Race and sex differences in the longitudinal changes in multidimensional self-reported sleep health characteristics in aging older adults
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
OBJECTIVES: We examined within-individual changes in self-reported sleep health as community-dwelling older adults age as well as potential differences in these changes by self-reported sex and racial identity. METHODS: Participants were from the United States and enrolled in the Rush Memory and Aging Project, Minority Aging Research Study, or Religious Orders Study (N = 3539, 20% Black, 75% female, mean 78years [range 65-103]), and they received annual, in-person clinical evaluations (median 5 visits [range 1-27]). A sleep health composite score measured the number of poor sleep characteristics among satisfaction, daytime sleepiness, efficiency, and duration. Mixed effects models estimated associations of age, race, sex, and their interactions on the composite and individual sleep measures, accounting for key confounders. RESULTS: As they aged, Black participants shifted from reporting two poor sleep characteristics to one poor sleep characteristic, while White participants shifted from one poor characteristic to two. Regardless of age, sex, and race, participants reported that they "often" felt satisfied with their sleep and "sometimes" had trouble staying asleep. Females over age 85 and males of all ages reported the most daytime sleepiness, and older White participants (>age 90) reported the most difficulty falling asleep. CONCLUSIONS: Although self-reported sleep characteristics were typically stable across age, identifying race and sex differences in self-reported sleep health can help guide future research to understand the mechanisms that underlie these differences.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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