Analysis of the Spatial Distribution Characteristics of Abnormal Bone Density in Male Long-Distance Runners from Different Regions in China

• 作者: Longxing Fan Wenjie Zhang Huanhuan Cui Yanqing Liu Ziquan Liu
• 来源期刊: 流行病学期刊(英文)
• 学科: 医学
• 关键词: Spatial Epidemiology REGIONS ATHLETES Bone Density
• 年，卷（期）: 2021,（1）
• 页码范围: 80-91
• 页数: 12页
• 分类号: R68

摘要

<strong>Objective:</strong> To investigate the occurrence pattern of abnormal bone density in male long-distance runners from several different regions of China, and provide a basis for elucidating the influences of geo-environmental differences on bone density. <strong>Methods:</strong> We employed a set of well-designed exclusion-inclusion criteria to recruit study subjects, in which compounding factors were managed and regional environmental traits were fully incorporated. WHO (World Health Organization) criteria for the diagnosis of osteoporosis were then used to examine the subjects to determine occurrence of abnormal bone density. The resulting data were analyzed using methods of spatial statistics, which included several approaches, such as spatial autocorrelation, hot spot analysis, and Geodetector Software analysis, to depict and analyze the spatial distribution of abnormal bone density in male athletes from different regions in China, thereby investigating the influences of geo-environmental factors (e.g., temperature, humidity, and altitude) on bone density. <strong>Results:</strong> A total of 685 subjects were effectively examined in this study, including 486 with normal bone density, 185 with osteopenia, and 14 with osteoporosis. Spatial distribution analysis revealed that the distribution of subjects with abnormal bone density overall exhibited a pattern indicating that the level of abnormal bone density in the eastern regions was higher than that in the western regions and that the levels of abnormal bone density in the southern and northern regions were higher than that in the middle regions. Spatial autocorrelation analysis revealed a Moran’s <em>I</em> = 0.136, <em>Z</em>-score = 1.114, and <em>P</em> value = 0.265 and indicated that the athletes with abnormal bone density were randomly distributed in each region. Hot spot analysis revealed that Tibet and Qinghai displayed distributions of cold spots. Geodetector Software analysis yielded a <em>Q</em> value for annual average temperature of 1