scores indicating a larger social network and <12 points indicating social isolation 2.2.8. Lifestyle, Coping Behavior, and Stressors Related to the Mild Lockdown With extensive references to the literature on the COVID-19 pandemic [ 44 – 48 ], we developed eight lifestyle and coping behavior items, and seven stressor items were assumed to be associated with mild lockdown (Table 1 ). We asked participants to rate the frequency of implementation and experience of these items from the start of the mild lockdown to the time of the survey on a scale of 1 (not at all) to 7 (extremely). Since these items have not been validated for total score, each item was scored separately Table 1. Items about lifestyle, coping behavior, and stressors related to mild lockdown 1 I exercised for my health (whether indoors or outdoors) 2 I took meals considering the nutrition balance 3 I kept regular awakening time and bedtime approximately 4 I engaged in activities such as hobbies with absorbing interest 5 I interacted with my family or friends on a face-to-face basis (outside of work or class) 6 I interacted with my family or friends online using chat or video calling (except work or class) 7 I spontaneously refrained from going out or took preventive behaviors (e.g., wearing a mask) to prevent coronavirus disease 2019 infection to my family or other people 8 I thought about the future positively 9 The family budget has tightened 10 A personal relationship with a close person such as family or friends got worse 11 I have become easily annoyed or irate due to life changes 12 I felt nervous or anxious when I watched the news about coronavirus disease 2019 13 Because I kept thinking about coronavirus disease 2019 infection, I could not sleep 14 My daily life was disrupted due to the shortage of materials relating to prevention for coronavirus disease 2019 infection (e.g., mask or thermometer) or other daily supplies 15 My work or schoolwork was disrupted due to a life change.

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Int. J. Environ. Res. Public Health 2021 , 18 , 13318 5 of 13 2.3. Statistical Analysis The χ 2 test was applied to compare sociodemographic data between the three AU- DIT groups. The t -test was used to compare psychological indexes between the sexes We used multivariate analysis of variance (MANOVA) and one-way analysis of variance (ANOVA) to compare each variable between the three AUDIT groups, and a post hoc test with Scheffe’s method was employed to test the differences between groups. For all tests, significance was set at α = 0.05, two-tailed. Cramer’s V (0.100 small; 0.300 medium; 0.600 large) and η 2 (0.010 small; 0.060 medium; 0.140~ large) were calculated as the effect sizes for the χ 2 test and one-way ANOVA and used to interpret the results because the sample size of this study was large. We used multivariate analysis of covariance (MANCOVA) to compare psychological indexes and items related to lifestyle, coping behavior, and stressors related to mild lockdown conditions between the three AUDIT groups adjusting for sociodemographic characteristics. Multinomial logistic regression analyses using the backward stepwise method were conducted to examine the effects of hazardous alcohol use and potential alcoholism on sociodemographic characteristics, psychological index, and items regarding lifestyle, coping behavior, and stressors related to the mild lockdown. Multicollinearity among the independent variables of the final model was checked to assess potential bias in the results due to collinearity. Statistical analyses were performed using SPSS software (version 25.0; IBM Corp, New York, NY, USA) 3. Results 3.1. Descriptive Results A total of 11453 individuals participated in the study. Excluding participants under the age of 20, who were prohibited from drinking by Japanese law, 11,427 participants were included in the analysis (48.5% female, mean age = 48.82 ± 13.30 years, range = 20–90 years) In our dataset, although 1152 participants (10.1%) did not provide any data regarding annual household income, there were no missing data for the other variables. The item “Unknown” in annual household income includes the missing values ( N = 1254) The average AUDIT scores in males and females were 5.42 ± 6.51 and 2.82 ± 4.80 Based on the classification according to AUDIT scores, the No Problem group ( ≤ 7) had 9379 (82.1%), the hazardous user group (8–14) had 1221 (10.7%), and the potential alcoholism group ( ≥ 15) had 827 (7.2%) (Table 2 ) people each. There was a significant difference in age between the three groups ( F [2, 11424] = 21.31, p < 0.001, η 2 = 0.004), but the difference did not exceed the lower limit of “small effect size” (i.e., η 2 > 0.010). The age of the hazardous user group (51.05 ± 12.61 years) was significantly higher than those of the No Problem group (48.47 ± 13.52 years, p < 0.001) and the Potential Alcoholism group (49.46 ± 11.37 years, p = 0.024). Although there were significant differences between the groups in all psychological indexes, only GAD-7 and LSNS-6 exceeded the lower limit of the “small effect size” (Cohen’s d > 0.200, Table 3 ). 3.2. Differences in Sociodemographic Characteristics between the Three AUDIT Groups Table 2 shows the differences in sociodemographic data between the three AUDIT groups. There were significant differences between the three AUDIT groups in all sociodemographic characteristics. The results of the residual analysis that exceeded the lower limit of “small effect size” (i.e., Cramer’s V > 0.100) showed that the prevalence of males in the hazardous user and potential alcoholism groups was higher than in the no problem group 3.3. Differences in Psychological Index Scores and COVID-19 Related Variables between the Three AUDIT Groups In the result of MANOVA for psychological index scores and COVID-19 related variables in the three AUDIT groups, the Box’s M value of 1493.69 was associated with a p -value of <0.001, which indicated that the covariance matrices between the groups were not assumed to be equal for the MANOVA. Thus, the one-way ANOVA was conducted to compare the three AUDIT groups.

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Int. J. Environ. Res. Public Health 2021 , 18 , 13318 6 of 13 Table 2. Comparisons of sociodemographic data between three AUDIT group N (%) in Each AUDIT Group Group Difference Total No Problem Hazardous User Potential Alcoholism χ 2 p Cramer’s V Overall 11,427 9379 (82.1) 1221 (10.7) 827 (7.2) Sex 409.01 <0.001 0.189 Male 5881 4413 (75.0) [ − ] 865 (14.7) [+] 603 (10.3) [+] Female 5546 4966 (89.5) [+] 356 (6.4) [ − ] 224 (4.0) [ − ] Age 108.40 <0.001 0.069 20–39 3018 2634 (87.3) [+] 229 (7.6) [ − ] 155 (5.1) [ − ] 40–64 6922 5500 (79.5) [ − ] 817 (11.8) [+] 605 (8.7) [+] ≥ 65 1487 1245 (83.7) 175 (11.8) 67 (4.5) [ − ] Occupation 156.61 <0.001 0.083 Employed 7994 6360 (79.6) [ − ] 949 (11.9) [+] 685 (8.6) [+] Homemaker 1754 1609 (91.7) [+] 98 (5.6) [ − ] 47 (2.7) [ − ] Student 124 102 (82.3) 13 (8.8) 9 (7.3) Unemployed 1213 1023 (84.3) [+] 124 (10.2) 66 (5.4) [ − ] Other 342 285 (83.3) 37 (10.8) 20 (5.8) Marital status 14.67 0.001 0.036 Married 7217 5864 (81.3) [ − ] 832 (11.5) [+] 521 (7.2) Unmarried 4210 3515 (83.5) [+] 389 (9.2) [ − ] 306 (7.3) The presence of child 12.42 0.002 0.033 Yes 6388 5185 (81.2) [ − ] 740 (11.6) [+] 463 (7.2) No 5039 4194 (83.2) [+] 481 (9.5) [ − ] 364 (7.2) Annual household income 67.22 <0.001 0.061 <2.0 million JPY 715 601 (84.1) [+] 57 (8.0) [ − ] 57 (8.0) 2.0–3.9 million JPY 2065 1740 (84.3) [+] 207 (10.0) [ − ] 118 (5.7) [ − ] 4.0–5.9 million JPY 2246 1819 (81.0) 271 (12.1) 156 (6.9) 6.0–7.9 million JPY 1670 1343 (80.4) 178 (10.7) 149 (8.9) [+] ≥ 8.0 million JPY 2313 1757 (76.0) [ − ] 339 (14.7) [+] 217 (9.4) [+] Cramer’s V : 0.100~small; 0.300~medium; 0.600~large. [+]: adjusted residuals ≥ 1.96 [ − ]: adjusted residuals ≤ − 1.96. AUDIT: Alcohol Use Disorders Identification Test. No Problem: AUDIT score < 8. Hazardous User: AUDIT score = 8~14. Potential Alcoholism: AUDIT score ≥ 15 Table 3. Comparisons of psychological index scores between men and women Mean (SD) Group Difference Male Female Difference (95%CI) p Cohen’s d K 6 3.77 (5.26) 4.78 (5.50) − 1.00 ( − 1.20, − 0.80) <0.001 0.186 PHQ-9 3.76 (5.62) 4.83 (5.79) − 1.06 ( − 1.27, − 0.85) <0.001 0.187 GAD-7 2.71 (4.40) 3.69 (4.79) − 0.98 ( − 1.15, − 0.81) <0.001 0.213 UCLA-LS 3 24.37 (5.60) 23.71 (6.08) 0.66 (0.45, 0.87) <0.001 0.113 LSNS-6 8.92 (6.30) 10.25 (5.81) − 1.33 ( − 1.55, − 1.11) <0.001 0.219 Cohen’s d : 0.200~small; 0.500~medium; 0.800~large Table 4 indicates the differences in psychological index scores between the three AUDIT groups. There were significant differences between the three AUDIT groups in all psychological index scores. Regarding the K 6, PHQ-9, and GAD-7, which exceeded the lower limit of “small effect size” (i.e., η 2 > 0.010), multiple comparison analysis by Scheffe’s method showed that the scores in the potential alcoholism group were significantly higher than those in the hazardous user and no problem groups Table 5 shows the differences in COVID-19 related variables between the three AUDIT groups. There were significant group differences in all items except “Offline interaction with familiar people”. In the items “Altruistic preventive behaviors of COVID-19”, “Deterioration of relationship with familiar people”, “COVID-19-related sleeplessness”, “Difficulties owing to the lack of daily necessities”, and “Difficulties in work or schoolwork”, when the item exceeded the lower limit of “small effect size” ( η 2 > 0.010), multiple comparisons using Scheffe’s method were conducted. These indicated that there were significant differences in all combinations between the three AUDIT groups in “Altruistic preventive behaviors of COVID-19”, “Deterioration of relationship with familiar people”

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Int. J. Environ. Res. Public Health 2021 , 18 , 13318 7 of 13 and “Difficulties in work or schoolwork”. In other variables that exceeded the lower limit of “small effect size”, the potential alcoholism group showed a significantly higher score than the no problem and hazardous user group Table 4. Comparisons of psychological index scores between three AUDIT groups Mean (SD) Group Difference Total No Problem Hazardous User Potential Alcoholism F p η 2 K 6 4.26 (5.40) 4.08 (5.29) 3.90 (4.95) 6.83 (6.49) 103.36 <0.001 *1 0.018 PHQ-9 4.28 (5.72) 4.05 (5.53) 3.93 (5.31) 7.36 (7.39) 132.54 <0.001 *1 0.023 GAD-7 3.19 (4.62) 3.01 (4.48) 2.89 (4.16) 5.64 (5.97) 128.23 <0.001 *1 0.022 UCLA-LS 3 24.05 (5.85) 24.02 (5.92) 23.33 (5.57) 25.40 (5.11) 31.70 <0.001 *2 0.006 LSNS-6 9.57 (6.11) 9.43 (6.03) 10.51 (6.32) 9.66 (6.50) 16.82 <0.001 *3 0.003 η 2 : 0.010~ small; 0.060 medium; 0.140~ large. SD: standard deviation. No Problem: AUDIT score < 8. Hazardous User: AUDIT score = 8~14 Potential Alcoholism: AUDIT score ≥ 15. AUDIT: Alcohol Use Disorders Identification Test. K 6: Kessler Psychological Distress Scale-6 PHQ-9: Patient Health Questionnaire-9. GAD-7: Generalized Anxiety Disorder-7. UCLA-LS 3: UCLA Loneliness Scale Version 3. LSNS-6: the abbreviated Lubben Social Network Scale. *1 Significant difference between the no problem group and the potential alcoholism group and between the hazardous user group and the potential alcoholism group in multiple comparison analysis. *2 Significant differences between all groups in multiple comparison analyses. *3 Significant difference between the no problem group and the hazardous user group and between the hazardous user group and the potential alcoholism group in multiple comparison analysis Table 5. Comparisons of COVID-19 related variables between three AUDIT groups Mean (SD) Group Difference Total No Problem Hazardous User Potential Alcoholism F p η 2 Exercise 3.67 (1.89) 3.62 (1.90) 3.93 (1.88) 3.85 (1.84) 18.64 <0.001 *1 0.003 Healthy eating habits 4.13 (1.62) 4.15 (1.62) 4.15 (1.60) 3.93 (1.59) 6.86 0.001 *2 0.001 Healthy sleep habits 4.64 (1.74) 4.67 (1.74) 4.69 (1.69) 4.18 (1.68) 31.76 <0.001 *2 0.006 Favorite activity 3.65 (1.69) 3.63 (1.70) 3.81 (1.69) 3.67 (1.61) 6.80 0.001 *3 0.001 Offline interaction with familiar people 3.36 (1.79) 3.34 (1.80) 3.43 (1.78) 3.50 (1.67) 2.87 0.057 0.001 Online interaction with familiar people 2.66 (1.76) 2.61 (1.75) 2.73 (1.74) 3.08 (1.76) 27.78 <0.001 *2 0.005 Altruistic preventive behaviors of COVID-19 5.41 (1.70) 5.47 (1.69) 5.29 (1.72) 4.82 (1.77) 59.05 <0.001 *4 0.010 Optimism 4.15 (1.56) 4.16 (1.57) 4.28 (1.47) 3.88 (1.58) 16.65 <0.001 *4 0.003 Deterioration of household economy 3.49 (1.73) 3.45 (1.73) 3.49 (1.71) 3.90 (1.75) 25.74 <0.001 *2 0.004 Deterioration of relationship with familiar people 2.64 (1.58) 2.58 (1.56) 2.72 (1.60) 3.26 (1.66) 72.68 <0.001 *4 0.013 Frustration 3.23 (1.73) 3.19 (1.73) 3.21 (1.67) 3.71 (1.72) 35.56 <0.001 *2 0.006 COVID-19-related anxiety 3.47 (1.68) 3.45 (1.68) 3.41 (1.63) 3.72 (1.70) 10.26 <0.001 *2 0.002 COVID-19-related sleeplessness 2.47 (1.52) 2.41 (1.50) 2.46 (1.49) 3.11 (1.69) 79.99 <0.001 *2 0.014 Difficulties owing to the lack of daily necessities 2.57 (1.57) 2.50 (1.55) 2.60 (1.54) 3.23 (1.71) 82.58 <0.001 *2 0.014 Difficulties in work or schoolwork 2.86 (1.73) 2.78 (1.71) 2.96 (1.75) 3.50 (1.78) 67.71 <0.001 *4 0.012 η 2 : 0.010~ small; 0.060 medium; 0.140~ large. SD: standard deviation. No Problem: AUDIT score < 8. Hazardous User: AUDIT score = 8~14 Potential Alcoholism: AUDIT score ≥ 15. AUDIT: Alcohol Use Disorders Identification Test. COVID-19: Coronavirus disease 2019 *1 Significant difference between the no problem and hazardous user groups and between the no problem and potential alcoholism groups in the multiple comparison group. *2 Significant difference between the no problem and the potential alcoholism group and between the hazardous user and potential alcoholism groups in multiple comparison analysis. *3 Significant difference between the no problem and hazardous user groups in the multiple comparison analysis. *4 Significant differences between all groups in multiple comparison analyses 3.4. Psychosocial Factors Relating to Hazardous Alcohol Use and Potential Alcoholism In results of the MANCOVA for psychological index scores and COVID-19 related variables across the three AUDIT groups adjusting for sex, age group, job classification, marital status, presence of a child, and annual household income, the Box’s M value of

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Int. J. Environ. Res. Public Health 2021 , 18 , 13318 8 of 13 1475.14 was associated with a p -value of <0.001, indicating that the covariance matrices between the groups were not assumed to be equal Table 6 shows the results of the final multinomial logistic regression analysis examining psychosocial factors relating to hazardous alcohol use and potential alcoholism. No multicollinearity problems were found among the independent variables (all variance inflation factors <4.60). The variables that significantly related to the presence of hazardous alcohol use or the presence of potential alcoholism included male sex, high annual household income, higher age, higher LSNS-6 score, exercise, healthy eating habits, altruistic preventive behaviors of COVID-19, and difficulties in work or schoolwork. Additionally, the variables that significantly related to the presence of potential alcoholism also included higher GAD-7 and PHQ-9 scores, healthy sleeping habits, online interaction with familiar people, deterioration of relationships with familiar people, lower COVID-19-related anxiety, and COVID-19-related sleeplessness Table 6. Results of multinomial logistic regression analysis Hazardous Use Potential Alcoholism Independent Variables OR (95% CI) p OR (95% CI) p Sex (ref: female) Male 2.38 (2.00–2.84) <0.001 2.29 (1.85–2.84) <0.001 Occupation (ref: other) Employed 1.14 (0.75–1.73) 0.545 1.39 (0.81–2.39) 0.231 Homemaker 0.89 (0.55–1.45) 0.642 0.80 (0.42–1.53) 0.500 Student 1.52 (0.57–4.06) 0.402 1.52 (0.45–5.09) 0.498 Unemployed 0.91 (0.58–1.45) 0.699 0.82 (0.45–1.52) 0.534 Annual household income (ref: ≥ 8.0 million) 6.0–7.9 million 0.74 (0.61–0.90) 0.003 0.95 (0.75–1.20) 0.653 4.0–5.9 million 0.88 (0.73–1.05) 0.154 0.78 (0.62–0.98) 0.030 2.0–3.9 million 0.74 (0.61–0.91) 0.003 0.61 (0.47–0.79) <0.001 <2.0 million 0.61 (0.44–0.84) 0.003 0.71 (0.50–1.01) 0.055 Age 1.01 (1.00–1.02) 0.004 1.02 (1.01–1.03) <0.001 PHQ-9 1.02 (1.00–1.04) 0.101 1.05 (1.02–1.07) <0.001 GAD-7 1.00 (0.97–1.03) 0.866 1.05 (1.02–1.09) <0.001 UCLA 0.99 (0.97–1.00) 0.089 1.01 (0.99–1.03) 0.200 LSNS-6 1.03 (1.02–1.05) <0.001 1.04 (1.02–1.06) <0.001 Exercise 1.08 (1.03–1.13) 0.001 1.13 (1.06–1.20) <0.001 Healthy eating habits 0.94 (0.89–1.00) 0.038 0.88 (0.82–0.95) <0.001 Healthy sleep habits 1.00 (0.95–1.05) 0.946 0.93 (0.88–0.99) 0.018 Online interaction with familiar people 1.00 (0.95–1.04) 0.879 1.11 (1.05–1.18) <0.001 Altruistic preventive behaviors of COVID-19 0.94 (0.90–0.99) 0.010 0.86 (0.81–0.91) <0.001 Deterioration of relationship with familiar people 1.06 (1.00–1.12) 0.055 1.09 (1.01–1.16) 0.018 COVID-19-related anxiety 1.02 (0.96–1.07) 0.597 0.91 (0.84–0.98) 0.012 COVID-19-related sleeplessness 0.95 (0.89–1.01) 0.090 1.10 (1.02–1.19) 0.015 Difficulties in work or schoolwork 1.05 (1.00–1.11) 0.040 1.09 (1.02–1.16) 0.010 Note R 2 = 0.095 (Cox–Snell), and 0.133 (Nagelkerke). Model χ 2 (46) = 898.94, p < 0.001. No Problem: AUDIT score < 8. Hazardous Use: AUDIT score = 8 − 14. Potential Alcoholism: AUDIT score 15. COVID-19: Coronavirus disease 2019. PHQ-9: Patient Health Questionnaire-9. GAD-7: Generalized Anxiety Disorder-7. UCLA-LS 3: UCLA Loneliness Scale Version 3. LSNS-6: the abbreviated Lubben Social Network Scale 4. Discussion Our study indicated the prevalence of potential alcoholism (AUDIT score ≥ 15) and hazardous alcohol use (AUDIT score = 8–14) in the Japanese population during the COVID- 19 pandemic. The prevalence of potential alcoholism (men: 10.3%; women: 4.0%) and hazardous alcohol use (men: 14.7%; women: 6.4%) were higher than those found previously in Japan before the pandemic in 2018 (potential alcoholism: 5.2% for men and 0.7% for women; hazardous alcohol use: 16.2% for men and 3.8% for women) [ 25 ]. Even though the number of men who engage in problematic drinking has not increased, the number of cases that develop into addiction may have increased. Moreover, depression and anxiety in

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Int. J. Environ. Res. Public Health 2021 , 18 , 13318 9 of 13 women participants in this study were relatively higher than those in men, as well as when compared to the results found in many previous studies. This suggests the significance of examining whether women could be more mentally vulnerable to developing hazardous alcohol use or alcoholism in response to the prolonged stressful situation of the COVID-19 pandemic than men. Additionally, differences in the liver and muscle size and gastric emptying rate between men and women make women more susceptible to higher blood alcohol levels [ 49 ], and they may be more biologically vulnerable to alcohol-induced brain damage [ 50 , 51 ] and cirrhosis [ 52 ]. Although the prevalence of alcohol-related problems among men is a major problem during the COVID-19 pandemic, this study shows that it may be an important issue for women as well. Moreover, a previous study [ 53 ] suggested that the cut-off points of the AUDIT for effective detection of hazardous drinking in women need to be lowered from the originally recommended value of 8, and thus, there could be more women with hazardous alcohol use during the pandemic The potential alcoholism group scored significantly higher than the other groups on several psychological measures, including psychological distress, depression, and anxiety, while the hazardous user group scored the lowest. The results of multinomial regression analysis showed that higher anxiety and depression related to the presence of potential alcoholism, but not of hazardous alcohol use. These results suggest that it is not necessarily true that the seriousness of the drinking problem does not directly correlate to the seriousness of the psychological problem. Individuals with hazardous alcohol use should receive special notice as their mental problems may be less pronounced; therefore, they may not seek medical attention. In addition, the COVID-19 pandemic is stressful for almost all people, as psychological distress and depression scores in the participants outside of the potential alcoholism group were also higher than the situation before the pandemic [ 54 , 55 ]. Regarding loneliness and social network, while the differences between groups were not prominent considering the ANOVA results, the multinomial regression analysis showed that increased social network size related to the presence of hazardous alcohol use and potential alcoholism The LSNS-6 does not provide information about the quality of relationships, and thus, if they have poor interpersonal relationships with many people in their social networks, the resulting deterioration in their mental health may affect alcohol use. This speculation needs to be tested in future studies. However, loneliness and social network in our participants were also generally worse than in previous studies before the pandemic [ 39 , 40 ]. This suggests that those with addictive drinking habits may be at an even greater risk of worsening symptoms of alcoholism during the pandemic and that there might be an increased risk of developing alcoholism in non-addictive alcohol users with psychological vulnerability Regarding the results of the ANOVA for COVID-19-related variables, decreased altruistic preventive behaviors of COVID-19, deterioration of relationships with familiar people, COVID-19-related sleeplessness, difficulties due to the lack of daily necessities, and difficulties in work or schoolwork were prominent in the potential alcoholism group. Multinomial logistic regression analysis showed that these variables, except difficulties due to the lack of daily necessities, exercise, decreased healthy eating habits, decreased healthy sleeping habits, online interaction with familiar people, and decreased COVID-19-related anxiety related to the presence of potential alcoholism. Various difficulties in daily life due to the COVID-19 pandemic associated with the presence of potential alcoholism and individuals with it may require support in these issues. It was suggested that even if online interactions with familiar people increase, poor relationships with them may lead to worsening drinking behavior. The interpersonal relationship was previously reported to be a serious problem during the COVID-19 pandemic [ 56 ]. While drinking behavior is promoted as a way to cope with such interpersonal stress, it has also been reported that drinking as a way to cope with stress can increase interpersonal stress [ 57 ]. It was also suggested that not only relationship problems, but also COVID-19-related sleep problems could be targets for interventions for potential alcoholism. Although poor eating and sleep habits were also risk factors for potential alcoholism, increased exercise related to its presence. It is not difficult to imagine that a poor lifestyle may lead to potential

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Int. J. Environ. Res. Public Health 2021 , 18 , 13318 10 of 13 alcoholism, but the background of the results regarding exercise is difficult to interpret and requires further examination. While difficulties due to the lack of daily necessities and difficulties in work in people with potential alcoholism were prominent, and the latter related to the presence of potential alcoholism, they did not have a higher prevalence in the low-income group than in other groups, suggesting that these problems were not due to economic reasons, and a detailed analysis of the causes of these problems is needed in the future. The decrease in altruistic preventive behaviors and the disturbance of sleep due to concern about COVID-19 infection in people with potential alcoholism appear to be contradictory, but the latter might be caused by a decrease in offline interaction with others due to deteriorating relationships, and they may have fewer opportunities for altruistic preventive behaviors. The result that decreased COVID-19-related anxiety is associated with the presence of potential alcoholism is difficult to interpret. The item “I felt nervous or anxious when I watched the news about coronavirus disease 2019” is limited to situations where people are watching the news about COVID-19, and thus, people with potential alcoholism may not have access to (or avoid) such news. Regarding hazardous alcohol use, exercise, decreased healthy eating habits, altruistic preventive behaviors of COVID-19, and difficulties in work or schoolwork were risk factors. The addition of these factors to various psychosocial factors found only in potential alcoholism could exacerbate the problem of drinking. The same is true for psychological variables, but effect size is generally lower in the comparison between the three AUDIT groups for the COVID-19-related variables (see Tables 4 and 5 ). This may be due in part to the strong influence of demographic characteristics on the dependent variable, which increased the variance of values in each group. Analysis adjusting demographic characteristics may be essential to explore the relationship between alcohol use and psychological indexes or items regarding lifestyle, coping behavior, and stressors related to mild lockdown conditions (i.e., multinomial regression analysis or MANCOVA, which were conducted in this study) This study had several limitations. First, we did not collect data before the COVID-19 pandemic, and thus, we could not assess changes in alcohol use during the COVID-19 pandemic. Second, the data for this study were collected through an online survey and random sampling could not be conducted, so the representativeness of the sample could not be guaranteed; the sample we collected could not be matched to the proportions of each age group and gender group in each region. Third, because the study participants were registered with a survey company, they were likely to be more accustomed to completing surveys than individuals who were not registered, and the motivation to cooperate with the survey may differ between our participants and the population not registered with the survey company. Fourth, the items to investigate lifestyle, coping behavior, and stressors related to mild lockdown were developed in this study based on previous research Therefore, the reliability and validity of these items should be examined in future studies 5. Conclusions This study investigated alcohol use during the prolonged COVID-19 pandemic and its related psychosocial and demographic characteristics in the Japanese population. We found that the prevalence of potential alcoholism during the COVID-19 pandemic in our study was higher than that reported in previous studies, and this trend was particularly pronounced among women. The presence of potential alcoholism was related with by a deteriorated psychological status, particularly depression and anxiety. Psychological variables in our participants deteriorated in comparison with previous results before the pandemic, and thus, there could be an increased risk of worsening or developing alcoholism during the pandemic. Various difficulties in daily life due to the pandemic also related to the presence of potential alcoholism, and individuals with it may require support in these issues. In the future, intervention methods and systems should be developed to provide optimal assistance to people with psychological problems who are vulnerable to alcohol-related problems during the COVID-19 pandemic while conducting further long-term follow-up studies.

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Int. J. Environ. Res. Public Health 2021 , 18 , 13318 11 of 13 Author Contributions: Conceived and designed the study: N.S. (Nagisa Sugaya), T.Y., N.S. (Naho Suzuki) and C.U. Performed the study: N.S. (Nagisa Sugaya), T.Y., N.S. (Naho Suzuki) and C.U Analyzed the data: N.S. (Nagisa Sugaya). Wrote the paper, contributed to and have approved the final manuscript: N.S. (Nagisa Sugaya), T.Y., N.S. (Naho Suzuki) and C.U. All authors have read and agreed to the published version of the manuscript Funding: This work was supported by JSPS KAKENHI (grant number 18 K 13323, 20 K 10883, and 21 H 00949), FY 2021 Project for Creative Research of the Faculty of Integrated Science, Tokushima University, FY 2021 Discretionary Funds for Research Director of Tokushima University, JPA Research Grant for COVID-19 Pandemic, and Research-Aid, Meiji Yasuda Mental Health Foundation. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript Institutional Review Board Statement: The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Research Ethics Committee of the Graduate School of Social and Industrial Science and Technology, Tokushima University (no. 212) Informed Consent Statement: Informed consent was obtained from all subjects involved in the study Data Availability Statement: The data presented in this study are available on request from the corresponding author Conflicts of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest References 1 Liu, X.; Zhu, M.; Zhang, R.; Zhang, J.; Zhang, C.; Liu, P.; Feng, Z.; Chen, Z. Public Mental Health Problems during COVID-19 Pandemic: A Large-Scale Meta-Analysis of the Evidence Transl. Psychiatry 2021 , 11 , 384. [ CrossRef ] 2 Prati, G.; Mancini, A.D. The Psychological Impact of COVID-19 Pandemic Lockdowns: A Review and Meta-Analysis of Longitudinal Studies and Natural Experiments Psychol. Med 2021 , 51 , 201–211. [ CrossRef ] [ PubMed ] 3 Avena, N.M.; Simkus, J.; Lewandowski, A.; Gold, M.S.; Potenza, M.N. Substance Use Disorders and Behavioral Addictions during the COVID-19 Pandemic and COVID-19-Related Restrictions Front. Psychiatry 2021 , 12 , 653674. [ CrossRef ] [ PubMed ] 4 Bakaloudi, D.R.; Jeyakumar, D.T.; Jayawardena, R.; Chourdakis, M. The Impact of COVID-19 Lockdown on Snacking Habits, Fast-Food and Alcohol Consumption: A Systematic Review of the Evidence Clin. Nutr 2021 , in press . [ CrossRef ] 5 Hermosillo-de-la-Torre, A.E.; Arteaga-de-Luna, S.M.; Acevedo-Rojas, D.L.; Ju á rez-Loya, A.; Jim é nez-Tapia, J.A.; Pedroza-Cabrera, F.J.; Gonz á lez-Forteza, C.; Cano, M.; Wagner, F.A. Psychosocial Correlates of Suicidal Behavior among Adolescents under Confinement due to the COVID-19 Pandemic in Aguascalientes, Mexico: A Cross-Sectional Population Survey Int. J. Environ Res. Public Health 2021 , 18 , 4977. [ CrossRef ] 6 Sato, K.; Kobayashi, S.; Yamaguchi, M.; Sakata, R.; Sasaki, Y.; Murayama, C.; Kondo, N. Working from Home and Dietary Changes during the COVID-19 Pandemic: A Longitudinal Study of Health App (Calo Mama) Users Appetite 2021 , 165 , 105323. [ CrossRef ] 7 Singh, B.; Jain, S.; Rastogi, A. Effects of Nationwide COVID-19 Lockdown on Lifestyle and Diet: An Indian Survey J. Fam. Med Prim. Care 2021 , 10 , 1246–1250. [ CrossRef ] 8 Schimmel, J.; Vargas-Torres, C.; Genes, N.; Probst, M.A.; Manini, A.F. Changes in Alcohol-Related Hospital Visits during COVID-19 in New York City Addiction 2021 , 116 , 3525–3530. [ CrossRef ] 9 Winkler, P.; Mohrova, Z.; Mlada, K.; Kuklova, M.; Kagstrom, A.; Mohr, P.; Formanek, T. Prevalence of Current Mental Disorders before and during the Second Wave of COVID-19 Pandemic: An Analysis of Repeated Nationwide Cross-Sectional Surveys J. Psychiatr. Res 2021 , 139 , 167–171. [ CrossRef ] 10 Eastman, M.R.; Finlay, J.M.; Kobayashi, L.C. Alcohol Use and Mental Health among Older American Adults during the Early Months of the COVID-19 Pandemic Int. J. Environ. Res. Public Health 2021 , 18 , 4222. [ CrossRef ] [ PubMed ] 11 Papp, L.M.; Kouros, C.D. Effect of COVID-19 Disruptions on Young Adults’ Affect and Substance Use in Daily Life Psychol Addict. Behav 2021 , 35 , 391–401. [ CrossRef ] [ PubMed ] 12 Rossow, I.; Bye, E.K.; Moan, I.S.; Kilian, C.; Bramness, J.G. Changes in Alcohol Consumption during the COVID-19 Pandemic-Small Change in Total Consumption, but Increase in Proportion of Heavy Drinkers Int. J. Environ. Res. Public Health 2021 , 18 , 4231 [ CrossRef ] 13 Zhang, X.; Oluyomi, A.; Woodard, L.; Raza, S.A.; Adel Fahmideh, M.; El-Mubasher, O.; Byun, J.; Han, Y.; Amos, C.I.; Badr, H. Individual-Level Determinants of Lifestyle Behavioral Changes during COVID-19 Lockdown in the United States: Results of an Online Survey Int. J. Environ. Res. Public Health 2021 , 18 , 4364. [ CrossRef ] 14 Rossow, I.; Bartak, M.; Bloomfield, K.; Braddick, F.; Bye, E.K.; Kilian, C.; L ó pez-Pelayo, H.; Mäkelä, P.; Moan, I.S.; Moskalewicz, J.; et al. Changes in Alcohol Consumption during the COVID-19 Pandemic Are Dependent on Initial Consumption Level: Findings from Eight European Countries Int. J. Environ. Res. Public Health 2021 , 18 , 10547. [ CrossRef ]

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Int. J. Environ. Res. Public Health 2021 , 18 , 13318 12 of 13 15 Weerakoon, S.M.; Jetelina, K.K.; Knell, G.; Messiah, S.E. COVID-19 Related Employment Change Is Associated with Increased Alcohol Consumption during the Pandemic Am. J. Drug Alcohol Abuse 2021 , 47 , 730–736. [ CrossRef ] [ PubMed ] 16 Orlandi, M.; Rosselli, M.; Pellegrino, A.; Boddi, M.; Stefani, L.; Toncelli, L.; Modesti, P.A. Gender Differences in the Impact on Physical Activity and Lifestyle in Italy during the Lockdown, Due to the Pandemic Nutr. Metab. Cardiovasc. Dis 2021 , 31 , 2173–2180. [ CrossRef ] [ PubMed ] 17 Pabst, A.; Bollen, Z.; Creupelandt, C.; Fontesse, S.; Orban, T.; de Duve, M.; Pinon, N.; Maurage, P. Alcohol Consumption Changes During the First COVID-19 Lockdown: An Online Population Survey in a Convenience Sample of French-Speaking Belgian Residents Psychiatry Res 2021 , 300 , 113938. [ CrossRef ] 18 Schecke, H.; Fink, M.; Bäuerle, A.; Skoda, E.; 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. [ CrossRef ] 19 Koopmann, A.; Georgiadou, E.; Reinhard, I.; Müller, A.; Lemenager, T.; Kiefer, F.; Hillemacher, T. The Effects of the Lockdown during the COVID-19 Pandemic on Alcohol and Tobacco Consumption Behavior in Germany Eur. Addict. Res 2021 , 27 , 242–256 [ CrossRef ] 20 Alpers, S.E.; Skogen, J.C.; Mæland, S.; Pallesen, S.; Rabben, Å.K.; Lunde, L.; Fadnes, L.T. Alcohol Consumption during a Pandemic Lockdown Period and Change in Alcohol Consumption Related to Worries and Pandemic Measures Int. J. Environ. Res. Public Health 2021 , 18 , 1220. [ CrossRef ] [ PubMed ] 21 Shield, K.; Manthey, J.; Rylett, M.; Probst, C.; Wettlaufer, A.; Parry, C.D.; 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 , e 51–e 61 [ CrossRef ] 22 Yamamoto, T.; Uchiumi, C.; Suzuki, N.; Yoshimoto, J.; Murillo-Rodriguez, E. The Psychological Impact of “Mild Lockdown” in Japan during the COVID-19 Pandemic: A Nationwide Survey under a Declared State of Emergency Int. J. Environ. Res. Public Health 2020 , 17 , 9382. [ CrossRef ] 23 Huo, Y.; Lim, C.; Chiu, V.; Tachimori, H.; Leung, J. Psychological distress and the experience of self-restrained lifestyle through COVID-19 in Japan—public insights from #Corona-utsu on Twitter. In Proceedings of the 3 rd International Electronic Conference on Environmental Research and Public Health—Public Health Issues in the Context of the COVID-19 Pandemic, Online, 11–25 January 2021. [ CrossRef ] 24 Yamamoto, T.; Uchiumi, C.; Suzuki, N.; Sugaya, N.; Rodriguez, E.M.; Machado, S.; Imperatori, C.; Budde, H. The Influence of Repeated Mild Lockdown on Mental and Physical Health during the COVID-19 Pandemic: A Large-Scale Longitudinal Study in Japan Preprint at MedRxiv 2021 . [ CrossRef ] 25 Kinjo, A.; Osaki, Y.; Kuwabara, Y. Josei No Arukoru Shiyo to Koshueiseishisaku No Genjo J. Jpn. Soc. Alcohol-Relat. Probl 2019 , 21 , 1–5 26 Hiro, H.; Shima, S. Availability of the Alcohol Use Disorders Identification Test (AUDIT) for a Complete Health Examination in Japan Nihon Arukoru Yakubutsu Igakkai Zasshi 1996 , 31 , 437–450 27 World Health Organization AUDIT: The Alcohol Use Disorders Identification Test: Guidelines for Use in Primary Healthcare , 2 nd ed.; World Health Organization: Geneva, Switzerland, 2001 28 Japanese Ministry of Health, Labour and Welfare Standard Health Checkups and Health Guidance Program ; Japanese Ministry of Health: Tokyo, Japan, 2018. Available online: https://www.mhlw.go.jp/file/06-Seisakujouhou-10900000-Kenkoukyoku/00_3 .pdf (accessed on 11 October 2021) 29 Osaki, Y.; Kinjo, A.; Higuchi, S.; Matsumoto, H.; Yuzuriha, T.; Horie, Y.; Kimura, M.; Kanda, H.; Yoshimoto, H. Prevalence and Trends in Alcohol Dependence and Alcohol Use Disorders in Japanese Adults; Results from Periodical Nationwide Surveys Alcohol Alcohol 2016 , 51 , 465–473. [ CrossRef ] [ PubMed ] 30 Furukawa, T.A.; Kessler, R.C.; Slade, T.; Andrews, G. The Performance of the K 6 and K 10 Screening Scales for Psychological Distress in the Australian National Survey of Mental Health and Well-Being Psychol. Med 2003 , 33 , 357–362. [ CrossRef ] 31 Kessler, R.C.; Barker, P.R.; Colpe, L.J.; Epstein, J.F.; Gfroerer, J.C.; Hiripi, E.; Howes, M.J.; Normand, S.L.; Manderscheid, R.W.; Walters, E.E.; et al. Screening for Serious Mental Illness in the General Population Arch. Gen. Psychiatry 2003 , 60 , 184–189 [ CrossRef ] 32 Veldhuizen, S.; Cairney, J.; Kurdyak, P.; Streiner, D.L. The Sensitivity of the K 6 as a Screen for Any Disorder in Community Mental Health Surveys: A Cautionary Note Can. J. Psychiatry 2007 , 52 , 256–259. [ CrossRef ] 33 Prochaska, J.J.; Sung, H.Y.; Max, W.; Shi, Y.; Ong, M. Validity Study of the K 6 Scale as a Measure of Moderate Mental Distress Based on Mental Health Treatment Need and Utilization Int. J. Methods Psychiatr. Res 2012 , 21 , 88–97. [ CrossRef ] 34 Kessler, R.C.; Galea, S.; Gruber, M.J.; Sampson, N.A.; Ursano, R.J.; Wessely, S. Trends in Mental Illness and Suicidality after Hurricane Katrina Mol. Psychiatry 2008 , 13 , 374–384. [ CrossRef ] 35 Muramatsu, K.; Miyaoka, H.; Kamijima, K.; Muramatsu, Y.; Tanaka, Y.; Hosaka, M.; Miwa, Y.; Fuse, K.; Yoshimine, F.; Mashima, I.; et al. Performance of the Japanese Version of the Patient Health Questionnaire-9 (J-PHQ-9) for Depression in Primary Care Gen Hosp. Psychiatry 2018 , 52 , 64–69. [ CrossRef ] 36 Kroenke, K.; Spitzer, R.L.; Williams, J.B. The PHQ-9: Validity of a Brief Depression Severity Measure J. Gen. Intern. Med 2001 , 16 , 606–613. [ CrossRef ] [ PubMed ]

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Int. J. Environ. Res. Public Health 2021 , 18 , 13318 13 of 13 37 Muramatsu, K.; Miyaoka, H.; Ueshima, K.; Muramatsu, Y.; Fuse, K.; Yoshimine, F.; Hosaka, M.; Kutsumi, R.; Majima, I.; Katagiri, A.; et al. Validation and Utility of a Japanese Version of the GAD-7 Jpn. J. Psychosom. Med 2010 , 50 , 166 38 Spitzer, R.L.; Kroenke, K.; Williams, J.B.; Löwe, B. A Brief Measure for Assessing Generalized Anxiety Disorder: The GAD-7 Arch. Intern. Med 2006 , 166 , 1092–1097. [ CrossRef ] 39 Arimoto, A.; Tadaka, E. Reliability and Validity of Japanese Versions of the UCLA Loneliness Scale Version 3 for Use among Mothers with Infants and Toddlers: A Cross-Sectional Study BMC. Womens Health 2019 , 19 , 105. [ CrossRef ] 40 Russell, D.W. UCLA Loneliness Scale (Version 3): Reliability, Validity, and Factor Structure J. Pers. Assess 1996 , 66 , 20–40 [ CrossRef ] 41 Kurimoto, A.; Awata, S.; Ohkubo, T.; Tsubota-Utsugi, M.; Asayama, K.; Takahashi, K.; Suenaga, K.; Satoh, H.; Imai, Y. Reliability and Validity of the Japanese Version of the Abbreviated Lubben Social Network Scale Nihon Ronen Igakkai Zasshi 2011 , 48 , 149–157 [ CrossRef ] [ PubMed ] 42 Lubben, J.E. Assessing Social Networks among Elderly Populations Fam. Community Health 1988 , 11 , 42–52. [ CrossRef ] 43 Lubben, J.E.; Blozik, E.; Gillmann, G.; Iliffe, S.; von Renteln Kruse, W.R.; Beck, J.C.; Stuck, A.E. Performance of an Abbreviated Version of the Lubben Social Network Scale among Three European Community-Dwelling Older Adult Populations Gerontologist 2006 , 46 , 503–513. [ CrossRef ] [ PubMed ] 44 Ahorsu, D.K.; Lin, C.Y.; Imani, V.; Saffari, M.; Griffiths, M.D.; Pakpour, A.H. The Fear of COVID-19 Scale: Development and Initial Validation Int. J. Ment. Health Addict 2020 , 27 , 1–9. [ CrossRef ] 45 Brooks, S.K.; Webster, R.K.; Smith, L.E.; Woodland, L.; Wessely, S.; Greenberg, N.; Rubin, G.J. The Psychological Impact of Quarantine and How to Reduce It: Rapid Review of the Evidence Lancet 2020 , 395 , 912–920. [ CrossRef ] 46 Kisely, S.; Warren, N.; McMahon, L.; Dalais, C.; Henry, I.; Siskind, D. Occurrence, Prevention, and Management of the Psychological Effects of Emerging Virus Outbreaks on Healthcare Workers: A Rapid Review and Meta-Analysis BMJ 2020 , 369 , m 1642 [ CrossRef ] 47 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. [ CrossRef ] [ PubMed ] 48 Tang, W.; Hu, T.; Hu, B.; Jin, C.; Wang, G.; Xie, C.; Chen, S.; Xu, J. Prevalence and Correlates of PTSD and Depressive Symptoms One Month after the Outbreak of the COVID-19 Epidemic in a Sample of Home-Quarantined Chinese University Students J. Affect. Disord 2020 , 274 , 1–7. [ CrossRef ] [ PubMed ] 49 Sekime, A.; Horikoshi, M.; Funakoshi, A.; Miyasaka, K. Sex Difference in the Effects of Alcohol on Gastric Emptying in Healthy Volunteers: A Study Using the 13 C Breath Test Biomed. Res 2013 , 34 , 275–280. [ CrossRef ] 50 Hommer, D.; Momenan, R.; Kaiser, E.; Rawlings, R. Evidence for a Gender-Related Effect of Alcoholism on Brain Volumes Am. J Psychiatry 2001 , 158 , 198–204. [ CrossRef ] 51 Mann, K.; Ackermann, K.; Croissant, B.; Mundle, G.; Nakovics, H.; Diehl, A. Neuroimaging of Gender Differences in Alcohol Dependence: Are Women More Vulnerable? Alcohol. Clin. Exp. Res 2005 , 29 , 896–901. [ CrossRef ] [ PubMed ] 52 Becker, U.; Deis, A.; Sørensen, T.I.; Grønbaek, M.; Borch-Johnsen, K.; Müller, C.F.; Schnohr, P.; Jensen, G. Prediction of Risk of Liver Disease by Alcohol Intake, Sex, and Age: A Prospective Population Study Hepatology 1996 , 23 , 1025–1029. [ CrossRef ] 53 Reinert, D.F.; Allen, J.P. The alcohol use disorders identification test: An update of research findings Alcohol. Clin. Exp. Res 2007 , 31 , 185–199. [ CrossRef ] 54 Kato, T.; Baba, K.; Guo, W.; Chen, Y.; Nosaka, T. Impact of Bipolar Disorder on Health-Related Quality of Life and Work Productivity: Estimates from the National Health and Wellness Survey in Japan J. Affect. Disord 2021 , 295 , 203–214. [ CrossRef ] [ PubMed ] 55 Oshio, T.; Kan, M. Does Social Participation Accelerate Psychological Adaptation to Health Shocks? Evidence from a National Longitudinal Survey in Japan Qual. Life Res 2019 , 28 , 2125–2133. [ CrossRef ] [ PubMed ] 56 Evandrou, M.; Falkingham, J.; Qin, M.; Vlachantoni, A. Changing Living Arrangements and Stress during Covid-19 Lockdown: Evidence from Four Birth Cohorts in the UK SSM-Popul. Health 2021 , 13 , 100761. [ CrossRef ] [ PubMed ] 57 Armeli, S.; Litt, M.; Tennen, H. A Daily Level Analysis of Drinking to Cope Motivation and Interpersonal Stress Addict. Behav 2021 , 122 , 107030. [ CrossRef ] [ PubMed ]