Institute of Health Geography, School of Geography and Tourism, Shaanxi Normal University, Xi'an, 710119, China.
National Demonstration Center for Experimental Geography Education, Shaanxi Normal University, Xi'an, 710119, Shaanxi, China.
Int J Biometeorol. 2018 Dec;62(12):2099-2107. doi: 10.1007/s00484-018-1585-4. Epub 2018 Oct 27.
The blood urea nitrogen (BUN) is generally regarded as a significant serum marker in estimating renal function. This study aims to explore the geographical distribution of BUN reference values of Chinese healthy adults, and provide a scientific basis for determining BUN reference values of Chinese healthy adults of different regions according to local conditions. A total of 25,568 BUN reference values of healthy adults from 241 Chinese cities were collected in this study, and 17 geographical indices were selected as explanatory variables. The correlation analysis was used to examine the significance between BUN reference value and geographical factors, then five significant indices were extracted to build two predictive models, including principal component analysis (PCA) and support vector regression (SVR) model, then the optimal model was selected by model test to predict BUN reference values of the whole China, finally the distribution map was produced. The results show that BUN reference value of Chinese healthy adult was characteristically associated with latitude, altitude, annual mean temperature, annual mean relative humidity, and annual precipitation. The model test shows, compared with SVR model, the PCA model possesses superior simulative and predictive ability. The distribution map shows that the BUN reference values of Chinese healthy adult are lower in the east and higher in the west. These results indicate that the BUN reference value is significantly affected by geographical environment, and the BUN reference values of different regions could be seen clearly on distribution map.
血尿素氮(BUN)通常被认为是评估肾功能的重要血清标志物。本研究旨在探讨中国健康成年人 BUN 参考值的地理分布,为根据当地情况确定中国不同地区健康成年人 BUN 参考值提供科学依据。本研究共收集了来自中国 241 个城市的 25568 例健康成年人的 BUN 参考值,并选择了 17 个地理指标作为解释变量。采用相关分析检验 BUN 参考值与地理因素之间的显著性,然后提取 5 个显著指标,建立主成分分析(PCA)和支持向量回归(SVR)模型两个预测模型,通过模型测试选择最优模型来预测中国健康成年人的 BUN 参考值,最后生成分布图。结果表明,中国健康成年人的 BUN 参考值与纬度、海拔、年平均气温、年平均相对湿度和年降水量具有显著相关性。模型测试表明,与 SVR 模型相比,PCA 模型具有更好的模拟和预测能力。分布图显示,中国健康成年人的 BUN 参考值呈现出东部低、西部高的特点。这些结果表明,BUN 参考值受到地理环境的显著影响,分布图可以清晰地看到不同地区的 BUN 参考值差异。