Depressive Symptom Severity Mediates the association between Sleep Disturbance and Obesity in US Adults: Results from the NHANES
Bibliographic record
Abstract
BACKGROUND: The clustering of sleep alterations, cardiometabolic risk, and depressive symptoms suggests a convergence in their pathophysiology. We quantify the role of depressive symptoms in mediating the association between empirically derived sleep indices and body mass index (BMI). METHODS: Data were derived from 8,844 adult participants of the 2005 to 2008 US National Health and Nutrition Examination Survey. Factor analysis of the Sleep Disorders Questionnaire was conducted. Ordinary least squares path analysis quantified the effects of sleep indices on BMI directly and indirectly via depressive symptom severity (ie, Patient Health Questionnaire). RESULTS: Three sleep indices were extracted: poor sleep-related functional impairment, sleep disturbance, and daytime sleepiness. The associations between functional impairment, sleep disturbance, and daytime sleepiness and BMI were mediated by the effects of sleep on depressive symptoms (κ2 = 0.02) after adjustment for covariates. Daytime sleepiness was associated with BMI independent of depressive symptoms, whereas poor sleep-related functional impairment and sleep disturbance were not. CONCLUSIONS: Higher subjective ratings of sleep-related functional impairment, sleep disturbance, or daytime sleepiness indirectly increased BMI by worsening overall depressive symptom severity. A testable hypothesis is whether preemptive targeting of depressive symptoms in populations with sleep disturbances may decrease risk for obesity and other concurrent metabolic comorbidities.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".