Evidence map›Paper›PMID 28891988›Full record

ArticleInternational journal of environmental research and public health2017

A Multivariate Dynamic Spatial Factor Model for Speciated Pollutants and Adverse Birth Outcomes.

Kimberly A Kaufeld, Montse Fuentes, Brian J Reich, Amy H Herring, Gary M Shaw, Maria A Terres

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2017. 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
–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

3 citing papers in PubMed.

  1. Article
  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

6 authors.

Kimberly A KaufeldLos Alamos National Laboratory, P.O. Box 1663, Los Alamos, NM 87545, USA. kkaufeld@lanl.gov.
Montse FuentesDepartment of Biostatistics and Statistics and Operations Research, Virginia Commonwealth University, Richmond, VA 23284, USA. mfuentes@vcu.edu.
Brian J ReichDepartment of Statistics, North Carolina State University, Raleigh, NC 27695, USA. bjreich@ncsu.edu.
Amy H HerringDepartment of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. herring@unc.edu.
Gary M ShawDivision of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA. gmshaw@stanford.edu.
Maria A TerresThe Climate Corporation, San Francisco, CA 94103, USA. mterres.stat@gmail.com.

Funding

Research Services CoreP2CHD050924 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KAREN B GUZZO · 2015 to 2026
$9.6M
California Center of BD-STEPS - Finding Causes and Preventives of Birth DefectsU01DD001033 · DD · STANFORD UNIVERSITY · PI CARMICHAEL, SUZAN L, SHAW, GARY M · 2013 to 2017
$3.4M
Data Integration Methods for Environmental Exposures with Applications to Air Pollution and Asthma MorbidityR01ES027892 · NIEHS · EMORY UNIVERSITY · PI CHANG, HOWARD H · 2017 to 2021
$2.7M
Space-time Modeling for Linking Climate Change,Pollutant Exposure, Built EnvironmR01ES014843 · NIEHS · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI REICH, BRIAN J. · 2008 to 2013
$2.0M
ACL HHS U01DD001033NICHD NIH HHS P2C HD050924NIEHS NIH HHS R01 ES014843NIEHS NIH HHS R01 ES027892
6 · The paper itself

Abstract

Evidence suggests that exposure to elevated concentrations of air pollution during pregnancy is associated with increased risks of birth defects and other adverse birth outcomes. While current regulations put limits on total PM2.5 concentrations, there are many speciated pollutants within this size class that likely have distinct effects on perinatal health. However, due to correlations between these speciated pollutants, it can be difficult to decipher their effects in a model for birth outcomes. To combat this difficulty, we develop a multivariate spatio-temporal Bayesian model for speciated particulate matter using dynamic spatial factors. These spatial factors can then be interpolated to the pregnant women's homes to be used to model birth defects. The birth defect model allows the impact of pollutants to vary across different weeks of the pregnancy in order to identify susceptible periods. The proposed methodology is illustrated using pollutant monitoring data from the Environmental Protection Agency and birth records from the National Birth Defect Prevention Study.

Indexed as

Models, TheoreticalAdultAir PollutantsBayes TheoremCongenital AbnormalitiesEnvironmental ExposureFemaleHumansMultivariate AnalysisParticulate MatterPregnancyYoung AdultAir PollutantsParticulate Matterbirth defectsfactor analysismultivariatepollutantsspatiotemporal

Identifiers

PMID28891988
PMCPMC5615583

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.