Dietary Intake at 9 Years and Subsequent Body Mass Index in Adolescent Boys and Girls: A Study of Monozygotic Twin Pairs
Bibliographic record
Abstract
There is a lack of evidence pointing to specific dietary elements related to weight gain and obesity prevention in childhood and adulthood. Dietary intake and obesity are both inherited and culturally transmitted, but most prospective studies on the association between diet and weight status do not take genetics into consideration. The objective of this study was to document the association between dietary intake at 9 years and subsequent Body Mass Index (BMI) in adolescent monozygotic boy and girl twin pairs. This research used data from 152 twin pairs. Dietary data were collected from two 24-hour-recall interviews with a parent and the child aged 9 years. Height and weight were obtained when the twins were aged 9, 12, 13, and 14 years. Intrapair variability analysis was performed to identify dietary elements related to BMI changes in subsequent years. BMI-discordant monozygotic twin pairs were also identified to analyze the dietary constituents that may have generated the discordance. After eliminating potential confounding genetic factors, pre-adolescent boys who ate fewer grain products and fruit and consumed more high-fat meat and milk had higher BMIs during adolescence; pre-adolescent girls who consumed more grain products and high-fat meat and milk had higher BMIs during adolescence. Energy intake (EI) at 9 years was not related to BMI in subsequent years. Our study suggests that messages and interventions directed at obesity prevention could take advantage of sex-specific designs and' eventually' genetic information.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".