Evidence map›Paper›PMID 28043857›Full record

ArticleAppetite2017

Identifying eating behavior phenotypes and their correlates: A novel direction toward improving weight management interventions.

Sofia Bouhlal, Colleen M McBride, Niraj S Trivedi, Tanya Agurs-Collins, Susan Persky

Abstract read
In one paragraph

Article in Appetite, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Observational
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  14. Public perception of bariatric surgery.Saudi medical journal · 2019
    Article
  15. Review
  16. Article
  17. Article
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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.

Sofia BouhlalSocial and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health, Building 31, Room B1B54, Bethesda, MD 20892, USA. Electronic address: sofia.bouhlal@nih.gov.
Colleen M McBrideEmory University Rollins School of Public Health, 1518 Clifton Road NE Mailstop 1518-002-5AA (SPH: Behavioral Sciences & Health Education), Atlanta, GA 30322, USA. Electronic address: Colleen.marie.mcbride@emory.edu.
Niraj S TrivediComputational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, 50 South Drive, Room 5228, Bethesda, MD 20892, USA. Electronic address: niraj.trivedi@nih.gov.
Tanya Agurs-CollinsHealth Behaviors Research Branch, National Cancer Institute, National Institutes of Health, Rockville, MD, USA. Electronic address: collinsta@nih.gov.
Susan PerskySocial and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health, Building 31, Room B1B54, Bethesda, MD 20892, USA. Electronic address: perskys@mail.nih.gov.

Funding

Eating and Feeding Behavior: Exploring Phenotypes and Influencing OutcomesZIAHG200396 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI PERSKY, SUSAN · 2015 to 2025
$2.4M
Intramural NIH HHS ZIA HG200396
6 · The paper itself

Abstract

Common reports of over-response to food cues, difficulties with calorie restriction, and difficulty adhering to dietary guidelines suggest that eating behaviors could be interrelated in ways that influence weight management efforts. The feasibility of identifying robust eating phenotypes (showing face, content, and criterion validity) was explored based on well-validated individual eating behavior assessments. Adults (n = 260; mean age 34 years) completed online questionnaires with measurements of nine eating behaviors including: appetite for palatable foods, binge eating, bitter taste sensitivity, disinhibition, food neophobia, pickiness and satiety responsiveness. Discovery-based visualization procedures that have the combined strengths of heatmaps and hierarchical clustering were used to investigate: 1) how eating behaviors cluster, 2) how participants can be grouped within eating behavior clusters, and 3) whether group clustering is associated with body mass index (BMI) and dietary self-efficacy levels. Two distinct eating behavior clusters and participant groups that aligned within these clusters were identified: one with higher drive to eat and another with food avoidance behaviors. Participants' BMI (p = 0.0002) and dietary self-efficacy (p < 0.0001) were associated with cluster membership. Eating behavior clusters showed content and criterion validity based on their association with BMI (associated, but not entirely overlapping) and dietary self-efficacy. Identifying eating behavior phenotypes appears viable. These efforts could be expanded and ultimately inform tailored weight management interventions.

Indexed as

PhenotypeSelf EfficacyAdultAppetiteBody Mass IndexBulimiaCluster AnalysisEatingFeasibility StudiesFeeding BehaviorFemaleHumansInhibition, PsychologicalMaleSatiationSurveys and QuestionnairesBMIEating behaviorsHeatmapPhenotypesSelf-efficacy

Identifiers

PMID28043857
PMCPMC5304943

What OpenQuestion holds

Textmetadata
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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.