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Economic burden of stroke attributable to excess body mass in Hungary: a population-attributable fraction analysis
Tamas Jarecsny1,2, Csilla Arvane Egri3, Roland Kosik3
1Department of Neurology and Stroke, Saint John's Central Hospital of North Buda, Budapest, Hungary.
Background:
The prevalence of obesity in Hungary ranks among the highest in the European Union, representing a significant healthcare burden. In modern medicine, stroke remains one of the major cardiovascular cost drivers, with obesity being a key modifiable risk factor.
Aims:
To estimate annual stroke-related healthcare cost savings achievable through population-level reduction in body mass index (BMI) in Hungary, based on five international risk models.
Methods:
A cross-sectional study of 2,442 adults was conducted between June and August 2022 via the nationwide "Bringing Screening to You" program. Post-stratification weighting by sex and age was applied to align with the 2022 national census. Population-attributable fraction (PAF) analysis incorporated five published BMI-stroke models (HUNT, CHARLS-male cohort, Physicians' Health Study, meta-analysis, INTERSTROKE) and was applied to the €1.016 billion national stroke cost for 2022. Uncertainty was assessed using a 10,000-iteration Monte Carlo simulation.
Results:
Weighted overweight and obesity prevalence was 72.5% (95% CI: 70.6-74.4%), one of the highest observed among Central and Eastern European countries. The PAF of stroke cases associated with excess BMI ranged from 9.7% to 20.4%, corresponding to annual cost savings of €99-207 million under a theoretical maximum scenario of complete BMI normalization, assuming proportional cost reduction. Conservative estimates (HUNT model) projected €99 million in savings (95% CI: 75-127), while higher estimates (Physicians' Health Study) yielded €207 million (95% CI: 145-265).
Conclusions:
Population-level BMI reduction could reduce Hungary's annual stroke related healthcare expenditure by at least €99 million, representing substantial potential savings. These findings support implementation of population-level comprehensive obesity prevention strategies.
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