Men’s Health in Northern British Columbia: Analysis and Reporting of Early Intervention Screening Program Data Related to Cardiovascular Health
Bibliographic record
Abstract
Type 2 diabetes (T2D) is a well-established risk factor for cardiovascular disease (CVD). Higher rates of T2D are attributable to unhealthy lifestyle factors and a number of clinical and metabolic risk factors. There is paucity of research which investigated the association of lifestyle risk factors and metabolic markers amongst adult men in northern British Columbia (BC). Using a face-to-face screening questionnaire, we assessed the relationships between age, body mass index (BMI), and a number of CVD risk factors in a convenience sample of 123 eligible men recruited from communities across northern BC in February of 2011. In regards to the metabolic risk factors measured through screening blood tests (lipid profiles; blood glucose) responses to the questionnaire were dichotomized into high and low risk categories. These dichotomized variables were subsequently used to determine if significant associations existed with each of the age category variable and a standard BMI categorical variable. There were significant linear relationships between the categorical BMI variable and a number of metabolic risk factors, as well as smoking history. Older age (40+ years) was associated with higher BMI status (overweight/obese). Our findings provide compelling evidence that northern BC men possess a number of clinical, metabolic, and lifestyle risk factors associated with high CV risk. Future studies should examine other sociodemographic variables including occupation status, education attainment, and ethnicity, and other psychosocial determinants which include knowledge, attitudes, and perceptions (KAP) related to T2D and CV risk profile in adult men working and living in northern BC, Canada.
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 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".