Two denominators for one numerator: the example of neonatal mortality
- 122 Downloads
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.
KeywordsNeonatal mortality Fetal pathology Preterm delivery Gestational-age paradox
The authors gratefully acknowledge the comments on earlier drafts by Dr. Donna Baird, Dr. David Umbach, and anonymous reviewers.
This research has been supported in part by the Intramural Research Program of the National Institute of Environmental Health Sciences, National Institutes of Health.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
Publicly available data with no identifying details were used. For this type of study formal consent is not required.
- 1.Wang H, Liddell CA, Coates MM, Mooney MD, Levitz CE, Schumacher AE, et al. Global, regional, and national levels of neonatal, infant, and under-5 mortality during 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2014;384(9947):957–79.CrossRefPubMedPubMedCentralGoogle Scholar
- 2.Linked Birth/Infant Death Records 2007–2013, as compiled from data provided by the 57 vital statistics jurisdictions through the Vital Statistics Cooperative Program, on CDC WONDER On-line Database [database on the Internet] 2015. http://wonder.cdc.gov/lbd-current.html. Accessed 28 Aug 2015.
- 22.Birth Cohort Linked Birth-Infant Death Data Files [database on the Internet] 2006. http://www.cdc.gov/nchs/data_access/Vitalstatsonline.htm. Accessed 10 July 2015.
- 23.Fetal Death Data File [database on the Internet] 2006. http://www.cdc.gov/nchs/data_access/Vitalstatsonline.htm. Accessed 16 July 2015.
- 27.Sibai BM, Caritis SN, Hauth JC, MacPherson C, VanDorsten JP, Klebanoff M, et al. Preterm delivery in women with pregestational diabetes mellitus or chronic hypertension relative to women with uncomplicated pregnancies. The National Institute of Child Health and Human Development Maternal–Fetal Medicine Units Network. Am J Obstet Gynecol. 2000;183(6):1520–4.CrossRefPubMedGoogle Scholar
- 31.Platt RW. The fetuses-at-risk approach: an evolving paradigm. In: Louis GB, Platt RW, editors. Reproductive and perinatal epidemiology. Oxford: Oxford University Press; 2011.Google Scholar