Shorter sleep duration is associated with greater visceral fat mass in US adults: Findings from NHANES, 2011–2014
Bibliographic record
Abstract
Habitual declines in sleep duration and increased rates of obesity are public health concerns worldwide. Accumulating evidence suggests a prominent link between reduced sleep duration and weight gain. Our cross-sectional study investigated the relationship between sleep duration and body fat distribution in US adults. We extracted data for 5151 participants (2575 men and 2576 women) aged 18-59 years from the US National Health and Nutrition Examination Survey 2011-2012 and 2013-2014. Weekday or workday night-time sleep duration was estimated using an in-home interview questionnaire. Dual-energy x-ray absorptiometry scans were used to determine regional body fat mass (arms, legs, trunk [android and gynoid], and abdominal [subcutaneous and visceral]). Multiple linear regression and restricted cubic spline analyses were performed after adjusting for several demographic, anthropometric, and nutritional covariates. There was a significant negative association between sleep duration and visceral fat mass overall (β: -12.139, P < 0.001) and by sex (men: β: -10.096, P < 0.001; women: β: -11.545, P = 0.038), after adjusting for age, ethnicity, body mass index, total body fat mass, daily energy and alcohol intake, sleep quality and sleep disorder status. Sleep duration and visceral fat appeared to plateau at ≥ 8 h of daily sleep. Sleep duration is negatively associated with visceral fat mass accumulation during adulthood with possibly no benefits beyond 8 h of sleep per day. Mechanistic and prospective studies are required to confirm the effect of sleep duration on visceral adiposity and determine its causes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".