The Minimum Dietary Diversity for Women of Reproductive Age (MDD-W) Indicator Is Related to Household Food Insecurity and Farm Production Diversity: Evidence from Rural Mali
Bibliographic record
Abstract
BACKGROUND: The popularity of nutrition-sensitive interventions calls for high-quality monitoring and evaluation tools. In this context, the Minimum Dietary Diversity for Women of Reproductive Age (MDD-W), validated as a proxy of micronutrient adequacy, does fill a gap. However, because it is a newly endorsed indicator, information on its linkages with other dimensions of food and nutrition security is still scarce. OBJECTIVE: The objective of this study was to investigate whether the MDD-W is related to household food insecurity and farm production diversity. METHODS: A cross-sectional survey on a representative sample of 5046 women of reproductive age was conducted in the region of Kayes, Mali, in 2013. Dietary diversity was assessed through qualitative 24-h recall, and MDD-W was computed. MDD-W equaled 1 if the women consumed at least 5 different food groups and 0 otherwise. Food insecurity was measured using the Household Food Insecurity Access Scale and the Household Hunger Scale (HHS), and a farm production diversity score (FPDS) was calculated based on a count of food crops/livestock groups produced. Logistic regressions were used to assess the relation between MDD-W and the indicators of household food security. RESULTS: Only 27% of women reached the MDD-W. These women consumed animal source foods and/or vitamin A-rich vegetables and fruits more frequently than did other women. Women from extremely food insecure households (moderate to severe hunger according to the HHS) were less likely to reach the MDD-W (OR: 0.70; 95% CI: 0.50, 0.97). One more group in the FPDS increased the odds of attaining the MDD-W (OR: 1.12; 95% CI: 1.06, 1.18). CONCLUSION: In the rural region of Kayes, Mali, women's dietary diversity, as measured by the MDD-W, was associated with household-level food security indicators. This study was registered at ISRCTN.org as ISRCTN08435964.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".