Deep neural network for prediction of diet quality among doctors and nurses in North China during the COVID-19 pandemic.

Objective: The COVID-19 pandemic has placed unprecedented pressure on front-line healthcare workers, leading to poor health status, especially diet quality. This study aimed to develop a diet quality prediction model and determine the predictive effects of personality traits, socioeconomic status, lifestyles, and individual and working conditions on diet quality among doctors and nurses during the COVID-19 pandemic. Methods: A total of 5,013 doctors and nurses from thirty-nine COVID-19 designated hospitals provided valid responses in north China in 2022. Participants' data related to social-demographic characteristics, lifestyles, sleep quality, personality traits, burnout, work-related conflicts, and diet quality were collected with questionnaires. Deep Neural Network (DNN) was applied to develop a diet quality prediction model among doctors and nurses during the COVID-19 pandemic. Results: The mean score of diet quality was 46.14 ± 15.08; specifically, the mean scores for variety, adequacy, moderation, and overall balance were 14.33 ± 3.65, 17.99 ± 5.73, 9.41 ± 7.33, and 4.41 ± 2.98, respectively. The current study developed a DNN model with a 21-30-28-1 network framework for diet quality prediction. The DNN model achieved high prediction efficacy, and values of R2, MAE, MSE, and RMSE were 0.928, 0.048, 0.004, and 0.065, respectively. Among doctors and nurses in north China, the top five predictors in the diet quality prediction model were BMI, poor sleep quality, work-family conflict, negative emotional eating, and nutrition knowledge. Conclusion: During the COVID-19 pandemic, poor diet quality is prevalent among doctors and nurses in north China. Machine learning models can provide an automated identification mechanism for the prediction of diet quality. This study suggests that integrated interventions can be a promising approach to improving diet quality among doctors and nurses, particularly weight management, sleep quality improvement, work-family balance, decreased emotional eating, and increased nutrition knowledge.

A survey of Chinese consumers' knowledge, beliefs and behavioural intentions regarding salt intake and salt reduction.

OBJECTIVE: Globally, China is among the 'saltiest' nations. In order to support current nationwide salt reduction initiatives, we investigated Chinese consumers' knowledge, beliefs and behaviours related to salt intake and salt reduction. DESIGN: A cross-sectional face-to-face survey was carried out, focusing on salt knowledge, beliefs and behaviours related to salt intake and salt reduction, perceptions of salt reduction responsibility and support for different national strategies. SETTING: The survey was carried out in China mainland. PARTICIPANTS: Consumers (n 2444) from six of seven major geographical regions in China participated in the survey. After data cleaning, a sample of 2430 was included in the final analysis. RESULTS: A majority of Chinese consumers believed that salt added during home cooking was the biggest contributor to their salt intake. Knowledge gaps existed in the awareness of salt hidden in certain foods and flavouring products. Chinese consumers in general were interested in lowering their salt intake. They were aware of salt reduction tools, but the adoption level was low. Consumers expressed strong support for promotion of salt-restriction spoons and public education, but not fiscal policies (e.g. salt-related tax or subsidies). In terms of individual differences, education status demonstrated a substantial impact on salt reduction knowledge and behaviour. CONCLUSIONS: There is still big room to 'shake' Chinese consumers' salt habit. The present study provides important evidence and consumer insights to support China's efforts to meet its salt reduction targets.

[Study on the distribution of nutrient content in infant formula of China market].

OBJECTIVE: To collect the infant formula products in China, determining the nutrients content and analysing the distribution of the nutrients in the products. METHODS: Infant formula products( domestic production or import) in China market were collected from shopping malls, supermarkets, maternal and infant shops, production enterprises and so on. Nutrients content in the products were determined using GB methods. The status of the nutrient distribution was analyzed, and also compared with the limits of the national standard. RESULTS: A total of 1639 cases of infant formula products bought from 27 provinces( Guangdong, Hebei, Heilongjiang and Inner Mongolia, etc. )were included in this study, and the products were domestically manufactured or imported from the United States, Europe, Australia, Japan, Singapore, etc, covering the main products in China market. Nutrient analysing results showed that the content ofcarbohydrate, vitamin A, vitamin E, vitamin K_1, vitamin B_1, vitamin B_2, vitamin B_6, folic acid, pantothenic acid, vitamin C, sodium, potassium, magnesium, calcium, zinc, manganese were in the lower area of GB limits, while the content of linoleic acid and iron were distributed in the higher area, and the content of protein, fat, vitamin D, niacin, copper distributed uniformly between GB limits. CONCLUSION: Most nutrients in the infant formula products of China market are in the lower area of GB limits, so decreasing the upper limits of some nutrients according to the newest scientific evidence will not have too much impact to the current products.