Change in Weight, BMI, and Body Composition in a Population‐Based Intervention Versus Genetic‐Based Intervention: The NOW Trial
Bibliographic record
Abstract
Objective The aim of this study was to compare changes in body fat percentage (BFP), weight, and BMI between a standard intervention and a nutrigenomics intervention. Methods The Nutrigenomics, Overweight/Obesity and Weight Management (NOW) trial is a parallel‐group, pragmatic, randomized controlled clinical trial incorporated into the Group Lifestyle Balance TM (GLB) Program. Statistical analyses included two‐way ANOVA and split‐plot ANOVA. Inclusion criteria consisted of: BMI ≥ 25.0 kg/m 2 , ≥18 years of age, English speaking, willing to undergo genetic testing, having internet access, and not seeing another health care provider for weight‐loss advice outside of the study. Pregnancy and lactation were exclusion criteria. GLB groups were randomly assigned 1 to 1 ( N = 140) so that participants received either the standard 12‐month GLB program or a modified 12‐month program (GLB plus nutrigenomics), which included the provision of nutrigenomics information and advice for weight management. The primary outcome was percent change in BFP. Secondary outcomes were change in weight and BMI. Results The GLB plus nutrigenomics group experienced significantly ( P < 0.05) greater reductions in percent and absolute BFP at the 3‐month follow‐up and percent BFP at the 6‐month follow‐up compared with the standard GLB group. Conclusions The nutrigenomics intervention used in the NOW trial can optimize changes in body composition up to 6 months.
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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 | 0.000 | 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".