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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Circulation. Author manuscript; available in PMC Aug 26, 2009.
Published in final edited form as:
PMCID: PMC2730914
NIHMSID: NIHMS126422
Primary prevention of stroke by healthy lifestyle
Stephanie E. Chiuve, ScD,1 Kathryn M. Rexrode, MD, MPH,4 Donna Spiegelman, ScD,2,3 Giancarlo Logroscino, MD, PhD,2 JoAnn E. Manson, MD DrPH,2,4,5 and Eric B. Rimm, ScD1,2,5
1Department of Nutrition, Harvard School of Public Health, Boston
2Department of Epidemiology Harvard School of Public Health, Boston
3Department of Biostatistics, Harvard School of Public Health, Boston
4Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
5Department of Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
Corresponding Author: Stephanie Chiuve, Harvard School of Public Health, Department of Nutrition, 665 Huntington Ave., Boston, MA 02115, schiuve/at/hsph.harvard.edu, Phone: 617-432-6744; Fax: 617-432-2435
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 risk of stroke.
Methods and results
We conducted a prospective cohort study among 43,685 men from 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/m 2, ≥30 minutes/day of moderate activity, consuming alcohol modestly (men:5–30g; women:5–15g alcohol/day), 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 five low-risk factors had a relative risk of 0.21 (95%CI:0.12, 0.36) for total and 0.19 (95%CI:0.09, 0.40) for ischemic stroke, compared to 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%, 69%) of total and 54% (95%CI:15%, 78%) of ischemic stroke cases were attributable to lack of adherence to a low-risk lifestyle; among the men, 35% (95%CI:7%, 58%) of total and 52% (95%CI:19%, 75%) of ischemic stroke may have been prevented.
Conclusions
A low-risk lifestyle that is associated with a reduced risk of multiple chronic diseases may also be beneficial in the prevention of stroke, especially ischemic stroke.
Keywords: lifestyle, risk factors, epidemiology, stroke, prevention
Stroke is the third leading cause of death in the US and nonfatal stroke is a leading cause of permanent disability and economic losses due to impairment1. Adults lack the ability to regenerate damaged brain tissue fully, often making functional recovery incomplete2, and therefore prevention is considered the most effective strategy1. An overall healthy lifestyle, such as not smoking, diet, exercise and optimal body weight, may be more effective in lowering risk of cardiovascular disease(CVD), diabetes and cancer than any one single factor38. The etiology of stroke may differ from other cardiovascular diseases and may not share the same risk factors.
In this study, we examine the impact on stroke risk of a combination of healthy lifestyle characteristics and also calculate the burden of stroke that may be attributed to these unhealthy lifestyle choices.
Study population
The Nurses’ Health Study(NHS)9 was established in 1976 and the Health Professionals Follow-up Study(HPFS)10 in 1986. The populations are primarily composed of Caucasians (96.9% of the NHS and 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, use of medications, including aspirin and vitamin E supplements and in women, post-menopausal hormone use and menopausal status. Information on height and parental history of myocardial infarction (MI) was obtained on the baseline questionnaire. Physical activity was assessed repeatedly using a previously validated questionnaire on frequency of activity over the previous year11,12. 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 first completed the expanded food-frequency questionnaire (FFQ) in 1984, and again in 1986, 1990, 1994, 1998 and 2002. In the HPFS, we assessed dietary information using the FFQ 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 FFQs are high when compared with multiple one-week diet records and biochemical markers1315.
We created a summary diet score based on the Alternate Healthy Eating Index (AHEI)16, which is a variation of the USDA Healthy Eating Index designed to measure adherence to US Dietary Guidelines17. We included eight of nine components of the AHEI in our diet score: higher intakes of vegetables, fruit, nuts, soy and cereal fiber, high ratio of chicken plus fish:red meat and polyunsaturated: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 this component (yes=7.5, no=2.5 points). For the remaining components, the possible scores ranged from 0 to 10, depending on level of intake, where 10 signified optimal dietary behavior. Our diet score ranged from 2.5 (worst) to 77.5 (best).
We considered two additional dietary scores. The low-sodium Dietary Approaches to Stop Hypertension (DASH) diet score measures adherence to key components of the DASH diet18, which in clinical trials significantly lowers blood pressure19, a strong risk factor for stroke. The eight 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 six-nutrient diet score, previously associated with lower risk of CHD within the NHS3, but positively associated with stroke in the Women’s Health Study (WHS)20. The six nutrients, selected based on 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: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 5–40 (DASH) or 6–30 (6-nutrient).
Definition of low-risk lifestyle
We considered five lifestyle factors for our low-risk lifestyle -- smoking, exercise, diet, BMI and alcohol consumption -- based on the strength of evidence on risk of coronary heart disease3,4, diabetes5 and stroke20. For each lifestyle factor, we created a binary variable, where the participant received 1 if they 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 minutes/day 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 grams/day, with an upper limit of 15 day for women and 30 g/day in men, consistent with guidelines for moderate alcohol intake in the US21. Finally, optimal weight was defined as BMI <25 kg/m2 during mid-life (at baseline). In secondary analyses, we used most recent BMI prior to stroke diagnosis. Results were essentially the same when we defined low-risk for BMI as 18.5 <25 kg/m2 (data not shown).
Outcome Ascertainment
Confirmed strokes were defined using the National Survey of Stroke criteria22, 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 and 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 unknown22. Approximately 90% of the stroke cases classified as probable were of unknown type. The exclusion of probable strokes did not alter the results, and therefore 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, death or the end of follow-up in January (HPFS) or June (NHS) of 2004. We used the cumulative average of the diet scores from repeated dietary assessments, to represent long-term dietary information and reduce measurement error as described previously23. We stopped updating dietary information after new diagnoses of diabetes, angina, hypertension, hypercholesterolemia, coronary heart disease, transient ischemic attack or revascularization surgery. Mid-life 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 (RR) and 95% confidence intervals (CI) were estimated using Cox proportional hazards models stratified on age (in months) and calendar year of the questionnaire cycle. All models were adjusted for parental history of MI before 60(yes/no), regular aspirin use(yes/no) and vitamin E supplementation(yes/no) and use of hormone therapy for women(current vs. not current use). Further adjustment for history of hypertension, hypercholesterolemia or diabetes at baseline did not alter the results greatly. As 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%CI24. We compared individuals in the low-risk category with the rest of the population25. To allow for valid calculation of the PAR%, the RRs were estimated with age explicitly in the multivariate model24, using pooled logistic regression models26. When calculating the PAR%, individuals with missing values (<2% over all questionnaires) were placed in the high-risk category, to give the most conservative estimate. Although the distributive property is technically invalid when confounding is present25, the PAR% obtained was the same when all low-risk factors were entered in 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 more than one low-risk factor.
We stratified our models by 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.
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 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 2% 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/day). Among men the pattern was similar, although the relative risks 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; supplementary table). Mid-life BMI was more strongly associated with risk of stroke than most recent BMI (data not shown).
Table 1
Table 1
Relative risk (95% confidence intervals)* of stroke by categories of lifestyle factors in women and men
In general, the associations between lifestyle factors and risk of hemorrhagic stroke followed a similar pattern as with 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 confidence intervals. Therefore we focused on ischemic and total stroke for the remaining analyses.
Not smoking, optimal BMI, daily exercise and moderate alcohol were independent predictors of total stroke among the women (Table 2). Not smoking, optimal BMI and daily exercise 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 (Figure 1). Women and men who were adherent to all 5 low-risk factors had ~80% lower risk of ischemic stroke compared to women and men who had no low-risk factors.
Table 2
Table 2
Relative risk (95% confidence intervals) of stroke by individual low-risk factors in women and men
Figure 1
Figure 1
Figure 1
Relative risk and 95% confidence intervals for ischemic (A) and total (B) stroke by low-risk lifestyle score. Low-risk for each lifestyle factor was defined as not currently smoking, BMI<25 kg/m2, exercise moderate/vigorous intensity for ≥30 (more ...)
The risk of stroke among women and men in specific low-risk categories for three, four and five lifestyle factors are presented in Table 3. The PAR% for women and men with a low-risk lifestyle were greatest for ischemic stroke. For individuals at low-risk for all five 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.
Table 3
Table 3
Population attributable risk (PAR%) of stroke by low-risk lifestyle in women and men
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 most recent, rather than baseline, BMI (PAR%:49% in women, 31% in men) and when we used 0.1 g alcohol/day 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 dietary scores (PAR:54%) compared to 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 confidence intervals were not mutually exclusive (data not shown) and therefore all three diets performed relatively comparably to each other.
Smoking is a strong determinant of risk of disease, thus we looked separately among non-smokers. The PAR% among non-smokers at low-risk for the other 4 lifestyle factors was 40% (95%CI:8%, 65%) for total and 48% (95%CI:6%, 76%) for ischemic stroke among women. Among men, the PAR% was 32% for total and 50% for ischemic stroke.
In these two 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 mid-life) 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 stroke 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 CVD3, 80% of CHD3 and 90% of diabetes5 were attributed to not following a low-risk lifestyle defined by these same five factors. In the HPFS, 62% of CHD and 79% of CHD among men <65 were attributed to these same 5 factors4. Among men and women ≥70 years old, 61% of cardiovascular deaths may have been avoided through a healthy diet, moderate alcohol, daily exercise and not smoking7.
While many studies have focused on low-risk characteristics and risk of total CVD, 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 for 10 years, women with the healthiest lifestyle score, defined as never smoked, BMI<22 kg/m2, exercising ≥4 times/week, consuming ½ to 1 ½ drinks/day and following a healthy diet had a RR of 0.29 (95%CI: 0.14, 0.63) for ischemic stroke compared to women with the least healthy lifestyle20. Similarly, we found a RR for ischemic stroke of 0.19 in women and 0.21 in men, comparing the healthiest to 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/day in women; >30 g alcohol/day in men)27. Stamler et al found a low-risk lifestyle, defined as cholesterol<200 mg/dl, blood pressure<120/80 mmHg and not smoking, was associated with 52–76% lower risk of total stroke mortality in several cohorts, although the analyses were limited by few stroke deaths (<15 in any cohort)28.
We found that mid-life BMI was a stronger predictor of stroke than current BMI, as seen with other diseases2931. The association between obesity and risk of chronic disease is complicated and can be obscured by reduction in body weight due to pre-clinical or chronic disease. BMI measured during mid-life may be less influenced by underlying disease processes and may more accurately reflect the true relation between body weight and stroke risk31. 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 risk32. Because strokes often occur among the elderly, other measures, such as waist circumference or waist:hip ratio, may provide better assessment of obesity-related risk3335.
Although the impact of alcohol on stroke risk is unclear, we included moderate alcohol intake in our low-risk lifestyle. While heavy alcohol consumption (>2 drinks/d) may increase risk of stroke, the evidence for light to moderate alcohol intake has been mixed, showing both null and inverse associations with ischemic stroke risk36. In this study, we found a J-shaped association for both ischemic and hemorrhagic stroke, with increased risk at heavier 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 30–40% lower risk of CVD16. Additionally, we explored a dietary score based on the low-sodium DASH diet, due to its beneficial impact on blood pressure in clinical trials19 and a previously defined 6-nutrient diet score, which was unexpectedly associated with a greater risk of stroke in the WHS20. All three 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 WHS analysis20. 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 v. 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 non-differential with respect to disease status and would underestimate the true relative risk. 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 questionnaires1114. Although we attempted to control for any potential confounding variables, the possibility of residual confounding remains.
The PAR% is a population specific calculation, dependent on the prevalence of the exposure as well as its association with disease risk. The risk estimates between lifestyle factors and stroke are most likely generalizable to other populations, as 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 importantly prevalence of extreme levels of unhealthy behaviors, is greater in the US population than in our cohorts. For example, the prevalence of US adults with a BMI under 25 is 32%, compared to 59% of women and 46% of men in our cohorts and 32% of adults in the US are obese (BMI ≥30) compared with only 11% of women and 8% of men in these populations37. 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.
In conclusion, 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.
Supplementary Material
01
Acknowledgments
Funding Sources
This study was supported by NIH grants HL35464, HL34594, HL088521, CA55075 and CA87969.
Footnotes
Conflict of Interest Disclosures
None
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