Does Executive Function Explain the IQ-Mortality Association? Evidence from the Canadian Study on Health and Aging
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To assess the robustness of the association between intelligence quotient (IQ) and mortality in older adults and to examine whether or not the association can be explained by more specific cognitive processes, including individual differences in executive functioning. METHODS: We examined the associations among Full Scale IQ, individual IQ subtest scores, and 10-year mortality among older community-dwelling, adult participants in the Canadian Study of Health and Aging, who were verified as disease and cognitive-impairment free at baseline via comprehensive medical and neurological evaluation (n = 516). Survival analysis including Cox proportional hazards regression models were used to examine mortality risk as a function of Full Scale IQ and its specific subcomponents. RESULTS: An inverse association was found between IQ and mortality, but this did not survive adjustment for demographics and education. The association between IQ and mortality seemed to be predominantly accounted for by performance on one specific IQ subtest that taps executive processes (i.e., Digit Symbol (DS)). Performance on this subtest uniquely and robustly predicted mortality in both unadjusted and adjusted models, such that a 1-standard deviation difference in performance was associated with a 28% change in risk of mortality over the 10-year follow-up interval in adjusted models. CONCLUSIONS: The association between IQ and mortality in older adults may be predominantly attributable to individual differences in DS performance.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 it