Ideal cardiovascular health in adolescents and young adults is associated with alexithymia over two decades later: Findings from the cardiovascular risk in Young Finns Study Department: Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
Bibliographic record
Abstract
Abstract We evaluated the association of cardiovascular health in adolescence and young adulthood with alexithymia 25 years later. The study sample (n = 1122) participated in evaluations conducted in 1986 (baseline) and in 2011−2012 (T2). Baseline health factors and behaviors were assessed utilizing seven ideal cardiovascular health metrics (ICH index) including blood pressure, cholesterol and glucose levels, smoking, physical activity, body-mass-index, and diet. The stability of the ICH index was evaluated with corresponding assessments in 2007 (T1). At T2, alexithymia was measured with the 20-item Toronto Alexithymia Scale (TAS-20). The main analyses were conducted using ANCOVA and adjusted for depression, age, and present social and lifestyle factors. TAS-20 subscales, Difficulty Identifying Feelings (DIF), Difficulty Describing Feelings (DDF), and Externally Oriented Thinking, were analyzed separately. The ICH index was significantly associated with the TAS-20 total score, as well as both with DIF and DDF. A less ideal cardiovascular health was associated with higher alexithymia scores. However, regarding the separate factors, only the association between non-ideal dietary habits and DIF was significant in the multivariate analyses. The baseline ICH index score was stable from baseline to T1. We conclude that non-ideal cardiovascular lifestyle habits in adolescence and young adulthood are significantly associated with later alexithymia.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".