Negative emotions and gut microbiota during pregnancy both bear significant public health implications. However, the relationship between them has not been fully elucidated. This study, utilizing data from a pregnancy cohort, employed metagenomic sequencing to elucidate the relationship between anxiety, depression, and gut microbiota’s diversity, composition, species, and functional pathways. Data from 87 subjects, spanning 225 time points across early, mid, and late pregnancy, were analyzed. The results revealed that anxiety and depression significantly corresponded to lower alpha diversity (including the Shannon entropy and the Simpson index). Anxiety and depression scores, along with categorical distinctions of anxiety/non-anxiety and depression/non-depression, were found to account for 0.723%, 0.731%, 0.651%, and 0.810% of the variance in gut-microbiota composition (p = 0.001), respectively. Increased anxiety was significantly positively associated with the abundance of Oscillibacter sp. KLE 1745, Oscillibacter sp. PEA192, Oscillibacter sp. KLE 1728, Oscillospiraceae bacterium VE202 24, and Treponema socranskii. A similar association was significantly noted for Oscillibacter sp. KLE 1745 with elevated depression scores. While EC.3.5.3.1: arginase appeared to be higher in the anxious group than in the non-anxious group, vitamin B12-related enzymes appeared to be lower in the depression group than in the non-depression group. The changes were found to be not statistically significant after post-multiple comparison adjustment.

Drinking alcohol during adolescence has short-term and long-term effects on physical and mental health. At this stage, teenagers are greatly influenced by their schoolmates and friends. We conducted a multicenter cross-sectional study to investigate the association between school environment factors and adolescents’ drinking behavior in China. Using multistage stratified cluster sampling, the study investigated 27,762 middle school students from six cities in China. The logistic regression model was used to explore the association between the school environment and adolescent alcohol drinking behaviors after adjusting for confounders, including gender, age, city, location, and smoking status. Compared with students with none of their close friends drinking, students with more than half of their close friends drinking were more likely to drink in a year (OR = 20.148, 95% CI: 17.722–22.905, p < 0.001) and in a month (OR = 13.433, 95% CI: 11.779–15.319, p < 0.001). In addition, classmates’ drinking behaviors, friends’ persuasion, and attending parties were risk factors for adolescents’ drinking behavior, while the propaganda and regulations of banning drinking in school were protective factors. The school environment, especially friends drinking, is associated with students’ drinking behavior. It is necessary to mobilize the strength of schools and peers to strengthen the prevention and control of adolescent drinking.

Objective: The objective of this study was to evaluate the home food environment of the elderly in Beijing and analyze its association with the body mass index (BMI) of the elderly, as well as to provide recommendations for improving the home food environment for the elderly. Methods: This study was conducted in Beijing, China, in 2019. The participants were 1764 elderly individuals aged 65 to 80, recruited from 12 communities through a multistage stratified random sampling method. The study involved the use of questionnaire surveys to gather data on participants’ demographics, the availability of various foods in their households, and their living conditions. Socioeconomic status (SES) was evaluated based on their educational level, occupation, and income level. Height and weight measurements were taken to calculate BMI. We conducted both univariate analysis and multiple linear regression analysis to evaluate the relationship between the home food environment and BMI. Results: A total of 1800 questionnaires were distributed, of which 1775 were retrieved, resulting in a questionnaire recovery rate of 98.6%. Among these, 1764 questionnaires were deemed valid, corresponding to a questionnaire validity rate of 99.4%. The participants had a mean age of 69.7 ± 4.3 years old, over 40% of whom were overweight or obese. In terms of low-energy/high-nutrient-density foods, the most readily available items were fresh vegetables (95.6%), followed by coarse grains (94.1%), fresh fruits (90.4%), and dairy products (83.6%). Among high-energy/low-nutrient-density foods, preserved foods were the most available (51.9%), followed by salted snacks (40.6%), sugary beverages (28.2%), and fried foods (9.4%). Approximately 7.3% of participants lived alone. Elderly individuals with higher SES had a lower BMI compared to those with medium to low SES (25.9 vs. 26.5, 25.9 vs. 26.4, p < 0.05). Those living alone had a higher BMI than those who did not (27.2 vs. 26.2, p = 0.001). After controlling for potential confounding variables, older adults with high SES exhibited a BMI reduction of 0.356 kg/m² (p = 0.001), whereas those living alone exhibited an increase in BMI of 1.155 kg/m² (p < 0.001). The presence of preserved foods at home was linked to a BMI increase of 0.442 kg/m² (p = 0.008). Conclusion: This study underscores the significant impact of family SES, living conditions, and the availability of preserved foods on the BMI of elderly individuals.