PDF(Pubmed)
Abstract：
UNASSIGNED: Although the regular exercise population is a key metric for gaging the success of China\'s fitness-for-all activities, effective policy approaches to increase mass sports participation remain unclear. Previous research suggests that GDP, educational attainment, sports resources, and meteorological conditions could influence regular exercise participation. Therefore, this study first analyzed the macro-level correlates influencing China\'s regular exercise population.
UNASSIGNED: We utilize ordinary least squares (OLS) regression and geographical weighted regression (GWR) to theorize the relationship. The analysis encompasses data from the 31 administrative regions of Mainland China, as reported at the end of the 13th Five-Year Plan period. The log-log model enables us to quantify the marginal effect (elasticity) of the explanatory variables.
UNASSIGNED: The OLS regression showed that regional GDP and the proportion of the population with a university education were significant predictors. In the global model, the marginal effects of regional GDP and university education were 0.048 and 0.173, respectively. Furthermore, the GWR revealed a distinct geographic pattern that corresponds to the classic Hu Line.
UNASSIGNED: While regional GDP was also a significant correlate in our model, the elasticity demonstrates that university education had an asymmetric effect on China\'s regular exercise population. Therefore, this paper sheds light on a policy priority for the upcoming 15th Five-Year Plan, emphasizing the strategic importance of expanding university education to enhance mass sports participation. In turn, a better-educated populace may yield significant secondary effects on public health and contribute to the high-quality development of the Chinese path to modernization.
UNASSIGNED: We utilize ordinary least squares (OLS) regression and geographical weighted regression (GWR) to theorize the relationship. The analysis encompasses data from the 31 administrative regions of Mainland China, as reported at the end of the 13th Five-Year Plan period. The log-log model enables us to quantify the marginal effect (elasticity) of the explanatory variables.
UNASSIGNED: The OLS regression showed that regional GDP and the proportion of the population with a university education were significant predictors. In the global model, the marginal effects of regional GDP and university education were 0.048 and 0.173, respectively. Furthermore, the GWR revealed a distinct geographic pattern that corresponds to the classic Hu Line.
UNASSIGNED: While regional GDP was also a significant correlate in our model, the elasticity demonstrates that university education had an asymmetric effect on China\'s regular exercise population. Therefore, this paper sheds light on a policy priority for the upcoming 15th Five-Year Plan, emphasizing the strategic importance of expanding university education to enhance mass sports participation. In turn, a better-educated populace may yield significant secondary effects on public health and contribute to the high-quality development of the Chinese path to modernization.
摘要：
■尽管定期锻炼人群是衡量中国全民健身活动成功与否的关键指标，增加群众体育参与的有效政策方法仍不清楚。以前的研究表明，GDP，教育程度,体育资源,气象条件可能会影响定期锻炼的参与。因此,本研究首先分析了影响中国规律锻炼人群的宏观层面相关因素。
■我们利用普通最小二乘（OLS）回归和地理加权回归（GWR）来对关系进行理论化。分析包括来自中国大陆31个行政区的数据，在“十三五”期末报告。对数-对数模型使我们能够量化解释变量的边际效应(弹性)。
■OLS回归表明，地区GDP和受过大学教育的人口比例是重要的预测因素。在全局模型中，地区GDP和大学教育的边际效应分别为0.048和0.173。此外，GWR揭示了与经典胡线相对应的独特地理格局。
■虽然地区GDP在我们的模型中也是一个显著的相关性，弹性表明，大学教育对中国正常运动人群的影响是不对称的。因此,本文阐明了即将到来的“十五”计划的政策重点，强调扩大大学教育对增强群众体育参与的战略重要性。反过来,受过良好教育的民众可能会对公共卫生产生重大的二次影响，并有助于中国现代化道路的高质量发展。
■我们利用普通最小二乘（OLS）回归和地理加权回归（GWR）来对关系进行理论化。分析包括来自中国大陆31个行政区的数据，在“十三五”期末报告。对数-对数模型使我们能够量化解释变量的边际效应(弹性)。
■OLS回归表明，地区GDP和受过大学教育的人口比例是重要的预测因素。在全局模型中，地区GDP和大学教育的边际效应分别为0.048和0.173。此外，GWR揭示了与经典胡线相对应的独特地理格局。
■虽然地区GDP在我们的模型中也是一个显著的相关性，弹性表明，大学教育对中国正常运动人群的影响是不对称的。因此,本文阐明了即将到来的“十五”计划的政策重点，强调扩大大学教育对增强群众体育参与的战略重要性。反过来,受过良好教育的民众可能会对公共卫生产生重大的二次影响，并有助于中国现代化道路的高质量发展。
