- Email: [email protected]
Ethnic Differences
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Dietary Practices Among Stroke-survivors—Racial/Ethnic Differences D1X XOyinlola T. Babatunde, D2XPhD X , MPH, RDN,* D3X XPatrick M. Briley, MS D4X X ,† D5X XBrandi M. White, PhD D6X X , MPH,‡ D7X XXiangming Fang, D8XPhD X ,§ and D9X XCharles Ellis, D10XPhD X ║ Background: Healthy lifestyle choices, particularly optimal nutrition, are crucial to stroke prevention and reducing risk of recurrent stroke. Racial differences exist in poststroke outcomes; however, few studies have examined the influence of race on poststroke diet or nutrition practices, despite nutrition being critical to stroke recovery. The objective of this analyzes was therefore to examine racial/ ethnic differences in nutrition activities among stroke survivors using data from the National Health and Nutrition Examination Surveys. Methods: Cross-sectional data from National Health and Nutrition Examination Surveys (2011-2014) were analyzed for adults (n = 431) who responded “yes” that they had been told by a health professional that they had a stroke. The main outcome measure was food consumption/ nutrition behavior. Descriptive statistics were conducted for demographic characteristics. Pearson Chi square statistics were performed for baseline demographic and clinical comparisons. A negative binomial regression analysis was utilized for racial/ethnic comparisons of dietary/nutrition behaviors. Results: The mean age of the sample was 66.6 years (Standard Deviation, 12.7) but the mean age of stroke onset was 57.9 years (Standard Deviation, 15.8), with Mexican American/Hispanics experiencing their strokes at a younger age than other racial groups (P < .007). After controlling for baseline differences in key demographic and clinical covariates variables, Blacks consumed a higher number of ready-to-eat foods (P = .000) in the past 30 days while Mexican American/Hispanics consumed a higher number of frozen meals/pizza in the past 30 days (P = .004). Conclusions: Racial/ethnic differences in poststroke nutrition practices, highlight a potential need for focused nutrition counseling for minority population at higher risk of poor poststroke outcomes. Key Words: Stroke—racial-ethnic—National Health and Nutrition Examination Surveys (NHANES)—nutrition—dietary behavior/practice. © 2018 National Stroke Association. Published by Elsevier Inc. All rights reserved.
Introduction Worldwide estimates indicate that more than 15 million individuals are diagnosed with a stroke each year.1 In the United States (US) alone, approximately 795,000
Americans experience a new or recurrent stroke each year.2 Studies in the US and other countries consistently show racial disparities in stroke with Non-Hispanic Blacks (Blacks) being at twice the risk than Non-Hispanic Whites (Whites).2-5 These observed higher rates among
From the *Department of Nutrition Science, College of Allied Health Sciences, East Carolina University, Greenville, North Carolina; †Department of Communication Sciences & Disorders, College of Allied Health Sciences, East Carolina University, Greenville, North Carolina; ‡Department of Clinical Sciences, College of Health Sciences, University of Kentucky, Lexington, Kentucky; §Department of Biostatistics, College of Allied Health Sciences, East Carolina University, Greenville, North Carolina; and ║Department of Communication Sciences & Disorders, College of Allied Health Sciences, East Carolina University, Greenville, North Carolina. Received March 19, 2018; revision received May 13, 2018; accepted June 17, 2018. Where work was performed: College of Allied Health Sciences, East Carolina University, Greenville, NC, USA. Financial Disclosure: This study was funded by the East Carolina University Interdisciplinary Research Award, from the Division of Research, Economic Development, and Engagement. Address correspondence to Oyinlola T. Babatunde, PhD, MPH, RDN, Department of Nutrition Science, College of Allied Health Sciences, East Carolina University, Health Science Bldg, MailStop #668, Greenville, NC 27858. E-mail: [email protected] 1052-3057/$ - see front matter © 2018 National Stroke Association. Published by Elsevier Inc. All rights reserved. https://doi.org/10.1016/j.jstrokecerebrovasdis.2018.06.026
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Blacks continue to exist despite a substantial overall decrease in stroke among Whites in the US.5 Beyond racial differences in stroke rates, racial disparities also exist in stroke related outcomes. A recent review of the literature that included 17 studies, and 429,108 stroke survivors showed that Whites achieve better outcomes than Blacks even after both groups received rehabilitation.6 The underlying cause of these disparities are not entirely clear and studies are needed to examine issues beyond access to early stroke care, rehabilitation, and lack of family support. It is however, well established that an individual who has survived a stroke is at risk of experiencing another stroke within five years, hence adopting a healthy lifestyle to reduce the risk is recommended.7 Secondary stroke prevention has received substantial attention with risk reduction strategies primarily emphasizing strict management of comorbid disease conditions (hypertension, diabetes, high cholesterol, etc.) that contribute to stroke risk.8 Less attention has been given to diet/nutrition which is critical to both general stroke reduction and reductions in obesity, a risk factor commonly associated with stroke. National efforts from the American Heart Association (AHA) and American Stroke Association (ASA) currently exist to improve nutrition among stroke survivors. For example, the dietary guidelines for Americans 9 offer the foundation for both AHA and ASA “Guidelines for the Prevention of Stroke in Patients with Stroke and Transient Ischemic Attack”,8 and the American College of Cardiology/AHA guidelines on “Lifestyle Management to Reduce Cardiovascular Risk.”10 which emphasizes the importance of nutrition to reduce risk of cardiovascular conditions such as stroke. Both guidelines emphasize the role nutrition plays in optimal stroke recovery and secondary disease prevention. The AHA/ASA specifically notes that under nutrition and deficiency of specific micronutrients may negatively impact the stroke recovery process.8 Current AHA/ASA, general guidelines recommend nutritional assessments, reduction in cholesterol and sodium intake, vitamin supplementation, and counseling to facilitate Mediterranean-type diets for nutrition management in stroke survivors and to prevent secondary stroke.8 Although the American College of Cardiology/ AHA primarily emphasizes general cardiovascular risk and not stroke specifically, and recommends the Dietary Approaches to Stop Hypertension dietary principles, which has also been shown to reduce stroke risk.11 Though the approaches differ, both recommendations focus on dietary lifestyle modifications. To date, however, it is unclear how the comprehensive nutrition guidelines are utilized in stroke survivors to reduce risk of stroke reoccurrence and improve poststroke guidelines. Additionally, it is unclear that how well stroke survivors understand the impact of nutrition on stroke recovery or reduction of secondary stroke risk. Further, few studies have examined potential racial ethnic differences in
dietary/nutrition behavior and management among stroke survivors, and how potential differences may contribute to long standing racial ethnic differences in stroke outcomes. As a critical first step to understand these issues, the objective of this study was to examine racial ethnic differences in nutrition practices in stroke survivors. To complete this study, data from the National Health and Nutrition Examination Surveys (NHANES) was examined.12 This study was reviewed and approved by the East Carolina University Institutional Review Board.
Materials and Methods NHANES is an annual survey completed by the Centers for Disease Control and Prevention (CDC) national center for health statistics to estimate the number and percent of the US population with selected diseases and risk factors.12 The NHANES was initiated more than 50 years ago to monitor selected disease conditions and explore their relationship to diet, nutrition and health. NHANES is a two-year survey designed to be nationally representative by using a complex, stratified multistage probability sample of the non institutionalized US civilian population to generate estimates. Additional details about the survey are available at: https://www.cdc.gov/nchs/ nhanes/index.htm. The NHANES includes a wide range of survey topics and of specific importance to this work were the “Medical Conditions” and the “Diet Behavior & Nutrition” modules of the Questionnaire data.” The “Medical Conditions” module provides self-reported data on a broad range of health conditions including but not limited to: stroke, heart attack, coronary artery disease, congestive heart failure, and diabetes. Similarly, the NHANES “Diet Behavior & Nutrition” module examined the respondent's dietary and nutrition behaviors. For this study, data from the 2011-2012 and 2013-2014 (2011-2014) NHANES were utilized. The overall 20112014 sample consisted of 19,134 individuals (children and adults). The sample included in the study consisted of adults aged greater than18 years who responded “Yes”, when asked “Has a doctor or other health professional ever told you that you...had a stroke?” and completed the diet behavior and nutrition module. The diet behavior and nutrition module asked respondents: (a) how healthy they rated their diet and (b) how many meals were not prepared at home, were from fast food/pizza place, ready-to-eat or frozen meals/pizza. All respondents, self-identified their race/ethnicity as either Mexican American (MA) or Other Hispanic (HIS), Non-Hispanic White (whites), Non Hispanic Black (blacks) or other. Demographic information (age, age of stroke, sex, education, household income, health insurance and presence of other co morbid health conditions) were also collected.
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Statistical Analysis All analyses were conducted in IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corp and a significance level of 0.05 was adopted for all statistical tests. Two types of analyses were completed. First, baseline demographic characteristics were described for all relevant variables for the complete sample. Comparisons between the four racial ethnic groups (MA/HIS, Whites, Blacks and Other) were completed for continuous variables (age and age of stroke) using one way analysis of variance. Similar comparisons were completed for categorical variables (sex, education, household income, insurance status, marital status, and presence of: high blood pressure, high cholesterol, diabetes, overweight, congestive heart failure, coronary artery disease, angina, heart attack and current smoker) using Pearson Chi square statistics. Similarly, racial ethnic comparisons of healthiness of diet was completed with Pearson Chi square statistics. All of these first type of analyses were completed using the complex samples module in SPSS to account for the sample weights to represent the US noninstitutionalized population.13 The actual sample weights used in the analyses were derived from the NHANES weight variable, which was divided by 2 to account for the number of combined years of merged data. The second type of analyses was a negative binomial regression analysis to compare dietary/nutrition behaviors across the racial ethnic groups accounting for a nonnormal distribution due to excessive reports of zero food consumption in some food source outcome variables. Comparisons were completed across the four race groups, with race as the independent factor and consumption of one or more meals: (a) prepared outside the home, (b) fast
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food or pizza, (c) ready-to-eat foods, or (d) frozen foods, as the dependent variables controlling for baseline differences in demographic characteristics. The analyses were controlled for baseline differences in key demographic and clinical covariates variables including age, stroke age, household income, high cholesterol, current smoker, marital status, and health insurance coverage.
Results The study sample consisted of 431 adults who responded “yes” that they had been told by a health profession that they had a stroke. Forty-six percent of the sample were White, 30% Black, 14% MA/HIS, and 9% other. The mean age for the sample was 65.2 (Standard Error (SE) .71) years old. The mean age at stroke onset was 55.8 (Standard Error 96) thus respondents were on average 9.4 years poststroke. MA/ HIS were younger than other racial groups (P = .006). Fifty-four percent of the sample were women, 70% were a high school education or greater, and 76% had household incomes less than $55,000. Similarly, 91% reported having health insurance and 49% were married (Table 1). A range of co-morbid health conditions were reported, including 76% who reported high blood pressure, 57% high cholesterol, and 30% diabetes. Significant racial ethnic differences were observed in household income (P = .000), insurance (P = .000), and marital status (P = .000). Racial ethnic differences also existed in presence of high cholesterol (P = .034) and current smoking status (P = .005) (Table 2). Comparisons of self-reported healthiness of diet and consumption of meals, not prepared at home was compared across racial ethnic groups. Seventy-three percent
Table 1. Sociodemographic and health characteristics of individuals with prior stroke by race/ethnicity All
Age (mean/SE) Stroke onset age (mean/SE) Sex: Women EducationHigh school graduate Household income <$25,000 <$25,000-54,999 <$55,000-74,999 $75,000+ Health insurance: Yes Married: Yes
n 431
Mexican American/ Hispanic n = 62
Non-Hispanic White N = 201
Non-Hispanic Black n = 128
Other n = 40
65.24 (.71) 55.78 (.96) % 53.8
57.63 (2.7) 50.30 (2.59) % 51.1
66.49 (.96) 56.29 (1.40) % 56.9
63.24 (.95) 54.48 (1.75) % 47.2
66.97 (1.83) 59.93 (2.23) % 51.6
29.8 26.2 44.0
48.8 30.8 20.4
25.9 26.3 47.8
33.4 24.0 42.6
34.7 24.4 40.9
43.3 33.1 10.9 12.7 90.9 49.1
50.3 37.4 9.2 3.1 67.0 46.0
45.1 35.1 6.4 13.4 94.3 52.9
41.1 31.2 11.1 16.6 88.7 27.0
22.3 13.7 53.8 10.2 92.5 61.1
P value
.006 .032 .257 .162
.000
P value is for comparison across the four racial-ethnic groups. SE, standard error.
.000 .000
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Table 2. Health characteristics of individuals with prior stroke by race/ethnicity
High blood pressure: Yes High cholesterol: Yes Diabetes: Yes Overweight: Yes Congestive heart failure: Yes Coronary heart disease: Yes Angina: Yes Heart attack: Yes Current smoker: Yes
All n = 431
Mexican American/ hispanic n = 62
Non-Hispanic Whiten = 201
Non-Hispanic Black n = 128
Other n = 40
P value
76.0 57.0 30.0 37.3 20.3 17.6 11.9 20.2 40.2
67.0 33.9 33.7 50.2 10.9 12.6 5.6 15.4 22.3
74.7 58.9 27.2 34.3 22.5 19.3 14.0 22.7 35.3
81.4 56.4 25.8 38.1 13.4 11.1 7.7 18.5 58.9
87.5 68.0 38.5 46.3 21.3 21.2 9.6 7.7 75.8
.471 .034 .350 .340 .078 .590 .071 .551 .005
P-value is for comparison across the four racial-ethnic groups.
of the sample reported their diet was “Excellent or Very good/good”, when compared across racial ethnic groups, there was no statistical difference. One hundred and ninety-seven (45%) of the sample did not respond to questions related to consumption of foods prepared outside the home leaving 234 who reported consumption of foods prepared outside the home. In analyses, controlling for baseline differences (age, age at stroke onset, household income, high cholesterol, current smoker, marital status, and health insurance coverage), significant racial ethnic differences were present in the number of ready-to-eat foods and frozen meals/pizza consumed in the past 30 days. Blacks were most likely to consume ready-to-eat foods in the past 30 days (P = .000) and MA/HIS were more likely to consume frozen meals/pizza (P = .004). In contrast, there were no significant racial /ethnic differences in the number of meals not prepared at home or meals from fast foods or pizza place in the past seven days (Table 3).
Discussion This study explored racial/ethnic differences in dietary behaviors among a nationally representative sample of stroke survivors from the NHANES. Lifestyle changes,
particularly dietary modifications with consuming a Mediterranean-style diet high in fiber, low in cholesterol, red and processed meats, and salt/sodium has been shown to reduce the incidence and recurrence of a stroke.6,8-10 Yet in this sample, we found there may be racial-ethnic differences in nutrition practices thereby suggesting some stroke survivors may not be taking full advantage of the benefits of optional poststroke nutrition. Blacks reported the highest consumption of ready-to-eat foods and MA/HIS reported a higher consumption of frozen meals/pizza in the past 30 days compared to other racial/ethnic groups. The observed racial differences in consumption of ready-to-eat meals among Blacks is consistent with recent results of studies that suggest Blacks are more likely to make poor dietary choices and lifestyle behaviors, which are believed to contribute to higher risk of stroke and other cardiovascular diseases.3-5,7 More specifically, Blacks in this study sample consumed more ready-to-eat meals compared to other racial-ethnic groups, and MA/HIS consumed more frozen meals/pizza than other racial-ethnic groups. These meals/food choices are low in dietary fiber (whole grains, fruits and vegetables) and high in cholesterol, processed meats, and salt/sodium, which are leading dietary risk factors for stroke. However, it is unclear what specific factors primarily have influence
Table 3. Self-reported consumption of one or more meals prepared outside of the home, fast food or frozen foods All
Mexican American/ Non-Hispanic Non-Hispanic Other P value Hispanic White Black N = 234 N = 28 N = 123 N = 64 N = 19 Mean (SE) Mean (SE) Mean (SE) Mean (SE) Mean (SE) # of meals not prepared at home in past 7 days # of meals from fast foods or pizza place in the past 7 days # of ready-to-eat foods in past 30 days # frozen meals/pizza in past 30 days
1.92 (.26)
1.26 (.35)
1.99 (.35)
2.18 (.43)
1.63 (.54)
.692
1.30 (.11)
1.23 (.52)
1.10 (.11)
2.65 (.30)
.95 (.25)
.288
1.22 (.40) 1.78 (.27)
.21 (.13) 2.31 (.96)
1.08 (.21) 2.02 (.35)
2.77 (.227) 1.08 (.26)
.66 (.29) .35 (.16)
.000 .004
Group comparisons controlling for age, stroke age, household income, high cholesterol, current smoker, marital status, and health insurance coverage. P value is for comparison across four racial/ethnic groups with Bonferroni correction for multiple comparisons. SE, standard error.
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on the observed differences in dietary practices. It also remains unclear if the stroke survivors in this study sample have primary concern for the quality of their meal choices or understand the need for optimal nutrition and dietary changes to promote health and prevent future/secondary stroke. For example, ready-to-eat foods and frozen meals/pizza may be high in salt/sodium content and possibly comprised of at least some processed meats and foods likely to increase the risk of a subsequent stroke. Some researchers suggest the overriding factor may be lack of nutrition knowledge and/or receipt of diet counseling that is necessary to understand the importance of a healthy and/or optimal diet to stroke risk reduction.14-16 Additionally, social determinants of health, particularly access to and consumption of nutritious foods are likely to play a role in the observed differences.17 This hypothesis has yet to be adequately confirmed. Interestingly, the latest update from the Healthy People 2020 indicates that there has been little improvement in the Nutrition and Weight Status (NWS) Objective 6-1, which emphasizes “Increase the proportion of physician's office visit made by patients with a diagnosis of CVD, diabetes, or hyperlipidemia that include counseling or education related to diet and nutrition”.18 This most recent update notes that only 20% of patients receive nutrition counseling which is below the desired target (22.9%).18 The findings in the current analyses may also be linked or related to commonly reported racial/ethnic differences in poststroke risk, incidence and outcomes observed in other studies.2-6 More importantly, these findings may offer poststroke management goals as culturally sensitive and targeted nutrition information may serve as a mechanism to improve outcomes in this high risk group. Greater emphasis on meals prepared away from home and particularly from fast food restaurants should be a primary focus, given their higher total calories from excess total fat, cholesterol, and sodium as well as low dietary fiber (whole grains, fruits, and vegetables) and micronutrient content.19,20 Unfortunately, Americans and individuals from other developed countries consume high levels of prepackaged and restaurant foods that are not healthy options, particularly for stroke survivors or individuals with CVD risks.21,22 The findings of racial differences in nutrition practices are co-founded by racial-ethnic differences in several socio demographic characteristics. Blacks and MA/HIS experienced their strokes at a younger age than Whites and therefore are more likely to live longer with stroke and resulting disabilities thus counseling about optimal nutrition practices is warranted. Additionally, earlier age of stroke onset among racial-ethnic minorities has been consistently reported in the stroke literature and should be carefully considered when determining strategies to improve long-term outcomes.2 It is also notable that after controlling for baseline differences in sociodemographic characteristics, racial differences in nutrition practices remained. Understanding these baseline sociodemographic
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differences will be critical in understanding racial differences in poststroke nutrition practices and their relationship to poststroke outcomes.22 Interpretation of the findings here cannot be a straightforward process. Racial differences in nutrition practices can be tied to a range of factors such as cultural practices, beliefs and attitudes about health and well-being as well as management practices of other comorbid conditions. According to Kahan and Cheskin (2014), the current food environment is a major contributor to the difficulty with optimal nutrition practices because the best quality foods are the most expensive, thereby frequently forcing individuals who are socio-economically disadvantaged to make choices based on cost.23 Further, poor quality foods tend to be marketed more widely and are readily accessible compared to nutritious options.23 Additionally, clinicians who are on the front line of the healthcare system have minimal nutrition training, complicated by little time to address nutrition-related issues, and low compensation for nutrition-counseling.24 Despite these issues, Kahan and Mason (2017) suggest a baseline approach should minimally: (a) start the conversation about nutrition and dietary changes by possibly including a nutrition screening as part of the vital sign assessment conducted by medical assistants, (b) structure the encounter (motivational interviewing) to engage the individual about nutrition, (c) focus on making small steps in nutrition improvement, (d) use resources available to clinicians, (e) do not focus on making dramatic changes all at once, and (f) utilize a team approach to facilitate greater opportunities for the message to get across.16 Finally, some suggest greater use of novel technologies and policy changes may be required to adequately address this complex issue.14
Limitations Although the findings here are interesting, there are limitations. First, the data reported here were based on self-report. Self-reported responses can be limited by memory related issues or increasing/decreasing reports of issues such as nutrition that are linked to health outcomes. Particularly of note is the bias in self-reported dietary behavior (or nutrition activity) data and weight status, and implications for diet-disease associations.25-28 Second, the sample included in this report was relatively small despite analyzing multiple years of data. A smaller proportion of the representative sample responded to questions regarding dietary practices. Third, the data included a high number of zero responses (indicating no consumption of the foods of interest) thereby creating some challenges, analyzing the data because of the nonnormal distribution. To account for these issues, we utilized an analytic approach that did not utilize sample weights which in turn decreases generalizability of the data to the US population. However, we believe the findings from this data offer interesting evidence related to
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nutrition practices of stroke survivors. Fourth, there was an uneven distribution of respondents in the racial/ethnic groups, particularly the small number who identified as “Other”. In national data surveys, though some individuals self-identify as “Other”, the racial/ethnic group(s) of these individuals are not entirely clear, and/or how they contribute to the outcomes reported.
Conclusions Despite the reported limitations, racial/ethnic differences observed in this investigation highlight the racial disparities in dietary practices among stroke survivors and the importance of stroke providers emphasize dietary practices during stroke recovery. These findings underscore the importance of increasing awareness on poststroke nutrition practices. Minimally, primary-care providers can make nutrition counseling a key part of the treatment plan for stroke survivors. Employing culturally sensitive strategies should be considered to achieve the dietary behavior change necessary to improve stroke related outcomes among all stroke survivors.
References 1. World Health Organization. http://www.who.int/cardiovascular_diseases/en/cvd_atlas_15_burden_stroke. pdf; 2012 Accessed March 15, 2018. 2. Benjamin EJ, Blaha MJ, Chiuve SE, et al. Heart disease and stroke statistics—2017 update: a report from the American Heart Association. Circulation 2017;135:e146-e603. 3. National Stroke Association. African Americans and Stroke. http://www.stroke.org/site/PageServer?pagename=AAMER; 2013 Accessed March 15, 2018. 4. White H, Boden-Albala B, Wang C, et al. Ischemic stroke subtype incidence among whites, blacks, and Hispanics: the Northern manhattan study. Circulation 2005;111:1327-1331. 5. Kleindorfer DO, Khoury J, Moomaw CJ, et al. Stroke incidence is decreasing in whites but not in blacks: a population-based estimate of temporal trends in stroke incidence from the Greater Cincinnati/Northern Kentucky stroke study. Stroke 2010;41:1326-1331. 6. Ellis C, Hyacinth HI, Beckett J, et al. Racial/ethnic differences in post-stroke rehabilitation outcomes. Stroke Res Treat 2014. Article ID 950746, 12 pages. 7. Division for Heart Disease and Stroke Prevention. Stroke Treatment. https://www.cdc.gov/stroke/treatments. htm; 2018 Accessed February 22. 8. Kernan WN, Obiagele B, Black HR, et al. Guidelines for the prevention of stroke in patients with stroke and transient ischemic attack. A guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 2014;45:2160-2236. 9. Office of Disease Prevention and Health Promotion. Dietary guidelines. https://health.gov/dietaryguidelines/; 2018 Accessed March 15. 10. Eckel RH, Jakicic JM, Ard JD. AHA/ACC guidelines on lifestyle management to reduce cardiovascular risk. A report of the American College of Cardiology/American Heart Association task for on practice guidelines. Circulation 2013;129(25 Suppl 2):S76-S99.
11. Larson SC, Wallin A, Wolk A. Dietary approaches to stop hypertension diet and incidence of stroke. Results from 2 prospective cohorts. Stroke 2016;47:986-990. 12. Centers for Disease Control and Prevention (CDC). National Center for Health Statistics (NCHS). National health and nutrition examination survey data. Hyattsville, MD: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, [20112014]. Available at https://www.cdc.gov/nchs/tutorials/nhanes/SurveyOrientation/Navigate/frame7.htm; 2018 Accessed March 15 . 13. IBM Corp. IBM SPSS Statistics for windows, version 22.0. Armonk, New York IBM Corp. 14. Hankey GJ. The Role of Nutrition in the Risk and Burden of Stroke: An Update of the Evidence. Stroke 2017;48:3168-3174. 15. Office of Disease Prevention and Health Promotion. Dietary guidelines. https://health.gov/dietaryguidelines/; 2018 Accessed March 15. 16. Kahan S, Manson JE. Nutrition Counseling in Clinical Practice: How Clinicians Can Do Better. JAMA 2017;318:1101-1102. 17. Walker RE, Keane CR, Burke JG. Disparities and access to healthy food in the United States: a review of food deserts literature. Health Place 2010;16:876-884. 18. Office of Disease Prevention and Health Promotion. Healthy People 2020 objectives- Nutrition and weight status. https://www.healthypeople.gov/2020/data-search/ Search-the-Data#srch=nutrition; 2018 Accessed March 15. 19. Lin B-H, Guthrie J. Nutritional quality of food prepared at home and away from home, 1977-2008. EIB-105. US Dept Agric, Econ Res Serv 2012. 20. Lachat C, Nago E, Verstraeten R, et al. Eating out of home and its association with dietary intake: a systematic review of the evidence. Obes Rev 2012;13:329-346. 21. Micha R, Pe~ nalvo JL, Cudhea F, et al. Association between dietary factors and mortality from heart disease, stroke, and type 2 diabetes in the United States. JAMA 2017;317:912-924. 22. Pearson-Stuttard J, Bandosz P, Rehm CD, et al. Reducing US cardiovascular disease burden and disparities through national and targeted dietary policies: a modelling study. PLoS Med 2017;14:e1002311. 23. Kahan S, Cheskin LJ. Obesity and eating behaviors and behavior change. In: Kahan S, Gielen AC, Fagan PJ, Green LW, eds. Health behavior change in populations, Baltimore, MD: Johns Hopkins University Press; 2014. 24. Kolasa KM, Rickett K. Barriers to providing nutrition counseling cited by physicians. Nutr Clin Pract 2010;25:502-509. 25. Mendez MA. Invited commentary: dietary misreporting as a potential source of bias in diet-disease associations: future directions in nutritional epidemiology research. Am J Epidemiol 2015;181:234-236. 26. Millen AE, Tooze JA, Subar AF. Differences between food group reports of low-energy reporters and non-lowenergy reporters on a food frequency questionnaire. J Am Diet Assoc 2009;109:1194-1203. 27. Suchanek P, Poledne R, Hubacek JA. Dietary intake reports fidelity-fact or fiction? Neuro Endocrinol Lett 2011;32(Suppl 2):29-31. 28. Cainzos-Achirica M, Bilal U, Kapoor K, et al. Methodological issues in nutritional epidemiology research—sorting through the confusion. Curr Cardiovasc Risk Rep 2018;12:1-9.
Dietary Practices Among Stroke-survivors—Racial/Ethnic Differences D1X XOyinlola T. Babatunde, D2XPhD X , MPH, RDN,* D3X XPatrick M. Briley, MS D4X X ,† D5X XBrandi M. White, PhD D6X X , MPH,‡ D7X XXiangming Fang, D8XPhD X ,§ and D9X XCharles Ellis, D10XPhD X ║ Background: Healthy lifestyle choices, particularly optimal nutrition, are crucial to stroke prevention and reducing risk of recurrent stroke. Racial differences exist in poststroke outcomes; however, few studies have examined the influence of race on poststroke diet or nutrition practices, despite nutrition being critical to stroke recovery. The objective of this analyzes was therefore to examine racial/ ethnic differences in nutrition activities among stroke survivors using data from the National Health and Nutrition Examination Surveys. Methods: Cross-sectional data from National Health and Nutrition Examination Surveys (2011-2014) were analyzed for adults (n = 431) who responded “yes” that they had been told by a health professional that they had a stroke. The main outcome measure was food consumption/ nutrition behavior. Descriptive statistics were conducted for demographic characteristics. Pearson Chi square statistics were performed for baseline demographic and clinical comparisons. A negative binomial regression analysis was utilized for racial/ethnic comparisons of dietary/nutrition behaviors. Results: The mean age of the sample was 66.6 years (Standard Deviation, 12.7) but the mean age of stroke onset was 57.9 years (Standard Deviation, 15.8), with Mexican American/Hispanics experiencing their strokes at a younger age than other racial groups (P < .007). After controlling for baseline differences in key demographic and clinical covariates variables, Blacks consumed a higher number of ready-to-eat foods (P = .000) in the past 30 days while Mexican American/Hispanics consumed a higher number of frozen meals/pizza in the past 30 days (P = .004). Conclusions: Racial/ethnic differences in poststroke nutrition practices, highlight a potential need for focused nutrition counseling for minority population at higher risk of poor poststroke outcomes. Key Words: Stroke—racial-ethnic—National Health and Nutrition Examination Surveys (NHANES)—nutrition—dietary behavior/practice. © 2018 National Stroke Association. Published by Elsevier Inc. All rights reserved.
Introduction Worldwide estimates indicate that more than 15 million individuals are diagnosed with a stroke each year.1 In the United States (US) alone, approximately 795,000
Americans experience a new or recurrent stroke each year.2 Studies in the US and other countries consistently show racial disparities in stroke with Non-Hispanic Blacks (Blacks) being at twice the risk than Non-Hispanic Whites (Whites).2-5 These observed higher rates among
From the *Department of Nutrition Science, College of Allied Health Sciences, East Carolina University, Greenville, North Carolina; †Department of Communication Sciences & Disorders, College of Allied Health Sciences, East Carolina University, Greenville, North Carolina; ‡Department of Clinical Sciences, College of Health Sciences, University of Kentucky, Lexington, Kentucky; §Department of Biostatistics, College of Allied Health Sciences, East Carolina University, Greenville, North Carolina; and ║Department of Communication Sciences & Disorders, College of Allied Health Sciences, East Carolina University, Greenville, North Carolina. Received March 19, 2018; revision received May 13, 2018; accepted June 17, 2018. Where work was performed: College of Allied Health Sciences, East Carolina University, Greenville, NC, USA. Financial Disclosure: This study was funded by the East Carolina University Interdisciplinary Research Award, from the Division of Research, Economic Development, and Engagement. Address correspondence to Oyinlola T. Babatunde, PhD, MPH, RDN, Department of Nutrition Science, College of Allied Health Sciences, East Carolina University, Health Science Bldg, MailStop #668, Greenville, NC 27858. E-mail: [email protected] 1052-3057/$ - see front matter © 2018 National Stroke Association. Published by Elsevier Inc. All rights reserved. https://doi.org/10.1016/j.jstrokecerebrovasdis.2018.06.026
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Blacks continue to exist despite a substantial overall decrease in stroke among Whites in the US.5 Beyond racial differences in stroke rates, racial disparities also exist in stroke related outcomes. A recent review of the literature that included 17 studies, and 429,108 stroke survivors showed that Whites achieve better outcomes than Blacks even after both groups received rehabilitation.6 The underlying cause of these disparities are not entirely clear and studies are needed to examine issues beyond access to early stroke care, rehabilitation, and lack of family support. It is however, well established that an individual who has survived a stroke is at risk of experiencing another stroke within five years, hence adopting a healthy lifestyle to reduce the risk is recommended.7 Secondary stroke prevention has received substantial attention with risk reduction strategies primarily emphasizing strict management of comorbid disease conditions (hypertension, diabetes, high cholesterol, etc.) that contribute to stroke risk.8 Less attention has been given to diet/nutrition which is critical to both general stroke reduction and reductions in obesity, a risk factor commonly associated with stroke. National efforts from the American Heart Association (AHA) and American Stroke Association (ASA) currently exist to improve nutrition among stroke survivors. For example, the dietary guidelines for Americans 9 offer the foundation for both AHA and ASA “Guidelines for the Prevention of Stroke in Patients with Stroke and Transient Ischemic Attack”,8 and the American College of Cardiology/AHA guidelines on “Lifestyle Management to Reduce Cardiovascular Risk.”10 which emphasizes the importance of nutrition to reduce risk of cardiovascular conditions such as stroke. Both guidelines emphasize the role nutrition plays in optimal stroke recovery and secondary disease prevention. The AHA/ASA specifically notes that under nutrition and deficiency of specific micronutrients may negatively impact the stroke recovery process.8 Current AHA/ASA, general guidelines recommend nutritional assessments, reduction in cholesterol and sodium intake, vitamin supplementation, and counseling to facilitate Mediterranean-type diets for nutrition management in stroke survivors and to prevent secondary stroke.8 Although the American College of Cardiology/ AHA primarily emphasizes general cardiovascular risk and not stroke specifically, and recommends the Dietary Approaches to Stop Hypertension dietary principles, which has also been shown to reduce stroke risk.11 Though the approaches differ, both recommendations focus on dietary lifestyle modifications. To date, however, it is unclear how the comprehensive nutrition guidelines are utilized in stroke survivors to reduce risk of stroke reoccurrence and improve poststroke guidelines. Additionally, it is unclear that how well stroke survivors understand the impact of nutrition on stroke recovery or reduction of secondary stroke risk. Further, few studies have examined potential racial ethnic differences in
dietary/nutrition behavior and management among stroke survivors, and how potential differences may contribute to long standing racial ethnic differences in stroke outcomes. As a critical first step to understand these issues, the objective of this study was to examine racial ethnic differences in nutrition practices in stroke survivors. To complete this study, data from the National Health and Nutrition Examination Surveys (NHANES) was examined.12 This study was reviewed and approved by the East Carolina University Institutional Review Board.
Materials and Methods NHANES is an annual survey completed by the Centers for Disease Control and Prevention (CDC) national center for health statistics to estimate the number and percent of the US population with selected diseases and risk factors.12 The NHANES was initiated more than 50 years ago to monitor selected disease conditions and explore their relationship to diet, nutrition and health. NHANES is a two-year survey designed to be nationally representative by using a complex, stratified multistage probability sample of the non institutionalized US civilian population to generate estimates. Additional details about the survey are available at: https://www.cdc.gov/nchs/ nhanes/index.htm. The NHANES includes a wide range of survey topics and of specific importance to this work were the “Medical Conditions” and the “Diet Behavior & Nutrition” modules of the Questionnaire data.” The “Medical Conditions” module provides self-reported data on a broad range of health conditions including but not limited to: stroke, heart attack, coronary artery disease, congestive heart failure, and diabetes. Similarly, the NHANES “Diet Behavior & Nutrition” module examined the respondent's dietary and nutrition behaviors. For this study, data from the 2011-2012 and 2013-2014 (2011-2014) NHANES were utilized. The overall 20112014 sample consisted of 19,134 individuals (children and adults). The sample included in the study consisted of adults aged greater than18 years who responded “Yes”, when asked “Has a doctor or other health professional ever told you that you...had a stroke?” and completed the diet behavior and nutrition module. The diet behavior and nutrition module asked respondents: (a) how healthy they rated their diet and (b) how many meals were not prepared at home, were from fast food/pizza place, ready-to-eat or frozen meals/pizza. All respondents, self-identified their race/ethnicity as either Mexican American (MA) or Other Hispanic (HIS), Non-Hispanic White (whites), Non Hispanic Black (blacks) or other. Demographic information (age, age of stroke, sex, education, household income, health insurance and presence of other co morbid health conditions) were also collected.
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Statistical Analysis All analyses were conducted in IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corp and a significance level of 0.05 was adopted for all statistical tests. Two types of analyses were completed. First, baseline demographic characteristics were described for all relevant variables for the complete sample. Comparisons between the four racial ethnic groups (MA/HIS, Whites, Blacks and Other) were completed for continuous variables (age and age of stroke) using one way analysis of variance. Similar comparisons were completed for categorical variables (sex, education, household income, insurance status, marital status, and presence of: high blood pressure, high cholesterol, diabetes, overweight, congestive heart failure, coronary artery disease, angina, heart attack and current smoker) using Pearson Chi square statistics. Similarly, racial ethnic comparisons of healthiness of diet was completed with Pearson Chi square statistics. All of these first type of analyses were completed using the complex samples module in SPSS to account for the sample weights to represent the US noninstitutionalized population.13 The actual sample weights used in the analyses were derived from the NHANES weight variable, which was divided by 2 to account for the number of combined years of merged data. The second type of analyses was a negative binomial regression analysis to compare dietary/nutrition behaviors across the racial ethnic groups accounting for a nonnormal distribution due to excessive reports of zero food consumption in some food source outcome variables. Comparisons were completed across the four race groups, with race as the independent factor and consumption of one or more meals: (a) prepared outside the home, (b) fast
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food or pizza, (c) ready-to-eat foods, or (d) frozen foods, as the dependent variables controlling for baseline differences in demographic characteristics. The analyses were controlled for baseline differences in key demographic and clinical covariates variables including age, stroke age, household income, high cholesterol, current smoker, marital status, and health insurance coverage.
Results The study sample consisted of 431 adults who responded “yes” that they had been told by a health profession that they had a stroke. Forty-six percent of the sample were White, 30% Black, 14% MA/HIS, and 9% other. The mean age for the sample was 65.2 (Standard Error (SE) .71) years old. The mean age at stroke onset was 55.8 (Standard Error 96) thus respondents were on average 9.4 years poststroke. MA/ HIS were younger than other racial groups (P = .006). Fifty-four percent of the sample were women, 70% were a high school education or greater, and 76% had household incomes less than $55,000. Similarly, 91% reported having health insurance and 49% were married (Table 1). A range of co-morbid health conditions were reported, including 76% who reported high blood pressure, 57% high cholesterol, and 30% diabetes. Significant racial ethnic differences were observed in household income (P = .000), insurance (P = .000), and marital status (P = .000). Racial ethnic differences also existed in presence of high cholesterol (P = .034) and current smoking status (P = .005) (Table 2). Comparisons of self-reported healthiness of diet and consumption of meals, not prepared at home was compared across racial ethnic groups. Seventy-three percent
Table 1. Sociodemographic and health characteristics of individuals with prior stroke by race/ethnicity All
Age (mean/SE) Stroke onset age (mean/SE) Sex: Women Education
n 431
Mexican American/ Hispanic n = 62
Non-Hispanic White N = 201
Non-Hispanic Black n = 128
Other n = 40
65.24 (.71) 55.78 (.96) % 53.8
57.63 (2.7) 50.30 (2.59) % 51.1
66.49 (.96) 56.29 (1.40) % 56.9
63.24 (.95) 54.48 (1.75) % 47.2
66.97 (1.83) 59.93 (2.23) % 51.6
29.8 26.2 44.0
48.8 30.8 20.4
25.9 26.3 47.8
33.4 24.0 42.6
34.7 24.4 40.9
43.3 33.1 10.9 12.7 90.9 49.1
50.3 37.4 9.2 3.1 67.0 46.0
45.1 35.1 6.4 13.4 94.3 52.9
41.1 31.2 11.1 16.6 88.7 27.0
22.3 13.7 53.8 10.2 92.5 61.1
P value
.006 .032 .257 .162
.000
P value is for comparison across the four racial-ethnic groups. SE, standard error.
.000 .000
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Table 2. Health characteristics of individuals with prior stroke by race/ethnicity
High blood pressure: Yes High cholesterol: Yes Diabetes: Yes Overweight: Yes Congestive heart failure: Yes Coronary heart disease: Yes Angina: Yes Heart attack: Yes Current smoker: Yes
All n = 431
Mexican American/ hispanic n = 62
Non-Hispanic Whiten = 201
Non-Hispanic Black n = 128
Other n = 40
P value
76.0 57.0 30.0 37.3 20.3 17.6 11.9 20.2 40.2
67.0 33.9 33.7 50.2 10.9 12.6 5.6 15.4 22.3
74.7 58.9 27.2 34.3 22.5 19.3 14.0 22.7 35.3
81.4 56.4 25.8 38.1 13.4 11.1 7.7 18.5 58.9
87.5 68.0 38.5 46.3 21.3 21.2 9.6 7.7 75.8
.471 .034 .350 .340 .078 .590 .071 .551 .005
P-value is for comparison across the four racial-ethnic groups.
of the sample reported their diet was “Excellent or Very good/good”, when compared across racial ethnic groups, there was no statistical difference. One hundred and ninety-seven (45%) of the sample did not respond to questions related to consumption of foods prepared outside the home leaving 234 who reported consumption of foods prepared outside the home. In analyses, controlling for baseline differences (age, age at stroke onset, household income, high cholesterol, current smoker, marital status, and health insurance coverage), significant racial ethnic differences were present in the number of ready-to-eat foods and frozen meals/pizza consumed in the past 30 days. Blacks were most likely to consume ready-to-eat foods in the past 30 days (P = .000) and MA/HIS were more likely to consume frozen meals/pizza (P = .004). In contrast, there were no significant racial /ethnic differences in the number of meals not prepared at home or meals from fast foods or pizza place in the past seven days (Table 3).
Discussion This study explored racial/ethnic differences in dietary behaviors among a nationally representative sample of stroke survivors from the NHANES. Lifestyle changes,
particularly dietary modifications with consuming a Mediterranean-style diet high in fiber, low in cholesterol, red and processed meats, and salt/sodium has been shown to reduce the incidence and recurrence of a stroke.6,8-10 Yet in this sample, we found there may be racial-ethnic differences in nutrition practices thereby suggesting some stroke survivors may not be taking full advantage of the benefits of optional poststroke nutrition. Blacks reported the highest consumption of ready-to-eat foods and MA/HIS reported a higher consumption of frozen meals/pizza in the past 30 days compared to other racial/ethnic groups. The observed racial differences in consumption of ready-to-eat meals among Blacks is consistent with recent results of studies that suggest Blacks are more likely to make poor dietary choices and lifestyle behaviors, which are believed to contribute to higher risk of stroke and other cardiovascular diseases.3-5,7 More specifically, Blacks in this study sample consumed more ready-to-eat meals compared to other racial-ethnic groups, and MA/HIS consumed more frozen meals/pizza than other racial-ethnic groups. These meals/food choices are low in dietary fiber (whole grains, fruits and vegetables) and high in cholesterol, processed meats, and salt/sodium, which are leading dietary risk factors for stroke. However, it is unclear what specific factors primarily have influence
Table 3. Self-reported consumption of one or more meals prepared outside of the home, fast food or frozen foods All
Mexican American/ Non-Hispanic Non-Hispanic Other P value Hispanic White Black N = 234 N = 28 N = 123 N = 64 N = 19 Mean (SE) Mean (SE) Mean (SE) Mean (SE) Mean (SE) # of meals not prepared at home in past 7 days # of meals from fast foods or pizza place in the past 7 days # of ready-to-eat foods in past 30 days # frozen meals/pizza in past 30 days
1.92 (.26)
1.26 (.35)
1.99 (.35)
2.18 (.43)
1.63 (.54)
.692
1.30 (.11)
1.23 (.52)
1.10 (.11)
2.65 (.30)
.95 (.25)
.288
1.22 (.40) 1.78 (.27)
.21 (.13) 2.31 (.96)
1.08 (.21) 2.02 (.35)
2.77 (.227) 1.08 (.26)
.66 (.29) .35 (.16)
.000 .004
Group comparisons controlling for age, stroke age, household income, high cholesterol, current smoker, marital status, and health insurance coverage. P value is for comparison across four racial/ethnic groups with Bonferroni correction for multiple comparisons. SE, standard error.
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on the observed differences in dietary practices. It also remains unclear if the stroke survivors in this study sample have primary concern for the quality of their meal choices or understand the need for optimal nutrition and dietary changes to promote health and prevent future/secondary stroke. For example, ready-to-eat foods and frozen meals/pizza may be high in salt/sodium content and possibly comprised of at least some processed meats and foods likely to increase the risk of a subsequent stroke. Some researchers suggest the overriding factor may be lack of nutrition knowledge and/or receipt of diet counseling that is necessary to understand the importance of a healthy and/or optimal diet to stroke risk reduction.14-16 Additionally, social determinants of health, particularly access to and consumption of nutritious foods are likely to play a role in the observed differences.17 This hypothesis has yet to be adequately confirmed. Interestingly, the latest update from the Healthy People 2020 indicates that there has been little improvement in the Nutrition and Weight Status (NWS) Objective 6-1, which emphasizes “Increase the proportion of physician's office visit made by patients with a diagnosis of CVD, diabetes, or hyperlipidemia that include counseling or education related to diet and nutrition”.18 This most recent update notes that only 20% of patients receive nutrition counseling which is below the desired target (22.9%).18 The findings in the current analyses may also be linked or related to commonly reported racial/ethnic differences in poststroke risk, incidence and outcomes observed in other studies.2-6 More importantly, these findings may offer poststroke management goals as culturally sensitive and targeted nutrition information may serve as a mechanism to improve outcomes in this high risk group. Greater emphasis on meals prepared away from home and particularly from fast food restaurants should be a primary focus, given their higher total calories from excess total fat, cholesterol, and sodium as well as low dietary fiber (whole grains, fruits, and vegetables) and micronutrient content.19,20 Unfortunately, Americans and individuals from other developed countries consume high levels of prepackaged and restaurant foods that are not healthy options, particularly for stroke survivors or individuals with CVD risks.21,22 The findings of racial differences in nutrition practices are co-founded by racial-ethnic differences in several socio demographic characteristics. Blacks and MA/HIS experienced their strokes at a younger age than Whites and therefore are more likely to live longer with stroke and resulting disabilities thus counseling about optimal nutrition practices is warranted. Additionally, earlier age of stroke onset among racial-ethnic minorities has been consistently reported in the stroke literature and should be carefully considered when determining strategies to improve long-term outcomes.2 It is also notable that after controlling for baseline differences in sociodemographic characteristics, racial differences in nutrition practices remained. Understanding these baseline sociodemographic
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differences will be critical in understanding racial differences in poststroke nutrition practices and their relationship to poststroke outcomes.22 Interpretation of the findings here cannot be a straightforward process. Racial differences in nutrition practices can be tied to a range of factors such as cultural practices, beliefs and attitudes about health and well-being as well as management practices of other comorbid conditions. According to Kahan and Cheskin (2014), the current food environment is a major contributor to the difficulty with optimal nutrition practices because the best quality foods are the most expensive, thereby frequently forcing individuals who are socio-economically disadvantaged to make choices based on cost.23 Further, poor quality foods tend to be marketed more widely and are readily accessible compared to nutritious options.23 Additionally, clinicians who are on the front line of the healthcare system have minimal nutrition training, complicated by little time to address nutrition-related issues, and low compensation for nutrition-counseling.24 Despite these issues, Kahan and Mason (2017) suggest a baseline approach should minimally: (a) start the conversation about nutrition and dietary changes by possibly including a nutrition screening as part of the vital sign assessment conducted by medical assistants, (b) structure the encounter (motivational interviewing) to engage the individual about nutrition, (c) focus on making small steps in nutrition improvement, (d) use resources available to clinicians, (e) do not focus on making dramatic changes all at once, and (f) utilize a team approach to facilitate greater opportunities for the message to get across.16 Finally, some suggest greater use of novel technologies and policy changes may be required to adequately address this complex issue.14
Limitations Although the findings here are interesting, there are limitations. First, the data reported here were based on self-report. Self-reported responses can be limited by memory related issues or increasing/decreasing reports of issues such as nutrition that are linked to health outcomes. Particularly of note is the bias in self-reported dietary behavior (or nutrition activity) data and weight status, and implications for diet-disease associations.25-28 Second, the sample included in this report was relatively small despite analyzing multiple years of data. A smaller proportion of the representative sample responded to questions regarding dietary practices. Third, the data included a high number of zero responses (indicating no consumption of the foods of interest) thereby creating some challenges, analyzing the data because of the nonnormal distribution. To account for these issues, we utilized an analytic approach that did not utilize sample weights which in turn decreases generalizability of the data to the US population. However, we believe the findings from this data offer interesting evidence related to
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nutrition practices of stroke survivors. Fourth, there was an uneven distribution of respondents in the racial/ethnic groups, particularly the small number who identified as “Other”. In national data surveys, though some individuals self-identify as “Other”, the racial/ethnic group(s) of these individuals are not entirely clear, and/or how they contribute to the outcomes reported.
Conclusions Despite the reported limitations, racial/ethnic differences observed in this investigation highlight the racial disparities in dietary practices among stroke survivors and the importance of stroke providers emphasize dietary practices during stroke recovery. These findings underscore the importance of increasing awareness on poststroke nutrition practices. Minimally, primary-care providers can make nutrition counseling a key part of the treatment plan for stroke survivors. Employing culturally sensitive strategies should be considered to achieve the dietary behavior change necessary to improve stroke related outcomes among all stroke survivors.
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11. Larson SC, Wallin A, Wolk A. Dietary approaches to stop hypertension diet and incidence of stroke. Results from 2 prospective cohorts. Stroke 2016;47:986-990. 12. Centers for Disease Control and Prevention (CDC). National Center for Health Statistics (NCHS). National health and nutrition examination survey data. Hyattsville, MD: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, [20112014]. Available at https://www.cdc.gov/nchs/tutorials/nhanes/SurveyOrientation/Navigate/frame7.htm; 2018 Accessed March 15 . 13. IBM Corp. IBM SPSS Statistics for windows, version 22.0. Armonk, New York IBM Corp. 14. Hankey GJ. The Role of Nutrition in the Risk and Burden of Stroke: An Update of the Evidence. Stroke 2017;48:3168-3174. 15. Office of Disease Prevention and Health Promotion. Dietary guidelines. https://health.gov/dietaryguidelines/; 2018 Accessed March 15. 16. Kahan S, Manson JE. Nutrition Counseling in Clinical Practice: How Clinicians Can Do Better. JAMA 2017;318:1101-1102. 17. Walker RE, Keane CR, Burke JG. Disparities and access to healthy food in the United States: a review of food deserts literature. Health Place 2010;16:876-884. 18. Office of Disease Prevention and Health Promotion. Healthy People 2020 objectives- Nutrition and weight status. https://www.healthypeople.gov/2020/data-search/ Search-the-Data#srch=nutrition; 2018 Accessed March 15. 19. Lin B-H, Guthrie J. Nutritional quality of food prepared at home and away from home, 1977-2008. EIB-105. US Dept Agric, Econ Res Serv 2012. 20. Lachat C, Nago E, Verstraeten R, et al. Eating out of home and its association with dietary intake: a systematic review of the evidence. Obes Rev 2012;13:329-346. 21. Micha R, Pe~ nalvo JL, Cudhea F, et al. Association between dietary factors and mortality from heart disease, stroke, and type 2 diabetes in the United States. JAMA 2017;317:912-924. 22. Pearson-Stuttard J, Bandosz P, Rehm CD, et al. Reducing US cardiovascular disease burden and disparities through national and targeted dietary policies: a modelling study. PLoS Med 2017;14:e1002311. 23. Kahan S, Cheskin LJ. Obesity and eating behaviors and behavior change. In: Kahan S, Gielen AC, Fagan PJ, Green LW, eds. Health behavior change in populations, Baltimore, MD: Johns Hopkins University Press; 2014. 24. Kolasa KM, Rickett K. Barriers to providing nutrition counseling cited by physicians. Nutr Clin Pract 2010;25:502-509. 25. Mendez MA. Invited commentary: dietary misreporting as a potential source of bias in diet-disease associations: future directions in nutritional epidemiology research. Am J Epidemiol 2015;181:234-236. 26. Millen AE, Tooze JA, Subar AF. Differences between food group reports of low-energy reporters and non-lowenergy reporters on a food frequency questionnaire. J Am Diet Assoc 2009;109:1194-1203. 27. Suchanek P, Poledne R, Hubacek JA. Dietary intake reports fidelity-fact or fiction? Neuro Endocrinol Lett 2011;32(Suppl 2):29-31. 28. Cainzos-Achirica M, Bilal U, Kapoor K, et al. Methodological issues in nutritional epidemiology research—sorting through the confusion. Curr Cardiovasc Risk Rep 2018;12:1-9.