Determinants of dietary diversity among children 6–23 months: a cross‐sectional study in three regions of Haiti
Bibliographic record
Abstract
BACKGROUND: The prenatal, perinatal, postnatal and nutritional (A3PN) support study was a 4-year initiative aimed to reduce maternal mortality in Haiti. A cross-sectional study was developed to collect the baseline data for evaluation purposes of the A3PN. This study aimed to determine the factors contributing to dietary diversity (DD) in Haitian children aged 6-23 months. METHODS: A cross-sectional study during two seasons (the lean season and the harvest season) was carried out in Haiti to assess the DD of children and their mothers using non-quantitative 24-h recalls. Indicators of DD were minimum dietary diversity for children (MDD-C) and minimum dietary diversity for women (MDD-W). Mid-upper arm circumference was measured in women and children, and food security was assessed using the Household Hunger Scale. Focus groups were also conducted to gain a better understanding of the quantitative findings. RESULTS: Only 7.3% of the children included in this study met the MDD-C. Factors associated with MDD-C were the season (odds ratio [OR]: 0.141 [0.039-0.513]), land ownership or rental (OR: 4.603 [1.233-17.188]), maternal education (OR: 0.092 [0.011-0.749]), the mother's responsibility for the main or secondary source of income for the household (OR: 2.883 [1.030-8.069]) and her DD (OR: 5.690 [1.916-16.892]). Focus groups revealed the existence of various food restrictions. CONCLUSIONS: The results indicated that the low prevalence of MDD-C in three regions of study in Haiti is indicative of a serious public health concern that might be further aggravated by local food taboos. They also suggest that to fight against hunger, it is necessary to focus on women's well-being.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".