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(Circulation. 2008;117:3062-3069.)
© 2008 American Heart Association, Inc.
Epidemiology |
From the Department of Clinical Epidemiology, Aarhus University Hospital, Aalborg, Denmark (M.K.J., K.O.); Center for Cardiovascular Research (M.K.J., C.D., A.M.J., K.O.) and Department of Cardiology (A.M.J., K.O.), Aalborg Hospital, Aarhus University Hospital, Aalborg, Denmark; Department of Nutrition, Harvard School of Public Health, Boston, Mass (S.E.C., E.B.R.); Department of Epidemiology, Harvard School of Public Health, Boston, Mass (E.B.R.); Department of Medicine, Channing Laboratory, Brigham and Womens Hospital, Harvard Medical School, Boston, Mass (E.B.R.); and Institute of Cancer Epidemiology, Danish Cancer Society, Copenhagen, Denmark (A.T.).
Correspondence to Majken K. Jensen, Department of Clinical Epidemiology, Aarhus University Hospital, Sdr Skovvej 15, DK-9100 Aalborg, Denmark. E-mail mkj{at}dce.au.dk
Received December 14, 2007; accepted April 4, 2008.
| Abstract |
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Methods and Results— We followed up 54 783 women and men from the prospective Danish Diet, Cancer and Health study who were 50 to 64 years at baseline (1993 to 1997) and free of coronary artery disease and cancer. During a median of 7.7 years, 1127 incident cases of acute coronary syndrome (ACS) occurred. After multivariable adjustments, each unit of body mass index was associated with a 5% and 7% higher risk of ACS among women and men, respectively (both P<0.0001 for trend). Overweight (body mass index, 25 to 29.9 kg/m2) and obesity (body mass index
30 kg/m2) were associated with a higher risk of ACS among the physically active and inactive, in nonsmokers and smokers, and among those who adhered more or less to a heart-healthy dietary pattern. Obese individuals who were active 1 to 3.5 h/wk had a lower risk than sedentary, obese individuals. In addition, obese nonsmokers had a lower risk than obese smokers. Adherence to a healthy diet was associated with a lower risk of ACS; however, the relative risk was not different among obese individuals with the most healthy diet versus obese individuals with a less healthy diet.
Conclusions— Obesity confers an elevated risk of ACS in both healthy and less healthy subgroups of lifestyle behaviors. Adherence to healthy lifestyle behaviors was associated with a lower risk even among obese individuals.
Key Words: acute coronary syndrome epidemiology lifestyle nutrition obesity risk factors
| Introduction |
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Editorial p 3057
Clinical Perspective p 3069
American and European guidelines for cardiovascular risk reduction include aims for modifying the following behavioral risk factors: an unhealthy diet, smoking, and a sedentary lifestyle.6,7 Thus, although weight loss may be a long-term goal, these lifestyle factors can be modified over the short term, and cardiovascular benefits may be gained, even among the obese. It has been suggested by some,8,9 but not all,10–13 that physical fitness or activity may alleviate the cardiovascular risk associated with obesity. However, little is known about the cardiovascular risk associated with obesity in the context of other behavioral lifestyle factors. In light of the growing obesity epidemic, we find it of interest to explore whether obesity is associated with a lower risk in individuals whose lifestyle is otherwise healthy compared with individuals with less healthy lifestyle behaviors. Therefore, we report here an analysis of the associations of obesity combined with physical activity, smoking, and a Mediterranean diet with risk of acute coronary events in a prospective population-based study of 54 783 middle-aged men and women.
| Methods |
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Measures Obtained by Clinical Examination
Height and weight were measured at 2 study clinics by trained laboratory technicians and recorded to the nearest half-centimeter and 100 g, respectively. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared. A single measurement of blood pressure after 5 minutes of rest also was obtained, and serum total cholesterol was determined.
Measures Obtained by Self-Administered Questionnaires
Participants completed a lifestyle questionnaire at the study clinic. Smoking status was reported as current, former (years since quitting), never, duration of smoking in years, and the number of cigarettes, cigars, and cheroots/pipe smoked per day. Current tobacco consumption was calculated in grams per day by summing the reported numbers per day using conversion factors of 1 for cigarettes, 4.5 for cigars, and 3 for cheroots or pipe. Leisure-time physical activity during the past year was assessed from questions about average number of hours per week spent on 6 types of activities (walking, gardening, housework, home maintenance, sports, and biking) during summer and winter. Moderate to vigorous physical activity was defined as average hours per week spent on sport activities and biking (including as a mean of transport). Length of education was collected in predefined categories (<8, 8 to 10, and >10 years). Participants were asked whether a physician had ever diagnosed them with hypertension, diabetes, or hypercholesterolemia and whether they took medication for these conditions. Among women, we used information on menstruations during the previous year and use of hormone replacement therapy to define their menopausal status (premenopausal, perimenopausal, and postmenopausal with and without use of hormone replacement therapy).
Dietary information was obtained by a detailed, 192-item food-frequency questionnaire, which the study participants had received by mail before the visit to the study clinic. A description of the development and validation of the food-frequency questionnaire has previously been published.15,16 Participants were asked how often they consumed each food item on average over the past year. There were 12 choices for frequency of intake, ranging from "never or less than once per month" to "8 times or more per day." Total nutrient intake was calculated with the software program FoodCalc17 by multiplying the frequency of consumption of each food by the nutrient content of the specified portion and then summing the nutrient across all contributing foods. We used the Mediterranean diet score developed by Trichopoulou et al18 to estimate adherence to a heart-healthy diet in this Danish population. Recently, a modified version of this score, in which monounsaturated fats are replaced by all unsaturated fats, has been suggested to make its application more suitable to countries where olive oil is not the main source of unsaturated fatty acids.19 To calculate this modified diet score, sex-specific medians of 8 dietary components were estimated. Participants received 1 point if their intake was above the median for vegetables, legumes, fruits and nuts, cereals, fish, and the ratio of unsaturated to saturated fat. One point also was assigned if the consumption of meat and dairy products was below the median. The score ranged from 0 (least healthy) to 8 (most healthy). Although moderate alcohol intake (defined as 10 to 50 g/d among men and 5 to 25 g/d for women) was included in the original score, we considered it a separate lifestyle factor.
End Point and Validation
Information on the disease end point was obtained by linkage with central Danish registries via the unique identification number assigned to all Danish citizens.20 We identified participants who were registered with a first-time discharge diagnosis of acute coronary syndrome (ACS; unstable angina pectoris and nonfatal and fatal acute myocardial infarction; International Classification of Diseases [ICD], eighth revision, codes 410 to 410.99 and 427.27; and ICD-10 codes I20.0, I21.x, and I46.x) in the Danish National Register of Patients, which covers all hospital discharge diagnoses since 1977 and all discharge diagnoses from outpatient clinics since 1995 (until January 1, 2004).21 Hospital records of potential cases were retrieved from hospitals and reviewed by 3 reviewers. Cases were classified according to symptoms, signs, coronary biomarkers, ECGs, and/or autopsy findings in accordance with the current recommendations of the American Heart Association and the European Society of Cardiology as described by Luepker et al.22 A detailed description of the validation study is in press.22a Other validation studies have indicated that myocardial infarctions are recorded with a high degree of validity in this register.23 Furthermore, linkage to the Cause of Death Register allowed identification of participants with ACS coded as a primary or secondary cause of death (to January 1, 2004).
Statistical Analysis
The present study included a total of 54 783 participants who were free of coronary artery disease at baseline and for whom complete information on height, weight, and the chosen behavioral factors was available. We used World Health Organization cutoffs for healthy weight (BMI <25 kg/m2), overweight (25.0 to 29.9 kg/m2), and obesity (
30 kg/m2). For the behavioral factors, participants were categorized into nonsmokers (never/past), light current smokers (1 to 14 g/d), and heavy current smokers (
15 g/d). Categories for moderate to vigorous physical activity were as follows: <1, 1 to 3.49, and
3.5 h/wk; for the Mediterranean diet score, they were 0 to 2, 3 to 4, and 5 to 8; and for alcohol, they were <5, 5 to 25, and
25 g/d for women and <10, 10 to 50, and
50 g/d for men.
The observation time for each participant was the period from enrollment in the cohort (between December 1993 and May 1997) until the date of a registered nonfatal or fatal ACS event (n=1127), death resulting from other causes (n=2512), emigration (n=236), loss to follow-up (n=4), or January 1, 2004, whichever came first. Incidence rates were calculated by dividing the number of events by the accumulated person-time of follow-up within the groups of BMI. Cox proportional-hazards regression with age as the underlying time axis was performed to ensure that the estimation procedure was based on comparisons of individuals at the same age (STATA versus 9.1 program software, Stata Corp, College Station, Tex).24 Multivariable-adjusted models included smoking, physical activity, Mediterranean diet score, alcohol, education, and menopausal status among women. Proportional-hazards assumptions were tested in models including time-by-covariate interactions, and no violations were detected. Smoothing splines with 5 df were used to assess nonlinear associations of continuous variables.
To determine the combined effects of obesity and the behavioral factors, the BMI groups were cross-tabulated with each factor. Because we found no statistically significant sex-based differences, we combined men and women and allowed for sex-specific baseline hazards. We also examined the association of BMI and ACS in participants with and without existing diagnoses of the important clinical intermediates: hypertension, diabetes, and hypercholesterolemia. Results were similar when these clinical risk factors were defined according to self-reported physician diagnoses or by using the clinical measures of blood pressure and serum cholesterol. Statistical interaction was assessed on the multiplicative scale by deviance tests based on comparisons of –2 log likelihood in nested models with and without cross-product terms.
Because undiagnosed illness might bias our results, we compared the association between BMI and ACS in analyses including cases that occurred within the first 2 years of follow-up versus analyses that included cases that occurred after 2 years of follow-up. Further sensitivity analyses were performed by repeating analyses after the exclusion of unstable angina from the ACS end point (n=62). The results were similar in these analyses (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.
| Results |
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During a median follow-up of 7.7 years, 1127 incident cases of ACS were registered and verified. The association between BMI and ACS was strong and graded. Women and men who were healthy weight (BMI <25 kg/m2) had the lowest risk of ACS, and a higher BMI was associated with an incrementally higher risk of ACS (Table 2). We did not detect any departures from a linear association between BMI and ACS when using smoothing splines. After multivariable adjustments, each unit of BMI was associated with a 5% and 7% higher risk among women and men, respectively (both P<0.0001 for trend). Further adjustment for the clinical intermediates attenuated the associations, although obesity (BMI
30 kg/m2) remained statistically significantly associated with a higher risk of ACS among both women and men. Although the relative risk associated with obesity was of smaller magnitude among men than women, the absolute risk was substantially higher among men (differences in the unadjusted incidence rates between the healthy weight and obese individuals, 304 and 112 cases per 100 000 person-years among men and women, respectively). Smoking, not engaging in moderate to vigorous physical activity, a low adherence to the Mediterranean diet, and having the lowest alcohol intake were all associated with a higher risk of ACS, as were the diagnoses of hypertension, diabetes, and hypercholesterolemia (Table 3).
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Overweight and Obesity Combined With Behavioral Factors
In Table 4, we show that a higher BMI was associated with a higher risk of ACS in all 3 groups of physical activity, in smokers and nonsmokers, in those with a healthy and a less healthy diet, and among those with and without a moderate alcohol intake. Overweight (BMI, 25 to 29.9 kg/m2) and obesity (BMI
30 kg/m2) were strongly associated with risk of ACS regardless of smoking status; being a heavy smoker also was associated with a high risk of ACS in all BMI groups. Compared with the joint reference group of nonsmokers who were healthy weight (BMI <25 kg/m2), the risk associated with obesity was lower in nonsmokers (hazard ratio [HR], 2.35, 95% CI, 1.81 to 3.05) than in heavy smokers (HR, 3.74; 95% CI, 2.71 to 5.15).
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A low level of physical activity was associated with a higher risk of ACS in both healthy-weight and overweight individuals. Among the obese individuals, we did not see a clear trend for physical activity, but compared with the most physically active (
3.5 h/wk) who were healthy weight, the HR among obese individuals who were moderately active (1 to 3.5 h/wk) was lower than the HR among the obese who were physically inactive (<1 h/wk) (HR, 1.92, 95% CI, 1.42 to 2.59; and HR, 2.74; 95% CI, 2.04 to 3.68, respectively).
A higher BMI was associated with a higher risk of ACS across all groups of the Mediterranean diet score and alcohol intake. In overweight and healthy-weight individuals, greater adherence to the Mediterranean diet was associated with a lower risk of ACS, whereas the risk among obese individuals was not different among those who scored high on this dietary pattern and those with a less heart-healthy diet.
Only 8% of the participants were in the healthiest group of all 4 behavioral lifestyle risk factors (physically active
3.5 h/wk, nonsmoking, highest score on the Mediterranean diet scale, and a light to moderate alcohol intake), and only 47 cases of ACS occurred in this group during follow-up. Among these participants characterized by an overall healthy lifestyle, the HRs for ACS were 1.65 (95% CI, 0.82 to 3.22) for the overweight and 2.65 (95% CI, 1.12 to 6.27) for the obese (data not shown).
Overweight and Obesity Combined With Clinical Risk Factors
We also addressed whether obesity was associated with risk of ACS among individuals with and without preexisting diagnoses of the clinical intermediates (hypertension, hypercholesterolemia, and diabetes). BMI was strongly associated with risk of ACS among participants who did not have these conditions and among hypercholesterolemic participants. Among diabetic and hypertensive participants, the associations between BMI and ACS were not as strong; however, very few participants were diagnosed with diabetes in this cohort (<3%). The highest risk was consistently observed among participants who were both obese and diagnosed with any of the 3 clinical risk factors (Table 5).
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| Discussion |
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Few studies have explored obesity combined with potentially modifiable behavioral lifestyle factors in relation to coronary heart disease risk. However, detailed investigations of the relationship between obesity and physical activity/fitness is an important exception because their relative importance as predictors of cardiovascular risk remains an area of controversy.10–13,25 Although we had few participants who were both obese and physically active, our results are generally in line with cohort studies from Finland,11 Norway,13 and the US Nurses Health Study.10 These studies all suggest that both obesity and self-reported physical activity are important independent predictors of future coronary heart disease. Contrary observations have been reported from the Aerobics Center Longitudinal Study, in which body fatness was not associated with a higher risk of cardiovascular death among those who were physically fit as measured by a treadmill exercise test.25 Self-assessed physical activity and measures of fitness may not fully capture the same information because physical fitness is not determined solely by habitual physical activity but also reflects genetics and underlying diseases.26 We did not have measures of cardiorespiratory fitness available in our study; however, our findings are comparable to those observed in the Lipids Research Clinics Study, in which physical fitness also was measured.12
Our analysis extends the ongoing discussion of the role of body fatness among those who are physically active or fit by including 2 other well-established behavioral risk factors incorporated into international guidelines for cardiovascular disease reduction. We found that obese individuals had a considerable lower risk if they were nonsmokers compared with smokers. Smoking is a modifiable behavioral risk factor that adds substantially to the cardiovascular risk in all BMI groups of the population, and advice to quit seems applicable to both normal-weight and obese individuals. Although we observed that adherence to a Mediterranean style diet was associated with a lower risk of ACS, this dietary pattern was not strongly associated with risk among the obese individuals. The scoring system we used to operationalize this dietary pattern relies on strong epidemiological evidence for the individual dietary components; in addition, the score has been validated and shown to strongly predict morbidity and mortality in several European populations.18,19 However, we cannot exclude that a different dietary score might capture a healthy Nordic eating pattern better and that this could have a stronger association with ACS across all BMI groups. In addition, we found that BMI was associated with a higher risk across groups of alcohol intake.
BMI is an easily obtainable measure that remains widely used as an indicator of overweight and obesity.11,27–29 Although other adiposity measures such as waist circumference may better capture the adverse metabolic changes that are likely to mediate the association between obesity coronary heart disease,30 we found a strong and graded association between BMI and ACS. A strength of our study is the use of directly obtained measures of height and weight of all participants, which diminishes the potential bias toward a higher risk of ACS at lower BMI ranges resulting from possible understated weight in obese individuals.31 Recent weight loss before the baseline examination as a result of undiagnosed symptoms of cardiovascular illness could have biased our results toward a higher risk of ACS at lower levels of BMI. However, we observed a direct association between BMI and risk when cases that occurred during the first 2 and subsequent years of follow-up were considered.
Whether obesity exerts independent and direct effects on coronary atherosclerosis progression and cardiovascular disease beyond its strong association with established clinical risk factors remains controversial.32–37 Currently used risk functions for the prediction of coronary events in the general population do not include measures of excess body weight because it is considered to affect risk indirectly through more proximal physiological and metabolic factors such as blood pressure, lipid levels, and diabetes.38 Results from the present study support other studies that have found that obesity predicts risk of cardiovascular disease incidence and mortality beyond the established clinical conditions.27,32,35,37,39 Improvements in the understanding of adipose tissue as a metabolically active tissue that secretes various adipokines such as leptin, adiponectin, resistin, interleukin-6, and tumor necrosis factor-
suggest that further knowledge of less conventional risk factors associated with insulin resistance, inflammation, and thrombosis is needed to fully elucidate the mechanisms behind the obesity-associated cardiovascular risk.40
This prospective study has its major strengths in its size, minimal loss to follow-up, and use of validated end-point data. In the validation of all incident cases of ACS that occurred during 10 years of follow-up, we used the most recently suggested definition.22 Exclusion of the subjects who had confirmed unstable angina pectoris rendered our results somewhat stronger, supporting the graded gravity of the subdiagnoses included in this syndrome.
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| Acknowledgments |
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Source of Funding
The Diet, Cancer and Health study was funded by the Danish Cancer Society.
Disclosures
Dr Rimm has funding from Sanofi/Aventis to study the association between obesity and chronic disease in separate populations. The remaining authors report no conflicts.
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| Footnotes |
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Presented at the American Heart Association 47th Annual Conference on Cardiovascular Disease Epidemiology and Prevention in association with the Council on Nutrition, Physical Activity, and Metabolism, and published in abstract form (Circulation. 2007;115:e214–e301).
Related Article:
Circulation 2008 117: 3055-3056.
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