呼和浩特市商业型健身房空间格局及其影响因素分析

Analysis of the Spatial Layout and Influencing Factors of Commercial Gyms in Hohhot City

摘要: 随着“健康中国”战略的深入推进和全民健身需求的持续增长，商业型健身房已成为城市空间重构的重要载体。本文以呼和浩特市中心城区(玉泉区、新城区、回民区、赛罕区)为研究对象，基于1001个商业型健身房POI数据，综合运用标准差椭圆、核密度估计、最近邻指数及地理探测器模型，定量分析其空间格局特征及影响因素。研究表明：1) 空间分布呈“核心集聚 + 外围组团”模式，核密度高值区集中于赛罕区与新城区交界处，形成主核心；次级集聚点分布于新城区政策倾斜区，玉泉区与回民区分布稀疏，总体呈现东密西疏的不均衡特征。2) 标准差椭圆显示空间延展方向为“东–西”轴向，方向性明显，离散程度较低。3) 最近邻指数为0.405 (P < 0.01)，证实空间集聚显著。4) 地理探测器模型揭示交通便捷度、人口密度、居民购买力、经济质量是核心驱动因子，且因子间存在双变量增强交互效应。其中交通路网密度贡献最强，反映健身房高度邻近城市干道分布。5) 呼和浩特市商业型健身房空间分布受城市“一核双心”结构驱动，但存在核心–边缘失衡问题。未来优化需侧重交通设施建设，结合人口分布与经济活力优化布局，同时探索民族地区文化多元性对健身消费的潜在影响，本研究为健康中国战略下城市健身空间规划提供了实证依据与方法参考。

Abstract: With the in-depth advancement of the “Healthy China” strategy and the continuous growth of the demand for mass fitness, commercial gyms have become an important carrier for the reconstruction of urban space. This paper takes the central urban area of Hohhot (Yuquan District, Xincheng District, Huimin District, Saihan District) as the research object, based on 1001 POI data of commercial gyms, and comprehensively uses standard deviation ellipse, kernel density estimation, nearest neighbor index and geographical detector model to quantitatively analyze the spatial pattern characteristics and influencing factors. The research shows that: 1) The spatial distribution presents a “core aggregation + peripheral clusters” pattern, with high-density areas concentrated at the junction of Saihan District and Xincheng District, forming the main core; secondary aggregation points are distributed in the policy-tilted areas of Xincheng District, while the distribution in Yuquan District and Huimin District is sparse, overall showing an unbalanced feature of being denser in the east and sparser in the west. 2) The standard deviation ellipse shows that the spatial extension direction is along the “east-west” axis, with a clear directionality and low degree of dispersion. 3) The nearest neighbor index is 0.405 (P < 0.01), confirming significant spatial aggregation. 4) The geographical detector model reveals that traffic convenience, population density, residents’ purchasing power, and economic quality are the core driving factors, and there are bivariate enhancement interaction effects among the factors. Among them, the contribution of traffic network density is the strongest, reflecting that gyms are highly adjacent to urban arterial roads. 5) The spatial distribution of commercial gyms in Hohhot is driven by the city’s “one core and two centers” structure, but there is a core-periphery imbalance problem. Future optimization should prioritize improving the facility coverage in areas with weak transportation, guide balanced layout in combination with population distribution and economic vitality, and explore the potential impact of cultural diversity in ethnic areas on fitness consumption. This study provides empirical evidence and methodological references for urban fitness space planning under the “Healthy China” strategy.