Description
Cardiovascular disease is a leading cause of morbidity and mortality globally and in New York City. Significant disparities in prevalence and risk factors persist across city neighbourhoods and among populations of varying socio-economic status, racial and ethnic backgrounds. These disparities are shaped and sustained by the complex interplay of social determinants of health, including housing, employment, access to healthcare and structural inequities. This study builds on prior quantitative research conducted under the AI4HealthyCities initiative, which applied machine learning to identify spatial clusters of cardiovascular vulnerability and social disadvantage.
