Search

Objective To explore the relationship between Chongqing residents' characteristics and fit-ness behavior and the influencing factors of fitness behavior. A and to seek effective ways to motivate residents fitness behavior and so as to help residents form good exercise habits and improve the development of physical and mental health. Methods Residents aged 18-065 in Chongqing were selected as research objects. A 15-items questionnaire was carefully designed,involving the gender, age marital status, children's situation, education background occupation status, frequency of physical exercise, sports activities and other key indicators of the interviewees. In the process of analysis, the basic situation of residents' fitness was illustrated intuitively with the help of charts, and the influencing factors of residents' project selection were analyzed by logistic regression model. Results The residents in Chongqing mostly spent 30.--60 minutes (41. 48% ) on fitness, with purposes of fitness was to be body build (63. 57%) and keep fit (42. 50%). The amount of fitness expenditure was generally not high. Participants in different projects were obviously differentiated in terms of gender, fitness period, fitness frequency. fitness purpose, weekly fitness duration. etc. and the life status of each project was different. For example participants of the big-ball project were mostly male aged between 21 and 35 .and the fitness time was more than 60 minutes each time. Conclusion Participants of different fitness projects have obvious differences in gender,age. fitness frequency, fitness purpose, fitness period. fitness duration and other factors that combine personal basic situation, life status and fitness needs. Different sports are suitable for different life status, such as running, gym exercises and ball sports are still the most favorite sports activities among men and women, and ball sports are especially popular among boys. Mainly with the individual alone exercise and friends exercise together. [ABSTRACT FROM AUTHOR]

Objective To establish a mathematical diagnostic model of Alzheimer's disease (AD) and mild cognitive impairment (MCI) with a higher accuracy. Methods Taking the four selected indexes as input variables, 391 samples were randomly divided into the training set and the testing set. Generalized regression neural network (GRNN) was used for parameter training and simulation diagnosis in the training set and the testing set respectively, and the diagnosis effects were compared with those of BP neural network (BPNN), ra-dial basis function neural network (RBFNN) and perceptron neural network (PNN). Results The diagnostic accuracy rate of GRNN for the three groups of people was significantly higher than that of BPNN, RBFNN and PNN, the differences were statistically significant (P <0. 05). When the optimal smoothing factor of GRNN was 1. 5, the diagnostic accuracy rate of 391 samples reached 75. 7%. Conclusion The GRNN model has good diagnostic effect on AD and MCI, which can be used as an auxiliary means of clinical diagnosis. [ABSTRACT FROM AUTHOR]