Abstract

Equitable access to sports services has drawn much attention from policymakers and planners in China, as rapid urbanization and lifestyle changes have caused the pandemic of inactivity. An accurate measure of accessibility will enable the spatial equity of public facility allocation. Existing approaches to measure the spatial accessibility of sports facilities tend to ignore the heterogeneity in potential users’ preferences for facilities, thereby causing a bias in the measurement of accessibility. This paper proposes a multi-preference Gaussian two-step floating catchment area (MG2SFCA) method to measure the spatial accessibility of sports facilities, taking into account different travel modes, catchment sizes, and facility preferences among different age groups. Empirically, we adopted the MG2SFCA method in examining the spatial accessibility of sports facilities among children, young working-age population, old working-age population, and elderly population under walking, cycling, and driving modes in Dongguan. The results indicated a significant spatial disparity in the accessibility to sports facilities, with better accessibility in the north and poorer accessibility in the south. Children have the best access to sports facilities, followed by old working-age population, young working-age population, and older population. In the comparison among different transport modes, the accessibility distribution of sports facilities in walking mode showed the greatest spatial variation, while accessibility in driving mode was the most balanced. The MG2SFCA method is superior to the traditional Gaussian 2SFCA method because the former can capture disadvantaged people’s actual needs for sports facilities more accurately than the latter.

Highlights

  • List of abbreviations: 2SFCA: two-step floating catchment area; MG2SFCA: multi-preference Gaussian two-step floating catchment area; enhanced 2SFCA (E2SFCA): enhanced two-step floating catchment area; CHNS: China Health and Emerging evidence suggests that regular physical activity has a beneficial impact on physical and mental health, including increased positive effect, less loneliness, and reduced rates of obesity, diabetes and cardiovascular disease (Bourke et al, 2021; Gyasi et al, 2020; Hunter and Reddy, 2013; Senaratne et al, 2021; White et al, 2017; Zulyniak et al, 2020)

  • A plethora of studies have reported that the availability and accessibility of sports and recreational services play a prominent role in physical activity attainment (Halonen et al, 2015; Heath et al, 2012; Humpel et al, 2002; Liu et al, 2019)

  • To advance the field of measuring the spatial accessibility of sports facilities, we aim to propose a new, improved model, the multi-preference Gaussian two-step floating catchment area (MG2SFCA) method based on the original 2SFCA, allowing for a more accurate and rational measurement

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Summary

Introduction

Emerging evidence suggests that regular physical activity has a beneficial impact on physical and mental health, including increased positive effect, less loneliness, and reduced rates of obesity, diabetes and cardiovascular disease (Bourke et al, 2021; Gyasi et al, 2020; Hunter and Reddy, 2013; Senaratne et al, 2021; White et al, 2017; Zulyniak et al, 2020). With increasing emphasis on health and well-being, the promotion of physical activity has aroused intense attention from the government, the public, and researchers. In this regard, a plethora of studies have reported that the availability and accessibility of sports and recreational services play a prominent role in physical activity attainment (Halonen et al, 2015; Heath et al, 2012; Humpel et al, 2002; Liu et al, 2019). At present, approximately a quarter of adults and three-quarters of adolescents around the world fail to reach this recommendation, which is partially attributable to poor planning and design of sports and recreational facilities (WHO, 2018). Existing approaches to measure the spatial accessibility of sports facilities tend to ignore the heterogeneity in potential users’ demands and facility preferences, thereby causing a bias in the measurement of accessibility

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