 |
|
HEALTH CARE REFORM
Healthy Living Is the Best RevengeFindings From the European Prospective Investigation Into Cancer and Nutrition–Potsdam Study
Earl S. Ford, MD, MPH;
Manuela M. Bergmann, PhD;
Janine Kröger;
Anja Schienkiewitz, PhD, MPH;
Cornelia Weikert, MD, MPH;
Heiner Boeing, PhD, MSPH
Arch Intern Med. 2009;169(15):1355-1362.
ABSTRACT
Background Our objective was to describe the reduction in relative risk of developing major chronic diseases such as cardiovascular disease, diabetes, and cancer associated with 4 healthy lifestyle factors among German adults.
Methods We used data from 23 153 German participants aged 35 to 65 years from the European Prospective Investigation Into Cancer and Nutrition–Potsdam study. End points included confirmed incident type 2 diabetes mellitus, myocardial infarction, stroke, and cancer. The 4 factors were never smoking, having a body mass index lower than 30 (calculated as weight in kilograms divided by height in meters squared), performing 3.5 h/wk or more of physical activity, and adhering to healthy dietary principles (high intake of fruits, vegetables, and whole-grain bread and low meat consumption). The 4 factors (healthy, 1 point; unhealthy, 0 points) were summed to form an index that ranged from 0 to 4.
Results During a mean follow-up of 7.8 years, 2006 participants developed new-onset diabetes (3.7%), myocardial infarction (0.9%), stroke (0.8%), or cancer (3.8%). Fewer than 4% of participants had zero healthy factors, most had 1 to 3 healthy factors, and approximately 9% had 4 factors. After adjusting for age, sex, educational status, and occupational status, the hazard ratio for developing a chronic disease decreased progressively as the number of healthy factors increased. Participants with all 4 factors at baseline had a 78% (95% confidence interval [CI], 72% to 83%) lower risk of developing a chronic disease (diabetes, 93% [95% CI, 88% to 95%]; myocardial infarction, 81% [95% CI, 47% to 93%]; stroke, 50% [95% CI, –18% to 79%]; and cancer, 36% [95% CI, 5% to 57%]) than participants without a healthy factor.
Conclusion Adhering to 4 simple healthy lifestyle factors can have a strong impact on the prevention of chronic diseases.
INTRODUCTION
Many of the major chronic diseases, such as cardiovascular disease (CVD), cancer, and diabetes, which together comprise the overwhelming burden of mortality, are in large part preventable. An impressive body of research has implicated modifiable lifestyle factors such as smoking,1 physical activity,2 diet,3-5 and body weight6 in the causes of these diseases.
Previous studies have already demonstrated the potential that healthy lifestyle factors can have on reducing the risk of major chronic diseases.7-13 However, the adverse effects of smoking, physical inactivity, unhealthy diet, and excess body weight echo across multiple outcomes. Thus, a study of the potential reduction in chronic disease morbidity by these lifestyle factors would be instructive and informative for those making health policy decisions and allocating resources to prevention, in particular if specific combinations of those factors are considered. Therefore, our objective was to examine the extent to which 4 major lifestyle factors and their combinations are associated with reduced risk of developing 4 leading causes of morbidity and mortality, ie, diabetes, coronary heart disease (CHD), stroke, and cancer.14 Recognizing that other lifestyle choices can affect the risk of future chronic disease, we limited our analyses to not smoking, being physically active, adhering to healthy dietary principles, and avoiding excess body weight because these 4 healthy behaviors constitute a core set included in previous studies examining the effect of healthy lifestyles on morbidity and mortality. We did not include moderate use of alcohol as a potentially beneficial behavior given the adverse health impact of excessive use.
METHODS
STUDY POPULATION
The European Prospective Investigation Into Cancer and Nutrition (EPIC)-Potsdam study is part of the multicenter prospective cohort EPIC study.15-16 In Potsdam, Germany, men aged 40 to 65 years and women aged 35 to 65 years from the general population were invited to join the study. Between 1994 and 1998, 27 548 adults (16 644 women and 10 904 men) consented to participate.15 The baseline examination included anthropometric measurements, a personal interview that included questions on prevalent diseases, a questionnaire on sociodemographic and lifestyle characteristics, and a food frequency questionnaire. Follow-up questionnaires to identify incident cases of CHD, stroke, diabetes mellitus, and cancer were administered every 2 to 3 years, with response rates of 95% on average. For this analysis, we considered the follow-up period until December 2006. Consent was obtained from all those participating in the study, and approval was given by the ethics committee of the State of Brandenburg, Germany.
After excluding participants who were younger than 35 years or older than 65 years at recruitment (n = 263) and those who never completed a follow-up questionnaire (n = 721), those who self-reported diabetes, CVD, or cancer at baseline (n = 3130), those with unresolved prevalent or incident status of 1 of the 4 chronic conditions (n = 287), and those who had missing information for a lifestyle factor (n = 247) or missing covariates (n = 18), 23 153 participants (8965 men and 14 188 women) were included in our analyses.
ASCERTAINING INCIDENT CHD, STROKE, DIABETES, AND CANCER
Potential incident diseases were identified primarily using self-reports of the respective conditions and, additionally, self-reported medication (for diabetes, CHD, or stroke), reasons for a reported change in diet (all conditions), specific symptoms (stroke),17 or death information (all conditions). All potential incident diseases were verified through medical records from which the correct diagnosis, the date, and the means of confirmation of the diagnosis were abstracted to a standard inquiry form by the treating or study physician. Diseases were defined as incident when the date of diagnosis was later than the date of enrolment into the study. The diagnosis of CHD was based on the World Health Organization MONICA (Multinational Monitoring of Trends and Determinants in Cardiovascular Disease) criteria.18 Additional cancer cases were identified using record linkage with a cancer registry that is approximately 80% complete. Diseases were coded based in the International Statistical Classification of Diseases, 10th Revision (ICD-10) codes I21 for CHD; E11 for diabetes; I160, I161, I163, and I164 for stroke; and C00 to C97 for cancer (except C44: nonmelanoma skin cancer).
HEALTHY LIFESTYLE FACTORS
The study investigated 4 lifestyle factors (smoking status, body mass index [BMI; calculated as weight in kilograms divided by height in meters squared], physical activity, and diet). Each factor was dichotomized into 2 categories, healthy (1 point) and unhealthy (0 points). Healthy lifestyle factors included never smoking, a BMI lower than 30, engaging in physical activity for 3.5 h/wk or more, and healthy dietary pattern, as evidenced by having a value above the median of the summed z scores. Anthropometric measurement procedures followed standard protocols under strict quality control.19-20 Physical activity included the time spent doing sports and bicycle riding, which is a common mode of transportation in the Potsdam area. The consumption of fruits and vegetables, whole grain bread, and red meat reported on a food frequency questionnaire were used to construct a dietary score. For each of these variables that were expressed in grams of intake per day, we created a z score ([value – mean]/standard deviation) and then summed the 3 z scores. The z score for red meat consumption was set up in such a way that eating less red meat yielded higher positive z scores. The consumption of fish and fowl was not part of the dietary score. The food frequency questionnaire used in the EPIC-Potsdam study has been shown to have satisfactory reliability and validity.21 The correlation coefficients (corrected for intraindividual variation in dietary recall data) between the food frequency questionnaire and twelve 24-hour dietary recalls for energy-adjusted intake were 0.67 for meat, 0.54 for fruits, 0.42 for vegetables, and 0.54 for bread. A correlation coefficient specific to whole grain bread was not calculated.
COVARIATES
We included the following covariates that were assessed with a self-administered questionnaire and a personal interview during the baseline data collection: age, sex, educational attainment (no vocational training completed, vocational training completed, technical school, or university), occupational status (unemployed, employed full time, employed part time, hourly worker, or retired), marital status, number of adults and children living in the household, and alcohol consumption. Although we elected not to include moderate intake of alcohol as one of the healthy lifestyle factors, we did include the use of alcohol as a potential confounder. Daily intake of alcohol consumption (grams per day) was measured with a food frequency questionnaire.
STATISTICAL ANALYSIS
Cox proportional hazards analysis was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Age was used as the primary time-dependent variable in all models, with entry time defined as the subject's age at recruitment and exit time as the age at diagnosis of the chronic disease of interest, death, or return of the last follow-up questionnaire, whichever came first. Analyses were stratified by age at baseline and adjusted for baseline information including sex, education, and occupational status. All analyses were performed with SAS statistical software (release 9.1; SAS Institute Inc, Cary, North Carolina).
RESULTS
The mean (SD) age of the sample was 49.3 (8.8) years (men, 51.2 [7.9] years; women, 48.2 [9.1] years) at baseline. Approximately 37.6% had basic training at school, 24.8% had completed vocational training or technical school, and 37.6% had completed technical college or a university education. Furthermore, 63.4% worked full time, 8.0% worked part time, 2.2% were hourly workers, 10.5% were unemployed, and 16.0% were receiving retirement payments.
The mean and median follow-up times were 7.8 and 8.2 years, respectively. In all, 2006 participants (1081 men and 925 women) were clinically diagnosed as having 1 of the 4 study outcomes: 1868 participants had 1 event, 134 had 2 events, and 4 had 3 events. Among the 2006 participants with an incident disease, 871 had diabetes (43.4%), 214 had a myocardial infarction (10.7%), 195 had a stroke (9.7%), and 868 had cancer (43.2%). Approximately 84% of participants had a BMI lower than 30, 48% had never smoked, 50% had a healthy score for diet, and 32% participated in physical activity for at least 3.5 h/wk (Figure 1). Approximately 4% of participants had zero healthy factors at baseline, most had 1 to 3 healthy factors, and approximately 9% had 4 factors.
|
|
|
|
Figure 1. Distribution of healthy lifestyle factors among 23 153 participants aged 35 to 65 years (European Prospective Investigation Into Cancer and Nutrition–Potsdam study). BMI indicates body mass index (calculated as weight in kilograms divided by height in meters squared); PA, physical activity.
|
|
|
Although the percentage of participants with zero healthy factors was limited, a substantial number of adverse events occurred in this category, thus providing a solid baseline rate (Table 1). After adjusting for age, sex, educational status, and occupational status, the risk decreased substantially as the number of healthy lifestyle factors increased. Thus, participants with 4 healthy factors had a 78% (95% CI, 72%-83%) reduction in risk compared with those with none (P value for linear trend, <.001). We also examined additional models in which we adjusted for marital status, the number of adults in the household, the number of children in the household, and alcohol consumption and alcohol consumption squared at baseline. These additional adjustments, however, had little effect on the adjusted HR (aHR) (0.22; 95% CI, 0.17-0.28) and were not included in the models for parsimonious reasons. Reductions in risk were similar for men (reduction of 84%; 95% CI, 73%-90%) (P value for linear trend, <.001) and women (reduction of 72%; 95% CI, 60%-81%) (P value for linear trend, <.001) (P value for interaction between sex and lifestyle factors, .26).
|
|
|
|
Table 1. Adjusted HRs for Incident Chronic Disease (Cancer, Diabetes, Myocardial Infarction, and Stroke) During Almost 8 Years of Follow-up Among 23153 Participants Aged 35 to 65 Years From the European Prospective Investigation Into Cancer and Nutrition–Potsdam Study
|
|
|
Each healthy lifestyle factor was associated with a reduction in risk of any chronic disease after taking age, sex, educational status, occupational status, and the other lifestyle factors into account (Figure 2). In this comparison, a BMI lower than 30 exerted the largest reduction in risk, followed by never smoking, physical activity for 3.5 h/wk or more, and adhering to good dietary principles. Judging by the magnitude of the HRs, never smoking exerted a stronger protective effect on incident myocardial infarction and diabetes than on stroke and cancer. A BMI lower than 30 was a particularly strong protective factor for incident diabetes. Physical activity for 3.5 h/wk or more was a stronger protective factor for incident diabetes and myocardial infarction than for cancer. Finally, adhering to good dietary principles provided a similar degree of protection for incident diabetes, stroke, and cancer.
|
|
|
|
Figure 2. Adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for incident chronic disease (cancer, diabetes, myocardial infarction, and stroke) by individual healthy factors. Data for 23 153 participants aged 35 to 65 years from the European Prospective Investigation Into Cancer and Nutrition–Potsdam study were used. Results are stratified by age and adjusted for sex, education status, and occupational status. Individual healthy lifestyle factors are also adjusted for each other. BMI indicates body mass index (calculated as weight in kilograms divided by height in meters squared); PA, physical activity.
|
|
|
The 4 dichotomized healthy factors yielded 16 combinations. The aHRs for these combinations were calculated using participants who had no healthy factors as the reference group (Table 2). The smallest aHR was observed for participants with all 4 healthy factors (aHR, 0.23; 95% CI, 0.18-0.29). However, participants who never smoked and had a BMI lower than 30 had an aHR of the same order of magnitude (aHR, 0.28; 95% CI, 0.23-0.34). Other combinations of 2 healthy factors that also resulted in marked reductions in risk included having a BMI lower than 30 and participating in physical activity for 3.5 h/wk or more (aHR, 0.36; 95% CI, 0.29-0.45) as well as participating in physical activity for 3.5 h/wk or more and practicing good dietary behavior (aHR, 0.34; 95% CI, 0.22-0.54). When comparing the observed with the expected HRs for the 16 combinations using the information of the individual factors given in Table 1, the expected HRs were similar to the observed HRs for all combinations but one. The combination of participating in physical activity for 3.5 h/wk or more and practicing good dietary behavior yielded an expected HR of 0.69 compared with an observed HR of 0.34.
|
|
|
|
Table 2. Adjusteda HRs for Incident Chronic Disease (Cancer, Diabetes, Myocardial Infarction, Stroke) by Combination of Individual Healthy Factors Among 23 153 Participants Aged 35 to 65 Years From the European Prospective Investigation Into Cancer and Nutrition–Potsdam Study
|
|
|
The biggest impact of the 4 healthy lifestyle factors was on incident diabetes (Figure 3). Compared with participants with no healthy factors, those with all 4 healthy factors had reductions of 93% (95% CI, 88% to 95%) for diabetes (P value for linear trend, <.001), 81% (95% CI, 47% to 93%) for myocardial infarction (P value for linear trend, <.001), 50% (95% CI, –18% to 79%) for stroke (P value for linear trend, .054), and 36% (95% CI, 5% to 57%) for cancer (P value for linear trend, <.001). The prevented fractions were 75% for diabetes, 45% for myocardial infarction, 18% for stroke, and 19% for cancer.
|
|
|
|
Figure 3. Adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for incident diabetes, myocardial infarction, stroke, and cancer by number of healthy factors. Data for 23 153 participants aged 35 to 65 years from the European Prospective Investigation Into Cancer and Nutrition–Potsdam study were used. Results are stratified by age and adjusted for sex, educational status, and occupational status.
|
|
|
We included smoking status as one of the healthy factors, but these results are only applicable to a population of people who had never smoked. Because current smokers can only revert to former smokers but not to never smokers, we decided to conduct a separate set of analyses that examined the 3 healthy factors (BMI <30, physical activity for  3.5 h/wk, and adhering to good dietary principles) among participants who were never smokers, former smokers, and current smokers (Table 3). Among the 3 subgroups, reductions in the risk of developing a chronic disease ranged from 47% to 53% for participants with 1 healthy factor, from 59% to 64% among participants with 2 such factors, and from 68% to 71% among participants with 3 such factors (P value for linear trend, <.001 for all 3 groups).
|
|
|
|
Table 3. Adjusted HRs (95% CIs) for Incident Chronic Disease (Cancer, Diabetes, Myocardial Infarction, and Stroke) by Smoking Status During Almost 8 Years of Follow-up Among 23153 Participants Aged 35 to 65 Years From the European Prospective Investigation into Cancer and Nutrition–Potsdam Study
|
|
|
COMMENT
The message from our analysis of the data from the EPIC-Potsdam study is clear: adopting a few healthy behaviors can have a major impact on the risk of morbidity. The participants with all 4 healthy lifestyle factors had a reduced risk of major chronic diseases of almost 80% compared with those with none. These results applied equally to men and women.
Our results reinforce current public health recommendations to avoid smoking, to maintain a healthy weight, to engage in physical activity appropriately, and to eat adequate amounts of fruits and vegetables and foods containing whole grains and to partake of red meat prudently. By focusing our analyses on conditions that are among the leading causes of mortality in industrialized societies and that are on the rise in developing countries rather than on separate diseases, we have broadened the implications of our findings.
Although improvements in some behaviors have occurred, notably, the decline in the prevalence of smoking, substantial proportions of the population still engage in behaviors that are not conducive to achieving and maintaining health. Our data show that in this German cohort, approximately 9% of the participants met criteria for all 4 healthy lifestyle factors. Similarly, only a small fraction of the populations met recommendations for multiple lifestyle behaviors in US studies.22 Thus, the opportunity to improve many of the lifestyle behaviors of people abounds. The public health community and clinicians can all contribute to helping people adopt and maintain healthy lifestyle behaviors.
The potential for preventing morbidity and mortality from CVD, diabetes, and cancer through healthy living is enormous. For example, it is estimated that each year 565 000 people have a first myocardial infarction and 500 000 have a first stroke,23 1.3 million adults develop diabetes,24 and 1.4 million develop cancer25 in the United States. In addition, 221 000 deaths were attributable to myocardial infarction and 273 000 to stroke in 2002,23 69 301 deaths to diabetes in 2000,24 and almost 560 000 deaths to cancer.25
IN THE CONTEXT OF THE PREVIOUS STUDIES
Our findings build and expand on those from other prospective studies that have examined the relationships between the number of healthy lifestyle factors and various end points. Of the 84 129 participants of the Nurses' Health Study,7 1128 of whom developed a coronary event during 14 years of follow-up, those who were at low risk had a relative risk of developing CHD of 0.17 (95% CI, 0.07-0.41). The lifestyle factors considered were not currently smoking, a BMI lower than 25, alcohol consumption of at least 0.5 drinks per day, at least 0.5 hours of moderate to vigorous physical activity per day, and adhering to several dietary elements (increased intake of cereal fiber, marine omega-3fatty acids, and folate; increased ratio of polyunsaturated fats to saturated fats; and low trans fat intake and glycemic load). Another analysis8 of this same cohort showed that women who were at low risk as evidenced by practicing a healthy lifestyle had a substantially reduced risk of developing diabetes (3300 events during 16 years of follow-up) (relative risk, 0.09; 95% CI, 0.05-0.17). The behaviors of interest were similarly specified, but the dietary variable was modified.
Among 2539 participants of the Healthy Aging: a Longitudinal Study in Europe,26 the aHR was 0.35 (95% CI, 0.28-0.44) for those with all 4 factors of interest (Mediterranean diet, moderate alcohol use, physical activity, and not smoking) compared with those not engaging in any of these factors.
In an analysis of data from 37 636 participants aged 45 years or older from the Women's Health Study,10 450 of whom developed a stroke during a mean 10 years of follow-up, the aHRs for participants who scored higher on an index of lifestyle factors than those who scored lower were 0.45 (95% CI, 0.24-0.83) for total stroke, 0.29 (95% CI, 0.14-0.63) for ischemic stroke, and 1.27 (95% CI, 0.37-4.29) for hemorrhagic stroke. Lifestyle factors considered in this study were smoking, alcohol use, exercise, BMI, and diet.
In the Health Professionals Follow-up Study,9 42 847 men aged 40 to 75 years were followed up over 16 years, and 2183 developed a coronary event. Compared with men with no healthy lifestyle factors, those with all 5 factors had a large reduction in the risk of developing CHD (HR, 0.13; 95% CI, 0.09-0.19). The lifestyle factors in this study were characterized in much the same way as in the previous studies.
In an analysis of 15 708 participants in the Atherosclerosis Risk in Communities Study,11 those who adopted a healthy lifestyle experienced a lower risk of all-cause mortality (odds ratio, 0.60; 95% CI, 0.39-0.92) and CVD (odds ratio, 0.65; 95% CI, 0.39-0.92) during 4 years of follow-up. The 4 healthy lifestyles considered were eating 5 or more fruits and vegetables per day, exercising 2.5 h/wk or more, having a BMI between 18.5 and 30.0, and not smoking.
Among 20 244 participants in the EPIC-Norfolk study,12 sizeable reductions in all-cause mortality were demonstrated with increasing numbers of health factors. Participants with all 4 factors (current not smoking, not physically inactive, moderate alcohol use, and plasma vitamin C level greater than 0.88 mg/dL [to convert to micromoles per liter, multiply by 56.78] as a surrogate for fruit and vegetable consumption) had an advantage of approximately 14 years in chronological age over those without 1 of the 4 factors.
Finally, analyses of data from 43 685 participants in the Health Professionals Follow-up Study (994 strokes) and 71 243 participants in the Nurses' Health Study (1559 strokes) showed substantial reductions in the risk of developing an incident stroke among men (relative risk, 0.31; 95% CI, 0.19-0.53) and women (relative risk, 0.21; 95% CI, 0.12-0.36) who practiced a low-risk lifestyle compared with those who did not.13 Men were followed up from 1984 to 2004, and women were followed up from 1986 to 2004. The lifestyle factors considered were not currently smoking, at least 30 minutes of moderate to vigorous physical activity per day, a diet score in the top 40%, alcohol consumption of 5 to 15 g/d for women and 5 to 30 g/d for men, and a BMI lower than 25.
We showed that each lifestyle factor was associated with a reduction in risk and that the reduction in risk from combinations of factors followed the multiplicative model. This finding implies that each factor contributes to risk reduction independently of the other factors in the estimated magnitude. The only exception was the combination of diet index above the median and physical exercise, which showed a larger risk reduction as estimated from the relative risk of the single factors. The favorable effect on the risk of developing chronic disease of these 2 factors was likely partially mediated through BMI. The previous prospective studies that examined the effect of healthy factors on adverse outcomes did not examine the effects of different combinations of lifestyle factors on outcomes. Because our findings may have occurred by chance, the results of other studies investigating the effects of healthy lifestyle on incident chronic disease will be valuable in gauging the significance of this result.
In contrast to some of these studies, we elected not to include moderate use of alcohol as a potentially beneficial behavior. Because of the well-documented harms caused by alcohol abuse,27 a great deal of reluctance exists in the public health community to recommend drinking moderately for fear that the message will be misinterpreted and viewed as endorsing unfettered alcohol use. Although moderate alcohol consumption may add to the risk reduction generated by the other 4 behaviors, any recommendations regarding moderate use of alcohol will require a thoughtful evaluation of whether potential benefits outweigh the clear harms of alcohol abuse.
STUDY LIMITATIONS
Our results should be considered in the light of several limitations. The assessment of end points was based on self-reported information with physician confirmation. Thus, some proportion of incident end points remained undetected. If the association between the exposures and the end points was similar for detected and undetected end points, our HRs should be unbiased.28 Second, information about the lifestyle factors except BMI was self-reported and thus is subject to information bias and misclassification. If the misclassification were random, our HRs would have been attenuated. Third, we used a few simple concepts to define adherence to good dietary principles. However, other approaches to characterizing good dietary practices exist and could generate different results. Finally, the results of this study are generalizable to the German population where the study was conducted. Additional studies in other populations will be needed to evaluate how much of chronic disease morbidity and mortality is potentially preventable in other populations.
CONCLUSIONS
The data from the EPIC-Potsdam study show the unfulfilled potential of preventing chronic diseases. Adhering to recommendations for the 4 lifestyle factors considered in our analyses can potentially yield enormous reductions in the onset of major chronic diseases such as CVD, diabetes, and cancer. For those with none of the factors, achieving even 1 promises to increase the time free of the 4 chronic conditions, and further gains accrue as the number of such factors increases. However, our findings also illustrate the heterogeneity in potential risk reduction that exists among the various combinations of healthy factors, a finding that expands on the previous literature concerning the relationships between healthy lifestyle factors and the incidence of chronic disease. Our results and those of others emphasize the importance and urgency of continuing vigorous efforts to convince people to adopt healthy lifestyles. Because the roots of these factors often originate during the formative stages of life, it is especially important to start early in teaching the important lessons concerning healthy living.29
AUTHOR INFORMATION
Correspondence: Earl S. Ford, MD, MPH, Division of Adult and Community Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, 4770 Buford Hwy, Mail Stop K-66, Atlanta, GA 30341 (eford{at}cdc.gov).
Accepted for Publication: May 1, 2009.
Author Contributions: Dr Ford had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Ford and Boeing. Acquisition of data: Bergmann, Schienkiewitz, Weikert, and Boeing. Analysis and interpretation of data: Ford, Bergmann, Kröger, and Boeing. Drafting of the manuscript: Ford. Critical revision of the manuscript for important intellectual content: Bergmann, Kröger, Schienkiewitz, Weikert, and Boeing. Statistical analysis: Ford. Obtained funding: Boeing. Administrative, technical, and material support: Bergmann, Kröger, Schienkiewitz, Weikert, and Boeing.
Financial Disclosure: None reported.
Funding/Support: The recruitment phase of the EPIC-Potsdam study was supported by the Federal Ministry of Science, Germany (contract 01 EA 9401) and the European Union (grant SOC 95201408 05F02). The follow-up of the EPIC-Potsdam study was supported by the German Cancer Aid (grant 70-2488-Ha I) and the European Community (grant SOC 98200769 05F02). The study was also supported by a grant from the German Research Foundation (Deutsche Forschungsgemeinschaft, KFO 114).
Disclaimer: The findings and conclusions in this article are those of the authors and do not represent the official position of the Centers for Disease Control and Prevention.
Additional Information: The work for this article was performed while Dr Ford was a guest researcher at the German Institute of Human Nutrition.
Author Affiliations: Division of Adult and Community Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia (Dr Ford); Department of Epidemiology, German Institute of Human Nutrition (Deutsches Institut für Ernährungsforschung), Potsdam-Rehbrücke, Germany (Drs Bergmann, Schienkiewitz, Weikert, and Boeing and Ms Kröger).
REFERENCES
1. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health. The Health Consequences of Smoking: A Report of the Surgeon General. Washington, DC: US Government Printing Office; 2004.
2. US Department of Health and Human Services. Physical Activity and Health: A Report of the Surgeon General. Atlanta, GA: US Dept of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion; 1996.3. World Cancer Research Fund. Food, Nutrition and the Prevention of Cancer: A Global Perspective. Washington, DC: WCRF and American Institute for Cancer Research; 1997.4. Franz MJ, Bantle JP, Beebe CA; et al. Evidence-based nutrition principles and recommendations for the treatment and prevention of diabetes and related complications. Diabetes Care. 2002;25(1):148-198.
FREE FULL TEXT
5. Lichtenstein AH, Appel LJ, Brands M; et al, American Heart Association Nutrition Committee. Diet and lifestyle recommendations revision 2006: a scientific statement from the American Heart Association Nutrition Committee. Circulation. 2006;114(1):82-96.
FREE FULL TEXT
6. National Institutes of Health. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults—the evidence report. Obes Res. 1998;6(suppl 2):51S-209S.
WEB OF SCIENCE
| PUBMED
7. 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(1):16-22.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
8. Hu FB, Manson JE, Stampfer MJ; et al. Diet, lifestyle, and the risk of type 2 diabetes mellitus in women. N Engl J Med. 2001;345(11):790-797.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
9. 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(2):160-167.
FREE FULL TEXT
10. Kurth T, Moore SC, Gaziano JM; et al. Healthy lifestyle and the risk of stroke in women. Arch Intern Med. 2006;166(13):1403-1409.
FREE FULL TEXT
11. King DE, Mainous AG III, Geesey ME. Turning back the clock: adopting a healthy lifestyle in middle age. Am J Med. 2007;120(7):598-603.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
12. Khaw KT, Wareham N, Bingham S, Welch A, Luben R, Day N. Combined impact of health behaviours and mortality in men and women: the EPIC-Norfolk prospective population study. PLoS Med. 2008;5(1):e12.
FULL TEXT
| PUBMED
13. Chiuve SE, Rexrode KM, Spiegelman D, Logroscino G, Manson JE, Rimm EB. Primary Prevention of Stroke by Healthy Lifestyle. Circulation. 2008;118(9):947-954.
FREE FULL TEXT
14. National Center for Health Statistics. Health, United States, 2007, With Chartbook on Trends in the Health of Americans. Hyattsville, MD: National Center for Health Statistics; 2007.15. Boeing H, Korfmann A, Bergmann MM. Recruitment procedures of EPIC-Germany: European Investigation into Cancer and Nutrition. Ann Nutr Metab. 1999;43(4):205-215.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
16. Riboli E, Hunt KJ, Slimani N; et al. European Prospective Investigation into Cancer and Nutrition (EPIC): study populations and data collection. Public Health Nutr. 2002;5(6B):1113-1124.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
17. Berger K, Hense HW, Rothdach A, Weltermann B, Keil U. A single question about prior stroke versus a stroke questionnaire to assess stroke prevalence in populations. Neuroepidemiology. 2000;19(5):245-257.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
18. Tunstall-Pedoe H, Kuulasmaa K, Amouyel P, Arveiler D, Rajakangas AM, Pajak A. Myocardial infarction and coronary deaths in the World Health Organization MONICA Project: registration procedures, event rates, and case-fatality rates in 38 populations from 21 countries in four continents. Circulation. 1994;90(1):583-612.
FREE FULL TEXT
19. Klipstein-Grobusch K, Georg T, Boeing H. Interviewer variability in anthropometric measurements and estimates of body composition. Int J Epidemiol. 1997;26(suppl 1):S174-S180.
FREE FULL TEXT
20. Kroke A, Bergmann MM, Lotze G, Jeckel A, Klipstein-Grobusch K, Boeing H. Measures of quality control in the German component of the EPIC study: European Prospective Investigation into Cancer and Nutrition. Ann Nutr Metab. 1999;43(4):216-224.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
21. Bohlscheid-Thomas S, Hoting I, Boeing H, Wahrendorf J. Reproducibility and relative validity of food group intake in a food frequency questionnaire developed for the German part of the EPIC project: European Prospective Investigation into Cancer and Nutrition. Int J Epidemiol. 1997;26(suppl 1):S59-S70.
FREE FULL TEXT
22. Ford ES, Ford MA, Will JC, Galuska DA, Ballew C. Achieving a healthy lifestyle among United States adults: a long way to go. Ethn Dis. 2001;11(2):224-231.
PUBMED
23. Rosamond W, Flegal K, Friday G; et al, American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics–2007 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation. 2007;115(5):e69-e171.
FREE FULL TEXT
24. Centers for Disease Control and Prevention. National Diabetes Fact Sheet United States, 2003. http://www.cdc.gov/diabetes/pubs/pdf/ndfs_2003.pdf. Accessed on July 12, 2007.25. American Cancer Society. Cancer Facts & Figures 2007. http://www.cancer.org/downloads/STT/CAFF2007PWsecured.pdf. Accessed on July 12, 2007.26. Knoops KT, de Groot LC, Kromhout D; et al. Mediterranean diet, lifestyle factors, and 10-year mortality in elderly European men and women: the HALE project. JAMA. 2004;292(12):1433-1439.
FREE FULL TEXT
27. Room R, Babor T, Rehm J. Alcohol and public health. Lancet. 2005;365(9458):519-530.
WEB OF SCIENCE
| PUBMED
28. Rothman KJ, Greenland S. Modern Epidemiology. 2nd ed. Philadelphia, PA: Lippincott-Raven; 1998.29. McGill HC, McMahan CA, Gidding SS. Are pediatricians responsible for prevention of adult cardiovascular disease? Nat Clin Pract Cardiovasc Med. 2009;6(1):10-11.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
 CiteULike  Connotea  Delicious  Digg  Facebook  Reddit  Technorati  Twitter
What's this?
RELATED ARTICLES
In This Issue of Archives of Internal Medicine
Arch Intern Med. 2009;169(15):1350.
FULL TEXT
Life and Death, Knowledge and Power: Why Knowing What Matters Is Not What's the Matter: Comment on "Healthy Living Is the Best Revenge"
David L. Katz
Arch Intern Med. 2009;169(15):1362-1363.
EXTRACT
| FULL TEXT
THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES
|
Dairy Products and Cancer
Lampe
J. Am. Coll. Nutr. 2011;30:464S-470S.
ABSTRACT
| FULL TEXT
Adherence to a Low-Risk, Healthy Lifestyle and Risk of Sudden Cardiac Death Among Women
Chiuve et al.
JAMA 2011;306:62-69.
ABSTRACT
| FULL TEXT
Following Cancer Prevention Guidelines Reduces Risk of Cancer, Cardiovascular Disease, and All-Cause Mortality
McCullough et al.
Cancer Epidemiol. Biomarkers Prev. 2011;20:1089-1097.
ABSTRACT
| FULL TEXT
Primary prevention of stroke: blood pressure, lipids, and heart failure
Endres et al.
Eur Heart J 2011;32:545-552.
ABSTRACT
| FULL TEXT
Is prevention a fantasy, or the future of medicine? A panoramic view of recent data, status, and direction in cardiovascular prevention
Kones
Ther Adv Cardiovasc Dis 2011;5:61-81.
ABSTRACT
Association of adherence to lifestyle recommendations and risk of colorectal cancer: a prospective Danish cohort study
Kirkegaard et al.
BMJ 2010;341:c5504-c5504.
ABSTRACT
| FULL TEXT
School-Based Physical Activity and Fitness Promotion
Racette et al.
ptjournal 2010;90:1214-1218.
FULL TEXT
Influence of Individual and Combined Health Behaviors on Total and Cause-Specific Mortality in Men and Women: The United Kingdom Health and Lifestyle Survey
Kvaavik et al.
Arch Intern Med 2010;170:711-718.
ABSTRACT
| FULL TEXT
Healthy Living and Risk of Major Chronic Diseases in an Older Population
Gopinath et al.
Arch Intern Med 2010;170:208-209.
FULL TEXT
Comparative Effectiveness Research (CER): Opportunities and Challenges for the Nutritional Industry
Kaats et al.
J. Am. Coll. Nutr. 2009;28:234-237.
FULL TEXT
|
