Association Between Sociodemographic Factors and Self-reported Glaucoma in the National Health Interview Survey: A...

To investigate the association between social determinants of health (SDH) in the domains of social and community context, education access, environmental context, economic stability, and healthcare access, with glaucoma prevalence.

Cross-sectional study.

The study population consisted of adult participants who answered glaucoma-related questions on the 2017 National Health Interview Survey (NHIS), the most recent iteration that includes glaucoma-related questions. The main outcome measures included the relationships between SDH-related factors and self-reported glaucoma diagnosis as well as self-reported glaucomatous vision loss were examined using univariable and multivariable regression models.

In total, 26,696 of 26,742 (99.83%) NHIS respondents were included, of whom 880 (3.30%) reported a glaucoma diagnosis and 275 (1.03%) reported glaucomatous vision loss. Participants were predominantly middle-aged (50.95 ± 18.60 years), female (54.75%), and non-Hispanic White (70.49%). In age-adjusted multivariable regression (n = 25,456), non-Hispanic Black race (odds ratio [OR] = 1.87, 99% CI = [1.37, 2.55], P < .001, compared to non-Hispanic White race) and poor health status (OR = 1.54, 99% CI = [1.00, 2.37], P = .01, compared to good health status) were significant predictors of glaucoma diagnosis. For glaucomatous vision loss, having an income below the poverty threshold (OR = 2.41, 99% CI = [1.12, 5.20], P = .003, compared to income ≥5 times the poverty threshold) was the only significant predictor in univariable analyses. No SDH-related factors were significantly associated with glaucomatous vision loss in multivariable analysis (n = 848). Multicollinearity was minimal (variation inflation factor<1.6 for all independent variables).

Non-Hispanic Black race and poor health status were associated with self-reported glaucoma diagnosis. Physicians and policymakers may consider SDH when assessing clinical risk and designing public health interventions.