Food quality score and anthropometric status among 6‐year‐old children: A cross‐sectional study
Bibliographic record
Abstract
OBJECTIVE: Weight status and growth during childhood are indicative of healthy development throughout the lifespan. It is well understood that dietary patterns and overall quality of diet can prevent disease, improve health status and optimise growth and development. The current study investigates the relationship between overall diet quality and measures of childhood development including body mass index and height-for-age in 6-year-old children. METHODS: This cross-sectional study was conducted across 788 6-year-old children from Tehran, Iran, in 2018. Food quality score (FQS) was used to assess overall diet quality, in addition to a modified food-based diet quality score specific to children (modified FQS) developed by our group. RESULTS: Participants in the highest tertile using the modified FQS had the highest height-for-age z-score (HAZ) (-0.509 ± 0.028 vs -0.605 ± 0.028; P = .048). In contrast, participants in the highest tertile assessed using the original FQS had a higher BMI for age z-score (BAZ) compared to participants in the first tertile (0.391 ± 0.072 vs 0.266 ± 0.072; P = .023). Children within the highest tertile, according to the original FQS, compared to those within the lowest tertile were 49% less likely to be categorised as severely underweight (OR: 0.51; 95% CI: 0.47-0.98). CONCLUSIONS: Findings presented in this study demonstrate that FQS was significantly associated with participants characterised as severely underweight; however, FQS was not associated with other anthropometric parameters. Therefore, future well-designed cohort studies are required to address limitations of the current study.
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 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 | 0.003 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".