Abstract Background/Objectives To investigate the utility of using a census tract (CT) measure to assess neighbourhood disadvantage and to explore its effects on CT measures of visual difficulty and blindness (VDB). Subjects/Methods This cross-sectional study used census tract data from the 2018 to 2022 American Community Survey and the National Neighbourhood Data Archive Neighbourhood Socioeconomic Status and Demographic Characteristics. CT measures of neighbourhood disadvantage, VDB, and demographics were summarized with descriptive statistics (mean, standard deviation (SD)). The main outcome was the number of CTs residents reporting VDB and the association with neighbourhood disadvantage (an aggregate measure ranging from 0 to 1 with higher scores indicating more disadvantage) assessed using logistic regression. Results In total, 83,388 CTs were included, with a mean of 2.53% of the population reporting VDB (SD = 2.62) and a mean neighbourhood disadvantage of 0.18 (SD = 0.12). Neighbourhood disadvantage was associated with 2.9% increased odds of VDB (Odds Ratio (OR): 1.029; 95% Confidence Interval (CI): 1.029,1.029; p < 0.001), after adjusting for neighbourhood demographics including median age, percentage of the CT that were female sex, percentage of the CT that identified as a person of colour, population size of the CT, and the state in which the CT was located. Conclusion This study identified that neighbourhood disadvantage was associated with a greater number of residents reporting VDB. Clinicians could use this measure to identify neighbourhoods with both higher levels of visual impairment and greater neighbourhood deprivation, allowing for targeted interventions that provide eye disease screening and eye care to those most at risk for poor vision outcomes.
Hart et al. (2026) studied this question.