Inégalités de Genre et Anémie des Femmes en Union dans les Provinces de Cibitoke et Kirundo (Nord-Ouest et Nord du Burundi)
Bibliographic record
Abstract
Contexte : La prévalence de l’anémie chez les femmes en âge de procréer est de 52,5% dans la province de Cibitoke et de 60,4% dans celle de Kirundo, ce qui dépasse largement la moyenne nationale de 39%. Objectif : Cette étude vise à expliquer cette forte prévalence en analysant l’incidence des inégalités de genre. Méthodologie : Par la régression logistique binomiale, l’étude analyse les données collectées auprès de 270 et 276 femmes en union, de Cibitoke et de Kirundo, respectivement, qui ont accepté de se soumettre au test d'hémoglobines lors de l'Enquête Démographique et de Santé du Burundi (EDSB 2016-2017). Résultats : À Cibitoke, les femmes dont les maris décident seuls des gros achats pour la maison sont plus de 4 fois plus susceptibles d'être anémiées que celles qui sont impliquées dans ces décisions. À Kirundo, les femmes dont les maris décident seuls de l'utilisation de l'argent qu'ils ont gagné sont près de 2,5 fois plus susceptibles d'être anémiées que celles qui prennent ces décisions conjointement avec leurs maris. Conclusion : Ces résultats indiquent qu’au-delà de la suprématie masculine consacrée par le patriarcat burundais, les femmes sont victimes de violences économiques basées sur le genre dans ces provinces. Face aux conjoints qui dilapident les ressources des ménages dans des relations de concubinage et de polygamie, les femmes s'adaptent mal aux dynamiques familiales dans un contexte de changement climatique et de mutations rurales. D’où leur vulnérabilité vis-à-vis de l'anémie. Background: The prevalence of anemia among women of childbearing age is 52.5% in the province of Cibitoke and 60.4% in Kirundo, well above the national average of 39%. Objective: This study aims to explain this high prevalence by analyzing the incidence of gender inequalities. Methodology: Using binomial logistic regression, the study analyzes data collected from 270 and 276 women in the union, from Cibitoke and Kirundo respectively, who agreed to undergo hemoglobin testing during the Demographic and Health Survey of Burundi (DHSB 2016-2017). Results: In Cibitoke, women whose husbands make alone decision on major household purchases are more than 4 times more likely to be anemic than those who are involved in these decisions. In Kirundo, women who live in households where one of the partners decides alone how to use the money earned by the husband are almost 2.5 times more likely to suffer from anemia than those who make these decisions jointly within the couple. Conclusion: These results indicate that, over and above the male supremacy patriarchy, women are victims of gender-based economic violence in these provinces. Faced with spouses who squander household resources in concubinage and polygamy, women adapt themselves hardly to family dynamics in the context of climate change and rural mutations. This makes them vulnerable to anemia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".