Disparities in pedestrian streetscape environments by income and race/ethnicity
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Notice bibliographique
Résumé
Growing evidence suggests that microscale pedestrian environment features, such as sidewalk quality, crosswalks, and neighborhood aesthetics, may affect residents' physical activity. This study examined whether disparities in microscale pedestrian features existed between neighborhoods of differing socioeconomic and racial/ethnic composition. Using the validated Microscale Audit of Pedestrian Streetscapes (MAPS), pedestrian environment features were assessed by trained observers along ¼-mile routes (N = 2117) in neighborhoods in three US metropolitan regions (San Diego, Seattle, and Baltimore) during 2009 to 2010. Neighborhoods, defined as Census block groups, were selected to maximize variability in median income and macroscale walkability factors (e.g., density). Mixed-model linear regression analyses explored main and interaction effects of income and race/ethnicity separately by region. Across all three regions, low-income neighborhoods and neighborhoods with a high proportion of racial/ethnic minorities had poorer aesthetics and social elements (e.g., graffiti, broken windows, litter) than neighborhoods with higher median income or fewer racial/ethnic minorities (p<.05). However, there were also instances where neighborhoods with higher incomes and fewer racial/ethnic minorities had worse or absent pedestrian amenities such as sidewalks, crosswalks, and intersections (p<.05). Overall, disparities in microscale pedestrian features occurred more frequently in residential as compared to mixed-use routes with one or more commercial destination. However, considerable variation existed between regions as to which microscale pedestrian features were unfavorable and whether the unfavorable features were associated with neighborhood income or racial/ethnic composition. The variation in pedestrian streetscapes across cities suggests that findings from single-city studies are not generalizable. Local streetscape audits are recommended to identify disparities and efficiently allocate pedestrian infrastructure resources to ensure access and physical activity opportunities for all residents, regardless of race, ethnicity, or income level.
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Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| 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 | 0,000 | 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 découle