Evidence map›Paper›PMID 39327854›Full record

ArticlePediatric obesity2024

The predictive utility of the in utero exposome for childhood adiposity in independent and integrated frameworks.

Jonathan VanHawkins, Ryan Peterson, Kylie Harrall, Brandy Moon, Dana Dabelea, Katerina Kechris, Wei Perng

Abstract read
In one paragraph

Article in Pediatric obesity, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

7 authors.

Jonathan VanHawkinsDepartment of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.ORCID https://orcid.org/0009-0006-0389-0020
Ryan PetersonDepartment of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.
Kylie HarrallDepartment of Epidemiology, Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.
Brandy MoonDepartment of Epidemiology, Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.
Dana DabeleaDepartment of Epidemiology, Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.
Katerina KechrisDepartment of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.
Wei PerngDepartment of Epidemiology, Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.ORCID https://orcid.org/0000-0001-8552-6850

Funding

The Early Life Exposome and Childhood Health - The Colorado Healthy Start 3 Cohort StudyUH3OD023248 · OD · UNIVERSITY OF COLORADO DENVER · PI Traci Allison Bekelman, Dana Dabelea · 2018 to 2026
$14.8M
The Early Life Exposome and Childhood Health - The Colorado Healthy Start 3 Cohort StudyUG3OD023248 · OD · UNIVERSITY OF COLORADO DENVER · PI BEKELMAN, TRACI ALLISON, DABELEA, DANA · 2016 to 2024
$5.9M
Infant diet and cardiometabolic risk among children born pretermR01HD112751 · NICHD · BRIGHAM AND WOMEN'S HOSPITAL · PI Mandy Brown Belfort, Wei Perng · 2023 to 2026
$2.9M
Understanding the Pathophysiology of Type 2 Diabetes in Navajo YouthU01DK134981 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI Dana Dabelea, Wei Perng · 2023 to 2026
$2.7M
American Diabetes Association ADA-7-22-ICTSPM-08NICHD NIH HHS R01 HD112751NIDDK NIH HHS U01 DK134981NIH HHS U01 DK134981NIH HHS UG3 OD023248NIH HHS UH3 OD023248NIH HHS UH3OD023248
6 · The paper itself

Abstract

objectivesTo assess the predictive potential of the in utero exposome in relation to childhood adiposity as indicated by body mass index z-scores (BMIz) and the fourth versus first quartile of % fat mass (FM) at median age of 4.6 years.

methodsWe leveraged data on clinical risk factors for childhood obesity during the perinatal period, along with cord blood per/polyfluoroalkyl substances (PFAS) and cord blood DNA methylation, in 268 mother-offspring pairs. We used the sparsity ranked LASSO penalized regression framework for each outcome and assessed model performance based on % variability explained for BMIz and area under the receiver operating characteristic curve (AUC) for the fourth versus first quartile of %FM. We employed cross-validation for model tuning and split-sample validation for model evaluation.

resultsMean ± SD BMIz was 0.01 ± 1.1, %FM was 19.8 ± 6.34%. The optimal model for predicting BMIz explained 19.1% of the variability in the validation set and included only clinical characteristics: maternal pre-pregnancy BMI, paternal BMI, gestational weight gain, physical activity during pregnancy and child race/ethnicity. The optimal model for fourth versus first quartiles of %FM achieved an AUC of 0.82 ± 0.01 in the validation set, with the clinical features again emerging as the strongest predictors.

conclusionIn this study sample, perinatal chemical exposures and the epigenome have low utility in predicting childhood adiposity, beyond known clinical risk factors.

Indexed as

AdiposityBody Mass IndexExposomePediatric ObesityPrenatal Exposure Delayed EffectsAdultChildChild, PreschoolDNA MethylationFemaleFetal BloodHumansMaleMaternal ExposurePregnancyRisk Factorschildhood adiposityDNA methylationexposomeper‐ and polyfluoroalkyl substances

Identifiers

PMID39327854
PMCPMC11560695

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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.