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Background/Objectives <p>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).</p> Subjects/Methods <p>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.</p> Results <p>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; <i>p</i> &lt; 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.</p> Conclusion <p>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.</p>

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Vision in the margins: the association between census tract neighbourhood disadvantage and visual difficulty and blindness in the United States

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月15日

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  • Jenna Hart,
  • Minnie Bluhm,
  • Tiffani R. Spaulding,
  • Amanda Nwokeji,
  • Angela R. Elam,
  • Dean VanNasdale,
  • Erica Shelton,
  • Maria A. Woodward,
  • Paula Anne Newman-Casey,
  • Patrice M. Hicks

摘要

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.