ArticleNan fang yi ke da xue xue bao = Journal of Southern Medical University2026
[Key determinants of global burden of non-alcoholic fatty liver disease: machine learning combined with Mendelian randomization analysis based on GBD data].
Article in Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesTo analyze the global trends, drivers, and health inequalities of non-alcoholic fatty liver disease (NAFLD) burden to identify key predictors of NAFLD-related mortality.
methodsUsing data from the Global Burden of Disease (GBD) Study 2021, we extracted global measures of NAFLD from 1990 to 2021, and the trends were analyzed using joinpoint regression. Decomposition analysis was used to quantify the contributions of population growth, aging, and epidemiological changes. The health inequality was assessed using the concentration index. Using XGBoost-SHAP machine learning, the mortality predictors were identified, and two-sample Mendelian randomization was employed to test the causality for the key factors. All the analyses were conducted with data stratification by sex and the socio-demographic index (SDI).
resultsThe global age-standardized disability-adjusted life years (DALYs) rate showed an increasing trend in both males (average annual percentage change [AAPC]=+0.34%) and females (AAPC=+0.05%). Decomposition analysis revealed that population growth was the primary driver of the global increase in DALYs, while population aging contributed to 52.37% of male deaths in high-SDI regions. Health inequality analysis showed a concentration index of -0.05 for DALYs in 2021, indicating a concentration of burden among low-SDI populations. Machine learning identified smoking (relative importance=100%) and advanced age (70-74 years: 60%) as the most critical predictors of mortality, and the model demonstrated good fit on the test set (
conclusionsNAFLD burden is heavy globally with significant sex and socioeconomic inequalities. Smoking and advanced age are key risk factors for NAFLD, calling for integrated interventions for tobacco control, geriatric health management, and health equity promotion.
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