Correlate of adherence to exclusive breastfeeding while on anti-retroviral therapy: associated factors among mothers living with HIV in Port Harcourt, Nigeria
Bibliographic record
Abstract
Introduction: in low- and middle-income nations like Nigeria, vertical transmission of HIV is still common. Although there are recommended guidelines for infant feeding for women living with HIV, the level of adherence has significantly varied across African women. This study assessed the adherence to exclusive breastfeeding (EBF) guidelines and its associated factors among nursing mothers living with HIV/AIDS in Port Harcourt, Nigeria. Methods: a descriptive cross-sectional study was carried out between March and August 2022 among nursing mothers living with HIV/AIDS. Structured and validated questionnaires were used to collect data from 400 participants and were analyzed for this purpose. Chi-square statistics; bivariate and multivariate logistic regression analyses were carried out at alpha 0.05 to determine the correlates of adherence to the national guideline of exclusive breastfeeding while on anti-retroviral therapy. Results: the majority of the respondents were within the age range 30-39 years, 66.0% with a mean age of 34.6±5.6. Most respondents know (90.7%) of the mothers knew about the EBF policy and 65% adhered to the policy guidelines. Being employed/self-employed (OR=2.22, p=0.001); knowledge of the guidelines (OR=6.3, p=0.001); and support from household (OR=2.39, p=0.003), father/spouse (OR=65.6, p=0.001), close relatives (OR=3.5, p=0.001), healthcare (OR=38.2, p=0.01) were all associated with adherence to EBF. After adjusting for confounders, using the multivariate logistic regression, only support from father/spouse (OR=23.24, p=0.001) and healthcare (OR=47.6, p=0.01) were strong predictors of adherence to EBF guidelines. Conclusion: inclusive education involving mothers, social support networks, and healthcare providers will increase adherence to national guidelines EBF among mothers living with HIV.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".