Healthier dietary habits are associated with lower depression and anxiety among medical students at a private university in Lima, Peru: A cross-sectional study

Adriana Daniel Armas; Diego S Polanco Taipe; David R Soriano-Moreno

doi:10.1371/journal.pone.0346062

. 2026 Jun 18;21(6):e0346062. doi: 10.1371/journal.pone.0346062

Healthier dietary habits are associated with lower depression and anxiety among medical students at a private university in Lima, Peru: A cross-sectional study

Adriana Daniel Armas ¹, Diego S Polanco Taipe ¹, David R Soriano-Moreno ^1,^*

Editor: Yordanis Enríquez Canto²

PMCID: PMC13278413 PMID: 42313744

Abstract

Introduction

Anxiety and depression are common conditions among medical students. In recent years, numerous factors associated with these disorders have been investigated; however, evidence regarding the role of dietary habits remains limited.

Objective

To evaluate the association between dietary habits and the presence of anxiety and depressive symptoms among medical students at a private university in Lima, Peru.

Methods

An analytical cross-sectional study was conducted in 2025 among medical students aged 18 years and older. Dietary habits were assessed using the Healthy Eating Index, while anxiety and depression were measured using the GAD-7 and PHQ-9 scales, respectively. Poisson regression with robust variance was used to calculate prevalence ratios (PR).

Results

A total of 264 students were included. Only a minority had healthy dietary habits (1.1%), and the prevalences of anxiety (34.9%) and depression (45.1%) were high. For each additional point in the Healthy Eating Index, the prevalence of anxiety decreased by 3% (aPR: 0.97; 95% CI: 0.95 to 0.98), while the prevalence of depression decreased by 2% (aPR: 0.98; 95% CI: 0.96 to 0.99).

Conclusion

Dietary habits were inversely associated with the prevalence of anxiety and depression among medical students. These findings highlight the importance of promoting healthy dietary patterns as part of comprehensive strategies for the prevention and promotion of mental health in this population.

Introduction

Mental health disorders, particularly anxiety and depression, represent a major public health problem worldwide, affecting more than 300 million people and contributing substantially to the global burden of years lived with disability [1,2]. These conditions more frequently affect adolescents and young adults, a life stage characterized by significant academic, social, and personal transitions [3]. In the Peruvian context, anxiety and depression also constitute relevant mental health concerns, university student, and especially medical students, being a particularly vulnerable population, in whom the prevalence of depression ranges from 18% to 50% and that of anxiety from 17% to 54% [4]. This higher prevalence may be explained by academic pressure, lifestyle changes, the transition to adulthood, and exposure to persistent stressors [5].

Several studies have identified multiple factors associated with the deterioration of mental health among university students, including academic stress or overload, sleep disturbances, and financial difficulties [6–9]. However, one of the less explored modifiable factors in this population is dietary habits, which are particularly relevant in the Peruvian university context, where the habitual diet has been characterized by a high intake of refined carbohydrates, fats, and ultra-processed foods, potentially negatively impacting both physical and mental health [10–12]. Emerging evidence suggests that specific dietary patterns and nutrients may play an important role in mood regulation and in the pathophysiology of mental disorders. For example, the intake of micronutrients such as omega-3 fatty acids and zinc has been shown to have neuroprotective effects, whereas high consumption of sugars and ultra-processed foods has been associated with inflammatory processes and alterations in neurotransmission systems linked to anxiety and depression [13–17].

Observational studies, as well as systematic reviews and meta-analyses, have consistently reported that unhealthy dietary habits are associated with a higher prevalence of depressive and anxiety symptoms, whereas healthy dietary patterns, characterized by greater consumption of fruits and vegetables, are linked to better mental health indicators [18–22]. However, despite the growing body of evidence, important knowledge gaps remain, particularly among university populations in middle-income countries such as Peru. Most available studies originate from European or North American contexts and do not consistently account for sociocultural specificities, local dietary patterns, or the academic environments specific to medical training in Latin America [20]. Furthermore, a considerable proportion of the evidence is derived from studies that did not adequately adjust for potential confounding variables, which may overestimate or underestimate the true magnitude of the association. This gap hinders the development of context-specific, evidence-based preventive interventions and underscores the need for analytical studies that address these methodological limitations in this vulnerable population.

Hence, the aim of the present study was to evaluate the association between dietary habits and the prevalence of anxiety and depressive symptoms among medical students at a private university in Lima, Peru.

Methods

Design, population and sample

An analytical cross-sectional study was conducted in 2025 among medical students at a private university in Lima, Peru (Universidad Peruana Unión). Students aged 18 years and older who were enrolled from the first to the sixth academic year, carried a full academic load, and voluntarily agreed to participate were included. Students in their seventh year (internship) and those with incomplete survey data were excluded.

A non-probabilistic convenience sampling approach was used. Sample size was calculated using Epidat version 4.2, considering an approximate population of 657 medical students from the first to the sixth year, an expected outcome prevalence of 34%, a 95% confidence level, and a 5% precision, yielding a required sample of 227 students. Assuming a 20% non-response rate, the survey was distributed to 272 students.

Context

The study was conducted in Universidad Peruana Unión, an institution sponsored by the Seventh-day Adventist Church. The Seventh-day Adventist Church promotes a healthy lifestyle that includes predominantly plant-based and balanced dietary habits, emphasizing the consumption of fruits, vegetables, whole grains, legumes, nuts, and other plant-based foods as part of its holistic health message [23].

Variables

Depression was measured using the Patient Health Questionnaire-9 (PHQ-9), which includes nine items based on DSM-IV criteria assessing depressive symptoms over the previous two weeks. The PHQ-9 has been previously validated in medical students in Lima, Peru, demonstrating high reliability (Cronbach’s alpha = 0.903) [24]. Total scores range from 0 to 27; each item is scored from 0 to 3, where 0 corresponds to “Not at all,” 1 to “Several days,” 2 to “More than half the days,” and 3 to “Nearly every day,” with higher scores indicating greater depressive symptom severity. A score ≥10 was used to define the presence of depression, as this cutoff demonstrates adequate sensitivity (88%) and specificity (85%) [25].

Anxiety was assessed using the GAD-7 questionnaire, which consists of seven items based on DSM-5 criteria for generalized anxiety disorder symptoms reported over the past two weeks. The GAD-7 has been validated in Spanish among Colombian medical professionals and shows high reliability (Cronbach’s alpha = 0.920) [26]. The total score ranges from 0 to 21; each item was scored from 0 to 3, where 0 corresponded to “Not at all,” 1 to “Several days,” 2 to “More than half the days,” and 3 to “Nearly every day,”. Participants were considered to have anxiety if they had a score ≥10, as this cutoff has adequate sensitivity (87%) and specificity (78%) [27].

Healthy dietary habits were assessed using the Spanish-adapted Healthy Eating Index (HEI) [28]. This instrument was selected because no HEI adaptation has been validated specifically for the Peruvian population. The Spanish-adapted HEI was considered suitable for this study because it is available in Spanish, uses broad food groups that are understandable for Peruvian students, and includes dietary domains that are broadly consistent with the Peruvian Dietary Guidelines, such as fruits, vegetables, legumes, dairy products, animal-source foods, sweets, sugar-sweetened beverages, and processed meats [29]. The instrument consists of 10 items categorized into: daily recommended food groups (items 1–4: cereals and derivatives, vegetables, fruits, dairy products); weekly recommended food groups (items 5–6: meats and legumes); non-recommended foods (items 7–9: processed meats, sweets, and sugar-sweetened beverages); and dietary variety (item 10). Each component received a score from 0 to 10, where 10 indicated full adherence to the recommendations established by the Spanish Society of Community Nutrition. The total score ranged from 0 to 100. Final scores were categorized as: > 80 (“healthy”), 50–80 (“needs improvement”), and <50 (“unhealthy”). Nevertheless, these cut-off points should be interpreted cautiously, as they have not been specifically validated in Peruvian populations or among university students. The HEI has demonstrated a Cronbach’s alpha of 0.67 in U.S. populations [30] and is designed as a quantitative assessment of overall diet quality [31].

Other covariates that were collected included sex, age, marital status, nationality, academic year, current living arrangement, prior diagnosis of anxiety, prior diagnosis of depression, and current use of psychiatric medication.

Procedures

Prior to data collection, the study protocol was approved by the university’s ethics committee. Data collection was conducted from 15/07/2025to 15/12/2025, corresponding to the second academic semester at Universidad Peruana Unión. This period includes regular academic activities and the end-of-semester examination phase, during which students are often exposed to constant evaluations and sustained academic stress, both of which may influence dietary behaviors and mental health symptom burden. The survey, created using Google Forms, was distributed through academic year representatives. Additionally, in-person administration was conducted during academic hours to increase coverage and response rates. Participation was encouraged through a raffle of monetary incentives. Before completing the questionnaire, participants were informed about the study objectives and provided written informed consent. The structured questionnaire included sections on informed consent, sociodemographic data, dietary habits assessed with the HEI, and the PHQ-9 and GAD-7 scales.

Statistical analysis

Data were cleaned in Microsoft Excel and subsequently analyzed using Stata version 19.0. Categorical variables were presented as absolute and relative frequencies, whereas numerical variables were presented as mean and standard deviation or median and interquartile range, depending on distribution. For bivariate analyses according to the presence of depression or anxiety, chi-square or Fisher’s exact tests were used for categorical variables, and Student’s t-test or the Mann–Whitney U test for continuous variables, as appropriate. The association between the Healthy Eating Index score and the prevalence of depression or anxiety was evaluated using Poisson regression with robust variance, estimating crude (cPR) and adjusted prevalence ratios (aPR) with 95% confidence intervals (95% CI). Before fitting the regression models, the linearity assumption between the HEI score and each outcome was assessed using the “lincheck” command. The categorization of the HEI score as unhealthy, needs improvement, and healthy was applied only for descriptive analyses. As a sensitivity analysis, the same adjusted Poisson regression models were refitted using 99% confidence intervals (99% CI) in order to evaluate the robustness of the estimated associations under a more conservative precision threshold. Variables considered potential confounders based on theoretical and epidemiological criteria were included in the adjusted model [32–34]. Marital status was not included in the adjusted model because it had very few observations in some categories, and most participants were single. Multicollinearity among the independent variables was formally assessed using the variance inflation factor (VIF). When age was initially modelled as a continuous variable, a VIF of 25.7 was observed, indicating severe collinearity; therefore, age was recategorized into tertiles for inclusion in the adjusted analyses, after which all VIF values were below 10. Post-estimation graphs were generated to assess the relationship between the HEI score and the prevalence of depression and anxiety. A p-value <0.05 was considered statistically significant.

Ethical considerations

The study was conducted in accordance with the ethical principles for research involving human subjects established in the Declaration of Helsinki. The protocol was reviewed and approved by the Research Ethics Committee of the Faculty of Health Sciences at Universidad Peruana Unión (approval code: 2024-CEB-FCS - UPeU-«N°178»), and institutional authorization was obtained. Participation was voluntary, and written informed consent was obtained from all participants. Survey responses and data were collected anonymously and maintained confidentially.

Results

A total of 264 medical students were surveyed, with no exclusions due to missing data. The median age was 21 years, with the majority being female (62.5%), single (96.6%), of Peruvian nationality (93.9%), and in the first year of study (23.5%). Regarding prior history, 6.8% reported a previous diagnosis of anxiety, 9.8% of depression, and 6.4% reported current use of psychiatric medication at the time of the survey. With respect to dietary habits, most students needed to make changes to their diet (77.3%), and a minority had healthy dietary habits (1.1%) (Table 1). The frequencies of food consumption by item are detailed in S1 Table.

Table 1. Characteristics of medical students at a private university in Lima, Peru (n = 264).

Characteristics	n (%)
Sex
Male	99 (37.5)
Female	165 (62.5)
Age (years), median [IQR]	21 [19 to 23]
Marital status
Single	255 (96.6)
Married	5 (1.9)
Cohabiting	4 (1.5)
Nationality
Peru	248 (93.9)
Non-Peruvian	16 (6.1)
Academic year
First year	62 (23.5)
Second year	57 (21.6)
Third year	31 (11.7)
Fourth year	32 (12.1)
Fifth year	40 (15.2)
Sixth year	42 (15.9)
Current living arrangement
Alone	128 (48.5)
Nuclear family	107 (40.5)
Extended family	8 (3.0)
Friends/partner	21 (8.0)
Previous diagnosis of anxiety
No	246 (93.2)
Yes	18 (6.8)
Previous diagnosis of depression
No	238 (90.2)
Yes	26 (9.8)
Current psychiatric medication use
No	247 (93.6)
Yes	17 (6.4)
Total dietary habits score, mean ± SD	56.9 ± 11.0
Dietary habits
Unhealthy	57 (21.6)
Needs improvement	204 (77.3)
Healthy	3 (1.1)
Anxiety (GAD-7 ≥ 10)
No	172 (65.2)
Yes	92 (34.9)
Depression (PHQ-9 ≥ 10)
No	145 (54.9)
Yes	119 (45.1)

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IQR: interquartile range; SD: standard deviation; GAD-7: Generalized Anxiety Disorder-7; PHQ-9: Patient Health Questionnaire-9.

The prevalence of anxiety was 34.9%, being more frequent among those with unhealthy dietary habits (63.2%, p < 0.001) and lower scores on the healthy eating scale (mean 52.2 ± 10.1, p < 0.001). In addition, it was significantly more prevalent among younger students (median 20: IQR [19 to 23], p = 0.042), those in basic sciences years (42.9%, p = 0.013), and those currently using psychiatric medication (76.5%, p < 0.001) (Table 2). The frequencies of anxiety symptoms are detailed in S2 Table.

Table 2. Bivariate analysis between sample characteristics and anxiety (n = 264).

Characteristics	Anxiety		p-value*
Characteristics	Absent 172 (65.2%) n (%)	Present 92 (34.9%) n (%)	p-value*
Sex			0.894
Male	65 (65.7)	34 (34.3)
Female	107 (64.9)	58 (35.1)
Age (years), median [IQR]	21 (19–24)	20 (19–23)	0.042
Academic year			0.013
Basic sciences (first to second year)	68 (57.1)	51 (42.9)
Clinical sciences (third to sixth year)	104 (71.7)	41 (28.3)
Current living arrangement			0.288
Alone	78 (60.9)	50 (39.1)
Nuclear/extended family	78 (67.8)	37 (32.2)
Friends/partner	16 (76.2)	5 (23.8)
Previous diagnosis of anxiety			0.056
No	164 (66.7)	82 (33.3)
Yes	8 (44.4)	10 (55.6)
Previous diagnosis of depression			0.401
No	157 (66.0)	81 (34.0)
Yes	15 (57.7)	11 (42.3)
Current psychiatric medication use			<0.001
No	168 (68.0)	79 (32.0)
Yes	4 (23.5)	13 (76.5)
Total dietary habits score, mean ± SD	59.4 ± 10.7	52.2 ± 10.1	<0.001
Dietary habits			<0.001
Unhealthy	21 (36.8)	36 (63.2)
Needs improvement	148 (72.6)	56 (27.5)
Healthy	3 (100)	0 (0)

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SD: standard deviation; IQR: interquartile range.

*p-value calculated using chi-square test, Fisher’s exact test, Student’s t-test, or Mann–Whitney U test.

Depression had a prevalence of 45.1%, being more frequent among students with unhealthy dietary patterns (71.9%, p < 0.001) and among those with lower scores on the healthy eating scale (mean 53.7 ± 11.1, p < 0.001). Likewise, a higher prevalence was observed among those in basic sciences years (54.6%, p = 0.005) and among students who reported current use of psychiatric medication (70.6%, p = 0.029) (Table 3). The frequencies of depressive symptoms are detailed in S3 Table.

Table 3. Bivariate analysis between sample characteristics and depression (n = 264).

Characteristics	Depression		p-value*
Characteristics	Absent 145 (54.9%) n (%)	Present 119 (45.1%) n (%)	p-value*
Sex			0.389
Male	51 (51.5)	48 (48.5)
Female	94 (57.0)	71 (43.0)
Age (years), median [IQR]	21 (19–23)	20 (19–23)	0.098
Academic year			0.005
Basic sciences (first to second year)	54 (45.4)	65 (54.6)
Clinical sciences (third to sixth year)	91 (62.8)	54 (37.2)
Current living arrangement			0.230
Alone	64 (50.0)	64 (50.0)
Nuclear/extended family	67 (58.3)	48 (41.7)
Friends/partner	14 (66.7)	7 (33.3)
Previous diagnosis of anxiety			0.157
No	138 (56.1)	108 (43.9)
Yes	7 (38.9)	11 (61.1)
Previous diagnosis of depression			0.076
No	135 (56.7)	103 (43.3)
Yes	10 (38.5)	16 (61.5)
Current psychiatric medication use			0.029
No	140 (56.7)	107 (43.3)
Yes	5 (29.4)	12 (70.6)
Total dietary habits score, mean ± SD	59.6 ± 10.2	53.7 ± 11.1	<0.001
Dietary habits			<0.001
Unhealthy	16 (28.1)	41 (71.9)
Needs improvement	127 (62.3)	77 (37.8)
Healthy	2 (66.7)	1 (33.3)

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SD: standard deviation; IQR: interquartile range.

*p-value calculated using chi-square test, Fisher’s exact test, Student’s t-test, or Mann–Whitney U test.

In the adjusted regression analysis, healthier dietary habits were associated with a lower prevalence of both anxiety and depression. Specifically, for each additional point on the HEI scale, the prevalence of anxiety decreased by 3% (aPR: 0.97; 95% CI: 0.95 to 0.98; p < 0.001), while the prevalence of depression decreased by 2% (aPR: 0.98; 95% CI: 0.96 to 0.99; p < 0.001) (Table 4). In the sensitivity analysis using 99% CIs, the estimates remained highly statistically significant (anxiety: aPR: 0.97; 99% CI: 0.95 to 0.98; p < 0.001; depression: aPR: 0.98; 99% CI: 0.96 to 0.99; p < 0.001). Likewise, the graphical representation shows an inversely proportional relationship between healthy dietary habit scores and the prevalence of anxiety and depression (Figs 1 and 2).

Table 4. Association between healthy dietary habits score and the prevalence of depression and anxiety (n = 264).

Variable	Crude PR (IC 95%)	p-value	Adjusted PR (IC 95%)*	p-value
Anxiety prevalence	0.96 (0.95 to 0.98)	<0.001	0.97 (0.95 to 0.98)	<0.001
Depression prevalence	0.97 (0.96 to 0.99)	<0.001	0.98 (0.96 to 0.99)	<0.001

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PR: prevalence ratio; 95% CI: 95% confidence interval.

*Adjusted for age, sex, academic year, current living arrangement, previous diagnosis of anxiety, previous diagnosis of depression, and current use of psychiatric medication.

Discussion

Main findings

In the present study conducted among Peruvian medical students, a high prevalence of depressive and anxiety symptoms was observed, as well as a high frequency of dietary habits that did not meet nutritional recommendations. Additionally, healthier dietary habits were inversely associated with the prevalence of anxiety and depression.

Similarly, a systematic review of university students that included more than 100 000 participants reported a prevalence of depressive symptoms of 33.6% and anxiety symptoms of 39.0%, with higher prevalences observed among medical students and in low- and middle-income countries [35]. Other studies conducted among students in Peru have reported even higher prevalences, exceeding 60% for these disorders [36,37]. These elevated figures may be explained by high academic demands, adaptation difficulties, lack of physical activity, family problems, financial constraints, social instability, and limited access to specialized mental health services [38,39]. Additionally, it is noteworthy that, unlike most previous reports, depression prevalence in our study was higher than anxiety prevalence. One possible explanation is that prolonged exposure to chronic academic stress may promote a state of emotional exhaustion more closely aligned with depressive symptomatology than with acute anxiety [40].

The low proportion of students classified as having healthy dietary habits is consistent with previous Latin American evidence. In Peru, a study from Huancavelica using the HEI found that only 0.8% of adults had a healthy diet [41]. Similarly, among Chilean university students, only 9.3% had a healthy diet, while 55.3% needed changes and 35.4% had an unhealthy diet [42]. In Mexico, only 1% of adolescent women were classified as having good diet quality using an adapted HEI [43]. This may reflect the difficulty of meeting strict healthy eating thresholds in real-world student populations, as well as irregular eating schedules, academic stress, limited time for meal planning, and high availability of ultra-processed foods and sugar-sweetened beverages.

Regarding the association between dietary habits and anxiety, a systematic review with a search date up to 2022 included 45 studies, of which 36 reported that better diet quality was associated with lower levels of depression, anxiety, and stress. However, stress and anxiety were also associated with poorer dietary habits, suggesting a bidirectional relationship [20]. Similarly, another systematic review conducted among adolescents found consistent results linking better diet quality with improved mental health outcomes [44]. In our study, this association was also supported by the strength and consistency of the findings, as each additional point in the HEI was associated with a 3% lower prevalence of anxiety, and this association remained highly statistically significant in the sensitivity analysis using 99% CI. Additionally, evidence from several systematic reviews indicates that the consumption of processed foods or fast food is associated with worse mental health outcomes [45,46]. In this context, plausible biological pathways proposed in the literature suggest that healthy dietary patterns may protect against depression and anxiety by reducing inflammation and oxidative stress, improving metabolic health, and modulating the gut–brain axis and neurotransmitter regulation [47,48]. On the other hand, high consumption of ultra-processed foods may contribute to worsening mental health by promoting inflammation, dysregulation of the hypothalamic–pituitary–adrenal axis, and alterations in the synthesis of serotonin, dopamine, and norepinephrine [14].

Implications and recommendations

Our findings may be generalizable to similar university settings where medical students facing high academic demands exhibit a high prevalence of depressive (45.1%) and anxiety (34.9%) symptoms, along with a high frequency of dietary patterns that “need improvement” (77.3%) or are considered “unhealthy” (21.6%). However, the study context should be considered when interpreting external validity. This university is sponsored by the Seventh-day Adventist Church, which promotes a predominantly plant-based diet, regular physical activity, and abstinence from alcohol and tobacco. As a result, students may be influenced by institutional, religious, and peer-related factors that shape dietary habits differently from those universities without a religious affiliation. Notably, these disorders were more frequent during the early years of study, suggesting that this subgroup may represent a particularly vulnerable population. Our findings, together with the existing literature, suggest that diet quality may be a relevant factor to consider in the development of comprehensive student well-being strategies, including periodic mental health screening, nutritional counselling and education, and improved availability of healthy food in university cafeterias. Finally, multicenter longitudinal studies are needed to confirm the directionality of this association, and ideally, clinical trials should evaluate the impact of healthy dietary programs on mental health outcomes.

Limitations and strengths

Our study used a non-probabilistic convenience sampling approach, which limits the generalizability of the findings. Furthermore, as this was a single-center study conducted at an Adventist institution, the extrapolation of the results to other settings may be limited. The cross-sectional design precludes establishing temporality and directionality between dietary habits and symptoms of anxiety and depression, hence reverse causality is plausible, as symptoms of depression and anxiety are known to alter appetite, food preferences, and eating behavior, which may result in poorer diet quality. Although validated instruments were used, the PHQ-9 and GAD-7 do not replace a clinical reference diagnosis. Regarding dietary exposure, the Spanish-adapted HEI has not been culturally validated in Peru or among Peruvian university students, which may have introduced non-differential exposure misclassification because it may not fully capture local dietary patterns, portion sizes, cooking methods, sodium intake, or degree of food processing. Also, its categorical cut-offs have not been standardized for the Peruvian population, which may explain the very low proportion of students classified as having ‘healthy’ dietary habits (1.1%), although this finding is consistent with previous Latin American evidence. In addition, residual confounding is an important limitation. Variables associated with both dietary habits and mental health in university students, such as sleep quality, physical activity, academic stress, and socioeconomic status, were not measured and therefore could not be included in the adjusted models. This is particularly relevant because data collection included the end-of-semester examination phase, when academic stress, sleep disruption, reduced physical activity, limited time for meal preparation, and worsening mental health symptoms may co-occur. Therefore, unmeasured academic and socioeconomic factors may partly explain the observed association between diet quality and anxiety or depression, potentially leading to underestimation or overestimation of the observed associations. On the other hand, we adjusted for the main potential confounding variables, thereby strengthening the internal validity of the findings. In addition, the strength of the association, even with 99% CI, and the inversely proportional relationship supports a potential association between the variables. Finally, this study addressed a population that has been underexplored in the Peruvian context, where the magnitude of the association may be particularly relevant.

Conclusion

Among Peruvian medical students, a high prevalence of depressive and anxiety symptoms was observed, along with a high frequency of dietary habits that did not meet nutritional recommendations. Healthier dietary habits were inversely associated with the prevalence of depression and anxiety. These findings suggest that promoting healthy dietary patterns should be considered as part of comprehensive strategies aimed at improving mental health among medical students.

Supporting information

S1 Table. Frequency of food consumption according to the healthy eating index.

(DOCX)

pone.0346062.s001.docx^{(16.2KB, docx)}

S2 Table. Frequency of anxiety symptoms according to GAD-7 items (n = 264).

(DOCX)

pone.0346062.s002.docx^{(15.1KB, docx)}

S3 Table. Frequency of depressive symptoms according to PHQ-9 items (n = 264).

(DOCX)

pone.0346062.s003.docx^{(15.3KB, docx)}

S1 File. Data.

(XLSX)

pone.0346062.s004.xlsx^{(39.4KB, xlsx)}

Data Availability

All relevant data underlying the findings of this study are available as Supporting information. The minimal dataset has been uploaded as a fully de-identified database.

Funding Statement

The author(s) received no specific funding for this work.

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PLoS One. doi: 10.1371/journal.pone.0346062.r001

Decision Letter 0

Yordanis Enríquez Canto

13 Apr 2026

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PONE-D-26-09038

Healthier dietary habits are associated with lower depression and anxiety among medical students at a private university in Lima, Peru: A cross-sectional study

PLOS One

Dear Dr. Soriano-Moreno,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Before addressing the specific revisions listed below, the authors should carefully review and respond to all comments provided by the reviewers. In summary, the main issues identified during peer review include:

Insufficient methodological transparency, particularly regarding the selection of variables for bivariate and multivariable analyses, and the procedures used to assess and manage multicollinearity.
Concerns about the dietary assessment instrument, as only 1.1% of participants were classified as having “healthy” dietary habits. This raises the possibility of misclassification and the need for stronger justification of the Spanish‑adapted Healthy Eating Index in this population.
Overinterpretation of findings, including language suggesting a dose–response relationship or causal mechanisms that cannot be inferred from a cross-sectional design.
Potential residual confounding, due to the absence of key variables such as sleep, physical activity, academic stress, socioeconomic status, and BMI in the adjusted models.
Overreliance on p‑values, with a need to emphasize effect sizes and confidence intervals as the primary indicators of association.
Limitations in generalizability, given the single‑center, convenience sample and the specific characteristics of the institutional context.
The revised manuscript should address these issues comprehensively and ensure that all reviewer comments are incorporated into the response letter and the revised text.

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Kind regards,

Yordanis Enríquez Canto, Ph.D.

Academic Editor

PLOS One

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Additional Editor Comments:

After careful evaluation of the manuscript and consideration of the reviewers’ comments, I believe your study addresses an important topic and provides potentially valuable evidence regarding dietary habits and mental health among medical students in Peru. However, both reviewers identified methodological and interpretive issues that must be addressed before the manuscript can be considered for publication.

On this basis, I invite you to submit a revised version of your manuscript. The revision should address all required points listed below. I distinguish clearly between required and recommended changes, and I provide editorial guidance where reviewer comments diverge.

1. Required Revisions

1.1. Clarify and justify the analytical approach

Both reviewers noted insufficient transparency regarding the selection of variables for bivariate and multivariable analyses. The manuscript should:

Provide a clear description of the variable selection strategy for regression models (e.g., theoretical criteria, epidemiological relevance, or statistical thresholds).

Explain how multicollinearity was assessed and handled. The manuscript mentions categorizing age into tertiles due to multicollinearity, but the diagnostics (e.g., VIF values or correlation matrices) are not described.

Report goodness‑of‑fit measures appropriate for Poisson regression with robust variance.

These additions are essential for evaluating the robustness of your findings.

1.2. Address concerns regarding the dietary assessment instrument

Reviewer 2 raised a substantive concern: only 1.1% of participants were classified as having “healthy” dietary habits. This extremely low proportion suggests potential misclassification or lack of calibration of the Spanish‑adapted Healthy Eating Index (HEI) for this population.

Please:

Provide a stronger justification for using the Spanish-adapted HEI in Peruvian medical students.

Discuss explicitly the possibility of exposure misclassification, including how cultural and dietary differences may affect scoring.

Consider conducting a sensitivity analysis (e.g., tertiles or quartiles of HEI score) to evaluate whether the association remains consistent under alternative categorizations.

1.3. Revise interpretation to avoid causal implications

The manuscript currently suggests a “dose–response effect” and discusses biological mechanisms in a way that implies causality. Given the cross-sectional design:

Remove or rephrase any language implying temporal ordering or causal inference.

Expand the discussion of reverse causation, acknowledging that mental health symptoms may influence dietary behavior.

Ensure that biological mechanisms are presented as hypothetical and not as explanations supported by the present study.

1.4. Discuss unmeasured confounding

The adjusted models do not include several important confounders (e.g., sleep quality, physical activity, academic stress, socioeconomic status, BMI). While these variables may not have been collected:

Provide a clear justification for their absence.

Expand the discussion of residual confounding and how it may influence the observed associations.

1.5. Emphasize effect sizes and confidence intervals

Reviewer 1 recommends reducing reliance on p‑values. Please:

Highlight prevalence ratios and confidence intervals as the primary indicators of association.

Avoid interpreting results solely based on statistical significance.

2. Recommended Revisions (Not Required but Strongly Encouraged)

Improve the clarity and flow of the writing, particularly in the Introduction and Discussion, to enhance readability.

Expand the discussion of generalizability, considering the single‑center, convenience sample and the unique characteristics of a Seventh‑day Adventist institution.

Provide additional descriptive insights into dietary patterns if the dataset allows (e.g., distribution of HEI components).

Consider adding a conceptual diagram illustrating potential pathways and confounders.

3. Editorial Notes

After reviewing the manuscript in detail, I also recommend:

Clarifying the data collection period in relation to the academic calendar, as mental health symptoms may vary across semesters.

Ensuring consistency in reporting (e.g., whether HEI is treated as continuous, categorical, or both).

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Reviewers' comments:

Reviewer's Responses to Questions

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1. Is the manuscript technically sound, and do the data support the conclusions?

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Reviewer #1: Yes

Reviewer #2: Partly

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-->2. Has the statistical analysis been performed appropriately and rigorously? -->

Reviewer #1: Yes

Reviewer #2: No

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The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.-->

Reviewer #1: Yes

Reviewer #2: Yes

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-->4. Is the manuscript presented in an intelligible fashion and written in standard English?

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Reviewer #1: Yes

Reviewer #2: Yes

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-->5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)-->

Reviewer #1: The paper and its findings are interesting, and it is commendable that all data have been made available so that interested readers can verify the results and even conduct additional analyses if desired.

The analytical methods are primarily exploratory in nature, which is appropriate given that a convenience sample was used. In addition to simple bivariate associations, Poisson regression and adjusted regression models have been applied.

However, there are several areas that would benefit from further clarification and improvement. The original dataset contains more than 30 variables, yet it is unclear how variables were selected for inclusion in the bivariate analyses and subsequent regression models. A systematic description of this variable selection process is needed.

Furthermore, the manuscript does not address how correlations among independent variables were handled in the regression analyses. If multicollinearity is present, the authors should describe the steps taken to assess and mitigate its impact (e.g., variable selection procedures, variance inflation factors, or other diagnostics).

For all regression models, appropriate goodness-of-fit measures should be reported to help readers evaluate model adequacy.

Additionally, reliance on p-values is not ideal in the context of exploratory analysis. Instead, the authors are encouraged to emphasize effect sizes along with 95% or 99% confidence intervals, which provide more informative measures of uncertainty.

Overall, this is an interesting and potentially valuable paper, but greater methodological transparency would strengthen its rigor and reproducibility.

Reviewer #2: This manuscript examines the association between dietary habits and symptoms of anxiety and depression in medical students; however, in its current form, it presents substantial methodological and interpretive limitations that weaken the validity of its conclusions. While the use of validated screening tools (PHQ-9, GAD-7) and prevalence ratios is appropriate, the reliance on a single-centre, convenience sample from a private Adventist university severely limits external validity and introduces potential selection bias. More importantly, the measurement of the exposure is problematic. Only 1.1% of participants were classified as having “healthy” dietary habits, which suggests a lack of calibration of the instrument for this population. The use of a Spanish-adapted Healthy Eating Index, based on dietary recommendations from the Spanish context, may not be adequately justified for Peruvian medical students and may not reflect local dietary patterns. This raises concern that the instrument is misclassifying participants, thereby undermining the validity and interpretability of the exposure itself.

The manuscript also overreaches in its interpretation. The authors invoke a “dose-response effect” under the Limitations and Strengths section and suggest that the observed gradient supports a potential causal relationship, which is not justified given the cross-sectional design. Temporal ambiguity and reverse causation remain unresolved, particularly because mental health status may influence dietary behaviour. In addition, the adjusted models omit several key confounders, including sleep, physical activity, academic stress, socioeconomic status, and BMI, increasing the likelihood of residual confounding. The discussion further extends beyond the evidence by invoking biological mechanisms and policy implications that are not supported by the study design. Taken together, these issues indicate that the manuscript, in its current form, does not meet the standard of analytical rigour expected for publication. I recommend major revision, with substantial revision of the interpretation, explicit justification or reconsideration of the dietary measurement approach, and a more rigorous treatment of the study’s limitations.

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2026 Jun 18;21(6):e0346062. doi: 10.1371/journal.pone.0346062.r002

Author response to Decision Letter 1

20 Apr 2026

RESPONSE TO REVIEWERS

Manuscript title: Healthier dietary habits are associated with lower depression and anxiety among medical students at a private university in Lima, Peru: A cross-sectional study

Manuscript ID: PONE-D-26-09038

We sincerely thank the Academic Editor, and both reviewers for their thorough, rigorous, and constructive evaluation of our manuscript. Their comments identified areas requiring greater methodological transparency, more cautious interpretation of findings, and more explicit discussion of the study’s limitations. We have addressed each concern systematically in the response below, and we believe the revised manuscript is substantially stronger because of this process.

ACADEMIC EDITOR COMMENTS

Comment AE 1.1. “Clarify and justify the analytical approach. Provide a clear description of the variable selection strategy for regression models (e.g., theoretical criteria, epidemiological relevance, or statistical thresholds). Explain how multicollinearity was assessed and handled—the manuscript mentions categorizing age into tertiles due to multicollinearity, but the diagnostics are not described. Report goodness-of-fit measures appropriate for Poisson regression with robust variance.”

Response: We appreciate this important observation. Covariates for the adjusted regression models were selected a priori on the basis of theoretical association with the outcomes and epidemiological relevance, rather than on statistical cut-offs such as p-values in the bivariate analysis. We recognize that this strategy was not sufficiently described in the original manuscript and have expanded the Statistical analysis section accordingly, adding references supporting the selection of each covariate. Multicollinearity among the independent variables included in each adjusted model was formally evaluated using the variance inflation factor (VIF). When age was initially entered as a continuous variable, a VIF of 25.7 was observed, indicating severe multicollinearity. To address this, age was recategorized into tertiles and included in this categorical form in the adjusted models, after which all VIF values were below the conventional threshold of 10. Regarding goodness-of-fit, we respectfully note that the aim of our analysis was etiologic/associational rather than predictive. Consequently, the regression models were not intended to maximize predictive performance but to estimate the association between dietary habits and the prevalence of anxiety and depression while adjusting for theoretically relevant confounders. For this reason, goodness-of-fit indices were not a primary focus of the analysis. We have clarified this analytical purpose in the revised Methods.

Modified text in manuscript (Methods – Statistical analysis):

“The association between the Healthy Eating Index score and the prevalence of depression or anxiety was evaluated using Poisson regression with robust variance, estimating crude (cPR) and adjusted prevalence ratios (aPR) with 95% confidence intervals (95% CI). Variables considered potential confounders based on theoretical and epidemiological criteria were included in the adjusted model [31–33]. Marital status was not included in the adjusted model because it had very few observations in some categories, and most participants were single. Multicollinearity among the independent variables was formally assessed using the variance inflation factor (VIF). When age was initially modelled as a continuous variable, a VIF of 25.7 was observed, indicating severe collinearity; therefore, age was recategorized into tertiles for inclusion in the adjusted analyses, after which all VIF values were below 10.”

Comment AE 1.2. “Address concerns regarding the dietary assessment instrument. Only 1.1% of participants were classified as having ‘healthy’ dietary habits. This extremely low proportion suggests potential misclassification or lack of calibration of the Spanish-adapted HEI for this population. Provide a stronger justification for using the Spanish-adapted HEI; discuss exposure misclassification including how cultural and dietary differences may affect scoring; consider a sensitivity analysis using tertiles or quartiles of HEI score.”

Response: We fully agree with the Academic Editor that the Spanish-adapted HEI provides categorical cut-offs that have not been standardized or formally calibrated for the Peruvian population, and this represents an important limitation of the instrument. For this reason, the three categories (unhealthy, needs improvement, healthy) were reported descriptively only, to characterize the sample and to enable comparison with previous literature. Crucially, the regression models estimating the association between dietary habits and anxiety/depression were not based on these categories but on the HEI total score modelled as a continuous variable. This analytical choice avoids reliance on cut-offs that have not been validated in Peruvian youth and preserves the full informational content of the scale. For the same reason, we respectfully consider that a complementary analysis using tertiles or quartiles of the HEI score would not add substantive information beyond what the linear model and its post-estimation plots already convey and could in fact reintroduce arbitrary categorizations of the exposure. We selected the Spanish-adapted HEI because it is the best-documented instrument available in Spanish for quantitative assessment of overall diet quality, and because the dietary recommendations underlying its scoring are closer to the Peruvian dietary context than those of purely Anglo-American instruments. We have added a clear acknowledgement of exposure misclassification and of the lack of Peruvian calibration of the categorical cut-offs to the Methods and the Limitations section.

Modified text in manuscript (Methods – Variables):

“The total score ranged from 0 to 100. Final scores were categorized as: >80 (“healthy”), 50–80 (“needs improvement”), and <50 (“unhealthy”). Nevertheless, these cut-off points should be interpreted cautiously, as they have not been specifically validated in Peruvian populations or among university students.”

Modified text in manuscript (Limitations and strengths):

“Also, the categorical cut-offs proposed for the Spanish-adapted HEI have not been standardized for the Peruvian population. This may help explain the very low proportion of students classified as having ‘healthy’ dietary habits (1.1%).”

Comment AE 1.3. “Revise interpretation to avoid causal implications. The manuscript suggests a ‘dose–response effect’ and discusses biological mechanisms in a way that implies causality. Remove or rephrase language implying temporal ordering or causal inference; expand the discussion of reverse causation; ensure biological mechanisms are presented as hypothetical.”

Response: We agree and have carefully revised the language throughout the manuscript. The term “dose–response effect” has been removed and replaced, where appropriate, with “inverse linear relationship” or “inversely proportional relationship” between the healthy eating score and the prevalence of anxiety and depression, which better reflects the statistical behaviour of the association. Statements that could imply temporal ordering or causal inference have been softened or removed. Biological mechanisms are now explicitly framed as hypothetical explanations supported by previous literature rather than as findings of the present study. Furthermore, we have expanded the discussion of reverse causation, acknowledging that symptoms of anxiety and depression may themselves modify dietary behaviour.

Modified text in manuscript (Limitations and strengths):

“Second, the cross-sectional design precludes establishing temporality and directionality between dietary habits and symptoms of anxiety and depression, hence reverse causality is plausible, as symptoms of depression and anxiety are known to alter appetite, food preferences, and eating behavior, which may result in poorer diet quality.”

“In addition, the strength of the association and the inversely proportional relationship supports a potential association between the variables.”

Modified text in manuscript (Discussion – second paragraph on mechanisms):

“In this context, plausible biological pathways proposed in the literature suggest that healthy dietary patterns may protect against depression and anxiety by reducing inflammation and oxidative stress, improving metabolic health, and modulating the gut–brain axis and neurotransmitter regulation [43,44]. On the other hand, high consumption of ultra-processed foods may contribute to worsening mental health by promoting inflammation, dysregulation of the hypothalamic–pituitary–adrenal axis, and alterations in the synthesis of serotonin, dopamine, and norepinephrine [14].”

Comment AE 1.4. “Discuss unmeasured confounding. The adjusted models do not include several important confounders (sleep quality, physical activity, academic stress, socioeconomic status, BMI). Provide a clear justification for their absence and expand the discussion of residual confounding.”

Response: We thank the Academic Editor for this well-taken observation. We acknowledge that sleep quality, physical activity, academic stress, and socioeconomic status were not collected in this study and therefore could not be included in the adjusted models, which is a genuine limitation that we have added explicitly to the Limitations section. We also note that residual confounding by the variables mentioned by the Academic Editor may have led to either underestimation or overestimation of the observed association. As is often the case, adjustment for additional correlated lifestyle confounders (e.g., physical activity, sleep) might move the effect estimate somewhat toward the null, though the direction and magnitude cannot be anticipated with certainty. An important distinction that we would like to raise is that body mass index (BMI) is most plausibly a mediator rather than a confounder of the relationship between dietary habits and mental health, since diet quality is an established determinant of BMI, and BMI itself has been linked to depressive and anxiety symptoms. Adjusting for BMI could therefore produce overadjustment bias and partially block the total effect of diet quality on mental health. For these reasons, BMI would not have been included in the adjusted model even if it had been available. These considerations have been added to the revised Discussion.

Modified text in manuscript (Limitations and strengths):

“In addition, residual confounding is an important limitation. Variables associated with both dietary habits and mental health in university students, such as sleep quality, physical activity, academic stress, and socioeconomic status, were not measured and therefore could not be included in the adjusted models. This may have led to underestimation or overestimation of the observed associations.”

Comment AE 1.5. “Emphasize effect sizes and confidence intervals. Highlight prevalence ratios and confidence intervals as the primary indicators of association; avoid interpreting results solely based on statistical significance.”

Response: We fully agree. The Results and Discussion have been revised to place the adjusted prevalence ratios and their 95% confidence intervals at the center of interpretation, rather than focusing on p-values alone. To further reinforce the robustness and precision of the estimates, we added a sensitivity analysis using 99% confidence intervals. The results remained consistent: anxiety aPR = 0.97 (99% CI: 0.95 to 0.98; p<0.001) and depression aPR = 0.98 (99% CI: 0.96 to 0.99; p<0.001). We have added this sensitivity analysis to the Methods, Results, and Discussion sections, and we have reframed the interpretation of the findings around effect size and precision. We wish to note, however, that we have been careful not to overclaim certainty or causality on the basis of these findings.

Modified text in manuscript (Methods – Statistical analysis):

“As a sensitivity analysis, the same adjusted Poisson regression models were refitted using 99% confidence intervals (99% CI) in order to evaluate the robustness of the estimated associations under a more conservative precision threshold.”

Modified text in manuscript (Results):

“In the sensitivity analysis using 99% CIs, the estimates remained highly statistically significant (anxiety: aPR: 0.97; 99% CI: 0.95 to 0.98; p<0.001; depression: aPR: 0.98; 99% CI: 0.96 to 0.99; p<0.001).”

Modified text in manuscript (Discussion – Main findings):

“In our study, this association was also supported by the strength and consistency of the findings, as each additional point in the HEI was associated with a 3% lower prevalence of anxiety, and this association remained highly statistically significant in the sensitivity analysis using 99% CI.”

Comment AE 2.1. “[Recommended] Expand the discussion of generalizability, considering the single-center, convenience sample and the unique characteristics of a Seventh-day Adventist institution.”

Response: We agree and have expanded the discussion of external validity in the Limitations and in the Implications and recommendations sections. The study was conducted at a single institution, with non-probabilistic convenience sampling, in medical students from a university sponsored by the Seventh-day Adventist Church. The Adventist tradition explicitly promotes a predominantly plant-based dietary pattern, regular physical activity, and abstinence from alcohol and tobacco as part of its health message.

Modified text in manuscript (Implications and recommendations):

“Our findings may be generalizable to similar university settings where medical students facing high academic demands exhibit a high prevalence of depressive (45.1%) and anxiety (34.9%) symptoms, along with a high frequency of dietary patterns that “need improvement” (77.3%) or are considered “unhealthy” (21.6%). However, the study context should be considered when interpreting external validity. This university is sponsored by the Seventh-day Adventist Church, which promotes a predominantly plant-based diet, regular physical activity, and abstinence from alcohol and tobacco. As a result, students may be influenced by institutional, religious, and peer-related factors that shape dietary habits differently from those in secular universities.”

Comment AE 3.1. “[Editorial Note] Clarify the data collection period in relation to the academic calendar, as mental health symptoms may vary across semesters.”

Response: We agree and have clarified the data collection period and its position within the academic calendar in the Methods section. We have also noted that the window included the end-of-semester examination phase, which is typically associated with heightened academic stress and may influence both dietary behavior and mental health symptom burden.

Modified text in manuscript (Methods – Procedures):

“Data collection was conducted from 15/07/2025 to 15/12/2025, corresponding to the second academic semester at Universidad Peruana Unión. This period includes regular academic activities and the end-of-semester examination phase, during which students are often exposed to constant evaluations and sustained academic stress, both of which may influence dietary behaviors and mental health symptom burden.”

Comment AE 3.2. “[Editorial Note] Ensure consistency in reporting (e.g., whether HEI is treated as continuous, categorical, or both).”

Response: We thank the Academic Editor for this helpful observation. We have revised the manuscript to ensure consistency throughout. Specifically, we now state explicitly that: the HEI was used categorically for descriptive purposes only.

Modified text in manuscript (Methods – Statistical analysis):

“The categorization of the HEI score as unhealthy, needs improvement, and healthy was applied only for descriptive analyses.”

REVIEWER #1 COMMENTS

Comment R1.1. “The original dataset contains more than 30 variables, yet it is unclear how variables were selected for inclusion in the bivariate analyses and subsequent regression models. A systematic description of this variable selection process is needed.”

Response: We thank the Reviewer for highlighting this point. Most of t

Attachment

Submitted filename: Response to reviewers.docx

pone.0346062.s005.docx^{(3.4MB, docx)}

PLoS One. doi: 10.1371/journal.pone.0346062.r003

Decision Letter 1

Yordanis Enríquez Canto

13 May 2026

-->PONE-D-26-09038R1-->-->Healthier dietary habits are associated with lower depression and anxiety among medical students at a private university in Lima, Peru: A cross-sectional study-->-->PLOS One

Dear Dr. Soriano-Moreno,

While your revised manuscript addresses most of the concerns raised previously, two key issues remain. First, you are asked to provide a stronger justification for the choice of dietary assessment tool and to perform a sensitivity analysis with an alternative exposure specification. Second, the limitations section should more explicitly address potential residual confounding related to academic stress and socioeconomic status, especially during the examination period. Please refer to the reviewer’s detailed comments below.

Please submit your revised manuscript by Jun 27 2026 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We look forward to receiving your revised manuscript.

Kind regards,

Yordanis Enríquez Canto, Ph.D.

Academic Editor

PLOS One

Journal Requirements:

If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

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Additional Editor Comments:

Thank you for your careful and thorough response to the issues raised in the first round of review. Reviewer 2 acknowledges significant improvements to the manuscript, particularly regarding external validity, causal interpretation, reverse causation, and the discussion of biological mechanisms and practical implications. The clarification of the institutional context and the use of the HEI score as a continuous variable are also noted as strengths.

However, two main points require further attention:

Justification and Sensitivity of the Dietary Instrument:

While the usage of the Spanish-adapted HEI is now more clearly explained, Reviewer 2 notes that linguistic adaptation does not necessarily equate to cultural or dietary suitability for the Peruvian context. Please clarify whether other Latin American adaptations of the HEI (such as the Brazilian version) were considered, and provide a rationale for selecting the Spanish-adapted version. In addition, please conduct a sensitivity analysis with an alternative specification of the dietary exposure variable—such as a flexible approach (e.g., restricted cubic splines) or a categorization based on the sample distribution—to examine whether the association is robust beyond the assumed linear relationship.

Residual Confounding:

While the revised manuscript acknowledges residual confounding and reverse causality, we recommend making the limitation more explicit, particularly with respect to academic stress and socioeconomic status during the end-of-semester examination period. These factors could plausibly influence both diet quality and anxiety/depressive symptoms and were not measured. Please add a statement clarifying that the observed association may in part reflect broader academic and socioeconomic conditions.

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Reviewers' comments:

Reviewer's Responses to Questions

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Reviewer #2: All comments have been addressed

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Reviewer #2: Yes

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Reviewer #2: Yes

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-->6. Review Comments to the Author

Reviewer #2: The authors have responded seriously to the concerns raised in the first round, and several of the revisions improve the manuscript. I consider the concerns regarding external validity, causal overinterpretation, reverse causation, and the discussion of biological mechanisms and practical implications to be largely addressed. In particular, the manuscript now better acknowledges the single-centre Adventist institutional context, removes the previous "dose-response" wording, explicitly discusses reverse causation, and frames biological mechanisms and practical implications more cautiously.

The authors have adequately addressed my concern regarding external validity. The revised text appropriately frames the Adventist affiliation as part of the institutional context, without assuming students’ individual religious affiliation or adherence to Adventist practices. I do not request further revisions on this point.

My main remaining concern relates to the dietary exposure measure. The authors have improved the manuscript by clarifying that the HEI categories were used only descriptively and that the regression models used the total HEI score as a continuous variable. They also appropriately acknowledge that the categorical cut-offs have not been validated in Peruvian populations and that this may help explain the very low proportion of participants classified as having "healthy" dietary habits. However, the concern is not limited to the cut-offs, but also to the contextual validity of the dietary score itself. The justification for using the Spanish-adapted HEI remains somewhat limited, since linguistic availability does not necessarily imply dietary or cultural suitability for Peru. I recommend that the authors clarify whether other Latin American adaptations of the HEI, including Brazilian adaptations, were considered, and explain why the Spanish-adapted instrument was preferred.

In addition, although I understand the authors’ concern that tertiles or quartiles may introduce arbitrary categorisation, an additional sensitivity analysis using an alternative exposure specification would strengthen the manuscript. This need not be limited to tertiles or quartiles. A flexible modelling approach, such as restricted cubic splines, or a sample-distribution-based categorisation, could help assess whether the association depends on assuming a linear relationship across the HEI score range.

I appreciate that the authors now acknowledge residual confounding and reverse causality. However, given that the data collection period included the end-of-semester examination phase, a period in which academic stress, sleep disruption, reduced physical activity, reduced time for meal preparation, and poorer mental health symptoms may co-occur, I recommend making the residual confounding limitation slightly more explicit with regard to academic stress and socioeconomic status. These factors may plausibly affect both diet quality and anxiety/depressive symptoms. The manuscript should therefore make clear that the observed association may partly reflect broader academic and socioeconomic conditions that were not measured.

Overall, the manuscript has improved, and several of my initial concerns have been adequately addressed. I recommend further revision focusing on two remaining issues: first, a stronger justification and sensitivity assessment of the dietary exposure measure; second, a more explicit treatment of residual confounding, especially in relation to the examination period and socioeconomic status.

**********

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Reviewer #2: No

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PLoS One. 2026 Jun 18;21(6):e0346062. doi: 10.1371/journal.pone.0346062.r004

Author response to Decision Letter 2

18 May 2026

RESPONSE TO REVIEWERS

Manuscript title: Healthier dietary habits are associated with lower depression and anxiety among medical students at a private university in Lima, Peru: A cross-sectional study

Manuscript ID: PONE-D-26-09038

We sincerely thank the Academic Editor and Reviewer 2 for their prompt response and for the thorough, rigorous, and constructive evaluation of our manuscript. Their comments identified areas requiring greater methodological transparency, more cautious interpretation of findings, and a more explicit discussion of the study’s limitations. We have addressed each concern systematically in the response below, and we believe the revised manuscript is substantially stronger because of this process.

REVIEWER #2 COMMENTS

Comment R2.1. “My main remaining concern relates to the dietary exposure measure. The authors have improved the manuscript by clarifying that the HEI categories were used only descriptively and that the regression models used the total HEI score as a continuous variable. They also appropriately acknowledge that the categorical cut-offs have not been validated in Peruvian populations and that this may help explain the very low proportion of participants classified as having "healthy" dietary habits. However, the concern is not limited to the cut-offs, but also to the contextual validity of the dietary score itself. The justification for using the Spanish-adapted HEI remains somewhat limited, since linguistic availability does not necessarily imply dietary or cultural suitability for Peru. I recommend that the authors clarify whether other Latin American adaptations of the HEI, including Brazilian adaptations, were considered, and explain why the Spanish-adapted instrument was preferred.”

Response: We thank the reviewer for this important observation. We agree that the concern is not limited to the categorical cut-offs, but also relates to the contextual validity of the dietary score itself. Therefore, we have revised the Methods, Discussion, and Limitations sections to clarify this issue.

In the Methods section, we now explain that the Spanish-adapted HEI was selected because, to our knowledge, no HEI adaptation has been validated specifically for the Peruvian population or for Peruvian university students. Although originally developed in Spain, this instrument was considered suitable for our questionnaire-based study because it is available in Spanish, uses broad and easily understandable food groups, and includes dietary domains that are broadly consistent with the Peruvian Dietary Guidelines, including fruits, vegetables, legumes, dairy products, animal-source foods, sweets, sugar-sweetened beverages, and processed meats. We also expanded the Discussion to contextualize the low proportion of students classified as having healthy dietary habits. We now mention that similarly low frequencies have been reported in previous Latin American studies, including 0.8% in an adult population from urban Huancavelica, Peru, 9.3% among Chilean university students, and 1% among Mexican adolescent women. Therefore, the low frequency observed in our study (1.1%) does not appear to be an isolated finding, but rather is consistent with previous regional evidence. We also discuss that this may reflect the difficulty of meeting strict healthy eating thresholds in real-world student populations, irregular eating schedules, academic stress, limited time for meal planning, and high availability of ultra-processed foods and sugar-sweetened beverages. Finally, we strengthened the Limitations.

Modified text in Methods: “Healthy dietary habits were assessed using the Spanish-adapted Healthy Eating Index (HEI) [28]. This instrument was selected because no HEI adaptation has been validated specifically for the Peruvian population. The Spanish-adapted HEI was considered suitable for this study because it is available in Spanish, uses broad food groups that are understandable for Peruvian students, and includes dietary domains that are broadly consistent with the Peruvian Dietary Guidelines, such as fruits, vegetables, legumes, dairy products, animal-source foods, sweets, sugar-sweetened beverages, and processed meats [29].”

Added text in Discussion: “The low proportion of students classified as having healthy dietary habits is consistent with previous Latin American evidence. In Peru, a study from Huancavelica using the HEI found that only 0.8% of adults had a healthy diet [41]. Similarly, among Chilean university students, only 9.3% had a healthy diet, while 55.3% needed changes and 35.4% had an unhealthy diet [42]. In Mexico, only 1% of adolescent women were classified as having good diet quality using an adapted HEI [43]. This may reflect the difficulty of meeting strict healthy eating thresholds in real-world student populations, as well as irregular eating schedules, academic stress, limited time for meal planning, and high availability of ultra-processed foods and sugar-sweetened beverages.”

Added text in Limitations: “Although validated instruments were used, the PHQ-9 and GAD-7 do not replace a clinical reference diagnosis. Regarding dietary exposure, the Spanish-adapted HEI has not been culturally validated in Peru or among Peruvian university students, which may have introduced non-differential exposure misclassification because it may not fully capture local dietary patterns, portion sizes, cooking methods, sodium intake, or degree of food processing. Also, its categorical cut-offs have not been standardized for the Peruvian population, which may explain the very low proportion of students classified as having ‘healthy’ dietary habits (1.1%), although this finding is consistent with previous Latin American evidence.”

Comment R2.2. “In addition, although I understand the authors’ concern that tertiles or quartiles may introduce arbitrary categorisation, an additional sensitivity analysis using an alternative exposure specification would strengthen the manuscript. This need not be limited to tertiles or quartiles. A flexible modelling approach, such as restricted cubic splines, or a sample-distribution-based categorisation, could help assess whether the association depends on assuming a linear relationship across the HEI score range.”

Response: We thank the reviewer for this helpful suggestion. We agree that alternative exposure specifications may be useful when the association between a continuous exposure and the outcome is non-linear. However, in our study, the linearity assumption between the HEI score and each outcome was assessed before fitting the regression models using the “lincheck” command, showing an approximately linear inverse relationship with both anxiety and depression. Therefore, we considered the continuous linear specification appropriate. Using restricted cubic splines would have added unnecessary complexity without improving interpretability.

Added text in Methods, Statistical analysis: “Before fitting the regression models, the linearity assumption between the HEI score and each outcome was assessed using the “lincheck” command.”

Comment R2.3. “I appreciate that the authors now acknowledge residual confounding and reverse causality. However, given that the data collection period included the end-of-semester examination phase, a period in which academic stress, sleep disruption, reduced physical activity, reduced time for meal preparation, and poorer mental health symptoms may co-occur, I recommend making the residual confounding limitation slightly more explicit with regard to academic stress and socioeconomic status. These factors may plausibly affect both diet quality and anxiety/depressive symptoms. The manuscript should therefore make clear that the observed association may partly reflect broader academic and socioeconomic conditions that were not measured.”

Response: We thank the reviewer for this helpful comment. We agree that residual confounding should be described more explicitly, particularly because data collection included the end-of-semester examination phase. We have revised the Limitations section to clarify that unmeasured factors such as academic stress, sleep quality, physical activity, time available for meal preparation, and socioeconomic status may influence both diet quality and anxiety or depressive symptoms.

Added text in Discussion, limitations: “In addition, residual confounding is an important limitation. Variables associated with both dietary habits and mental health in university students, such as sleep quality, physical activity, academic stress, and socioeconomic status, were not measured and therefore could not be included in the adjusted models. This is particularly relevant because data collection included the end-of-semester examination phase, when academic stress, sleep disruption, reduced physical activity, limited time for meal preparation, and worsening mental health symptoms may co-occur. Therefore, unmeasured academic and socioeconomic factors may partly explain the observed association between diet quality and anxiety or depression, potentially leading to underestimation or overestimation of the observed associations.”

Attachment

Submitted filename: Response_to_reviewers_auresp_2.docx

pone.0346062.s006.docx^{(3.4MB, docx)}

PLoS One. doi: 10.1371/journal.pone.0346062.r005

Decision Letter 2

Yordanis Enríquez Canto

3 Jun 2026

Healthier dietary habits are associated with lower depression and anxiety among medical students at a private university in Lima, Peru: A cross-sectional study

PONE-D-26-09038R2

Dear Dr. Soriano-Moreno,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Yordanis Enríquez Canto, Ph.D.

Academic Editor

PLOS One

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

-->Comments to the Author

Reviewer #2: All comments have been addressed

**********

-->2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Yes

**********

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Reviewer #2: Yes

**********

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Reviewer #2: Yes

**********

-->5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

**********

-->6. Review Comments to the Author

Reviewer #2: The authors have adequately addressed my remaining concerns. The revised manuscript now provides a stronger justification for the use of the Spanish-adapted HEI, acknowledges its lack of cultural validation in Peru, contextualises the low prevalence of "healthy" dietary habits using previous Latin American evidence, and more clearly discusses possible residual confounding related to the examination period, academic stress, socioeconomic status and other unmeasured factors. The authors also assessed the linearity assumption before modelling the HEI score as a continuous exposure. I have no further substantive concerns.

**********

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Reviewer #2: No

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PLoS One. doi: 10.1371/journal.pone.0346062.r006

Acceptance letter

Yordanis Enríquez Canto

PONE-D-26-09038R2

PLOS One

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Table. Frequency of food consumption according to the healthy eating index.

(DOCX)

pone.0346062.s001.docx^{(16.2KB, docx)}

S2 Table. Frequency of anxiety symptoms according to GAD-7 items (n = 264).

(DOCX)

pone.0346062.s002.docx^{(15.1KB, docx)}

S3 Table. Frequency of depressive symptoms according to PHQ-9 items (n = 264).

(DOCX)

pone.0346062.s003.docx^{(15.3KB, docx)}

S1 File. Data.

(XLSX)

pone.0346062.s004.xlsx^{(39.4KB, xlsx)}

Attachment

Submitted filename: Response to reviewers.docx

pone.0346062.s005.docx^{(3.4MB, docx)}

Attachment

Submitted filename: Response_to_reviewers_auresp_2.docx

pone.0346062.s006.docx^{(3.4MB, docx)}

Data Availability Statement

All relevant data underlying the findings of this study are available as Supporting information. The minimal dataset has been uploaded as a fully de-identified database.

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PERMALINK

Healthier dietary habits are associated with lower depression and anxiety among medical students at a private university in Lima, Peru: A cross-sectional study

Adriana Daniel Armas

Diego S Polanco Taipe

David R Soriano-Moreno

Roles

Abstract

Introduction

Objective

Methods

Results

Conclusion

Introduction

Methods

Design, population and sample

Context

Variables

Procedures

Statistical analysis

Ethical considerations

Results

Table 1. Characteristics of medical students at a private university in Lima, Peru (n = 264).

Table 2. Bivariate analysis between sample characteristics and anxiety (n = 264).

Table 3. Bivariate analysis between sample characteristics and depression (n = 264).

Table 4. Association between healthy dietary habits score and the prevalence of depression and anxiety (n = 264).

Fig 1. Relationship between healthy eating score and adjusted prevalence of anxiety.

Fig 2. Relationship between healthy eating score and adjusted prevalence of depression.

Discussion

Main findings

Implications and recommendations

Limitations and strengths

Conclusion

Supporting information

Data Availability

Funding Statement

References

Decision Letter 0

Yordanis Enríquez Canto

Roles

Author response to Decision Letter 1

Decision Letter 1

Yordanis Enríquez Canto

Roles

Author response to Decision Letter 2

Decision Letter 2

Yordanis Enríquez Canto

Roles

Acceptance letter

Yordanis Enríquez Canto

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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