Han Xiao, Ge Miao, Dong Jie, Xue Ranying, Wang Zixuan, He Jinwei
Department of Geography, Tourism and Environment College of Shaanxi Normal University, Xi'an, 710119 Shaanxi, China.
Exp Gerontol. 2014 Sep;57:250-5. doi: 10.1016/j.exger.2014.06.014. Epub 2014 Jun 21.
The aim of this paper is to analyze the geographical distribution of reference value of aging people's left ventricular end systolic diameter (LVDs), and to provide a scientific basis for clinical examination.
The study is focus on the relationship between reference value of left ventricular end systolic diameter of aging people and 14 geographical factors, selecting 2495 samples of left ventricular end systolic diameter (LVDs) of aging people in 71 units of China, in which including 1620 men and 875 women. By using the Moran's I index to make sure the relationship between the reference values and spatial geographical factors, extracting 5 geographical factors which have significant correlation with left ventricular end systolic diameter for building the support vector regression, detecting by the method of paired sample t test to make sure the consistency between predicted and measured values, finally, makes the distribution map through the disjunctive kriging interpolation method and fits the three-dimensional trend of normal reference value.
It is found that the correlation between the extracted geographical factors and the reference value of left ventricular end systolic diameter is quite significant, the 5 indexes respectively are latitude, annual mean air temperature, annual mean relative humidity, annual precipitation amount, annual range of air temperature, the predicted values and the observed ones are in good conformity, there is no significant difference at 95% degree of confidence. The overall trend of predicted values increases from west to east, increases first and then decreases from north to south.
If geographical values are obtained in one region, the reference value of left ventricular end systolic diameter of aging people in this region can be obtained by using the support vector regression model. It could be more scientific to formulate the different distributions on the basis of synthesizing the physiological and the geographical factors.
-Use Moran's index to analyze the spatial correlation. -Choose support vector machine to build model that overcome complexity of variables. -Test normal distribution of predicted data to guarantee the interpolation results. -Through trend analysis to explain the changes of reference value clearly.
本文旨在分析老年人左心室收缩末期内径（LVDs）参考值的地理分布情况，为临床检查提供科学依据。
本研究聚焦于老年人左心室收缩末期内径参考值与14个地理因素之间的关系，选取了中国71个单位的2495例老年人左心室收缩末期内径（LVDs）样本，其中男性1620例，女性875例。通过使用莫兰指数（Moran's I index）确定参考值与空间地理因素之间的关系，提取与左心室收缩末期内径有显著相关性的5个地理因素用于构建支持向量回归模型，采用配对样本t检验方法进行检测以确保预测值与测量值之间的一致性，最后通过析取克里金插值法制作分布图并拟合正常参考值的三维趋势。
发现所提取的地理因素与左心室收缩末期内径参考值之间的相关性非常显著，这5个指标分别为纬度、年平均气温、年平均相对湿度、年降水量、气温年较差，预测值与观测值吻合良好，在95%置信度下无显著差异。预测值的总体趋势是从西向东增加，从北向南先增加后减少。
如果获取了某一地区的地理值，就可以通过支持向量回归模型得到该地区老年人左心室收缩末期内径的参考值。综合生理和地理因素制定不同的分布情况可能会更科学。
