Association of dietary diversity of 6–23 months aged children with prenatal and postnatal obstetric care: evidence from a nationwide cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Dietary diversity is a key determinant of infant and young child eating patterns for a variety of food groups taken by children between the ages of 6-23 months. The study aimed to examine the association between prenatal and postnatal obstetric care factors of mother and child's dietary diversity, and specific food practices in Bangladesh. METHODS: This study analyzed the data of 2497 children between the age of 6-23 extracted from the latest countrywide Bangladesh Demographic Health Survey 2017-2018 and explored relationships between prenatal and postnatal obstetric care received by mother and dietary diversity score (DDS), minimum dietary diversity (MDD), and introduction of solid, semi-solid, and soft foods (ISSSF) of their children. RESULTS: Findings revealed that ≥ 4 antenatal care (ANC) visits care visits increased the DDS (adjusted [Formula: see text]: 0.32, 95% CI [0.21, 0.43]), increased the likelihood of MDD (AOR 1.54, 95% CI [1.23, 1.93]), and ISSSF (AOR 1.24, 95% CI [1.08, 1.48]), consuming eggs (AOR 1.47, 95% CI [1.23, 1.76]), and vitamin A vegetables and fruits (AOR 1.38, 95% CI [1.15, 1.66]). Moreover, DDS (adjusted β: 0.05, 95% CI [0.00, 0.11]) and MDD (AOR 1.66, 95% CI [1.31, 2.11]) are linked to childbirth in a medical facility. The C-section delivery influences the DDS (adjusted [Formula: see text]: 0.05, 95% CI [0.00, 0.10]), MDD (AOR 1.39, 95% CI [1.10, 1.75]), and ISSSF (AOR 1.22, 95% CI [1.02, 1.48]). Besides, postnatal visits within 48 h of delivery linked to MDD (AOR 0.66, 95% CI [0.49, 0.89]) and ISSSF (AOR 0.76, 95% CI [0.59, 0.97]), and physicians or professionals providing postnatal checkups were significantly associated with DDS (adjusted [Formula: see text]: 0.09, 95% CI [0.02, 0.16]), MDD (AOR 1.69, 95% CI [1.26, 2.26]), and ISSSF (AOR 1.30, 95% CI [1.04, 1.62]). CONCLUSION: Knowledge of child nutritional feeding should emphasize during prenatal and postnatal obstetric care of mother, particularly during antenatal and postnatal visits, C-section delivery, and birth in a healthcare facility to eradicate malnutrition and establish healthy child feeding practices.
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 | 0.002 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".