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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.
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PURPOSE: To assess changes in vision care availability at Federally Qualified Health Centers (FQHCs) between 2017 and 2021 and whether neighborhood-level demographic social risk factors (SRFs) associated with eye care services provided by FQHCs. DESIGN: Secondary data analysis of the Health Resources and Services Administration (HRSA) data and 2017-2021 American Community Survey (ACS). PARTICIPANTS: Federally Qualified Health Centers. METHODS: Patient and neighborhood characteristics for SRFs were summarized. Differences in FQHCs providing and not providing vision care were compared via Wilcoxon-Mann-Whitney tests for continuous measures and chi-square tests for categorical measures. Logistic regression models were used to test the associations between neighborhood measures and FQHCs providing vision care, adjusted for patient characteristics. MAIN OUTCOME MEASURES: Odds ratios (ORs) with 95% confidence intervals (CIs) for neighborhood-level predictors of FQHCs providing vision care services. RESULTS: Overall, 28.5% of FQHCs (n = 375/1318) provided vision care in 2017 versus 32% (n = 435/1362) in 2021 with some increases and decreases in both the number of FQHCs and those with and without vision services. Only 2.6% of people who accessed FQHC services received eye care in 2021. Among the 435 FQHCs that provided vision care in 2021, 27.1% (n = 118) had added vision services between 2017 and 2021, 71.5% (n = 311) had been offering vision services since at least 2017, and 1.4% (n = 6) were newly established. FQHCs providing vision care in 2021 were more likely to be in neighborhoods with a higher percentage of Hispanic/Latino individuals (OR, 1.08, 95% CI, 1.02-1.14, P = 0.0094), Medicaid-insured individuals (OR, 1.08, 95% CI, 1.02-1.14, P = 0.0120), and no car households (OR, 1.07, 95% CI, 1.01-1.13, P = 0.0142). However, FQHCs with vision care, compared to FQHCs without vision care, served a lower percentage of Hispanic/Latino individuals (27.2% vs. 33.9%, P = 0.0007), Medicaid-insured patients (42.8% vs. 46.8%, P < 0.0001), and patients living at or below 100% of the federal poverty line (61.3% vs. 66.3%, P < 0.0001). CONCLUSIONS: Vision care services are available at a few FQHCs, localized to a few states. Expanding eye care access at FQHCs would meet patients where they seek care to mitigate vision loss to underserved communities. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found after the references.
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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, 73â¯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.
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Ceguera , Humanos , Estudios Transversales , Masculino , Femenino , Ceguera/epidemiología , Estados Unidos/epidemiología , Persona de Mediana Edad , Anciano , Adulto , Factores Socioeconómicos , Factores de Riesgo , Pobreza , Características del Vecindario , Inequidades en SaludRESUMEN
PRCIS: Targeted glaucoma screenings in populations with high levels of poverty and high proportions of people who identify as African American or Hispanic/Latino identified a 27% rate of glaucoma and suspected glaucoma, which is 3 times the national average. PURPOSE: To describe the neighborhood-level social risk factors across the 3 SIGHT Study sites and assess potential characteristics of these populations to help other researchers effectively design and implement targeted glaucoma community-based screening and follow-up programs in high-risk groups. METHODS/RESULTS: In 2019, Columbia University, the University of Michigan, and the University of Alabama at Birmingham each received 5 years of CDC funding to test a wide spectrum of targeted telehealth delivery methods to detect glaucoma in community-based health delivery settings among high-risk populations. This collaborative initiative supported innovative strategies to better engage populations most at risk and least likely to have access to eye care to detect and manage glaucoma and other eye diseases in community-based settings. Among the initial 2379 participants enrolled in all 3 SIGHT Studies; 27% screened positive for glaucoma/glaucoma suspect. Of all SIGHT Study participants, 91% were 40 years of age and older, 64% identified as female, 60% identified as African-American, 32% identified as White, 19% identified as Hispanic/Latino, 53% had a high school education or less, 15% had no health insurance, and 38% had Medicaid insurance. Targeted glaucoma screenings in populations with high levels of poverty and high proportions of people who identify as African American or Hispanic/Latino identified a 27% rate of glaucoma and suspected glaucoma, three times the national average. CONCLUSION: These findings were consistent across each of the SIGHT Studies, which are located in 3 geographically distinct US locations in rural Alabama, small urban locations in Michigan, and urban New York City.
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Determinantes Sociales de la Salud , Humanos , Femenino , Persona de Mediana Edad , Masculino , Adulto , Anciano , Factores de Riesgo , Tamizaje Masivo/métodos , Glaucoma/diagnóstico , Estados Unidos/epidemiología , Telemedicina , Negro o Afroamericano/estadística & datos numéricos , Presión Intraocular/fisiología , Hispánicos o Latinos/estadística & datos numéricosRESUMEN
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.