International Journal ofEnvironmental Researchand Public Health

ArticleLoneliness and Increased Hazardous Alcohol Use: Data froma Nationwide Internet Survey with 1-Year Follow-Up
Mami Wakabayashi 1, * , Yoshifumi Sugiyama 2 , Midori Takada 3 , Aya Kinjo 4 , Hiroyasu Iso 1
and Takahiro Tabuchi 5,6
1

2

3

4

5
6

*

Citation: Wakabayashi, M.;
Sugiyama, Y.; Takada, M.; Kinjo, A.;
Iso, H.; Tabuchi, T. Loneliness andIncreased Hazardous Alcohol Use:
Data from a Nationwide Internet
Survey with 1-Year Follow-Up. Int. J.
Environ. Res. Public Health 2022, 19,
12086. https://doi.org/10.3390/
ijerph191912086
Academic Editors: Mellissa Withers,
Jill Murphy, Ishtar Govia andMatias Irarrazaval

Institute for Global Health Policy Research, Bureau of International Health Cooperation, National Center
for Global Health and Medicine, 1-21-1, Toyama Shinjuku-ku, Tokyo 162-8655, Japan
Division of Clinical Epidemiology, Research Center for Medical Sciences, The Jikei University Schoolof Medicine, Tokyo 105-8461, Japan
Department of Cardiovascular Disease Prevention, Osaka Center for Cancer and Cardiovascular
Disease Prevention, Osaka 536-8588, Japan
Division of Environmental and Preventive Medicine, Department of Social Medicine, Faculty of Medicine,
Tottori University, Tottori 683-8503, Japan
Cancer Control Center, Osaka International Cancer Institute, Osaka 541-8567, JapanThe Tokyo Foundation for Policy Research, Tokyo 106-6234, Japan
Correspondence: mwakabayashi@it.ncgm.go.jp; Tel.: +81-3-6228-0562; Fax: +81-3-6228-0564

Abstract: We aimed to examine the association between loneliness and developing alcohol dependence or hazardous alcohol use. A cohort study was conducted utilizing data from a nationwide
internet survey in 2021 and 2022 in Japan. A total of 15,854 follow-up participants (55% men, witha mean age of 52.8 years) were divided based on AUDIT scores: nondrinkers (AUDIT: 0), low-risk
drinkers (AUDIT: 1–7), medium-risk drinkers (AUD: 8–14), high-risk drinkers (AUDIT: 15–19), andprobable alcohol dependence (AUDIT: 20–40). The University of California, Los Angeles Loneliness
Scale (Version 3), a short-form three-item scale, was used to assess loneliness (high loneliness score of≥6). The prevalence of high loneliness was higher in nondrinkers than that in low- and medium-risk
drinkers, i.e., 22%, 18%, and 17%, respectively, as well as in high-risk drinkers (32%) and thosewith probable alcohol dependence (43%) compared to non-high-risk drinkers (19%). After adjustingfor various factors (sociodemographic, social isolation, psychological distress, and smoking), nonhigh-risk drinkers (AUDIT: 0–14) with high loneliness were more likely to become high-or-over-risk
drinkers (AUDIT: 15–40) than those without high loneliness, with adjusted risk ratios of 1.45 (95%
confidence interval: 1.08–1.96) through multivariable binary logistic regression. Among non-high-risk
drinkers, people with high loneliness scores at baseline were associated with increased high-risk
drinking patterns with probable alcohol dependence.

Received: 31 August 2022
Accepted: 19 September 2022
Published: 24 September 2022

Keywords: alcohol use disorders identification test; hazardous alcohol use; alcohol use disorders;loneliness; COVID-19

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1. Introduction
Mental disorders are associated with poor health behaviors; mentally distressedindividuals are more likely to engage in unhealthy behaviors such as harmful alcoholuse [1]. Various studies reported that lonely people who engaged in heavy drinking weremore vulnerable to alcohol-related problems due to a lack of social support as well as
community peer pressure [2–4]. However, there is no clear evidence on whether lonelinessis likely to develop alcohol dependence or hazardous alcohol use [1,5,6]. Thus, identifying
causal correlations between loneliness and hazardous alcohol use could have high publichealth relevance.
Alcohol use is a major global concern associated with disease onset and often leads
to death [7,8]. Quarantine and social isolation during the COVID-19 pandemic haveInt. J. Environ. Res. Public Health 2022, 19, 12086. https://doi.org/10.3390/ijerph191912086

https://www.mdpi.com/journal/ijerph

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resulted in increased alcohol consumption and alcohol abuse [9–11]. The government ofJapan has implemented preventive measures, such as quarantine, gathering regulations,
reducing business hours for restaurants, and regulation of serving alcoholic beverages
at restaurants [12]. The regulations for the prevention of COVID-19 were enforced foralmost 7 months in 2021 and from January to mid-March of 2022 (as of September 2022) atprefectures under a “State of Emergency” in Japan [13]. As such, it is plausible to concurthat people have experienced loneliness throughout the pandemic [14]. This study aimed
to examine the association between loneliness and developing alcohol dependence or
hazardous alcohol use during the COVID-19 pandemic.
2. Materials and Methods
2.1. Data Source and Study Population
2.1.1. Internet Survey
We used data from the Japan Society and New Tobacco Internet Survey (JASTIS), alarge internet-based cohort study that has focused on tobacco issues since 2015 and has
expanded to various health behaviors since 2021. The JASTIS cohort profile has beenpreviously published [15]. The present study utilized two waves of longitudinal data fromFebruary 2021 (baseline, JASTIS2021) to February 2022 (JASTIS2022) and examined how
the COVID-19 pandemic affected individuals’ health behaviors in Japan. This web-based,
self-reported questionnaire survey was administrated by a large internet research agency,
Rakuten Insight, Inc., which pooled approximately 2.3 million panelists. Survey requests
were sent by the research agency to the panelists, who were each selected based on sex, age,and prefecture. The panelists who consented to participate accessed the designated website
and responded to the survey. The participants were given the option not to respond toany part of the survey or discontinue it at any point. The survey was closed when thetarget number of respondents for sex, age, and prefecture was met. The total number ofparticipants in each survey was 26,000 and 33,000 participants in 2021 and 2022, respectively.
2.1.2. Managing the Data Quality and Generating the Study Population
To ensure data quality, respondents with discrepancies or artificial/unnatural responses were excluded from the study [15]. In this regard, the following three items wereused: (1) “Please choose the second from the bottom”, (2) “choosing ‘yes’ in all questions on
alcohol and nine illegal drug uses”, and (3) “choosing ‘yes’ in all questions regarding nine
chronic diseases”. Moreover, 871 respondents who had inconsistent answers to alcoholrelated questions were excluded: respondents who answered “Never” in the question “Do
you drink alcohol?” but answered “monthly or more” in the question “How often do you
have a drink containing alcohol?”. In addition, the study participants were limited only toindividuals aged ≥20 years, the legal drinking age in Japan. Overall, the total number offollow-up participants was 15,854. The selection flow of the study population is shown in
Supplementary Figure S1.
2.2. Measures
2.2.1. Explanatory Variables
A Japanese version of the University of California, Los Angeles Loneliness Scale(Version 3), a short-form three-item scale (UCLA-LS-SF3), was used to assess loneliness.
UCLA-LS-SF3 was initially developed in English [16], and its Japanese version was previously validated and found to be reliable [17,18]. Participants were asked the following threequestions about their condition over the past 30 days: “How often do you feel that you lackcompanionship?”, “How often do you feel left out?”, and “How often do you feel isolated
from others?”. Their responses to these questions were recorded using a 5-point scale used
in JASTIS2021 (1: never, 2: rarely, 3: sometimes, 4: usually, and 5: always). We integrated
these recorded scales into a 3-point scale (1 hardly ever [never and rarely], 2 some of thetime [sometime], and 3 often [usually and always]) based on UCLA-LS-SF3. The total
score range of these three questions was 3 to 9, categorized into two groups: people with

Int. J. Environ. Res. Public Health 2022, 19, 12086

3 of 13a score of 3–5 were designated as “non-low loneliness” and people with a score of 6–9
were designated as “high loneliness” [16,19]. The Cronbach’s alpha value of the internalconsistency for the three items was 0.93.
2.2.2. Outcome Variables
Nondrinkers and current drinkers were identified by the AUDIT, which was developed by the WHO and is one of the most effective screening tools in identifying individuals
with alcohol use disorders and those involved in harmful alcohol use [20]. The AUDIT isa 10-item screening measure that assesses alcohol use during the last 12 months [21,22].
Although the AUDIT does not intend to offer a clinical diagnosis, it can indicate the presence and severity of alcohol problems or alcohol use disorders [23]. Furthermore, the
AUDIT translated into Japanese was validated to identify harmful to hazardous alcohol
use and alcohol use disorders as a screening tool [24]. Each item in the AUDIT has a scoreof 0–4 points, except items 9 and 10, which inquire about alcohol-related injury or violence,with scores of 0, 2, or 4 points (the details of each question are shown in Supplementary
Table S1). The total scores range from 0 to 40 points. According to the National Health Guidance and Brief Intervention to Support Alcohol Reduction in Japan based on a validation
study, an AUDIT score of 0–7 is considered normal, people with a score 8–14 are advised toreduce hazardous drinking, and people with a score ≥ 15 are recommended to see a specialist for further diagnostic evaluation of alcohol dependence [25]. On the other hand, the
AUDIT original guideline proposed by the WHO interprets the AUDIT scores as follows:
people with a score of 8–15 are advised to focus on the reduction of hazardous drinking,people with a score of 16–19 are advised to receive brief counseling and be monitored continuously, and people with a score ≥ 20 clearly warrant further diagnostic evaluation foralcohol dependence [21]. Considering these two guidelines, the participants of this study
were categorized into five groups based on the total score: nondrinker (AUDIT: 0), low-risk
drinker (AUDIT: 1–7), medium-risk drinker (AUDIT: 8–14), high-risk drinker (AUDIT:
15–19), and probable alcohol dependence (AUDIT: 20–40) [21,25,26]. Participants who werecategorized as having high-risk alcohol use and probable alcohol dependence were identified as high-or-over-risk drinkers (AUDIT: 15–40) for the cutoff point in alcohol patternchanges regarding an association of the prevalence of loneliness, whereas other participants
were regarded as non-high-risk drinkers (AUDIT: 0–14), including nondrinkers.
Changes in AUDIT scores from 2021 to 2022 were categorized into four patterns asfollows: no changes from non-high-risk drinkers (0–14) to non-high-risk drinkers (0–14),
non-high-risk drinkers (0–14) to high-or-over-risk drinkers (15–40), no changes from highor-over-risk drinkers (15–40) to high-or-over-risk drinkers (15–40), and high-or-over-risk
drinkers (15–40) to non-high-risk drinkers (0–14).
2.2.3. Demographics and Potential Health Factors Related to Alcohol Use
Demographic questions inquired about the following variables: age, sex, educational
level, job, equivalent annual household income, marital status, and current living arrangements. Educational level was categorized as low (graduated from high school orlower), middle (graduated from vocational or junior college), and high (graduated fromuniversity or higher). Equivalent annual household income is the household income
divided by the square root of the number of household members. This factor is categorized as <2 million yen, 2–4 million yen, 4–6 million yen, 6–10 million yen, ≥10 million
yen, and do not know/want to answer. Jobs were categorized into regular jobs including self-employment, non-regular employee, no main income job (students, retirees, andhousework only), and unemployed. Marital status was categorized as married, single, anddivorced/widowed. The current living arrangements reported whether the participants
lived with someone or alone. Finally, potential factors related to alcohol use include current
smoker and the Kessler Psychological Distress Scale (K6: ≥13) [27].

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4 of 132.3. Statistical Analyses
Statistical analyses were performed using the Stata MP version 15 (StataCorp LLC,
College Station, TX, USA). The means and standard deviations were presented as continuous variables and proportions for categorical variables. First, we determined variationsin the means and proportions of demographics, and the potential health factors based on
AUDIT scores for each category. The difference (p for difference) between non-high-risk
drinkers and high-or-over-risk drinkers was assessed using the t-test for the mean andusing the chi-square test for the proportion. Second, multivariable binary logistic regression
was performed among non-high-risk drinkers at baseline to examine the relationship between loneliness and alcohol use changes from non-high-risk drinkers to high-or-over-risk
drinkers. Model 1 was univariable, Model 2 was adjusted for sociodemographic factors,
and Model 3 was further adjusted for marital status and living arrangement as potentialsocial isolation factors [1] and smoking. Model 4 was further adjusted for K6 as psychological distress due to strong correlations with loneliness and hazardous alcohol use under
the COVID-19 preventive measures. Finally, the adjusted risk ratios (aRR) and 95% confidence intervals (CIs) for AUDIT pattern changes were observed. All statistical tests were
two-sided, and a p value < 0.05 was considered statistically significant.
2.4. Ethical Approval
All procedures were conducted as per the ethical standards of the 1975 Helsinki
Declaration (revised in 2013). The Research Ethics Committee of the Osaka International
Cancer Institute reviewed and approved the study protocol (approval No. 1412175183). All
participants provided their informed consent before responding to the online questionnaire.
Furthermore, the internet survey agency respected the Act on Protection of Personal
Information in Japan. As an incentive, credit points (known as “E-points”), which can beused for internet shopping and cash conversion, were provided to participants.
3. Results
3.1. Participant Characteristics
Of the 15,854 follow-up participants, 52% (n = 8239) were men with a mean age of
52.8 (±15.6) (range, 20–80) years at baseline. Based on the participant characteristics, sociodemographic categories with the highest proportion of responses were a high educationlevel (48%), married (64%), living with someone (81%), having a regular job (43%), andincome level of 2–4 million (36%) (Table 1). This study also included current smokers(20%) and those with a K6 score of ≥13 (10%). The distribution of each characteristic of thefollow-up population was similar to that of participants from JASTIS2021 and JASTIS2022,
although participants who could not be followed up in 2022 were younger, more likely
females, and had a lower percentage of K6 scale score than those who were followed up(data not shown).
Table 1. Characteristics of the follow-up participants based on categories, 2021.
Drinking Categories Based on AUDIT
Follow-Up

N = 15,854

Non-HighRisk(0–14)

Nondrinker(0)

Low-Risk(1–7)

MediumRisk(8–14)

High-orOver-Risk(=15)

High-Risk(15–19)Probable
Alcohol
Dependence(20–40)N = 15,091(95.2%)

N = 4719(29.8%)

N = 8749(55.2%)

N = 1623(10.2%)

N = 763(4.8%)

N = 404(2.5%)

N = 359(2.3%)

p
Value *

4.1 (±1.8)4.0 (±1.8)4.2 (±1.9)4.0 (±1.75)

3.9 (±1.7)4.9 (±2.2)

4.6 (±2.1)

5.1 (±2.3)<0.001

Score < 6 (%)

12,648 (80)

12,172 (81)3669 (78)7157 (82)1346 (83)476 (62)273 (68)203 (57)<0.001

Score = 6 (%)

3206 (20)2919 (19)1050 (22)1592 (18)277 (17)287 (38)131 (32)156 (43)52.8(±15.6)52.9(±15.7)

52.5(±16.0)52.9(±15.8)54.6(±14.0)49.4(±13.7)50.3(±14.2)

48.4(±13.0)Loneliness (Mean, SD)

Age, year (Mean, SD)<0.001

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Table 1. Cont.
Drinking Categories Based on AUDIT
Non-HighRisk(0–14)

Nondrinker(0)

Low-Risk(1–7)

MediumRisk(8–14)

High-orOver-Risk(=15)

High-Risk(15–19)Probable
Alcohol
Dependence(20–40)N = 15,854

N = 15,091(95.2%)

N = 4719(29.8%)

N = 8749(55.2%)

N = 1623(10.2%)

N = 763(4.8%)

N = 404(2.5%)

N = 359(2.3%)

p
Value *

20–39 years (%)

3513 (22)3337 (22)1144 (24)1942 (22)251 (15)176 (23)

96 (24)80 (22)<0.001

40–59 years (%)

6246 (39)5855 (39)1778 (38)3381 (39)696 (43)391 (51)

189 (47)

202 (56)

60 or over (%)

6095 (38)5899 (39)1797 (38)3426 (39)676 (42)196 (26)

119 (29)

77 (21)

Women

7615 (48)7449 (49)2895 (61)4209 (48)345 (21)166 (22)69 (17)97 (27)

Men

8239 (52)7642 (51)1824 (39)4540 (52)1278 (79)597 (78)335 (83)262 (73)

Follow-Up

Sex (%)<0.001

Education (%)<0.001

Low

4899 (31)4647 (31)1704 (36)2483 (28)460 (28)

252 (33)

123 (30)

Middle3342 (21)3244 (22)1168 (25)1827 (21)249 (15)98 (13)47 (12)129 (36)51 (14)High7613 (48)7200 (48)1847 (39)4439 (51)914 (56)413 (54)234 (58)

179 (50)

Marriage

10,121 (64)9631 (64)2792 (59)5687 (65)1152 (71)490 (64)271 (67)219 (61)

No marriage

4085 (26)3893 (26)1327 (28)2237 (26)329 (20)

192 (25)

96 (24)96 (27)

Divorced/Widowed

1648 (10)1567 (10)600 (13)825 (9)142 (9)81 (11)37 (9)

44 (12)

Living with someone

12,849 (81)12,261 (81)3788 (80)7155 (82)1318 (81)588 (77)322 (80)

26,674)

Living alone

3005 (19)2830 (19)931 (20)1594 (18)305 (19)175 (23)82 (20)93 (26)

Regular job

6823 (43)6308 (42)1573 (33)3793 (43)942 (58)515 (68)279 (69)236 (66)

Non-regular employee

2964 (19)2856 (19)953 (20)1658 (19)245 (15)108 (14)52 (13)56 (16)

No main income job asstudents/retiree/
housework

3798 (24)3753 (25)1412 (30)2146 (25)195 (12)45 (6)

23 (6)

22 (6)

2269 (14)2174 (14)781 (17)1152 (13)241 (15)95 (12)50 (12)45 (13)

Marital status (%)

0.919

Living arrangements (%)

0.004

Job (%)

Unemployed<0.001

Income (%)<0.001

Under 2 million yen

2537 (16)2417 (16)960 (20)1229 (14)228 (14)120 (16)61 (15)59 (16)

2–4 million yen

5769 (36)5491 (36)1634 (35)3283 (38)574 (35)278 (36)

153 (38)125 (35)

4–6 million yen

2550 (16)2403 (16)588 (12)1501 (17)314 (19)147 (19)72 (18)75 (21)

6–10 million yen

1650 (10)1532 (10)322 (7)976 (11)234 (14)118 (15)71 (18)47 (13)10 million or more

367 (2)334 (2)77 (2)

191 (2)66 (4)

33 (4)

21 (5)

12 (3)

Don’t know/want toanswer2981 (19)2914 (19)1138 (24)1569 (18)207 (13)67 (9)

26 (6)

41 (11)

No

12,763 (81)12,305 (82)4093 (87)7109 (81)1103 (68)458 (60)

237 (59)

221 (62)Yes

3091 (20)2786 (18)626 (13)1640 (19)520 (32)305 (40)167 (41)

138 (38)

4.6 (±5.6)

4.5 (±5.5)4.8 (±5.8)4.3 (±5.3)

4.4 (±5.5)7.3 (±6.6)

6.6 (±5.9)8.1 (±7.2)<0.001

K6 < 13 (%)

14,268 (90)13,669 (91)4214 (89)7992 (91)1463 (90)599 (79)334 (83)

265 (74)<0.001K6 = 13 (%)

1586 (10)1422 (9)505 (11)757 (9)160 (10)164 (21)70 (17)94 (26)

Current smoker (%)

Psychological Distress(Mean, SD)<0.001* The difference in mean and difference in proportion of each category was based on two drinking categories
between non-high-risk drinking and high-risk drinking.

3.2. Characteristics of Participants according to AUDIT Scores
The number of high-or-over-risk drinkers (AUDIT ≥ 15) was 763 (5% of the follow-up
population) (Table 1). In addition, their mean age was 49.4 (±13.7) years. Most of thehigh-or-over-risk drinkers were aged 40–59 years (51%), males (78%), had a high educationlevel (54%), were living alone (23%), had a regular job (68%), earned 4–6 million yen (19%),
current smokers (40%), and had a K6 score of ≥13 (21%).

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6 of 133.3. Loneliness and Hazardous Alcohol Use Based on AUDIT Scores
The mean score for loneliness was 4.1 (±1.8), and the proportion of participants withhigh loneliness score (≥6) was 20% among the followed-up participants. The proportionof participants with high loneliness scores in nondrinkers was 22%, which was higher
than that in low-risk (18%) and medium-risk drinkers (17%). The proportion of highrisk drinkers with high loneliness scores was 32%, whereas the proportion of those withprobable alcohol dependence having high loneliness scores was 43%. The proportion ofhigh-or-over-risk drinkers with high loneliness scores was twice as high as the proportionof non-high-risk drinkers with high loneliness scores. Statistical analysis revealed that themeans of loneliness score were significantly different between non-high-risk drinkers andhigh-or-over-risk drinkers (p < 0.05).
3.4. Association between Loneliness and AUDIT Score Pattern Changes
Table 2 shows the mean and proportion of loneliness scores based on AUDIT score
pattern changes from 2021 to 2022. A greater proportion of participants with high lonelinessscores was observed in the pattern of non-high-risk drinkers (AUDIT: 0–14) to high-or-overrisk drinkers (AUDIT: 15–40) compared with those in the non-high-risk drinkers (AUDIT:
0–14) to non-high-risk drinkers (AUDIT: 0–14) (respective proportions were 27% and 19%).
Furthermore, the proportion of individuals with high loneliness scores in the no-patternchanges from high-or-over-risk drinkers to high-or-over-risk drinkers had a slightly higher
proportion of high loneliness scores than those in the pattern changes from high-or-over to
non-high-risk drinkers (39% vs. 36%; Supplementary Table S3).
Table 2. The change of AUDIT patterns from 2021 to 2022 and associated factors based on 2021
among non-high-risk drinking patterns, 2021.
Non-High-Risk at Baseline
N = 15,091
Non-High-Risk
to Non-High-Risk(0–14) to (0–14)

Non-High-Risk
to High-or-Over(0–14) to (15=)

N = 14,742

N = 349

N (%)

N (%)

4.0 (±1.8)4.4 (±1.9)

Score < 6

11,918 (81)254 (73)

Score = 62824 (19)95 (27)53.0 (±15.7)

49.9 (±14.5)

20–39 years

3246 (22)91 (26)40–59 years

5695 (39)160 (46)

60–79 years

5801 (39)

98 (28)

Women7382 (50)67 (19)Men

7360 (50)282 (81)Low

4561 (31)

86 (25)

Middle3173 (22)71 (20)High7008 (48)192 (55)

Loneliness (Mean, SD)

Age, year (Mean, SD)

Sex

Education

Marital status

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Table 2. Cont.
Non-High-Risk at Baseline
N = 15,091
Non-High-Risk
to Non-High-Risk(0–14) to (0–14)

Non-High-Risk
to High-or-Over(0–14) to (15=)

N = 14,742

N = 349

N (%)

N (%)

Marriage

9398 (64)233 (67)

No marriage

3810 (26)83 (24)

Divorced/Widowed

1534 (10)33 (9)

Living with someone

11,987 (81)274 (79)

Living alone

2755 (19)75 (21)

Regular job

6093 (41)215 (62)

Non-regular employee

2800 (19)56 (16)

No main income job,
students/retiree/housework

3716 (25)

37 (11)

Unemployed

2133 (14)41 (12)

Under 2 million yen

2366 (16)51 (15)

2–4 million yen

5354 (36)137 (39)

4–6 million yen

2342 (16)61 (17)

6–10 million yen

1477 (10)55 (16)

10 million or more

327 (2)7 (2)Don’t know/want to answer

2876 (20)38 (11)

No

12,075 (82)230 (66)Yes

2667 (18)119 (34)

4.4 (±5.4)6.0 (±6.2)

K6 < 13

13,370 (91)299 (86)

K6 = 131372 (9)50 (14)

Living arrangements

Job

IncomeCurrent smoker

Psychological Distress (Mean, SD)

Table 3 presents the aRR for the AUDIT score pattern changes from non-high-risk tohigh-risk drinkers related to loneliness among non-high-risk drinkers at baseline. In theunivariable model (Model 1), participants with high loneliness scores at baseline had an
association with the changing patterns from non-high-risk to high-risk drinkers comparedwith participants with non-low loneliness (RR: 1.56, 95% CI: 1.24–1.97). The association
was a little attenuated after adjusting for sociodemographic factors, including sex, inModel 1. A slight change in the association between loneliness and changes in high-risk
drinking patterns was seen after adjusting for potential social isolation factors (marital
status and living arrangements) and smoking in Model 3. After further adjustment forpsychological distress in Model 4, participants with high loneliness scores at baseline had an
association with the changing patterns from non-high-risk to high-risk drinkers comparedwith participants with non-low loneliness (aRR: 1.45, 95% CI: 1.08–1.96).

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Table 3. Risk ratios of loneliness for increased high-risk drinking by AUDIT pattens from (0–14) in
2021 to (15–40) in 2022 among non-high-risk drinking patterns at baseline (N = 15,901).
Model 1Model 2Model 3Model 4

RR (95%CI)

aRR (95%CI)

aRR (95%CI)

aRR (95%CI)

Score < 6

ref

ref

ref

Ref

Score = 6

1.56 (1.24–1.97)

1.52 (1.18–1.96)

1.57 (1.22–2.03)

1.45 (1.08–1.96)

20–39 years

ref

ref

Ref

40–59 years

0.97 (0.73–1.27)

0.81 (0.61–1.07)

0.81 (0.61–1.08)

60–79 years

0.76 (0.54–1.06)

0.57 (0.39–0.81)

0.58 (0.40–0.83)

Women

ref

ref

ref

Men

4.43 (3.17–6.19)

4.26 (3.01–6.02)

4.27 (3.02–6.04)

Low

ref

ref

ref

Middle1.36 (0.97–1.91)

1.39 (0.99–1.94)

1.38 (0.99–1.94)

High

1.05 (0.80–1.38)

1.10 (0.83–1.44)

1.09 (0.83–1.43)

ref

ref

ref

Non-regular employee

1.06 (0.76–1.49)

1.17 (0.83–1.66)

1.18 (0.83–1.66)

No main income job asstudents/retiree/housework

0.73 (0.47–1.12)

0.81 (0.53–1.26)

0.81 (0.52–1.26)

Unemployed

0.76 (0.49–1.16)

0.87 (0.57–1.34)

0.87 (0.56–1.34)

ref

ref

ref

2–4 million yen

1.06 (0.76–1.48)

1.02 (0.73–1.42)

1.02 (0.73–1.42)

4–6 million yen

0.90 (0.60–1.33)

0.83 (0.56–1.24)

0.84 (0.56–1.25)

6–10 million yen

1.29 (0.86–1.95)

1.21 (0.80–1.83)

1.21 (0.80–1.83)

10 million or more

0.76 (0.34–1.69)

0.68 (0.30–1.52)

0.68 (0.31–1.53)

ref

ref

No marriage

0.50 (0.34–0.71)

0.49 (0.34–0.71)

Divorced/Widowed

0.90 (0.58–1.41)

0.90 (0.57–1.40)

ref

ref

1.49 (1.05–2.13)

1.50 (1.05–2.14)

ref

ref

1.63 (1.29–2.06)

1.62 (1.28–2.05)

Loneliness

Age

Sex

Education

Job
Regular job

IncomeUnder 2 million yen

Marital status
Marriage

Living arrangement
Living with someone
Living alone
Smoking
Non-smoker
Current smoker
Psychological distressK6 < 13
K6 = 13ref1.23 (0.84–1.80)
Bold items were significant (p < 0.05). Model 1: univariable. Model 2: adjusted socioeconomic factors (age, sex,
education, job, income,). Model 3: adjusted additional social isolation (living arrangement, marital status) in
Model 2 and health factors (smoker, sleeping duration, BMI). Model 4: further adjusted K6 (Kessler PhycologicalDistress Scale).

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4. Discussion
In this nationwide longitudinal study, loneliness was associated with increased severity of hazardous alcohol drinking patterns with 1-year follow-up during the COVID-19
pandemic, independent of objective social isolation, psychological distress, and other potential confounders. We found that nondrinkers scored slightly higher on loneliness than lowand medium-risk drinkers. Nondrinkers had much lower loneliness scores than high-risk
drinkers and those with probable alcohol dependence.
Drinking is a social facilitator. Previous studies showed that elderly people enjoyedalcoholic beverages during social gatherings in Australia [28], and social networks from
relatives and friends were associated with individuals’ drinking behaviors in the U.S. [29].
During the COVID-19 pandemic, social gatherings, such as dining out with a large group,
were regulated by governments as a preventive measure against transmission worldwide.
This led to social isolation, and in turn, increased feelings of loneliness [30]. In Japan,
the prevalence of social isolation increased by 6.7% during the COVID-19 pandemic [31].
However, only a few studies have examined the impact of social isolation and lonelinesson increased risky drinking patterns. Our results suggested that social isolation had acomparable impact on increased risky drinking patterns as well as loneliness, probably
because living alone during the COVID-19 pandemic led to social isolation due to theregulation of gatherings, restriction of dining out with groups, and staying at home.
Loneliness has been reported to be associated with mental disorders, such as depressive symptoms [32]. Psychological distress due to COVID-19 was associated with higher
rates of high-risk drinking [33,34]. A possible causal relationship may occur between psychological distress and increased high-risk drinking in a public health emergency situation.
However, our results showed that loneliness was an independent risk factor for increased
risk of drinking patterns after adjusting for psychological distress.
In a previous cross-sectional study, loneliness was not associated with at-risk drinking
or binge drinking in the U.S. [6]. In the abovementioned previous study, at-risk drinking
was defined as the volume of average drinking per week and per day, and nondrinkers were
defined as having no alcohol consumption in the last 3 months. Another study showed noclear evidence between loneliness and hazardous alcohol use or alcohol dependence (basedon genetic variants) [5]. On the other hand, a cross-sectional survey of the nine countries ofthe former Soviet Union showed that loneliness was associated with alcohol consumption,
hazardous drinking, and problem drinking, although no association was observed in someof the countries [35]. We noted that the relationship between loneliness and drinking was
not linear; low- and medium-risk drinkers may feel less lonely than nondrinkers, possibly
owing to social interaction during drinking. In our study, we did not distinguish between
lifelong abstinence, current abstainers, and former problem drinkers among nondrinkers.
Previous studies showed that current abstainers and former problem drinkers did not
drink probably due to their health status [36,37] and former drinkers were less healthythan current drinkers and lifelong abstainers [38]. In addition, nondrinkers tended to haveworse socioeconomic status compared to the general population and current drinkers [37].
The definition of nondrinkers and/or at-risk drinkers may lead to inconsistent results inprevious cross-sectional studies.
Our results suggested that loneliness triggered the development of hazardous alcohol
use as defined by AUDIT. Loneliness scores among drinkers with symptoms such as lackof control when drinking; feeling guilty or experiencing blackouts after drinking; andalcohol-related injuries, including hurting others, were higher than those in drinkers who
did not present these symptoms (Supplementary Table S4). The effective interventions
for reducing loneliness were explored, such as meditation/mindfulness, social cognitive
training, and social support [39]. Those interventions may be helpful for people with highloneliness to prevent hazardous alcohol use.
The main strength of this study was its large sample size due to the nationwide
sampling design to evaluate the relationship between loneliness and the development of
hazardous alcohol use, including probable alcohol dependence. However, this study also

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had several limitations. First, we used self-reported loneliness measures and drinking
patterns based on AUDIT, which could have led to measurement errors. Nonetheless, bothself-reported loneliness measures and drinking patterns based on AUDIT are accepted
as relevant screening tests and are reliable and valid in Japanese individuals [24,40]. Second, the current study design restricted the results from being generalized to the general
Japanese populations. Our data showed that 5% of people (7% for men and 2% for women)
had an AUDIT score ≥15, which was greater than that reported in the national survey (2.9%;
5.2% for men and 2.9% for women) in 2018 [41]. However, an increase in hazardous alcohol
use during the COVID-19 pandemic was reported in the U.S. [42,43], suggesting that theprevalence of high-risk alcohol drinkers being higher in our study than that reported in the2018 national survey was valid. Third, our follow-up population with data on all variables
slightly differed from the overall sample, which could have led to a selection bias. For
example, the follow-up population was older than the overall population. Yet, similarprevalence of main variables, including loneliness and AUDIT, between the follow-up population and overall population allowed us to examine the association between lonelinessand the development of high-risk drinking. Fourth, we were unable to compare the current
data with those reported in the pre-pandemic period. The preventive measures aimed
at reducing COVID-19 transmission might have affected the survey outcomes. Further
investigations are warranted to clarify this under no social restrictions. Fifth, although we
adjusted for a wide range of confounders, the possibility of residual confounding, such as
duration of high loneliness and drinking styles (e.g., social drinking, drinking at home, anddrinking alone), cannot be excluded.
5. Conclusions
This study examined the association between loneliness and increased hazardous
alcohol consumption during the COVID-19 pandemic. Individuals experiencing high loneliness were more susceptible to engaging in hazardous alcohol use. Providing appropriate
support to people experiencing high degrees of loneliness, such as social supports, will
have a positive impact on the prevention of potential alcohol dependence.
Supplementary Materials: The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijerph191912086/s1, Figure S1: The flow diagram of the study
population, Table S1: AUDIT questions and each score of answers, Table S2: The scale score of ourstudy based on UCLA-LS-SF3, and the original score scale on JASTIS questionnaire, Table S3: The
four patterns of AUDIT categories’ changes and their characteristics based on 2021, Table S4: The
percentage and means of loneliness score in each AUDIT item among follow-up populations.
Author Contributions: Conceptualization, M.W.; Methodology, M.W., Y.S., M.T., A.K., T.T.; Formal Analysis, M.W.; Investigation, M.W.; Data Curation, M.W.; Writing—Original Draft, M.W.;
Writing—Review and Editing, Y.S., M.T., A.K., T.T., H.I., Visualization, M.W.; Supervision, H.I.;
Project Administration, T.T.; Funding Acquisition, T.T., M.W. All authors have read and agreed to the
published version of the manuscript.
Funding: This study was supported by KAKENHI Grants from the Japan Society for the Promotion of
Science (JSPS) [Grant Nos. 15K19256, 17H03589, 19K10671, 19K10446, 18H03107, 18H03062, 19H03860,
and 21H04856]; a JSPS Grant-in-Aid for Young Scientists [Grant No. 19K19439]; the Research Support
Program to Apply the Wisdom of the University to Tackle COVID-19-Related Emergency Problems,
University of Tsukuba; Health Labour Sciences Research Grants [Grant Nos. 19FA1005; 19FG2001; and19FA1012]; the Japan Agency for Medical Research and Development (AMED) [Grant No. 2033648];
Health Labor Sciences Research Grants [H26-junkankitou-ippan-023, H28-junkankitou-ippan-002,
H28-junkankitou-ippan-008, and H29-tokubetsu-site-006], and the Health, Labor and Welfare Sciences
Research Grants: Research on policies for global health issues [JPMH21BA1001]. The findings andconclusions of this study are the primary responsibilities of the authors and do not represent theofficial views of the research funders.

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Institutional Review Board Statement: All procedures were conducted as per the ethical standardsof the 1975 Helsinki Declaration (revised in 2013). The Research Ethics Committee of the Osaka
International Cancer Institute reviewed and approved the study protocol (approval No. 1412175183).
Informed Consent Statement: All participants provided their informed consent before responding
to the online questionnaire.
Data Availability Statement: The data that support the findings of this study are available on
reasonable request. However, restrictions apply to the availability of these data to protect personal
identification; research data are not shared. If any person wishes to verify our data, they are welcome
to contact the corresponding author.
Acknowledgments: We would like to thank the JASTIS team for their support with the data collection.
Conflicts of Interest: The authors declare no conflict of interest.

Abbreviations
AUDIT
aRR
CI
COVID-19
JASTISSD
WHO

Alcohol Use Disorders Identification Test
Adjusted risk ratios
Confidence interval
Coronavirus infectious disease identified in 2019Japan Society and New Tobacco Internet Survey
Standard deviation
World Health Organization

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