Is resting metabolic rate different between men and women?
Bibliographic record
Abstract
A low resting metabolic rate (RMR) has been proposed as a possible cause for the increased body fat commonly seen in women compared with men. Absolute RMR is higher in men, but whether RMR adjusted for lean body mass (LBM) remains higher is unresolved. The objective of the present study was to determine whether RMR adjusted for various body composition factors differed between healthy adult men and women. Thirty men years, BMI and twenty-eight women years, BMI were included in the analyses. RMR was measured by open-circuit indirect calorimetry for 60 min. Extracellular water (ECW) was measured by corrected Br(-) space and total body water (TBW) by 2H dilution. LBM was estimated as TBW/0.732. Intracellular water (ICW) was calculated as TBW-ECW, and body cell mass (BCM) as ICW/0.732. Men were heavier and had higher BMI, LBM, BCM and ECW, but less fat mass. Absolute RMR was higher in men than women v. P<0.0001). This difference became non-significant when RMR was adjusted for LBM by ANCOVA v. P=0.2191), but remained significant when adjusted for BCM v. P=0.0249). Fat mass explained a significant amount of variation in RMR in women (r(2) 0.28, P=0.0038), but not in men (r(2) 0.03, P=0.3301). The relationships between body fat and the various subcompartments of BCM and RMR require further elucidation.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".