Analyzing sibship correlations in birth weight using large sibships from Norway.
Data from the Medical Birth Registry of Norway were used to estimate sibship correlations in large sibships (each with > or = 5 infants among singleton live births surviving the first year of life), while adjusting for covariates such as infant gender, gestational age, maternal age, parity, and time since last pregnancy. This sample of 12,356 full sibs in 2,462 sibships born in Norway between 1968 and 1989 was selected to maximize the information on parity, and a robust approach to estimating both regression coefficients and the sibship correlation using generalized estimating equations (GEE) was employed. In concordance with previous studies, these data showed a high overall correlation in birth weight among full sibs (0.48 +/- 0.01), but this sibship correlation was influenced by parity. In particular, the correlation between the firstborn infant and a subsequent infant was slightly lower than between two subsequent sibs (0.44 +/- 0.01 vs. 0.50 +/- 0.01, respectively). The effect of time between pregnancies was statistically significant, but its predicted impact was modest over the period in which most of these large families were completed. While these data cannot discriminate whether factors influencing birth weight are maternal or fetal in nature, this analysis does illustrate how robust statistical models can be used to estimate sibship correlations while adjusting for covariates in family studies.
Beaty
T H
TH
Department of Epidemiology, School of Hygiene and Public Health, Johns Hopkins University, Baltimore, Maryland 21205, USA.
Skjaerven
R
R
Breazeale
D R
DR
Liang
K Y
KY
D001719:Birth Certificates; D001724:Birth Weight; D016000:Cluster Analysis; D005260:Female; D005838:Genotype; D005865:Gestational Age; D006801:Humans; D007231:Infant, Newborn; D016013:Likelihood Functions; D016014:Linear Models; D008297:Male; D008423:Maternal Age; D015233:Models, Statistical; D009664:Norway; D009679:Nuclear Family; D010298:Parity; D011247:Pregnancy; D012042:Registries; D012044:Regression Analysis