Assessing the impact of street-level greenery on older adults' emotional well-being: A longitudinal study of equigenic potential and socioeconomic disparities

The equigenesis hypothesis suggests that greenery has the potential to reduce health disparities across socioeconomic groups. This is important in high-density urban setting, because greenery can improve human health, but also promotes equitable access to health benefits thus reducing health disparities. However, findings are inconsistent, partly due to the predominance of cross-sectional studies. Moreover, the equigenic effects of street-level greenery, remains underexplored. This longitudinal study examined the effect of street-level greenery on the emotional well-being of older adults. We analyzed 3110 street view images from 1,550 locations in Fuzhou, China, collected in 2014 and 2020. Street-level built environment features were measured using the DeeplabV3 network. Emotional well-being, operationalized as perceptions of pleasantness, was quantitatively evaluated using the Microsoft Trueskill approach to convert the paired comparisons of images into a ranked score. Moderation effects of street-level greenery, were investigated through interactions with educational attainment and economic status, based on individual-level fixed effect models. Our findings revealed that: 1) street-level greenery had the most significant influence on enhancing perceptions of pleasantness; 2) the interaction between street-level greenery and average education years, was positively associated with perceptions of pleasantness, while a negative interaction was observed with economic status. These results suggest that while street-level greenery may mitigate income-related disparities, it could accelerate education-related disparities in emotional well-being among older adults. This study offers new insights into the equigenesis hypothesis through a longitudinal lens, demonstrating that street-level greenery may not uniformly improve mental health equity among older adults in Chinese cities.