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(Chest. 2004;125:1205-1212.)
© 2004 American College of Chest Physicians

Prevalence and Secular Trends of Excess Body Weight and Impact on Outcomes After Myocardial Infarction in the Community*

Francisco Lopez-Jimenez, MD, MSc; Steven J. Jacobsen, MD, PhD; Guy S. Reeder, MD; Susan A. Weston, MS; Ryan A. Meverden, BS and Véronique L. Roger, MD, MPH

* From the Division of Cardiovascular Diseases and Internal Medicine (Drs. Lopez-Jimenez, Reeder, and Roger), Division of Clinical Epidemiology (Dr. Jacobsen), and the Division of Biostatistics (Ms. Weston and Mr. Meverden), Mayo Clinic and Mayo Foundation, Rochester, MN.

Correspondence to: Véronique L. Roger, MD, MPH, Division of Cardiovascular Diseases and Internal Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905; e-mail: roger.veronique{at}mayo.edu


   Abstract
TOP
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 Conclusion
 References
 
Objectives: To determine the trends in the prevalence of overweight and obese individuals among patients with myocardial infarction (MI), and to assess the association between weight and outcomes after MI.

Design: Population-based cohort study.

Methods: MIs occurring in Olmsted County, MN, between 1979 and 1998 were validated using standardized criteria. Clinical characteristics and outcomes were ascertained from community medical records. The prevalence and trends of excess weight and its association with outcomes were analyzed.

Results: Sixty-four percent of the 2,277 subjects with incident MI were overweight or obese. The prevalence of overweight/obese patients increased from 58% in the period from 1979 to 1983, to 72% in the period from 1994 to 1998 (p < 0.001), while the prevalence of class 3 obesity (body mass index >= 40) increased from 0.6 to 4.4%. Overweight and obese patients were more likely to have diabetes, hypertension, familial coronary disease, and hyperlipidemia than persons with normal weight but less likely to have comorbidities (obstructive lung disease, heart failure, cancer, renal failure, and stroke) [all p values < 0.05]. When compared to patients with normal weight, after adjusting for age and other confounders, overweight and obese patients had a lower mortality (risk ratio [RR], 0.84; 95% confidence interval [CI], 0.73 to 0.96 for overweight; and RR, 0.85; 95% CI, 0.72 to 1.02 for obese) and a similar risk of cardiac events.

Conclusion: The prevalence of overweight and obese individuals among patients with MI is high and increased over time. Despite a higher prevalence of other cardiovascular risk factors among patients with excess weight, these patients did not experience worse outcomes, underscoring the need to further study the paradoxical relation between weight and post-MI outcomes.

Key Words: body mass index • myocardial infarction • obesity • outcomes • prevalence


   Introduction
TOP
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 Conclusion
 References
 
Obesity is a worldwide epidemic, the prevalence of which is steadily increasing.1234 Excess weight is associated with higher mortality and cardiovascular events in patients without coronary disease.56 Novel mechanisms whereby excess body fat affects the cardiovascular system were identified, including inflammation, a high turnover of free fatty acids with a lipotoxic effect on myocardial cells, and the effect of leptin on arterial distensibility.7 The American Heart Association declared obesity an independent cardiovascular risk factor,8 and the joint American Heart Association/American College of Cardiology guidelines9 for the management of patients with coronary disease recommend weight loss for patients with body mass index (BMI) >= 25.

Despite the increase in the prevalence of obesity in the population, there are few data on the prevalence of overweight and obese individuals among patients with myocardial infarction (MI). Additionally, the impact of obesity on post-MI outcomes is controversial. While a study10 showed a modest direct association between obesity and recurrent coronary events, others have shown no association,1112 or a paradoxical association between increased body weight and recurrent clinical events.13 These studies, however, had several methodologic issues that limit their inference. Indeed, most were case series, clinical trials, or registries, and are thus subject to selection bias. They seldom ascertained comorbidities such as heart or renal failure, and the ascertainment of outcomes and follow-up may have been incomplete.121314 Thus, there is a gap in knowledge with regards to the effect of body weight on clinical outcomes after MI in populations representative of the entire spectrum of MI and with appropriate ascertainment of potential confounders. Geographically defined populations represent the full spectrum of disease and can contribute to fill this gap in knowledge by providing complete follow-up controlling for baseline characteristics. This study examines the prevalence of overweight and obese individuals, its trend over time, and its association with out-comes in a cohort of MI in the population of Olmsted County, MN.


   Materials and Methods
TOP
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 Conclusion
 References
 
Study Setting
This study was conducted in Olmsted County, MN, where epidemiologic research is possible because it is relatively isolated from other centers and nearly all medical care is delivered to local residents by few providers. With the exception of a higher proportion of the working population employed in the health-care industry, the characteristics of the population of Olmsted County are similar to those of US whites.14 The Mayo Clinic provides approximately half of the primary care and nearly all specialty care for the community. Olmsted Medical Center and its affiliated hospital, along with the Mayo Clinic, provide care in every discipline. The epidemiologic potential in the community is enhanced by the fact that each provider uses a comprehensive medical record system, whereby all data are assembled in one place. Data are easily retrievable because the Mayo Clinic has maintained since the early 1900s extensive indexes based on clinical and histologic diagnoses and surgical procedures. Since 1966, similar indexes have been developed for non-Mayo providers under the aegis of the Rochester Epidemiology Project. This linkage system thus constitutes a unique opportunity to ensure complete ascertainment of tests in defined disease processes.

Data Collection
Assembling the MI Incidence Cohort:
The cohort of incident MI was assembled with standardized surveillance methods described in detail previously.1516 Briefly, all the records of patients discharged between 1979 and 1998 with diagnoses compatible with MI were reviewed by abstractors who verified residency in Olmsted County and collected clinical data. The target Ninth Revision of the International Classification of Disease (ICD-9) codes were 410 (MI), 411 (other acute and subacute forms of ischemic heart disease), 412 (old MI), 413 (angina pectoris), and 414 (other forms of ischemic heart disease). All events coded as 410 were reviewed, while samples of coronary heart disease codes other than codes 410 (411–414) were reviewed using sampling fractions comparable to those used in other studies. ECGs were assigned a Minnesota code by the ECG Reading Center at the University of Minnesota.17

Baseline Characteristics and Ascertainment of Overweight, Obesity, and Other Comorbidities:
The ascertainment of overweight, obesity, and other cardiovascular risk factors was based on the medical records. BMI was calculated by dividing the first body weight value registered in the chart at the time of the index hospitalization (in kilograms) by the square of the height (in meters). Overweight was defined as BMI >= 25 but < 30, obesity as BMI >= 30 but < 40, and obesity class 3 if the BMI was >= 40. Smokers were classified as past, current, or no history of smoking. Current smokers included those who smoked within the 6 months prior to the MI. Clinician’s diagnoses ascertained hyperlipidemia, hypertension, and diabetes mellitus. History of familial coronary disease was defined as first-degree relatives < 55 years old (men) or < 65 years old (women) with history of MI or coronary bypass grafting. Comorbidity was measured with the Charlson index,18 a standardized measure of comorbidity.

The ratio of the peak creatine kinase (CK) to the upper limit of normal was used to assess maximum CK. Reperfusion therapy was defined as thrombolysis or coronary angioplasty within 24 h after symptom onset. Dismissal medications, including beta-blockers, angiotensin-converting enzyme inhibitors, and aspirin were ascertained from the medical record discharge summary.

Ascertainment of Outcomes:
Follow-up for mortality was performed passively through community medical records, death certificates, and obituary notices. In the hospital, vital status was determined at discharge. Thereafter, it was determined from the death certificate or from data obtained from the Minnesota Department of Health in electronic format. Standardized nosologic algorithms were used to determine the cause of death in subjects for whom a state nosologist assignment was not available.

Cardiac causes of death included ICD-9 codes 390–398, 401–405, and 420–429. Sudden cardiac death was defined as having died out of the hospital and having an ICD-9 code 410–414. The occurrence of recurrent MI was ascertained by reviewing the medical record, and based on the documentation of a physician’s diagnosis of a new MI, while excluding statements such as "history of MI," "history of heart attack," "silent MI," and "old infarct by ECG."

Statistical Analysis
Patients with missing body weight (n = 14, 0.6% of the subjects) were not included in the analysis. Analyses were performed using three BMI categories: normal, overweight, and a combination of obesity and class 3 obesity. Changes in the prevalence of BMI category was assessed using the Mantel-Haenszel {chi}2 test for trend. Categorical baseline characteristics were compared across BMI categories using the Mantel-Haenszel {chi}2 test. The change of these associations over time was tested by combining the overweight and obese categories and using the Breslow-Day test for homogeneity of the odds ratios (ORs). Continuous baseline characteristics were compared across BMI categories using the F test from analysis of variance. The outcomes were all-cause death and cardiac event, defined as either cardiac death or recurrent MI. Kaplan-Meier curves were constructed to compare the event-free survival among body weight groups. Proportional hazards regression examined the association between BMI category and outcomes while controlling for age, sex, year of incident MI, hypertension, diabetes mellitus, history of smoking, peak CK ratio, comorbidity, and reperfusion therapy. All analyses were weighted to account for the sampling strategy, where the weights applied were the inverse of the sampling fractions for each ICD-9 target code used to ascertain incident MI. Results of the final selected models were summarized by presenting the relative risk (RR) and 95% confidence interval (CI) for each variable; a p value of 0.05 was selected for the threshold of statistical significance. Analyses were performed using S-Plus statistical software (version 6.0.4; Insightful, Lucent Technologies; Seattle, WA). This study was approved by the Mayo Foundation Institutional Review Board.


   Results
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 Conclusion
 References
 
Baseline Characteristics: Prevalence of Obesity and Other Cardiovascular Risk Factors
Between 1979 and 1998, 2,277 subjects in Olmsted County were hospitalized with an incident MI, and 2,263 patients (99.4%) with a body weight value were included in this analysis. When comparing to patients with normal weight, obese patients were younger (62.8 ± 13.5 years vs 71.9 ± 13.5 years) [mean ± SD], more likely to be men (58% vs 49%), and more likely to have reperfusion therapy (34% vs 20%) [all p < 0.001]. Peak CK ratio was not different between groups (5.3 ± 5.3 vs 5.5 ± 6). At the time of the index MI, excess weight was the most prevalent cardiovascular risk factor, as 40% of the patients were overweight and 24% were obese. The prevalence of class 3 obesity (BMI >= 40) was 2.1%. A history of hypertension was present in 56% of patients, diabetes in 20% of patients, and current smoking in 29% of the patients.

Association of Body Weight With Other Cardiovascular Risk Factors and Comorbidities
Overweight and obesity were associated with a higher prevalence of other risk factors, except for advanced age, sex, and history of smoking. The higher the BMI group, the higher the prevalence of hypertension, diabetes mellitus, history of familial coronary disease, and hyperlipidemia (all p < 0.05; Fig 1 ). Conversely, patients with obesity were less likely to have other comorbidities, including obstructive pulmonary disease, heart failure, cancer, elevated serum creatinine, or history of stroke (all p < 0.05; Fig 2 ).



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  		Figure 1. Prevalence of cardiovascular risk factors by BMI. Normal weight, BMI < 25; overweight, >= 25 and < 30; obese, >= 30; p values represent significance for difference among body groups Hx = history.

 


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  		Figure 2. Prevalence of comorbidities by BMI group. CHF = congestive heart failure. See Figure 1 legend for other definition.

 
The secular trends of overweight and obesity are presented in Table 1 . When compared to patients with a MI in 1979 to 1983, patients who had an MI in 1994 to 1998 were more likely to be either overweight or obese (72% vs 58%, p < 0.001), to be obese (33% vs 19%, p < 0.001), and have class 3 obesity (4.4% vs 0.6%, p < 0.001).


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  		Table 1. Prevalence of Overweight and Obese Individuals in 2,277 Patients With an Incident MI Between 1979 and 1998 in Olmsted County*

 
The association between being overweight or obese and hypertension and smoking changed over time. In the time period from 1979 to 1983, the OR between being either overweight or obese and hypertension was 2.34, while in the time period between 1994 and 1998 it was 0.88 (p = 0.0016). The OR for history of smoking and being either overweight or obese in the same periods increased from 0.82 to 1.23 (p = 0.039). The OR for the association between diabetes mellitus and being either overweight or obese did not change over time.

Association Between Body Weight and Outcomes
The duration of follow-up was 14,852 person-years (median, 5.7 years; 25th to 75th percentile, 2.2 to 9.4 years).

All-Cause Mortality:
There were 1,152 deaths. Patients who were obese or overweight had a lower mortality rate than patients with normal weight (Fig 3 , top). After adjusting for age, the difference was attenuated but survival remained better for patients with greater weight with a dose-response effect (RR, 0.77; 95% CI, 0.68 to 0.88 for overweight; and RR, 0.83; 95% CI, 0.71 to 0.98 for obese patients) when compared to patients with normal weight. The RR did not change after adding other variables in the model: peak CK ratio, the comorbidity index, year of the index MI, and reperfusion therapy (Table 2 ). Excluding deaths occurring in the first 3 years after MI did not change the RRs (RR, 0.93; 95% CI, 0.76 to 1.14 for overweight; RR, 0.92; 95% CI, 0.72 to 1.18 for obesity).



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  		Figure 3. Top: Survival after index MI by BMI group. Bottom: Survival free of cardiac event after index MI by BMI group.

 

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  		Table 2. Association Between Weight and Outcomes According to Different Cox Proportional Hazards Models*

 
Cardiac Events:
There were 1,020 cardiac events. Recurrent MI (n = 589) and sudden cardiac death (n = 252) accounted for 73% of the cardiac events. Overweight and obese patients were less likely to have cardiac events during follow-up than patients with normal weight (Fig 3, bottom). However, the RRs for cardiac events were similar for all weight groups after adjusting for age (RR, 1.00; 95% CI, 0.87 to 1.16 for overweight; and RR, 1.07; 95% CI, 0.90 to 1.26 for obese) and remained unchanged after controlling for peak CK ratio, the comorbidity index, year of the index MI, and reperfusion therapy (RR, 0.99; 95% CI, 0.85 to 1.15 for overweight; and RR, 1.06; 95% CI, 0.89 to 1.27 for obese) [Table 2].


   Discussion
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
Conclusion
 References
 
Excess weight is the most prevalent cardiovascular risk factor in patients with MI, and increased over time. However, it was not associated with adverse outcomes. Data from the European Action on Secondary Prevention by Intervention To Reduce Events study19 showed that 6 months after MI and revascularization, 42% of women and 57% of men were overweight and 33% of women and 23% of men were obese. In the present study, the combination of overweight and obesity represented the most prevalent cardiovascular risk factor, followed by other risk factors related to obesity such as hypertension and hyperlipidemia. Furthermore, the pre-valence of overweight and obese individuals increased over time, particularly the prevalence of type 3 obesity that increased sevenfold in 20 years. Other risk factors linked to obesity also increased over time. This trend qualitatively exceeds the increase in the prevalence of overweight and obese individuals in the general population. Indeed, in the US adult population, the prevalence of obesity increased from 12% in 1991 to 18% in 1998,20 while in the present MI cohort, the prevalence of obesity increased from 19% in the period 1989 to 1993 to 33% in the period 1994 to 1998. This underscores the importance of documenting the impact of obesity on outcomes after MI.

In our analysis, patients with obesity had better survival and similar rates of cardiac events as compared to patients with normal weight, even after extensive adjustment for potential confounders. Similar findings had been reported after coronary revascularization. A study including 9,633 patients undergoing percutaneous coronary revascularization showed that patients with normal weight had a higher in-hospital and 1-year mortality when compared to overweight and obese patients.21 The rate of MI and revascularization, however, was similar among different weight groups. Other studies2223 on patients undergoing percutaneous coronary revascularization showed similar findings. Data after coronary bypass grafting showed similar results.2425

The lack of, or an inverse association between, obesity and recurrent cardiac events after revascularization has been termed the obesity paradox, recalling the paradoxical association between smoking and outcomes after MI2627; these studies, however, did not control for several comorbidities, included nonconsecutive or selected groups of patients, and were not limited to MI. To the best of our knowledge, only one study11 reported more coronary events in obese patients after MI.

The paradoxical association between BMI and survival and the lack of association between BMI and cardiac events after MI may have several explanations. Misclassification of body fat by using BMI2829 could bias results toward the null, thereby potentially masking a negative association between BMI and outcomes. It is important to underscore that most studies of obesity used BMI and that the present results document a dose-response effect between BMI and mortality, conventional criteria for causality.

Another potential explanation is that weight loss that may occur after MI in turn affects outcomes. As there is limited information on BMI changes after MI, this hypothesis should be examined in subsequent studies. Another reason to the paradoxical association between obesity and better outcomes is that the potential beneficial effect of leanness after MI is offset by higher complications after thrombo-lysis and angioplasty in patients with low body weight.30 The present results, however, do not support this hypothesis, as the protective association between weight and outcomes persisted after controlling for reperfusion therapy. Additionally, the analyses excluding deaths during the first 3 years after MI, in effect excluding deaths from occult comorbidities including cancer, showed no difference in survival among groups. Furthermore, the Charlson comorbidity index used in the multivariate analysis includes conditions that explain the majority of nonaccidental deaths. Therefore, important residual confounding is unlikely to explain the findings. It is also conceivable that overweight and obese patients may have been treated more aggressively for hypertension and hyperlipidemia, and that the effect of these medications could in turn play a role in the more favorable outcomes among this group.

Finally, overweight or obesity may be truly unrelated to recurrent cardiac events after MI. This, however, should be considered with caution because overweight and obesity have consistently shown to affect mortality in many patient populations and to play a causal role in the incidence of other cardiovascular risk factors like hypertension, hyperlipidemia, and diabetes.31 Also, the lack of an association between BMI and recurrent cardiac events does not prove that weight loss may not be beneficial after MI. To this end, despite the consistent association between cigarette smoking and better outcomes after MI, patients who quit smoking have a lower rate of recurrent events than patients who keep smoking.32

These results provide important insights into the prevalence and trends of overweight and obesity among patients with MI and into its associations with outcomes. Potential limitations should be kept in mind, however, while interpreting the data. Olmsted County is becoming more diverse, but during the study period more limited diversity may limit the generalization of these data to groups underrepresented in the population. The increase in the pre-valence of other risk factors may reflect in part changes in the diagnostic criteria or heightened clinical awareness of these risk factors increasing screening.

The use of passive follow-up for mortality could result in the underascertainment of deaths if persons emigrated from the community and had no ongoing medical care and did not have an obituary published locally. Based on estimates of in-migration and outmigration, this number is likely to be small and it seems unlikely that it would be related to baseline measures of BMI. Moreover, the magnitude of RR associated with BMI is sufficiently great that underascertainment would have to be quite large. These potential limitations, however, are offset by unique strengths of the study, including the inclusion of all MIs rigorously ascertained in a geographically defined population, with comprehensive ascertainment of comorbidities and outcomes.


   Conclusion
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusion
References
 
The prevalence of overweight and obese individuals among patients with MI in the population is high and has increased over time. Despite a higher prevalence of other cardiovascular risk factors among patients with excess weight, these did not experience worse outcomes, underscoring the need to further study the paradoxical relation between weight and post-MI outcomes.


   Footnotes
 
Abbreviations: BMI = body mass index; CI = confidence interval; CK = creatine kinase; ICD-9 = Ninth Revision of the International Classification of Disease; MI = myocardial infarction; OR = odds ratio; RR = risk ratio

This study was supported in part by a research grant from the Public Health Service, National Institute of Health (HL59205) and by the Harry B. Graf Career Development Award in Preventive Cardiology from the American College of Cardiology.

Received for publication July 1, 2003. Accepted for publication September 19, 2003.


   References
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusion
 References
 

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