Low Psychological Resilience Predict the Risk for Alcohol Use Disorder in General Population: National Mental Health Survey of Korea 2021

Seung-Hoon Lee; Junhyung Kim; Changsu Han

doi:10.9758/cpn.24.1171

2025; 23(1): 53-64 https://doi.org/10.9758/cpn.24.1171

Low Psychological Resilience Predict the Risk for Alcohol Use Disorder in General Population: National Mental Health Survey of Korea 2021

Seung-Hoon Lee, Junhyung Kim, Changsu Han

Department of Psychiatry, Korea University Guro Hospital, College of Medicine, Korea University, Seoul, Korea

Correspondence to: Changsu Han
Department of Psychiatry, Korea University Guro Hospital, 148 Gurodong-ro, Guro-gu, Seoul 08308, Korea
E-mail: hancs@korea.ac.kr
ORCID: https://orcid.org/0000-0002-4021-8907

Received: January 31, 2024; Accepted: February 16, 2024; Published online: March 20, 2024.

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract: Objective: Prior research has emphasized psychological resilience as a potential protective factor against alcohol use disorder in diverse populations, with limited exploration of its relationship in the general population. This study investigated the association between the lifetime and one-year prevalence of alcohol use disorder and resilience.
Methods: Data obtained from the National Mental Health Survey of Korea 2021 (5,511 participants; 40.7% response rate) encompassed information on alcohol use disorders, resilience, experiences of psychological trauma, and major mental disorders. The analyses compared demographics, psychological trauma, resilience, and the prevalence of major mental disorders based on alcoholism. The contribution of resilience to alcoholism was assessed utilizing Rao-Scott logistic regression, with adjustments made for confounding variables.
Results: Individuals with both lifetime and 1-year alcohol use disorder and dependence exhibited significantly lower levels of resilience on the Connor-Davidson Resilience Scale. Diminished resilience predicted morbidity and persisted even after adjusting for depressive and anxiety disorders, psychological trauma, nicotine use disorders, age, gender, education, income, marital status, and occupation.
Conclusion: Diminished resilience is a prognostic indicator of increased likelihood of both lifetime and current alcoholism in the general population.; Keywords: Resilience, psychological; Alcoholism; Alcohol dependence; Mental disorders; National Mental Health Survey of Korea

INTRODUCTION

Alcohol use disorder (AUD) poses a substantial global burden, exerting pervasive effects on health, mortality, and socioeconomic well-being. Linked to diverse health issues such as liver disease and mental health disorders, AUD is responsible for 3.8% of global deaths and 4.6% of disability-adjusted life years [1]. Beyond its direct health implications, AUD exerts significant economic ramifications, strains healthcare systems [2] and impairs workplace productivity [3]. Socially, it disrupts interpersonal bonds [4], fosters violence [5], and perpetuates social disparities [6]. Recognizing AUD as a public health challenge and effectively addressing its worldwide impact necessitate coordinated efforts in prevention, treatment, and policy formulation to alleviate its far-reaching consequences for individuals and societies globally.

Unraveling the risks and protective factors inherent in AUD is imperative for the development of targeted preventive strategies. The identification of risk elements, including genetic predispositions and environmental influences, enables precise intervention approaches, particularly for individuals with heightened susceptibility [7]. Concurrently, recognizing and fortifying protective factors, such as robust social support and effective coping mechanisms, are integral to preventive efforts [8].

The susceptibility to stress is widely recognized as a risk factor for the development of AUD [9]. Psychological resilience denotes an individual’s capacity to effectively navigate stressors and adapt to environmental changes while sustaining psychological well-being in challenging circumstances. The prominence of the resilience concept arose from observations of individuals who demonstrated superior recovery and adaptation compared to others following highly stressful events [10].

Recent studies consistently indicate that psychological resilience plays a pivotal role in preventing AUD [11]. However, most studies focusing on community populations have constraints in assessing AUD as a substance use disorder, relying predominantly on self-report questionnaires to assess problematic drinking [12-14] or inquiring about the quantity of alcohol consumed [15]. Overstreet et al. [16] employed the structured AUD and Associated Disabilities Interview to investigate the correlation between resilience and AUD in the general population, with a predominant representation of White, Black, and Hispanic ethnicities. Additionally, within the context of Korean research, investigations have primarily centered on patients [17,18] or specific populations [19], restricting the extrapolation of existing findings on the correlation between resilience and AUDs to a broader community-based general population [20,21].

This study primarily aimed to assess and compare current resilience levels based on lifetime and current occurrences of alcoholism, investigating the role of resilience in influencing AUD among community-based populations in South Korea. Additionally, we focused on investigating the association between resilience and AUD while adjusting for the impact of sociodemographic indicators and the prevalence of co-occurring mental illnesses that may influence alcoholism.

METHODS

Participants

The National Mental Health Survey of Korea (NMHSK), conducted every 5 years since 2001, aims to assess the prevalence, risk factors, and sociodemographic distribution of mental disorders in the South Korean community, providing fundamental data for mental health policy formulation. This study utilized secondary data from the 2021 NMHSK, conducted between June 19 and August 31, 2021. The survey included participants aged 18−79 years and excluded institutionalized individuals and foreigners from South Korea. Employing a complex sample design, the survey covered the entire country with stratification variables including province, city, town, county, and household type. A probability sampling method proportional to the size was utilized to sample the primary and enumeration units, with households selected through systematic random sampling. The interviewers visited 13,530 households, resulting in 5,511 completed interviews (response rate: 40.7%). Demographic characteristics, physical health details, and mental health-related information were collected through interviews and diagnostic tools. For more comprehensive information on the data collection and findings, please refer to the 2021 NMHSK Fact Sheet (available at https://mhs.ncmh.go.kr/) and Rim et al. [22] study on mental illness prevalence in South Korea based on survey data.

Ethics Approval and Consent to Participate

This study received approval from the Institutional Review Board of Korea University Guro Hospital (IRB number: 2023GR0194). Written consent was waived by the Institutional Review Board of the Korea University Guro Hospital since we utilized the 2021 NMHSK microdata, which comprised de-identified secondary data.

Measure

Composite International Diagnostic Interview 2.1

The 2021 Mental Health Survey of Korea utilized the Korean version of the Composite International Diagnostic Interview 2.1 (K-CIDI) [23] to collect data on the prevalence of mental illness, suicidal ideation, and mental health service utilization. The K-CIDI is a diagnostic tool consisting of a fully structured interview that diagnoses mental disorders according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) [23]. In contrast to prior Mental Health Surveys of Korea, the 2021 Mental Health Survey utilized a modified K-CIDI with tablet-assisted personal interviews, enhancing the efficiency and accuracy of the interview pro-cess. The K-CIDI was employed to ascertain an individual’s lifetime, 1-year, and 1-month prevalence of AUD, alcohol dependence, alcohol abuse, nicotine use disorders, anxiety disorders (obsessive-compulsive disorder, posttraumatic stress disorder, panic disorder, agoraphobia, social phobia, generalized anxiety disorder, and specific phobia), depressive disorders (major depressive disorder and dysthymia), and suicidal ideation, plans, and attempts [22].

Psychological Resilience

The 10-item Connor-Davidson Resilience Scale (CD-RISC) [24] was employed in this study to assess participants’ psychological resilience. Originally comprising 25 items, the CD-RISC was streamlined to a more concise 10-item version as a result of factor analysis instability [25]. A standardization study conducted by Campbell-Sills and Stein [26] confirmed the robust psychometric property of the revised 10-item CD-RISC, establishing it as an efficient measure of resilience. The scoring range for the CD-RISC, with its 10 items, spans from 0 to 40 points, with higher scores indicating greater resilience [26,27]. The internal consistency of the Korean-translated 10-item CD-RISC, as evaluated by the Cronbach alpha coefficient, was determined to be 0.95 in a study conducted by Baek et al. [27,28].

Psychological Trauma History

Psychological trauma manifests as an emotional response to a deeply distressing incident, such as an accident, sexual assault, or natural disaster [29,30]. According to the DSM-5 text revision (DSM-5-TR) [29], psychological trauma, as defined by Criterion A diagnostic criteria for posttraumatic stress disorder (PTSD), can arise from exposure to death, threat of death, actual or threatened serious injury, or actual or threatened sexual violence. This exposure may occur through direct personal experience, witnessing a traumatic event, or learning about an event occurring to a close relative or friend. Recognizing that traumatic psychological experiences serve as risk factors for alcoholism [31], this study explored individuals’ experiences utilizing the traumatic experiences questionnaire from PTSD Diagnostic Criteria A of the K-CIDI [23].

Statistical Analyses

To compare demographic data, the prevalence of co-occurring psychiatric disorders, and resilience (CD-RISC score) based on 1-year and lifetime prevalence of AUD (dependence and abuse), we conducted a cross-tabulation analysis and generalized linear analysis, considering a complex sampling design. Additionally, to ascertain the contribution of the CD-RISC to AUD as dependent variables and the variables that exhibited significant differences between the case and control groups as covariates, we performed logistic regression analysis considering complex sampling. All analyses were conducted utilizing the Statistical Package for the Social Sciences, version 21.0 for Windows (IBM Co.).

RESULTS

Demographics Depending on AUD

Individuals with a lifetime history of AUD exhibited a higher prevalence among men, a greater average household income, and a higher rate of unemployment compared to those without AUD. For individuals with Lifetime Alcohol Dependence, the average age was significantly higher, whereas no significant difference was observed in monthly household income. Similar trends were observed for other variables, such as lifetime AUD. In the context of lifetime alcohol abuse, there was a higher household income, greater proportion of men, and relatively higher incidence of unemployment (Table 1-1).

In the context of 1-year AUD, younger individuals showed a higher proportion of men and exhibited higher education levels (more than 13 years) and a higher rate of never being married. In the case of 1-year alcohol dependency, younger individuals indicated a higher household income and higher proportion of men, in addition to a greater percentage of those with more than 13 years of education. Regarding 1-year alcohol abuse, there was a higher proportion of younger individuals, those with higher household income, and those who had never been married (Table 1-2).

Comorbid Mental Disorder

In individuals with a lifetime history of AUD and alcohol dependence, the prevalence of lifetime depression, anxiety, and nicotine use disorders was significantly increased compared to those without alcoholism. In cases involving lifetime alcohol abuse, there was a high prevalence of lifetime depression and nicotine use disorders (Table 2-1).

For individuals with a history of AUD and alcohol abuse in the past year, the prevalence of depressive disorders, anxiety disorders, and nicotine use disorders was significantly higher than in those without AUD or alcohol abuse. When alcohol dependence was present in the past year, the prevalence of depressive disorder and nicotine use disorder was significantly higher than that in those without alcohol dependence (Table 2-2).

Regarding AUD, individuals with a lifetime history of the disorder and those who experienced the disorder in the past year reported a higher incidence of psychological trauma compared to individuals without a history of the disease. Concerning alcohol dependence and abuse, the prevalence of psychological trauma was elevated in those with a lifetime history of illness (Table 3).

Resilience (CD-RISC)

Resilience, as measured by the CD-RISC, was significantly lower among those with a lifetime and 1-year AUD and alcohol dependence compared to those without these disorders (Table 4).

Logistic Regression

A high resilience level predicted the absence of morbid AUD and alcohol dependence in both lifetime and one-year instances, as indicated by logistic regression analysis adjusted for age, gender, marital status, household income, educational level, and the prevalence of depressive disorder, anxiety disorder, and nicotine use disorder (Table 5).

DISCUSSION

In this study, resilience, as measured by the CD-RISC, was significantly lower in those with a lifetime and one-year history of AUD and alcohol dependence. Logistic regression analysis adjusted for various factors including age, gender, household income, employment as well as marital status, educational level, and comorbid major mental disorders, revealed that a high resilience level predicted the absence of morbidity associated with AUD or alcohol dependence in both the lifetime and 1-year time frames. These findings suggest that elevated resilience functions as a protective factor against the development of AUD.

Studies conducted on various population samples have consistently exhibited an association between AUD or problematic drinking and low resilience, aligning with the findings of the present study. In a cross-sectional study involving six cohorts with diverse population samples, including individuals with acquired immunodeficiency syndrome, drug users, and those at high risk of human immunodeficiency virus infection, higher levels of resilience were associated with a lower risk of alcohol misuse [12]. Similarly, a study on sexual minority women found an association between resilience and problematic drinking. [32]. Among college students, resilience predicted changes in alcohol use before and after COVID-19, and high resilience was associated with reductions in alcohol consumption [13]. Analyzing data from the Women’s Health Initiative, a study on older women revealed that high and moderate levels of resilience were correlated with moderate alcohol use [15]. Furthermore, an analysis of the correlation between alcohol use and resilience in veterans revealed that diminished resilience at the initial assessment was linked to alcohol misuse 1 year later [33]. High resilience was also associated with lower AUD identification test scores among combat veterans [34,35]. Finally, in a twin study examining genetic associations and gender differences in resilience to mental illness and problematic alcohol use, no significant interaction was found between resilience to alcohol-dependent symptoms and new stressful life events. However, individuals with high resilience and fewer stressful life events had fewer alcohol-dependent symptoms [36].

A previous study reported unfavorable findings concerning the association between resilience and AUD; however, it is important to acknowledge methodological distinctions between that study and the present investigation. In a study involving middle-aged individuals, the rate of moderate alcohol consumption did not differ depending on the resilience phenotype, and the phenotype did not predict changes in health behaviors, such as moderate alcohol use. Notably, in this study, the degree of resilience was evaluated by measuring psychological health based on adversity experiences rather than utilizing a questionnaire with guaranteed validity in measuring resilience [37]. Additionally, Nishimi et al. [37] only investigated alcohol consumption, and alcohol dependence and abuse as substance use disorders were not assessed.

Alcohol dependence is a chronic condition characterized by increased tolerance to alcohol, withdrawal symptoms, such as insomnia and tremors, compulsion to drink or cravings, and unsuccessful attempts to reduce alcohol consumption, ultimately leading to the need for continued alcohol consumption. Alcohol abuse is a state in which an individual persists in drinking despite recurring social, interpersonal, health, or legal issues stemming from alcohol consumption [38]. In the DSM-5-TR [39], unlike in the DSM-IV [29] and previous versions of the DSM, alcohol dependence and alcohol abuse were integrated into the AUD criteria. However, the K-CIDI [23] enables a diagnosis based on DSM-IV to be made; therefore, in addition to AUD as a comprehensive concept of alcoholism, alcohol dependence and alcohol abuse were also investigated in this study.

As previously established, individuals with AUDs often exhibit a heightened co-occurrence of depressive and anxiety disorders [40]. Moreover, the incidence of problematic alcohol use tends to rise among those who have experienced psychological trauma compared to those who have not [41]. Given the potential confounding influence of coexisting mental disorders and trauma history on the association between AUD and resilience, this study examined their relationship by adjusting for these factors. Remarkably, even after accounting for mental illness and a history of psychological trauma, elevated resilience remained a robust predictor of freedom from AUD in both the current and lifetime contexts.

Considering the potential psychological explanation for the association between low resilience and AUD, the capacity to cope with stressors, rebound from adversity, and sustain mental well-being functions as a protective mechanism against the initiation and progression of problematic alcohol consumption [42]. Moreover, resilient individuals tend to exhibit enhanced decision-making skills [43], diminishing the likelihood of engaging in risky drinking behaviors. Resilient individuals also demonstrate strong emotional regulation skills, enabling them to manage negative emotions without resorting to alcohol as a means of self-medication. This emotional stability reduces the likelihood of alcohol use to cope with or escape emotional distress [44]. Furthermore, resilient individuals demonstrate adaptability to challenges, reducing the need for maladaptive coping mechanisms, such as excessive alcohol consumption [45].

Alcohol dependence includes withdrawal and tolerance and reflects the biological and physiological state, while alcohol abuse focuses more on adaptation to occupational and social life [39]. In this study, we observed a relationship between resilience and alcohol dependence, prompting us to consider the possibility that a shared biological mechanism between resilience and alcohol dependence might be involved.

Genetic influences on resilience overlapped with genetic contributions to alcohol abuse in a twin study [46]. Previous studies have suggested that resilient individuals exhibit a more balanced regulation of neurotransmitters in the brain, including serotonin [47-49], dopamine [50-52], and gamma-aminobutyric acid (GABA) [53,54]. Proper neurotransmitter balance is crucial for mood stability and impulse control [50], reducing the susceptibility to alcohol as a means of self-medication. Moreover, accumulating evidence indicates that alcohol directly activates the hypothalamic-pituitary-adrenal axis and influences glucocorticoid receptors, which play a role in the stress response, across the extrahypothalamic, limbic forebrain, and medial prefrontal cortex circuits [55]. Resilient individuals often exhibit improved prefrontal cortex function, which is involved in decision-making, impulse control, and emotional regulation [56,57]. A well-functioning prefrontal cortex contributes to better judgment and the ability to resist impulsive behaviors, including excessive alcohol consumption. Resilience may be associated with a more balanced endogenous opioid system that regulates the brain’s response to pleasure and reward, which, in turn, affects alcoholism [58].

Despite the significant findings of this study, it is crucial to recognize several limitations. First, although a correlation was observed between resilience and alcoholism, the cross-sectional design impeded the establishment of a causal relationship between these variables. Furthermore, while structured interviews were utilized to investigate mental illness and the history of alcoholism, the reliance on participant memory introduced the potential for memory decay bias. Notably, severe mental illnesses such as bipolar disorder and schizophrenia, which carry an elevated risk of AUD [59,60], were not addressed in the 2021 NMHSK, necessitating further investigation. Additionally, the influence of personality traits and temperament on the relationship between resilience and alcoholism cannot be entirely discounted, underscoring the importance of considering these factors as potential mediators.

Notwithstanding the acknowledged limitations, this comprehensive study explored the influence of resilience on AUDs in the general Asian population, with a specific focus on Koreans. This study addressed previous research limitations by ensuring racial diversity and enhancing the diagnostic validity of AUD in the general population. Particularly, resilience emerged as an independent protective factor for AUD, particularly alcohol dependence, even after accounting for potentially confounding variables such as depressive and anxiety disorders. This correlation between resilience and AUD holds significant promise for future applications in screening and evaluating individuals at risk for AUD.

Conclusion

We evaluated the correlation between resilience and AUD in a community sample representing the general South Korean population. Our findings indicate that low resilience remains a distinct risk factor for AUD, especially alcohol dependence, within the lifetime and current use timeframe, even when accounting for various potential confounding factors. As a result of the limitations of the current study, future studies with a longitudinal study design are warranted to determine the relationship between alcoholism and resilience. The incorporation of a resilience assessment is valuable for gauging the contemporary risk of alcoholism in subsequent research and for informing substance use prevention policies.

Funding: This research was supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI22C1983).

Acknowledgements: This study used the data from the 2021 National Mental Health Survey 2021 (NNMHSK-30). The datasets generated or analyzed during the current study are available upon request and were reviewed and permitted by the National Center for Mental Health, Republic of Korea, a data management organization of the NMHSK repository (https://mhs.ncmh.go.kr/). The study results are unrelated to the Ministry of Health and Welfare of South Korea.

Conflicts of Interest: No potential conflict of interest relevant to this article was reported.

Author Contributions: Methodology: Seung-Hoon Lee, Junhyung Kim. Data acquisition: Seung-Hoon Lee. Software: Seung-Hoon Lee. Formal analysis: Seung-Hoon Lee, Junhyung Kim. Valid-ation: Seung-Hoon Lee, Junhyung Kim, Changsu Han. Funding: Changsu Han. Writing—original draft: Seung-Hoon Lee. Writing—review & editing: Seung-Hoon Lee, Junhyung Kim, Changsu Han. All the authors have read and approved the final version of the manuscript.

Tables

Table 1-1

Demographic data based on lifetime prevalence of alcoholism

	Alcohol use disorder-lifetime					Alcohol dependence-lifetime					Alcohol abuse-lifetime

	Positive (n = 643)	Negative (n = 4,868)	Statistics			Positive (n = 353)	Negative (n = 5,158)	Statistics			Positive (n = 290)	Negative (n = 5,221)	Statistics

			t	p	χ²			t	p	χ²			t	p	χ²
Age (yr)	47.77 ± 0.65	47.01 ± 0.16	−1.054	0.292		48.94 ± 0.90	46.97 ± 0.15	−2.034	0.042		48.94 ± 0.90	46.97 ± 0.15	0.724	0.469
Monthly house income^a	441.72 ± 12.00	411.48 ± 4.09	−2.527	0.012		436.47 ± 17.28	413.53 ± 4.05	−1.341	0.181		447.97 ± 15.49	413.13 ± 4.18	−2.232	0.026
Gender (man)	499 (76.77)	2,258 (46.93)		< 0.001	200.81	268 (76.30)	2,489 (48.65)		< 0.001	98.787	231 (77.29)	2,526 (48.87)		< 0.001	89.802
Education level			3.403	0.477				0.695	0.905				4.038	0.397
0−11 yr	95 (13.27)	746 (14.69)				57 (14.73)	784 (14.51)				38 (11.56)	803 (14.69)
12 yr	258 (37.78)	1,793 (34.38)				137 (36.55)	1,914 (34.65)				121 (39.23)	1,930 (34.52)
13−15 yr	124 (21.72)	1,048 (23.46)				68 (21.87)	1,104 (23.35)				56 (21.55)	1,116 (23.36)
≥ 16 yr	166 (27.23)	1,277 (27.47)				91 (26.85)	1,352 (27.49)				75 (21.64)	1,368 (27.43)
Employment status			57.703	< 0.001				24.433	< 0.001				33.265	< 0.001
Unemployed	71 (11.26)	342 (7.20)				41 (11.91)	372 (7.38)				30 (10.49)	383 (7.51)
Employed	508 (77.87)	3,454 (69.73)				274 (75.68)	3,688 (70.33)				234 (80.43)	3,728 (70.12)
Homemaker	47 (7.35)	874 (17.68)				31 (9.44)	890 (16.95)				16 (4.89)	905 (17.13)
Student	17 (3.53)	195 (5.40)				7 (2.96)	205 (5.33)				10 (4.19)	202 (5.24)
Marital status			2.286	0.366				4.982	0.130				0.196	0.919
Married or living with a partner	416 (63.29)	3,229 (62.97)				227 (62.69)	3,418 (63.03)				189 (63.99)	3,456 (62.95)
Bereaved, separated, divorced	93 (11.40)	552 (9.78)				57 (13.19)	588 (9.75)				36 (9.31)	609 (10.00)
Never been married	134 (25.31)	1,087 (27.25)				69 (24.12)	1,152 (27.22)				1,156 (27.04)	65 (26.70)

Values are presented as mean ± standard error or number (%).

^aMonthly house income is presented in ten thousand Korean Won.

Table 1-2

Demographic data based on the one-year prevalence of alcoholism

	Alcohol use disorder-1 yr					Alcohol dependence-1 yr					Alcohol abuse-1 yr

	Positive (n = 134)	Negative (n = 5,377)	Statistics			Positive (n = 79)	Negative (n = 5,432)	Statistics			Positive (n = 55)	Negative (n = 5,456)	Statistics

			t	p	χ²			t	p	χ²			t	p	χ²
Age (yr)	40.47 ± 1.40	47.27 ± 0.14	4.742	< 0.001		43.35 ± 1.79	47.15 ± 0.14	2.078	0.038		36.52 ± 2.12	47.21 ± 0.13	5.011	< 0.001
Monthly house incomea	506.80 ± 32.26	412.54 ± 3.99	−2.941	0.003		528.16 ± 44.95	413.22 ± 4.02	−2.567	0.011		475.79 ± 34.22	414.32 ± 4.10	−1.813	0.07
Gender (man)	92 (65.74)	2,665 (49.97)		0.003	13.957	54 (66.55)	2,703 (50.13)		0.012	8.850	38 (64.63)	2,719 (50.22)		0.095	4.982
Education level			14.285	0.017				10.831	0.041				3.994	0.394
0−11 yr	10 (0.96)	831 (14.76)				5 (4.78)	836 (14.67)				5 (6.15)	836 (14.61)
12 yr	48 (32.21)	2,003 (34.84)				28 (30.55)	2,023 (34.84)				20 (34.49)	2,031 (34.77)
13−15 yr	37 (32.14)	1,135 (21.76)				23 (34.57)	1,149 (23.09)				14 (28.81)	1,158 (23.20)
≥ 16 yr	39 (30.29)	1,404 (27.37)				23 (30.10)	1,420 (27.41)				16 (30.55)	1,427 (27.41)
Employment status			8.751	0.095				3.127	0.481				7.805	0.119
Unemployed	13 (9.47)	400 (7.62)				9 (10.50)	404 (7.62)				4 (8.06)	409 (7.66)
Employed	97 (69.66)	3,865 (70.70)				56 (66.48)	3,906 (70.73)				41 (74.01)	3,921 (70.63)
Homemaker	14 (11.24)	907 (16.62)				9 (14.49)	912 (16.51)				5 (6.79)	916 (16.59)
Student	10 (9.63)	202 (5.06)				5 (8.53)	207 (5.13)				5 (11.14)	207 (5.12)
Marital status			15.467	0.001				3.657	0.197				14.297	0.001
Married or living with a partner	80 (52.35)	3,565 (63.30)				49 (56.58)	3,596 (63.11)				31 (46.53)	3,614 (63.19)
Bereaved, separated, divorced	14 (6.47)	631 (10.06)				9 (7.39)	636 (10.00)				5 (5.20)	640 (10.02)
Never been married	40 (41.18)	1,181 (26.64)				21 (36.03)	1,200 (26.88)				19 (48.27)	1,202 (26.79)

Values are presented as mean ± standard error or number (%).

^aMonthly house income is presented in ten thousand Korean Won.

Table 2-1

Comorbid mental disorder prevalence based on lifetime alcoholism morbidity

Timeframe	Comorbid mental disorders	Alcohol use disorder-lifetime				Alcohol dependence-lifetime				Alcohol abuse-lifetime

		Positive	Negative	Statistics		Positive	Negative	Statistics		Positive	Negative	Statistics

				χ²	p			χ²	p			χ²	p
Lifetime	Depressive disorders	119 (19.42)	288 (6.21)	137.994	< 0.001	85 (24.71)	322 (6.61)	148.033	< 0.001	34 (13.24)	373 (7.43)	13.140	0.004
	Anxiety disorders	91 (13.66)	427 (8.78)	15.862	< 0.001	58 (15.79)	460 (8.92)	17.962	< 0.001	33 (11.17)	485 (9.24)	1.226	0.333
	Tobacco use disorders	175 (28.29)	334 (7.01)	297.713	< 0.001	122 (37.29)	387 (7.62)	330.891	< 0.001	53 (17.76)	456 (9.01)	24.802	< 0.001

Values are presented as number (estimated %).

Table 2-2

Comorbid mental disorder prevalence based on one-year alcoholism morbidity

Timeframe	Comorbid mental disorders	Alcohol use disorder-one-year				Alcohol dependence-one-year				Alcohol abuse-one-year

		Positive	Negative	Statistics		Positive	Negative	Statistics		Positive	Negative	Statistics

				χ²	p			χ²	p			χ²	p
One-year	Depressive disorders	21 (19.52)	73 (1.27)	272.745	< 0.001	16 (24.47)	78 (1.39)	254.903	< 0.001	5 (12.73)	89 (1.62)	43.267	< 0.001
	Anxiety disorders	13 (8.65)	168 (2.99)	14.761	0.001	6 (6.71)	175 (3.08)	3.543	0.076	7 (11.32)	174 (3.05)	13.480	0.001
	Tobacco use disorders	27 (21.89)	119 (2.21)	204.770	< 0.001	23 (32.64)	123 (2.27)	285.151	< 0.001	4 (7.16)	142 (2.68)	4.542	0.040

Values are presented as number (estimated %).

Table 3

Psychological trauma history depending on alcoholism morbidity

Alcoholism morbidity-timeframe	Psychological trauma history (+)	χ²	p value
Alcohol use disorder-lifetime		53.718	< 0.001
Positive	123 (17.22)
Negative	450 (8.26)
Alcohol dependence-lifetime		20.523	< 0.001
Positive	62 (16.16)
Negative	511 (7.79)
Alcohol abuse-lifetime		30.900	< 0.001
Positive	61 (18.46)
Negative	512 (8.78)
Alcohol use disorder-one-year		4.538	0.047
Positive	25 (14.38)
Negative	548 (9.16)
Alcohol dependence-one-year		3.906	0.096
Positive	14 (15.53)
Negative	559 (9.20)
Alcohol abuse-one-year		0.894	0.300
Positive	11 (12.80)
Negative	562 (9.25)

Values are presented as number (estimated %).

Table 4

Resilience depending on alcoholism morbidity

Timeframe	Comorbid mental disorders	n (%)	Connor-Davidson Resilience Scale	t	p value
Lifetime	Alcohol use disorder			4.486	< 0.001
	Negative	4,868 (88.43)	25.41 ± 0.20
	Positive	643 (11.57)	23.48 ± 0.42
	Alcohol dependence			5.345	< 0.001
	Negative	5,158 (93.76)	25.38 ± 0.20
	Positive	353 (6.24)	22.31 ± 0.56
	Alcohol abuse			0.699	0.485
	Negative	5,221 (94.67)	25.21 ± 0.20
	Positive	290 (5.33)	24.85 ± 0.51
One-year	Alcohol use disorder			3.850	< 0.001
	Negative	5,377 (97.39)	25.30 ± 0.20
	Positive	134 (2.61)	21.24 ± 1.04
	Alcohol dependence			4.654	< 0.001
	Negative	5,432 (98.49)	25.28 ± 0.20
	Positive	79 (1.51)	19.39 ± 1.25
	Alcohol abuse			1.159	0.247
	Negative	5,456 (98.90)	25.21 ± 0.20
	Positive	55 (1.10)	23.78 ± 1.23

Values are presented as number (%) or mean ± standard error.

Table 5

Logistic regression analysis

Dependent variable	B	SE	95% CI		t	df	p value	Exp (B)	95% CI of Exp (B)

			Lower limit	Upper limit					Lower limit	Upper limit
Lifetime alcohol use disorder	0.033	0.008	0.017	0.050	4.004	507	< 0.001	1.034	1.017	1.051
Lifetime alcohol dependence	0.048	0.010	0.028	0.068	4.748	507	< 0.001	1.049	1.029	1.070
Lifetime alcohol abuse	0.008	0.011	−0.013	0.028	0.730	507	0.466	1.008	0.987	1.029
One-year alcohol use disorder	0.053	0.015	0.023	0.082	3.541	507	< 0.001	1.054	1.024	1.085
One-year alcohol dependence	0.070	0.016	0.038	0.101	4.309	507	< 0.001	1.072	1.039	1.107
One-year alcohol abuse	0.022	0.024	−0.025	0.069	0.913	507	0.362	1.022	0.975	1.072

Adjusted covariates: age, gender, monthly household income, years of education, marital status, employment status, depressive disorders, anxiety disorders, nicotine use disorders, and psychological trauma.

SE, standard error; CI, confidence interval; df, degree of freedom; Exp, exponential function.

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