Prevalence of and Factors Associated With Lactational Mastitis in Eastern and Southern Africa: An Exploratory Analysis of Community-Based Household Surveys
Bibliographic record
Abstract
Abstract BackgroundLactational mastitis is an extremely painful and distressing inflammation of the breast, which can seriously disrupt breastfeeding. Most of the evidence on the frequency of this condition and its risk factors is from high-income countries. Thus, there is a crucial need for more information on lactational mastitis and its associated factors in Sub-Saharan Africa (SSA).MethodsWe used data from representative, community-based cross-sectional household surveys conducted with 3,315 women from four countries (Ethiopia, Kenya, Malawi, and Tanzania) who reported ever-breastfeeding their last child born in the two years before the survey. We first estimated country-specific and pooled prevalence of self-reported lactational mastitis and examined mastitis-related breastfeeding discontinuation. Additionally, we examined factors associated with reporting mastitis in the pooled sample using bivariate and multivariable logistic regression accounting for clustering at the country level and post-stratification weights.ResultsThe prevalence of self-reported lactational mastitis ranged from 3.1% in Ethiopia to 12.0% in Kenya. Close to 17.0% of women who experienced mastitis stopped breastfeeding because of mastitis. The adjusted odds of self-reported lactational mastitis were approximately two-fold higher among women who completed at least some primary school compared to women who had no formal education. Study participants who delivered by caesarean section had 1.46 times higher odds of reporting lactational mastitis than women with a vaginal birth. Despite wide confidence intervals, our models also indicate that young women (15 – 24 years) and women who practiced prelacteal feeding had higher odds of experiencing lactational mastitis than older women (25+ years) and women who did not give prelacteal feed to their newborn. ConclusionThe prevalence of lactational mastitis in four countries of SSA might be somewhat lower than estimates reported from other settings. We found that lactational mastitis may result in breastfeeding discontinuation in approximately 1 in 5 woman-infant dyads affected by the condition. Factors such as younger age, higher education, caesarean section, and prelacteal feeding may be associated with experiencing mastitis. Further studies should explore the risk and protective factors for lactational mastitis in African contexts and address the negative consequences on breastfeeding.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".