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Association Between Social Determinants of Health and Examination-Based Vision Loss vs Self-reported Vision Measures. | LitMetric

AI Article Synopsis

  • Social determinants of health (SDOH) significantly impact vision loss, and it's essential to understand how these associations vary between clinically evaluated vision impairment and self-reported issues.
  • The study analyzed data from various health surveys, focusing on five SDOH domains: economic stability, education, healthcare access, neighborhood and environment, and social context.
  • Results indicated that factors like higher income and employment status were strong predictors of better vision, emphasizing the role of socioeconomic conditions in visual health outcomes.

Article Abstract

Importance: Recent evidence suggests that social determinants of health (SDOH) affect vision loss, but it is unclear whether estimated associations differ between clinically evaluated and self-reported vision loss.

Objective: To identify associations between SDOH and evaluated vision impairment and to assess whether these associations hold when examining self-reported vision loss.

Design, Setting, And Participants: This population-based cross-sectional comparison included participants 12 years and older in the 2005 to 2008 National Health and Nutrition Examination Survey (NHANES), participants of all ages (infants and older) in the 2019 American Community Survey (ACS), and adults 18 years and older in the 2019 Behavioral Risk Factor Surveillance System (BRFSS).

Exposures: Five domains of SDOH that are based on Healthy People 2030: economic stability, education access and quality, health care access and quality, neighborhood and built environment, and social and community context.

Main Outcomes And Measures: Presenting vision impairment of 20/40 or worse in the better-seeing eye (NHANES) and self-reported blindness or serious difficulty seeing, even with glasses (ACS and BRFSS).

Results: Of 3 649 085 included participants, 1 873 893 were female (51.1%) and 2 504 206 were White (64.4%). SDOH across domains of economic stability, educational attainment, health care access and quality, neighborhood and built environment, and social context were significant predictors of poor vision. For example, higher income (poverty to income ratio [NHANES]: OR, 0.91; 95% CI, 0.85-0.98; [ACS]: OR, 0.93; 95% CI, 0.93-0.94; categorical income [BRFSS:<$15 000 reference]: $15 000-$24 999; OR, 0.91; 95% CI, 0.91-0.91; $25 000-$34 999: OR, 0.80; 95% CI, 0.80-0.80; $35 000-$49 999: OR, 0.71; 95% CI, 0.71-0.72; ≥$50 000: OR, 0.49; 95% CI, 0.49-0.49), employment (BRFSS: OR, 0.66; 95% CI, 0.66-0.66; ACS: OR, 0.55; 95% CI, 0.54-0.55), and owning a home (NHANES: OR, 0.85; 95% CI, 0.73-1.00; BRFSS: OR, 0.82; 95% CI, 0.82-0.82; ACS: OR, 0.79; 95% CI, 0.79-0.79) were associated with lower odds of vision loss. The study team identified no differences in the general direction of the associations when using either clinically evaluated or self-reported vision measures.

Conclusions And Relevance: The study team found evidence that associations between SDOH and vision impairment track together when using either clinically evaluated or self-reported vision loss. These findings support the use of self-reported vision data in a surveillance system to track trends in SDOH and vision health outcomes within subnational geographies.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10080399PMC
http://dx.doi.org/10.1001/jamaophthalmol.2023.0723DOI Listing

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