Table 5.
Association between serum sex hormone levels and the proportion of normal sperm morphologya
Sperm parameters | n | Normal sperm morphology (%) | ||
---|---|---|---|---|
Least-squares mean (95% CI) | P | P for trend | ||
Luteinizing hormone | ||||
Tertile 1 | 112 | 6.8(6.5, 7.5) | Ref | 0.01 |
Tertile 2 | 114 | 6.9(6.4, 7.3) | 0.74 | |
Tertile 3 | 112 | 6.0(5.5, 6.5) | 0.01 | |
Luteinizing hormoneb | ||||
Tertile 1 | 111 | 6.9(6.4, 7.4) | Ref | 0.04 |
Tertile 2 | 111 | 6.8(6.4, 7.3) | 0.87 | |
Tertile 3 | 109 | 6.1(5.6, 6.6) | 0.04 | |
Follicle-stimulating hormone | ||||
Tertile 1 | 112 | 7.0(6.5, 7.5) | Ref | 0.01 |
Tertile 2 | 114 | 6.8(6.3, 7.3) | 0.46 | |
Tertile 3 | 112 | 6.0(5.5, 6.5) | 0.01 | |
Follicle-stimulating hormoneb | ||||
Tertile 1 | 109 | 7.0(6.5, 7.5) | Ref | 0.02 |
Tertile 2 | 114 | 6.8(6.3, 7.2) | 0.54 | |
Tertile 3 | 108 | 6.1(5.6, 6.6) | 0.02 | |
Total testosterone | ||||
Tertile 1 | 96 | 7.1(6.5, 7.6) | Ref | 0.06 |
Tertile 2 | 97 | 6.8(6.2, 7.3) | 0.41 | |
Tertile 3 | 97 | 6.3(5.7, 6.9) | 0.06 | |
Free testosterone | ||||
Tertile 1 | 96 | 6.7(6.1, 7.2) | Ref | 0.94 |
Tertile 2 | 97 | 6.7(6.2, 7.2) | 0.99 | |
Tertile 3 | 97 | 6.7(6.2, 7.3) | 0.94 | |
Total estradiol | ||||
Tertile 1 | 113 | 6.5(6.0, 7.0) | Ref | 0.91 |
Tertile 2 | 115 | 6.8(6.3, 7.3) | 0.50 | |
Tertile 3 | 110 | 6.6(6.1, 7.1) | 0.92 | |
Free estradiol | ||||
Tertile 1 | 96 | 6.5(5.9, 7.0) | Ref | 0.49 |
Tertile 2 | 97 | 6.9(6.4, 7.4) | 0.27 | |
Tertile 3 | 97 | 6.7(6.2, 7.3) | 0.50 | |
Sex hormone-binding hormone | ||||
Tertile 1 | 112 | 7.0(6.5, 7.6) | Ref | 0.06 |
Tertile 2 | 113 | 6.5(6.0, 7.0) | 0.14 | |
Tertile 3 | 113 | 6.3(5.8, 6.8) | 0.06 |
aGeneral linear models were adjusted for age at sample collection, BMI (continuous), current smoking (yes or no), and current alcohol consumption (yes or no). P for trend was calculated by treating hormone categories as ordinal predictors in multivariate linear regression models
bMutual adjustment for hormones associated with the proportion of normal sperm morphology in multivariate linear regression models