BREASTFEEDING AND ACUTE RESPIRATORY INFECTION (ARI) IN INFANTS: A SYSTEMATIC REVIEW IN NIGERIA.
Bibliographic record
Abstract
Background: Acute Respiratory Infections (ARIs) significantly contribute to infant morbidity and mortality worldwide, especially in developing countries like Nigeria, where factors such as inadequate nutrition, poor environmental conditions, and partial immunization increase their incidence, while exclusive breastfeeding (EBF) offers immune protection that can reduce their incidence and severity. Therefore this review assessed the role of breastfeeding, especially exclusive breastfeeding, in reducing the risk and severity of ARIs in Nigerian infants, while also evaluating factors influencing breastfeeding practices. Methods: A systematic review was conducted following PRISMA guidelines, involving a comprehensive search of databases such as PubMed, Scopus, ScienceDirect, Google Scholar, and African Journals Online. Twelve studies conducted between 2004 and 2024 focusing on breastfeeding practices and their impact on ARIs in Nigerian infants aged 0-6 months were selected. The review focused on primary studies with observational and cohort designs. Results: The review found that exclusive breastfeeding significantly reduces the risk of ARIs in infants, with non-exclusively breastfed infants facing a fourfold increase in ARI risk. Breast milk contains immunologically active components like secretory IgA, lactoferrin, and lysozyme, which enhance immune defenses and reduce the severity of ARIs such as pneumonia. However, only 25-40% of infants in Nigeria are exclusively breastfed for six months due to cultural beliefs, maternal employment, lack of education etc. Conclusion: Exclusive breastfeeding significantly protects Nigerian infants against ARIs, but cultural misconceptions, socioeconomic barriers, insufficient maternal education etc hinder optimal practices, necessitating targeted public health initiatives and policy interventions to improve infant health outcomes.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".