Association of dietary macronutrient composition and non-alcoholic fatty liver disease in an ageing population: the Rotterdam Study
Bibliographic record
Abstract
Objective A healthy lifestyle is the first-line treatment in non-alcoholic fatty liver disease (NAFLD), but specific dietary recommendations are lacking. Therefore, we aimed to determine whether dietary macronutrient composition is associated with NAFLD. Design Participants from the Rotterdam Study were assessed on (1) average intake of macronutrients (protein, carbohydrate, fat, fibre) using a Food Frequency Questionnaire and (2) NAFLD presence using ultrasonography, in absence of excessive alcohol, steatogenic drugs and viral hepatitis. Macronutrients were analysed using the nutrient density method and ranked (Q1–Q4). Logistic regression analyses were adjusted for sociodemographic, lifestyle and metabolic covariates. Moreover, analyses were adjusted for and stratified by body mass index (BMI) (25 kg/m 2 ). Also, substitution models were built. Results In total, 3882 participants were included (age 70±9, 58% female). NAFLD was present in 1337 (34%) participants of whom 132 were lean and 1205 overweight. Total protein was associated with overweight NAFLD after adjustment for sociodemographic and lifestyle covariates (OR Q4vsQ1 1.40; 95% CI 1.11 to 1.77). This association was driven by animal protein (OR Q4vsQ1 1.54; 95% CI 1.20 to 1.98). After adjustment for metabolic covariates, only animal protein remained associated with overweight NAFLD (OR Q4vsQ1 1.36; 95% CI 1.05 to 1.77). Monosaccharides and disaccharides were associated with lower overall NAFLD prevalence (OR Q4vsQ1 0.66; 95% CI 0.52 to 0.83) but this effect diminished after adjustment for metabolic covariates and BMI. No consistent associations were observed for fat subtypes or fibre. There were no substitution effects. Conclusion This large population-based study shows that high animal protein intake is associated with NAFLD in overweight, predominantly aged Caucasians, independently of well-known risk factors. Contrary to previous literature, our results do not support a harmful association of monosaccharides and disaccharides with NAFLD.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| 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".