How social and commercial determinants influence exclusive breastfeeding in the Philippines
Bibliographic record
Abstract
Abstract Background The World Health Organization recommends exclusive breastfeeding (EBF) for the first six months after delivery. However, the EBF rate in the Philippines is only 29%. Existing literature suggests that the influence of infant formula marketing (IFM), communication channels, and traditional health beliefs are possible contributors to low EBF rates, but rare studies have been conducted in low-resource settings. Methods: To bridge the gap, 15 barangays in Palawan were selected; 97 interviews were conducted with lactating mothers (LM), health workers (HW), traditional healers, infant formula sellers, and community leaders (CL) to represent different perspectives. The results were coded and analyzed inductively. Results LM received EBF information through multiple resources. Poverty, lacking breast milk (BM), EBF education, and health benefits (HB) to infants are top contributors to EBF while maternal employment and no BM are top barriers to EBF. Elders, traditional health beliefs (THB), and the influence of COVID-19 can influence EBF in both directions. LM emphasized more on poverty and elders to EBF while HW and CL emphasized the role of EBF education and HB. Urban LM tend to have more regular EBF education, use pumps when going out, and are more influenced by IFM. LM in remote areas tend to have more THB, have more BM substitutes, and share BM. Social classes, locations, Indigeneity, migration, and poverty are intersectioned to influence EBF. Conclusions Multiple social and commercial determinants influenced EBF. LM is facing more challenges to EBF under globalization and capitalism. Remote LM are less benefited from new technologies and policies to promote EBF. Different stakeholders have echo chambers to perceive the determinants of EBF. To improve health equity and EBF, the situations of marginalized people in remote areas should be more considered in policy making. Community building should also be considered differently to assist in EBF. Key messages • The project focuses on social and commercial determinants of exclusive breastfeeding with people in extreme poverty. • The project includes plenty of Indigenous breastfeeding behavior that are underreported.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".