Healthy Relationship Between Peak Filling Rate Reference Value And Environmental Factors

Objective:There are many factors that can affect the peak filling rate of human beings, such as race, heredity, gender, age, living habits and so on. However, the environment factors effect on the peak filling rate also is critical, for instance, altitude, temperature, and so on, all have some effects on the peak filling rate of human beings. Currently, there are little researching on the relationship between peak filling rate and the environment. At the same time, with the lack of normal reference value of peak filling rate in different geographical environment at home and abroad, there are much difficulty for scientific research. So this paper will discuss the relationship between the environment factors and the peak filling rate reference value of normal male and female from18-80years old in different environment conditions of China, for the sake of revealing the geographical distribution of normal reference value of Chinese peak filling rate and providing scientific basis for formulating the normal reference value standards of peak filling rate of healthy people in China. Methods:The reference values of PFR of9948healthy people of eighteen to eighty from30provinces, municipalities and autonomous regions of China were collected. And The persons were divided into6groups which are the young men and women who are18to44years old, the middle-aged men and women who are45to59years old, the old men and women who are60to80years old. Besides, Ten environmental factors which altitude(m), annual sunshine duration(h), annual mean air temperature(℃), annual mean relative humidity(%), annual precipitation amount(mm), annual range of air temperature (℃), annual mean wind speed (m/s), the organic matter of topsoil (%wt), the pH value of topsoil and the bulk density of topsoil were contained in the thesis. To begin with, we analyzed the relationship between the normal reference value of Chinese peak filling rate and environment factors. Besides, we selected the regression analysis, the Curve analysis and the factor analysis altogether to get the equations of the reference value of Chinese peak filling rate. In order to get the best results, by comparing with the peak filling rate’s real value and the predicted value of the models through correlate analysis, regression analysis and factor analysis, we selected the best forecast models of the peak filling rate. Last but not least, with the GIS10.0software we got the regional distribution thematic maps of the PFR reference value of three age groups of normal male and female from18-80years old in China. Results:We found that there was significant correlation relationship between the normal reference value of Chinese peak filling rate and environment factors. And the best forecast models of PFR of the healthy young men, middle-aged men, middle-aged women, elderly women were all the models of correlate analysis, while the best forecast models of PFR of the healthy young women was the model of factor analysis, the best forecast models of PFR of the healthy elderly men was the model of regression analysis. The distribution thematic maps of the PFR reference value of healthy Chinese people showed the regional differences. Conclusion: If the environment factors in some area in China are known, the reference values of PFR of healthy different kinds of Chinese people in this area will be reckoned by using the best forecast models. At the same time, we can also get the PFR predicted reference value of Chinese healthy people anywhere from the regional distribution thematic maps.