LONELINESS IS INVERSELY ASSOCIATED WITH EXERCISE AND SLEEP APNEA IN OLDER WOMEN AT RISK FOR ALZHEIMER’S DISEASE
Bibliographic record
Abstract
Abstract Background Modifiable risk factors (MRF) for Alzheimer’s disease (AD) include sedentary behavior, sleep apnea, and loneliness; however, how these MRFs influence one another is unclear. We examined correlations among loneliness, physical activity and sleep apnea among older women at higher risk for AD. Methods Data were collected as part of the Women: Inflammation and Tau Study, which recruits women age 65–85 with higher AD genetic risk and mild impairment on the Montreal Cognitive Assessment. Participants completed the UCLA Loneliness Scale and home sleep tests to derive the Apnea Hypopnea Index (AHI), a measure of sleep apnea severity. Women wore ActiGraph accelerometers for one week to measure average Moderate-Vigorous Activity per day (MVPA). We used Spearman correlation to examine the relationships among AHI, MVPA and Loneliness Scale score. Results Preliminary data were available for 12 women (mean age=72.4 [SD=2.8], 100% non-Hispanic White). MVPA ranged from 0.3–52.8 minutes (mean=9.38 [SD=14.1]; AHI ranged from 1.5–28.3 (mean=14.0 [SD=9.0] and Loneliness Scale score ranged from 0–34 (mean=9.8 [SD=x]). Significant, positive associations were observed between AHI and Loneliness (rho=.80, p=.006) and a moderate relationship at trend level was notable between higher MVPA and less Loneliness (rho=-9.53, p=.07). AHI did not relate to MVPA. Conclusion Results suggest that loneliness independently relate to both sleep apnea severity and sedentary behavior in older women. Combined interventions that target loneliness in addition to physical activity and sleep may be important in women at-risk for AD.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".