Evidence map›Paper›PMID 25722958›Full record

ArticleCurrent epidemiology reports2015

Are epidemiological approaches suitable to study risk/preventive factors for human birth defects?

Sonia Hernandez-Diaz, Anna Sara Oberg

Open access · bronzeAbstract read
In one paragraph

Article in Current epidemiology reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 30% of its field
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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Article
  3. 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

2 authors at 1 institution in 1 country.

Sonia Hernandez-DiazDepartment of Epidemiology, Harvard School of Public Health, Address: 677 Huntington Avenue, Boston, 02115 MA, shernan@hsph.harvard.edu | oberg@hsph.harvard.edu , | 857-756-0770.
Anna Sara ObergDepartment of Epidemiology, Harvard School of Public Health, Address: 677 Huntington Avenue, Boston, 02115 MA, shernan@hsph.harvard.edu | oberg@hsph.harvard.edu , | 857-756-0770.
Harvard University · US

Funding

Comparative Safety of commonly prescribed Psychotropic Drugs in pregnant WomenR01MH100216 · NIMH · HARVARD SCHOOL OF PUBLIC HEALTH · PI HERNANDEZ-DIAZ, SONIA · 2014 to 2016
$1.4M
NIMH NIH HHS R01 MH100216
6 · The paper itself

Abstract

Birth defects are a major cause of infant morbidity and mortality and contribute substantially to long-term disability. One out of every 33 babies is born with some type of birth defect. Despite decades of research on environmental, behavioral and genetic risk factors, the vast majority of birth defects still occur without known cause. It is possible that birth defects are largely stochastic (and unavoidable) events, at which efforts to investigate their causes would be futile and unjustified. In this commentary we argue for the continued research into risk/preventive factors of human birth defects, and outline why epidemiological studies are suitable for such endeavors. First we discuss what factors to target (genetic or environmental) and how to define the pertinent research questions. Then we present a short review of both epidemiological contributions in the past and approaches to advance the field in the future. After considering also their limitations, we conclude that modern epidemiologic approaches are invaluable to advance our understanding of risk factors for human birth defects, and that interdisciplinary collaborations will also be essential to further our knowledge.

Indexed as

Birth defectsCongenital malformationsEpidemiologyObservational studiesRisk factors

Identifiers

PMID25722958
PMCPMC4337838
OpenAlexW2095585261

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.