Daily physical activity and macronutrient distribution of low-calorie diets jointly affect body fat reduction in obese women
Bibliographic record
Abstract
Inadequate dietary patterns and sedentary lifestyles are believed to be important factors in predisposing people to obesity. This study analyzed the potential interaction between habitual physical activity and the carbohydrate (CHO)-fat distribution in 2 hypocaloric diets and the impact of such interplay on body composition changes. Forty healthy obese women, 20-50 years old, were randomly assigned to a high- or low-CHO energy-restricted diet, which was low or high in fat, respectively, during 10 weeks. Baseline and final measurements were performed to assess dietary habits, resting metabolic rate, and body composition changes. Physical activity was measured with a triaxial accelerometer and with a questionnaire. There were no significant differences in anthropometric and metabolic variables between both dietary groups at baseline. However, there was a positive correlation between total free-living physical activity and arm muscle preservation after 10 weeks (r = 0.371; p = 0.024). Interestingly, an interaction between macronutrient (CHO-fat distribution) intake and physical activity was found, since less-active subjects with a high-CHO-low-fat diet showed a greater fat loss than those more active with a lower-CHO-high-fat diet, whereas more-active subjects with a high-CHO-low-fat diet showed a smaller fat loss than those receiving a low-CHO-high-fat diet. Physical activity and the macronutrient content of energy-restricted diets, when designed to promote body fat mass reduction, should be considered together to better predict the outcome.
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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 | 0.000 | 0.001 |
| 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".