Neighborhood Poverty and Clinic Attendance in the Michigan Screening and Intervention for Glaucoma and Eye Health through Telemedicine Program.

PRECIS: Higher neighborhood-level poverty is associated with greater odds of missing a free eye disease screening appointment, underscoring the importance of community-based interventions to address upstream social determinants of health. PURPOSE: To investigate the association between neighborhood-level characteristics and attendance for a free eye disease screening. PATIENTS AND METHODS: The MI-SIGHT program is conducted in two community clinics in Southeastern Michigan. Participant-level demographics were extracted from electronic health records. Neighborhood level-characteristics including Area Deprivation Index (ADI), median household income (HHI), percent of households with >30% rent burden, percent of households without vehicles, percent of households in subsidized housing, and energy burden were obtained from the Wisconsin Neighborhood Atlas and the United States census. Logistic regression was used to model the probability of clinic visit attendance, which was the main outcome measure. RESULTS: 1431 participants were scheduled for screening appointments between July 2020 to November 2021, with a no-show rate of 23%. Individuals lived an average of 7.7 miles from each clinic (SD=8.1) and in neighborhoods with a mean ADI of 6.8 (SD=3.2, 1-10 scale where 10 is the most deprived). After adjusting for age, sex, race, and ethnicity, participants from neighborhoods with higher deprivation were more likely to have missed clinic visits. For example, there was an 8% higher odds of missed clinic visits for every 1-point increase in ADI (odds ratio, OR=1.08, P=0.020) and an 18% higher odds of a missed visit with every 10% increase in households without a vehicle (OR=1.18, P=0.013). CONCLUSION: Higher neighborhood-level poverty was associated with greater odds of missing a free eye disease screening appointment after adjusting for individual characteristics. Increased neighborhood-level resources are likely needed to bolster engagement in preventive eye care.

Place-Based Measures of Inequity and Vision Difficulty and Blindness.

Importance: Known social risk factors associated with poor visual and systemic health in the US include segregation, income inequality, and persistent poverty. Objective: To investigate the association of vision difficulty, including blindness, in neighborhoods with measures of inequity (Theil H index, Gini index, and persistent poverty). Design, Setting, and Participants: This cross-sectional study used data from the 2012-2016 American Community Survey and 2010 US census tracts as well as Theil H index, Gini index, and persistent poverty measures from PolicyMap. Data analysis was completed in July 2023. Main Outcomes and Measures: The main outcome was the number of census tract residents reporting vision difficulty and blindness (VDB) and the association with the Theil H index, Gini index, or persistent poverty, assessed using logistic regression. Results: In total, 73 198 census tracts were analyzed. For every 0.1-unit increase in Theil H index and Gini index, there was an increased odds of VDB after controlling for census tract-level median age, the percentage of the population that identified as female sex, the percentage of the population that identified as a member of a racial or ethnic minority group, state, and population size (Theil H index: odds ratio [OR], 1.14 [95% CI, 1.14-1.14; P < .001]; Gini index: OR, 1.15 [95% CI, 1.15-1.15; P < .001]). Persistent poverty was associated with an increased odds of VDB after controlling for census tract-level median age, the percentage of the population that identified as female sex, the percentage of the population that identified as a member of a racial or ethnic minority group, state, and population size compared with nonpersistent poverty (OR, 1.36; 95% CI, 1.35-1.36; P < .001). Conclusions and Relevance: In this cross-sectional study, residential measures of inequity through segregation, income inequality, or persistent poverty were associated with a greater number of residents living with VDB. It is essential to understand and address how neighborhood characteristics can impact rates of VDB.

Factors Associated With Laboratory Test Negativity Following a Transition in Specimen Collection in Microbial Keratitis Cases.

PURPOSE: Negative laboratory results make targeting microbial keratitis treatment difficult. We investigated factors associated with laboratory negativity in patients with microbial keratitis in the context of a transition to a new specimen collection method. METHODS: Microbial keratitis patients with associated laboratory tests were identified in the electronic health record of a tertiary care facility from August 2012 to April 2022. Patient demographics and laboratory results were obtained. Random sampling of 50% of charts was performed to assess the impact of the ocular history and pretreatment measures. The relationship between probability of negative laboratory results with demographics, ocular history, pretreatment measures, and utilization of a new specimen collection method (i.e. ESwab) was evaluated by multivariable logistic regression. RESULTS: Of 3395 microbial keratitis patients identified, 31% (n = 1051) had laboratory tests. Laboratory testing increased over time (slope = 2.5% per year, p < 0.001; 19.6% in 2013 to 42.2% in 2021). Laboratory negative rate increased over time (slope = 2.2% per year, p = 0.022; 48.5% in 2013 to 62.3% in 2021). Almost one-third of patients (31.2%, n = 164) were pretreated with steroids. Over two-thirds of patients were pretreated with antibiotics (69.5%, n = 367). 56.5% (n = 297) of patients were outside referrals. In multivariable regression, patients with corticosteroid pretreatment had lower odds of negative laboratory results (odds ratio [OR] = 0.49, p = 0.001). There were higher odds of negative laboratory results for every additional antibiotic prescribed to a patient prior to presentation (OR = 1.30, p = 0.006) and for specimens collected using ESwabs (OR = 1.69, p = 0.005). Age, prior eye trauma, outside referrals, and contact lens wear were not significantly associated with negative laboratory results. CONCLUSION: More microbial keratitis associated laboratory tests are being taken over time. Over 60% of tests were negative by 2022. Factors associated with negative laboratory test results included pretreatment with antibiotics and specimens collected with the new collection method.

Association of Contrast Sensitivity With Eye Disease and Vision-Related Quality of Life.

PURPOSE: To investigate contrast sensitivity (CS) as a screening tool to detect eye disease and assess its association with both eye disease and vision-related quality of life. DESIGN: Cross-sectional study. METHODS: Setting and population: Adults receiving care from a free clinic and a Federally Qualified Health Center in Michigan. MAIN OUTCOME MEASURES: Screening positive for eye disease and Visual Function Questionnaire (VFQ) score. OBSERVATION: Participants received a vision exam reviewed via telemedicine for disease, completed a demographic survey, and the 9-item VFQ. The ability of CS to predict eye disease was explored and area under the curve (AUC) is reported. Logistic and linear regression were used to investigate the continuous effect of CS on the probability of screening positive for eye disease and VFQ score, respectively, adjusting for age and visual acuity. RESULTS: 1159 included participants were, on average, 54.9 ± 14.5 years old, 62% identified as female, 34% as White, 54% as Black, 10% as Hispanic/Latino, and reported mean VFQ score of 79.7 ± 15.3. CS ranged from 0.00 to 1.95 log units (mean = 1.54 ± 0.24), 21% of eyes had glaucoma, 19% cataract, 6% DR, and 2% AMD. AUCs were 0.53 to 0.73. A 0.3 log unit decrease in better eye CS was associated with increased odds of glaucoma (odds ratio [OR] = 1.35, confidence interval [CI] = 1.09-1.67), cataract (OR = 1.35, CI = 1.05-1.72), DR (OR = 2.05, CI = 1.51-2.77), and AMD (OR = 2.08, CI = 1.10-3.91). A 0.3 log unit increase in better eye CS was associated with a 5.9 unit increase in VFQ. CONCLUSION: While CS alone is not sufficient to identify people with eye disease, it is an important measure of visual function that can add value to comprehensive eye screening.