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

Author

Listed:
  • Zihan Tong

    (Key Laboratory of Exercise and Physical Fitness, Ministry of Education, Beijing Sport University, Beijing 100084, China)

  • Zhenxing Kong

    (Key Laboratory of Exercise and Physical Fitness, Ministry of Education, Beijing Sport University, Beijing 100084, China)

  • Xiao Jia

    (Key Laboratory of Exercise and Physical Fitness, Ministry of Education, Beijing Sport University, Beijing 100084, China)

  • Hanyue Zhang

    (Institute of Physical Education, Northeast Normal University, Changchun 130024, China)

  • Yimin Zhang

    (Key Laboratory of Exercise and Physical Fitness, Ministry of Education, Beijing Sport University, Beijing 100084, China)

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 R 2 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.

Suggested Citation

  • Zihan Tong & Zhenxing Kong & Xiao Jia & Hanyue Zhang & Yimin Zhang, 2022. "Multiscale Impact of Environmental and Socio-Economic Factors on Low Physical Fitness among Chinese Adolescents and Regionalized Coping Strategies," IJERPH, MDPI, vol. 19(20), pages 1-24, October.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:20:p:13504-:d:946567
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    1. María Rivera-Ochoa & Javier Brazo-Sayavera & Barbara Vizmanos-Lamotte & Asier Mañas & Juan Ricardo López-Taylor & Marcela González-Gross & Amelia Guadalupe-Grau, 2020. "Health-Related Factors in Rural and Urban Mexican Adolescents from the State of Jalisco: The HELENA-MEX Study," IJERPH, MDPI, vol. 17(23), pages 1-16, December.
    2. Levi N. Bonnell & Benjamin Littenberg, 2022. "Nonlinear Relationships among the Natural Environment, Health, and Sociodemographic Characteristics across US Counties," IJERPH, MDPI, vol. 19(11), pages 1-10, June.
    3. Maria E Hermosillo-Gallardo & Russell Jago & Simon J Sebire, 2018. "Association between urbanicity and physical activity in Mexican adolescents: The use of a composite urbanicity measure," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-16, September.
    4. Yunxi Tian & Lingfang Liu & Xuhui Wang & Xue Zhang & Yang Zhai & Kai Wang & Jianjun Liu, 2021. "Urban-Rural Differences in Physical Fitness and Out-of-School Physical Activity for Primary School Students: A County-Level Comparison in Western China," IJERPH, MDPI, vol. 18(20), pages 1-17, October.
    5. Gerhard Ruedl & Martin Niedermeier & Lukas Wimmer & Vivien Ploner & Elena Pocecco & Armando Cocca & Klaus Greier, 2021. "Impact of Parental Education and Physical Activity on the Long-Term Development of the Physical Fitness of Primary School Children: An Observational Study," IJERPH, MDPI, vol. 18(16), pages 1-13, August.
    6. Ziqi Li & A. Stewart Fotheringham & Taylor M. Oshan & Levi John Wolf, 2020. "Measuring Bandwidth Uncertainty in Multiscale Geographically Weighted Regression Using Akaike Weights," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 110(5), pages 1500-1520, September.
    7. Daniel Puciato & Michał Rozpara, 2020. "Demographic and Socioeconomic Determinants of Body Mass Index in People of Working Age," IJERPH, MDPI, vol. 17(21), pages 1-12, November.
    8. He Jin & Yongmei Lu, 2017. "Academic Performance of Texas Public Schools and Its Relationship with Students' Physical Fitness and Socioeconomic Status," International Journal of Applied Geospatial Research (IJAGR), IGI Global, vol. 8(3), pages 37-52, July.
    9. Hengyu Gu & Hanchen Yu & Mehak Sachdeva & Ye Liu, 2021. "Analyzing the distribution of researchers in China: An approach using multiscale geographically weighted regression," Growth and Change, Wiley Blackwell, vol. 52(1), pages 443-459, March.
    10. A. Stewart Fotheringham & Wenbai Yang & Wei Kang, 2017. "Multiscale Geographically Weighted Regression (MGWR)," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 107(6), pages 1247-1265, November.
    11. Zhiyu Fan & Qingming Zhan & Chen Yang & Huimin Liu & Meng Zhan, 2020. "How Did Distribution Patterns of Particulate Matter Air Pollution (PM 2.5 and PM 10 ) Change in China during the COVID-19 Outbreak: A Spatiotemporal Investigation at Chinese City-Level," IJERPH, MDPI, vol. 17(17), pages 1-19, August.
    12. Xiangxiang Zhang & Hong Liu, 2022. "Heterogeneity Perspective on the Dynamic Identification of Low-Income Groups and Quantitative Decomposition of Income Increase: Evidence from China," Sustainability, MDPI, vol. 14(15), pages 1-18, July.
    13. Yu Chen & Mengke Zhu & Qian Zhou & Yurong Qiao, 2021. "Research on Spatiotemporal Differentiation and Influence Mechanism of Urban Resilience in China Based on MGWR Model," IJERPH, MDPI, vol. 18(3), pages 1-26, January.
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    Cited by:

    1. Zihan Tong & Zhenxing Kong & Xiao Jia & Jingjing Yu & Tingting Sun & Yimin Zhang, 2023. "Spatial Heterogeneity and Regional Clustering of Factors Influencing Chinese Adolescents’ Physical Fitness," IJERPH, MDPI, vol. 20(5), pages 1-18, February.
    2. Zisis Kozlakidis, 2023. "Promoting Health for Adolescents: An Editorial," IJERPH, MDPI, vol. 20(14), pages 1-4, July.

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