Sociodemographic differences in young adult actigraphic sleep among a diverse, national sample: the Future of Families Young Adult Sleep Study
Bibliographic record
Abstract
Abstract Study Objectives Sleep health is essential for wellbeing, yet few studies examine sociodemographic differences among young adults using objective sleep measures. We examined sociodemographic differences in actigraphic sleep health among a national, diverse sample of several hundred young adults. Methods Data from the Young Adult Sleep Sub-Study were collected during year 22 (mean age = 22.1 ± 0.3 years; range 21.6–24.4) of the Future of Families and Child Wellbeing Study (n = 442), a national, diverse sample of US-based young adults. Participants wore wrist-actigraphs for ~2 weeks. Multivariable linear regression models assessed whether sex, race, Hispanic/Latino ethnicity, education level, and employment status (simultaneously adjusted) were associated with dimensions of actigraphic sleep health. Results In adjusted models, women had longer total sleep time (TST), earlier sleep onset, and less weekend night catchup sleep than men. Black young adults had shorter TST, later sleep onset, more variability in nighttime TST, in sleep onset, and in sleep maintenance efficiency, and lower sleep regularity index (SRI) than White young adults. Young adults with a lower education level had greater variability in nighttime TST and in sleep timing and lower SRI than those with a higher education level. Young adults who were unemployed had later sleep timing, lower SRI, and less weekend night catchup sleep than those employed full-time. Conclusions Male sex, Black race, lower education level, and unemployment are associated with poorer actigraphic sleep health among this sample of young adults. Strategies to improve young adult sleep health should specifically prioritize men, marginalized populations, and those of lower socioeconomic status. Statement of Significance The present study examined sociodemographic differences in several dimensions of actigraphic sleep health, including total sleep time, sleep timing, sleep quality, and variability of these measures, among a large, national, diverse sample of young adults. Our findings indicate considerable disparities in young adult sleep health particularly affecting men, Black young adults, those with lower education levels, and those who are unemployed. Efforts should be made to address potential sources of these sleep disparities to improve young adult sleep health across the population.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".