A “healthy diet–optimal sleep” lifestyle pattern is inversely associated with liver stiffness and insulin resistance in patients with nonalcoholic fatty liver disease
Bibliographic record
Abstract
Several lifestyle habits have been described as risk factors for nonalcoholic fatty liver disease (NAFLD). Given that both healthy and unhealthy habits tend to cluster, the aim of this study was to identify lifestyle patterns and explore their potential associations with clinical characteristics of individuals with NAFLD. One hundred and thirty-six consecutive patients with ultrasound-proven NAFLD were included. Diet and physical activity level were assessed through appropriate questionnaires. Habitual night sleep hours and duration of midday naps were recorded. Optimal sleep duration was defined as sleep hours ≥ 7 and ≤ 9 h/day. Lifestyle patterns were identified using principal component analysis. Eight components were derived explaining 67% of total variation of lifestyle characteristics. Lifestyle pattern 3, namely high consumption of low-fat dairy products, vegetables, fish, and optimal sleep duration was negatively associated with insulin resistance (β = -1.66, P = 0.008) and liver stiffness (β = -1.62, P = 0.05) after controlling for age, sex, body mass index, energy intake, smoking habits, adiponectin, and tumor necrosis factor-α. Lifestyle pattern 1, namely high consumption of full-fat dairy products, refined cereals, potatoes, red meat, and high television viewing time was positively associated with insulin resistance (β = 1.66, P = 0.005), although this association was weakened after adjusting for adiponectin and tumor necrosis factor-α. A "healthy diet-optimal sleep" lifestyle pattern was beneficially associated with insulin resistance and liver stiffness in NAFLD patients independent of body weight status and energy intake.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".