Adherence to planetary health diet index in relation to dietary diversity score and anthropometric indices among Iranian older adults
Bibliographic record
Abstract
BACKGROUND: Ensuring a nutritious and sustainable diet for an expanding population presents a formidable challenge. In response to this pressing issue, the EAT-Lancet Commission has proposed a sustainable diet framework. This study aimed to investigate the relationship between Planetary Health Diet (PHDI), Dietary Diversity Score (DDS), and anthropometric indices among Iranian elders. METHODS: In this cross-sectional study, 398 participants aged ≥ 60 y were included. Dietary data was collected using a validated 168-item food frequency questionnaire and the DDS was computed based on five distinct food groups. Anthropometric measurements were conducted by standard protocol to derive relevant indices. Binary logistic and linear regression models, adjusted for potential confounders, were employed to analyze the association between adherence to PHDI and outcomes of interest using SPSS version 26. RESULT: Subjects had a mean age of 63.28 years (SD = 3.58), ranging from 60 to 84 years, of whom 50% were females. PHDI was categorized into tertiles, with 34.7% of individuals in the highest tertile. Highest adherence to PHDI, compared to the lowest, was found to be inversely associated with a lower probability of high BMI (OR: 0.31, 95% CI: 0.17, 0.56), WC (OR: 0.53, 95% CI: 0.32, 0.90), and BRI (OR: 0.43, 95% CI: 0.25, 0.75) in fully adjusted models. Additionally, every 10-point increase in PHDI was linked to a 38%, 25%, and 28% decrease in odds of high BMI, WC, and BRI, respectively, after adjustments for potential confounders. Notably, no significant associations were observed between PHDI and other anthropometric indices or DDS in the fully adjusted model. CONCLUSION: In conclusion, this study reveals a negative association between adherence to EAT-Lancet recommendations (PHDI) and unfavorable anthropometric measures in Iranian older adults. These findings suggest that promoting diets aligned with the EAT-Lancet guidelines may support healthier aging and help prevent obesity-related health risks. Further, prospective studies are needed to confirm these results and inform public health strategies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".