Body composition indices of a load–capacity model: gender- and BMI-specific reference curves
Bibliographic record
Abstract
OBJECTIVE: Fat mass (FM) and fat-free mass (FFM) are frequently measured to define body composition phenotypes. The load-capacity model integrates the effects of both FM and FFM to improve disease-risk prediction. We aimed to derive age-, gender- and BMI-specific reference curves of load-capacity model indices in an adult population (≥18 years). DESIGN: Cross-sectional study. Dual-energy X-ray absorptiometry was used to measure FM, FFM, appendicular skeletal muscle mass (ASM) and truncal fat mass (TrFM). Two metabolic load-capacity indices were calculated: ratio of FM (kg) to FFM (kg) and ratio of TrFM (kg) to ASM (kg). Age-standardised reference curves, stratified by gender and BMI (<25.0 kg/m2, 25.0-29.9 kg/m2, ≥30.0 kg/m2), were constructed using an LMS approach. Percentiles of the reference curves were 5th, 15th, 25th, 50th, 75th, 85th and 95th. SETTING: Secondary analysis of data from the 1999-2004 National Health and Nutrition Examination Survey (NHANES). SUBJECTS: The population included 6580 females and 6656 males. RESULTS: The unweighted proportions of obesity in males and females were 25.5 % and 34.7 %, respectively. The average values of both FM:FFM and TrFM:ASM were greater in female and obese subjects. Gender and BMI influenced the shape of the association of age with FM:FFM and TrFM:ASM, as a curvilinear relationship was observed in female and obese subjects. Menopause appeared to modify the steepness of the reference curves of both indices. CONCLUSIONS: This is a novel risk-stratification approach integrating the effects of high adiposity and low muscle mass which may be particularly useful to identify cases of sarcopenic obesity and improve disease-risk prediction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".