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Record W2587824778 · doi:10.1093/ije/dyx022

Obesity-induced hypoadiponectinaemia: the opposite influences of central and peripheral fat compartments

2017· article· en· W2587824778 on OpenAlexfundno aff
Maria Carolina Borges, Isabel Oliveira, Deise Farias Freitas, Bernardo Lessa Horta, Ken K. Ong, Denise P. Gigante, Aluísio J. D. Barros

Bibliographic record

VenueInternational Journal of Epidemiology · 2017
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsnot available
FundersMedical Research CouncilNational Institutes of HealthUniversidade Federal de PelotasWellcome TrustMcGill University
KeywordsAdiponectinAbdominal obesityMedicineWaistAdipose tissueInternal medicineEndocrinologyMendelian randomizationIntra-Abdominal FatObesityConfidence intervalInsulin resistanceVisceral fatBiology

Abstract

fetched live from OpenAlex

Background and Aims: The substantial reduction in adiponectin concentration among obese individuals seems to depend on fat distribution and is a marker of metabolic and adipose tissue dysfunction. We aimed to: (i) address whether abdominal fat from different compartments (visceral, deep subcutaneous abdominal and superficial subcutaneous abdominal) and gluteofemoral fat are independently associated with blood adiponectin concentration; and (ii) investigate whether abdominal (proxied by waist circumference) and gluteofemoral fat (proxied by hip circumference) accumulation causally determine blood adiponectin concentration. Methods: To investigate the independent association of abdominal and gluteofemoral fat with adiponectin concentration, we used multivariable regression and data from 30-year-old adults from the 1982 Pelotas Birth Cohort (n = 2,743). To assess the causal role of abdominal and gluteofemoral fat accumulation on adiponectin concentration, we used Mendelian randomization and data from two consortia of genome-wide association studies-the GIANT (n > 210 000) and ADIPOGen consortia (n = 29 347). Results: In the multivariable regression analysis, all abdominal fat depots were negatively associated with adiponectin concentration, specially visceral abdominal fat [men: β = -0.24 standard unit of log adiponectin per standard unit increase in abdominal fat; 95% confidence interval (CI) = -0.31, -0.18; P = 8*10-13; women: β = -0.31; 95% CI = -0.36, -0.25; P = 7*10-27), whereas gluteofemoral fat was positively associated with adiponectin concentration (men: β = 0.13 standard unit of log adiponectin per standard unit increase in gluteofemoral fat; 95% CI = 0.03, 0.22; P = 0.008; women: β = 0.24; 95% CI = 0.17, 0.31; P = 7*10-11). In the Mendelian randomization analysis, genetically-predicted waist circumference was inversely related to blood adiponectin concentration (β = -0.27 standard unit of log adiponectin per standard unit increase in waist circumference; 95% CI = -0.36, -0.19; P = 2*10-11), whereas genetically-predicted hip circumference was positively associated with blood adiponectin concentration (β = 0.17 standard unit of log adiponectin per standard unit increase in hip circumference; 95% CI = 0.11, 0.24; P = 1*10-7). Conclusions: These results support the hypotheses that there is a complex interplay between body fat distribution and circulating adiponectin concentration, and that whereas obesity-induced hypoadiponectinaemia seems to be primarily attributed to abdominal fat accumulation, gluteofemoral fat accumulation is likely to exert a protective effect.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.062
GPT teacher head0.372
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations41
Published2017
Admission routes1
Has abstractyes

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