Background: Studies reveal that promoting the breastfeeding knowledge level help to improve breastfeeding behaviors. Promoting breastfeeding knowledge is a simple and economical way to increase breastfeeding rates. However, there are no studies focus on the level of breastfeeding knowledge and factors influencing the knowledge in women with gestational diabetes mellitus (GDM), which is defined as any degree of glucose tolerance impairment first diagnosed during pregnancy. Thus, the objectives of this study were to investigate the breastfeeding knowledge level of GDM pregnant women and explore factors influencing the knowledge level. Methods: Cross-sectional survey and convenience sampling were conducted in this study. The sociodemographic characteristics, caregivers in pregnancy, knowledge source, breastfeeding status and breast status information of participants were collected. Breastfeeding Knowledge Scale was used to assess the breastfeeding knowledge level of pregnant women with GDM. Multiple linear regression was used to analyze the influence factors of breastfeeding knowledge level in this study. Results: A total of 226 questionnaires were issued and finally 212 valid questionnaires were collected. Some misconceptions still existed (e.g. ‘breastfeeding cannot prevent your baby from being overweight’ and ‘it is advisable to breastfeed 3-4 times per day within 2-3 days after delivery’), although women with GDM had a good score of breastfeeding knowledge (mean score: 103.5 ± 10.4). Multiple linear regression analysis found that gestational age, family per capita monthly income, educational level, knowledge source were the independent protective factors for breastfeeding knowledge and minority nationality was the independent risk factor. The educational level had the greatest influence on the breastfeeding knowledge level of GDM pregnant women (β = 0.210, t = 2.978, P = 0.003). Conclusion: GDM pregnant women with insufficient gestational age, low educational level, low family per capita monthly income and single access to knowledge should be included in the focus of health education on breastfeeding. In-depth and systematic health education should be conducted for pregnant women with GDM to improve their breastfeeding rate.

Dietary patterns influence children and adolescents’ health not only in the present but also in their adulthood. Family characteristics and functioning play a crucial role in food choices and are important modifiable factors for early interventions aimed at preventing unhealthy diets. The study aimed to analyze the dietary patterns of Chinese children and adolescents and explore their associations with family characteristics and functioning. 6276 participants aged 6 to 17 years were recruited for the multicenter cross-sectional study through cluster sampling. Food intake, family characteristics, and family function were assessed. Dietary patterns were identified through factor analysis based on food intake data, and a multiple logistic regression model was used to investigate the associations between dietary patterns, family characteristics, and family functioning. Three distinct dietary patterns were identified: the “Diverse dietary pattern” (characterized by a rich diet and balanced nutrition), the “Fast food concentrated dietary pattern” (primarily consisting of fried foods, sugary drinks, processed meats, and other junk food), and the “Traditional dietary pattern” (mainly vegetables and grains). Girls, those living in rural areas, and those with better family functioning were more likely to adhere to the “Diverse dietary pattern” (p < 0.01). Girls, primary school students, and those with lower educated mothers tended to have higher adherence to the “Traditional dietary pattern” (p < 0.01). High adherence to the “Fast food concentrated dietary pattern” were associated with boys, older age, Han ethnicity, family dysfunction, living with both parents, being an only-child, having a better educated father, lower family income, and higher pocket money (p < 0.01). Children and adolescents from different family backgrounds exhibit distinct dietary patterns, highlighting the importance of early screening and intervention tailored to these varying family characteristics. Among the modifiable family factors, better family functioning stands out as a key area of focus for promoting and sustaining healthy dietary patterns in Chinese children and adolescents.

The purpose of this study was to analyze the growth status and to identify the risk factors that influence the catch-up growth of preterm infants after discharge and to provide evidence for feeding strategies and the need for further research. A descriptive correlational analysis was applied. The sample consisted of 309 preterm infants and their caregivers selected from June to August 2017 from five women’s and children’s hospitals. Self-designed questionnaires based on knowledge, attitude and practice and the Health Belief Model (HBM) were used to measure the catch-up growth status of preterm infants after discharge. Logistic regression was used to determine the risk factors for the catch-up growth of preterm infants. The results showed that of 309 preterm infants, only 14 (4.5%) were underweight, and 52 (17.4%) did not meet the criteria for catch-up growth at 12 months of actual age. The logistic regression analysis showed that gestational age, regular health care, caregivers’ educational background, mothers’ daily contact with the baby, monthly average family income, the addition of a breast milk supplement, and daily milk volume were risk factors that affected the catch-up growth of preterm infants after discharge. The rate of catch-up growth of preterm infants is still not high. We should pay much more attention to preterm infants of small gestational age and guide their child care on a regular basis to detect and correct risk factors in a timely fashion, especially those involving lower daily milk volume, lower degree of culture and family economic difficulties. Second, we suggest that the government publish relevant policy that appropriately increases the length of maternity leave for preterm mothers. Future studies should have larger sample sizes and explore other important factors influencing the catch-up growth of preterm infants.