Evidence map›Paper›PMID 27748744›Full record

Trial reportInternational journal of obesity (2005)2017

Metabolic phenotypes of obesity: frequency, correlates and change over time in a cohort of postmenopausal women.

G C Kabat, W Y-Y Wu, J W Bea, C Chen, L Qi, M L Stefanick, R T Chlebowski, D S Lane, J Wactawski-Wende, S Wassertheil-Smoller and 1 more

Abstract readClinical TrialMulticenter StudyObservational Study
PubMed Publisher
In one paragraph

Trial report in International journal of obesity (2005), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

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

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Article
  6. Review
  7. The evolution of the understanding of obesity over the last 100 years.International journal of obesity (2005) · 2025
    Review
  8. Article
  9. Article
  10. Article
  11. Metabolic and Obesity Phenotype Trajectories in Taiwanese Medical Personnel.International journal of environmental research and public health · 2022
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Metabolically Healthy Obesity.Endocrine reviews · 2020
    Review
  18. Observational
  19. Article
  20. 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

11 authors.

G C KabatDepartment of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.
W Y-Y WuDepartment of Radiation Sciences Oncology, Umeå University, Umeå, Sweden.
J W BeaDepartment of Medicine, Arizona Cancer Center, Tucson, AZ, USA.
C ChenDepartment of Epidemiology, School of Public Health, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
L QiDepartment of Public Health Sciences, School of Medicine, University of California at Davis, Davis, CA, USA.
M L StefanickStefanick Department of Medicine, Stanford University, Stanford, CA, USA.
R T ChlebowskiLos Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA.
D S LaneDepartment of Preventive Medicine, School of Medicine, Stony Brook University, Stony Brook, NY, USA.
J Wactawski-WendeDepartment of Social and Preventive Medicine, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY, USA.
S Wassertheil-SmollerDepartment of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.
T E RohanDepartment of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe possibility that a subset of persons who are obese may be metabolically healthy-referred to as the 'metabolically healthy obese' (MHO) phenotype-has attracted attention recently. However, few studies have followed individuals with MHO or other obesity phenotypes over time to assess change in their metabolic profiles. The aim of the present study was to examine transitions over a 6-year period among different states defined simultaneously by body mass index (BMI) and the presence/absence of the metabolic syndrome (MetS).

methodsWe used repeated measurements available for a subcohort of participants enrolled in the Women's Health Initiative (N=3512) and followed for an average of 6 years to examine the frequency of different metabolic obesity phenotypes at baseline, the 6-year transition probabilities to other states and predictors of the risk of different transitions. Six phenotypes were defined by cross-tabulating BMI (18.5-<25.0, 25.0-<30.0, ⩾30.0 kg m

resultsOver the 6 years of follow-up, one-third of women with the healthy obese phenotype transitioned to the metabolically unhealthy obese (MUO) phenotype. Overall, there was a marked tendency toward increased metabolic deterioration with increasing BMI and toward metabolic improvement with lower BMI. Among MHO women, the 6-year probability of becoming MUO was 34%, whereas among unhealthy normal-weight women, the probability of 'regressing' to the metabolically healthy normal-weight phenotype was 52%.

conclusionsThe present study demonstrated substantial change in metabolic obesity phenotypes over a 6-year period. There was a marked tendency toward metabolic deterioration with greater BMI and toward metabolic improvement with lower BMI.

Indexed as

AgedBiomarkersBlood GlucoseBody Fat DistributionBody Mass IndexCardiovascular DiseasesFemaleFollow-Up StudiesHumansInflammationInsulin ResistanceMarkov ChainsMetabolic SyndromeMiddle AgedObesity, AbdominalPhenotypeBiomarkersBlood Glucose

Identifiers

PMID27748744

What OpenQuestion holds

Textmetadata
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Registered trials

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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.