Year: 2026
Type: article
Study design: Observational Study
Abstract: Armed conflicts, like the Russian invasion in Ukraine, devastated healthcare systems and amplified chronic disease burdens. This study aimed to unveil novel links between environmental and social factors and chronic illnesses during crises.This study uniquely combined individual-level data on chronic diseases, living conditions, and winter preparedness in Ukraine during crisis conditions. A multivariable logistic regression model, using age- and gender-adjusted analyses, revealed striking associations, while machine learning models employed rigorous feature selection and data balancing. Six algorithms predicted disease outcomes using validated metrics, ensuring robust and interpretable insights.Surveying 1,552 Ukrainians revealed high chronic disease rates, with hypertension (31.7%) and arthritis (13.9%) prominently linked to environmental and socioeconomic stressors. Poor air quality, crowding, and financial strain emerged as critical drivers. Machine learning pinpointed the top 10 key predictors, showcasing exceptional predictive accuracy. These novel findings underscore the profound health impacts of resource limitations and living conditions during crises.This study reveals unexpected links between environment, socioeconomic status, and healthcare access in chronic disease risks during crises. These insights demand urgently tailored interventions.
Source: Communications Medicine
Language: English
Topic: Health and Conflict Studies
Subfield: General Health Professions
Field: Health Professions
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,690
Award: G979940031
OpenAlex ID: W4412138300
