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Figure.
Calibration Plot of Observed to Estimated 25-Year Risk for Atherosclerotic Cardiovascular Disease (ASCVD)
Calibration Plot of Observed to Estimated 25-Year Risk for Atherosclerotic Cardiovascular Disease (ASCVD)

Risk for ASCVD is based on the Healthy Heart Score derived in the Nurses’ Health Study and the Health Professionals Follow-up Study and applied to 4893 participants in the baseline Coronary Artery Risk Development in Young Adults study (January 1, 1985, through December 31, 1986). GND indicates Greenwood-Nam-D’Agostino statistic. The diagonal line represents a perfect calibration.

Table 1.  
Characteristics of the 4893 CARDIA Participants at the Baseline Examination
Characteristics of the 4893 CARDIA Participants at the Baseline Examination
Table 2.  
Comparison of HHS Components for Participants in the CARDIA Study and the Original Derivation Cohortsa
Comparison of HHS Components for Participants in the CARDIA Study and the Original Derivation Cohortsa
Table 3.  
Model Performance of the HHS in Young Adults Aged 18 to 30 Years in the CARDIA Study to Estimate Incidence of ASCVD Before 55 Years of Agea
Model Performance of the HHS in Young Adults Aged 18 to 30 Years in the CARDIA Study to Estimate Incidence of ASCVD Before 55 Years of Agea
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Original Investigation
September 2017

Application of a Lifestyle-Based Tool to Estimate Premature Cardiovascular Disease Events in Young Adults: The Coronary Artery Risk Development in Young Adults (CARDIA) Study

Author Affiliations
  • 1Division of Adolescent and Young Adult Medicine, Boston Children’s Hospital, Boston, Massachusetts
  • 2Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
  • 3Division of Chronic Disease Research Across the Life Course, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, Massachusetts
  • 4now affiliated with Office of the Director, Environmental Influences on Child Health Outcomes Program, National Institutes of Health, Bethesda, Maryland
  • 5Center for Health Metrics and Evaluation, American Heart Association, Dallas, Texas
  • 6Office of the Dean, Colorado School of Public Health, Denver
  • 7now affiliated with National Heart, Lung, and Blood Institute, Bethesda, Maryland
  • 8Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
  • 9AbbVie, Inc, Pharmaceuticals, West Roxbury, Massachusetts
JAMA Intern Med. 2017;177(9):1354-1360. doi:10.1001/jamainternmed.2017.2922
Key Points

Question  How effective is a lifestyle-based risk tool at estimating atherosclerotic cardiovascular disease events that occur before 55 years of age?

Findings  In the Coronary Artery Risk Development in Young Adults cohort study, the Healthy Heart Score performed moderately well at estimating the 25-year risk for early atherosclerotic cardiovascular disease events when applied to healthy adults aged 18 to 30 years. The Healthy Heart Score did not perform as well in young adults who already had at least 1 clinical atherosclerotic cardiovascular disease risk factor, such as elevated blood pressure or cholesterol or glucose levels.

Meaning  The Healthy Heart Score is an attractive tool for risk assessment and counseling for primary prevention of atherosclerotic cardiovascular disease, especially in those who have not yet developed traditional clinical risk factors.

Abstract

Importance  Few tools exist for assessing the risk for early atherosclerotic cardiovascular disease (ASCVD) events in young adults.

Objective  To assess the performance of the Healthy Heart Score (HHS), a lifestyle-based tool that estimates ASCVD events in older adults, for ASCVD events occurring before 55 years of age.

Design, Setting, and Participants  This prospective cohort study included 4893 US adults aged 18 to 30 years from the Coronary Artery Risk Development in Young Adults (CARDIA) study. Participants underwent measurement of lifestyle factors from March 25, 1985, through June 7, 1986, and were followed up for a median of 27.1 years (interquartile range, 26.9-27.2 years). Data for this study were analyzed from February 24 through December 12, 2016.

Exposures  The HHS includes age, smoking status, body mass index, alcohol intake, exercise, and a diet score composed of self-reported daily intake of cereal fiber, fruits and/or vegetables, nuts, sugar-sweetened beverages, and red and/or processed meats. The HHS in the CARDIA study was calculated using sex-specific equations produced by its derivation cohorts.

Main Outcomes and Measures  The ability of the HHS to assess the 25-year risk for ASCVD (death from coronary heart disease, nonfatal myocardial infarction, and fatal or nonfatal ischemic stroke) in the total sample, in race- and sex-specific subgroups, and in those with and without clinical ASCVD risk factors at baseline. Model discrimination was assessed with the Harrell C statistic; model calibration, with Greenwood-Nam-D’Agostino statistics.

Results  The study population of 4893 participants included 2205 men (45.1%) and 2688 women (54.9%) with a mean (SD) age at baseline of 24.8 (3.6) years; 2483 (50.7%) were black; and 427 (8.7%) had at least 1 clinical ASCVD risk factor (hypertension, hyperlipidemia, or diabetes types 1 and 2). Among these participants, 64 premature ASCVD events occurred in women and 99 in men. The HHS showed moderate discrimination for ASCVD risk assessment in this diverse population of mostly healthy young adults (C statistic, 0.71; 95% CI, 0.66-0.76); it performed better in men (C statistic, 0.74; 95% CI, 0.68-0.79) than in women (C statistic, 0.69; 95% CI, 0.62-0.75); in white (C statistic, 0.77; 95% CI, 0.71-0.84) than in black (C statistic, 0.66; 95% CI, 0.60-0.72) participants; and in those without (C statistic, 0.71; 95% CI, 0.66-0.76) vs with (C statistic, 0.64; 95% CI, 0.55-0.73) clinical risk factors at baseline. The HHS was adequately calibrated overall and within each subgroup.

Conclusions and Relevance  The HHS, when measured in younger persons without ASCVD risk factors, performs moderately well in assessing risk for ASCVD events by early middle age. Its reliance on self-reported, modifiable lifestyle factors makes it an attractive tool for risk assessment and counseling for early ASCVD prevention.

Introduction

Mortality rates associated with atherosclerotic cardiovascular disease (ASCVD) have steadily declined in past decades owing to advances in prevention, detection, and treatment.1 Unfortunately, scientists caution this trend may soon reverse owing to increasing obesity rates and unhealthy diet and exercise patterns in younger individuals.2 Adolescents and young adults are a prime target for ASCVD prevention efforts,3,4 especially because most do not yet have major clinical risk factors for ASCVD, such as hypertension, hyperlipidemia, and diabetes.1 Often termed primordial prevention, such efforts to prevent the development of these clinical risk factors through healthy behaviors hold promise for reducing ASCVD events across the life course.5 Decades of epidemiologic research have demonstrated that adults who maintain optimal levels of traditional ASCVD risk factors over time have low rates of ASCVD.6-8 Furthermore, restoration of low risk is difficult after these clinical risk factors develop, even with efficacious pharmacologic treatment.9

Although numerous risk calculators exist to estimate the future risk for ASCVD among individuals and populations,10 few are validated for use in adults younger than 30 years of age. Even fewer focus on the behavioral factors (diet, exercise, tobacco exposure, and weight status) that are key for primordial prevention and most likely to need improvement in this age group. One promising lifestyle-based tool to estimate ASCVD risk is the Healthy Heart Score (HHS).11 Chiuve et al11 developed the HHS for middle-aged adults for whom the short-term risk for ASCVD is low but the long-term risk is high.12,13 A range of health behaviors known to affect the development of ASCVD risk factors were considered in the development of the tool. Derived and validated in adults aged 40 to 75 years at the time of lifestyle factor measurement, the HHS demonstrated good discrimination (C statistic, 0.72 in men and 0.77 in women) and calibration for predicting ASCVD events during 24 years of follow-up, especially for individuals without elevated blood pressure or cholesterol levels at baseline.8

The ability of the HHS to estimate ASCVD events in individuals without established clinical risk factors makes it an attractive tool for estimating early ASCVD events in young adults. The present study aimed to assess the performance of the HHS for estimating ASCVD events occurring before 55 years of age in a population of young adults aged 18 to 30 years at the time of lifestyle factor measurement.

Methods
Study Sample

The Coronary Artery Risk Development in Young Adults (CARDIA) study is a population-based longitudinal cohort begun with baseline collection of data from March 25, 1985, through June 7, 1986, with 5115 young adults aged 18 to 30 years from 4 sites across the United States (University of Alabama at Birmingham; Northwestern University, Chicago, Illinois; University of Minnesota, Minneapolis; and Kaiser Permanente of Oakland, California).14 Participants were selected to include approximately equal distribution by sex, self-identified race (black or white), educational attainment (high school graduate or beyond), and age (18-24 or 25-30 years). Participants were contacted for follow-up every 6 months and queried regarding interim medical events annually. For the current analyses, participants missing data required to complete the HHS at baseline or who were pregnant at the baseline examination were excluded, for a final sample of 4893 individuals (95.7% of the original cohort). The CARDIA study has been continuously approved by the institutional review boards at each of the 4 sites, and all participants provided written informed consent to participate.

Healthy Heart Score

Chiuve et al11 developed the HHS using data from 61 025 women in the Nurses’ Health Study (NHS) and 34 478 men in the Health Professionals Follow-up Study (HPFS) who did not have ASCVD, cancer, or diabetes at the time of baseline ascertainment of health habits in 1986. The mean (SD) age for women and men at baseline was 52 (7) and 52 (9) years; women were followed up for a median of 23.9 years (interquartile range, 0.24 years) and men for a median of 23.7 years (interquartile range, 0.28 years). To derive the most parsimonious model to best estimate 20-year risk for ischemic ASCVD events (nonfatal myocardial infarction, fatal coronary heart disease, and ischemic stroke, all verified through medical record review), the investigators considered a variety of health behaviors previously shown to be associated with ASCVD in the literature. The final sex-specific score included age (in years), smoking status (past, current, or never), body mass index (BMI) (calculated as weight in kilograms divided by height in meters squared), exercise (hours per week), alcohol consumption (grams per day), and a diet score consisting of cereal fiber consumption (grams per day) and servings of fruits and/or vegetables, nuts, sugar-sweetened beverages, and red and/or processed meats (servings per day) (eFigure 1 in the Supplement). Because the original HHS includes negative coefficients for unhealthy dietary habits such as intake of sugar-sweetened beverages and red and/or processed meat, negative values of the dietary component of the score are possible. A higher overall HHS indicates a higher risk for ASCVD. Individuals can calculate their HHS at https://healthyheartscore.sph.harvard.edu/.

Application of the HHS to the CARDIA Cohort

We calculated the HHS for each CARDIA participant using data from the baseline 1985-1986 examination. Body mass index was calculated from height and weight measured with participants wearing light clothing and no shoes. Physical activity was measured with the CARDIA Physical Activity History questionnaire, which assesses 13 categories of varying intensity during the past 12 months.15 We included only data regarding moderate- to vigorous-intensity activities assessed in CARDIA (running, racquet sports, biking, swimming, dancing, basketball/softball, and bowling/golf) to be consistent with exercise categories assessed in the NHS and HPFS derivation cohorts. Because the CARDIA Physical Activity questionnaire did not ask about hours per week of physical activity, we calculated hours per week by multiplying the number of months in which participants reported meeting the threshold of x hours per week of each activity by 4.2 weeks, then divided by 52 weeks per year to arrive at x hours per week. We then summed each of the activity categories to create a variable for total hours per week of moderate- to vigorous-intensity exercise. Food and alcohol intake during the previous 28 days was assessed with the CARDIA dietary history interview.16 Cereal fiber data were not available in CARDIA; therefore, we used grams per day of fiber intake from whole grain foods as a surrogate because correlations between whole grain and cereal fiber were high in the original cohorts from which the HHS was derived.17 Cigarette smoking, age, sex, and race were self-reported via questionnaire.

Assessment of Clinical ASCVD Risk Factors and ASCVD Events

We defined the presence of clinical ASCVD risk factors at the baseline examination as any hypertension (measured blood pressure, ≥140/90 mm Hg or use of blood pressure–lowering medication), hyperlipidemia (total cholesterol level ≥240 mg/dL [to convert to millimoles per liter, multiply by 0.0259] or use of medication to lower lipid levels), or diabetes (fasting glucose level ≥126 mg/dL [to convert to millimoles per liter, multiply by 0.0555] or self-reported diabetes). Blood pressure was measured after 5 minutes of rest in the seated position using a random zero sphygmomanometer; the means of the second and third systolic and fifth-phase diastolic recordings were used.18 After a 12-hour fast, total cholesterol and glucose levels were measured using standard methods.18 Participants self-reported medication use and clinical history of diabetes.

We defined the outcome of ASCVD events as any death due to coronary heart disease, nonfatal myocardial infarction, and fatal or nonfatal ischemic stroke. Participants were asked about hospitalizations during annual telephone interviews, and deaths were reported by participants’ next-of-kin every 6 months.19 Reported events were validated through medical record review from year 15 onward and adjudicated by 2 members of the morbidity and mortality committee using standard definitions.20-23

Statistical Analysis

Data were analyzed from February 24 through December 6, 2016. We estimated the 25-year risk for ASCVD using Cox proportional hazards models. The HHS was calculated using the original coefficients from the HHS derivation cohorts first, then with CARDIA cohort–specific coefficients in a secondary analysis. Proportional hazard assumptions were found to be appropriate. We evaluated the predictive utility of the HHS in the CARDIA sample based on discrimination and calibration of the model for the full study sample, then separately for men and women, for white and black participants, and for those with and without risk factors. Discrimination assesses the ability of the model to differentiate those with and without events and was evaluated using the Harrell C statistic; larger values indicate better discrimination. We compared the discrimination of models incorporating the HHS score with models including age only. We assessed calibration using plots comparing the estimated probabilities of ASCVD with the observed event rates. We used the Greenwood-Nam-D’Agostino statistic to evaluate goodness of fit of the models. All analyses were conducted using SAS software (version 9.2; SAS Institute Inc).

Results

Baseline characteristics of the 4893 individuals included in the sample are displayed in Table 1. Mean (SD) age at ascertainment of the HHS was 24.8 (3.6) years; 2688 participants (54.9%) were women; 2205 (45.1%) were men; 2483 (50.7%) were black; and 427 (8.7%) had at least 1 clinical ASCVD risk factor (hypertension, hyperlipidemia, or diabetes) at baseline. CARDIA participants were a mean of 27 years younger than participants in the NHS and HPFS cohorts in which the HHS was derived and thus had lower mean HHS scores (Table 2). CARDIA participants had slightly lower mean BMI levels and better exercise habits compared with NHS and HPFS participants but poorer diet quality and greater frequency of smoking.

During a median follow up of 27.1 years (interquartile range, 26.9-27.2 years), 69 total ASCVD events occurred in 64 women (31 coronary heart disease events [1.2% of female participants] and 38 ischemic stroke events [1.4% of female participants]) and 104 total ASCVD events occurred in 99 men (75 coronary heart disease events [3.4% of male participants] and 29 ischemic stroke events [1.3% of male participants]). The incidence of ASCVD per 1000 person-years was 0.90 for women and 1.75 for men. ASCVD events occurred at a mean age of 45.9 years (range, 28.0-58.8 years). Most cases (121 of 163 [74.2%]) occurred in participants with no clinical ASCVD risk factors at the baseline examination, although participants who later had an ASCVD event had higher mean systolic and diastolic blood pressures and fasting glucose and total cholesterol levels in young adulthood compared with those who did not (eTable in the Supplement). Participants who experienced an ASCVD event had on average unhealthier levels of all HHS variables in young adulthood (eTable in the Supplement).

The discrimination of the HHS was moderate in the CARDIA study. Compared with the model with age only, the HHS score increased the C statistic from 0.63 (95% CI, 0.59-0.68) to 0.71 (95% CI, 0.66-0.76). Furthermore, the HHS increased the C statistic compared with models based on age alone for all subgroups (Table 3). We further compared model discrimination across subgroups. The model performed better in white vs black participants (C statistic difference, 0.11; 95% CI, 0.02-0.20) and somewhat better in men vs women (C statistic difference, 0.05; 95% CI, −0.03 to 0.13) and in the absence vs presence of clinical risk factors at baseline (C statistic difference, 0.08; 95% CI, −0.03 to 0.19). Model discrimination was weakest for those with at least 1 clinical ASCVD risk factor at baseline (C statistic, 0.64; 95% CI, 0.55-0.73). Application of cohort-specific coefficients for the lifestyle factors improved model discrimination slightly (Table 3). The Greenwood-Nam-D’Agostino statistic suggested adequate fit of the HHS model for the total population and for all subgroups (Table 3). The HHS model was overall well calibrated for 25-year ASCVD risk assessment based on the calibration plots for the total population (C statistic, 0.71; 95% CI, 0.66-0.76) (Figure) and all subgroups (eFigure 2 in the Supplement).

Discussion

In this population of healthy young adults with low rates of traditional clinical ASCVD risk factors similar to rates seen in nationally representative samples of the same age group,1 the HHS performed moderately well at estimating 25-year risk for early ASCVD events. The C statistics for the HHS in the total population, for white participants, and for men are similar to those seen in the original derivation cohorts.8 They also approach those seen with the Framingham Risk Score (which has C statistics of 0.75 to 0.80, depending on the population),24 a well-established tool for estimating 10-year risk for ASCVD events in middle-aged and older adults. Because the 10-year risk for ASCVD events is so low in individuals younger than 30 years, the Framingham Risk Score and other 10-year risk calculators such as the 2013 American College of Cardiology–American Heart Association Pooled Cohort Equations25 have limited utility in this younger population. Furthermore, those 10-year risk calculators incorporate the clinical ASCVD risk factors of elevated blood pressure, blood cholesterol level, and diabetes, which often have not yet developed in young adults. The HHS did not perform particularly well in CARDIA participants who had already established clinical ASCVD risk factors. Therefore, a risk calculator that uses lifestyle and clinical risk factors may best estimate ASCVD risk in those individuals.

The major strength of the HHS lies in its reliance on lifestyle factors, including BMI, smoking, alcohol intake, physical activity, and dietary patterns, all of which can easily be self-reported. Practicing physicians could choose to have patients complete the HHS in advance of a visit at home or in the waiting area and use the resulting report to begin a patient-centered discussion of ways to improve cardiovascular health and prevent early ASCVD. The HHS could also be used to educate young persons about their ASCVD risk at community-based public health outreach events or online through websites and social media. This outreach could be coupled with health promotion materials or individually tailored action plans targeting healthy behavior change, as well as encouragement to follow up with a primary care physician for additional blood pressure, cholesterol level, and diabetes screening as needed. Lack of awareness of cardiovascular risk factors among young adults is well documented,26 and this age group is also the most likely to forego routine primary care.27 Whether and how a risk estimation tool such as the HHS can be used to motivate young persons to seek regular primary care and lower their risk for ASCVD through behavior change remains an area for future research.

Previous studies in the CARDIA cohort have found that participants who adopted healthy lifestyle factors after young adulthood had lower odds of subclinical atherosclerosis28 and a higher prevalence of the low cardiovascular risk profile29 in middle age compared with participants who did not demonstrate behavior change. In older adults, the HHS estimates ASCVD events and the antecedent clinical risk factors of hypertension, hyperlipidemia, and diabetes.30 The prevention of these risk factors through sustained healthy lifestyle behaviors is a viable strategy for reducing ASCVD morbidity and mortality. Because few individuals retain the full constellation of healthy behaviors and absence of clinical risk factors identified by the American Heart Association as ideal cardiovascular health,1 individual and population strategies are needed to increase the HHS of young adults worldwide.

Limitations

Study limitations should be noted. Healthy Heart Score variables other than BMI were self-reported and are subject to measurement error and desirability bias. We used modified dietary variables (substituting whole grain for cereal fiber) and physical activity variables (calculating total hours per week from more general estimates of exercise habits). In general, these limitations most likely improved the HHS score of CARDIA participants, thus underestimating the risk for ASCVD events. Vital status data were not available for 307 individuals (6.0%); censoring these individuals before the full 25 years of follow-up also likely underestimates the performance of the models. Other factors such as family history of early ASCVD, illicit drug use, or pregnancy-related complications may be important in the pathogenesis of ASCVD events in younger persons; because our goal was to validate the previously published HHS, we did not investigate the role of these potential factors. Finally, health behaviors were ascertained and the HHS was calculated at only 1 point. Young adulthood is a time of significant change, and improvements in health behaviors during this period have been shown to reduce the likelihood of having intermediate markers of atherosclerosis in the CARDIA28 and other longitudinal cohorts.31

Conclusions

Among participants aged 18 to 30 years in a longitudinal cohort study, the HHS performed moderately well at assessing the risk for an ASCVD event before 55 years of age, especially when applied to individuals without any established clinical ASCVD risk factors. Its reliance on self-reported, modifiable lifestyle factors makes it an attractive tool for risk assessment and counseling for early ASCVD prevention.

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Article Information

Corresponding Author: Holly C. Gooding, MD, MS, Division of Adolescent and Young Adult Medicine, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115 (holly.gooding@childrens.harvard.edu).

Accepted for Publication: May 15, 2017.

Published Online: July 17, 2017. doi:10.1001/jamainternmed.2017.2922

Author Contributions: Drs Lloyd-Jones and Chiuve are co-senior authors. Dr Ning had full access to all 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: Gooding, Shay, Lloyd-Jones, Chiuve.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Gooding.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Ning, Gillman.

Obtained funding: Gooding, Goff, Lloyd-Jones.

Administrative, technical, or material support: Shay, Allen.

Study supervision: Lloyd-Jones.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was supported by award K23HL122361-01A1 from the National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH) (Dr Gooding); by the NHLB in collaboration with awards HHSN268201300025C and HHSN268201300026C from the University of Alabama at Birmingham, award HHSN268201300027C from Northwestern University, award HHSN268201300028C from the University of Minnesota, award HHSN268201300029C from the Kaiser Foundation Research Institute, and award HHSN268200900041C from Johns Hopkins University School of Medicine (Coronary Artery Risk Development in Young Adults [CARDIA] study); and by the Intramural Research Program of the National Institute on Aging (NIA) and intra-agency agreement AG0005 between the NIA and NHLBI (CARDIA study).

Role of the Funder/Sponsor: This manuscript has been reviewed by a publications committee of CARDIA investigators for scientific content. The funding sources had no other role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The views expressed in this article do not necessarily represent the views of the United States Government, the Department of Health and Human Services, the NHLBI, or the NIH.

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