Chloramphenicol has been used in veterinary medicine, where its residues can remain in food of animal origin, thus potentially causing adverse health effects. This facilitated the ban for its use in food-producing animals globally, but its residues have remained ubiquitous. In this study, food commodities possibly contaminated with chloramphenicol, including livestock meat, poultry, edible viscera, fish, shrimp and crab, molluscs, milk, and eggs, were collected from domestic retail shops in all the 11 districts of Guangzhou and tested for its residue. Probabilistic risk assessment model calculations for its dietary exposure, and the margin of exposure (displayed as mean values and 5th percentile to 95th percentile ranges) were performed by using @RISK software based on a Monte Carlo simulation with 10,000 iterations. The results indicated the detection of chloramphenicol in 248 out of 1454 samples (17.1%), which averaged to a level of 29.1 μg/kg. The highest average value was observed in molluscs (148.2 μg/kg, with the top value as 8196 μg/kg); meanwhile, based on the dietary structure of a typical Cantonese, pond fish, pork, and poultry meat contributed most (about 80%) to the residents’ dietary exposure to chloramphenicol. The margin of exposure for dietary chloramphenicol exposure in Guangzhou residents was 2489, which was apparently below 5000 (the borderline for judging a health risk), particularly low in preschool children (2094, suggesting an increased risk). In conclusion, the study suggests that chloramphenicol exposure in Guangzhou residents is considerable, and its relevant health hazard, especially for preschool children, is worthy of further investigation.

Anemia affects 1.8 billion people worldwide, and diet is one of the key modifiable factors for treating anemia in children. The dietary pattern has changed rapidly in recent decades, but its effect on childhood anemia has not been reported. This study aimed to identify dietary patterns among children in rural areas of Guangzhou, China, and explore their association with anemia. A total of 1476 children aged 9–16 years old were included in this study. Demographics, lifestyle, and anthropometric and dietary information were collected. Factor analysis was used to identify dietary patterns, and anemia was diagnosed based on hemoglobin levels. Robust Poisson regression and subgroup analysis were used to analyze the association between dietary patterns and anemia. The prevalence of anemia in children was 10.4%, with 6.1% in boys and 15.4% in girls. Four dietary patterns were identified, including a fast food pattern, a vegetarian pattern, a meat and egg pattern, and a rice and wheat pattern. A high score in the fast food pattern was positively associated with risk of anemia in children entering puberty (PR = 1.767, 95% CI: 1.026~3.043, p = 0.039), especially in girls after menarche, with marginal significance (PR = 1.740, 95% CI: 0.977~3.097, p = 0.059). A high score in the meat and egg pattern was negatively associated with risk of anemia in children entering puberty (PR = 0.498, 95% CI: 0.286~0.866, p = 0.013), especially in boys after spermatorrhea (PR = 0.237, 95% CI: 0.031~0.590, p = 0.007). The fast food pattern was a risk factor for anemia in children, and the meat and egg pattern was a protective factor for anemia in children entering puberty. The findings of this study could be used to guide the strategies of evidence-based preventive nutrition interventions to curb anemia in children.

Cadmium and its compounds are human carcinogens with severe organ toxicity, and their contamination of agricultural soil in China has been frequently reported; however, the dietary exposure to cadmium in residents and the relevant health risk have seldom been reported. In this study, the concentration of cadmium in various types of food collected from 2013 to 2015 were analyzed using graphite furnace atomic absorption spectrometry, and the dietary exposure to cadmium assessed based on a dietary survey in 2976 Guangzhou residents. In total, 3074 out of 4039 food samples had cadmium levels above the limit of detection. The mean ± standard deviation (50th, 95th percentile) cadmium content in all samples was 159.0 ± 112.7 (8.6, 392.4) μg/kg, with levels ranging from 1.0 to 7830 μg/kg. Using the mean cadmium concentrations, the average monthly dietary exposure of Guangzhou residents to cadmium was 14.4 (μg/kg body weight (BW), accounting for 57.6% of the provisional tolerable monthly intake (PTMI). Rice, laver, vegetables, and live aquatic products were the main sources of cadmium intake, on average accounting for 89% of the total value. The dietary cadmium exposure in high consumers (95th percentile food consumption) was 41.0 μg/kg·BW/month, accounting for 163% of the PTMI. Additionally, dietary cadmium exposure at mean consumption but high cadmium food concentration (95th percentile) was 32.3 μg/kg·BW/month, corresponding to 129% of the PTMI. The level of dietary exposure to cadmium in most Guangzhou residents was within the safety limit, thus increased health risk from dietary cadmium exposure is low at present. However, continued efforts by local governments to monitor the levels of cadmium in the four main food categories contributing to exposure are necessary.

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: The global rise in childhood obesity has heightened its recognition as a major public health concern, with obesity being an independent risk factor for metabolic abnormalities. However, the metabolomics mechanisms linking pediatric obesity to metabolic abnormalities remain unclear.Methods: This case-control study utilized data from a 2023 cross-sectional survey of children aged 9–18 years in Guangzhou, China. A total of 246 participants were included, with 123 obese and 123 normal-weight participants matched for age and sex. Serum metabolomics profiling was performed via LC-MS. A dual machine learning approach combining penalized multivariable Least Absolute Shrinkage and Selection Operator (LASSO) regression and random forest with recursive feature elimination (RF-RFE) was employed to identify robust obesity-associated serum metabolites independent of metabolic abnormalities and logistic regression was employed to construct the obesity metabolomics signature (OB-MS) model. Multivariable logistic regression was used to assess the associations between the OB-MS and metabolic abnormalities and their components, including hyperglycemia, hypertension, hypertriglyceridemia, and reduced HDL-C.Results: Among 934 detected metabolites, 10 core metabolites were selected to construct the OB-MS, which showed high discriminative power, with an ROC-AUC of 0.986 in the testing set. Elevated OB-MS scores were significantly associated with increased risks of metabolic abnormalities, particularly hypertension and hypertriglyceridemia. Additionally, six key metabolites, including oxidative stress markers and dipeptides, were independently associated with metabolic abnormalities.Conclusions: This study established a pediatric obesity-specific metabolomics signature (OB-MS), implicating oxidative stress, protein catabolism, and glucocorticoid metabolism in obesity-related metabolic abnormalities. These finding illustrate the metabolic mechanisms underlying the relationship between childhood obesity and metabolic abnormalities and provide new scientific support for early and precise prevention of metabolic abnormalities in children. Further longitudinal studies and experimental validation are warranted to elucidate its biological mechanisms and clinical utility.