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Enregistrement W4390646845 · doi:10.5463/thesis.556

Poverty and high parity in rural settings

2024· dissertation· en· W4390646845 sur OpenAlexaff
Manuela Straneo

Notice bibliographique

Revuenon disponible
Typedissertation
Langueen
DomaineMedicine
ThématiqueGlobal Maternal and Child Health
Établissements canadiensAthena Sustainable Materials Institute
Organismes subventionnairesEuropean Commission
Mots-clésTanzaniaChildbirthPovertyParity (physics)MedicineHealth facilityHealth careSocioeconomicsEnvironmental healthDemographyPregnancyPopulationEconomic growthHealth servicesSociologyEconomics

Résumé

récupéré en direct d'OpenAlex

In this thesis I have studied where women give birth within the health system in sub-Saharan Africa, firstly in Tanzania and then in other countries, focusing on the use of hospitals in rural settings. Though childbirth care is available at different levels of the health system, hospitals are generally where advanced management of childbirth complications is available. This is particularly important for women with risk factors, at greater risk of complications and death. The research has examined the interaction of biological risk (high parity) with socio-economic vulnerability (poverty), identifying a subgroup of women who are poor, rural and of high parity who, despite greater risk of childbirth complications, have lower use of hospitals. In Iringa rural district in Tanzania, with nearly universal facility births coverage, my co-researchers and I found poor women were underrepresented in the only hospital in the district. This finding led to hypothesizing that women from poorer households were more likely to use primary care facilities for childbirth. Use of hospitals in all Tanzania was studied using nationally representative Demographic and Health Survey data. In rural Tanzania, we found that the effect of poverty on use of hospitals depended on the level of parity. Women who were both poor and at high parity used hospitals least: only around one in ten women who were poor and at high parity had given birth in a hospital in the period studied. The complex interacting and interdependant factors related to high parity, poverty and rurality are likely to be responsible. High parity, poor, rural women have remained marginalized in use of hospitals over the most recent 25 years for which data were available (1991-2016). This finding is particularly relevant as the country has been at the forefront in rolling out primary health care since independence. High population growth brought an increase of 35,000 births/year over this period. Health system expansion during this time to achieve universal coverage of essential services to a growing, mostly rural population prioritized primary care facilities compared to hospitals. Across a range of sub-Saharan African countries, we found the same pattern of low use of hospitals by high parity, poor, rural women. Using a simple, reproducible tool, some countries had comparatively higher socio-economic equality and use of hospitals by women at high parity. Malawi and Liberia, closely followed by Zimbabwe, the Gambia and Rwanda, ranked higher in a composite use and equity index. Further studies on policy in these countries are needed to identify policies and guidelines that facilitate equitable use of hospitals by women, particularly at high parity. Low use of hospitals by high parity women impacts perinatal mortality in SSA. In a study on births in 16 hospitals across four SSA countries (Benin, Malawi, Tanzania and Uganda), women of high parity had a high risk of intrapartum (fresh stillbirths and very early neonatal deaths) mortality when they reached hospitals following intrapartum referral. The risk of death of a baby born to a woman of high parity referred intrapartum was 2.5 times greater than that of high parity women who reached hospitals without referral. To reduce the risk associated with intrapartum referral among these women, measures are urgently needed to ensure all high parity women use hospitals for childbirth. Policy makers’ recognition of this marginalized group of women is urgently needed to put in place measures to mitigate their disadvantage and higher risk of adverse outcomes, including improved access to hospitals.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut 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 enseignants0,007
Score d'incertitude au seuil0,018

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0020,001
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0050,000

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 Opus0,005
Tête enseignante GPT0,278
Écart entre enseignants0,273 · 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 source (Gemma direct ou Codex distillé), 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

Citations1
Publié2024
Routes d'admission1
Résumé présentoui

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