The effects of contemporary redlining on the mental health of Black residents
Notice bibliographique
Résumé
Understanding how structural racism, including institutionalized practices such as redlining, influence persistent inequities in health and neighborhood conditions is still emerging in urban health research. Such research often focuses on historical practices, giving the impression that such practices are a thing of the past. However, mortgage lending bias can be readily detected in contemporary datasets and is an active form of structural racism with implications for health and wellbeing. The objective of the current study was to test for associations among multiple measures of mental health and a measure of contemporary redlining. We linked a redlining index constructed using Home Mortgage Disclosure Act data (2007-2013) to 2021 health data for Black/African American participants in the Study of Active Neighborhoods in Detroit (n = 220 with address data). We used multilevel regression models to examine the relationship between redlining and a suite of mental health outcomes (perceived stress, anxiety, depressive symptoms, and satisfaction with life), accounting for covariates including racial composition of the neighborhood. We considered three mediating factors: perceived neighborhood cohesion, aesthetics, and discrimination. Although all participants lived in redlined neighborhoods compared to the complete Detroit Metropolitan area, participants with very low income, low levels of experienced discrimination, and lower perceptions of neighborhood aesthetics resided in highly redlined neighborhoods (score ≥5). We observed that higher resident-reported neighborhood aesthetics were found in neighborhoods with lower redlining scores and were associated with higher levels of satisfaction with life. We found that lower levels of redlining were significantly associated with higher levels of perceived discrimination, which was significantly, positively associated with anxiety, depressive symptoms, and perceived stress scores. Our findings highlight that contemporary redlining practices may influence the aesthetics of the built environment because these neighborhoods experience less investment, with implications for residents' satisfaction with life. However, areas with lower redlining may be areas where Black/African American people experience increased perceived discrimination.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».