Effects of a Caloric Restriction Weight Loss Diet and Exercise on Inflammatory Biomarkers in Overweight/Obese Postmenopausal Women: A Randomized Controlled Trial
Bibliographic record
Abstract
Obese and sedentary persons have increased risk for cancer; inflammation is a hypothesized mechanism. We examined the effects of a caloric restriction weight loss diet and exercise on inflammatory biomarkers in 439 women. Overweight and obese postmenopausal women were randomized to 1-year: caloric restriction diet (goal of 10% weight loss, N = 118), aerobic exercise (225 min/wk of moderate-to-vigorous activity, N = 117), combined diet + exercise (N = 117), or control (N = 87). Baseline and 1-year high-sensitivity C-reactive protein (hs-CRP), serum amyloid A (SAA), interleukin-6 (IL-6), leukocyte, and neutrophil levels were measured by investigators blind to group. Inflammatory biomarker changes were compared using generalized estimating equations. Models were adjusted for baseline body mass index (BMI), race/ethnicity, and age. Four hundred and thirty-eight (N = 1 in diet + exercise group was excluded) were analyzed. Relative to controls, hs-CRP decreased by geometric mean (95% confidence interval, P value): 0.92 mg/L (0.53-1.31, P < 0.001) in the diet and 0.87 mg/L (0.51-1.23, P < 0.0001) in the diet + exercise groups. IL-6 decreased by 0.34 pg/mL (0.13-0.55, P = 0.001) in the diet and 0.32 pg/mL (0.15-0.49, P < 0.001) in the diet + exercise groups. Neutrophil counts decreased by 0.31 × 10(9)/L (0.09-0.54, P = 0.006) in the diet and 0.30 × 10(9)/L (0.09-0.50, P = 0.005) in the diet + exercise groups. Diet and diet + exercise participants with 5% or more weight loss reduced inflammatory biomarkers (hs-CRP, SAA, and IL-6) compared with controls. The diet and diet + exercise groups reduced hs-CRP in all subgroups of baseline BMI, waist circumference, CRP level, and fasting glucose. Our findings indicate that a caloric restriction weight loss diet with or without exercise reduces biomarkers of inflammation in postmenopausal women, with potential clinical significance for cancer risk reduction.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".