Abstract
Purpose :
People with vision impairment and blindness (VIB) have different needs based on their age, economic, housing, neighborhood, and other impairment characteristics. Better information on individuals with VIB could help target preventive and support services. We applied social vulnerability methods developed for disaster preparedness to create Census Tract level community vulnerability profiles (CVPs) for Richmond, Virginia.
Methods :
We used calibration methods to transform American Community Survey (ACS) 5-year estimates (2015-19) into a synthetic dataset of person-level records in each census tract and subset the data to persons who answered yes to the question “Are you blind or do you have serious difficulty seeing even when wearing glasses?” To identify individual vulnerability profiles (IVP), we applied divisive clustering to 17 variables measuring individual demographics, non-vision disability status, socioeconomics (SES), housing, and access and independence. We labeled tracts with categorical community vulnerability profile (CVP) names based on their predominant IVP types. We mapped the CVPs and overlay information on the number of estimated people with VIB and the National Walkability Index, which we hypothesized measured people's ability to live independently.
Results :
A total of 6,743 people in Richmond had VIB, 2.97% of the population. Among them, we identified 7 IVP clusters which we combined and mapped into 6 CVPs; 1. Seniors (age 65 and older); 2. Low SES Younger; 3. Low SES Older; 4. Mixed SES; 5. Higher SES; and 6. Adults in Group Quarters. CVPs in Southwest Richmond predominantly contained Low SES Younger and Older CVPs. Senior CVPs were in Northern Richmond, and Mixed and Higher SES CVPs were concentrated in the center city. Two tracts that contained universities and jails were identified as adults in group quarters CVPs. Three CVPs had lower-than-average walkability.
Conclusions :
This pilot project illustrates how ACS data can be used to better understand people with VIB at the granular census tract level. Further application is needed to assess the utility of these methods for programmatic purposes.
This abstract was presented at the 2023 ARVO Annual Meeting, held in New Orleans, LA, April 23-27, 2023.