Factors Associated with Subclinical Mastitis (SCM) Among Indigenous Mothers in the Western Highlands of Guatemala
Bibliographic record
Abstract
Background SCM is an asymptomatic inflammatory condition of the lactating breast where a breast milk ratio of Na/K>0.6 is the current indicator. Our objective was to determine maternal and infant factors associated with an increased or decreased likelihood of SCM. Methods Breast milk samples were collected from 105 lactating Mam‐Mayan mothers with infants < 6 mo. Inductively Coupled Plasma Mass Spectrometry measured Na and K. A structured in‐depth questionnaire for independent factors including socio‐demographic characteristics, maternal and infant health status, breastfeeding (category, initiation, feeding frequency), cultural practices and beliefs, and maternal physical activity that might be associated with SCM was administered to mothers; anthropometry of both mother and infant was measured. Results Fourteen‐percent had a breast milk Na/K ratio >0.6. SCM was associated with maternal age (OR=1.1, p=0.011), parity (OR=1.3, p=0.011), walking (OR=1.7, p=0.008), breastfeeding frequency (OR=1.1, p=0.024), and infant weight‐for‐age (WAZ) score (OR=0.57, p=0.049) Conclusion Results suggest that interventions to decrease the prevalence of SCM should be targeted to older mothers with high parity. Interestingly, breastfeeding frequency and walking were associated with SCM whereas cultural practices and beliefs were not in our population. Our findings were consistent with previous research where maternal SCM was associated with decreased infant weight. Funding McGill University International Mobility Travel Award
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".