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

Does the introduction explain the objective of the research presented in the preprint?

Yes

Yes, the introduction of the preprint clearly explains the objective of the research presented, stating that the study examined the impact of specific unhealthy eating behaviors on sleep quality (SQ) among university students. The research specifically sought to explore how detrimental dietary behaviors, including eating close to bedtime, substituting meals with snacks, late-night snacking, skipping breakfast, consuming heavy evening meals, and irregular eating schedules, affect sleep quality in international university students. Furthermore, the aim of understanding how dietary habits affect sleep during the significant lifestyle transitions experienced by students is to inform health promotion strategies, and the study hypothesized that these detrimental dietary patterns would be associated with poorer sleep quality among international university students.

Are the methods well-suited for this research?

Somewhat appropriate

The research methods employed, which consisted of a cross-sectional quantitative study using a self-administered questionnaire and the validated Pittsburgh Sleep Quality Index among international university students, were moderately suited for the objective of exploring the associations between specific unhealthy eating behaviors and poor sleep quality (SQ). Key strengths supporting the methodology include the use of the PSQI, a well-validated tool that evaluates multiple sleep parameters, and the large sample size, which bolstered the statistical power and generalizability of the findings within the university student population. Furthermore, the researchers strengthened the analysis by conducting multivariate logistic regression, which adjusted for a comprehensive list of potential demographic and lifestyle confounders, thereby enhancing the validity of the associations identified between dietary habits and sleep outcomes. However, the cross-sectional design is fundamentally limited because, although suitable for exploration, it cannot establish a causal relationship between the observed unhealthy eating behaviors and poor sleep quality. Lastly, limitations that affect the overall suitability include the reliance on self-reported data, which introduces the potential for response and recall bias, and the omission of other factors that could impact sleep quality, such as mental health and environmental variables.

Are the conclusions supported by the data?

Highly supported

The conclusions of the preprint are generally supported by the statistical results presented, particularly the main finding regarding the strong associations between specific unhealthy eating behaviors and poor sleep quality. The study utilized multivariate logistic regression, adjusting for multiple demographic and lifestyle confounders, which strengthened the validity of the reported associations. Specifically, the key behaviors highlighted in the conclusion, consuming heavy evening meals, replacing meals with snacks, and having a short meal-to-bedtime interval, were identified as significant and independent predictors of overall poor sleep quality based on the data, with adjusted odds ratios (ORs) ranging from 2.06 to 2.73 and statistically significant p-values (all p≤0.012). Additionally, cross-tabulation analyses showed that these and other detrimental habits like late-night snacking and skipping breakfast were significantly associated with multiple components of the Pittsburgh Sleep Quality Index (PSQI), such as sleep latency, sleep efficiency, and subjective sleep quality. Despite the robust statistical support for these associations, the authors appropriately acknowledge the key limitation inherent in the cross-sectional design, which is that it permits the exploration of associations but cannot establish causality between the observed dietary behaviors and poor sleep quality

Are the data presentations, including visualizations, well-suited to represent the data?

Highly appropriate and clear

The data presentations employed in the preprint, primarily consisting of statistical tables, are well-suited to represent the various layers of analysis performed during the research. Descriptive statistics, using frequencies and percentages, effectively summarize the sociodemographic characteristics of the student population and the overall prevalence of poor sleep quality. Cross-tabulation analysis is used appropriately to assess the strength of association between individual eating habits, such as late-night snacking or skipping breakfast, and the distinct components of sleep quality, presenting these relationships through Odds Ratios (ORs), 95% Confidence Intervals (CIs), and p-values. Most notably, the key findings identifying the strongest independent predictors of overall poor sleep quality were presented using multivariate logistic regression analysis, displaying adjusted ORs, CIs, and p-values in a table format, which is the necessary and most suitable way to present complex relationships while demonstrating that the results have been controlled for numerous demographic and lifestyle confounders.

How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research?

Very clearly

The authors clearly discuss and interpret their findings by contextualizing the high prevalence of poor sleep quality (51.7%) among international university students within the framework of lifestyle transitions and stressors typical of this population. They offered detailed interpretations for the strongest independent predictors, which are: consuming heavy evening meals, replacing meals with snacks, and a short meal-to-bedtime interval, by explaining that these habits disrupt circadian rhythm synchronization, can elevate core body temperature, and lead to physiological issues like gastroesophageal reflux disease (GERD), all of which impair sleep. Furthermore, the discussion interprets secondary findings, such as the cross-tabulation associations linking skipping breakfast to longer sleep latency and increased daytime dysfunction, by relating these outcomes to established concerns like reduced cognitive performance and deficiencies in essential sleep-regulating nutrients. The research’s limitations are explicitly addressed, highlighting the inability of the cross-sectional design to establish causality and acknowledging the potential for bias from self-reported data, as well as the need to incorporate factors like mental health and environmental variables in future work. Regarding next steps, the authors conclude that implementing health promotion interventions focused on appropriate meal timing and healthier dietary patterns is a practical strategy to enhance sleep quality in this student demographic, further suggesting that future research should utilize longitudinal designs and randomized controlled trials to build upon these associations

Is the preprint likely to advance academic knowledge?

Highly likely

The preprint is highly likely to advance academic knowledge, primarily by offering robust, adjusted associations between specific detrimental eating patterns and poor sleep quality within the distinct and vulnerable population of international university students, a demographic critical to study due to their complex lifestyle changes. The research contributes significant new insight by using multivariate logistic regression, which controlled for numerous demographic and lifestyle confounders, to identify consuming heavy evening meals, replacing meals with snacks, and a short meal-to-bedtime interval as independent and strong predictors of poor sleep quality. This systematic analysis strengthens the understanding of how chrono-nutrition impacts sleep health. Furthermore, the authors enhance academic continuity by clearly delineating the study’s limitations, such as its cross-sectional design and reliance on self-reported data, while explicitly recommending future longitudinal designs and randomized controlled trials to build upon these associations and establish causality. Ultimately, the documented findings provide necessary evidence to inform targeted health promotion interventions focused on appropriate meal timing and healthier eating patterns to enhance overall well-being in this student demographic.

Would it benefit from language editing?

No

The language utilized throughout the preprint is generally professional, precise, and highly effective for communicating the complex research findings, such as the presentation of multivariate logistic regression results and the detailed explanations of chrono-nutrition concepts. Although the text is predominantly clear and easy to follow, there are isolated minor grammatical inaccuracies, such as the incorrect verb tense when describing chrononutrition ("the idea that emphasize" instead of "emphasizes"), and some instances where sentences might be viewed as fragments or awkward phrasing (e.g., "Second, the sample size used in this study" or the list of specific behaviors in the introduction). Nevertheless, the overall coherence and technical clarity are consistently maintained, ensuring that these minor issues do not impede the comprehensive understanding of the research objectives, methodology, or interpretation of results

Would you recommend this preprint to others?

Yes, it’s of high quality

Yes, the preprint is of high quality and is recommended for its robust contribution to academic knowledge regarding the impact of chrono-nutrition on sleep quality among international university students. The study utilized a comprehensive cross-sectional design, employing the validated Pittsburgh Sleep Quality Index (PSQI) and strong statistical methods, including multivariate logistic regression, adjusted for a large number of potential demographic and lifestyle confounders.

Is it ready for attention from an editor, publisher or broader audience?

Yes, after minor changes

While the research is methodologically sound and the data support the conclusions, and despite the clarity of the presentation and discussion, minor language issues were noted earlier, which, although not impeding comprehension, should be addressed through light editing before the work is disseminated to a broader audience or submitted to a publisher.

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.