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Enregistrement W7042603006

Prevalence of mental health disorders among pregnant women living in public housing in Manitoba.

2024· dissertation· en· W7042603006 sur OpenAlexaboutno aff

Notice bibliographique

RevueMspace (University of Manitoba) · 2024
Typedissertation
Langueen
DomaineMedicine
ThématiqueMaternal Mental Health During Pregnancy and Postpartum
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMental healthPregnancyPublic healthPsychological interventionPostpartum periodPrevalence of mental disordersMental illness
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Background: Women are more likely to experience a higher burden of mental health disorders than men. Pregnancy is one of the most sensitive and complex periods in a woman’s life; the physical and psychological changes that take place during pregnancy can impact pregnant women’s mental health. In Canada, approximately one in four women experience a mental health disorder during pregnancy or the postpartum period. Maternal mental health disorders include a range of disorders and symptoms, including but not limited to depression, anxiety, and psychosis. Housing is considered one of the most critical social determinants of physical and mental health, particularly among pregnant women. Public housing (PH) is a government-funded housing program that provides affordable housing to individuals or families with limited or fixed incomes. Finlayson et al., (2013), found a higher proportion of women in PH than men. Women with mental health disorders during pregnancy and living in poor quality housing conditions are less likely to receive adequate prenatal care. They are also more likely to engage in unhealthy behaviours such as smoking and use of alcohol and other substances which are known to cause devastating consequences for mothers, babies, and society. While there is evidence to suggest that people living in PH have a higher burden of mental health disorders, little is known about these disorders among pregnant women living in PH. This is despite the unique physiological and social changes that they experience as they transition to parenthood. Objectives: The study examined the prevalence and incidence of mental health disorders (mood and anxiety, substance use, psychotic and personality disorders and any mental health disorders) among pregnant women who had a live singleton birth while living in PH and compared with pregnant women who did not live in PH during the study period. Methods: A population-based retrospective cohort study was conducted among 2,226 pregnant women who lived in PH and 57,132 pregnant women who did not live in PH, aged 18 to 45 years who experienced at least one pregnancy that resulted in a singleton, live birth between April 1, 2009–March 31, 2018 in Manitoba. Descriptive statistics were used to describe maternal demographic characteristics (age, income quintiles, receipt of income assistance, high school completion, parity, Charlson Commodity Index, region of residence). Univariate and multiple logistic regressions were used to calculate the diagnostic prevalence of mental health disorders before conception among pregnant women in both groups. Negative binomial regression was used to compare the incidence rates of these disorders among the same two groups of women during pregnancy and postpartum period. Results: When compared with the women who did not live in PH, women who lived in PH had significantly higher odds of being diagnosed with all mental health disorders five years before conception: (a) mood and anxiety disorder (OR, 2.08; 95% CI, 1.91, 2.26), (b) substance use disorder (OR, 3.03; 95% CI, 2.65-3.47), (c) personality disorder (OR, 2.85; 95% CI, 2.17-3.73), (d) psychotic disorder (OR 3.26; 95% CI, 2.25-4.72), and (e) any mental health disorders (OR 2.21; 95% CI, 2.03-2.41). However, I found no significant differences in the odds for mood & anxiety disorders, substance use disorders, and any mental health disorders when comparing women who lived in PH with their comparison after adjusting for the covariates. Personality and psychotic disorders could not be compared between the two groups in the multivariable analysis due to the small number of events. Furthermore, the unadjusted incident rates of mental health disorders diagnosed during pregnancy and after birth were significantly higher among women who lived in PH compared with their comparison for mood and anxiety disorders (RR, 1.23; 95% CI, 1.06-1.42), substance use disorders (RR, 1.54; 95% CI, 1.16-2.03), personality disorders (RR 2.71; 95% CI, 1.56-4.72), and any mental health disorders (RR 1.12; 95% CI, 0.99-1.27). There was no statistically significant difference for psychotic disorders (RR 1.30; 95% CI, 0.48-3.61). After adjusting for the covariates, the incident rate of substance use disorders was significantly lower among the women who lived in PH compared with women who did not live in PH. There were no significant differences in the incident rates for mood & anxiety disorders and any mental health disorders between the two groups. Conclusion: Unadjusted models showed that women living in PH had higher diagnostic prevalence and incidence of mental health disorders when compared with those who did not live in PH. However, in the fully adjusted models, receipt of income assistance (IA) accounted for much of the observed differences in mental health disorders between those who lived and those who did not live in PH. This study highlights the critical importance of addressing income inequities among residents of public housing with limited financial resources to improve their overall health and social outcomes.

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)0,000
score de la tête « metaresearch » (Gemma)0,001
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 enseignants0,283
Score d'incertitude au seuil0,570

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0020,001
Communication savante0,0010,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,016
Tête enseignante GPT0,244
Écart entre enseignants0,229 · 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

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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