Is Sex Good for Your Brain? A National Longitudinal Study on Sexuality and Cognitive Function among Older Adults in the United States
Bibliographic record
Abstract
Using a life course approach, we examined how sexuality is related to cognitive function for partnered older adults. We utilized longitudinal data from two rounds of the National Social Life, Health, and Aging Project (NSHAP) to analyze 1,683 respondents. Cognitive function was measured using a continuous Montreal Cognitive Assessment (MoCA) score. We considered both sexual frequency and sexual quality (i.e., physical pleasure, emotional satisfaction). We estimated cross-lagged models to consider the potential reciprocal relationship between sexuality and cognitive function. Results indicated that sexuality was not related to later cognitive function in the total sample, but the pattern varied by age and gender. For adults aged 62-74, better sexual quality (i.e., feelings of physical pleasure and emotional satisfaction) was related to better cognitive functioning, while for those aged 75-90, more frequent sex was related to better cognitive functioning. Feelings of physical pleasure were related to better cognitive functioning for men but not women. There was no evidence of cognitive functioning being related to later sexuality. The findings highlight the importance of age and gender in modifying the link between sexuality and cognition in later life.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".