Adapting the environmental risk transition theory for urban health inequities: An observational study examining complex environmental riskscapes in seven neighborhoods in Global North cities
Bibliographic record
Abstract
Theories of epidemiologic transition analyze the shift in causes of mortality due to changes in risk factors over time, and through processes of urbanization and development by comparing risk factors between countries or over time. These theories do not account for health inequities such as those resulting from environmental injustice, in which minority and lower income residents are more likely to be exposed to environmental hazards or have less access to environmental goods. Neighborhoods with histories of environmental injustice are also at risk for gentrification as they undergo environmental improvements and new greening projects. We aimed to understand how environmental injustice, urban renewal and green gentrification could inform the understanding of epidemiologic risk transitions. We examined 7 case neighborhoods in cities in the United States and Western Europe which were representative in terms of city region and type, which 1) had experienced a history of environmental injustice and 2) exhibited evidence of recent processes of urban renewal and/or gentrification. In each city, we conducted semi-structured qualitative interviews (n = 172) with city representatives, activists, non-profits, developers and residents. Respondents reported health implications of traditional (heavy pollutants, poor social conditions), transitional (decontamination, new amenities), new (gentrification, access to amenities), and emerging (displacement, climate-related risks, re-emergence of traditional exposures) exposures. Respondents reported renewed, complexified and overlapping exposures leading to poor mental and physical health and to new patterns of health inequity. Our findings point to the need for theories of environmental and epidemiologic risk transitions to incorporate analysis of trends 1) on a city-scale, acknowledging that segregation and patterns of environmental injustice have created unequal conditions within cities and 2) over a shorter and more recent time period, taking into account worsening patterns of social inequity in cities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".