Objective: To analyze the current situation of adolescent depressive symptoms in singleparent families in Jianyang City, and to construct and verify the early warning model, so as to provide a scientific basis for the government to formulate a plan of promoting the development of adolescent mental health. Methods: A stratified cluster random sampling method was used to select 12 125 middle and high school students from 25 middle schools in Jianyang City from March 2022 to October 2023 for an anonymous selffilling questionnaire survey, and a total of 1 142 adolescents from valid singleparent families were obtained as the survey objects. They were randomly divided into the training set (914 participants) and the verification set (228 participants) according to the ratio of 8∶2. The Chinese version of Beck depression Inventory (BDI) was used to evaluate depressive symptoms among adolescents from singleparent families in Jianyang City. The factors related of depressive symptoms in adolescents from singleparent families were analyzed, and a prediction model was established to verify the model and evaluate its effectiveness. Results: There were 158 adolescents (17.29%) in the training set and 43 adolescents (18.86%) in the verification set with depressive symptoms. Multivariate Logistic regression analysis showed that learning stress (OR=4.31, 95%CI=1.67-11.13), Connor-Davidson Resilience Scale (CDRISC) score (OR=0.29, 95%CI=0.12-0.71) and Family Adaptability and Cohesion Scale (FACESⅡ) scores (OR=0.19, 95%CI=0.06-0.63) were all related factors the occurrence of depressive symptoms in adolescents from singleparent families (P<0.05). The results showed that the C-index was 0.80 (95%CI=0.75-0.80), and the correction curve for predicting the occurrence of depressive symptoms in singleparent families was close to the ideal curve (χ2=0.26, P>0.05). Receiver operating characteristic (ROC) curve results of the training set showed that the sensitivity and specificity of the nomogram model in predicting depressive symptoms in adolescents from singleparent families were 80.38% and 80.03% respectively, ROC area under the curve (AUC) was 0.84 (95%CI=0.76-0.92). The ROC curve results of the verification set showed that the sensitivity, specificity and AUC of histogram model to predict depressive symptoms in adolescents from singleparent families were 79.07%, 82.16% and 0.83 (95%CI=0.76-0.91). Conclusions Learning stress, mental resilience and family function are all factors that affect the occurrence of depressive symptoms in adolescents from single parent families in Jianyang City. Based on this, the early warning model can predict depressive symptoms in Jianyang City.

ObjectiveTo explore the risk factors of stroke， and to provide reference for the prevention and health management of stroke. MethodsFrom February 2022 to March 2022， four community residents over 60 years old with stroke in Shanghai were randomly selected as the case group （n=100）， and non-stroke residents were selected as the control group （n=100）. The survey was in the form of questionnaires to record and compare the age， body mass index （BMI）， blood lipids， blood pressure-related indicators， family history of other diseases， living habits， mood and sleep conditions of all subjects. The value of predicting the incidence of stroke among the elderly in Shanghai community was analyzed by receiver operating characteristic （ROC）， and the influencing factors of stroke were analyzed by logistic model. ResultsBMI， hypertension， heart disease， diabetes， transient ischemic attack （TIA）， dyslipidemia， family history of stroke， smoking， lack of exercise or only light physical labor， SBP， DBP， TG levels were significantly higher in the case group （P<0.05）. The level of HDL-C was significantly lower than that in the control group （P<0.05）. BMI， SBP， DBP， TG， HDL-C predicted the incidence of stroke by ROC analysis （P<0.05）. Logistic regression analysis showed that BMI≥23.820 kg·m^-2， heart disease， diabetes， TIA， dyslipidemia， family history of stroke， smoking， lack of exercise or only light physical labor， SBP≥139.535 mmHg， DBP≥89.605 mmHg， TG≥1.565 mmol·L^-1 and HDL-C≤1.105 mmol·L^-1 were risk factors for stroke （P<0.05）. ConclusionPhysical health status including blood lipids and blood pressure， family history of certain diseases， and living habits could be important risk factors for stroke in the elderly in Shanghai community. Preventive intervention measures for the above factors have important clinical significance.