Multiscale Impact of Environmental and Socio-Economic Factors on Low Physical Fitness among Chinese Adolescents and Regionalized Coping Strategies

Spatial-temporal evolution of overweight and obesity among Chinese adolescents from 2016 to 2020

This study examines the spatial-temporal evolution of overweight and obesity among Chinese adolescents aged 14-17. Data from five national surveys conducted between 2016 and 2020 were analyzed to determine distribution patterns and trends. Results showed that overweight and obesity exhibit spatial clustering, with greater severity in the north and less severity in the south. The issue has spread from the northeast to the southwest of Mainland China. Using a local autocorrelation model, the regions were divided into a northern disease cold spot area (Inner Mongolia) and a southern disease hot spot area (Guangxi). Over the past five years, overweight rates among Chinese adolescents have not been effectively curbed, but obesity has shown some success in control and reversal until 2019. Future efforts should focus on the spatial-temporal pattern of disease spread, targeting hotspot areas and abnormal values for regional synergy and precise prevention and control.

Promoting Health for Adolescents: An Editorial

The research area of adolescent health corresponds to the summary of a wide range of scientific interests and investigations, focusing on the first years of life of an individual [...].

Spatial Heterogeneity and Regional Clustering of Factors Influencing Chinese Adolescents' Physical Fitness

There is often significant spatial heterogeneity in the factors influencing physical fitness in adolescents, yet less attention has been paid to this in established studies. Based on the 2018 Chinese National Student Physical Fitness Standard Test data, this study uses a multi-scale, geographically weighted regression (MGWR) model combined with a K-means clustering algorithm to construct a spatial regression model of the factors influencing adolescent physical fitness, and to investigate the degree of spatial variation in the physical fitness of Chinese adolescents from a socio-ecological perspective of health promotion. The following conclusions were drawn: the performance of the youth physical fitness regression model was significantly improved after taking spatial scale and heterogeneity into account. At the provincial scale, the non-farm output, average altitude, and precipitation of each region were strongly related to youth physical fitness, and each influencing factor generally showed a banded spatial heterogeneity pattern, which can be summarized into four types: N-S, E-W, NE-SW, and SE-NW. From the perspective of youth physical fitness, China can be divided into three regions of influence: the socio-economic-influenced region, mainly including the eastern region and some of the central provinces of China; the natural-environment-influenced region, which mainly includes the northwestern part of China and some provinces in the highland region; and the multi-factor joint-influenced region, which mainly includes the provinces in the central and northeastern regions of China. Finally, this study provides syndemic suggestions for physical fitness and health promotion for youths in each region.

A study of the influence of sports venues on the intra-city population layout based on multi-source data-Taking Xi'an city and Zhengzhou city as examples

Revealing the influence of sports sports venues on the population in the built-up areas of cities contributes to the high-quality development of cities and the well-being of people. This study applies kernel density estimation to characterize the distribution of sports venues using reclassified POI (Point of Information) data, visualizes the distribution of intra-city population using population raster data from the WorldPop database, and analyses the distribution of sports venues and the urban population in Xi'an and Zhengzhou cities in 2020 from both the general and local perspectives based on various regression methods, such as MGWR, GWR, and linear fitting. The results show that the distribution of sports venues in Xi'an and Zhengzhou cities in 2020 was a good indicator of the population. The spatial distribution of sports venues and the population within the cities have a centre-periphery structure. From the global perspective, the distribution of sports venues is positively correlated with the intra-city population, and the promoting effect is significant. From the local perspective, the effect is spatially heterogeneous. Finally, this study explores the rationality of the complex impact and indicates that the research methodology can provide a reliable reference for other cities.