Disparities in nutrition knowledge among college students: A cross-sectional study and factor analysis in Wuxi, China

Disparities in nutrition knowledge among college students: A cross-sectional study and factor analysis in Wuxi, China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Disparities in nutrition knowledge among college students: A cross-sectional study and factor analysis in Wuxi, China Yu Meng, Ping Liu, Jiaqi Chen, Jinming Wang, Minguo Gao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8485476/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Nutritional knowledge is fundamental for healthy dietary practices. College students are a key group for establishing lifelong health behaviors. However, existing studies suggest significant gaps in their nutrition knowledge, with a disconnect between knowledge and practice. Methods A cross-sectional survey was conducted among 765 undergraduates in Wuxi, China. A standardized questionnaire “Nutrition and health knowledge questionnaire for Chinese adults aged 18–64” assessed knowledge across five domains: dietary recommendations, food characteristics, nutrition and disease, food selection, and food safety. The overall awareness rates and domain-specific rates were calculated. Statistical analyses included group comparisons and logistic regression. Results The overall awareness rate was 24.3%. Significant disparities existed across domains: Food safety had the highest rate (73.9%), while dietary recommendations (16.7%) and food characteristics (16.3%) were notably low. Key knowledge gaps included quantitative limits for salt, sugar, and oil, and portion estimation. Female students showed significantly higher awareness than males (OR = 1.47, 95% CI: 1.04–2.08, P = 0.030). Family income and BMI were not independent factors after adjustment. Conclusions Nutrition knowledge among college students is generally low and imbalanced, with major deficiencies in quantitative and practical aspects. Female gender was an independent predictor of higher knowledge. Future interventions should focus on enhancing practical skills and implementing targeted strategies. Nutritional knowledge College students Cross-sectional study Health education Knowledge-practice gap Figures Figure 1 Introduction Awareness of nutrition and health knowledge serves as the fundamental prerequisite for adopting and maintaining healthy dietary practices, and is closely linked to the improvement of public health [ 1 ]. In contemporary society, the health of the entire population has become an important indicator of a country’s development level, while scientific nutritional literacy forms the cornerstone for maintaining individual health and preventing chronic diseases [ 2 , 3 ]. “Healthy China 2030” blueprint explicitly emphasizes the need to enhance public health literacy and guide residents toward developing scientific nutritional perspectives and healthy lifestyles [ 4 ]. For college students, this stage represents a critical transitional period in life, characterized by significantly increased personal autonomy [ 5 ]. It serves not only as a key window for cultivating lifelong healthy behaviors, but also as a phase when students begin to take independent responsibility for their dietary choices [ 6 ]. As future contributors to national development and a backbone force in society, college students are in a crucial stage of forming health-related behaviors and cognitions. Their level of nutritional knowledge not only directly affects their current physical and mental health and academic performance, but also exerts a profound influence on their long-term quality of life and even the overall health literacy of society [ 7 , 8 ]. However, existing research indicates that the nutritional health status of Chinese college students is not optimistic. On the one hand, irregular schedules, imbalanced dietary patterns, and growing consumption of sugar-sweetened beverages and high-salt, high-fat foods have contributed to prominent issues such as overweight, obesity, and micronutrient deficiencies among young adults [ 9 , 10 ]. On the other hand, multiple regional surveys suggest significant gaps in college students’ nutritional health knowledge, particularly in areas such as quantitative dietary recommendations, understanding of nutrient characteristics in foods, and practical application, where awareness rates are generally low [ 11 ]. The disconnection in the “knowledge-attitude-practice” continuum, where insufficient knowledge or cognitive biases fail to translate into healthy behaviors, posing a major challenge for current health promotion efforts in higher education [ 12 ]. Although prior studies have focused on the status of nutritional knowledge among college students, most have certain limitations: some use non-standardized assessment tools, limiting comparability of results [ 13 ]; others offer broad descriptions without detailed analysis or comparison across different dimensions within the knowledge structure [ 14 ]; still others provide insufficient in-depth exploration of key socio-demographic factors influencing knowledge levels, especially lacking statistical analysis to identify independent influencing factors after multifactor adjustment [ 15 ]. Therefore, employing standardized, authoritative assessment tools to systematically deconstruct the nutritional health knowledge profile of college students and thoroughly investigate its association with multidimensional characteristic factors holds urgent practical significance for accurately identifying knowledge gaps and formulating targeted intervention strategies [ 16 ]. In summary, this study conducted a cross-sectional survey among college students in Wuxi from 2022 to 2023, using the “Nutrition and health knowledge questionnaire for Chinese adults aged 18–64” developed by the National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention [ 17 ]. The study aims to systematically assess the overall and domain-specific awareness of nutritional health knowledge among college students, identify structural weaknesses within the specific knowledge framework, and analyze differences in knowledge levels across students with various demographic characteristics and health statuses. Furthermore, through multifactor regression models, it seeks to explore independent factors associated with knowledge awareness rates. The findings are expected to provide evidence-based support for the development of precise and stratified nutrition health education strategies by universities and public health departments, thereby contributing empirical support to the effective implementation of the healthy China strategy among young adults. Methods Data collection and instruments Data were collected using the standardized “Nutrition and Health Knowledge Questionnaire for Chinese Adults Aged 18–64”, developed and validated by the National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention [ 17 ]. Scoring followed the institute’s established guidelines (Additional file 1). The questionnaire captured demographic characteristics (such as gender, academic year, family income), health-related behaviors (including smoking and alcohol consumption), and nutrition knowledge. As shown in Additional file 2, knowledge was assessed through 20 items grouped into five domains: dietary recommendations, food characteristics, nutrition and disease, food selection, and food safety. Study design and participants This cross-sectional study utilized data from the 2022 and 2023 “Wuxi University Student Nutrition and Health Monitoring Program”, which followed consistent protocols across both years. A random cluster sampling method was applied. One university in Wuxi was randomly selected annually, followed by random selection of two colleges within each university. The study included full-time undergraduates in their first to third years from the chosen colleges. Fourth-year students were excluded due to their frequent participation in off-campus internships. Definitions and measurements The overall awareness rate is the proportion of participants whose total questionnaire score reaches 75 or above (out of a full score of 100) among the total surveyed population. The domain-specific (or item-specific) awareness rate is the proportion of participants whose score in that domain (or item) reaches 75% or above of the full score for that domain (or item) among the total surveyed population. The accuracy rate for a specific knowledge point refers to the proportion of participants who answered that knowledge point correctly (with each option in multiple-choice questions treated as an independent knowledge point) among the total surveyed population. Height and weight were obtained from university routine health examination records. Body mass index (BMI) was computed as weight divided by height squared. Participants were classified as normal weight or overweight/obese based on Chinese criteria. Quality control and statistical analysis All field investigators completed standardized training prior to data collection. Double data entry was performed using Microsoft Excel to ensure accuracy. Statistical analyses were conducted in SPSS version 25.0. Continuous variables are presented as medians with interquartile ranges, and categorical variables as frequencies with percentages. Group comparisons were performed using the Mann–Whitney U test, Kruskal–Wallis test, or chi-square test, as appropriate. Factors associated with nutrition knowledge awareness were examined with binary logistic regression; results are reported as odds ratios (OR) with 95% confidence intervals (CI). A two-tailed p-value < 0.05 indicated statistical significance. Ethical considerations The study was approved by the Institutional Review Board of the National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention (Approval No. 2022-037). Written informed consent was obtained from every participant after the study's nature and purpose were fully explained. Results Item-specific nutrition and health knowledge awareness rates As illustrated in Fig. 1 , awareness of dietary recommendation varied considerably across items. While principles of a balanced diet (73.9%) and fruit and vegetable intake (71.5%) were widely recognized, knowledge of recommended limits for salt, sugar, and oil remained critically low (5.4%). In terms of food characteristics, identification of high-fat or high-salt foods scored favorably (79.7%), yet awareness of iron-rich (26.8%) and vitamin A-rich (34.8%) foods was notably limited. Over 80% of participants understood the importance of maintaining a healthy weight, yet only 38.2% could correctly define criteria for overweight or obesity. Strengths were observed in food selection—balanced lunch combinations (84.0%) and label interpretation (82.5%)—but portion estimation emerged as a major weakness (13.9%). Food safety awareness was robust, with 73.9% adhering to raw and cooked food separation practices. The visual representation further highlights a distinct polarization in performance across items, with some (such as 15, 17, 19) exceeding 80% awareness, while others (such as 2, 16) fell below 15%. Different domain-specific nutrition health knowledge awareness rates analysis Nutrition and health knowledge awareness varied notably across domains, as detailed in Table 1 . The food safety domain achieved the highest awareness rate (73.9%), followed by nutrition and disease (63.0%). Awareness was considerably lower in food selection (24.7%) and especially in dietary recommendations (16.7%) as well as food characteristics (16.3%). Statistically, the differences in domain-specific awareness rates were highly significant ( P < 0.001). Table 1 Analysis of different domain-specific awareness rates Knowledge domain Full marks Median (Q25, Q75) Awareness numbers Awareness rate (%) Dietary recommendations 30 18.5 (15.0, 21.0) 128 16.7 Food characteristics 21 12.0 (10.5, 15.0) 125 16.3 Nutrition and disease 22 17.0 (13.2, 19.0) 482 63.0 Food selection 19 12.0 (9.5, 14.0) 189 24.7 Food safety 8 8.0 (4.0, 8.0) 565 73.9 χ ༒ 966.915 P < 0.001 Analysis of the accuracy nutrition health knowledge rate for a specific knowledge point Table 2 highlights substantial gaps in practical nutrition knowledge, where fewer than 30% of participants provided correct responses across 6 key knowledge point. In dietary recommendations, only 26.2% knew the daily limit for added sugar and 28.1% for cooking oil. Knowledge of food characteristics also showed clear deficits: just 24.2% identified beef as having higher iron bioavailability, while merely 24.7% recognized oranges as rich in vitamin A. Food selection ability was particularly limited, with only 20.7% accurately estimating the recommended vegetable intake and 26.0% correctly judging portion sizes for steamed buns. Table 2 Analysis of knowledge point accuracy rates below 30% Knowledge Domain Specific item Knowledge point Accuracy numbers (%) Dietary recommendations Recommended limits for salt, added sugar, and cooking oil Added sugar limit (g/day) 200 (26.1) Cooking oil limit (g/day) 215 (28.1) Food characteristics Iron-rich and bioavailable foods Beef as iron-rich and highly absorbable 185 (24.2) Vitamin A-rich foods Oranges as vitamin A source 189 (24.7) Food selection Food portion estimation Estimating vegetable portions 158 (20.7) Estimating steamed bun portions 199 (26.0) Distribution of participant characteristics and overall nutrition health knowledge awareness rates As presented in Table 3 , the analysis of 765 participants revealed an overall awareness rate of 24.3% and a median health score of 67.5 (58.0–74.5), with significant disparities observed across several subgroups: awareness was notably higher in women (28.5%) than men (20.1%, P = 0.007) as were median health scores (69.5 vs. 65.0, P < 0.001); although awareness declined from freshmen (26.0%) to juniors (22.0%), only health scores varied significantly by academic year ( P = 0.001); awareness consistently increased with family income (19.4% in low-income vs. 33.3% in high-income groups, P = 0.013), paralleled by rising health scores ( P < 0.001); individuals with normal BMI exhibited both higher awareness (26.2% vs. 18.9%, P = 0.037) and health scores ( P = 0.009) than overweight/obese participants, while no significant associations were found for smoking or drinking status ( P > 0.05). Table 3 Analysis of the overall awareness rates among participants with different characteristics (n = 765) Characteristics Numbers of survey (%) Median (Q25, Q75) Awareness numbers Awareness rate (%) Gender Male 383 (50.1) 65.0 (51.5, 73.5) 77 20.1 Female 382 (49.9) 69.5 (62.5, 75.5) 109 28.5 Z / χ ༒ 5.529 7.385 P 0.000 0.007 Academic Year Freshman 288 (37.6) 69.0 (62.5, 75.0) 75 26.0 Sophomore 241 (31.5) 67.0 (56.0, 74.5) 59 24.5 Junior 236 (30.8) 65.3 (50.1, 74.5) 52 22.0 Z / χ ༒ 13.707 1.138 P 0.001 0.566 Family Income Unknown 144 (18.8) 67.8 (57.0, 74.0) 33 22.9 Low 294 (38.4) 66.5 (55.0, 73.5) 57 19.4 Medium 180 (23.5) 68.0 (59.1, 75.0) 47 26.1 High 147 (19.2) 70.0 (62.0, 76.5) 49 33.3 Z / χ ༒ 17.200 10.844 P 0.001 0.013 BMI Normal 564 (73.7) 68.5 (58.6, 75.0) 148 26.2 Overweight/Obese 201 (26.3) 65.5 (54.0, 73.5) 38 18.9 Z / χ ༒ -2.602 4.333 P 0.009 0.037 Smoking Status Smoker 15 (2.0) 68.5 (52.5, 75.0) 4 26.7 Non-smoker 750 (98.0) 67.5 (58.0, 74.5) 182 24.3 Z / χ ༒ 0.270 P 0.787 0.767 Drinking Status Drinker 512 (66.9) 67.8 (58.0, 74.5) 124 24.2 Non-drinker 253 (33.1) 67.5 (58.2, 74.5) 62 24.5 Z / χ ༒ 0.125 0.008 P 0.901 0.931 Total 765 (100.0) 67.5 (58.0, 74.5) 186 24.3 Logistic regression analysis of factors influencing overall awareness rates A binary logistic regression model was performed to identify factors associated with overall awareness rates (Table 4 ). After adjusting for covariates, female university students exhibited significantly higher odds of awareness than males (OR = 1.470, 95% CI: 1.039–2.081, P = 0.030), confirming gender as an independent determinant. Household income was not significantly associated with awareness in the adjusted model (all P > 0.05). Additionally, although overweight/obese students displayed a trend toward lower awareness compared to normal-weight peers, the association did not reach statistical significance. Table 4 Logistic regression analysis of factors influencing overall awareness rates Characteristics β SE Wald P OR 95% CI Gender Male (Ref) Female 0.385 0.177 4.730 0.030 1.470 1.039–2.081 Family Income Unknown (Ref) Low -0.240 0.250 0.921 0.337 0.787 0.482–1.284 Medium 0.127 0.263 0.231 0.631 1.135 0.667–1.902 High 0.474 0.268 3.132 0.077 1.607 0.950–2.718 BMI Normal (Ref) Overweight/Obese -0.313 0.211 2.194 0.139 0.731 0.483–1.107 Discussion This study assessed the nutrition and health knowledge levels among university students in Wuxi and identified associated factors. The results indicated a generally low overall awareness rate among students, with a notable imbalance in knowledge acquisition. Substantial disparities were observed across different nutrition knowledge domains. The highest awareness rate was noted for food safety, which may be attributed to extensive public campaigns and campus-based education initiatives [ 18 ]. In contrast, awareness rates were critically low for dietary recommendations, which involve specific quantitative guidelines, and for areas requiring an understanding of food characteristics. This finding corresponds with observations by Qiu et al [ 19 ]. Particularly noteworthy was students' limited ability to estimate food portions accurately, with correct response rates ranging only from 13.9% to 26.0%, highlighting a predominant emphasis on theoretical knowledge over practical application in current nutrition education [ 20 ]. Educational approaches often remain conceptual, lacking effective guidance to translate knowledge into actual dietary behaviors, a key factor contributing to the "knowledge-practice gap." Female university students demonstrated significantly higher nutrition knowledge awareness than their male counterparts, a finding consistent with most existing research [ 21 ]. This disparity may be linked to traditional social role distributions, where females often assume greater responsibility for household dietary management, thereby accumulating more relevant knowledge [ 22 ]. Additionally, women generally exhibit higher health consciousness and proactively seek nutrition-related information [ 23 ]. Correspondingly, male students tend to consume unhealthy foods at relatively higher rates [ 24 , 25 ]. Consequently, nutrition education targeting male students requires adapted strategies, such as integrating topics like sports nutrition and employing methods better aligned with their interests and learning preferences [ 26 ]. The association between household economic status and nutrition knowledge diminished in multivariate analysis, suggesting that socioeconomic status may operate through indirect pathways such as educational resources and family environment [ 27 , 28 ]. Similarly, the relationship between weight status and knowledge level demonstrated complexity. Body weight is influenced by multiple factors including genetics, behavior, and environmental contexts; greater nutrition knowledge does not necessarily translate into healthier weight outcomes [ 29 , 30 ]. This observation aligns with findings from intervention studies indicating that knowledge-based education alone has limited effectiveness in weight management [ 31 ]. Therefore, health promotion strategies for different population groups should adopt comprehensive approaches that combine knowledge dissemination with behavioral support and environmental modifications. Several limitations should be acknowledged in this study. First, the cross-sectional design precludes causal inferences. Second, although random cluster sampling was employed, the sample was confined to universities in Wuxi, limiting the generalizability of findings to broader geographical regions and diverse institutional types. Finally, while multiple influencing factors were examined, not all potential variables, such as parental education level, academic major, and preferences for nutrition information channels. Future research could employ longitudinal designs, incorporate mixed methods, and encompass broader behavioral and contextual measurements to more comprehensively understand barriers to knowledge translation. Conclusion This study systematically reveals structural weaknesses in university students' nutrition knowledge and the differential impacts of factors such as gender. Future nutrition and health education should undergo the following transformations: shifting from conceptual dissemination to the cultivation of quantitative skills, with a focus on enhancing practical abilities in dietary guidance, food identification, and portion estimation; transitioning from universal campaigns to targeted interventions, particularly addressing the specific needs of groups such as male students; and evolving from individual knowledge education to "individual-environment" interactive support, integrated with the creation of healthy campus environments. These approaches will effectively promote the substantive translation of knowledge into behavior, providing a scientific foundation for enhancing the health literacy of young adults. Abbreviations BMI Body mass index OR Odds ratios CI Confidence intervals Declarations Ethics approval and consent to participate The study was approved by the Institutional Review Board of the National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention (Approval No. 2022-037). Written informed consent was obtained from every participant after the study's nature and purpose were fully explained. Consent for publication Not applicable. Availability of data and materials All data analyzed during this study are included in this article. Competing interests The authors declare that they have no competing interests. Fundings This work was supported by the Maternal and Child Health Research Project of Wuxi [No. FYKY202407] and Science Popularization Foundation of Wuxi Health Commission [No. P202513]. Authors' Contributions YM and MG conceived and designed the study. YM, PL, JC and JW conducted the data gathering. YM performed data analysis. YM and MG wrote the main manuscript text. All authors read and approved the final manuscript. Acknowledgements Not applicable. References Murakami K, Shinozaki N, Livingstone MBE, Yuan X, Tajima R, Matsumoto M, et al. Associations of food choice values and food literacy with overall diet quality: a nationwide cross-sectional study in Japanese adults. Br J Nutr. 2023;130(10):1795–805. World Health Organization. World health statistics 2025: monitoring health for the SDGs, sustainable development goals. 2025. Available from: https://www.who.int/publications/i/item/9789240110496 Mozaffarian D, Angell SY, Lang T, Rivera JA. Role of government policy in nutrition-barriers to and opportunities for healthier eating. BMJ. 2018;361:k2426. Gao C, Xu J, Liu Y, Yang Y. Nutrition Policy and Healthy China 2030 Building. Eur J Clin Nutr. 2021;75(2):238–46. Siri A, Bragazzi NL, Khabbache H, Spandonari MM, Cáceres LA. Mind the gap between high school and university! A field qualitative survey at the National University of Caaguazú (Paraguay). Adv Med Educ Pract. 2016;7:301–8. Mizia S, Felińczak A, Włodarek D, Syrkiewicz-Świtała M. Evaluation of eating habits and their impact on health among adolescents and young adults: A cross-sectional study. Int J Environ Res Public Health. 2021;18(8):3996. Wang-Chen Y, Kellow NJ, Choi TST. Exploring the determinants of food choice in Chinese mainlanders and Chinese immigrants: A Systematic Review. Nutrients. 2022;14(2):346. Guiné RPF, Florença SG, Aparício MG, Cardoso AP, Ferreira M. Food Knowledge for Better Nutrition and Health: A Study among University Students in Portugal. Healthc (Basel). 2023;11(11):1597. Liu L, Gong W, Li J, Zhou W, Lin L. Eating habits, nutritional status, and lifestyle correlates of body composition in Chinese university students: a cross-sectional study. Front Public Health. 2025;13:1668307. Liu J, Pan Y, Wang L, Tao A, Deng Y, Qiu Y, et al. The association between appetite and eating behaviors among Chinese female university students. Heliyon. 2024;10(18):e37564. Wu J, Yu W, Xu Z, Chen Y, Li J, Sun Q. Dietary knowledge, attitude, practice survey and nutritional knowledge-based intervention: A cross-sectional and randomized controlled trial study among college undergraduates in China. Nutrients. 2024;16(14):2365. Alves F. The relationship between health-related knowledge and attitudes and health risk behaviors among Portuguese university students. Glob Health Promot. 2024;31(1):36–44. Liu Q, Chen J. Awareness and associated factors of prepackaged food nutrition labels by college students in China: a cross-sectional study. Front Public Health. 2025;13:1577633. Sethi D, Sethi S. Assessing the nutritional knowledge gap: students' view of UK medical school education. Cureus. 2025;17(11):e96280. Gao T, Duan Y, Qi Q, Mo G, Han S, Liu H, et al. Nutrition literacy differs based on demographics among university students in Bengbu, China. Front Public Health. 2023;11:1113211. Griebler R, Schütze D, Link T, Schindler K. Brief instruments for measuring nutrition literacy - the Nutrition Health Literacy Scale and the Self-Perceived Food Literacy Scale Short Form. Nutr J. 2024;23(1):73. Ding C, Qiu Y, Li W, Yuan F, Gong W, Chen Z, et al. Expert consistency evaluation on nutrition and health knowledge questionnaire items for Chinese adults. J hygiene Res. 2022;51(06):866–70. Qiu Y, Ding C, Yuan F, Yu T, Liu A. National Survey on Nutrition Knowledge Assessment Among Junior High School Students – 31 PLADs, China, 2023–2024. China CDC Wkly. 2025;7(38):1214–19. Qiu Y, Ding C, Zhang Y, Yuan F, Gong W, Zhou Y, et al. The Nutrition knowledge level and influencing factors among Chinese women aged 18–49 years in 2021: data from a nationally representative survey. Nutrients. 2023;15(9):2034. Ma C, Ren Z, Chen Z, Li C. The association between interactive health literacy and dietary behaviors among Chinese college students: a large-scale cross-sectional study. Front Psychol. 2024;15:1363885. Qiu Y, Ding C, Yuan F, Gong W, Yu T, Zhang Y, et al. Knowledge of Salt, Oil, and Sugar Reduction (Three Reductions) and Its Association with Nutrition-Related Chronic Diseases in Chinese Adults: A Nationwide Cross-Sectional Study. Nutrients. 2025;17(17):2766. Grzymisławska M, Puch EA, Zawada A, Grzymisławski M. Do nutritional behaviors depend on biological sex and cultural gender? Adv Clin Exp Med. 2020;29(1):165–72. Wardle J, Haase AM, Steptoe A, Nillapun M, Jonwutiwes K, Bellisle F. Gender differences in food choice: the contribution of health beliefs and dieting. Ann Behav Med. 2004;27(2):107–16. Beaulieu K, Oustric P, Finlayson G. The Impact of Physical Activity on Food Reward: Review and Conceptual Synthesis of Evidence from Observational, Acute, and Chronic Exercise Training Studies. Curr Obes Rep. 2020;9(2):63–80. Kagawa M, Hills AP. Preoccupation with Body Weight and Under-Reporting of Energy Intake in Female Japanese Nutrition Students. Nutrients. 2020;12(3):830. Ashton LM, Hutchesson MJ, Rollo ME, Morgan PJ, Collins CE. A scoping review of risk behaviour interventions in young men. BMC Public Health. 2014;14:957. Darmon N, Drewnowski A. Does social class predict diet quality? Am J Clin Nutr. 2008;87(5):1107–17. Malo JS, Schafer MH, Stull AJ. Healthy eating in life course context: Asymmetric implications of socioeconomic origins and destinations. Soc Sci Med. 2025;372:117936. Spronk I, Kullen C, Burdon C, O'Connor H. Relationship between nutrition knowledge and dietary intake. Br J Nutr. 2014;111(10):1713–26. Yahia N, Brown CA, Rapley M, Chung M. Level of nutrition knowledge and its association with fat consumption among college students. BMC Public Health. 2016;16(1):1047. Matheson EM, King DE, Everett CJ. Healthy lifestyle habits and mortality in overweight and obese individuals. J Am Board Fam Med. 2012;25(1):9–15. Additional Declarations No competing interests reported. Supplementary Files TextS1.docx Additional file 1: Text S1: Nutrition and health knowledge questionnaire. TableS1.docx Additional file 2: Table S1: Scoring criteria for the items of nutrition and health knowledge. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 20 Apr, 2026 Reviewers agreed at journal 25 Mar, 2026 Reviewers agreed at journal 02 Feb, 2026 Reviewers agreed at journal 02 Feb, 2026 Reviewers invited by journal 07 Jan, 2026 Editor invited by journal 02 Jan, 2026 Editor assigned by journal 01 Jan, 2026 Submission checks completed at journal 01 Jan, 2026 First submitted to journal 30 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8485476","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":570908001,"identity":"3353556a-2f02-4a04-8fa1-602c070574ab","order_by":0,"name":"Yu Meng","email":"","orcid":"","institution":"Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Meng","suffix":""},{"id":570908002,"identity":"195ab7df-1b5b-485d-ac40-24c09e6930ea","order_by":1,"name":"Ping Liu","email":"","orcid":"","institution":"Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Ping","middleName":"","lastName":"Liu","suffix":""},{"id":570908003,"identity":"979fdfe5-11ff-4e05-8908-4fa94a53575b","order_by":2,"name":"Jiaqi Chen","email":"","orcid":"","institution":"Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Jiaqi","middleName":"","lastName":"Chen","suffix":""},{"id":570908004,"identity":"535fd547-29ff-4ab1-ab91-8e851e0c915c","order_by":3,"name":"Jinming Wang","email":"","orcid":"","institution":"Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Jinming","middleName":"","lastName":"Wang","suffix":""},{"id":570908006,"identity":"ce577136-d907-4040-9272-9f232666ba10","order_by":4,"name":"Minguo Gao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAs0lEQVRIiWNgGAWjYLCCBBDB3kCyFp4DJFslkUCkQnn3w0c3PNxRm9gv+XjjDYYam2iCWgzPpKXdSDxzPHHm7LRiC4ZjabkNBLU05JjdSGw7lrjhdo6ZBGPDYSK09L+Barl5hkgt8hJgW2oSN9zgIVKLgcQzoF/aDhjP7AH6JYEYv8j3Jx+7+bOtTraf/fDGGx9qbIiw5QCYOgyxMYGQcrAtEEPrIFqI0TEKRsEoGAUjDwAA+edF5V2T/H0AAAAASUVORK5CYII=","orcid":"","institution":"Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi Center for Disease Control and Prevention","correspondingAuthor":true,"prefix":"","firstName":"Minguo","middleName":"","lastName":"Gao","suffix":""}],"badges":[],"createdAt":"2025-12-31 03:38:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8485476/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8485476/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":99893181,"identity":"5bdfad73-c603-456e-8ea0-3486c787198c","added_by":"auto","created_at":"2026-01-09 14:09:12","extension":"tif","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2838236,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-8485476/v1/229d8372317d1d837bf662cf.tif"},{"id":99893146,"identity":"b3ad2291-20de-43f9-b28c-554dbf7085da","added_by":"auto","created_at":"2026-01-09 14:09:11","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":184620,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.docx","url":"https://assets-eu.researchsquare.com/files/rs-8485476/v1/f171df79e3d2969aa1b4b7bc.docx"},{"id":100359361,"identity":"94fe104c-71de-4f18-9ced-973a97ba1448","added_by":"auto","created_at":"2026-01-16 07:22:07","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":25732,"visible":true,"origin":"","legend":"","description":"","filename":"Table.docx","url":"https://assets-eu.researchsquare.com/files/rs-8485476/v1/b6e5e8df5fafa55f359f0e66.docx"},{"id":100358580,"identity":"21d9452f-d2ea-428b-b029-10a547fce850","added_by":"auto","created_at":"2026-01-16 07:21:11","extension":"json","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":6448,"visible":true,"origin":"","legend":"","description":"","filename":"fb6e001626fe4fbc9117dda9f414887a.json","url":"https://assets-eu.researchsquare.com/files/rs-8485476/v1/d1f4b23f27ed67e7b4b66d4f.json"},{"id":99893187,"identity":"701699ae-855a-407c-9188-60d8f9f51dce","added_by":"auto","created_at":"2026-01-09 14:09:12","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":19005,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8485476/v1/f93c83b1c67ddc55b0375bbf.docx"},{"id":99893182,"identity":"1a11e3c6-213b-4de2-a6c0-999e8d9dbd64","added_by":"auto","created_at":"2026-01-09 14:09:12","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":23632,"visible":true,"origin":"","legend":"","description":"","filename":"TextS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8485476/v1/510f920653e786a362e0e7e5.docx"},{"id":99893144,"identity":"85625bb9-2068-4dd1-8634-e7ffbf01691f","added_by":"auto","created_at":"2026-01-09 14:09:11","extension":"xml","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":122402,"visible":true,"origin":"","legend":"","description":"","filename":"fb6e001626fe4fbc9117dda9f414887a1enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8485476/v1/64b9a4483e40e61c7adb8428.xml"},{"id":99893154,"identity":"a5f3ca03-58ad-44bb-8fa6-d9c9b7148f21","added_by":"auto","created_at":"2026-01-09 14:09:12","extension":"tif","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2838236,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-8485476/v1/0baf18d56a0b88c9b7f77ca4.tif"},{"id":99893185,"identity":"2efae2a6-4d4f-4db5-95f5-7b7426f74159","added_by":"auto","created_at":"2026-01-09 14:09:12","extension":"jpeg","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":217700,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8485476/v1/ee8705b697a8f724e16f9c3e.jpeg"},{"id":99893147,"identity":"ad0ce63c-4a97-4237-b80d-cf131862cd42","added_by":"auto","created_at":"2026-01-09 14:09:11","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":430565,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8485476/v1/437e58227aef43f0c8be1773.png"},{"id":99893151,"identity":"7726f129-6b9a-4f2e-9b8c-ba6dc74c7796","added_by":"auto","created_at":"2026-01-09 14:09:12","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":36295,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8485476/v1/1b8224ce4f0106c6e7342caa.png"},{"id":99893143,"identity":"0f167e5e-6756-4694-8c06-7ceb6a0a33a4","added_by":"auto","created_at":"2026-01-09 14:09:11","extension":"xml","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":121902,"visible":true,"origin":"","legend":"","description":"","filename":"fb6e001626fe4fbc9117dda9f414887a1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8485476/v1/64d298bcf7b28c0e8947c57d.xml"},{"id":99893183,"identity":"e15e0030-207d-4e98-bff6-9534068cce68","added_by":"auto","created_at":"2026-01-09 14:09:12","extension":"html","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":132197,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8485476/v1/3d8e6326f8209af196e6fc6a.html"},{"id":99893173,"identity":"18cd8a2e-467d-498b-9f30-4bdcd0d55a7b","added_by":"auto","created_at":"2026-01-09 14:09:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":863143,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAwareness and unawareness rates for different nutrition and health knowledge questions\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8485476/v1/d4839b6ae9ff3dc219051986.png"},{"id":100377046,"identity":"de24f378-6d6e-4a36-a446-338cf22e1eaa","added_by":"auto","created_at":"2026-01-16 08:46:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1867016,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8485476/v1/f5c6e61d-e843-44ec-8ca7-9b25ecba93e8.pdf"},{"id":99893145,"identity":"1b0eb494-1d53-474a-8912-ed4663d78b45","added_by":"auto","created_at":"2026-01-09 14:09:11","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":23632,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 1: Text S1: Nutrition and health knowledge questionnaire.\u003c/p\u003e","description":"","filename":"TextS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8485476/v1/9b63603099160bd7bf626ef4.docx"},{"id":99893107,"identity":"f28b7b0e-e18f-4b1c-ac7b-3ac16bb23a3b","added_by":"auto","created_at":"2026-01-09 14:09:09","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":19005,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 2: Table S1: Scoring criteria for the items of nutrition and health knowledge.\u003c/p\u003e","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8485476/v1/21dffd7fcca8c87822ca8c1f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Disparities in nutrition knowledge among college students: A cross-sectional study and factor analysis in Wuxi, China","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAwareness of nutrition and health knowledge serves as the fundamental prerequisite for adopting and maintaining healthy dietary practices, and is closely linked to the improvement of public health [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In contemporary society, the health of the entire population has become an important indicator of a country\u0026rsquo;s development level, while scientific nutritional literacy forms the cornerstone for maintaining individual health and preventing chronic diseases [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. \u0026ldquo;Healthy China 2030\u0026rdquo; blueprint explicitly emphasizes the need to enhance public health literacy and guide residents toward developing scientific nutritional perspectives and healthy lifestyles [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor college students, this stage represents a critical transitional period in life, characterized by significantly increased personal autonomy [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. It serves not only as a key window for cultivating lifelong healthy behaviors, but also as a phase when students begin to take independent responsibility for their dietary choices [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. As future contributors to national development and a backbone force in society, college students are in a crucial stage of forming health-related behaviors and cognitions. Their level of nutritional knowledge not only directly affects their current physical and mental health and academic performance, but also exerts a profound influence on their long-term quality of life and even the overall health literacy of society [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, existing research indicates that the nutritional health status of Chinese college students is not optimistic. On the one hand, irregular schedules, imbalanced dietary patterns, and growing consumption of sugar-sweetened beverages and high-salt, high-fat foods have contributed to prominent issues such as overweight, obesity, and micronutrient deficiencies among young adults [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. On the other hand, multiple regional surveys suggest significant gaps in college students\u0026rsquo; nutritional health knowledge, particularly in areas such as quantitative dietary recommendations, understanding of nutrient characteristics in foods, and practical application, where awareness rates are generally low [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The disconnection in the \u0026ldquo;knowledge-attitude-practice\u0026rdquo; continuum, where insufficient knowledge or cognitive biases fail to translate into healthy behaviors, posing a major challenge for current health promotion efforts in higher education [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough prior studies have focused on the status of nutritional knowledge among college students, most have certain limitations: some use non-standardized assessment tools, limiting comparability of results [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]; others offer broad descriptions without detailed analysis or comparison across different dimensions within the knowledge structure [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]; still others provide insufficient in-depth exploration of key socio-demographic factors influencing knowledge levels, especially lacking statistical analysis to identify independent influencing factors after multifactor adjustment [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Therefore, employing standardized, authoritative assessment tools to systematically deconstruct the nutritional health knowledge profile of college students and thoroughly investigate its association with multidimensional characteristic factors holds urgent practical significance for accurately identifying knowledge gaps and formulating targeted intervention strategies [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn summary, this study conducted a cross-sectional survey among college students in Wuxi from 2022 to 2023, using the \u0026ldquo;Nutrition and health knowledge questionnaire for Chinese adults aged 18\u0026ndash;64\u0026rdquo; developed by the National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The study aims to systematically assess the overall and domain-specific awareness of nutritional health knowledge among college students, identify structural weaknesses within the specific knowledge framework, and analyze differences in knowledge levels across students with various demographic characteristics and health statuses. Furthermore, through multifactor regression models, it seeks to explore independent factors associated with knowledge awareness rates. The findings are expected to provide evidence-based support for the development of precise and stratified nutrition health education strategies by universities and public health departments, thereby contributing empirical support to the effective implementation of the healthy China strategy among young adults.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData collection and instruments\u003c/h2\u003e \u003cp\u003eData were collected using the standardized \u0026ldquo;Nutrition and Health Knowledge Questionnaire for Chinese Adults Aged 18\u0026ndash;64\u0026rdquo;, developed and validated by the National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Scoring followed the institute\u0026rsquo;s established guidelines (Additional file 1). The questionnaire captured demographic characteristics (such as gender, academic year, family income), health-related behaviors (including smoking and alcohol consumption), and nutrition knowledge. As shown in Additional file 2, knowledge was assessed through 20 items grouped into five domains: dietary recommendations, food characteristics, nutrition and disease, food selection, and food safety.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy design and participants\u003c/h3\u003e\n\u003cp\u003e This cross-sectional study utilized data from the 2022 and 2023 \u0026ldquo;Wuxi University Student Nutrition and Health Monitoring Program\u0026rdquo;, which followed consistent protocols across both years. A random cluster sampling method was applied. One university in Wuxi was randomly selected annually, followed by random selection of two colleges within each university. The study included full-time undergraduates in their first to third years from the chosen colleges. Fourth-year students were excluded due to their frequent participation in off-campus internships.\u003c/p\u003e\n\u003ch3\u003eDefinitions and measurements\u003c/h3\u003e\n\u003cp\u003eThe overall awareness rate is the proportion of participants whose total questionnaire score reaches 75 or above (out of a full score of 100) among the total surveyed population. The domain-specific (or item-specific) awareness rate is the proportion of participants whose score in that domain (or item) reaches 75% or above of the full score for that domain (or item) among the total surveyed population. The accuracy rate for a specific knowledge point refers to the proportion of participants who answered that knowledge point correctly (with each option in multiple-choice questions treated as an independent knowledge point) among the total surveyed population.\u003c/p\u003e \u003cp\u003eHeight and weight were obtained from university routine health examination records. Body mass index (BMI) was computed as weight divided by height squared. Participants were classified as normal weight or overweight/obese based on Chinese criteria.\u003c/p\u003e\n\u003ch3\u003eQuality control and statistical analysis\u003c/h3\u003e\n\u003cp\u003eAll field investigators completed standardized training prior to data collection. Double data entry was performed using Microsoft Excel to ensure accuracy. Statistical analyses were conducted in SPSS version 25.0. Continuous variables are presented as medians with interquartile ranges, and categorical variables as frequencies with percentages. Group comparisons were performed using the Mann\u0026ndash;Whitney U test, Kruskal\u0026ndash;Wallis test, or chi-square test, as appropriate. Factors associated with nutrition knowledge awareness were examined with binary logistic regression; results are reported as odds ratios (OR) with 95% confidence intervals (CI). A two-tailed p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicated statistical significance.\u003c/p\u003e\n\u003ch3\u003eEthical considerations\u003c/h3\u003e\n\u003cp\u003eThe study was approved by the Institutional Review Board of the National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention (Approval No. 2022-037). Written informed consent was obtained from every participant after the study's nature and purpose were fully explained.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eItem-specific nutrition and health knowledge awareness rates\u003c/h2\u003e \u003cp\u003eAs illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, awareness of dietary recommendation varied considerably across items. While principles of a balanced diet (73.9%) and fruit and vegetable intake (71.5%) were widely recognized, knowledge of recommended limits for salt, sugar, and oil remained critically low (5.4%). In terms of food characteristics, identification of high-fat or high-salt foods scored favorably (79.7%), yet awareness of iron-rich (26.8%) and vitamin A-rich (34.8%) foods was notably limited. Over 80% of participants understood the importance of maintaining a healthy weight, yet only 38.2% could correctly define criteria for overweight or obesity. Strengths were observed in food selection\u0026mdash;balanced lunch combinations (84.0%) and label interpretation (82.5%)\u0026mdash;but portion estimation emerged as a major weakness (13.9%). Food safety awareness was robust, with 73.9% adhering to raw and cooked food separation practices. The visual representation further highlights a distinct polarization in performance across items, with some (such as 15, 17, 19) exceeding 80% awareness, while others (such as 2, 16) fell below 15%.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDifferent domain-specific nutrition health knowledge awareness rates analysis\u003c/h3\u003e\n\u003cp\u003eNutrition and health knowledge awareness varied notably across domains, as detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The food safety domain achieved the highest awareness rate (73.9%), followed by nutrition and disease (63.0%). Awareness was considerably lower in food selection (24.7%) and especially in dietary recommendations (16.7%) as well as food characteristics (16.3%). Statistically, the differences in domain-specific awareness rates were highly significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnalysis of different domain-specific awareness rates\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKnowledge domain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFull marks\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003cp\u003e(Q25, Q75)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAwareness numbers\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAwareness rate (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDietary recommendations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.5 (15.0, 21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood characteristics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.0 (10.5, 15.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNutrition and disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.0 (13.2, 19.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood selection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.0 (9.5, 14.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood safety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.0 (4.0, 8.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e565\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e73.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e༒\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e966.915\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of the accuracy nutrition health knowledge rate for a specific knowledge point\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e highlights substantial gaps in practical nutrition knowledge, where fewer than 30% of participants provided correct responses across 6 key knowledge point. In dietary recommendations, only 26.2% knew the daily limit for added sugar and 28.1% for cooking oil. Knowledge of food characteristics also showed clear deficits: just 24.2% identified beef as having higher iron bioavailability, while merely 24.7% recognized oranges as rich in vitamin A. Food selection ability was particularly limited, with only 20.7% accurately estimating the recommended vegetable intake and 26.0% correctly judging portion sizes for steamed buns.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnalysis of knowledge point accuracy rates below 30%\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKnowledge Domain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpecific item\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKnowledge point\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAccuracy numbers (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDietary recommendations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRecommended limits for salt, added sugar, and cooking oil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdded sugar limit\u003c/p\u003e \u003cp\u003e(g/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e200 (26.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCooking oil limit\u003c/p\u003e \u003cp\u003e(g/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e215 (28.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFood characteristics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIron-rich and bioavailable foods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBeef as iron-rich and highly absorbable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e185 (24.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVitamin A-rich foods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOranges as vitamin A source\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e189 (24.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFood selection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFood portion estimation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEstimating vegetable portions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e158 (20.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEstimating steamed bun portions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e199 (26.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDistribution of participant characteristics and overall nutrition health knowledge awareness rates\u003c/h2\u003e \u003cp\u003eAs presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the analysis of 765 participants revealed an overall awareness rate of 24.3% and a median health score of 67.5 (58.0\u0026ndash;74.5), with significant disparities observed across several subgroups: awareness was notably higher in women (28.5%) than men (20.1%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007) as were median health scores (69.5 vs. 65.0, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001); although awareness declined from freshmen (26.0%) to juniors (22.0%), only health scores varied significantly by academic year (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001); awareness consistently increased with family income (19.4% in low-income vs. 33.3% in high-income groups, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013), paralleled by rising health scores (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001); individuals with normal BMI exhibited both higher awareness (26.2% vs. 18.9%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.037) and health scores (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009) than overweight/obese participants, while no significant associations were found for smoking or drinking status (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnalysis of the overall awareness rates among participants with different characteristics (n\u0026thinsp;=\u0026thinsp;765)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumbers of survey (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003cp\u003e(Q25, Q75)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAwareness numbers\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAwareness rate (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e383 (50.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65.0 (51.5, 73.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e382 (49.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69.5 (62.5, 75.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eZ / χ\u003c/em\u003e\u003csup\u003e\u003cem\u003e༒\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.385\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcademic Year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFreshman\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e288 (37.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69.0 (62.5, 75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSophomore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e241 (31.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.0 (56.0, 74.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e236 (30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65.3 (50.1, 74.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e / \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e༒\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.138\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.566\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e144 (18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.8 (57.0, 74.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e294 (38.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66.5 (55.0, 73.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e180 (23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68.0 (59.1, 75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e147 (19.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70.0 (62.0, 76.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e/ \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e༒\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.844\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e564 (73.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68.5 (58.6, 75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight/Obese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e201 (26.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65.5 (54.0, 73.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e/ \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e༒\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-2.602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.333\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68.5 (52.5, 75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e750 (98.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.5 (58.0, 74.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e/ \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e༒\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.767\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrinking Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e512 (66.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.8 (58.0, 74.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e253 (33.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.5 (58.2, 74.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e/ \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e༒\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.931\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e765 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.5 (58.0, 74.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eLogistic regression analysis of factors influencing overall awareness rates\u003c/h2\u003e \u003cp\u003eA binary logistic regression model was performed to identify factors associated with overall awareness rates (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). After adjusting for covariates, female university students exhibited significantly higher odds of awareness than males (OR\u0026thinsp;=\u0026thinsp;1.470, 95% CI: 1.039\u0026ndash;2.081, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.030), confirming gender as an independent determinant. Household income was not significantly associated with awareness in the adjusted model (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Additionally, although overweight/obese students displayed a trend toward lower awareness compared to normal-weight peers, the association did not reach statistical significance.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression analysis of factors influencing overall awareness rates\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.730\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.039\u0026ndash;2.081\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.482\u0026ndash;1.284\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.631\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.667\u0026ndash;1.902\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.950\u0026ndash;2.718\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight/Obese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.483\u0026ndash;1.107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study assessed the nutrition and health knowledge levels among university students in Wuxi and identified associated factors. The results indicated a generally low overall awareness rate among students, with a notable imbalance in knowledge acquisition.\u003c/p\u003e \u003cp\u003eSubstantial disparities were observed across different nutrition knowledge domains. The highest awareness rate was noted for food safety, which may be attributed to extensive public campaigns and campus-based education initiatives [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In contrast, awareness rates were critically low for dietary recommendations, which involve specific quantitative guidelines, and for areas requiring an understanding of food characteristics. This finding corresponds with observations by Qiu et al [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Particularly noteworthy was students' limited ability to estimate food portions accurately, with correct response rates ranging only from 13.9% to 26.0%, highlighting a predominant emphasis on theoretical knowledge over practical application in current nutrition education [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Educational approaches often remain conceptual, lacking effective guidance to translate knowledge into actual dietary behaviors, a key factor contributing to the \"knowledge-practice gap.\"\u003c/p\u003e \u003cp\u003eFemale university students demonstrated significantly higher nutrition knowledge awareness than their male counterparts, a finding consistent with most existing research [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This disparity may be linked to traditional social role distributions, where females often assume greater responsibility for household dietary management, thereby accumulating more relevant knowledge [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Additionally, women generally exhibit higher health consciousness and proactively seek nutrition-related information [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Correspondingly, male students tend to consume unhealthy foods at relatively higher rates [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Consequently, nutrition education targeting male students requires adapted strategies, such as integrating topics like sports nutrition and employing methods better aligned with their interests and learning preferences [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe association between household economic status and nutrition knowledge diminished in multivariate analysis, suggesting that socioeconomic status may operate through indirect pathways such as educational resources and family environment [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Similarly, the relationship between weight status and knowledge level demonstrated complexity. Body weight is influenced by multiple factors including genetics, behavior, and environmental contexts; greater nutrition knowledge does not necessarily translate into healthier weight outcomes [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. This observation aligns with findings from intervention studies indicating that knowledge-based education alone has limited effectiveness in weight management [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Therefore, health promotion strategies for different population groups should adopt comprehensive approaches that combine knowledge dissemination with behavioral support and environmental modifications.\u003c/p\u003e \u003cp\u003eSeveral limitations should be acknowledged in this study. First, the cross-sectional design precludes causal inferences. Second, although random cluster sampling was employed, the sample was confined to universities in Wuxi, limiting the generalizability of findings to broader geographical regions and diverse institutional types. Finally, while multiple influencing factors were examined, not all potential variables, such as parental education level, academic major, and preferences for nutrition information channels. Future research could employ longitudinal designs, incorporate mixed methods, and encompass broader behavioral and contextual measurements to more comprehensively understand barriers to knowledge translation.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study systematically reveals structural weaknesses in university students' nutrition knowledge and the differential impacts of factors such as gender. Future nutrition and health education should undergo the following transformations: shifting from conceptual dissemination to the cultivation of quantitative skills, with a focus on enhancing practical abilities in dietary guidance, food identification, and portion estimation; transitioning from universal campaigns to targeted interventions, particularly addressing the specific needs of groups such as male students; and evolving from individual knowledge education to \"individual-environment\" interactive support, integrated with the creation of healthy campus environments. These approaches will effectively promote the substantive translation of knowledge into behavior, providing a scientific foundation for enhancing the health literacy of young adults.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBody mass index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOdds ratios\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence intervals\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Institutional Review Board of the National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention (Approval No. 2022-037). Written informed consent was obtained from every participant after the study's nature and purpose were fully explained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data analyzed during this study are included in this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFundings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Maternal and Child Health Research Project of Wuxi [No. FYKY202407] and Science Popularization Foundation of Wuxi Health Commission [No. P202513].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYM and MG conceived and designed the study. YM, PL, JC and JW conducted the data gathering. YM performed data analysis. YM and MG wrote the main manuscript text. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMurakami K, Shinozaki N, Livingstone MBE, Yuan X, Tajima R, Matsumoto M, et al. Associations of food choice values and food literacy with overall diet quality: a nationwide cross-sectional study in Japanese adults. Br J Nutr. 2023;130(10):1795\u0026ndash;805.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. World health statistics 2025: monitoring health for the SDGs, sustainable development goals. 2025. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications/i/item/9789240110496\u003c/span\u003e\u003cspan address=\"https://www.who.int/publications/i/item/9789240110496\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMozaffarian D, Angell SY, Lang T, Rivera JA. Role of government policy in nutrition-barriers to and opportunities for healthier eating. BMJ. 2018;361:k2426.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGao C, Xu J, Liu Y, Yang Y. Nutrition Policy and Healthy China 2030 Building. Eur J Clin Nutr. 2021;75(2):238\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSiri A, Bragazzi NL, Khabbache H, Spandonari MM, C\u0026aacute;ceres LA. Mind the gap between high school and university! A field qualitative survey at the National University of Caaguaz\u0026uacute; (Paraguay). Adv Med Educ Pract. 2016;7:301\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMizia S, Felińczak A, Włodarek D, Syrkiewicz-Świtała M. Evaluation of eating habits and their impact on health among adolescents and young adults: A cross-sectional study. Int J Environ Res Public Health. 2021;18(8):3996.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang-Chen Y, Kellow NJ, Choi TST. Exploring the determinants of food choice in Chinese mainlanders and Chinese immigrants: A Systematic Review. Nutrients. 2022;14(2):346.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuin\u0026eacute; RPF, Floren\u0026ccedil;a SG, Apar\u0026iacute;cio MG, Cardoso AP, Ferreira M. Food Knowledge for Better Nutrition and Health: A Study among University Students in Portugal. Healthc (Basel). 2023;11(11):1597.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu L, Gong W, Li J, Zhou W, Lin L. Eating habits, nutritional status, and lifestyle correlates of body composition in Chinese university students: a cross-sectional study. Front Public Health. 2025;13:1668307.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu J, Pan Y, Wang L, Tao A, Deng Y, Qiu Y, et al. The association between appetite and eating behaviors among Chinese female university students. Heliyon. 2024;10(18):e37564.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu J, Yu W, Xu Z, Chen Y, Li J, Sun Q. Dietary knowledge, attitude, practice survey and nutritional knowledge-based intervention: A cross-sectional and randomized controlled trial study among college undergraduates in China. Nutrients. 2024;16(14):2365.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlves F. The relationship between health-related knowledge and attitudes and health risk behaviors among Portuguese university students. Glob Health Promot. 2024;31(1):36\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu Q, Chen J. Awareness and associated factors of prepackaged food nutrition labels by college students in China: a cross-sectional study. Front Public Health. 2025;13:1577633.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSethi D, Sethi S. Assessing the nutritional knowledge gap: students' view of UK medical school education. Cureus. 2025;17(11):e96280.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGao T, Duan Y, Qi Q, Mo G, Han S, Liu H, et al. Nutrition literacy differs based on demographics among university students in Bengbu, China. Front Public Health. 2023;11:1113211.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGriebler R, Sch\u0026uuml;tze D, Link T, Schindler K. Brief instruments for measuring nutrition literacy - the Nutrition Health Literacy Scale and the Self-Perceived Food Literacy Scale Short Form. Nutr J. 2024;23(1):73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDing C, Qiu Y, Li W, Yuan F, Gong W, Chen Z, et al. Expert consistency evaluation on nutrition and health knowledge questionnaire items for Chinese adults. J hygiene Res. 2022;51(06):866\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQiu Y, Ding C, Yuan F, Yu T, Liu A. National Survey on Nutrition Knowledge Assessment Among Junior High School Students \u0026ndash;\u0026thinsp;31 PLADs, China, 2023\u0026ndash;2024. China CDC Wkly. 2025;7(38):1214\u0026ndash;19.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQiu Y, Ding C, Zhang Y, Yuan F, Gong W, Zhou Y, et al. The Nutrition knowledge level and influencing factors among Chinese women aged 18\u0026ndash;49 years in 2021: data from a nationally representative survey. Nutrients. 2023;15(9):2034.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMa C, Ren Z, Chen Z, Li C. The association between interactive health literacy and dietary behaviors among Chinese college students: a large-scale cross-sectional study. Front Psychol. 2024;15:1363885.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQiu Y, Ding C, Yuan F, Gong W, Yu T, Zhang Y, et al. Knowledge of Salt, Oil, and Sugar Reduction (Three Reductions) and Its Association with Nutrition-Related Chronic Diseases in Chinese Adults: A Nationwide Cross-Sectional Study. Nutrients. 2025;17(17):2766.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrzymisławska M, Puch EA, Zawada A, Grzymisławski M. Do nutritional behaviors depend on biological sex and cultural gender? Adv Clin Exp Med. 2020;29(1):165\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWardle J, Haase AM, Steptoe A, Nillapun M, Jonwutiwes K, Bellisle F. Gender differences in food choice: the contribution of health beliefs and dieting. Ann Behav Med. 2004;27(2):107\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeaulieu K, Oustric P, Finlayson G. The Impact of Physical Activity on Food Reward: Review and Conceptual Synthesis of Evidence from Observational, Acute, and Chronic Exercise Training Studies. Curr Obes Rep. 2020;9(2):63\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKagawa M, Hills AP. Preoccupation with Body Weight and Under-Reporting of Energy Intake in Female Japanese Nutrition Students. Nutrients. 2020;12(3):830.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAshton LM, Hutchesson MJ, Rollo ME, Morgan PJ, Collins CE. A scoping review of risk behaviour interventions in young men. BMC Public Health. 2014;14:957.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDarmon N, Drewnowski A. Does social class predict diet quality? Am J Clin Nutr. 2008;87(5):1107\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMalo JS, Schafer MH, Stull AJ. Healthy eating in life course context: Asymmetric implications of socioeconomic origins and destinations. Soc Sci Med. 2025;372:117936.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSpronk I, Kullen C, Burdon C, O'Connor H. Relationship between nutrition knowledge and dietary intake. Br J Nutr. 2014;111(10):1713\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYahia N, Brown CA, Rapley M, Chung M. Level of nutrition knowledge and its association with fat consumption among college students. BMC Public Health. 2016;16(1):1047.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatheson EM, King DE, Everett CJ. Healthy lifestyle habits and mortality in overweight and obese individuals. J Am Board Fam Med. 2012;25(1):9\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Nutritional knowledge, College students, Cross-sectional study, Health education, Knowledge-practice gap","lastPublishedDoi":"10.21203/rs.3.rs-8485476/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8485476/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eNutritional knowledge is fundamental for healthy dietary practices. College students are a key group for establishing lifelong health behaviors. However, existing studies suggest significant gaps in their nutrition knowledge, with a disconnect between knowledge and practice.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional survey was conducted among 765 undergraduates in Wuxi, China. A standardized questionnaire \u0026ldquo;Nutrition and health knowledge questionnaire for Chinese adults aged 18\u0026ndash;64\u0026rdquo; assessed knowledge across five domains: dietary recommendations, food characteristics, nutrition and disease, food selection, and food safety. The overall awareness rates and domain-specific rates were calculated. Statistical analyses included group comparisons and logistic regression.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe overall awareness rate was 24.3%. Significant disparities existed across domains: Food safety had the highest rate (73.9%), while dietary recommendations (16.7%) and food characteristics (16.3%) were notably low. Key knowledge gaps included quantitative limits for salt, sugar, and oil, and portion estimation. Female students showed significantly higher awareness than males (OR\u0026thinsp;=\u0026thinsp;1.47, 95% CI: 1.04\u0026ndash;2.08, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.030). Family income and BMI were not independent factors after adjustment.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eNutrition knowledge among college students is generally low and imbalanced, with major deficiencies in quantitative and practical aspects. Female gender was an independent predictor of higher knowledge. Future interventions should focus on enhancing practical skills and implementing targeted strategies.\u003c/p\u003e","manuscriptTitle":"Disparities in nutrition knowledge among college students: A cross-sectional study and factor analysis in Wuxi, China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-09 14:08:46","doi":"10.21203/rs.3.rs-8485476/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-20T14:53:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"184090483332068478205731406426095091700","date":"2026-03-25T13:05:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"75499888133276091944398080034395745531","date":"2026-02-03T02:39:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"112389025573404867267883539794359576273","date":"2026-02-02T07:27:41+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-07T14:05:52+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-02T07:05:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-02T04:26:36+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-02T04:26:14+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-12-31T03:35:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"20ef0082-0b71-479a-9c02-8664e7faff64","owner":[],"postedDate":"January 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-09T14:08:47+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-09 14:08:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8485476","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8485476","identity":"rs-8485476","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}