Long-Term Trends in Counseling for Stress and Depression Among Adults, 2009–2024, Considering the Impact of COVID-19 Pandemic: A Nationwide Representative Study in South Korea

Article information

Psychiatry Investig. 2026;23(4):556-575
Publication date (electronic) : 2026 April 6
doi : https://doi.org/10.30773/pi.2025.0463
1Center for Digital Health, Medical Science Research Institute, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, Republic of Korea
2Department of Biotechnology, Korea University College of Life Science and Biotechnology, Seoul, Republic of Korea
3Department of Precision Medicine, Kyung Hee University College of Medicine, Seoul, Republic of Korea
4Department of Regulatory Science, Kyung Hee University, Seoul, Republic of Korea
5Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
6Mass General Brigham Department of Anesthesiology, Massachusetts General Hospital, Boston, MA, USA
7Health Unit, Eni, Maputo, Mozambique
8Health Unit, Eni, San Donato Milanese, Italy
9Department of Pediatrics, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, Republic of Korea
10School of Health and Environmental Science, Korea University College of Health Science, Seoul, Republic of Korea
11Department of Health and Safety Convergence Science, Graduate School, Korea University, Seoul, Republic of Korea
Correspondence: Dong Keon Yon, MD, PhD Department of Pediatrics, Kyung Hee University College of Medicine, 23 Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea Tel: +82-2-961-0680, E-mail: yonkkang@gmail.com
Correspondence: Jiseung Kang, PhD School of Health and Environmental Science, Korea University College of Health Science, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea Tel: +82-2-3290-5682, E-mail: wltmd1006@gmail.com
*These authors contributed equally to this work.
Received 2025 December 17; Revised 2026 January 14; Accepted 2026 January 27.

Abstract

Objective

Despite the impact of the COVID-19 pandemic on global mental health, few studies have examined changes in the demand for mental health counseling over time. This study investigated 16-year national trends in counseling for stress and depression in South Korea, with a focus on the pandemic’s impact and evolving population-level risk factors.

Methods

This study analyzed trends in stress and depression counseling using data from 3,195,912 Korean adults in the Korea Community Health Survey (2009–2024). Counseling was defined by self-reported responses. The period was categorized as pre-pandemic (2009–2019), intra-pandemic (2020–2022), and post-pandemic (2023–2024). Weighted logistic regression was used to assess prevalence trends, high-risk groups, and changes in risk patterns over time.

Results

The prevalence of counseling for stress steadily increased from 1.54% (2009–2010) to 2.16% (2017–2019), peaked at 3.06% in 2022 during the pandemic, and remained elevated at 2.97% in 2023–2024. Depression counseling showed a similar pattern. Higher rates were consistently observed among young adults, women, those with poor self-rated health, and individuals with sleep <6 or ≥8 hours. Notably, while low education was a key pre-pandemic risk factor, counseling increased more among highly educated individuals during the pandemic.

Conclusion

The COVID-19 pandemic affected mental health counseling in South Korea and led to the emergence of new at-risk groups. Sustained high counseling rates among young adults and the highly educated highlight the need for targeted, population-specific interventions.

INTRODUCTION

Mental disorders are one of the top ten leading causes of disease burden [1]. According to the Global Burden of Disease Study 2021, the age-standardized incidence rate of mental disorders has increased by 15.23% between 1990 and 2021 [2]. In South Korea, the burden of mental health conditions has also grown steadily, with increasing rates of stress, depression, and suicide representing critical public health concerns [3]. Notably, South Korea has the highest rate among Organization for Economic Co-operation and Development (OECD) countries, about 2.4 times higher than the average suicide rate of other OECD countries [4].

The COVID-19 pandemic caused significant disruptions in daily life, adversely affecting socioeconomic stability, education, employment, and interpersonal relationships [5,6]. These changes intensified psychological distress across various segments of the population, underscoring the urgent need to address mental health [7]. Although numerous global studies have examined the acute psychological impacts of the pandemic, few have assessed how these patterns have evolved across the distinct phases of the pandemic and into the post-pandemic. In South Korea, our prior study also aimed to investigate the impact of COVID on the trends in prevalence of counseling of depression and stress, but included data only up to 2021, thus capturing only the early phase of the pandemic [8].

Herein, we investigated trends in mental health counseling for stress and depression in South Korea from 2009 to 2024. By dividing the study period into pre-pandemic (2009–2019), intra-pandemic (2020–2022), and post-pandemic (2023–2024), we examined temporal changes in counseling utilization and assessed associated demographic, socioeconomic, behavioral, and health-related factors. The findings of this study are anticipated to provide critical evidence to inform targeted public health interventions and guide future mental health policy development.

METHODS

Study design

In this study, data were obtained from the Korea Community Health Survey (KCHS) [9]. The Korea Disease Control and Prevention Agency (KDCA) has conducted an anonymous, computer-assisted personal interview survey every year since 2008, targeting individuals aged 19 years and older, to assess their health status and behaviors. After excluding participants with missing data on key covariates, a total of 3,195,912 participants were included in the final analysis (Supplementary Table 1 and Supplementary Figure 1). To assess trends in stress and depression from 2009 to 2024 and evaluate the impact of COVID-19, the study period was divided into three phases: pre-pandemic (2009–2019), intra-pandemic (2020–2022), and post-pandemic (2023–2024), based on the timeline of the first confirmed case in January 2020 and the easing of restrictions by the end of 2022 [10,11]. The study protocol was approved by the Institutional Review Board of the KDCA (2010-02CON-22-P, 2011-05CON04-C, 2012-07CON-01-2C, 2013-06EXP-01-3C, 2014-08EXP-09-4CA, and 2016-10-01-TA) for primary data collection and Kyung Hee University (KHSIRB-25-125) for secondary analysis. The KCHS data for the years covered by this study were anonymized, and written informed consent was obtained from all participants before they participated in the study. Ethical considerations were upheld, adhering to the Declaration of Helsinki. Furthermore, the KCHS provides public access to its data, which can be utilized as a valuable resource for diverse epidemiological investigations.

Outcome measures

We used counseling experience related to depression or stress as an indicator to assess mental health status. This was measured using the following questions: “Have you received professional counseling due to stress experienced in your usual daily life?” and “In the past year, have you received professional counseling due to feeling sadness or hopelessness for two consecutive weeks or more, to the extent that it interfered with your daily life?”

Covariates

The covariates included age (19–30, 31–40, 41–50, 51–60, 61–70, and ≥71 years), sex (male and female), region of residence (urban and rural) [12], level of education (elementary school or lower, middle school, high school, and college of higher education), household income (lowest, second, third, and highest quartile), smoking status (smoker, ex-smoker, and nonsmoker), alcohol consumption (<2, 2–12, and ≥13 days/month), self-rated-health (SRH; high, middle, and low), average sleep duration per day (<6, 6–6.9, 7–7.9, and ≥8 hours/day) and body mass index (BMI: underweight [<18.5 kg/m2], normal weight [18.5–22.9 kg/m2], overweight [23.0–24.9 kg/m2], and obese [≥25 kg/m2]) [13]. BMI categories were defined according to the WHO-Asia and Korean Society for the Study of Obesity criteria [14]. In addition, SRH is a subjective assessment that divides the perception of personal health into three levels: high, middle, and low [15].

Data analyses

This study utilized data from the KCHS spanning 2009 to 2024. The prevalence of counseling for stress and depression was estimated annually as the weighted proportion of respondents reporting such services, accounting for the complex survey design. Weighted multivariate logistic regression models were used to estimate weighted odds ratios (wORs) and their corresponding 95% confidence intervals (CIs), in order evaluate factors associated with the prevalence of counseling for stress and depression [16]. To assess temporal trends, linear regression models were applied to estimate absolute differences in β coefficients across predefined time periods. Analyses were conducted for the overall study population and stratified subgroups based on relevant risk factors. Additionally, wORs were examined across the pre-pandemic, intra-pandemic, and postpandemic periods, and comparisons were made to identify period-specific patterns and disparities in counseling utilization [17]. All statistical analyses were performed using SAS software (version 9.4; SAS Institute). A p-value of <0.05 (two-sided) was considered statistically significant.

RESULTS

Table 1 presents the basic characteristics of the study population participating in the KCHS from 2009 to 2024. We conducted an in-depth analysis of a nationally representative sample comprising 3,195,912 South Korean adults who provided complete responses to the questionnaire. Females accounted for the larger proportion of participants, comprising 53.61% of the total sample (n=1,713,173).

General characteristics of Korean based on data obtained from the KCHS, 2009 to 2024 (N=3,195,912)

Table 2 and Figure 1 present trends in the prevalence of counseling for stress across the pre-, intra-, and post-pandemic. Overall, the prevalence increased during pre- and intra-pandemic and remained elevated in the post-pandemic. A particularly notable increase was observed among individuals aged 19–30 years at the onset of the pandemic, with the prevalence rising from 2.51% (95% CI, 2.37 to 2.65) in 2017– 2019 to 3.31% (3.06 to 3.57) in 2020. In addition, the prevalence of counseling for stress was consistently higher among females compared to males. At the beginning of the intra-pandemic, individuals with low SRH exhibited a marked increase in the prevalence of counseling for stress. Notably, the gap in stress counseling prevalence between individuals with and without diabetes narrowed during the pandemic and reversed in the post-pandemic. In 2017–2019, individuals with diabetes had a higher prevalence (2.50% [95% CI, 2.32 to 2.67]) than those without diabetes (2.13% [2.07 to 2.18]). By 2022, the rates converged at 3.06% in both groups. In 2023–2024, the trend reversed, with a slightly higher prevalence observed among individuals without diabetes (2.98% [95% CI, 2.88 to 3.08]) than among those with diabetes (2.90% [2.64 to 3.15]). Lastly, a higher prevalence of counseling for stress was generally observed among individuals reporting an average sleep duration of less than 6 hours (Supplementary Table 2).

Trends in the prevalence of counseling for stress throughout pre-, intra-, and post-pandemic (weighted % [95% CI]), based on data obtained from the KCHS

Figure 1.

Nationwide trends in the prevalence of counseling for stress (A and B) and depression (A and C) in pre-, intra-, and post-pandemic. SRH, self-rated health.

Nationwide trends in the prevalence of counseling for stress (A and B) and depression (A and C) in pre-, intra-, and post-pandemic. SRH, self-rated health.

Table 3 and Figure 1 present trends in the prevalence of counseling for depression during pre-, intra-, and post-pandemic. Overall, the prevalence exhibited an upward trend during the pre- and intra-pandemic and sustained high levels in the post-pandemic. At the onset of the intra-pandemic, the prevalence of counseling for depression also increased, particularly among individuals aged 19–30 years. In this group, the prevalence rose from 1.36% (95% CI, 1.26 to 1.46) in 2017– 2019 to 1.83% (1.64 to 2.02) in 2020. Consistent with the pattern observed for stress, females showed a consistently higher prevalence of counseling for depression compared to males throughout the study period. Additionally, underweight individuals reported a higher prevalence of counseling for stress relative to other BMI categories. Among underweight individuals, while the prevalence of counseling for stress continued to increase after the pandemic, the prevalence of counseling for depression declined from 3.26% (95% CI, 2.80 to 3.72) in 2022 to 2.67% (2.26 to 3.07) in 2023–2024. The βdiff between intra- and post-pandemic was significant at -1.10% (95% CI, -1.81 to -0.39) (Supplementary Table 3). Individuals in the lowest household income group reported a higher prevalence of counseling for depression compared to those in higher income groups. Moreover, at the beginning of the pandemic in 2020, individuals with low SRH exhibited a notable increase in the prevalence of counseling for depression, rising from 4.10% (95% CI, 3.93 to 4.27) in 2017–2019 to 5.53% (5.12 to 5.95) in 2020. In addition, a higher prevalence of counseling for depression was generally observed among individuals who reported an average sleep duration of less than 6 hours.

Trends in the prevalence of counseling for depression throughout pre-, intra-, and post-pandemic (weighted % [95% CI]), based on data obtained from the KCHS

Table 4 shows the wORs from an analysis conducted to investigate trends in counseling for stress and depression. Counseling rates increased significantly during the pandemic compared to the pre-pandemic. In contrast, no significant differences were observed between the intra-pandemic and postpandemic. When compared to the pre-pandemic, the rates of counseling for both stress and depression increased significantly during the pandemic among individuals aged 19–30 years, those classified as underweight and current smokers. Specifically, among individuals aged 19–30 years, the wORs were 2.07 (95% CI, 1.95 to 2.19) for stress and 2.23 (2.07 to 2.41) for depression. In the underweight group, the wORs were 1.73 (95% CI, 1.58 to 1.90) for stress and 1.83 (1.63 to 2.06) for depression. Among smokers, the wORs were 1.89 (95% CI, 1.79 to 1.99) for stress and 2.00 (1.87 to 2.15) for depression.

Weighted ORs as a trend of counseling for stress and counseling for depression rates, based on data obtained from the KCHS

Table 5 and Figure 2 show the risk factors associated with vulnerability to counseling for stress and depression, expressed as the wOR. Female, urban residents, and individuals with low household income were identified as key vulnerable groups. During the pre-pandemic period, individuals with the lowest level of education (elementary school or below) were the most vulnerable compared to those with a college education or higher (1.27 [95% CI, 1.22 to 1.31]). However, since the onset of the intra-pandemic, this trend reversed, and the group with a college or higher education has become the most vulnerable to stress. Age-related shifts were also notable. Prior to the pandemic, individuals aged 19–30 were not considered a high-risk group for depression. However, they became significantly more vulnerable during the intra-pandemic (95% CI, 1.36 [1.24 to 1.48]) and post-pandemic (1.39 [1.20 to 1.59]) compared to those aged ≥71 years. Across all time periods, individuals with low SRH and those with average sleep durations of fewer than 6 hours or more than 8 hours per day remained the most vulnerable groups.

Ratio of weighted ORs for risk factors for the vulnerable group of counseling for stress and depression pre-, intra-, and post-pandemic, based on data obtained from the KCHS

Figure 2.

Ratio of weighted ORs for risk factors for the vulnerable group of counseling for depression pre-, intra-, and post-pandemic, based on data obtained from the KCHS. BMI, body mass index; SRH, self-rated health; OR, odds ratio; CI, confidence interval; ref, reference; KCHS, Korea Community Health Survey.

DISCUSSION

Key finding

This study analyzed trends in counseling for stress and depression in South Korea from 2009 to 2024. The overall prevalence of counseling for stress and depression had been steadily increasing even before the pandemic and has not returned to pre-pandemic levels after its end. In other words, while the overall trend was not significantly affected by the pandemic, certain subgroups were notably impacted by it. Both types of counseling showed a sharp increase among young adults (aged 19–30) during the intra-pandemic. In addition, individuals with low SRH and abnormal sleep duration were identified as a risk factor for both stress and depression across all periods. Notably, a reversal in the trend of counseling for stress was observed based on diabetes status. Also, prior to the pandemic, those with an elementary school education or lower were the most vulnerable group to stress, but after the pandemic, the most vulnerable group shifted to those with a college education or higher.

Comparison of previous studies

Other studies to date have shown mixed findings regarding the mental health impact of the COVID-19 pandemic [18,19]. Among U.S. adults, the prevalence of depression was 25.2% before the COVID-19 pandemic, rose to 37.6% during the pandemic, and subsequently declined to 29.5% in the postpandemic [18,19]. Nevertheless, it remains elevated compared to the pre-pandemic level [18,19]. In addition, a survey conducted in the U.S reported that 71.2% of participants experienced increased stress levels during the pandemic [20]. However, in the Netherlands, the prevalence of depression symptoms was 16.8% in 2019 and 17.0% in 2020, indicating that the pandemic did not lead to a short-term increase in depression [21]. According to a study that examined changes in depressive symptoms in China between 2019 and 2020, approximately 70% of participants experienced no change in their symptoms, while around 15% reported either worsening or improvement. Subgroup analysis further revealed that, except for the male group, the number of individuals whose depressive symptoms improved exceeded those whose symptoms worsened [22]. In a study con-ducted in China, 82.9% participants reported low to mild stress in 2020 [23].

These findings likely reflect not only differences in underlying levels of psychological distress across countries but also variation in health system organization, access pathways to mental health services, and cultural norms surrounding helpseeking [24]. In this context, South Korea represents a distinct setting characterized by relatively strong stigma toward mental illness and rapid expansion of mental health support and remote counseling during the pandemic [25,26]. Most previous studies focused primarily on trends during the pandemic (2020– 2022), with depression, a representative mental illness, as the main outcome. In contrast, this study examined the relationship between COVID-19 pandemic and mental health in South Korea, not only intra-but also post-pandemic, incorporating both depression and stress as key outcomes, allowing a more comprehensive assessment of how beyond the acute phase of the pandemic.

Plausible underlying mechanisms

The overall prevalence of counseling for stress and depression had been steadily increasing even before the pandemic and has not returned to pre-pandemic levels since its end. Counseling utilization reflects not only underlying mental health needs but also access to care, mental health awareness, stigma, service availability, and help-seeking behavior, all of which plausibly changed during and after the pandemic [27]. Consequently, increases in counseling utilization should not be interpreted solely as indicators of worsening psychological distress; they may also reflect improved access to services or reduced stigma surrounding mental health care. In South Korea, the pandemic period was accompanied by changes in mental health service delivery, including expanded use of remote and tele-counseling and national efforts to strengthen psychological support, which may have influenced the observed utilization patterns [25,28].

Regardless of periods, low SRH and abnormal sleep duration were the key risk factors. Previous studies have shown that individuals with low SRH experience poorer physical and mental quality of life and are more prone to negative thinking, which increases life dissatisfaction, a factor closely linked to depressive symptoms [29,30]. In addition, those who do not get sufficient sleep are nearly three times more likely to experience frequent psychological distress compared to those who sleep adequately [31]. In our study, individuals with an average sleep duration of eight hours or more also emerged as a vulnerable group for counseling for depression. This may be attributed to lower levels of physical activity during prolonged sleep durations. Increased levels of neurotransmitters such as dopamine and serotonin, enhanced endorphin release, and the facilita-tion of brain aminergic synaptic transmission are known to reduce the risk of depression [32]. Therefore, long sleepers who spend less time engaging in physical activity may be more likely to experience depressive symptoms [32].

Notably, a prominent change was observed in counselling utilization patterns across educational groups following the onset of the COVID-19 pandemic. After the pandemic, the prevalence of counseling for stress significantly increased among highly educated individuals. This may be attributed not only to shifts in underlying vulnerability but also to differences in help-seeking behavior, access to counselling services, and mental health awareness across socioeconomic strata [33]. Highly educated individuals are more likely to be employed in whitecolor professionals and may have experienced substantial changes in work during the pandemic, including a rapid transition to remote work [34]. From the perspective of the Job Demand-Resources model, the sudden shift to remote work and the accompanying increase in job demands during the pandemic may have heightened the risk of burnout among highly educated individuals and improved access to counselling. At the same time, reduced organizational peer support due to prolonged remote work may have further intensified their stress [35].

Strengths and limitations

This study has several limitations. First, as a cross-sectional study, this research could not account for the temporal order of events, limiting the ability to infer causality. However, our dataset from 2009 to 2024, which includes about 3 million individuals, is nationally representative. Second, mental health status related to stress and depression was assessed using selfreported counseling experience rather than standardized clinical diagnostic tools. Although self-reported stress is widely used as a subjective measure, prior studies have suggested that counseling experience may serve as a more objective proxy for clinically significant psychological distress, particularly in population-based health surveys [36]. Third, this study classified insufficient and excessive sleep as less than 6 hours and more than 8 hours per day, respectively. This approach may not have adequately reflected differences in optimal sleep duration by age group. Given that organizations such as the National Sleep Foundation have established age-specific sleep guidelines, future research should adopt more refined sleep classifications that incorporate age-based recommendations. Lastly, due to the absence of data from 2023, the post-pandemic in this analysis was limited to the year 2024, restricting the ability to evaluate long-term trends following the COVID-19 pandemic.

Despite these limitations, this study has considerable strengths. This study utilized data from 2009 to 2024, allowing for a comprehensive assessment of the impact of the COVID-19 pandemic on mental health trends. By incorporating key factors critically affected during the pandemic, this study provides valuable insights into the evolving patterns and determinants of mental health counseling both during and after the pandemic, over a span of more than a decade.

Clinical and policy implications

Even before the COVID-19 pandemic, certain population groups already exhibited relatively high vulnerability in terms of mental health counseling. In the current post-pandemic context, the demand for mental health support remains high, highlighting the need for responsive policy interventions. The World Health Organization launched the global campaign “Depression: Let’s Talk” in 2017 to raise awareness about depression and encourage help-seeking behaviors. However, media-based awareness efforts have shown limited long-term impact on behavioral change compared to contact-based interventions [37]. In South Korea, stigma-related help avoidance remains a significant barrier to mental health service utilization [38]. Accordingly, rather than relying solely on media campaigns, there is a growing need to expand community-based and participatory anti-stigma programs. In parallel, the widespread shift to remote work highlights the urgency of implementing workplace-based mental health initiatives to address the psychological burdens associated with changing work environments. Moreover, given that low SRH and abnormal sleep durations (<6 or ≥8 hours) were consistently associated with mental health problems across all periods, it is essential to incorporate routine assessments of SRH and sleep patterns into primary care. Establishing a systematic referral pathway to mental health counseling services would facilitate early detection and timely intervention for at-risk individuals.

Conclusion

This study examined the impact of the COVID-19 pandemic on counseling trends for stress and depression in South Korea, and despite the significant expansion of national-level mental health infrastructure during the pandemic, the counseling rates for stress and depression have remained largely unchanged even after the pandemic officially ended. In particular, young adults, low SRH, highly educated individuals, and those with extreme sleep durations constituted vulnerable groups. Enhancing the capacity of primary care to identify individuals in need and ensure timely access to mental health counseling will be critical to establishing a more responsive and forwardlooking mental health care system.

Supplementary Materials

The Supplement is available with this article at https://doi.org/10.30773/pi.2025.0463.

Supplementary Table 1.

General characteristics of Korean based on data obtained from the KCHS, 2009 to 2024 (N=3,195,912)

pi-2025-0463-Supplementary-Table-1.pdf
Supplementary Table 2.

β-coefficients and β-differences in counseling for stress trends across pre-, intra-, and post-pandemic periods (weighted % [95% CI])

pi-2025-0463-Supplementary-Table-2.pdf
Supplementary Table 3.

β-coefficients and β-differences in counseling for depression trends across pre-, intra-, and post-pandemic periods (weighted % [95% CI])

pi-2025-0463-Supplementary-Table-3.pdf
Supplementary Figure 1.

Study population flowchart. SRH, self-rated health; BMI, body mass index.

pi-2025-0463-Supplementary-Fig-1.pdf

Notes

Availability of Data and Material

The data are available on reasonable request. Study protocol, statistical code: available from DKY (email: yonkkang@gmail.com). Data set: available from the Korea Disease Control and Prevention Agency (KDCA) and the Ministry of Education through a data use agreement.

Conflicts of Interest

The authors have no potential conflicts of interest to disclose.

Author Contributions

Conceptualization: Seungjae Byun, Kyeongeun Kim, Dong Keon Yon, Jiseung Kang. Data curation: Seungjae Byun, Kyeongeun Kim, Dong Keon Yon, Jiseung Kang. Formal analysis: Seungjae Byun, Kyeongeun Kim, Dong Keon Yon, Jiseung Kang. Funding acquisition: Dong Keon Yon. Investigation: Seungjae Byun, Kyeongeun Kim, Dong Keon Yon, Jiseung Kang. Methodology: Seungjae Byun, Kyeongeun Kim, Dong Keon Yon, Jiseung Kang. Project administration: Dong Keon Yon, Jiseung Kang. Resources: Dong Keon Yon. Software: Dong Keon Yon. Supervision: Dong Keon Yon, Jiseung Kang. Visualization: Seungjae Byun, Kyeongeun Kim, Dong Keon Yon, Jiseung Kang. Writing—original draft: Seungjae Byun, Kyeongeun Kim, Dong Keon Yon, Jiseung Kang. Writing—review & editing: Hyesu Jo, Christa J Nehs, Damiano Pizzol, Dong Keon Yon, Jiseung Kang.

Funding Statement

This research was supported by the Ministry of Science and ICT (RS-2024-00509257 and IITP-2024-RS-2024-00438239) and the Ministry of Health & Welfare (RS-2025-02220492), Republic of Korea. The funders had no role in study design, data collection, data analysis, data interpretation, or writing of the report.

Acknowledgments

None

References

1. Walker ER, McGee RE, Druss BG. Mortality in mental disorders and global disease burden implications: a systematic review and metaanalysis. JAMA Psychiatry 2015;72:334–341.
2. Fan Y, Fan A, Yang Z, Fan D. Global burden of mental disorders in 204 countries and territories, 1990-2021: results from the global burden of disease study 2021. BMC Psychiatry 2025;25:486.
3. Moon DU, Kim H, Jung J, Han K, Jeon HJ. Suicide risk and living alone with depression or anxiety. JAMA Netw Open 2025;8e251227.
4. Kim GE, Jo MW, Shin YW. Increased prevalence of depression in South Korea from 2002 to 2013. Sci Rep 2020;10:16979.
5. Pancheshnikov A, Cuneo CN, Matias WR, Cázares-Adame R, Santos López AG, Paxton RM, et al. Case studies in adaptation: centring equity in global health education during the COVID-19 pandemic and beyond. BMJ Glob Health 2023;8e011682.
6. Cho J, Kim TH, Oh J, Lee S, Kim K, Park J, et al. Association between social engagement frequency and the risk of depression in South Korea, the United States, and the United Kingdom: multinational evidence from longitudinal studies of aging. J Gerontol B Psychol Sci Soc Sci 2025;80:gbaf036.
7. Ettman CK, Abdalla SM, Cohen GH, Sampson L, Vivier PM, Galea S. Prevalence of depression symptoms in US adults before and during the COVID-19 pandemic. JAMA Netw Open 2020;3e2019686.
8. Kang J, Park J, Lee H, Lee M, Kim S, Koyanagi A, et al. National trends in depression and suicide attempts and COVID-19 pandemic-related factors, 1998-2021: a nationwide study in South Korea. Asian J Psychiatr 2023;88:103727.
9. Lee HE, Kim YG, Jeong JY, Kim DH. Data resource profile: the Korean Community Health Status Indicators (K-CHSI) database. Epidemiol Health 2023;45e2023016.
10. Pierce M, Hope H, Ford T, Hatch S, Hotopf M, John A, et al. Mental health before and during the COVID-19 pandemic: a longitudinal probability sample survey of the UK population. Lancet Psychiatry 2020;7:883–892.
11. Sachs JD, Karim SSA, Aknin L, Allen J, Brosbøl K, Colombo F, et al. The Lancet Commission on lessons for the future from the COVID-19 pandemic. Lancet 2022;400:1224–1280.
12. Kim SY. Nationwide COVID-19 vaccination coverage and COVID-19 incidence in South Korea, January 2022: a national official report. Life Cycle 2022;2e2.
13. Son Y, Park J, Choi Y, Kim H, Kang J, Smith L, et al. National trends of allergic diseases and pandemic-related factors among individuals with obesity in South Korea: a nationwide representative serial study, 2005-2021. Heliyon 2024;10e29921.
14. Kim SY, Kim MS, Sim S, Park B, Choi HG. Association between obesity and falls among Korean adults: a population-based cross-sectional study. Medicine (Baltimore) 2016;95e3130.
15. Kim M, Khang YH, Kang HY, Lim HK. Educational inequalities in self-rated health in Europe and South Korea. Int J Environ Res Public Health 2020;17:4504.
16. Kim K, Lee K, Son Y, Park S, Udeh R, Kang J, et al. National trends in influenza vaccination rates in South Korea before and during the COVID-19 pandemic, 2011-2022. Biomed Environ Sci 2025;38:1044–1057.
17. Woo HG, Park S, Yon H, Lee SW, Koyanagi A, Jacob L, et al. National trends in sadness, suicidality, and COVID-19 pandemic-related risk factors among South Korean adolescents from 2005 to 2021. JAMA Netw Open 2023;6e2314838.
18. Shah AD, Laternser C, Tatachar P, Duong P. The COVID-19 pandemic and its effects on mental health-a before, during, and after comparison using the U.S. census Bureau’s Household Pulse Survey. Int J Environ Res Public Health 2024;21:1306.
19. Jiang Y, Deng W, Zhao M. Influence of the COVID-19 pandemic on the prevalence of depression in U.S. adults: evidence from NHANES. Sci Rep 2025;15:3107.
20. Wang X, Hegde S, Son C, Keller B, Smith A, Sasangohar F. Investigating mental health of US college students during the COVID-19 pandemic: cross-sectional survey study. J Med Internet Res 2020;22e22817.
21. van der Velden PG, Contino C, Das M, van Loon P, Bosmans MWG. Anxiety and depression symptoms, and lack of emotional support among the general population before and during the COVID-19 pandemic. A prospective national study on prevalence and risk factors. J Affect Disord 2020;277:540–548.
22. Huang Y, Wang Y, Wang H, Liu Z, Yu X, Yan J, et al. Prevalence of mental disorders in China: a cross-sectional epidemiological study. Lancet Psychiatry 2019;6:211–224.
23. Zhang M, Zhao X, Liu Y, Yang J. Perceived stress and possible stressors in the general public in China during the COVID-19 pandemic. Ethics Med Public Health 2021;18:100695.
24. Office of the Surgeon General (US); Center for Mental Health Services (US); National Institute of Mental Health (US). Mental Health: Culture, Race, and Ethnicity: A Supplement to Mental Health: A Report of the Surgeon General Rockville: Substance Abuse and Mental Health Services Administration (US); 2001.
25. Lee E, Kim G. Comparative Study of Mental Health Care Availability and Stigma in the United States and South Korea. Research Archive of Rising Scholars [Preprint]. August 3, 2025 Available at: https://doi.org/10.58445/rars.2831. Accessed August 4, 2025.
26. Kim KH, Lee SM, Hong M, Han KM, Paik JW. Trends in telemedicine utilization for mental illness during the COVID-19 pandemic: an analysis of a nationwide database in Korea. BMC Psychiatry 2023;23:777.
27. Kukoyi O, Orok E, Oluwafemi F, Oluwadare T, Oni O, Bamitale T, et al. Factors affecting the utilization of mental health services among undergraduate students in a Nigerian University. Heliyon 2022;8e11476.
28. Hyun J, You S, Sohn S, Kim SJ, Bae J, Baik M, et al. Psychosocial support during the COVID-19 outbreak in Korea: activities of multidisciplinary mental health professionals. J Korean Med Sci 2020;35e211.
29. Ambresin G, Chondros P, Dowrick C, Herrman H, Gunn JM. Self-rated health and long-term prognosis of depression. Ann Fam Med 2014;12:57–65.
30. Muhammad T, Skariah AE, Kumar M, Srivastava S. Socioeconomic and health-related inequalities in major depressive symptoms among older adults: a Wagstaff’s decomposition analysis of data from the LASI baseline survey, 2017-2018. BMJ Open 2022;12e054730.
31. Roberts RE, Duong HT. The prospective association between sleep deprivation and depression among adolescents. Sleep 2014;37:239–244.
32. Zhai L, Zhang H, Zhang D. Sleep duration and depression among adults: a meta-analysis of prospective studies. Depress Anxiety 2015;32:664–670.
33. Halme M, Rautava P, Sillanmäki L, Sumanen M, Suominen S, Vahtera J, et al. Educational level and the use of mental health services, psychotropic medication and psychotherapy among adults with a history of physician diagnosed mental disorders. Int J Soc Psychiatry 2023;69:493–502.
34. Baek SU, Kim MS, Lim MH, Kim T, Yoon JH, Won JU. Characteristics and socio-demographic distribution of precarious employment among Korean wage workers: a proposition of multidimensional approach using a summative score. Saf Health Work 2023;14:476–482.
35. Pham M, Nguyen LT, Nguyen ATT, Nguyen AV. The interplay of incivility, peer support, and psychological capital in higher education. Sci Rep 2025;15:21569.
36. Wang PS, Lane M, Olfson M, Pincus HA, Wells KB, Kessler RC. Twelve-month use of mental health services in the United States: results from the National Comorbidity Survey Replication. Arch Gen Psychiatry 2005;62:629–640.
37. Corrigan PW, Morris SB, Michaels PJ, Rafacz JD, Rüsch N. Challenging the public stigma of mental illness: a meta-analysis of outcome studies. Psychiatr Serv 2012;63:963–973.
38. Jang J, Lee SA, Kim W, Choi Y, Park EC. Factors associated with mental health consultation in South Korea. BMC Psychiatry 2018;18:17.

Article information Continued

Figure 1.

Nationwide trends in the prevalence of counseling for stress (A and B) and depression (A and C) in pre-, intra-, and post-pandemic. SRH, self-rated health.

Nationwide trends in the prevalence of counseling for stress (A and B) and depression (A and C) in pre-, intra-, and post-pandemic. SRH, self-rated health.

Figure 2.

Ratio of weighted ORs for risk factors for the vulnerable group of counseling for depression pre-, intra-, and post-pandemic, based on data obtained from the KCHS. BMI, body mass index; SRH, self-rated health; OR, odds ratio; CI, confidence interval; ref, reference; KCHS, Korea Community Health Survey.

Table 1.

General characteristics of Korean based on data obtained from the KCHS, 2009 to 2024 (N=3,195,912)

Variables Total 2009–2010 2011–2013 2014–2016 2017–2019 2020 2021 2022 2023–2024
Overall, N 3,195,912 412,288 612,113 645,296 634,822 218,402 222,275 225,539 225,177
Weighted rate (95% CI)
 Age (yr)
  19–30 18.73 (18.65 to 18.81) 21.81 (21.61 to 22.02) 20.35 (20.19 to 20.51) 19.27 (19.12 to 19.43) 18.78 (18.62 to 18.94) 18.36 (18.10 to 18.63) 17.99 (17.73 to 18.26) 17.64 (17.37 to 17.91) 16.44 (16.17 to 16.72)
  31–40 17.88 (17.79 to 17.97) 22.54 (22.29 to 22.78) 21.30 (21.11 to 21.49) 19.32 (19.15 to 19.50) 17.60 (17.42 to 17.77) 16.66 (16.37 to 16.96) 16.23 (15.93 to 16.53) 15.59 (15.31 to 15.87) 15.17 (14.89 to 15.45)
  41–50 20.22 (20.13 to 20.30) 22.61 (22.40 to 22.82) 22.33 (22.16 to 22.49) 21.64 (21.47 to 21.80) 20.49 (20.32 to 20.66) 19.45 (19.17 to 19.74) 19.07 (18.78 to 19.36) 18.70 (18.42 to 18.98) 18.27 (17.98 to 18.56)
  51–60 19.06 (18.98 to 19.13) 15.91 (15.74 to 16.07) 18.18 (18.04 to 18.32) 19.55 (19.41 to 19.69) 19.83 (19.69 to 19.98) 19.77 (19.52 to 20.02) 19.59 (19.35 to 19.83) 19.51 (19.27 to 19.75) 19.50 (19.25 to 19.75)
  61–70 13.23 (13.17 to 13.30) 10.12 (9.99 to 10.26) 10.38 (10.27 to 10.49) 11.10 (10.99 to 11.22) 12.57 (12.45 to 12.69) 13.79 (13.57 to 14.01) 14.47 (14.24 to 14.70) 15.59 (15.37 to 15.82) 16.71 (16.48 to 16.95)
  ≥71 10.89 (10.82 to 10.95) 7.01 (6.90 to 7.13) 7.47 (7.37 to 7.56) 9.11 (9.01 to 9.22) 10.74 (10.62 to 10.85) 11.96 (11.75 to 12.18) 12.65 (12.42 to 12.88) 12.97 (12.75 to 13.20) 13.91 (13.67 to 14.14)
 Sex
  Male 50.00 (49.94 to 50.07) 50.03 (49.88 to 50.18) 50.47 (50.34 to 50.60) 50.29 (50.17 to 50.41) 50.22 (50.09 to 50.35) 49.90 (49.68 to 50.12) 49.80 (49.58 to 50.02) 49.73 (49.51 to 49.95) 49.67 (49.44 to 49.89)
  Female 50.00 (49.93 to 50.06) 49.97 (49.82 to 50.12) 49.53 (49.40 to 49.66) 49.71 (49.59 to 49.83) 49.78 (49.65 to 49.91) 50.10 (49.88 to 50.32) 50.20 (49.98 to 50.42) 50.27 (50.05 to 50.49) 50.33 (50.11 to 50.56)
 Region of residence
  Urban 45.19 (44.99 to 45.39) 47.40 (46.65 to 48.14) 47.15 (46.64 to 47.66) 46.15 (45.65 to 46.65) 45.19 (44.69 to 45.70) 44.23 (43.31 to 45.15) 44.20 (43.29 to 45.11) 44.17 (43.28 to 45.05) 43.76 (42.89 to 44.62)
  Rural 54.81 (54.61 to 55.01) 52.60 (51.86 to 53.35) 52.85 (52.34 to 53.36) 53.85 (53.35 to 54.35) 54.81 (54.30 to 55.31) 55.77 (54.85 to 56.69) 55.80 (54.89 to 56.71) 55.83 (54.95 to 56.72) 56.24 (55.38 to 57.11)
 BMI group*
  Underweight 4.75 (4.71 to 4.79) 5.75 (5.65 to 5.85) 5.56 (5.48 to 5.64) 5.16 (5.09 to 5.24) 4.54 (4.47 to 4.61) 4.13 (4.02 to 4.24) 4.38 (4.26 to 4.50) 4.57 (4.45 to 4.69) 4.20 (4.09 to 4.32)
  Normal 42.66 (42.57 to 42.74) 48.04 (47.82 to 48.25) 46.77 (46.60 to 46.95) 44.94 (44.77 to 45.11) 40.87 (40.70 to 41.05) 40.79 (40.50 to 41.08) 40.78 (40.49 to 41.07) 40.68 (40.40 to 40.96) 39.95 (39.67 to 40.24)
  Overweight 23.76 (23.69 to 23.84) 23.68 (23.50 to 23.86) 23.64 (23.49 to 23.78) 23.74 (23.60 to 23.88) 23.67 (23.53 to 23.82) 24.05 (23.81 to 24.29) 24.08 (23.84 to 24.33) 23.60 (23.37 to 23.84) 23.61 (23.37 to 23.85)
  Obese 28.83 (28.75 to 28.92) 22.54 (22.35 to 22.72) 24.02 (23.88 to 24.17) 26.16 (26.01 to 26.31) 30.92 (30.75 to 31.08) 31.03 (30.74 to 31.31) 30.76 (30.49 to 31.04) 31.15 (30.88 to 31.42) 32.24 (31.96 to 32.52)
 Education
  Elementary school or lower education 11.39 (11.33 to 11.46) 14.66 (14.47 to 14.85) 12.56 (12.42 to 12.69) 11.72 (11.59 to 11.85) 11.11 (10.99 to 11.24) 11.06 (10.85 to 11.28) 10.58 (10.37 to 10.79) 10.32 (10.12 to 10.52) 9.90 (9.71 to 10.10)
  Middle school 8.37 (8.32 to 8.42) 9.79 (9.66 to 9.93) 9.16 (9.06 to 9.27) 8.61 (8.51 to 8.71) 8.34 (8.24 to 8.43) 8.10 (7.93 to 8.27) 7.67 (7.51 to 7.83) 8.00 (7.84 to 8.16) 7.68 (7.52 to 7.83)
  High school 29.99 (29.89 to 30.08) 32.17 (31.93 to 32.41) 31.33 (31.14 to 31.52) 30.35 (30.17 to 30.54) 29.92 (29.74 to 30.11) 29.88 (29.56 to 30.20) 29.20 (28.88 to 29.52) 29.14 (28.83 to 29.45) 28.50 (28.19 to 28.81)
  College or higher education 50.25 (50.12 to 50.38) 43.38 (43.05 to 43.70) 46.95 (46.70 to 47.20) 49.32 (49.06 to 49.57) 50.63 (50.37 to 50.88) 50.96 (50.51 to 51.40) 52.54 (52.08 to 53.00) 52.54 (52.10 to 52.98) 53.92 (53.48 to 54.36)
 Household income
  Lowest quartile 8.94 (8.88 to 9.01) 11.00 (10.81 to 11.19) 9.40 (9.27 to 9.54) 11.28 (11.13 to 11.43) 8.54 (8.42 to 8.67) 8.98 (8.75 to 9.20) 8.79 (8.57 to 9.02) 7.82 (7.62 to 8.02) 6.29 (6.12 to 6.46)
  Second quartile 28.34 (28.22 to 28.47) 40.09 (39.73 to 40.46) 33.16 (32.89 to 33.42) 32.93 (32.68 to 33.19) 26.46 (26.23 to 26.70) 26.33 (25.93 to 26.74) 25.39 (24.99 to 25.78) 23.70 (23.33 to 24.06) 21.66 (21.31 to 22.01)
  Third quartile 28.69 (28.57 to 28.81) 30.68 (30.36 to 31.01) 31.93 (31.68 to 32.17) 33.09 (32.83 to 33.35) 30.67 (30.42 to 30.91) 27.81 (27.40 to 28.21) 26.56 (26.17 to 26.95) 26.13 (25.76 to 26.50) 23.86 (23.51 to 24.21)
  Highest quartile 34.02 (33.85 to 34.20) 18.23 (17.88 to 18.57) 25.52 (25.22 to 25.81) 22.70 (22.40 to 22.99) 34.33 (34.01 to 34.65) 36.88 (36.32 to 37.44) 39.26 (38.70 to 39.81) 42.36 (41.82 to 42.90) 48.19 (47.65 to 48.72)
 Smoking status
  Smoker 20.18 (20.11 to 20.26) 25.43 (25.24 to 25.62) 23.96 (23.81 to 24.11) 21.80 (21.65 to 21.95) 20.02 (19.87 to 20.17) 18.32 (18.07 to 18.56) 17.69 (17.44 to 17.93) 18.19 (17.95 to 18.44) 17.60 (17.37 to 17.84)
  Ex-smoker 18.60 (18.53 to 18.67) 13.74 (13.60 to 13.88) 15.96 (15.84 to 16.08) 17.21 (17.09 to 17.33) 18.38 (18.25 to 18.51) 18.69 (18.46 to 18.92) 18.99 (18.76 to 19.22) 21.60 (21.37 to 21.83) 22.83 (22.60 to 23.06)
  Non-smoker 61.22 (61.14 to 61.31) 60.83 (60.64 to 61.02) 60.08 (59.92 to 60.23) 60.99 (60.84 to 61.14) 61.60 (61.44 to 61.76) 62.99 (62.71 to 63.28) 63.32 (63.03 to 63.61) 60.21 (59.93 to 60.48) 59.57 (59.30 to 59.84)
 Alcohol consumption (day/mon)
  <2 55.65 (55.56 to 55.75) 54.31 (54.07 to 54.54) 51.54 (51.35 to 51.72) 50.43 (50.24 to 50.61) 51.88 (51.68 to 52.07) 59.05 (58.72 to 59.37) 61.02 (60.70 to 61.34) 57.98 (57.67 to 58.29) 57.75 (57.44 to 58.06)
  2–12 38.35 (38.25 to 38.44) 39.39 (39.16 to 39.63) 41.61 (41.43 to 41.79) 42.40 (42.22 to 42.58) 41.10 (40.91 to 41.28) 35.80 (35.48 to 36.12) 34.03 (33.72 to 34.34) 36.67 (36.36 to 36.98) 36.77 (36.46 to 37.08)
  ≥13 6.00 (5.96 to 6.04) 6.30 (6.19 to 6.40) 6.85 (6.77 to 6.94) 7.17 (7.09 to 7.26) 7.03 (6.94 to 7.12) 5.16 (5.03 to 5.29) 4.95 (4.82 to 5.08) 5.35 (5.22 to 5.48) 5.48 (5.35 to 5.61)
 Hypertension
  Yes 20.30 (20.22 to 20.37) 15.43 (15.27 to 15.59) 16.90 (16.77 to 17.03) 18.66 (18.52 to 18.79) 20.14 (20.00 to 20.29) 20.87 (20.62 to 21.12) 21.75 (21.49 to 22.01) 22.80 (22.54 to 23.06) 24.35 (24.08 to 24.61)
  No 79.70 (79.63 to 79.78) 84.57 (84.41 to 84.73) 83.10 (82.97 to 83.23) 81.34 (81.21 to 81.48) 79.86 (79.71 to 80.00) 79.13 (78.88 to 79.38) 78.25 (77.99 to 78.51) 77.20 (76.94 to 77.46) 75.65 (75.39 to 75.92)
 Diabetes
  Yes 8.50 (8.45 to 8.55) 5.81 (5.71 to 5.90) 6.42 (6.34 to 6.50) 7.48 (7.39 to 7.56) 8.22 (8.13 to 8.32) 8.96 (8.79 to 9.12) 9.47 (9.30 to 9.64) 10.16 (9.99 to 10.33) 10.64 (10.46 to 10.82)
  No 91.50 (91.45 to 91.55) 94.19 (94.10 to 94.29) 93.58 (93.50 to 93.66) 92.52 (92.44 to 92.61) 91.78 (91.68 to 91.87) 91.04 (90.88 to 91.21) 90.53 (90.36 to 90.70) 89.84 (89.67 to 90.01) 89.36 (89.18 to 89.54)
 SRH
  High 45.29 (45.18 to 45.40) 46.72 (46.45 to 46.99) 44.37 (44.16 to 44.57) 42.29 (42.10 to 42.49) 40.26 (40.05 to 40.46) 52.84 (52.50 to 53.19) 45.55 (45.21 to 45.89) 45.89 (45.55 to 46.23) 44.23 (43.88 to 44.57)
  Middle 41.64 (41.54 to 41.73) 39.21 (38.96 to 39.46) 41.63 (41.43 to 41.82) 43.59 (43.41 to 43.77) 45.43 (45.24 to 45.63) 37.84 (37.53 to 38.16) 42.39 (42.09 to 42.70) 41.22 (40.91 to 41.52) 41.57 (41.25 to 41.88)
  Low 13.07 (13.01 to 13.14) 14.07 (13.91 to 14.23) 14.01 (13.88 to 14.13) 14.11 (13.99 to 14.24) 14.31 (14.18 to 14.44) 9.31 (9.13 to 9.49) 12.06 (11.86 to 12.26) 12.89 (12.68 to 13.10) 14.21 (13.99 to 14.43)
 Average sleep duration (hr/day)
  <6 14.21 (14.15 to 14.27) 13.75 (13.59 to 13.91) 15.20 (15.07 to 15.33) 16.74 (16.61 to 16.87) 16.07 (15.94 to 16.20) 11.62 (11.43 to 11.80) 13.23 (13.03 to 13.43) 13.81 (13.60 to 14.01) 13.51 (13.30 to 13.71)
  6–6.9 27.49 (27.41 to 27.57) 29.29 (29.08 to 29.50) 31.11 (30.95 to 31.28) 31.84 (31.68 to 32.01) 30.44 (30.28 to 30.61) 23.54 (23.29 to 23.79) 24.82 (24.56 to 25.07) 25.03 (24.78 to 25.28) 25.06 (24.81 to 25.31)
  7–7.9 33.47 (33.38 to 33.56) 32.72 (32.50 to 32.93) 32.63 (32.46 to 32.80) 32.00 (31.84 to 32.16) 32.95 (32.78 to 33.12) 34.53 (34.24 to 34.81) 34.06 (33.77 to 34.35) 33.84 (33.56 to 34.13) 34.68 (34.39 to 34.97)
  ≥8 24.83 (24.75 to 24.91) 24.24 (24.04 to 24.45) 21.06 (20.91 to 21.20) 19.42 (19.28 to 19.56) 20.54 (20.39 to 20.69) 30.32 (30.03 to 30.61) 27.89 (27.61 to 28.17) 27.32 (27.05 to 27.59) 26.76 (26.49 to 27.02)
 Stress counseling
  Yes 2.41 (2.38 to 2.44) 1.54 (1.49 to 1.59) 1.66 (1.62 to 1.71) 1.99 (1.95 to 2.04) 2.16 (2.10 to 2.21) 2.67 (2.57 to 2.77) 2.94 (2.84 to 3.04) 3.06 (2.96 to 3.17) 2.97 (2.87 to 3.08)
  No 97.59 (97.56 to 97.62) 98.46 (98.41 to 98.51) 98.34 (98.29 to 98.38) 98.01 (97.96 to 98.05) 97.84 (97.79 to 97.90) 97.33 (97.23 to 97.43) 97.06 (96.96 to 97.16) 96.94 (96.83 to 97.04) 97.03 (96.92 to 97.13)
 Depression counseling
  Yes 1.41 (1.39 to 1.43) 0.94 (0.90 to 0.98) 0.92 (0.88 to 0.95) 1.11 (1.08 to 1.14) 1.28 (1.24 to 1.32) 1.48 (1.40 to 1.55) 1.72 (1.65 to 1.80) 1.88 (1.80 to 1.96) 1.80 (1.72 to 1.88)
  No 98.59 (98.57 to 98.61) 99.06 (99.02 to 99.11) 99.08 (99.05 to 99.12) 98.89 (98.86 to 98.92) 98.72 (98.68 to 98.76) 98.52 (98.45 to 98.60) 98.28 (98.20 to 98.35) 98.12 (98.05 to 98.20) 98.20 (98.12 to 98.28)
*

according to Asia-Pacific guidelines, BMI is divided into 4 groups: underweight (<18.5 kg/m2), normal (18.5–22.9 kg/m2), overweight (23.0–24.9 kg/m2), and obese (≥25 kg/m2).

KCHS, Korea Community Health Survey; CI, confidence interval; BMI, body mass index; SRH, self-rated health.

Table 2.

Trends in the prevalence of counseling for stress throughout pre-, intra-, and post-pandemic (weighted % [95% CI]), based on data obtained from the KCHS

Pre-pandemic
Intra-pandemic
Post-pandemic
2009–2010 2011–2013 2014–2016 2017–2019 2020 2021 2022 2023–2024
Overall 1.54 (1.49 to 1.59) 1.66 (1.62 to 1.71) 1.99 (1.95 to 2.04) 2.16 (2.10 to 2.21) 2.67 (2.58 to 2.77) 2.94 (2.84 to 3.03) 3.06 (2.97 to 3.16) 2.97 (2.88 to 3.07)
Age (yr)
 19–30 1.24 (1.13 to 1.35) 1.60 (1.49 to 1.71) 2.08 (1.96 to 2.19) 2.51 (2.37 to 2.65) 3.31 (3.06 to 3.57) 3.95 (3.67 to 4.22) 4.03 (3.75 to 4.31) 3.99 (3.70 to 4.28)
 31–40 1.49 (1.38 to 1.60) 1.72 (1.62 to 1.82) 2.33 (2.21 to 2.44) 2.72 (2.58 to 2.85) 3.68 (3.40 to 3.96) 3.93 (3.66 to 4.19) 4.35 (4.06 to 4.64) 4.51 (4.21 to 4.80)
 41–50 1.63 (1.52 to 1.75) 1.52 (1.43 to 1.61) 1.84 (1.74 to 1.93) 2.16 (2.05 to 2.27) 2.84 (2.63 to 3.05) 3.22 (3.00 to 3.44) 3.40 (3.16 to 3.63) 3.43 (3.19 to 3.66)
 51–60 1.73 (1.59 to 1.86) 1.72 (1.62 to 1.82) 1.82 (1.72 to 1.91) 1.80 (1.70 to 1.90) 2.19 (2.01 to 2.37) 2.36 (2.17 to 2.56) 2.44 (2.25 to 2.63) 2.27 (2.10 to 2.45)
 61–70 1.87 (1.72 to 2.02) 1.92 (1.79 to 2.05) 1.99 (1.87 to 2.11) 1.85 (1.74 to 1.96) 2.05 (1.87 to 2.24) 2.10 (1.93 to 2.28) 2.09 (1.93 to 2.25) 1.96 (1.81 to 2.11)
 ≥71 1.43 (1.28 to 1.59) 1.61 (1.48 to 1.74) 1.85 (1.72 to 1.97) 1.63 (1.52 to 1.74) 1.53 (1.36 to 1.69) 1.65 (1.49 to 1.81) 1.84 (1.68 to 1.99) 1.71 (1.56 to 1.87)
Sex
 Male 0.96 (0.90 to 1.03) 1.10 (1.04 to 1.15) 1.40 (1.34 to 1.45) 1.56 (1.50 to 1.63) 2.06 (1.95 to 2.18) 2.14 (2.03 to 2.26) 2.24 (2.12 to 2.35) 2.15 (2.03 to 2.26)
 Female 2.12 (2.03 to 2.20) 2.24 (2.17 to 2.31) 2.60 (2.52 to 2.67) 2.75 (2.68 to 2.83) 3.28 (3.14 to 3.42) 3.73 (3.58 to 3.87) 3.88 (3.74 to 4.03) 3.79 (3.65 to 3.94)
Region of residence
 Urban 1.65 (1.56 to 1.74) 1.78 (1.71 to 1.85) 2.07 (1.99 to 2.14) 2.28 (2.20 to 2.36) 2.83 (2.68 to 2.98) 3.17 (3.02 to 3.33) 3.29 (3.13 to 3.45) 3.20 (3.04 to 3.36)
 Rural 1.44 (1.38 to 1.50) 1.56 (1.51 to 1.61) 1.93 (1.87 to 1.98) 2.05 (1.99 to 2.12) 2.55 (2.43 to 2.66) 2.75 (2.64 to 2.86) 2.89 (2.77 to 3.00) 2.80 (2.69 to 2.91)
BMI group*
 Underweight 1.98 (1.74 to 2.22) 2.18 (1.98 to 2.39) 3.03 (2.78 to 3.27) 3.30 (3.00 to 3.59) 3.74 (3.19 to 4.29) 4.52 (3.99 to 5.04) 4.97 (4.40 to 5.55) 5.08 (4.48 to 5.69)
 Normal 1.47 (1.40 to 1.54) 1.62 (1.56 to 1.69) 1.94 (1.88 to 2.01) 2.08 (2.01 to 2.16) 2.57 (2.43 to 2.71) 2.87 (2.73 to 3.02) 2.94 (2.79 to 3.08) 2.79 (2.65 to 2.93)
 Overweight 1.44 (1.34 to 1.54) 1.46 (1.37 to 1.54) 1.68 (1.60 to 1.77) 1.92 (1.82 to 2.02) 2.20 (2.03 to 2.37) 2.43 (2.25 to 2.60) 2.61 (2.43 to 2.79) 2.43 (2.26 to 2.60)
 Obese 1.68 (1.57 to 1.80) 1.82 (1.73 to 1.92) 2.15 (2.06 to 2.24) 2.26 (2.17 to 2.36) 3.04 (2.86 to 3.21) 3.20 (3.03 to 3.37) 3.30 (3.12 to 3.47) 3.33 (3.16 to 3.50)
Education
 Elementary school or lower education 2.06 (1.92 to 2.19) 2.14 (2.03 to 2.26) 2.43 (2.31 to 2.55) 2.15 (2.04 to 2.27) 2.11 (1.92 to 2.29) 2.34 (2.14 to 2.55) 2.44 (2.23 to 2.64) 2.15 (1.95 to 2.35)
 Middle school 2.00 (1.81 to 2.18) 1.84 (1.70 to 1.98) 2.21 (2.05 to 2.36) 2.09 (1.94 to 2.24) 2.35 (2.09 to 2.61) 2.29 (2.04 to 2.54) 2.44 (2.19 to 2.69) 2.54 (2.27 to 2.81)
 High school 1.54 (1.45 to 1.63) 1.66 (1.58 to 1.74) 2.01 (1.93 to 2.10) 2.10 (2.01 to 2.19) 2.52 (2.36 to 2.69) 2.79 (2.63 to 2.95) 2.93 (2.77 to 3.10) 2.67 (2.51 to 2.83)
 College or higher education 1.26 (1.18 to 1.34) 1.51 (1.44 to 1.57) 1.84 (1.77 to 1.90) 2.20 (2.12 to 2.28) 2.94 (2.80 to 3.08) 3.23 (3.10 to 3.37) 3.36 (3.21 to 3.50) 3.35 (3.21 to 3.49)
Household income
 Lowest quartile 2.79 (2.60 to 2.98) 2.91 (2.74 to 3.08) 3.43 (3.27 to 3.59) 3.69 (3.50 to 3.89) 3.81 (3.49 to 4.13) 4.06 (3.74 to 4.38) 4.40 (4.06 to 4.74) 4.54 (4.14 to 4.94)
 Second quartile 1.54 (1.46 to 1.62) 1.81 (1.74 to 1.89) 2.09 (2.01 to 2.17) 2.40 (2.30 to 2.50) 2.83 (2.66 to 3.00) 3.04 (2.86 to 3.22) 3.41 (3.21 to 3.60) 3.43 (3.23 to 3.64)
 Third quartile 1.22 (1.13 to 1.31) 1.36 (1.29 to 1.44) 1.62 (1.55 to 1.70) 1.78 (1.69 to 1.87) 2.54 (2.37 to 2.72) 2.79 (2.62 to 2.97) 2.83 (2.65 to 3.02) 2.71 (2.53 to 2.89)
 Highest quartile 1.33 (1.20 to 1.45) 1.39 (1.30 to 1.47) 1.68 (1.58 to 1.77) 1.92 (1.83 to 2.01) 2.38 (2.23 to 2.53) 2.72 (2.56 to 2.87) 2.77 (2.62 to 2.92) 2.70 (2.56 to 2.83)
Smoking status
 Smoker 1.37 (1.26 to 1.47) 1.58 (1.49 to 1.67) 2.06 (1.96 to 2.16) 2.35 (2.23 to 2.47) 3.17 (2.94 to 3.41) 3.39 (3.15 to 3.63) 3.63 (3.39 to 3.86) 3.56 (3.32 to 3.79)
 Ex-smoker 1.11 (0.99 to 1.23) 1.30 (1.20 to 1.39) 1.53 (1.43 to 1.63) 1.79 (1.68 to 1.90) 2.48 (2.27 to 2.69) 2.70 (2.50 to 2.90) 2.77 (2.58 to 2.96) 2.72 (2.53 to 2.91)
 Non-smoker 1.71 (1.64 to 1.78) 1.79 (1.74 to 1.85) 2.10 (2.04 to 2.16) 2.20 (2.14 to 2.27) 2.59 (2.47 to 2.70) 2.88 (2.77 to 3.00) 3.00 (2.88 to 3.12) 2.90 (2.78 to 3.02)
Alcohol consumption (day/mon)
 <2 1.80 (1.73 to 1.88) 1.93 (1.87 to 2.00) 2.29 (2.22 to 2.36) 2.37 (2.30 to 2.44) 2.79 (2.67 to 2.91) 2.95 (2.84 to 3.07) 3.19 (3.07 to 3.31) 3.14 (3.02 to 3.27)
 2–12 1.20 (1.12 to 1.28) 1.36 (1.29 to 1.42) 1.65 (1.58 to 1.72) 1.88 (1.81 to 1.96) 2.40 (2.26 to 2.55) 2.88 (2.72 to 3.05) 2.82 (2.66 to 2.97) 2.65 (2.50 to 2.79)
 ≥13 1.42 (1.22 to 1.61) 1.50 (1.33 to 1.66) 1.91 (1.74 to 2.08) 2.15 (1.97 to 2.34) 3.20 (2.76 to 3.64) 3.13 (2.72 to 3.55) 3.39 (2.98 to 3.81) 3.38 (2.97 to 3.78)
Hypertension
 Yes 1.42 (1.36 to 1.48) 2.15 (2.03 to 2.26) 2.43 (2.32 to 2.54) 2.25 (2.14 to 2.35) 2.57 (2.38 to 2.76) 2.77 (2.59 to 2.95) 2.75 (2.58 to 2.92) 2.56 (2.40 to 2.71)
 No 2.16 (1.93 to 2.38) 1.57 (1.52 to 1.61) 1.89 (1.84 to 1.94) 2.13 (2.07 to 2.19) 2.70 (2.59 to 2.81) 2.98 (2.88 to 3.09) 3.16 (3.05 to 3.27) 3.11 (3.00 to 3.22)
Diabetes
 Yes 1.50 (1.45 to 1.56) 2.48 (2.28 to 2.68) 2.64 (2.46 to 2.82) 2.50 (2.32 to 2.67) 2.94 (2.64 to 3.24) 2.92 (2.63 to 3.22) 3.06 (2.80 to 3.33) 2.90 (2.64 to 3.15)
 No 3.02 (2.83 to 3.21) 1.61 (1.56 to 1.65) 1.94 (1.89 to 1.99) 2.13 (2.07 to 2.18) 2.65 (2.55 to 2.74) 2.94 (2.84 to 3.04) 3.06 (2.96 to 3.17) 2.98 (2.88 to 3.08)
SRH
 High 0.61 (0.57 to 0.66) 0.67 (0.63 to 0.72) 0.85 (0.80 to 0.90) 0.94 (0.89 to 0.99) 1.44 (1.34 to 1.53) 1.49 (1.39 to 1.60) 1.49 (1.39 to 1.59) 1.50 (1.40 to 1.60)
 Middle 1.57 (1.48 to 1.65) 1.63 (1.56 to 1.70) 1.95 (1.88 to 2.02) 2.13 (2.05 to 2.20) 3.14 (2.98 to 3.30) 3.06 (2.91 to 3.20) 3.38 (3.23 to 3.54) 3.08 (2.93 to 3.22)
 Low 4.54 (4.32 to 4.76) 4.91 (4.72 to 5.10) 5.54 (5.34 to 5.73) 5.67 (5.47 to 5.87) 7.76 (7.29 to 8.24) 7.97 (7.55 to 8.38) 7.66 (7.28 to 8.04) 7.28 (6.92 to 7.63)
Average sleep duration (hr/day)
 <6 1.41 (1.32 to 1.51) 3.20 (3.04 to 3.35) 3.60 (3.46 to 3.75) 4.07 (3.90 to 4.23) 5.13 (4.78 to 5.47) 5.31 (4.99 to 5.63) 5.45 (5.13 to 5.76) 5.26 (4.95 to 5.58)
 6–6.9 1.12 (1.04 to 1.19) 1.43 (1.35 to 1.50) 1.66 (1.59 to 1.74) 1.87 (1.78 to 1.95) 2.53 (2.34 to 2.72) 2.61 (2.43 to 2.78) 2.85 (2.67 to 3.03) 2.73 (2.55 to 2.90)
 7–7.9 1.42 (1.32 to 1.53) 1.20 (1.14 to 1.27) 1.42 (1.35 to 1.49) 1.57 (1.50 to 1.65) 2.09 (1.95 to 2.23) 2.30 (2.16 to 2.44) 2.29 (2.15 to 2.43) 2.25 (2.11 to 2.39)
 ≥8 1.66 (1.62 to 1.71) 1.62 (1.52 to 1.71) 2.09 (1.99 to 2.20) 2.02 (1.92 to 2.13) 2.51 (2.35 to 2.67) 2.88 (2.71 to 3.06) 3.01 (2.83 to 3.20) 2.99 (2.81 to 3.17)
*

according to Asia-Pacific guidelines, BMI is divided into 4 groups: underweight (<18.5 kg/m2), normal (18.5–22.9 kg/m2), overweight (23.0–24.9 kg/m2), and obese (≥25 kg/m2).

CI, confidence interval; KCHS, Korea Community Health Survey; BMI, body mass index; SRH, self-rated health.

Table 3.

Trends in the prevalence of counseling for depression throughout pre-, intra-, and post-pandemic (weighted % [95% CI]), based on data obtained from the KCHS

Pre-pandemic
Intra-pandemic
Post-pandemic
2009–2010 2011–2013 2014–2016 2017–2019 2020 2021 2022 2023–2024
Overall 0.94 (0.90 to 0.98) 0.92 (0.88 to 0.95) 1.11 (1.08 to 1.14) 1.28 (1.24 to 1.32) 1.48 (1.41 to 1.55) 1.72 (1.65 to 1.79) 1.88 (1.80 to 1.95) 1.80 (1.73 to 1.87)
Age (yr)
 19–30 0.65 (0.57 to 0.74) 0.79 (0.71 to 0.87) 0.92 (0.84 to 1.00) 1.36 (1.26 to 1.46) 1.83 (1.64 to 2.02) 2.09 (1.89 to 2.28) 2.24 (2.03 to 2.45) 2.20 (1.98 to 2.43)
 31–40 0.75 (0.67 to 0.82) 0.78 (0.71 to 0.84) 1.05 (0.97 to 1.13) 1.26 (1.17 to 1.35) 1.59 (1.42 to 1.77) 1.71 (1.53 to 1.88) 2.11 (1.91 to 2.32) 2.16 (1.95 to 2.36)
 41–50 0.97 (0.88 to 1.06) 0.82 (0.75 to 0.88) 0.96 (0.89 to 1.03) 1.17 (1.09 to 1.26) 1.44 (1.29 to 1.59) 1.69 (1.52 to 1.85) 1.74 (1.58 to 1.90) 1.81 (1.64 to 1.98)
 51–60 1.16 (1.05 to 1.26) 1.04 (0.96 to 1.12) 1.23 (1.15 to 1.31) 1.24 (1.16 to 1.33) 1.30 (1.16 to 1.44) 1.55 (1.40 to 1.70) 1.79 (1.63 to 1.94) 1.58 (1.43 to 1.73)
 61–70 1.37 (1.24 to 1.51) 1.33 (1.22 to 1.44) 1.40 (1.30 to 1.50) 1.37 (1.27 to 1.46) 1.36 (1.22 to 1.51) 1.61 (1.45 to 1.76) 1.73 (1.58 to 1.88) 1.50 (1.37 to 1.64)
 ≥71 1.18 (1.04 to 1.32) 1.07 (0.96 to 1.17) 1.38 (1.28 to 1.49) 1.33 (1.23 to 1.43) 1.26 (1.10 to 1.41) 1.68 (1.51 to 1.85) 1.61 (1.46 to 1.75) 1.60 (1.45 to 1.75)
Sex
 Male 0.52 (0.48 to 0.57) 0.52 (0.49 to 0.56) 0.68 (0.64 to 0.72) 0.86 (0.81 to 0.90) 1.02 (0.94 to 1.10) 1.14 (1.06 to 1.22) 1.20 (1.11 to 1.28) 1.24 (1.15 to 1.33)
 Female 1.35 (1.29 to 1.42) 1.31 (1.26 to 1.37) 1.54 (1.49 to 1.60) 1.71 (1.65 to 1.77) 1.93 (1.83 to 2.04) 2.30 (2.19 to 2.42) 2.55 (2.43 to 2.66) 2.36 (2.25 to 2.47)
Region of residence
 Urban 0.98 (0.91 to 1.05) 0.96 (0.91 to 1.02) 1.17 (1.11 to 1.23) 1.32 (1.26 to 1.39) 1.61 (1.49 to 1.72) 1.86 (1.75 to 1.98) 2.01 (1.89 to 2.13) 1.95 (1.82 to 2.07)
 Rural 0.90 (0.85 to 0.94) 0.87 (0.83 to 0.91) 1.06 (1.02 to 1.10) 1.24 (1.19 to 1.29) 1.37 (1.29 to 1.46) 1.61 (1.52 to 1.70) 1.77 (1.68 to 1.86) 1.69 (1.60 to 1.78)
BMI group*
 Underweight 1.30 (1.10 to 1.51) 1.39 (1.22 to 1.55) 1.64 (1.47 to 1.81) 2.02 (1.80 to 2.24) 2.23 (1.81 to 2.65) 3.01 (2.56 to 3.46) 3.26 (2.80 to 3.72) 2.67 (2.26 to 3.07)
 Normal 0.90 (0.85 to 0.96) 0.89 (0.84 to 0.94) 1.12 (1.06 to 1.17) 1.29 (1.22 to 1.35) 1.46 (1.36 to 1.56) 1.75 (1.64 to 1.86) 1.84 (1.73 to 1.96) 1.71 (1.60 to 1.82)
 Overweight 0.87 (0.79 to 0.95) 0.81 (0.75 to 0.87) 0.96 (0.90 to 1.02) 1.13 (1.05 to 1.20) 1.24 (1.12 to 1.37) 1.38 (1.25 to 1.50) 1.68 (1.54 to 1.82) 1.55 (1.41 to 1.69)
 Obese 0.98 (0.90 to 1.06) 0.97 (0.90 to 1.04) 1.13 (1.06 to 1.20) 1.28 (1.21 to 1.35) 1.58 (1.46 to 1.71) 1.78 (1.65 to 1.90) 1.87 (1.74 to 2.00) 1.98 (1.85 to 2.11)
Education
 Elementary school or lower education 1.57 (1.45 to 1.68) 1.44 (1.34 to 1.54) 1.80 (1.69 to 1.91) 1.68 (1.58 to 1.79) 1.55 (1.39 to 1.72) 2.09 (1.90 to 2.29) 2.24 (2.05 to 2.43) 1.94 (1.75 to 2.13)
 Middle school 1.31 (1.17 to 1.45) 1.25 (1.14 to 1.37) 1.58 (1.45 to 1.71) 1.60 (1.46 to 1.73) 1.80 (1.57 to 2.03) 1.99 (1.75 to 2.22) 2.06 (1.84 to 2.29) 2.06 (1.83 to 2.29)
 High school 0.94 (0.87 to 1.01) 0.99 (0.93 to 1.05) 1.20 (1.13 to 1.26) 1.37 (1.30 to 1.45) 1.53 (1.40 to 1.65) 1.76 (1.63 to 1.89) 1.92 (1.79 to 2.06) 1.85 (1.72 to 1.98)
 College or higher education 0.63 (0.58 to 0.69) 0.66 (0.62 to 0.70) 0.81 (0.77 to 0.86) 1.08 (1.03 to 1.14) 1.38 (1.29 to 1.48) 1.59 (1.49 to 1.69) 1.75 (1.65 to 1.85) 1.71 (1.61 to 1.81)
Household income
 Lowest quartile 2.15 (1.99 to 2.32) 2.12 (1.98 to 2.27) 2.65 (2.51 to 2.80) 3.04 (2.86 to 3.22) 3.08 (2.78 to 3.37) 3.86 (3.54 to 4.18) 4.27 (3.94 to 4.60) 4.24 (3.86 to 4.63)
 Second quartile 0.94 (0.87 to 1.00) 1.05 (0.99 to 1.10) 1.19 (1.13 to 1.25) 1.58 (1.50 to 1.66) 1.83 (1.69 to 1.97) 2.09 (1.94 to 2.24) 2.37 (2.21 to 2.53) 2.59 (2.42 to 2.76)
 Third quartile 0.65 (0.59 to 0.72) 0.66 (0.61 to 0.71) 0.73 (0.69 to 0.78) 0.98 (0.92 to 1.04) 1.22 (1.10 to 1.34) 1.38 (1.26 to 1.51) 1.59 (1.46 to 1.73) 1.57 (1.43 to 1.71)
 Highest quartile 0.68 (0.59 to 0.76) 0.62 (0.57 to 0.68) 0.77 (0.70 to 0.83) 0.88 (0.82 to 0.94) 1.03 (0.93 to 1.13) 1.24 (1.13 to 1.34) 1.33 (1.23 to 1.44) 1.24 (1.15 to 1.33)
Smoking status
 Smoker 0.77 (0.70 to 0.85) 0.82 (0.75 to 0.88) 1.12 (1.04 to 1.19) 1.39 (1.30 to 1.49) 1.82 (1.64 to 2.00) 1.90 (1.71 to 2.09) 2.32 (2.13 to 2.51) 2.19 (1.99 to 2.38)
 Ex-smoker 0.68 (0.59 to 0.77) 0.73 (0.65 to 0.80) 0.81 (0.74 to 0.88) 1.07 (0.99 to 1.15) 1.20 (1.06 to 1.34) 1.51 (1.36 to 1.66) 1.57 (1.42 to 1.72) 1.65 (1.51 to 1.79)
 Non-smoker 1.06 (1.01 to 1.12) 1.01 (0.96 to 1.05) 1.19 (1.15 to 1.23) 1.31 (1.26 to 1.35) 1.46 (1.38 to 1.54) 1.74 (1.65 to 1.83) 1.85 (1.76 to 1.94) 1.75 (1.66 to 1.84)
Alcohol consumption (day/mon)
 <2 1.17 (1.12 to 1.23) 1.12 (1.07 to 1.17) 1.38 (1.33 to 1.43) 1.50 (1.45 to 1.56) 1.65 (1.55 to 1.74) 1.92 (1.83 to 2.02) 2.06 (1.97 to 2.16) 2.02 (1.92 to 2.11)
 2–12 0.62 (0.56 to 0.67) 0.67 (0.62 to 0.71) 0.81 (0.76 to 0.86) 0.99 (0.93 to 1.04) 1.19 (1.08 to 1.29) 1.36 (1.25 to 1.47) 1.56 (1.45 to 1.67) 1.44 (1.32 to 1.55)
 ≥13 0.87 (0.72 to 1.02) 0.86 (0.73 to 0.99) 0.97 (0.86 to 1.09) 1.35 (1.20 to 1.50) 1.58 (1.28 to 1.88) 1.78 (1.47 to 2.10) 2.01 (1.66 to 2.35) 1.98 (1.67 to 2.30)
Hypertension
 Yes 1.41 (1.30 to 1.53) 1.31 (1.22 to 1.40) 1.58 (1.49 to 1.66) 1.54 (1.45 to 1.62) 1.68 (1.53 to 1.83) 1.86 (1.72 to 1.99) 2.13 (1.98 to 2.28) 1.83 (1.70 to 1.96)
 No 0.85 (0.81 to 0.89) 0.83 (0.80 to 0.87) 1.00 (0.97 to 1.04) 1.21 (1.17 to 1.26) 1.42 (1.35 to 1.50) 1.69 (1.60 to 1.77) 1.80 (1.72 to 1.89) 1.79 (1.71 to 1.88)
Diabetes
 Yes 1.63 (1.43 to 1.83) 1.61 (1.45 to 1.77) 1.88 (1.73 to 2.03) 1.79 (1.64 to 1.94) 1.84 (1.60 to 2.07) 2.06 (1.84 to 2.28) 2.48 (2.24 to 2.72) 2.07 (1.86 to 2.29)
 No 0.89 (0.85 to 0.93) 0.87 (0.83 to 0.90) 1.05 (1.01 to 1.08) 1.23 (1.19 to 1.27) 1.44 (1.37 to 1.51) 1.69 (1.61 to 1.76) 1.81 (1.73 to 1.89) 1.77 (1.69 to 1.85)
SRH
 High 0.32 (0.28 to 0.35) 0.30 (0.27 to 0.33) 0.40 (0.37 to 0.44) 0.47 (0.43 to 0.51) 0.71 (0.65 to 0.78) 0.74 (0.67 to 0.81) 0.81 (0.74 to 0.89) 0.80 (0.72 to 0.87)
 Middle 0.82 (0.76 to 0.88) 0.79 (0.75 to 0.84) 0.93 (0.89 to 0.98) 1.11 (1.05 to 1.16) 1.55 (1.43 to 1.66) 1.61 (1.51 to 1.72) 1.81 (1.70 to 1.92) 1.66 (1.55 to 1.77)
 Low 3.32 (3.13 to 3.51) 3.22 (3.06 to 3.37) 3.77 (3.61 to 3.92) 4.10 (3.93 to 4.27) 5.53 (5.12 to 5.95) 5.82 (5.48 to 6.17) 5.88 (5.56 to 6.21) 5.32 (5.02 to 5.63)
Average sleep duration (hr/day)
 <6 1.81 (1.67 to 1.95) 1.82 (1.71 to 1.94) 2.07 (1.96 to 2.18) 2.40 (2.28 to 2.53) 3.04 (2.78 to 3.30) 3.39 (3.13 to 3.64) 3.64 (3.38 to 3.91) 3.54 (3.28 to 3.80)
 6–6.9 0.76 (0.69 to 0.82) 0.74 (0.68 to 0.79) 0.87 (0.81 to 0.92) 0.98 (0.92 to 1.05) 1.28 (1.15 to 1.41) 1.44 (1.31 to 1.57) 1.61 (1.47 to 1.74) 1.50 (1.37 to 1.63)
 7–7.9 0.62 (0.57 to 0.68) 0.58 (0.53 to 0.62) 0.72 (0.67 to 0.77) 0.89 (0.84 to 0.95) 1.04 (0.94 to 1.13) 1.19 (1.09 to 1.30) 1.32 (1.22 to 1.43) 1.25 (1.14 to 1.35)
 ≥8 1.08 (0.99 to 1.17) 1.05 (0.97 to 1.13) 1.31 (1.23 to 1.39) 1.46 (1.37 to 1.55) 1.54 (1.41 to 1.66) 1.83 (1.69 to 1.97) 1.92 (1.77 to 2.06) 1.92 (1.78 to 2.06)
*

according to Asia-Pacific guidelines, BMI is divided into 4 groups: underweight (<18.5 kg/m2), normal (18.5–22.9 kg/m2), overweight (23.0–24.9 kg/m2), and obese (≥25 kg/m2).

CI, confidence interval; KCHS, Korea Community Health Survey; BMI, body mass index; SRH, self-rated health.

Table 4.

Weighted ORs as a trend of counseling for stress and counseling for depression rates, based on data obtained from the KCHS

Counseling for stress
Counseling for depression
Pre-pandemic (reference) vs. intra-pandemic
Intra-pandemic (reference) vs. post-pandemic
Pre-pandemic (reference) vs. intra-pandemic
Intra-pandemic (reference) vs. post-pandemic
Weighted OR (95% CI) Weighted OR (95% CI) Weighted OR (95% CI) Weighted OR (95% CI)
Overall 1.58 (1.54 to 1.62)* 1.03 (0.99 to 1.07) 1.60 (1.55 to 1.65)* 1.06 (1.01 to 1.12)*
Age (yr)
 19–30 2.07 (1.95 to 2.19)* 1.06 (0.97 to 1.17) 2.23 (2.07 to 2.41)* 1.08 (0.95 to 1.22)
 31–40 1.98 (1.88 to 2.09)* 1.14 (1.05 to 1.24)* 1.91 (1.77 to 2.06)* 1.20 (1.06 to 1.36)*
 41–50 1.79 (1.69 to 1.88)* 1.09 (1.00 to 1.19)* 1.67 (1.55 to 1.79)* 1.12 (0.99 to 1.25)
 51–60 1.32 (1.25 to 1.40)* 0.97 (0.88 to 1.07) 1.32 (1.23 to 1.42)* 1.02 (0.90 to 1.15)
 61–70 1.09 (1.03 to 1.17)* 0.94 (0.85 to 1.04) 1.15 (1.07 to 1.24)* 0.95 (0.85 to 1.07)
 ≥71 1.02 (0.95 to 1.09) 1.02 (0.91 to 1.15) 1.21 (1.12 to 1.31)* 1.05 (0.93 to 1.19)
Sex
 Male 1.71 (1.64 to 1.78)* 1.00 (0.93 to 1.07) 1.73 (1.63 to 1.83)* 1.11 (1.01 to 1.21)*
 Female 1.51 (1.46 to 1.55)* 1.05 (1.01 to 1.10) 1.53 (1.48 to 1.59)* 1.04 (0.98 to 1.11)
Region of residence
 Urban 1.60 (1.54 to 1.67)* 1.03 (0.97 to 1.10) 1.65 (1.58 to 1.74)* 1.07 (0.98 to 1.15)
 Rural 1.56 (1.51 to 1.61)* 1.03 (0.98 to 1.08) 1.55 (1.49 to 1.62)* 1.07 (1.01 to 1.14)
BMI group†
 Underweight 1.73 (1.58 to 1.90)* 1.15 (0.99 to 1.35) 1.83 (1.63 to 2.06)* 0.93 (0.77 to 1.12)
 Normal 1.58 (1.53 to 1.65)* 1.00 (0.94 to 1.06) 1.62 (1.54 to 1.70)* 1.02 (0.94 to 1.10)
 Overweight 1.49 (1.41 to 1.57)* 1.01 (0.92 to 1.10) 1.52 (1.42 to 1.63)* 1.08 (0.97 to 1.21)
 Obese 1.59 (1.53 to 1.66)* 1.05 (0.98 to 1.12) 1.58 (1.49 to 1.67)* 1.14 (1.05 to 1.24)*
Education
 Elementary school or lower education 1.05 (0.98 to 1.11) 0.94 (0.84 to 1.05) 1.21 (1.13 to 1.30)* 0.99 (0.88 to 1.12)
 Middle school 1.16 (1.08 to 1.26)* 1.08 (0.94 to 1.24) 1.37 (1.25 to 1.49)* 1.06 (0.91 to 1.22)
 High school 1.51 (1.44 to 1.58)* 0.97 (0.90 to 1.05) 1.55 (1.46 to 1.64)* 1.07 (0.97 to 1.17)
 College or higher education 1.85 (1.79 to 1.92)* 1.06 (0.99 to 1.11) 1.95 (1.86 to 2.05)* 1.09 (1.01 to 1.17)*
Household income
 Lowest quartile 1.28 (1.21 to 1.36)* 1.12 (1.01 to 1.25)* 1.51 (1.42 to 1.61)* 1.15 (1.02 to 1.29)*
 Second quartile 1.61 (1.55 to 1.69)* 1.12 (1.04 to 1.21)* 1.81 (1.71 to 1.90)* 1.25 (1.14 to 1.36)*
 Third quartile 1.82 (1.73 to 1.92)* 0.99 (0.91 to 1.08) 1.85 (1.73 to 1.98)* 1.13 (1.01 to 1.26)*
 Highest quartile 1.63 (1.55 to 1.70)* 1.03 (0.96 to 1.09) 1.60 (1.50 to 1.72)* 1.03 (0.93 to 1.13)
Smoking status
 Smoker 1.89 (1.79 to 1.99)* 1.05 (0.96 to 1.15) 2.00 (1.87 to 2.15)* 1.09 (0.97 to 1.22)
 Ex-smoker 1.83 (1.72 to 1.94)* 1.02 (0.94 to 1.12) 1.71 (1.58 to 1.86)* 1.15 (1.03 to 1.29)*
 Non-smoker 1.45 (1.41 to 1.49)* 1.03 (0.98 to 1.08) 1.48 (1.42 to 1.53)* 1.04 (0.97 to 1.11)
Alcohol consumption (day/mon)
 <2 1.42 (1.38 to 1.47)* 1.06 (1.01 to 1.11)* 1.45 (1.40 to 1.51)* 1.08 (1.01 to 1.14)*
 2–12 1.77 (1.70 to 1.85)* 0.98 (0.91 to 1.05) 1.77 (1.67 to 1.88)* 1.05 (0.95 to 1.16)
 ≥13 1.86 (1.69 to 2.05)* 1.04 (0.89 to 1.22) 1.77 (1.55 to 2.01)* 1.11 (0.90 to 1.36)
Hypertension
 Yes 1.20 (1.14 to 1.26)* 0.95 (0.87 to 1.02) 1.29 (1.22 to 1.37)* 0.97 (0.88 to 1.06)
 No 1.69 (1.65 to 1.74)* 1.06 (1.01 to 1.11)* 1.68 (1.62 to 1.75)* 1.10 (1.03 to 1.16)*
Diabetes
 Yes 1.21 (1.13 to 1.30)* 0.97 (0.87 to 1.09) 1.23 (1.13 to 1.34)* 0.97 (0.85 to 1.10)
 No 1.62 (1.57 to 1.66)* 1.04 (0.99 to 1.08) 1.63 (1.58 to 1.69)* 1.08 (1.02 to 1.14)*
SRH
 High 1.93 (1.83 to 2.03)* 1.02 (0.94 to 1.11) 2.02 (1.88 to 2.18)* 1.06 (0.94 to 1.19)
 Middle 1.76 (1.69 to 1.82)* 0.96 (0.91 to 1.02) 1.81 (1.72 to 1.90)* 1.00 (0.92 to 1.09)
 Low 1.54 (1.48 to 1.61)* 0.93 (0.87 to 0.99)* 1.63 (1.55 to 1.71)* 0.92 (0.85 to 0.99)
Average sleep duration (hr/day)
 <6 1.54 (1.47 to 1.61)* 0.99 (0.92 to 1.07) 1.67 (1.58 to 1.77)* 1.05 (0.96 to 1.16)
 6–6.9 1.68 (1.60 to 1.77)* 1.02 (0.94 to 1.11) 1.73 (1.62 to 1.85)* 1.04 (0.93 to 1.16)
 7–7.9 1.68 (1.60 to 1.76)* 1.01 (0.94 to 1.09) 1.68 (1.57 to 1.79)* 1.05 (0.95 to 1.17)
 ≥8 1.58 (1.51 to 1.66)* 1.07 (0.99 to 1.16) 1.44 (1.36 to 1.53)* 1.10 (1.01 to 1.21)
*

p<0.05; †according to Asia-Pacific guidelines, BMI is divided into 4 groups: underweight (<18.5 kg/m2), normal (18.5–22.9 kg/m2), overweight (23.0–24.9 kg/m2), and obese (≥25 kg/m2).

OR, odds ratio; KCHS, Korea Community Health Survey; CI, confidence interval; BMI, body mass index; SRH, self-rated health.

Table 5.

Ratio of weighted ORs for risk factors for the vulnerable group of counseling for stress and depression pre-, intra-, and post-pandemic, based on data obtained from the KCHS

Variables Counseling for stress
Counseling for depression
Overallv
Pre-pandemic
Intra-pandemic
Post-pandemic
Overall
Pre-pandemic
Intra-pandemic
Post-pandemic
Weighted OR (95% CI) Weighted OR (95% CI) Weighted OR (95% CI) Weighted OR (95% CI) Weighted OR (95% CI) Weighted OR (95% CI) Weighted OR (95% CI) Weighted OR (95% CI)
Age (yr)
 ≥71 (ref) 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
 19–30 1.71 (1.64 to 1.79)* 1.13 (1.07 to 1.19)* 2.29 (2.13 to 2.47)* 2.39 (2.12 to 2.69)* 1.05 (0.99 to 1.11) 0.73 (0.69 to 0.78)* 1.36 (1.24 to 1.48)* 1.39 (1.20 to 1.59)*
 31–40 1.83 (1.75 to 1.91)* 1.25 (1.19 to 1.31)* 2.43 (2.26 to 2.62)* 2.71 (2.41 to 3.04)* 0.97 (0.92 to 1.02) 0.75 (0.71 to 0.80)* 1.19 (1.08 to 1.30)* 1.36 (1.18 to 1.55)*
 41–50 1.50 (1.44 to 1.57)* 1.09 (1.04 to 1.14)* 1.91 (1.77 to 2.06)* 2.04 (1.82 to 2.28)* 0.92 (0.87 to 0.97)* 0.77 (0.73 to 0.82)* 1.07 (0.98 to 1.17) 1.13 (0.99 to 1.29)
 51–60 1.24 (1.19 to 1.30)* 1.08 (1.02 to 1.13)* 1.40 (1.30 to 1.51)* 1.33 (1.18 to 1.51)* 0.96 (0.91 to 1.01) 0.93 (0.88 to 0.98)* 1.02 (0.93 to 1.11) 0.99 (0.86 to 1.13)
 61–70 1.20 (1.14 to 1.25)* 1.16 (1.10 to 1.22)* 1.25 (1.15 to 1.35)* 1.15 (1.02 to 1.29)* 1.03 (0.98 to 1.09) 1.09 (1.02 to 1.15)* 1.04 (0.95 to 1.13) 0.94 (0.82 to 1.07)
Sex
 Male (ref) 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
 Female 1.81 (1.77 to 1.86)* 1.95 (1.89 to 2.00)* 1.72 (1.65 to 1.79)* 1.80 (1.68 to 1.92)* 2.11 (2.05 to 2.18)* 2.30 (2.21 to 2.39)* 2.05 (1.94 to 2.16)* 1.93 (1.77 to 2.10)*
Region of residence
 Rural (ref) 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
 Urban 1.12 (1.09 to 1.15)* 1.11 (1.08 to 1.14)* 1.14 (1.09 to 1.19)* 1.15 (1.08 to 1.23)* 1.12 (1.08 to 1.15)* 1.09 (1.05 to 1.12)* 1.16 (1.10 to 1.22)* 1.16 (1.06 to 1.26)*
BMI group†
 Underweight (ref) 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
 Normal 0.63 (0.60 to 0.67)* 0.68 (0.64 to 0.71)* 0.62 (0.57 to 0.67)* 0.54 (0.47 to 0.61)* 0.63 (0.59 to 0.67)* 0.66 (0.62 to 0.71)* 0.58 (0.53 to 0.65)* 0.64 (0.54 to 0.75)*
 Overweight 0.57 (0.54 to 0.60)* 0.62 (0.59 to 0.66)* 0.53 (0.49 to 0.58)* 0.47 (0.40 to 0.54)* 0.56 (0.52 to 0.60)* 0.60 (0.56 to 0.64)* 0.50 (0.44 to 0.55)* 0.58 (0.48 to 0.69)*
 Obese 0.75 (0.72 to 0.79)* 0.77 (0.73 to 0.81)* 0.71 (0.65 to 0.77)* 0.64 (0.56 to 0.74)* 0.69 (0.65 to 0.74)* 0.70 (0.65 to 0.75)* 0.60 (0.54 to 0.67)* 0.74 (0.62 to 0.88)*
Education
 College or higher education (ref) 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
 Elementary school or lower education 0.87 (0.84 to 0.90)* 1.27 (1.22 to 1.31)* 0.72 (0.67 to 0.76)* 0.64 (0.57 to 0.70)* 1.43 (1.37 to 1.49)* 2.01 (1.92 to 2.10)* 1.25 (1.16 to 1.34)* 1.14 (1.01 to 1.28)*
 Middle school 0.86 (0.83 to 0.90)* 1.17 (1.12 to 1.23)* 0.74 (0.69 to 0.79)* 0.75 (0.67 to 0.85)* 1.36 (1.30 to 1.43)* 1.77 (1.68 to 1.87)* 1.24 (1.14 to 1.35)* 1.21 (1.06 to 1.37)*
 High school 0.90 (0.87 to 0.92)* 1.06 (1.02 to 1.09)* 0.86 (0.82 to 0.90)* 0.79 (0.74 to 0.85)* 1.16 (1.12 to 1.21)* 1.39 (1.33 to 1.45)* 1.10 (1.04 to 1.17)* 1.08 (0.98 to 1.19)
Household income
 Highest quartile (ref) 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
 Lowest quartile 1.62 (1.56 to 1.68)* 2.00 (1.91 to 2.08)* 1.57 (1.48 to 1.68)* 1.72 (1.55 to 1.91)* 3.02 (2.88 to 3.16)* 3.36 (3.18 to 3.55)* 3.16 (2.93 to 3.41)* 3.53 (3.13 to 3.98)*
 Second quartile 1.09 (1.06 to 1.12)* 1.19 (1.14 to 1.23)* 1.18 (1.12 to 1.24)* 1.28 (1.19 to 1.39)* 1.56 (1.49 to 1.63)* 1.55 (1.47 to 1.63)* 1.74 (1.63 to 1.87)* 2.12 (1.91 to 2.35)*
 Third quartile 0.91 (0.88 to 0.94)* 0.92 (0.89 to 0.96)* 1.04 (0.98 to 1.09) 1.01 (0.92 to 1.09) 1.03 (0.98 to 1.08) 1.01 (0.95 to 1.07) 1.16 (1.07 to 1.25)* 1.27 (1.13 to 1.43)*
Smoking status
 Ex-smoker (ref) 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
 Smoker 1.19 (1.15 to 1.24)* 1.25 (1.19 to 1.31)* 1.29 (1.21 to 1.37)* 1.32 (1.19 to 1.46)* 1.23 (1.17 to 1.30)* 1.21 (1.14 to 1.28)* 1.41 (1.30 to 1.54)* 1.34 (1.18 to 1.51)*
 Non-smoker 1.12 (1.08 to 1.16)* 1.34 (1.29 to 1.40)* 1.06 (1.01 to 1.12)* 1.07 (0.99 to 1.16) 1.18 (1.13 to 1.23)* 1.37 (1.30 to 1.44)* 1.18 (1.10 to 1.26)* 1.06 (0.96 to 1.17)
Alcohol consumption (day/mon)
 <2 (ref) 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
 2–12 1.25 (1.22 to 1.28)* 1.38 (1.34 to 1.42)* 1.11 (1.06 to 1.16)* 1.19 (1.11 to 1.28)* 1.53 (1.48 to 1.59)* 1.68 (1.61 to 1.74)* 1.38 (1.30 to 1.46)* 1.41 (1.29 to 1.55)*
 ≥13 1.18 (1.12 to 1.24)* 1.15 (1.09 to 1.22)* 1.21 (1.11 to 1.32)* 1.29 (1.12 to 1.47)* 1.30 (1.22 to 1.40)* 1.32 (1.22 to 1.42)* 1.32 (1.17 to 1.48)* 1.39 (1.16 to 1.66)*
SRH
 High (ref) 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
 Middle 2.24 (2.14 to 2.34)* 2.42 (2.33 to 2.52)* 2.21 (2.10 to 2.32)* 2.09 (1.92 to 2.27)* 2.24 (2.14 to 2.34)* 2.49 (2.36 to 2.63)* 2.22 (2.07 to 2.38)* 2.10 (1.87 to 2.36)*
 Low 8.17 (7.82 to 8.53)* 7.06 (6.79 to 7.33)* 5.66 (5.36 to 5.97)* 5.17 (4.74 to 5.63)* 8.17 (7.82 to 8.53)* 10.01 (9.50 to 10.54)* 8.07 (7.52 to 8.66)* 6.99 (6.28 to 7.78)*
Average sleep duration (hr/day)
 <6 (ref) 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
 6–6.9 2.47 (2.39 to 2.55)* 2.69 (2.59 to 2.79)* 2.46 (2.33 to 2.60)* 2.41 (2.21 to 2.64)* 2.83 (2.71 to 2.95)* 2.92 (2.78 to 3.06)* 2.91 (2.71 to 3.13)* 2.90 (2.59 to 3.25)*
 7–7.9 1.16 (1.13 to 1.20)* 1.20 (1.16 to 1.25)* 1.20 (1.14 to 1.28)* 1.22 (1.11 to 1.34)* 1.16 (1.11 to 1.22)* 1.19 (1.13 to 1.25)* 1.22 (1.13 to 1.32)* 1.20 (1.07 to 1.36)*
 ≥8 1.33 (1.29 to 1.38)* 1.34 (1.29 to 1.40)* 1.26 (1.20 to 1.33)* 1.34 (1.22 to 1.46)* 1.61 (1.54 to 1.69)* 1.73 (1.65 to 1.82)* 1.49 (1.39 to 1.60)* 1.55 (1.38 to 1.73)*
*

p<0.05; †according to Asia-Pacific guidelines, BMI is divided into 4 groups: underweight (<18.5 kg/m2), normal (18.5–22.9 kg/m2), overweight (23.0–24.9 kg/m2), and obese (≥25 kg/m2).

OR, odds ratio; KCHS, Korea Community Health Survey; CI, confidence interval; BMI, body mass index; SRH, self-rated health.