Objective To understand the trajectory and classification of adult body mass index(BMI)in Jiangsu Province.Methods Based on China Health and Nutrition Survey,this study used the linear mixed model tree to explore the trajectory and classification of BMI of people aged 18-65 in Jiangsu Province.Results The linear mixed model tree had 13 nodes and the depth was 6.The classification nodes were baseline BMI,average calorie intake and baseline age.Conclusion The linear mixed model tree can identify the trajectory of BMI and expand the research method of longitudinal data.

Objective To evaluate the risk factors and sonographic findings of pregnancies complicated by placenta increta or placenta percreta. Methods Totally, 2219 cases were retrospectively analyzed from 20 tertiary hospitals in China from January 2011 to December 2015. The data were collected based on the original case records. All cases were divided into two groups, the placenta increta (PI) group (79.1％, 1755/2219) and the placenta percreta (PP) group (20.9％, 464/2219), according to the degree of placental implantation. The risk factors and sonographic findings of placenta increta or percreta were analyzed by uni-factor and logistic regression statistic methods. Results The risk factors associated with the degree of placental implantation were age, gravida, previous abortion or miscarriage, previous cesarean sections, and placenta previa (all P<0.05), especially, previous cesarean sections (χ2=157.961) and placenta previa (χ2=91.759). Sonographic findings could be used to predict the degree of placental invasion especially the boundaries between placenta and uterine serosa, the boundary between placenta and myometrium, the disruption of the placental-uterine wall interface and loss of the normal retroplacental hypoechoic zone(all P<0.01). Conclusions Previous cesarean sections and placenta previa are the main independent risk factors associated with the degree of placenta implantation. Ultrasound could be used to make a prenatal suggestive diagnosis of placenta accreta spectrum disorders.