Abstract
Background:
Stroke is the fifth leading cause of death and disability in the United States. Social risk factors contribute to recovery from stroke, however the relationship between social risk factors and functional limitation among stroke survivors remains unknown.
Methods:
Data on 2,888 adults with stroke from the National Health Interview Survey from 2016–2018 was analyzed. The primary independent variables included six social risk factors: economic instability, lack of community, educational deficit, food insecurity, social isolation, and inadequate access to care. The outcome measure was functional limitation count. Negative binomial regression models were run to test the relationship between the independent and dependent variables adjusting for covariates.
Results:
Overall, 56% of the study participants were aged 65+, 70% were Non-Hispanic White, and 95% had at least one comorbidity. The mean functional limitation count was 1.8. In the unadjusted model, each social risk factor was significantly associated with functional limitation. In the fully adjusted model, significant association with functional limitation was found in individuals reporting economic instability (Incidence rate ratio [IRR] 1.65, 95% CI 1.33, 2.06), food insecurity (IRR 1.28, 95% CI 1.15, 1.42), and social isolation (IRR 1.64, 95% CI 1.48, 1.82).
Conclusions:
Social risk factors such as economic instability, food insecurity and social isolation are significantly associated with functional limitation in adults with stroke. Interventions designed to address both social and medical needs have the potential to improve physical functioning and other clinical outcomes in stroke survivors.
Keywords: social risk, social determinants of health, functional limitation, stroke
Stroke is the fifth leading cause of death and disability in the United States (Centers for Disease Control and Prevention, 2022). Every year approximately 795,000 people in the United States have a stroke, with an estimated 77% representing first time strokes. In 2014, 38% of strokes affected people under the age of 65 (Centers for Disease Control and Prevention, 2022), suggesting an impact on individuals in the workforce. Stroke can result in deficits of functional ability such as vision impairment, paralysis, speech and language complications, and/or memory loss, which can, in turn, result in challenges with mobility, communication, and behavioral and emotional changes (American Heart Association, 2022). Stroke can also affect fine motor skills by reducing motor control, proprioception, sensation, and strength (American Heart Association, 2022). This can cause difficulties with daily tasks such as dressing or eating, as well as many other actions required for work or hobbies, leading to functional limitations. The extent of functional limitation not only affects a patient’s quality of life, but also has varied financial consequences (Majersik, 2020). Those with higher post-stroke disability scores experienced up to 5 times higher annual healthcare costs than those with no measurable post-stroke disability (Majersik, 2020). Additionally, improvements from a score of 3 to 2 on the 3-month modified Rankin Score showed an 85% direct cost reduction (Majersik, 2020), demonstrating how improvement in post-stroke functional limitation can reduce the financial burden of stroke disability.
While certain aspects of a stroke, such as location and severity, can impact the extent and type of functional limitations in a stroke survivor, there are other factors that can influence functional limitations. Social risk factors, defined as the adverse social conditions that lead to poor health are widely studied in their relation to disease and disability, functioning, and quality-of-life outcomes (Office of Disease Prevention and Healthy Promotion, 2022, Rhee, 2021, Chang, 2018, Petersen, 2019, Gyasi 2022, Tang, 2021). Specifically, low levels of social support have been shown to increase risk of functional limitation among stroke survivors (Jiao, 2021), food insecurity is associated with worse functional limitations (Chang, 2018, Petersen, 2019, Gyasi 2022, Tang, 2021), and poverty as a social risk factor has shown greater risk of severe functional limitation (Serrano-Alarcón 2017). In addition, lack of access to care is shown to increase functional limitation rate (Lorenz, 2021).
Overall, social risk factors may significantly impact recovery for stroke survivors, however little has been done to understand the contribution of multiple social risk factors on functional ability among stroke survivors at a national level. This study therefore aims to address this gap in knowledge by examining the association of 6 key social risk factors and functional limitations among stroke survivors in a national sample of US adults.
Methods
Data Source
We used the National Health Interview Survey (NHIS) as our data source. The NHIS interviews United States residents within their homes. The information collected pertains to health status, health care utilization, and other health and socio topics (NHIS). We chose to use 2016–2018 data from the sample adult files along with the person and family files. These years were chosen because the information needed to create the six social determinants of health are included here. Our sample population included adults with stroke (2,888 unweighted). The weighted sample was 6,840,643. Reporting for this study adheres to the observational cohort guideline (von Elm E, 2008).
Measures
Six social risk factors, representing social determinants of health (SDOH) domains fashioned by Wray et al. in 2022 were used as the independent variables (Wray, 2021). These domains were treated as binary: the domain being present or not present. The presence of the domain was defined as reporting an agreeing response to any of the prompts in the domain. Missing was defined as completely missing all prompts in a domain. The individual prompts used to define each domain are shown in Table 2. The outcome of interest was functional limitations. This was a count variable of all 36 specific limitation questions followed by the prompt, “any functional limitation, all conditions.” The 36 specific limitation questions are shown in Table 4. Responding ‘not limited in any way ‘to “any functional limitation, all conditions” was recorded as 0 for the count variable. If the response was ‘limited in any way ‘then the sum of affirmative responses from the 36 limitation-specific questions was used for the count. The covariates used were age, sex, race with ethnicity, insurance status, obesity, and comorbidities: hypertension, coronary heart disease, heart attack, asthma, ulcer, cancer, emphysema/COPD, kidney disease, liver disease, arthritis, migraine, and chronic pain.
Table 2:
Characteristics of Social Determinants of Health Domains in Adults with Stroke, NHIS, 2016–2018
| Adults with Stroke (N = 6,840,643) (n = 2,888) | |
|---|---|
| Economic instability | 93.2% |
| Welfare assistance | 1.6% |
| Income from state/county welfare | 2.0% |
| Unemployed | 79.4% |
| Ever applied for Social Security Disability Insurance (SSDI) | 29.6% |
| Subsidized rent | 7.9% |
| Worry about maintaining current standard of living | 39.7% |
| Worry about enough money for retirement | 44.2% |
| Worry about paying normal monthly bills | 35.1% |
| Worry about inability to pay rent, mortgage, or housing costs | 26.2% |
| Worry about making minimum payment on credit cards | 11.9% |
| Lack of community | 42.8% |
| People in your neighborhood do not help each other out | 20.6% |
| There are no people you can count on in your neighborhood | 19.1% |
| People in your neighborhood cannot be trusted | 19.9% |
| Do not live in a close-knit neighborhood | 38.1% |
| Educational deficit | 50.8% |
| No college or graduate degree | 49.3% |
| English not well spoken | 6.4% |
| Food insecurity | 35.4% |
| Lose weight because not enough money for food | 5.6% |
| Cut size of meals or skip meals in the past month | 12.2% |
| Eat less than you should because not enough money for food | 12.6% |
| Ever hungry but did not eat because no money for food | 7.9% |
| Ever receive food stamps/SNAP in past year | 22.3% |
| Worried that food would run out | 21.5% |
| Food did not last until you could buy more | 20.5% |
| Did not eat balanced meals due to costs | 18.4% |
| Received benefits or food subsidies from WIC program | 2.2% |
| Social isolation | 59.2% |
| Lives alone | 27.2% |
| Difficult to participate in social activities | 33.2% |
| Difficult to going to events | 40.1% |
| Delayed getting medical care due to lack of transportation | 6.6% |
| Inadequate access to care | 4.6% |
| Lacks regular place to go to when sick or need health advice | 4.6% |
Table 4:
Functional Limitations Items
| 1. | Vision/problem seeing causes difficulty with activity |
| 2. | Hearing problem causes difficulty with activity |
| 3. | Arthritis/rheumatism causes difficulty with activity |
| 4. | Back or neck problem causes difficulty with activity |
| 5. | Fracture, bone/joint injury causes difficulty with activity |
| 6. | Other injury causes difficulty with activity |
| 7. | Heart problem causes difficulty with activity |
| 8. | Stroke problem causes difficulty with activity |
| 9. | Hypertension/high blood pressure causes difficulty with activity |
| 10. | Diabetes causes difficulty with activity |
| 11. | Lung/breathing problem (e.g., asthma) causes difficulty with activity |
| 12. | Cancer causes difficulty with activity |
| 13. | Birth defect causes difficulty with activity |
| 14. | Intellectual disability, AKA mental retardation causes difficulty with activity |
| 15. | Other developmental problem (eg, cerebral palsy) causes difficulty with activity |
| 16. | Senility causes difficulty with activity |
| 17. | Depression/anxiety/emotional problem causes difficulty with activity |
| 18. | Weight problem causes difficulty with activity |
| 19. | Missing or amputated limb/finger/digit causes difficulty with activity |
| 20. | Musculoskeletal/connective tissue problem causes difficulty with activity |
| 21. | Circulation problems (including blood clots) cause difficulty with activity |
| 22. | Endocrine/nutritional/metabolic problem causes difficulty with activity |
| 23. | Nervous system/sensory organ condition causes difficulty with activity |
| 24. | Digestive system problem causes difficulty with activity |
| 25. | Genitourinary system problem causes difficulty with activity |
| 26. | Skin/subcutaneous system problem causes difficulty with activity |
| 27. | Blood or blood-forming organ problem causes difficulty with activity |
| 28. | Benign tumor/cyst causes difficulty with activity |
| 29. | Alcohol/drug/substance abuse problem causes difficulty with activity |
| 30. | Other mental problem/ADD/Bipolar/Schizophrenia causes difficulty with activity |
| 31. | Surgical after-effects/medical treatment causes difficulty with activity |
| 32. | “Old age”/elderly/aging-related problem causes difficulty with activity |
| 33. | Fatigue/tiredness/weakness causes difficulty with activity |
| 34. | Pregnancy-related problem causes difficulty with activity |
| 35. | Other impairment/problem (1) causes difficulty with activity |
| 36. | Other impairment/problem (2) causes difficulty with activity |
Analyses
All analyses were completed using R v 4.0.3 with alpha level of 0.05 indicating significance. All descriptive information and subsequent analyses were weighted using the survey package in R according to NHIS direction. Summary information of each variable is reported with mean and standard deviation for numeric variables and percentage for categorical variables. Negative binomial models were chosen due to the non-normal distribution of functional limitations. Both Poisson and beta standardization models were tested as well to find the best fit. Unadjusted models were created for each social risk factor on the functional limitations outcome. In the unadjusted models, univariate models were run separately for each social risk factor and the outcome functional limitations. An adjusted model including all 6 social risk factors was then created. Lastly, a fully adjusted model was created using all 6 social risk factors as well as covariates (age, race/ethnicity, insurance status, obesity, and comorbidities).
Results
Table 1 displays the sample demographics for the sample of adults with stroke who completed the NHIS survey in the years 2016–2018. The mean functional limitation count reported by an adult stroke survivor was 1.8 (standard deviation 1.9). The majority of the respondents were aged 50+ (84.7%). A total of 50.4% identified as male and 69.7% identified as Non-Hispanic White, 15.2% Non-Hispanic Black, 10.8% Hispanic, and 4.2% Non-Hispanic Other. Of the respondents, 94.9% reported being insured, 31.8% reported 5+ comorbidities, 35.4% 3–4 comorbidities, 27.9% 1–2 comorbidities, and 4.9% no comorbidities.
Table 1:
Characteristics of Adults with Stroke, NHIS, 2016–2018
| Adults with Stroke (N = 6,840,643) (n = 2,888) | |
|---|---|
| Functional Limitation | 1.8 ± 1.9 |
| Count | |
| Age | |
| 18–39 | 5.9% |
| 40–49 | 9.4% |
| 50–64 | 28.4% |
| 65–74 | 26.3% |
| 75+ | 30.0% |
| Sex | |
| Male | 50.4% |
| Female | 49.6% |
| Race/Ethnicity | |
| Non-Hispanic White | 69.7% |
| Non-Hispanic Black | 15.2% |
| Non-Hispanic Other | 4.2% |
| Hispanic | 10.8% |
| Health Insurance | 94.9% |
| Obese | 36.9% |
| Hypertension | 73.5% |
| Coronary Heart | 23.1% |
| Disease | |
| Heart Attack | 18.0% |
| Asthma | 16.7% |
| Ulcer | 14.6% |
| Cancer | 22.0% |
| Emphysema/COPD | 16.4% |
| Kidney Disease | 11.5% |
| Diabetes | 30.0% |
| Liver Disease | 4.5% |
| Arthritis | 51.6% |
| Migraine | 21.5% |
| Chronic Pain | 59.3% |
| Comorbidity Count | |
| 0 | 4.9% |
| 1–2 | 27.9% |
| 3–4 | 35.4% |
| 5+ | 31.8% |
COPD = Chronic obstructive pulmonary disease
Table 2 displays characteristics of social determinants domains in our sample. Majority (93.2%) had economic instability, with 79.4% of respondents being unemployed, 44.2% reported they worried about having enough money for retirement, and 39.7% reported they worried about maintaining their current standard of living. Over 42.8% of respondents felt they lacked community, with 38.1% feeling they did not live in a close-knit neighborhood. Majority (50.8%) had an educational deficit, where 49.3% had no college or graduate degree. About a third (35.4%) were food insecure, with 22.3% reported having received food stamps/SNAP in the past year and 21.5% worrying that food would run out. A majority of the sample (59.2%) felt socially isolated. Some respondents found it difficult to participate in social activities (33.2%) and going to events (40.1%). Only 4.6% had inadequate access to care by lacking a regular place to go when sick or needing health advice.
Table 3 displays negative binomial regression of functional limitation count using incidence rate ratios (IRR). The unadjusted analyses (univariate models examining the independent relationship between each social risk factor with the functional limitation outcome separately) found significant associations with functional limitations in each of the 6 social risk factors. Specifically, economic instability, lack of community, educational deficit, food insecurity, and social isolation were associated with increased incidences of functional limitations. Inadequate access to care was associated with significant decreased incidence. When adjusting for the other social risks (multivariate model), educational deficit was no longer associated with incidence of functional limitation, however economic instability, lack of community, food insecurity, social isolation, and inadequate access to care remained significantly associated with incidence of functional limitation. When fully adjusted for the other social risks and demographic factors, economic instability (IRR 1.65, 95% CI 1.33, 2.06), food insecurity (IRR 1.28, 95% CI 1.15, 1.42), and social isolation (IRR 1.64, 95% CI 1.48, 1.82) were significantly associated with increased incidence of functional limitations.
Table 3:
Negative Binomial Regression for Functional Limitation Count
| Unadjusted IRR (95% CI)1 | Adults with Stroke Domain Adjusted IRR (95% CI)2 | Fully Adjusted IRR (95% CI) | |
|---|---|---|---|
| Economic instability | 3.12 (2.39, 4.09)*** | 2.03 (1.58, 2.62)*** | 1.65 (1.33, 2.06)*** |
| Lack of community | 1.19 (1.08, 1.32)** | 1.09 (1.00, 1.19)* | 1.06 (0.98, 1.15) |
| Educational deficit | 1.23 (1.12, 1.35)*** | 1.07 (0.98, 1.17) | 1.06 (0.97, 1.16) |
| Food insecurity | 1.72 (1.56, 1.90)*** | 1.45 (1.32, 1.59)*** | 1.28 (1.15, 1.42)*** |
| Social isolation | 2.19 (1.96, 2.46)*** | 1.91 (1.71, 2.13)*** | 1.64 (1.48, 1.82)*** |
| Inadequate access to care | 0.72 (0.54, 0.96)* | 0.75 (0.58, 0.97)* | 0.91 (0.71, 1.16) |
| Age | |||
| 18–39 (ref) | - | - | - |
| 40–49 | - | - | 1.17 (0.82, 1.66) |
| 50–64 | - | - | 1.15 (0.82, 1.62) |
| 65–74 | - | - | 1.19 (0.84, 1.69) |
| 75+ | - | - | 1.24 (0.87, 1.76) |
| Sex (Male) | - | - | 0.95 (0.87, 1.04) |
| Race/Ethnicity | |||
| Hispanic (ref) | - | - | - |
| NHB | - | - | 0.84 (0.71, 0.99)* |
| NHO | - | - | 0.96 (0.70, 1.31) |
| NHW | - | - | 0.89 (0.76, 1.05) |
| Health Insurance | - | - | |
| (Uninsured) | 1.05 (0.82, 1.36) | ||
| Obesity | - | - | 1.02 (0.93, 1.12) |
| Hypertension | - | - | 1.12 (1.01, 1.24)* |
| Coronary Heart Disease | - | - | 1.08 (0.99, 1.19) |
| Heart Attack | - | - | 1.21 (1.08, 1.35)*** |
| Asthma | - | - | 1.08 (0.97, 1.20) |
| Ulcer | - | - | 1.09 (0.98, 1.22) |
| Cancer | - | - | 1.02 (0.93, 1.12) |
| Emphysema/COPD | - | - | 1.11 (1.00, 1.23)* |
| Kidney Disease | - | - | 1.11 (0.99, 1.26) |
| Diabetes | - | - | 1.20 (1.10, 1.32)*** |
| Liver Disease | - | - | 1.25 (1.01, 1.55)* |
| Arthritis | - | - | 1.38 (1.25, 1.52)*** |
| Migraine | - | - | 1.20 (1.08, 1.32)*** |
| Chronic Pain | - | - | 1.28 (1.17, 1.41)*** |
Abbreviations: NHB: Non-Hispanic Black; NHO: Non-Hispanic Other; NHW: Non-Hispanic White.
p-value < 0.05,
p-value < 0.01,
p-value < 0.001
Each Social Determinants of Health Domain is its own, univariate model
All Social Determinants of Health Domains are included in one multivariate model
Discussion
In a nationally representative sample of adult stroke survivors, this study found the population had on average 1.8 functional limitation counts and a high prevalence of social risk. Specifically, 93% reported economic instability, 43% reported lack of community, 51% had an educational deficit, 35% were food insecure, 59% reported social isolation, and nearly 5% lacked adequate access to care. When looking at the relationship between individual social risk factors and functional limitations, after adjusting for relevant covariates and social risk domains, economic instability was significantly related to a 65% increased rate of functional limitation, food insecurity with 28% increased rate of functional limitation, and social isolation with 64% increased rates of functional limitation.
This study expands the current body of knowledge by examining 6 social risk factors and their relationship with functional limitation in a nationally representative sample of stroke survivors. While the finding that economic instability, food insecurity, and social isolation are significantly related to higher rates of functional limitation are consistent with existing literature (Serrano-Alarcón, 2017; Ouyang, 2018; Awuviry-Newton, 2022; Gundersen, 2015; Zhang, 2021; Leigh-Hunt, 2017), this is among the first studies to 1) examine the prevalence of multiple social risk factors within the stroke population at the national level, and 2) control for social risk domains. For example, Ouyang and colleagues found that stroke survivors with a lower income were more likely to suffer from functional impairment when compared to their higher-earning counterparts (Ouyang, 2018). Serrano-Alarcon and colleagues reported subjective poverty was associated with a higher probability of severe functional limitation among stroke survivors (Serrano-Alarcón, 2017). Food insecurity is shown to relate to poorer global cognition and worse depressive symptoms among stroke survivors (McMichael, 2022), as well as increased prevalence of stroke (Te Vazquez, 2021). Social isolation is shown to impact various dimensions of health among individuals who may be at risk for stroke (Zhang, 2021; Schrempft 2019), and result in worse cardiovascular and mental health outcomes (Leigh-Hunt, 2017), however the current study is one of the first to examine the role of social isolation and functional limitations among stroke survivors. Overall, by examining social risks together and controlling for each domain, the current study provides new findings by demonstrating the independent relationship between economic instability, food insecurity, and social isolation and functional limitations, respectively among US stroke survivors.
This study did not find any significant association between lack of community and inadequate access to care with functional limitation rate, necessitating additional work to further understand if these social risk factors relate to other health outcomes critical for stroke recovery. Specifically, further research should explore how access to rehabilitation facilities relates to outcomes on functional limitation. Additionally, lack of community was not found to relate to functional limitation count in stroke survivors in this study. Current research on the effect of community has shown that lower social cohesion is possibly linked to worse health, but that neighborhood social environments are complex to measure, and research is still limited (Diez Roux, 2010). Future research should be aimed at exploring community within the context of rehabilitation and its relationship to clinical outcomes.
Clinically, these findings highlight the importance of screening for social risks specifically for patients under rehabilitation medicine. Existing programs exploring the integration of social and medical care may serve as models for how to leverage existing community resources to address social risk factors within rehabilitation medicine. For example, Anderman and colleagues outline a framework for addressing key social risk factors within clinical practice using existing resources that include food assistance programs (i.e. SNAP or FoodShare), Older Americans Act nutrition services, food pantries, tenant-based housing voucher programs, Community Aging in Place, Advancing Better Living for Elders (CAPABLE), tax credits, supplemental income support, non-emergency medical transport, support groups, and organizations that pair isolated elderly with volunteers and activities to reduce loneliness (Whitman). Once resources are identified, providers, or integrated social services such as community health workers or social workers, may be used for patient navigation to access eligible resources (Andermann 2016; Whitman 2022). Rehabilitation teams may also consider working collaboratively toward addressing the social risks identified through screening at the onset of rehabilitation and, promoting a holistic and person-centered approach (Juanamasta, 2021, Yokose, 2021, Love, 2022). Further, having knowledge of social risk factors can be important for other aspects of care provided to the patients. For example, recognizing economic instability and food insecurity are important factors related to functional ability should inform recommendations for food access, rehabilitation equipment, programs, facilities, and providing discharge instructions. Similarly, consideration for the role of social isolation should also promote connecting patients with their peers and problem solving to address barriers preventing them from participating in social activities. Routine follow-ups should not only include physical, emotional, and functional aspects of the patient, but how social risks are being addressed as well.
Finally, for policy, these findings show the importance of considering social risks when determining standards of care for stroke survivors. For example, the National Institute of Neurological Disorders and Stroke (NINDS) lists multiple factors affecting the outcome of stroke rehabilitation but fails to mention social risks directly (U.S. Department of Health and Human Services). Optimizing recovery from stroke could reduce the functional limitation count for a patient, potentially reducing the financial burdens associated with stroke, for both the patient and the healthcare system. The above findings should be further explored to determine if addressing pertinent social risks in a patient’s rehabilitation care plan can reduce functional limitations. In addition, insurance companies should consider certain social risks to be medically necessary to address to maximize functional gains. Existing programs to reduce food insecurity and enhance social connections should be considered as part of rehabilitation care plans, especially in the critical period of first 2–3 months immediately post-stroke. Next steps are needed to identify gaps in programs that are available to address these social risks, and resources should be allocated to help close these gaps.
Limitations
The data is cross-sectional so causation between social risk factors and functional limitations cannot be determined based on these results. Future work using longitudinal follow-up will allow for insight into the long-term impacts of social risk factors on functional limitations. All responses were self-report, potentially increasing risk for recall bias. The analysis was based on data from the NHIS survey, which does not include information on severity of stroke, such as if the stroke is a new or repeat stroke, time since stroke, nor any information on the extent/quality of rehabilitation received which are critical factors in understanding functional limitations. Rehabilitation services nor level of participation could be standardized. Additionally, some domains may not be fully represented in complexity due to the questions asked. Absence of data on the extent or quality of rehabilitation received by participants limits understanding of recovery dynamics and the influence of social risk factors. In addition, while the study examines several social risk factors, it may not comprehensively capture the complexity and interplay of all relevant social determinants of health. Future research should examine social risks in relation to stroke rehabilitation and see if improvements can be made in severity of functional limitation. While this study represents the US population, future research should include further examination of social risk factors that may impact more diverse and younger stroke survivor populations. Finally, future research is needed using qualitative methods to contextualize social risk factors among stroke survivors to better understand the lived experience and challenges faced by survivors.
Conclusions
In conclusion, this study found that in US adult stroke survivors, social risk factors, specifically, economic instability, food insecurity, and social isolation, were significantly related to higher rates of functional limitations. To effectively account for the social needs driving functional limitation, work is needed to integrate social and medical needs to optimize health for stroke survivors. Next steps should include examination of pathways and mechanisms as well as how these social risks affect other health outcomes for stroke survivors.
Acknowledgements
Effort for this study was partially supported by the National Institute of Diabetes and Digestive Kidney Disease (R01DK118038, R01DK120861, PI: Egede; K01DK131319, PI: Campbell), the National Institute for Minority Health and Health Disparities (R01MD013826, PI: Egede/Walker).
Footnotes
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Financial Disclosures: No financial disclosures are reported by the authors of this paper.
Declaration of Interest: The authors declare that there are no conflicts of interest to disclose.
REFERENCES
- 1.Centers for Disease Control and Prevention. Leading causes of death. Centers for Disease Control and Prevention. Published 2022. https://www.cdc.gov/nchs/fastats/leading-causes-of-death.htm [Google Scholar]
- 2.Stroke Facts | cdc.gov. www.cdc.gov. Published January 31, 2020. https://www.cdc.gov/stroke/facts.htm#:~:text=Every%20year%2C%20more%20than%20795%2C000
- 3.Effects of Stroke. www.stroke.org. Published 2022. https://www.stroke.org/en/aboutstroke/effects-of-stroke.
- 4.Improving Fine Motor Skills. www.stroke.org. Published 2022. Accessed March 24, 2023. https://www.stroke.org/en/about-stroke/effects-of-stroke/physical-effects-ofstroke/physical-impact/improving-fine-motor-skills.
- 5.Majersik JJ, Woo D. The enormous financial impact of stroke disability. Neurology. 2020;94(9):377–378. doi: 10.1212/WNL.0000000000009030 [DOI] [PubMed] [Google Scholar]
- 6.Office of Disease Prevention and Health Promotion. Social Determinants of Health - Healthy People 2030. Published 2022. [Google Scholar]
- 7.Rhee TG, Lee K, Schensul JJ. Black-white Disparities in Social and Behavioral Determinants of Health Index and Their Associations with Self-rated Health and Functional Limitations in Older Adults. The Journals of Gerontology: Series A. Published online October 13, 2020. doi: 10.1093/gerona/glaa264 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Chang Y, Hickman H. Food Insecurity and Perceived Diet Quality Among Low-Income Older Americans with Functional Limitations. Journal of Nutrition Education and Behavior. 2018;50(5):476–484. doi: 10.1016/j.jneb.2017.09.006 [DOI] [PubMed] [Google Scholar]
- 9.Petersen CL, Brooks JM, Titus AJ, Vasquez E, Batsis JA. Relationship Between Food Insecurity and Functional Limitations in Older Adults from 2005–2014 NHANES. Journal of Nutrition in Gerontology and Geriatrics. 2019;38(3):231–246. doi: 10.1080/21551197.2019.1617219 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Gyasi RM, Abass K, Frempong F, et al. Food insecurity and geriatric functional limitations: Observational analysis from the AgeHeaPsyWel–HeaSeeB Survey. Experimental Gerontology. 2022;160:111707. doi: 10.1016/j.exger.2022.111707 [DOI] [PubMed] [Google Scholar]
- 11.Tang X, Blewett LA. Food Security Status among U.S. Older Adults: Functional Limitations Matter. Journal of Nutrition in Gerontology and Geriatrics. 2021;40(2–3):108–124. doi: 10.1080/21551197.2021.1924337 [DOI] [PubMed] [Google Scholar]
- 12.Jiao D, Watanabe K, Sawada Y, et al. Multimorbidity and functional limitation: the role of social relationships. Archives of Gerontology and Geriatrics. 2021;92:104249. doi: 10.1016/j.archger.2020.104249 [DOI] [PubMed] [Google Scholar]
- 13.Serrano-Alarcón M, Perelman J. Ageing under unequal circumstances: a cross-sectional analysis of the gender and socioeconomic patterning of functional limitations among the Southern European elderly. International Journal for Equity in Health. 2017;16(1). doi: 10.1186/s12939-017-0673-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Lorenz LS, Doonan M. Value and Cost Savings From Access to Multi-disciplinary Rehabilitation Services After Severe Acquired Brain Injury. Frontiers in Public Health. 2021;9. doi: 10.3389/fpubh.2021.753447 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE)statement: guidelines for reporting observational studies. J Clin Epidemiol. 2008. Apr;61(4):344–9. [DOI] [PubMed] [Google Scholar]
- 16.National Health Interview Survey. (2022). About the National Health Interview Survey. National Center for Health Statistics. Accessed from: https://www.cdc.gov/nchs/nhis/about_nhis.htm [Google Scholar]
- 17.Wray CM, Tang J, López L, Hoggatt K, Keyhani S. Association of Social Determinants of Health and Their Cumulative Impact on Hospitalization Among a National Sample of Community-Dwelling US Adults. J Gen Intern Med. 2022. Jun;37(8):1935–1942. doi: 10.1007/s11606-021-07067-y. Epub 2021 Aug 5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Ouyang F, Wang Y, Huang W, et al. Association between socioeconomic status and post-stroke functional outcome in deprived rural southern China: a population-based study. BMC Neurology. 2018;18. doi: 10.1186/s12883-018-1017-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Gundersen C, Ziliak JP. Food Insecurity And Health Outcomes. Health Affairs. 2015;34(11). doi: 10.1377/hlthaff.2015.0645 [DOI] [PubMed] [Google Scholar]
- 20.Awuviry-Newton K, Amoah D, Tavener M, et al. Food Insecurity and Functional Disability Among Older Adults in Ghana: The Role of Sex and Physical Activity. Journal of the American Medical Directors Association. 2022;23(8):1432.e1–1432.e7. doi: 10.1016/j.jamda.2022.01.065 [DOI] [PubMed] [Google Scholar]
- 21.McMichael AJ, McGuinness B, Lee J, Minh HV, Woodside JV, McEvoy CT. Food insecurity and brain health in adults: A systematic review. Critical Reviews in Food Science and Nutrition. 2021;62(31):1–16. doi: 10.1080/10408398.2021.1932721 [DOI] [PubMed] [Google Scholar]
- 22.Te Vazquez J, Feng SN, Orr CJ, Berkowitz SA. Food Insecurity and Cardiometabolic Conditions: a Review of Recent Research. Current Nutrition Reports. 2021;10(4). doi: 10.1007/s13668-021-00364-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Zhang Y, Hu W, Feng Z. Social isolation and health outcomes among older people in China. BMC Geriatrics. 2021;21(1). doi: 10.1186/s12877-021-02681-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Leigh-Hunt N, Bagguley D, Bash K, et al. An overview of systematic reviews on the public health consequences of social isolation and loneliness. Public Health. 2017;152(152):157–171. doi: 10.1016/j.puhe.2017.07.035 [DOI] [PubMed] [Google Scholar]
- 25.Post-Stroke Rehabilitation Fact Sheet | National Institute of Neurological Disorders and Stroke. www.ninds.nih.gov. Published July 25, 2022. https://www.ninds.nih.gov/post-stroke-rehabilitation-fact-sheet
- 26.Diez Roux AV, Mair C. Neighborhoods and health. Annals of the New York Academy of Sciences. 2010;1186(1):125–145. doi: 10.1111/j.1749-6632.2009.05333.x [DOI] [PubMed] [Google Scholar]
- 27.Schrempft S, Jackowska M, Hamer M, Steptoe A. Associations between social isolation, loneliness, and objective physical activity in older men and women. BMC Public Health. 2019;19(1). doi: 10.1186/s12889-019-6424-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Juanamasta IG, Aungsuroch Y, Gunawan J, Suniyadewi NW, Nopita Wati NM. Holistic Care Management of Diabetes Mellitus: An Integrative Review. Int J Prev Med. 2021;12:69. Published 2021 Jun 25. doi: 10.4103/ijpvm.IJPVM_402_20 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Yokose C, McCormick N, Choi HK. Dietary and Lifestyle-Centered Approach in Gout Care and Prevention. Current Rheumatology Reports. 2021;23(7):51. doi: 10.1007/s11926-021-01020-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Love L, Newmeyer A, Ryan-Wenger N, Noritz G, Skeens MA. Lessons learned in the development of a nurse-led family centered approach to developing a holistic comprehensive clinic and integrative holistic care plan for children with cerebral palsy. Journal for Specialists in Pediatric Nursing. 2021;27(1). doi: 10.1111/jspn.12354 [DOI] [PubMed] [Google Scholar]
- 31.Andermann A; CLEAR Collaboration. Taking action on the social determinants of health in clinical practice: a framework for health professionals. CMAJ. 2016. Dec 6;188(17–18):E474–E483. doi: 10.1503/cmaj.160177. Epub 2016 Aug 8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Whitman A, De Lew N, Chappel A, Aysola V, Zuckerman R, Sommers BD. Addressing social determinants of health: Examples of successful evidence-based strategies and current federal efforts. Off Heal Policy. 2022. Apr 1:1–30. [Google Scholar]