The Burden of Steatotic Liver Disease in Canada: Sex Differences in Prevalence and Cardiometabolic Profiles
Bibliographic record
Abstract
Background: Steatotic Liver Disease (SLD) is largely absent from public health agendas. We conducted Canada's first SLD prevalence study, focusing on sex disparities. Methods: We used 2012-2018 data from the comprehensive arm of the Canadian Longitudinal Study on Aging (n=30,097), a cohort that prospectively follows adults between 45 and 85 years old from 11 sites across Canada. Data on sociodemographic, lifestyle, and clinical factors are collected every 3 years. Steatosis was identified with the serum biomarker-based NAFLD Ridge Score (NRS) that uses ALT, HDL cholesterol, triglycerides, hemoglobin A1c, leukocyte count, and hypertension. An NRS dual cut-off <0.24 (rule-out steatosis) and >0.44 (rule-in steatosis) has a sensitivity of 92% and specificity of 90%. We estimated the prevalence of metabolic (dysfunction)-associated steatotic liver disease (MASLD), metabolic (dysfunction)-associated alcohol-associated liver disease (MetALD) and alcohol-associated liver disease (ALD). Poisson regression with robust standard errors and sampling weights were used to estimate adjusted prevalence ratios (aPR) with (95% CI). We also explored the association between total household income and incident cases of MASLD. Sensitivity analyses evaluated the extent of measurement error and missing data. Results: Our observational cohort included 24,888 people (51.4% female, median age 58 years (IQR: 51-67)). The most common subtype of SLD was MASLD, 35% (34-36%), followed by MetALD 2.6% (2.3-2.9%), and ALD 0.8% (0.6-1.0%). Prevalence of males with MASLD was 46% (45-48%) compared to 24% (23-26%) females with MASLD and males with MetALD 3.7% (3.2-4.2%) compared to females 1.6% (1.2-2.1%). After stratifying by sex and adjusting for age and lifestyle factors, differences in prevalence by income were more pronounced in females than in males. Lower household incomes were associated with higher MASLD prevalence in females (aPR: 2.9, 2.4-3.5) and males (aPR: 1.13, 1.01-1.28). We also found significant sex disparities in disease management: 38% (95%CI: 35-42%) of females had low HDL cholesterol but were not on lipid-lowering therapy, compared to 29% of males (95%CI: 26-32%). Discussion: In this large Canadian cohort, we found significant sex disparities in MASLD prevalence, cardiometabolic risk factors, and management. Epidemiological assessments are crucial in improving national preparedness for the projected increase in advanced liver disease.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".