Abstract
Urban nature, including green and blue spaces, vegetation cover, and biodiversity, has been linked to improved cardiometabolic health. However, most exposure metrics oversimplify complex environmental conditions, limiting their relevance for public health and equity. We developed a multidimensional classification of urban nature using eight high-resolution indicators within 300-meter residential buffers for 36,830 New York City residents aged ≥ 55 years. Using k-means clustering, we identified five distinct exposure profiles based on their mean feature: Low Green, Street Trees, High Cover, Park Access, and Waterfront. We estimated associations between these profiles and incident atherosclerotic cardiovascular disease (ASCVD) from 2013 to 2022 using Cox proportional hazards models with competing risks, and evaluated effect modification by sex, race/ethnicity, and neighborhood-level poverty and racial composition. Over a median follow-up of 3.8 years, 28.7 % of participants experienced an ASCVD event. Compared with the Low-green profile, ASCVD risk was lower for Waterfront (HR = 0.88; 95 % CI: 0.81-0.95), Park Access (0.89; 0.84-0.94), Street Trees (0.92; 0.87-0.98), and High Cover (0.95; 0.88-1.02) profiles in fully adjusted Cox models. Significant interaction term indicated that the association between the Park Access profile and ASCVD risk differed by sex, with stronger protective associations observed for males (interaction p-value: 0.04). Similarly, Street Trees were more protective in areas with higher percentages of non-Hispanic Black residents (interaction p-value: 0.02). These results underscore the value of multidimensional urban nature metrics for understanding and promoting cardiovascular health equity in dense cities.