Objective To investigate the status of work fatigue of the disabled and the healthy so that we get to know their employment quality and compressive strength, and then provide the theory basis for the national policy formulation and vocational rehabilitation. Methods We randomly investigated 280 employees (220 disabled, 60 healthy people) in 3 companies from 3 provinces with Fatigue Impact Scale (FIS). Results There was no statistically significant difference between disabled and healthy people about work fatigue, and also that of 3 domains including psycho-social, cognitive and physical activity. After comparison of 40 items on FIS，the disabled had higher fatigue than that of the healthy in 4 items which belonged to psycho-social domain (P<0.05). Conclusion Disabled people are no less than healthy people in compression capability and working capability. They should believe in themselves, and their family and the employees should have more confidence about their work capability than before. Government should provide some support with them on job retention.

Objective: To analyze the association between physical activity and screen time with overweight and obesity in preschool children, and to provide evidence for childhood obesity prevention and control. Methods: Using a case control study design, 109 overweight or obese children (the case group) were recruited from four kindergartens from a community of Chaoyang District, Beijing, and 117 children with normal weight in the same kindergarten (the control group) were recruited as control. Gender and age were matched between the case and the control group. Univariate analysis was used to compare the demographics, physical activity time, screen time, sleep and diet characteristics between the two groups. Logistic regression was used to analyze the association of physical activity and screen time with overweight and obesity in preschool children with adjustment for covariates. Results: After adjusting for age, gender, average daily sleep time, the total score of Children s Sleep Habits Questionnaire (CSHQ), Chinese diet balance index for preschool children (DBI-C), children with <3 h of daily physical activity had an increased risk of overweight and obesity compared with those with ≥3 h of physical activity ( OR=2.55,95%CI=1.16-5.64，P =0.02), and the risk of overweight and obesity increased with each additional quartile of daily screen time in children ( OR=2.44,95%CI=1.69-3.52, P <0.01). Conclusion Insufficient physical activity and excessive screen time are independent risk factors of overweight and obesity in preschool children. Comprehensive intervention measures should be taken to effectively increase physical activity and reduce screen time for overweight and obesity prevention and control in preschool children.

Objective:To examine the associations of pre-pregnancy body mass index (BMI), gestational weight gain, and gestational diabetes mellitus (GDM) with early childhood BMI trajectories.Methods:A total of 1 227 mother-child pairs from the Peking University Birth Cohort in Tongzhou were included in this study. In the cohort, maternal pre-pregnancy weight, height, gestational weight gain, and GDM diagnosis were collected. The children were followed up at birth and at 1, 3, 6, 9, 12, 18, 24, 30, and 36 months of age to obtain height/length and weight data. The longitudinal data-based k-means clustering algorithm was used to identify early childhood BMI trajectory groups. The associations of maternal pre-pregnancy BMI, gestational weight gain, and GDM with early childhood BMI trajectories were analyzed using the logistic regression model. We further explored whether there is an interaction effect between pre-pregnancy overweight/obesity and excessive gestational weight gain on the risk of the high BMI trajectory in early childhood through multiplicative and additive interaction analyses. Results:The prevalence rates of overweight and obesity before pregnancy were 21.2% (260 cases) and 6.6% (81 cases) respectively. The prevalence of excessive gestational weight gain and GDM was 57.7% (708 cases) and 30.9% (379 cases). The early childhood BMI trajectories were named low, medium, and high trajectories, accounting for 30.5%, 45.4% and 24.1%, respectively. After controlling potential confounding factors, it was found that pre-pregnancy overweight ( OR=1.54, 95% CI: 1.12-2.12), obesity ( OR=2.33, 95% CI: 1.41-3.85), and excessive gestational weight gain ( OR=1.47, 95% CI: 1.10-1.97) were risk factors for being in the high BMI trajectory in early childhood. GDM was not significantly associated with early childhood BMI trajectories ( P>0.05). Compared with the independent effects of pre-pregnancy overweight/obesity ( OR=1.90, 95% CI: 1.17-3.09) and excessive gestational weight gain ( OR=1.45, 95% CI: 1.03-2.04), the risk of being in the high BMI trajectory in early childhood was greater when the two factors coexisted ( OR=2.38, 95% CI: 1.60-3.54). However, both the multiplicative and additive models showed no interaction effect between pre-pregnancy overweight/obesity and excessive gestational weight gain. Conclusions:Maternal pre-pregnancy overweight/obesity and excessive gestational weight gain are independent risk factors for children being in the high BMI trajectory in early childhood, providing scientific evidence for obesity prevention.

Objective:To compare the association between body mass index(BMI)trajectories deter-mined by different methods and the risk of overweight in early childhood in a prospective cohort study,and to identify children with higher risk of obesity during critical growth windows of early childhood.Methods:A total of 1 330 children from Peking University Birth Cohort in Tongzhou(PKUBC-T)were included in this study.The children were followed up at birth,1,3,6,9,12,18,and 24 months and 3 years of age to obtain their height/length and weight data,and calculate BMI Z-score.Latent class growth mixture modeling(GMM)and longitudinal data-based k-means clustering algorithm(KML)were used to determine the grouping of early childhood BMI trajectories from birth to 24 mouths.Linear regres-sion was used to compare the association between early childhood BMI trajectories determined by different methods and BMI Z-score at 3 years of age.The predictive performance of early childhood BMI trajecto-ries determined by different methods in predicting the risk of overweight(BMI Z-score＞1)at 3 years was compared using the average area under the curve(AUC)of 5-fold cross-validation in Logistic regres-sion models.Results:In the study population included in this research,the three-category trajectories determined using GMM were classified as low,medium,and high,accounting for 39.7％,54.1％,and 6.2％of the participants,respectively.The two-category trajectories determined using the KML method were classified as low and high,representing 50.3％and 49.7％of the participants,respectively.The three-category trajectories determined using the KML method were classified as low,medium,and high,accounting for 31.1％,47.4％,and 21.5％of the participants,respectively.There were certain differ-ences in the growth patterns reflected by the early childhood BMI trajectories determined using different methods.Linear regression analysis found that after adjusting for maternal ethnicity,educational level,delivery mode,parity,maternal age at delivery,gestational week at delivery,children's gender,and breastfeeding at 1 month of age,the association between the high trajectory group in the three-category trajectories determined by the KML method(manifested by a slightly higher BMI at birth,followed by rapid growth during infancy and a stable-high BMI until 24 months)and BMI Z-scores at 3 years was the strongest.Logistic regression analysis revealed that the three-category trajectory grouping determined by the KML method had the best predictive performance for the risk of overweight at 3 years.The results were basically consistent after additional adjustment for the high bound score of the child's diet balanced index,average daily physical activity time,and screen time.Conclusion:This study used different methods to identify early childhood BMI trajectories with varying characteristics,and found that the high trajectory group determined by the KML method was better able to identify children with a higher risk of overweight in early childhood.This provides scientific evidence for selecting appropriate methods to de-fine early childhood BMI trajectories.