Evidence map›Paper›PMID 42751656›Full record

ArticleJournal of the Royal Statistical Society. Series C, Applied statistics2026

Multi-Tree Model for Precision Environmental Health with Longitudinally Assessed Mixture Exposure.

Seongwon Im, Daniel Mork, Ander Wilson

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the Royal Statistical Society. Series C, Applied statistics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Seongwon ImDepartment of Statistics, Colorado State University, 851 Oval Drive, 80523, CO, USA.ORCID 0009-0000-8447-5852
Daniel MorkDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, 02115, MA, USA.ORCID 0000-0002-7924-0706
Ander WilsonDepartment of Statistics, Colorado State University, 851 Oval Drive, 80523, CO, USA.ORCID 0000-0003-4774-3883

Funding

Statistical methods to characterize causal mechanisms by which air pollution affects the recurrence of cardiovascular eventsR01ES034021 · NIEHS · UNIVERSITY OF ROCHESTER · PI Francesca Dominici, Ashkan Ertefaie · 2023 to 2026
$2.5M
Air Pollution and Pregnancy LossR01ES029943 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI DEYSSENROTH, MAYA ARIANE, KIOUMOURTZOGLOU, MARIANTHI-ANNA · 2020 to 2024
$2.5M
Statistical Methods for Precision Environmental Health with Mixture ExposuresR01ES035735 · NIEHS · COLORADO STATE UNIVERSITY · PI Thomas Ander Wilson · 2024 to 2026
$1.5M
Children’s Cardiovascular Health in a Changing Climate: The Impacts of Extreme Heat and Wildfire SmokeR01ES036185 · NIEHS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Shohreh F Farzan, Rima Habre · 2025 to 2026
$1.3M
NIEHS NIH HHS R01 ES029943NIEHS NIH HHS R01 ES034021NIEHS NIH HHS R01 ES035735NIEHS NIH HHS R01 ES036185
6 · The paper itself

Abstract

Precision environmental health seeks to estimate how the effects of the environment vary across the population to inform targeted interventions and public health policy. However, there is a lack of statistical methods to estimate the heterogeneous effects of environmental exposures, particularly mixture exposures that are assessed longitudinally. We examine the heterogeneous exposure effect of weekly-average fine particulate matter (PM

Indexed as

Bayesian additive regression treesDistributed lag modelEnvironmental mixtureHeterogeneityPrecision environmental health

Identifiers

PMID42751656
PMCPMC13580615

What OpenQuestion holds

Textmetadata
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.