[Association between different growth patterns and metabolic syndrome in children and adolescents aged 7 to 17 years].

Objective: To analyze the association between different growth patterns and metabolic syndrome in children and adolescents aged 7 to 17 years, and to provide suggestions for the prevention and control of metabolic syndrome in Chinese children and adolescents.

Methods: Data were collected from the research project "Development and Application of Technology and Related Standards for Prevention and Control of Major Diseases among Students" of public health industry in 2012. This project is a cross-sectional study design. A total of 65 347 students from 93 primary and secondary schools in 7 provinces including Guangdong were selected by stratified cluster random sampling method. Given the budget, 25% of the students were randomly selected to collect blood samples. In this study, 10 176 primary and middle school students aged 7 to 17 years with complete physical measurements and blood biochemical indicators were selected as research objects. Chi-square test was used to compare the distribution differences of growth patterns under different demographic characteristics. Birth weight, waist circumference and blood biochemical indexes were expressed in the form of mean ± standard deviation, and the differences among different groups were compared by variance analysis. Binary Logistic regression model was used to analyze the relationship between different growth patterns and metabolic syndrome in children and adolescents aged 7 to 17 years.

Results: The prevalence of metabolic syndrome in children and adolescents was 6.56%, 7.18% in boys and 5.97% in girls. The risk of metabolic syndrome was higher in the catch-down growth group than in the normal growth group ( OR =1.417, 95% CI : 1.19-1.69), and lower in the catch-up growth group( OR =0.66, 95% CI : 0.53-0.82). After adjusting for gender, age and so on, the risk of developing metabolic syndrome in the catch-down growth group was higher than that in the normal growth group ( OR =1.25, 95% CI : 1.02-1.52), but there was no significant difference between the catch-up growth group and the normal growth group ( OR =0.79, 95% CI : 0.62-1.01). Stratified analysis showed that the association between different growth patterns and metabolic syndrome was statistically significant in the 7-12 years group, urban population, and Han Chinese student population.

Conclusion: There is a correlation between different growth patterns and metabolic syndrome in children and adolescents. The risk of developing metabolic syndrome in children and adolescents with catch-down growth is higher than that in the normal growth group, which suggests that attention should be paid to the growth and development of children and adolescents, timely correction of delayed growth and prevention of adverse health outcomes.