Metabolic syndrome has become a significant public health concern. This study aims to investigate the impact of dietary patterns on metabolic syndrome in young adults and how physical activity modulates this effect. A cross-sectional study was conducted at a health management center in Tianjin, China, from September 2022 to March 2023. Participants aged 18–35 years were recruited using convenience sampling. Dietary intake was assessed using a validated food frequency questionnaire. Logistic regression models evaluated associations between these patterns and metabolic syndrome, adjusting for potential confounders. Among 442 participants, four dietary patterns were identified: Legume–Nut, Alcohol–Meat, Sugar–Processed, and Egg–Vegetable. The Legume–Nut dietary pattern was associated with a higher risk of metabolic syndrome (OR = 2.63, 95% CI: 1.08–6.37), while the Egg–Vegetable dietary pattern was associated with a lower risk (OR = 0.26, 95% CI: 0.10–0.70). No significant associations were found for the Sugar–Processed and Alcohol–Meat patterns. Subgroup analysis revealed that the Legume–Nut pattern increased the risk of metabolic syndrome among those with irregular physical activity, whereas the Egg–Vegetable pattern decreased the risk. These findings highlight the significant influence of dietary patterns on the risk of metabolic syndrome in young adults and the modifying effect of regular physical activity, underscoring the need for targeted dietary and lifestyle interventions to prevent metabolic syndrome in this population.

Aims: This study aimed to uncover hidden patterns and predictors of symptom multi-trajectories within 30 days after discharge in patients with heart failure and assess the risk of unplanned 30-day hospital readmission in different patterns. Methods and results: The study was conducted from September 2022 to September 2023 in four third-class hospitals in Tianjin, China. A total of 301 patients with heart failure were enrolled in the cohort, and 248 patients completed a 30-day follow-up after discharge. Three multi-trajectory groups were identified: mild symptom status (24.19%), moderate symptom status (57.26%), and severe symptom status (18.55%). With the mild symptom status group as a reference, physical frailty, psychological frailty, and comorbid renal dysfunction were predictors of the moderate symptom status group. Physical frailty, psychological frailty, resilience, taking diuretics, and comorbid renal dysfunction were predictors of the severe symptom status group. Compared with the mild symptom status group, the severe symptom status group was significantly associated with high unplanned 30-day hospital readmission risks. Conclusion: This study identified three distinct multi-trajectory groups among patients with heart failure within 30 days after discharge. The severe symptom status group was associated with a significantly increased risk of unplanned 30-day hospital readmission. Common and different factors predicted different symptom multi-trajectories. Healthcare providers should assess the physical and psychological frailty and renal dysfunction of patients with heart failure before discharge. Inpatient care aimed at alleviating physical and psychological frailty and enhancing resilience may be important to improve patients’ symptom development post-discharge.

Aims: To reveal the multi-trajectory of anxiety and depression in patients with HF (heart failure) and their caregivers within 3 months post-discharge and to illustrate the interconnections among these trajectories and dyadic burden components. Methods and results: We recruited 248 pairs of patients with HF and caregivers from four tertiary hospitals in Tianjin, China. Data were collected at baseline, 2 weeks, 4 weeks, and 3 months post-discharge. Group-Based Trajectory Modelling (GBTM) was used to identify the trajectories, while network analysis was used to explore interconnections among these trajectories and dyadic burdens components. Expected Influence (EI) was utilized to identify core nodes within the network. Three co-joint trajectories were identified: mild disorder (27.4%), moderate disorder (58.9%), and severe disorder (13.7%), with significant demographic differences noted among groups. The five most core nodes in the network were personal burden (EI = 1.19), role burden (EI = 1.07), dyspnoea when lying down (EI = 0.83), daytime dyspnoea (EI = 0.38), and difficulty sleeping (EI = 0.36). The nodes most strongly associated with anxiety and depression trajectories included chest pain, fatigue, and dizziness. Sensitivity analysis affirmed the findings’ robustness. Conclusion: Anxiety and depression co-joint trajectories among patients with HF and caregivers showed heterogeneity, with core constructions identified for future intervention studies to reduce dyadic burdens and improve the adverse development of anxiety and depression. Registration: ChiTR ChiCTR2400088241.