Globally, the high consumption levels of sugar-sweetened beverages (SSBs) and their effect on health have drawn significant attention. This study aimed to identify the consumption patterns of SSBs among children in rural areas of Guangzhou, China, and explore their association with undernutrition. A total of 1864 children aged 9–17 years old were included in this study. Demographics, lifestyle behaviors, and anthropometric and dietary information were collected. Factor analysis was used to identify patterns of SSBs, while nutritional status was assessed using Body Mass Index (BMI). Latent class analysis was used to establish dietary preference models. Log-binomial regression analysis was used to analyze the association between SSBs consumption patterns and undernutrition. The undernutrition prevalence in children was 14.54–19.94% in boys and 9.07% in girls. Three SSB consumption patterns were identified, including the plant protein pattern, dairy-containing pattern, and coffee pattern. Both medium-high (Q3) and the highest (Q4) scores in the dairy-containing pattern were positively associated with the risk of undernutrition, especially in boys. Furthermore, the highest scores in the plant protein pattern and coffee pattern were positively associated with the risk of undernutrition in children aged 9–10 years old. The dairy-containing pattern was a risk factor for undernutrition in children, especially for boys; the plant protein patterns and coffee patterns were risk factors for undernutrition in children aged 9–10 years old. The findings of the study can provide scientific evidence and policy recommendations for improving children’s health conditions.

Background: Childhood obesity is a major public health challenge in the 21st century, and diet is one of the key modifiable factors in its prevention. This study examined the link between dietary patterns of children and general and central obesity, including the role of C-reactive protein (CRP). Methods: This study enrolled 2413 children aged 9–17. Anthropometric measurements, CRP levels, and dietary data were collected. Factor analysis identified dietary patterns, and logistic regression examined the association between CRP levels and childhood obesity. Multiple linear regression determined the correlation between dietary patterns and CRP. Mediation analysis assessed the role of CRP in the link between dietary patterns and childhood obesity. Results: Three dietary patterns were identified. The rice and meat pattern was significantly correlated to the risk of childhood obesity (OR = 1.166, 95%CI: 1.000, 1.359 for general obesity; OR = 1.215, 95%CI: 1.071, 1.377 for central obesity). CRP was positively correlated with childhood obesity risk (OR = 2.301, 95%CI: 1.776, 2.982 for general obesity; OR = 2.165, 95%CI: 1.738, 2.697 for central obesity). The fruit and vegetable pattern was inversely related to CRP (β= −0.059, 95%CI: −0.081, −0.036), while the snack pattern was positively correlated (β= 0.043, 95%CI: 0.020, 0.065). CRP had a suppressive effect on the association between the fruit and vegetable pattern and snack pattern with childhood obesity. Conclusions: This study revealed the rice and meat pattern as a risk factor for childhood obesity, and cross-sectional evidence linked the fruit and vegetable pattern and snack pattern to childhood obesity risk, mediated by CRP.

Background: Elevated serum uric acid (SUA) levels in young people have become a significant public health concern. Dietary habits are a key factor influencing SUA levels. This study aimed to investigate dietary patterns (DPs) of children and adolescents and their associations with SUA. Methods: This cross-sectional study included children and adolescents in Guangzhou, China. We used structured questionnaires to collect data on demographics, lifestyle, and dietary intake, and we collected blood samples for biochemical analysis. DPs were identified by factor analysis. We used robust linear regression to examine the association between these patterns and SUA levels. Parallel mediation analysis was utilized to assess the mediating role of body mass index (BMI) Z-score and waist circumference (WC). Results: The study encompassed 4100 children and adolescents between ages 9–17. The median SUA level was 374 (IQR: 319, 438) μmol/L and the prevalence of hyperuricemia was 41.7%. We identified four DPs, including plant-based, snack–beverage, highprotein, and meat–carbohydrate patterns. There was a positive correlation between the meat–carbohydrate pattern and SUA (β = 3.67 μmol/L, 95% CI: 1.22–6.12). The Q4 group of the highprotein pattern was associated with higher SUA levels (9.17 μmol/L, 95% CI: 2.41–15.93) compared to the Q1 group. BMI Z-score and WC mediated the association between the meat–carbohydrate pattern and SUA. Conclusions: Our findings suggest that BMI Z-score and WC mediated the association between the meat–carbohydrate pattern and SUA. This study emphasizes the significance of targeted dietary interventions for weight control in addressing the increasing SUA levels in children and adolescents. Future research could focus on exploring the molecular mechanisms, developing personalized dietary intervention programs, and conducting multicenter prospective cohort studies.