SOCIOECONOMIC POSITION, GENDER AND HYPERTENSION IN A RURAL CANADIAN POPULATION
Bibliographic record
Abstract
Background: High blood pressure is the leading risk factor for disease burden worldwide, contributing to more than 9 million deaths each year. Some research suggests that the prevalence of hypertension increases as individual/household socioeconomic position (SEP) decreases. The results of multilevel studies also suggest an association between poorer neighborhood socioeconomic circumstances and hypertension. Further, at both the individual/household- and area-level, high blood pressure may be more strongly related to SEP among women than men. Most research, however, has been restricted to urban populations. There has not been much research which examines risk factors for hypertension in rural Canada and, in particular, socioeconomic risk factors. Objectives: To examine the relationship between individual/household- and area- level socioeconomic circumstances, gender, and high blood pressure in a rural Saskatchewan population. Methods: There were two data sources for this study. Individual/household-level data were from the Saskatchewan Rural Health Study (SRHS). Analyses focused on adults (n=8,261) who completed the cross-sectional baseline questionnaire. Census subdivisions were used to link SRHS data with area-level data from the 2006 Canadian census. The dependent variable was self-reported diagnosed high blood pressure. The primary independent variables were gender and four measures of socioeconomic circumstances: household income, educational attainment, arealevel material deprivation, and area-level social deprivation. Principal components analysis was used to derive the area-level measures of deprivation. Multilevel logistic regression was the primary method of analysis. Results: Four main findings emerged: 1) low educational attainment was associated with a greater odds of high blood pressure; 2) the relationship between low household income and high blood pressure was more pronounced among women than men; 3) the relationship between higher area-level social deprivation and high blood pressure was more pronounced among men than women; and 4) area-level material deprivation was not associated with high blood pressure. iii Conclusion: Study results revealed complex relationships between SEP, gender, and high blood pressure in this rural Saskatchewan population. Future research applying a longitudinal design is needed to advance understanding of the relationship between SEP and incident hypertension in rural Canada, including the identification of vulnerable subgroups. Also needed is research examining the factors which explain (i.e. mediate) associations between SEP and hypertension in rural settings, particularly at the area-level.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".