The effects of contemporary redlining on the mental health of Black residents
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".