The effect of geographical indices on left ventricular structure in healthy Han Chinese population

Minyi Cen1, Miao Ge2, Yonglin Liu1

  • 1College of Tourism and Environment, Shaanxi Normal University, Chang'an Road NO.620, Xi'an, 710119, China.

Insights

Geographical factors like latitude and temperature significantly influence left ventricular (LV) structural indices in healthy Han adults. A back propagation neural network model accurately predicts these variations across China, showing higher values in the west.

Area of Science:

  • Cardiology
  • Geomedicine
  • Biostatistics

Background:

  • Left ventricular posterior wall thickness (LVPWT) and interventricular septum thickness (IVST) are key indicators of left ventricular (LV) structure.
  • Understanding geographical influences on these indices is crucial for establishing regional health standards.

Purpose of the Study:

  • To investigate the impact of geographical factors on LV structural indices in healthy Han adults in China.
  • To develop predictive models for LV structural indices based on geographical variables.
  • To create a scientific basis for unified reference values of adult LV structural indices in China.

Main Methods:

  • Correlation analysis was used to examine relationships between 15 geographical indices and LV structural indices.
  • Back propagation neural network (BPNN) and support vector regression (SVR) models were developed for prediction.
  • Geographical distribution maps of LV structural indices were generated.

Main Results:

  • LV structural indices showed significant associations with latitude, longitude, altitude, temperature, wind velocity, and soil properties.
  • The BPNN model demonstrated superior predictive accuracy compared to the SVR model.
  • LV structural indices were found to be higher in western China and lower in eastern China.

Conclusions:

  • Geographical environment significantly affects the reference values of adult LV structural indices.
  • BPNN models offer a practical approach for calculating regional LV structural index reference values.
  • Geographical distribution maps visually represent regional variations in LV structural indices.