Socio-Economic and Cultural Influence on Vitamin A Intake of Lactating Mothers in Ngaoundere Cameroon
Bibliographic record
Abstract
Background: Vitamin A deficiency (VAD) is a widespread public health problem in developing nations affecting greatly pregnant and lactating women. The intake of Vitamin A rich foods highly recommended to reduce the prevalence in these vulnerable groups are greatly influenced by the level of education, geographic origin and differences in food habits. Aims of the Study: To evaluate the Influence of socio-economic, cultural, geographic origin, and demographic factors on vitamin A (VA) intake of lactating mothers in Ngaoundere, Cameroon. Method: A total of 100 lactating mothers attending pediatric consultations at four major health structures in Ngaoundere were involved in the survey. A questionnaire was used to get information on socio-economic, cultural, demographic factors, geographic origin, anthropometric parameters and culinary practices. Dietary intake was assessed using a 24-hour dietary recall method. Meals potentially rich in VA consumed by these women were collected, their carotenoids contents quantified and VA activity determined. Results: Average VA intake of lactating women of Northern origin was significantly (p< 0.05) lower (595.2±60.4μg/day) than that of women of Southern origin (737.6±55.6μg/day), although both were below the recommended intake of 850μg/day. VA intake was also higher in the more educated women. Marital status, number of children, age of the mother and body mass index did not significantly influence the daily VA intake of the women. Lactating women of Northern origin, with three or more children and having no formal education, are more at risk of acute VA Deficiency. Conclusion: While the level of education influenced the VA intake in lactating women from the Northern Region, the age of the baby influenced those from the Southern Region.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".