Front. Psychiatry Frontiers in Psychiatry Front. Psychiatry 1664-0640 Frontiers Media S.A. 10.3389/fpsyt.2025.1651630 Psychiatry Original Research Longitudinal association of breakfast and midnight snacks with depressive symptoms in China multi-ethnic adolescents Xu Honglv 1 2 * Zhang Gaohong 1 Liu Zihan 1 2 Xue Xiaolu 3 Hu Dongyue 1 2 Yang Jieru 1 2 Jia Jing 1 Zhang Xuemei 1 1 School of Medicine, Kunming University, Kunming, China 2 Community Nursing Research Team of Kunming University, Kunming, Yunnan, China 3 School of Nursing, Yunnan University of Chinese Medicine, Kunming, China

Edited by: Tomoya Hirota, University of California, San Francisco, United States

Reviewed by: Chen Hong, First Affiliated Hospital of Wenzhou Medical University, China

Shu Wang, Capital Medical University, China

*Correspondence: Honglv Xu, x___hl@126.com

09 10 2025 2025 16 1651630 22 06 2025 09 09 2025 Copyright © 2025 Xu, Zhang, Liu, Xue, Hu, Yang, Jia and Zhang. 2025 Xu, Zhang, Liu, Xue, Hu, Yang, Jia and Zhang

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

 Introduction

Studies have suggested a link between dietary behavior and adolescent depressive symptoms, but longitudinal data are scarce. This study examines the longitudinal association of breakfast and midnight snacks consumption with depressive symptoms among multi-ethnic adolescents in China.

 Methods

From October 2022 to October 2024, 1,693 middle school students (52.3% females) from Yunnan Province participated in five follow-up surveys (T1-T5) conducted every six months. Breakfast and midnight snacks consumption were assessed using questionnaires, and depressive symptoms were measured using Children’s Depression Inventory. The latent growth curve model was analyzed using Mplus software to assess the potential growth trajectories of breakfast days, midnight snacks days, and depressive symptom scores across five time points. The generalized estimation equation model was applied to examine the association between the number of breakfast and midnight snacks days and depressive symptom scores. Two models were established: Model 1 was unadjusted, without controlling any variables; Model 2 was adjusted for demographic variables and other potential confounders influencing depressive symptoms. A restricted cubic spline analysis was used to examine the relationship between the number of breakfast days per week, midnight snacks days per week, and depressive symptoms.

 Results

The prevalence of depressive symptoms increased from 26.3% at T1 to 37.3% at T5 (P < 0.01). After adjusting for confounders, breakfast frequency (β = -0.71, 95%CI: -0.87-0.56) and midnight snacks frequency in males (β = 0.39, 95%CI: 0.24 - 0.55) and females (β = -0.77, 95%CI: -0.92 - -0.63; β = 0.17, 95%CI: 0.02 - 0.32) were associated with depressive symptoms (all P < 0.05). Males eating breakfast and midnight snacks fewer than three days and more than four days, respectively, per week, and females eating breakfast and midnight snacks fewer than four days and more than two day, respectively, per week, had an increased risk of depressive symptoms.

 Discussion

Skipping breakfast and eating midnight snacks are related to depressive symptoms in multi-ethnic Chinese adolescents. Addressing unhealthy eating behaviors is critical for preventing and mitigating adolescent depressive symptoms.

 adolescent depressive symptoms breakfast midnight snacks longitudinal study section-in-acceptance Adolescent and Young Adult Psychiatry Introduction

Adolescent depression is a significant public health concern. This developmental stage is marked by rapid social, emotional, and cognitive changes, as well as major life transitions (1). Adolescence is also the peak period for depression onset (2) and represents a substantial disease burden in this age group (3, 4). Furthermore, depression is a key risk factor for self-harm and suicidal behaviors among adolescents (5, 6). Globally, the incidence and prevalence of depressive symptoms in adolescents are increasing (7–9). A representative study in Germany reported a prevalence of 18.4%, with both the severity and frequency of depressive symptoms being higher in females than in males. Additionally, depressive symptoms were found to increase with age (10). The prevalence of depressive symptoms among adolescents in the United exceeds 30% (11). Numerous studies have examined the prevalence of depressive symptoms among adolescents in developing countries. In Malaysia and India, reported prevalence rates range from 26.2% to 52.3%. In Bangladesh, 25.0% of adolescents experience depressive symptoms, with a higher prevalence in females (30.0%) compared to males (19.0%) (12). In China, the prevalence of depressive symptoms among adolescents is close to 40% (13). However, data on the prevalence of depressive symptoms among multi-ethnic adolescents in western China remain limited. Existing research suggests that depressive symptoms are influenced by multiple factors, including academic pressure, family stress, physical activity, screen time, and physical literacy (14–18). Recently, the relationship between dietary behaviors and depressive symptoms in adolescents has gained increasing attention.

Emerging evidence suggests that healthy dietary patterns, such as adherence to the Mediterranean diet, are negatively associated with depressive symptoms (19). In contrast, unhealthy dietary behaviors— including frequent snacking, skipping breakfast, consuming sugar-sweetened beverages, and eating ultra-processed foods —are positively linked to depressive symptoms in adolescents (20–23). Previous research has primarily examined the relationship between breakfast consumption and adolescent mental health (24, 25). Systematic reviews and meta-analyses indicate that skipping breakfast is positively associated with an increased risk of depressive symptoms in adolescents (25). In contrast, regular breakfast consumption (≥6 days per week) among Japanese adolescents is negatively associated with depressive symptoms (26, 27). Studies conducted in Spain, Turkey, and Bangladesh have identified skipping breakfast as a predictor of depressive symptoms. Adolescents who skip breakfast or consume it fewer than five days per week have a significantly higher incidence of depressive symptoms compared to those who eat breakfast regularly (12, 28, 29). However, few cross-sectional studies in China have examined the relationship between breakfast consumption and depressive symptoms in adolescents (30). Among Chinese adolescents aged 12–17 years, inconsistent breakfast consumption is a significant risk factor for mental health problems, with a more pronounced effect in females (31). Compared to those who consume breakfast ≥6 per week, the risk of depressive symptoms is higher in adolescents who eat breakfast 2–5 days per week (OR = 1.76) and those who do so ≤1 day per week (OR = 3.78) (32). Additionally, a study in eastern China among adolescents aged 11–19 years found that skipping breakfast (OR = 2.56) was independently associated with depressive symptoms (33).

Few studies have examined midnight snacks consumption among adolescents (34). Midnight snacks, also referred to as nighttime eating, typically involves consuming food between 9:00 PM and 04:00 AM, in addition to the three main daily meals. This behavior includes a variety of foods, such as snacks, vegetables, desserts, and other small meals. Previous research suggests that midnight snacks are common among adolescents, with reported prevalence rates of 9.0% in Canada (35), 16.6% in Bangladesh (36), and 29.7% in Palestine (37). Notably, the prevalence of midnight snacks among Chinese adolescents is significantly higher (72.5%) (38). Previous studies suggest associations between adolescent dietary disorders, intuitive eating, nighttime eating syndrome, and mental health (39–41). However, research on the relationship between midnight snacks and depressive symptoms in adolescents remains unlimited. In Palestinian adolescents, nighttime eating was linked to mental health issues, including depressive symptoms (OR = 4.18) (37). Additionally, a cross-sectional study of adolescents aged 12–13 years found that nighttime eating was associated with severe depressive symptoms (OR = 1.04) (35). A cross-sectional study in Turkey found that adolescents who frequently consumed midnight snacks reported higher levels of depressive symptoms (42). Similarly, studies in the United States and Switzerland indicated that depressive symptoms were more prevalent among adolescents diagnosed with night-eating syndrome (43, 44). Additionally, among Chinese children and adolescents in grades 1-9, those who ate before bedtime had a 1.28 times higher risk of depressive symptoms compared to those who did not (45).

While some studies have examined the relationship between breakfast and midnight snacks behaviors and adolescent depressive symptoms, research on multi-ethnic adolescents in China remains scarce. Yunnan Province, located in southwest China, is a major multi-ethnic region. Due to the influence of diverse food cultures and economic situations, adolescents in this area may be more likely to skip breakfast and consume midnight snacks. This study hypothesizes a longitudinal association between skipping breakfast, midnight snacks, and depressive symptoms among multi-ethnic adolescents in China. To test this hypothesis, we conducted a follow-up survey in Yunnan Province.

 Materials and methods Participants

A longitudinal questionnaire survey was conducted among 1,693 middle school students from four schools in three regions of Yunnan Province, China. The baseline survey (T1) took place in October 2022, followed by an assessment every six months. The subsequent follow-up surveys were conducted in June 2023 (T2), October 2023 (T3), June 2024 (T4), and October 2024 (T5). The attrition rates for each follow-up were 15.6%, 2.7%, 1.7%, and 3.7%, respectively. Ultimately, 1,693 participants were included in the final analysis. A flowchart depicting the inclusion of study participants is presented in Figure 1 . The average age the participants was (12.5 ± 0.5) years, with the minimum age being 12 years and the maximum 15 years. The final sample consisted of 808 males (47.7%), and 885 females (52.3%). The participants comprised 629 Han (37.2%), 628 Yi (37.1%), 66 Hani (3.9%), 143 Lahu (8.4%), 78 Dai (4.6%), and 149 individuals from other ethnic groups (8.8%). Among them, 1,278 (75.5%) resided in rural areas, while 415 (24.5%) were from urban areas. In terms of family structure, 1,391 participants (82.2%) came from two-parent families, 166 (9.8%) from single-parent families, 110 (6.5%) from blended families, and 26 (1.5%) from other family types. Additionally, 321 participants (19.0%) were only children. Regarding socioeconomic status, participants self-reported as follows: 49 (2.9%) as “worse,” 180 (10.6%) as “poor,” 1,132 (66.9%) as “medium,” 246 (14.5%) as “good,” and 86 (5.1%) as “better.” Table 1 displays the distribution of demographic variables in relation to the prevalence of depressive symptoms. The study was in accordance with the requirement of the World Medical Association Declaration of Helsinki and granted with consent from the students, schools, and parents. The questionnaire survey was conducted anonymously, with voluntary participation from all teenage respondents. Participants retained the right to withdraw from the follow-up survey at any time. All collected data were treated with strict confidentiality and used exclusively for data analysis in this study, with no other applications. The study was approved by the Medical Ethics Committee of the School of Medicine, Kunming University (Approval Number: 20210222).

Flow chart of participants.

Four line graphs show the relationship between eating habits and depressive symptoms. Graph A shows a decrease in symptoms with more breakfast days per week. Graph B illustrates a similar trend, with a distinction between sexes: males (blue line) and females (red line). Graph C indicates an increase in symptoms with more midnight snacks per week. Graph D reflects the same pattern, also distinguishing between sexes. Confidence intervals are shaded around the lines.

The distribution of the positive rate of depressive symptoms in adolescents.

Variables Category T1 T2 T3 T4 T5
Depressive symptomS Normal χ2 P Depressive symptomS Normal χ2 P Depressive symptomS Normal χ2 P Depressive symptomS Normal χ2 P Depressive symptomS Normal χ2 P
Sex Male 175 633 17.07 <0.01 203 605 27.47 <0.01 232 576 19.41 <0.01 260 548 9.66 0.002 255 553 21.57 <0.01
Female 270 615 327 558 344 541 349 536 376 509
Residence Rural 357 921 7.32 0.007 417 861 4.25 0.039 449 829 2.87 0.091 465 813 0.39 0.534 479 799 0.10 0.755
Urban 88 327 113 302 127 288 144 271 152 263
Age(year) 12 243 716 1.24 0.539 311 648 1.34 0.511 328 631 0.07 0.965 357 602 1.55 0.460 374 585 2.92 0.232
13 195 517 212 500 241 471 244 468 250 462
14-15 7 15 7 15 7 15 8 14 7 15
Ethnicity Han 145 484 44.77 <0.01 198 431 2.45 0.785 200 429 9.36 0.096 219 410 2.05 0.842 231 398 2.35 0.799
Hani 28 38 26 40 32 34 25 41 29 37
Yi 142 486 191 437 217 411 226 402 230 398
Lahu 63 80 44 99 45 98 49 94 52 91
Dai 29 49 23 55 25 53 30 48 33 45
Other 38 111 48 101 57 92 60 89 56 93
The number of close friends 0 15 18 77.40 <0.01 12 21 13.40 0.009 14 19 9.04 0.060 15 18 9.97 0.041 15 18 8.10 0.088
1-2 89 85 74 100 75 99 69 105 78 96
3-4 84 209 95 198 101 192 115 178 117 176
5-6 60 248 94 214 102 206 122 186 108 200
≥7 197 688 255 630 284 601 288 597 313 572
The only child in the family Yes 80 241 0.38 0.538 97 224 0.22 0.641 106 215 0.18 0.674 113 208 0.10 0.750 115 206 0.35 0.552
No 365 1007 433 939 470 902 496 876 516 856
Family type Two-parent family 351 1040 5.39 0.146 430 961 0.99 0.804 467 924 0.92 0.822 494 897 3.98 0.264 517 874 1.35 0.717
One-parent family 48 118 55 111 61 105 59 107 64 102
Combined family 37 73 35 75 38 72 42 68 38 72
Other 9 17 10 16 10 16 14 12 12 14
Self-perceived socioeconomic status Worse 18 31 48.24 <0.01 19 30 20.93 <0.01 28 21 33.40 <0.01 23 26 6.83 0.145 27 22 17.20 0.002
Poor 82 98 78 102 84 96 73 107 81 99
Medium 283 849 351 781 376 756 400 732 416 716
Good 47 199 64 182 67 179 89 157 85 161
Better 15 71 18 68 21 65 24 62 22 64
Father's education level Illiteracy 55 95 11.92 0.018 50 100 1.68 0.794 52 98 1.68 0.794 60 90 5.91 0.206 54 96 2.00 0.736
Elementary school 116 299 135 280 148 267 153 262 160 255
Secondary school 196 593 237 552 268 521 276 513 292 497
High school 51 179 76 154 76 154 90 140 90 140
University 27 82 32 77 32 77 30 79 35 74
Mother's education level Illiteracy 63 131 7.04 0.134 61 133 2.10 0.717 73 121 3.16 0.531 73 121 2.14 0.711 73 121 2.17 0.704
Elementary school 123 310 147 286 154 279 164 269 151 282
Secondary school 190 594 236 548 262 522 275 509 305 479
High school 43 131 52 122 52 122 63 111 62 112
University 26 82 34 74 35 73 34 74 40 68
Father's occupation Civil servant 237 628 4.41 0.491 262 603 10.39 0.065 305 560 5.30 0.381 300 565 14.43 0.013 322 543 7.98 0.157
Worker 29 85 33 81 31 83 39 75 37 77
Staff 87 253 117 223 117 223 142 198 139 201
Merchant 29 119 38 110 45 103 39 109 43 105
Farmer 16 40 26 30 23 33 26 30 23 33
Other 47 123 54 116 55 115 63 107 67 103
Mother's occupation Civil servant 270 701 3.77 0.583 299 672 6.13 0.293 344 627 4.47 0.484 347 624 4.22 0.518 366 605 2.94 0.709
Worker 25 83 27 81 31 77 32 76 37 71
Staff 42 137 62 117 62 117 68 111 68 111
Merchant 42 128 48 122 49 121 57 113 55 115
Farmer 15 57 24 48 23 49 28 44 28 44
Other 51 142 70 123 67 126 77 116 77 116
Methods Survey methods

A cross-sectional questionnaire survey was conducted among middle school students across 11 counties in Yunnan Province using random cluster sampling. The details of this methodology have been described in our previously published work (46). Based on the cross-sectional survey, four middle schools with high multi-ethnic representation and strong participant compliance were selected for the longitudinal follow-up study. All seventh-grade (Grade 7) students from the selected schools participated in the survey. The adolescents completed a self-administered questionnaire in a classroom setting. The survey collected data on demographic characteristics (e.g., gender, age, ethnicity, only child status, family residence, self-rated family economic status, family structure, number of close friends, parental education levels, and parental occupations). Additionally, it assessed dietary behaviors (breakfast and midnight snacks), depressive symptoms, and potential confounding factors influencing adolescents’ depression, including family changes, hospitalization history, screen time, smoking, alcohol consumption, physical activity, family history of depression, self-rated academic pressure impact of the COVID-19 pandemic. Trained surveyors administered the survey in person, addressing participants’ questions face-to-face. Adolescents completed the questionnaire independently without discussing responses with peers. The process took approximately 15–20 minutes. Surveyors reviewed the completed questionnaires upon collection, promptly addressing any missing responses.

 Evaluation of depressive symptoms

Depressive symptoms were assessed using the Chinese version of the Children’s Depression Inventory (CDI), a widely used self-report scale for measuring depression in children and adolescents (47, 48). The CDI evaluates depressive mood and behavior in individuals aged 7–17 years, based on self-reported experiences over the past two weeks. The inventory consists of 27 items across five dimensions: anhedonia, negative mood, negative self-esteem, ineffectiveness, and interpersonal problems. Each item is rated on a 3-point scale (“occasionally,” “often” and “always”), with scores ranging from 0 to 2 per item, resulting in a total possible score of 0-54. Higher scores indicate more severe depressive symptoms. A total CDI score ≥19 was considered indicative of depressive symptoms, while a score < 19 was classified as negative. Studies on Chinese children and adolescents (aged 7–17 years) have demonstrated that the CDI has good reliability and validity, with a Cronbach’s α of 0.84 (49). Research on Chinese middle school students further supports the CDI’s high reliability and validity, confirming its suitability for assessing depressive symptoms in this population (Cronbach’s α coefficient of 0.853) (50). Cronbach’s α coefficients at T1 –T5 were 0.861, 0.892, 0.900, 0.893 and 0.904, respectively, indicating strong internal consistency.

 Breakfast behavior and midnight snacks behavior evaluation

Adolescent dietary behaviors were assessed using a dietary frequency questionnaire developed by the research group, which has been repeatedly validated for good reliability and validity (46, 51). Firstly, a pilot test was conducted in 131 middle school students before the field survey to assess participant understanding of the questionnaire. The pilot test results showed that middle school students were able to fully understand the content of the questionnaire, and the average time taken to complete the questionnaire was 16 minutes. Secondly, in each follow-up survey, we evaluated the reliability and validity of the dietary frequency questionnaire, the Cronbach’s α coefficients at T1 –T5 were 0.921, 0.936, 0.942, 0.945, and 0.940, respectively.

Midnight snacks behavior refers to the behavior of consumption of food between 21:00 and 04:00, in addition to the three main meals of the day. This includes various snacks, desserts, and other food items. Breakfast behavior refers to the consumption of the first meal of the day, typically between 06:00 and 08:00. This study the breakfast and midnight snacks behaviors of multi-ethnic adolescents. Participants were asked the following questions (1): “How many days did you eat breakfast in the past week?” Response options included (1) 0 days (2), 1–2 days (3), 3–4 days (4), 5–6 days (5), 7 days (2). “How many days did you consume midnight snacks (including snacks) before going to bed in the past week?” The response options included (1) 0 days (2), 1–2 days (3), 3–4 days (4), 5–6 days (5), 7 days. Adolescents selected the number of days they consumed breakfast and midnight snacks based on their actual eating habits.

 Statistical analysis

Data were entered into a database using EpiData 3.0. After data verification, statistical analyses were conducted using SPSS (version 23.0; SPSS Inc., Chicago, IL, USA), R (version 4.3.1), and Mplus (version 7.4). Descriptive statistics, χ2 tests, and generalized estimation equation (GEE) models were performed in SPSS. Restricted cubic spline analysis was conducted using R software. The latent growth curve model (LGCM) was analyzed using Mplus software to assess the potential growth trajectories of breakfast days, midnight snacks days, and depressive symptom scores across five time points. Intercept and slope factors were included as observation indices. A χ2 test was used to compare differences in the detection rates of depressive symptoms among college students with different demographic characteristics over time. The generalized estimation equation (GEE) model was applied to examine the association between the number of breakfast and midnight snacks days and depressive symptom scores. In the model, breakfast days and the number of midnight snacks per week were treated as independent variables, while depressive symptom scores were the dependent variable. Both independent and dependent variables were continuous variables. Two models were established: Model 1, which was unadjusted, without controlling any variables; Model 2, which was adjusted for demographic variables and other potential confounders influencing depressive symptoms, followed by an association analysis. The identification of confounding factors mainly stems from the variables reported in the literature that have evidence suggesting they may affect adolescent depression symptoms. The adjustment method is to include both the confounding variables and the analysis variables (the days of eating breakfast per week and the days of eating midnight snacks per week) in the model as independent variables. A restricted cubic spline analysis was used to examine the relationship between the number of breakfast days per week, midnight snacks days per week, and depressive symptoms. The statistical significance level was set at α = 0.05.

 Results The growth trajectories of breakfast and midnight snacks consumption and depressive symptoms among adolescents

The prevalence rates of depressive symptoms from T1 to T5 were 26.3%, 31.3%, 34.0%, 36.0%, and 37.3%, respectively. The reported frequencies of breakfast consumption on day 0, day 1–2, day 3–4, day 5–6, and day 7 in the past week were as follows: T1 (5.0%, 9.2%, 13.3%, 21.5%, and 51.1%, respectively), T2 (6.1%, 13.1%, 14.6%, 21.7%, and 44.5%, respectively), T3 (1.4%, 7.6%, 14.2%, 30.5%, and 46.3%, respectively), T4 (2.2%, 7.0%, 15.2%, 26.8%, and 48.7%, respectively), and T5 (4.7%, 9.2%, 14.7%, 24.6%, and 46.8%, respectively). The reported frequencies of eating a midnight snacks on day 0, day 1–2, day 3–4, day 5–6, and day 7 in the past week were as follows: T1 (28.7%, 36.3%, 18.7%, 7.6%, and 8.7%, respectively), T2 (22.9%, 40.6%, 20.3%, 7.6%, and 8.6%, respectively), T3 (19.7%, 43.4%, 20.5%, 8.5%, and 7.9%, respectively), T4 (16.6%, 41.0%, 22.1%, 10.7%, and 9.6%, respectively), and T5 (21.3%, 39.8%, 20.1%, 8.3%, and 10.5%, respectively). Table 2 shows the fitting results of the latent growth curve model. The fitting index Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Sample-Size Adjusted BIC, Chi-Square Test of Model Fit (P-Value), Root Mean Square Error Of Approximation (RMSEA), Comparative Fit Index (CFI), Tucker-Lewis index (TLI), and Standardized Root Mean Square Residual (SRMR) of the days of eating midnight snacks per week were 25170.64, 25279.32, 25215.78, 92.19 (<0.01), 0.07, 0.96, 0.96, and 0.05, respectively. These indices of the days of eating breakfast per week were 25016.14, 25124.82, 25061.28, 210.95 (<0.01), 0.11, 0.87, 0.87, and 0.09, respectively. These indices of depressive symptoms were 55776.48, 55885.17, 55821.63, 362.53 (<0.01), 0.14, 0.93, 0.93, and 0.12, respectively. Figure 2 illustrates the potential growth trajectories of adolescents’ breakfast consumption, midnight snacks consumption, and depressive symptom scores over the past week. The variance estimates for the intercept and slope factors of breakfast consumption and depressive symptom scores were statistically significant for both males and females (all P < 0.01), indicating differences in initial levels and growth rates of breakfast consumption and depressive symptoms among adolescents.

The latent growth curve of depressive symptoms, the days of eating midnight snack and breakfast per week.

Variable Sex Growth factor Estimate SE Est/SE P-Value
The days of eating midnight snack per week Male Intercept factor 0.51 0.06 8.21 <0.01
Slope factor 0.01 0.01 1.18 0.237
Female Intercept factor 0.45 0.05 9.07 <0.01
Slope factor 0.04 0.01 5.97 <0.01
The days of eating breakfast per week Male Intercept factor 0.45 0.06 7.63 <0.01
Slope factor 0.03 0.01 4.37 <0.01
Female Intercept factor 0.37 0.05 6.86 <0.01
Slope factor 0.03 0.01 4.05 <0.01
Depressive symptoms Male Intercept factor 30.39 2.51 12.13 <0.01
Slope factor 1.73 0.25 7.10 <0.01
Female Intercept factor 40.29 3.03 13.31 <0.01
Slope factor 2.35 0.26 9.120 <0.01

The latent growth curve of depressive symptoms, the days of eating midnight snack and breakfast per week. (A) breakfast days, (B) midnight snack days, (C) depressive symptoms.

Three line graphs labeled A, B, and C depict changes over time in breakfast days, midnight snack days, and depressive symptoms, respectively. Each graph shows sample and estimated means for male and female groups. Graph A indicates a consistent trend in breakfast days. Graph B illustrates a slight increase in midnight snack days. Graph C shows a gradual increase in depressive symptoms, with visible differences between male and female groups over time.

The variance estimates for the intercept factor and slope factors of the potential growth trajectory of midnight snacks days in the previous week were statistically significant for females (all P < 0.01). However, for males, the variance estimates for the intercept factor of the potential growth trajectory of male slope factors were not statistically significant (P > 0.05). There were differences in the initial level and growth rate of the number of midnight snacks days for females in the last week, whereas there were differences only in the initial level of the number of midnight snacks days for males in the last week, and there was no difference in the growth rate.

 Distribution of depressive symptoms among adolescents

Table 1 presents the prevalence of depressive symptoms among adolescents with different demographic characteristics. Significant differences were observed between boys and girls at all five time points (T1: χ2 = 17.07, T2: χ2 = 27.47, T3: χ2 = 19.41, T4: χ2 = 9.66, T5: χ2 = 21.57; all P < 0.01). In addition, the prevalence of depressive symptoms varied significantly at certain time points based on family residence, ethnicity, number of close friends, self-rated family economic status, father’s education level, and father’s occupation (P < 0.05). However, no significant differences in the prevalence of depressive symptoms were observed across other demographic variables (P > 0.05).

 The association between adolescents’ breakfast behavior and midnight snacks behavior and depressive symptoms

Table 3 presents the results of the generalized linear model analysis of the association between the number of breakfast and midnight snacks days and depressive symptom scores in adolescents in the past week. After adjusting for confounding variables, the number of breakfast days was negatively associated with depressive scores across all groups: adolescents overall (β = -0.76, 95%CI: -0.87 to -0.65, P < 0.01), males (β = -0.71, 95%CI: -0.87 to -0.56, P < 0.01) and females (β = -0.77, 95%CI: -0.92 to -0.63, P < 0.01). In addition, the number of midnight snacks days was positively associated with depressive symptoms across all groups: adolescents overall (β = 0.29, 95%CI: 0.18 to 0.40, P < 0.01), males (β = 0.39, 95%CI: 0.24 to 0.55, P < 0.01), and females (β = 0.17, 95%CI: 0.02 to 0.32, P = 0.027). Figure 3 shows the results of the restricted cubic spline analysis of the association between the number of breakfast and midnight snacks days per week and depressive symptom scores. Overall, breakfast and midnight snacks behaviors were related to adolescent depressive symptoms. Males’ breakfast behavior was more sensitive to depressive symptoms, whereas females’ midnight snacks behavior was more sensitive to depressive symptoms. Adolescents who ate breakfast fewer than four days in the past week and consumed midnight snacks more than two day per week exhibited an increased risk of depressive symptoms. Among males, eating breakfast fewer than three days per week and eating midnight snacks more than four days per week increased the risk of depressive symptoms. Among females, eating breakfast fewer than four days per week and eating midnight snacks more than two day per week was associated with an increased risk of depressive symptoms.

Longitudinal association of breakfast and midnight snack with depressive symptoms in Yunnan multi-ethnic adolescents.

Model Adolescents Variables β (95% CI) SE Wald χ2 P
Model 1 All participants The days of eating breakfast per week -0.98(-1.09−-0.87) 0.06 288.10 <0.01
The days of eating midnight snack per week 0.51(0.39−0.62) 0.06 77.28 <0.01
Male The days of eating breakfast per week -0.95(-1.11−-0.79) 0.08 131.15 <0.01
The days of eating midnight snack per week 0.60(0.44−0.76) 0.08 54.71 <0.01
Female The days of eating breakfast per week -1.00(-1.16−-0.84) 0.08 156.13 <0.01
The days of eating midnight snack per week 0.40 (0.24−0.56) 0.08 23.86 <0.01
Model 2 All participants The days of eating breakfast per week -0.76(-0.87−-0.65) 0.06 185.87 <0.01
The days of eating midnight snack per week 0.29(0.18−0.40) 0.06 26.59 <0.01
Male The days of eating breakfast per week -0.71(-0.87−-0.56) 0.08 80.32 <0.01
The days of eating midnight snack per week 0.39(0.24−0.55) 0.08 24.21 <0.01
Female The days of eating breakfast per week -0.77(-0.92−-0.63) 0.07 107.73 <0.01
The days of eating midnight snack per week 0.17(0.02−0.32) 0.08 4.89 0.027

Model 1 unadjusted for variables. Model 2 adjusted for age, ethnicity, residence, the only child in the family, family type, parental educational level, parental occupation, family changes, hospital experience, the impact of COVID-19, family history of depression, self-perceived socioeconomic status, self-perceived academic stress, video time, physical activity, smoking, alcohol consumption, the number of close friends, consumption of takeaway fast food and sugar-sweetened beverage.

Association of breakfast and midnight snack with depressive symptoms in Yunnan multi-ethnic adolescents.

Timeline of investigations from October 2022 to October 2024, with details for each. First in October 2022: 2,248 investigated, 2,196 completed, 2,183 valid. Second in June 2023: 2,183 investigated, 2,110 completed, 1,842 valid, 341 lost to follow-up. Third in October 2023: 1,842 investigated, 1,795 completed, 1,792 valid, 50 lost. Fourth in June 2024: 1,792 investigated, 1,763 completed, 1,758 valid, 34 lost. Fifth in October 2024: 1,758 investigated, 1,693 completed, 1,693 valid, 65 lost. Total participants: 1,693. Discussion

This follow-up study revealed that the prevalence of depressive symptoms among multi-ethnic adolescents in China ranged from 26.3%-37.3%, showing a significant increasing trend. The prevalence found in this study aligns closely with that of adolescents in Eastern (36.2%) (13), as well as Bangladesh (36.6%) (52). However, the prevalence of depressive symptoms among adolescents in this study was higher than that in Northeast China (28.2%) (24) and lower than in India (52.3%) (53). Moreover, the latent growth trajectory analysis indicated that depressive symptom scores among multi-ethnic adolescents in China increased over the follow-up period. These findings are consistent with other studies, which have reported a significant increase in depression prevalence among Chinese adolescents from 2021 to 2023 (54). The results highlight that depressive symptoms among multi-ethnic adolescents in China are at a high level. While Eastern and Central China have seen societal, school, and family attention toward adolescent depression, ethnic adolescents in Western China have not received sufficient attention. Therefore, school-based health promotion programs targeting depression among multi-ethnic adolescents in China should be prioritized on the national agenda.

The reported rate of not eating breakfast for ≥1 d in the past week among Chinese multi-ethnic adolescents was 48.9%-55.5%, which is comparable to the rate in Turkish adolescents (54.1%) (29), higher than that of South Korean adolescents (29.2%) (55), and lower than that of Brazilian adolescents (87%) (56). We indicate that the number of days per week that males and females ate breakfast was negatively correlated with the risk of developing depressive symptoms. Specifically, the risk of depressive symptoms increased when males ate breakfast less than three days per week, and females ate breakfast less than four days per week. These results align with previous studies. For instance, a cross-sectional study found that Turkish adolescents who ate breakfast ≤5 days per week were at a higher risk for depressive and anxiety symptoms, and low breakfast quality was also linked to these mental health issues (29). Studies have shown that skipping breakfast is associated with higher levels of depressive symptoms. Spanish individuals who did not eat breakfast exhibited more depressive symptoms than those who did (28). Among Japanese adolescents, regular breakfast consumption (≥6 days per week) was negatively correlated with depressive symptoms (26, 27). A Chinese study found a similar pattern, with a stronger association observed in younger adolescents (11–15) compared to older ones (16–19) (33). Additionally, research on children in grades 1–9 in Shanghai, China, indicated that adolescents who skipped breakfast had a 2.70 times higher risk of depressive symptoms than those who ate breakfast regularly (45). Few longitudinal studies have examined this relationship. However, a one-year prospective cohort study in China found that compared to adolescents who ate breakfast ≥6 days per week, those who ate breakfast only 2–5 days per week had a significantly higher risk of depressive symptoms (OR = 2.045), with an even greater risk for those eating breakfast ≤1 day per week (OR = 2.722) (32). Similarly, a large-sample prospective study in the United States confirmed a positive association between breakfast and depressive symptoms (57). Moreover, skipping breakfast has been linked to an increased risk of suicidal ideation, planning, and attempts among adolescents in the United States and South Korea (58, 59). Given these findings, promoting consistent breakfast consumption among adolescents is crucial for mental health.

This study found that 71.3%-83.4% of multi-ethnic Chinese adolescents consumed midnight snacks at least once in the past week, a significantly higher rate than that of Bangladeshi (16.6%) (36) and Palestinian (29.7%) adolescents (37). Additionally, our findings indicate a positive correlation between the frequency of midnight snacks consumption and the risk of depressive symptoms in both males and females. The risk of depressive symptoms increased when males consumed midnight snacks more than four days per week and females more than two day per week. This finding aligns with previous research indicating that midnight snacks are associated with a higher risk of depressive symptoms in adolescents (41, 43). Similarly, children and adolescents in grades 1–9 in Shanghai, China who ate before bedtime showed a significantly elevated risk of depressive symptoms (45). Turkish adolescents aged 13–18 who ate after 10 PM were also more likely to experience depressive symptoms (42). Similarly, a longitudinal study in Montreal that followed Canadian adolescents from ages 12 to 17 found that nighttime eating was longitudinally associated with an increased risk of depressive symptoms (OR = 1.75) (35).

Our research data indicate the gender-specific thresholds for skipping breakfast and eating midnight snacks increase the risk of depressive symptoms, the possible explanations include Physiological and social-cultural factors. Meta-analysis shows that the gender difference for diagnoses of depression emerged earlier than previously thought, peaked in adolescence, but then declined and remained stable in adulthood (60). The Social Signal Transduction Theory posits that adolescent females are more sensitive to experiences of social-environmental adversity. Moreover, fluctuations in hormone levels can regulate the sensitivity of females to stress, as well as the structure and function of the brain, and their reactivity, which leads to a higher likelihood of depressive symptoms in adolescent females (61).

In this study, skipping breakfast and eating midnight snacks among multi-ethnic Chinese adolescents were longitudinally associated with depressive symptoms. Several mechanisms may explain this relationship. First, both behaviors negatively impact physical health, which serves as the foundation for mental well-being. Breakfast is a crucial meal of the day, providing essential energy and nutrients that contribute significantly to daily dietary intake. Breakfast typically includes grains, dairy products such as cheese or milk, and eggs. Whole grains are rich in several macronutrients, including magnesium (62); dairy products are excellent sources of Calcium, magnesium and vitamins (such as B2, B12, A), amino acids (such as proline, tyrosine, serine, lysine, valine, and leucine) (63); and eggs provide a high amount of choline (64). These nutrients may contribute positively to mental health. Consistently skipping breakfast can result in nutrient deficiencies, while frequent midnight snacks places excessive strain on the gastrointestinal tract, potentially leading to indigestion. Additionally, frequent midnight snacks can contribute to obesity, increasing the likelihood of adolescents entering a sub-health state. Research indicates that sub-health serves as a mediating factor in the relationship between dietary behaviors and depressive symptoms (65). Second, both skipping breakfast and eating midnight snacks can negatively impact sleep quality and even contribute to insomnia (33, 66). Previous studies have suggested that night eating symptoms have a direct effect on the chronotype differences and insomnia and an indirect effect on disordered eating attitudes, by increasing insomnia scores (67). Midnight snacks keeps the stomach full, disrupts sleep, and is a significant predictor of depressive symptoms (68). Third, irregular eating habits, such as skipping breakfast and frequently eating midnight snacks, can disrupt the biological clock and lead to endocrine imbalances, which may further contribute to depressive symptoms (69). Fourth, most midnight snacks consumed by adolescents are ultra-processed foods that are easy to access and are significant predictors of depressive symptoms (70). Nighttime eating is also linked to food addiction (71). These foods—such as sugar-sweetened beverages, processed meat, sweets, and snacks—are frequently consumed, further increasing the risk of depressive symptoms in adolescents (23).

The data collected in this study were during the COVID-19 pandemic. Therefore, the depressive symptoms of adolescents might have been affected by COVID-19. A nationwide, multicenter, cross-sectional study in China revealed that the COVID-19 pandemic has exacerbated anxiety, depression, and sleep problems among people (72). Moreover, social isolation and reduced outdoor activities have emerged as significant risk factors for anxiety, depression, and insomnia (73). However, we have taken into account the impact of the COVID-19 pandemic on the participants’ depressive symptoms, and in the multivariate analysis model, we have adjusted for the COVID-19 pandemic.

Adolescent depression is a pressing global public health concern (74). It not only impacts adolescents’ well-being but also affects their long-term health and that of future generations (60). From a life-cycle perspective, as well as in terms of treatment effectiveness and health economics, preventing adolescent depression is crucial (1). The link between adolescent dietary behaviors and depressive symptoms has garnered increasing attention (75). Research suggests that dietary interventions can effectively prevent depression or serve as an alternative or adjunct therapy (76). Therefore, the habits of skipping breakfast and eating midnight snacks among multi-ethnic adolescents in China require attention. Effective health education and behavioral interventions should be implemented to correct these unhealthy eating patterns. Adolescents should be encouraged to eat a balanced breakfast regularly, maintain consistent meal timing, and develop healthy dietary habits to support mental well-being.

Emerging evidence suggests a bidirectional relationship between dietary behaviors and depressive symptoms among adolescents. Specifically, depressive symptoms may adversely influence eating behaviors, leading to poorer nutritional choices (77). Empirical research supports this association, demonstrating a significant link between depression and uncontrolled eating behaviors (β = 0.61) (78). Consistent with these findings, a Brazilian study involving college students revealed that elevated depressive symptom scores were correlated with increased consumption of hyperpalatable foods, indicating a preference for energy-dense, nutrient-poor diets (79). Further corroborating this trend, an Indian longitudinal study observed that adolescents with depressive symptoms exhibited a higher propensity for unhealthy dietary practices, subsequently elevating their risk of weight gain (80). We will further explore the association of depressive symptoms with breakfast and midnight snacks in China multi-ethnic adolescents.

This study has several strengths. First, it explored the longitudinal relationship between breakfast and midnight snacks behaviors and depressive symptoms among multi-ethnic adolescents in China, reducing the risk of spurious correlations often found in cross-sectional studies. Our research findings hold practical value for developing intervention strategies aimed at modifying unhealthy dietary behaviors among multi-ethnic adolescents in Yunnan Province, fostering healthy eating habits, and promoting psychological well-being. Second, this is the first study to examine the breakfast and midnight snacks habits of multi-ethnic adolescents in Yunnan, China, and their impact on depressive symptoms, addressing a gap in existing research on this population.

This study has some limitations. First, self-reported questionnaires used to assess dietary behaviors and depressive symptoms may introduce recall bias or social desirability bias, particularly among adolescents. throughout the study, we implemented several strategies to mitigate such biases. Second, the study focuses only on the frequency of breakfast and midnight snacks consumption while ignoring critical factors like the nutritional content of breakfast and the type of midnight snacks, limiting the interpretation of whether associations stem from quantity or quality, which may limit the precision of the analysis. Third, although the study adjusted for confounders such as demographics and lifestyle factors, it omitted other relevant variables (e.g., family dietary habits, peer influence, specific nutrient deficiencies), which may leave residual confounding. Fourth, this study has a limited sample size and was conducted only in specific regions of Yunnan Province, which may not fully represent all Yunnan. Consequently, the generalizability and application of the findings are constrained.

 Conclusion

In conclusion, our longitudinal data indicate that skipping breakfast and eating midnight snacks are significant predictors of depressive symptoms among multi-ethnic adolescents in China. These findings underscore the importance of implementing school-based health education and behavioral interventions. By guiding students to adopt healthy dietary habits—such as eating breakfast regularly and avoiding midnight snacks—depressive symptoms can be prevented and improved, ultimately promoting better health among multi-ethnic adolescents in China.

 Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

 Ethics statement

The study was approved by the Ethics Committee of School of Medicine, Kunming University (approval number: 20210222). The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation in this study was provided by the participants’ legal guardians/next of kin.

 Author contributions

HX: Funding acquisition, Investigation, Methodology, Project administration, Supervision, Writing – original draft. GZ: Data curation, Writing – review & editing. ZL: Investigation, Writing – review & editing. XX: Investigation, Writing – review & editing. DH: Investigation, Writing – review & editing. JY: Investigation, Writing – review & editing. JJ: Data curation, Writing – review & editing. XZ: Data curation, Writing – review & editing.

 Funding

The author(s) declare financial support was received for the research and/or publication of this article. This work was supported by the National Natural Science Foundation of China (82160622), the Young Talents Special Project of “Xingdian Talent Support Plan” in Yunnan Province (XDYC-QNRC-2022-0289) and Yunnan Fundamental Research Projects (202501AT070481).

 Acknowledgments

We would like to thank the participants of the behavior and sub-health study in Yunnan adolescents (BSSYA).

 Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

 Generative AI statement

The author(s) declare that no Generative AI was used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

 Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

 References Thapar A Eyre O Patel V Brent D . Depression in young people. Lancet. (2022) 400:617–31. doi: 10.1016/S0140-6736(22)01012-1, PMID: 35940184 Nota MHC Nicolas S O'Leary OF Nolan YM . Outrunning a bad diet: Interactions between exercise and a Western-style diet for adolescent mental health, metabolism and microbes. Neurosci Biobehav Rev. (2023) 149:105147. doi: 10.1016/j.neubiorev.2023.105147, PMID: 36990371 Eray Ş Tekcan D Baran Y . More anxious or more shy? Examining the social anxiety levels of adolescents with primary enuresis nocturna: a controlled study. J Pediatr Urol. (2019) 15:341–3. doi: 10.1016/j.jpurol.2019.04.002, PMID: 31036479 Malhi GS Mann JJ . Depression. Lancet. (2018) 392:2299–312. doi: 10.1016/S0140-6736(18)31948-2, PMID: 30396512 Senior M Pierce M Taxiarchi VP Garg S Edge D Newlove-Delgado T . 5-year mental health outcomes for children and adolescents presenting with psychiatric symptoms to general practitioners in England: a retrospective cohort study. Lancet Psychiatry. (2024) 11:274–84. doi: 10.1016/S2215-0366(24)00038-5, PMID: 38490760 Reangsing C Punsuwun S Schneider JK . Effects of mindfulness interventions on depressive symptoms in adolescents: A meta-analysis. Int J Nurs Stud. (2021) 115:103848. doi: 10.1016/j.ijnurstu.2020.103848, PMID: 33383273 Liu J Liu Y Ma W Tong Y Zheng J . Temporal and spatial trend analysis of all-cause depression burden based on Global Burden of Disease (GBD) 2019 study. Sci Rep. (2024) 14:12346. doi: 10.1038/s41598-024-62381-9, PMID: 38811645 Shorey S Ng ED Wong CHJ . Global prevalence of depression and elevated depressive symptoms among adolescents: A systematic review and meta-analysis. Br J Clin Psychol. (2022) 61:287–305. doi: 10.1111/bjc.12333, PMID: 34569066 Xiang AH Martinez MP Chow T Carter SA Negriff S Velasquez B . Depression and anxiety among US children and young adults. JAMA Netw Open. (2024) 7:e2436906. doi: 10.1001/jamanetworkopen.2024.36906, PMID: 39352699 Konig L Schroder R Hamer T Suhr R . Depression and health literacy among adolescents and adults in Germany: findings from two representative samples. Front Psychol. (2024) 15:1494333. doi: 10.3389/fpsyg.2024.1494333, PMID: 39726619 Randhawa SS Marcenes W Stansfeld SA Bernabe E . Depressive symptoms and traumatic dental injuries among adolescents. Dent Traumatol. (2020) 36:192–7. doi: 10.1111/edt.12524, PMID: 31667970 Khan A Ahmed R Burton NW . Prevalence and correlates of depressive symptoms in secondary school children in Dhaka city, Bangladesh. Ethn Health. (2020) 25:34–46. doi: 10.1080/13557858.2017.1398313, PMID: 29096523 Yang R Tan S Abdukerima G Lu T Chen C Song L . Combined effect of the smartphone addiction and physical activity on the depressive symptoms in secondary school students: a cross sectional study in Shanghai, China. Front Psychiatry. (2024) 15:1473752. doi: 10.3389/fpsyt.2024.1473752, PMID: 39831059 Steare T Lewis G Lange K Lewis G . The association between academic achievement goals and adolescent depressive symptoms: a prospective cohort study in Australia. Lancet Child Adolesc Health. (2024) 8:413–21. doi: 10.1016/S2352-4642(24)00051-8, PMID: 38642573 Reck AJ Kogan SM . Family stress and rural african-american adolescents’ Depressive symptoms. J Adolesc Health. (2021) 69:1006–12. doi: 10.1016/j.jadohealth.2021.05.005, PMID: 34092476 Cohen A Lang JJ Prince SA Colley RC Tremblay MS Chaput J . Are adolescents who do physical activity with their parents more active and mentally healthier? Health Rep. (2025) 36:19–33. doi: 10.25318/82-003-x202500100002-eng, PMID: 39832193 Pastor-Cisneros R Lopez-Gil JF Carl J Adsuar JC Mendoza-Munoz M . Exploring the associations of perceived physical literacy with depression, anxiety, and stress among Spanish adolescents. Complement Ther Clin Pract. (2025) 59:101948. doi: 10.1016/j.ctcp.2025.101948, PMID: 39827701 Velazquez B Petresco S Pereira R Buchweitz C Manfro PH Caye A . Physical activity and depressive symptoms among adolescents in a school-based sample. Braz J Psychiatry. (2022) 44:313–6. doi: 10.1590/1516-4446-2021-2235, PMID: 35262617 Jimenez-Lopez E Mesas AE Visier-Alfonso ME Pascual-Morena C Martinez-Vizcaino V Herrera-Gutierrez E . Adherence to the Mediterranean diet and depressive, anxiety, and stress symptoms in Spanish adolescents: results from the EHDLA study. Eur Child Adolesc Psychiatry. (2024) 33:2637–46. doi: 10.1007/s00787-023-02351-0, PMID: 38170283 Faisal-Cury A Leite MA Escuder MML Levy RB Peres MFT . The relationship between ultra-processed food consumption and internalising symptoms among adolescents from Sao Paulo city, Southeast Brazil. Public Health Nutr. (2022) 25:2498–506. doi: 10.1017/S1368980021004195, PMID: 34610854 Chopra C Mandalika S Kinger N . Does diet play a role in the prevention and management of depression among adolescents? A narrative review. Nutr Health. (2021) 27:243–63. doi: 10.1177/0260106020980532, PMID: 33416032 Khanna P Chattu VK Aeri BT . Nutritional aspects of depression in adolescents - A systematic review. Int J Prev Med. (2019) 10:42. doi: 10.4103/ijpvm.IJPVM_400_18, PMID: 31057727 Malmir H Mahdavi FS Ejtahed H Kazemian E Chaharrahi A Mohammadian Khonsari N . Junk food consumption and psychological distress in children and adolescents: A systematic review and meta-analysis. Nutr Neurosci. (2023) 26:807–27. doi: 10.1080/1028415X.2022.2094856, PMID: 35816403 Cao R Gao T Ren H Hu Y Qin Z Liang L . Unique and cumulative effects of lifestyle-related behaviors on depressive symptoms among Chinese adolescents. Int J Soc Psychiatry. (2022) 68:354–64. doi: 10.1177/0020764021996739, PMID: 33622084 Zahedi H Djalalinia S Sadeghi O Zare Garizi F Asayesh H Payab M . Breakfast consumption and mental health: a systematic review and meta-analysis of observational studies. Nutr Neurosci. (2022) 25:1250–64. doi: 10.1080/1028415X.2020.1853411, PMID: 33314992 Yamaguchi S Kawasaki Y Oura A Kimura S Horii M Watanabe S . Differential associations of sports participation with self-rated health and depressive symptoms among Japanese adolescents. Cureus. (2023) 15:e43776. doi: 10.7759/cureus.43776, PMID: 37731422 Tanaka M Hashimoto K . Impact of consuming green and yellow vegetables on the depressive symptoms of junior and senior high school students in Japan. PloS One. (2019) 14:e211323. doi: 10.1371/journal.pone.0211323, PMID: 30730901 Ferrer-Cascales R Sanchez-SanSegundo M Ruiz-Robledillo N Albaladejo-Blazquez N Laguna-Perez A Zaragoza-Marti A . Eat or skip breakfast? The important role of breakfast quality for health-related quality of life, stress and depression in spanish adolescents. Int J Environ Res Public Health. (2018) 15:1781. doi: 10.3390/ijerph15081781, PMID: 30126240 Gurbuz M Bayram HM Kabayel N Turker ZS Sahin S Icer S . Association between breakfast consumption, breakfast quality, mental health and quality of life in Turkish adolescents: A high school-based cross-sectional study. Nutr Bull. (2024) 49:157–67. doi: 10.1111/nbu.12668, PMID: 38470057 Yao L Liang K Huang L Xiao J Zhou K Chen S . Longitudinal associations between healthy eating habits, resilience, insomnia, and internet addiction in chinese college students: A cross-lagged panel analysis. Nutrients. (2024) 16:2470. doi: 10.3390/nu16152470, PMID: 39125349 Liang K Chen S Chi X . Care their diet and mind: association between eating habits and mental health in chinese left-behind children. Nutrients. (2022) 14:524. doi: 10.3390/nu14030524, PMID: 35276882 Ren Z Cao J Cheng P Shi D Cao B Yang G . Association between breakfast consumption and depressive symptoms among chinese college students: A cross-sectional and prospective cohort study. Int J Environ Res Public Health. (2020) 17:1571. doi: 10.3390/ijerph17051571, PMID: 32121348 Li S Li X Wang J Jiang D Zhang Y Lou W . Associations between insufficient sleep, skipping breakfast and depressive symptoms in children and adolescents: A school-based cross-sectional study in China. Prev Med. (2024) 184:107978. doi: 10.1016/j.ypmed.2024.107978, PMID: 38697227 He J Huang F Yan J Wu W Cai Z Fan X . Prevalence, demographic correlates, and association with psychological distress of night eating syndrome among Chinese college students. Psychol Health Med. (2018) 23:578–84. doi: 10.1080/13548506.2017.1400669, PMID: 29105500 Guentcheva I Dugas EN Hanusaik N Drapeau V Sylvestre M O'Loughlin J . Depression symptoms and night eating in young adulthood. Eat Weight Disord. (2020) 25:1593–600. doi: 10.1007/s40519-019-00796-4, PMID: 31673988 Sahrin S Banna MHA Hamiduzzaman M Gbordzoe NI Disu TR Akter S . Night eating syndrome among university students in Bangladesh: investigation of prevalence and associated factors. Brain Behav. (2024) 14:e70118. doi: 10.1002/brb3.70118, PMID: 39444104 Hamdan M Badrasawi M Zidan S Thawabteh R Mohtaseb R Arqoub KA . Night eating syndrome is associated with mental health issues among palestinian undergraduate students-cross sectional study. J Eat Disord. (2023) 11:1. doi: 10.1186/s40337-022-00727-2, PMID: 36600295 Li X Ao Y Huang G Zhang X Wang L Li Y . Association between eating at night and skipping breakfast with anxiety symptoms among freshman in colleges in Yunnan Province. Chin J Sch Health. (2023) 44:274–7. doi: 10.16835/j.cnki.1000-9817.2023.02.026 Sinclair-Mcbride K Cole DA . Prospective relations between overeating, loss of control eating, binge eating, and depressive symptoms in a school-based sample of adolescents. J Abnorm Child Psychol. (2017) 45:693–703. doi: 10.1007/s10802-016-0186-0, PMID: 27401881 Hazzard VM Telke SE Simone M Anderson LM Larson NI Neumark-Sztainer D . Intuitive eating longitudinally predicts better psychological health and lower use of disordered eating behaviors: findings from EAT 2010-2018. Eat Weight Disord. (2021) 26:287–94. doi: 10.1007/s40519-020-00852-4, PMID: 32006391 Lepley T Schwager Z Khalid Z . Identification and management of night eating syndrome in the adolescent and young adult population. Prim Care Companion CNS Disord. (2022) 24:21r03062. doi: 10.4088/PCC.21r03062, PMID: 35180815 Tuncay S Sarman A . Late-night eating and inactivity: Links to depression and suicide risk in adolescents living in Turkey. J Child Adolesc Psychiatr Nurs. (2024) 37:e12474. doi: 10.1111/jcap.12474, PMID: 38924640 Runfola CD Allison KC Hardy KK Lock J Peebles R . Prevalence and clinical significance of night eating syndrome in university students. J Adolesc Health. (2014) 55:41–8. doi: 10.1016/j.jadohealth.2013.11.012, PMID: 24485551 Fischer S Meyer AH Hermann E Tuch A Munsch S . Night eating syndrome in young adults: delineation from other eating disorders and clinical significance. Psychiatry Res. (2012) 200:494–501. doi: 10.1016/j.psychres.2012.07.028, PMID: 22883837 Li H Lu Z Zhang E Zhang J Cui S Takahashi M . Meal timing and depression among chinese children and adolescents: cross-sectional study. JMIR Public Health Surveill. (2024) 10:e54275. doi: 10.2196/54275, PMID: 39632366 Xu H Zhang M Yang C Fu Y Yang J Yang W . Fast food and anxiety symptoms of Chinese multi-ethnic adolescents: The moderating role of regulatory emotional self-efficacy. J Affect Disord. (2025) 374:160–70. doi: 10.1016/j.jad.2025.01.036, PMID: 39800067 Samm A Varnik A Tooding L Sisask M Kolves K von Knorring A . Children’s Depression Inventory in Estonia. Single items and factor structure by age and gender. Eur Child Adolesc Psychiatry. (2008) 17:162–70. doi: 10.1007/s00787-007-0650-z, PMID: 17876502 Gomez R Vance A Gomez A . Children’s Depression Inventory: invariance across children and adolescents with and without depressive disorders. Psychol Assess. (2012) 24:1–10. doi: 10.1037/a0024966, PMID: 21859217 Wang L Feng Z Yang G Yang Y Wang K Dai Q . Depressive symptoms among children and adolescents in western China: An epidemiological survey of prevalence and correlates. Psychiatry Res. (2016) 246:267–74. doi: 10.1016/j.psychres.2016.09.050, PMID: 27741479 Hong X Li J Liang Y Wang Z Xu F . Reliability and validity of the Chinese version of Children’ s Depression Inventory. Chin J Sch Health. (2012) 33:1182–5. doi: 10.16835/j.cnki.1000-9817.2012.10.011 Xu H Wang J Yang J Yang W Zhang M Fu Y . Association between latent classes of dietary patterns and depressive symptoms among first-grade students from multi-ethnic middle schools in Yunnan Province. Chin J Sch Health. (2024) 45:168–72. doi: 10.16835/j.cnki.1000-9817.2024049 Anjum A Hossain S Sikder T Uddin ME Rahim DA . Investigating the prevalence of and factors associated with depressive symptoms among urban and semi-urban school adolescents in Bangladesh: a pilot study. Int Health. (2022) 14:354–62. doi: 10.1093/inthealth/ihz092, PMID: 31693088 Gupta S Das S Das M Banerjee S Neogi R Mukherjee S . Prevalence and correlates of depression, anxiety, and stress among high school students in a block of Hooghly district, West Bengal: Across-sectional study. J Educ Health Promot. (2023) 12:345. doi: 10.4103/jehp.jehp_1769_22, PMID: 38144014 Du X Wu H Yalikun S Li J Jia J Duan T . Trajectories of Chinese adolescent depression before and after COVID-19: A cross-temporal meta-analysis with segmented regression. J Affect Disord. (2024) 373:333–44. doi: 10.1016/j.jad.2024.12.094, PMID: 39740746 Lee JY Ban D Kim H Kim SY Kim JM Shin IS . Sociodemographic and clinical factors associated with breakfast skipping among high school students. Nutr Diet. (2021) 78:442–8. doi: 10.1111/1747-0080.12642, PMID: 33047479 Garcez MR de Castro MA César CLG Goldbaum M Fisberg RM . A chrononutrition perspective of diet quality and eating behaviors of Brazilian adolescents in associated with sleep duration. Chronobiol Int. (2021) 38:387–99. doi: 10.1080/07420528.2020.1851704, PMID: 33441036 Gong W Fong DY Wang M Lam T Chung TW Ho S . Skipping breakfast and eating breakfast away from home were prospectively associated with emotional and behavioral problems in 115, 217 chinese adolescents. J Epidemiol. (2022) 32:551–8. doi: 10.2188/jea.JE20210081, PMID: 34148915 Liu BP Fang HJ Jia CX . The serial mediation of the association between breakfast skipping and suicidality by weight status and depressive symptoms: findings from the national youth risk behavior surveys of the United States. Nutrients. (2022) 14:956. doi: 10.3390/nu14050956, PMID: 35267931 Park H Lee K . Association between breakfast consumption and suicidal attempts in adolescents. Psychol Res Behav Manag. (2022) 15:2529–41. doi: 10.2147/PRBM.S380192, PMID: 36124336 Salk RH Hyde JS Abramson LY . Gender differences in depression in representative national samples: Meta-analyses of diagnoses and symptoms. Psychol Bull. (2017) 143:783–822. doi: 10.1037/bul0000102, PMID: 28447828 Slavich GM Sacher J . Stress, sex hormones, inflammation, and major depressive disorder: Extending Social Signal Transduction Theory of Depression to account for sex differences in mood disorders. Psychopharmacol (Berl). (2019) 236:3063–79. doi: 10.1007/s00213-019-05326-9, PMID: 31359117 Anjom-Shoae J Sadeghi O Hassanzadeh Keshteli A Afshar H Esmaillzadeh A Adibi P . The association between dietary intake of magnesium and psychiatric disorders among Iranian adults: a cross-sectional study. Br J Nutr. (2018) 120:693–702. doi: 10.1017/S0007114518001782, PMID: 30068404 Gorska-Warsewicz H Rejman K Laskowski W Czeczotko M . Milk and dairy products and their nutritional contribution to the average polish diet. Nutrients. (2019) 11:1771. doi: 10.3390/nu11081771, PMID: 31374893 Riley CA Renshaw PF . Brain choline in major depression: a review of the literature. Psychiatry ResNeuroimaging. (2018) 271:142–53. doi: 10.1016/j.pscychresns.2017.11.009, PMID: 29174766 Xu H Yang Z Liu D Yu C Zhao Y Yang J . Mediating effect of physical sub-health in the association of sugar-sweetened beverages consumption with depressive symptoms in Chinese college students: A structural equation model. J Affect Disord. (2023) 342:157–65. doi: 10.1016/j.jad.2023.09.020, PMID: 37730148 Beigrezaei S Mazidi M Davies IG Salehi-Abargouei A Ghayour-Mobarhan M Khayyatzadeh SS . The association between dietary behaviors and insomnia among adolescent girls in Iran. Sleep Health. (2022) 8:195–9. doi: 10.1016/j.sleh.2021.12.002, PMID: 35131218 Kandeger A Egilmez U Sayin AA Selvi Y . The relationship between night eating symptoms and disordered eating attitudes via insomnia and chronotype differences. Psychiatry Res. (2018) 268:354–7. doi: 10.1016/j.psychres.2018.08.003, PMID: 30098543 Chen SJ Que J Chan NY Shi L Li SX Chan JWY . Effectiveness of app-based cognitive behavioral therapy for insomnia on preventing major depressive disorder in youth with insomnia and subclinical depression: A randomized clinical trial. PloS Med. (2025) 22:e1004510. doi: 10.1371/journal.pmed.1004510, PMID: 39836656 Qu Y Li T Xie Y Tao S Yang Y Zou L . Association of chronotype, social jetlag, sleep duration and depressive symptoms in Chinese college students. J Affect Disord. (2023) 320:735–41. doi: 10.1016/j.jad.2022.10.014, PMID: 36270445 Reales-Moreno M Tonini P Escorihuela RM Solanas M Fernández-Barrés S Romaguera D . Ultra-processed foods and drinks consumption is associated with psychosocial functioning in adolescents. Nutrients. (2022) 14:4831. doi: 10.3390/nu14224831, PMID: 36432518 Nolan LJ Geliebter A . Food addiction” is associated with night eating severity. Appetite. (2016) 98:89–94. doi: 10.1016/j.appet.2015.12.025, PMID: 26724725 Wang S Zhang Y Ding W Meng Y Hu H Liu Z . Psychological distress and sleep problems when people are under interpersonal isolation during an epidemic: A nationwide multicenter cross-sectional study. Eur Psychiatry. (2020) 63:e77. doi: 10.1192/j.eurpsy.2020.78, PMID: 32854786 Wang S Zhang Y Guan Y Ding W Meng Y Hu H . A nationwide evaluation of the prevalence of and risk factors associated with anxiety, depression and insomnia symptoms during the return-to-work period of coronavirus disease 2019 in China. Soc Psychiatry Psychiatr Epidemiol. (2021) 56:2275–86. doi: 10.1007/s00127-021-02046-4, PMID: 33616693 Diener MJ Gottdiener WH Keefe JR Levy KN Midgley N . Treatment of depression in children and adolescents. Lancet Psychiatry. (2021) 8:97. doi: 10.1016/S2215-0366(20)30518-6, PMID: 33485419 Measelle JR Stice E Hogansen JM . Developmental trajectories of co-occurring depressive, eating, antisocial, and substance abuse problems in female adolescents. J Abnorm Psychol. (2006) 115:524–38. doi: 10.1037/0021-843X.115.3.524, PMID: 16866592 Bear TLK Dalziel JE Coad J Roy NC Butts CA Gopal PK . The role of the gut microbiota in dietary interventions for depression and anxiety. Adv Nutr. (2020) 11:890–907. doi: 10.1093/advances/nmaa016, PMID: 32149335 Rodgers RF Paxton SJ Chabrol H . Depression as a moderator of sociocultural influences on eating disorder symptoms in adolescent females and males. J Youth Adolesc. (2010) 39:393–402. doi: 10.1007/s10964-009-9431-y, PMID: 20229229 Mutwalli H Herle M Kan C Keeler JL Steves C Treasure J . Lifetime history of depression and eating behaviours: a co-twin control study of the TwinsUK registry. J Affect Disord. (2025) 382:264–73. doi: 10.1016/j.jad.2025.04.111, PMID: 40280426 Verly-Miguel M Lopes CDS Freitas JV Garcia MC Marques MC Paravidino VB . Depression, anxiety and change in eating habits during the COVID-19 pandemic in Brazilian university students. PloS One. (2025) 20:e0326856. doi: 10.1371/journal.pone.0326856, PMID: 40577286 Moitra P Madan J Shaikh NI . Eating habits and sleep patterns of adolescents with depression symptoms in Mumbai, India. Matern Child Nutr. (2020) 16:e12998. doi: 10.1111/mcn.12998, PMID: 33347724