University students tend to have poor dietary practices, which ultimately affect their nutritional status. International students are becoming more prevalent in China. The current study aimed to compare the nutritional status, knowledge attitude and practices (KAP) and dietary intake between international and Chinese students in China. A comparative study was conducted in undergraduate students of Nanjing Medical University aged 17–31 years including 308 international and 393 Chinese students. Data was collected by self-administered questionnaire. Body composition was detected by bioelectrical impedance analysis (BIA). Student t-test and chi square test were used for comparison. Linear regressions were used for association of nutritional status with determinants. The prevalence of overweight and obesity in international student was higher than Chinese students. International male and female students were having significantly (p < 0.05) high BMI and percent body fats than Chinese male and female students. Nutritional KAP scores of Chinese students was significantly (p < 0.05) higher than international students. As for diet consumption, daily milk consumption was high in international students while daily egg and weekly fish and meat consumption were found more in Chinese students. Fast foods and carbonated drinks weekly consumption was significantly (p < 0.001) high in international students. After adjusted for age, gender, education, sleeping duration and physical exercise, the inverse association of nutritional KAP with BMI remained significant. Our data indicate that international students had more percent body fats, less nutritional KAP scores and unhealthy dietary habits than Chinese students. Proper nutrition education and guidance for improving good habits and nutritional status is suggested for international students.

Objective: To investigate university students’ knowledge, attitudes and practice (KAP) regarding vitamin D.Design: The students were requested to answer a questionnaire related to vitamin D and sun exposure. The consumption frequency of foods rich in vitamin D was assessed. Additionally, the intake of vitamin D-containing supplements was recorded.Setting: A medical university in Nanjing, China.Subjects: Five hundred and fifteen medical students were included.Results: The highest rate of correct responses for the quiz was 68·0 %, while the lowest was 9·6 %. Most students lacked sun exposure because they did not want to get tanned; 82·7 % of students used some sun protection and sunscreen use was more popular in the female group. The consumption frequency of foods rich in vitamin D was low and 5·6 % of the students used vitamin D supplements. The students’ knowledge on vitamin D was derived mainly from the media and health professionals. Most of the students were interested to know more about vitamin D.Conclusions: The present study suggested that medical students had little knowledge and unfavourable behaviours. They should get more health education through the media and health professionals. It is advisable to increase their consumption of foods rich in vitamin D.

Existing formulas cannot fully explain the variation of resting metabolic rate (RMR). This study aims to examine potential influencing factors beyond anthropometric measurements and develop more accurate equations using accessible parameters. 324 healthy adults (230 females; 18–32 years old) participated in the study. Height, fat-free mass (FFM), fat mass (FM) and RMR were measured. Menstrual cycle, stress levels, living habits, and frequency of consuming caffeinated foods were collected. Measured RMR were compared with predictive values of the new equations and previous 11 equations. Mean RMR for men and women was 1825.2 ± 248.8 and 1345.1 ± 178.7 kcal/day, respectively. RMR adjusted for FFM^0.66FM^0.066 was positively correlated with BMI. The multiple regression model showed that RMR can be predicted in this population with model 1 (with FFM, FM, age, sex and daily sun exposure duration) or model 2 (with weight and height replacing FFM and FM). The accuracy was 75.31% in the population for predictive model 1 and 70.68% for predictive model 2. The new equations had overall improved performance when compared with existing equations. The predictive formula that consider daily sun exposure duration improve RMR prediction in young adults. Additional investigation is required among individuals in the middle-aged and elderly demographic.