Published online before print August 12, 2008, doi: 10.1161/CIRCULATIONAHA.108.781062
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(Circulation. 2008;118:947-954.)
© 2008 American Heart Association, Inc.
Stroke |
Primary Prevention of Stroke by Healthy Lifestyle
From the Departments of Nutrition (S.E.C., E.B.R.), Epidemiology (D.S., G.L., J.E.M., E.B.R.), and Biostatistics (D.S.), Harvard School of Public Health, and Division of Preventive Medicine (K.M.R., J.E.M.) and Channing Laboratory (J.E.M., E.B.R.), Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Mass.
Correspondence to Stephanie Chiuve, Harvard School of Public Health, Department of Nutrition, 665 Huntington Ave, Boston, MA 02115. E-mail schiuve{at}hsph.harvard.edu
Received March 19, 2008; accepted June 23, 20008.
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Abstract |
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Background— The combination of healthy lifestyle factors is associated with lower risk of coronary heart disease, diabetes, and total cardiovascular disease. Little is known about the impact of multiple lifestyle factors on the risk of stroke.
Methods and Results— We conducted a prospective cohort study among 43 685 men from the Health Professionals Follow-up Study and 71 243 women from the Nurses’ Health Study. Diet and other lifestyle factors were updated from self-reported questionnaires. We defined a low-risk lifestyle as not smoking, a body mass index <25 kg/m2, 
30 min/d of moderate activity, modest alcohol consumption (men, 5 to 30 g/d; women, 5 to 15 g/d), and scoring within the top 40% of a healthy diet score. We documented 1559 strokes (853 ischemic, 278 hemorrhagic) among women and 994 strokes (600 ischemic, 161 hemorrhagic) among men during follow-up. Women with all 5 low-risk factors had a relative risk of 0.21 (95% confidence interval [CI], 0.12, 0.36) for total and 0.19 (95% CI, 0.09, 0.40) for ischemic stroke compared with women who had none of these factors. Among men, the relative risks were 0.31 (95% CI, 0.19, 0.53) for total and 0.20 (95% CI, 0.10, 0.42) for ischemic stroke for the same comparison. Among the women, 47% (95% CI, 18 to 69) of total and 54% (95% CI, 15 to 78%) of ischemic stroke cases were attributable to lack of adherence to a low-risk lifestyle; among the men, 35% (95% CI, 7 to 58) of total and 52% (95% CI, 19 to 75) of ischemic stroke may have been prevented.
Conclusion— A low-risk lifestyle that is associated with a reduced risk of multiple chronic diseases also may be beneficial in the prevention of stroke, especially ischemic stroke.
Key Words: epidemiology • lifestyle • prevention • risk factors • stroke
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Introduction |
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Stroke is the third leading cause of death in the United States, and nonfatal stroke is a leading cause of permanent disability and economic losses as a result of impairment.1 Adults lack the ability to regenerate damaged brain tissue fully, often making functional recovery incomplete2; therefore, prevention is considered the most effective strategy.1 An overall healthy lifestyle such as not smoking, eating a healthful diet, exercising, and maintaining optimal body weight may be more effective in lowering risk of cardiovascular disease, diabetes, and cancer than any 1 single factor.3–8 The cause of stroke may differ from other cardiovascular diseases and may not share the same risk factors.
Editorial p 904
Clinical Perspective p 954
In this study, we examine the impact on stroke risk of a combination of healthy lifestyle characteristics and calculate the burden of stroke that may be attributed to these unhealthy lifestyle choices.
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Methods |
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Study Population
The Nurses’ Health Study (NHS)9 was established in 1976; the Health Professionals Follow-up Study (HPFS)10 was established in 1986. The populations are composed primarily of whites (96.9% of the NHS, 97.4% of the HPFS). Detailed information on lifestyle habits and medical history is updated biennially. Dietary information is updated approximately every 4 years. We included 43 685 men and 71 243 women who were free of cardiovascular disease and cancer and provided dietary data at baseline. The Institutional Review boards at the Harvard School of Public Health and Brigham and Women’s Hospital approved the study protocol.
Ascertainment of Lifestyle Factors
We obtained information biennially on smoking status, weight, physician diagnosis of hypertension, hypercholesterolemia, and diabetes, and use of medications, including aspirin and vitamin E supplements; in women, information on postmenopausal hormone use and menopausal status also was obtained. Information on height and parental history of myocardial infarction was obtained on the baseline questionnaire. Physical activity was assessed repeatedly with a previously validated questionnaire on frequency of activity over the previous year.11,12 We calculated the average hours per week spent in moderate to vigorous activities (brisk walking [3 mph], jogging, running, bicycling, swimming, tennis, squash, racquetball, rowing, and calisthenics).
The women in the NHS completed the expanded food-frequency questionnaire first in 1984 and again in 1986, 1990, 1994, 1998, and 2002. In the HPFS, we assessed dietary information using the food-frequency questionnaire every 4 years from 1986 to 2002. Nutrient intakes were calculated by multiplying the frequency of intake for each food by its nutrient content and summing these products across all food items. The reproducibility and validity of these food-frequency questionnaires are high compared with multiple 1-week diet records and biochemical markers.13–15
We created a summary diet score based on the Alternate Healthy Eating Index (AHEI),16 which is a variation of the US Department of Agriculture Healthy Eating Index designed to measure adherence to US dietary guidelines.17 We included 8 of 9 components of the AHEI in our diet score: higher intakes of vegetables, fruit, nuts, soy, and cereal fiber; high ratio of chicken plus fish to red meat and polyunsaturated to saturated fat; low intake of trans fat; and multivitamin use of 5 years. The ninth component, alcohol, was considered a separate lifestyle factor in this analysis. The multivitamin component was dichotomized to avoid overweighting of this component (yes=7.5, no=2.5 points). For the remaining components, the possible scores ranged from 0 to 10 (optimal dietary behavior), depending on level of intake. Our diet score ranged from 2.5 (worst) to 77.5 (best).
We considered 2 additional dietary scores. The low-sodium Dietary Approaches to Stop Hypertension (DASH) diet score measures adherence to key components of the DASH diet,18 which in clinical trials significantly lowers blood pressure,19 a strong risk factor for stroke. The 8 components of the DASH diet score were high intake of fruits, vegetables, nuts/legumes, low-fat dairy, and whole grains and low intake of sodium, sugar-sweetened beverages, and red meat. We also considered a 6-nutrient diet score, previously associated with lower risk of coronary heart disease (CHD) within the NHS3 but positively associated with stroke in the Women’s Health Study.20 The 6 nutrients, selected on the basis of their relation with CHD and not stroke specifically, were low intake of trans fat and glycemic load, high intake of cereal fiber, marine n-3 fatty acids and folate, and a high ratio of polyunsaturated to saturated fat. For both diet scores, we divided these nutrients into quintiles, assigned a score between 1 and 5 (most favorable), and summed to create a composite score ranging from 5 to 40 (DASH score) or 6 to 30 (6-nutrient score).
Definition of Low-Risk Lifestyle
We considered 5 lifestyle factors for our low-risk lifestyle—smoking, exercise, diet, body mass index (BMI), and alcohol consumption—based on the strength of evidence on risk of CHD,3,4 diabetes,5 and stroke.20 For each lifestyle factor, we created a binary variable; the participant received 1 if he or she met the criteria for low risk and 0 otherwise.
For smoking, we defined low risk as not currently smoking. Because we focused on modifiable factors, we included former smokers in our low-risk category. For physical activity, we classified low risk as 30 min/d of moderate or vigorous activity. A low-risk diet was defined as a diet score in the top 40% of each cohort distribution. We defined moderate alcohol consumption as at least 5 g/d, with an upper limit of 15 g/d for women and 30 g/d for men, consistent with guidelines for moderate alcohol intake in the United States.21 Finally, optimal weight was defined as BMI <25 kg/m2 during midlife (at baseline). In secondary analyses, we used most recent BMI before stroke diagnosis. Results were essentially the same when we defined low risk for BMI as 18.5 to <25 kg/m2 (data not shown).
Outcome Ascertainment
Confirmed strokes were defined with the National Survey of Stroke criteria,22 requiring neurological deficit of rapid or sudden onset lasting 24 hours or until death. We requested permission to review medical records of all participants who self-reported a physician diagnosis of a stroke during the follow-up. Physicians blinded to risk factor status reviewed the medical records. Strokes that required hospitalization and for which confirmatory information was obtained but medical records were unavailable were designated as probable (25% in NHS, 23% in HPFS of total strokes). Fatal strokes were identified by next of kin, postal authorities, or the National Death Index and confirmed by medical records, autopsy reports, and death certificates with stroke listed as the underlying cause.
We categorized types of stroke as ischemic (embolic or thrombotic), hemorrhagic (subarachnoid or intracerebral), and unknown.22 Approximately 90% of the stroke cases classified as probable were of unknown type. Because the exclusion of probable strokes did not alter the results, we included both confirmed and probable strokes in this analysis.
Statistical Analysis
Individuals contributed person-time from the return of the baseline questionnaire (NHS, 1984; HPFS, 1986) until the date of stroke, diagnosis of cancer, or death or the end of follow-up in January (HPFS) or June (NHS) 2004. We used the cumulative average of the diet scores from repeated dietary assessments to represent long-term dietary information and to reduce measurement error as described previously.23 We stopped updating dietary information after new diagnoses of diabetes, angina, hypertension, hypercholesterolemia, CHD, transient ischemic attack, or revascularization surgery. Midlife BMI was calculated using self-reported weight from the baseline questionnaire; all other lifestyle factors were updated every 2 years. Physical activity was not assessed on the 1984 questionnaire in the NHS; therefore, we used the average of the 1980 and 1982 activity data to represent baseline activity.
Multivariable relative risks (RRs) and 95% confidence intervals [CIs] were estimated with Cox proportional-hazards models stratified by age (in months) and calendar year of the questionnaire cycle. All models were adjusted for parental history of myocardial infarction before 60 years of age (yes/no), regular aspirin use (yes/no), and vitamin E supplementation, (yes/no), plus use of hormone therapy for women (current versus not current use). Further adjustment for history of hypertension, hypercholesterolemia, or diabetes at baseline did not alter the results greatly. Because these are potential intermediate factors on the causal pathway between lifestyle characteristics and stroke, we did not include these variables in the final model.
To estimate the proportion of strokes that could be attributed to an unhealthy lifestyle, we calculated the population-attributable risk percent (PAR%) and 95% CI.24 We compared individuals in the low-risk category with the rest of the population.25 To allow valid calculation of the PAR%, the RRs were estimated with age explicitly in the multivariate model24 using pooled logistic regression models.26 When calculating the PAR%, we placed individuals with missing values (<2% over all questionnaires) in the high-risk category to give the most conservative estimate. Although the distributive property is technically invalid when confounding is present,25 the PAR% obtained was the same when all low-risk factors were entered into the model as individual polytomous variables or as a single binary categorical variable. For simplicity and increased statistical efficiency, we used a single binary categorical variable to calculate the PAR% pertaining to the impact of >1 low-risk factor.
We stratified our models by the presence or absence of hypertension and age (<65, 65 years); however, small numbers within these subgroups lead to relatively unstable estimates, thus making it difficult to draw any strong conclusions (data not shown).
The authors had full access to and take full responsibility for the integrity of the data. All authors have read and agree to the manuscript as written.
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Results |
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During follow-up, we documented 1559 cases of stroke (853 ischemic, 278 hemorrhagic, 428 unknown type) in the NHS and 994 cases of stroke (600 ischemic, 161 hemorrhagic, 233 unknown type) in the HPFS. The mean age at baseline was 50 years in the women and 54 years in the men. In the NHS, 4% of the women were at low risk for none of the lifestyle factors; 2% were at low risk for all 5 factors. In the HPFS, 2% of men were at low risk for none of the lifestyle factors, and 4% were at low risk for all 5 factors.
Among the women and men, smoking, exercise, diet, and BMI were directly associated with the risk of total and ischemic stroke (Table 1
). Alcohol had a J-shaped association with risk of stroke in women, with a lower risk among light drinkers but an elevated risk among heavier drinkers (30 g alcohol/d). Among men, the pattern was similar, although the RRs were not significant. In general, lower scores on all 3 dietary scores (AHEI, DASH, and the 6-nutrient score) were associated with greater risk of stroke (Table 1 and the Table in the online Data Supplement). Midlife BMI was more strongly associated with risk of stroke than most recent BMI (data not shown).
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In general, the associations between lifestyle factors and risk of hemorrhagic stroke followed a pattern similar to ischemic stroke but were not as strong (Table 1
). The low number of incident hemorrhagic strokes, combined with weak associations with the lifestyle factors, led to unstable PAR% estimates with wide CIs. Therefore, we focused on ischemic and total stroke for the remaining analyses.
Not smoking, maintaining optimal BMI, exercising daily, and consuming alcohol moderately were independent predictors of total stroke among the women (Table 2). Not smoking, maintaining optimal BMI, and exercising daily were independent predictors of total stroke in the men. Overall, the total number of low-risk factors was associated with lower risk of ischemic and total stroke (the Figure). Women and men who were adherent to all 5 low-risk factors had an 
80% lower risk of ischemic stroke compared with women and men who had no low-risk factors.
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The risks of stroke among women and men in specific low-risk categories for 3, 4, and 5 lifestyle factors are presented in Table 3. The PAR% for women and men with a low-risk lifestyle was greatest for ischemic stroke. For individuals at low risk for all 5 factors, the PAR% for ischemic stroke was 54% among the women and 52% among the men. More than half of the ischemic strokes in both populations might have been prevented if all individuals had been in the low-risk group.
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We also calculated the PAR% using alternative definitions of low risk for the same 5 lifestyle factors. For both women and men, the PAR% for ischemic stroke was lower when we used the most recent rather than the baseline BMI (PAR%, 49% in women, 31% in men) and when we used 0.1 g alcohol/d as the lower limit of low risk (PAR%, 50% in women, 43% in men). Among women, the PAR% for ischemic stroke was slightly higher when we defined healthy diet using the AHEI (PAR%, 54%) or DASH (PAR%, 54%) dietary scores compared with the 6-nutrient diet scores (PAR%, 30%). Among men, the DASH diet (PAR%, 67%) was more strongly associated with risk of ischemic stroke than the AHEI (PAR%, 52%) or the 6-nutrient diet scores (PAR%, 48%). The CIs were not mutually exclusive (data not shown); therefore, all 3 diets performed relatively comparably to each other.
Because smoking is a strong determinant of risk of disease, we looked at nonsmokers separately. The PAR% among nonsmokers at low risk for the other 4 lifestyle factors was 40% (95% CI, 8 to 65) for total and 48% (95% CI, 6 to 76%) for ischemic stroke among women. Among men, the PAR% was 32% (95% CI, 3 to 56) for total and 50% (95% CI, 16 to 74) for ischemic stroke.
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Discussion |
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In these 2 populations of US health professionals, individuals with a low-risk lifestyle (not smoking, exercising daily, consuming a prudent diet [including moderate alcohol], and having a healthy weight during midlife) had a significantly lower risk of stroke than individuals without a low-risk lifestyle. These estimates were driven mainly by lower risk of ischemic rather than hemorrhagic stroke. Within these study populations, approximately half of ischemic strokes could be attributed to unhealthy lifestyle factors.
A combination of lifestyle factors has been associated with substantially lower risk of many chronic diseases within these and other populations. In the NHS, 70% of total cardiovascular disease,3 80% of CHD,3 and 90% of diabetes5 were attributed to not following a low-risk lifestyle defined by these same 5 factors. In the HPFS, 62% of CHD and 79% of CHD among men <65 years of age were attributed to these same 5 factors.4 Among men and women 70 years old, 61% of cardiovascular deaths may have been avoided through a healthy diet, moderate alcohol intake, daily exercise, and not smoking.7
Although many studies have focused on low-risk characteristics and risk of total cardiovascular disease, fewer studies have addressed the impact of these characteristics on stroke exclusively. In the Women’s Health Study, a prospective cohort study of 37 636 women followed up for 10 years, women with the healthiest lifestyle score, defined as never smoking, having a BMI <22 kg/m2, exercising 4 times a week, consuming 
to 1 drinks a day, and following a healthy diet, had an RR of 0.29 (95% CI, 0.14 to 0.63) for ischemic stroke compared with women with the least healthy lifestyle.20 Similarly, we found an RR for ischemic stroke of 0.19 in women and 0.21 in men, comparing the healthiest to the least healthy individuals. Lifestyle likely influences the risk of stroke in part through clinical risk factors, including hypertension and diabetes. In the EPIC Potsdam study, almost 60% of ischemic stroke cases could be attributed to hypertension, diabetes, hypercholesterolemia, smoking, and heavy alcohol consumption (>15 g alcohol/d in women, >30 g alcohol/d in men).27 Stamler et al28 found that a low-risk lifestyle, defined as cholesterol <200 mg/dL, blood pressure <120/80 mm Hg, and not smoking, was associated with 52% to 76% lower risk of total stroke mortality in several cohorts, although the analyses were limited by few stroke deaths (<15 in any cohort).
We found that midlife BMI was a stronger predictor of stroke than current BMI, as seen with other diseases.29–31 The association between obesity and risk of chronic disease is complicated and can be obscured by a reduction in body weight as a result of preclinical or chronic disease. BMI measured during midlife may be less influenced by underlying disease processes and may more accurately reflect the true relation between body weight and stroke risk.31 Additionally, the loss of lean body mass with age may lead to a reduction in BMI but an increase in percent of body fat. In this case, BMI may no longer capture the impact of adiposity on disease risk.32 Because strokes often occur among the elderly, other measures such as waist circumference or waist-to-hip ratio may provide better assessment of obesity-related risk.33–35
Although the impact of alcohol on stroke risk is unclear, we included moderate alcohol intake in our low-risk lifestyle. Heavy alcohol consumption (>2 drinks a day) may increase risk of stroke, but the evidence for light to moderate alcohol intake has been mixed, showing both null and inverse associations with ischemic stroke risk.36 In this study, we found a J-shaped association for both ischemic and hemorrhagic stroke, with increased risk at higher quantities of alcohol. This study supports previous evidence that moderate alcohol consumption is not associated with greater risk of stroke and may provide additional benefit in stroke prevention. Moderate alcohol may be considered part of a healthy lifestyle for overall chronic disease prevention, including stroke, when consumed responsibility and not contraindicated by other factors.
We explored the association of several dietary patterns on stroke risk. We focused on the AHEI-based diet score, which is associated with a 30% to 40% lower risk of cardiovascular disease.16 Additionally, we explored a dietary score based on the low-sodium DASH diet, because of its beneficial impact on blood pressure in clinical trials,19 and a previously defined 6-nutrient diet score, which was unexpectedly associated with a greater risk of stroke in the Women’s Health Study.20 All 3 diets encompass an overall healthy dietary pattern, and adherence to any of these diets may contribute to the prevention of stroke risk.
Our low-risk lifestyle was not significantly associated with risk of hemorrhagic stroke, consistent with results from the Women’s Health Study analysis.20 Individually, these lifestyle factors were more strongly associated with risk of ischemic than hemorrhagic stroke, although power was limited by the few hemorrhagic stroke cases. Future studies should focus on differences in risk factors between stroke types to enhance prevention strategies for both ischemic and hemorrhagic stroke. Likewise, we did not have adequate power to assess the impact on thrombotic stroke subtypes such as lacunar versus large-artery strokes.
Limitations of our study warrant discussion. As in any observational study, measurement error in self-reported variables is inevitable; however, misclassification in this prospective study should be nondifferential with respect to disease status and would underestimate the true RR. Furthermore, a key strength of these participants is the high level of education and health interest, which has led to high-quality and valid information through self-administered questionnaires.11–14 Although we attempted to control for any potential confounding variables, the possibility of residual confounding remains.
The PAR% is a population-specific calculation that is dependent on the prevalence of the exposure and its association with disease risk. The risk estimates between lifestyle factors and stroke are most likely generalizable to other populations because the underlying biology should be similar across ethnicity, race, and geography. However, the PAR% most likely underestimates the burden of unhealthy behavior on risk of stroke in the general population because the prevalence of these low-risk factors and, more important, the prevalence of extreme levels of unhealthy behaviors are greater in the US population than in our cohorts. For example, the prevalence of US adults with a BMI <25 kg/m2 is 32% compared with 59% of women and 46% of men in our cohorts, and 32% of adults in the United States are obese (BMI 30 kg/m2) compared with only 11% of women and 8% of men in these populations.37 Greater benefit is likely to be gained by adherence to healthy lifestyle choices in populations with a less healthy lifestyle than in these populations of health professionals.
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Conclusions |
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We found that a low-risk lifestyle is associated with lower risk of stroke, especially ischemic stroke, which adds to the data on the prevention of multiple chronic diseases, including CHD and diabetes. This study further supports the beneficial impact of a low-risk lifestyle on the primary prevention of chronic disease and long-term well-being.
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Acknowledgments |
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Sources of Funding
This study was supported by National Institutes of Health grants HL35464, HL34594, HL088521, CA55075, and CA87969.
Disclosures
None.
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References |
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1. Goldstein LB, Adams R, Alberts MJ, Appel LJ, Brass LM, Bushnell CD, Culebras A, Degraba TJ, Gorelick PB, Guyton JR, Hart RG, Howard G, Kelly-Hayes M, Nixon JV, Sacco RL. Primary prevention of ischemic stroke: a guideline from the American Heart Association/American Stroke Association Stroke Council. Stroke. 2006; 37: 1583–1633.
2. Cramer SC, Koroshetz WJ, Finklestein SP. The case for modality-specific outcome measures in clinical trials of stroke recovery-promoting agents. Stroke. 2007; 38: 1393–1395.
3. Stampfer MJ, Hu FB, Manson JE, Rimm EB, Willett WC. Primary prevention of coronary heart disease in women through diet and lifestyle. N Engl J Med. 2000; 343: 16–22.
4. Chiuve SE, McCullough ML, Sacks FM, Rimm EB. Healthy lifestyle factors in the primary prevention of coronary heart disease among men: benefits among users and nonusers of lipid-lowering and antihypertensive medications. Circulation. 2006; 114: 160–167.
5. Hu FB, Manson JE, Stampfer MJ, Colditz G, Liu S, Solomon CG, Willett WC. Diet, lifestyle, and the risk of type 2 diabetes mellitus in women. N Engl J Med. 2001; 345: 790–797.
6. Platz EA, Willett WC, Colditz GA, Rimm EB, Spiegelman D, Giovannucci E. Proportion of colon cancer risk that might be preventable in a cohort of middle-aged US men. Cancer Causes Control. 2000; 11: 579–588.[CrossRef][Medline] [Order article via Infotrieve]
7. Knoops KT, de Groot LC, Kromhout D, Perrin AE, Moreiras-Varela O, Menotti A, van Staveren WA. Mediterranean diet, lifestyle factors, and 10-year mortality in elderly European men and women: the HALE project. JAMA. 2004; 292: 1433–1439.
8. Trichopoulou ACT, Bamia C, Trichopoulos D. Adherence to a Mediterranean diet and survival in a Greek population. N Engl J Med. 2003; 348: 2599–608.
9. Willett WC, Green A, Stampfer MJ, Speizer FE, Colditz GA, Rosner B, Monson R, Stason W, Hennekens CH. Relative and absolute excess risks of coronary heart disease among women who smoke cigarettes. N Engl J Med. 1987; 317: 1303–1309.[Abstract]
10. Colditz GA, Rimm EB, Giovannucci E, Stampfer MJ, Rosner BA, Willett WC. A prospective study of parental history of myocardial infarction and coronary artery disease in men. Am J Cardiol. 1991; 67: 933–938.[CrossRef][Medline] [Order article via Infotrieve]
11. Chasan-Taber S, Rimm EB, Stampfer MJ, Spiegelman D, Colditz GA, Giovannucci E, Ascherio A, Willett WC. Reproducibility and validity of a self-administered physical activity questionnaire for male health professionals. Epidemiology. 1996; 7: 81–86.[Medline] [Order article via Infotrieve]
12. Wolf A, Hunter D, Colditz GA, Manson JE, Stampfer MJ, Corsano K, Corsano KA, Rosner B, Kriska A, Willett WC. Reproducibility and validity of a self-administered physical activity questionnaire. Int J Epidemiol. 1994; 23: 991–999.
13. Rimm EB, Giovannucci EL, Stampfer MJ, Colditz GA, Litin LB, Willett WC. Reproducibility and validity of a expanded self-administered semiquantitative food frequency questionnaire among male health professionals. Am J Epidemiol. 1992; 135: 1114–1126.
14. Feskanich D, Rimm EB, Giovannucci EL, Colditz GA, Stampfer MJ, Litin LB, Willett WC. Reproducibility and validity of food intake measurements from a semiquantitative food frequency questionnaire. J Am Diet Assoc. 1993; 93: 790–796.[CrossRef][Medline] [Order article via Infotrieve]
15. Giovannucci E, Colditz G, Stampfer MJ, Rimm EB, Litin L, Sampson L, Willett WC. The assessment of alcohol consumption by a simple self-administered questionnaire. Am J Epidemiol. 1991; 133: 810–817.
16. McCullough ML, Feskanich D, Stampfer MJ, Giovannucci EL, Rimm EB, Hu FB, Spiegelman D, Hunter DJ, Colditz GA, Willett WC. Diet quality and major chronic disease risk in men and women: moving toward improved dietary guidance. Am J Clin Nutr. 2002; 76: 1261–1271.
17. Kennedy ET, Ohls J, Carlson S, Fleming K. The Healthy Eating Index: design and applications. J Am Diet Assoc. 1995; 95: 1103–1108.[CrossRef][Medline] [Order article via Infotrieve]
18. Fung TT, Chiuve SE, McCullough ML, Rexrode KM, Logroscino G, Hu FB. Adherence to a DASH-style diet and risk of coronary heart disease and stroke in women. Arch Intern Med. 2008; 168: 713–720.
19. Sacks FM, Svetkey LP, Vollmer WM, Appel LJ, Bray GA, Harsha D, Obarzanek E, Conlin PR, Miller ER, Simons-Morton D, Karanja N, Lin PH. Effects on blood pressure of reduced dietary sodium and the Dietary Approaches to Stop Hypertension (DASH) diet. N Engl J Med. 2001; 344: 3–10.
20. Kurth T, Moore SC, Gaziano JM, Kase CS, Stampfer MJ, Berger K, Buring JE. Healthy lifestyle and the risk of stroke in women. Arch Intern Med. 2006; 166: 1403–1409.
21. US Department of Agriculture, US Department of Health and Human Services. Dietary Guidelines for Americans. 6th ed. Washington, DC: US Government Printing Office; 2005.
22. Walker AE, Robins M, Weinfeld FD. The national survey of stroke: clinical findings. Stroke. 1981; 12 (suppl I): I-13–I-44.
23. Hu FB, Stampfer MJ, Rimm E, Ascherio A, Rosner BA, Spiegelman D, Willett WC. Dietary fat and coronary heart disease: a comparison of approaches for adjusting total energy intake and modeling repeated dietary measurements. Am J Epidemiol. 1999; 149: 531–540.
24. Spiegelman D, Hertzmark E, Wand HC. Point and interval estimates of partial population attributable risks in cohort studies: examples and software. Cancer Causes Control. 2007; 18: 571–579.[CrossRef][Medline] [Order article via Infotrieve]
25. Wacholder S, Benichou J, Heineman EF, Hartge P, Hoover RN. Attributable risk: advantages of a broad definition of exposure. Am J Epidemiol. 1994; 140: 303–309.
26. D'Agostino RB, Lee ML, Belanger AJ, Cupples LA, Anderson K, Kannel WB. Relation of pooled logistic regression to time dependent Cox regression analysis: the Framingham Heart Study. Stat Med. 1990; 9: 1501–1515.[Medline] [Order article via Infotrieve]
27. Weikert C, Berger K, Heidemann C, Bergmann MM, Hoffmann K, Klipstein-Grobusch K, Boeing H. Joint effects of risk factors for stroke and transient ischemic attack in a German population: the EPIC Potsdam Study. J Neurol. 2007; 254: 315–321.[CrossRef][Medline] [Order article via Infotrieve]
28. Stamler J, Stamler R, Neaton JD, Wentworth D, Daviglus ML, Garside D, Dyer AR, Liu K, Greenland P. Low risk-factor profile and long-term cardiovascular and noncardiovascular mortality and life expectancy: findings for 5 large cohorts of young adult and middle-aged men and women. JAMA. 1999; 282: 2012–2018.
29. Kurth T, Gaziano JM, Rexrode KM, Kase CS, Cook NR, Manson JE, Buring JE. Prospective study of body mass index and risk of stroke in apparently healthy women. Circulation. 2005; 111: 1992–1998.
30. Harris TB, Savage PJ, Tell GS, Haan M, Kumanyika S, Lynch JC. Carrying the burden of cardiovascular risk in old age: associations of weight and weight change with prevalent cardiovascular disease, risk factors, and health status in the Cardiovascular Health Study. Am J Clin Nutr. 1997; 66: 837–844.
31. Adams KF, Schatzkin A, Harris TB, Kipnis V, Mouw T, Ballard-Barbash R, Hollenbeck A, Leitzmann MF. Overweight, obesity, and mortality in a large prospective cohort of persons 50 to 71 years old. N Engl J Med. 2006; 355: 763–778.
32. Baik I, Ascherio A, Rimm EB, Giovannucci E, Spiegelman D, Stampfer MJ, Willett WC. Adiposity and mortality in men. Am J Epidemiol. 2000; 152: 264–271.
33. Suk SH, Sacco RL, Boden-Albala B, Cheun JF, Pittman JG, Elkind MS, Paik MC. Abdominal obesity and risk of ischemic stroke: the Northern Manhattan Stroke Study. Stroke. 2003; 34: 1586–1592.
34. Rimm EB, Stampfer MJ, Giovannucci E, Ascherio A, Spiegelman D, Colditz GA, Willett WC. Body size and fat distribution as predictors of coronary heart disease among middle-aged and older US men. Am J Epidemiol. 1995; 141: 1117–1127.
35. Lu M, Ye W, Adami HO, Weiderpass E. Prospective study of body size and risk for stroke amongst women below age 60. J Intern Med. 2006; 260: 442–450.[CrossRef][Medline] [Order article via Infotrieve]
36. Reynolds K, Lewis B, Nolen JD, Kinney GL, Sathya B, He J. Alcohol consumption and risk of stroke: a meta-analysis. JAMA. 2003; 289: 579–588.
37. Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM. Prevalence of overweight and obesity in the United States, 1999–2004. JAMA. 2006; 295: 1549–1555.
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Footnotes |
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The online Data Supplement can be found with this article at http://circ.ahajournals.org/cgi/content/full/CIRCULATIONAHA.108.781062/DC1.
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  J. Garcia-Aymerich, R. Varraso, J. M. Anto, and C. A. Camargo Jr. Prospective Study of Physical Activity and Risk of Asthma Exacerbations in Older Women Am. J. Respir. Crit. Care Med., June 1, 2009; 179(11): 999 - 1003. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 L. B. Goldstein and P. M. Rothwell Advances in Primary Prevention and Health Services Delivery Stroke, May 1, 2009; 40(5): e295 - e297. [Full Text] [PDF]
|
|
|
|
 |
|
 T. Kurth Methodological considerations and differences according to sex and stroke subtypes BMJ, March 31, 2009; 338(mar31_1): b1305 - b1305. [Full Text]
|
|
|
|
|
|
M. F Giles Risk of stroke and lifestyle BMJ, February 19, 2009; 338(feb19_2): b14 - b14. [Full Text]
|
|
|
|
 |
|
 A. R. Folsom, K. Yamagishi, A. Hozawa, L. E. Chambless, and for the Atherosclerosis Risk in Communities Study Absolute and Attributable Risks of Heart Failure Incidence in Relation to Optimal Risk Factors Circ Heart Fail, January 1, 2009; 2(1): 11 - 17. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 V. Hachinski Shifts in Thinking About Dementia JAMA, November 12, 2008; 300(18): 2172 - 2173. [Full Text] [PDF]
|
|
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