https://orcid.org/0000-0001-9302-667X
Figures
Abstract
Introduction
University students face a variety of challenges, including mental health issues, which are often compounded by societal and individual factors such as body image concerns, obesity, and experiences of intimate partner violence. These factors may adversely affect their mental health and academic performance. Yet, limited research exists on studies evaluating the impact of these factors on depression in Nigerian institutions of higher learning. This study aims to address this gap by examining the impact of these factors on self-reported depression with a focus on the moderating role of sex.
Objective
To assess the associations between body image concerns, obesity, intimate partner violence, and sexual coercion with depression among university students in Nigeria and to explore how these relationships vary by sex.
Methodology
This cross-sectional study was conducted over a one-month period among university students in Nigeria. Data was collected through structured, self-administered questionnaires. The primary outcome variables were self-reported depression. Explanatory variables included body image concerns, BMI categories (obese vs. normal BMI), intimate partner violence, and sexual coercion. Sex was examined as a moderator.
Inverse probability weighting was used to account for confounding variables, including age, sex, year in school, parental education, household income, smoking and alcohol consumption, and other comorbidities. Multivariable regression analyses were performed to evaluate the relationships between explanatory variables and outcomes, adjusting for potential confounders.
Results
The study included 501 participants, with 64.5% females and 35.6% males. Most respondents (83.4%) were aged 18–20 years. Obesity was observed in 18.6% of participants, higher in females (20.7%) than males (14.6%).
Sexual coercion was reported by 10.8% (males: 5.6%; females: 13.6%), while 3.4% experienced intimate partner violence (IPV), with similar rates in both genders. Depression was reported by 33.5% of participants, more common in females (35.3%) than males (30.3%).
Body image concerns increased the risk of depression by 35.3% (95% CI: 13.0%−57.7%, p = 0.002), particularly in males (26.3%, 95% CI: 16.4%−69.1%, p = 0.227). Obesity was linked to significantly higher depression rates in males (25.9%, 95% CI: 1.9%−50.0%, p = 0.035) but not in females. Sexual coercion strongly correlated with higher depression rates in both genders
(males: 43.0%, 95% CI: 23.5%−62.6%, p < 0.001; females: 39.5%, 95% CI: 20.9%−58.1%, p < 0.001). IPV showed a weaker link to depression, with rates of 21.1% in males and 30.1% in females, though not statistically significant.
Conclusion
This study highlights the complex interplay between psychosocial factors and their impact on mental health outcomes among university students in Nigeria. Addressing these factors, particularly through gender-sensitive interventions, is crucial for improving student mental health.
Policy implications
The findings call for the integration of mental health and psychosocial support services in university settings, including counseling and educational programs on body image and intimate partner violence. Policymakers and university administrators should prioritize gender-sensitive approaches to address the unique challenges faced by male and female students. Additionally, strategies to promote healthy lifestyle behaviors and prevent obesity among students should be implemented to enhance their mental health and academic performance.
Citation: Akinyemi O, Ekundayo OK, Fasokun M, Ogunyankin F, Ifoto OS, Alatise OD, et al. (2025) Body image, obesity, and sexual coercion: Impacts on depression among students at a Nigerian university. PLoS One 20(6): e0319308. https://doi.org/10.1371/journal.pone.0319308
Editor: Patrick Ifeanyi Okonta, Delta State University, NIGERIA
Received: January 30, 2025; Accepted: May 19, 2025; Published: June 17, 2025
Copyright: © 2025 Akinyemi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting Information files.
Funding: National Institute on Minority Health and Health Disparities Award Number: 2U54MD007597 | Recipient: William Southerland PhD., The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interest exist.
Introduction
Depression is a significant global public health issue and a leading contributor to disability, affecting over 280 million people worldwide [1,2]. Among university students, the prevalence of depression is alarmingly high, with estimates ranging from 10% to 30% globally [3–5]. University students are particularly vulnerable due to the transitional nature of their academic and personal lives, which often involves managing academic pressures, social relationships, financial constraints, and future career uncertainties [6–8]. In low- and middle-income countries (LMICs), including Nigeria, the burden of depression among university students is particularly pronounced, with studies indicating that approximately one-quarter to one-third of students exhibit depressive symptoms, and some research reporting even higher rates [9–12].
Several psychosocial factors have been identified as significant contributors to depression [13,14]. Body image concerns, defined as negative perceptions, thoughts, and feelings about one’s physical appearance, are particularly associated with low self-esteem, social anxiety, and depressive symptoms, especially in the context of increasing obesity rates [15–17]. Obesity, defined by a Body Mass Index (BMI) of 30 or higher, not only carries physical health risks but also contributes to psychological distress due to societal stigma and discrimination [18–20]. These challenges are particularly relevant in university settings, where social comparison and peer influence significantly impact students’ body image and mental health, with studies reporting that peer pressure and appearance-based comparisons are strongly linked to body dissatisfaction and depressive symptoms among students [21,22].
Intimate partner violence (IPV), encompassing physical, emotional, and sexual abuse within a romantic relationship, is another critical factor affecting students’ mental health and academic outcomes [23,24]. IPV is associated with a heightened risk of depression, post-traumatic stress disorder, and disruptions in daily functioning. In university populations, the prevalence of IPV ranges from 20% to 30%, with profound psychological and academic consequences, particularly among female students [23–27].
Sexual coercion, a non-consensual sexual activity that occurs due to psychological pressure, threats, manipulatons, or misuse of authority, rather than outright force, is a less explored variable but may play a significant role in influencing mental health [28,29]. Inconsistent or negative experiences in such sexual relationships can exacerbate feelings of isolation, distress, and depression, further impacting academic outcomes [30–32]. Exploring the interplay between sexual coercion and other psychosocial factors is essential, particularly in culturally diverse settings like Nigeria, where societal norms and gender dynamics shape relationship experiences.
While these factors affect a lot of students, their impact may vary significantly between genders. Sex differences are a crucial consideration in understanding the relationships between these psychosocial factors, depression, and academic performance [33,34]. Evidence suggests that female students may be more vulnerable to body image concerns and IPV, leading to higher rates of depression and academic difficulties compared to their male counterparts [35,36].
Understanding these gender-specific dynamics is essential for developing targeted interventions.
Despite the growing recognition of these issues, research on the combined impact of body image concerns, obesity, IPV, and sexual coercion on depression in Nigerian university students remains limited. Additionally, the moderating role of sex in these relationships is underexplored. Addressing these gaps is critical for informing gender-sensitive policies and interventions aimed at improving mental health outcomes among university students.
This study aims to investigate the associations between body image concerns, obesity, IPV, and sexual coercion with self-reported depression, with a particular focus on the moderating role of sex. The findings are expected to offer valuable insights into the psychosocial determinants of mental health, contributing to the development of effective strategies for promoting student wellbeing in Nigerian universities.
Methodology
Study design
This cross-sectional study examined the associations between body image concerns, obesity, intimate partner violence (IPV), sexual coercion, and depression among university students in Nigeria. The moderating role of sex in these relationships was also investigated.
Study setting and population
The study was conducted over a one-month period from September 20, 2024, to October 21, 2024, at Afe Babalola University, a private institution located in Ado-Ekiti, Southwestern Nigeria, within an urban setting [37]. The university draws students from diverse socioeconomic and cultural backgrounds across the country.
A total of 550 questionnaires were distributed, and 501 were completed and returned, yielding a response rate of 91.1%. Eligible participants were undergraduate students aged 18 years or older enrolled in various academic programs. Recruitment was facilitated through announcements in lecture halls, campus notice boards, and student email lists, with faculty representatives ensuring broad dissemination.
To maintain confidentiality and anonymity, participants completed structured, self-administered questionnaires in private settings. Completed forms were deposited anonymously into sealed drop boxes at designated secure locations within faculty offices and the student affairs building. Research assistants provided guidance but were not present during questionnaire completion to minimize response bias.
Sample size and sampling technique
Based on power calculations, a sample size of 500 students was determined to detect moderate effect sizes for the primary outcomes. Participants were selected using stratified random sampling, with strata defined by academic year and faculty. This approach ensured a proportional representation of students from different academic levels and disciplines.
The sample size for this study was calculated to determine the minimum number of participants needed to detect statistically significant associations between selected factors and depression among university students in Nigeria. Based on prior research, the prevalence of depression among higher education students in Nigeria was estimated at approximately 26% [38]. Using a confidence level of 95% (Z = 1.96) and a margin of error of 5% (e = 0.05), the initial sample size was computed using the formula:
This calculation yielded approximately 288 participants. To account for potential non-response, the sample size was adjusted by adding 10%, resulting in a final required sample size of 317 participants. However, at the conclusion of the study, data were collected from 501 students, exceeding the calculated sample size. All respondents were included in the final analysis. Participants were selected using stratified random sampling, with strata defined by academic year and faculty. This ensured proportional representation across academic disciplines and levels. Detailed distributions are provided in Table 1 and S1 and S2 Tables.
Data collection
Data was collected using a structured questionnaire incorporating validated instruments:
Depression.
Assessed using the Patient Health Questionnaire-9 (PHQ-9) [39], consisting of 9 items scored on a 4-point Likert scale (0 = “Not at all” to 3 = “Nearly every day”). Total scores range from 0 to 27, with higher scores indicating greater depressive severity. Example item: “Over the last two weeks, how often have you felt little interest or pleasure in doing things?” (Cronbach’s alpha = 0.85).
Body image concerns.
Measured using the Body Image Satisfaction Scale (BISS) [40,41], comprising 6 items rated on a 9-point scale. Higher scores indicate greater body satisfaction. Example item: “How satisfied are you with your appearance today?” (Cronbach’s alpha = 0.77).
Obesity.
Defined using BMI categories calculated from self-reported height and weight [42,43], classified as underweight (<18.5), normal (18.5–24.9), overweight (25–29.9), and obese ≥ [30].
Intimate Partner Violence (IPV).
Evaluated via selected items from the Conflict Tactics Scale (CTS2) [44], focusing on physical, emotional, and sexual abuse experiences. Responses were binary (Yes/No). (Cronbach’s alpha = 0.79).
Sexual coercion.
Assessed using adapted items from validated relationship cohesion scales [45], focusing on mutual consent and comfort in sexual relationships. Higher scores reflected better sexual cohesion (Cronbach’s alpha = 0.81).
Confounding variables
Potential confounders included demographic factors (age categorized in years, sex, academic year, parental education level, household income brackets), lifestyle behaviors (current smoking status, alcohol consumption, physical activity frequency), and health factors (self-reported comorbidities). These variables were incorporated into the Inverse Probability Weighting (IPW) models to adjust for baseline differences and reduce confounding bias in estimating the association between psychosocial factors and depression.
Data analysis
Descriptive statistics summarized participant characteristics. Bivariate analyses assessed relationships between key variables and depression. IPW was applied to balance covariates, followed by multivariable regression analyses to estimate average treatment effects. Interaction terms were included to explore sex-based moderation effects.
Ethical considerations
Ethical approval was obtained from Afe Babalola University’s Institutional Review Board (AMSH/REC/24/089). Written informed consent was obtained from all participants. Confidentiality and anonymity were strictly maintained, with no personal identifiers collected.
Inclusivity in global research
Additional information regarding the ethical, cultural, and scientific considerations specific to inclusivity in global research is included in the Supporting Information (S3 Checklist).
Result
Baseline characteristics
Table 1 highlights the baseline characteristics of the study respondents, stratified by sex. The study population comprised 501 university students, with 178 males (35.5%) and 323 females (64.5%). Most participants were between 18–20 years of age (83.4%), with no significant difference between males (85.4%) and females (82.4%). Regarding maternal educational attainment, 33.3% of the participant’s mothers had advanced education, while 42.9% had tertiary education, and 23.8% reported high school or lower education. Household income was predominantly greater than 150,000 NGN for 78.8% of the participants, and no significant differences were observed between males and females (p = 0.445). Most participants came from monogamous family structures (83.2%), with fewer from polygamous (9.6%) or single-parent households (7.2%), with no significant differences between genders (p = 0.788).
In terms of explanatory variables, 3.4% of students reported experiencing intimate partner violence (IPV), with no difference between males and females (p = 0.984). However, coerced sex was significantly more prevalent among females (13.6%) than males (5.6%) (p = 0.006). BMI categories revealed that 48.9% of participants were of normal weight, 22.0% overweight, 18.6% obese, and 10.6% underweight. Obesity was more common among females (20.7%) than males (14.6%) (p = 0.042). For lifestyle behaviors, alcohol consumption was reported by 20.8% of participants, while 4.4% reported smoking, with no significant differences by gender for either behavior.
33.5% of participants had experienced some form of depression, with a higher prevalence among females (35.3%) compared to males (30.3%), though this difference was not statistically significant (p = 0.261). Academic performance, measured by CGPA, was higher among females (4.2 ± 0.6) compared to males (4.0 ± 0.7) (p = 0.001) (Table 1).
The stratified random sampling ensured proportional representation across academic years and faculties. Detailed distributions of participants by academic year and reclassified faculty categories are provided in S1 and S2 Tables.
Predicting depression among male students by Body Mass Index
Table 2 presents the Average Treatment Effect of BMI categories on the incidence of depression among male respondents. The relationship between the BMI categories and depression among male students was analyzed using an inverse probability weighting approach. Students with a normal BMI had a depression incidence rate of 17.0% (Coef. = 0.1701, 95% CI: 0.0875–0.2527, p < 0.001).
Overweight students experienced a 19.6% higher incidence of depression compared to those with a normal BMI (Coef. = 0.1959, 95% CI: 0.0004–0.3913, p = 0.05). Similarly, obese students showed a significant positive association with depression, further increasing the odds of depressive symptoms by 25.9% (Coef. = 0.2594, 95% CI: 0.0187–0.5001, p = 0.035). However, underweight students showed no significant association with depression (Coef. = −0.0115, 95% CI: −0.1615 to 0.1385, p = 0.881) (Table 2).
Predicting depression among female students by BMI
Table 3 presents the Average Treatment Effect of BMI categories on the incidence of depression among female respondents. Female students with normal BMI reported the highest incidence of depression among students with a normal BMI (Coef. = 0.3999, 95% CI: 0.3219–0.4779, p < 0.001).
Overweight students demonstrated a negative association with depression, suggesting a lower likelihood of depressive symptoms compared to those with a normal BMI (Coef. = −0.1406, 95% CI: −0.2611 to −0.0201, p = 0.022). However, underweight students showed no significant difference from the baseline, which were students with a normal BMI (Coef. = −0.1213, 95% CI: −0.2851 to 0.0424, p = 0.146). Similarly, obesity was not significantly associated with depression in this cohort (Coef. = 0.0170, 95% CI: −0.1167 to 0.1508, p = 0.803) (Table 3).
Depression among male students across body image concerns
Table 4 illustrates the impact of body image concerns on the incidence of depression among male student respondents. Students with moderate body image concerns had a significantly higher likelihood of reporting depression compared to those with low concerns (Coef. = 0.4207, 95% CI: 0.1966–0.6447, p < 0.001). Though students with high body image concerns have a 26.3% higher incidence of depression than the baseline, this was not statistically significant depression (Coef. = 0.2633, 95% CI: −0.1640–0.6906, p = 0.227). Students with low body image concerns have a 26.2% adjusted incidence of depression (Coef. = 0.2621, 95% CI: 0.1901–0.3342, p < 0.001) (Table 4).
Depression among female students across body image concerns
Table 5 illustrates the impact of body image concerns on the incidence of depression among female student respondents. Female students with moderate body image concerns had a 23.7% incidence of depression compared to those with low concerns (Coef. = 0.2370, 95% CI: 0.0983–0.3757, p = 0.001). Similarly, high body image concerns were significantly associated with depression, with an even greater magnitude of effect (Coef. = 0.3532, 95% CI: 0.1296–0.5769, p = 0.002).
Students with low body image concerns also (the reference group) reported an adjusted incidence of depression of 26.4% (Coef. = 0.2642, 95% CI: 0.2045–0.3239, p < 0.001) (Table 5).
IPV and depression among male students
Table 6 presents the effect of IPV on the incidence of depression among male student respondents. Male students who did not experience IPV had an adjusted incidence of 30.1% (Coef. = 0.3009, 95% CI: 0.2324–0.3695, p < 0.001).
Interestingly, male students who experienced IPV had a 21.1% higher adjusted incidence of depression, though the association was not statistically significant (Coef. = 0.2107, 95% CI: -
0.4130 to 0.8344, p = 0.508), indicating that IPV may not be a critical determinant of depression in this cohort (Table 6).
IPV and depression among female students
Table 7 presents the effect of IPV on the incidence of depression among female student respondents. Female students who did not experience IPV had a high incidence of depression (Coef. = 0.3477, 95% CI: 0.2951–0.4003, p < 0.001).
In contrast, for those who experienced IPV, the association with depression was not significantly different from those who did not experience IPV (Coef. = 0.3011, 95% CI: −0.1769 to 0.7792, p = 0.217) (Table 7).
Depression among male students by sexual coercion (Coerced sex)
Table 8 highlights the impact of sexual coercion on the incidence of depression among male student respondents. Male students who reported experiencing coerced sex had a significantly higher likelihood of reporting depression (Coef. = 0.4304, 95% CI: 0.2346–0.6263, p < 0.001).
However, those who did not experience coerced sex had an adjusted incidence rate of 29.1% (Coef. = 0.2912, 95% CI: 0.2222–0.3601, p < 0.001) (Table 8).
Depression among female students by sexual coercion (Coerced sex)
Table 9 shows the impact of sexual coercion on the incidence of depression among female student respondents. Female students who reported experiencing coerced sex had a significantly higher incidence of depression, 39.5% (Coef. = 0.3952, 95% CI: 0.2089–0.5814, p < 0.001).
Female students without such experience reported an adjusted incidence of depression at 30.8% (Coef. = 0.3081, 95% CI: 0.2543–0.3619, p < 0.001). The magnitude of this association was smaller compared to those who reported coerced sex.
Discussion
This study highlights the factors associated with self-reported depression among university students in Nigeria, with rates notably higher among female students than their male counterparts. This finding aligns with global trends, which often show that women are more likely to experience depression due to biological, social, and cultural factors [46–48]. However, the high prevalence observed in this population underscores the urgent need for targeted mental health interventions within university settings to address gender-specific vulnerabilities.
One of the most striking findings of this study is the presence of IPV and sexual coercion issues among male students, challenging traditional beliefs that such exposures predominantly affect women. While IPV and sexual coercion were reported more frequently among female students, their occurrence among male students suggests a broader societal issue that warrants further investigation highlighting the need for inclusive support systems and education programs [49] that address IPV and sexual coercion across all genders, promoting healthier relationships and reducing the associated mental health burden [50].
Interestingly, no significant association was found between obesity and self-reported depression, particularly among female university students, although the results suggested a possible trend. The lack of statistical significance may be attributed to insufficient sample size or the complex interplay of factors that mediate the relationship between obesity and mental health. These findings align with some previous studies that suggest the relationship between obesity and depression may be influenced by confounding variables, such as stigma, self-esteem, and cultural perceptions of body image [51–54]. Further research is needed to explore these dynamics in greater detail.
Body image concerns emerged as a key predictor of self-reported depression, with a high proportion of students expressing moderate to high concerns about their body image. These concerns were more prevalent among female students, reflecting societal pressures and gender norms disproportionately affecting women [35,54]. Similarly, experiencing sexual coercion was significantly associated with depression, with individuals exposed to these factors experiencing higher odds of depressive symptoms. Although IPV did not demonstrate a significant association, the effect sizes were substantial enough to justify further investigation. These findings underscore the critical role of psychosocial factors in shaping mental health outcomes [24,55] and highlight the importance of addressing these issues as part of university mental health initiatives.
The findings also emphasize the importance of gender-sensitive interventions. Female students were disproportionately affected by IPV, sexual coercion, and body image concerns, which contributed significantly to their higher rates of depression. Male students, while reporting lower rates of these exposures, also demonstrated significant associations with depression, particularly in the context of sexual coercion. This highlights the need for tailored mental health programs that account for the unique experiences of both genders.
Strengths and limitations
This study has several notable strengths. First, it provides valuable insights into the psychosocial factors influencing depression and academic performance among university students in Nigeria, a context where limited research exists on this topic. By incorporating variables such as body image concerns, intimate partner violence (IPV), sexual coercion, and obesity, the study adopts a comprehensive approach to understanding the complex interplay of factors affecting mental health and academic outcomes.
Second, the use of a cross-sectional design with a relatively large and diverse sample (N = 501) enhances the representativeness of the findings for the studied university population. The stratified random sampling method ensured representation across different academic disciplines, socioeconomic backgrounds, and genders, thereby minimizing selection bias.
Third, the study’s robust analytical approach using inverse probability weighting (IPW) strengthens the validity of the findings. By adjusting for potential confounding variables, such as age, parental education, household income, and lifestyle behaviors, the study isolates the independent effects of explanatory variables on depression and academic performance. This methodology is particularly effective in reducing bias and ensuring reliable estimates of associations.
Lastly, the study’s focus on gender-specific analyses provides nuanced insights into how psychosocial factors impact male and female students differently. This approach underscores the importance of gender-sensitive mental health interventions and contributes to a growing body of literature advocating for tailored mental health strategies.
Despite its strengths, this study has several limitations. First, the cross-sectional design restricts the ability to draw causal inferences and may not fully capture potential bidirectional relationships between variables. While the findings offer valuable insights into associations among psychosocial factors and depression, longitudinal studies are needed to explore temporal dynamics and causal pathways.
Second, reliance on self-reported measures for key variables—such as depression, body image concerns, IPV, and sexual coercion—introduces the potential for social desirability and recall biases. These biases may have led to underreporting of sensitive experiences, particularly regarding IPV and sexual coercion, potentially underestimating their true prevalence.
Third, the study was conducted within a single private university setting, which may limit the generalizability of the findings to other institutions, particularly public universities in Nigeria. Private and public universities often differ in terms of socioeconomic composition, cultural environments, and access to mental health resources. As such, caution should be exercised when extrapolating these results to the broader Nigerian student population. Nonetheless, this study provides critical groundwork in highlighting psychosocial determinants of mental health in a low- and middle-income country (LMIC) context and serves as a foundation for future multi-institutional research that can better address these generalizability concerns.
Fourth, the absence of detailed clinical data—such as prior mental health diagnoses, healthcare access, and comorbidities—limits the ability to fully adjust for important health-related confounders. Additionally, unmeasured factors like social support networks, coping mechanisms, or resilience may influence mental health outcomes but were not captured in this study.
Finally, while the relationship between obesity and depression was explored, the lack of significant associations could reflect insufficient statistical power or the multifaceted nature of this relationship. Future studies should consider larger sample sizes and incorporate more nuanced measures of obesity, such as waist-to-hip ratio or body composition analyses, to better elucidate these links.
Conclusion
The present study provides valuable insights into the complex interplay of psychosocial factors and their impact on depression among university students in Nigeria. The findings highlight the need for comprehensive, gender-sensitive mental health strategies that address body image concerns, IPV, and sexual coercion. Universities should prioritize creating safe, supportive environments and provide accessible mental health services to mitigate these risk factors and promote the well-being and academic success of their students. Future research should explore longitudinal trends and the effectiveness of targeted interventions in reducing depression and its associated burdens.
Supporting information
S1 Table. Distribution of study participants by academic year.
https://doi.org/10.1371/journal.pone.0319308.s001
(DOCX)
S2 Table. Distribution of study participant by faculty.
https://doi.org/10.1371/journal.pone.0319308.s002
(DOCX)
S3 Checklist. Inclusivity in global research.
https://doi.org/10.1371/journal.pone.0319308.s003
(DOCX)
Acknowledgments
The authors thank all participants and personnel who supported this project. Special thanks to the Clive O. Callender Outcomes Research Center at the Howard University College of Medicine for their invaluable support.
References
- 1. Ma J, Zhou H, Fu Q, Lu G. Facilitators and barriers in the development and implementation of depression prevention and treatment policies in China: a qualitative study. BMC Public Health. 2023;23(1):276. pmid:36750813
- 2. McLaughlin KA. The public health impact of major depression: a call for interdisciplinary prevention efforts. Prev Sci. 2011;12(4):361–71. pmid:21732121
- 3. Gao L, Xie Y, Jia C, Wang W. Prevalence of depression among Chinese university students: a systematic review and meta-analysis. Sci Rep. 2020;10(1):15897. pmid:32985593
- 4. Luo M-M, Hao M, Li X-H, Liao J, Wu C-M, Wang Q. Prevalence of depressive tendencies among college students and the influence of attributional styles on depressive tendencies in the post-pandemic era. Front Public Health. 2024;12:1326582. pmid:38333740
- 5. Sarokhani D, Delpisheh A, Veisani Y, Sarokhani MT, Manesh RE, Sayehmiri K. Prevalence of depression among university students: a systematic review and meta-analysis study. Depress Res Treat. 2013;2013:373857. pmid:24187615
- 6. Pedrelli P, Nyer M, Yeung A, Zulauf C, Wilens T. College students: mental health problems and treatment considerations. Acad Psych. 2015;39(5):503–11. pmid:25142250
- 7. Barbayannis G, Bandari M, Zheng X, Baquerizo H, Pecor KW, Ming X. Academic stress and mental well-being in college students: correlations, affected groups, and COVID-19. Front Psychol. 2022;13.
- 8. Barbayannis G, Bandari M, Zheng X, Baquerizo H, Pecor KW, Ming X. Academic stress and mental well-being in college students: correlations, affected groups, and COVID-19. Front Psychol. 2022;13:886344. pmid:35677139
- 9. Akhtar P, Ma L, Waqas A, Naveed S, Li Y, Rahman A, et al. Prevalence of depression among university students in low and middle income countries (LMICs): a systematic review and meta-analysis. J Affect Disord. 2020;274:911–9. pmid:32664032
- 10. Ahangba AM, Joshua O, Misbah NZ, Uzochukwu CF, Dhikirullah Y, Aboki EA. Prevalence of depression among clinical medical students at a tertiary health facility in Jos, North Central Nigeria. Nigerian J Med. 2023;32(6):580–5.
- 11. Isara AR, Nwokoye OI, Odaman AO. Prevalence and risk factors of depression among undergraduate medical students in a Nigerian university. Ghana Med J. 2022;56(4):303–10. pmid:37575622
- 12. Luo M-M, Hao M, Li X-H, Liao J, Wu C-M, Wang Q. Prevalence of depressive tendencies among college students and the influence of attributional styles on depressive tendencies in the post-pandemic era. Front Public Health. 2024;12:1326582. pmid:38333740
- 13. Carlos KM, Ahmadi H, Uban KA, Riis JL. Behavioral and psychosocial factors related to mental distress among medical students. Front Public Health. 2023;11:1225254. pmid:37575125
- 14. Gandarillas MÁ, Elvira-Zorzo MN, Pica-Miranda GA, Correa-Concha B. The impact of family factors and digital technologies on mental health in university students. Front Psychol. 2024;15.
- 15. O Y, Xue X, Jiong L, Z Y. Research on the influence of body image on college students’ weight-loss intention: chained intermediary analysis of self-efficacy and self-esteem. Front Psychol. 2024;15.
- 16.
Akinyemi OAO, Omokhodion O, Bello NO, Tanna R, Akingbule A, Utomi A, et al. Impact of obesity on college student academic performance: a comparison between the United States and Nigeria. Edition 63. HPHR; 2022.
- 17. Sarigiani PA, Olsavsky AL, Camarena PM, Sullivan SM. Obesity and depressive symptoms in college women: analysis of body image experiences and comparison to non-obese women. Int J Adolesc Youth. 2020;25(1):765–79.
- 18.
Fulton M, Dadana S, Srinivasan VN. Obesity, stigma, and discrimination. Treasure Island (FL): StatPearls Publishing; 2025.
- 19.
Segal Y, Gunturu S. Psychological issues associated with obesity. Treasure Island (FL): StatPearls Publishing; 2025.
- 20. Timkova V, Mikula P, Nagyova I. Psychosocial distress in people with overweight and obesity: the role of weight stigma and social support. Front Psychol. 2025;15:1474844. pmid:39845561
- 21. Sharpe H, Patalay P, Choo T-H, Wall M, Mason SM, Goldschmidt AB, et al. Bidirectional associations between body dissatisfaction and depressive symptoms from adolescence through early adulthood. Dev Psychopathol. 2018;30(4):1447–58. pmid:29144209
- 22.
Hill PK. Instagram ideals: College women’s bod gram ideals: College women’s body image and social comparison. University of Tennessee, Knoxville; 2022. mailto:phill16@vols.utk.edu
- 23. Klencakova LE, Pentaraki M, McManus C. The impact of intimate partner violence on young women’s educational well-being: a systematic review of literature. Trauma Violence Abuse. 2023;24(2):1172–87. pmid:34894875
- 24. Wood L, Voth Schrag R, Busch-Armendariz N. Mental health and academic impacts of intimate partner violence among IHE-attending women. J Am Coll Health. 2020;68(3):286–93. pmid:30557086
- 25. Dillon G, Hussain R, Loxton D, Rahman S. Mental and physical health and intimate partner violence against women: a review of the literature. Int J Family Med. 2013;2013:313909. pmid:23431441
- 26. Wong JS, Bouchard J, Lee C. The effectiveness of college dating violence prevention programs: a meta-analysis. Trauma Violence Abuse. 2023;24(2):684–701. pmid:34342255
- 27. Tsui EK, Santamaria EK. Intimate partner violence risk among undergraduate women from an urban commuter college: the role of navigating off- and on-campus social environments. J Urban Health. 2015;92(3):513–26.
- 28. de Visser RO, Rissel CE, Richters J, Smith AM. The impact of sexual coercion on psychological, physical, and sexual well-being in a representative sample of Australian women. Archiv Sex Behav. 2007;36(5):676–86.
- 29. Agardh A, Tumwine G, Asamoah BO, Cantor-Graae E. The invisible suffering: sexual coercion, interpersonal violence, and mental health--a cross-sectional study among university students in south-western Uganda. PLoS One. 2012;7(12):e51424. pmid:23240021
- 30. Dubé S, Lavoie F, Blais M, Hébert M. Consequences of casual sex relationships and experiences on adolescents’ psychological well-being: a prospective study. J Sex Res. 2017;54(8):1006–17. pmid:28010123
- 31. Molstad TD, Weinhardt JM, Jones R. Sexual assault as a contributor to academic outcomes in university: a systematic review. Trauma Violence Abuse. 2023;24(1):218–30.
- 32. Molstad TD, Weinhardt JM, Jones R. Sexual assault as a contributor to academic outcomes in university: a systematic review. Trauma Violence Abuse. 2023;24(1):218–30. pmid:34689635
- 33. Gao W, Ping S, Liu X. Gender differences in depression, anxiety, and stress among college students: a longitudinal study from China. J Affect Disord. 2020;263:292–300. pmid:31818792
- 34. Seehuus M, Moeller RW, Peisch V. Gender effects on mental health symptoms and treatment in college students. J Am Coll Health. 2021;69(1):95–102. pmid:31513464
- 35. El Ansari W, Dibba E, Stock C. Body image concerns: levels, correlates and gender differences among students in the United Kingdom. Cent Eur J Public Health. 2014;22(2):106–17. pmid:25230539
- 36. Spencer CN, Khalil M, Herbert M, Aravkin AY, Arrieta A, Baeza MJ, et al. Health effects associated with exposure to intimate partner violence against women and childhood sexual abuse: a burden of proof study. Nat Med. 2023;29(12):3243–58. pmid:38081957
- 37. Orok E, Nwifama S, Oni O, Ojo T, Oluwadare T, Bamitale T, et al. Students’ perception of healthcare services and factors affecting their utilization at a Nigerian University: a cross-sectional study. Sci Rep. 2024;14(1):23893. pmid:39396088
- 38.
Cui SBA, Kim E, Egonu R. A systematic review and meta-analysis of depression prevalence amongst Nigerian students pursuing higher education. 2022;12.
- 39. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16(9):606–13.
- 40. Bardi L, Arnaud C, Bagès C, Langlois F, Rousseau A. Translation and validation of a state-measure of body image satisfaction: the body image state scale. Front Psychol. 2021;12.
- 41. Mebarak Chams M, Tinoco L, Mejia-Rodriguez D, Martinez-Banfi ML, Preuss H, Hammerle F, et al. The Spanish body image state scale: factor structure, reliability and validity in a Colombian population. Front Psychol. 2019;10:2553. pmid:31824372
- 42. Davies A, Wellard-Cole L, Rangan A, Allman-Farinelli M. Validity of self-reported weight and height for BMI classification: a cross-sectional study among young adults. Nutrition. 2020;71:110622. pmid:31837644
- 43. Craig BM, Adams AK. Accuracy of body mass index categories based on self-reported height and weight among women in the United States. Matern Child Health J. 2009;13(4):489–96. pmid:18607705
- 44. Douglas EM. A short form of the revised conflict tactics scales, and typologies for severity and mutuality. Violence Victims. 2004;19(5):507–20.
- 45. Tsoutsi V, Dikeos D. Family functioning and cohesion scale: validation of a short instrument for the assessment of intrafamily relations. Behav Sci (Basel). 2024;14(10).
- 46. Di Benedetto MG, Landi P, Mencacci C, Cattaneo A. Depression in women: potential biological and sociocultural factors driving the sex effect. Neuropsychobiol. 2024;83(1):2–16. pmid:38272005
- 47. Albert PR. Why is depression more prevalent in women?. J Psychiatry Neurosci. 2015;40(4):219–21.
- 48. Salk RH, Hyde JS, Abramson LY. Gender differences in depression in representative national samples: meta-analyses of diagnoses and symptoms. Psychol Bull. 2017;143(8):783–822. pmid:28447828
- 49. Goldfarb ES, Lieberman LD. Three decades of research: the case for comprehensive sex education. J Adolesc Health. 2021;68(1):13–27. pmid:33059958
- 50. White SJ, Sin J, Sweeney A, Salisbury T, Wahlich C, Montesinos Guevara CM, et al. Global prevalence and mental health outcomes of intimate partner violence among women: a systematic review and meta-analysis. Trauma Violence Abuse. 2024;25(1):494–511. pmid:36825800
- 51. Clark O, Lee MM, Jingree ML, O’Dwyer E, Yue Y, Marrero A. Weight stigma and social media: evidence and public health solutions. Front Nutr. 2021;8:739056.
- 52. Fowler-Brown AG, Ngo LH, Wee CC. The relationship between symptoms of depression and body weight in younger adults. Obesity (Silver Spring). 2012;20(9):1922–8. pmid:22016102
- 53. Emmer C, Bosnjak M, Mata J. The association between weight stigma and mental health: a meta-analysis. Obes Rev. 2020;21(1):e12935. pmid:31507062
- 54. Shi P, Yang A, Zhao Q, Chen Z, Ren X, Dai Q. A hypothesis of gender differences in self-reporting symptom of depression: implications to solve under-diagnosis and under-treatment of depression in males. Front Psych. 2021;12:589687. pmid:34759845
- 55. Devries KM, Mak JY, Bacchus LJ, Child JC, Falder G, Petzold M, et al. Intimate partner violence and incident depressive symptoms and suicide attempts: a systematic review of longitudinal studies. PLoS Med. 2013;10(5):e1001439. pmid:23671407