Primary Preventive Potential for Stroke by Avoidance of Major Lifestyle Risk Factors
The European Prospective Investigation Into Cancer and Nutrition-Heidelberg Cohort
Background and Purpose—Because primary prevention of stroke is a priority, our aim was to assess the primary preventive potential of major lifestyle risk factors for stroke in middle-aged women and men.
Methods—Among 23 927 persons, 551 (195 women and 356 men) had a first diagnosis of stroke during an average follow-up of 12.7 years. Using Cox proportional hazards models, we estimated the associations of adiposity, smoking, physical activity, alcohol consumption, and diet with risk of developing stroke. A competing risk model built from cause-specific proportional hazards models accounting for concurrent risk of death was used to calculate relative and absolute reductions in stroke occurrences that could have been achieved by maintaining a healthy lifestyle pattern.
Results—Obesity, smoking, alcohol consumption, diet, and physical inactivity were each identified as modifiable lifestyle risk factors for stroke. About 38% of stroke cases were estimated as preventable through adherence to a healthy lifestyle profile (never smoking, maintaining optimal body mass index and waist circumference, performing physical exercise, consuming a moderate quantity of alcohol, and following a healthy dietary pattern). Age-specific estimates of 5-year incidence rates for stroke in the actual cohort and in a hypothetical, comparable cohort of individuals following a healthy lifestyle would be reduced from 153 to 94 per 100 000 women and from 261 to 161 per 100 000 men for the age group 60 to 65 years.
Conclusions—Our analysis confirms the strong primary prevention potential for stroke based on avoidance of excess body weight, smoking, heavy alcohol consumption, unhealthy diet, and physical inactivity.
Large epidemiological studies have identified several primary modifiable risk factors for stroke, including smoking, overall and abdominal obesity, alcohol consumption, diet, and physical inactivity.1–5 In addition, prospective cohort studies have provided estimates on the overall reduction in stroke risk that may be obtained by maintaining a healthy lifestyle.6,7
Because primary prevention of stroke is a priority, knowledge is required about the primary risk factors that should be targeted through generalized prevention campaigns and about the overall part of stroke occurrences that could be prevented. In this context, it is relevant not only to estimate relative increases or reductions in the occurrence of stroke, in terms of relative risk and population attributable fractions, but also to estimate the effects that prevention measures may have on individuals’ absolute risks in terms of age-specific incidence rates and lifetime cumulative risks. The estimation of age-specific incidence rates, overall or for individuals with low- or high-risk lifestyle profiles, allows comparisons not only within a given study cohort but also across study populations and can underscore to both policymakers and individuals the importance that primary prevention can have for avoidance of major disease outcomes.
Here, we present results from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Heidelberg, a cohort of middle-aged men and women recruited around the town of Heidelberg, in South-West Germany. In particular, we examined associations of modifiable lifestyle factors with the risk of stroke and quantified both relative and absolute reductions in stroke occurrences that could be achieved by maintaining a comprehensive, healthy lifestyle pattern.
Study Population and Methods
EPIC-Heidelberg is a prospective cohort study that is a part of a large-scale Europe-wide study, the EPIC. The full EPIC-Heidelberg cohort consists of 25 540 persons comprised of 11 928 men aged 40 to 64 years and 13 612 women aged 35 to 64 years, who were recruited between 1994 and 1998 from the general population around Heidelberg. All participants gave informed consent at the study entry, which was approved by the ethical committee of Heidelberg University Medical School. A detailed description of the study design, the data collected at recruitment, and during prospect follow-up for the EPIC-Heidelberg was previously published.8 Briefly, at baseline, all individuals completed a general questionnaire and a computer-guided interview about basic demographic factors, prevalent diseases, and lifestyle factors. For all study participants, weight, height, hip, and waist circumferences were measured by trained study nurses, following a standardized protocol. Detailed description of lifestyle factors and classification of variables used in this study is described in the online-only Data Supplement.
Prospective Ascertainment of Stroke Cases
Since baseline recruitment, at regular 3-year intervals information about incident diseases was collected by means of a self-administered questionnaire, and the prospective ascertainment of incident stroke cases was complemented by regular record linkages to the University Clinics of Heidelberg and Mannheim. Information on vital status was collected through municipal population registries. All cases of stroke were systematically verified by a trained study physician and in collaboration with a neurologist, who jointly reviewed relevant medical records and official death certificates. All cases were then coded according to the International Classification of Diseases, 10th Revision (ICD-10) and classified as ischemic stroke (ICD-10 I63), intracerebral or subarachnoid hemorrhage (ICD-10 I61, ICD-10 I60), or undetermined stroke (ICD-10 I64). Only first-ever verified stroke cases with a diagnosis date were considered as the confirmed incident cases of stroke. This study reports follow-up data until December 2009 (4 rounds of follow-up). Participants who had reported a previous diagnosis of stroke at baseline recruitment were excluded (n=238).
All analyses were performed separately for men and women. We estimated the preventive potentials of major lifestyle risk factors for stroke by looking at the reduction in stroke risk, at both the individual and the population level. This was done through fitting multivariable Cox models, which were then combined in a competing risk framework, considering death before occurrence of stroke as the competing event. Age was used as the underlying time scale, modeling delayed entry by left truncation. A detailed description of the statistical analysis used in this study is reported previously9 and described in the online-only Data Supplement. All analyses were performed with R (the R foundation for Statistical Computing, Vienna, Austria).
During an average follow-up period of 12.7 years, 551 persons including 356 men and 195 women developed stroke. Furthermore, 814 cases of death occurred among men and 436 among women without previous occurrence of stroke. General characteristics of the study population at baseline and number of observed stroke events are presented in Table 1.
In Cox proportional hazards models, anthropometric indices for both general obesity (body mass index) and abdominal obesity (waist circumference) were related with an increased risk of stroke in men and women, although in multivariable models these associations were no longer significant, with the exception of abdominal obesity among women (Table 2). Regarding physical activity, women engaging in any level of physical activity, compared with the inactive category of our combined physical activity index, showed a reduced risk of stroke, which persisted after controlling for the other variables in the study. In men, by contrast, the risk estimates by different levels of physical activity categories were weaker and mostly not statistically significant. Irrespective of controlling for other lifestyle factors, subjects who reported current smoking at the time of recruitment had an ≤2-fold risk increase in risk of stroke compared with never smokers, among both men and women. For alcohol, no statistically significant association between average lifetime consumption levels and stroke risk was observed among women. Among men, those with the highest level of lifetime mean alcohol consumption (>60 g/d) had a significant 57% increase in risk (hazard ratio=1.57; 95% confidence interval, 1.11–2.23) compared with the reference group, although this association was reduced after adjustment for the other lifestyle factors. The healthiest diet score was inversely associated with stroke risk in men but not in women.
Absolute risk models, accounting for the competing risk of death, predicted 316 stroke cases among the men in our cohort (compared with 356 cases actually observed) and 180 stroke cases among the women (195 actually observed) during the follow-up period. The time-truncated concordance index C(t)—a measure for the predictive ability of our competing risk model—at ages 50, 55, 60, and 65 was estimated as 66.9, 65.5, 62.1, and 60.2 for the men and 58.7, 57.6, 60.3, and 58.6 for the women, respectively (data not shown).
Figure 1A and 1B shows the cumulative incidence function of stroke using the competing risk model. For a 42-year-old man with a high-risk profile (current smoker, obese with large waist circumference, physically inactive, with high alcohol consumption, and unhealthy diet score), who had no stroke to date, the model predicted a 13.1% absolute risk of developing stroke by the age of 75 years. Likewise, for a 38-year-old woman with a high-risk profile, the predicted absolute risk was 17.2%. By comparison, for a man or a woman with the healthiest risk profile (never smoking, optimal body weight [body mass index] and waist circumference, physically active, consuming a moderately low quantity of alcohol, and having a healthy diet score), the estimated absolute risks to develop stroke by age 75 years were 5.3% and 2.7%, respectively.
In terms of overall preventable fraction, the predicted number of stroke cases would be reduced by 21.5% for men and 27.2% for women if all persons in our study population had maintained an optimal body mass index and waist circumference (Table in the online-only Data Supplement). About 37.0% of stroke cases among men and 37.8% of stroke cases among women could have been prevented if the study participants had lived with the healthy lifestyle profile as defined above. It is important to point out that the respective reductions of stroke cases without inclusion of diet in our models would be 32.6% for men and 42.8% for women, respectively.
Figure 2A and 2B shows the substantial disparity in the predicted 5-year incidence rates for stroke in the actual study population and in a hypothetical, comparable cohort with the healthy lifestyle profile, which would be reduced from 261 to 161 per 100 000 (38.3% reduction) men and from 153 to 94 per 100 000 (38.5% reduction) women in the age group of 60 to 65 years.
The present prospective study confirms that obesity, smoking, heavy alcohol consumption, unhealthy diet, and physical inactivity are significant lifestyle risk factors for stroke among middle-aged men and women. For the actual study population, and for a hypothetical, comparable population where all individuals would have avoided excess body weight, abdominal obesity, smoking, high alcohol consumption, physical inactivity, and unhealthy diet, differences in the predicted 5-year incidence rates for stroke were observed. Overall, our estimates indicate that ≈38% of stroke cases could have been prevented if the study participants had lived with the healthy lifestyle profile as defined above.
Our basic findings for the 2 strongest lifestyle risk factors—smoking and excess body weight—are much in line with those from previous studies, which also showed 2-fold and higher increases in risk among current smokers compared with nonsmokers1,2,5 and increased risks among both men and women with abdominal obesity, especially, as defined by large waist circumference.1,3 Furthermore, being a former smoker was not associated with stroke risk, showing that cessation of smoking is effective in stroke prevention.5 In contrast to the well-documented influence of smoking and obesity, the relationship of alcohol consumption with stroke risk is more controversial. Existing evidence suggests a J-shaped association, where the consumption of >60 g of alcohol per day may increase the risk of stroke by >60%, whereas moderate consumption levels of <12 g/d has been associated with a 15% to 20% risk reduction in comparison with abstainers.1,10 Our data showed a tendency toward a risk increase for stroke among men with a history of relatively heavy alcohol consumption (>60 g/d) but no clear association among women. By contrast, no evidence for a possible protective effect of light alcohol consumption against stroke was found, contrary to findings from some previous studies.6,10
The association between stroke risk and physical activity has been studied extensively but with inconsistent results varying from no or a weak association7,11 to moderately strong relationships.1,12,13 Some studies also showed sex-specific associations.12,13 Taken together, however, the results from these studies do suggest that lack of any physical activity is a relevant modifiable risk factor for stroke. In our study, women who reported any level of physical activity above the lowest inactive level showed a major reduction in the risk of stroke, in the order of 50%. Our results thus seem to confirm earlier interpretations that moderately intense levels of physical activity are sufficient to achieve a risk reduction among women and that more intense activity may not confer any further benefit.12 In line with a previous study, we observed that adherence to a Dietary Approach to Stop Hypertension–style diet contributes to the prevention of stroke risk.6 Interestingly, this association was not present among women in our cohort.
Our combined risk factor analysis indicated that ≈38% of primary stroke occurrences could have been prevented in our study population if all study participants had maintained the healthiest risk profile (optimal body weight/waist circumference, not smoking, moderate alcohol consumption, physically active, and following a healthy dietary pattern). Similar and sometimes even greater estimates of lifestyle-related attributable risks have been reported from other prospective studies, and it has been proposed that ≤60 or even 90% of stroke cases might be preventable through lifestyle modifications (eg, not smoking, optimal body mass index, physical activity equivalent to >30 minutes/d of walking, moderate alcohol consumption, and healthy diet), in combination with the avoidance of other important risk factors, such as hypertension and type-2 diabetes mellitus.2,4,14 For comparison, however, it should be mentioned that our analysis did not include any measures of blood pressure, blood lipids, or other preclinical indicators of stroke risk because such factors would most likely reflect intermediate factors on the pathway between lifestyle and disease development, whereas our primary aim was to estimate the potential for stroke prevention specifically with respect the up-front, primary lifestyle risk factors.
With regard to incidence rates, we estimated average age-specific risks in our study cohort to be ≈261/100 000 for men and 153/100 000 for women in the age range of 60 to 65, which is relatively comparable to the rates reported from regional stroke registries in different German subpopulations (eg, Ludwigshafen and Erlangen). Within Germany, estimates from these registries indicate corresponding rates for 55- to 64-year-old persons varying from 188 to 368 for men and from 203 to 240 for women.15,16 Studies in Europe and Asia indicate ≤8-fold variation in 1-year incidence rates ranging from ≈100/100 000 in Italy17 to 330 to 433/100 000 in The Netherlands and Japan18,19 and with relatively extreme values as high as from 500 to 800/100 000 in Ukraine and Russia20,21 for men and women aged 55 to 64 years. The incidence rates in Germany and in our cohort thus lay within the midrange of the rates reported worldwide.
Our estimated stroke incidence rates in a hypothetical population of men and women with the healthy lifestyle profile were on average 30% to 40% lower compared with the rates in the actual study population. The 5-year incidence rates for women and men with the healthiest lifestyle profile are comparable to the mean rates observed in populations with low incident rates, such as low-risk regions in Italy17 and France.22
With regard to long-term absolute risks as a function of lifestyle profiles, the absolute risk to develop stroke by age 75 years would diminish to 5.3% for men and 2.7% for women if lifestyle factors were modified to the healthiest level. It is worth mentioning that, in a parallel analysis, we and others found similar or even greater differences in the long-term absolute risks of developing myocardial infarction, essentially depending on the same risk factors as those considered in the present analysis.9,23 Taken together, the high absolute lifetime risks for stroke, myocardial infarction, and other chronic diseases among subjects with unhealthy lifestyle patterns, and the large difference with those who had a low-risk pattern, provide a compelling argument to health policymakers, as well as single individuals, to increase efforts for primary prevention and to maintain healthy habits.
Although our study has several strengths—in particular, its prospective design, a reasonably large number of incident cases, and detailed clinical verification and coding of stroke end points—it also has several limitations. In line with conclusions and interpretations from many previous studies, we assumed that to a large extent the risk factors retained for our overall risk modeling were genuine and independent primary determinants of stroke incidence. However, although mutual adjustments between the risk factors could be made in our multivariable risk models, residual confounding biases cannot ever be ruled out entirely. Possible confounding factors that we could not adjust for in our analysis include, for example, chronic (eg, work-related) psychological stress as source of hypertension, socioeconomic determinants of having access to or making use of regular healthcare and health surveillance, and use of antihypertensive drugs or other forms of medication (eg, nonsteroidal anti-inflammatory drugs, lipid-lowering drugs), which, in subsets of cohort, may have been recommended to specifically target increased risk states that may be intermediate between primary lifestyle factors and stroke as an end point.
Finally, as in most observational studies, it is likely that measurement errors caused substantial regression dilution bias in effect estimates of each of the basic lifestyle factors considered in this analysis. The assessments of alcohol consumption, diet, smoking habits, and physical activity levels were all based on self-reports and may not be fully accurate with respect to true exposure levels. The same applies to our anthropometric indices of excess weight, which provide only approximate measures of overall and abdominal adiposity, which are likely to be the true risk determinants. Also, as in many other studies, we did not account for possible changes in smoking or other lifestyle factors during follow-up. Besides a non-negligible underestimation of relative risks and attributable fractions, random assessment errors would also lead to an incomplete differentiation between highest and lowest absolute risk estimates for subjects classified by high- and low-risk factor scores.
In conclusion, our results support previously established classical lifestyle risk factors for stroke and emphasize the importance of avoiding high-risk lifestyle factors for the preventions of stroke. Our estimates show that incidence rates for men and women who adhere to a healthy lifestyle pattern can be as low as those documented for typical low-risk regions in Europe. For increased differentiation between the absolute risks of low- and high-risk individuals, future prospective studies should invest in increasing the accuracy of assessments of lifestyle factors and body composition, including repeat measurements over time. From our and other analyses, it seems that especially smoking and excess body weight are the 2 major risk factors that should be targeted with greatest priority for primary prevention strategies.
We would like to thank Marcus von Hornung and Christoph Neumann for their valuable work to database management in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Heidelberg cohort and all the EPIC-Heidelberg cohort participants for their active participation in the study.
Sources of Funding
This study was funded by the German Federal Ministry of Education and Research.
The online-only Data Supplement is available with this article at http://stroke.ahajournals.org/lookup/suppl/doi:10.1161/STROKEAHA.114.005025/-/DC1.
- Received January 30, 2014.
- Revision received April 8, 2014.
- Accepted April 17, 2014.
- © 2014 American Heart Association, Inc.
- Suk SH,
- Sacco RL,
- Boden-Albala B,
- Cheun JF,
- Pittman JG,
- Elkind MS,
- et al
- Chiuve SE,
- Rexrode KM,
- Spiegelman D,
- Logroscino G,
- Manson JE,
- Rimm EB
- Evenson KR,
- Rosamond WD,
- Cai J,
- Toole JF,
- Hutchinson RG,
- Shahar E,
- et al
- Kiely DK,
- Wolf PA,
- Cupples LA,
- Beiser AS,
- Kannel WB
- Willett WC
- Kolominsky-Rabas PL,
- Sarti C,
- Heuschmann PU,
- Graf C,
- Siemonsen S,
- Neundoerfer B,
- et al
- Palm F,
- Urbanek C,
- Rose S,
- Buggle F,
- Bode B,
- Hennerici MG,
- et al
- Morikawa Y,
- Nakagawa H,
- Naruse Y,
- Nishijo M,
- Miura K,
- Tabata M,
- et al
- Mihalka L,
- Smolanka V,
- Bulecza B,
- Mulesa S,
- Bereczki D
- Feigin VL,
- Wiebers DO,
- Whisnant JP,
- O’Fallon WM
- Lloyd-Jones DM,
- Leip EP,
- Larson MG,
- D’Agostino RB,
- Beiser A,
- Wilson PW,
- et al