Skip main navigation

Effectiveness-Based Guidelines for the Prevention of Cardiovascular Disease in Women—2011 Update

A Guideline From the American Heart Association
Originally published 2011;123:1243–1262

Substantial progress has been made in the awareness, treatment, and prevention of cardiovascular disease (CVD) in women since the first women-specific clinical recommendations for the prevention of CVD were published by the American Heart Association (AHA) in 1999.1 The myth that heart disease is a “man's disease” has been debunked; the rate of public awareness of CVD as the leading cause of death among US women has increased from 30% in 1997 to 54% in 2009.2 The age-adjusted death rate resulting from coronary heart disease (CHD) in females, which accounts for about half of all CVD deaths in women, was 95.7 per 100 000 females in 2007, a third of what it was in 1980.3,4 Approximately 50% of this decline in CHD deaths has been attributed to reducing major risk factors and the other half to treatment of CHD including secondary preventive therapies.4 Major randomized controlled clinical trials such as the Women's Health Initiative have changed the practice of CVD prevention in women over the past decade.5 The investment in combating this major public health issue for women has been significant, as have the scientific and medical achievements.

Despite the gains that have been made, considerable challenges remain. In 2007, CVD still caused ≈1 death per minute among women in the United States.6 These represent 421 918 deaths, more women's lives than were claimed by cancer, chronic lower respiratory disease, Alzheimer disease, and accidents combined.6 Reversing a trend of the past 4 decades, CHD death rates in US women 35 to 54 years of age now actually appear to be increasing, likely because of the effects of the obesity epidemic.4 CVD rates in the United States are significantly higher for black females compared with their white counterparts (286.1/100 000 versus 205.7/100 000). This disparity parallels the substantially lower rate of awareness of heart disease and stroke that has been documented among black versus white women.2,68 Of concern is that in a recent AHA national survey, only 53% of women said the first thing they would do if they thought they were having a heart attack was to call 9-1-1. This distressing lack of appreciation by many women for the need for emergency care for acute cardiovascular events is a barrier to optimal survival among women and underscores the need for educational campaigns targeted to women.2

CVD rates in the United States are significantly higher for black females compared with their white counterparts (286.1/100 000 versus 205.7/100 000), which parallels the substantially lower rate of awareness of heart disease and stroke that has been documented among black versus white women.2,68 Each year, 55 000 more women than men have a stroke. Atrial fibrillation is independently associated with a 4- to 5-fold increased risk of ischemic stroke and is responsible for 15% to 20% of all ischemic strokes. It has been shown that undertreatment with anticoagulants doubles the risk of recurrent stroke; therefore, the expert panel voted to include recommendations for the prevention of stroke among women with atrial fibrillation.6,9,10

Adverse trends in CVD risk factors among women are an ongoing concern. After 65 years of age, a higher percentage of women than men have hypertension, and the gap will likely increase with the continued aging of the female population.6 The prevalence of hypertension in blacks in the United States is among the highest in the world, and it is increasing. From 1988 to 1994 through 1999 to 2002, the prevalence of hypertension in adults increased from 35.8% to 41.4% among blacks, and it was particularly high among black women at 44.0%.11

A very ominous trend is the ongoing increase in average body weight, with nearly 2 of every 3 US women >20 years of age now overweight or obese.6 The rise in obesity is a key contributor to the burgeoning epidemic of type 2 diabetes mellitus now seen in >12 million US women. Furthermore, the rate of diabetes mellitus is more than double in Hispanic women compared with non-Hispanic white women (12.7% versus 6.45%, respectively).6 The increasing prevalence of diabetes mellitus is concerning for many reasons, especially for its association with a greatly increased overall risk of myocardial infarction (MI) and stroke.12

The challenge of CVD in women is not limited to the United States. Recent data document the global scope of the problem: Heart disease is the leading cause of death in women in every major developed country and most emerging economies.13

Given the worldwide health and economic implications of CVD in women, there is strong rationale to sustain efforts to control major CVD risk factors and to apply evidence-based therapies in women.

In 2004, the AHA, in collaboration with numerous other organizations, expanded its focus on female-specific clinical recommendations and sponsored the “Evidence-Based Guidelines for Cardiovascular Disease Prevention in Women” and updated them in 2007.14,15 Initially, the guidelines challenged the conventional wisdom that women should be treated the same as men, primarily related to concerns about the lack of representation of women in clinical trials. As more women have participated in CVD research studies and more gender-specific analyses have been published, data have become available to make more definitive recommendations. Evolving science suggests that the overwhelming majority of recommendations to prevent CVD are similar for women and men, with few exceptions. Notably, aspirin is routinely recommended for the primary prevention of MI in men but not women.16,17 However, there is a growing appreciation that there may be gender differences in the magnitude of the relative and absolute potential benefits and risks of preventive interventions. The panel acknowledged unique opportunities to identify women at risk (eg, pregnancy) and addressed concerns that women often have more comorbidities and are older than men when they experience CHD.

The current guidelines encompass prevention of the scope of atherosclerotic thrombotic cardiovascular outcomes in women. However, it should be noted that the majority of data used to develop these guidelines is based on trials of CHD prevention. Future guidelines should consider recommendations for specific outcomes of particular importance in women, such as stroke. Each year, 55 000 more women die of stroke than men, and before 75 years of age. Stroke accounts for a higher proportion of CVD events than CHD in females, whereas the ratio is the opposite for males. Women have unique risk factors for stroke such as pregnancy and hormone therapy, have a greater prevalence of hypertension in older ages, a major risk factor for stroke, and may have different benefits and risks associated with interventions to reduce stroke risk compared with men.6 Atrial fibrillation is independently associated with a 4- to 5-fold increased risk of ischemic stroke and is responsible for 15% to 20% of all ischemic strokes. It has been shown that undertreatment with anticoagulants doubles the risk of recurrent stroke; therefore, the expert panel voted to include recommendations for the prevention of stroke among women with atrial fibrillation.6,9,10

Current systematic and critical review of the literature continues to update the guidelines, which have become the foundation to inform national educational programs for healthcare professionals and women consumers of healthcare. A major evolution from previous guidelines to the 2011 update is that effectiveness (benefits and risks observed in clinical practice) of preventive therapies was strongly considered and recommendations were not limited to evidence that documents efficacy (benefits observed in clinical research); hence, in the transformation from “evidence-based” to “effectiveness-based” guidelines for the prevention of cardiovascular disease in women, the panel voted to update recommendations to those therapies that have been shown to have sufficient evidence of clinical benefit for CVD outcomes. Class III recommendations from prior guidelines that are not recommended for use for the prevention of CVD (Table 1) were retained as no new evidence has become available to alter the recommendations. The list of Class III recommendations is not exhaustive, and therapies that were previously searched were based on those preventive interventions commonly believed to have a potential benefit for the prevention of CVD in women despite a lack of definitive clinical trial evidence of benefit. Uses of medications for indications beyond the prevention of ischemic CVD are not addressed in this document. Some interventions (eg, screening for depression) were recognized to lack data on direct CVD outcomes benefit but were included in an algorithm for approaches to the evaluation of women because they may indirectly impact CVD risk through adherence to prevention therapies or other mechanisms (Figure). The expert panel also recognized that cost-effectiveness, which may differ by sex, needed to be addressed; thus, a comprehensive review of current literature on the topic has been added. The guidelines continue to prioritize lifestyle approaches to the prevention of CVD, likely the most cost-effective strategy. The panel also acknowledged that difficulty in adhering to lifestyle and medical recommendations limits effectiveness; therefore, new sections were added on guideline implementation.

Table 1. Class III Interventions (Not Useful/Effective and May Be Harmful) for the Prevention of CVD in Women

Menopausal therapy
Hormone therapy and selective estrogen-receptor modulators (SERMs) should not be used for the primary or secondary prevention of CVD (Class III, Level of Evidence A).
Antioxidant Supplements
Antioxidant vitamin supplements (eg, vitamin E, C, and beta carotene) should not be used for the primary or secondary prevention of CVD (Class III, Level of Evidence A).
Folic Acid*
Folic Acid, with or without B6 and B12 supplementation, should not be used for the primary or secondary prevention of CVD (Class III, Level of Evidence A).
Aspirin for MI in women <65 years of age
Routine use of aspirin in healthy women <65 years of age is not recommended to prevent MI (Class III, Level of Evidence B).

CVD indicates cardiovascular disease; MI, myocardial infarction.

*Folic acid supplementation should be used in the childbearing years to prevent neural tube defects.


Figure. Flow diagram for CVD preventive care in women. CVD indicates cardiovascular disease; DASH, Dietary Approaches to Stop Hypertension; CHD, coronary heart disease; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; and ACS, acute coronary syndrome.

CVD Risk Assessment

In the 2007 update, a new algorithm for risk classification in women was adopted that stratified women into 3 categories: “at high risk,” based on the presence of documented CVD, diabetes mellitus, end-stage or chronic kidney disease, or 10-year predicted risk for CHD >20%; “at risk,” given the presence of ≥1 major CVD risk factors, metabolic syndrome, evidence of subclinical vascular disease (eg, coronary calcification), or poor exercise tolerance on treadmill testing; and “at optimal risk” in the setting of a Framingham risk score <10%, absence of major CVD risk factors, and engagement in a healthy lifestyle. This approach to risk classification in women was based on several observations: (1) The lifetime risk for CVD is high in almost all women and approaches 1 in 2 on average, so prevention is important in all women18; (2) most clinical trial data used to formulate the recommendations included either women at high risk because of known CVD or apparently healthy women with a spectrum of risk, which allowed the scheme to align the guidelines with the evidence; and (3) the appreciation of the limitations of standard risk stratification schemes such as the Framingham risk score is growing. These limitations include the narrow focus on only short-term (10-year) risk and on only MI and CHD death, the lack of inclusion of family history, overestimation or underestimation of risk in nonwhite populations, and the fact that subclinical CVD can have relatively high prevalence among women who are scored as being at low risk.6,19

The 2007 panel believed that a Framingham 10-year predicted risk for CHD >20% could be used to identify a woman at high risk but that a lower score was not sufficient to ensure that an individual woman was at low risk. Thus, the algorithm included consideration of factors beyond the 10-year predicted risk for CHD used in current National Cholesterol Education Panel guidelines of lipid management.20 The panel emphasized that healthcare professionals should take several factors into consideration beyond just the Framingham risk score, including medical and lifestyle history, family history of CVD, markers of preclinical disease, and other conditions, as they make decisions about the intensity of preventive therapy.

Since the 2007 update, a number of lines of evidence have emerged to support the risk classification algorithm adopted in 2007. Hsia et al21 directly evaluated the algorithm in 161 808 women 50 to 79 years of age who were enrolled in the Women's Health Initiative and followed up for a mean of 7.8 years. When the 2007 update categories were applied, 11% of women were found to be at high risk, 72% were at risk, and 4% were at optimal risk.21 Of note, 13% of women could not be classified by the 2007 algorithm because, although they lacked risk factors, they did not adhere to a healthy lifestyle.

Among high-risk, at-risk, optimal risk, and unclassified women, the rates of MI, CHD death, or stroke were 19.0%, 5.5%, 2.2%, and 2.6% per 10 years, respectively (P for trend <0.0001).20 Although absolute event rates differed among women of different race/ethnic groups, the 2007 risk classification algorithm appropriately ordered event rates in all groups, with a 7- to 20-fold difference in event rates between optimal-risk and high-risk women. The 2007 update algorithm discriminated those who experienced coronary events with accuracy similar to current National Cholesterol Education Panel Adult Treatment Panel III risk categories (<10%, 10% to 20%, and >20%) based on Framingham 10-year predicted risks.20

Therefore, the current panel elected to continue this general approach to risk classification in women for the 2011 guidelines with some modifications (Table 2). First, the AHA recently defined a new concept of “ideal cardiovascular health” defined by the absence of clinical CVD and the presence of all ideal levels of total cholesterol (<200 mg/dL), blood pressure (<120/80 mm Hg), and fasting blood glucose (<100 mg/dL), as well as adherence to healthy behaviors, including having a lean body mass index (<25 kg/m2), abstinence from smoking, participation in physical activity at recommended levels, and pursuit of a Dietary Approaches to Stop Hypertension–like eating pattern.22 When achieved or maintained into middle age, the overall pattern of ideal cardiovascular health is associated with greater longevity; dramatic reductions in short-term, intermediate-term, and lifetime risks for CVD events; greater quality of life in older ages; and lower Medicare costs at older ages.22 It should also be noted that several factors, which have been associated with an increased risk of CVD in women, have been identified, but their utility for screening and improving clinical outcomes has not been determined.

Table 2. Classification of CVD Risk in Women

Risk StatusCriteria
High risk (≥1 high-risk states)Clinically manifest CHD
Clinically manifest cerebrovascular disease
Clinically manifest peripheral arterial disease
Abdominal aortic aneurysm
End-stage or chronic kidney disease
Diabetes mellitus
10-y Predicted CVD risk ≥10%
At risk (≥1 major risk factor[s])Cigarette smoking
SBP ≥120 mm Hg, DBP ≥80 mm Hg, or treated hypertension
Total cholesterol ≥200 mg/dL, HDL-C <50 mg/dL, or treated for dyslipidemia
Obesity, particularly central adiposity
Poor diet
Physical inactivity
Family history of premature CVD occurring in first-degree relatives in men <55 y of age or in women <65 y of age
Metabolic syndrome
Evidence of advanced subclinical atherosclerosis (eg, coronary calcification, carotid plaque, or thickened IMT)
Poor exercise capacity on treadmill test and/or abnormal heart rate recovery after stopping exercise
Systemic autoimmune collagen-vascular disease (eg, lupus or rheumatoid arthritis)
History of preeclampsia, gestational diabetes, or pregnancy-induced hypertension
Ideal cardiovascular health (all of these)Total cholesterol <200 mg/dL (untreated)
BP <120/<80 mm Hg (untreated)
Fasting blood glucose <100 mg/dL (untreated)
Body mass index <25 kg/m2
Abstinence from smoking
Physical activity at goal for adults >20 y of age: ≥150 min/wk moderate intensity, ≥75 min/wk vigorous intensity, or combination
Healthy (DASH-like) diet (see Appendix)

CVD indicates cardiovascular disease; CHD, coronary heart disease; SBP, systolic blood pressure; DBP, diastolic blood pressure; HDL-C; high-density lipoprotein cholesterol; IMT, intima-media thickness; BP, blood pressure; and DASH, Dietary Approaches to Stop Hypertension.

Other modifications to the risk classification algorithm include acknowledgement of the availability of several 10-year risk equations for the prediction of 10-year global CVD risk such as the updated Framingham CVD risk profile and the Reynolds risk score for women.23,24 The panel considered that either of these scores would be appropriate for use, particularly given their inclusion of CVD events beyond just CHD, but did not endorse routine screening with high-sensitivity C-reactive protein (hsCRP), which would be required for use of the Reynolds risk score, because there are no data to support the association between a reduction in hsCRP and improved clinical outcomes. Numerous other multivariable risk scores exist and may be clinically useful if based on a population and on end points relevant to the patient in question.2527 In this context, the current guidelines recommend use of a new cut point for defining high risk as ≥10% 10-year risk for all CVD, not just CHD alone.

Recent analyses of clinical trial data suggest that at approximately this threshold statin therapy is associated with high cost-effectiveness (and possibly cost savings) in the era of generic statins.28 In addition, the recent Justification for Use of Statins in Prevention, an Intervention Trial Evaluating Rosuvastatin (JUPITER) in primary prevention populations demonstrated the efficacy of statin medications in lowering global CVD event risk, including among women, although the absolute benefit was small and the number needed to treat to prevent a major CVD event was greater than in men.29

Several lines of evidence support the focus of women's guidelines on long-term risk for CVD rather than solely on 10-year risk for CHD. First, observational and clinical trial data indicate that women's risks for stroke and heart failure through middle and older age typically exceed their risk for CHD, in contrast to the pattern observed in men, for whom CHD risk increases earliest.30,31 Thus, the focus in the current National Cholesterol Education Panel Adult Treatment Panel III guidelines on 10-year CHD risk may substantially underestimate clinically relevant overall CVD risk and therefore tends to preclude the warranted, intensive preventive measures for most high-risk women.32

Indeed, it is difficult for a woman <75 years of age, even with several markedly elevated risk factors, to exceed a 10% (let alone a 20%) 10-year predicted risk for CHD with the Adult Treatment Panel III risk estimator.33,34 Thus, few women qualify for aggressive CVD prevention when 10-year risk is used to determine its need. Fortunately, more recent Framingham equations are now available to predict 10- and 30-year risk for all CVD events (including CHD, stroke, heart failure, and claudication).3436

A focus on long-term CVD risk, not solely on 10-year CHD risk, is also supported by recent data indicating that 56% of American adults (87 million people), including 47.5 million women overall and 64% of women 60 to 79 years of age, have a 10-year predicted risk for CHD of <10% but a predicted lifetime risk for CVD of ≥39%.37

The role that novel CVD risk biomarkers (eg, hsCRP or advanced lipid testing) and imaging technologies (eg, coronary calcium scoring assessment) should play in risk assessment and in delineation of appropriate preventive interventions is not yet well defined. It should be noted that JUPITER did not test a strategy of routine screening with hsCRP to determine benefit of statin therapy because those with lower hsCRP levels were not studied.29 These approaches should not be used for routine screening of all women. Instead, the AHA and other national groups have recommended that the use of these novel modalities should be reserved for refining risk estimates in intermediate-risk patients when there is uncertainty about the need to start drug therapy.3841 Further research is needed on added benefits, risks, and costs associated with such strategies. Although recent evidence suggests that using imaging modalities such as coronary calcium scoring and carotid ultrasound to demonstrate the presence of advanced atherosclerosis has the greatest utility for reclassifying risk in those (including women) predicted to be at intermediate risk on the basis of short-term risk equations such as the Framingham risk score, their value in improving clinical outcomes has not been established.42,43 It should also be noted that several novel risk factors, which have been associated with an increased risk of CVD in women, have been identified, but their utility for screening and improving clinical outcomes has not been determined.

Because of its unique cardiovascular and metabolic stress, pregnancy provides a unique opportunity to estimate a woman's lifetime risk. For example, preeclampsia may be an early indicator of CVD risk.44,45 A recent large meta-analysis found that women with a history of preeclampsia have approximately double the risk for subsequent ischemic heart disease, stroke, and venous thromboembolic events over the 5 to 15 years after pregnancy.46 In these patients, the physiological “metabolic syndrome of pregnancy” may provoke pregnancy complications. The latter could be considered a “failed stress test,” possibly unmasking early or preexisting endothelial dysfunction and vascular or metabolic disease.47 Therefore, appropriate referral postpartum by the obstetrician to a primary care physician or cardiologist should occur so that in the years after pregnancy, risk factors can be carefully monitored and controlled. Healthcare professionals who meet women for the first time later in their lives should take a careful and detailed history of pregnancy complications with focused questions about a history of gestational diabetes mellitus, preeclampsia, preterm birth, or birth of an infant small for gestational age.4850

Future research should evaluate the potential for exposures, events, or interaction with the medical system during periods of potential vulnerability across a woman's lifespan such as menarche, pregnancy, and menopause to identify women at risk and to determine the effectiveness of diagnostic and preventive interventions during these critical times.

Other factors that are more prevalent among women and/or may make special contributions to CVD risk in women need further clarification in the context of defining effective interventions to improve CVD outcomes, as well as functional outcomes and adherence to therapy. These include depression and other psychosocial risk factors, as well as autoimmune diseases. Systemic lupus erythematosus and rheumatoid arthritis may be unrecognized risk factors in women and have been associated with a significantly increased relative risk for CVD.51 Women with such conditions but without clinically evident CVD should be considered at risk and screened for CVD risk factors, whereas women with prior CVD events should be screened for these conditions to allow appropriate secondary CVD prevention efforts and to allow the autoimmune condition to be addressed.

Diversity, Disparities, and Population Representation

The changing demographics of the United States, and indeed the world, necessitate that healthcare professionals consider the diversity of the patients that they encounter. Diversity may denote a variety of factors to each member of a healthcare team. In addition to the well-recognized classifications of race/geographic origin and ethnic origin, other facets of diversity need to be considered such as age, language, culture, literacy, disability, frailty, socioeconomic status, occupational status, and religious affiliation, among others. A better understanding of these aspects of diversity may help to reduce disparities in healthcare delivery. The Institute of Medicine defines disparity as a difference in treatment provided to members of ethnic or racial groups that is not justified by health condition differences or treatment preferences. The Institute of Medicine report also states that these disparities exist even when controlling for insurance status, socioeconomic status, and comorbidities.52 Disparities in cardiovascular health continue to be a serious public health issue in the United States. Despite the remarkable declines in cardiovascular mortality observed nationally over the past few decades, many population subgroups defined by race, ethnicity, gender, socioeconomic status, educational level, or geography, still show striking disparities in cardiovascular health. The pervasive nature of these disparities and compelling evidence of the adverse impact they have on clinical outcomes and quality of life in black and Hispanic women need to be recognized by clinicians. The root causes of disparities include variations and lack of understanding of health beliefs, cultural values and preferences, and patients' inability to communicate symptoms in a language other than their own, among other factors.5355 During the past decade, the clinical research focus on innovative methods to eliminate healthcare disparities has demonstrated some promise in multiteam culturally tailored interventions such as those with nurse-led case managers and community health workers. Cultural competence, therefore, has emerged as a process that unites the assessment and recognition of cultural differences, cultural knowledge, and cultural skills.56 Culturally sensitive care includes the adaptation of healthcare delivery to meet the needs of a diverse patient population. Thus, diversity, as defined above, in the context of healthcare, is concerned with delivering equitable care for all individuals.5759

Although guidelines may be applied across all groups, it is important to remember the higher prevalence of risk factors in certain racial/ethnic groups such as hypertension among black women or diabetes mellitus in women of Hispanic descent.6 Notably, the highest coronary heart death rates and the highest overall CVD morbidity and mortality occur in black women. Furthermore, the mortality from coronary artery disease for black women is similar to that of white men.6 These disparities in the occurrence of CVD and established risk factors underscore the need for heightened preventive efforts in subpopulations of women.

Ethnic categorization often fails to recognize cultural differences such as within Hispanics. Although the broad term is “Latino” or “Hispanic,” the actual definition includes people of Cuban, Mexican, Puerto Rican, or South or Central American origin. These cultures have distinct backgrounds, health behaviors, and beliefs, but they are often grouped together. Hispanics living in the United States may be faced with stresses of immigration, lower socioeconomic status, and inadequate access to healthcare. Despite these adversities, Hispanics, with a burden of cardiovascular risk factors similar to that of non-Hispanic whites, have a lower mortality. This observation has been called the “Hispanic paradox” as confirmed in recent data released by the National Center for Health Statistics, which finds Hispanic life expectancy to be 80 years compared with 77.5 years for non-Hispanic whites and 72.3 years for non-Hispanic blacks.60,61 Although deaths from heart disease have decreased in all groups, Hispanics have the lowest percentage of cardiovascular deaths (21.7%) compared with non-Hispanics (26.3%).62 The life expectancy for Hispanic women was the highest for all groups at 83.1 years compared with 80.4 years for non-Hispanic white women, 76.2 years for non-Hispanic black women, 77.9 years for Hispanic men, and 75.6 years for non-Hispanic white men. The lowest life expectancy was for non-Hispanic black men at 69.2 years.63

In addition to racial and ethnic diversity, the healthcare professional should be familiar with the patient's socioeconomic status, which may make attaining healthy lifestyles and using medications more difficult. In this context, recommendations that are more appropriate to the life circumstances of the patient may have to be adapted. Age should also be considered in the context of diversity because in the life continuum of women, application of the guidelines may need adaptation to stages such as pregnancy or the frailty of the elderly. Thus, the recognition of all aspects of diversity and the delivery of culturally sensitive care must guide clinicians to apply these guidelines broadly to match the diversity of women patients they treat, avoiding disparity of care.6466

International Issues

The international applicability of these guidelines is a critical issue because CVD has become a global pandemic among women. Approximately 81% of all CVD deaths in women occur in low- and middle-income countries with limited capacity for guidelines development.67 International applicability can be defined as the desirability and capacity to adopt the recommendations proposed in this guidelines document “as is” or after appropriate adaptation by medical societies, clinicians, and patients in other countries.

The World Health Organization and other international organizations have proposed measures for evaluating the international applicability of a guidelines document.6872 In the Global Program on Evidence for Health Policy. Guidelines for WHO Guidelines, 4 criteria were proposed for assessing the international applicability of guidelines: (1) efficacy and safety, (2) cost-effectiveness, (3) affordability, and (4) population benefits.68 The Appraisal of Guidelines Research and Evaluation project, an international collaboration, also designed an instrument to appraise clinical guidelines.69 The indicators for applicability assessment include potential organizational barriers in applying the guidelines, cost implications of applying the recommendations, and the presence of key review criteria for monitoring and audit purposes.70 Methods and tools are available for international users to determine whether recommendations provided in guidelines are suitable for local applications or whether some modifications are needed before application of guidelines.7075

International applicability is an important feature of the updated women's guidelines because almost all of the recommendations can be used in most countries or regions, either directly or with slight modifications. The descriptions of the recommendations are easy to comprehend and apply in clinical practice. Risk classification is practical and should be feasible for clinicians and patients worldwide. Additionally, generic drugs are available for most of the therapies recommended in this guidelines document. Some modifications, however, may be required, depending on the specific demands of the countries or regions such as the definition of generalized overweight obesity and central obesity.

It is noteworthy that some of the recommendations in the guidelines for CVD prevention in women are based on studies with relatively small sample sizes of women, which is particularly problematic when considering women with different cultural and racial-ethnic backgrounds. Thus, the conclusions of meta-analyses based on these studies may not be generalizable to women worldwide.

Healthcare Professional Implementation

Achievement of both the desired degree and persistence of CVD preventive care has been disappointing in both women and men. Although improving, the level of public awareness and rates of treatment and control of lipids, hypertension, and diabetes mellitus remain suboptimal.7678 For instance, ≈50% of Americans with hypertension are not treated to goal. Furthermore, ethnic/racial disparities in the management of hypertension, lipids, and diabetes mellitus persist.76

By establishing scientific levels of evidence and desired treatment strategies, guidelines are fundamental to improving CVD preventive care. However, multiple patient, clinician, and systemic barriers limit adherence to CVD prevention guidelines for women.79,80 A meta-analysis of >100 medical adherence studies shows that women are as likely to be nonadherent to medical therapies as men.81 It is ironic that the level of scientific evidence incorporated in most guidelines is much more robust than the research available for practical implementation and maintenance of adherence to those guidelines. Multiple barriers hinder adoption of guidelines, including lack of access to primary care services and lack of knowledge and skill in guideline implementation on the part of internists, family practitioners, and gynecologists.82,83 For instance, in a study of impediments to CVD prevention, one half of obstetrician-gynecologists and one third of internists surveyed were unaware that tobacco use is the leading cause of MIs in younger women.84

The physicians who reported time as a barrier were less likely to discuss smoking cessation with their women patients.83 Impediments to implementation of guidelines include time pressures, lack of organizational support, and patient resistance to behavioral change.84,85 Conclusions about the best methods for implementation of CVD prevention have been difficult to reach because of heterogeneity in interventions and outcomes between studies and other methodological limitations.84,85 The preponderance of evidence suggests that unidimensional interventions such as brief initial patient education and traditional patient reminders are generally ineffective.84,85 The most robust interventions are multifaceted, are interactive, and incorporate decision systems and feedback.84,85

An intervention increasingly advocated improving guidelines adherence is “pay for performance.” Performance measures are available for primary prevention of CVD, and the literature suggests some improvement in healthcare professional adherence to healthcare quality measures when pay-for-performance policies are implemented.86,87 Unfortunately, however, because of reliance on patient outcomes, such policies may also result in unintended detrimental consequences such as reduced access to care for sicker patients.87 Similar to the literature supporting guidelines adherence in general, much more research is needed on best practices, benefits, and hidden costs of pay-for-performance initiatives, including whether performance measures sometimes increase disparities in care.

Improvement in adherence to CHD guideline has been documented in centers implementing the Get With The Guidelines program of the AHA.88 Of note, disparities in MI guidelines adherence by gender, age, ethnicity, and race appeared to narrow over time in hospitals instituting this program.88,89 The AHA is now initiating a Get With The Guidelines–Outpatient program, and the American College of Cardiology has embraced quality improvement activities in implementation of CVD prevention guidelines.

The evidence base for practical methods for improving guideline adherence by effectively addressing substantive patient, clinician, and system-level barriers is generally lacking; however, there is some cause for optimism. There is increasing patient and clinician knowledge of the importance of CHD in women, and there have been improvements in CVD risk factor awareness, treatment, and control.89

Achieving the goal of improving cardiovascular health while reducing death and disability from CVD and stroke in women will require concerted efforts toward further research and the dissemination and implementation of lifestyle and treatment interventions. In the interim, quality improvement efforts can focus on incorporating multidimensional, interactive systems to increase accountability among payers, healthcare professionals, and patients for cardiovascular preventive care in women.90

Patient and Public Education

In 2000, it was estimated that only 7% of people with CHD adhered to prescribed treatments for CVD lifestyle risk factors.91 Studies evaluating adherence to medical therapies for CVD prevention also show similarly low rates of persistence. In addition, it is estimated that people with chronic illnesses may see up to 16 different physicians annually, making adherence reinforcement even more challenging for patients and healthcare professionals.92,93 Thirty percent to 70% of all hospital admissions for medication-related illness are attributed to poor adherence, resulting in billions of dollars in additional healthcare costs annually. Addressing adherence to recommendations in guidelines is of utmost importance.94,95 Effective implementation of national guidelines for the primary prevention of CVD will require a team-based approach to education that includes the patient, the family, and key healthcare professionals.93

The Joint Commission emphasizes the importance of patient education that is directed at improving patient outcomes, including quality of life.96 National guidelines for the primary prevention of CVD rely on patient education to support the importance of lifestyle change and medication adherence to reduce acute MI and stroke.32,97 Providing successful patient education is challenging for clinicians because of many factors, including limited time for healthcare visits, patients with complex comorbidities, lack of staff for teaching and follow-up, lack of training in counseling patients about behavior change, and lack of reimbursement for prevention in general and patient education in particular.98 Patient-related nonadherence is common and is most prevalent in several circumstances, including low socioeconomic status, low literacy level, depression and other psychiatric illnesses, older age, poor hearing or vision, poor cognitive function, and lack of fluency in English, as well as in certain cultures and religions in which confidence in and cooperation with Western medicine may be limited.

Understanding effective educational theories/practices can improve the ability of clinicians to effect behavior change and adherence to therapies. Well-recognized approaches include behaviorally based individual counseling, “motivational interviewing,” “self-efficacy,” and “stages of readiness for change.”99101 Self-monitoring (eg, food records, blood pressure/blood glucose logs), group sessions/shared medical visits (eg, for newly diagnosed diabetes mellitus), computer-assisted reminders, and other electronic communication to support behavioral change have been shown to improve both lifestyle and medication adherence.102106 Involving the patient and the patient's family in setting appropriate short-term achievable goals with frequent follow-up will also enhance success.

These guidelines call for a renewed focus on health education, including systematic follow-up to assess effectiveness of medical and lifestyle therapies. Assessment of barriers to adherence and interventions to address them must be integrated into clinical practice, and barriers specific for women must be considered. Barriers hindering adherence to CVD prevention recommendations are common among women and include family and caretaking responsibilities, stress, sleep deprivation, fatigue, and lack of personal time. Educational efforts are critically important, because increased awareness of personal cardiovascular risk factors has been associated with improved health and lifestyles for women and their family members.107


Selection of Expert Panel

The AHA Manuscript Oversight Committee commissioned the update of the guidelines and approved the writing group chair, the executive writing committee members with specific expertise (methods and cost-effectiveness, risk assessment, healthcare professional implementation, patient and consumer education, diversity and population representation, and international issues), and expert panel members to review the literature for updates to the recommendation topic areas. The leadership of each AHA scientific council was asked to nominate a recognized expert in CVD prevention who had particular knowledge about women.

Major professional or government organizations with a mission consistent with CVD prevention were solicited to serve as cosponsors and were asked to nominate 1 representative with full voting rights to serve on the expert panel. Each executive writing committee and expert panel member completed a conflict of interest statement and was asked to abstain from discussion or voting on any recommendations deemed to be a potential conflict of interest. Panelists also suggested diverse professional and community organizations to endorse the final document after its approval by the AHA Science Advisory and Coordinating Committee and cosponsoring organizations.

Selection of Topics and Systematic Search

The expert panel reviewed the list of recommendations in the 2007 guidelines and suggested additional topics to be searched to determine if they warranted discussion or a clinical recommendation. The search terms for the systematic search were similar to those conducted in 2007 and previously described.14,15 The databases searched for this update were PubMed, Embase, and Cochrane. The timeframe for the updated search was January 2006 through January 2010. Briefly, studies were included if they were randomized clinical trials or large prospective cohort studies (>1000 subjects) of CVD risk–reducing interventions, meta-analyses that used a quantitative systematic review process, or surrogate end-point studies with at least 10 cases of major clinical CVD end points reported. The systematic search was conducted by the AHA librarian. Class III recommendations from the 2007 guidelines update were not searched because of consensus by the expert panel members that data remained insufficient for modification (ie, menopausal therapy, antioxidants, and folic acid supplementation). Some topics were not included in the systematic search if they were covered in recent guidelines (eg, treatment of atrial fibrillation for stroke prevention).10

Evidence Rating and Recommendation Procedures

Subcommittees were organized by subtopic and were charged with preparation of summary evidence tables based on the updated literature review. These tables were then reviewed in series of conference calls, after which the subcommittee modified or retained the current recommendation on the basis of the discussions. Each recommendation was assigned both a strength of recommendation (Class I, IIa, IIb, or III) and a Level of Evidence (A, B, or C) as outlined in Table 3. The updated recommendations were voted on by the expert panel by individual ballot to determine by a majority vote the final rating of evidence, the strength of the recommendation, and its wording. Further minor modifications to text and clinical recommendations were based on peer review comments and cosponsor reviews. The guidelines were then finalized and approved by the expert panel (Table 4).

Table 3. Classification and Levels of Evidence

Classification and Level of EvidenceStrength of Recommendation
    Class IIntervention is useful and effective
    Class IIaWeight of evidence/opinion is in favor of usefulness/efficacy
    Class IIbUsefulness/efficacy is less well established by evidence/opinion
    Class IIIProcedure/test not helpful or treatment has no proven benefit
Procedure/test excess cost without benefit or harmful or treatment harmful to patients
Level of evidence
    ASufficient evidence from multiple randomized trials
    BLimited evidence from single randomized trial or other nonrandomized studies
    CBased on expert opinion, case studies, or standard of care

Table 4. Guidelines for the Prevention of CVD in Women

Lifestyle Interventions
    Cigarette smoking
    Women should be advised not to smoke and to avoid environmental tobacco smoke. Provide counseling at each encounter, nicotine replacement, and other pharmacotherapy as indicated in conjunction with a behavioral program or formal smoking cessation program (Class I; Level of Evidence B).
    Physical activity
    Women should be advised to accumulate at least 150 min/wk of moderate exercise, 75 min/wk of vigorous exercise, or an equivalent combination of moderate- and vigorous-intensity aerobic physical activity. Aerobic activity should be performed in episodes of at least 10 min, preferably spread throughout the week (Class I; Level of Evidence B).
    Women should also be advised that additional cardiovascular benefits are provided by increasing moderate-intensity aerobic physical activity to 5 h (300 min)/wk, 2 1/2 h/wk of vigorous-intensity physical activity, or an equivalent combination of both (Class I; Level of Evidence B).
    Women should be advised to engage in muscle-strengthening activities that involve all major muscle groups performed on ≥2 d/wk (Class I; Level of Evidence B).
    Women who need to lose weight or sustain weight loss should be advised to accumulate a minimum of 60 to 90 min of at least moderate-intensity physical activity (eg, brisk walking) on most, and preferably all, days of the week (Class I; Level of Evidence B).
    Cardiac rehabilitation
    A comprehensive CVD risk-reduction regimen such as cardiovascular or stroke rehabilitation or a physician-guided home- or community-based exercise training program should be recommended to women with a recent acute coronary syndrome or coronary revascularization, new-onset or chronic angina, recent cerebrovascular event, peripheral arterial disease (Class I; Level of Evidence A) or current/prior symptoms of heart failure and an LVEF ≤35% (Class I; Level of Evidence B).
    Dietary intake
    Women should be advised to consume a diet rich in fruits and vegetables; to choose whole-grain, high-fiber foods; to consume fish, especially oily fish, at least twice a week; to limit intake of saturated fat, cholesterol, alcohol, sodium, and sugar; and avoid trans-fatty acids. See Appendix (Class I; Level of Evidence B).
    Note: Pregnant women should be counseled to avoid eating fish with the potential for the highest level of mercury contamination (eg, shark, swordfish, king mackerel, or tile fish).
    Weight maintenance/reduction
    Women should maintain or lose weight through an appropriate balance of physical activity, caloric intake, and formal behavioral programs when indicated to maintain or achieve an appropriate body weight (eg, BMI <25 kg/m2 in US women), waist size (eg, <35 in), or other target metric of obesity. (Class I; Level of Evidence B).
    Omega-3 fatty acids
    Consumption of omega-3 fatty acids in the form of fish or in capsule form (eg, EPA 1800 mg/d) may be considered in women with hypercholesterolemia and/or hypertriglyceridemia for primary and secondary prevention (Class IIb; Level of Evidence B).
    Note: Fish oil dietary supplements may have widely variable amounts of EPA and DHA (likely the only active ingredients).
Major risk factor interventions
    Blood pressure: optimal level and lifestyle
    An optimal blood pressure of <120/80 mm Hg should be encouraged through lifestyle approaches such as weight control, increased physical activity, alcohol moderation, sodium restriction, and increased consumption of fruits, vegetables, and low-fat dairy products (Class I; Level of Evidence B).
    Blood pressure: pharmacotherapy
    Pharmacotherapy is indicated when blood pressure is ≥140/90 mm Hg (≥130/80 mm Hg in the setting of chronic kidney disease and diabetes mellitus). Thiazide diuretics should be part of the drug regimen for most patients unless contraindicated or if there are compelling indications for other agents in specific vascular diseases. Initial treatment of high-risk women with acute coronary syndrome or MI should be with β-blockers and/or ACE inhibitors/ARBs, with addition of other drugs such as thiazides as needed to achieve goal blood pressure (Class I; Level of Evidence A).
    Note: ACE inhibitors are contraindicated in pregnancy and ought to be used with caution in women who may become pregnant.
    Lipid and lipoprotein levels: optimal levels and lifestyle
    The following levels of lipids and lipoproteins in women should be encouraged through lifestyle approaches: LDL-C <100 mg/dL, HDL-C >50 mg/dL, triglycerides <150 mg/dL, and non–HDL-C (total cholesterol minus HDL) <130 mg/dL (Class I; Level of Evidence B).
    Lipids: pharmacotherapy for LDL-C lowering, high-risk women
    LDL-C–lowering drug therapy is recommended simultaneously with lifestyle therapy in women with CHD to achieve an LDL-C <100 mg/dL (Class I; Level of Evidence A) and is also indicated in women with other atherosclerotic CVD or diabetes mellitus or 10-year absolute risk >20% (Class I; Level of Evidence B).
    A reduction to <70 mg/dL is reasonable in very-high-risk women (eg, those with recent ACS or multiple poorly controlled cardiovascular risk factors) with CHD and may require an LDL-lowering drug combination (Class IIa; Level of Evidence B).
    Lipids: pharmacotherapy for LDL-C lowering, other at-risk women
    LDL-C–lowering with lifestyle therapy is useful if LDL-C level is ≥130 mg/dL, there are multiple risk factors, and the 10-y absolute CHD risk is 10% to 20% (Class I; Level of Evidence B).
    LDL-C lowering is useful with lifestyle therapy if LDL-C level is ≥160 mg/dL and multiple risk factors even if 10-y absolute CHD risk is <10% (Class I; Level of Evidence B).
    LDL-C lowering with lifestyle therapy is useful if LDL ≥190 mg/dL regardless of the presence or absence of other risk factors or CVD (Class I; Level of Evidence B).
    In women >60 y of age and with an estimated CHD risk >10%, statins could be considered if hsCRP is >2 mg/dL after lifestyle modification and no acute inflammatory process is present (Class IIb; Level of Evidence B).
    Lipids: pharmacotherapy for low HDL-C or elevated non–HDL-C
    Niacin or fibrate therapy can be useful when HDL-C is low (<50 mg/dL) or non–HDL-C is elevated (>130 mg/dL) in high-risk women after LDL-C goal is reached (Class IIb; Level of Evidence B).
    Diabetes mellitus
    Lifestyle and pharmacotherapy can be useful in women with diabetes mellitus to achieve an HbA1C <7% if this can be accomplished without significant hypoglycemia (Class IIa; Level of Evidence B).
Preventive drug interventions
    Aspirin: high-risk women
    Aspirin therapy (75–325 mg/d) should be used in women with CHD unless contraindicated (Class I; Level of Evidence A).
    Aspirin therapy (75–325 mg/d) is reasonable in women with diabetes mellitus unless contraindicated (Class IIa; Level of Evidence B).
    If a high-risk woman has an indication but is intolerant of aspirin therapy, clopidogrel should be substituted (Class I; Level of Evidence B).
    Aspirin: other at-risk or healthy women
    Aspirin therapy can be useful in women ≥65 y of age (81 mg daily or 100 mg every other day) if blood pressure is controlled and benefit for ischemic stroke and MI prevention is likely to outweigh risk of gastrointestinal bleeding and hemorrhagic stroke (Class IIa; Level of Evidence B) and may be reasonable for women <65 y of age for ischemic stroke prevention (Class IIb; Level of Evidence B).
    Aspirin: atrial fibrillation
    Aspirin 75–325 mg should be used in women with chronic or paroxysmal atrial fibrillation with a contraindication to warfarin or at low risk of stroke (<1%/y or CHADS2 score of <2) (Class I; Level of Evidence A).
    Warfarin: atrial fibrillation
    For women with chronic or paroxysmal atrial fibrillation, warfarin should be used to maintain the INR at 2.0 to 3.0 unless they are considered to be at low risk for stroke (<1%/y or high risk of bleeding) (Class I; Level of Evidence A).
    Dabigatran: atrial fibrillation
    Dabigatran is useful as an alternative to warfarin for the prevention of stroke and systemic thromboembolism in patients with paroxysmal to permanent AF and risk factors for stroke or systemic embolization who do not have a prosthetic heart valve or hemodynamically significant valve disease, severe renal failure (creatinine clearance <15 mL/min), or advanced liver disease (impaired baseline clotting function) (Class I; Level of Evidence B).
    β-Blockers should be used for up to 12 mo (Class I; Level of Evidence A) or up to 3 y (Class I; Level of Evidence B) in all women after MI or ACS with normal left ventricular function unless contraindicated.
    Long-term β-blocker therapy should be used indefinitely for women with left ventricular failure unless contraindications are present (Class I; Level of Evidence A).
    Long-term β-blocker therapy may be considered in other women with coronary or vascular disease and normal left ventricular function (Class IIb; Level of Evidence C).
    ACE inhibitors/ARBs
    ACE inhibitors should be used (unless contraindicated) in women after MI and in those with clinical evidence of heart failure, LVEF ≤40%, or diabetes mellitus (Class I; Level of Evidence A).
    In women after MI and in those with clinical evidence of heart failure, an LVEF ≤40%, or diabetes mellitus who are intolerant of ACE inhibitors, ARBs should be used instead (Class I; Level of Evidence B).
    Note: ACE inhibitors are contraindicated in pregnancy and ought to be used with caution in women who may become pregnant.
    Aldosterone blockade
    Use of aldosterone blockade (eg, spirololactone) after MI is indicated in women who do not have significant hypotension, renal dysfunction, or hyperkalemia who are already receiving therapeutic doses of an ACE inhibitor and β-blocker and have LVEF ≤40% with symptomatic heart failure (Class I; Level of Evidence B).

LVEF indicates left ventricular ejection fraction; BMI, body mass index; EPA, eicosapentaenoic acid; DHA, docosahexaenoic acid; ACE, angiotensin-converting enzyme; ARB, angiotensin receptor blocker; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; CHD, coronary heart disease; CVD, cardiovascular disease; ACS, acute coronary syndrome; hsCRP, high-sensitivity C-reactive protein; HbA1C, hemoglobin A1C; MI, myocardial infarction; CHADS2, Congestive Heart Failure, Hypertension, Age, Diabetes, Prior Stroke; and INR, international normalized ratio.


Cost-effectiveness analyses reviewed were published between 2000 and 2010, focusing on randomized controlled trials and observational studies of omega-3 use, dietary intake, β-blocker and aspirin therapy, and management of obesity, smoking, and hypertension in secondary and primary prevention of CVD.108125 Few of these studies included gender-stratified or gender-specific analyses119,122; however, some cost-effectiveness analyses with Markov or simulation modeling presented gender-specific or women-only data.126138

Often the cost inputs and methodologies were insufficiently described or used resource consumption as a surrogate for cost. On the basis of these analyses, aspirin appears cost-effective in women ≥65 years of age with moderate to severe CVD risk.133135 Antihypertensive treatments and smoking cessation treatments appear cost-effective for women.126132 Weight management approaches, including drug therapy and gastric bypass surgery, appear effective for weight loss but add costs, with decision analytic approaches noting favorable cost-effective ratios in younger and middle-aged obese women.123,137,138

The expert panel emphasized the need for more cost-effective analyses according to gender. Consistent with a recent Institute of Medicine report on women's health research, the expert panel recommends adequate participation of women and reporting of gender-stratified analyses in health research.139 The panel also emphasized the need for reporting of gender-specific analyses for both efficacy and adverse effects of preventative interventions to inform the development of future gender-specific guidelines.


Writing Group Disclosures

Writing Group MemberEmploymentResearch GrantOther Research SupportSpeakers' Bureau/HonorariaExpert WitnessOwnership InterestConsultant/Advisory BoardOther
Lori MoscaColumbia UniversityNoneNoneNoneNoneNoneNoneNone
Emelia J. BenjaminBoston University Schools of Medicine and Public HealthItamar Medical; NIH: NHLBI/NIANoneNoneNoneNoneNoneNone
Kathy BerraStanford UniversityNoneNoneBoehringer-Ingelheim*; Novartis*; Pfizer*NoneNoneAspirin Task Force (Partnership for Prevention)*None
Judy L. BezansonAmerican Heart AssociationNoneNoneNoneNoneNoneNoneNone
Rowena J. DolorDuke UniversityAHRQ; NIHNoneNoneNoneNoneNoneNone
Donald M. Lloyd-JonesNorthwestern UniversityNoneNonePfizer*NoneNoneNoneNone
L. Kristin NewbyDuke University Medical CenterAmgen; Amylin*; AstraZeneca*; diaDexus; GlaxoSmithKline Merck & Company; Schering Plough (now owned by Merck)NoneNoneNoneNoneNoneNone
Ileana L. PiñaCase Western Reserve UniversityNIH*NoneAstraZeneca*; Boehringer Ingelheim*; Innovia*; Merck*; Otuska*; Sanofi-Aventis*; Solvay*NoneNoneFDA;* GE HealthcareNone
Véronique L. RogerMayo Clinic RochesterNoneNoneNoneNoneNoneNoneNone
Leslee J. ShawEmory UniversityBracco Diagnostics; GE HealthcareNoneNoneNoneNoneNoneNone
Dong ZhaoCapital Medical University/Beijing Anzhen Hospital/Beijing Institute of Heart, Lung, and Blood Vessel DiseasesNoneNonePresented ″Women's Health″ to a group of female cardiologists from ≈20 hospitals in Beijing. This lecture was organized by Woman Physician Association but sponsored by Novartis*NoneNoneNoneNone
Theresa M. BeckieUniversity of South FloridaNoneNoneNoneNoneNoneNoneNone
Cheryl BushnellWake Forest University Health SciencesNIH KO2NS058760, PI, Sex Differences in Markers of Vascular RiskBristol-Myers Squibb, co-PI for AVAIL RegistryNoneNoneNoneNoneNone
Jeanine D'ArmientoColumbia UniversityNoneNoneNoneNoneNoneNoneNone
Penny M. Kris-EthertonPennsylvania State UniversityNoneUSDA, PI on “Development, Implementation, and Testing Educational programs to Track Weight Loss using the 2005 Dietary GLs in Premenopausal Women”NoneNoneNoneWomenHeart Advisory Board Member*None
Jing FangCDCNoneNoneNoneNoneNoneNoneNone
Theodore G. GaniatsUCSDAmgen*; NIH*NoneNoneWitness for plaintiff in case about failure to give DVT prophylaxis*NoneAmerican Academy of Family Physicians; American College of Cardiology*; American Heart Association*None
Antoinette S. GomesUCLA School of MedicineNoneNoneNoneNoneNoneNoneNone
Clarisa R. GraciaUniversity of PennsylvaniaNoneNoneNoneNoneNoneNoneNone
Constance K. HaanUniversity of Florida College of Medicine–JacksonvilleNoneNoneNoneNoneNoneNoneNone
Elizabeth A. JacksonUniversity of Michigan Health SystemNIH; University of Michigan Cardiovascular CenterNoneACC*; McKesson*; PriMed*NoneNoneACC*; McKesson*; PriMed*None
Debra R. JudelsonCardiovascular Medical Group of Southern CaliforniaNoneNoneNoneExpert on Seroquel for AstraZeneca (no case, deposition or trial); expert on fentanyl for ALZA/Johnson & Johnson (no case, deposition, or trial); addendum: deposition fentanyl case: Auburn vs Johnson & Johnson et al, no trial); addendum: expert on OrthoEvra for Johnson & Johnson et al., deposition Crespin v. Johnson & Johnson et al., no trial)NoneNoneNone
Ellie KelepourisDrexel University College of MedicineNoneNoneGenzyme Corp*NoneNoneGenzyme Corp*None
Carl J. LavieOchsner Health SystemNoneNoneAbbott Laboratories; GlaxoSmithKline; PfizerNoneNoneNoneNone
Anne MooreVanderbilt School of NursingNoneNoneBayer*; Teva Pharmaceuticals*NoneNoneBayer*; Teva Pharmaceuticals*None
Nancy A. NussmeierSUNY Upstate Medical UniversityConmed*; Nonin*NoneSchering Plough*NoneNoneNovo Nordisk*; Schering Plough*None
Elizabeth OfiliMorehouse School of MedicineBristol Myers Squibb; NIHNoneNovartisNoneNoneMerck & Co*; Novartis*; Sanofi AventisNone
Suzanne OparilUniversity of Alabama at BirminghamNoneNoneNoneNoneNoneNoneNone
Pamela OuyangJohns Hopkins UniversityBristol-Myers Squibb; NIHNoneNoneNoneNoneSociety of Women's Health Research, ISIS Fund CVD Network*None
Vivian W. PinnDepartment of Health and Human Services (NIH)NoneNoneNoneNoneNoneNoneGovernment employee bound by HHS ethics
Katherine SherifDrexel University College of MedicineNoneNoneGlaxoSmithKline*NoneNoneNoneNone
Sidney C. Smith, JrUniversity of North Carolina at Chapel HillNoneNoneNoneNoneNoneNoneNone
George SopkoNHLBINoneNoneNoneNoneNoneNoneNone
Nisha Chandra- StrobosJohns Hopkins Bayview Medical CenterNoneNoneNoneNoneNoneNoneNone
Elaine M. UrbinaCincinnati Children's HospitalNoneNoneNoneNoneNoneNoneNone
Viola VaccarinoEmory University School of MedicineNoneNoneNoneNoneNoneNoneNone
Nanette K. WengerEmory University School of MedicineGilead Sciences; Merck; NHLBI; Pfizer; Sanofi-Aventis; Schering-PloughAbbott; Eli Lilly; NHLBINoneNoneNoneAbbott Laboratories; CV Therapeutics; Eli Lilly; Pfizer; Schering-PloughNone

This table represents the relationships of writing group members that may be perceived as actual or reasonably perceived conflicts of interest as reported on the Disclosure Questionnaire, which all members of the writing group are required to complete and submit. A relationship is considered to be “significant” if (a) the person receives $10 000 or more during any 12-month period, or 5% or more of the person's gross income; or (b) the person owns 5% or more of the voting stock or share of the entity, or owns $10 000 or more of the fair market value of the entity. A relationship is considered to be “modest” if it is less than “significant” under the preceding definition.



Reviewer Disclosures

ReviewerEmploymentResearch GrantOther Research SupportSpeakers' Bureau/HonorariaExpert WitnessOwnership InterestConsultant/Advisory BoardOther
Vera BittnerUniversity of Alabama at BirminghamGilead: WISQ Study; Roche–DAL-Outcomes Study; GSK–Stability Trial; NIH/Yale–VIRGO Registry; NIH/Abbott–AIM HIGH trialNational Coordinator for the ALECARDIO trial (Roche)*NoneNoneNonePfizer*Immediate past president, National Lipid Association*
Eliot A. BrintonUniversity of UtahAbbott; GSK; MerckNoneAbbott; Daiichi-Sankyo*; GSK; Kaneka*; Merck; TakedaNoneNoneAbbott*; Amarin*; Atherotech; Daiichi-Sankyo*; Essentialis*; GSK*; Merck*; Takeda*None
Monique V. ChireauDuke UniversityDuke Translational Research Institute; Duke Clinical Research Unit*NoneNoneNoneNoneChireau Consultant/Advisory Board, Templeton Foundation*None
Jennifer CummingsAkron General Medical CenterNoneNoneSanofi Aventis*; Boston Scientific*; Medtronic*; St Jude*NoneNoneCorazon Consulting*; St Jude*; Medtronic*None
Claire DuvernoyVA Healthcare SystemVA Cooperative Studies Program*Sanofi-Aventis*NoneNoneNoneNoneNone
Federico GentileCentro Medico Diagnostico (Naples, Italy)NoneNoneNoneNoneNoneNoneNone
Suzanne HughesSumma Health System (Akron, OH)NoneNoneNoneNoneNoneNoneNone
Courtney O. JordanUniversity of MinnesotaNoneNoneNoneNoneNoneNoneNone
Sanjay KaulCedars-Sinai Medical CenterHoffman La Roche*NoneNoneNoneJohnson & Johnson*Hoffman La Roche*; FDA*None
Mary McGrae McDermottNorthwestern UniversityNHLBINoneNoneNoneNoneNoneContributing editor, JAMA
Laxmi S. MehtaOhio State UniversityNoneNoneNoneNoneNoneNoneNone
C. Venkata S. RamDallas Nephrology AssociatesNoneNoneNoneNoneNoneNoneNone
Rita F. RedbergUCSFFlight Attendant Medical Research Institute*NoneNoneNoneNoneGTAF*; FDA CVD Expert Panel*None
Vincent L. SorrellUniversity of ArizonaNoneNoneNoneNoneNoneNoneNone
Deborah WesleyWake Forest UniversityNoneNoneNoneNoneNoneNoneNone

This table represents the relationships of reviewers that may be perceived as actual or reasonably perceived conflicts of interest as reported on the Disclosure Questionnaire, which all reviewers are required to complete and submit. A relationship is considered to be “significant” if (a) the person receives $10 000 or more during any 12-month period, or 5% or more of the person's gross income; or (b) the person owns 5% or more of the voting stock or share of the entity, or owns $10 000 or more of the fair market value of the entity. A relationship is considered to be “modest” if it is less than “significant” under the preceding definition.




We are greatly appreciative of Vanessa S. Perez, MLS, librarian at AHA National Center, for her expertise in performing the extensive literature review for all the topic areas and Sheila M. McNallan, MPH, for her assistance with the cost-effectiveness literature review. We are indebted to Dr Jose Maria E. Ferrer, AHA Associate Science and Medicine Advisor, and Dr Cheryl L. Perkins, AHA Science and Medicine Advisor, for their support in assisting with responses to peer review and final submission of the manuscript.

Appendix. Specific Dietary Intake Recommendations for Women

NutrientServingServing Size
Fruits and vegetables≥4.5 cups/d1 cup raw leafy vegetable, 1/2 cup cut-up raw or cooked vegetable, 1/2 cup vegetable juice; 1 medium fruit, 1/4 cup dried fruit, 1/2 cup fresh, frozen, or canned fruit, 1/2 cup fruit juice
Fish2/wk3.5 oz, cooked (preferably oily types of fish)
Fiber30 g/d (1.1 g/10 g carbohydrate)Bran cereal, berries, avocado, etc
Whole grains3/d1 slice bread, 1 oz dry cereal, 1/2 cup cooked rice, pasta, or cereal (all whole-grain products)
Sugar≤5/wk (≤450 kcal/wk from sugar-sweetened beverages)1 tablespoon sugar, 1 tablespoon jelly or jam, 1/2 cup sorbet, 1 cup lemonade
Nuts, legumes, and seeds≥4/wk1/3 cup or 1 1/2 oz nuts (avoid macadamia nuts and salted nuts), 2 tablespoons peanut butter, 2 tablespoon or 1/2 oz seeds, 1/2 cup cooked legumes (dry beans and peas)
Saturated fat<7%/total energy intakeFound in fried foods, fat on meat or chicken skin, packaged desserts, butter, cheese, sour cream, etc
Cholesterol<150 mg/dFound in animal meats, organ meats, eggs, etc
Alcohol≤1/d4 oz wine, 12 oz beer, 1.5 oz of 80-proof spirits, or 1 oz of 100-proof spirits
Sodium<1500 mg/d
Trans-fatty acids00

Note: The recommended serving amounts are based on a 2000-kcal diet, and recommendations vary according to individual preference and needs.141

Note for Vitamin D: It is expected that ongoing research regarding the role of vitamin D supplementation in the prevention of cardiovascular disease will shed further light on this issue for future versions of this guideline.142


The following American Heart Association councils were also cosponsors: Council on Arteriosclerosis, Thrombosis and Vascular Biology; Council on Basic Cardiovascular Sciences; Council on Cardiopulmonary, Critical Care, Perioperative and Resuscitation; Council on Cardiovascular Disease in the Young; Council on Cardiovascular Nursing; Council on Cardiovascular Radiology and Intervention; Council on Cardiovascular Surgery and Anesthesia; Council on Clinical Cardiology; Council on Epidemiology and Prevention; Council for High Blood Pressure Research; Council on the Kidney in Cardiovascular Disease; Council on Nutrition, Physical Activity and Metabolism; Council on Peripheral Vascular Disease; Interdisciplinary Council on Functional Genomics and Translational Biology; and Interdisciplinary Council on Quality of Care and Outcomes Research.

This report has been endorsed by the American Academy of Physician Assistants; American Association for Clinical Chemistry; American Association of Cardiovascular and Pulmonary Rehabilitation; American College of Chest Physicians; American Diabetes Association; American Society for Preventive Cardiology; American Society of Echocardiography; American Society of Nuclear Cardiology; Association of Women's Health, Obstetric and Neonatal Nurses; Department of Health and Human Services Office on Women's Health; Hartford Institute for Geriatric Nursing; HealthyWomen; The Mended Hearts, Inc.; National Black Nurses Association; The National Coalition for Women with Heart Disease; North American Menopause Society; Preeclampsia Foundation; Preventive Cardiovascular Nurses Association; Society for Vascular Medicine and Biology; Society for Women's Health Research; Women in Thoracic Surgery; and WomenHeart.

*The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

†Representation does not imply endorsement by the American College of Physicians.

The American Heart Association makes every effort to avoid any actual or potential conflicts of interest that may arise as a result of an outside relationship or a personal, professional, or business interest of a member of the writing panel. Specifically, all members of the writing group are required to complete and submit a Disclosure Questionnaire showing all such relationships that might be perceived as real or potential conflicts of interest.

This statement was approved by the American Heart Association Science Advisory and Coordinating Committee on January 7, 2011. A copy of the statement is available at by selecting either the “topic list” link or the “chronological list” link. To purchase additional reprints, call 843-216-2533 or e-mail .

The online-only Data Supplement is available with this article at

The American Heart Association requests that this document be cited as follows: Mosca L, Benjamin EJ, Berra K, Bezanson JL, Dolor RJ, Lloyd-Jones DM, Newby LK, Piña IL, Roger VL, Shaw LJ, Zhao D; Beckie TM, Bushnell C, D'Armiento J, Kris-Etherton PM, Fang J, Ganiats TG, Gomes AS, Gracia CR, Haan CK, Jackson EA, Judelson DR, Kelepouris E, Lavie CJ, Moore A, Nussmeier NA, Ofili E, Oparil S, Ouyang P, Pinn VW, Sherif K, Smith SC Jr, Sopko G, Chandra-Strobos N, Urbina EM, Vaccarino V, Wenger NK. Effectiveness-based guidelines for the prevention of cardiovascular disease in women—2011 update: a guideline from the American Heart Association. Circulation. 2011;123:1243–1262.

Expert peer review of AHA Scientific Statements is conducted at the AHA National Center. For more on AHA statements and guidelines development, visit

Permissions: Multiple copies, modification, alteration, enhancement, and/or distribution of this document are not permitted without the express permission of the American Heart Association. Instructions for obtaining permission are located at A link to the “Permission Request Form” appears on the right side of the page.


  • 1. Mosca L, Grundy SM, Judelson D, King K, Limacher M, Oparil S, Pasternak R, Pearson TA, Redberg RF, Smith SC, Winston M, Zinberg S. Guide to preventive cardiology for women: AHA/ACC Scientific Statement Consensus panel statement. Circulation. 1999; 99:2480–2484.LinkGoogle Scholar
  • 2. Mosca L, Mochari-Greenberger H, Dolor RJ, Newby LK, Robb KJ. Twelve-year follow-up of American women's awareness of cardiovascular disease risk and barriers to heart health. Circ Cardiovasc Qual Outcomes. 2010; 3:120–127.LinkGoogle Scholar
  • 3. Xu JQ, Kochanek KD, Murphy SL, B. T-V. Deaths: Final Data for 2007: National Vital Statistics Reports. Hyattsville, MD: National Center for Health Statistics; 2010.Google Scholar
  • 4. Ford ES, Ajani UA, Croft JB, Critchley JA, Labarthe DR, Kottke TE, Giles WH, Capewell S. Explaining the decrease in U.S. deaths from coronary disease, 1980–2000. N Engl J Med. 2007; 356:2388–2398.CrossrefMedlineGoogle Scholar
  • 5. Rossouw JE, Anderson GL, Prentice RL, LaCroix AZ, Kooperberg C, Stefanick ML, Jackson RD, Beresford SA, Howard BV, Johnson KC, Kotchen JM, Ockene JWriting Group for the Women's Health Initiative Investigators. Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results from the Women's Health Initiative randomized controlled trial [summary for patients appears in CMAJ. 2002; 2167:2377–2378and J Fam Pract. 2002;2051:2821]. JAMA. 2002;288:321–333.Google Scholar
  • 6. Roger VL, Go AS, Lloyd-Jones DM, Adams RJ, Berry JD, Brown TM, Carnethon MR, Dai S, de Simone G, Ford ES, Fox CS, Fullerton HJ, Gillespie C, Greenlund KJ, Hailpern SM, Heit JA, Ho PM, Howard VJ, Kissela BM, Kittner SJ, Lackland DT, Lichtman JH, Lisabeth LD, Makuc DM, Marcus GM, Marelli A, Matchar DB, McDermott MM, Meigs JB, Moy CS, Mozaffarian D, Mussolino ME, Nichol G, Paynter NP, Rosamond WD, Sorlie PD, Stafford RS, Turan TN, Turner MB, Wong ND, Wylie-Rosett Jon behalf of the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics—2011 update: a report from the American Heart Association [published correction appears in Circulation. 2011;123:e240]. Circulation. 2011; 123:e18–e209.LinkGoogle Scholar
  • 7. Kleindorfer D, Khoury J, Broderick JP, Rademacher E, Woo D, Flaherty ML, Alwell K, Moomaw CJ, Schneider A, Pancioli A, Miller R, Kissela BM. Temporal trends in public awareness of stroke: warning signs, risk factors, and treatment. Stroke. 2009; 40:2502–2506.LinkGoogle Scholar
  • 8. Ferris A, Robertson RM, Fabunmi R, Mosca LAmerican Heart Association; American Stroke Association. American Heart Association and American Stroke Association national survey of stroke risk awareness among women. Circulation. 2005; 111:1321–1326.LinkGoogle Scholar
  • 9. Wann LS, Curtis AB, January CT, Ellenbogen KA, Lowe JE, Estes NA, Page RL, Ezekowitz MD, Slotwiner DJ, Jackman WM, Stevenson WG, Tracy CM, Jacobs AK. 2011 ACCF/AHA/HRS focused update on the management of patients with atrial fibrillation (updating the 2006 guideline): a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Circulation. 2010; 123:104–123.MedlineGoogle Scholar
  • 10. Fuster V, Ryden LE, Cannom DS, Crijns HJ, Curtis AB, Ellenbogen KA, Halperin JL, Le Heuzey JY, Kay GN, Lowe JE, Olsson SB, Prystowsky EN, Tamargo JL, Wann S, Smith SC, Jacobs AK, Adams CD, Anderson JL, Antman EM, Halperin JL, Hunt SA, Nishimura R, Ornato JP, Page RL, Riegel B, Priori SG, Blanc JJ, Budaj A, Camm AJ, Dean V, Deckers JW, Despres C, Dickstein K, Lekakis J, McGregor K, Metra M, Morais J, Osterspey A, Tomargo JL, Zamorano JL. ACC/AHA/ESC 2006 guidelines for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and the European Society of Cardiology Committee for Practice Guidelines (Writing Committee to Revise the 2001 Guidelines for the Management of Patients With Atrial Fibrillation): developed in collaboration with the European Heart Rhythm Association and the Heart Rhythm Society. Circulation. 2006; 114:e257–e354.LinkGoogle Scholar
  • 10a. Wann LS, Curtis AB, Ellenbogen KA, Estes NAM, Ezekowitz MD, Jackman WM, January CT, Lowe JE, Page RL, Slotwiner DJ, Stevenson WG, Tracy CMwriting on behalf of the 2006 ACC/AHA/ESC Guidelines for the Management of Patients With Atrial Fibrillation Writing Committee. 2011 ACCF/AHA/HRS focused update on the management of patients with atrial fibrillation (update on dabigatran): a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Circulation. February14, 2011. DOI: 10.1161/CIR.0b013e31820f14c0. Accessed February 14, 2011.Google Scholar
  • 11. Hertz RP, Unger AN, Cornell JA, Saunders E. Racial disparities in hypertension prevalence, awareness, and management. Arch Intern Med. 2005; 165:2098–2104.CrossrefMedlineGoogle Scholar
  • 12. Preis SR, Hwang SJ, Coady S, Pencina MJ, D'Agostino RB, Savage PJ, Levy D, Fox CS. Trends in all-cause and cardiovascular disease mortality among women and men with and without diabetes mellitus in the Framingham Heart Study, 1950 to 2005. Circulation. 2009; 119:1728–1735.LinkGoogle Scholar
  • 13. Gholizadeh L, Davidson P. More similarities than differences: an international comparison of CVD mortality and risk factors in women. Health Care Women Int. 2008; 29:3–22.CrossrefMedlineGoogle Scholar
  • 14. Mosca L, Appel LJ, Benjamin EJ, Berra K, Chandra-Strobos N, Fabunmi RP, Grady D, Haan CK, Hayes SN, Judelson DR, Keenan NL, McBride P, Oparil S, Ouyang P, Oz MC, Mendelsohn ME, Pasternak RC, Pinn VW, Robertson RM, Schenck-Gustafsson K, Sila CA, Smith SC, Sopko G, Taylor AL, Walsh BW, Wenger NK, Williams CLAmerican Heart Association. Evidence-based guidelines for cardiovascular disease prevention in women. Circulation. 2004; 109:672–693.LinkGoogle Scholar
  • 15. Mosca L, Banka CL, Benjamin EJ, Berra K, Bushnell C, Dolor RJ, Ganiats TG, Gomes AS, Gornik HL, Gracia C, Gulati M, Haan CK, Judelson DR, Keenan N, Kelepouris E, Michos ED, Newby LK, Oparil S, Ouyang P, Oz MC, Petitti D, Pinn VW, Redberg RF, Scott R, Sherif K, Smith SC, Sopko G, Steinhorn RH, Stone NJ, Taubert KA, Todd BA, Urbina E, Wenger NKfor the Expert Panel/Writing Group including the American Heart Association; American Academy of Family Physicians; American College of Obstetricians and Gynecologists; American College of Cardiology Foundation; Society of Thoracic Surgeons; American Medical Women's Association; Centers for Disease Control and Prevention; Office of Research on Women's Health; Association of Black Cardiologists; American College of Physicians; World Heart Federation; National Heart, Lung, and Blood Institute; American College of Nurse Practitioners. Evidence-based guidelines for cardiovascular disease prevention in women: 2007 update [published correction appears in Circulation. 2007;115:e407]. Circulation. 2007; 115:1481–1501.LinkGoogle Scholar
  • 16. Mosca L. Aspirin chemoprevention: one size does not fit all. Circulation. 2008; 117:2844–2846.LinkGoogle Scholar
  • 17. Berger JS, Roncaglioni MC, Avanzini F, Pangrazzi I, Tognoni G, Brown DL. Aspirin for the primary prevention of cardiovascular events in women and men: a sex-specific meta-analysis of randomized controlled trials. JAMA. 2006; 295:306–313.CrossrefMedlineGoogle Scholar
  • 18. Lloyd-Jones DM, Leip EP, Larson MG, D'Agostino RB, Beiser A, Wilson PW, Wolf PA, Levy D. Prediction of lifetime risk for cardiovascular disease by risk factor burden at 50 years of age. Circulation. 2006; 113:791–798.LinkGoogle Scholar
  • 19. Lakoski SG, Greenland P, Wong ND, Schreiner PJ, Herrington DM, Kronmal RA, Liu K, Blumenthal RS. Coronary artery calcium scores and risk for cardiovascular events in women classified as “low risk” based on Framingham risk score: the Multi-Ethnic Study of Atherosclerosis (MESA). Arch Intern Med. 2007; 167:2437–2442.CrossrefMedlineGoogle Scholar
  • 20. National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation. 2002; 106:3143–3421.LinkGoogle Scholar
  • 21. Hsia J, Rodabough RJ, Manson JE, Liu S, Freiberg MS, Graettinger W, Rosal MC, Cochrane B, Lloyd-Jones D, Robinson JG, Howard BVWomen's Health Initiative Research Group. Evaluation of the American Heart Association cardiovascular disease prevention guideline for women. Circ Cardiovasc Qual Outcomes. 2010; 3:128–134.LinkGoogle Scholar
  • 22. Lloyd-Jones DM, Hong Y, Labarthe D, Mozaffarian D, Appel LJ, Van Horn L, Greenlund K, Daniels S, Nichol G, Tomaselli GF, Arnett DK, Fonarow GC, Ho PM, Lauer MS, Masoudi FA, Robertson RM, Roger V, Schwamm LH, Sorlie P, Yancy CW, Rosamond WDon behalf of the American Heart Association Strategic Planning Task Force and Statistics Committee. Defining and setting national goals for cardiovascular health promotion and disease reduction: the American Heart Association's Strategic Impact Goal through 2020 and beyond. Circulation. 2010; 121:586–613.LinkGoogle Scholar
  • 23. D'Agostino RB, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM, Kannel WB. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation. 2008; 117:743–753.LinkGoogle Scholar
  • 24. Ridker PM, Buring JE, Rifai N, Cook NR. Development and validation of improved algorithms for the assessment of global cardiovascular risk in women: the Reynolds Risk Score. JAMA. 2007; 297:611–619.CrossrefMedlineGoogle Scholar
  • 25. Assmann G, Cullen P, Schulte H. Simple scoring scheme for calculating the risk of acute coronary events based on the 10-year follow-up of the prospective cardiovascular Munster (PROCAM) study. Circulation. 2002; 105:310–315.LinkGoogle Scholar
  • 26. Conroy RM, Pyorala K, Fitzgerald AP, Sans S, Menotti A, De Backer G, De Bacquer D, Ducimetiere P, Jousilahti P, Keil U, Njolstad I, Oganov RG, Thomsen T, Tunstall-Pedoe H, Tverdal A, Wedel H, Whincup P, Wilhelmsen L, Graham IMScore Project Group. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J. 2003; 24:987–1003.CrossrefMedlineGoogle Scholar
  • 27. Hippisley-Cox J, Coupland C, Vinogradova Y, Robson J, May M, Brindle P. Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study. BMJ. 2007; 335:136.CrossrefMedlineGoogle Scholar
  • 28. Heart Protection Study Collaborative Group. Statin cost-effectiveness in the United States for people at different vascular risk levels. Circ Cardiovasc Qual Outcomes. 2009; 2:65–72.LinkGoogle Scholar
  • 29. Ridker PM, Danielson E, Fonseca FA, Genest J, Gotto AM, Kastelein JJ, Koenig W, Libby P, Lorenzatti AJ, MacFadyen JG, Nordestgaard BG, Shepherd J, Willerson JT, Glynn RJ. Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein. N Engl J Med. 2008; 359:2195–2207.CrossrefMedlineGoogle Scholar
  • 30. Ridker PM, Cook NR, Lee IM, Gordon D, Gaziano JM, Manson JE, Hennekens CH, Buring JE. A randomized trial of low-dose aspirin in the primary prevention of cardiovascular disease in women. N Engl J Med. 2005; 352:1293–1304.CrossrefMedlineGoogle Scholar
  • 31. Lloyd-Jones DM, Leip EP, Larson MG, Vasan RS, Levy D. Novel approach to examining first cardiovascular events after hypertension onset. Hypertension. 2005; 45:39–45.LinkGoogle Scholar
  • 32. Grundy SM, Cleeman JI, Merz CN, Brewer HB, Clark LT, Hunninghake DB, Pasternak RC, Smith SC, Stone NJ. Implications of recent clinical trials for the National Cholesterol Education Program Adult Treatment Panel III guidelines [published correction appears in Circulation. 2004;110:763]. Circulation. 2004; 110:227–239.LinkGoogle Scholar
  • 33. Cavanaugh-Hussey MW, Berry JD, Lloyd-Jones DM. Who exceeds ATP-III risk thresholds? Systematic examination of the effect of varying age and risk factor levels in the ATP-III risk assessment tool. Prev Med. 2008; 47:619–623.CrossrefMedlineGoogle Scholar
  • 34. Vasan RS, Sullivan LM, Wilson PW, Sempos CT, Sundstrom J, Kannel WB, Levy D, D'Agostino RB. Relative importance of borderline and elevated levels of coronary heart disease risk factors. Ann Intern Med. 2005; 142:393–402.CrossrefMedlineGoogle Scholar
  • 35. Marma AK, Lloyd-Jones DM. Systematic examination of the updated Framingham Heart Study general cardiovascular risk profile. Circulation. 2009; 120:384–390.LinkGoogle Scholar
  • 36. Pencina MJ, D'Agostino RB, Larson MG, Massaro JM, Vasan RS. Predicting the 30-year risk of cardiovascular disease: the Framingham Heart Study. Circulation. 2009; 119:3078–3084.LinkGoogle Scholar
  • 37. Marma AK, Berry JD, Ning H, Persell SD, Lloyd-Jones DM. Distribution of 10-year and lifetime predicted risks for cardiovascular disease in US adults: findings from the National Health and Nutrition Examination Survey 2003 to 2006. Circ Cardiovasc Qual Outcomes. 2010; 3:8–14.LinkGoogle Scholar
  • 38. Pearson TA, Mensah GA, Alexander RW, Anderson JL, Cannon RO, Criqui M, Fadl YY, Fortmann SP, Hong Y, Myers GL, Rifai N, Smith SC, Taubert K, Tracy RP, Vinicor FCenters for Disease Control and Prevention; American Heart Association. Markers of inflammation and cardiovascular disease: application to clinical and public health practice: a statement for healthcare professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation. 2003; 107:499–511.LinkGoogle Scholar
  • 39. Hlatky MA, Greenland P, Arnett DK, Ballantyne CM, Criqui MH, Elkind MS, Go AS, Harrell FE, Hong Y, Howard BV, Howard VJ, Hsue PY, Kramer CM, McConnell JP, Normand SL, O'Donnell CJ, Smith SC, Wilson PWAmerican Heart Association Expert Panel on Subclinical Atherosclerotic Diseases and Emerging Risk Factors and the Stroke Council. Criteria for evaluation of novel markers of cardiovascular risk: a scientific statement from the American Heart Association. Circulation. 2009; 119:2408–2416.LinkGoogle Scholar
  • 40. Greenland P, Bonow RO, Brundage BH, Budoff MJ, Eisenberg MJ, Grundy SM, Lauer MS, Post WS, Raggi P, Redberg RF, Rodgers GP, Shaw LJ, Taylor AJ, Weintraub WS, Harrington RA, Abrams J, Anderson JL, Bates ER, Grines CL, Hlatky MA, Lichtenberg RC, Lindner JR, Pohost GM, Schofield RS, Shubrooks SJ, Stein JH, Tracy CM, Vogel RA, Wesley DJAmerican College of Cardiology Foundation Clinical Expert Consensus Task Force (ACCF/AHA Writing Committee to Update the 2000 Expert Consensus Document on Electron Beam Computed Tomography); Society of Atherosclerosis Imaging and Prevention; Society of Cardiovascular Computed Tomography. ACCF/AHA 2007 clinical expert consensus document on coronary artery calcium scoring by computed tomography in global cardiovascular risk assessment and in evaluation of patients with chest pain: a report of the American College of Cardiology Foundation Clinical Expert Consensus Task Force (ACCF/AHA Writing Committee to Update the 2000 Expert Consensus Document on Electron Beam Computed Tomography). Circulation. 2007; 115:402–426.LinkGoogle Scholar
  • 41. Greenland P, Alpert JS, Beller GA, Benjamin EJ, Budoff MJ, Fayad ZA, Foster E, Hlatky MA, Hodgson JM, Kushner FG, Lauer MS, Shaw LJ, Smith SC, Taylor AJ, Weintraub WS, Wenger NK, Jacobs AK. 2010 ACCF/AHA guideline for assessment of cardiovascular risk in asymptomatic adults: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Circulation. 2010; 122:e584–e636.LinkGoogle Scholar
  • 42. Polonsky TS, McClelland RL, Jorgensen NW, Bild DE, Burke GL, Guerci AD, Greenland P. Coronary artery calcium score and risk classification for coronary heart disease prediction. JAMA. 2010; 303:1610–1616.CrossrefMedlineGoogle Scholar
  • 43. Nambi V, Chambless L, Folsom AR, He M, Hu Y, Mosley T, Volcik K, Boerwinkle E, Ballantyne CM. Carotid intima-media thickness and presence or absence of plaque improves prediction of coronary heart disease risk: the ARIC (Atherosclerosis Risk In Communities) study. J Am Coll Cardiol. 2010; 55:1600–160.CrossrefMedlineGoogle Scholar
  • 44. Wilson BJ, Watson MS, Prescott GJ, Sunderland S, Campbell DM, Hannaford P, Smith WC. Hypertensive diseases of pregnancy and risk of hypertension and stroke in later life: results from cohort study. BMJ. 2003; 326:845.CrossrefMedlineGoogle Scholar
  • 45. Ray JG, Vermeulen MJ, Schull MJ, Redelmeier DA. Cardiovascular Health After Maternal Placental Syndromes (CHAMPS): population-based retrospective cohort study. Lancet. 2005; 366:1797–1803.CrossrefMedlineGoogle Scholar
  • 46. Bellamy L, Casas JP, Hingorani AD, Williams DJ. Pre-eclampsia and risk of cardiovascular disease and cancer in later life: systematic review and meta-analysis. BMJ. 2007; 335:974.CrossrefMedlineGoogle Scholar
  • 47. Kaaja RJ, Greer IA. Manifestations of chronic disease during pregnancy. JAMA. 2005; 294:2751–2757.CrossrefMedlineGoogle Scholar
  • 48. Banerjee M, Cruickshank JK. Pregnancy as the prodrome to vascular dysfunction and cardiovascular risk. Nat Clin Pract Cardiovasc Med. 2006; 3:596–603.CrossrefMedlineGoogle Scholar
  • 49. Garovic VD, Hayman SR. Hypertension in pregnancy: an emerging risk factor for cardiovascular disease. Nat Clin Pract Nephrol. 2007; 3:613–622.CrossrefMedlineGoogle Scholar
  • 50. Sattar N. Do pregnancy complications and CVD share common antecedents?Atheroscler Suppl. 2004; 5:3–7.CrossrefMedlineGoogle Scholar
  • 51. Salmon JE, Roman MJ. Subclinical atherosclerosis in rheumatoid arthritis and systemic lupus erythematosus. Am J Med. 2008; 121(suppl 1):S3–S8.CrossrefMedlineGoogle Scholar
  • 52. Institute of Medicine. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Washington, DC: National Academies Press; 2002.Google Scholar
  • 53. Gornick ME. Disparities in Medicare services: potential causes, plausible explanations, and recommendations. Health Care Financ Rev. 2000; 21(4):23–43.MedlineGoogle Scholar
  • 54. Coleman-Miller B. A physician's perspective on minority health. Health Care Financ Rev. 2000; 21(4):45–56.MedlineGoogle Scholar
  • 55. Williams DR, Rucker TD. Understanding and addressing racial disparities in health care. Health Care Financ Rev. 2000; 21(4):75–90.MedlineGoogle Scholar
  • 56. Campinha-Bacote J. The process of cultural competence in the delivery of healthcare services: a model of care. J Transcult Nurs. 2002; 13:181–184;discussion 200–201.CrossrefMedlineGoogle Scholar
  • 57. Institute of Medicine CoQHCiA. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: National Academy Press; 2001.Google Scholar
  • 58. Institute of Medicine CoUaERaEDiHC. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Washington, DC: National Academy Press; 2003.Google Scholar
  • 59. Beach MC, Cooper LA, Robinson KA, et al.Johns Hopkins University Evidence-Based Practice Center. Strategies for Improving Minority Healthcare Quality: Final Report. Rockville, MD: US Agency for Healthcare Research and Quality; 2004. Report No. 04-E008-02. Contract No. 290-02-0018.Google Scholar
  • 60. Gallo LC, Penedo FJ, Espinosa de los Monteros K, Arguelles W. Resiliency in the face of disadvantage: do Hispanic cultural characteristics protect health outcomes?J Pers. 2009; 77:1707–1746.CrossrefMedlineGoogle Scholar
  • 61. Markides KS, Eschbach K. Aging, migration, and mortality: current status of research on the Hispanic paradox. J Gerontol B Psychol Sci Soc Sci. 2005; 60(spec No. 2):68–75.CrossrefMedlineGoogle Scholar
  • 62. Heron M. Deaths: Leading Causes for 2006. Hyattsville, MD: National Center for Health Statistics; 2010.Google Scholar
  • 63. Arias E. United States Life Tables by Hispanic Origin. Washington, DC: National Center for Health Statistics; 2010.Google Scholar
  • 64. Betancourt GA, Carrillo JE. Cultural competence in health care: emerging frameworks and practical approaches. The Commonwealth Fund. October2002.Google Scholar
  • 65. Saha S, Beach MC, Cooper LA. Patient centeredness, cultural competence and healthcare quality. J Natl Med Assoc. 2008; 100:1275–1285.CrossrefMedlineGoogle Scholar
  • 66. Davis AM, Vinci LM, Okwuosa TM, Chase AR, Huang ES. Cardiovascular health disparities: a systematic review of health care interventions. Med Care Res Rev. 2007; 64(suppl):29S–100S.CrossrefMedlineGoogle Scholar
  • 67. Lopez AD, Mathers CD, Ezzati M, Jamison DT, CJL. M. Global Burden of Disease and Risk Factors. Oxford, UK: Oxford University Press and World Bank; 2006.CrossrefGoogle Scholar
  • 68. Global Program on Evidence for Health Policy. Guidelines for WHO Guidelines. EPI/GPE/EQC/2003.I. Geneva, Switzerland: World Health Organization; 2003.Google Scholar
  • 69. AGREE Collaboration. Development and validation of an international appraisal instrument for assessing the quality of clinical practice guidelines: the AGREE project. Qual Saf Health Care. 2003; 12:18–23.CrossrefMedlineGoogle Scholar
  • 70. SIG Network. SIGN Guideline Development Handbook: SIGN 50. 2010.Google Scholar
  • 71. Shiffman RN, Shekelle P, Overhage JM, Slutsky J, Grimshaw J, Deshpande AM. Standardized reporting of clinical practice guidelines: a proposal from the Conference on Guideline Standardization. Ann Intern Med. 2003; 139:493–498.CrossrefMedlineGoogle Scholar
  • 72. Schunemann HJ, Fretheim A, Oxman AD. Improving the use of research evidence in guideline development, 13: applicability, transferability and adaptation. Health Res Policy Syst. 2006; 4:25.CrossrefMedlineGoogle Scholar
  • 73. National Institute for Health and Clinical Excellence. Putting guidance into practice. Accessed October 16, 2010.Google Scholar
  • 74. Guidelines International Network. International guideline library. Accessed October 16, 2010.Google Scholar
  • 75. Edejer TT. Improving the use of research evidence in guideline development, 11: incorporating considerations of cost-effectiveness, affordability and resource implications. Health Res Policy Syst. 2006; 4:23.CrossrefMedlineGoogle Scholar
  • 76. Egan BM, Zhao Y, Axon RN. US trends in prevalence, awareness, treatment, and control of hypertension, 1988–2008. JAMA. 2010; 303:2043–2050.CrossrefMedlineGoogle Scholar
  • 77. Hyre AD, Muntner P, Menke A, Raggi P, He J. Trends in ATP-III-defined high blood cholesterol prevalence, awareness, treatment and control among U.S. adults. Ann Epidemiol. 2007; 17:548–555.CrossrefMedlineGoogle Scholar
  • 78. Ong KL, Cheung BM, Wong LY, Wat NM, Tan KC, Lam KS. Prevalence, treatment, and control of diagnosed diabetes in the U.S. National Health and Nutrition Examination Survey 1999–2004. Ann Epidemiol. 2008; 18:222–229.CrossrefMedlineGoogle Scholar
  • 79. Cabana MD, Rand CS, Powe NR, Wu AW, Wilson MH, Abboud PA, Rubin HR. Why don't physicians follow clinical practice guidelines? A framework for improvement. JAMA. 1999; 282:1458–1465.CrossrefMedlineGoogle Scholar
  • 80. Cabana MD, Kim C. Physician adherence to preventive cardiology guidelines for women. Womens Health Issues. 2003; 13:142–149.CrossrefMedlineGoogle Scholar
  • 81. DiMatteo MR. Variations in patients' adherence to medical recommendations: a quantitative review of 50 years of research. Med Care. 2004; 42:200–209.CrossrefMedlineGoogle Scholar
  • 82. Doroodchi H, Abdolrasulnia M, Foster JA, Foster E, Turakhia MP, Skelding KA, Sagar K, Casebeer LL. Knowledge and attitudes of primary care physicians in the management of patients at risk for cardiovascular events. BMC Fam Pract. 2008; 9:42.CrossrefMedlineGoogle Scholar
  • 83. Barnhart J, Lewis V, Houghton JL, Charney P. Physician knowledge levels and barriers to coronary risk prevention in women: survey results from the Women and Heart Disease Physician Education Initiative. Womens Health Issues. 2007; 17:93–100.CrossrefMedlineGoogle Scholar
  • 84. Francke AL, Smit MC, de Veer AJ, Mistiaen P. Factors influencing the implementation of clinical guidelines for health care professionals: a systematic meta-review. BMC Med Inform Decis Mak. 2008; 8:38.CrossrefMedlineGoogle Scholar
  • 85. Prior M, Guerin M, Grimmer-Somers K. The effectiveness of clinical guideline implementation strategies: a synthesis of systematic review findings. J Eval Clin Pract. 2008; 14:888–897.CrossrefMedlineGoogle Scholar
  • 86. Redberg RF, Benjamin EJ, Bittner V, Braun LT, Goff DC, Havas S, Labarthe DR, Limacher MC, Lloyd-Jones DM, Mora S, Pearson TA, Radford MJ, Smetana GW, Spertus JA, Swegler EWAmerican Academy of Family Physicians; American Association of Cardiovascular and Pulmonary Rehabilitation; Preventive Cardiovascular Nurses Association. AHA/ACCF [corrected] 2009 performance measures for primary prevention of cardiovascular disease in adults: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Performance Measures (Writing Committee to Develop Performance Measures for Primary Prevention of Cardiovascular Disease): developed in collaboration with the American Academy of Family Physicians; American Association of Cardiovascular and Pulmonary Rehabilitation; and Preventive Cardiovascular Nurses Association [published correction appears in Circulation. 2010;121:e445–e446]. Circulation. 2009; 120:1296–1336.MedlineGoogle Scholar
  • 87. Petersen LA, Woodard LD, Urech T, Daw C, Sookanan S. Does pay-for-performance improve the quality of health care?Ann Intern Med. 2006; 145:265–272.CrossrefMedlineGoogle Scholar
  • 88. Cohen MG, Fonarow GC, Peterson ED, Moscucci M, Dai D, Hernandez AF, Bonow RO, Smith SC. Racial and ethnic differences in the treatment of acute myocardial infarction: findings from the Get With the Guidelines–Coronary Artery Disease program. Circulation. 2010; 121:2294–2301.LinkGoogle Scholar
  • 89. Lewis WR, Ellrodt AG, Peterson E, Hernandez AF, LaBresh KA, Cannon CP, Pan W, Fonarow GC. Trends in the use of evidence-based treatments for coronary artery disease among women and the elderly: findings from the get With the Guidelines Quality-Improvement Program. Circ Cardiovasc Qual Outcomes. 2009; 2:633–641.LinkGoogle Scholar
  • 90. Clark CE, Smith LF, Taylor RS, Campbell JL. Nurse led interventions to improve control of blood pressure in people with hypertension: systematic review and meta-analysis. BMJ. 2010; 341:c3995.CrossrefMedlineGoogle Scholar
  • 91. Miller RR, Sales AE, Kopjar B, Fihn SD, Bryson CL. Adherence to heart-healthy behaviors in a sample of the U.S. population. Prev Chronic Dis. 2005; 2:A18.MedlineGoogle Scholar
  • 92. Pham HH, Schrag D, O'Malley AS, Wu B, Bach PB. Care patterns in Medicare and their implications for pay for performance. N Engl J Med. 2007; 356:1130–1139.CrossrefMedlineGoogle Scholar
  • 93. Bodenheimer T. Coordinating care: a perilous journey through the health care system. N Engl J Med. 2008; 358:1064–1071.CrossrefMedlineGoogle Scholar
  • 94. Jackevicius CA, Mamdani M, Tu JV. Adherence with statin therapy in elderly patients with and without acute coronary syndromes. JAMA. 2002; 288:462–467.CrossrefMedlineGoogle Scholar
  • 95. Cramer J, Rosenheck R, Kirk G, Krol W, Krystal JVA Naltrexone Study Group 425. Medication compliance feedback and monitoring in a clinical trial: predictors and outcomes. Value Health. 2003; 6:566–573.CrossrefMedlineGoogle Scholar
  • 96. Joint Commission. The Joint Commission announces the 2008 National Patient Safety Goals and Requirements. Jt Comm Perspect. 2007; 27:1,9–22.Google Scholar
  • 97. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL, Jones DW, Materson BJ, Oparil S, Wright JT, Roccella EJJoint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. National Heart, Lung, and Blood Institute; National High Blood Pressure Education Program Coordinating Committee. Seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. Hypertension. 2003; 42:1206–1252.LinkGoogle Scholar
  • 98. Kok G, van den Borne B, Mullen PD. Effectiveness of health education and health promotion: meta-analyses of effect studies and determinants of effectiveness. Patient Educ Couns. 1997; 30:19–27.CrossrefMedlineGoogle Scholar
  • 99. Bandura A, D C. Self-evaluative and self-efficacy mechanisms governing the motivational effects of goal systems. J Pers Soc Psych. 1983; 45:1017–1028.CrossrefGoogle Scholar
  • 100. Miller WSR. Motivational Interviewing: Preparing People for Change. 2nd ed.New York, NY: Guilford; 2002.Google Scholar
  • 101. Prochaska J, Norcross JCD. Changing for Good: A Revolutionary Six Stage Program for Overcoming Bad Habits and Moving Your Life Positively Forward. New York, NY: Avon Books, Inc; 1984.Google Scholar
  • 102. Bobrie G, Postel-Vinay N, Delonca J, Corvol PSETHI Investigators. Self-measurement and self-titration in hypertension: a pilot telemedicine study. Am J Hypertens. 2007; 20:1314–1320.CrossrefMedlineGoogle Scholar
  • 103. Pickering TG, Miller NH, Ogedegbe G, Krakoff LR, Artinian NT, Goff DAmerican Heart Association; American Society of Hypertension; Preventive Cardiovascular Nurses Association. Call to action on use and reimbursement for home blood pressure monitoring: a joint scientific statement from the American Heart Association, American Society of Hypertension, and Preventive Cardiovascular Nurses Association. Hypertension. 2008; 52:10–29.LinkGoogle Scholar
  • 104. Artinian NT, Fletcher GF, Mozaffarian D, Kris-Etherton P, Van Horn L, Lichtenstein AH, Kumanyika S, Kraus WE, Fleg JL, Redeker NS, Meininger JC, Banks J, Stuart-Shor EM, Fletcher BJ, Miller TD, Hughes S, Braun LT, Kopin LA, Berra K, Hayman LL, Ewing LJ, Ades PA, Durstine JL, Houston-Miller N, Burke LEAmerican Heart Association Prevention Committee of the Council on Cardiovascular Nursing. Interventions to promote physical activity and dietary lifestyle changes for cardiovascular risk factor reduction in adults: a scientific statement from the American Heart Association. Circulation. 2010; 122:406–441.LinkGoogle Scholar
  • 105. Lorig KR, Ritter PL, Dost A, Plant K, Laurent DD, McNeil I. The Expert Patients Programme online, a 1-year study of an Internet-based self-management programme for people with long-term conditions. Chronic Illn. 2008; 4:247–256.CrossrefMedlineGoogle Scholar
  • 106. Riegel B, Moser DK, Anker SD, Appel LJ, Dunbar SB, Grady KL, Gurvitz MZ, Havranek EP, Lee CS, Lindenfeld J, Peterson PN, Pressler SJ, Schocken DD, Whellan DJon behalf of the American Heart Association Council on Cardiovascular Nursing; Council on Cardiovascular Nursing; Council on Clinical Cardiology; Council on Nutrition, Physical Activity, and Metabolism; and Interdisciplinary Council on Quality of Care and Outcomes Research. State of the science: promoting self-care in persons with heart failure: a scientific statement from the American Heart Association. Circulation. 2009; 120:1141–1163.LinkGoogle Scholar
  • 107. Mosca L, Mochari H, Christian A, Berra K, Taubert K, Mills T, Burdick KA, Simpson SL. National study of women's awareness, preventive action, and barriers to cardiovascular health. Circulation. 2006; 113:525–534.LinkGoogle Scholar
  • 108. Quist-Paulsen P, Lydersen S, Bakke PS, Gallefoss F. Cost effectiveness of a smoking cessation program in patients admitted for coronary heart disease. Eur J Cardiovasc Prev Rehabil. 2006; 13:274–280.CrossrefMedlineGoogle Scholar
  • 109. Franzosi MG, Brunetti M, Marchioli R, Marfisi RM, Tognoni G, Valagussa FGISSI-Prevenzione Investigators. Cost-effectiveness analysis of n-3 polyunsaturated fatty acids (PUFA) after myocardial infarction: results from Gruppo Italiano per lo Studio della Sopravvivenza nell'Infarto (GISSI)-Prevenzione Trial. Pharmacoeconomics. 2001; 19:411–420.CrossrefMedlineGoogle Scholar
  • 110. Lindgren P, Buxton M, Kahan T, Poulter NR, Dahlof B, Sever PS, Wedel H, Jonsson B: ASCOT Trial Investigators. Economic evaluation of ASCOT-BPLA: antihypertensive treatment with an amlodipine-based regimen is cost effective compared with an atenolol-based regimen. Heart. 2008; 94:e4.CrossrefMedlineGoogle Scholar
  • 111. Heidenreich PA, Davis BR, Cutler JA, Furberg CD, Lairson DR, Shlipak MG, Pressel SL, Nwachuku C, Goldman L. Cost-effectiveness of chlorthalidone, amlodipine, and lisinopril as first-step treatment for patients with hypertension: an analysis of the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). J Gen Intern Med. 2008; 23:509–516.CrossrefMedlineGoogle Scholar
  • 112. Jonsson B, Buxton M, Hertzman P, Kahan T, Poulter NAnglo-Scandinavian Cardiac Outcomes Trial, Health Economics Working Group. Health economics of prevention of coronary heart disease and vascular events: a cost-effectiveness analysis based on the Anglo-Scandinavian Cardiac Outcomes Trial (ASCOT). J Hum Hypertens. 2001; 15(suppl 1):S53–S56.CrossrefMedlineGoogle Scholar
  • 113. Oostenbrink JB, Tangelder MJ, Busschbach JJ, van Hout BA, Buskens E, Algra A, Lawson JA, Eikelboom BCDutch Bypass Oral Anticoagulants or Aspirin (BOA) Study Group. Cost-effectiveness of oral anticoagulants versus aspirin in patients after infrainguinal bypass grafting surgery. J Vasc Surg. 2001; 34:254–262.CrossrefMedlineGoogle Scholar
  • 114. Darba J, Izquierdo I, Pontes C, Navas C, Rovira J. Economic evaluation of triflusal and aspirin in the treatment of acute myocardial infarction. Pharmacoeconomics. 2002; 20:195–201.CrossrefMedlineGoogle Scholar
  • 115. Graves N, Barnett AG, Halton KA, Veerman JL, Winkler E, Owen N, Reeves MM, Marshall A, Eakin E. Cost-effectiveness of a telephone-delivered intervention for physical activity and diet. PLoS One. 2009; 4:e7135.CrossrefMedlineGoogle Scholar
  • 116. Delahanty LM, Sonnenberg LM, Hayden D, Nathan DM. Clinical and cost outcomes of medical nutrition therapy for hypercholesterolemia: a controlled trial. J Am Diet Assoc. 2001; 101:1012–1023.CrossrefMedlineGoogle Scholar
  • 117. Masley S, Phillips S, Copeland JR. Group office visits change dietary habits of patients with coronary artery disease: the Dietary Intervention and Evaluation Trial (D.I.E.T.). J Fam Pract. 2001; 50:235–239.MedlineGoogle Scholar
  • 118. Cox RH, White AH, Gaylord CK. A video lesson series is effective in changing the dietary intakes and food-related behaviors of low-income homemakers. J Am Diet Assoc. 2003; 103:1488–1493.CrossrefMedlineGoogle Scholar
  • 119. Befort CA, Donnelly JE, Sullivan DK, Ellerbeck EF, Perri MG. Group versus individual phone-based obesity treatment for rural women. Eat Behav. 2010; 11:11–17.CrossrefMedlineGoogle Scholar
  • 120. Sherwood NE, Jeffery RW, Pronk NP, Boucher JL, Hanson A, Boyle R, Brelje K, Hase K, Chen V. Mail and phone interventions for weight loss in a managed-care setting: weigh-to-be 2-year outcomes. Int J Obes (Lond). 2006; 30:1565–1573.CrossrefMedlineGoogle Scholar
  • 121. Southard BH, Southard DR, Nuckolls J. Clinical trial of an Internet-based case management system for secondary prevention of heart disease. J Cardiopulm Rehabil. 2003; 23:341–348.CrossrefMedlineGoogle Scholar
  • 122. Wheeler JR, Janz NK, Dodge JA. Can a disease self-management program reduce health care costs? The case of older women with heart disease. Med Care. 2003; 41:706–715.CrossrefMedlineGoogle Scholar
  • 123. Malone DC, Raebel MA, Porter JA, Lanty FA, Conner DA, Gay EC, Merenich JA, Vogel EA. Cost-effectiveness of sibutramine in the LOSE Weight Study: evaluating the role of pharmacologic weight-loss therapy within a weight management program. J Manag Care Pharm. 2005; 11:458–468.CrossrefMedlineGoogle Scholar
  • 124. Lapuerta P, Simon T, Smitten A, Caro JCHOICE Study Group; Caring for Hypertension on Initiation: Costs and Effectiveness. Assessment of the association between blood pressure control and health care resource use. Clin Ther. 2001; 23:1773–1782.CrossrefMedlineGoogle Scholar
  • 125. Boersma C, Carides GW, Atthobari J, Voors AA, Postma MJ. An economic assessment of losartan-based versus atenolol-based therapy in patients with hypertension and left-ventricular hypertrophy: results from the Losartan Intervention For Endpoint reduction (LIFE) study adapted to The Netherlands. Clin Ther. 2007; 29:963–971.CrossrefMedlineGoogle Scholar
  • 126. Bolin K, Lindgren B, Willers S. The cost utility of bupropion in smoking cessation health programs: simulation model results for Sweden. Chest. 2006; 129:651–660.CrossrefMedlineGoogle Scholar
  • 127. Hurley SF, Matthews JP. The Quit Benefits Model: a Markov model for assessing the health benefits and health care cost savings of quitting smoking. Cost Eff Resour Alloc. 2007; 5:2.CrossrefMedlineGoogle Scholar
  • 128. Johansson PM, Tillgren PE, Guldbrandsson KA, Lindholm LA. A model for cost-effectiveness analyses of smoking cessation interventions applied to a Quit-and-Win contest for mothers of small children. Scand J Public Health. 2005; 33:343–352.CrossrefMedlineGoogle Scholar
  • 129. Pradelli L, Iannazzo S, Zaniolo O. The cost effectiveness and cost utility of valsartan in chronic heart failure therapy in Italy: a probabilistic Markov model. Am J Cardiovasc Drugs. 2009; 9:383–392.CrossrefMedlineGoogle Scholar
  • 130. Ekman M, Bienfait-Beuzon C, Jackson J. Cost-effectiveness of irbesartan/hydrochlorothiazide in patients with hypertension: an economic evaluation for Sweden. J Hum Hypertens. 2008; 22:845–855.CrossrefMedlineGoogle Scholar
  • 131. Zethraeus N, Strom O, Borgstrom F, Kanis JA, Jonsson B. The cost-effectiveness of the treatment of high risk women with osteoporosis, hypertension and hyperlipidaemia in Sweden. Osteoporos Int. 2008; 19:819–827.CrossrefMedlineGoogle Scholar
  • 132. Montgomery AA, Fahey T, Ben-Shlomo Y, Harding J. The influence of absolute cardiovascular risk, patient utilities, and costs on the decision to treat hypertension: a Markov decision analysis. J Hypertens. 2003; 21:1753–1759.CrossrefMedlineGoogle Scholar
  • 133. Greving JP, Buskens E, Koffijberg H, Algra A. Cost-effectiveness of aspirin treatment in the primary prevention of cardiovascular disease events in subgroups based on age, gender, and varying cardiovascular risk. Circulation. 2008; 117:2875–2883.LinkGoogle Scholar
  • 134. Pignone M, Earnshaw S, Pletcher MJ, Tice JA. Aspirin for the primary prevention of cardiovascular disease in women: a cost-utility analysis. Arch Intern Med. 2007; 167:290–295.CrossrefMedlineGoogle Scholar
  • 135. Jensen C, Flum DR2004 ABS Consensus Conference. The costs of nonsurgical and surgical weight loss interventions: is an ounce of prevention really worth a pound of cure?Surg Obes Relat Dis. 2005; 1:353–357.CrossrefMedlineGoogle Scholar
  • 136. Salem L, Devlin A, Sullivan SD, Flum DR. Cost-effectiveness analysis of laparoscopic gastric bypass, adjustable gastric banding, and nonoperative weight loss interventions. Surg Obes Relat Dis. 2008; 4:26–32.CrossrefMedlineGoogle Scholar
  • 137. Craig BM, Tseng DS. Cost-effectiveness of gastric bypass for severe obesity. Am J Med. 2002; 113:491–498.CrossrefMedlineGoogle Scholar
  • 138. Picot J, Jones J, Colquitt JL, Gospodarevskaya E, Loveman E, Baxter L, Clegg AJ. The clinical effectiveness and cost-effectiveness of bariatric (weight loss) surgery for obesity: a systematic review and economic evaluation. Health Technol Assess. 2009; 13:1–190,215–357, iii–iv.CrossrefGoogle Scholar
  • 139. Adler NE, Adashi EY, Aguilar-Gaxiola S, Amaro H, Anthony M, Brown DR, Col N, Cu-Uvin S, Faustman DL, Finnegan JR, Hazzard WR, Hefner JE, Miranda J, Mosca L, Peterson H, Pisano ED, Salganicoff A, Snetselaar LGInstitute of Medicine's (IOM) Committee on Women's Health Research. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: National Academies Press; 2010.Google Scholar
  • Deleted in proof.Google Scholar
  • 141. Lichtenstein AH, Appel LJ, Brands M, Carnethon M, Daniels S, Franch HA, Franklin B, Kris-Etherton P, Harris WS, Howard B, Karanja N, Lefevre M, Rudel L, Sacks F, Van Horn L, Winston M, Wylie-Rosett J. Diet and lifestyle recommendations revision 2006: a scientific statement from the American Heart Association Nutrition Committee. Circulation. 2006; 114:82–96.LinkGoogle Scholar
  • 142. Institute of Medicine. Dietary Reference Intakes for Calcium and Vitamin D. Washington, DC: National Academies Press; 2011.Google Scholar