Epidemiology of Lifestyle-Related Disorders

Abstract

Lifestyle-related disorders -- encompassing obesity, type 2 diabetes, cardiovascular disease driven by modifiable risk factors, alcohol-related liver disease, and smoking-attributable cancers -- collectively account for over 70% of premature deaths in Europe and consume 75-85% of healthcare expenditure, yet preventive interventions targeting the underlying behavioural determinants remain poorly integrated into health systems. The epidemiological landscape of these conditions is shifting: obesity prevalence has tripled since 1975, type 2 diabetes has doubled, and alcohol-related liver disease has emerged as the fastest-growing indication for liver transplantation. We analysed lifestyle-related disease burden, risk factor trends, and intervention effectiveness across 32 European countries using data from the Global Burden of Disease Study 2021, WHO European Health Information Gateway, Eurostat, and national health survey datasets from 2000 to 2022. We compared five epidemiological surveillance and intervention frameworks: traditional risk factor surveys, linked administrative data analyses, digital phenotyping through wearable devices, population-level policy evaluation using natural experiments, and ML-driven individual risk prediction from EHR data. Our Lifestyle Disease Surveillance Score (LDSS) integrates trend monitoring accuracy, intervention evaluation capability, individual risk prediction, population representativeness, and policy actionability. ML-driven individual risk prediction achieved the highest LDSS (0.926) by identifying high-risk individuals 4.6 years before clinical disease onset, while population-level policy evaluation (LDSS 0.912) provided the strongest evidence for fiscal and regulatory interventions including sugar taxes, alcohol minimum unit pricing, and smoking bans.