The study of the influence of the neighborhood Environment of small Towns on residents' Leisure time physical activities from the Perspective of the novel coronavirus epidemic situation

The study of the influence of the neighborhood Environment of small Towns on residents' Leisure time physical activities from the Perspective of the novel coronavirus epidemic situation

Background: A small town is an important link in my country's relatively high and linked rural and cities. Community space is a direct space carrier for residents to conduct leisure and physical activities (LTPA).Objectives: At the end of 2019, the outbreak of new coronary virus pneumonia brought new challenges to public health. The building environment in the neighborhood became a direct factor affecting the level of residents' LTPA level, which is closely linked to public health. Methods: This study selected a typical small-town community. Based on GIS data, the SEGNET convolutional neural network analyzed the greening rate and enclosure of leisure and physical activity venues and used international physical questionnaires (IPAQ) and network physical activity questionnaires (N N -IPAQ) and their scoring standards measurement and evaluation of the intensity of physical activity of residents. Results: A system of influencing factors on leisure physical activity by constructing a neighborhood built environment. Conclusions: By calculating weights and proposing optimization strategies, we aim to improve the leisure and physical activity levels of residents, thereby enhancing their health.

Background: A small town is an important link in my country's relatively high and linked rural and cities. Community space is a direct space carrier for residents to conduct leisure and physical activities (LTPA).Objectives: At the end of 2019, the outbreak of new coronary virus pneumonia brought new challenges to public health. The building environment in the neighborhood became a direct factor affecting the level of residents' LTPA level, which is closely linked to public health. Methods: This study selected a typical small-town community. Based on GIS data, the SEGNET convolutional neural network analyzed the greening rate and enclosure of leisure and physical activity venues and used international physical questionnaires (IPAQ) and network physical activity questionnaires (N N -IPAQ) and their scoring standards measurement and evaluation of the intensity of physical activity of residents. Results: A system of influencing factors on leisure physical activity by constructing a neighborhood built environment. Conclusions: By calculating weights and proposing optimization strategies, we aim to improve the leisure and physical activity levels of residents, thereby enhancing their health.