Exploring the relationship between lifestyle factors and depressive symptoms in Korean adolescents amid the COVID-19 pandemic

Background

COVID-19 has brought about disruptions in the lives of adolescents, which pose a threat to mental health. While multiple studies have suggested a trend of increased depression during COVID-19, only few have explored the protective factors that could support their mental health during this critical period, highlighting a significant gap in the literature.

Methods

The current study investigated the association between lifestyle modifications and changes in COVID-19-induced depressive mood. By analyzing the data of 54,848 adolescents from a nationally representative sample of the Korea Youth Risk Behavior Web-based Survey (KYRBS), we examined the associations between four lifestyle behavior changes – increased physical activity, increased breakfast consumption, decreased alcohol use, and decreased smoking – and decreased depressive mood during COVID-19 using multinomial logistic regression.

Results

Our results indicated that all four lifestyle behavioral changes were associated with the decreased depressive mood in adolescents. Logistic regression model illustrated that the odds ratios (ORs) of decreased depressive mood for each lifestyle behavior change are (1) increased physical activity 2.481 (95% CI 2.311–2.663; p < 0.001); (2) increased breakfast 1.649 (95% CI 1.521–1.783; p < 0.001); (3) decreased drinking 3.169 (95% CI 2.677–3.752; p < 0.001), and (4) decreased smoking 7.113 (95% CI 6.009–8.420; p < 0.001). After accounting for all confounding variables, the odds ratios remained robust and significant.

Conclusions

This study is one of the first large-scale analyses on associations between lifestyle behavior modifications and perceived depressive mood in Korean adolescent population during COVID-19 pandemic. In our study, healthier lifestyle behaviors were significantly associated with a decrease in perceived depressive symptoms, even in individuals at a high risk for mental health issues. Reducing household challenges and enhancing social support can help drive positive lifestyle modifications. During the pandemic, policymakers must secure resources and services, including teletherapy and online tools, that are easily accessible for adolescents.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12888-025-06988-w.

Key points and relevance

• COVID-19 brought a number of changes in the lives of Korean adolescents’, which led to psychological distress.

• We employed four different lifestyle behavior modifications – increased physical activity, increased breakfast consumption, decreased alcohol consumption, and decreased smoking – and found that healthier modifications in adolescents’ lifestyle behavior are positively associated with a decrease in the depressive mood of adolescents.

• Even in a high-risk group of clinical depression, a relationship between lifestyle behavior modification and a decrease in adolescents’ depressive mood remained robust and positive.

• Physical activity and breakfast consumption are well-known for its positive impact on adolescents’ mental health beforehand COVID-19, and regarding decreased alcohol consumption and smoking, whether the adolescent is in an adverse surrounding must be accounted.

• In an advent of pandemics, such as COVID-19, policymakers should take it into consideration that healthier lifestyle modifications can be used to mitigate the negative impact of pandemic on adolescents’ mental health and employ various tools to safeguard adolescents’ mental well-being.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12888-025-06988-w.

Background

COVID-19 is a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic began in 2020. It causes a viral pneumonia outbreak and spreads from human to human by inhalation or contact with infected droplets. The incubation period for COVID-19 varies from 5 to 14 days. Therefore, 14-day medical observation period or quarantine for exposed and close contact persons is suggested to prevent the spread of the virus [1]. To protect susceptible people from COVID-19 transmission, the Korean government implemented a “social distancing” policy by encouraging remote work, limiting social gatherings, and closing public institutions, particularly schools [1]. On March 22, 2020, the government announced several intensified social distancing policies. These included advising more remote work, restricting open hours at after-school clubs, recreational facilities, religious facilities, and limiting mass gathering events in public [2]. In 2020, schools attempted to change their in-person classes to a hybrid of online and in-person courses during the spring semester (March to August). However, the second wave of COVID-19 in Korea occurred in August, prompting the Korean government to mandate higher levels of social distancing policies. These measures severely restricted the daily lives of adolescents, including a complete ban on gatherings of more than five people [3, 4].

While the Korean government prioritized preventing the transmission of COVID-19 through social distancing measures, such as school closures, restrictions on mobility, and limits on social interactions, these policies have had a considerable impact on the lives of adolescents. Notable changes in Korean adolescents’ physical, psychological, economic, and educational sectors [5–7] have significantly changed their daily lifestyle behaviors. Korean adolescents reported decreased physical activity [8], increased sedentary time [9], increased consumption of breakfast [6], reduced consumption of fast food [6], and shortened sleep duration [9] during the COVID-19 pandemic.

The disruption of daily life during the COVID-19 pandemic not only affected the routines of Korean adolescents but also had a profound impact on their mental health. Adolescents acquire social skills and establish lifestyle behaviors essential for mental well-being by engaging with personal, social, and health-related stimuli [10, 11]. However, the pandemic led to the sudden loss of structured educational and social activities– such as school curricula, extracurricular programs, peer interactions, and physical activity– making adolescents more vulnerable to mental health problems [12]. The developing brains of adolescents are malleable for constructive adjustments but are also vulnerable to mental stress. Research shows that half of all lifetime cases start by the age of 14 years, reaching 75% of lifetime prevalence by the age of 24 years [13]. During the pandemic, rates of depression, suicidal ideation, and stress awareness among Korean adolescents increased notably in 2021 [14]. Several previous studies have identified COVID-19 as a risk factor for heightened adolescent depression [3, 7, 12, 15–19]. This mental health burden is reflected in a recent study: a higher prevalence of depressive symptoms (31%), anxiety symptoms (31%), and sleep disturbances (42%) compared to the early pandemic [20]. Such trends are concerning, as childhood adversity can trigger long-term effects on brain development, leading to mental and behavioral disturbances through neurochemical and physiological imbalances [21].

Our literature review consistently highlights that lifestyle behavior changes during COVID-19, such as reduced physical activity or disrupted eating habits, are closely associated with an increased risk of depression in adolescents [15, 17, 22]. In a meantime, children and adolescents may proactively adopt positive lifestyle changes to mitigate psychological distress caused by the pandemic [23]. Interestingly, these strategies for coping with pandemics have historical roots. Back in 1918, a strategy to survive from the pandemic was to adhere to good hygiene, nutrition, fresh air, and rest [24]. This approach remains relevant today, as recent systematic reviews reported that healthier changes in lifestyle behaviors can play an essential role in reducing the risk of mental health problems [25]. Motivated by these findings, we questioned whether healthier lifestyle behavior changes in Korean adolescents are related to a decrease in COVID-19-induced depressive mood.

Understanding which positive lifestyle changes benefit adolescents’ mental health may lead to the development of effective strategies to safeguard their well-being during social crises. For instance, physical activity is widely recognized for its antidepressant effects. A meta-analysis indicated that engaging in physical activity might effectively alleviate depressive symptoms in adolescents with depression [26]. Likewise, dietary behavior patterns also have a substantial impact on mental health. Regular breakfast consumption is associated with improved mood, cognitive function, and overall well-being [27]. Moreover, while the relationship between substance use (like alcohol and tobacco) and depression is not strictly causal, depression can predict higher substance use among adolescents [28]. A study of on South Korean adolescents reported that depression is strongly linked to alcohol and tobacco use among youths.

Given these insights, we propose that encouraging positive changes in physical activity level, nutrition, and substance use reduction can be an effective strategy for mitigating depression among adolescents during the pandemic. Based on these considerations, our research aims to explore whether healthier lifestyle modifications are associated with decreased depressive moods in Korean adolescents during the COVID-19 pandemic. Therefore, we asked the following questions: First, are lifestyle modifications correlated with decreased COVID-19-induced depressive mood? Based on prior knowledge, we hypothesized that more physical activity, more breakfast consumption, and less alcohol and tobacco use would be associated with decreased COVID-19-induced depressive mood. Second, based on the association between lifestyle modifications and decreased depressive mood due to COVID-19, how can we use this information to protect adolescents’ mental health in pandemic situations such as COVID-19?

Methods

Study population

Data for this study were obtained from the 21st Korea Youth Risk Behavior Web-based Survey (KYRBS), conducted in 2021 by the Korea Centers for Disease Control and Prevention. A nationally representative sample of Korean adolescents aged 12–18 underwent the KYRBS, which included 113 questions across 16 domains of health-risk behaviors [14]. A representative sample was selected using a multistage clustered probability design based on local districts and school levels (middle, academic high, and specialized high school). Fifty-four thousand eight hundred forty-eight students (response rate: 92.9%) from 796 schools (response rate: 99.5%) were included. Written informed consent was obtained from all participants at the time of data collection. All data used in this study were collected through self-report surveys and were fully anonymized before the analysis. This study included 54,848 adolescents aged 12–18 who completed an online health examination. The study procedure was approved by the Institutional Review Board of Wonju Severance Christian Hospital in Wonju, Korea (CR324306).

Measures

Participant self-reported for five different categories through the question, “This is about specific changes in your daily life owing to the COVID-19 pandemic. What differences have you noticed compared to before the COVID-19 outbreak?”: physical activity, skipping breakfast, drinking, smoking, and depressive mood. Participants were divided into five groups according to the changes in lifestyle behaviors due to COVID-19: (1) Significantly Increased, (2) Moderately Increased, (3) No Change, (4) Moderately Decreased, and (5) Significantly Decreased.

For an outcome variable, perceived change in depressive mood due to COVID-19 was assessed. We classified the participants into two categories, utilizing the question above: (1) Decreased depressive mood and (2) Not decreased depressive mood. Participants who reported that their depressive mood was (4) moderately or (5) significantly decreased were categorized into the ‘decreased depressive mood’ group. Participants who reported that their depressive mood had (1) significantly increased, (2) moderately increased, or (3) remained unchanged were categorized into the ‘not decreased depressive mood’ group.

For the exposure variables, changes in physical activity, skipping breakfast, drinking, and smoking due to COVID-19 were assessed. To compare the impact of healthier changes in lifestyle behaviors, the answers to each change were classified into two categories: (1) Increased vs. Not increased physical activity; (2) Increased vs. Not increased breakfast; (3) Decreased vs. Not decreased drinking and (4) Decreased vs. Not decreased smoking. To highlight the impact of healthier changes, those who reported that their behavior had significantly or moderately increased were categorized in the ‘increased behavior’ group. In contrast, those who indicated that their behavior had considerably decreased, moderately decreased, or remained unchanged were categorized into the ‘not increased behavior’ group. Similarly, to compare decreased behavior with non-decreased behavior, participants who reported significantly or moderately decreased behavior were categorized into the ‘decreased behavior’ group, while those who indicated that their behavior had considerably increased or moderately increased or remained unchanged were categorized into the ‘not decreased behavior’ group.

The demographic characteristics of the control variables included sex, age, residential area, socioeconomic status, sleep duration, subjective health status, academic achievement, and exposure to violence. Residential areas were divided into three categories: large cities (major cities), small cities (small-to middle-sized regions), and rural (country or rural areas). Socioeconomic status was assessed using the question, “What is your family’s economic status?” The five possible response categories (very high, high, middle, low, and very low) were combined into three subgroups: high (very high or high), medium (middle), and low (very low or low). Sleep hours were divided into under 6 h and six or more hours. Subjective health status was assessed using the question, “How do you usually perceive your health condition?” Five possible response categories (very healthy, healthy, normal, unhealthy, and very unhealthy) were combined into three subgroups: healthy (very healthy or healthy), average (standard), and harmful (unhealthy or very unhealthy). We also evaluated the participants’ academic achievement using the question, “How have your academic achievements been in the last 12 months?” Five possible response categories were classified under the socioeconomic status mentioned above. To examine exposure to violence, we used the question, “Have you had any experience of receiving treatment at a hospital for violence (being physically assaulted, threatened, or bullied) from friends or superiors?” (Yes/No).

Psychosocial factors included the duration of smartphone use, drug abuse, generalized anxiety disorder, stress level, sleep satisfaction, loneliness, suicidal ideation, suicide attempts, and suicide plans. Smartphone use time was assessed by the question, “On an average school day, how many hours do you use a smartphone?” Participants were divided into four groups according to the time spent in smartphone use: (1) less than one h; (2) 1–2 h; (3) 3–4 h; and (4) 5 h or more a day [29]. To examine drug abuse, we utilized the question, “Excluding therapeutic purposes, have you habitually used any drugs or substances up to now?” (Yes/No). Generalized anxiety disorders were evaluated using the Generalized Anxiety Disorder-7 (GAD-7) questions. The GAD-7 is a recently developed, easy-to-use 7-item scale based on the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) to identify likely cases of GAD [30]. The participants were classified into a low-risk group (score ≥ 10) and a high-risk group (score ≤ 9). The subjective stress level of participants was assessed by the question, “How much stress do you usually feel?” The five possible answers (very much, a lot, a little, not much, or not at all) were classified into two groups: high (very much, a lot, or a little) and low (neither much nor not at all). We evaluated the sleep satisfaction by asking, “Do you think the amount of sleep you’ve had in the last seven days has been sufficient for fatigue recovery?” They classified the five possible answers (very satisfied, satisfied, not so satisfied, unsatisfied, and very unsatisfied) into three groups: satisfied (very satisfied, satisfied) and unsatisfied (not so satisfied, unsatisfied, or very unsatisfied). The participants’ loneliness was examined by asking, “How frequently have you felt loneliness in the last 12 months?” Five responses were possible: not at all, rarely, often, frequently, and always. Respondents were divided into two groups: lonely (usually, frequently, and consistently) and not lonely (seldom, not at all). To determine whether suicidal thoughts, plans, or attempts had occurred, three questions assessed suicidal ideation, plans, and attempts over the past 12 months (Yes/No).

Statistical analysis

The participants’ characteristics according to the change in depressive mood were summarized using either a Pearson chi-square test for categorical variables with Bonferroni correction or an independent t-test for continuous variables. We also performed a chi-square test to investigate the proportion of responses to changes in each lifestyle behavior.

To analyze the associations between the change in each lifestyle behavior and decreased depressive mood, binomial logistic regression tests were performed using “each healthier lifestyle behavior change” as the principal predictor and decreased depressive mood as the primary outcome variable. As several demographic characteristics and psychosocial factors were statistically significant, we calculated the odds ratio for each healthier lifestyle behavior change after adjusting for age, sex, residential area, socioeconomic status, hours of sleep, subjective health status, academic achievement, exposure to violence, smartphone use time, generalized anxiety disorder, subjective stress level, sleep satisfaction, loneliness, suicidal ideation, suicide plans, and suicide attempt; other lifestyle behaviors are also included as cofounders to isolate the effect of each lifestyle modification. To evaluate whether the influence of each lifestyle behavior manifested differently within the psychologically high-risk group, we categorized the subjects into high- and low-risk groups and calculated the odds ratios (ORs) for each group. All statistical analyses were performed using the IBM SPSS 27.0 (IBM Corp., Armonk, NY, USA), and p-values < 0.05 were considered statistically significant.

Results

The significant findings regarding demographic characteristics according to changes in depressive mood due to COVID-19 are summarized in Table 1. Among the 54,848 participants, 5,543(10.1%) reported decreased depressive mood due to COVID-19. The results showed that the proportion of boys, residential areas in small cities and rural areas, high socioeconomic status, and moderate-to-low academic achievement showed decreased depressive mood during COVID-19 compared to the not decreased group. Korean adolescents with a positively perceived health status and sufficient sleep (more than six hours) reported decreased depressive mood. As shown in Table 2, individuals without psychological risk also exhibited a significant decrease in depressive mood, such as no exposure to violence, low-risk group of GAD-7, low subjective stress level, no loneliness, no suicidal ideation, no suicide plan, and no suicide attempt. Finally, it is interesting to note that both 1–2 h and more than five hours of smartphone use resulted in a decreased depressive mood. (All p < 0.05).

Table 1.

Demographic characteristics of participants according to a decrease in depressive mood due to COVID-19 (N = 54,848)

Characteristics	Decreased depressive mood due to COVID-19			t/x or F	P-value
	Total sample	Decreased	Not Decreased
	N = 54,848 (%)	N = 5543 (10.1%)	N = 49,305 (89.9%)
Sex				624.943	< 0.001
Boys	28,401 (51.8)	3752 (67.7)	24,649 (50.0)
Girls	26,447 (48.2)	1791 (32.3)	24,656 (50.0)
Age				0.063	0.801
Mean (SD)	15.09	15.2	15.03
Area of residence				7.604	0.022
Large city	23,862 (43.5)	2339 (42.2)	21,523 (43.7)
Small city	26,864 (49.0)	2745 (49.5)	24,119 (48.9)
Rural area	4122 (7.5)	459 (8.3)	3663 (7.4)
Socioeconomic status				76.803	< 0.001
High	21,568 (39.3)	2477 (44.7)	19,091 (38.7)
Middle	27,077 (49.4)	2461 (44.4)	24,616 (49.9)
Low	6203 (11.3)	605 (10.9)	5598 (11.4)
Sleep Hour				69.932	< 0.001
< 6 h	8731 (17.6)	646 (13.3)	8085 (18.1)
≥ 6 h	40,822 (82.4)	4218 (86.7)	36,604 (81.9)
Subjective Health Status				163.959	< 0.001
Healthy	35,529 (64.8)	4021 (72.5)	31,508 (63.9)
Normal	14,298 (26.1)	1145 (20.7)	13,153 (26.7)
Unhealthy	5021 (9.2)	377 (6.8)	4644 (9.4)
Academic Achievement				131.283	< 0.001
High	20,528 (37.4)	1722 (31.1)	18,806 (38.1)
Moderate	16,903 (30.8)	1743 (31.4)	15,160 (30.7)
Low	17,417 (31.8)	2078 (37.5)	15,339 (31.1)
Violence				14.457	< 0.001
No	54,073 (98.6)	5433 (98.0)	48,640 (98.7)
Yes	775 (1.4)	110 (2.0)	665 (1.3)

Table 2.

Psychosocial characteristics of participants according to a decrease in depressive mood due to COVID-19 (N = 54,848)

Characteristics	Decreased depressive mood due to COVID-19			t/x or F	P-value
	Total sample	Decreased	Not Decreased
	N = 54,848 (%)	N = 5543 (10.1%)	N = 49,305 (89.9%)
Smartphone use time				14.328	0.002
< 1 h	870 (1.6)	86 (1.6)	784 (1.6)
1 h ~ 2 h	11,930 (22.5)	1241 (23.3)	10,689 (22.4)
3 h ~ 4 h	18,575 (35.0)	1735 (32.6)	16,840 (35.2)
> 4 h	21,748 (40.9)	2254 (42.4)	19,494 (40.8)
Drug Abuse				0	0.989
No	54,453 (99.3)	5503 (99.3)	48,950 (99.3)
Yes	395 (0.7)	40 (0.7)	355 (0.7)
Generalized Anxiety Disorder				210.667	< 0.001
Low Risk	48,143 (87.8)	5201 (93.8)	42,942 (87.1)
High Risk	6705 (12.2)	342 (6.2)	6363 (12.9)
Stress Level				306.836	< 0.001
No	10,377 (18.9)	1533 (27.7)	8844 (17.9)
Yes	44,471 (81.1)	4010 (72.3)	40,461 (82.1)
Sleep Satisfactory				355.187	< 0.001
Satisfied	12,839 (34.8)	1815 (48.7)	11,024 (33.2)
Not Satisfied	24,098 (65.2)	1912 (51.3)	22,186 (66.8)
Loneliness				616.974	< 0.001
No	26,321 (48.0)	3536 (63.8)	22,785 (46.2)
Yes	28,527 (52.0)	2007 (36.2)	26,520 (53.8)
Suicide Ideation				175.264	< 0.001
No	6956 (12.7)	5151 (92.9)	42,741 (86.7)
Yes	47,892 (87.3)	392 (7.1)	6564 (13.3)
Suicide Attempt				13.634	< 0.001
No	53,603 (97.7)	5456 (98.4)	48,147 (97.7)
Yes	1245 (2.3)	87 (1.6)	1158 (2.3)
Suicide Plan				14.026	< 0.001
No	52,642 (96.0)	5372 (96.9)	47,270 (95.9)
Yes	2206 (4.0)	171 (3.1)	2035 (4.1)

Table 3 illustrates the chi-squared analysis of changes in depressive mood due to COVID-19 according to changes in lifestyle behaviors. The proportion of decreased depressive mood due to COVID-19 was significantly different between individuals who adopted healthier behaviors, such as increased physical activity, improved breakfast consumption, reduced drinking, and decreased smoking, and those who did not.

Table 3.

Lifestyle behavior changes according to a decrease in depressive mood due to COVID-19

Lifestyle behaviors	Change in depressive mood due to COVID-19		χ2	P-value
	Decreased	Not Decreased
	N = 5543 (10.1%)	N = 49,305 (89.9%)
Increased Physical activity			1841.616	< 0.001
Not increased	3205 (57.8)	40,549 (82.2)
Increased	2338 (42.2)	8756 (17.8)
Increased Breakfast			3092.23	< 0.001
Not increased	3502 (63.2)	44,214 (89.7)
Increased	2041 (36.8)	5091 (10.3)
Decreased Alcohol Use			14705.944	< 0.001
Not decreased	1605 (29.0)	44,818 (90.9)
Decreased	3938 (71.0)	4487 (9.1)
Decreased Smoking			15382.869	< 0.001
Not decreased	1559 (28.1)	44,959 (91.2)
Decreased	3984 (71.9)	4346 (8.8)

Decreased depressive mood was significantly associated with healthier lifestyle behavioral changes due to COVID-19: increased physical activity, increased breakfast consumption, reduced drinking, and decreased smoking (Table 4). In the binomial logistic regression analysis, the odds ratios (ORs) of decreased depressive mood for each lifestyle behavior change were calculated as follows: increased physical activity, 2.481 (95% Confidence Interval (CI) 2.311–2.663; p < 0.001); increased breakfast, 1.649 (95% CI 1.521–1.783; p < 0.001); decreased drinking, 3.169 (95% CI 2.677–3.752; p < 0.001), and reduced smoking, 7.113 (95% 6.009–8.420; p < 0.001). Decreased smoking showed the strongest association with decreased depressive mood due to COVID-19, whereas increased breakfast consumption showed the weakest positive association.

Table 4.

Odds ratios and adjusted odds ratios (95% confidence interval) for decreased depressive mood due to COVID-19

Lifestyle behaviors	Univariate				Multivariate
	OR	95% CI	P-value	AOR		95% CI	P-value
Increased Physical activity	2.481	2.311–2.663	< 0.001	2.222		2.012–2.454	< 0.001
Increased Breakfast	1.649	1.525–1.783	< 0.001	1.628		1.461–1.814	< 0.001
Decreased Alcohol Use	3.169	2.677–3.752	< 0.001	3.263		2.584–4.120	< 0.001
Decreased Smoking	7.113	6.009–8.420	< 0.001	7.030		5.571–8.872	< 0.001

The multivariate analyses were adjusted for age, sex, residential area, socioeconomic status, hours of sleep, subjective health status, academic achievement, exposure of violence, smartphone use time, generalized anxiety disorder, subjective stress level, sleep satisfactory, loneliness, suicide ideation, suicide plan, and suicide attempt. OR = Odds Ratios. CI = Confidence Interval. AOR = Adjusted Odds Ratios

After controlling for all potential confounding variables, the lifestyle behavior changes remained strongly associated with the outcome in the binomial logistic regression analysis. The adjusted ORs were 2.222 (95% CI 2.012–2.454; p < 0.001), 1.628 (95% CI 1.461–1.814; p < 0.001), 3.263 (95% CI 2.584–4.120; p < 0.001), 7.030 (95% CI 5.571–8.872; p < 0.001) for increased physical activity, increased breakfast consumption, decreased drinking, and for decreased smoking respectively (Table 4). Decreased depressive mood due to COVID-19 illustrated the strongest association with increased physical activity and the weakest association with increased breakfast consumption. Particularly, male and high socioeconomic status participants presented stronger associations between decreased depressed mood and healthier lifestyle modifications. [See Additional file 1 and Additional file 2]

To explore if the benefits of healthier behaviors persist in individuals within the psychologically high-risk group, the high-risk and low-risk groups for clinical depression were compared (Fig. 1). Even the high-risk groups reported a significant relationship between each lifestyle behavior change and decreased depressive mood. The impact of other psychosocial factors on the association between each lifestyle behavior modification and decreased depression is shown in additional file 3 [see Additional file 3].

Fig. 1.

Effects of lifestyle behavior modifications between high- and low-risk groups of clinical depression. Odds ratios for decreased depressive mood in each lifestyle behavior modification are illustrated. OR = Odds Ratios. CI = Confidence Interval. AOR = Adjusted Odds Ratios

Discussion

We investigated the relationship between changes in lifestyle behaviors due to COVID-19 and decreased depressive moods in Korean adolescents. Healthier changes in lifestyle behaviors, such as more physical activity, more breakfast consumption, less drinking, and less smoking, had positive associations with decreased depressive mood due to COVID-19. After adjusting for covariates, decreased depressive mood maintained strong associations with healthier changes in lifestyle behaviors due to COVID-19.

It is well established that physical activity positively affects mood states through various physiological and biochemical mechanisms [31]. Previous studies have reported that physical activity alleviates the adverse effects of COVID-19 on adolescents’ mental health [32, 33]. Our findings are consistent with previous studies, as increased physical activity was strongly associated with decreased depressive mood. During the COVID-19 pandemic, Korean adolescents have experienced fewer outdoor activities. In 2020, the Korean government implemented a strict social distancing policy, banning gatherings of five or more people, limiting indoor and outdoor sports facilities, and closing schools, academic facilities, and workplaces. These strict policies must have played a role by taking away proper settings for exercise. Moreover, due to the high academic pressure, Korean students predominantly lead a sedentary lifestyle. According to the guidelines from American Academy of Paediatrics, adolescents should not spend more than 2 h per day in screen-based activities [34]. However, Korean students spend more than six sedentary hours solely on academic activities [35]. Given the already prolonged sedentary behavior, it is crucial to emphasize the need for increased physical activity, especially during the pandemic, when the sedentary behavior tends to rise. Therefore, policymakers should secure a proper level of physical activity by adding supplementary online PE classes and creating an outdoor low-density architecture [36]. Creating movement-friendly environments for Korean students can encourage greater physical activity, which may also serve as an effective strategy for alleviating the depressive symptoms exacerbated by the COVID-19 pandemic.

The importance of regular breakfast eating is accentuated in Korea because skipping breakfast has shown an association with suicidal behaviors in multiple studies [37–39]. In this study, breakfast consumption was shown to have a positive association with decreased depressive mood, and this finding is consistent with previous studies on the relationship between regular breakfast and youth mental health [40, 41]. Although the exact mechanism between regular breakfast and better mental health is yet to be discovered, two aspects of breakfast seem to have contributed to adolescents’ mental health: (i) the biochemical advantages of breakfast and (ii) social benefits. First, breakfast fuels carbohydrates converted into glucose and changes acetylcholine, insulin, serotonin, glutamate, and cortisol levels [42]; serotonin is a neurotransmitter that regulates depressive symptoms, irritable mood, and cognitive function [42]. Breakfast benefits adolescents’ cognitive function, mood regulation, and behavior by providing essential nutrients for brain function. A previous study reported that skipping breakfast was associated with an increased stress risk and depressive mood, specifically in Korean adolescents [38]. In addition, the social perspectives of breakfast must be underscored. Increasing breakfast eating is linked to more social gatherings around the Table [43]. Gathering around the table, adolescents can feel support from their families, which might favor mood and family functioning [43]. Parental involvement also take part in breakfast encouragement; maternal encouragement of breakfast is significantly correlated with a greater breakfast consumption of adolescents [44]. Breakfast benefits adolescents through biochemical mechanisms, while parental involvement and social gatherings further enhance its positive effects on their well-being. Overall, several positive aspects associated with regular breakfast consumption may collectively contribute to improved mental well-being.

Compared to Western countries, Korea has reported a lower prevalence of alcohol and substance use among adolescents [45, 46]. It is also evident in national data, which indicate that the alcohol and tobacco use among Korean adolescents had continuously decreased from 2005 to 2021 [47]. This trend can be attributed to the Korean government’s efforts: promoting “No Smoking Education Project”, raising cigarette prices, and restricting smoking area for non-smokers. These policies reinforced social norms discouraging smoking among adolescents [48]. Korea’s collectivist culture, which prioritizes group harmony and family reputation, may deter adolescents from behaviors like drinking and smoking. However, despite these long-standing cultural and policy-driven deterrents, the pandemic introduced new challenges, which led to the slowdown in the decline of substance use.

Peer reputation and parental or household factors play a critical role in adolescent substance use patterns. However, with school lockdowns during the pandemic, students inevitably spent more time at home, shifting the influence from peer groups to family environments. This prolonged time within the household emerged as both a protective and risk factor for adolescent substance use—offering increased parental supervision for some while exacerbating family stress and conflict for others. Some adolescents experience limited access to substances from increased parental presence [49]. On the other hand, some adolescents experience the exposure to problematic situation, such as parental substance use, family dysfunction, and domestic violence from longer family time [50, 51]. Notably, COVID-19-induced stress within household led to an increase in family conflicts and dysfunction [49, 52]. In South Korea, there was a reported rise in domestic incidents, familial discord, and intentional injuries during social distancing [53]. These heightened tensions and conflicts in families during the pandemic were associated with maladaptive coping strategies of increased substance use [54, 55], as well as earlier initiation of substance use [56, 57]. Given the well-established link between stress and substance misuse, it is essential to recognize that depression and substance misuse share important risk factors, such as anxiety, family conflict, and economic stress. In this study, both decreased drinking and decreased smoking were strongly associated with decreased depressive mood. This suggests that lower exposure to these risk factors– through increased parental supervision or lower stress levels– may contribute to improved mental well-being [58].

Even though the history of depression can significantly influence an individual’s lifestyle choices, our findings suggest that lifestyle modifications can still play a crucial role in maintaining psychological well-being and mitigating depression, even in highly vulnerable individuals. Adolescents with pre-existing mental health conditions may be more vulnerable to developing symptoms during the pandemic, necessitating tailored interventions [59–61]. In our study, even among adolescents at high-risk for clinical depression, positive lifestyle modifications were linked to improvements in depressed mood. This result aligns with previous research showing adolescents predisposed to depression also experienced relief from depressive mood through living healthier lives [62–64]. These results highlight the importance of fostering a healthier lifestyle as a crucial intervention in safeguarding adolescent mental health, particularly for those at elevated risk of developing mood disorders; therefore, ensuring that adolescents have the necessary resources and support to adopt and maintain healthy behaviors is essential for long-term mental health benefits.

Living in highly competitive and academically demanding society, Korean students are already living under high stress. In the time of pandemic, when the psychological stress peaks, trying to maintain healthy life is vital to secure mental well-being. To build a comprehensive support system, individual, familial, and social factors need to work in tandem. A cohesive family environment is associated with more significant psychological adjustment [58]. However, most households experienced economic hardship, increased parental stress, and other challenges that affected family well-being [65, 66]. In addition, Korean families found it challenging to spend intensive time with their family, to share gendered family responsibilities, and to support other families [66]. Stress from negative family dynamics was amplified in lower socioeconomic status, increasing risks for depression and anxiety [67, 68]. This underscores the elevated risk of depression in socially disadvantaged children during the COVID-19 pandemic. Social support networks also have been identified as key factors in supporting individuals through mental health challenges [69]. Virtual support groups, online therapy sessions, and community-based initiatives that offer social connection can help mitigate the isolation that often exacerbates depression. Students reported the alleviation of stress by staying close to online friends [70], and digital interventions can alleviate the depressions from COVID-induced stressors [71], even in a single session [72]. Governmental departments have a significant role to play in supporting mental health during this time. Policies that ensure access to public services, including mental health hotlines, community outreach programs, and health campaigns that emphasize the importance of self-care, nutrition, and physical activity, can help individuals overcome barriers to lifestyle changes [21].

Limitations

This study had some limitations. First, the selection of variables was limited as this study was a secondary analysis of the KYRBS data. As mentioned previously, the study did not include variables related to relationships with parents or family environments to assess the influence of a longer time at home. In addition, some details were missing for each variable. For instance, the type of physical activity was not specified; therefore, the analysis did not include an individual’s preference for physical, aerobic, or anaerobic activity. Second, the measure of depressive mood was relied solely on self-reports. Students were not assessed by clinicians or clinician-related scale (i.e., Hamilton Rating Scale for Depression), so the objective measure of change in depressed mood is not included in this study. Next, this study does not account for the pre-pandemic mental health status of the participants. To eliminate these limitations and reinforce this study, for further evaluations, we can take genetic predisposition, personality traits, or social support systems into account for the established associations between lifestyle behavior modifications and perceived depressed mood. Thus, the confounding influence of pre-existing psychiatric condition is not sufficiently incorporated into this analysis. Finally, this was a cross-sectional study, and the data could not be used to identify causal relationships between the variables. The causality between variables warrants further exploration in future research.

Nevertheless, this study has several strengths. This is the first nationally representative study on positive lifestyle changes and decreased depressive mood. Lifestyle behavioral changes, including physical activity related to breakfast and substance use, cover several factors in Korean students’ daily routines. The additional factors discussed in this study should be considered for further research, such as family environment, child-parent relationship, and social support. Additionally, a follow-up study of changes in lifestyle behaviors during the readjustment period and students’ mood changes during the post-COVID-19 era should be conducted to expand our understanding of lifestyle behavior changes and mood regulation.

Conclusion

The COVID-19 pandemic has led to unprecedented changes in lives of Korean adolescents who usually have a routine that is heavily anchored in school. However, the emergence of a detrimental virus has forced social isolation and home confinement, and this change caused Korean adolescents to modify their lifestyle behaviors that are often associated with negative impacts on mood. Yet, some modifications have been shown to related to alleviated depressive mood in adolescents, such as more physical activity, regular breakfast, less smoking, and less alcohol consumption. In our study, healthy lifestyle behaviors are positively associated with decreased depressive mood due to COVID-19. These associations remained robust even after adjusting confounding variables, suggesting that the promotion of lifestyle modifications could be a potent strategy to mitigate depressive symptoms. Therefore, an integrated approach, incorporating psychiatric treatment along with these lifestyle interventions, is vital for enhancing mental well-being, particularly in the context of the ongoing COVID-19 pandemic.

Electronic supplementary material

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Abbreviations

CI

Confidence Interval

KYRBS

Korea Youth Risk Behavior Web-based Survey

ORs

The odds ratios

PE

Physical Education

Author contributions

YL conceived of the presented idea and performed the computations. YL, EJ, and SP verified the analytical methods. YL was a major contributor in writing the manuscript. JL supervised the project.

Funding

This work was supported by the Government of the Republic of Korea (Ministry of Science and ICT, MSIT) and the National Research Foundation of Korea (NRF) under grant number (NRF-RS-2024-00466764, FY2025). This research was also supported by the Basic Science Research Program through the NRF, funded by the Ministry of Education (RS-2023-00240674).

Additionally, this work 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 (RS-2024-00439956).

Data availability

The data supporting the findings of this study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

The study was conducted in accordance with the guidelines of the Declaration of Helsinki and approved by Wonju Severance Christian Hospital Institutional Review Board (CR324306). As this study involved secondary analysis of de-identified public data, the requirement for informed consent was waived by Wonju Severance Christian Hospital Institutional Review Board (CR324306).

Consent for publication

Not applicable—no individual details, images or videos used.

Competing interests

The authors declare no competing interests.

Clinical trial number

Not applicable.