The Influence of Walking environment on the Sports Participation Willingness and Physiological and psychological health of Urban Residents: Evidence from Western China

The Influence of Walking environment on the Sports Participation Willingness and Physiological and psychological health of Urban Residents: Evidence from Western China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Influence of Walking environment on the Sports Participation Willingness and Physiological and psychological health of Urban Residents: Evidence from Western China Li Liu, Tingran Zhang, Yongsen Liu, jiong luo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3996575/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective To explore the impact of community walking environment on residents' willingness to participate in sports and health status in western China's urban communities. Methods this study takes the layout of community fitness paths in the Chengdu-Chongqing Economic Zone community of western China as the survey object, and uses SPSS 21.0 statistical analysis software to process the obtained database. Results The choice of fitness path is not related to the gender and personal income of residents, but rather to their educational level, occupational category, and age; The exercise willingness of residents is influenced by factors such as the safety of the exercise path, the safety of the surrounding environment, residential density, accessibility of public facilities, the quality of the path facilities, the path landscape, and the size of the space. Conclusion The exercise willingness is the most important factor affecting the physiological and psychological health of residents. Improving the exercise obstacles in the walking environment and further ensuring the safety of the exercise process and fitness facilities is the key to enhancing the exercise willingness of residents. sports participation Physical health Path environment Willingness to exercise Physical and mental health Introduction The environment plays a key role in the causes of human illness. Although modern developed medical technology can delay death, it cannot change the important factor of illness, that is, the slow influence of the environment [ 1 , 2 , 3 ]. In 1998, the Alma-Ata Declaration of the World Health Organization emphasized the implementation of the national participation strategy to create a permanent healthy environment, and then started the national attention to the impact of the living environment on health. With the rapid growth of China's economy, the urbanization speed is faster and faster. Now, the natural elements in the first and second tier cities are increasingly reduced due to population concentration and urban development; At the same time, the driving or parking of a large number of motor vehicles will occupy the fitness activity space of urban community residents, reducing the area of green garden roads, park green space and open space, resulting in the inability of community residents to walk from their homes to nearby fitness paths and park activities, the inability of day students to walk to and from school, and the difficulty of the elderly to walk to open space activities. If residents want to go to the surrounding leisure and fitness venues for exercise, they often need to rely on motor vehicles to achieve, which greatly reduces the opportunities for urban residents to go out of outdoor activities, thereby increasing the incidence of psychological diseases. Fitness paths arose in the 1980s in economically developed countries in Europe and the United States. The vast majority of fitness paths are arranged in parks, green space, rivers and other places with good environment [ 4 , 5 ]. A kind of sport equipment is installed at intervals, and various equipment is connected by paths, so they are called fitness paths [ 6 ]. In June 1995, the State Council of China promulgated the Outline of the National Fitness Program. Since then, a series of laws and regulations have been issued, and mass sports and fitness for all have been able to develop along a healthy track [ 7 ]. The "National Fitness Plan", which aims to comprehensively improve the national physique and health level, focuses on young people and children, and advocates that all people should participate in more than one physical activity every day, learn more than two fitness methods, and conduct a physical fitness test every year. In order to implement the national fitness program and promote the development of urban and rural residents' fitness activities, the government has invested in the construction of national fitness centers and multi-function sports venues to provide venues, equipment, etc. for residents' fitness activities. The "national fitness path" is an important part of it [ 8 ]. Since the first fitness path was completed in Guangzhou in 1996, it has been rapidly extended to major urban planning in China as one of the four basic models of the national fitness project [ 9 ]. In 2007, General Administration of sport invested 30 million yuan to build 1000 fitness paths across the country; By 2010, the investment will be increased to 62.5 million yuan [ 10 ]. At present, under the guidance of national policies and guidelines, most urban and rural areas in China have built up community fitness paths, administrative village fitness paths, park fitness paths, etc. They are both fitness and fun, and are the best interpretation of the Communist Party of China’s(CPC)concept of governing for the people. Their purpose is to encourage Chinese people to make good use of these path facilities, integrate leisure and fitness activities into their daily life, so as to cultivate a healthy habit of engaging in regular sport, So as to strengthen the national physique. Today, 25 years after the promulgation of the national fitness program, the number of fitness paths in cities and towns in China has already exceeded tens of thousands. It has become one of the important public space leisure modes widely used by the whole people, and has been highly concerned by the majority of urban residents in China [ 11 ]. The author consulted the relevant literature on the "national fitness path" from 2005 to 2020, and obtained a total of 395 articles(365 in Chinese and 30 in English). Few scholars have discussed the impact of the path environment on the physical and mental health of residents. Based on many environmental factors that affect residents' leisure and fitness activities, in addition to the facility conditions of the path itself, it also includes urban design, accessibility of fitness paths, etc. From a few foreign reports, it is agreed that environmental factors in the leisure field will affect the frequency and time of people's activities [ 12 , 13 , 14 ]. In the face of the increasing problems such as the reduction of public open space, environmental pollution, energy consumption, people's physical and mental health and social aging in most cities in China, people's demand for walking environment is increasing in the future, and whether these path environment can support and increase the willingness of urban community residents to participate, and then benefit residents to improve their physical and mental health is indeed a topic worth exploring [ 15 ]. Chengdu Chongqing Economic Zone is the most important economic center, scientific and technological innovation center, new highland of reform and opening up, and livable place of high-quality life in western China [ 16 ]. In the 2022 National Fitness Trend Report, "People Love Fitness" released by People's Daily Online, Chengdu and Chongqing were both ranked among the top 10 "vigorous" cities in China [ 17 ]. Therefore, this study chooses Chengdu Chongqing Economic Zone as the representative of fitness cities in the western region, starting with its walking environment, and then reveals the impact of path environment on residents' willingness to participate in fitness activities and their physical and mental health, which can provide important reference for the suitability layout of fitness paths, parks and green spaces, schools, banks, mass transport stations and other facilities in future urban planning. Objects and methods Object determination Chengdu and Chongqing have 11 and 9 main urban areas respectively. First, they are ranked according to the gross domestic product (GDP) strength of each district, and then one district is randomly selected from the top 50% and the bottom 50%, that is, Chengdu and Chongqing each have two main urban areas. Finally, Jiangbei District and Shapingba District of Chongqing were selected, while Wuhou District and Chenghua District of Chengdu were selected. In order to ensure the representativeness of fitness paths, the fitness paths in the main urban areas are classified into four categories according to previous scholars' research [ 18 ]: community fitness paths, street fitness paths, sidewalk fitness paths and park green space fitness paths. Then, according to the relevant information provided by the planning office of the main urban areas of the four districts and the field survey by the members of the research team, 14 representative survey points were finally selected for each district, including 5 community paths, 5 street paths, 2 sidewalk paths, and 2 park greenbelt paths. In order to avoid the questionnaire measurement error caused by new residents' unfamiliar with the walking environment in the residential area, according to the research of Balfour JL, & Kaplan GA. (2002) [ 19 ], the longer they live, the more they can truly understand the local environmental conditions. Generally, they have been familiar with the local environment for more than 3 years. Based on this, in order to collect the subjects who really understand the environmental conditions of the adjacent path, the subjects are limited to two conditions: whether they have lived near the fitness path for more than 5 years and whether they are over 16 years old. The crowd who came to these fitness paths for fitness activities was investigated by using the method of squatting survey. A total of 6 investigation groups (3 people in each group) were established, and the stay time was 7:00–8:30 a.m. and 6:00–7:30 p.m. the whole investigation time was from March 15 to May 15, 2015, lasting for 2 months. Generally, the ratio of the total number of questionnaire items to the sample size should be greater than 10:1. Since the total items of the questionnaire used in this study are 79, the sample size should exceed 790 [ 20 ]. During the actual survey, 1171 questionnaires were distributed, 87 of which failed to answer key questions were deducted, and 1084 valid questionnaires were finally recovered. Among the 1084 valid samples that entered the analysis, women accounted for 61.4%, and the age distribution ranged from 18 to 81 years old. The education level of the target is dominated by high school students (55.8%); In terms of occupation, civil servants and teachers account for the highest proportion (33.5%); In terms of income, those whose monthly income is less than 5000 yuan account for the highest proportion (45.6%) (See Table 1). Research methods In order to fully understand the impact of walking environment in Chengdu Chongqing Economic Zone on residents' willingness to participate in activities and physical and mental health, this topic designed the questionnaire on walking environment, leisure participation and physical and mental health status of residents in Chengdu Chongqing Area. The content includes five main aspects: basic information of fitness activity participants, path environment scale, leisure activity participation intention scale, conscious health status scale and personal physical health index (BMI). The basic personal information mainly includes gender, age, education level, occupation, average monthly income and living time. Measuring tools (1) Neighborhood Environment Walkability Scale(NEWS) The NEWS is mainly modified with reference to the fitness environment measurement tool developed by Cerin [ 21 ] and in combination with the actual conditions of fitness paths in Chengdu and Chongqing. In addition to the facilities of fitness venues, the scale also includes urban design, accessibility of public facilities and other contents. The density of houses near the path (including 6 items), the time from the residential area to the fitness path, the accessibility of public facilities (including 3 items), the connection of roads around the path (2 items), the path itself (6 items), the landscape around the path (5 items), the traffic safety around the path (3 items), the security around the path (3 items), the parking space around the path, the number of dead lanes around the path, and whether the path slope is steep. (2) Sport participation intention measurement scale (SPIMS) The SPIMS includes the purpose, frequency and time of fitness activities of urban residents using fitness paths. Among them, the purpose of use is to strengthen the physique, prevent diseases, kill time, make friends, relieve stress and gain cognition. The frequency and time of fitness activities are based on the previous study [ 22 ], in which the frequency is divided into two situations: ≤3 times/week and ≥ 4 times/week. Similarly, the time of each fitness activity is divided into ≤ 40min/time and>40min/time. (3) Conscious Health Status Scale (CHSS-12) The CHSS-12 is a general psychological measurement tool, founded by Mohammed [ 23 ], which is a short version of the short form 36 health survey(SF-36). It not designs for specific age, disease or treatment. It contains 12 items, which are divided into two parts: the Physiological health aspects (PHA) and mental health aspect (MHA). PHA includes physiological function (PF, 2 items), role-physical (RP, 2 items), bodily pain (BP), general health (GH); MHA includes vitality (VT), social functioning (SF), role-emotional (RE, 2 items), and mental health (MH, 2 items). (4) Body Mass Index(BMI)measurement The severity of obesity was evaluated by converting the height and weight of the subjects into body mass index (BMI), BMI = weight(kg)/ height(m) 2 . Referring to the normal standard value range of Chinese body mass index 18.5 ≤ BMI<22.6, that is, BMI more than 22.6 (lower than 24.9 in Europe and the United States and 22.9 in Asia) is overweight, BMI more than 30 is obese, and BMI<18.5 is too light [24. Validity and reliability of the questionnaire The research group first invited four experts in related fields to revise the semantics of the questionnaire. Then the discrimination and reliability of the questionnaire were tested. The members of the research group obtained 77 test papers from 7 fitness path points. After inspection, the path environment scale of 31 items has good discrimination. In the internal consistency test, cronbach's of each dimension of the scale α coefficient value is between 0.75–0.87, and the overall scale α value is 0.81. It shows that the health path environment scale has good measurement reliability. Since the perceived health scale directly adopts Stewart's simplified version, it has been widely recognized internationally, so this study only tested its measurement reliability, including PHA and MHA cronbach α coefficients are 0.89 and 0.91 respectively, indicating that the reliability of the scale applied to the western region is high. Among them Mathematical statistics Establishment of binary logistic regression model. Residents' willingness to participate in fitness is not only restricted by individual family, socio-economic background, cultural quality, marital status, physical status and other factors, but also restricted by path environmental factors. To find out the key influencing factors of fitness environment from many influencing factors, logistic regression analysis is the most ideal. This study takes the activity frequency and activity time in residents' fitness participation willingness as the outcome variables (Y), which are typical binary variables (ie. 3 times and less / week and 4 times and more / week; within 40min/time and more than 40 min /time). Let the dependent variable Y obey the binomial distribution, the value of the binomial distribution is 1 or0, and the probability of Y = 1 (i.e. 4 times or more/week or more than 40min/time) is µ , The influencing factors (independent variables) selected in this study are x 1 , x 2 ,... x 16 ), so the binomial logistic regression model constructed is: where, x 1 , x 2 ,... x 16 respectively represent gender, age, education, occupation, residential density, public accessibility, connection status, path facility status, surrounding landscape, Safety, surrounding public security, space around the path, dead lane, path slope, physical obstacles. β 0 is intercept (or constant term). β j (j = 1, 2, 3,... 16) is the corresponding regression coefficient, which is solved by the maximum likelihood method. In addition to the main use of logistic regression analysis, there are independent sample t-test and partial correlation as the main analysis methods to conduct multivariable correlation analysis on the test indicators of the subjects. The significance level of all indicators is set as α = 0.05。 Results Individual and environmental factors and fitness willingness Table 1 shows the influencing factor model of the frequency and time of residents' participation in fitness in Chengdu and Chongqing. The global test results of the model showed that the fitness frequency model (model 1) reached a significant level after excluding five variables that had no significant impact, such as gender, monthly income, residential density (score x 2 = 369.14; p = 0.000 < 0.05); The fitness time model (model 2) reached a significant level (score x 2 = 511.58; p = 0.000 < 0.05) after excluding seven variables that had no significant impact on the model, such as gender, education, occupation, etc. On the other hand, the Hosmer and lemeshow chi square values x 2 of the two models are 12.19 and 13.57 respectively, of which the P values are 0.068 and 0.061 respectively, both of which are greater than 0.05, which further shows that the fitting effect of the two models is better. It shows that the corresponding odds ratio (OR) value in Table 1 has good reliability. The following information can be obtained from table 1: (A)According to the background factors of the respondents, gender and average monthly income have no effect on residents' willingness to participate in fitness activities. Education and occupation only affect the frequency of residents' fitness participation. OR value clearly shows that the proportion of primary school and below, high school students, and universities and colleges participating more than 4 times a week is 0.61, 2.64 and 3.17 times that of graduate students, respectively. Taking retirees as the base ratio, there is no difference in the participation frequency of service industry, freelance and students, but the proportion of civil servants, teachers and business administrators who participate more than four times a week is 2.91 and 4.31 times that of retirees, respectively. Residents' age significantly affects their participation frequency and time. Taking people over the age of 66 as the base ratio, there is not any difference in participation frequency and time between the ages of 56–65, while there is a very significant difference in other age groups. The proportion of participating more than 4 times a week and more than 40min each time between the ages of 18–25, 26–35, 36–45 and 46–55 is 4.17, 6.19, 5.31, 2.19 times and 2.69, 4.11, 3.24 and 1.77 times that of people over the age of 66, respectively. (B) from the impact of path environmental factors on residents' willingness to participate in fitness, it can be seen that the slope of the footpath has no significant effect on the frequency and time of residents' participation in fitness. The condition of road connection and physical barriers only affects the fitness participation time. If the road connection is poor and there are more physical barriers as the base ratio, and the path environment with good road connection and less physical barriers, the proportion of residents participating in fitness for more than 40min each time will be increased to 1.84 times and 1.89 times respectively. Traffic safety and public security around the route only affect the participation frequency of residents. If the traffic safety along the route and poor public security around the route are taken as the base ratio, the proportion of residents who go to the route with good traffic safety and good public security around the route to participate in fitness more than 4 times will be increased to 1.51 times and 1.48 times respectively. Table 1: Statistical table of logistic regression analysis on the participation frequency and time of bodybuilders due to personal background and path environmental factors (odds ratio OR = Exp(β)) Model 1 Model 2 Model 1 Model 2 Model 2 Model 2 Variable classification N; % Exp(β) Exp(β) Variable classification N; % Exp(β) Exp(β) Gender 1084 Accessibility of public facilities male 418(38.6%) 1.14 0.97 Far accessibility (Reference line) 126 (11.6%) 1.00 female(Reference line) 666(61.4%) 1.00 1.00 Medium accessibility 557(51.4%) 1.87** 1.64* Age Near accessibility 401(37.0%) 4.65*** 3.09*** 18–25 years old 387(35.7%) 4.71*** 2.69** Road connection condition 26–35 years old 180(16.6%) 6.19*** 4.11*** Poor connection(Reference line) 345(31.7%) 1.00 1.00 36–45 years old 227(20.9%) 5.31*** 3.24*** Connect well 739(68.3%) 1.17 1.84** 46–55 years old 198(18.3%) 2.19* 1.77* Status of route facilities 56–65 years old 51(4.7%) 1.21 1.19 poor(Reference line) 559(51.6%) 1.00 66 years old(Reference line) 41(3.8%) 1.00 1.00 good 525(48.4%) 1.86** 2.50*** Education Landscape around the path Primary school and below 114(10.5%) 0.61*** 0.89 poor(Reference line) 530(48.9%) 1.00 1.00 Middle school(special school) 605(55.8%) 2.64* 1.17 good 554(51.1%) 1.64** 1.81** universities and colleges 237(21.9%) 3.17** 1.05 Traffic safety Graduate degree (Reference line) 128(11.8%) 1.00 1.00 unsafe(Reference line) 474(43.7%) 1.00 1.00 Occupation security 610(56.3%) 1.51* 1.15 Civil servants and teachers 363(33.5%) 2.91** 1.07 Security around the route Business Administrator 133(12.3%) 4.31** 0.97 poor 281(25.9%) 1.00 1.00 service 116(10.7%) 1.09 1.14 good 803(74.1%) 1.48* 1.17 Freelance 137(12.6%) 1.14 0.91 Path surrounding space student 178(16.4%) 1.23 0.87 Narrow space(Reference line) 616(56.8%) 1.00 Retired personnel (Reference line) 157(14.5%) 1.00 1.00 Large space 468(43.2%) 2.21** 1.91* Monthly income Number of dead tunnels Below 5000 yuan 494(45.6%) 1.08 0.87 more 440(40.6%) 1.00 1.00 5001–6000 yuan 240(22.1%) 0.97 1.20 less 644(59.4%) 1.61** 1.44* 6001–8000 yuan 233(21.5% 1.15 0.97 Footpath slope Above 8001 yuan (Reference line) 117(10.8%) 1.00 1.00 Steep (Reference line) 334(30.8%) 1.00 1.00 Residential density Not steep 750(69.2%) 1.13 0.81 high-density 237(21.9%) 1.97** 1.79*** Physical barrier Medium density 413(38.1%) 1.54* 1.61** more(Reference line) 250(21.3%) 1.00 1.00 low density(Reference line) 434(40.0%) 1.00 1.00 less 834(78.7%) 1.19 1.89** Notes: The test of model 1(Participation frequency model): Hosmer and lemeshow chi square x 2 = 12.19, p = 0.068 > 0.05, indicating that the model fitting effect is good; In the global test results, score x 2 = 369.14, p = 0.000 0.05, indicating that the model fitting effect is good; The global test was score x 2 = 511.58, p = 0.000 < 0.05, indicating that the model was statistically significant. “*”“**”“***”represents the significant level of 0.05, 0.01 and 0.001 respectively. Six factors, including residential density, accessibility of public facilities, condition of path facilities, landscape around the path, space around the path and the number of dead alleys around the path, have a significant impact on the frequency and time of residents' fitness participation. Taking low residential density as the base ratio, fitness paths around medium and high-density residential areas are more likely to cause residents' willingness to participate, The frequency (≥ 4 times/week) and time (≥ 40min/time) of residents who go to these fitness sessions will be increased to 1.54, 1.97 times and 1.61, 1.79 times respectively. Based on the distance between public facilities, if the distance between fitness paths is medium or close, the frequency (≥ 4 times/week) and time (≥ 40min/time) of residents going to fitness week will be increased to 1.87, 4.65 times and 1.64, 3.09 times respectively. If the fitness paths with poor condition of path facilities, poor landscape around the path, too narrow space around the path and too many dead alleys around the path are taken as the base ratio, and which facilities are in good condition, good landscape around the path, large space and few dead alleys, the proportion of residents' going to fitness frequency (≥ 4 times / week) and time (≥ 40min/ time) will be increased to 1.86 and 2.50 times, 1.64 and 1.81 times, 2.21 and 1.91 times, 1.61 and 1.44 times respectively. Table 2 influence of residents' willingness to participate (frequency and time) on their physiology and psychology ≤ 3 time/week ≥ 4 time/week T;P ≤ 40min/time >40min/time T;P PF 87.15 ± 17.69 89.77 ± 17.15 -0.88; 89.61 ± 17.27 87.54 ± 21.66 -0.37; RP 81.14 ± 31.12 83.21 ± 30.36 -0.73; 81.08 ± 31.24 83.17 ± 31.36 0.47; BP 82.66 ± 28.34 84.61 ± 22.28 -0.81; 82.17 ± 25.18 84.69 ± 22.23 -0.85; GH 44.08 ± 21.64 52.89 ± 25.32 -4.38;*** 45.25 ± 20.25 51.36 ± 25.77 -4.33;*** VT 61.67 ± 25.14 71.69 ± 21.36 -3.59;*** 64.12 ± 22.14 66.26 ± 20.81 -0.83; SF 71.44 ± 17.12 77.08 ± 25.32 -3.32;** 73.36 ± 17.24 70.98 ± 41.01 -0.95; RE 69.38 ± 39.90 75.99 ± 37.43 -1.77; 74.55 ± 31.14 72.68 ± 45.12 0.78; MH 66.06 ± 21.57 74.68 ± 18.32 -3.91;*** 71.17 ± 15.23 75.68 ± 18.84 -2.93;* PHA 297.33 ± 68.27 310.51 ± 71.24 -2.25;* 295.15 ± 64.14 311.25 ± 75.36 -1.31; MHA 272.12 ± 70.63 297.24 ± 75.39 -3.72;*** 285.22 ± 73.17 289.27 ± 81.64 -0.59; BMI 21.58 ± 5.61 23.17 ± 4.84 0.29; 23.78 ± 3.15 21.89 ± 2.58 2.02;* “*”“**”“***”represents the significant level of 0.05, 0.01 and 0.001 respectively. Fitness frequency, time and physiological and mental health Table 2 shows (A) Among the effects of fitness participation frequency on Residents' physical and mental health, residents who participate in the frequency of ≥ 4 times/week are significantly better than those who participate in the frequency of ≤ 3 times/week (GH: 52.89 ± 25.32 vs 44.08 ± 21.64, P < 0.001. VT: 71.69 ± 21.36 vs 61.67 ± 25.14, P < 0.001. SF: 77.08 ± 25.32 vs 71.44 ± 17.12, P < 0.01. MH: 74.68 ± 18.32 vs 66.06 ± 21.57, P < 0.001. PHA: 310.51 ± 71.24 vs 297.33 ± 68.27, P < 0.05. MHA: 297.24 ± 75.39 vs 272.12 ± 70.63, P < 0.05). These indicators indicate that the higher the participation frequency, the better the overall physical and mental health of residents. However, the frequency of fitness participation seems to have no effect on the BMI of residents. (B)The time of fitness participation significantly affected the general health (GH), mental health (MH) and body mass index (BMI) of the residents. The performance was that those who walked for more than 40 minutes each time were significantly better than those who walked for less than 40 minutes each time (GH: 51.36 ± 25.77 vs. 45.25 ± 20.25, P < 0.001, MH: 75.68 ± 18.84 vs. 71.17 ± 15.23, P < 0.05, BMI: 21.89 ± 2.58 vs. 23.78 ± 3.15, P < 0.05). Fitness environment, physical and mental health, and BMI As the relationship between environmental factors, physical and mental health status and BMI of residents' fitness path may be affected by many factors, such as the social and economic background, participation frequency, participation time, etc. In order to avoid these factors affecting the relationship between the three, this study takes personal socio-economic background variables (gender, age, education, occupation and monthly income) and willingness to participate variables (participation frequency and time) as control variables (covariants), and uses partial correlation analysis to explore the relationship between walking environment al factors, physical and mental health and BMI. Table 3 statistical table of partial correlation coefficient between walking environment, cardiogenic health and BMI PHA MHA BMI Residential density around the path (the higher the score, the higher the residential density) -0.08 -0.25* -0.04 Accessibility of public facilities (the higher the score, the better or closer the accessibility) 0.23* 0.27* 0.01 Road connection around the route (the higher the score, the better the intention) 0.26* 0.11 -0.05 Facilities of the route itself (the higher the score, the better the intention) 0.45*** 0.32* -0.05 Landscape around the path (the higher the score, the better the intention) 0.22* 0.24* 0.08 Traffic safety of the route (the higher the score, the worse the intention) -0.07 -0.35** 0.02 Security conditions around the route (the higher the score, the worse the intention) -0.33* -0.51*** 0.06 Space around the path (the higher the score, the less the intention) -0.25* -0.21* -0.02 Number of dead lanes around the path (the higher the score, the less the intention) 0.19* 0.27* -0.04 The gradient of the path (the higher the score, the more intention) 0.26* -0.24* -0.02 Physical obstacle of the path itself (the higher the score, the more the intention) -0.08 -0.55*** 0.05 “*”“**”“***”represents the significant level of 0.05, 0.01 and 0.001 respectively. Table 3 shows: (A)The PHA is significantly positively correlated with the accessibility of public facilities around the route (r = 0.23*), the road connection condition around the route (r = 0.26*), the condition of the own facilities along the route (r = 0.45**), the landscape around the route (r = 0.22*), the gradient of the path (r = 0.26*), and the number of dead lanes (r = 0.19*); PHA is significantly negatively correlated with the security situation around the route (r=-0.33*) and the space around the route (r=-0.25 *); On the whole, there is a strong relationship between PHA and the facilities of the route itself and the security situation around the route. (B) Except for the road connection around the path, MHA has a significant correlation with other path environmental factors. Among them, the residential density around the route (r=-0.25*), the traffic safety of the route (r=-0.35*), the public security situation around the route (r=-0.51**), the space around the route (r=-0.21*), the gradient of the path (r=-0.24*), and the physical barrier of the route (r=-0.55**) are significantly negatively correlated with MHA; However, the time between the route and shops and public facilities (r = 0.27*), the accessibility of public facilities (r = 0.21*), the condition of the own facilities of the route (r = 0.32*), the landscape around the route (r = 0.24*) and the number of dead lanes around the route (r = 0.27*) are significantly positively correlated with MHA. There was no significant correlation between body mass index (BMI) and the path environmental factors. Discussion From the impact of path environment on residents' willingness to participate Inoue et al found [ 25 ] in the discussion of the influence of neighborhood environmental factors on the physical activities of adults, the high population density in residential areas has a significant positive impact on Residents' fitness willingness, which is manifested in that the high residential density can significantly increase residents' physical activity time, making their weekly exercise time more than 150 minutes. JenJia & ShiaoTe found [ 26 ] that if the average floor area per unit of land in the children's living area is larger, it will increase the choice opportunity of walking and taking the bus accompanied by others. This study found that the frequency (≥ 4 times / week) and time (≥ 40min / time) of residents participating in fitness in the fitness path around the medium and high-density residential areas were 1.54, 1.97 times and 1.61, 1.79 times higher than those in the low-density residential areas, respectively. This result corroborates the research results of the above scholars. This study found that the accessibility of public facilities near the fitness path has a very significant impact on residents' fitness participation willingness. The better the accessibility is, the greater the positive impact on residents' fitness participation. According to Xiaoling's research findings [ 27 ], regular exercises are related to the accessibility of public facilities or sports space. When interviewing 1194 urban adult residents over the age of 18, Vale et al found [ 28 ] that the accessibility of sidewalks and shopping centers is easier to guide people's willingness to exercise regularly. Giles et al found [ 29 ] in a survey of 1803 healthy workers and home managers that after controlling for individual socio-economic variables, the farther the beach, river, golf course, swimming pool and other leisure and entertainment places are from the residential area, the lower the utilization rate. Cervero et al believes [ 30 ] that convenient residents' fitness centers are negatively related to the increase of walking activity, that is, the closer the distance, the more people will walk and increase their physical activity. Therefore, the results of this study are basically consistent with those of many scholars. This study found that the traffic safety of the round-trip fitness path and the surrounding public security also significantly affect the residents' fitness participation frequency, which is shown that the safer the traffic and the better the public security situation, the higher the residents' participation frequency. This result is also similar to the research conclusions of many scholars. As showed by hillnhutter research [ 31 ], too high traffic flow is an obstacle for residents to walk. According to Cuifang's investigation [ 32 ], the higher the intersection density, the higher the chance of traffic accidents, so it is very easy to reduce people's physical activity. Obviously, public security is an important source of fear in people's daily life. Urban public space is considered to be places with high risks, such as parks, campuses, streets, lanes, squares, stations, public buildings (parking lots, electric stairwells) or remote and undeveloped open space. They are most likely to create space dead ends and become crime sites. Especially after nightfall, they are more likely to form a short lost space, making people feel dangerous fear and uneasiness, so it is self-evident that the public security around the fitness path has an impact on residents' fitness participation willingness [ 33 , 34 , 35 ]. In addition, this study also found that the surrounding landscape, space size, steepness, number of dead lanes and physical barriers also have a greater impact on residents' fitness participation willingness. In fact, the landscape and space around the path are related to the street shape, scale, slope, road facilities and land use status on both sides of the residential area. Sugiyama et al [ 36 ] used the greening degree of the neighborhood to explore the people's health and psychological health. The results showed that the higher the greening degree, the more people would be attracted to walk or ride bicycles for outdoor leisure activities. Therefore, the greening degree is an important inducing factor to promote people's health. From the field investigation, it is found that many fitness paths do not consider the growth of tree roots, which makes their pavement appear to be uplifted. Moreover, motor vehicles are often parked and manhole covers are laid, resulting in the destruction of the path landscape. On the other hand, when residents are active at night, some fitness paths lack lighting equipment or the lights are dimmed. These factors will affect the internal obstacles of residents and lead to their reduced fitness willingness. From the impact of residents' fitness intention on their physical and mental health From the physiological point of view, physical activity is the movement of the body caused by the contraction of skeletal muscle, which leads to energy consumption, and the energy consumption caused by the activity process is positively related to the growth of physical fitness [ 37 , 38 , 39 ]. Many studies have found that exercise can improve and promote the physiological, psychological and social functions of the elderly. Regular exercise can prevent the occurrence of diseases and reduce the chance of disability, and avoid the occurrence of immobility syndrome [ 40 , 41 ]; Reduce anxiety, stress, depression and depression, and promote positive emotional development [ 42 ]. From the psychological point of view, the fitness path is conducive to physical health, relieving psychological stress and other benefits, and it is one of the main ways of leisure activities of modern people; Regular physical activities are very important for teenagers' mental health. If teenagers have leisure time and engage in sport, they will have better mental health, physical health and mood [ 43 , 44 ]. This study found that the higher the frequency of residents' participation in path fitness, the more beneficial it is to improve their mental vitality, increase the interaction between social networks and friends and improve their depression. Therefore, on the whole, walking frequency has the most extensive impact on mental health; The longer the walking time, the better the mental and physical health of residents, such as general conscious health status and BMI. These results are consistent with some previous studies [ 45 , 46 ]. This is because the longer walking time can increase physiological metabolism, reduce the probability of obesity, and then achieve physiological health. From the relationship between walking environment and physical and mental health This study controlled the variables such as personal socioeconomic background and fitness participation willingness (frequency and time) to explore the relationship between path environment, physical and mental health and BMI. The results showed that most path environment variables were significantly related to physical and mental health. From the physiological aspect, the condition of the route facilities has the greatest impact, followed by the public security around the route. It seems that a well-equipped and safe route environment will increase the utilization rate and thus achieve physical health; On the contrary, if the public security situation around the route is poor, people will not dare to go to fitness or reduce the frequency and time of fitness, which will affect the activity of residents and reduce their physical health. In addition, public accessibility, path and road connection, landscape, space and slope are also highly correlated with PHA. Ewing et al [ 47 ] found that the obesity rate and BMI of residents in cities with poor pedestrian environment planning and areas with low population density and low street connectivity and accessibility were relatively high after controlling the social economic variables and covariates of health willingness. Brown's research points out [ 48 ] that the closer to the park green space or leisure facilities, the more people will visit and effectively reduce the incidence of obesity. The conclusions of this study further corroborate the findings of the above experts. From the perspective of psychological orientation (MHA), this study finds that the top three environmental variables that have an impact on MHA are the physical barrier of the route, surrounding public security and traffic safety, followed by the condition of the route facilities, public accessibility, the condition of the route facilities, the surrounding landscape, the number of dead lanes and the density of houses, which also have an impact on MHA. That is, people are not willing to exercise in the path environment with poor traffic safety and public security, small space and many physical obstacles. This path environment has a great negative effect on Residents' psychology. However, this study found that the gradient of the path is too large to cause people's psychological rejection (the two are negatively correlated), but the gradient is positively correlated with the PHA, that is, the path environment with a large gradient can increase muscle activity and thus improve physical health. Conclusion (A) The probability of residents going to the fitness path has nothing to do with their gender and personal income, but has a close relationship with their education, occupation and age; The roads around the route are well connected and there are few physical obstacles, and the residents' participation time in fitness is significantly increased. The better the traffic safety of the round-trip fitness path and the better the public security around the path, the higher the frequency of residents' fitness participation. The higher the residential density around the route, the closer the accessibility of public facilities, the better the condition of the route facilities, the better the surrounding landscape, the larger the space, the fewer the number of dead lanes, and the frequency and time of residents' fitness participation have significantly increased. (B) In residents' willingness to participate in fitness, the influence of fitness exercise frequency on mental health is greater than that of fitness time, which is shown that the higher the frequency of fitness path participation is, the more helpful it is to improve their mental vitality and mood depression, while the longer the fitness time is, the more important it is to improve residents' physical health, This seems to imply that exercise and fitness must ensure sufficient time for each exercise to improve physiological metabolism. (C) The physical and mental health of residents were significantly positively correlated with the accessibility of public facilities around the route, the condition of the route facilities, the landscape around the route, and the number of dead lanes around the route, but significantly negatively correlated with the security situation and space size around the route; In addition to the negative correlation with the security and space size around the route, mental health is also highly negatively correlated with the surrounding residential density, the traffic safety of the route, the slope of the route and the physical obstacles of the route. Declarations Acknowledgments: I would like to thank the Humanities and Social Sciences Department of the Ministry of Education for providing financial support for this research, and the leaders and colleagues of the School of Physical Education of Southwest University for their selfless contributions and help to this research. Authors’ contributions Li Liu and Jiong Luo contributed to the design and implementation of the research, to the analysis of the results and to the writing of the manuscript. Tingran Zhang, and Yongsen Liu designed the original study and collected the survey data. All the authors read and approved the final manuscript. FUNDING This project is supported by the Humanities and Social Science Foundation of the Ministry of education (Project No.: 20YJA890018) Availability of data and materials The data that support the findings of this study are available from the corresponding author upon reasonable request. Ethical approval Our study did not require an ethical board approval because it did not contain human or animal trials. Consent for publication Participants were made aware of the intent to publish the study during the original study’s consent process. 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Although modern developed medical technology can delay death, it cannot change the important factor of illness, that is, the slow influence of the environment [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In 1998, the Alma-Ata Declaration of the World Health Organization emphasized the implementation of the national participation strategy to create a permanent healthy environment, and then started the national attention to the impact of the living environment on health. With the rapid growth of China's economy, the urbanization speed is faster and faster. Now, the natural elements in the first and second tier cities are increasingly reduced due to population concentration and urban development; At the same time, the driving or parking of a large number of motor vehicles will occupy the fitness activity space of urban community residents, reducing the area of green garden roads, park green space and open space, resulting in the inability of community residents to walk from their homes to nearby fitness paths and park activities, the inability of day students to walk to and from school, and the difficulty of the elderly to walk to open space activities. If residents want to go to the surrounding leisure and fitness venues for exercise, they often need to rely on motor vehicles to achieve, which greatly reduces the opportunities for urban residents to go out of outdoor activities, thereby increasing the incidence of psychological diseases.\u003c/p\u003e \u003cp\u003eFitness paths arose in the 1980s in economically developed countries in Europe and the United States. The vast majority of fitness paths are arranged in parks, green space, rivers and other places with good environment [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. A kind of sport equipment is installed at intervals, and various equipment is connected by paths, so they are called fitness paths [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In June 1995, the State Council of China promulgated the Outline of the National Fitness Program. Since then, a series of laws and regulations have been issued, and mass sports and fitness for all have been able to develop along a healthy track [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The \"National Fitness Plan\", which aims to comprehensively improve the national physique and health level, focuses on young people and children, and advocates that all people should participate in more than one physical activity every day, learn more than two fitness methods, and conduct a physical fitness test every year. In order to implement the national fitness program and promote the development of urban and rural residents' fitness activities, the government has invested in the construction of national fitness centers and multi-function sports venues to provide venues, equipment, etc. for residents' fitness activities. The \"national fitness path\" is an important part of it [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Since the first fitness path was completed in Guangzhou in 1996, it has been rapidly extended to major urban planning in China as one of the four basic models of the national fitness project [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In 2007, General Administration of sport invested 30\u0026nbsp;million yuan to build 1000 fitness paths across the country; By 2010, the investment will be increased to 62.5\u0026nbsp;million yuan [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. At present, under the guidance of national policies and guidelines, most urban and rural areas in China have built up community fitness paths, administrative village fitness paths, park fitness paths, etc. They are both fitness and fun, and are the best interpretation of the Communist Party of China\u0026rsquo;s(CPC)concept of governing for the people. Their purpose is to encourage Chinese people to make good use of these path facilities, integrate leisure and fitness activities into their daily life, so as to cultivate a healthy habit of engaging in regular sport, So as to strengthen the national physique.\u003c/p\u003e \u003cp\u003eToday, 25 years after the promulgation of the national fitness program, the number of fitness paths in cities and towns in China has already exceeded tens of thousands. It has become one of the important public space leisure modes widely used by the whole people, and has been highly concerned by the majority of urban residents in China [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The author consulted the relevant literature on the \"national fitness path\" from 2005 to 2020, and obtained a total of 395 articles(365 in Chinese and 30 in English). Few scholars have discussed the impact of the path environment on the physical and mental health of residents. Based on many environmental factors that affect residents' leisure and fitness activities, in addition to the facility conditions of the path itself, it also includes urban design, accessibility of fitness paths, etc. From a few foreign reports, it is agreed that environmental factors in the leisure field will affect the frequency and time of people's activities [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In the face of the increasing problems such as the reduction of public open space, environmental pollution, energy consumption, people's physical and mental health and social aging in most cities in China, people's demand for walking environment is increasing in the future, and whether these path environment can support and increase the willingness of urban community residents to participate, and then benefit residents to improve their physical and mental health is indeed a topic worth exploring [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Chengdu Chongqing Economic Zone is the most important economic center, scientific and technological innovation center, new highland of reform and opening up, and livable place of high-quality life in western China [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In the 2022 National Fitness Trend Report, \"People Love Fitness\" released by People's Daily Online, Chengdu and Chongqing were both ranked among the top 10 \"vigorous\" cities in China [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Therefore, this study chooses Chengdu Chongqing Economic Zone as the representative of fitness cities in the western region, starting with its walking environment, and then reveals the impact of path environment on residents' willingness to participate in fitness activities and their physical and mental health, which can provide important reference for the suitability layout of fitness paths, parks and green spaces, schools, banks, mass transport stations and other facilities in future urban planning.\u003c/p\u003e"},{"header":"Objects and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eObject determination\u003c/h2\u003e \u003cp\u003eChengdu and Chongqing have 11 and 9 main urban areas respectively. First, they are ranked according to the gross domestic product (GDP) strength of each district, and then one district is randomly selected from the top 50% and the bottom 50%, that is, Chengdu and Chongqing each have two main urban areas. Finally, Jiangbei District and Shapingba District of Chongqing were selected, while Wuhou District and Chenghua District of Chengdu were selected. In order to ensure the representativeness of fitness paths, the fitness paths in the main urban areas are classified into four categories according to previous scholars' research [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]: community fitness paths, street fitness paths, sidewalk fitness paths and park green space fitness paths. Then, according to the relevant information provided by the planning office of the main urban areas of the four districts and the field survey by the members of the research team, 14 representative survey points were finally selected for each district, including 5 community paths, 5 street paths, 2 sidewalk paths, and 2 park greenbelt paths.\u003c/p\u003e \u003cp\u003eIn order to avoid the questionnaire measurement error caused by new residents' unfamiliar with the walking environment in the residential area, according to the research of Balfour JL, \u0026amp; Kaplan GA. (2002) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], the longer they live, the more they can truly understand the local environmental conditions. Generally, they have been familiar with the local environment for more than 3 years. Based on this, in order to collect the subjects who really understand the environmental conditions of the adjacent path, the subjects are limited to two conditions: whether they have lived near the fitness path for more than 5 years and whether they are over 16 years old. The crowd who came to these fitness paths for fitness activities was investigated by using the method of squatting survey. A total of 6 investigation groups (3 people in each group) were established, and the stay time was 7:00\u0026ndash;8:30 a.m. and 6:00\u0026ndash;7:30 p.m. the whole investigation time was from March 15 to May 15, 2015, lasting for 2 months. Generally, the ratio of the total number of questionnaire items to the sample size should be greater than 10:1. Since the total items of the questionnaire used in this study are 79, the sample size should exceed 790 [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. During the actual survey, 1171 questionnaires were distributed, 87 of which failed to answer key questions were deducted, and 1084 valid questionnaires were finally recovered. Among the 1084 valid samples that entered the analysis, women accounted for 61.4%, and the age distribution ranged from 18 to 81 years old. The education level of the target is dominated by high school students (55.8%); In terms of occupation, civil servants and teachers account for the highest proportion (33.5%); In terms of income, those whose monthly income is less than 5000 yuan account for the highest proportion (45.6%) (See Table\u0026nbsp;1).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eResearch methods\u003c/h3\u003e\n\u003cp\u003eIn order to fully understand the impact of walking environment in Chengdu Chongqing Economic Zone on residents' willingness to participate in activities and physical and mental health, this topic designed the questionnaire on walking environment, leisure participation and physical and mental health status of residents in Chengdu Chongqing Area. The content includes five main aspects: basic information of fitness activity participants, path environment scale, leisure activity participation intention scale, conscious health status scale and personal physical health index (BMI). The basic personal information mainly includes gender, age, education level, occupation, average monthly income and living time.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMeasuring tools\u003c/h2\u003e \u003cp\u003e(1) Neighborhood Environment Walkability Scale(NEWS)\u003c/p\u003e \u003cp\u003eThe NEWS is mainly modified with reference to the fitness environment measurement tool developed by Cerin [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and in combination with the actual conditions of fitness paths in Chengdu and Chongqing. In addition to the facilities of fitness venues, the scale also includes urban design, accessibility of public facilities and other contents. The density of houses near the path (including 6 items), the time from the residential area to the fitness path, the accessibility of public facilities (including 3 items), the connection of roads around the path (2 items), the path itself (6 items), the landscape around the path (5 items), the traffic safety around the path (3 items), the security around the path (3 items), the parking space around the path, the number of dead lanes around the path, and whether the path slope is steep.\u003c/p\u003e \u003cp\u003e(2) Sport participation intention measurement scale (SPIMS)\u003c/p\u003e \u003cp\u003eThe SPIMS includes the purpose, frequency and time of fitness activities of urban residents using fitness paths. Among them, the purpose of use is to strengthen the physique, prevent diseases, kill time, make friends, relieve stress and gain cognition. The frequency and time of fitness activities are based on the previous study [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], in which the frequency is divided into two situations: \u0026le;3 times/week and \u0026ge;\u0026thinsp;4 times/week. Similarly, the time of each fitness activity is divided into \u0026le;\u0026thinsp;40min/time and\u0026gt;40min/time.\u003c/p\u003e \u003cp\u003e(3) Conscious Health Status Scale (CHSS-12)\u003c/p\u003e \u003cp\u003eThe CHSS-12 is a general psychological measurement tool, founded by Mohammed [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], which is a short version of the short form 36 health survey(SF-36). It not designs for specific age, disease or treatment. It contains 12 items, which are divided into two parts: the Physiological health aspects (PHA) and mental health aspect (MHA). PHA includes physiological function (PF, 2 items), role-physical (RP, 2 items), bodily pain (BP), general health (GH); MHA includes vitality (VT), social functioning (SF), role-emotional (RE, 2 items), and mental health (MH, 2 items).\u003c/p\u003e \u003cp\u003e(4) Body Mass Index(BMI)measurement\u003c/p\u003e \u003cp\u003eThe severity of obesity was evaluated by converting the height and weight of the subjects into body mass index (BMI), BMI\u0026thinsp;=\u0026thinsp;weight(kg)/ height(m)\u003csup\u003e2\u003c/sup\u003e. Referring to the normal standard value range of Chinese body mass index 18.5\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026lt;22.6, that is, BMI more than 22.6 (lower than 24.9 in Europe and the United States and 22.9 in Asia) is overweight, BMI more than 30 is obese, and BMI\u0026lt;18.5 is too light [24.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eValidity and reliability of the questionnaire\u003c/h2\u003e \u003cp\u003eThe research group first invited four experts in related fields to revise the semantics of the questionnaire. Then the discrimination and reliability of the questionnaire were tested. The members of the research group obtained 77 test papers from 7 fitness path points. After inspection, the path environment scale of 31 items has good discrimination. In the internal consistency test, cronbach's of each dimension of the scale α coefficient value is between 0.75\u0026ndash;0.87, and the overall scale α value is 0.81. It shows that the health path environment scale has good measurement reliability. Since the perceived health scale directly adopts Stewart's simplified version, it has been widely recognized internationally, so this study only tested its measurement reliability, including PHA and MHA cronbach α coefficients are 0.89 and 0.91 respectively, indicating that the reliability of the scale applied to the western region is high. Among them\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eMathematical statistics\u003c/h2\u003e \u003cp\u003eEstablishment of binary logistic regression model. Residents' willingness to participate in fitness is not only restricted by individual family, socio-economic background, cultural quality, marital status, physical status and other factors, but also restricted by path environmental factors. To find out the key influencing factors of fitness environment from many influencing factors, logistic regression analysis is the most ideal. This study takes the activity frequency and activity time in residents' fitness participation willingness as the outcome variables (Y), which are typical binary variables (ie. 3 times and less / week and 4 times and more / week; within 40min/time and more than 40 min /time). Let the dependent variable Y obey the binomial distribution, the value of the binomial distribution is 1 or0, and the probability of Y\u0026thinsp;=\u0026thinsp;1 (i.e. 4 times or more/week or more than 40min/time) is \u003cb\u003e\u0026micro;\u003c/b\u003e, The influencing factors (independent variables) selected in this study are x\u003csub\u003e1\u003c/sub\u003e, x\u003csub\u003e2\u003c/sub\u003e,... x\u003csub\u003e16\u003c/sub\u003e), so the binomial logistic regression model constructed is:\u003c/p\u003e \u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\u003cp\u003ewhere, x\u003csub\u003e1\u003c/sub\u003e, x\u003csub\u003e2\u003c/sub\u003e,... x\u003csub\u003e16\u003c/sub\u003e respectively represent gender, age, education, occupation, residential density, public accessibility, connection status, path facility status, surrounding landscape, Safety, surrounding public security, space around the path, dead lane, path slope, physical obstacles. β\u003csub\u003e0\u003c/sub\u003e is intercept (or constant term). β\u003csub\u003ej\u003c/sub\u003e (j\u0026thinsp;=\u0026thinsp;1, 2, 3,... 16) is the corresponding regression coefficient, which is solved by the maximum likelihood method.\u003c/p\u003e \u003cp\u003eIn addition to the main use of logistic regression analysis, there are independent sample t-test and partial correlation as the main analysis methods to conduct multivariable correlation analysis on the test indicators of the subjects. The significance level of all indicators is set as α\u0026thinsp;=\u0026thinsp;0.05。\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eIndividual and environmental factors and fitness willingness\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;1 shows the influencing factor model of the frequency and time of residents' participation in fitness in Chengdu and Chongqing. The global test results of the model showed that the fitness frequency model (model 1) reached a significant level after excluding five variables that had no significant impact, such as gender, monthly income, residential density (score x\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;369.14; p\u0026thinsp;=\u0026thinsp;0.000\u0026thinsp;\u0026lt;\u0026thinsp;0.05); The fitness time model (model 2) reached a significant level (score x\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;511.58; p\u0026thinsp;=\u0026thinsp;0.000\u0026thinsp;\u0026lt;\u0026thinsp;0.05) after excluding seven variables that had no significant impact on the model, such as gender, education, occupation, etc. On the other hand, the Hosmer and lemeshow chi square values x\u003csup\u003e2\u003c/sup\u003e of the two models are 12.19 and 13.57 respectively, of which the P values are 0.068 and 0.061 respectively, both of which are greater than 0.05, which further shows that the fitting effect of the two models is better. It shows that the corresponding odds ratio (OR) value in Table\u0026nbsp;1 has good reliability.\u003c/p\u003e \u003cp\u003eThe following information can be obtained from table 1:\u003c/p\u003e \u003cp\u003e(A)According to the background factors of the respondents, gender and average monthly income have no effect on residents' willingness to participate in fitness activities. Education and occupation only affect the frequency of residents' fitness participation. OR value clearly shows that the proportion of primary school and below, high school students, and universities and colleges participating more than 4 times a week is 0.61, 2.64 and 3.17 times that of graduate students, respectively. Taking retirees as the base ratio, there is no difference in the participation frequency of service industry, freelance and students, but the proportion of civil servants, teachers and business administrators who participate more than four times a week is 2.91 and 4.31 times that of retirees, respectively. Residents' age significantly affects their participation frequency and time. Taking people over the age of 66 as the base ratio, there is not any difference in participation frequency and time between the ages of 56\u0026ndash;65, while there is a very significant difference in other age groups. The proportion of participating more than 4 times a week and more than 40min each time between the ages of 18\u0026ndash;25, 26\u0026ndash;35, 36\u0026ndash;45 and 46\u0026ndash;55 is 4.17, 6.19, 5.31, 2.19 times and 2.69, 4.11, 3.24 and 1.77 times that of people over the age of 66, respectively.\u003c/p\u003e \u003cp\u003e(B) from the impact of path environmental factors on residents' willingness to participate in fitness, it can be seen that the slope of the footpath has no significant effect on the frequency and time of residents' participation in fitness. The condition of road connection and physical barriers only affects the fitness participation time. If the road connection is poor and there are more physical barriers as the base ratio, and the path environment with good road connection and less physical barriers, the proportion of residents participating in fitness for more than 40min each time will be increased to 1.84 times and 1.89 times respectively. Traffic safety and public security around the route only affect the participation frequency of residents. If the traffic safety along the route and poor public security around the route are taken as the base ratio, the proportion of residents who go to the route with good traffic safety and good public security around the route to participate in fitness more than 4 times will be increased to 1.51 times and 1.48 times respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eTable\u0026nbsp;1: Statistical table of logistic regression analysis on the participation frequency and time of bodybuilders due to personal background and path environmental factors (odds ratio OR\u0026thinsp;=\u0026thinsp;Exp(β))\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabc\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable classification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN; %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExp(β)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eExp(β)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVariable classification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN; %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eExp(β)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eExp(β)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eAccessibility of public facilities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e418(38.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFar accessibility (Reference line)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e126 (11.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efemale(Reference line)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e666(61.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMedium accessibility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e557(51.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.87**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.64*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNear accessibility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e401(37.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.65***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.09***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;25 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e387(35.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.71***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.69**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eRoad connection condition\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u0026ndash;35 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e180(16.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.19***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.11***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePoor connection(Reference line)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e345(31.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36\u0026ndash;45 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e227(20.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.31***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.24***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eConnect well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e739(68.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.84**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e46\u0026ndash;55 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e198(18.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.19*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.77*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eStatus of route facilities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e56\u0026ndash;65 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51(4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003epoor(Reference line)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e559(51.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e66 years old(Reference line)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41(3.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003egood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e525(48.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.86**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.50***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eLandscape around the path\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary school and below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114(10.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.61***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003epoor(Reference line)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e530(48.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle school(special school)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e605(55.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.64*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003egood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e554(51.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.64**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.81**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003euniversities and colleges\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e237(21.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.17**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eTraffic safety\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGraduate degree\u003c/p\u003e \u003cp\u003e(Reference line)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e128(11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eunsafe(Reference line)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e474(43.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOccupation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003esecurity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e610(56.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.51*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCivil servants and teachers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e363(33.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.91**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eSecurity around the route\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBusiness Administrator\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133(12.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.31**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003epoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e281(25.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eservice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116(10.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003egood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e803(74.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.48*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFreelance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e137(12.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ePath surrounding space\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003estudent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e178(16.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNarrow space(Reference line)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e616(56.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetired personnel\u003c/p\u003e \u003cp\u003e(Reference line)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e157(14.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLarge space\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e468(43.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.21**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.91*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMonthly income\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eNumber of dead tunnels\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelow 5000 yuan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e494(45.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e440(40.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5001\u0026ndash;6000 yuan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e240(22.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eless\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e644(59.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.61**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.44*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6001\u0026ndash;8000 yuan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e233(21.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eFootpath slope\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbove 8001 yuan\u003c/p\u003e \u003cp\u003e(Reference line)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117(10.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSteep (Reference line)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e334(30.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidential density\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNot steep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e750(69.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehigh-density\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e237(21.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.97**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.79***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ePhysical barrier\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium density\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e413(38.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.54*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.61**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emore(Reference line)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e250(21.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elow density(Reference line)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e434(40.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eless\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e834(78.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.89**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eNotes: The test of model 1(Participation frequency model): Hosmer and lemeshow chi square x\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;12.19, p\u0026thinsp;=\u0026thinsp;0.068\u0026thinsp;\u0026gt;\u0026thinsp;0.05, indicating that the model fitting effect is good; In the global test results, score x\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;369.14, p\u0026thinsp;=\u0026thinsp;0.000\u0026thinsp;\u0026lt;\u0026thinsp;0.05, indicating that the model is statistically significant. Test of model 2(Participation time model): Hosmer and lemeshow chi square x\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;13.57, p\u0026thinsp;=\u0026thinsp;0.061\u0026thinsp;\u0026gt;\u0026thinsp;0.05, indicating that the model fitting effect is good; The global test was score x\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;511.58, p\u0026thinsp;=\u0026thinsp;0.000\u0026thinsp;\u0026lt;\u0026thinsp;0.05, indicating that the model was statistically significant. \u0026ldquo;*\u0026rdquo;\u0026ldquo;**\u0026rdquo;\u0026ldquo;***\u0026rdquo;represents the significant level of 0.05, 0.01 and 0.001 respectively.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSix factors, including residential density, accessibility of public facilities, condition of path facilities, landscape around the path, space around the path and the number of dead alleys around the path, have a significant impact on the frequency and time of residents' fitness participation. Taking low residential density as the base ratio, fitness paths around medium and high-density residential areas are more likely to cause residents' willingness to participate, The frequency (\u0026ge;\u0026thinsp;4 times/week) and time (\u0026ge;\u0026thinsp;40min/time) of residents who go to these fitness sessions will be increased to 1.54, 1.97 times and 1.61, 1.79 times respectively. Based on the distance between public facilities, if the distance between fitness paths is medium or close, the frequency (\u0026ge;\u0026thinsp;4 times/week) and time (\u0026ge;\u0026thinsp;40min/time) of residents going to fitness week will be increased to 1.87, 4.65 times and 1.64, 3.09 times respectively. If the fitness paths with poor condition of path facilities, poor landscape around the path, too narrow space around the path and too many dead alleys around the path are taken as the base ratio, and which facilities are in good condition, good landscape around the path, large space and few dead alleys, the proportion of residents' going to fitness frequency (\u0026ge;\u0026thinsp;4 times / week) and time (\u0026ge;\u0026thinsp;40min/ time) will be increased to 1.86 and 2.50 times, 1.64 and 1.81 times, 2.21 and 1.91 times, 1.61 and 1.44 times respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003einfluence of residents' willingness to participate (frequency and time) on their physiology and psychology\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;3 time/week\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;4 time/week\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eT;P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;40min/time\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026gt;40min/time\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eT;P\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87.15\u0026thinsp;\u0026plusmn;\u0026thinsp;17.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.77\u0026thinsp;\u0026plusmn;\u0026thinsp;17.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.88;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e89.61\u0026thinsp;\u0026plusmn;\u0026thinsp;17.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e87.54\u0026thinsp;\u0026plusmn;\u0026thinsp;21.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.37;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81.14\u0026thinsp;\u0026plusmn;\u0026thinsp;31.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83.21\u0026thinsp;\u0026plusmn;\u0026thinsp;30.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.73;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e81.08\u0026thinsp;\u0026plusmn;\u0026thinsp;31.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83.17\u0026thinsp;\u0026plusmn;\u0026thinsp;31.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.47;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82.66\u0026thinsp;\u0026plusmn;\u0026thinsp;28.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.61\u0026thinsp;\u0026plusmn;\u0026thinsp;22.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.81;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82.17\u0026thinsp;\u0026plusmn;\u0026thinsp;25.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e84.69\u0026thinsp;\u0026plusmn;\u0026thinsp;22.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.85;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.08\u0026thinsp;\u0026plusmn;\u0026thinsp;21.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.89\u0026thinsp;\u0026plusmn;\u0026thinsp;25.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4.38;***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.25\u0026thinsp;\u0026plusmn;\u0026thinsp;20.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51.36\u0026thinsp;\u0026plusmn;\u0026thinsp;25.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-4.33;***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.67\u0026thinsp;\u0026plusmn;\u0026thinsp;25.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.69\u0026thinsp;\u0026plusmn;\u0026thinsp;21.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.59;***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.12\u0026thinsp;\u0026plusmn;\u0026thinsp;22.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e66.26\u0026thinsp;\u0026plusmn;\u0026thinsp;20.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.83;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.44\u0026thinsp;\u0026plusmn;\u0026thinsp;17.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.08\u0026thinsp;\u0026plusmn;\u0026thinsp;25.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.32;**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e73.36\u0026thinsp;\u0026plusmn;\u0026thinsp;17.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e70.98\u0026thinsp;\u0026plusmn;\u0026thinsp;41.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.95;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.38\u0026thinsp;\u0026plusmn;\u0026thinsp;39.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.99\u0026thinsp;\u0026plusmn;\u0026thinsp;37.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.77;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74.55\u0026thinsp;\u0026plusmn;\u0026thinsp;31.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72.68\u0026thinsp;\u0026plusmn;\u0026thinsp;45.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.78;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.06\u0026thinsp;\u0026plusmn;\u0026thinsp;21.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.68\u0026thinsp;\u0026plusmn;\u0026thinsp;18.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.91;***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71.17\u0026thinsp;\u0026plusmn;\u0026thinsp;15.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75.68\u0026thinsp;\u0026plusmn;\u0026thinsp;18.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-2.93;*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePHA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e297.33\u0026thinsp;\u0026plusmn;\u0026thinsp;68.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e310.51\u0026thinsp;\u0026plusmn;\u0026thinsp;71.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.25;*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e295.15\u0026thinsp;\u0026plusmn;\u0026thinsp;64.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e311.25\u0026thinsp;\u0026plusmn;\u0026thinsp;75.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1.31;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMHA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e272.12\u0026thinsp;\u0026plusmn;\u0026thinsp;70.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e297.24\u0026thinsp;\u0026plusmn;\u0026thinsp;75.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.72;***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e285.22\u0026thinsp;\u0026plusmn;\u0026thinsp;73.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e289.27\u0026thinsp;\u0026plusmn;\u0026thinsp;81.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.59;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.58\u0026thinsp;\u0026plusmn;\u0026thinsp;5.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.17\u0026thinsp;\u0026plusmn;\u0026thinsp;4.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.29;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.78\u0026thinsp;\u0026plusmn;\u0026thinsp;3.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.89\u0026thinsp;\u0026plusmn;\u0026thinsp;2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.02;*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u0026ldquo;*\u0026rdquo;\u0026ldquo;**\u0026rdquo;\u0026ldquo;***\u0026rdquo;represents the significant level of 0.05, 0.01 and 0.001 respectively.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eFitness frequency, time and physiological and mental health\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows\u003c/p\u003e \u003cp\u003e(A) Among the effects of fitness participation frequency on Residents' physical and mental health, residents who participate in the frequency of \u0026ge;\u0026thinsp;4 times/week are significantly better than those who participate in the frequency of \u0026le;\u0026thinsp;3 times/week (GH: 52.89\u0026thinsp;\u0026plusmn;\u0026thinsp;25.32 vs 44.08\u0026thinsp;\u0026plusmn;\u0026thinsp;21.64, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001. VT: 71.69\u0026thinsp;\u0026plusmn;\u0026thinsp;21.36 vs 61.67\u0026thinsp;\u0026plusmn;\u0026thinsp;25.14, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001. SF: 77.08\u0026thinsp;\u0026plusmn;\u0026thinsp;25.32 vs 71.44\u0026thinsp;\u0026plusmn;\u0026thinsp;17.12, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01. MH: 74.68\u0026thinsp;\u0026plusmn;\u0026thinsp;18.32 vs 66.06\u0026thinsp;\u0026plusmn;\u0026thinsp;21.57, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001. PHA: 310.51\u0026thinsp;\u0026plusmn;\u0026thinsp;71.24 vs 297.33\u0026thinsp;\u0026plusmn;\u0026thinsp;68.27, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. MHA: 297.24\u0026thinsp;\u0026plusmn;\u0026thinsp;75.39 vs 272.12\u0026thinsp;\u0026plusmn;\u0026thinsp;70.63, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These indicators indicate that the higher the participation frequency, the better the overall physical and mental health of residents. However, the frequency of fitness participation seems to have no effect on the BMI of residents.\u003c/p\u003e \u003cp\u003e(B)The time of fitness participation significantly affected the general health (GH), mental health (MH) and body mass index (BMI) of the residents. The performance was that those who walked for more than 40 minutes each time were significantly better than those who walked for less than 40 minutes each time (GH: 51.36\u0026thinsp;\u0026plusmn;\u0026thinsp;25.77 vs. 45.25\u0026thinsp;\u0026plusmn;\u0026thinsp;20.25, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, MH: 75.68\u0026thinsp;\u0026plusmn;\u0026thinsp;18.84 vs. 71.17\u0026thinsp;\u0026plusmn;\u0026thinsp;15.23, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, BMI: 21.89\u0026thinsp;\u0026plusmn;\u0026thinsp;2.58 vs. 23.78\u0026thinsp;\u0026plusmn;\u0026thinsp;3.15, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eFitness environment, physical and mental health, and BMI\u003c/h2\u003e \u003cp\u003eAs the relationship between environmental factors, physical and mental health status and BMI of residents' fitness path may be affected by many factors, such as the social and economic background, participation frequency, participation time, etc. In order to avoid these factors affecting the relationship between the three, this study takes personal socio-economic background variables (gender, age, education, occupation and monthly income) and willingness to participate variables (participation frequency and time) as control variables (covariants), and uses partial correlation analysis to explore the relationship between walking environment al factors, physical and mental health and BMI.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003estatistical table of partial correlation coefficient between walking environment, cardiogenic health and BMI\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePHA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMHA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidential density around the path (the higher the score, the higher the residential density)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.25*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccessibility of public facilities (the higher the score, the better or closer the accessibility)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.23*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.27*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoad connection around the route (the higher the score, the better the intention)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.26*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacilities of the route itself (the higher the score, the better the intention)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.45***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.32*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLandscape around the path (the higher the score, the better the intention)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.22*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTraffic safety of the route (the higher the score, the worse the intention)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.35**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecurity conditions around the route (the higher the score, the worse the intention)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.33*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.51***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpace around the path (the higher the score, the less the intention)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.25*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.21*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of dead lanes around the path (the higher the score, the less the intention)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.19*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.27*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe gradient of the path (the higher the score, the more intention)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.26*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.24*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical obstacle of the path itself (the higher the score, the more the intention)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.55***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u0026ldquo;*\u0026rdquo;\u0026ldquo;**\u0026rdquo;\u0026ldquo;***\u0026rdquo;represents the significant level of 0.05, 0.01 and 0.001 respectively.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows:\u003c/p\u003e \u003cp\u003e(A)The PHA is significantly positively correlated with the accessibility of public facilities around the route (r\u0026thinsp;=\u0026thinsp;0.23*), the road connection condition around the route (r\u0026thinsp;=\u0026thinsp;0.26*), the condition of the own facilities along the route (r\u0026thinsp;=\u0026thinsp;0.45**), the landscape around the route (r\u0026thinsp;=\u0026thinsp;0.22*), the gradient of the path (r\u0026thinsp;=\u0026thinsp;0.26*), and the number of dead lanes (r\u0026thinsp;=\u0026thinsp;0.19*); PHA is significantly negatively correlated with the security situation around the route (r=-0.33*) and the space around the route (r=-0.25 *); On the whole, there is a strong relationship between PHA and the facilities of the route itself and the security situation around the route.\u003c/p\u003e \u003cp\u003e(B) Except for the road connection around the path, MHA has a significant correlation with other path environmental factors. Among them, the residential density around the route (r=-0.25*), the traffic safety of the route (r=-0.35*), the public security situation around the route (r=-0.51**), the space around the route (r=-0.21*), the gradient of the path (r=-0.24*), and the physical barrier of the route (r=-0.55**) are significantly negatively correlated with MHA; However, the time between the route and shops and public facilities (r\u0026thinsp;=\u0026thinsp;0.27*), the accessibility of public facilities (r\u0026thinsp;=\u0026thinsp;0.21*), the condition of the own facilities of the route (r\u0026thinsp;=\u0026thinsp;0.32*), the landscape around the route (r\u0026thinsp;=\u0026thinsp;0.24*) and the number of dead lanes around the route (r\u0026thinsp;=\u0026thinsp;0.27*) are significantly positively correlated with MHA. There was no significant correlation between body mass index (BMI) and the path environmental factors.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eFrom the impact of path environment on residents' willingness to participate\u003c/h2\u003e \u003cp\u003eInoue et al found [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] in the discussion of the influence of neighborhood environmental factors on the physical activities of adults, the high population density in residential areas has a significant positive impact on Residents' fitness willingness, which is manifested in that the high residential density can significantly increase residents' physical activity time, making their weekly exercise time more than 150 minutes. JenJia \u0026amp; ShiaoTe found [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] that if the average floor area per unit of land in the children's living area is larger, it will increase the choice opportunity of walking and taking the bus accompanied by others. This study found that the frequency (\u0026ge;\u0026thinsp;4 times / week) and time (\u0026ge;\u0026thinsp;40min / time) of residents participating in fitness in the fitness path around the medium and high-density residential areas were 1.54, 1.97 times and 1.61, 1.79 times higher than those in the low-density residential areas, respectively. This result corroborates the research results of the above scholars.\u003c/p\u003e \u003cp\u003eThis study found that the accessibility of public facilities near the fitness path has a very significant impact on residents' fitness participation willingness. The better the accessibility is, the greater the positive impact on residents' fitness participation. According to Xiaoling's research findings [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], regular exercises are related to the accessibility of public facilities or sports space. When interviewing 1194 urban adult residents over the age of 18, Vale et al found [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] that the accessibility of sidewalks and shopping centers is easier to guide people's willingness to exercise regularly. Giles et al found [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] in a survey of 1803 healthy workers and home managers that after controlling for individual socio-economic variables, the farther the beach, river, golf course, swimming pool and other leisure and entertainment places are from the residential area, the lower the utilization rate. Cervero et al believes [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] that convenient residents' fitness centers are negatively related to the increase of walking activity, that is, the closer the distance, the more people will walk and increase their physical activity. Therefore, the results of this study are basically consistent with those of many scholars.\u003c/p\u003e \u003cp\u003eThis study found that the traffic safety of the round-trip fitness path and the surrounding public security also significantly affect the residents' fitness participation frequency, which is shown that the safer the traffic and the better the public security situation, the higher the residents' participation frequency. This result is also similar to the research conclusions of many scholars. As showed by hillnhutter research [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], too high traffic flow is an obstacle for residents to walk. According to Cuifang's investigation [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], the higher the intersection density, the higher the chance of traffic accidents, so it is very easy to reduce people's physical activity. Obviously, public security is an important source of fear in people's daily life. Urban public space is considered to be places with high risks, such as parks, campuses, streets, lanes, squares, stations, public buildings (parking lots, electric stairwells) or remote and undeveloped open space. They are most likely to create space dead ends and become crime sites. Especially after nightfall, they are more likely to form a short lost space, making people feel dangerous fear and uneasiness, so it is self-evident that the public security around the fitness path has an impact on residents' fitness participation willingness [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition, this study also found that the surrounding landscape, space size, steepness, number of dead lanes and physical barriers also have a greater impact on residents' fitness participation willingness. In fact, the landscape and space around the path are related to the street shape, scale, slope, road facilities and land use status on both sides of the residential area. Sugiyama et al [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] used the greening degree of the neighborhood to explore the people's health and psychological health. The results showed that the higher the greening degree, the more people would be attracted to walk or ride bicycles for outdoor leisure activities. Therefore, the greening degree is an important inducing factor to promote people's health. From the field investigation, it is found that many fitness paths do not consider the growth of tree roots, which makes their pavement appear to be uplifted. Moreover, motor vehicles are often parked and manhole covers are laid, resulting in the destruction of the path landscape. On the other hand, when residents are active at night, some fitness paths lack lighting equipment or the lights are dimmed. These factors will affect the internal obstacles of residents and lead to their reduced fitness willingness.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eFrom the impact of residents' fitness intention on their physical and mental health\u003c/h2\u003e \u003cp\u003eFrom the physiological point of view, physical activity is the movement of the body caused by the contraction of skeletal muscle, which leads to energy consumption, and the energy consumption caused by the activity process is positively related to the growth of physical fitness [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Many studies have found that exercise can improve and promote the physiological, psychological and social functions of the elderly. Regular exercise can prevent the occurrence of diseases and reduce the chance of disability, and avoid the occurrence of immobility syndrome [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]; Reduce anxiety, stress, depression and depression, and promote positive emotional development [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. From the psychological point of view, the fitness path is conducive to physical health, relieving psychological stress and other benefits, and it is one of the main ways of leisure activities of modern people; Regular physical activities are very important for teenagers' mental health. If teenagers have leisure time and engage in sport, they will have better mental health, physical health and mood [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. This study found that the higher the frequency of residents' participation in path fitness, the more beneficial it is to improve their mental vitality, increase the interaction between social networks and friends and improve their depression. Therefore, on the whole, walking frequency has the most extensive impact on mental health; The longer the walking time, the better the mental and physical health of residents, such as general conscious health status and BMI. These results are consistent with some previous studies [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. This is because the longer walking time can increase physiological metabolism, reduce the probability of obesity, and then achieve physiological health.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eFrom the relationship between walking environment and physical and mental health\u003c/h2\u003e \u003cp\u003eThis study controlled the variables such as personal socioeconomic background and fitness participation willingness (frequency and time) to explore the relationship between path environment, physical and mental health and BMI. The results showed that most path environment variables were significantly related to physical and mental health. From the physiological aspect, the condition of the route facilities has the greatest impact, followed by the public security around the route. It seems that a well-equipped and safe route environment will increase the utilization rate and thus achieve physical health; On the contrary, if the public security situation around the route is poor, people will not dare to go to fitness or reduce the frequency and time of fitness, which will affect the activity of residents and reduce their physical health. In addition, public accessibility, path and road connection, landscape, space and slope are also highly correlated with PHA. Ewing et al [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] found that the obesity rate and BMI of residents in cities with poor pedestrian environment planning and areas with low population density and low street connectivity and accessibility were relatively high after controlling the social economic variables and covariates of health willingness. Brown's research points out [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] that the closer to the park green space or leisure facilities, the more people will visit and effectively reduce the incidence of obesity. The conclusions of this study further corroborate the findings of the above experts.\u003c/p\u003e \u003cp\u003eFrom the perspective of psychological orientation (MHA), this study finds that the top three environmental variables that have an impact on MHA are the physical barrier of the route, surrounding public security and traffic safety, followed by the condition of the route facilities, public accessibility, the condition of the route facilities, the surrounding landscape, the number of dead lanes and the density of houses, which also have an impact on MHA. That is, people are not willing to exercise in the path environment with poor traffic safety and public security, small space and many physical obstacles. This path environment has a great negative effect on Residents' psychology. However, this study found that the gradient of the path is too large to cause people's psychological rejection (the two are negatively correlated), but the gradient is positively correlated with the PHA, that is, the path environment with a large gradient can increase muscle activity and thus improve physical health.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003e(A) The probability of residents going to the fitness path has nothing to do with their gender and personal income, but has a close relationship with their education, occupation and age; The roads around the route are well connected and there are few physical obstacles, and the residents\u0026apos; participation time in fitness is significantly increased. The better the traffic safety of the round-trip fitness path and the better the public security around the path, the higher the frequency of residents\u0026apos; fitness participation. The higher the residential density around the route, the closer the accessibility of public facilities, the better the condition of the route facilities, the better the surrounding landscape, the larger the space, the fewer the number of dead lanes, and the frequency and time of residents\u0026apos; fitness participation have significantly increased.\u003c/p\u003e\n\u003cp\u003e(B) In residents\u0026apos; willingness to participate in fitness, the influence of fitness exercise frequency on mental health is greater than that of fitness time, which is shown that the higher the frequency of fitness path participation is, the more helpful it is to improve their mental vitality and mood depression, while the longer the fitness time is, the more important it is to improve residents\u0026apos; physical health, This seems to imply that exercise and fitness must ensure sufficient time for each exercise to improve physiological metabolism.\u003c/p\u003e\n\u003cp\u003e(C) The physical and mental health of residents were significantly positively correlated with the accessibility of public facilities around the route, the condition of the route facilities, the landscape around the route, and the number of dead lanes around the route, but significantly negatively correlated with the security situation and space size around the route; In addition to the negative correlation with the security and space size around the route, mental health is also highly negatively correlated with the surrounding residential density, the traffic safety of the route, the slope of the route and the physical obstacles of the route.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI would like to thank the Humanities and Social Sciences Department of the Ministry of Education for providing financial support for this research, and the leaders and colleagues of the School of Physical Education of Southwest University for their selfless contributions and help to this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLi Liu and Jiong Luo contributed to the design and implementation of the research, to the analysis of the results and to the writing of the manuscript. Tingran Zhang, and Yongsen Liu designed the original study and collected the survey data. All the authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFUNDING\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project is supported by the Humanities and Social Science Foundation of the Ministry of education \u0026nbsp; (Project No.: 20YJA890018)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding \u0026nbsp;author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study did not require an ethical board approval because it did not contain human or animal trials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants were made aware of the intent to publish the study during the original study\u0026rsquo;s consent process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJohnson ST, Martin C, Anens E, Johansson AC, Hellstrom K. 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Improving the exercise obstacles in the walking environment and further ensuring the safety of the exercise process and fitness facilities is the key to enhancing the exercise willingness of residents.\u003c/p\u003e","manuscriptTitle":"The Influence of Walking environment on the Sports Participation Willingness and Physiological and psychological health of Urban Residents: Evidence from Western China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-01 22:12:39","doi":"10.21203/rs.3.rs-3996575/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"06bb75ac-0dc7-4589-91d5-142af8a4659b","owner":[],"postedDate":"March 1st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-12T08:18:23+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-01 22:12:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3996575","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3996575","identity":"rs-3996575","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}