Abstract Birth-weight-specific infant mortality is examined using a novel statistical procedure, parametric mixtures of logistic regressions. The results indicate that birth cohorts are composed of two or more subpopulations that are heterogeneous with respect to infant mortality. One subpopulation appears to account for the "normal" process of fetal development, while the other, which accounts for the majority of births at both low and high birth weights, may represent fetuses that were "disturbed" during development. Surprisingly, estimates of neonatal and infant mortality indicate that the "disturbed" subpopulation has lower birth-weight-specific mortality, although overall crude mortality rates are higher for this subpopulation. It is hypothesized that this is due to high rates of fetal loss among the "disturbed" subpopulation, resulting in a highly selected group at birth. The heterogeneity identified in the birth cohort could be responsible for recent decelerations in the decline in infant mortality, and might be the cause of unexplained ethnic differences in birth-weight-specific infant mortality. The novel statistical methodology developed here has broad application within human biology. In particular, it could be used in any context where parametric mixture modeling is applied, such as complex segregation analysis.