Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Demographic Variation in Nutrition Knowledge and Relationship with Eating Attitudes among Chinese University Students

Version 1 : Received: 4 January 2024 / Approved: 4 January 2024 / Online: 4 January 2024 (07:46:30 CET)

A peer-reviewed article of this Preprint also exists.

Deng, W.-J.; Yi, Z.; Lee, J.C.-K. The Demographic Variation in Nutrition Knowledge and Relationship with Eating Attitudes among Chinese University Students. Int. J. Environ. Res. Public Health 2024, 21, 159. Deng, W.-J.; Yi, Z.; Lee, J.C.-K. The Demographic Variation in Nutrition Knowledge and Relationship with Eating Attitudes among Chinese University Students. Int. J. Environ. Res. Public Health 2024, 21, 159.

Abstract

There is a noticeable absence of health education among college students. This study aimed to evaluate the extent of general nutrition knowledge among Chinese university students and explore its association with eating attitudes. Data were collected from a group of 273 students in Spring of 2023, using a valid and reliable research instrument consisting of three sections: demographic variables, the General Nutrition Knowledge Questionnaire (GNKQ), and the Eating Attitudes Test (EAT-26). The results were analyzed using SPSS, with correlations and t-tests to examine the relationships between nutritional knowledge and dietary attitudes. Furthermore, the present study employed the Random Forest (RF) algorithm, a machine learning technique, utilizing the Mean Decrease Impurity (MDI) method to investigate the influence of various features on participants' eating attitudes. The findings revealed that Chinese university students had an average accuracy of over 60% in their nutritional knowledge, but their understanding of the relationship between diet and disease still needs improvement. Moreover, male students had significantly lower nutritional knowledge than female students, and there was a positive correlation between nutritional knowledge and parents’ income. The study also found a significant correlation between the level of nutritional knowledge and eating attitudes. RF results indicated that family income level exhibited the most substantial impact on the eating attitudes of the participants. The study highlights the need for nutrition education curriculum developers to focus more on improving students' nutritional knowledge, with particular attention given to male students, low-income individuals, and those with an abnormal BMI.

Keywords

Nutrition knowledge; Machine learning; Eating attitudes; University students; China

Subject

Public Health and Healthcare, Public, Environmental and Occupational Health

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