Objective: To understand the early life factors that influence cardiometabolic risk factors in children and adolescents, so as to provide effective measures to curb cardiometabolic risk factors such as hypertension and diabetes in children and adolescents. Methods: Data were sourced from the 2020 follow up survey of the Xiamen Adolescent Development Cohort. The study involved 1 197 subjects for whom completed anthropometric examination and blood biochemistry testing data, as well as early life data. Early life and sociodemographic data were obtained through questionnaire surveys, while cardiometabolic indicator data were sourced through physical examinations and blood testing. Logistic regression analysis was performed to analyze the impact of early life factors on the cardiometabolic risk factors after adjusting for gender, age, and family history. Results: The prevalence rate of cardiometabolic risk factors clustering in children and adolescents in Xiamen was 17.96%, with boys (26.67%) reporting higher rates than girls (9.64%), and the difference was statistically significant ( χ 2=57.69, P <0.01). For every additional early life risk factor, the risk factors of obesity increased 0.35 times ( OR=1.35, 95%CI=1.03-1.78, P <0.05). Post term pregnancy may be a primary early life risk factors for cardiometabolic risk factors, and it was associated with an increased risk of cardiometabolic risk factors clustering (OR=2.45, 95% CI =1.11-5.41) and high triglycerides ( OR=3.25, 95%CI =1.39-7.61)( P <0.05). Conclusion Increased cardiometabolic risk factors in youth is associated with early life adverse factors. It is crucial to pay greater attention to post term pregnancy as an early life factor and to consider obesity as a cardiometabolic risk factors. Controlling early life adverse factors is important for the prevention of cardiovascular disease.

Objective: To understand the current status of obesity and high blood pressure (HBP) comorbidity and their multidimensional influencing factors in children aged 7-12 years in Xiamen, so as to provide reference basis for subsequent preventive measures. Methods: Based on the baseline survey of the Xiamen pubertal development cohort in 2017, a total of 4 798 primary school students from second to sixth grade were selected in the study by cluster random sampling method. And physical examination and questionnaires were conducted. The Logistic regression was used to screen potential variables for obesity combined with HBP. A multivariate Logistic regression model was used to analyse the factors influencing obesity combined with HBP. Results: About 9.15 % children were found with obesity and 11.65% with HBP. The rate of obesity combined with HBP was 3.00% in boys and 1.80 % in girls. The rate of HBP was 8.28% in normal weight children and 26.88% in obese children. Multivariate Logistic regression models showed that consumption of sugary drinks at least once a week ( OR =2.50), daily consumption of salted or pickled vegetables ( OR =4.52), family history of obesity ( OR =3.09) were positively associated with obesity combined with HBP ( P <0.05). Girls ( OR =0.53), consumption of highenergy snacks at least once a week ( OR =0.40) and adequate physical activity ( OR =0.58) were negatively associated with comorbidity of obesity and HBP ( P <0.05). Conclusion Gender differences in comorbidity burden of obesity and HBP exist among children aged 7-12 years in Xiamen. Dietary behaviour and exercise behaviour are the main dimensions influencing the comorbidity of obesity and HBP. Prevention and control of obesity and HBP in children should be based on multiple dimensions, including diet and exercise behavioural environment, to prevent early the occurrence for comorbidity of obesity and HBP in children.

Objective: To investigate the prevalence of Internet addiction and depression of students, and to analyze the co-occurrence and trend, so as to provide a theoretical basis for prevention and controlling measures of Internet addiction and depression. Methods: A total of 6 317,7 152,81 808,71 180 and 89 932 students aged 10 to 24 years from 12 leagues (103 banners) in Inner Mongolia Autonomous Region were selected by stratified random cluster sampling in September each year from 2017 to 2021. The Internet Addiction Scale and the Central for Epidemiologic Studies Depression Scale(CES-D) was used to measure Internet addiction and depression. And the annual inspection rate, group difference and annual change trend in students were calculated. Multivariate linear regression and restricted cubic spline analysis were used to estimate the linear and non linear associations between Internet addiction and depression in students. Results: The Internet addiction proportion in students gradually decreased from 4.1% in 2017 to 2.1% in 2020, but increased to 3.9% in 2021. And the depressive symptoms proportion increased from 20.9% in 2017 to 28.0% in 2020 and 27.0% in 2021. The detection rate of Internet addiction and depression comorbidities remained at 1.8% to 2.5 %. The Internet addiction proportion in boys was higher than that in girls( χ 2=42.82， P <0.05). The depressive symptoms prevalence in girls was higher than that in boys( χ 2= 553.90， P <0.05). Taking reversal in prevalence of Internet addiction in urban and rural areas was observed in 2019. The detection rates of depressive symptoms and comorbidity were higher in urban areas than these in suburban counties on the whole, and the difference showed a trend of decreasing or even equalizing year by year. Internet addiction was positively correlated with depressive symptoms score ( B=1.67, 95%CI =1.64-1.71), the proportion of depressive symptoms ( OR=1.39, 95%CI =1.38-1.41) and the proportion of major depressive symptoms ( OR=1.35, 95%CI =1.33-1.36) among students in 2021 ( P <0.05). An N-shaped curve was found in the significant nonlinear associations between internet addiction and depression across sex, region and school stage. Conclusion Internet addiction and depression in students show significant linear and non-linear associations, which are consistent in different sexes, regions and school stages. Therefore, relevant measures should be made and implemented in each region, especially in suburb areas, so as to prevent the increasingly development of adolescents and children s Internet addiction and depression.