Association of Public Works Disasters with Substance Use Difficulties: Evidence from Flint, Michigan, Five Years after the Water Crisis Onset
Bibliographic record
Abstract
Public works environmental disasters such as the Flint water crisis typically occur in disenfranchised communities with municipal disinvestment and co-occurring risks for poor mental health (poverty, social disconnection). We evaluated the long-term interplay of the crisis and these factors with substance use difficulties five years after the crisis onset. A household probability sample of 1970 adults living in Flint during the crisis was surveyed about their crisis experiences, use of substances since the crisis, and risk/resilience factors, including prior potentially traumatic event exposure and current social support. Analyses were weighted to produce population-representative estimates. Of the survey respondents, 17.0% reported that substance use since the crisis contributed to problems with their home, work, or social lives, including 11.2% who used despite a doctor’s warnings that it would harm their health, 12.3% who used while working or going to school, and 10.7% who experienced blackouts after heavy use. A total of 61.6% of respondents reported using alcohol since the crisis, 32.4% using cannabis, and 5.2% using heroin, methamphetamine, or non-prescribed prescription opioids. Respondents who believed that exposure to contaminated water harmed their physical health were more likely to use substances to the detriment of their daily lives (RR = 1.32, 95%CI: 1.03–1.70), as were respondents with prior potentially traumatic exposure (RR = 2.99, 95%CI: 1.90–4.71), low social support (RR = 1.94, 95%CI: 1.41–2.66), and PTSD and depression (RR’s of 1.78 and 1.49, respectively, p-values < 0.01). Public works disasters occurring in disenfranchised communities may have complex, long-term associations with substance use difficulties.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".