The Impact Mechanism Of Urban Park Features On Users’ Recreation Physical Activity

Urban parks are important activity places for urban residents in their spare time,as well as the main carriers for recreational physical activities.Appropriate physical activity is an effective way to prevent chronic diseases.This study obtained the park characteristics of 5parks(Yangling Arboretum,Jiaojia Garden,Houji Park,Convention and Exhibition Center Green Space,and Yangling Weihe Wetland Park)in the main urban area of Yangling Demonstration Zone,Shaanxi Province through field research.Through random structured interviews with park visitors,a total of 1,099 park users’ demographic characteristics,physical activity data and Body Mass Index data were obtained.The chi-square test,non-parametric test,Pearson correlation test and other statistical methods are used to analyze the correlation between park characteristics and user behaviors.By constructing a linear regression model and a logistic regression model,the study explores the influence mechanism of park characteristics on park users’ recreational physical activities.Results indicates that:(1)There is a significant difference in the per capita MET of the park.Park users have the highest activity intensity in the green space of the convention and exhibition center,and the lowest activity intensity in the arboretum.The green space of the convention and exhibition center has the highest attraction for users to perform higherintensity physical activities.(2)Among all adult interviewees,326 were overweight,accounting for 32.83%.They may have a risk of obesity.There are 134 retirees who are overweight,accounting for 41.1% of all overweight people.28 mental workers are overweight,ranking second in proportion.(3)Construct a multiple linear regression model,and get the regression equation: MET=4.062+0.017×(number of professional sports courts)-0.108×(number of multifunctional sports squares).The number of professional courts and multifunctional sports squares can have an impact on personal MET,and the impact coefficients are 0.017 and-0.18,respectively.(4)Constructing a multiple linear regression equation found that the BMI of visitors to medium-sized parks and large-scale parks was significantly lower than that of small-scale parks(convention center green space).(5)Through binary logistic regression fitting,the regression equation is obtained: logit(p)=-0.109+0.016×(number of professional sports courts)-0.088×(number of multifunctional sports squares).(6)Establish an ordered logistic regression model.The number of professional sports courts will have a significant positive impact on the intensity of physical activity.The number of multifunctional sports square will have a significant negative impact on the intensity of physical activity.