| Objective:Pulse wave velocity (PWV), augment index (AI), arterial compliance (AC), pressure-strain elastic coefficient (Ep) and stiffness parameter (β) are important indicators reflecting arterial elasticity. They are non-invasive, and have significance in clinical diagnosis of cardiovascular disease. The existing researches have shown that there are many factors, which can influence the reference value of arterial elastic indicators, including blood pressure, age, monitoring site, living habits (like smoking, drinking, etc.). At present, it still lacks research on the relationship between arterial elastic indicators’ reference value and environment. There is no uniform standard of arterial elastic indicators’ reference value. The study of geographical factors’influence on arterial elastic index reference value is a quantitative analysis. It provides a scientific basis for the selection of arterial elastic indicators’reference value, and has important application value.Methods:Used literature retrieval method to collected carotid arterial elastic indicators’ value of healthy people from different region of China, and finally selected 8799 samples’carotid arterial PWVβ value measured by the relevant departments from 39 regions,8907 samples’carotid arterial β value measured by the relevant departments from 39 regions,6794 samples’ carotid arterial AC value measured by the relevant departments from 41 regions,7167 samples’ carotid arterial Ep value measured by the relevant departments from 42 regions,5474 samples’ carotid arterial AI value measured by the relevant departments from 39 regions. Used correlation analysis to research the relationship between the 5 indicators and 25 geographical factors, including altitude, longitude, latitude, the annual average temperature, annual sunshine hours, annual average relative humidity, annual temperature range, annual precipitation, annual average wind speed, topsoil sand content, topsoil clay content, topsoil silt content, topsoil reference capacity, topsoil bulk density, topsoil gravel content, topsoil organic carbon, PH, topsoil CEC (soil), topsoil CEC (clay), topsoil base saturation, topsoil TEB, topsoil gypsum, topsoil calcium carbonate, topsoil sodicity (ESP), topsoil salinity (ECe). Choose related geographical factors of each elastic indicator to construct prediction model by regression analysis and principal component analysis. Use spatial analysis, applied by ArcGIS, to explore the spatial distribution of each carotid artery elastic indicator’s reference value.Results:Correlation analysis has showed that there was significant correlation between the reference value of each carotid arterial elastic indicator (PWVβ, AC,β, Ep, AI) and a numbers of geographical factors. The reference value of PWVβ is negatively associated with latitude, annual temperature range, annual sunshine hours and annual average wind speed, topsoil PH, topsoil CEC (clay), topsoil base saturation, topsoil and salinity (ECe), and positive associated with annual average temperature, annual precipitation and annual average relative humidity. The reference value of AC is positive associated with latitude, annual temperature range and topsoil CEC (clay), and negatively associated with annual average temperature and annual precipitation. The reference value of β is negatively associated with latitude, annual temperature range, annual sunshine hours, annual average wind speed, topsoil sand fraction, topsoil PH, topsoil CEC (clay), topsoil base saturation, topsoil and salinity (ECe), and positive associated with annual average temperature, annual precipitation and annual average relative humidity. The reference value of Ep is negatively associated with latitude, annual temperature range, annual sunshine hours and topsoil CEC (clay), and positive associated with annual average temperature and annual precipitation. The reference value of AI is negatively associated with latitude, annual sunshine hours and topsoil CEC (clay), and positive associated with topsoil gravel content and topsoil CEC (soil). By the comparative study of the linear regression model and principal component analysis model, we obtained 5 optimal prediction model of the indicators’reference value. Finally fit out the geographical distribution map of the five indices’reference value by spatial analysis based on the optimal models.Conclusion:The reference value of each indicator has certain regularity in the spatial distribution. On the whole, the distribution of middle-aged carotid PWVP’s reference value in China is that the reference value of west is higher than which of east, while the value of south is higher than which of north. The distribution of middle-aged carotid AC reference value in China is that the reference value of north is higher than which of south, and descending from north to south. The distribution of middle-aged carotid P reference value in China is that the reference value of south is higher than which of north, and increasing from north to south. The distribution of middle-aged carotid Ep reference value in China is that the reference value of north is lower than which of south, and increasing from north to south. The distribution of middle-aged carotid AI reference value in China is that the reference value of south is higher than north. |
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