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