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Abstract MP047: Abdominal Skeletal Muscle Density is Significantly Associated With Selected Measures of Adiposity Associated Inflammation: the Multi-Ethnic Study of Atherosclerosis

2017· article· en· W2954812357 on OpenAlexaff
Rachel Van Hollebeke, Mary Cushman, Matthew Allison

Bibliographic record

VenueCirculation · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Disease and Adiposity
Canadian institutionsMount Allison University
Fundersnot available
KeywordsMedicineAdipokineInternal medicineResistinEndocrinologyDyslipidemiaPopulationObesityLeptin

Abstract

fetched live from OpenAlex

Background: Excess adiposity is associated with higher levels of certain inflammatory markers that have been linked to cardiometabolic disease. Lean skeletal muscle is the largest regulator of glucose metabolism but few population-based studies have examined the associations between muscle and inflammation. Therefore, we studied the relationships between abdominal muscle mass [area] and density with selected measures of adiposity-associated inflammation. Methods: Nearly 2,000 subjects enrolled in the Multi-Ethnic Study of Atherosclerosis underwent computed tomography (CT) of the abdomen and had venous fasting blood drawn concomitantly. The CT scans were interrogated for visceral and subcutaneous fat, as well as lean muscle areas and densities in the rectus abdominus, obliques, paraspinus and psoas muscle groups. We then categorized the muscle in locomotion (psoas) and stabilization groups (rectus, obliques and paraspinus). The blood samples were assayed for interleukin-6, resistin, C-reactive protein, and tumor necrosis factor - alpha. Multivariable linear regression was used to determine the independent associations between muscle area and density with each of the aforementioned adipokines. Results: The mean age was 64.7 years and 49% were female. Forty percent were non-Hispanic White, 26% were Hispanic/ Latino American, 21% were African American, 13% were Chinese American. The mean BMI was 28.0 kg/m 2 and 30% were obese (BMI > 30 kg/m 2 ). With adjustment for age, gender, race, dyslipidemia, diabetes, hypertension, eGFR, coronary artery calcium, physical activity, sedentary behavior, selected adipokines and both subcutaneous and visceral fat, a 1-SD increment in the mean densities for total abdominal muscle, total stabilization muscle and total locomotive muscle were each significantly associated with lower levels of interleukin-6 (-15%, -15% and -9%, p < 0.01 for all) and resistin (-0.11, -0.11 and -0.07 ng/mL, p < 0.02 for all), but not CRP or TNF-alpha. These associations remained significant after additional adjustment for muscle area in the corresponding muscle group. Conversely, the areas of the muscle variables were not independently associated with any of the adipokines, especially after adjustment for muscle density. There were no significant interactions between ethnicity and both muscle area and density for any of the adipokines. Conclusions: Higher densities of several muscle groups in the abdomen are significantly associated with lower interleukin-6 and resistin levels, independent of the muscle area in these groups. Techniques that either enhance or maintain muscle density levels may reduce the risk of cardiometabolic diseases linked to adverse levels of inflammation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.060
GPT teacher head0.279
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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