Predictive models and spatial variations of vital capacity in healthy people from 6 to 84 years old in China based on geographical factors

• Published in: International journal of biometeorology Vol. 58; no. 5; pp. 769 - 779
• Main Authors: He, Jinwei, Ge, Miao, Wang, Congxia, Jiang, Naigui, Zhang, Mingxin, Yun, Pujun
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer-Verlag 01.07.2014; Springer Berlin Heidelberg; Springer Nature B.V
• Subjects: Adolescent; Adult; Aged; Aged, 80 and over; Air temperature; altitude; Animal Physiology; atmospheric precipitation; Biological and Medical Physics; Biophysics; Child; China; computer software; Earth and Environmental Science; Environment; Environmental Health; Female; females; Geographical distribution; Geography; Humans; kriging; Male; males; Meteorology; Middle Aged; Models, Theoretical; Original Paper; people; Plant Physiology; Prediction models; Public health; Reference Values; Relative humidity; solar radiation; Spatial Analysis; t-test; Vital Capacity; Weather; Wind speed; Young Adult; China; China, People's Rep; Vital capacity; Spatial variation; Geographical factor; Modeling
• ISSN: 0020-7128; 1432-1254; 1432-1254
• DOI: 10.1007/s00484-013-0658-7

The aim of this study was to provide a scientific basic for a unified standard of the reference value of vital capacity (VC) of healthy subjects from 6 and 84 years old in China. The normal reference value of VC was correlated to seven geographical factors, including altitude (X ₁), annual duration of sunshine (X ₂), annual mean air temperature (X ₃), annual mean relative humidity (X ₄), annual precipitation amount (X ₅), annual air temperature range (X ₆) and annual mean wind speed (X ₇). Predictive models were established by five different linear and nonlinear methods. The best models were selected by t-test. The geographical distribution map of VC in different age groups can be interpolated by Kriging’s method using ArcGIS software. It was found that the correlation of VC and geographical factors in China was quite significant, especially for both males and females aged from 6 to 45. The best models were built for different age groups. The geographical distribution map shows the spatial variations of VC in China precisely. The VC of healthy subjects can be simulated by the best model or acquired from the geographical distribution map provided the geographical factors for that city or county of China are known.