Socioeconomic disparity is associated with faster retinal neurodegeneration in multiple sclerosis
Open accessAbstract
Disease course in multiple sclerosis is notably heterogeneous, and few prognostic indicators have been consistently associated with multiple sclerosis severity. In the general population, socioeconomic disparity is associated with multimorbidity and may contribute to worse disease outcomes in multiple sclerosis. Herein, we assessed whether indicators of socioeconomic status are associated with disease progression in patients with multiple sclerosis using highly sensitive imaging tools such as optical coherence tomography, and determined whether differential multiple sclerosis management or comorbidity mediate any observed socioeconomic status-associated effects. We included 789 participants with longitudinal optical coherence tomography and low contrast letter acuity (at 1.25 and 2.5%) in whom neighbourhood- (derived via nine-digit postal codes) and participant-level socioeconomic status indicators were available ≤10 years of multiple sclerosis symptom onset. Sensitivity analyses included participants with socioeconomic status indicators available ≤3years of symptom onset (n = 552). Neighbourhood-level indicators included state and national area deprivation indices, median household income and the Agency for Healthcare Research and Quality (AHRQ) Socioeconomic Status Index. Participant-level indicators included education level. Biannual optical coherence tomography scans were segmented to quantify thickness of the composite macular ganglion cell+inner plexiform (GCIPL) layer. We assessed the association between socioeconomic status indicators and GCIPL atrophy or low contrast letter acuity loss using mixed models adjusting for demographic (including race and ethnicity) and disease-related characteristics. We also assessed socioeconomic status indicators in relation to multiple sclerosis therapy changes and comorbidity risk using survival analysis. More disadvantaged neighbourhood-level and patient-level socioeconomic status indicators were associated with faster retinal atrophy. Differences in rate of GCIPL atrophy for individuals in the top quartile (most disadvantaged) relative to the bottom quartile (least) for state area deprivation indices were −0.12 µm/year faster [95% confidence interval (CI): −0.19, −0.04; P = 0.003], for national area deprivation indices were −0.08 µm/year faster (95% CI: −0.15, −0.005; P = 0.02), for household income were −0.11 µm/year faster (95% CI: −0.19, −0.03; P = 0.008), for AHRQ Socioeconomic Status Index were −0.12 µm/year faster (95% CI: −0.19, −0.04) and for education level were −0.17 µm/year faster (95% CI: −0.26, −0.08; P = 0.0002). Similar associations were observed for socioeconomic status indicators and low contrast letter acuity loss. Lower socioeconomic status was associated with higher risk of incident comorbidity during follow-up. Low socioeconomic status individuals had faster rates of therapy escalation, suggesting the association between socioeconomic status and GCIPL atrophy may not be explained by differential contemporaneous multiple sclerosis therapy management. In conclusion, socioeconomic disparity is associated with faster retinal neurodegeneration in multiple sclerosis. As low socioeconomic status was associated with a higher risk of incident comorbidities that may adversely affect multiple sclerosis outcomes, comorbidity prevention may mitigate some of the unfavourable socioeconomic status-associated consequences.
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A few observational studies have documented an inverse association between educational attainment and retinal neurodegeneration.
“Furthermore, a few observational studies have documented an inverse association between educational attainment and subsequent MS disability31 as well as retinal neurodegeneration49.”
From Locus for severity implicates CNS resilience in progression of multiple sclerosis (2023) · cites this paper as [49]
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Self-citationDisparidades de salud en el mundo real de los pacientes con esclerosis múltiple
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- Authors
- Vasileiou, E. S., Filippatou, A. G., Pimentel Maldonado, D., Kalaitzidis, G., Ehrhardt, H., Lambe, J., Saidha, S., Sotirchos, E. S., Mowry, E. M., Calabresi, P. A., & Fitzgerald, K. C.
- Affiliations
- Johns Hopkins University (US)
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Corresponding author
- Fitzgerald, Kathryn C
- ORCID
- Venue
- Brain
- Publisher
- Oxford University Press (OUP)
- Published
- 2021-10-29
- Volume
- 144
- Issue
- 12
- Pages
- 3664-3673
- ISSN
- 0006-8950 (ISSN-L)
- 1460-2156
- PMC
- PMC8759504
- OpenAlex
- W3208713003
- Cited by
- 32
- References
- 0
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 9 · 2023: 10 · 2022: 3 · 2021: 1
- FWCI
- 3.83
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Brain (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (1K01MH121582-01, R01NS082347)
- National Multiple Sclerosis Society (TA-1805–31136, RG-1606–08768)
- Race to Erase Multiple Sclerosis Foundation
- Genentech Corporation
- Topics
- Health Sciences › Medicine › Pathology and Forensic Medicine › Multiple Sclerosis Research Studies
- Health Sciences › Medicine › Ophthalmology › Glaucoma and retinal disorders
- Health Sciences › Medicine › Ophthalmology › Drug-Induced Ocular Toxicity
- Keywords
- multiple sclerosis, socioeconomic status, socioeconomic disparities, retinal neurodegeneration, optical coherence tomography, neighborhood disadvantage, household income, educational attainment, multimorbidity, disease progression, prognosis, comorbidities, visual function decline, racial and ethnic disparities
- MeSH terms
- Humans, Multiple Sclerosis, Retinal Degeneration, Socioeconomic Factors, Visual Acuity, Disease Progression, Tomography, Optical Coherence, Healthcare Disparities
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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