Alexithymia Is Associated With Increased Cardiovascular Mortality in Middle-Aged Finnish Men
Bibliographic record
Abstract
Objective: To explore the associations between alexithymia and increased somatic morbidity. The mechanisms underlying these associations, however, are still unclear. Furthermore, data on the association between alexithymia and mortality are scarce. Methods: A total of 2321 Finnish men, aged 46 to 61 years, were followed up for an average of 20 years. Mortality rates were obtained from the national register. The associations between baseline alexithymia and cardiovascular disease (CVD), all-cause, injury, and cancer deaths were examined with adjustments for age and several behavioral (smoking, alcohol consumption, physical activity), physiological (low- and high-density lipoprotein cholesterol, body mass index, systolic blood pressure, history of CVD), and psychosocial (marital status, education, depression) factors. Results: After all adjustments, the risk of CVD death was increased by 1.2% for each 1-point increase in Toronto Alexithymia Scale-26 scores. Conclusions: Alexithymia is associated with increased cardiovascular mortality. BDI = Beck Depression Inventory; BMI = body mass index; CI = confidence interval; CVD = cardiovascular disease; HDL-C = high-density lipoprotein cholesterol; HPL Depression Scale = Human Population Laboratory Depression Scale; LDL-C = low-density lipoprotein cholesterol; RR = risk ratio; TAS = Toronto Alexithymia Scale.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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 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".