PREreview of The Impact of Unhealthy Eating Behaviors on Sleep Quality Among University Students: A Cross‐Sectional Study

Overall Evaluation

This manuscript explores the association between specific eating behaviors and sleep quality among international university students using a cross-sectional design and the PSQI. The topic is clearly relevant. Poor sleep in university populations is well established, and meal timing and eating patterns are modifiable behaviors with obvious public health implications. The sample size is solid, the PSQI is an appropriate and validated measure, and the statistical analyses are generally clear and interpretable.

That said, there are several issues that limit the manuscript in its current form. Most of these relate to conceptual precision, consistency between claims and study design, clarity around how key variables are defined and measured (particularly dietary behaviors and stress), and some aspects of statistical interpretation. The study adds data to an existing literature on chrono-nutrition and sleep, but it is not yet entirely clear what distinguishes this work from other cross-sectional studies in student populations. With revision, the paper could make a stronger and more focused contribution.

Major Comments

1. Conceptual Framing and Scope of Contribution

The manuscript frequently refers to the “impact” of unhealthy dietary behaviors on sleep quality. Given the cross-sectional design, that wording overreaches. This study examines associations, not causal effects. Throughout the Introduction, Methods, and Discussion, causal phrasing should be revised to reflect this. This is not a minor stylistic issue. It is central to conceptual accuracy.

More broadly, the paper would benefit from clearly stating what it adds to existing knowledge. At present, it is not entirely clear whether the novelty lies in:

• The focus on international students in Hungary,

• The specific combination of meal timing indicators examined,

• The breadth of covariate adjustment,

• Or the chrono-nutrition framing applied to this population.

Right now, the study reads as population-specific rather than theoretically advancing. Clarifying the intended contribution would strengthen the manuscript considerably.

2. Construct Specification and Measurement Clarity

Sleep Quality

In the Introduction, sleep quality is described as an overall evaluation of sleep. Analytically, however, it is treated as a dichotomized PSQI global score. The PSQI is appropriate and widely used, but the manuscript should clarify how sleep quality is being conceptualized: as subjective appraisal, multidimensional sleep health, or a screening indicator for poor sleep.

The decision to dichotomize PSQI (>5 vs. ≤5) should also be justified explicitly. Dichotomization simplifies interpretation but reduces information and may create artificial thresholds. Reporting the continuous PSQI distribution (mean, SD, possibly median and IQR) alongside the prevalence of poor sleep would improve transparency.

Dietary Behaviors

The term “unhealthy eating behaviors” is used throughout. However, the dietary variables are binary self-report items without frequency thresholds, portion sizes, or quantitative intake measures.

For example:

• “Heavier evening meals” is based on subjective comparison to daytime meals.

• “Replacing meals with snacks” does not specify how often this occurs.

• “Late-night snacks” are defined as after 10 PM, without a contextual explanation.

Given this, describing these as definitively “unhealthy” may overstate what is actually measured. It may be more precise to refer to them as meal timing and pattern indicators unless the authors provide stronger justification grounded in established dietary guidance.

In addition, stress, included as an adjustment variable, appears to be measured with a single self-report item (Normal / Mild / Moderate / Severe). This should be clearly stated in the Methods. Because stress is treated as a confounder in multivariate models, readers need to understand that it is based on a single-item measure rather than a validated multi-item instrument.

3. Theoretical Integration

The Discussion references circadian disruption, peripheral clocks, GERD mechanisms, thermogenic effects, and nutrient pathways. These are plausible and supported in the broader literature. However, this study does not measure caloric intake, nutrient composition, circadian phase markers, or physiological outcomes.

The manuscript should more clearly separate what the data directly show, associations between self-reported meal patterns and PSQI-defined sleep quality, from mechanistic explanations that remain hypothetical in this dataset. Adding clearer qualifiers would prevent overinterpretation.

If the authors wish to broaden the appeal of the manuscript, they might also consider integrating behavioral or psychosocial frameworks relevant to university students. For example, routine disruption, stress-related eating, time management, and cultural adaptation may help explain both eating patterns and sleep. At present, the discussion leans heavily toward physiological mechanisms.

4. Statistical Reporting and Interpretation

The statistical methods are generally appropriate for a cross-sectional association study. Still, several clarifications are needed:

• Table 3 presents a large number of associations across multiple sleep components and eating behaviors. The manuscript does not address multiple testing or distinguish exploratory from primary analyses.

• It appears that the adjusted logistic regression (Table 4) represents the main inferential model. This should be stated clearly.

• The rationale for including the full set of covariates (age, sex, nationality, BMI, smoking, stress, napping, caffeine, etc.) should be briefly explained in terms of confounding control.

• With poor sleep prevalence at 51.7%, odds ratios may overstate relative risk magnitude. A short interpretive note would strengthen the statistical discussion.

Overall, the conclusions are broadly supported at the level of association. The language simply needs to reflect that boundary consistently.

5. Sampling and Generalizability

Convenience sampling was used, and participants were recruited via campus visits. While this is acknowledged, the manuscript occasionally implies broader generalizability to university students more generally. Given the single-site design and non-random sampling, this should be tempered.

The sample is predominantly female (68.8%) and heavily weighted toward health-related faculties (68.6%). This may influence both dietary awareness and sleep behaviors. A short reflection on how sample composition may shape findings would improve transparency.

Minor Comments

• The 10 PM threshold for defining late-night snacking may vary culturally. A brief justification would be helpful.

• The manuscript describes region-specific BMI cutoffs for Asian participants. Clarify whether analyses used unified or region-specific classifications.

• Daily napping is reported at 73.8%. It would be helpful to clarify how “daily” corresponds to the questionnaire response categories.

• Some parts of the Discussion summarize prior literature using strong causal phrasing. For consistency, this could be softened where appropriate.

• The data availability statement may need to be expanded depending on journal policy.

Ethical Considerations

Ethical approval, informed consent, funding disclosures, and conflict of interest statements are clearly reported. No ethical concerns are apparent.

Conclusion & Recommendation

This study addresses an important and practical issue and reports findings that align with existing literature on meal timing and sleep quality in student populations. The methodology is appropriate for a cross-sectional design, and the use of the PSQI is a clear strength.

However, the manuscript requires revision to:

• Align language with the limits of the design,

• Clarify operational definitions of dietary exposures and stress,

• Justify analytic choices such as dichotomization,

• Distinguish exploratory from primary analyses and address multiple testing,

• Strengthen the clarity of its conceptual contribution.

I recommend a major revision. With more disciplined framing and clearer positioning, this manuscript could offer a solid and careful contribution to the literature on dietary patterns and sleep among university students.

Competing interests

The author declares that they have no competing interests.

Use of Artificial Intelligence (AI)

The author declares that they did not use generative AI to come up with new ideas for their review.