Correlations Between Metabolic Rate, Hunger, and Energy Intake With and Without Exercise in Lean Men
Bibliographic record
Abstract
Recent evidence suggests that resting metabolic rate (RMR) is correlated with hunger and energy intake (EI) in overweight and obese adults (Caudwell et al. 2013); however, this relationship has not been examined in lean adults. Furthermore, whether pre-meal metabolic rate is associated with subsequent hunger or meal EI remains to be elucidated. PURPOSE: To assess relationships between measures of energy expenditure (EE), hunger, and EI in lean men. METHODS: Following an overnight fast, eight physically active men (age: 25 ± 3 y, body mass: 79.6 ± 9.7 kg, body fat 13 ± 6%; mean ± SD) completed four 10-h test days in the laboratory. Three buffet-type meals were served per test day. Prior to each meal, 30-min breath-by-breath gas measures were collected in addition to hunger ratings. One of the test days, exercise day (Ex), included a sprint interval exercise session (four “all out” 30-s running bouts) performed 1.5 h prior to lunch. The other three test days were non-exercise days (NoEx). The trapezoid method was used to calculate 10-h area under the curve (AUC) for hunger ratings and gas collections (eight per test day) to obtain total EE (TEE). Pearson correlation coefficients are reported. Relationships within subjects were analyzed with the Bland and Altman (1995) method using multiple regression analysis. RESULTS: TEE was significantly correlated with total (3-meal) EI (TEI; Ex: r = 0.71, P = 0.05 and NoEx: r = 0.77, P = 0.03), but not with hunger AUC (Ex: r = 0.47, P = 0.24 and NoEx: r = 0.62, P = 0.10). The correlation between hunger AUC and TEI approached significance during Ex (r = 0.69, P = 0.06) but not NoEx (r = 0.34, P = 0.40). Correlations between RMR and TEI (Ex: r = 0.57, P = 0.14 and NoEx: r = 0.65, P = 0.08), and RMR and hunger AUC (Ex: r = 0.65, P = 0.08 and NoEx: r = 0.67, P = 0.07) approached significance. Relationships within subjects (96 observations) showed that pre-meal metabolic rate was correlated with hunger (r = 0.18, P < 0.001) and with meal EI (r = 0.11, P < 0.001). CONCLUSIONS: These data appear to confirm the robustness of the relationship between RMR and EI in a sample of lean men, and extend these findings to pre-meal metabolic status despite the small sample size. Relationships between measures of EE, EI and hunger in lean adults may also be strengthened with exercise. Supported by GSSI, Subway, PepsiCo and Real Canadian Superstore.
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 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 | 0.000 | 0.002 |
| 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) | 0.001 | 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".