China News Service, Beijing, July 17 (Reporter Sun Zifa) Springer Nature's open access academic journal "Science Report" recently published a public health research paper saying that a research team in Yantai, Shandong, China adopted a predictive model developed by The body mass index (BMI) of Chinese children can be predicted 5 years in advance, with an accuracy rate of 70%, or it can be used to identify children with a higher risk of obesity.
The prediction model found that the local obesity rate for children aged 6-11 years will increase by 2023. The paper also specially reminds that since all the data of the prediction model are all from the same province, the generality of the results may be limited.
Corresponding author of the paper, Xu Jinjie and colleagues at the Yantai Center for Disease Control and Prevention in Shandong Province collected data on 45,540 boys and 43,440 girls aged 6-11 years old in Yantai from 2013 to 2018, and divided all children according to their BMI Four groups: low weight (2940 people), normal weight (48924 people), heavy weight (15278 people), and obesity (21838 people).
The research team found that of the children who were classified as obese in 2013, 65% of the children were still in the obese group by 2018, while only 13% and 22% of the children from the obese group entered the normal-weight group and the weight-recombination group. . They also found that the risk of being overweight or obese among boys, taller, and urban children also tended to be higher.
Based on these results, the research team developed a computer algorithm to predict the risk of overweight and obesity of all children in the study by 2023. The model shows that without any intervention, the obesity rate for 6-11 year old boys in rural areas will increase from 22% to 26% and girls from 14% to 16%; the obesity rate for children in urban areas is expected to remain unchanged .
The results of this study indicate that a weight development trend may be formed early in childhood, and this trend will be accompanied by a lifetime. The team’s predictive model may help find out which children can benefit from primary school interventions and reduce their incidence of obesity during adolescence and adulthood. (Finish)