Effect of Mediterranean Diet Adherence and Its Interaction with Genetic Susceptibility to Obesity on Adiposity in European Children: The IDEFICS/I.Family Study
Bibliographic record
Abstract
Introduction: The Mediterranean Diet (MD) has been associated with a better adiposity profile in different cohorts of European children. However, these beneficial effects might be influenced by genetic variations, which could potentially modulate the MD–adiposity association. Objectives: To investigate if higher adherence to the MD, or any of the MD food groups, is associated with lower adiposity during youth. Also, to observe the degree by which the adherence to the MD or any of the MD food groups could modulate the genetic susceptibility to obesity, in relation to adiposity. Methods: Design: Cohort study with three measurement surveys: baseline (T0), follow-up 1 (T1), and follow-up 2 (T3), between 2007 and 2014. Setting: The pan-European IDEFICS/I.Family cohort. Participants: 3098 children aged 2–16 years were genotyped. A total of 1907 participants at time measurement 3 (T3) were included, with complete information in all parameters of interest. Outcome measures: body mass index (BMI) and waist circumference (WC). A 7-item Mediterranean Diet Score (MDS) to assess the degree of MD adherence, and a genome-wide polygenic risk score (PRS) for BMI previously built within the IDEFICS/I.Family consortium, from a previous GWAS to capture obesity risk. Statistical analysis: In T3, multiple linear regressions to test MD–adiposity and MD-food-groups–adiposity associations, adjusted by age, sex, parental education, genetic susceptibility to obesity, population stratification, region of residence, screen sedentary time (SST), and physical activity. Then, the same models were used to estimate gene x diet effects, based on the PRS x MD adherence. Results: No associations were found between MDS and BMI or WC adiposity markers (p-value 0.26, B 0.10). In terms of food groups, higher vegetable consumption was inversely associated to BMI (p-value < 0.01, B −0.01) and WC (p-value 0.01, B −0.02), although no gene x vegetables interaction effects were found (BMI p-value 0.43, B < 0.01; WC p-value 0.49, B 0.01). Age and SST were also significantly associated to BMI (p-value 0.01, B −0.12; p-value < 0.01, B 0.02), and only SST to WC (p-value 0.03, B 0.05), respectively. Conclusions: Higher consumption of vegetables might be associated with lower obesity, irrespective of their obesity genetic risk.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".