Determinants of Exclusive Breastfeeding and Introduction of Complementary foods in Rural Egyptian Communities
Bibliographic record
Abstract
BACKGROUND: Determinants of breastfeeding (BF) exclusivity at a rural Egyptian setting are largely unknown. This cross-sectional study aimed to assess BF indicators, specifically exclusivity and the timely complementary feeding while assessing potential determinants that affect exclusivity of BF among a sample of mothers inhabiting Egyptian rural communities. METHODS: A community based cross-sectional study was carried out over a period of four months with inclusion of 1000 eligible women having infants aged less than two years through a multi-stage random sampling method. Personal interview, using structured questionnaire, to collect information on socio-demographic characteristics, antenatal care services, women's lactation practices, complementary feeding practices and knowledge about BF. RESULTS: All the included mothers had breastfed their infants, and 32.4% of them initiated BF within the first hour of life and 29.9% exclusively breastfed their infants for 6 months after birth. Complementary feeding was introduced for children aged 6-9 months in 63.6% of them. Bivariate analysis showed that factors favoring exclusive BF were age of the mother (< 25 years), with secondary or higher education, number of children, with no history of complicated pregnancy or lactation problems, received health education about BF and having knowledge about BF. Logistic regression model showed that most influential significant predictor for exclusive BF was receiving of health education about BF and adequate knowledge of BF. CONCLUSIONS: Although all rural Egyptian mothers included, initiated BF, the rate of its exclusivity was low. Comprehensive education about BF during pregnancy is strongly needed to promote BF among them.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".