The Association Between Hair Cortisol, Hair Cortisone, and Cognitive Function in a Population-Based Cohort of Older Adults: Results From The Irish Longitudinal Study on Ageing
Bibliographic record
Abstract
Experimental evidence to date largely supports an association between the stress hormone cortisol and cognitive performance. Older adults, in particular, may be vulnerable to the neurotoxic effects of prolonged increases in cortisol; however, the assessment of chronic hormone levels has previously been challenging. Hair cortisol analysis has advantages over other cortisol metrics for this purpose as it facilitates the assessment of total hormone secretion over several months. Cortisol and cortisone were measured in the scalp hair of 1,876 older adults from The Irish Longitudinal Study on Ageing. Participants underwent a battery of cognitive tests assessing global function, memory, executive function, and processing speed. After adjustment for hair characteristics, demographics, metabolic risk factors, cardiovascular conditions, and depression, regression analysis revealed an inverse relationship of hair glucocorticoids to immediate (cortisol: β = -.12, p = .032; cortisone: β = -.021, p = .036) and delayed (cortisol: β = -.13, p = .003; cortisone: β = -.23, p = .006) word recall performance. They were also associated with more errors on the Mini-Mental State Examination (cortisol: incidence rate ratio (IRR) = 1.06, p = .008; cortisone: IRR = 1.14, p = .002) and Montreal Cognitive Assessment (cortisone: IRR = 1.06, p = .015). Higher hair glucocorticoids are inversely associated with memory and global cognition in a population-based sample of older adults. Future work should explore the prognostic significance of these findings.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".