The Influence of Resource-reliance and Community-level Social Environmental Factors on Self-reported Health Measures: A Hierarchical Analysis Using the Canadian Community Health Survey
Bibliographic record
Abstract
P-384 Abstract: Resource-reliant communities, those that are economically centred on primary resources (fishing, forestry, agriculture, and mining), have played an important role in the economic formation and settlement of Canada. Current realities of increased global competition, environmental contamination and dwindling resources are challenging the sustained existence of these communities. Evidence from the social science literature indicates that these resource communities experience higher unemployment, poverty, and social instability; this evidence suggests that these socio-economic conditions are having a negative impact on the health status of the communities. The goal of this study was to explore the associations between individual health status variables (including self-reported health, self-reported mental health and self-reported work stress) and community-level socio-economic characteristics (education levels, employment rate, urban/rural, average income and % resource reliance (work sector in resource industries)). The individual-level variables were obtained from the Canadian Community Health Survey Master Data file (Cycle 2.1 2003 n∼135′000), and were linked by the census-subdivision geography to community-level socioeconomic variables from the 2001 Canadian Census. Non-linear hierarchical modelling (Bernoulli method) was used to explore the effect of the community characteristics on individual-level health status through regression analysis, while accounting for the nested-data structure. HLM 6 (Scientific Software International, 2004) software, which permitted the use of level-1 design weights, was used for the analysis. We found that high self-reported health status was significantly associated with community-level education (OR=3.14), % of resource reliance (OR=0.79) and urban/rural (OR= 0.90), controlling for age and gender at the individual level. With the inclusion of individual-level education status and income, the effects of the community-level variables on self-reported health were reduced, but community-level education, in particular, remained significant (OR=3.75). Results for self-reported mental health followed a similar pattern of a reduced impact of community-level variables with the inclusion of individual-level education and income. Living in communities that were not resource-reliant increased the likelihood of high self-reported health status, after controlling for individual level variables, as well as community-level education. Self-reported mental health and self-reported work stress revealed the opposite association, showing living in a resource-community as protective. These results should prompt further exploration of resource-reliance as a contributing community characteristic to individual-level health status. Policy implications of this research extend beyond health services and suggest economic policy and development should be considered in terms of their impact on health. Resource-reliant communities remain largely under-explored and warrant further investigation.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".