Evidence map›Paper›PMID 30643709›Full record

ArticleCurrent epidemiology reports2018

Environmental exposure mixtures: questions and methods to address them.

Ghassan B Hamra, Jessie P Buckley

Abstract read
In one paragraph

Article in Current epidemiology reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 102 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
102citing papers in PubMed, 2 pooled it
–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

102 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  6. [Association between mixed metal element exposure and the risk of thyroid carcinoma: a case-control study].Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences · 2026
    Article
  7. Article
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  9. Workflow for Statistical Analysis of Environmental Mixtures.Environmental health perspectives · 2026
    Review
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  11. Review
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42 more citing papers are in PubMed but not listed here.

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.

Ghassan B HamraDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, MD, USA.
Jessie P BuckleyDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, MD, USA.

Funding

ECHODAC (Environmental Influences on Child Health Outcomes Data Analysis Center)U24OD023382 · OD · JOHNS HOPKINS UNIVERSITY · PI Diane J Catellier, LISA P JACOBSON · 2016 to 2026
$148.4M
NIH HHS U24 OD023382
6 · The paper itself

Abstract

purpose of this reviewThis review provides a summary of statistical approaches that researchers can use to study environmental exposure mixtures. Two primary considerations are the form of the research question and the statistical tools best suited to address that question. Because the choice of statistical tools is not rigid, we make recommendations about when each tool may be most useful. RECENT

findingsWhen dimensionality is relatively low, some statistical tools yield easily interpretable estimates of effect (e.g., risk ratio, odds ratio) or intervention impacts. When dimensionality increases, it is often necessary to compromise this interpretablity in favor of identifying interesting statistical signals from noise; this requires applying statistical tools that are oriented more heavily towards dimension reduction via shrinkage and/or variable selection. SUMMARY: The study of complex exposure mixtures has prompted development of novel statistical methods. We suggest that further validation work would aid practicing researchers in choosing among existing and emerging statistical tools for studying exposure mixtures.

Indexed as

Bayesian methodscomplex mixturesenvironmental epidemiologymachine learning

Identifiers

PMID30643709
PMCPMC6329601

What OpenQuestion holds

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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.