Abstract
The fetal origins hypothesis emphasizes the life-long health impacts of prenatal conditions. Birth weight, birth length, and gestational age are indicators of the fetal environment. However, these variables often have missing data and are subject to random and systematic errors caused by delays in measurement, differences in measurement instruments, and human error. With data from the Cebu (Philippines) Longitudinal Health and Nutrition Survey, we use structural equation models, to explore random and systematic errors in these birth outcome measures, to analyze how maternal characteristics relate to birth outcomes, and to take account of missing data. We assess whether birth weight, birth length, and gestational age are influenced by a single latent variable that we call favorable fetal growth conditions (FFGC) and if so, which variable is most closely related to FFGC. We find that a model with FFGC as a latent variable fits as well as a less parsimonious model that has birth weight, birth length, and gestational age as distinct individual variables. We also demonstrate that birth weight is more reliably measured than is gestational age. FFGCs were significantly influenced by taller maternal stature, better nutritional stores indexed by maternal arm fat and muscle area during pregnancy, higher birth order, avoidance of smoking, and maternal age 20-35 years. Effects of maternal characteristics on newborn weight, length, and gestational age were largely indirect, operating through FFGC.