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

Abstract

As low physical fitness in adolescents increases their risk of all-cause mortality in future adulthood as well as regional public health budgets, many scholars have studied the factors influencing physical fitness in adolescents. However, the spatial non-stationarity and scale between physical fitness and influencing factors in adolescents are often neglected. To rectify this situation, this study constructed a multi-scale geographically weighted regression model based on data from the China National Student Fitness Survey and the China Statistical Yearbook in 2018 to investigate the spatial patterns of factors influencing low physical fitness among adolescents. The results showed that the influencing factors for measuring the physical fitness of Chinese adolescents had significant spatial heterogeneity and multi-scale effects. The local R² values were relatively low in the western region of China. Consideration should be given to increasing the lifestyle and ethnic and cultural characteristics of local residents when selecting influencing factors in the future. The physical fitness of men was mainly influenced by socio-economic factors, while that of women was influenced by natural environmental factors. According to the different spatial distribution patterns of MGWR, this study suggests that each region should develop regionalized strategies to cope with the low physical fitness of adolescents, including taking advantage of the natural environment to develop physical fitness promotion projects, accelerating the upgrading of industrial structures in the north-eastern and western regions, and the need to remain cautious of rapid urbanization in the east.

Keywords: China; coping strategies; environmental factors; multi-scale geographic weighted regression (MGWR); physical fitness; public health; socio-economic factors; spatial heterogeneity.

Figure 1

The study area: China’s 34 provincial administrative units and four economic regions.

Figure 2

Spatial patterns of local R-squared in the MGWR. (a) Local R-squared spatial patterns of the male group in China, (b) local R-squared spatial patterns of the female group in China.

Figure 3

Spatial patterns of coefficients in the MGWR. (a) Annual precipitation in the male group; (b) annual precipitation in the female group; (c) non-farm output ratio in the male group; (d) nonfarm output ratio in the female group; (e) urbanization rate in the male group; (f) elevation in the female group.