Impact of reducing dietary greenhouse gas emissions on micronutrient intakes: preliminary results from the MyPlanetDiet randomised controlled trial – Retracted
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
Simultaneously improving diet quality and minimising dietary environmental impacts are central to the development of sustainable healthy diets. Altering dietary patterns to increase the proportion of plant-based foods and reduce animal-source foods has the potential to reduce dietary greenhouse gas emissions (GHGEs) and other environmental indicators (1) . However, data evaluating the impacts of these dietary changes on micronutrient intakes are scarce (2) . The MyPlanetDiet randomised controlled trial (RCT) was conducted in healthy adults across the island of Ireland [NCT05253547]. Participants were randomly assigned to follow a diet with reduced GHGEs (intervention group), or a diet based on national dietary guidelines (control group), for 12 weeks. Otherwise, all study procedures were identical. Dietary intake was assessed at baseline and endpoint using three non-consecutive 24-hour recalls, collected remotely using the Foodbook24 web-based dietary assessment tool (3) . Dietary GHGEs and micronutrient intakes were calculated from food sources only. Data were analysed using paired t-tests to assess for withingroup differences between baseline and week 12, and one-way analysis of covariance (ANCOVA) to test for differences between groups at week 12, whilst controlling for baseline intakes. Here, we present data from one of three sites (University College Cork). Of the 127 participants enrolled, 108 completed the trial (n = 57, intervention group; n = 51, control group). The mean (SD) age of participants was 42.2 (11.9) years and 59% were female. Ninety-three percent of participants were white and 88% completed third-level education. At baseline, mean (SD) GHGEs were 7.3 (3.1) kg CO 2 equivalents/day. GHGEs reduced significantly in the intervention group (p<0.001), and GHGEs were significantly lower in the intervention group compared to the control group at week 12 (4.6 (1.5) vs. 6.8 (2.9) kg CO 2 equivalents/day, p<0.001). In the control group, intakes of carotene, vitamins B12 and C increased significantly from baseline (p<0.05), whereas vitamin E reduced significantly (p = 0.005). In the intervention group, intakes of retinol, riboflavin, niacin equivalents, vitamins B6 and B12, biotin, pantothenate, calcium, phosphorous, zinc, and potassium reduced significantly (p<0.05). Compared to the control group at week 12, the intervention group had significantly higher intakes of vitamin E (p = 0.015) and significantly lower intakes of retinol, thiamin, riboflavin, niacin equivalents, vitamins B6 and B12, biotin, pantothenate, calcium, phosphorous, zinc and potassium (p<0.05). There were no differences in carotene, retinol equivalents, total folates, vitamin C, magnesium, iron, copper, or selenium. Micronutrient intakes generally remained similar or improved in the healthy control group, whereas the low-GHGE diet resulted in reductions in some key micronutrients. Further analysis of dietary composition, the prevalence of inadequate intakes, and biomarkers of nutritional status will enable a more comprehensive understanding of the impacts of such a dietary transition on nutritional status.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".