Evidence map›Paper›PMID 26703702›Full record

ArticleInternational journal of environmental research and public health2015

Using an External Exposome Framework to Examine Pregnancy-Related Morbidities and Mortalities: Implications for Health Disparities Research.

Tonny J Oyana, Patricia Matthews-Juarez, Stephania A Cormier, Xiaoran Xu, Paul D Juarez

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Pervasive structural racism in environmental epidemiology.Environmental health : a global access science source · 2021
    Article
  6. Semantic standards of external exposome data.Environmental research · 2021
    Review
  7. Article
  8. Article
  9. Article
  10. Review
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

5 authors.

Tonny J OyanaResearch Center on Health Disparities, Equity & the Exposome, Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN 38163, USA. toyana@uthsc.edu.
Patricia Matthews-JuarezPediatrics, Infectious Disease and Microbiology, Immunology & Biochemistry, University of Tennessee Health Science Center, Le Bonheur Children's Medical Center, Memphis, TN 36163, USA. pmatthews-juarez@mmc.edu.
Stephania A CormierPediatrics, Infectious Disease and Microbiology, Immunology & Biochemistry, University of Tennessee Health Science Center, Le Bonheur Children's Medical Center, Memphis, TN 36163, USA. scormier@uthsc.edu.
Xiaoran XuPediatrics, Infectious Disease and Microbiology, Immunology & Biochemistry, University of Tennessee Health Science Center, Le Bonheur Children's Medical Center, Memphis, TN 36163, USA. xxu24@uthsc.edu.
Paul D JuarezPediatrics, Infectious Disease and Microbiology, Immunology & Biochemistry, University of Tennessee Health Science Center, Le Bonheur Children's Medical Center, Memphis, TN 36163, USA. pjuarez@mmc.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveWe have conducted a study to assess the role of environment on the burden of maternal morbidities and mortalities among women using an external exposome approach for the purpose of developing targeted public health interventions to decrease disparities.

methodsWe identified counties in the 48 contiguous USA where observed low birthweight (LBW) rates were higher than expected during a five-year study period. The identification was conducted using a retrospective space-time analysis scan for statistically significant clusters with high or low rates by a Discrete Poisson Model.

resultsWe observed statistically significant associations of LBW rate with a set of predictive variables. However, in one of the two spatiotemporal models we discovered LBW to be associated with five predictive variables (teen birth rate, adult obesity, uninsured adults, physically unhealthy days, and percent of adults who smoke) in two counties situated in Alabama after adjusting for location changes. Counties with higher than expected LBW rates were similarly associated with two environmental variables (ozone and fine particulate matter).

conclusionsThe county-level predictive measures of LBW offer new insights into spatiotemporal patterns relative to key contributory factors. An external framework provides a promising place-based approach for identifying "hotspots" with implications for designing targeted interventions and control measures to reduce and eliminate health disparities.

Indexed as

Infant, Low Birth WeightInfant MortalityInfant, PrematureAdolescentAdultAlabamaFemaleHealthcare DisparitiesHumansInfantInfant, NewbornMorbidityPregnancyPregnancy ComplicationsPregnancy OutcomePregnant Peoplediscrete Poisson modelexternal exposomegeographic information systemshealth disparitiesinfant mortalitylow birthweightmaternal mortalitypregnancy outcomespremature birth

Identifiers

PMID26703702
PMCPMC4730404

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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.