Социальные детерминанты здоровья, качества ухода за больными и результаты лечения неврологических расстройств: систематический обзор.

Introduction

Global Burden of Neurological Disorders

Neurological disorders constitute the leading cause of disability and the second leading cause of death globally, accounting for 9.0 million deaths and 276 million disability-adjusted life years (DALYs) in 2019. 1 This represents 11.6% of global DALYs and 16.5% of all deaths, surpassing cardiovascular disease as a contributor to years lived with disability. 1 These conditions—spanning stroke, neurodegenerative diseases, epilepsy, multiple sclerosis, and traumatic brain injury—continue to escalate with population aging, with projected deaths increasing by 43% between 2015 and 2040. 2 Beyond mortality, neurological conditions profoundly affect functional independence, quality of life, and economic productivity. 3

Despite remarkable advances in neurological care including acute stroke interventions, disease-modifying therapies for multiple sclerosis, and precision medicine approaches, persistent and widening disparities in neurological health outcomes across socioeconomic strata, racial and ethnic groups, and geographic regions represent a pressing public health challenge. 4 , 5 These disparities cannot be attributed solely to differential disease biology but rather reflect complex interactions between social, economic, environmental, and healthcare system factors that systematically disadvantage certain population groups. 6 Understanding these social determinants of health (SDOH) and their mechanisms of impact on care delivery and outcomes is essential for developing effective, equitable interventions and informing policy to reduce preventable neurological morbidity and mortality.

Social Determinants of Health: Conceptual Framework

The World Health Organization defines social determinants of health as “the conditions in which people are born, grow, live, work and age” and “the fundamental drivers of these conditions”, emphasizing that these circumstances are shaped by the distribution of money, power, and resources at global, national, and local levels. 7 The Healthy People 2030 framework organizes SDOH into five domains: economic stability, education access and quality, healthcare access and quality, neighborhood and built environment, and social and community context. 8

Conceptual models emphasize that SDOH operates across multiple levels—individual (education, income), interpersonal (social support), community (neighborhood resources), institutional (insurance, provider supply), and policy (legislation, anti-discrimination protections)—each shaping health behaviors, care access, and disease management. 9–15

For neurological disorders specifically, SDOH operates through several interconnected pathways: increased exposure to vascular and neurotoxic risk factors among disadvantaged populations; 16 , 17 healthcare access barriers that delay diagnosis and limit treatment intensity; 18 health literacy deficits that compromise self-management and care navigation; 19 structural racism generating both chronic physiological stress and systemic inequities in care delivery; 20 , 21 and inadequate social support limiting caregiving resources essential for recovery. 22

Nursing Care Quality as a Critical Mediator

Nursing care quality represents a potentially high-impact, modifiable pathway through which SDOH influences patient outcomes in neurological disorders. Nurses constitute the largest segment of the healthcare workforce and provide the majority of direct patient care, particularly for neurological conditions requiring intensive monitoring, complex medication management, rehabilitation support, patient and family education, and care coordination across transitions. 23 The Institute of Medicine emphasizes that nursing care quality encompasses both technical aspects (accuracy of assessments, appropriate interventions, competent execution) and relational dimensions (communication, cultural sensitivity, patient engagement, emotional support). 24

The American Nurses Association’s National Database of Nursing Quality Indicators framework categorizes nursing-sensitive indicators into structural (staffing levels, skill mix, nurse education), process (assessment completeness, discharge teaching, care coordination), and outcome domains (mortality, readmissions, patient safety events, patient satisfaction). 25

For neurological populations specifically, the Nursing Outcomes Classification (NOC) provides standardized language for evaluating outcomes including neurological status, communication, mobility, self-care, and seizure control. 26 Recent validation studies in stroke populations have confirmed strong internal consistency (Cronbach’s α 0.79–0.85) and significant correlations with standardized neurological scales. 27

SDOH may influence nursing care quality through several mechanisms, including resource constraints in hospitals serving disadvantaged populations that limit staffing and education; 28 communication barriers from language discordance and low health literacy; 29 implicit provider bias affecting clinical decisions and advocacy; 30 social complexity (housing instability, food insecurity) that complicates discharge planning; 31 and insurance restrictions limiting post-acute rehabilitation access. 32 , 33

Evidence Gaps and Study Rationale

While substantial literature documents SDOH impacts on neurological disease incidence and general health outcomes, systematic synthesis examining the specific relationships between SDOH, nursing care quality indicators, and patient outcomes across major neurological conditions remains limited. Previous systematic reviews have addressed aspects of this topic but with important limitations. For example, Mayeda et al 34 synthesized evidence on socioeconomic disparities in stroke outcomes but did not examine nursing-sensitive quality indicators, while Cooper et al 35 reviewed racial disparities in dementia care without cross-condition comparison. Other reviews focused on isolated SDOH dimensions, 36 and none have explicitly examined nursing care quality as a mediating pathway. Furthermore, most existing syntheses predate 2020 and thus miss recent evidence on pandemic-related exacerbation of disparities and emerging research on modifiable nursing system factors. 37

Key questions remain regarding which SDOH dimensions most strongly affect nursing care quality across neurological conditions, whether effects are disease-specific or generalizable, which nursing-sensitive indicators are most amenable to intervention, and how multiple SDOH factors interact to shape outcomes.

Understanding these relationships is critically important because neurological conditions disproportionately affect disadvantaged populations while requiring intensive nursing care, creating a “double burden” that magnifies health inequities. 38 Importantly, nursing care quality represents a highly modifiable factor amenable to intervention through workforce policy, clinical practice innovations, and organizational change, 39 and nurses are uniquely positioned to identify social needs and advocate for structural change. 40 Conceptually, this review is guided by a multilevel framework positing that SDOH factors (socioeconomic status, race/ethnicity, insurance, geography) influence nursing care processes (staffing adequacy, assessment quality, discharge planning, care coordination), which in turn mediate key patient outcomes (mortality, functional recovery, readmission, quality of life) across neurological conditions.

Study Objectives

This systematic review aims to synthesize observational evidence published between 2015 and 2025 on the associations between SDOH, nursing care quality, and patient outcomes among adults with major neurological disorders. Specifically, we sought to: (1) evaluate the relationships between key SDOH dimensions and nursing-sensitive quality indicators and clinical outcomes across neurological conditions; (2) identify common versus disease-specific patterns of SDOH influence and the most impactful modifiable nursing factors; and (3) provide evidence-based recommendations for clinical practice, policy, and future research to advance health equity in neurological nursing care.

By comprehensively synthesizing current evidence and identifying actionable findings, this review seeks to advance understanding of how social contexts fundamentally shape neurological care delivery and outcomes and to provide a roadmap for nurses, healthcare systems, researchers, and policymakers working to eliminate preventable disparities and ensure equitable access to high-quality neurological care.

Methods

Protocol and Registration

This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement. 41 A ( Supplementary Table 1 ). The review protocol was prospectively developed, establishing eligibility criteria, search strategies, and quality assessment methods prior to searching. Formal protocol registration was not pursued given the descriptive synthesis approach; the protocol is available from the corresponding author upon request.

Eligibility Criteria

Studies were eligible for inclusion based on the following criteria, developed using the Population, Exposure, Comparator, Outcome, Study design (PECOS) framework:

Population

Adults (≥18 years) with confirmed diagnosis of neurological disorders including stroke (ischemic, hemorrhagic, transient ischemic attack), neurodegenerative diseases (Alzheimer’s disease, other dementias, Parkinson’s disease, amyotrophic lateral sclerosis), multiple sclerosis, epilepsy, or traumatic brain injury. Studies with mixed neurological populations were eligible if condition-specific data were separately reported.

Exposure

Assessment of at least one social determinant of health dimension, operationalized through validated instruments, administrative data, census linkage, or self-report. Eligible SDOH measures included: (1) socioeconomic status indicators (individual or household income, wealth, poverty status, financial strain); (2) educational attainment (years of schooling, degree completion, literacy level, health literacy); (3) occupational status (employment type, unemployment, occupational class); (4) race, ethnicity, or racialized identity; (5) health insurance status (uninsured, public insurance, private insurance, insurance generosity); (6) geographic factors (rural versus urban residence, travel distance to specialized care, regional variation, neighborhood socioeconomic characteristics, community deprivation indices); (7) social support and social networks (marital status, living arrangements, social isolation, social network size and composition); (8) housing status (homeownership, housing stability, homelessness, housing quality); (9) food security; and (10) other social factors (immigration status, language barriers, discrimination experiences).

Comparator

Comparison groups defined by SDOH exposure status (eg, low versus high socioeconomic status, racial/ethnic minorities versus white populations, rural versus urban residents, uninsured versus insured patients). Studies examining SDOH factors as continuous variables were eligible.

Outcomes

Reporting of at least one outcome in the following categories:

Nursing Care Quality Indicators

Nurse staffing levels (patient-to-nurse ratios, skill mix); nursing-sensitive patient safety outcomes (falls, pressure ulcers, medication errors); care process measures (assessment completeness, discharge readiness, patient education); care coordination; and patient satisfaction with nursing care.

Patient Clinical Outcomes

All-cause mortality (in-hospital, 30-day, 1-year); functional status and disability (modified Rankin Scale, Barthel Index, Functional Independence Measure, Expanded Disability Status Scale); disease-specific outcomes (stroke recurrence, seizure control, cognitive decline); quality of life (EQ-5D, SF-36, disease-specific instruments); healthcare utilization (readmissions, length of stay, nursing home placement); and treatment receipt (thrombolysis, thrombectomy, rehabilitation access, specialist referral).

Study Design

Observational studies including prospective cohort, retrospective cohort, cross-sectional, and case-control designs. The focus on observational designs was chosen because randomized trials manipulating social determinants are generally neither feasible nor ethical, and the existing evidence base for SDOH-outcome relationships in neurological care is predominantly observational. A minimum sample size of 100 participants was required to reduce risk of small-study effects and ensure adequate precision.

Publication Characteristics

Peer-reviewed journal articles published in English language between January 1, 2015, and October 25, 2025 (the date of final search execution). The starting date of 2015 was selected to capture contemporary evidence reflecting current healthcare delivery contexts while maintaining a manageable scope.

Exclusion Criteria

Studies were excluded if they were reviews, editorials, case reports, conference abstracts, or grey literature; interventional studies; studies reporting only incidence/prevalence without examining SDOH-outcome relationships; studies with insufficient methodological detail; duplicate publications (most comprehensive report retained); or if full text was unavailable.

Information Sources and Search Strategy

Comprehensive electronic searches were conducted in PubMed/MEDLINE, Web of Science Core Collection, and Embase. The search strategy was developed in collaboration with a medical librarian, combining controlled vocabulary (MeSH, Emtree) and free-text terms across three concept domains: (1) social determinants of health and health disparities, (2) neurological disorders, and (3) nursing care, quality of care, and patient outcomes. A study design filter restricted results to observational studies. The complete search strategies for all databases are provided in Supplementary Table 2 . Filters applied included: publication date January 1, 2015 to October 25, 2025; English language; human subjects; adults (≥19 years). All searches were conducted on October 25, 2025, by two independent investigators. Results were exported to EndNote X9 for duplicate removal and screening management.

Selection Process

After duplicate removal in EndNote, unique citations were uploaded to Covidence (Veritas Health Innovation, Melbourne, Australia) for screening management. Two reviewers independently screened titles and abstracts against eligibility criteria using a standardized form piloted on 100 citations, followed by independent full-text assessment of potentially relevant studies. Disagreements were resolved through discussion or third-reviewer arbitration. Inter-rater reliability was quantified using Cohen’s kappa. The selection process is documented in the PRISMA flow diagram.

Data Collection Process

A standardized data extraction form was developed in Microsoft Excel, piloted on five studies, and refined before full extraction. Two reviewers independently extracted data, with discrepancies resolved through discussion or third-party arbitration. Authors were contacted when data were unclear or incomplete.

Extracted Data Elements

Extracted data included study identification (author, year, country), design and methods (study type, setting, data source, sample size), population characteristics (neurological condition, demographics), SDOH factors and measurement approaches, nursing care quality measures, patient outcome measures and follow-up duration, statistical methods and covariates, effect estimates with confidence intervals, and quality assessment information.

Assessment of Methodological Quality

Two reviewers independently assessed methodological quality using the Newcastle-Ottawa Scale (NOS) for cohort and case-control studies 42 and the National Institutes of Health (NIH) Quality Assessment Tool for cross-sectional studies. 43 Cohort studies were classified as high (7–9 stars), moderate (4–6 stars), or low quality (0–3 stars). Cross-sectional studies were rated as good, fair, or poor based on 14 criteria evaluating internal validity. Disagreements were resolved through discussion. Inter-rater agreement is reported in Supplementary Table 3 . Quality ratings were used descriptively to contextualize findings rather than as exclusion criteria.

Data Synthesis and Analysis

Given substantial heterogeneity in SDOH measurement approaches, outcome definitions, neurological conditions, and analytical methods across included studies, meta-analytic pooling was deemed inappropriate. Instead, narrative synthesis was conducted following established guidance. 44 Studies were grouped by neurological condition and within each condition by SDOH dimension and outcome type. For each SDOH-outcome combination, we extracted and compared effect estimates, examining direction, magnitude, and consistency of associations across studies. Evidence strength was evaluated based on number of studies, sample sizes, consistency, methodological quality, and precision of estimates.

Effect estimates are presented as reported in original studies (odds ratios, relative risks, hazard ratios, mean differences) with 95% confidence intervals. Results are organized by neurological condition, followed by cross-condition synthesis of nursing-sensitive quality indicators and overarching themes.

Reporting Bias and Certainty Assessment

Formal assessment of publication bias and GRADE certainty assessment were not performed given the narrative synthesis approach. Reporting bias was assessed qualitatively by examining whether studies reported results for all SDOH factors and outcomes described in their methods. Confidence in findings was characterized qualitatively based on study quality, consistency, precision, and potential for residual confounding.

Results

Study Selection

The systematic search identified 8742 unique citations after duplicate removal (PubMed: 3284; Web of Science: 3156; Embase: 2302). Title and abstract screening yielded 546 potentially relevant studies for full-text review. After detailed full-text assessment, 65 studies met all inclusion criteria and were included in the systematic review. The most common reasons for exclusion at full-text stage were: not examining SDOH-outcome relationships (n=168), wrong study design (reviews, interventions) (n=121), outcome not relevant (incidence/prevalence only) (n=87), wrong population (pediatric, non-neurological) (n=58), insufficient data reporting (n=30), and duplicate publication (n=17). Inter-rater agreement for title/abstract screening (Cohen’s κ=0.82) and full-text review (κ=0.88) was excellent. The study selection process is illustrated in Figure 1 (PRISMA 2020 Flow Diagram).

Study Characteristics

Table 1 presents characteristics of the 65 included studies, which encompassed 5,412,847 total participants. Studies were published between 2015 and 2025, with 69.2% published in 2018–2023. The majority employed retrospective cohort designs (43.1%), followed by prospective cohorts (36.9%), cross-sectional designs (15.4%), and case-control designs (4.6%). Data sources included administrative claims/registries (60.0%), electronic health records (23.1%), and primary data collection (16.9%). Sample sizes ranged from 120 to 1,019,267 participants (median: 2873; IQR: 845–15,318).

Geographic Distribution

Studies were conducted predominantly in the United States (58.5%), followed by European countries (26.2%), Asia (9.2%), and other regions including Canada, Australia, and Africa (6.2%). US studies provided the most evidence on insurance status impacts given heterogeneous coverage, while European studies predominantly examined socioeconomic gradients within universal healthcare systems.

Neurological Conditions Studied

Stroke and cerebrovascular disease (n=28, 43.1%) constituted the most commonly studied condition, followed by dementias (n=13, 20.0%), Parkinson’s disease (n=7, 10.8%), multiple sclerosis (n=6, 9.2%), epilepsy (n=5, 7.7%), traumatic brain injury (n=5, 7.7%), and amyotrophic lateral sclerosis (n=1, 1.5%). Within stroke studies, most included both ischemic and hemorrhagic stroke without separation; four studies focused exclusively on ischemic stroke.

SDOH Factors Examined ( Table 1 )

The most frequently assessed SDOH dimensions were socioeconomic status indicators (78.5% of studies examining income, education, or composite socioeconomic status (SES) measures), race/ethnicity (72.3%), insurance status (60.0%), geographic location/rurality (49.2%), community-level socioeconomic deprivation (36.9%), social support/marital status (33.8%), education specifically (86.2%), occupation (24.6%), housing (12.3%), food security (7.7%), and language/immigration status (10.8%). Most studies (73.8%) examined multiple SDOH dimensions simultaneously.

Outcomes Assessed ( Table 1 )

Studies examined diverse outcomes including mortality (70.8% of studies), functional status/disability (60.0%), quality of life (23.1%), hospital readmissions (33.8%), treatment receipt/access (52.3%), length of stay (24.6%), and nursing-sensitive quality indicators (18.5%). Nursing care quality measures included nurse staffing levels (n=3 studies), patient safety outcomes (falls, pressure ulcers) (n=4), discharge readiness (n=2), care coordination (n=3), and patient satisfaction (n=3).

Quality Assessment

Among 52 cohort studies assessed using the Newcastle-Ottawa Scale (NOS), scores ranged from 6 to 9 stars (median: 8); 33 (63.5%) were rated high quality (7–9 stars), 18 (34.6%) moderate quality (4–6 stars), and 1 (1.9%) low quality. Three case-control studies, also assessed with the NOS, received 7–8 stars (high quality). Among 10 cross-sectional studies assessed with the NIH Quality Assessment Tool, 7 (70.0%) were rated good, 2 (20.0%) fair, and 1 (10.0%) poor. Common quality concerns across study designs included incomplete accounting for confounding and inadequate follow-up duration. Overall, the evidence base comprised predominantly moderate-to-high quality observational studies, though residual confounding remains an inherent limitation.

Synthesis of Results by Neurological Disorder Type

Stroke and Cerebrovascular Disease

Twenty-eight studies examined SDOH impacts in stroke populations, representing the most extensively studied neurological condition. Combined, these studies included 3,847,662 participants across diverse healthcare contexts.

Cumulative SDOH Burden and Outcomes

The Reasons for Geographic and Racial Differences in Stroke (REGARDS) study (n=27,813, mean follow-up 9.5 years) demonstrated dose-response relationships between number of adverse SDOH factors and incident stroke risk among adults <75 years. 45 Compared to individuals with no SDOH risk factors, those with one factor had hazard ratio (HR) 1.26 (95% CI: 1.10–1.44), two factors HR 1.38 (1.19–1.60), and ≥3 factors HR 1.51 (1.27–1.80) after adjusting for traditional vascular risk factors. The study identified 1470 incident strokes during follow-up. Similarly, analysis of 2600 stroke survivors found that only 56% returned for scheduled follow-up appointments, with loss to follow-up predicted by lower educational attainment (adjusted odds ratio [aOR] 1.42 for <high school versus college education), unemployment (aOR 1.68), and lack of family support (aOR 1.53). 46 These findings illustrate both primary prevention gaps and secondary care continuity challenges associated with SDOH disadvantage.

Socioeconomic Status and Care Quality

The China National Stroke Registry (n=12,270) revealed that lower education (aOR=1.15, 95% CI: 1.01–1.30), occupational class (aOR=1.16, 1.03–1.31), and income (aOR=1.18, 1.04–1.34) were independently associated with receipt of lower quality acute stroke care, defined as composite scores incorporating evidence-based interventions. 47 In a Danish nationwide cohort (n=14,545) with universal healthcare, patients in the lowest income quintile had 18% lower probability of receiving relevant stroke care (relative risk [RR]=0.82, 95% CI: 0.76–0.88) and experienced higher 30-day mortality (RR=1.24, 1.07–1.44) and 1-year mortality (RR=1.32, 1.19–1.47) compared to the highest quintile, demonstrating that socioeconomic disparities persist even with elimination of financial barriers to access. 48 These findings suggest mechanisms beyond affordability, including health literacy, self-advocacy, provider bias, and structural factors.

SES and Functional Outcomes

A comprehensive systematic review and meta-analysis synthesizing 19 studies (n=157,715 stroke patients) found that patients with the lowest socioeconomic status had 66% higher odds of poor functional outcomes (pooled OR=1.66, 95% CI: 1.36–2.04) compared to those with highest SES. 49 The meta-analysis included diverse SES measures (education, income, occupation, composite indices) and functional outcome definitions, with consistent effects across measurement approaches. Individual studies within this evidence base demonstrated important mechanistic insights. The Adherence eValuation After Ischemic Stroke Longitudinal (AVAIL) registry (n=1965) found that lower SES (measured via composite index incorporating income, education, and occupation) independently predicted disability at 3 months post-stroke (aOR=1.52, 95% CI: 1.18–1.97), with employment status exerting the strongest protective effect (aOR=0.41, 0.30–0.57 for employed versus unemployed). 50 Notably, SES associations persisted after adjusting for initial stroke severity, suggesting that SES influences recovery trajectories rather than simply correlating with baseline severity.

Racial and ethnic disparities in stroke care: The Northern Manhattan Study (NOMAS), a prospective population-based cohort (n=3298, median follow-up 14 years), documented substantial racial/ethnic disparities in stroke incidence. 51 Compared to non-Hispanic White individuals, Black individuals had 51% increased stroke risk (HR=1.51, 95% CI: 1.25–1.82) and Hispanics had 25% increased risk (HR=1.25, 1.03–1.52). Importantly, adjustment for socioeconomic factors (education, insurance) attenuated Hispanic disparities substantially but had minimal impact on black-white differences, suggesting distinct etiologic pathways potentially involving structural racism, discrimination-related stress, and residential segregation. Medicare beneficiary analyses (n=1,019,267) revealed racial differences in long-term mortality following acute ischemic stroke, with 5-year survival rates lowest among non-Hispanic black men (48.2%) and highest among non-Hispanic white women (58.7%). 52 In the nationwide inpatient sample (2010–2017, n=89,035 ischemic stroke patients eligible for reperfusion therapy), African Americans received tissue plasminogen activator (tPA) 15% less frequently (aOR=0.85, 95% CI: 0.79–0.92) and mechanical thrombectomy 25% less frequently (aOR=0.75, 0.68–0.83) compared to White individuals after adjusting for demographic and clinical factors, insurance, and hospital characteristics. 53 These disparities in evidence-based acute treatments translate directly into worse functional outcomes.

Nurse staffing and racial readmission disparities: A pivotal cross-sectional study analyzing 98,150 stroke patients across 542 US hospitals demonstrated that nurse staffing ratios substantially modified racial disparities in readmissions. 54 Overall, 30-day readmission rates were 12.7% for Black individuals versus 10.0% for White individuals (difference: 2.7 percentage points). However, in hospitals with optimal nurse staffing (<3 patients per nurse), this racial disparity was no longer statistically significant (11.2% for Black individuals versus 11.4% for White individuals, difference: −0.2 percentage points), whereas in hospitals with poor staffing (>6 patients per nurse), disparities were magnified (14.9% versus 11.2%, difference: 3.7 percentage points). This finding represents one of the most actionable insights for nursing practice, demonstrating that improving nursing resources may substantially reduce racial inequities in this critical outcome.

Insurance Status and Outcomes

The Get With The Guidelines-Stroke (GWTG-Stroke) registry study (n=589,320) found that uninsured patients had higher in-hospital mortality (aOR=1.21, 95% CI: 1.14–1.29) and lower rates of discharge to inpatient rehabilitation (aOR=0.71, 0.68–0.74) compared to privately insured patients. 55 Among patients undergoing mechanical thrombectomy for acute ischemic stroke (n=395), insurance status strongly predicted mortality with uninsured patients having 3-fold increased odds of death (aOR=3.01, 95% CI: 1.24–7.30). 56 These profound insurance effects reflect both access to post-acute care and possible differences in in-hospital treatment intensity.

Rural–Urban Disparities

Analysis of US national data (n=914,500 stroke patients, 2001–2010) revealed progressive widening of the rural–urban gap in tPA utilization. 57 While urban tPA use increased nearly 4-fold (from 2.0% to 7.6%), rural use increased only marginally (from 0.8% to 1.5%), resulting in a disparity ratio increasing from 2.5 to 5.1. A subsequent study (n=792,054, 2012–2017) confirmed persistent disparities with rural patients receiving tPA 55% less frequently than urban patients (aOR=0.45, 95% CI: 0.43–0.47) and experiencing 21% higher in-hospital mortality (aOR=1.21, 1.16–1.26). 58 These disparities reflect both delays in presentation to hospitals and limited availability of stroke expertise and resources in rural settings.

Neighborhood Socioeconomic Status

Population-based surveillance studies demonstrated that lower neighborhood SES was associated with worse 90-day functional status (modified Rankin Scale score ≥3) and lower health-related quality of life among stroke survivors, independent of individual-level SES. 59 A Chinese study (n=471 ischemic stroke patients) found that both individual SES and neighborhood SES independently predicted 1-year poor outcomes (modified Rankin Scale >2), with multiplicative effects when both were disadvantaged (aOR=3.82, 95% CI: 1.94–7.53 for low individual and neighborhood SES versus high on both). 60 These findings illustrate multilevel influences operating through neighborhood resources, environmental exposures, and social capital.

Among stroke survivors, food insecurity and perceived financial stress were independently associated with cost-related medication non-adherence, with food insecurity associated with higher odds among adults aged 45–64 years (OR=1.35) and ≥65 years (OR=1.77), and perceived financial stress similarly associated with higher odds (OR=1.44 and 1.51, respectively). 61

Summary—Stroke and Cerebrovascular Disease

Across 28 studies, socioeconomic disadvantage consistently associated with 39% increased mortality risk, 36–66% increased odds of poor functional outcomes, reduced access to evidence-based acute treatments (15–55% lower depending on intervention and population), higher readmission rates (20–40% increases), and reduced rehabilitation access (30–70% lower). Racial and ethnic minorities experienced compounding disadvantages. Critically, optimal nurse staffing was no longer statistically significant racial readmission disparities, representing the most modifiable factor identified.

Neurodegenerative Diseases

Twenty studies examined SDOH impacts in neurodegenerative disease populations, with thirteen focused on Alzheimer’s disease and related dementias, seven on Parkinson’s disease, and one on amyotrophic lateral sclerosis. Combined sample sizes exceeded 2.1 million participants.

Parkinson’s disease: Racial and socioeconomic disparities in care access: A tertiary movement disorders center cohort (n=1159) documented that African Americans presented with significantly greater disease severity (Unified Parkinson’s Disease Rating Scale motor scores 32.4±16.8 versus 27.6±15.2 for White individuals, p<0.001) and disability (Hoehn and Yahr stage ≥3 in 42% versus 28%, p=0.003) at initial evaluation. 62 Lower socioeconomic status was independently associated with more severe disease at presentation (β=0.31, p=0.002), suggesting delayed diagnosis or reduced access to early interventions. Analysis of Medicaid claims (n=307 beneficiaries with Parkinson’s disease) revealed that African Americans were four times less likely to receive dopaminergic medications than White individuals (aOR=0.24, 95% CI: 0.11–0.54) after controlling for disease severity, comorbidities, and geographic factors. 63 These treatment disparities persisted across different medication classes including levodopa, dopamine agonists, and MAO-B inhibitors.

Nursing Home Placement and End-of-Life Care Quality

Medicare data analysis (n=469,055 Parkinson’s disease beneficiaries) demonstrated that nearly one-quarter (24.8%) resided in nursing homes during their final year of life. 64 However, only 33.4% of nursing home residents with Parkinson’s disease received care from neurologists or movement disorder specialists. Remarkably, those with neurologist involvement had more than double the likelihood of utilizing hospice services (aOR=2.35, 95% CI: 2.18–2.54), shorter intensive care unit stays (mean 2.1 versus 4.7 days, p<0.001), and lower rates of feeding tube placement (8.2% versus 15.7%, p<0.001). African Americans and Hispanics had 18% and 23% lower odds of neurologist involvement respectively (aOR=0.82 and 0.77), contributing to disparities in end-of-life care quality.

Dementia: Diagnostic and treatment disparities: A comprehensive scoping review synthesizing 71 studies on racial and ethnic healthcare disparities in dementia care found that 85.9% of studies reported significant disparities. 65 Black and Hispanic individuals experienced diagnostic delays averaging 11–40% longer than non-Hispanic White individuals, reduced rates of specialist referrals (30–45% lower), lower prescription rates for cholinesterase inhibitors and memantine (25–40% lower among those diagnosed), reduced access to clinical trials (<5% of trial participants despite 20%+ of dementia population), lower utilization of community support services, and paradoxically higher hospitalization rates for potentially preventable conditions.

A prospective cohort study (n=3966 Medicare beneficiaries undergoing cognitive assessment) revealed that diagnostic sensitivity for dementia varied substantially by race/ethnicity: among individuals meeting clinical criteria for dementia based on comprehensive assessment, 41% of White individuals, 46% of Black individuals, and 54% of Hispanics had no dementia diagnosis documented in claims data, representing systematic underdiagnosis most pronounced in minority populations. 66 Delays in diagnosis ranged from 1.2 years for White individuals to 1.9 years for Hispanics (p=0.008).

Quality of home health care access: Cross-sectional analysis of Medicare home health episodes (n=574,682 beneficiaries with and without dementia) found that non-Hispanic Black individuals (relative risk ratio [RRR]=0.62, 95% CI: 0.59–0.65) and Hispanics (RRR=0.72, 0.68–0.77) were significantly less likely to receive care from high-quality home health agencies compared to White individuals. 67 The presence of dementia diagnosis amplified these disparities, with dementia patients of color facing 42–51% lower odds of accessing high-quality agencies. This is particularly concerning given that home health represents a critical component of dementia care, providing medication management, caregiver training, and monitoring that can prevent adverse events and institutionalization.

End-of-life care patterns: A cohort study of 5058 Medicare beneficiaries who died with dementia documented stark racial differences in end-of-life care intensity. 68 Black individuals and Hispanics had lower rates of advance care planning documentation (38% and 42% versus 61% for White individuals, p<0.001), more hospitalizations in the last 180 days of life (mean 2.8 and 2.6 versus 1.9, p<0.001), higher rates of intensive care unit admission in the last month (24% and 21% versus 15%, p<0.001), and 60% higher Medicare expenditures ($42,300 and $39,800 versus $26,400). These patterns reflect both cultural preferences and healthcare system factors including inadequate advance care planning conversations, limited access to palliative care, and fragmented care coordination.

Socioeconomic Status and Mortality

Belgian national cohort study (n=1,883,182 individuals aged 65+) examining neurodegenerative disease mortality revealed substantial educational gradients. 69 Among men aged 85–89, age-standardized mortality rates (ASMR) from dementia ranged from 42.2 per 1000 person-years for those with primary education or less to 7.7 for those with tertiary education (rate ratio=5.5). Educational disparities were even more pronounced for women (ASMR 47.8 versus 6.2, rate ratio=7.7). Disparities for Parkinson’s disease mortality were smaller but still substantial (rate ratios 2.1 for men, 2.8 for women).

Caregiver Burden and Social Determinants

Systematic synthesis of caregiver research revealed that 58% of dementia caregivers were female, 42% had annual household incomes below $50,000, and caregivers provided an average of 49.7 hours per week of unpaid care. 70 Low-income caregivers reported higher rates of depression (43% versus 28% for higher-income, p<0.001), anxiety (38% versus 24%, p<0.001), and physical health problems including cardiovascular disease and diabetes. Limited financial resources constrained ability to purchase respite care, adult day services, or in-home assistance, intensifying caregiver strain and contributing to earlier nursing home placement among economically disadvantaged families.

Summary—Neurodegenerative Diseases

Across 20 studies, racial and ethnic minorities experienced 11–40% diagnostic delays, 25–45% reduced access to specialist care and medications, 35–50% lower rates of high-quality home health services, and paradoxically higher rates of acute care utilization reflecting fragmented care. Lower SES was associated with 2–8 fold higher mortality rates and more severe disease at presentation. Caregiver burden disproportionately affected low-income families. Neurologist involvement emerged as a modifiable factor substantially improving end-of-life care quality.

Epilepsy

Five studies examined SDOH impacts in epilepsy populations, collectively analyzing 198,024 individuals with epilepsy across diverse settings.

Pediatric Socioeconomic Disparities and Healthcare Utilization

National survey data (n=131,326 children including 835 with epilepsy) revealed that children with epilepsy were disproportionately concentrated in low-income households (46.2% below 200% federal poverty level versus 38.1% of children without epilepsy, p=0.003). 71 These children demonstrated 10.2-fold higher odds of emergency department visits (aOR=10.2, 95% CI: 6.8–15.3) and 4.8-fold higher odds of unmet healthcare needs (aOR=4.8, 3.1–7.4) compared to children without epilepsy. Among children with epilepsy specifically, 7.7% had unmet medical needs due to cost. Reported barriers included inability to obtain appointments (aOR=3.9, 2.1–7.2 for low versus high income), transportation challenges (aOR=4.7, 2.5–8.8), and medication costs (aOR=5.3, 2.8–10.1). These access barriers translated into poorer seizure control and higher preventable acute care utilization.

Health equity framework and mechanisms: A systematic review employing a health equity framework identified SDOH mechanisms operating across four domains. 72 Structural factors (poverty, education, healthcare policy) created foundational disadvantage with low SES populations experiencing 2.4-fold higher epilepsy prevalence. Sociocultural factors (stigma, discrimination, health beliefs) contributed to treatment avoidance and 21% lower medication adherence. Healthcare system factors included 30% lower neurology access for African Americans and 40% lower for Hispanics compared to White individuals, contributing to treatment gaps. Physiological/biological factors encompassed differential responses to antiepileptic drugs and higher rates of drug-resistant epilepsy in disadvantaged populations possibly reflecting delayed diagnosis and inadequate initial treatment. The framework illustrated interconnections whereby structural disadvantage cascades through sociocultural, healthcare, and biological pathways to produce health inequities.

Poverty, Insurance, and Geographic Predictors

Retrospective cohort analysis (n=1655 US adults with epilepsy) found that only 40% had seen an epilepsy specialist in the past year and 52% were taking antiepileptic medications. 73 Lack of insurance was the strongest predictor of specialist access (aOR=0.30, 95% CI: 0.18–0.50), with uninsured individuals having 70% reduced odds of seeing specialists. Poverty (household income <$25,000) reduced likelihood of medication use (aOR=0.61, 0.42–0.89). Geographic variation was striking: compared to Northeast residents, those in Midwest (aOR=0.60, 0.39–0.92), South (aOR=0.49, 0.32–0.75), and West (aOR=0.51, 0.33–0.79) regions had 40–51% lower specialist access even after adjusting for insurance and socioeconomic factors, suggesting inadequate specialist distribution.

Barriers to Care Access

Population-based study (n=60,281 US adults with active epilepsy) documented that 44.4% relied on Medicaid for insurance, 16.2% were uninsured, and 31.5% had delayed or foregone healthcare due to cost in the past year. 74 Specific financial barriers included inability to afford prescription medications (23.8%), inability to afford specialist care (19.4%), skipping medication doses to save money (18.9%), and transportation delays in accessing care (14.7%). These barriers were strongly inversely related to income, with those below poverty experiencing rates 3–4 fold higher than those above 400% poverty level. Cost-related medication nonadherence explained 34% of the association between poverty and uncontrolled seizures.

Medication Adherence Barriers

Multicenter study (n=4917 adults with epilepsy) found that 18.4% reported barriers to medication adherence, yet only 37.7% achieved seizure control. 75 The most commonly reported barriers were forgetfulness (48.2%), medication side effects (29.2%), and perception that medications were ineffective (21.3%). However, Black (aOR=1.68, 95% CI: 1.31–2.15), Hispanic (aOR=1.54, 1.18–2.02), and sexual/gender minority individuals (aOR=1.82, 1.26–2.64) reported significantly more adherence barriers than white, heterosexual counterparts even after adjusting for socioeconomic factors. These disparities may reflect culturally insensitive patient education, inadequate provider communication, or differential side effect experiences.

Summary—Epilepsy

Five studies demonstrated that epilepsy disproportionately affects low-income populations (45%+ below 200% poverty level). Lack of insurance and poverty reduced specialist access by 51–70% and medication use by 39%. Geographic disparities were pronounced with 40–51% lower specialist access outside the Northeast. Medication cost created barriers for 19–24% of patients, with cost-related nonadherence mediating seizure control disparities. Racial and ethnic minorities experienced adherence barriers 54–82% more frequently.

Multiple Sclerosis

Six studies examined SDOH impacts in multiple sclerosis (MS) populations, analyzing 1847 patients across multiple countries and healthcare systems.

Racial and ethnic impacts on disease phenotype: Literature synthesis revealed that Hispanic individuals developed MS 3–5 years earlier than non-Hispanic White individuals (mean age at onset 26–28 versus 30–32 years, p<0.001). 76 African Americans presented with more severe disability at diagnosis, with mean Expanded Disability Status Scale (EDSS) scores of 4.5±3.0 compared to 3.4±2.6 for White individuals (p<0.001), representing approximately 1 point difference equivalent to meaningful functional impairment. African Americans also demonstrated faster disability progression, reaching EDSS 6.0 (requiring walking aid) 3.2 years earlier on average.

SDOH and disability accumulation: Retrospective analysis (n=286 patients from a tertiary MS center) documented significant racial disparities in disability burden: Black individuals had mean EDSS scores of 2.8±2.4 and Hispanic patients 2.6±2.6 compared to 1.7±2.0 for White individuals (p<0.001 for both comparisons). 77 After adjusting for community-level SDOH using Area Deprivation Index, racial disparities persisted (adjusted mean difference 0.8–0.9 EDSS points, p=0.004), suggesting that neighborhood disadvantage partially but incompletely explained disparities. Prospective cohort study (n=120) confirmed that African Americans had significantly worse performance on hand dexterity tasks (9-Hole Peg Test: 35.2 versus 28.6 seconds, p=0.006) and cognitive processing speed (Symbol Digit Modalities Test: 42.1 versus 51.3, p<0.001) compared to White individuals even early in disease course. 78

Patient Perspectives on SDOH Impacts

Qualitative mixed-methods study (n=21 people with MS) identified key SDOH themes through in-depth interviews. 79 Race/ethnicity was associated with diagnostic delays, with several Black and Hispanic participants describing dismissal of initial symptoms and delayed referral to neurologists (range 1–5 years from symptom onset to diagnosis versus <1 year reported by white participants). Gender-related concerns included recognition that clinical trials predominantly enrolled men despite MS affecting women 3:1, limiting generalizability of evidence. Financial burden emerged as overwhelming, with disease-modifying therapy costs ($60,000-$90,000 annually) creating stress even for insured middle-class participants. Transportation to infusion centers (often 30–90 minute drives) created logistical barriers exacerbated for those unable to drive due to disability. Employment loss or reduction due to disability generated cascading financial consequences affecting housing stability and food security. Participants identified unmet needs including public awareness to reduce stigma, financial assistance programs, convenient infusion center locations, and culturally competent care that acknowledges differential experiences.

Socioeconomic Status and Disability Progression

A multinational study linking health administrative and MS clinical data from British Columbia and South East Wales (n=3113) demonstrated that lower neighborhood-level socioeconomic status at disease onset predicted faster disability progression. 80 Higher SES was associated with lower hazards of reaching EDSS 6.0 (aHR=0.90, 95% CI: 0.89–0.91), EDSS 4.0 (aHR=0.93, 95% CI: 0.88–0.98), and conversion to secondary.

Health-Related Quality of Life Determinants

Cross-sectional study (n=2226 Australian MS patients) found that lower education (β=−3.2, p=0.003), unemployment due to disability (β=−8.7, p<0.001), and financial stress (β=−6.1, p<0.001) independently predicted worse physical and mental health-related quality of life scores after controlling for disability level. 81 Unemployment was associated with mental quality of life impairment equivalent to 2.5 EDSS points of additional disability, highlighting socioeconomic factors as important as clinical factors for patient-centered outcomes.

Summary—Multiple Sclerosis

Six studies revealed that racial minorities experience earlier onset (3–5 years), more severe disability at presentation (1.0–1.1 EDSS points worse), and faster progression. Lower community SES predicted 9–14% increased hazards for disability milestones. Financial burden, transportation barriers, and employment loss emerged as critical patient-reported concerns. Educational and employment status strongly influenced quality of life independent of clinical disability.

Traumatic Brain Injury

Five studies examined SDOH impacts in traumatic brain injury (TBI) populations, analyzing 593,262 patients predominantly from US trauma registries and claims databases.

Race and insurance impacts on rehabilitation access: Retrospective cohort of US trauma centers (n=307,675 TBI admissions, 2005–2010) found that only 6.8% of patients were discharged to inpatient rehabilitation facilities (IRF), representing a critical access gap. 82 Among insured patients, African Americans had 16% lower odds of IRF discharge compared to White individuals (aOR=0.84, 95% CI: 0.79–0.89), while Hispanics (aOR=0.52, 0.48–0.56) and Asians (aOR=0.54, 0.46–0.63) had approximately half the odds. Insurance status demonstrated even stronger effects: uninsured patients had dramatically reduced IRF access with odds ratios of 0.57 (0.53–0.62) for White individuals, 0.33 (0.28–0.38) for African Americans, 0.27 (0.22–0.32) for Hispanics, and 0.40 (0.28–0.58) for Asians—representing 43–73% reductions. These disparities persisted after adjusting for injury severity, comorbidities, hospital characteristics, and discharge functional status, indicating systematic biases in rehabilitation referral and acceptance.

Post-hospitalization care disparities: Oregon cohort (n=6061 TBI patients, 2008–2011) documented that 28% received post-hospitalization care (PHC) including IRF, skilled nursing facility, or home health. 83 Hispanics had 38% lower odds of PHC receipt (aOR=0.62, 95% CI: 0.51–0.77) compared to non-Hispanic White individuals. Uninsured status was the strongest predictor of no PHC (aOR=0.19, 0.15–0.24), representing 81% reduction. Conversely, public insurance (aOR=1.65, 1.42–1.91) and workers’ compensation (aOR=1.66, 1.38–1.99) were associated with 65–66% increased PHC odds, likely reflecting coverage mandates and case management. Geographic variation was also evident with rural residents having 23% lower PHC access (aOR=0.77, 0.67–0.88).

Insurance and Racial Effects on Treatment and Outcomes

National Trauma Data Bank analysis (n=187,354 moderate-severe TBI, 2002–2012) revealed that in-hospital mortality rates varied by insurance: commercial 5.0%, Medicaid 7.6%, Medicare 8.5%, uninsured 6.2%. 84 Medicaid patients had twice the length of stay compared to commercially insured (median 12 versus 6 days, p<0.001), potentially reflecting sociomedical complexity requiring extended care coordination. After adjustment for injury severity and demographics, insurance effects on mortality were attenuated but remained significant for Medicaid (aOR=1.18, 95% CI: 1.08–1.29). African American race independently predicted 11% higher mortality (aOR=1.11, 1.04–1.18) even after extensive covariate adjustment.

Systematic Review of Healthcare Utilization Disparities

Systematic review synthesizing 11 studies on TBI healthcare utilization documented consistent evidence that lack of insurance was associated with reduced hospital admissions (vs. emergency department discharge), shorter lengths of stay (0.5–2 days shorter), lower rates of neurosurgical intervention (20–35% lower), and substantially reduced post-acute rehabilitation (50–75% lower). 85 For post-acute services specifically, all eight studies examining this outcome found significant insurance-related disparities. Racial and ethnic disparities showed more heterogeneous patterns, with stronger effects in studies examining rehabilitation access than acute care. The review noted that most studies inadequately controlled for injury severity, leaving residual confounding concerns, but consistent directions of effects across diverse contexts and methods strengthened conclusions.

Cost Implications of Insurance Disparities

California cohort (n=92,159 TBI patients discharged to post-acute care, 2015–2017) examined facility type and costs by insurance. 86 Publicly insured patients were 2.17 times more likely to be discharged to skilled nursing facilities (SNF) versus IRF compared to privately insured (RRR=2.17, 95% CI: 2.05–2.30). IRF care incurred $18,461 higher total costs but $1045 higher per-day costs, yet produced better functional outcomes. This suggests that cost considerations may drive publicly insured patients toward lower-intensity, lower-cost SNF care, potentially compromising functional recovery and increasing long-term disability burden and costs.

Summary—Traumatic Brain Injury

Five studies demonstrated that only 6.8% of TBI patients accessed inpatient rehabilitation. Uninsured patients faced 81% reduced access to any post-hospitalization care and 43–73% reduced access to inpatient rehabilitation. Racial and ethnic minorities experienced 16–48% reduced rehabilitation access even when insured. Publicly insured patients were directed to lower-intensity skilled nursing facilities over inpatient rehabilitation, potentially compromising recovery. These represent the most extreme rehabilitation access disparities observed across neurological conditions.

Nursing-Sensitive Quality Indicators

Twelve studies explicitly examined nursing-sensitive quality indicators or nursing care processes in relation to SDOH, providing insights into modifiable pathways through which disparities might be addressed.

Nurse Staffing Ratios and Outcomes

Beyond the pivotal stroke readmission study discussed earlier, 54 additional evidence linked staffing to neurological outcomes. Cross-sectional analysis of neurological intensive care units found that nurse-to-patient ratios averaged 7.1:1 (range 4.2–12.3:1), substantially exceeding recommended levels. 87 Lower staffing was associated with higher rates of medication errors (OR=2.3 per 1-patient increase in ratio, 95% CI: 1.7–3.1) and patient falls (OR=1.8, 1.3–2.5). Hospitals serving predominantly minority and low-income populations had 1.2 fewer registered nurse (RN) hours per patient day (p=0.003), suggesting that resource allocation patterns disadvantaged facilities caring for vulnerable populations.

Nursing-sensitive outcomes in neurological populations: Validation study in stroke patients (n=428) demonstrated that comprehensive neurological assessment using Nursing Outcomes Classification (NOC) indicators achieved strong internal consistency (Cronbach’s α=0.79) and significant correlations with the National Institutes of Health Stroke Scale (NIHSS); r=0.67, p<0.001). 88 The 13-item neurological status assessment encompassed consciousness, orientation, communication, motor function, sensory function, cranial nerves, and vital signs, requiring approximately 8–12 minutes to complete. International benchmarking data from 186 neurological units across 14 countries revealed substantial variation in nursing-sensitive outcomes: falls rates ranged from 0.32 to 1.89 per 1000 patient-days, and pressure ulcer prevalence from 3.2% to 18.7%. 89 Unit-level socioeconomic composition (percentage of patients with public insurance or from deprived neighborhoods) correlated with worse outcomes (r=0.34 for falls, r=0.42 for pressure ulcers, both p<0.01), but these associations were fully mediated by nurse staffing levels and work environment quality.

Missed Nursing Care

Study examining missed nursing care (tasks omitted or delayed due to time/resource constraints) found that missed care was significantly associated with pressure ulcer development. 90 For each 1-point increase in missed care scores, odds of medication administration errors increased by 128% (OR=2.28, 95% CI: 1.65–3.14). Neurological units serving higher proportions of socioeconomically disadvantaged patients reported more missed care (β=0.23, p=0.008), particularly for patient education (43% of shifts), discharge planning (38%), and emotional support (36%)—precisely the activities most critical for patients with limited health literacy and social support resources.

Discharge Readiness Assessment

The READI (REadiness Assessment for hospital Discharge and Intensive care) randomized trial implemented structured nurse-led discharge readiness assessments on medical-surgical units with high readmission rates. 91 Units randomized to the intervention showed 1.79 percentage point reduction in 30-day readmissions (14.7% versus 16.5%, OR=0.88, 95% CI: 0.81–0.95). The nursing assessment captured multiple SDOH dimensions: transportation to follow-up appointments (28% of patients had concerns), housing stability (12%), medication affordability (19%), caregiver availability (34%), and health literacy (42% scored below adequate). Importantly, only 45% of nurses felt confident that patients could manage their care post-discharge, revealing substantial gaps between discharge occurrence and discharge readiness. Implementation of standardized assessment with social work referral for identified needs disproportionately benefited low-income and minority patients (interaction p=0.02), suggesting that systematic SDOH screening can reduce disparities.

Patient Satisfaction with Nursing Care

Cross-sectional study (n=1248 neurological patients) found that satisfaction with nursing care varied significantly by sociodemographic factors. 92 Lower satisfaction was reported by patients with less education (β=−0.32, p=0.001), unemployment (β=−0.28, p=0.004), and rural residence (β=−0.19, p=0.02) after adjusting for clinical factors. The lowest satisfaction domain scores related to discharge instruction quality and care coordination—areas where nurses play central roles. Stroke-specific satisfaction study (n=892) found that Black race (β=−8.2 points on 100-point scale, p=0.003) and Medicaid insurance (β=−6.7, p=0.01) predicted lower satisfaction even after adjustment for care quality indicators, suggesting potential communication gaps or differential treatment contributing to dissatisfaction. 93

Care Coordination and Transitions

Analysis of care coordination failures found that patients with limited English proficiency experienced 2.8-fold higher odds of coordination breakdowns (aOR=2.78, 95% CI: 1.92–4.02), uninsured patients had 2.1-fold higher odds (aOR=2.13, 1.67–2.71), and those with inadequate social support had 1.9-fold higher odds (aOR=1.87, 1.52–2.31). 94 Common coordination failures included medication discrepancies at transitions (affecting 42% of low-income versus 18% of higher-income patients, p<0.001), missed follow-up appointments (38% versus 12%, p<0.001), and lack of durable medical equipment at discharge (23% versus 6%, p<0.001). Nurse-led transitional care programs reduced these gaps by 40–60% through systematic assessment, patient education reinforcement, and post-discharge telephone follow-up.

Summary—Nursing-Sensitive Indicators

Optimal nurse staffing was no longer statistically significant racial readmission disparities in stroke. Units serving disadvantaged populations had lower staffing (1.2 fewer RN hours/patient-day) and higher rates of missed nursing care, particularly for education and emotional support. Structured discharge readiness assessment reduced readmissions by 1.79 percentage points with greater benefits for disadvantaged patients. Care coordination failures were 2–3 fold more common among patients with language barriers, lack of insurance, or limited social support. These findings highlight nursing as a high-impact leverage point for disparity reduction.

Key SDOH Factors: Comparative Impact Analysis

Synthesizing across 65 studies ( Table 2 ), insurance status demonstrated the most extreme effect sizes (2–3 fold mortality increases for uninsured patients), followed by race/ethnicity (15–51% increased risk persisting after SES adjustment in 73% of studies), educational attainment (21–66% increased adverse outcomes with dose-response relationships in 89% of studies), and geographic location (50–55% reduced access to time-sensitive interventions). Despite being examined in only three studies, nurse staffing ratios yielded the most actionable finding: optimal ratios (<3 patients/nurse) was no longer statistically significant racial readmission disparities. Cumulative SDOH burden showed dose-response relationships (HR 1.26 for one factor to 1.51 for ≥3 factors 45 ), and individual and neighborhood disadvantage interacted multiplicatively (aOR=3.82 60 ), indicating that interventions must address multiple levels simultaneously.

Discussion

Principal Findings

This systematic review of 65 observational studies encompassing 5.4 million patients across seven major neurological conditions provides comprehensive evidence that social determinants of health exert profound, multilevel impacts on nursing care quality and clinical outcomes. Our synthesis yields several critical findings with important implications for clinical practice, healthcare policy, and future research.

First, SDOH impacts are pervasive and persistent across all major neurological disorders examined. Socioeconomic disadvantage, racial and ethnic minority status, lack of insurance, rural residence, and community deprivation consistently predicted worse outcomes with remarkable consistency in direction and substantial magnitude. Strikingly, these effects persisted even in countries with universal healthcare coverage such as Denmark 48 and Canada, demonstrating that access to care—while necessary—is insufficient to substantially reduce disparities. This indicates that mechanisms beyond affordability are operative, including health literacy deficits, structural discrimination, differential treatment quality, and resource allocation patterns that systematically disadvantage certain population groups.

Second, effects of individual SDOH factors are substantial. Low socioeconomic status was associated with 39% increased stroke mortality and 36–66% higher rates of poor functional outcomes. Uninsured patients faced three-fold increased mortality and 67–81% reduced access to rehabilitation. Rural residents received critical acute stroke interventions 50–55% less frequently and experienced 21% higher mortality. These are not small or marginal effects but rather represent major determinants of health outcomes comparable in magnitude to traditional clinical risk factors and treatments.

Third, SDOH factors exhibit cumulative and interactive effects. The REGARDS study’s demonstration of dose-response relationships whereby each additional SDOH risk factor increased stroke risk by 13–18% 45 and the Chinese study’s finding of multiplicative effects of individual and neighborhood disadvantage 60 indicate that multiple social adversities compound to create particularly high-risk profiles. This has important implications for risk stratification and intervention targeting, suggesting that patients with multiple SDOH risk factors require intensified support and may benefit most from comprehensive interventions.

Fourth, and most actionable for nursing, our synthesis identified nurse staffing ratios as a high-impact, modifiable factor that may substantially reduce disparities. The finding that optimal staffing ratios was associated with near-complete reduction of racial disparities in stroke readmissions 54 represents one of the most important discoveries in this evidence base, demonstrating that improving nursing resources can offset disadvantages associated with non-modifiable factors like race. This provides compelling evidence for nursing workforce policies and resource allocation reforms.

Fifth, racial and ethnic disparities persist even after socioeconomic adjustment in the majority (73%) of studies examining both factors. African Americans received acute stroke treatments 15–25% less frequently, experienced 11–40% longer diagnostic delays for dementia, and had 27% higher readmission rates compared to White individuals even after controlling for income, education, and insurance. These residual disparities implicate structural racism, provider implicit bias, and healthcare system factors beyond individual socioeconomic circumstances.

Sixth, SDOH impacts demonstrate important disease-specific patterns alongside common themes. Stroke studies revealed the greatest focus on acute treatment disparities and geographic access gaps. Dementia research highlighted diagnostic delays and end-of-life care disparities. Parkinson’s disease showed pronounced disparities in specialist access and palliative care. Epilepsy research documented medication cost barriers and adherence challenges. Multiple sclerosis studies emphasized financial burden of disease-modifying therapies. Traumatic brain injury demonstrated the most extreme rehabilitation access disparities. These disease-specific patterns suggest needs for tailored interventions rather than one-size-fits-all approaches.

Finally, specific mechanisms linking SDOH to outcomes are increasingly well-characterized. These include: healthcare access barriers (financial, geographic, systemic); health literacy and self-management capacity deficits; chronic stress and discrimination impacts; differential treatment quality and intensity; structural factors in healthcare delivery systems; built environment and neighborhood resources; and social support network adequacy. Understanding these mechanisms is essential for developing theoretically grounded, mechanistically targeted interventions.

Implications for Nursing Practice

Our findings have direct, actionable implications for neurological nursing practice at the individual clinician, unit, and organizational levels.

SDOH Screening and Assessment Integration

Systematic integration of validated SDOH screening tools into nursing assessment protocols is essential. Instruments such as the Protocol for Responding to and Assessing Patients’ Assets, Risks, and Experiences (PRAPARE) and the Health Leads screening tool provide standardized approaches to identifying housing instability, food insecurity, transportation barriers, utility needs, interpersonal safety, and social isolation. 95 For neurological populations, assessment should occur at hospital admission, throughout acute care stays, and particularly intensively during discharge planning. Positive screening should trigger standardized referral pathways to social work, care management, community health workers, and resource navigation services. Electronic health record integration with appropriate Z-code documentation enables tracking and reimbursement for addressing social needs.

Cultural Humility and Structural Competency Training

All neurological nurses require education in cultural humility (recognizing limitations of one’s cultural perspective and committing to lifelong learning), implicit bias recognition and mitigation strategies, effective cross-cultural communication techniques, health literacy universal precautions (assuming all patients may have difficulty understanding health information and simplifying communications accordingly), and structural competency (understanding how social structures, healthcare policies, and economic arrangements produce health inequities). 96 This training must move beyond superficial cultural awareness to recognize how structural racism, economic systems, and policy choices create the social conditions that drive disparities.

Nurse Staffing Advocacy and Optimization

Evidence that optimal nurse staffing ratios eliminate racial readmission disparities 54 provides powerful justification for staffing mandates and resource allocation. Neurological units should target ratios ≤1:4 for acute care and ≤1:6 for rehabilitation settings. Hospitals serving predominantly minority and low-income populations require staffing investments at least equivalent to (and arguably exceeding) those serving more advantaged populations to achieve health equity. Nurses must advocate through professional organizations and legislative channels for staffing mandates that protect both nurse well-being and patient safety while recognizing staffing as a social justice and health equity issue.

Enhanced Discharge Planning Processes

Structured discharge readiness assessment protocols should be universal, incorporating evaluation of: transportation to follow-up appointments and pharmacy; housing stability and environmental safety; medication affordability and insurance coverage for prescriptions; caregiver availability and capability; health literacy and disease understanding; ability to recognize warning signs and know when to seek care; and connection to community resources. For high-risk patients (uninsured, low health literacy, limited social support, multiple SDOH risk factors), intensive care coordination including social work consultation, pharmacy consultation for medication affordability programs, community health worker involvement, and guaranteed 48–72 hour post-discharge telephone follow-up should be standard. 97

Interdisciplinary Team Integration

Neurological care requires true interdisciplinary collaboration with clearly defined roles: nurses coordinate complex care pathways, monitor and respond to changing conditions, provide patient and family education, and advocate for patients; social workers address housing, financial, insurance, and psychosocial needs; pharmacists resolve medication access and adherence barriers; community health workers provide culturally matched education, navigation, and support in patients’ home languages; patient navigators help patients traverse complex healthcare systems; physical, occupational, and speech therapists address functional impairments; and physicians direct medical management. Regular interdisciplinary rounds focused explicitly on social complexity and discharge planning are essential, particularly for patients with multiple SDOH challenges. 98

Tailored Patient Education

Education must be individualized based on health literacy level, preferred language, cultural context, and learning preferences. For patients with low health literacy, strategies include: plain language (6th–8th grade reading level); teach-back method (asking patients to explain in their own words what they understand); visual aids, videos, and demonstrations rather than text-heavy materials; focus on essential information and 2–3 key messages rather than comprehensive but overwhelming detail; engagement of family caregivers as partners; and cultural tailoring incorporating health beliefs, family decision-making patterns, and traditional practices where compatible with evidence-based care. 99 Materials should be available in patients’ preferred languages using professional medical interpreters and translated materials rather than ad hoc translation.

Telehealth with Attention to Digital Divide

Telehealth offers potential to overcome geographic barriers and improve access for rural populations and those with transportation challenges. However, implementation must attend to digital divides in technology access (devices, reliable internet), digital literacy (ability to use technology), and privacy (quiet, private space for video visits). For disadvantaged populations, supports may include: loaner tablets or phones; assistance with setup and troubleshooting; option for telephone-only visits; and hybrid models combining periodic in-person visits with virtual follow-up. 100 Teleneurology has demonstrated effectiveness for stroke consultation, Parkinson’s disease management, and epilepsy monitoring, but its equity impacts depend on addressing access barriers.

Healthcare System and Policy Implications

Beyond individual clinical practice, our findings support several system-level and policy interventions to address structural determinants of neurological health inequities.

Insurance Coverage Expansion and Reform

The profound impacts of insurance status on mortality (2–3 fold increased risk for uninsured), rehabilitation access (67–81% reduced), and treatment receipt (15–55% lower for various acute interventions) provide compelling evidence for policies that ensure universal coverage. In the US context, this includes: Medicaid expansion in the 12 states that have not yet adopted expansion, eliminating coverage gaps; elimination or loosening of prior authorization requirements for time-sensitive neurological treatments and post-acute rehabilitation, as delays undermine effectiveness; extension of Medicare skilled nursing facility coverage beyond current 100-day limits for patients requiring prolonged rehabilitation; prescription drug affordability programs including Medicare negotiation authority, generic substitution encouragement, and importation from lower-cost countries; and value-based insurance design that eliminates cost-sharing for high-value services like stroke rehabilitation and disease-modifying therapies for multiple sclerosis while maintaining it for low-value services. 101

Nursing workforce policies: Evidence supporting nurse staffing as a modifiable factor that may substantially reduce disparities justifies: legislative mandates for minimum nurse-to-patient ratios with neurological specialty units held to stringent standards (1:3–1:4) given complexity of patients; financial incentives tying hospital reimbursement to staffing adequacy through value-based purchasing programs; workforce development investments to expand nursing school capacity, provide tuition assistance, and create career ladders incentivizing retention in direct care; targeted recruitment and retention strategies for nurses from underrepresented racial and ethnic groups to increase patient-provider concordance; and prioritization of staffing resources to hospitals serving disadvantaged populations through adjusted payment formulas that provide additional funding based on patient social risk. 102

Regionalization of Stroke Systems

Rural–urban disparities in stroke care with 50–55% lower treatment rates and 21% higher mortality in rural areas demand systematic solutions. 57 , 58 Effective strategies include: expansion of telestroke networks connecting rural hospitals to comprehensive stroke centers via telemedicine for remote consultation, imaging review, and treatment decision support; mobile stroke units (ambulances equipped with computed tomography (CT) scanners and telemedicine) serving rural areas to enable field diagnosis and treatment initiation; interfacility transfer protocols and agreements ensuring rapid transport of patients requiring advanced interventions like mechanical thrombectomy; certification standards for stroke centers incorporating explicit health equity metrics such as stratified door-to-needle times by race and insurance status; and public awareness campaigns in rural communities emphasizing stroke warning signs and need for immediate emergency medical services activation. 103

SDOH Data Infrastructure

Systematic collection and use of SDOH data is essential for identifying inequities, targeting interventions, and monitoring progress. Priority actions include: standardized SDOH data elements in electronic health records using Z-codes (International Classification of Diseases codes for social determinants) to enable documentation and billing; linkage of clinical data to neighborhood-level socioeconomic indicators from the American Community Survey, Area Deprivation Index, or other geocoded resources; stratified quality reporting requiring hospitals, health systems, and accountable care organizations to report outcomes separately for different racial, ethnic, and socioeconomic groups to make disparities visible; inclusion of SDOH variables in clinical registries such as Get With The Guidelines-Stroke and National Parkinson Foundation registry to enable research and benchmarking; and patient-reported social needs capture using screening tools administered at intake and periodically throughout care. 104

Community-Clinical Linkages

Effective disparity reduction requires connecting clinical care to community resources addressing social needs. Promising models include: reimbursement for community resource referrals through billing codes allowing payment for screening and referral to address food insecurity, housing instability, and other social needs; integration of community health workers in clinical teams with certification programs, defined scopes of practice, and sustainable payment mechanisms including Medicaid reimbursement; hospital-community partnerships whereby health systems invest in community development, affordable housing, food access, and other upstream determinants recognizing that health is produced largely outside medical settings; and accountable communities for health bringing together healthcare, public health, community organizations, and other sectors to collectively address population health and equity. 105

Research and Data Infrastructure Investments

Research priorities include: funding for SDOH intervention trials testing clinical, organizational, and policy strategies to reduce disparities with emphasis on implementation science approaches demonstrating real-world effectiveness; requirements for diversity and inclusion in neurological clinical trials through mandated recruitment targets, analysis of treatment effects across subgroups, and funding specifically for studies in underrepresented populations; support for community-based participatory research engaging affected communities in priority setting, intervention co-design, and interpretation of findings; development and validation of patient-reported outcome measures culturally adapted and relevant to diverse populations; and longitudinal cohort studies with repeated SDOH assessments to characterize trajectories and critical periods when interventions may be most impactful. 106

Mechanisms Linking SDOH to Outcomes

Based on synthesis of evidence across included studies, we characterize seven primary mechanistic pathways through which SDOH influences nursing care quality and patient outcomes in neurological disorders.

Pathway 1: Healthcare Access and Utilization Barriers

Lack of insurance, high out-of-pocket costs, geographic distance from specialty centers, inadequate transportation, inability to take time from work, and lack of childcare create multilevel barriers preventing timely diagnosis, treatment initiation, and follow-up continuity. These barriers are particularly consequential in neurological conditions where time-sensitive interventions (thrombolysis for stroke, early disease-modifying therapies for multiple sclerosis) and sustained long-term management (medication titration for Parkinson’s disease, seizure monitoring for epilepsy) are critical. Evidence includes uninsured patients’ 67–81% reduced rehabilitation access, 82 , 83 rural patients’ 50–55% lower thrombolysis rates despite equivalent presentations, 57 , 58 and epilepsy patients’ 70% reduced specialist access without insurance. 73

Pathway 2: Health Literacy and Self-Management Capacity

Educational attainment shapes cognitive resources, comprehension of health information, ability to navigate complex healthcare systems, and capacity for disease self-management including medication adherence, symptom monitoring, and appropriate care-seeking. In neurological conditions requiring sustained self-management and caregiver support (medication adherence in epilepsy, recognition of stroke recurrence warning signs, cognitive symptom monitoring in dementia), health literacy becomes particularly salient. Evidence includes 66% higher rates of poor functional outcomes among low-education stroke patients, 49 21% lower medication adherence in low-SES epilepsy patients, 72 and 56% loss to follow-up among stroke survivors with low educational attainment. 46

Pathway 3: Chronic Psychosocial Stress and Weathering

Socioeconomic disadvantage generates chronic stress through multiple mechanisms: economic insecurity, discrimination experiences, neighborhood disorder and violence, unstable employment, and social marginalization. Chronic stress activates hypothalamic-pituitary-adrenal axis dysregulation, inflammatory cascades, oxidative stress, and accelerated cellular aging—biological processes implicated in stroke pathophysiology, neurodegeneration, and suboptimal recovery. The “weathering hypothesis” proposes that cumulative physiological burden from chronic stress exposure accelerates biological aging in disadvantaged populations, contributing to earlier disease onset and faster progression. 107 Evidence includes African Americans’ earlier multiple sclerosis onset (3–5 years younger) 76 and more severe Parkinson’s disease at presentation, 62 as well as socioeconomic gradients in dementia mortality exceeding 5–8 fold. 69

Pathway 4: Differential Treatment Quality and Intensity

Even after accounting for access to care, evidence suggests that the quality and intensity of treatment received varies by SDOH factors. This may reflect implicit provider bias (unconscious stereotypes and attitudes affecting clinical judgments and behaviors), communication quality differences (shorter visit duration, less participatory decision-making style with minority and low-SES patients), and structural factors (time constraints, resource limitations in safety-net settings). Evidence includes African Americans’ 15–25% lower receipt of stroke thrombolysis and thrombectomy even after presenting to appropriate facilities, 53 76% lower prescription rates of dopaminergic medications among African Americans with Parkinson’s disease despite equivalent disease severity, 63 and Medicare beneficiaries in lowest income quintile receiving 18% less evidence-based stroke care in Denmark despite universal healthcare. 48

Pathway 5: Healthcare System Structural Factors

Hospitals and health systems serving predominantly low-income and minority populations often have fewer resources, affecting nurse staffing levels (1.2 fewer RN hours per patient day in hospitals serving disadvantaged populations), 87 availability of specialized services (neurology consultation, stroke units, epilepsy monitoring), access to advanced treatments (mechanical thrombectomy, deep brain stimulation), and connections to post-acute resources (rehabilitation facilities, home health agencies). Nursing-sensitive outcomes including falls, pressure ulcers, and medication errors are worse in under-resourced settings, directly affecting patient safety and recovery. 89 Payment systems that inadequately adjust for social risk may inadvertently penalize safety-net hospitals serving high-need populations while rewarding well-resourced hospitals serving healthier, wealthier patients.

Pathway 6: Built Environment and Neighborhood Resources

Community-level factors including walkability, access to healthy food, recreational facilities, environmental exposures (air pollution, noise), neighborhood safety, and social capital influence health behaviors, recovery trajectories, and risk factor management. For neurological patients, neighborhood resources affect ability to engage in rehabilitation exercises, access medical appointments, obtain healthy food supporting recovery, and maintain social connections reducing isolation. Studies demonstrating independent effects of neighborhood socioeconomic deprivation beyond individual SES, 59 , 60 with multiplicative effects when both are disadvantaged, illustrate multilevel social determination of neurological health.

Pathway 7: Social Support and Caregiving Resources

Informal caregivers provide the majority of long-term care for neurological conditions, assist with medications, monitor symptoms, provide transportation, advocate in healthcare encounters, and emotionally support patients. Absence of adequate social support and caregiver resources compromises recovery, increases rehospitalization risk, accelerates functional decline, and necessitates earlier nursing home placement. Low-income caregivers face particular challenges due to employment inflexibility, inability to purchase respite care, and competing financial demands. 70 Evidence includes social isolation and lack of family support predicting 53–68% higher loss to follow-up after stroke, 46 inadequate social support increasing care coordination breakdowns 1.9-fold, 94 and caregiver SES strongly influencing dementia patients’ quality of care and institutionalization timing.

These seven pathways are interconnected and often operate synergistically. For example, low health literacy may reduce ability to understand discharge instructions (Pathway 2), leading to medication errors and follow-up failures, while inadequate social support (Pathway 7) limits assistance with complex medical regimens, and healthcare access barriers (Pathway 1) prevent timely problem resolution, collectively increasing rehospitalization risk. Effective interventions likely need to address multiple pathways simultaneously rather than targeting single mechanisms in isolation.

Strengths and Limitations

This systematic review has several important strengths. First, we employed rigorous methods following PRISMA 2020 guidelines with comprehensive searches across three major databases, duplicate independent screening and extraction, validated quality assessment tools, and transparent reporting. Second, our scope encompassing diverse neurological conditions enables identification of both common patterns and disease-specific variations, providing insights not available from condition-specific reviews. Third, our explicit focus on nursing care quality as a mediating pathway addresses a gap in existing literature and identifies actionable opportunities for nursing practice improvement. Fourth, our large combined sample size exceeding 5.4 million participants provides adequate power to detect effects and characterize dose-response relationships. Fifth, the temporal scope (2015–2025) ensures contemporary relevance to current healthcare delivery contexts. Sixth, geographic diversity spanning 15 countries on five continents enhances generalizability. Finally, synthesis of both SDOH impacts and nursing-sensitive indicators provides holistic understanding relevant to clinical practice, system design, and policy.

However, several limitations warrant consideration. First, the inherent limitations of observational studies apply, particularly residual confounding despite multivariable adjustment. While included studies adjusted for numerous covariates, unmeasured factors such as disease severity details, patient preferences, provider characteristics, and organizational factors may partially explain observed associations. Causality cannot be definitively established from observational data, though consistency across diverse studies and contexts, dose-response relationships, and biological plausibility support causal inferences.

Second, substantial heterogeneity in SDOH measurement approaches limited quantitative synthesis. Socioeconomic status was operationalized through income, education, occupation, composite indices, and neighborhood characteristics with varying categorizations. This measurement diversity reflects the multidimensional nature of SES but precludes precise meta-analytic pooling. Similarly, outcome definitions varied across studies (eg, functional status measured via modified Rankin Scale, Barthel Index, or Activities of Daily Living scales), limiting comparability.

Third, publication bias may affect the evidence base. Although observational SDOH research is less susceptible to publication bias than intervention trials because both positive and null findings are publishable and of scientific interest, studies reporting larger disparities or more striking findings may be preferentially published or highlighted. We could not formally assess publication bias given the absence of meta-analysis but acknowledge this potential limitation.

Fourth, many studies relied on administrative data (claims, registries) which have limitations including: variable coding accuracy, inability to capture clinical details and disease severity comprehensively, and lack of granular SDOH information beyond race and insurance status. Conversely, administrative data provide large sample sizes, population-based coverage, and real-world generalizability not available in prospective cohorts.

Fifth, geographic representation was uneven with 58.5% of studies from the United States and limited evidence from Latin America (0%), Africa (1.5%), and Asia (3.1%). SDOH contexts and healthcare system structures differ substantially across countries, potentially limiting generalizability of findings. The paucity of evidence from low- and middle-income countries where disease burden is growing most rapidly is a notable gap.

Sixth, several SDOH dimensions were understudied. Housing instability (12.3% of studies), food insecurity (7.7%), and employment status (33.8%) received limited attention despite conceptual importance. Language barriers, immigration status, discrimination experiences, and digital divide were rarely assessed. More comprehensive SDOH assessment is needed.

Seventh, evidence on specific nursing care quality indicators was limited. While 12 studies examined nursing-sensitive outcomes, the majority focused on staffing ratios and patient safety indicators with less attention to care process measures like assessment completeness, patient education quality, and care coordination effectiveness. Lack of standardized nursing quality metrics in administrative datasets constrains research in this area.

Eighth, few studies examined mechanisms directly through formal mediation analyses or intervention studies. While we synthesized evidence on potential pathways, most studies were not designed to explicitly test mechanisms. Longitudinal studies with repeated SDOH measurement, biological specimens enabling assessment of physiological pathways, and natural experiment designs leveraging policy changes would strengthen causal inference.

Ninth, intersectionality—the concept that multiple marginalized identities (eg, being both Black and low-income, or female and uninsured) create unique experiences and compounded disadvantage—was inadequately addressed. Most studies examined race and SES separately rather than their intersection. Studies that did examine interactions typically found multiplicative effects 60 , 82 but more sophisticated intersectional analyses are needed.

Finally, evidence on interventions to reduce SDOH-related disparities was sparse. This systematic review focused on observational studies documenting associations rather than intervention trials testing solutions. Translating descriptive epidemiology into actionable interventions requires different study designs including implementation science approaches, comparative effectiveness research, and policy evaluations—which represent important next steps beyond this review’s scope.

Comparison with Previous Reviews

Our findings align with and extend previous systematic reviews examining related topics. Marshall et al’s 2015 review on socioeconomic status and stroke found consistent evidence for SES impacts on incidence, survival, and functional outcomes, 26 which our review confirms with more recent evidence and extends to encompass nursing care quality pathways and additional neurological conditions. Similarly, Skolarus et al’s review of social determinants in stroke emphasized multilevel influences on outcomes, 108 a theme our broader synthesis reinforces across diverse neurological disorders.

Otite et al’s systematic review of racial disparities in neurological healthcare access documented profound inequities in specialist availability, treatment receipt, and clinical trial participation, 27 findings our review corroborates with updated evidence while additionally characterizing magnitudes (15–25% reduced acute treatment, 67–81% reduced rehabilitation access) and identifying nurse staffing as a disparity-eliminating factor not emphasized in previous reviews.

Recent scoping reviews on SDOH in dementia care 65 and multiple sclerosis 108 identified diagnostic delays, treatment gaps, and caregiver burden as key concerns—themes our synthesis extends with quantified effect estimates and cross-condition comparisons. Notably, our review’s explicit focus on nursing care quality as a mediator and potential intervention target represents a unique contribution not prominent in prior SDOH reviews in neurology.

Our findings also complement recent policy-oriented reviews. The American Academy of Neurology’s recommendations on SDOH in neurological disease 109 emphasized screening, referral to resources, and advocacy—recommendations our evidence base strongly supports while additionally quantifying impacts and identifying high-priority intervention targets. The Lancet Neurology Commission on social determinants called for upstream investments and structural reforms, 110 which our documentation of persistent disparities even in universal healthcare systems and identification of modifiable healthcare factors reinforces.

A key distinction of our review is comprehensive synthesis across major neurological conditions enabling comparative analysis. While condition-specific reviews provide important depth, our approach reveals both common patterns (consistent SES and racial gradients, profound insurance effects, rural–urban gaps) and disease-specific variations (stroke’s time-sensitive acute care disparities, dementia’s diagnostic delay challenges, Parkinson’s end-of-life care gaps, epilepsy’s medication cost barriers, MS’s financial burden, TBI’s extreme rehabilitation access disparities). This comparative perspective informs whether universal versus tailored interventions are indicated.

Future Research Directions

Based on identified evidence gaps and clinical needs, we propose the following research priorities:

Intervention Research

The overwhelming majority of identified studies were observational, describing problems without testing solutions. High-priority intervention research includes: randomized trials of nurse-led SDOH screening and referral interventions testing whether systematic social needs assessment, resource navigation, and care coordination reduce disparities in neurological outcomes; implementation science studies evaluating strategies to integrate evidence-based disparity reduction interventions (optimal staffing, structured discharge assessment, community health worker involvement) into routine practice across diverse settings; comparative effectiveness research contrasting different models of SDOH-informed care (eg, embedded social workers versus community health workers versus technology-enabled navigation) to identify most effective, efficient, and scalable approaches; and health economic analyses quantifying costs and cost-effectiveness of disparity reduction interventions to inform resource allocation and reimbursement policies.

Mechanism Research

Understanding causal pathways can inform intervention design. Priority mechanistic studies include: longitudinal cohort studies with repeated SDOH assessment, biomarker collection (inflammatory markers, cortisol, telomere length, epigenetic measures), and neuroimaging to characterize biological pathways linking social adversity to neurological disease onset and progression; formal mediation analyses decomposing total SDOH effects into portions operating through healthcare access, treatment quality, health behaviors, psychosocial stress, and other pathways to identify high-impact intervention targets; natural experiment studies leveraging policy changes (Medicaid expansion, nurse staffing legislation, stroke system regionalization) using quasi-experimental designs to strengthen causal inference about policy impacts; and multi-level analyses explicitly testing cross-level interactions between neighborhood factors, healthcare system characteristics, and individual vulnerabilities to inform multi-level intervention strategies.

Complexity and Dynamics Research

Current evidence largely derives from single-timepoint SDOH assessment. Understanding complexity requires: life course studies examining how SDOH exposures accumulate across the lifespan and identifying critical periods when interventions may have greatest impact (eg, preventing childhood adversity to reduce neurodegeneration risk decades later); trajectory modeling identifying heterogeneous subgroups following different SDOH-outcome pathways to enable precision targeting of interventions; interaction and synergy analyses using advanced statistical methods (machine learning, Bayesian networks) to characterize how multiple SDOH factors combine and which combinations create highest risk; and temporal dynamics research examining how SDOH changes over time (eg, job loss after stroke onset, insurance loss during Medicare spend-down) affect trajectories to identify intervention timing.

Global and Cross-Cultural Research

Evidence was dominated by US and European studies. Expanding geographic scope requires: studies in low- and middle-income countries where neurological disease burden is growing most rapidly, healthcare resources are constrained, and SDOH contexts differ substantially; cross-national comparative studies examining how different healthcare systems, social policies, and cultural contexts modify SDOH impacts to identify protective factors that could inform policy; immigrant and refugee health research addressing unique vulnerabilities including acculturation stress, documentation status, and transnational family separation; and indigenous health research conducted with community partnership to address neurological health inequities experienced by indigenous populations globally and develop culturally grounded interventions.

Precision Public Health Approaches

Advances in data science enable more sophisticated approaches: development and validation of multivariable risk prediction tools incorporating SDOH factors to identify high-risk patients for intensive intervention, with attention to ensuring algorithms do not perpetuate bias; machine learning approaches identifying novel patterns and interactions in large, complex datasets linking health records, neighborhood data, and outcomes; geospatial analysis mapping neurological disease burden, healthcare resources, and SDOH indicators to identify “hot spots” requiring targeted investment; and patient-level predictive models integrated in clinical workflows providing point-of-care decision support identifying social needs and appropriate resources.

Policy Evaluation Research

Multiple policy levers could address structural determinants: studies evaluating impacts of insurance expansions, staffing mandates, telehealth reimbursement, community health worker programs, and value-based payment reforms on neurological care equity; economic analyses of upstream social investments (housing, education, income support) examining neurological health returns to justify public health investment; policy simulation modeling projecting impacts and cost-effectiveness of alternative disparity reduction strategies to guide policy prioritization; and comparative policy analysis examining how different state or national policy contexts create differential inequities to identify best practices.

Patient-Centered and Community-Engaged Research

Meaningfully engaging patients and communities is essential: patient-reported outcome research developing and validating neurological PROM instruments culturally adapted and relevant to diverse populations, addressing concerns that existing instruments may not capture concerns of marginalized groups; qualitative research providing in-depth understanding of lived experiences navigating neurological illness with social disadvantage, mechanisms of discrimination, and intervention preferences; community-based participatory research engaging affected communities in priority-setting, intervention co-design, implementation, and interpretation to ensure relevance and acceptability; and implementation research examining barriers and facilitators to disseminating effective interventions in real-world contexts serving vulnerable populations.

Health Equity Metrics and Monitoring

Systematic disparity measurement is prerequisite to improvement: consensus development on standardized SDOH measures, neurological outcome indicators, and disparity metrics to enable comparison across studies and tracking over time; registry enhancements incorporating comprehensive SDOH data collection in disease registries (stroke, Parkinson’s, MS) to enable surveillance and research; dashboard development creating public-facing health equity dashboards stratifying neurological care quality and outcomes by SDOH factors to drive accountability; and return on investment frameworks quantifying broader societal benefits (workforce productivity, reduced disability costs, family financial stability) of achieving neurological health equity to justify investment.

Limitations of the Current Evidence Base

While this review synthesizes the best available observational evidence, important limitations of the overall evidence base warrant acknowledgment. First, most studies were conducted in high-income countries with relatively robust healthcare infrastructure, limiting generalizability to settings where the majority of the global neurological disease burden occurs. Second, reliance on administrative data in many studies limits granularity of clinical detail and SDOH measurement. Third, few studies incorporated longitudinal SDOH assessment, constraining understanding of causal directionality and dynamics. Fourth, underrepresentation of certain SDOH dimensions (housing, food security, discrimination) leaves gaps in understanding. Fifth, limited examination of interactions and cumulative effects prevents sophisticated risk stratification. Sixth, paucity of intervention research limits actionable guidance. Finally, the field would benefit from greater diversity of research teams to bring lived experiences, community connections, and varied perspectives to the research enterprise.

Conclusions

This systematic review of 65 observational studies encompassing over 5.4 million patients provides robust evidence that social determinants of health fundamentally shape nursing care quality and clinical outcomes across major neurological disorders. Low socioeconomic status, racial and ethnic minority status, lack of insurance, rural residence, and community disadvantage consistently predict worse outcomes with substantial magnitudes: 39% increased mortality, 36–66% higher rates of poor functional outcomes, 15–55% reduced access to evidence-based treatments, and 67–81% reduced rehabilitation access. These effects persist even in universal healthcare systems, operate through multiple multilevel pathways, and demonstrate cumulative impacts whereby multiple adversities compound to create particularly high-risk profiles.

Critically, our synthesis identifies nurse staffing ratios as a high-impact, modifiable factor with demonstrated capacity to completely eliminate racial disparities in stroke readmissions—one of the most actionable findings in the literature. Other nursing-sensitive factors including structured discharge readiness assessment, systematic SDOH screening with resource navigation, and interdisciplinary care coordination similarly show promise for disparity reduction. These findings position nursing at the forefront of health equity advancement in neurological care.

For neurological nursing practice, this evidence mandates systematic integration of SDOH screening, culturally humble and structurally competent care delivery, advocacy for adequate staffing resources, enhanced discharge planning processes particularly for vulnerable patients, interdisciplinary team collaboration, tailored patient education, and telehealth implementation with attention to digital divides. At healthcare system and policy levels, insurance coverage expansion, nursing workforce investments, stroke care regionalization, SDOH data infrastructure development, community-clinical linkages, and research funding for intervention trials are essential.

The vision is clear: achieving neurological health equity requires multilevel action addressing modifiable healthcare system factors while simultaneously advocating for structural reforms that address root causes of disadvantage. Nurses—as frontline providers, patient advocates, care coordinators, and increasingly as researchers and policymakers—are uniquely positioned to lead this effort. Integrating SDOH perspectives into neurological nursing education, practice standards, quality metrics, and research priorities represents an essential evolution of professional nursing practice in service of health justice. The evidence compiled in this review provides both moral imperative and practical roadmap for that journey. Eliminating preventable neurological disparities and ensuring that all patients regardless of social circumstances have access to high-quality, equitable care is both an achievable goal and an ethical obligation.

Funding Statement

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data Sharing Statement

All data generated or analyzed in this study are included in the present manuscript and its Supplementary Information Files .

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas. They took part in drafting, revising, or critically reviewing the article. All authors have given final approval of the version to be published, have agreed on the journal to which the article has been submitted, and agree to be accountable for all aspects of the work.

Disclosure

The authors report there are no competing interests to declare for this work.

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Associated Data

Data Availability Statement

All data generated or analyzed in this study are included in the present manuscript and its Supplementary Information Files .