Spatial Vision Inequalities: A Literature Review of the Impact of Place on Vision and Eye Health Outcomes

“

TL;DR

This narrative review synthesizes evidence linking neighborhood and built environment social risk factors—such as housing quality, transportation access, green spaces, pollution, and safety—to adverse eye health outcomes including visual impairment, ocular hospitalizations, and delayed care. The findings underscore that place-based inequities significantly contribute to disparities in eye care utilization and disease prevalence, highlighting the need for targeted interventions and policy changes to advance eye health equity.

Full summary

5,098 CHARS

**Background:** Social determinants of health (SDoH) account for 80% to 90% of modifiable health risk factors at a population level. The neighborhood and built environment domain includes housing, transportation, green spaces, pollution, and safety. This narrative review collates research on how these factors impact eye health and vision outcomes, identifies knowledge gaps, and discusses how geocoding can inform policy to advance health equity.

**Methods:** The authors conducted a literature review, summarizing studies that examined associations between neighborhood and built environment social risk factors (SRFs) and various eye health outcomes. Studies included cross-sectional analyses (e.g., NHANES, National Health Interview Survey), retrospective cohort studies (e.g., Medicare inpatient data, National Trauma Data Bank), and longitudinal school-based studies. Key metrics included housing quality, transportation access, green space exposure, air/land/water pollutants, neighborhood safety, and composite indices (Area Deprivation Index [ADI], Social Vulnerability Index [SVI], Theil's H Index).

**Key Results:** - **Housing:** Participants reporting mildew/musty odor had increased odds of fair vision (OR=1.67; 95% CI, 1.20–2.32; P=0.005) and poor vision (OR=2.10; 95% CI, 1.27–3.46; P=0.006) (Shiue). Communities with severe housing problems above median (14.38%) had 13% increased odds of ocular hospitalization (OR=1.13; 95% CI, 1.09–1.18; P<0.01) (French et al.). - **Transportation:** Households without a car had 14% decreased likelihood of eye examination within 5 years (risk ratio=0.86; 95% CI, 0.86–0.87) (Wright et al.). Higher percentage of households with no car was associated with increased odds of presenting visual acuity <20/40 in microbial keratitis (OR=1.25 per 1 percentage point increase; 95% CI, 1.12–1.40; P=0.001) (Hicks et al.). Transportation barriers were associated with delayed glaucoma care (aOR=2.22; 95% CI, 1.68–2.91; P<0.0001) (Kim et al.). - **Green Spaces:** Ten minutes of green space exposure reduced eye strain (post-stimulation 8.20±8.15 vs. post-relax 5.85±6.45; P<0.001) (Lu et al.). Higher neighborhood greenness decreased odds of astigmatism by 45% (aOR=0.55; 95% CI, 0.43–0.70; P<0.001) and myopia by 38% (aOR=0.62; 95% CI, 0.38–0.99; P<0.05) in preschoolers (Huang et al.). For every 0.1-unit increase in green space at school, myopia prevalence increase was 3.6% lower over 2 years (95% CI, 1.8%–5.5%; P<0.001) (Yang et al.). - **Pollution:** Air pollutants increased dry eye disease risk: ozone (OR=3.97; 95% CI, 3.67–4.29; P<0.0001), PM2.5 (OR=2.01; 95% CI, 1.79–2.26; P<0.0001), SO2 (OR=1.64; 95% CI, 1.50–1.79; P<0.0001) (Yu et al.). Communities with fine particulate matter above median (11.62 µg/m³) had increased odds of ocular hospitalization (OR=1.05; 95% CI, 1.01–1.08; P<0.01) (French et al.). Heavy metals: every twofold increase in urinary cadmium led to 23% increased odds of cataract surgery (OR=1.23; 95% CI, 1.04–1.46; P=0.021) (Wang et al.). PFAS exposures were associated with visual impairment (linear perfluorooctane sulfonate OR=3.37; 95% CI, 2.50–4.56) (Zhao et al.). - **Safety:** Neighborhood violent crimes were associated with increased odds of ocular hospitalization (OR=1.07; 95% CI, 1.02–1.11; P<0.01) (French et al.). Unsafe neighborhoods were linked to delayed prescription refills for diabetes (aOR=1.69; 95% CI, 1.19–2.40; P=0.004) (Billimek and Sorkin). Greater violent crimes increased odds of missed medical appointments (OR=1.27; 95% CI, 1.19–1.35) (French et al.). - **Neighborhood Measures:** Historical redlining: each 1-unit increase in redlining score increased odds of visual impairment/blindness by 13% (OR=1.13; 95% CI, 1.131–1.138; P<0.001) (Elam et al.). ADI: every 10-unit worse ADI increased odds of presenting visual acuity <20/40 in corneal ulcers by 30% (OR=1.30; 95% CI, 1.25–1.35; P<0.001) (Hicks et al.). SVI: 0.1-unit increase in SVI was associated with 146% increased odds of missing ophthalmology appointment (aOR=2.46; 95% CI, 1.99–3.06; P<0.01) (Scanzera et al.). Theil's H Index: every 0.1-unit increase increased odds of visual acuity <20/40 in microbial keratitis (OR=1.44; 95% CI, 1.30–1.61; P<0.001) (Hicks et al.).

**Clinical Implications:** This review demonstrates that multiple neighborhood and built environment factors—including housing quality, transportation, green spaces, pollution, safety, and composite deprivation indices—are significantly associated with eye health outcomes, ranging from visual impairment and ocular hospitalizations to delayed care and disease progression. Clinicians should consider these social risk factors when assessing patients' barriers to eye care and adherence. Geocoding and composite indices (ADI, SVI) can identify high-need communities for targeted screening and intervention programs. Future research should explore epigenetic mechanisms linking neighborhood exposures to eye disease, leverage big data with standardized metrics, and employ community-engaged approaches to develop effective, equitable interventions.