Observational Study Open Access
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Psychiatry. Sep 19, 2025; 15(9): 109611
Published online Sep 19, 2025. doi: 10.5498/wjp.v15.i9.109611
College students' depression and body image: Unraveling the Link
Zhao-Jun Cheng, Hu Tao, Chun-Mei Wu, Qi Wang, Ming Hao, School of Public Health and Health Management, Gannan Medical University, Ganzhou 341000, Jiangxi Province, China
Hua-Guo Huan, Jiangxi College of Applied Technology, Ganzhou 341000, Jiangxi Province, China
ORCID number: Ming Hao (0000-0001-7402-9234).
Co-first authors: Zhao-Jun Cheng and Hu Tao.
Author contributions: Cheng ZJ and Tao H were responsible for data collection, data analysis, and manuscript writing as the co-first authors of the paper; Huan HG was responsible for study design, and data analysis; Wu CM was responsible for data collection, study design and data analysis; Wang Q was responsible for study design, data collection, and funding acquisition; Hao M was responsible for study design, data collection, data analysis, manuscript writing, and funding acquisition; all of the authors read and approved the final version of the manuscript to be published.
Supported by Starting Research Fund from the Gannan Medical University, No. QD202121.
Institutional review board statement: This study was approved by the Ethics Committee of the Gannan Medical University. This study was conducted according to the guidelines in the Declaration of Helsinki.
Informed consent statement: All study participants provided informed consent, agreeing to the required measurement and survey completion procedures. All methods were performed in accordance with the relevant guidelines and regulations.
Conflict-of-interest statement: The authors declare no conflict of interest.
STROBE statement: The authors have read the STROBE Statement—checklist of items, and the manuscript was prepared and revised according to the STROBE Statement—checklist of items.
Data sharing statement: The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Ming Hao, Associate Professor, School of Public Health and Health Management, Gannan Medical University, No. 4 Experimental Building, Rongjiang New Area, Ganzhou 341000, Jiangxi Province, China. hm48922200@yahoo.co.jp
Received: May 19, 2025
Revised: June 11, 2025
Accepted: July 15, 2025
Published online: September 19, 2025
Processing time: 101 Days and 20.9 Hours

Abstract
BACKGROUND

With the increasing global incidence of mental illness, depression has become a serious problem among college students.

AIM

To investigate the relationship between depression and its correlates in Chinese adolescents and to identify diagnostic predictors of depression, examine the effects of binge eating, physical activity, and body dissatisfaction on depression among college students and to determine a diagnostic cutoff value for depression based on body dissatisfaction.

METHODS

We conducted a cross-sectional survey of 1286 college students in South China. Physical activity level, depressive symptoms, and binge eating behavior were assessed using the Physical Activity Scale-3, Zung Self-Rating Depression Scale, and Dutch Eating Behavior Questionnaire, respectively. The absolute difference between actual body mass index (BMI) and ideal BMI was used to indicate the level of body dissatisfaction. Structural equation modeling (SEM) and receiver operating characteristic (ROC) curve analysis were used to examine the relationships between these variables and depression.

RESULTS

The findings showed that female college students reported higher levels of depression. Physical activity, body dissatisfaction, and binge eating behavior were significantly associated with depression. SEM revealed that body dissatisfaction played a mediating role. A body dissatisfaction score of 1.73 was identified as the diagnostic cutoff value for predicting depression, with an area under the ROC curve of 70.0%, providing a basis for targeted interventions.

CONCLUSION

This study demonstrated a significant positive correlation between body dissatisfaction and depression. Low levels of physical activity and binge eating behaviors were found to heighten the risk of depression. Therefore, promoting physical activity and healthy eating habits among adolescents is essential. Additionally, the identification of a diagnostic threshold for body dissatisfaction represents a novel finding with important implications for early screening. Future longitudinal studies are recommended to further refine this diagnostic criterion.

Key Words: College students; Depression; Physical activity; Binge eating; Body dissatisfaction; Structural equation modeling; Receiver operating characteristic curves

Core Tip: This study investigates the relationship between depression and body dissatisfaction among Chinese college students, revealing that body dissatisfaction is a significant mediator. It identifies a critical cutoff value (body mass index difference ≥ 1.73) for predicting depression, highlighting the importance of promoting physical activity and healthy eating behaviors to reduce depression risk.



INTRODUCTION

The incidence of mental illness has increased globally in recent decades. Among the various types of mental illnesses, depression is particularly common, and its impact is felt worldwide. According to statistics from the World Health Organization (WHO), the number of people suffering from depression globally has exceeded 350 million. Depression has become the fourth most common disease in the world, and its incidence rate continues to increase rapidly. The WHO further predicts that by 2030, depression will jump to the top of the global burden of disease, and its associated economic and social burdens will be the heaviest[1,2]. In a systematic review of data on major depressive disorder published between January 1, 2020, and January 29, 2021, the prevalence and burden of the disease by age, sex, and geography were quantified for the first time in 204 countries and territories. The meta-analysis results showed a 25% increase in the global prevalence of depression and an even higher 28% increase in the prevalence of major depression[3]. In addition, depression can have adverse health consequences for individual patients, including substance abuse, anxiety attacks, and an increased risk of suicide[4]. Of particular concern is the fact that with continued socioeconomic development and the accelerating pace of life, people face increasing stress, which undoubtedly drives the continued increase in the prevalence of depression[5]. In summary, depression has become a major social and public health problem affecting human health, posing a serious challenge to global public health and necessitating in-depth research and effective interventions.

A study on the global burden of depression in youth from 1990 to 2019 showed that individuals aged 10-24 years, including college students, had a high prevalence of depression[6]. College students, as a special group, are known to experience academic and employment pressures and undergo a period of transition to society; therefore, they may be more prone to depression. In China, college students’ mental health problems are extremely serious. For example, a systematic evaluation and meta-analysis of the prevalence of depression among Chinese college students showed that the overall prevalence of depression was 28.4% (n = 185787)[7]. The prevalence of depression among Chinese college students is more prominent than that in the international scenario. A systematic evaluation and meta-analysis of data on the prevalence of depression among students from 167 cross-sectional studies (n = 116628) and 16 Longitudinal studies (n = 5728) in 43 countries revealed an overall depression prevalence of 27.2%[8]. This indicates a serious concern regarding depression among college students in China, and the increase in the detection rate of depression among college students in recent years is even more concerning[9]. This poses a significant threat to the mental health of college students and other young people. Therefore, exploring ways to reduce the incidence of depression among this group is crucial for improving the mental health of the whole population. This is necessary to foster the development of psychosocial health, and demands extensive attention and in-depth research.

Several studies have firmly established that body dissatisfaction is a key and powerful predictor of depressive symptoms, particularly among young adults such as adolescents and college students[10-12]. Body dissatisfaction, defined as the negative subjective perception of one’s appearance, weight, or body shape, is believed to lead to depression through a variety of pathways. These include diminished self-esteem and self-worth, increased social anxiety and withdrawal, heightened rumination, and engagement in maladaptive coping behaviors such as disordered eating and the deliberate avoidance of social or physical activities[13-15]. Longitudinal research has provided highly persuasive evidence for a causal relationship between body dissatisfaction and depression. Relevant studies have shown that adolescents who report higher levels of body dissatisfaction are significantly more likely to develop depression in late adolescence or young adulthood compared to their peers, even when baseline depressive symptoms are taken into account[16-18]. The strength of this association is striking: Research has found that individuals with body dissatisfaction are several times more likely to experience clinically significant depression than those who are satisfied with their bodies[10]. Moreover, this association exhibits notable gender differences. Typically, females report much higher levels of body dissatisfaction than males, and the link between body dissatisfaction and subsequent depression is also much stronger in females[19], perhaps due to the societal and cultural emphasis on thinness as the ideal for women. Although most current research focuses on body dissatisfaction related to the perception of being overweight or obese, there is also evidence that dissatisfaction associated with being underweight or having insufficient muscle mass (which is more common in males) is similarly linked to poorer mental health outcomes, including depression[20-22]. Therefore, an in-depth exploration of the complex interplay between body dissatisfaction and depression is of vital importance for the development of precise and effective interventions targeting this vulnerable population.

In recent years, an increasing number of studies have been conducted on the effectiveness of physical activity in alleviating depression, and the benefits of physical activity on mental health have gradually been recognized by the public. For example, a study on the effects of different types of physical activity on depression demonstrated that low-intensity physical activity can effectively reduce the risk of depression, compared with not participating in physical activity; this positive effect is reflected across different populations, including healthy adults, people with mental health disorders, and people with a variety of chronic diseases[23-25]. Additionally, people with higher levels of physical activity tend to be less prone to obesity and a high body mass index (BMI); accordingly, they have lower levels of dissatisfaction with their bodies[26]. As the effect of body dissatisfaction on depression has been widely recognized, this population also suffers from relatively few cases of depression[27]. However, college students tend to exhibit lower exercise levels. For example, a study assessing the relationship between diet and physical activity behaviors and loneliness among 264 freshmen in the United States reported that the percentage of students engaging in low-intensity exercise was as high as 53.8%[28]. In China, a cross-sectional study on physical exercise among college students found that approximately 77.6% of participants engaged in low-intensity physical activity and reported a significant negative correlation between physical activity and depression[29]. In another study examining physical exercise behavior among college students at five universities in southern China, 66.1% were found to engage in low-intensity exercise[30]. These findings suggest that the physical activity levels of college students in southern China are generally low, highlighting the urgent need to improve physical activity among this population. Given that physical activity is a key factor in significantly reducing depression levels in most populations, assessing the exercise levels of Chinese college students is particularly critical. Moreover, targeted measures can help improve mental health and reduce the incidence of depression.

The impact of healthy eating behavior on mental health is evident[31]. Healthy dietary behaviors also play an important role in preventing the onset of depression. However, most studies on the relationship between diet and depression have focused on middle-aged and older adults, with relatively few focusing on college students[32]. The dietary situation of college students is even more complex because they undergo a shift from eating at home to relying on school meals in high school. In college, students have more freedom and are not bound by their parents, which increases their likelihood of developing poor eating habits. For example, a study of college students’ perceptions of processed foods showed that most students preferred to buy processed foods, such as bagged snacks and canned foods, as part of their daily dietary choices. Students favor these processed foods because of their convenience and variety of flavors[33]. At the same time, young Chinese people also exhibit poor eating behavior. For example, a study conducted in southern China showed that 2.5% of young Chinese engaged in high-risk eating behaviors[34]. In addition, poor eating behaviors can negatively affect both physical and mental health, including contributing to depression[35]. Such dietary habits therefore have significant adverse effects on overall well-being. For college students, developing reasonable and healthy eating behaviors is crucial for the prevention of depression and other psychological disorders.

In this context, this study aimed to investigate the effects of binge eating, physical exercise, and body dissatisfaction on college students’ depression, and to utilize receiver operating characteristic (ROC) curve analysis with body dissatisfaction as a predictor of depression. The findings are expected to fill a research gap concerning the college student population and provide a theoretical basis for mental health interventions. We propose the following hypotheses: (1) H1: Physical activity negatively affects body dissatisfaction; (2) H2: Binge eating positively affects body dissatisfaction; (3) H3: Body dissatisfaction positively affects depression; (4) H4: Physical activity negatively affects depression; and (5) H5: Binge eating positively affects depression.

MATERIALS AND METHODS
Participants

This cross-sectional study was conducted from March 22 to April 15, 2024. Data were collected using a questionnaire title “Questionnaire on Physical Dissatisfaction, Physical Activity, Eating Behavior, and Depression among College Students”, which was distributed via the social media application WeChat. The survey contained 70 items and took approximately 6 minutes to complete. University students from southern China were selected as the study population. Invitation letters were sent, and a total of 1286 students agreed to participate. Among them, 45.10% were male (n = 580), and 54.90% were female (n = 706).

Inclusion criteria: (1) Current undergraduate students enrolled in universities in South China (excluding junior colleges to maintain consistency in educational background); (2) Aged 18 years or older (meeting ethical guidelines for adult participants); (3) Willing to sign an informed consent form, which outlined the study’s objectives, procedures, and privacy protections; and (4) Capable of reading and writing Chinese and completing the questionnaire independently.

Exclusion criteria: (1) Failure to sign the informed consent form; (2) Missing demographic information; (3) Inconsistent or disengaged responses (e.g., selecting the same response repeatedly); (4) Prior diagnosis of schizophrenia, bipolar disorder, or acute severe depression by a psychiatrist; (5) Diagnosis of malignant tumors, severe cardiovascular or cerebrovascular diseases (e.g., coronary heart disease, stroke), or endocrine disorders (e.g., uncontrolled diabetes) within the past year; and (6) Failure to complete at least 20% of the questionnaire or missing physical measurements (e.g., height and weight). Ultimately, 1286 valid questionnaires were included in the final analysis (Figure 1).

Figure 1
Figure 1 Participant enrollment and exclusion flowchart. Flowchart depicting the participant selection process, including inclusion criteria (South China undergraduates, ≥ 18 years, informed consent) and exclusion criteria (missing data, severe medical/mental conditions). A total of 1286 valid participants were included.
Body dissatisfaction

Weight was measured using a calibrated body composition instrument (BC 601, Tanita) with an accuracy of 0.1 kg. Height was measured with a stadiometer (Seca 213, Seca Nihon) accurate to 0.1 cm. These measurements were used to calculate actual BMI. Participants also reported their ideal body weight, which was used to calculate their ideal BMI using the formula: BMI = weight (kg)/height2 (m). The absolute value of the difference between actual and ideal BMI was used as an index of body dissatisfaction, with larger values indicating greater body dissatisfaction[36]. This method, widely used in body image research[37-39], provides an objective and continuous measure of dissatisfaction, avoiding the biases commonly found in subjective self-reports.

Physical activity

The Physical Activity Scale-3 was used to assess participants’ physical activity levels[40]. The scale includes three items measuring intensity, duration, and frequency of exercise. Each item was rated on a 5-point scale (1-5), and total activity volume was calculated by multiplying the three scores. The resulting scores ranged from 0 to 100 and were categorized as follows: (1) Low (0-19); (2) Moderate (20-42); and (3) High (43-100).

Zung Self-Rating Depression Scale

Depressive symptoms were measured using the Zung Depression Self-Rating Scale (SDS)[41], a 20-item self-report questionnaire covering emotional, psychological, and physical aspects of depression. Each item is rated from 1 to 4, yielding a total score from 20 to 80, with higher scores indicating more severe symptoms. Participants were classified into two groups: (1) Non-depressive (SDS < 40); and (2) Depressive (SDS ≥ 40). The SDS has been validity in China with good reliability: (1) Cronbach’s alpha = 0.862; and (2) Test-retest reliability = 0.820.

Dutch Eating Behavior Questionnaire

Diet behavior was assessed using the Dutch Eating Behavior Questionnaire (DEBQ)[42], which evaluates restrained, emotional, and external eating. The DEBQ consists of 33 items: (1) Restrained eating (10 items, e.g., “How often do you try to eat between meals because you are watching your weight?”); (2) Emotional eating (13 items, e.g., “Do you have the desire to eat when you are anxious, worried, or stressed?”); and (3) External eating (10 items, e.g., “If you see someone else eating, do you also have the desire to eat?”). Items are rated on a 5-point Likert scale from “never” (1) to “very often” (5). Average subscale scores were calculated by dividing the total subscale score by the number of items. Higher scores indicate higher levels of the corresponding eating behavior. The DEBQ was adapted cross-culturally by two independent translators who translated it into Polish. The jointly agreed-upon version was then back-translated into English. The translation process continued until linguistic consistency was achieved between the Polish and original versions. The adapted scale was pre-tested on a group of 49 students who reported no difficulty completing the questionnaire. The internal consistency reliabilities of the Chinese version of the DEBQ ranged from 0.76 to 0.93, the combined reliabilities from 0.88 to 0.94, and the retest reliabilities from 0.72 to 0.81. Overall, they demonstrated good reliability and validity, making the scale suitable for assessing eating behaviors of Chinese university students.

Statistical analysis

Statistical Package for the Social Sciences (version 26.0) was used for statistical analysis. Descriptive statistics were reported as mean ± SD for continuous variables and frequency (percentage) for categorical variables. The t-test and one-way analysis of variance were used to examine the relationships between independent variables and loneliness. Statistical significance was set at P (two-sided) < 0.05. AMOS (version 24) was used to conduct structural equation modeling (SEM) to assess the relationships among depression (dependent variable), physical activity and eating behavior (independent variables), and BMI difference (mediating variable). Pearson’s correlation coefficients were calculated to analyze associations among variables. To assess model fit, the following indices were used: (1) Root mean squared error of approximation (RMSEA) ≤ 0.10; (2) Comparative fit index (CFI) > 0.90; and (3) Tucker-Lewis index (TLI) > 0.90[43]. Bootstrapping was applied to test the indirect, total, and mediated effects of physical activity and diet on depression through body dissatisfaction. Additionally, an ROC curve was plotted to determine the optimal cutoff point of body dissatisfaction for predicting depression. The area under the curve (AUC) was used to evaluate the precision of the predictor. Statistical significance was set at P < 0.05.

RESULTS
Participants’ general characteristics

The characteristics of the study population are summarized in Table 1. The sample comprised 1286 students attending college in Jiangxi Province and included 54.90% males (n = 706) and 45.10% females (n = 580). Their mean age was approximately 19.6 years. Their mean BMI difference was 2.91, and their mean depression score was 44.77. Finally, their mean dietary and exercise scores were 85.12 and 17.21, respectively, and body dissatisfaction (t = 0.17, P < 0.05), physical activity (t = 10.57, P < 0.001), diet (t = -11.43, P < 0.001) and depression (t = -4.35, P < 0.001) differed by gender. Figure 2 shows the percentage of Chinese university students based on their physical activity level. The percentage of students with a low level of physical activity was as high as 71.2%, and the percentages of those with moderate- and high-intensity physical activity were 15.9% and 12.9%, respectively.

Figure 2
Figure 2 Percentage of Chinese college students by physical activity level. Distribution of low-intensity, moderate-intensity, and high-intensity physical activity levels among participants, stratified by gender. Data from the Physical Activity Scale-3 show 71.2% of students engaged in low-intensity activity, with a higher proportion of females in this category.
Table 1 Demographic characteristics of college students in Southern China.
Demographic characteristics
mean ± SD
P value

Male (n = 706)
Female (n = 580)
Total (n = 1286)
Age (years)19.78 ± 2.0119.29 ± 1.7219.56 ± 1.90< 0.05
Body mass index (kg/m²)22.41 ± 3.7521.78 ± 3.0322.13 ± 3.46< 0.01
Body dissatisfaction (kg/m²)2.92 ± 2.002.90 ± 1.822.91 ± 1.92< 0.05
Physical activity score22.16 ± 21.0411.19 ± 14.8917.21 ± 19.31< 0.01
Diet score79.64 ± 19.7891.79 ± 17.9385.12 ± 19.90< 0.05
Depression score43.73 ± 9.6846.04 ± 9.1944.77 ± 9.53< 0.01
Bivariate analysis

The correlation between each variable was explored using Pearson’s correlation analysis, and the results are presented in Table 2. A significant correlation was observed between the variables at the 99% level. Based on the correlation coefficients, BMI differences were positively correlated with depression and diet and negatively correlated with physical activity. Depression was positively correlated with diet and negatively correlated with physical activity (P < 0.01).

Table 2 Results of Pearson’s correlation analysis between the variables.
Dimension
Body dissatisfaction
Depression
Diet
Physical activity
Body dissatisfaction1
Depression0.21511
Diet0.14310.13211
Physical activity-0.1691-0.1381-0.14711
SEM

Figure 3 shows the assessed structural models and obtained standardized β. The models had a good fit with the data (RMSEA = 0.098, 95%CI: 0.081-0.116, CFI = 0.881, and TLI = 0.745). The hypothesized relationships were tested using SEM (physical activity, body dissatisfaction, diet, and depression). Table 3 presents the direct effects of each structural model, which were significant for all paths (P < 0.001), indicating that the five hypotheses were supported. The SEM results revealed the following. First, physical activity had a negative direct effect on body dissatisfaction (β = -0.016, P < 0.001; H1). Second, diet had a positive direct effect on body dissatisfaction (β = 0.048, P < 0.001; H2). Third, body dissatisfaction had a positive direct effect on depression (β = 0.894, P < 0.001; H3). Fourth, physical activity had a negative effect on depression (β = -0.046, P < 0.001; H4). Finally, diet had a positive effect on depression (β = 0.309, P < 0.001; H5).

Figure 3
Figure 3 Hypothetical path model for relationships between study variables. Standardized path coefficients from structural equation modeling. Circles represent latent variables (e.g., depression, body dissatisfaction), and rectangles denote observed variables (e.g., physical activity, diet). Arrows indicate standardized β coefficients and significance (aP < 0.001), illustrating direct/indirect effects of physical activity and diet on depression via body dissatisfaction.
Table 3 Results of the structural equation modeling path relationship test.
Pathway relationship
Estimate
SE
Critical ratio
P value
Physical activity negatively affects body dissatisfactionPhysical activity turns to body dissatisfaction-0.1570.003-5.735< 0.001
Binge eating positively affects body dissatisfactionDiet turns to body dissatisfaction0.1140.0133.563< 0.001
Body dissatisfaction positively affects depressionBody dissatisfaction turns to depression0.1800.1376.535< 0.001
Physical activity negatively affects depressionPhysical activity turns to depression-0.0930.013-3.397< 0.001
Binge eating positively affects depressionDiet turns to depression0.1480.0674.614< 0.001
Analysis of mediating effects

Figure 4 and Tables 4 and 5 show the effect values of the mediation model (P < 0.01), where the bootstrap 95%CI for the mediating effects of diet and physical activity on body dissatisfaction and depression did not contain a 0. The direct effect of diet on depression was 0.0492 (P < 0.001), where β = 0.0137 (P < 0.001) was mediated through body dissatisfaction. The direct effect of physical activity on depression was 0.0492 (P < 0.001), where β = 0.0137 (P < 0.001) was mediated through body dissatisfaction. This indicated a mediating effect in this relationship, accounting for 78.2% and 21.8% of the total effect (0.0630) for the direct (0.0492) and indirect (0.0137) effects, respectively. Additionally, the direct effect of physical activity on depression was β = -0.0517 (P < 0.001), and the indirect effect mediated through physical dissatisfaction was β = -0.0164 (P < 0.001), which accounted for 75.9% of the total effect (-0.0681) for the direct effect (-0.0517) and 24.1% for the indirect effect (-0.0164).

Figure 4
Figure 4 Mediation model. A: Mediation model of diet, body dissatisfaction, and depression. Path diagram of direct and indirect effects of dietary behavior on depression. Standardized coefficients show diet influences depression through body dissatisfaction (indirect effect β = 0.0137) and a direct pathway (β = 0.0492), with mediation accounting for 218% of the total effect (bP < 0.01); B: Mediation model of physical activity, body dissatisfaction, and depression. Path diagram of direct and indirect effects of physical activity on depression. Standardized coefficients show physical activity influences depression through body dissatisfaction (indirect effect β = -0.0164) and a direct pathway (β = -0.0517), with mediation accounting for 241% of the total effect (cP < 0.01).
Table 4 Analysis of mediating effects of diet on depression.

Effect value
SE
Lower limit confidence interval
Upper limit confidence interval
Effect size (%)
P value
Total effect0.06300.01320.03700.0890< 0.001
Direct effect0.04920.01310.02350.075078.2%< 0.001
Indirect effect0.01370.00310.00810.020121.8%< 0.001
Table 5 Analysis of mediating effects of physical activity on depression.

Effect value
SE
Lower limit confidence interval
Upper limit confidence interval
Effect size (%)
P value
Total effect-0.06810.0136-0.0948-0.0413< 0.001
Direct effect-0.05170.0136-0.0783-0.025075.9%< 0.001
Indirect effect-0.01640.0032-0.0234-0.010624.1%< 0.001
ROC curve analysis

We found that the BMI difference can directly affect depression and indirectly act as a mediator. Therefore, we employed it as a predictor of depression by creating an ROC curve, as shown in Figure 5. According to the ROC curve analysis, the BMI difference demonstrated good predictive performance with a cutoff point of 1.73 and an AUC of 70.0% (P < 0.001). Thus, we inferred that body dissatisfaction is associated with depression and that body dissatisfaction ≥ 1.73 is accurate as a diagnostic clinical point for depression with high sensitivity and specificity.

Figure 5
Figure 5 Receiver operating characteristic curve for body mass index difference predicting depression. Receiver operating characteristic curve evaluating body dissatisfaction (body mass index difference) as a predictor of depression. The optimal cutoff value of 1.73 yields an area under the curve of 70.0%, with 84.6% sensitivity and 46.8% specificity (P < 0.001). AUC: Area under the curve.
DISCUSSION

The results of our study demonstrate that the higher the level of body dissatisfaction, the higher the depression score (Tables 2 and 3). A study conducted in Korea on the correlation between body image dissatisfaction and depression showed that patients with body image dissatisfaction were 8.59 times more likely to have depressive symptoms than patients without body image dissatisfaction[44]. Another longitudinal study on body dissatisfaction and depression in 457 women revealed that women with body image dissatisfaction had a fourfold higher risk of developing depression[45]. This finding is consistent with the results of the present study. Moreover, according to our results, there was a difference in depression in terms of sex, and females were significantly more depressed than males. Interestingly, the level of body dissatisfaction was higher among males than among females (Table 1). In the gender-additive model of depression, body dissatisfaction and eating disorder symptoms were better predictors of depression in adolescent girls than in boys, indicating that this set of risk factors outweighed other risk factors predicting depression in both sexes[46]. This explains why higher levels of depression were observed in females than in males.

However, another study on the relationship between body dissatisfaction and the prevalence of depression among Spanish university graduates revealed no association between body dissatisfaction and depression in adult males or females[47]. This illustrates the complexity of the differences in depression levels between men and women, which may be influenced by several factors, such as diet and exercise. This is because when women face body dissatisfaction, their eating behavior may change. Conversely, men may choose to exercise more often to achieve their desired body[48]. Thus, these risk factors may influence depression. In this study, we examined binge eating and physical activity to determine the complex mechanisms of body dissatisfaction and depression that promote mental health and physical harmony at multiple levels.

However, the current study has a limitation in that it focused only on the relationship between body dissatisfaction and depression. Most current research on body dissatisfaction focuses on body dissatisfaction due to obesity[49]. However, other conditions must be explored further. For example, body dissatisfaction due to thinness may occur in some populations, in which case they may prefer a normal or more robust body type than their current one. Such dissatisfaction with one’s physical condition may lead to psychological changes. For example, the results of a cross-sectional study on body image and depressive symptoms in a Danish sample of 9963 people showed that those who were too thin were at risk for depression[50]. Furthermore, the self-esteem of both obese and thin people may be affected, possibly because they are more likely to be dissatisfied with themselves[51,52]. This psychological state makes them more vulnerable to depression. In summary, body dissatisfaction should not only be seen as a predictor of depression in the obese population but also in the thin population. Given that body dissatisfaction is an important factor affecting depression, sufficient attention should be paid to prevent its adverse effects on mental health.

As shown in Figure 2, physical activity had a significant negative effect on depressive symptoms. College students face several stressors, and engaging in appropriate sports plays a crucial role in relieving stress, which can undoubtedly reduce their risk of depression[53]. This finding is consistent with ours. We also found that physical activity reduced the probability of developing depression by indirectly affecting body dissatisfaction as a pathway (Table 5, Figure 4B). For example, a study of 15632 participants on body dissatisfaction and its association with physical activity showed that physical activity levels were negatively associated with participants’ reported body dissatisfaction[54]. This is mainly because appropriate exercise levels can help maintain the desired body shape without exceeding the normal range, which reduces the likelihood of body dissatisfaction and subsequent depression.

Conversely, when a person’s physical activity level is low, the frequency of going out tends to decrease. Those with high exercise levels have a higher probability of socializing or being active in groups. This positive behavior can contribute to a better state of mind, which makes them less likely to fall into a state of depression[55]. Our results demonstrated that among Chinese college students, the proportion of those who engaged in low-intensity exercise was 71.2%, indicating that the overall exercise level of Chinese college students was low (Figure 3). This could explain the high rate of depression. Evidently, appropriate physical exercise has a crucial effect in reducing body dissatisfaction and depression. Therefore, college students should be encouraged to participate actively in sports.

According to our results, a significant positive correlation was observed between binge drinking behavior and body dissatisfaction (Table 2). Consistent with our findings, a study on the predictors of repeated binge eating and inappropriate weight compensation behaviors among 2555 first-year college students showed that body dissatisfaction was a predictor of frequent binge eating behaviors[56]. In addition, we found that the more severe the binge eating behavior, the greater the likelihood of depression (Table 3). Here, binge eating was not considered a separate eating disorder, but a type of maladaptive eating behavior influenced by psychological factors related to stress, emotions, and personal feelings. Eating is a way to gain satisfaction and relieve stress quickly; people often choose to relieve their stress by eating. However, college students who are inexperienced in dealing with stress are more likely to develop such undesirable eating behaviors. Those with binge eating behavior are more inclined to consume high-energy, high-fat foods[57].

Therefore, this behavior is detrimental to depression and leads to an increase in body weight or obesity, thereby worsening depression, as revealed by our results (Table 4, Figure 4A). Furthermore, a study on the association between BMI and emotional eating among 506 healthy adults found that people with a high BMI were more likely to be affected by poor eating behaviors such as binge eating[58]. This creates a vicious circle—only by promoting good eating behaviors can depression be more effectively and fundamentally alleviated in the college population.

The results of our study clearly demonstrate that physical activity and healthy eating behaviors can effectively reduce the likelihood of depression. Body dissatisfaction played a key mediating role between physical activity, healthy eating, and depression and directly influenced depression (Figure 2). The importance of body dissatisfaction in the development of depression was also emphasized by the results of a prospective study of 2078 women and 1675 men, which showed that body dissatisfaction predicted the onset of depression[59]. Therefore, it is important to consider body dissatisfaction as a core research topic for preventing the onset of depression. By quantifying and determining a diagnostic cutoff point, the diagnosis and treatment of depression in college students can be significantly transformed. This will provide key guidance for research and practice in the field of college students’ mental health and is expected to play a key role in improving their mental health and promoting research in related fields.

The area under the ROC curve is a key indicator of diagnostic accuracy, representing the area that indicates whether a randomly selected participant with a disease has a higher probability of being (correctly) rated or ranked than a randomly selected participant without a disease[60]. It is most widely used for assessing prediction and the ability to differentiate between diseased and non-diseased individuals. Based on this, we analyzed the ROC curves. The results showed that the area under the ROC curve for body dissatisfaction was 70%. In some clinical scenarios, an AUC of 0.65 is considered high[61]. This indicated the high accuracy of using body dissatisfaction ≥ 1.73 as a diagnostic point for depression (Table 6). Based on our results, we identified and proposed a diagnostic cutoff value for depression in a college population for the first time. This groundbreaking finding holds significance for early screening of university students globally and provides a key quantitative benchmark for mental health monitoring in higher education settings. It also facilitates the development of an early warning systems to identify and support students at risk of depression in a timely manner.

Table 6 Work characteristics curve analysis for participants with body mass index differences.
Indicator
Cutoff value
An area under the curve (%)
Sensitivity (%)
Specificity (%)
Jordon’s index (%)
SE
Lower limit confidence interval
Upper limit confidence interval
P value
Body dissatisfaction1.7370.084.646.831.40.0160.6630.727< 0.001

Notably, the significant association between body dissatisfaction and depression identified in this study reflects the combined influence of sociocultural factors and behavioral patterns. In Chinese society, where the aesthetic ideal of “thin is beautiful” is widespread, the persistent portrayal of idealized body types on social media compels college students to strongly link their external appearance with their self-worth. This often results in heightened sensitivity to the discrepancy between their actual BMI and the ideal value[62]. This social conditioning has a particularly pronounced impact on women; traditional gender role expectations lead women to focus more on their appearance, while men tend to prioritize other areas[16]. This partly explains the paradox observed in this study: Women exhibited higher depression scores but slightly lower body dissatisfaction (Table 1). In terms of behavioral patterns, low-intensity exercise (71.2%) undoubtedly exacerbates body dissatisfaction through uncontrolled weight management and increases the likelihood of depression due to reduced social interaction. Binge eating, as a stress-compensation behavior, creates a vicious cycle of emotional eating—body image anxiety—depression, which is particularly evident among college students who lack emotional management skills[63].

Based on these results, universities worldwide can promote healthy lifestyle interventions, such as encouraging regular physical activity and a balanced diet, to prevent depression and enhance students’ health and resilience. These strategies can help reduce disruptions and social difficulties caused by depression, ultimately improving the quality of higher education, supporting students’ personal development, and contributing to broader societal stability.

Limitations

However, we must be aware of the limitations of this diagnostic cutoff. Although our sample was representative, it may not have covered the diversity of all college students. The relationship between body dissatisfaction and depression may differ across college students from different regions, cultural backgrounds, and majors, which may affect the generalizability of the cutoff value. Therefore, when applying a cutoff value in practice, various factors must be considered to improve the accuracy and comprehensiveness of the diagnosis.

In this study, we identified depression diagnosis points among college students; however, further validation is needed to ensure that the results more accurately reflect real-world conditions. In the future, we plan to collaborate with other universities to select participants from diverse backgrounds, including different regions, majors, and sex ratios, to ensure broader diversity and more comprehensively assess the long-term effectiveness and stability of these diagnostic points in predicting and diagnosing depression.

Although this study provides a quantitative threshold for depression screening, its limitations must be carefully considered. First, the cross-sectional design did not establish a causal direction; physical dissatisfaction may be a symptom of depression rather than a cause. Second, the single location of the sample (Southern China) affects the generalizability of the conclusions. Additionally, the study did not include potential variables, such as family support and social media use, which could indirectly influence depression by reinforcing physical dissatisfaction. Therefore, these interactions should be investigated in future studies.

CONCLUSION

This study focused on the effects of binge eating, physical activity, and body dissatisfaction on depression among college students and used ROC curve analysis to determine cutoff values to measure depression. The results showed that body dissatisfaction was positively associated with depression, and that body dissatisfaction was a significant factor in depression across all body types. Low physical activity and binge eating behaviors increase depression; therefore, it is important to encourage adolescents to be physically active and adopt good eating behaviors. We also identified body dissatisfaction ≥ 1.73 as a diagnostic threshold for depression in college students, which is significant for early screening, and our study uncovered a novel finding not found in previous studies. Based on this, we propose a longitudinal study in the future to further refine it.

Footnotes

Provenance and peer review: Unsolicited article; Externally peer reviewed.

Peer-review model: Single blind

Specialty type: Psychology

Country of origin: China

Peer-review report’s classification

Scientific Quality: Grade A, Grade B, Grade B

Novelty: Grade A, Grade B, Grade C

Creativity or Innovation: Grade A, Grade B, Grade C

Scientific Significance: Grade A, Grade B, Grade B

P-Reviewer: Liu YT; Wang XZ; Zhu ZY S-Editor: Luo ML L-Editor: A P-Editor: Zhang L

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