Associations between salivary testosterone levels and cognitive function among 70‐year‐old Japanese elderly: A cross‐sectional analysis of the <scp>SONIC</scp> study
Bibliographic record
Abstract
AIM: This cross-sectional study aimed to investigate the associations between salivary testosterone concentrations and cognitive function in 70-year-old Japanese elderly people without dementia and stroke. METHODS: Participants were 197 Japanese community-dwelling people aged 69-71 years. Their salivary samples were collected, and their cognitive function was assessed using the Japanese version of the Montreal Cognitive Assessment (MoCA-J). Participants were also administered a 10-item recall and a 24-item recognition test. The data for 179 (106 men and 73 women) individuals were analyzed, excluding individuals with a past history of stroke and dementia. Multivariate logistic regression analyses were performed after adjusting for lifestyle factors and analyzing data separately for men and women. RESULTS: MoCA-J scores showed that men with low testosterone concentrations had a significantly greater risk of low cognitive performance than those with high testosterone concentrations (adjusted odds ratio: 4.72, 95% confidence interval: 1.06-21.00), while no significant association was found in women. The 10-item recall test scores showed that higher testosterone concentrations were significantly associated with greater recall in the second trial in women (standardized beta = 0.24, P = 0.040), whereas no significant association was found in men. Salivary testosterone concentrations were positively associated with better cognitive performance in older men and women. CONCLUSIONS: The associations between salivary testosterone concentrations and cognitive function were shown by different tasks for men and women. Geriatr Gerontol Int 2022; 22: 1040-1046.
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.
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) | 0.001 | 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".