Objective To construct a trajectory model for the changes in body roundness index(BRI)of elderly people in China from 2011 to 2018 based on the data derived from Chinese Longitudinal Healthy Longevity Survey(CLHLS),and analyze the influencing factors of different BRI trajectories.Methods Based on the longitudinal cohort data from the CLHLS platform,group-based trajectory model(GBTM)analysis was used to construct longitudinal change trajectories of 3 waves of BRI(2011,2014,and 2018)that meet our research criteria.Unordered multinomial logistic regression analysis was employed to identify the influencing factors of different BRI trajectories.Results A total of 2 512 valid samples were included in the analysis.The BRI trajectory of Chinese elderly people fitted by GBTM was optimally grouped into low-,medium-,and high-level growth trajectory models.There were statistically significant differences among different BRI trajectory groups in gender,length of education,resident place,living with spouse,retirement pension,sleep quality,smoking history,drinking history,continuous exercise,frequency of fruit consumption,frequency of salt-preserved vegetables consumption,and"fruit+protein"dietary patterns(P<0.05).Disordered multiclass logistic regression analysis found that,using the low-level growth trajectory model as a reference,males and those with a history of smoking were less likely to exhibit moderate to high growth levels of BRI trajectories;Elderly people with retirement pensions were more likely to exhibit a moderate to high growth level of BRI trajectory;People with a history of alcohol consumption were more likely to exhibit a moderate steady growth level of BRI trajectory;People with longer than 10 years of education were less likely to exhibit a high level of growth in the BRI trajectory,while urban residents and those who frequently consumed fruits and salted vegetables were more likely to exhibit a high level of growth in the BRI trajectory.Conclusion The trajectory of BRI changes among elderly people in China from 2011 to 2018 can be divided into 3 groups,which are influenced by multiple factors such as gender,resident place,and length of education.It is necessary to pay attention to and make measures in advance to improve the quality of life in the elderly.Countermeasures It is advisable to incorporate BRI as a core indicator in elderly health monitoring systems,establish a dynamic management mechanism for high-risk populations,and implement precision-targeted lifestyle interventions and health guidance.

With the continuous progress of research methodology in the real world and the growing maturity of artificial intelligence technology， a method for conducting “quantitative” research to guide clinical practice based on traditional Chinese medicine （TCM） diagnosis and treatment data was gradually developed. However， there is still a need for further improvements in the overall design of studies and the transformation of findings into clinical practice. Based on this， we put forward a comprehensive overall design concept and application approach for real-world study and artificial intelligence research based on clinical diagnosis and treatment data of TCM. This approach consists of five steps： Constructing a research-based database with a large sample size and high data quality； Mining and classification of core prescriptions； Conducting cohort studies to evaluate the effectiveness of core prescriptions； Utilizing case-control studies to clarify the dominant population； Establishing predictive models to achieve precision medicine. Additionally， it is imperative for researchers to establish a standardized system for collecting TCM variables and processing data， optimize the determination and measurement methods of confounding factors， further improve and promote methodologies， and strengthen the training of interdisciplinary talents. By following this research method， we anticipate that the clinical translation of research findings will be facilitated， leading to advancements in TCM precision medicine. Real-world study and artificial intelligence research share similar research foundations， and clinical applications complement each other. In the future， the two will merge together.

Objective:To evaluate the effects of sensomotor insole (SMI) on gait and energy expenditure in children with spastic cerebral palsy during walking. Methods:From December, 2014 to March, 2016, 42 children with spastic cerebral palsy aged three to 15 years were recruited. Their gait parameters and energy expenditure of six minute walking were measured under two test conditions: walking with shoes and walking with shoes and SMI. Results:After wearing SMI, the walking distance, speed, left step length and right step length were all greater (t = -6.022~-4.331, Z= -4.814~-4.183, P < 0.001), the both feet single limb support was shorter (t = 2.954, P < 0.05), and the energy expenditure was higher than before (t = -2.358, P < 0.05). Conclusion:SMI as a sort of orthopedic insole, could improve the gait parameters of children with cerebral palsy immediately after wearing it, and increase the energy expenditure slightly.