Background—Although the inverse association between high-density lipoprotein cholesterol (HDL-C) and risk of cardiovascular disease (CVD) has been long established, it remains unclear whether low HDL-C remains a CVD risk factor when levels of low-density lipoprotein cholesterol (LDL-C) and triglycerides (TG) are not elevated. This is a timely issue because recent studies have questioned whether HDL-C is truly an independent predictor of CVD. Methods and Results—3590 men and women from the Framingham Heart Study offspring cohort without known CVD were followed between 1987 and 2011. Low HDL-C (<40 mg/dL in men and <50 mg/dL in women) was defined as isolated if TG and LDL-C were both low (<100 mg/dL). We also examined higher thresholds for TG (150 mg/dL) and LDL-C (130 mg/dL) and compared low versus high HDL-C phenotypes using logistic regression analysis to assess association with CVD. Compared with isolated low HDL-C, CVD risks were higher when low HDL-C was accompanied by LDL-C ≥100 mg/dL and TG <100 mg/dL (odds ratio 1.3 [1.0, 1.6]), TG ≥100 mg/dL and LDL-C <100 mg/dL (odds ratio 1.3 [1.1, 1.5]), or TG and LDL-C ≥100 mg/dL (odds ratio 1.6, [1.2, 2.2]), after adjustment for covariates. When low HDL-C was analyzed with higher thresholds for TG (≥150 mg/dL) and LDL-C (≥130 mg/dL), results were essentially the same. In contrast, compared with isolated low HDL-C, high HDL-C was associated with 20% to 40% lower CVD risk except when TG and LDL-C were elevated. Conclusions—CVD risk as a function of HDL-C phenotypes is modulated by other components of the lipid panel.

BACKGROUND:Cardiovascular diseases are the leading cause of preventable morbidity and mortality in the USA. Medical schools must prepare trainees to address prevention, including improving ability in counseling patients to modify lifestyle risk factors. Most medical students do not receive significant training or clinical experience in preventive medicine until the clinical years of medical school. To enhance student education in disease prevention and lifestyle counseling, and simultaneously target cardiovascular disease prevention in high-risk Chicago neighborhoods, the Northwestern University Feinberg School of Medicine and Chicago Department of Public Health with support from the GE Foundation, developed the Keep Your Heart Healthy program.METHODS:Medical students participated in intensive faculty-led training. They subsequently screened local residents to identify and counsel for cardiovascular disease risk factors. Fifty-one predominantly preclinical medical students screened residents of the Humboldt Park and North Lawndale neighborhoods in Chicago, IL, at 31 screening events from August to December 2013. Fifty students (98% response rate) completed a survey assessing the educational value of various program components following the pilot.RESULTS:Of all respondents, 92% of students reported improved knowledge of cardiovascular disease prevention and 94% reported improved knowledge of vulnerable populations and health equity. The majority (88%) reported that their participation supplemented material they learned in the classroom. Eighty-six percent of students reported that their encounters with community participants were of educational value. Integration of this program into the medical school curriculum was supported by 68% of students.CONCLUSION:Keep Your Heart Healthy educates primarily preclinical medical students in cardiovascular disease prevention and prepares them to apply this knowledge for patient counseling. Results from student surveys demonstrate that this service-learning initiative enhances medical student knowledge in cardiovascular disease prevention, supplements classroom material, and provides students a valuable opportunity to apply interviewing and counseling skills in a real patient encounter.

Introduction: AHA’s Life’s Simple 7 (LS7) is an easy guide toward achieving ideal cardiovascular health. However, few large-scale projects have assessed whether the AHA LS7 can have a significant i...

This study examined self-reported staging for the goal of eating a low-fat diet and several specific dietary consumption behaviors to understand better readiness for dieting. Self-assessed motivation, food frequency measures, and psychosocial variables were obtained from 2057 low-income women enrolled in the Maryland Food for Life Program. Results indicated that staging of specific dietary consumption behaviors was significantly related to staging for the global goal of eating a low-fat diet. Women evaluate their motivation about eating low-fat diets based on perceived efforts and specific activities related to dietary consumption with important implications for dietary behavior change measurement and interventions.

Low levels of HDL-C are inversely correlated with risk of coronary heart disease (CHD). However, the association between low HDL-C and CHD risk in subjects with normal TG and LDL-C levels has not been well studied. We hypothesized that low HDL-C raises CHD risk in subjects with elevated levels of TG

Background: Cardiovascular diseases (CVD) are largely preventable yet remain leading causes of morbidity and mortality in Chicago, especially in minority neighborhoods. Hypothesis: Medical schools can engage students to conduct community CVD screening and consultation to reduce risks in low income Chicago communities with high CVD mortality rates. Objectives: Keep Your Heart Healthy (KYHH) initiative is a collaboration of the Feinberg School of Medicine, Chicago Department of Public Health, and community partners. The KYHH pilot aims to engage medical students to determine current CVD risks through screening and consultation in primarily Hispanic (Humboldt Park) and African American (North Lawndale) Chicago communities. We report on the pilot: August 1, 2013 to date. Methods: A total of 54 medical students volunteered, including 26% of the first-year class. A convenience sample of adults was recruited by community health workers. Medical student volunteers, trained by Feinberg faculty, conducted interviews to assess CVD risk by participant self report, measured body weight and blood pressure, and provided brief, personalized counseling based on the American Heart Association’s “Life’s Simple 7.” Participants with blood pressure ≥ 140/90 were referred to their primary care providers or a Federally Qualified Health Center. Randomly selected participants provided post-event survey feedback. Results: At 17 events, students (mean = 8) screened 650 participants in Humboldt Park (further data n=329 at time of submission) and 119 participants in North Lawndale. Demographics (Humboldt Park vs North Lawndale) were as follows: race/ethnicity (82% Latino vs 94% African American); age (63% vs 54% 40-65 years old); gender (62% vs 75% women). Self-reported CVD risk factors included cigarette smoking (31% vs 21%), diabetes (33% vs 17%), hypertension (47% vs 34%), and prior heart attack (8% vs 7%) or stroke (5% vs 1%). Obesity (42% vs 57%) and uncontrolled hypertension (20% vs 23%) rates were high. Humboldt Park and North Lawndale participants rarely (19% vs 15%) or sometimes (41% vs 43%) ate fruit/vegetables, and sometimes (42% vs 50%) or often (20% vs 22%) ate high-salt foods. Participants often lacked insurance or a usual source of care (32% vs 34%). The most common participant-identified goals were achieving a healthier body weight (51% vs 42%) or diet (41% vs 34%). Of 131 participants who provided post-event feedback, 95% indicated they learned something new about their heart health, 92% made goals to improve it, 99% indicated they understood their own personal risks, and 99% indicated they would recommend the screening to others. Conclusion: CVD risk factor burden is high in low income Chicago communities. KYHH is a model for engaging medical students to advance community health by conducting personalized screening and consultation. Early efforts have been well received by community residents.

IMPORTANCE Excess consumption of sodium is an important cause of hypertension, a major risk factor for heart disease and stroke.The higher the level of consumption, the greater is a person's likelihood of developing hypertension.Numerous organizations have recommended reductions in sodium intake in the United States.Roughly 80% of the sodium consumed by Americans has been added by food manufacturers and restaurants.OBJECTIVE To compare the mean (SD) levels of sodium for identical products ascertained in 2005, 2008, and 2011.DESIGN AND SETTING Comparison study in an academic research setting.PARTICIPANTS AND EXPOSURES Center for Science in the Public Interest staff have monitored sodium levels in selected processed foods and fast-food restaurant foods for many years.MAIN OUTCOMES AND MEASURES The sodium content in identical foods, as measured in 2005, 2008, and 2011.RESULTS Between 2005 and 2011, the sodium content in 402 processed foods declined by approximately 3.5%, while the sodium content in 78 fast-food restaurant products increased by 2.6%.Although some products showed decreases of at least 30%, a greater number of products showed increases of at least 30%.The predominant finding is the absence of any appreciable or statistically significant changes in sodium content during 6 years.CONCLUSIONS AND RELEVANCE Based on our sample, reductions in sodium levels in processed and restaurant foods are inconsistent and slow.These findings are in accord with other data indicating the slow pace of voluntary reductions in sodium levels in processed and restaurant foods.Stronger action (eg, phased-in limits on sodium levels set by the federal government) is needed to lower sodium levels and reduce the prevalence of hypertension and cardiovascular diseases.

HomeCirculationVol. 120, No. 13AHA/ACCF 2009 Performance Measures for Primary Prevention of Cardiovascular Disease in Adults Free AccessReview ArticlePDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessReview ArticlePDF/EPUBAHA/ACCF 2009 Performance Measures for Primary Prevention of Cardiovascular Disease in AdultsA 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 WRITING COMMITTEE MEMBERS Rita F. Redberg, Emelia J. Benjamin, Vera Bittner, Lynne T. Braun, David C. GoffJr, Stephen Havas, Darwin R. Labarthe, Marian C. Limacher, Donald M. Lloyd-Jones, Samia Mora, Thomas A. Pearson, Martha J. Radford, Gerald W. Smetana, John A. Spertus and Erica W. Swegler WRITING COMMITTEE MEMBERS , Rita F. RedbergRita F. Redberg , Emelia J. BenjaminEmelia J. Benjamin , Vera BittnerVera Bittner , Lynne T. BraunLynne T. Braun , David C. GoffJrDavid C. GoffJr , Stephen HavasStephen Havas , Darwin R. LabartheDarwin R. Labarthe , Marian C. LimacherMarian C. Limacher , Donald M. Lloyd-JonesDonald M. Lloyd-Jones , Samia MoraSamia Mora , Thomas A. PearsonThomas A. Pearson , Martha J. RadfordMartha J. Radford , Gerald W. SmetanaGerald W. Smetana , John A. SpertusJohn A. Spertus and Erica W. SweglerErica W. Swegler Originally published21 Sep 2009https://doi.org/10.1161/CIRCULATIONAHA.109.192617Circulation. 2009;120:1296–1336is corrected byCorrectionOther version(s) of this articleYou are viewing the most recent version of this article. Previous versions: September 21, 2009: Previous Version 1 Preamble…12971. Introduction…1299 1.1. Scope of the Problem…1300 1.2. Structure and Membership of the Writing Committee…1300 1.3. Disclosure of Relationships With Industry…1300 1.4. Review and Endorsement…13002. Methodology…1300 2.1. Target Population and Care Period…1300 2.2. Dimensions of Care…1301 2.3. Literature Review…1301 2.4. Definition of Potential Measures…1301 2.5. Selection of Measures for Inclusion in the Performance Measure Set…13023. Primary Prevention of CVD Performance Measures…1303 3.1. Definition of Primary Prevention…1303 3.2. Brief Summary of the Measurement Set…1303 3.3. Data Collection…1303 3.4. Exclusion Criteria and Challenges to Implementation…13034. Discussion…1304 4.1. Sex…1304 4.2. Frequency of Screening…1304 4.3. Risk Screening…1304 4.4. Lifestyle Counseling…1304 4.5. Weight Management…1305 4.6. Hypertension…1305 4.7. Lipid Screening and Control…1306 4.8. Global Risk Estimation…1306 4.9. Stroke Risk Assessment…1306 4.10. Aspirin Use…1307 4.11. Diabetes Mellitus…1307 4.12. Dietary Supplementation…13075. Conclusions…1307Appendix A. Author Relationships With Industry and Other Entities—AHA/ACCF 2009 Performance Measures for Primary Prevention of Cardiovascular Disease in Adults…1308Appendix B. Peer Reviewer Relationships With Industry and Other Entities— AHA/ACCF 2009 Performance Measures for Primary Prevention of Cardiovascular Disease in Adults…1309Appendix C. Sample Performance Measure Survey Form and Exclusion Criteria Definitions…1310Appendix D. AHA/ACCF 2009 Primary Prevention of Cardiovascular Disease Performance Measurement Set Specifications…1312Appendix E. Sample Prospective Data Collection Flow Sheet…1329Appendix F. Coronary Heart Disease Risk Prediction…1331Appendix G. Measuring Waist Circumference…1333Appendix H. Body Mass Index Table…1333References…1334PreambleOver the past decade, there has been an increasing awareness that the quality of medical care in the United States is highly variable. In its seminal document dedicated to characterizing deficiencies in delivering effective, timely, safe, equitable, efficient, and patient-centered medical care, the Institute of Medicine described a quality "chasm."1 Recognition of the magnitude of the gap between the care that is delivered and the care that ought to be provided has stimulated interest in the development of measures of quality of care and the use of such measures for the purposes of quality improvement and accountability.Consistent with this national focus on healthcare quality, the American College of Cardiology Foundation (ACCF) and the American Heart Association (AHA) have taken a leadership role in developing measures of the quality of care for cardiovascular disease (CVD) in several clinical areas (Table 1). The ACCF/AHA Task Force on Performance Measures was formed in February 2000 and was charged with identifying the clinical topics appropriate for the development of performance measures and assembling writing committees composed of clinical and methodological experts. When appropriate, these committees have included representation from other organizations involved in the care of patients with the condition of focus. The committees are informed about the methodology of performance measure development and are instructed to construct measures for use both prospectively and retrospectively, rely on easily documented clinical criteria, and, where appropriate, incorporate administrative data. The data elements required for the performance measures are linked to existing ACCF/AHA clinical data standards to encourage uniform measurements of cardiovascular care. The writing committees are also instructed to evaluate the extent to which existing nationally recognized performance measures conform to the attributes of performance measures described by the ACCF/AHA and to strive to create measures aligned with acceptable existing measures when this is feasible. Table 1. ACCF/AHA Performance Measurement SetsTopicOriginal Publication DatePartnering OrganizationsStatusACC indicates American College of Cardiology; ACCF, American College of Cardiology Foundation; AHA, American Heart Association; PCPI, American Medical Association–Physician Consortium for Performance Improvement; AACVPR, American Association of Cardiovascular and Pulmonary Rehabilitation; ACR, American College of Radiology; SCAI, Society for Cardiac Angiography and Interventions; SIR, Society for Interventional Radiology; SVM, Society for Vascular Medicine; SVN, Society for Vascular Nursing; and SVS, Society for Vascular Surgery.*Planned publication date.Chronic heart failure22005ACC/AHA—inpatient measuresCurrently undergoing updateACC/AHA/PCPI—outpatient measuresCurrently undergoing updateChronic stable coronary artery disease32005ACC/AHA/PCPICurrently undergoing updateHypertension42005ACC/AHA/PCPICurrently undergoing updateST-elevation and non–ST-elevation myocardial infarction52006ACC/AHAUpdated 2008Cardiac rehabilitation62007AACVPR/ACC/AHAAtrial fibrillation72008ACC/AHA/PCPIPrimary prevention of cardiovascular disease2009AHA/ACCFPeripheral arterial disease2010*ACCF/AHA/ACR/SCAI/SIR/SVM/SVN/SVSThe initial measure sets published by the ACCF/AHA focused primarily on processes of medical care or actions taken by healthcare providers, such as the prescription of a medication for a condition. These process measures are founded on the strongest recommendations contained in the ACCF/AHA clinical practice guidelines, delineating actions taken by clinicians in the care of patients, such as the prescription of a particular drug for a specific condition. Specifically, the writing committees consider as candidates for measures those processes of care that are recommended by the guidelines either as Class I, which identifies procedures/treatments that should be administered, or Class III, which identifies procedures/treatments that should not be administered (Table 2). Class II recommendations are not considered as candidates for performance measures. The methodology guiding the translation of guideline recommendations into process measures has been explicitly delineated by the ACCF/AHA, providing guidance to the writing committees.8Download figureDownload PowerPointTable 2. Applying Classification of Recommendations and Level of Evidence*Data available from clinical trials or registries about the usefulness/efficacy in different subpopulations, such as gender, age, history of diabetes, history of prior myocardial infarction, history of heart failure, and prior aspirin use. A recommendation with Level of Evidence B or C does not imply that the recommendation is weak. Many important clinical questions addressed in the guidelines do not lend themselves to clinical trials. Even though randomized trials are not available, there may be a very clear clinical consensus that a particular test or therapy is useful or effective.†In 2003, the ACCF/AHA Task Force on Practice Guidelines developed a list of suggested phrases to use when writing recommendations. All guideline recommendations have been written in full sentences that express a complete thought, such that a recommendation, even if separated and presented apart from the rest of the document (including headings above sets of recommendations), would still convey the full intent of the recommendation. It is hoped that this will increase readers' comprehension of the guidelines and will allow queries at the individual recommendation level.Although they possess several strengths, processes of care are limited as the sole measures of quality. Thus, current ACCF/AHA Performance Measures Writing Committees are instructed to consider structures of care, outcomes, and efficiency as complements to process measures. In developing such measures, the committees are guided by methodology established by the ACC/AHA.9 Although implementation of measures of outcomes and efficiency is currently not as well established as that of process measures, it is expected that such measures will become more pervasive over time.Although the focus of the performance measures writing committees is on measures intended for quality improvement efforts, other organizations may use these measures for external review or public reporting of provider performance. Therefore, it is within the scope of the writing committee's task to comment, when appropriate, on the strengths and limitations of such external reporting for a particular CVD state or patient population. Thus, the metrics contained within this document are categorized as either performance measures or test measures. Performance measures are those metrics that the committee designates as appropriate for use for both quality improvement and external reporting. In contrast, test measures are those that have been deemed appropriate for the purposes of quality improvement but not for external reporting until further validation and testing are performed.All measures have limitations and pose challenges to implementation that could result in unintended consequences when used for accountability. The implementation of measures for purposes other than quality improvement requires field testing to address issues related but not limited to sample size, frequency of use of an intervention, comparability, and audit requirements. The manner in which these issues is addressed is dependent on several factors, including the method of data collection, performance attribution, baseline performance rates, incentives, and public reporting methods. The ACCF/AHA encourages those interested in implementing these measures for purposes beyond quality improvement to work with the ACCF/AHA to consider these complex issues in pilot implementation projects, to assess limitations and confounding factors, and to guide refinements of the measures to enhance their utility for these additional purposes.By facilitating measurements of cardiovascular healthcare quality, ACCF/AHA performance measurement sets may serve as vehicles to accelerate appropriate translation of scientific evidence into clinical practice. These documents are intended to provide practitioners and institutions that deliver care with tools to measure the quality of their care and identify opportunities for improvement. It is our hope that application of these performance measures will provide a mechanism through which the quality of medical care can be measured and improved.Frederick A. Masoudi, MD, MSPH, FACCChair, ACCF/AHA Task Force on Performance Measures1. IntroductionThe AHA/ACCF Primary Prevention of Cardiovascular Disease Performance Measures Writing Committee (the Writing Committee) was charged to develop performance measures for the prevention of CVD. These performance measures do not specifically address prevention of stroke, although because risk factors for heart disease and stroke overlap, their use should contribute to the prevention of stroke as well. These measures are intended for adults (18 years of age and older) evaluated in the outpatient setting. The Writing Committee designed most of the measures, including all of the lifestyle measures, to begin at age 18 because we recognize that risk for atherosclerosis accumulates over a lifetime and, although it is never too late to make changes to prevent heart disease, the greatest benefit accrues with early lifestyle changes. The relation between cardiovascular risk factors and the extent and severity of coronary atherosclerosis in the teenage years and earlier is well established on the basis of autopsy studies.10,11 Evidence from long-term follow-up studies demonstrates that a favorable risk factor profile during the working years is associated with a longer, healthier life and reduced medical care expenses after age 65.12–17 These observations indicate the value of prevention of risk factors in the first place, beginning in childhood and youth, as called for by the AHA's "Guidelines for Primary Prevention of Atherosclerotic Cardiovascular Disease Beginning in Childhood."18 Although the greatest long-term benefit occurs with changes early in life, changes in adults are also encouraged because they have been demonstrated to reduce risk and prevent heart disease in both middle-aged and older adults. The Writing Committee also acknowledges that the field of primary prevention is rapidly evolving because of the contributions of observational research, registries, and clinical trials. Hence, modifications to these performance measures for primary prevention will be necessary as the field advances.The Writing Committee designed the performance measures to be applicable to the broadest possible population. A healthy lifestyle is believed to be beneficial across the entire spectrum of age, race, and sex. With respect to age, however, we recognize that there comes a time when the benefits of screening and treatment to avert future events may be of limited value because life expectancy is limited. Moreover, a number of the investigations establishing the benefits of primary prevention have not included elderly patients. In an effort to balance the competing interests of applying primary prevention as broadly as possible and being consistent with other organizations' age criteria, the Writing Committee recommends the use of the proposed measures for patients older than 18 years of age both for accountability and for public reporting. Certain measures have an upper age limit of 80 years because of a paucity of evidence to support the measure in an older age group. In addition, there may be measurement circumstances in which a narrower target age range is appropriate, and those who implement measures may choose to specify an age range that is less broad.Certain measures, such as blood pressure control, may not be achievable in all patients. Good blood pressure control is a challenge for providers in selected patient subsets, including those with multiple comorbidities and some older patients with isolated systolic hypertension. In addition, patient adherence to medical regimens varies for many reasons. The Writing Committee recognizes that providers may care for patients with complex medical and socioeconomic conditions for whom attainment of target levels for risk factors is difficult. Thus, target levels for attainment of performance measure goals will vary by patient population and by practice setting; for internal quality improvement initiatives, they are set by the providers.1.1. Scope of the ProblemFor more than a century, CVD has been the number 1 killer in the United States for all but 1 year (1918, in which there was an influenza pandemic). CVD is the underlying cause of 36.3% of all deaths, or 1 of every 2.8 deaths, in the United States, according to data from 2004. In 2008, an estimated 770 000 Americans suffered a first coronary attack (this includes myocardial infarction and unstable angina). Another 175 000 had a silent, or unrecognized, myocardial infarction. The total cost of CVD and stroke in the United States for 2007 is estimated at $448.5 billion.19Given the magnitude of the problem and the financial burden of CVD, improvements in the quality of primary prevention of cardiovascular disease will lead to substantial improvement in healthcare outcomes. Despite advances and wide publication and dissemination of prevention guidelines in the cardiovascular literature, the inconsistent application of best practices does a disservice to patients and leaves many opportunities for improvement in care and systems. Accountability at the practice level is 1 step toward more consistent application of best practice guidelines and improved clinical outcomes. The size of the performance measure set may place a burden on the practitioner but reflects the complexity of CVD prevention due to its multifactorial pathogenesis. Many practitioners are assuming this burden to ensure the quality of their practice.20,21 In addition, external groups are engaged in quality performance measurement and reporting. Where logical, the Writing Committee has attempted to distinguish between measures that are appropriate for accountability or public reporting and those that should be used only for internal quality improvement.1.2. Structure and Membership of the Writing CommitteeThe members of the Writing Committee included senior clinicians (physicians and an advanced practice nurse) and specialists in internal and family medicine, cardiology, preventive medicine, and epidemiology. The Writing Committee also included representatives from the American Academy of Family Physicians; American Association of Cardiovascular and Pulmonary Rehabilitation; American College of Physicians; Preventive Cardiovascular Nurses Association; and Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Division for Heart Disease and Stroke Prevention.1.3. Disclosure of Relationships With IndustryThe work of the Writing Committee was supported exclusively by the ACCF and AHA. Committee members volunteered their time, and there was no commercial support for the development of these performance measures. Meetings of the Writing Committee were confidential and attended only by Writing Committee members and staff. Writing Committee members were required to disclose in writing all financial relationships with industry relevant to this topic according to standard ACCF and AHA reporting policies, and they verbally acknowledged these relationships to the other members (Appendix A).1.4. Review and EndorsementBetween January 22 and February 22, 2008, the performance measures document underwent a 30-day public comment period, during which ACCF and AHA members and other health professionals had an opportunity to review and comment on the text in advance of its final approval and publication. The official peer and content review of the document was conducted simultaneously with the 30-day public comment period, with 2 peer reviewers nominated by the ACCF and 2 nominated by the AHA. We sought additional comments from clinical content experts and performance measurement experts. See Appendix B for relationships with industry and other entities of the peer reviewers.The AHA/ACCF 2009 Performance Measures for Primary Prevention of Cardiovascular Disease in Adults was adopted by the respective boards of directors of the ACCF and AHA in June 2009. These measures will be reviewed for currency once annually and updated as needed. They should be considered valid until either updated or rescinded by the ACCF/AHA Task Force on Performance Measures.2. MethodologyThe development of performance systems involves identification of a set of measures that target a specific patient population observed over a particular time period. To achieve this goal, the ACCF/AHA Task Force on Performance Measures has outlined 5 mandatory sequential steps. Sections 2.1 through 2.5 outline how the Writing Committee addressed these elements.2.1. Target Population and Care PeriodThe target population consists of patients 18 years of age or older. We developed exclusion criteria and upper age limits for certain measures to further specify the target population. These performance measures are intended for primary prevention in the adult population and do not address prevention specific to children and adolescents. More information on primary prevention for children and adolescents can be found in the AHA "Guidelines for Primary Prevention of Atherosclerotic Cardiovascular Disease Beginning in Childhood."18The Writing Committee recognizes that there are many opportunities and healthcare settings for primary prevention of CVD. Thus, these performance measures are aimed at any physician or healthcare professional who sees adult patients (age 18 years and older) at risk for CVD. For this document, the outpatient care period is defined as the period of care provided in an outpatient setting. An ongoing relationship with the healthcare professional is critical to both the initiation and eventual success of preventive measures. In addition, any single visit may not provide the opportunity to address the full range of preventive care required, and in general, the Writing Committee recommends that evidence of at least 2 encounters over a period of 1 year be established before the physician is expected to have responsibility for primary CVD prevention. However, certain measures, such as smoking cessation, are so important for prevention that the Writing Committee believed they should occur even in 1 acute visit over a 2-year period.2.2. Dimensions of CareGiven the multiple potential domains of treatment that can be measured, the Writing Committee identified the relevant dimensions of care that should be evaluated. We placed each potential performance measure into the relevant dimension-of-care categories. Performance measures selected for inclusion in the final set and their dimensions of care are summarized in Table 3. Download figureDownload PowerPointTable 3. AHA/ACCF Primary Prevention of Cardiovascular Disease Performance Measurement Set: Dimension of Care Measures MatrixAlthough the Writing Committee considered a number of additional measures that focus on equally important aspects of care, length and complexity considerations did not allow their inclusion in the present set. Final selection of performance measures was based on (1) the evidence base for a given measure, (2) ease/complexity of measurement, and (3) coverage in other measurement sets. The Writing Committee focused on outcome measures rather than process measures whenever possible. The Writing Committee recognized that for some patients, there are many obstacles to attaining the desired outcome. For example, it is difficult for some patients to attain blood pressures less than 140/90 mm Hg because of medication noncompliance, costs, side effects, or other reasons. To avoid penalizing clinicians who care for such patients, the Writing Committee designed performance measures that give credit for good faith attempts to attain the treatment goal (eg, documentation of the use of at least 2 antihypertensive medications in patients with blood pressures greater than 140/90 mm Hg), as well for attainment of the desired outcome. Such a strategy fulfills the goals of performance measurement by balancing attainment of targets for blood pressure or lipids with recognition of obstacles despite attention to goals. For internal quality improvement purposes, the Writing Committee believed that the standards could be more rigorous. The final set includes both process measures (risk assessment and risk factor counseling) and intermediate outcome measures (blood pressure, cholesterol values).2.3. Literature ReviewThe Writing Committee used the 2002 AHA "Guidelines for Primary Prevention of Cardiovascular Disease and Stroke" as the primary source for deriving these measures.22 In addition, the Writing Committee reviewed other more recent guidelines to consider the most current available evidence. These included the US Preventive Services Task Force's "Guide to Clinical Preventive Services,"23 the European guidelines on CVD prevention in clinical practice,24 the AHA's "Evidence-Based Guidelines for Cardiovascular Disease Prevention in Women: 2007 Update,"25 the Joint British Societies' "Guidelines on Prevention of Cardiovascular Disease in Clinical Practice,"26 the Third Report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III),27 and the seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure.282.4. Definition of Potential MeasuresExplicit criteria exist for the development of performance measures that accurately reflect quality of care, including defining the numerators and denominators of potential measures and evaluating their applicability, interpretability, and feasibility. To select measures for inclusion in the performance measurement set, the Writing Committee prioritized the recommendations from the 2002 AHA guidelines for primary prevention of CVD and stroke.22The AHA primary prevention guidelines22 were drafted before the AHA's adoption of a formal rating system regarding the strength of the recommendation and the level of evidence. That system, adopted by the AHA and the ACCF, enables guideline writing groups to specify the degree to which the benefit of the care is likely to outweigh any potential risk, as well as the level of evidence supporting that conclusion. In general, ACCF/AHA Class I (benefit >>> risk) and Class III (risk greater than or equal to benefit) indications for therapy identify potential dimensions of care and processes for performance measurement; however, not all performance measures must be based on grade A level of evidence (general consistency of direction and magnitude of effect from multiple [3 to 5] randomized trials or meta-analyses with population risk strata evaluated). In particular, when considering interventions to remove harmful exposures (eg, smoking cessation counseling), or to restore norms that existed during earlier phases of human evolution (eg, increased consumption of fruits, vegetables, and whole grains and decreased consumption of animal products), the need to obtain evidence from clinical trials is less obligatory than for recommendations to add a pharmaceutical agent to a patient's regimen. The Writing Committee recognizes that randomized, controlled trials of lifestyle interventions are more difficult to perform than pharmaceutical trials; however, lifestyle behavior change remains the cornerstone of a successful prevention strategy. The recommended performance measures in this document are based on processes of care that are expected to lead to benefit that far outweighs any potential risk based on evidence sufficiently strong to support broad population-wide applicability. For some measures, we needed to make recommendations despite the absence of evidence from randomized, controlled trials that used clinical events and deaths as outcomes.The Writing Committee recognizes that performance measures imply performance standards, and there are those who may find these implicit standards lower than their own practice standards, particularly with respect to assessment frequency and target intermediate outcomes, such as cholesterol and blood pressure. Physicians using these measures to assess their practice quality are invited to choose more aggressive measure specifications. The measures outlined herein are geared towards the minimum level of acceptable performance rather than optimal care, particularly when used to compare providers or for public reporting.2.5. Selection of Measures for Inclusion in the Performance Measure SetFrom analysis of these recommendations, the Writing Committee identified potential measures relevant to the primary prevention of CVD and then independently evaluated their potential for use as performance measures using 8 exclusion criteria adapted from the "ACCF/AHA Attributes of Performance Measures" (Table 4) and the Sample Performance Measure Survey Form and Exclusion Criteria Definitions (Appendix C). As part of this process, the Writing Committee also evaluated the optimal use of each measure for accountability/public reporting (A/PR) versus internal quality improvement (IQI) only. Member ratings of all the potential measures were collated and discussed by the full Writing Committee to reach consensus about which measures should advance for inclusion in the final measure set and whether any should be designated as IQI measures. Nineteen potential measures were advanced initially for full specification to assess their suitability as performance measures. These were eventually reduced to 13 final measures

BACKGROUND:The 5 A Day for Better Health community studies demonstrated in randomized trials the efficacy of population-based strategies to increase fruit and vegetable consumption in diverse geographic areas and settings.PURPOSE:Mediation analysis can help to elucidate the theoretical basis of changing dietary habits. This is important for informing more powerful cancer prevention and control interventions to achieve broad public health impact.METHODS:Five sites that focused on adults were included in mediation analyses to determine whether theoretically derived constructs assessed at baseline and follow-up contributed to explaining change in fruit and vegetable (F&V) consumption. These variables were knowledge, self-efficacy, and autonomy/responsibility. Stage of change also was considered as a potential moderating variable.RESULTS:Self-efficacy and knowledge of the 5 A Day recommendation increased in those who received the interventions and were positively associated with higher F&V. Mediation of intervention effect was demonstrated for these variables. Autonomy/responsibility did not meet the criteria for mediation. There was no evidence of differential effect of mediators according to baseline stage.CONCLUSIONS:The present study findings provide strong support for mediation of F&V consumption by two variables: self-efficacy and knowledge. The authors discuss the findings in relation to study limitations and future research directions.

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Objective: To examine whether dietary attitudes and demographics differ based on smoking status among low-income women participating in a dietary intervention. Methods: Smoking status, stages of change for eating a healthier diet, and dietary intake were examined among 2066 women participating in the Maryland Women, Infants, and Children (WIC) Food for Life Program. Results: Relative to nonsmokers, current smokers reported significantly higher overall calories; higher percentages of calories from fat, sweets, and alcohol; and lower percentage of calories from protein. Never smokers who received the dietary intervention evidenced the greatest dietary changes over time. Conclusions: Future interventions should consider targeting smoking and diet simultaneously or employ different strategies for smokers and nonsmokers.

Although an inverse association between triglyceride (TG) and (HDL-C) is well documented, the impact of lowering TG on HDL-C levels has not been well established. Therefore, data were analyzed in 151 consecutive dyslipidemic patients who made multiple visits (n=1830) to the University of Maryland Preventive Cardiology Center between 1991 and 2005. At baseline, fasting TG levels at or above the median (178 mg/dL) were associated with significantly lower HDL-C than TG levels below the median (32.6+/-11.1 mg/dL versus 45.1+/-14.2 mg/dL; P<0.0001). Following baseline evaluation, various therapies were employed (i.e., dietary, exercise, medication) to reduce mean LDL (147.3+/-53.4 mg/dL) and TG (306.1+/-414.9 mg/dL). Using a fully adjusted mixed regression model, each 50 mg/dL reduction in TG was independently associated with a 0.5 mg/dL increase in HDL-C in hypertriglyceridemic subjects (e.g., TG> or =200 mg/dL) and a 1.7 mg/dL increase in HDL-C in the absence of elevated TG (P<0.0001). The use of niacin (P<0.0001), statins (P=0.0003) and fibrates (P=0.03) were also associated with significant increases in HDL-C beyond that anticipated with TG reduction. These data indicate that lowering TG is independently and inversely correlated with HDL-C, effects that are most pronounced in the absence of hypertriglyceridemia.

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Across populations, the level of blood pressure, the incremental rise in blood pressure with age, and the prevalence of hypertension are directly related to sodium intake. Observational studies and randomized controlled trials document a consistent effect of sodium consumption on blood pressure. The majority of sodium consumption in the United States is derived from amounts added during food processing and preparation. Leading scientific organizations and governmental agencies advise limiting sodium intake to 2400 mg or less daily (approximately 6000 mg of salt). Substantial public health benefits accrue from small reductions in the population blood pressure distribution. A 1.3-g/d lower lifetime sodium intake translates into an approximately 5-mm Hg smaller rise in systolic blood pressure as individuals advance from 25 to 55 years of age, a reduction estimated to save 150,000 lives annually. With an appropriate food industry response, combined with consumer education and knowledgeable use of food labels, the average consumer should be able to choose a lower-sodium diet without inconvenience or loss of food enjoyment. In the continued absence of voluntary measures adopted by the food industry, new regulations will be required to achieve lower sodium concentrations in processed and prepared foods.

Tight control of blood glucose levels and risk factors for cardiovascular disease (e.g., hypertension, hypercholesterolemia) can substantially reduce the incidence of microvascular and macrovascular complications from type 1 diabetes. Physicians play an important role in helping patients make essential lifestyle changes to reduce the risk of these complications. Key recommendations that family physicians can give patients to optimize their outcomes include: take control of daily decisions regarding your health, focus on preventing and controlling risk factors for cardiovascular disease, tightly control your blood glucose level, be cognizant of potentially inaccurate blood glucose test results, use physiologic insulin replacement regimens, and learn how to manage and prevent hypoglycemia.