The associations of resting metabolic rate with chronic conditions and weight loss
Bibliographic record
Abstract
The aim of this study was to examine the associations between baseline and changes in resting metabolic rate (RMR) with chronic condition(s) and weight loss (WL). Sex stratified analysis was undertaken on 393 adults from the Wharton Weight Management Clinics. The association between baseline RMR and WL was examined adjusting for age, BMI, ethnicity and treatment time. The association between changes in RMR (ΔRMR) and WL was also examined adjusting for baseline RMR and above covariates. Models were further adjusted for high glucose, triglycerides, blood pressure, low-density lipoprotein (LDL) and low high-density lipoprotein (HDL). While men (6.0 ± 8.6 kg) and women (5.6 ± 8.3 kg) had significant WL throughout the intervention, their measured decreases in RMR (-48 ± 322 kcal and -5 ± 322 kcal, respectively) were non-significant (P > 0.05). Individuals with a high blood pressure had a higher baseline RMR and women with a high LDL had a lower baseline RMR than those without the chronic condition (P < 0.05). Regardless of sex, WL was not significantly associated with baseline RMR or ΔRMR (P > 0.05) in both models. Participants with a low baseline RMR do not appear to be at a disadvantage for WL. Further, WL can occur without decreases in RMR in populations with high levels of obesity and obesity-related comorbidities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".