Two denominators for one numerator: the example of neonatal mortality

Abstract

Preterm delivery is one of the strongest predictors of neonatal mortality. A given exposure may increase neonatal mortality directly, or indirectly by increasing the risk of preterm birth. Efforts to assess these direct and indirect effects are complicated by the fact that neonatal mortality arises from two distinct denominators (i.e. two risk sets). One risk set comprises fetuses, susceptible to intrauterine pathologies (such as malformations or infection), which can result in neonatal death. The other risk set comprises live births, who (unlike fetuses) are susceptible to problems of immaturity and complications of delivery. In practice, fetal and neonatal sources of neonatal mortality cannot be separated-not only because of incomplete information, but because risks from both sources can act on the same newborn. We use simulations to assess the repercussions of this structural problem. We first construct a scenario in which fetal and neonatal factors contribute separately to neonatal mortality. We introduce an exposure that increases risk of preterm birth (and thus neonatal mortality) without affecting the two baseline sets of neonatal mortality risk. We then calculate the apparent gestational-age-specific mortality for exposed and unexposed newborns, using as the denominator either fetuses or live births at a given gestational age. If conditioning on gestational age successfully blocked the mediating effect of preterm delivery, then exposure would have no effect on gestational-age-specific risk. Instead, we find apparent exposure effects with either denominator. Except for prediction, neither denominator provides a meaningful way to define gestational-age-specific neonatal mortality.

Keywords: Fetal pathology; Gestational-age paradox; Neonatal mortality; Preterm delivery.

FIGURE 1

Simulated gestational-week-specific rates for two subsets of neonatal mortality. Mortality due to intrauterine pathology (dotted line) expressed per 1000 fetuses. Mortality due to birth-dependent pathology (dashed line) expressed per 1000 live births. Based on live births, fetal deaths and neonatal deaths to singleton non-Hispanic white mothers in the United States 2006.

FIGURE 2

Simulated week-specific rates of neonatal mortality Distribution of live births (dashed lines) and fetuses (dotted lines) for an exposed (red) and unexposed (black) cohort (Panel A). Subset mortality rates (Figure 1) are applied to each gestational age distribution in Panel A. The pooled neonatal mortality (solid line) is expressed per 1000 fetuses at risk (Panel B) or per 1000 live births (Panel C). Based on live births, fetal deaths and neonatal deaths observed in the United States 2006.

FIGURE 3

Directed acyclic graph for effects of an exposure (E) on neonatal mortality through effects on gestational age at birth (“preterm delivery”) in the presence of an intrauterine pathology (previously “unmeasured confounder” U) that causes both preterm delivery and neonatal mortality. In the simulation, the exposure (pregestational diabetes) affects only preterm delivery. The gestational-age-specific effects of preterm delivery do not vary by exposure status. Intrauterine pathology is assumed to have gestational-age-specific effects on neonatal mortality proportional to its effects on fetal death, and these are also independent of exposure. In the simulation, intrauterine pathology is strongly associated with preterm delivery (61%) and neonatal mortality (100%), but not with E.