title: Reference value of presenile human hematocrit and geographical factors.
abstract: The aim of this study was to provide a scientific basis for a unified standard of the reference value of healthy presenile human hematocrit in China. We studied the relationship between the reference values of healthy presenile human hematocrit, tested according to Wintrobe's laws, and five geographical factors. It was found that altitude is the most important factor affecting the reference value of the hematocrit. As the altitude gradually increases, the reference value of the hematocrit also increases. The relationship is quite significant. By using the method of stepwise regression analysis, two multivariate regression equations were deduced: Y1 = 39.7 + 0.00328X1 + 0.00169X2 + 0.00117X5 +/- 2.3, Y2 = 38.8 + 0.00275X1 + 0.000578X2 -0.00298X4 +/- 2.2 In these equations, Y1 is the reference value of presenile men's hematocrit (%); Y2 is the reference value of presenile women's hematocrit (%); X1 is altitude (m); X2 is the average annual hours of sunshine (h); X4 is the average annual temperature (degrees C), and X5 is the average annual precipitation (mm). If the geographical index values in a particular area in China are known, the reference value of presenile human hematocrit in this area can be calculated approximately by means of the regression equations.
authors.affiliation: Department of Geography, Shaanxi Normal University, Xi'an, People's Republic of China.
authors.forename: Ge
authors.initials: G
authors.lastname: Miao
authors.forename: Yang
authors.initials: Y
authors.lastname: Qingsheng
authors.forename: Ren
authors.initials: R
authors.lastname: Zhiyuan
authors.forename: Zhang
authors.initials: Z
authors.lastname: Hongxian
authors.forename: Zhang
authors.initials: Z
authors.lastname: Yanfang
authors.forename: Yin
authors.initials: Y
authors.lastname: Shuyan
mesh_terms: D002681:China; D005260:Female; D006400:Hematocrit; D018056:Hemorheology; D006801:Humans; D008297:Male; D008875:Middle Aged; D012016:Reference Values; D012044:Regression Analysis