Mental Health, Cardiovascular Disease and Declining Economies in British Columbia Mining Communities
Bibliographic record
Abstract
The purpose of this study was to investigate the relationship between community-level exposure to changes in economic conditions and the incidence and prevalence of mental disorders and cardiovascular disease in 29 resource-based communities (with a focus on mining communities) in British Columbia (BC) during a period of time marked by an economic downturn (1991–2002) The investigation relied on Labour Force Survey (LFS) and Statistics Canada Census data, and health records from the British Columbia Ministry of Health (MoH). Age and sex adjusted prevalence and incidence rates were calculated for each community from 1991 to 2002 and the development of an economic change indicator defined using Census data and industry/government documents allowed for yearly assessment of community-level exposure to economic conditions. The relationship between exposure to economic change and rates of acute and chronic cardiovascular disease and mental disorders across the 29 study communities was investigated using a generalized linear model (stratified by type of community, and adjusted for the effect of the community). Findings indicate an impact on the prevalence rates for acute cardiovascular disease (CVD) during periods of economic decline (rate increased by 13.1 cases per 1,000 population, p < 0.0001 as compared with stable periods) and bust conditions (rate increased by 30.1 cases per 1,000 population, p < 0.0001 as compared with stable conditions) and mental disorders (rate increased by 13.2 cases per 1,000 population, p = 0.0001) in mining communities during declining economic conditions as compared to steady periods of mining employment. This is not observed in other resource-based communities. The paper concludes by highlighting implications for the mining industry to consider as they begin to recognize and commit to mining community health.
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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 | 0.001 | 0.000 |
| 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".