Consuming an unprocessed diet reduces energy intake: a post-hoc analysis of a randomized controlled trial reveals a role for human nutritional intelligence
Bibliographic record
Abstract
In 2019 Hall et al. reported a randomized clinical trial showing an ultra-processed diet increases energy intake by ∼500 kcal/d compared to an unprocessed diet. This post-hoc analysis assessed whether participants selected meal components with specific nutritional characteristics and how this affected energy intake. Twenty weight-stable adults received an ad libitum ultra-processed or unprocessed diet for 2 weeks, followed by the alternate diet. ANOVA and t -tests assessed diet effects; a linear mixed model assessed predictors of meal size. With the unprocessed diet, participants selected components with a less-equal blend of energy from carbohydrate and fat (“blend index” difference; lunch = 0.22 (95% CI: 0.19, 0.26), P < 0.0001, d = 0.76; dinner = 0.24 (95% CI: 0.19, 0.28), P < 0.0001, d = 0.71). These components formed meals that had a lower blend index (less balanced) than ultra-processed meals (lunch, F (1, 19) = 18.49, P < 0.0004, partial η 2 = 0.493; dinner, F (1, 19) = 24.85, P < 0.0001, partial η 2 = 0.57). With the unprocessed diet, participants preferentially chose low-energy-dense components (<1.0 kcal/g, mostly fruits and vegetables), creating meals lower in energy (unprocessed = 719.4 ± 11.6 kcal vs ultra-processed = 829.5 ± 12.51 kcal), ( F (1,19) = 14.9, P < 0.001, η 2 G = 0.0457), yet significantly larger (57%) by mass (unprocessed = 665.5 ± 10.74 g vs ultra-processed = 423.5 ± 8.03 g), ( F (1,19) = 82.9, P < 0.001, η 2 G = 0.274). Modelled together, low-energy-dense mass and blend index strongly predict observed energy intakes (r = 0.78, df = 1676, P < 0.001). Unprocessed meals may reduce energy intake because: (1) they have a less balanced carbohydrate-fat blend; and (2) they promote a form of nutritional intelligence whereby a compromise is struck between consuming calories and consuming micronutrients, which we refer to as “micronutrient deleveraging.” The original study protocol was approved by the Institutional Review Board of the National Institute of Diabetes & Digestive & Kidney Diseases (ClinicalTrials.gov Identifier NCT03407053, 2018-01-20).
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".