Evidence map›Paper›PMID 29516296›Full record

ArticleEuropean journal of epidemiology2018

Two denominators for one numerator: the example of neonatal mortality.

Quaker E Harmon, Olga Basso, Clarice R Weinberg, Allen J Wilcox

Abstract read
In one paragraph

Article in European journal of epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Quaker E HarmonNational Institute of Environmental Health Sciences, P.O. Box 12233, Durham, NC, 27709, USA. quaker.harmon@nih.gov.ORCID http://orcid.org/0000-0002-5866-848X
Olga BassoDepartment of Obstetrics and Gynecology, McGill University, Montreal, QC, Canada.
Clarice R WeinbergBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA.
Allen J WilcoxNational Institute of Environmental Health Sciences, P.O. Box 12233, Durham, NC, 27709, USA.

Funding

Epidemiologic Study Of Reproductive Outcomes And Environmental ExposuresZIAES044003 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI WILCOX, ALLEN J · 2009 to 2020
$4.7M
Statistical Methods In Epidemiology--generalZIAES040006 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI WEINBERG, CLARICE · 2009 to 2025
$4.5M
Environmental And Genetic Causes Of Birth DefectsZIAES049027 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI WILCOX, ALLEN J · 2009 to 2020
$2.6M
Intramural NIH HHS Z99 ES999999Intramural NIH HHS ZIA ES044003
6 · The paper itself

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.

Indexed as

Infant MortalityFetusGestational AgeHumansInfantInfant, NewbornPremature BirthRisk FactorsFetal pathologyGestational-age paradoxNeonatal mortalityPreterm delivery

Identifiers

PMID29516296
PMCPMC6023405

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.