Evidence map›Paper›PMID 30374755›Full record

ReviewCurrent nutrition reports2018

Gene-Environment Interplay in Child Eating Behaviors: What the Role of "Nature" Means for the Effects of "Nurture".

Alexis C Wood

Abstract readReview
In one paragraph

Review in Current nutrition reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.5field-weighted citation impact, top 11% of its field
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

15 citing papers in PubMed, 33 citations in OpenAlex.

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  15. Case Reports: Multifaceted Experiences Treating Youth with Severe Obesity.International journal of environmental research and public health · 2019
    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

1 author at 1 institution in 1 country.

Alexis C WoodUSDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, 1100 Bates Street, Houston, TX, 77030, USA. Lekki.Wood@Gmail.com.
Children's Nutrition Research Center at Baylor College of Medicine · US

Funding

Overcoming Obstacles in Epigenetic Analysis of Human TwinsR21HD087860 · NICHD · BAYLOR COLLEGE OF MEDICINE · PI WATERLAND, ROBERT A, WOOD, ALEXIS CAROLINE · 2016 to 2017
$389k
NICHD NIH HHS R21 HD087860
6 · The paper itself

Abstract

purpose of reviewThis narrative review describes the evidence for both genetic and environmental influences on child appetitive traits and suggests ways of thinking about how these interact and correlate to influence how a child eats. RECENT

findingsEmerging evidence from social network analysis, and from longitudinal studies questioning the direction of association between parent feeding behaviors and child obesity risk, suggest that children's genes may shape the environmental risk for obesity that they are exposed to. There is strong evidence that child appetitive traits are both heritable and shaped by the environment. Instead of thinking about how genetic and environmental factors operate independently on each appetitive trait, research needs to expand the current paradigm to examine how genes and environments interact and shape each other.

Indexed as

Child BehaviorFeeding BehaviorGene-Environment InteractionParentingAdolescentAge FactorsAppetite RegulationChildChild Nutritional Physiological PhenomenaChild, PreschoolHeredityHumansInfantInfant, NewbornNutritional StatusPediatric ObesityBMIChildDynamic geneticsEating behaviorsEnvironmentFTOGene-by-environment correlationGene-by-environment interactionGenesHeritabilityMolecular geneticsNatureNurtureObesityObesogenic environmentParentingPediatricsReviewTwin study

Identifiers

PMID30374755
PMCPMC6251706
OpenAlexW2899251590

What OpenQuestion holds

Textmetadata
LicenceTDM
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.