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IARC 60th Anniversary - 19-21 May 2026

Session : Rapid Fire

Steatotic Liver Diseases, Socioeconomic Position and Risk of Type 2 Diabetes: A Syndemic Analysis within the EPIC InterAct Cohort

DESTA A. 1,2,3, ATTANASIO M. 2, FREISLING H. 3, VIALLON V. 3, FERRARI P. 3, RICCERI F. 4, JENAB M. 3

1 Department of Statistics, Computer Science, Applications (DiSIA), University of Florence, Florence, Italy; 2 Dipartimento di Scienze Economiche, Aziendali e Statistiche (SEAS), University of Palermo, Palermo, Italy; 3 IARC, Lyon [Rhône], France; 4 Department of Clinical and Biological Sciences, University of Turin, Torino, Italy

Background: Steatotic liver diseases (SLD) have hepatic and extra-hepatic consequences. SLD includes three major chronic liver diseases: Metabolic dysfunction–associated SLD (MASLD), Metabolic dysfunction–associated alcohol-related liver disease (MetALD), and Alcohol-related liver disease (ALD). An association between SLD with risk of T2D, a major cancer risk factor, has been shown in some studies, but there is a paucity of data from large, prospective cohort studies. Moreover, potential syndemic interactions with socioeconomic position (SEP) have not been well studied.
Aims: This study investigated associations between SLD, SEP, and T2D risk using a syndemic approach, a method examining co-occurring health conditions that interact synergistically and are driven by shared social, structural, or environmental factors, producing outcomes greater than their individual effects.
Methods: We used data from the EPIC-InterAct prospective case-cohort study on 8,985 incident T2D cases and 12,372 healthy participants. SLD were identified based on the Fatty Liver Index (FLI), cardiometabolic factors, and questionnaire-assessed alcohol consumption levels. SEP was measured using the Relative Index of Inequality (RII) derived from educational attainment. We implemented prentice weighted multivariable Cox proportional hazard models stratified by centre. Four separate models were developed to assess associations between T2D incidence and (a) SLD sub-types, (b) MASLD+SEP, (c) MetALD+ SEP, and (d) ALD+SEP.
Results: After adjustment for covariates and stratification factor, MASLD (HR=3.35, 95%CI:3.19–3.51), MetALD (HR=2.93, 95%CI:2.72–3.16), and ALD (HR=2.77, 95%CI:2.50–3.07) were strongly associated with T2D compared to no SLD. The SLD-T2D risk association was always positive at any age, however, the strength of the association declined steadily from ages 40 to 80. Age?specific HRs decreased from 6.21 (95%CI:5.31–7.26) at 40 years to 2.28 (95%CI:2.05–2.53) at 80 years for MASLD, from 4.75 (95%CI:3.67–6.14) to 2.17 (95%CI:1.81–2.60) for MetALD, and from 4.10 (95%CI:2.80–6.01) to 2.17 (95% CI:1.65–2.86) for ALD. Females with SLD had a higher risk of T2D than males (MASLD: HR=3.59, 95%CI=3.38–3.82) vs 2.80 (2.60–3.01); MetALD: 3.32 (2.87–3.83) vs 2.52 (2.30–2.77); ALD: 2.86 (1.97–4.16) vs 2.51 (2.22–2.82)). Low SEP amplified the association between SLDs and T2D, attenuating with age. For low SEP + MASLD, HR decreased from 12.20 (95% CI:8.71–15.69) at 40 years to 2.78 (95% CI:2.24–3.32) at 80 years; for low SEP + MetALD, from 9.10 (95% CI:5.14–13.06) to 2.37 (95% CI: 2.14–2.56); and for low SEP + ALD, from 7.67 (95% CI:4.34–13.56) to 1.92 (95% CI:1.22–3.04).
Conclusions: SLD are associated with higher T2D risk in a gradient with MASLD >MetALD >ALD. T2D risk is much higher among younger adults with any SLD. Lower SEP consistently amplifies T2D risk compared to medium or higher SEP levels, except in ALD. Incorporating SLD, age, and SEP into risk stratification criteria may enable earlier identification of high-risk individuals for T2D and guide tailored interventions. Such an approach could ameliorate the effectiveness of T2D and cancer prevention strategies and address health inequities linked to SLD and SEP. Further study and validation in different populations is required.