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Stroke. 2000;31:1877-1881

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(Stroke. 2000;31:1877.)
© 2000 American Heart Association, Inc.


Original Contributions

Behavioral Risk Factor Prevalence and Lifestyle Change After Stroke

A Prospective Study

Judith Redfern, MSc; Chris McKevitt, PhD; Ruth Dundas, MSc; Anthony G. Rudd, FRCP Charles D.A. Wolfe, FFPHM

From the Division of Primary Care and Public Health Sciences, Guy’s, King’s and St Thomas’ School of Medicine, King’s College London, London, UK.

Correspondence to Judith Redfern, 5th Floor Capital House, GKT, 42 Weston St, London SE1 3QD, UK. E-mail judith.m.redfern{at}kcl.ac.uk


*    Abstract
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Background and Purpose—Stroke patients have a 15-fold increased risk of recurrent stroke, and those with >=1 risk factor have a further increased risk of recurrence. Previous work found management of physiological risk factors after stroke to be unsatisfactory, but there is little information on behavioral risks within the stroke population. This study estimates behavioral risk factor prevalence after stroke and explores lifestyle change.

Methods—The study used data from the population-based South London Stroke Register, collected prospectively between 1995 and 1998. Main measures included smoking status, alcohol use, and obesity. Logistic regression was used to determine sociodemographic differences in these measures.

Results—At 1 year after stroke, 22% of patients still smoked, 36% of patients were obese, and 4% drank excessively. Younger patients, whites, and men were more likely to smoke, and younger whites were more likely to drink excessively. Women and nonwhites were more likely to be obese. Those living in hospital, nursing home, or residential care and nonwhites were more likely to give up smoking, but there were no other associations between lifestyle change and the sociodemographic characteristics of patients.

Conclusions—Different behavioral risk factors were associated with specific sociodemographic groups within the stroke population. After stroke, high-risk groups should continue to be targeted to prevent stroke recurrence. However, the relationship between sociodemographic characteristics and lifestyle change remains unclear; more research is needed into the process of change to find out how best to intervene to improve secondary prevention.


Key Words: lifestyle • risk factors • stroke prevention


*    Introduction
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In the United Kingdom, Our Healthier Nation targets aim to reduce mortality from stroke by a third by 2010.1 Stroke survivors have a 15-fold increased risk of stroke recurrence compared with the general population2 and represent an important group to focus on if targets are to be achieved. Reducing recurrent stroke and death from recurrence is also recognized as a European priority, with targets set out in the Helsingborg Declaration.3

Patients with >=1 clinical or behavioral risk factor have a further increased risk of stroke recurrence, and appropriate management of risk factors has been shown to be important for secondary prevention.4 Recent work focusing on management of physiological risk factors in an inner-city multiethnic population found secondary prevention to be inadequate with high rates of nontreatment in patients for whom antihypertensive and antithrombotic therapies are appropriate.5 Few data are available on behavioral risk factors within the stroke population.

One reason for focusing on clinical rather than behavioral risks is that lifestyle change is commonly assumed to be difficult to achieve, and secondary prevention interventions often have limited success in reducing behavioral risk factors.6 7 8 However, randomized controlled trials have shown that interventions to modify specific behaviors, such as physicians’ advice to give up smoking9 and excessive drinking,10 can be successful, and the assumption that patients (elderly patients in particular) are unwilling to engage in health promoting behavior is not justified.11

Our Healthier Nation emphasizes the importance of empowering patients to make educated decisions regarding health and lifestyle and the importance of identifying high-risk groups to provide high-quality services. If stroke secondary prevention is to be successful, more information is needed about current management of such risk factors. This study aims to answer 2 key questions: What is the prevalence of behavioral risk factors following stroke, and what factors are associated with reduced risk?


*    Subjects and Methods
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*Subjects and Methods
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The study used data from the South London Stroke Register, a population-based register that since 1995 has been collecting data prospectively on first-in-a-lifetime strokes in patients of all age groups. Twelve overlapping referral sources are used to attain complete notification of such strokes in the study area, which comprises 22 wards of the Lambeth, Southwark and Lewisham Health Authority, with a population of 234 533. The total population is 72% white, 21% black (11% African Caribbean, 7.5% West African, and 2.5% black mixed), and 3% Asian, Bangladeshi, and Pakistani. The methodology has been described in detail elsewhere.12

Data were collected on patients’ sociodemographic characteristics, including age, sex, ethnic group, social class, and place of residence. Face-to-face consultations with patients were conducted at 3 months and 1 year after stroke to collect data on functional ability and risk factors. Functional ability after stroke was measured with the Barthel Index. Data on physiological risk factors (atrial fibrillation, hypertension,13 and diabetes) were collected at the time of stroke and after 3 months and 1 year. Diagnoses were based on patients’ reported history and general practitioner and hospital records. A detailed description of the classification of physiological risk factors is presented elsewhere.5

Behavioral risk factor measures for alcohol consumption (units per week) and smoking status were based on standardized questions.14 15 "Sensible" drinking limits were based on current published guidelines and defined as 14 U/wk for women and 21 U/wk for men,16 17 18 where 1 unit is approximately equivalent to half a pint of beer, lager, or cider; a single measure of spirits; 1 glass of wine; or 1 small glass of fortified wine. Waist and hip circumferences were measured, and waist-to-hip ratio (WHR) was calculated. Obesity is defined as WHR >0.98 for men and >0.88 for women.19 20 Change in smoking status is indicated by the patient giving up smoking or reducing the amount smoked compared with the amount smoked before the stroke. Measures of smoking status and alcohol use were taken at the time of stroke and at the 3-month and 1-year follow-ups. Obesity was measured at the time of stroke and 1-year follow-up only. Questions concerning obesity and reduction in the amount smoked were asked only of patients registered until July 1997.

Bivariate associations between patient characteristics and behavioral risk factors were analyzed with {chi}2 tests. Multiple logistic regression was used to analyze associations between age, sex, ethnic group, social class, disability, physiological risks, and behavioral risk factors.


*    Results
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Follow-Up Rates
Between January 1, 1995, and December 31, 1998, 1139 patients were registered with first-in-a-lifetime stroke. Of these, 377 (33.1%) died within the first 3 months after stroke, and of the survivors, 45 (5.9%) did not complete a 3-month follow-up questionnaire. Data at 1 year after stroke were available for all patients who registered before July1997 (769). Of these, 311 died within the first year, and of the survivors, 36 (7.9%) were lost at 1-year follow-up. For the purposes of this study, 717 of 1139 patients are included for analysis at 3 months and 422 of 769 patients are included for analysis at 1 year after stroke.

Characteristics of Stroke Patients
At the time of stroke, the average age of patients was 72 years. Just over half of the patients (593) were women. Most patients were white (905, 79.6%), but a relatively large minority were nonwhite, most of whom were black African or black Caribbean (181, 15.9%), with only 35 (3.1%) Asian, Bangladeshi, or Pakistani and 16 (1.4%) coming from other ethnic groups.

Three hundred fifty-eight patients (32.2%) were smokers at the time of stroke; 138 (13.2%) drank more than the weekly limit of alcohol; and 471 (56.3%) were obese.

Prevalence of Behavioral Risk Factors After Stroke
At 3 months after stroke, 150 patients (22.2%) smoked, and 33 (4.9%) drank more than the weekly limit. At 1 year, the prevalence rates had changed very little: 89 (22.4%) were still smoking, and 15 (3.6%) were drinking excessively. One hundred thirty-two patients (36.1%) were still obese at 1 year. Table 1Down shows the prevalence of behavioral risk factors at 3 months after stroke for smoking and alcohol use and at 1 year for obesity, identifying groups at high risk. Logistic regression analyses of associations between behavioral risk factors and sociodemographic and physiological risk factors are presented in Table 2Down.


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Table 1. Prevalence of Behavioral Risk Factors After Stroke


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Table 2. Association Between Behavioral Risk Factors and Sociodemographics, Physical Functioning, and Physiological Risk Factors After Stroke

Age, sex, and ethnicity were associated with behavioral risks in younger patients, with men and whites more likely to smoke at 3 months after stroke. Younger patients and whites were also more likely to be heavy drinkers at 3 months after stroke. Women and nonwhites were more likely to have a high WHR at 1 year. Patients still in hospital, nursing homes, or residential care at 3 months were also less likely to smoke, and none of these 149 patients were heavy drinkers. Fewer patients with physiological risk factors (atrial fibrillation, diabetes, and hypertension) reported being smokers, and the confidence intervals suggest that this association remained even after controlling for sociodemographic factors and stroke severity. There was no association between physiological risk factors and heavy drinking at 3 months or obesity at 1 year.

Risk Factor Change
Of those at risk prior to their stroke, a large minority of smokers (82, 34.8%) reported giving up completely 3 months later. One hundred sixty-nine patients who smoked before their stroke were registered before July 1997; of these, 61 (36.1%) had given up completely and another 44 (26.0%) reported having reduced the amount smoked. Seventy-five (72.1%) of those who drank heavily before their stroke no longer drank more than the weekly limit.

Analysis of change within the first year suggests that for smoking and alcohol use, most patients who made lifestyle changes did so within the first 3 months after stroke. Of the 151 smokers before stroke who were still alive at 1 year, 62 (41.1%) gave up smoking, 53 of whom gave up within the first 3 months and only an additional 9 gave up between 3 months and 1 year. Seventy-three excessive alcohol users survived to 1 year, of whom 62 reduced their drinking to less than the weekly limits. Fifty-five of these did so within the first 3 months, and only 7 did so between 3 months and 1 year. Of those who were obese before stroke, 72 (41.1%) were no longer obese 1 year later.

A minority of patients without behavioral risk factors at the time of stroke had increased their risks factors afterward. Four patients who were not heavy drinkers before stroke drank more than the weekly limit 3 months later, and 30 patients (16.4%) who were not obese at the time of stroke were obese at 1 year. Data on smoking status after stroke were available only for patients who were already smokers at the time of stroke. Factors associated with behavior change are presented in Table 3Down.


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Table 3. Association Between Change in Behavioral Risk and Sociodemographics, Physical Functioning, Physiological Risk Factors, and Health Service Use After Stroke

Giving up smoking at 3 months was associated with being nonwhite (black African, Caribbean, or other nonwhite ethnic group). Twenty patients (51.3%) from black ethnic groups did so compared with 62 (31.6%) of white patients. Living in institutionalized care was also associated with smoking cessation: 26 patients (66.7%) living in hospital, nursing home, or residential care had given up smoking compared with only 56 (28.4%) of those living in the community. All 16 patients living in hospital, nursing home, or residential care who previously drank more than the weekly limit had reduced their drinking at 3 months; therefore, place of residence could not be included in the logistic regression model for alcohol use.


*    Discussion
up arrowTop
up arrowAbstract
up arrowIntroduction
up arrowSubjects and Methods
up arrowResults
*Discussion
down arrowReferences
 
Previous work has discussed the appropriateness of physiological risk factor management after stroke,5 but no research to date has focused on behavioral risk factors. This study investigated 2 key issues: the prevalence of behavioral risk factors after stroke and whether specific problem groups could be identified. We also aimed to identify characteristics about those who change risk factors after stroke to help understand what factors help or hinder risk factor change.

Younger patients, whites, men, and those living in the community (as opposed to residential hospital or nursing home care) were more likely to be smokers, and these groups could be targeted with interventions to promote smoking cessation tailored to meet their needs. Younger patients and whites were also more likely to be at risk from excessive drinking; nonwhites and women were more likely to be obese. These groups could also be targeted with appropriate interventions to reduce their risk of second stroke.

A large minority of those with risk factors did modify their lifestyles after stroke; in particular, most excessive drinkers reduced their alcohol consumption within the first year. However, despite some successes, not all patients managed to change their risk factors. Half of those who still smoked at 3 months had reduced the amount they smoked, suggesting that they were willing to change their risk factors but might have needed further support to give up completely. A minority continued to drink more than the weekly limit, and most obese patients did not reduce their WHR.

Apart from living in institutionalized care (hospitals, nursing homes, or residential care), there were no particular patient characteristics associated with behavioral change, although nonwhites were more likely to give up smoking. Older patients were no less likely than their younger counterparts to change any behavioral risk factors after stroke, and this finding supports previous research10 emphasizing that older people should not be excluded from secondary prevention care because they are equally willing to change.

Of those who stopped smoking or cut down on alcohol use, most did so in the first 3 months, suggesting that smoking and alcohol use might be more amenable to change during this time. An alternative interpretation might be that health professionals offer secondary prevention advice only in the first 3 months, failing to deliver appropriate information in the longer term. However, further investigation is needed to determine whether this is the case.

These findings are based on a limited number of questions about patient characteristics and behavioral risk factors and as such can provide only an outline of the relationships between them. If the problems of inadequate management of behavioral risk factors are to be addressed, more research is needed into the actual process of change to find out why some patients change their risk factors while others do not. Trials of interventions to promote behavior change have shown positive results,9 10 but we do not know whether these interventions work for patients with stroke. Little is known about current health service management of behavioral risk factors, what secondary prevention interventions are used in practice, and which patients are being targeted.

We are currently conducting further research to gain a better understanding of risk factor management and the process of change, including interviews with stroke patients about their experiences of risk factor change and observational work to explore the role of health services in promoting secondary prevention or stroke.


*    Acknowledgments
 
This study was funded by Northern and Yorkshire Region Research and Development Program and The Stroke Association.

Received February 18, 2000; revision received May 9, 2000; accepted May 9, 2000.


*    References
up arrowTop
up arrowAbstract
up arrowIntroduction
up arrowSubjects and Methods
up arrowResults
up arrowDiscussion
*References
 

  1. Our Healthier Nation: A Contract for Health. London, UK: Stationery Office, Department of Health; 1998.
  2. Burn J, Dennis M, Bamford J, Sandercock P, Wade D, Warlow C. Long term risk of recurrent stroke after a first ever stroke. Stroke. 1994;25:333–337.[Abstract]
  3. Aborderin I, Venables G. Stroke management in Europe. J Intern Med. 1996;240:173–180.[Medline] [Order article via Infotrieve]
  4. Wolfe C, Stojcevic N, Stewart J. The effectiveness of measures aimed at reducing the incidence of stroke. In: Wolfe C, Rudd T, Beech R, eds. Stroke Services and Research. London, UK: The Stroke Association; 1996:39–86.
  5. Hillen T, Dundas R, Lawrence E, Stewart JA, Rudd AG, Wolfe CDA. Antithrombotic and antihypertensive management three months after ischemic stroke: a prospective study in an inner city population. Stroke. 2000;31:469–475.[Abstract/Free Full Text]
  6. Howitt A, Armstrong D. Implementing evidence based medicine in general practice: audit and qualitative study of antithrombotic treatment for atrial fibrillation. BMJ. 1999;318:1324–1327.[Abstract/Free Full Text]
  7. Jolly K, Bradley F, Sharpe S, Smith H, Thompson S, Kinmouth A, Mant D. Randomised controlled trial of follow-up care in general practice of patients with myocardial infarction and angina: final results of the Southampton Heart Integrated Care Project (SHIP). BMJ. 1999;318:706–711.[Abstract/Free Full Text]
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  12. Stewart JA, Dundas R, Howard RS, Rudd AG, Wolfe CDA. Ethnic differences in incidence of stroke: a prospective study with stroke register. BMJ. 1999;318:967–971.[Abstract/Free Full Text]
  13. Dannenburg AL, Garrison RJ, Kannel WB. Incidence of hypertension in the Framington study. Am J Public Health. 1998;29:53–57.
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  15. South East Thames Regional Health Authority. Health Quest South East. London, UK: SETRHA; 1993.
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