Dizygotic Male Pairs (N=33) | ||||||||

BIC1 | SSC1 | SUP1 | TRI1 | BIC2 | SSC2 | SUP2 | TRI2 | |

BIC1 | .1538 | |||||||

SSC1 | .1999 | .3007 | ||||||

SUP1 | .2266 | .3298 | .3795 | |||||

TRI1 | .1285 | .1739 | .2007 | .1271 | ||||

BIC2 | .0435 | .0336 | .0354 | .0376 | .1782 | |||

SSC2 | .0646 | .0817 | .0741 | .0543 | .2095 | .3081 | ||

SUP2 | .0812 | .0901 | .0972 | .0666 | .2334 | .3241 | .3899 | |

TRI2 | .0431 | .0388 | .0376 | .0373 | .1437 | .1842 | .2108 | .1415 |

Monozygotic Male Pairs (N=84) | ||||||||

BIC1 | SSC1 | SUP1 | TRI1 | BIC2 | SSC2 | SUP2 | TRI2 | |

BIC1 | .1285 | |||||||

SSC1 | .1270 | .1759 | ||||||

SUP1 | .1704 | .2156 | .3031 | |||||

TRI1 | .1035 | .1101 | .1469 | .1041 | ||||

BIC2 | .0982 | .1069 | .1491 | .0824 | .1233 | |||

SSC2 | .0999 | .1411 | .1848 | .0880 | .1295 | .1894 | ||

SUP2 | .1256 | .1654 | .2417 | .1095 | .1616 | .2185 | .2842 | |

TRI2 | .0836 | .0907 | .1341 | .0836 | .1010 | .1134 | .1436 | .1068 |

Variable Labels: BIC=Biceps; SSC=Subscapular; SUP=Suprailiac; | ||||||||

TRI=Triceps. ``1'' and ``2'' refer to measures on first and second twins |

An example Mx program for estimating the Cholesky factors of the additive genetic and within-family environmental covariance matrices is given in Appendix . The matrices

Genetic Factor | Environmental Factor | ||||||||

Variable | 1 | 2 | 3 | 4 | 1 | 2 | 3 | 4 | |

BIC | 0.340 | 0.000 | 0.000 | 0.000 | 0.170 | 0.000 | 0.000 | 0.000 | |

SSC | 0.396 | 0.182 | 0.000 | 0.000 | 0.160 | 0.138 | 0.000 | 0.000 | |

SUP | 0.487 | 0.159 | 0.148 | 0.000 | 0.180 | 0.117 | 0.093 | 0.000 | |

TRI | 0.288 | 0.016 | 0.036 | 0.110 | 0.117 | 0.039 | -0.004 | 0.085 |

Carrying out the pre- and post-multiplication of the Cholesky factors (see equations 10.8 and 10.9) gives the maximum-likelihood estimates of the genetic and environmental covariance matrices, which we present in the upper part of Table 10.9. The lower part of Table 10.9 gives the matrices of genetic and environmental correlations derived from these covariances (see 10.5 and 10.6).

Genetic | Environmental | ||||||||

Variable | BIC | SSC | SUP | TRI | BIC | SSC | SUP | TRI | |

BIC | 0.116 | 0.135 | 0.166 | 0.098 | 0.029 | 0.027 | 0.030 | 0.020 | |

SSC | 0.909 | 0.190 | 0.222 | 0.117 | 0.759 | 0.044 | 0.045 | 0.024 | |

SUP | 0.914 | 0.955 | 0.284 | 0.148 | 0.769 | 0.908 | 0.054 | 0.025 | |

TRI | 0.927 | 0.863 | 0.894 | 0.097 | 0.778 | 0.757 | 0.716 | 0.023 | |

Note: The variances are given on the diagonals of the two matrices |

We see that the genetic correlations between the four skinfold measures are indeed very large, suggesting that the amount of fat at different sites of the body is almost entirely under the control of the same genetic factors. However, in this example, the environmental correlations also are quite large, suggesting that environmental factors which affect the amount of fat at one site also have a generalized effect over all sites.