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To analyze the relationship of ideal cardiovascular health to disease-specific death.
We used data from the Aerobics Center Longitudinal Study from October 9, 1987, to March 3, 1999, to estimate the prevalence of ideal cardiovascular health in 11,993 individuals (24.3% women) and to examine its relationship with deaths from all causes, cardiovascular disease (CVD), and cancer.
During a mean follow-up of 11.6 years, 305 deaths occurred: 70 (23.0%) from CVD and 127 (41.6%) from cancer. In the entire cohort, only 29 individuals (0.2%) had 7 ideal metrics. After adjusting for age, sex, examination year, alcohol intake, and parental history of CVD, risk of death due to CVD was 55% lower in those participants who met 3 or 4 ideal metrics (hazard ratio, 0.45; 95% confidence interval, 0.27-0.77) and 63% lower in those with 5 to 7 ideal metrics (hazard ratio, 0.37; 95% confidence interval, 0.15-0.95), compared with those who met 0 to 2 ideal metrics. Although not significant, there was also a trend toward lower risk of death due to all causes across incremental numbers of ideal metrics. No association was observed for deaths due to cancer.
The prevalence of ideal cardiovascular health was extremely low in a middle-aged cohort of men and women recruited between 1987 and 1999. The American Heart Association construct reflects well the subsequent risk of CVD, as reflected by graded CVD mortality in relation to the number of ideal metrics.
Despite 4 decades of decline in age-standardized death rates, cardiovascular disease (CVD) and stroke continue to be the leading causes of morbidity and mortality in the United States.1 Their total annual cost in the United States has been projected to increase from $450 billion in 2010 to more than $1 trillion in 2030, including health expenditures (direct costs) and lost productivity (indirect costs).2 The costs for CVD are higher than for any other diagnostic group.1
Much of the literature on CVD has focused on factors associated with the increasing risk of CVD; however, a number of studies have recently defined the effects of healthy behaviors and lower CVD risk factor burden on CVD outcomes and longevity.3-7 Prevention of adverse levels of risk factors may be the most effective means for averting clinical events during the remaining lifespan. This is the meaning of primordial prevention,8,9 which targets earlier stages than does primary prevention (preventing the first occurrence of a clinical event in individuals with adverse levels of risk factors), and much earlier than secondary prevention (preventing the recurrence of clinical events in patients with manifest clinical disease).
The American Heart Association (AHA) has established a new construct, “ideal cardiovascular health,”10 that emphasizes 7 positive behaviors and factors that increase the odds of living free of CVD and stroke.11 This concept consists of (1) the simultaneous presence of 4 health behaviors: abstinence from smoking within the past year, ideal body mass index (BMI), physical activity at goal levels, and consumption of a dietary pattern that promotes cardiovascular health; (2) the simultaneous presence of 3 health factors: untreated total cholesterol less than 200 mg/dL (to convert to mmol/L, multiply by 0.0259), untreated blood pressure less than 120/80 mm Hg, and absence of diabetes mellitus; and (3) the absence of clinical CVD (eg, coronary heart disease, stroke, and heart failure).10
The purposes of this study were to report the prevalence of ideal cardiovascular health in the Aerobics Center Longitudinal Study (ACLS) cohort between 1987 and 1999, and to examine its relationship with disease-specific death due to all causes, CVD, and cancer.
The ACLS is a prospective observational study of individuals who underwent extensive preventive medical evaluation at the Cooper Clinic (Dallas, TX).12,13 Participants were unpaid volunteers sent by their employers or physicians or were self-referred. All participants gave informed consent to participate in the study. The Cooper Institute Institutional Review Board reviewed and approved the study protocol annually.
The present study included all participants aged 20 years or older with available complete information about all cardiovascular health behaviors (smoking, BMI, physical activity, and diet) and cardiovascular health factors (total cholesterol concentration, blood pressure, and glucose concentration). Of 14,372 participants, we excluded those with a history of CVD (heart attack or stroke) (n=265 [1.8%]) or cancer (n=835 [5.8%]), those with abnormal findings on electrocardiography (n=1137 [7.9%]); those who were underweight (BMI <18.5 kg/m2) (n=131 [0.09%]), and those with less than 1 year of follow-up (n=11 [0.07%]). These criteria resulted in 11,993 individuals (24.3% women) aged 20 to 88 years who underwent a baseline examination between October 9, 1987, and March 3, 1999. Participants were predominantly white, well educated, and within the middle to upper socioeconomic strata.
The baseline examination was completed after an overnight fast and included an extensive physical examination and an array of clinical measurements. Body mass index was computed as weight in kilograms divided by height in meters squared, measured using a standard clinical scale and stadiometer. Resting systolic and diastolic blood pressure was measured with the individual in the seated position as the first and fifth Korotkof sounds, using standard auscultation methods after at least 5 minutes of sitting quietly.14 Two or more readings separated by 2 minutes were averaged. If the first 2 readings differed by more than 5 mm Hg, additional readings were obtained and averaged. Concentrations of total cholesterol and fasting plasma glucose were measured using automated techniques in accordance with the standards of the Centers for Disease Control and Prevention lipid standardization program. Participants completed a standardized questionnaire on medical history that included a personal history of myocardial infarction, stroke, hypertension, diabetes, and cancer; a parental history of CVD; smoking status, alcohol intake (number of drinks per week, correcting for alcohol content, in which 1 unit of alcohol was defined as 12 oz of beer, 5 oz of wine, or 1.5 oz of hard liquor), and physical activity. Participants also completed a 3-day diet record.
A formerly validated questionnaire was used to assess self-reported leisure-time physical activity over the past 3 months.15 We created physical activity categories on the basis of responses to 10 specific activities: walking, jogging, running, treadmill exercise, cycling, stationary cycling, swimming, racquet sports, aerobic dance, and other sports-related activities (eg, basketball and soccer). Additional questions about the frequency (number of workouts per week) and duration (minutes of workout per session) of physical activity were also asked. The intensity of activities was estimated via speed-specific or activity-specific metabolic equivalent (MET) values from the Compendium of Physical Activities.16 The MET value for a given speed or activity was multiplied by the frequency and the duration and summed over all activities, resulting in total MET-minutes per week of physical activity.
All participants were classified into 3 categories on the basis of the 2008 Physical Activity Guidelines for Americans17: inactive (0 MET-min/wk), insufficient (1-499 MET-min/wk), and recommended (≥500 MET-min/wk). Five hundred MET-minutes per week is equivalent to 150 minutes per week of moderately intense activity or 75 minutes per week of vigorous activity.17
The 3-day dietary assessment required respondents to keep a detailed record of everything they consumed over 2 preassigned weekdays and 1 weekend day. Participants were provided with written instructions on how to accurately describe foods and estimate portion sizes. Participants kept an ongoing, real-time, written record of foods consumed during and between meals and reported portion sizes in common household measures. Registered dietitians at the Cooper Clinic coded and analyzed the diet records using the Cooper Clinic Nutrition and Exercise Evaluation system.18
We categorized achievement of the AHA diet goals10 as follows: 4.5 or more servings per day of fruits and vegetables; 2 or more 3.5-oz servings per week of fish, shellfish, or other seafood; 3 or more servings per day of whole grains; and less than 1500 mg/d of sodium.
Using the AHA definition of ideal cardiovascular health,10 we classified the level of each cardiovascular health metric at baseline as ideal, intermediate, or poor (Table 1). For ideal levels of total cholesterol and glucose concentrations and blood pressure, the AHA definition does not include achievement of ideal levels through medication use. This information is not available in the ACLS; therefore, ideal levels of these factors additionally required no previous physician diagnosis of hypercholesterolemia (for total cholesterol concentration), hypertension (for blood pressure), or diabetes or use of insulin (for fasting plasma glucose concentration).
Participants were grouped into 3 categories according to the number of metrics at the ideal level: 0 to 2, 3 to 4, and 5 to 7. Those participants meeting the fewest ideal metrics (0-2) were considered the reference group for the association with death. These categories represent a relatively even distribution of the prevalence of participants meeting the various numbers of metrics: approximately 40%, 40%, and 20% for 0 to 2, 3 to 4, and 5 to 7 ideal metrics, respectively.
All participants were followed up from the date of their baseline examination to the date of their death or December 31, 2003. We computed person-years of exposure as the sum of follow-up time in decedents and survivors. The National Death Index was the primary data source for mortality surveillance, augmented with death certificates. The National Death Index is an accurate method of ascertaining deaths in observational studies, with high sensitivity (96%) and specificity (100%).19
The underlying cause of death was determined from the index or by nosologist review of official death certificates obtained from the department of vital records in the decedent's state of residence. Death due to CVD was defined using International Classification of Diseases, Ninth Revision (ICD-9) codes 390 to 449.9 before 1999, and ICD, Tenth Revision (ICD-10) codes I00 to I78 during 1999-2003. Death due to cancer was defined by ICD-9 codes 140 to 208 and ICD-10 codes C00 to C97.
Baseline characteristics were summarized on the basis of sex and vital status, using analysis of variance for continuous variables and χ2 tests for categorical variables. Cox proportional hazards regression was used to estimate hazard ratios and 95% confidence intervals by total number of ideal metrics and also by level of each metric (ie, poor, intermediate, or ideal). When analyzing continuous metrics (BMI, physical activity, concentrations of total cholesterol and glucose, and blood pressure), the results are also given as standardized hazard ratios by transforming each metric to have a mean (SD) of 0 (1). No significant effect modification according to sex was observed using interaction terms in the Cox regression analyses; thus, the results of pooled analyses are given. All models were adjusted for age, sex, examination year, alcohol intake (heavy drinker [defined as >14 and >7 drinks per week for men and women, respectively] or not), and parental history of CVD.
Cumulative hazard plots grouped according to cardiovascular health groups suggested no appreciable violations of the proportional hazards assumption. Data analyses were performed using PWSA statistical package version 18.0 (SPSS, Inc, Chicago, IL), and all P values are 2-sided with an α level of .05.
Descriptive characteristics of the study population are given in Table 2. Mean (SD) age of the study population was 46.0 (9.9) years. Decedents had higher baseline values for age, BMI, total cholesterol and fasting plasma glucose concentrations, and blood pressure, as well as a higher prevalence of current smokers and individuals with hypercholesterolemia, diabetes mellitus, and hypertension. Values and prevalence of most characteristics also differed by sex.
The prevalence of poor, intermediate, and ideal levels of each cardiovascular health metric at baseline are shown in Figure 1. Only 4.2% of our population (n=499) met the ideal diet criteria. The individual diet components were met more often for fruits and vegetables (n=8322 [69.4%]) and fish (n=5155 [43.0%]) than for whole grains (n=1259 [10.5%]) and sodium (n=115 [1%]). For all other health components, the prevalence in participants meeting the ideal level was, in ascending order, blood pressure, 31.7% (n=3799); total cholesterol concentration, 41.9% (n=5021); BMI, 46.3% (n=5559); smoking, 55.5% (n=6661); physical activity, 60.3% (n=7226); and fasting plasma glucose concentration, 61.0% (n=7315). Only 29 individuals (0.2%) from the entire cohort had 7 ideal metrics, and 2202 (18.2%) had 5 or more. Approximately 42.7% of participants (n=5116) had 3 to 4 ideal metrics, and 39% (n=4675) had only 0 to 2 ideal metrics.
During mean follow-up of 11.6 years (range, 1.1-16.2 years) and 138,909 person-years of observation, 305 deaths occurred: 70 (23.0%) due to CVD, and 127 (41.6%) due to cancer. The distribution of deaths by number of ideal metrics is given in Table 3. There were no deaths due to CVD in participants who met 6 or more ideal metrics. After adjusting for age, sex, examination year, alcohol intake, and parental history of CVD (Table 4), the risk of dying of CVD in participants meeting 3 to 4 ideal metrics was 55% lower than in those who met 0 to 2 ideal metrics (hazard ratio, 0.45; 95% confidence interval, 0.27-0.77) and was 63% lower in those who met 5 to 7 ideal metrics (hazard ratio, 0.37; 95% confidence interval, 0.15-0.95). Although not statistically significant, there was also a trend toward a lower risk of deaths due to all causes across incremental numbers of ideal metrics (hazard ratios, 0.83 and 0.77 in the groups who met 3 to 4 and 5 to 7 metrics, respectively). Death due to cancer was not associated with the number of ideal metrics.
The independent association of each cardiovascular health metric with risk of death due to any cause, CVD, and cancer is given in Table 5. After adjusting for each other, smoking, BMI, blood pressure, and fasting plasma glucose concentration were associated with risk of death. For a given number of ideal behaviors, a higher number of ideal factors contributed to lower CVD mortality, and vice versa (Figure 2).
The AHA 2020 Impact Goal includes a new construct of cardiovascular health and presents metrics to monitor it over time.10 The 2 main findings in our study were that (1) among middle-aged men and women enrolled in the ACLS between 1987 and 1999, only 0.2% had ideal cardiovascular health (ie, ideal levels of all 7 metrics); and (2) the AHA construct indeed well reflects the subsequent risk of CVD, as reflected by graded CVD mortality in relation to the number of ideal metrics.
Comparable nationally representative prevalence estimates of cardiovascular health have been recently published.20 Compared with them, the percentage of participants who met ideal levels in our cohort was more similar for cardiovascular health factors (National Health and Nutrition Examination Survey [NHANES] 2003-2008) including age 40 to 64 years (40.7% of participants); total cholesterol concentration (35.5%-36.0% of participants), blood pressure (29.4%-37.4%), and fasting glucose concentration (46.6%-62.3%), whereas it was more diverse for cardiovascular health behaviors including smoking (69.8%-75.6%), BMI (21.5%-33.1%), physical activity (41.4%-48.9%), and diet (0.6%-1.1%). The possible reasons for these discrepancies could be related to some modifications we introduced in the original AHA metrics for smoking and diet (see subsequent discussion for further explanation), the measurement method (eg, differences between physical activity questionnaires), or examination year (1987-1999 for ACLS and 2003-2008 for NHANES). In addition, referral and volunteer biases in our cohort, compared with the more standardized sampling procedures in NHANES, must be taken into account. Yet, as in our study, less than 1% of all adults in NHANES exhibited ideal levels of all 7 metrics, and healthy diet (in particular, whole grains and sodium) was the least prevalent ideal component.20
In a middle-aged community-based study population (Heart Strategies Concentrating on Risk Evaluation [Heart SCORE] study), Bambs et al21 reported a prevalence of ideal cardiovascular health of 0.1%, virtually the same as in the present study. Fewer than 10% of participants met 5 or more components of ideal cardiovascular health,21 compared with approximately 18.2% in our study. Again, the greatest discrepancies were observed in physical activity (27.4% vs 60.3%) and diet (44.5% vs 4.2%), which included only fruits and vegetables.21 The same prevalence of ideal cardiovascular health (0.1%) was reported by Folsom et al22 in 12,744 participants enrolled in the Atherosclerosis Risk in Communities (ARIC) study between 1987 and 1989. Prospective 20-year follow-up demonstrated a graded and inverse relationship between the number of ideal metrics and the incidence of CVD events. No CVD events occurred in individuals who had ideal levels of all 7 metrics,22 while we observed no deaths from CVD among those meeting 6 or 7 ideal metrics.
In the only study to date relating ideal cardiovascular health with mortality, Ford et al23 observed a strong inverse relationship between the number of ideal metrics and death due to all causes and diseases of the circulatory system. This study used NHANES data from 1999 to 2002, and participants were followed up for mortality through 2006 (median follow-up, 5.8 years). When participants with self-reported CVD were excluded from the analyses (as in our study), the association with death due to diseases of the circulatory system was strengthened (being significant from just ≥1 ideal metrics), whereas all-cause mortality was significantly reduced only when meeting at least 5 ideal metrics.23 This can be critical to interpretation of our results because the AHA has explicitly defined ideal cardiovascular health as the simultaneous presence of 7 favorable health behaviors and factors plus the absence of clinical CVD.10 Of note, Ford et al23 used the Healthy Eating Index as the dietary metric and hemoglobin A1c as the glycemic metric. In both studies, data for men and women were considered together, and the analyses were adjusted for age, sex, excessive alcohol use, and history of CVD.23 Additional confounders used by Ford et al23 such as race/ethnicity, level of educational attainment, and health insurance could be not so pertinent in our sample because participants in the ACLS were predominantly white, well educated, and within the middle to upper socioeconomic strata.12,13
Before the establishment of ideal cardiovascular health by the AHA, other prediction models combined healthy lifestyles and optimal levels of risk factors and found dramatic benefits in CVD prevention.3-6 In our ACLS cohort, various combinations of healthy behaviors and factors were used that included not smoking, normal BMI or waist circumference, moderate to high cardiorespiratory fitness, light alcohol intake, and being physically active.24-27 We reported an inverse association of these combined and individual components (except alcohol intake) with the incidence of hypertension24 and coronary heart disease,25 death due to CVD,25,26 and deaths from all causes.27 Other studies are needed to further explore the association (or lack of it) with cancer incidence and mortality because the evidence suggests common pathways and risk factors for CVD and cancer.28
Some particular considerations of the ACLS cohort must be acknowledged. The main strengths of the present study include the relatively large number of participants, the prospective study design, the various mortality outcomes studied, and the extensive follow-up. Also, we excluded individuals with a history of CVD or cancer, those with abnormalities on electrocardiography, those with BMI less than 18.5 kg/m2, and those who died during the first year of follow-up, reducing the likelihood of undetected subclinical disease.
Limitations of our study also must be considered. First, most participants were white, well-educated, and of middle to upper socioeconomic status. The prevalence of healthy behaviors and factors may be significantly lower in a more general population with lower levels of educational achievement and/or different racial/ethnic backgrounds. However, the ACLS study group is similar to that of other large epidemiologic studies from the United States insofar as key clinical measures such as lipid and glucose concentrations and blood pressure.29,30 Second, although measurement of major risk factors is well standardized and, therefore, quite generalizable between studies, measurement of diet and physical activity may not be. Biases associated with self-report measures were minimized insofar as possible by using standardized procedures and validated instruments. Third, compared with the AHA definition of ideal cardiovascular health, we introduced some minor adaptations to diet, smoking status, and medication use. We had insufficient information to include sugar-sweetened beverages among the diet components, and we did not have data on the length of time since a former smoker had quit. Fourth, we could not consider possible changes in the 7 metrics during follow-up and did not have sufficient information about medication use, treatments, menopausal status, or pregnancy status. Such information should be included in future studies to expand on the findings reported herein.
The prevalence of ideal cardiovascular health is extremely low in a middle-aged cohort of men and women enrolled in the ACLS between 1987 and 1999. We found a decreasing number of deaths due to CVD in association with increasing numbers of ideal metrics. A tendency was observed only in the case of deaths due to all causes, and no association was found with deaths due to cancer. Our data support the notion that deaths due to CVD might be reduced by primordial prevention, in which individuals avoid CVD risk factors and risk behaviors in the first place.
We thank the Cooper Clinic physicians and technicians for collecting the data and staff at the Cooper Institute for data entry and data management.
See editorial comment,page 929
Grant Support: This work was supported by National Institutes of Health grants AG06945, HL62508, and R21DK088195; by an unrestricted research grant from The Coca-Cola Co, Atlanta, GA; and by Spanish Ministry of Education grants EX-2009-0899 and EX-2010-1008.
Potential Competing Interests: Dr Blair receives book royalties (<$5000/y) from Human Kinetics Publishers, Inc, Champaign, IL; and honoraria for service on the scientific/medical advisory boards of Alere, Inc, Waltham, MA; Technogym USA Corp, Seattle, WA; Santech, San Diego, CA; and Jenny Craig, Inc, Carlsbad, CA, and for lectures and consultations from scientific, corporate, educational, and lay groups.
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