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Enregistrement W4412806939 · doi:10.1186/s13690-025-01637-w

Trends and factors associated with anemia among women of reproductive age in Mali: analysis of data from 2001 to 2018 Mali demographic and health surveys

2025· article· en· W4412806939 sur OpenAlexaff
Ebenezer Kwesi Armah‐Ansah, Eugene Budu, Charity Oga‐Omenka, Марина Колосницына

Notice bibliographique

RevueArchives of Public Health · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueGlobal Maternal and Child Health
Établissements canadiensUniversity of Waterloo
Organismes subventionnairesnon disponible
Mots-clésPublic healthMedicineHealth services researchEnvironmental healthReproductive medicineHealth informaticsReproductive healthDemographyGeographyPopulationPregnancyNursingSociology

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Even though widespread attempts have been made to halve the incidence of anemia by 2025, the prevalence remains alarmingly high among women of reproductive age in Africa. The government of Mali has underscored the necessity for a multi-sectoral approach to reducing the anemia burden. However, no studies have considered the trends and factors associated with anemia among women of reproductive age in Mali. Hence, this study examined the prevalence and trends of anemia among women of reproductive age in Mali from 2001 to 2018. METHODS: The study analyzed datasets from the 2001, 2006, 2012–2013, and 2018 Mali Demographic and Health Surveys. We included a total weighted sample of 18,096 women of reproductive age who had participated in the hemoglobin test. Multilevel regression analysis was employed, and the results were presented as adjusted odds ratio (aOR), with 95% confidence intervals (CIs) and p-values used to show the results. RESULTS: We found that anemia prevalence in Mali remained persistently high, with a marginal increase from 63.4% in 2001 to 63.5% in 2018. The overall prevalence of anemia among women of reproductive age in Mali from 2001 to 2018 was 59.3% [95% CI: 58.2–60.4%]. We found, however, that about 2.6% were severely anemic. The study found that women of reproductive age who have secondary and above education [aOR = 0.75, 95% CI = 0.67–0.84], overweight women [aOR = 0.62, 95% CI = 0.55–0.70], women in the richest wealth quintile [aOR = 0.83, 95% CI = 0.71–0.97], women who have improved sources of drinking water [0.91, 95% CI = 0.84–1.10], women who lived in the Kidal Region [aOR = 0.38, 95% CI = 0.30–0.49], and women of reproductive age who lived in communities with medium literacy [aOR = 0.80, 95% CI = 0.73–0.87] had lower odds of being anemic. However, women who were captured in the 2018 survey year [aOR = 1.23, 95% CI = 1.11–1.37], women with four or more births [aOR = 1.15, 95% CI = 1.02–1.30], and women who were pregnant [aOR = 1.57, 95% CI = 1.42–1.73] had higher odds of developing anemia. CONCLUSION: The prevalence of anemia among women of reproductive age in Mali remains alarmingly high and virtually unchanged in 17 years. To address this persistent public health challenge, coordinated action is necessary. The government and public administrators should prioritize strengthening antenatal care services through free maternal health care, iron supplementation, treated mosquito nets, and deworming programs. Additionally, the Ministry of Water and Sanitation, in collaboration with traditional leaders and community health authorities, must ensure that every household has access to protected, potable drinking water. Finally, the Ministry of Education and the Ministry of Health and Public Hygiene should jointly develop targeted health and nutrition interventions and programs that would mitigate anemia prevalence among women of reproductive age in Mali. Without these concerted efforts, this significant public health burden is likely to persist.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,026
Score d'incertitude au seuil0,976

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0020,002
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,080
Tête enseignante GPT0,348
Écart entre enseignants0,268 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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