Skip to main content

Table 8 “Selected gender effects adjusted for by body height”

From: Biometry and visual function of a healthy cohort in Leipzig, Germany

Variable under investigation

Statistical significant difference male (m) versus female (f)

Regression analysis

Variable after adjustment for body height based on regression model

men: n = 108

women: n = 110

Mean anterior corneal radius (CCRant)

m: 7.87 (SD 0.25); f: 7.77 (SD 0.26); p = 0.003

CCRant = 6.37 + 0,00837 Height

m: 7.82 (SD 0.24); f: 7.83 (SD 0.26); p = 0.701

Mean posterior corneal radius (CCRpost)

m: 6.51 (SD 0.24); f: 6.43 (SD 0.25); p = 0.014

CCRpost = 5.26 + 0,00699 Height

m: 6.46 (SD 0.23); f: 6.48 (SD 0.24); p = 0.591

Central corneal thickness (CCT)

m: 558.7 (SD 32.3); f: 548.7 (SD 32.0); p = 0.023

CCT = 532 + 0.128 Height

m: 557.3 (SD 32.3); f: 549.2 (SD 32.2); p = 0.064

Anterior chamber depth (ACD)

m: 2.92 (SD 0.35); f: 2.74 (SD 0.38); p < 0.001

ACD = 1.25 + 0,00912 Height

m: 2.86 (SD 0.35); f: 2.81 (SD 0.38); p = 0.314

Anterior chamber volume (ACV)

m: 171.6 (SD 39.2); f: 148.9 (SD 36.7); p < 0.001

ACV = − 43.0 + 1,17 Height

m: 163.9 (SD 38.6); f: 157.8 (SD 36.8); 0.235

Axial length (AL)

m: 24.16 (SD 1.01); f: 23.44 (SD 0.97); p < 0.001

Axial length = 17.0 + 0.0393 Height

m: 23.88 (SD 0.97); f: 23.72 (SD 0.98); p = 0.219

Central foveal subfield thickness (CFST)

m: 284.6 (SD 20.3); f: 273.9 (SD 19.4); p < 0.001

CFST = 182 + 0.562 Height

m: 280.4 (SD 20.3); f: 277.7 (SD 19.2); p = 0.324

Men: n = 103

Women: n = 103

Minimal retinal thickness (CRTmin)

m: 233.4 (SD 20.1) median 232.0; f: 229.8 (SD 19.7) median 228.0; p(MW-U) = 0.162

CRTmin = 194 + 0,216 Height

m: 232.1 (SD 20.1) median: 230.6; f: 231.4 (SD 19.5) median 229.4; p (MW-U) = 0.903

Men: n = 103

Women: n = 103

  1. Caption: Mean data stratified by gender for men (n = 108) and women (n = 110) for corneal radii, CCT, ACD, ACV, AL and retinal thickness measured as CFST and CRTmin. All but CRTmin presented with statistically significant gender effects
  2. Association of respective variables with body height was investigated and adjusted based on a regression model where variable_new = variable_old –regression function + mean (variable_old). After adjustment for body height, all investigated variables presented with no gender effects, therefore differences in stature between men and women may explain some of the differences in the biometric data reported