Association between Maternal Dietary Inflammatory Index (DII) and abortion in Iranian women and validation of DII with serum concentration of inflammatory factors: case-control study
Bibliographic record
Abstract
Previous studies have shown that some dietary components may be implicated in the etiology of spontaneous abortion. However, the possible relationship between diet-related inflammation and the risk of abortion has not yet been investigated. We examined the ability of the literature-derived Dietary Inflammatory Index (DII) to predict the abortion incidence in women suffering from recurrent abortion in a case-control study conducted from April 2010 to March 2011. This included 67 incident cases and 68 controls (frequency matched to cases by age) who attended infertility and miscarriage specialized centers in Tehran, Iran. The DII was computed based on dietary intake assessed using a validated and reproducible 168 item food-frequency questionnaire. Logistic regression models were used to estimate multivariable ORs adjusted for age, education, occupation, and body mass index. Subjects with higher DII scores (i.e., a more pro-inflammatory diet) had higher odds of abortion, with the DII being used as a continuous variable (OR continuous = 2.12, 95% CI: 1.02–4.43). When analysis was carried out with DII expressed as a dichotomous variable, women in the pro-inflammatory diet group (DII > 1.24) were at 2.12 times higher odds of having abortion compared with women in the referent group (DII ≤ 1.24) (ORDII >1.24/≤1.24 = 2.12; 95% CI: 1.02–4.43). In the same study, for every 1-unit increase in DII, there was a corresponding increase in interleukin-6 by 0.15 pg/mL, 95% CI (<0.01, 0.28). In conclusion, subjects who consumed a more pro-inflammatory diet were at increased odds of abortion compared with those who consumed a more anti-inflammatory diet.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| 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 | 0.001 | 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".