Abstract 16147: Sex, Gender Factors and Cardiovascular Health in Canadian and Austrian Populations
Bibliographic record
Abstract
Introduction: Little evidence exists differentiating the effect of biological sex from gender-related (i.e. psycho-socio-cultural) characteristics in cardiovascular outcomes. Hypothesis: Here, we explored the association between sex, gender, and cardiovascular health (CVH) among Canadians (CAN) and Austrians (AT). Methods: Data from the Canadian Community Health Survey (CCHS) (n=63,522, 55% Females) and Austrian Health Interview Survey (AT-HIS) (n=15,771, 56% Females), were analyzed. The CANHEART index, a measure of ideal CVH composed of 6 cardiometabolic risk factors ranging from 0 (worst) to 6 (ideal), was calculated in the CCHS as well as AT-HIS databases (ATHEART). A country-specific gender score was computed using principal component analysis-derived propensity score methods. The final gender scores (Range=0-1, higher score identifying characteristics traditionally ascribed to women) included: i) household size, perceived life stress, education, sense of belonging to community, marital status, and income (CAN); ii) household size, frequency of negative emotions, education, marital status and income (AT). Results: Median CANHEART and CAN gender scores were 4 [3-5] and 0.53 [0.49-0.60] while median ATHEART and AT gender scores were 4 [3-5] and 0.55 [0.46-0.64]. Although higher gender scores (CCHS: β=-1.33, 95%CI (-1.44,-1.22); AT-HIS: β=-1.11, 95%CI (-1.30,-0.91)) were associated with worse CVH, female sex (CCHS: β=0.35, 95% CI (0.33,0.37); AT-HIS: β=0.59, 95%CI (0.55,0.64)) was associated with better CVH in both populations. Additionally, higher gender scores were associated with a higher risk of heart disease, compared to female sex. The magnitude of this risk was higher in AT population (Table1). Conclusions: Individuals with characteristics typically ascribed to women reported poorer CVH and exhibited higher risk of heart disease independent of biological sex. Gender factors must be targeted for improving cardiovascular health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".