Abstract P149: Ideal Cardiovascular Health is Associated With the Characteristics of and Better Access to Primary Care in a Publicly Funded Healthcare System
Bibliographic record
Abstract
Background: Cardiovascular health (CVH) and CVD prevention remains a top public health priority across North America. The health of Canadians is largely accredited to the publicly funded healthcare system, which affords “free” healthcare to all its citizens. However, there is little evidence demonstrating whether the characteristics of and access to primary care by Canadians directly impacts their likelihood of ideal CVH. Objective: To examine the association between ideal CVH and the characteristics of and access to primary care in Canadians. Data and Methods: This study is a cross-sectional design using adult data from the Canadian Community Health Survey (CCHS) 2015-2016 database. The CCHS is a nationwide, nationally representative survey that collects information on the health status, health care access and utilization, and health determinants of the Canadian population. CVH, defined using the AHA CVH Index (CVHI), was determined using self-reported responses in CCHS. Weighted logistic regression was performed to examine the association between ideal CVH and the characteristics of and access to primary care, including having regular care, receiving coordinated care, ER use and access to routine care. Models were also adjusted for individual characteristics known to affect CVH. Results: The majority of the population were females (51%), aged 40-60 (37%), with tertiary education (64%) and of the White race (79%). Overall, 19% of the population had ideal CVH (ideal status in 6-7 CVHI factors), representing approximately 6 million individuals nationwide. Individuals reported having a regular primary healthcare provider (82%), insurance for prescription medication (76%), high coordination in their healthcare between health professionals (10%), difficulties in accessing routine care in the past 12 months (3%). The likelihood of ideal CVH were highest in those who reported having: a regular provider (OR 1.11, 95% CI 1.05-1.17), higher coordination of care (OR 1.10, 95% CI 1.01-1.20) and using the ER less frequently (OR 0.90, 95% CI 0.80-0.95). After controlling for age, sex and race, only having a regular provider (OR 1.11, 95% CI 1.02-1.20) and not reporting difficulties in accessing routine care in the past 12 months (OR 1.02, 95% CI 1.01-1.04) were significantly associated with ideal CVH. Conclusion: Findings from this study suggest that individuals experiencing better primary healthcare, including having a regular primary care physician or having less difficulty accessing care, are more likely to have ideal CVH than those experiencing poor primary healthcare. Further studies should investigate policies that promote better primary healthcare as interventions for preventing CVD and improving CVH.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".