Associations between sleep, energy balance, and obesity markers over 6 months in Black emerging adults—pilot study findings from the Sleep, Health Outcomes, and Body Weight (SHOW) study
Bibliographic record
Abstract
Insufficient sleep (short sleep duration and poor sleep quality) is associated with obesity risk. Emerging adults (ages 18–28 years) have a greater risk of excess weight gain and insufficient sleep, and these risks are higher in Black individuals. Using a measurement burst design, we assessed associations between sleep with energy balance components and obesity marker changes over 6 months in 15 Black emerging adults (12 females; age: 21 ± 2.5 years; body mass index: 25.7 ± 4.5 kg/m2; body fat: 25.8 ± 11.9%). Since our sample was predominantly female (80%), we repeated our analyses for females only. Participants completed the following measurements at baseline (BLN) and 6 months later (6MO): 7 days of actigraphy-based sleep and physical activity energy expenditure (EE) and 2 nights of in-home polysomnography-based sleep; resting EE and thermic effect of food with indirect calorimetry; ad libitum energy intake (EI) via self-reported methods over 4 days and directly measured over 3 days with provided meals. Body weight (2.6 kg, p = 0.01) and waist circumference (2.4 cm, p = 0.03) increased from BLN to 6MO. Changes in actigraphy-based sleep duration were associated with changes in body weight (β = 0.03, standard error (SE) = 0.02, p = 0.04) and fat mass (β = 0.07, SE = 0.03 p = 0.03) in females only. Greater rapid eye movement sleep duration was associated with increases in resting EE (β = 2.24, SE = 0.84, p = 0.02). Greater slow-wave sleep was associated with increases in self-reported EI (β = 18.34, SE = 4.7, p < 0.01). Sleep may impact components of energy balance and risk of weight gain in Black emerging adults. Additional research is needed to confirm our pilot findings.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".