Socioeconomic Status and Risk of Chronic Respiratory Conditions in Rural Saskatchewan
Bibliographic record
Abstract
Chronic respiratory conditions (CRC) are a leading cause of morbidity and mortality globally. Research suggests that people of lower socioeconomic status (SES) are more likely to have CRC than those of higher status. However, the majority of these studies are cross-sectional in design, and in addition, have not considered the experience of rural dwellers, particularly in North America. Informed by a social determinants of health perspective, the primary purpose of this study was to: 1) determine the incidence of CRC in rural-dwelling adults in Saskatchewan; and 2) examine the association between SES and the incidence of CRC. The data source was the Saskatchewan Rural Health Study (SRHS), a prospective cohort study that consisted of a baseline survey in 2010 and a follow-up survey in 2014. The dependent variable was CRC, comprised of self-reported asthma and/or chronic obstructive pulmonary disease (COPD). The primary exposure of interest was SES, and assessed using measures of household income adequacy, educational attainment, and financial strain. Survival analysis was used to identify the risk factors of incidence of CRC, adjusting for various covariates. The cumulative incidence of CRC was 7.01%. Compared with high-income adequate participants, those with low and low- middle income adequacy had 2.22 times (95% CI: 1.01 – 4.89) and 1.66 times (95% CI: 1.08 – 2.56) higher risk of CRC, respectively. Financial strain and education were not related to the risk of CRC. Other statistically significant risk factors included the use of household natural gas, smoking status, parental history of lung disease, allergy, and diabetes. In conclusion, lower household income was associated with an increased risk of developing CRC over the four-year study period. I suggest that rural health policies should pay attention to the socioeconomic circumstances of rural people and not just access/distance to health services.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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 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".