Relationship between BMI and emotion-handling capacity in an adult Finnish population: The Northern Finland Birth Cohort 1966
Bibliographic record
Abstract
BACKGROUND: Alexithymia, a difficulty in identifying and expressing emotions, has been associated with obesity and eating disorders in small-scale cross-sectional studies. Here, we assess the relationship between body mass index (BMI) and alexithymia in a large cohort of free-living Finnish adults over a 15-year period. METHODS: Participants were drawn from the Northern Finnish Birth Cohort 1966 (NFBC1966). The 20-Item Toronto Alexithymia Scale (TAS-20) was used as a measure of alexithymia and was completed at the age of 31 years (31y: n = 4841), and 46 years (46y: n = 5404). BMI was recorded at both time points. Where data at both time points were available (n = 3274), the relationship between changes in BMI and TAS-20 over this time period was also investigated. RESULTS: BMI was significantly and positively associated with TAS-20 score (p<0.0001, both at 31 years and at 46 years of ages). The association remained statistically significant after adjustment for potential confounders (sex, marital status and several socio-economic indicators). In individuals who experienced the greatest change in BMI (in either direction) over the 15-year period, there was a modest mean increase in TAS-20 score. CONCLUSIONS: Our data revealed that TAS-20 score was correlated with and co-varied with body mass status. We suggest that future clinical research should consider the role of alexithymia in obesity. Further investigation of this relationship is warranted to ensure that the needs of obese subjects with undiagnosed alexithymia are considered in the design of weight management programmes.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".