Perceived Lifetime Risk for Cardiovascular Disease (from the Dallas Heart Study)
2014; Elsevier BV; Volume: 114; Issue: 1 Linguagem: Inglês
10.1016/j.amjcard.2014.04.006
ISSN1879-1913
AutoresElisabeth Joye Petr, Colby Ayers, Ambarish Pandey, James A. de Lemos, Tiffany M. Powell‐Wiley, Amit Khera, Donald M. Lloyd‐Jones, Jarett D. Berry,
Tópico(s)Health Literacy and Information Accessibility
ResumoLifetime risk estimation for cardiovascular disease (CVD) has been proposed as a useful strategy to improve risk communication in the primary prevention setting. However, the perception of lifetime risk for CVD is unknown. We included 2,998 subjects from the Dallas Heart Study. Lifetime risk for developing CVD was classified as high (≥39%) versus low (<39%) according to risk factor burden as described in our previously published algorithm. Perception of lifetime risk for myocardial infarction was assessed by way of a 5-point scale. Baseline characteristics were compared across levels of perceived lifetime risk. Multivariable logistic regression analyses were performed to determine the association of participant characteristics with level of perceived lifetime risk for CVD and with correctness of perceptions. Of the 2,998 participants, 64.8% (n = 1,942) were classified as having high predicted lifetime risk for CVD. There was significant discordance between perceived and predicted lifetime risk. After multivariable adjustment, family history of premature myocardial infarction, high self-reported stress, and low perceived health were all strongly associated with high perceived lifetime risk (odds ratio [OR] 2.37, 95% confidence interval [CI] 1.72 to 3.27; OR 2.17, 95% CI 1.66 to 2.83; and OR 2.71, 95% CI 2.09 to 3.53; respectively). However, the association between traditional CVD risk factors and high perceived lifetime risk was more modest. In conclusion, misperception of lifetime risk for CVD is common and frequently reflects the influence of factors other than traditional risk factor levels. These findings highlight the importance of effectively communicating the significance of traditional risk factors in determining the lifetime risk for CVD. Lifetime risk estimation for cardiovascular disease (CVD) has been proposed as a useful strategy to improve risk communication in the primary prevention setting. However, the perception of lifetime risk for CVD is unknown. We included 2,998 subjects from the Dallas Heart Study. Lifetime risk for developing CVD was classified as high (≥39%) versus low (<39%) according to risk factor burden as described in our previously published algorithm. Perception of lifetime risk for myocardial infarction was assessed by way of a 5-point scale. Baseline characteristics were compared across levels of perceived lifetime risk. Multivariable logistic regression analyses were performed to determine the association of participant characteristics with level of perceived lifetime risk for CVD and with correctness of perceptions. Of the 2,998 participants, 64.8% (n = 1,942) were classified as having high predicted lifetime risk for CVD. There was significant discordance between perceived and predicted lifetime risk. After multivariable adjustment, family history of premature myocardial infarction, high self-reported stress, and low perceived health were all strongly associated with high perceived lifetime risk (odds ratio [OR] 2.37, 95% confidence interval [CI] 1.72 to 3.27; OR 2.17, 95% CI 1.66 to 2.83; and OR 2.71, 95% CI 2.09 to 3.53; respectively). However, the association between traditional CVD risk factors and high perceived lifetime risk was more modest. In conclusion, misperception of lifetime risk for CVD is common and frequently reflects the influence of factors other than traditional risk factor levels. These findings highlight the importance of effectively communicating the significance of traditional risk factors in determining the lifetime risk for CVD. Although a majority of the population of the United States is at low risk for cardiovascular disease (CVD) in the short term (10-year estimate), most of these subjects are actually at high risk for developing CVD during their remaining life span.1Berry J.D. Dyer A. Cai X. Garside D.B. Ning H. Thomas A. Greenland P. Van Horn L. Tracy R.P. Lloyd-Jones D.M. Lifetime risks of cardiovascular disease.N Engl J Med. 2012; 366: 321-329Crossref PubMed Scopus (647) Google Scholar, 2Marma A.K. Berry J.D. Ning H. Persell S.D. Lloyd-Jones D.M. 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: 8-14Crossref PubMed Scopus (140) Google Scholar Physicians have routinely used short-term CVD risk estimation in primary prevention to guide decisions to treat blood pressure and cholesterol levels and encourage therapeutic lifestyle changes for those at highest risk.3Expert Panel on Detection Evaluation, and Treatment of High Blood Cholesterol in AdultsThird 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: 3143-3421PubMed Google Scholar However, short-term risk estimates have important limitations, classifying most adults aged <50 years and many women as having low risk regardless of risk factor burden.2Marma A.K. Berry J.D. Ning H. Persell S.D. Lloyd-Jones D.M. 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: 8-14Crossref PubMed Scopus (140) Google Scholar, 3Expert Panel on Detection Evaluation, and Treatment of High Blood Cholesterol in AdultsThird 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: 3143-3421PubMed Google Scholar Therefore, national guidelines have recently encouraged the use of long-term or lifetime risk as an adjunct to short-term risk communication in the primary prevention setting.3Expert Panel on Detection Evaluation, and Treatment of High Blood Cholesterol in AdultsThird 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: 3143-3421PubMed Google Scholar, 4Mosca L. 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Expert Panel/Writing GroupAmerican Heart AssociationAmerican Academy of Family PhysiciansAmerican College of Obstetricians and GynecologistsAmerican College of Cardiology FoundationSociety of Thoracic SurgeonsAmerican Medical Women's AssociationCenters for Disease Control and PreventionOffice of Research on Women's HealthAssociation of Black CardiologistsAmerican College of PhysiciansWorld Heart FederationNational HeartLung, and Blood InstituteAmerican College of Nurse PractitionersEvidence-based guidelines for cardiovascular disease prevention in women: 2007 update.Circulation. 2007; 115: 1481-1501Crossref PubMed Scopus (609) Google Scholar, 5Goff Jr., D.C. Lloyd-Jones D.M. Bennett G. Coady S. D'Agostino Sr., R.B. Gibbons R. Greenland P. Lackland D.T. Levy D. O'Donnell C.J. Robinson J. Schwartz J.S. Shero S.T. Smith Jr., S.C. Sorlie P. Stone N.J. Wilson P.W. 2013 ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines.Circulation. 2013 Nov 12; (Epub)Crossref Scopus (2238) Google Scholar Previous studies have observed that knowledge of short-term risk has been associated with healthy lifestyle patterns6Mosca L. Mochari H. Christian A. Berra K. Taubert K. Mills T. Burdick K.A. Simpson S.L. National study of women's awareness, preventive action, and barriers to cardiovascular health.Circulation. 2006; 113: 525-534Crossref PubMed Scopus (299) Google Scholar and the effectiveness of cholesterol-7Grover S.A. Lowensteyn I. Joseph L. Kaouache M. Marchand S. Coupal L. Boudrea G. Cardiovascular Health Evaluation to Improve Compliance and Knowledge Among Uninformed Patients (CHECK-UP) Study GroupPatient knowledge of coronary risk profile improves the effectiveness of dyslipidemia therapy: the CHECK-UP Study: a randomized controlled trial.Arch Intern Med. 2007; 167: 2296-2303Crossref PubMed Scopus (143) Google Scholar and blood pressure–lowering therapy.8Grover S. Lowensteyn I. Joseph L. Kaouache M. Marchand S. Coupal L. Boudrea G. Discussing coronary risk with patients to improve blood pressure treatment: secondary results from the CHECK-UP Study.J Gen Intern Med. 2009; 24: 33-39Crossref PubMed Scopus (24) Google Scholar However, little is known about the perception of lifetime risk for CVD in the general population. Therefore, we sought to determine the perception of lifetime risk for CVD by comparing Dallas Heart Study (DHS) participants' perceived lifetime risk with their predicted lifetime risk for CVD using our previously published algorithm.1Berry J.D. Dyer A. Cai X. Garside D.B. Ning H. Thomas A. Greenland P. Van Horn L. Tracy R.P. Lloyd-Jones D.M. Lifetime risks of cardiovascular disease.N Engl J Med. 2012; 366: 321-329Crossref PubMed Scopus (647) Google Scholar, 9Lloyd-Jones D.M. Leip E.P. Larson M.G. D'Agostino R.B. Beiser A. Wilson P.W.F. Wolf P.A. Levy D. Prediction of lifetime risk for cardiovascular disease by risk factor burden at 50 years of age.Circulation. 2006; 113: 791-798Crossref PubMed Scopus (900) Google Scholar, 10Berry J.D. Liu K. Folsom A.R. Polak J.F. Lewis C.E. Shea S. Sidney S. O'Leary D.H. Chan C. Lloyd-Jones D.M. Prevalence and progression of subclinical atherosclerosis in younger adults with low short-term but high lifetime estimated risk for cardiovascular disease: the coronary artery risk development in young adults study and multi-ethnic study of atherosclerosis.Circulation. 2009; 119: 382-389Crossref PubMed Scopus (220) Google ScholarMethodsThe DHS is a multiethnic population-based probability sample of adult residents of Dallas County ages 18 to 65 years enrolled from July 2000 to January 2002.11Victor R.G. Haley R.W. Willett D.L. Peshock R.M. Vaeth P.C. Leonard D. Basit M. Cooper R.S. Iannacchione V.G. Visscher W.A. Staab J.M. Hobbs H.H. Dallas Heart Study InvestigatorsThe Dallas Heart Study: a population-based probability sample for the multidisciplinary study of ethnic differences in cardiovascular health.Am J Cardiol. 2004; 93: 1473-1480Abstract Full Text Full Text PDF PubMed Scopus (433) Google Scholar All participants provided informed consent to participate in the study, and the protocol was approved by the Institutional Review Board of the University of Texas Southwestern Medical Center. In the initial home visit, 6,101 participants underwent extensive household interviews. A subset of 3,557 participants aged 30 to 65 years participated in a follow-up visit, providing fasting blood and urine specimens and serial blood pressure measurements. Details of the study design, including collection of medical history, blood pressure, anthropometric measurements, and laboratory measurements, have been described previously in detail.11Victor R.G. Haley R.W. Willett D.L. Peshock R.M. Vaeth P.C. Leonard D. Basit M. Cooper R.S. Iannacchione V.G. Visscher W.A. Staab J.M. Hobbs H.H. Dallas Heart Study InvestigatorsThe Dallas Heart Study: a population-based probability sample for the multidisciplinary study of ethnic differences in cardiovascular health.Am J Cardiol. 2004; 93: 1473-1480Abstract Full Text Full Text PDF PubMed Scopus (433) Google Scholar In the present study, we included 2,998 subjects who participated in the follow-up visit of the DHS after excluding participants with a self-report of previous myocardial infarction (MI) and/or stroke (n = 181), a nonfasting blood sample (n = 94), and those missing measured baseline covariates (n = 284).Race and/or ethnicity and current smoking status were defined by self-report. Education level was used as a surrogate for socioeconomic status instead of income level because many participants declined to provide financial information. High education level was defined as college degree or higher. Body mass index was calculated from measured height and weight. Diabetes mellitus was defined by a fasting glucose of ≥126 mg/dl, nonfasting glucose of ≥200 mg/dl, or the use of glucose-lowering medications. Family history of premature MI was defined as a first-degree male relative with a heart attack at age <50 years or a first-degree female relative with a heart attack at age <55 years in survey responses. Levels of stress and perceived health were determined by self-report to the following survey items in the DHS: "On a scale of 1-5, how would you rate your stress level? (1 = No stress at all; 5 = Extremely high stress)" and "How would you say your general health is? (excellent, very good, good, fair, or poor)." High perceived stress was defined as a score of 4 or 5; low perceived stress was defined as a score of 1 to 3. High perceived health was defined as excellent, very good, or good; low perceived health was defined as fair or poor. Perceived lifetime risk for CVD was measured using the participants' response to the following question: "On a scale of 1-5, how likely is it that you will have a heart attack in your lifetime? (1 = Least likely, 5 = Most likely)."12Patel M.J. de Lemos J.A. Philips B. Murphy S.A. Vaeth P.C. McGuire D.K. Khera A. Implications of family history of myocardial infarction in young women.Am Heart J. 2007; 154: 454-460Abstract Full Text Full Text PDF PubMed Scopus (29) Google ScholarWe estimated predicted lifetime risk according to our previously published algorithm1Berry J.D. Dyer A. Cai X. Garside D.B. Ning H. Thomas A. Greenland P. Van Horn L. Tracy R.P. Lloyd-Jones D.M. Lifetime risks of cardiovascular disease.N Engl J Med. 2012; 366: 321-329Crossref PubMed Scopus (647) Google Scholar, 9Lloyd-Jones D.M. Leip E.P. Larson M.G. D'Agostino R.B. Beiser A. Wilson P.W.F. Wolf P.A. Levy D. Prediction of lifetime risk for cardiovascular disease by risk factor burden at 50 years of age.Circulation. 2006; 113: 791-798Crossref PubMed Scopus (900) Google Scholar, 10Berry J.D. Liu K. Folsom A.R. Polak J.F. Lewis C.E. Shea S. Sidney S. O'Leary D.H. Chan C. Lloyd-Jones D.M. Prevalence and progression of subclinical atherosclerosis in younger adults with low short-term but high lifetime estimated risk for cardiovascular disease: the coronary artery risk development in young adults study and multi-ethnic study of atherosclerosis.Circulation. 2009; 119: 382-389Crossref PubMed Scopus (220) Google Scholar where we classified each participant into 1 of 5 mutually exclusive risk factor categories according to their level of measured traditional CVD risk factors: all optimal risk factors, ≥1 not optimal risk factor, ≥1 elevated risk factor, 1 major risk factor, or ≥2 major risk factors. Compared with subjects in the lowest 2 risk factor categories (i.e., all optimal or ≥1 not optimal risk factor), subjects in the top 3 risk factor categories (i.e., at least 1 elevated risk factor) represent a unique subset, with higher observed lifetime risks for CVD, the presence of at least 1 treatable risk factor, and a greater prevalence and progression of subclinical atherosclerosis.1Berry J.D. Dyer A. Cai X. Garside D.B. Ning H. Thomas A. Greenland P. Van Horn L. Tracy R.P. Lloyd-Jones D.M. Lifetime risks of cardiovascular disease.N Engl J Med. 2012; 366: 321-329Crossref PubMed Scopus (647) Google Scholar, 9Lloyd-Jones D.M. Leip E.P. Larson M.G. D'Agostino R.B. Beiser A. Wilson P.W.F. Wolf P.A. Levy D. Prediction of lifetime risk for cardiovascular disease by risk factor burden at 50 years of age.Circulation. 2006; 113: 791-798Crossref PubMed Scopus (900) Google Scholar, 10Berry J.D. Liu K. Folsom A.R. Polak J.F. Lewis C.E. Shea S. Sidney S. O'Leary D.H. Chan C. Lloyd-Jones D.M. Prevalence and progression of subclinical atherosclerosis in younger adults with low short-term but high lifetime estimated risk for cardiovascular disease: the coronary artery risk development in young adults study and multi-ethnic study of atherosclerosis.Circulation. 2009; 119: 382-389Crossref PubMed Scopus (220) Google Scholar Therefore, in the present study we used this previously validated threshold to determine the predicted lifetime risk for CVD, classifying each subject as having either "low predicted lifetime risk" or "high predicted lifetime risk" (Supplementary Table 1).Because perceived lifetime risk was measured on a relative (i.e., "least likely" to "most likely") rather than a quantitative scale, we studied further those subjects at the extremes of perceived lifetime risk. Therefore, those subjects who selected "5 (most likely)" were defined as having high perceived lifetime risk and those subjects who selected "1 (least likely)" were defined as having low perceived lifetime risk. We compared baseline characteristics across levels of perceived lifetime risk (1 [least likely] to 5 [most likely]) using linear trend tests and the Cochran-Armitage trend test for continuous and categorical variables, respectively.To determine the independent association between risk factors and the perception of lifetime risk for CVD, we first constructed multivariate logistic regression models for all study participants to test the association between demographics, traditional CVD risk factors, and other personal characteristics and the perception of lifetime risk for MI, with high perceived lifetime risk (i.e., score = 5) as the outcome variable. To identify factors associated with correct or incorrect perception of lifetime risk of MI, we constructed multivariate logistic regression models separately for subjects with low predicted lifetime risk (i.e., all optimal or ≥1 not optimal risk factor) and for those with high predicted lifetime risk (i.e., at least 1 elevated risk factor). In both high and low predicted lifetime risk subgroups, incorrectly perceived lifetime risk was the outcome variable (i.e., perceived < predicted, and perceived > predicted) and correctly perceived lifetime risk was the referent (i.e., perceived = predicted). In participants with low predicted lifetime risk, we determined the association between participant characteristics and overestimation of lifetime risk for CVD (perceived > predicted). Similarly, in participants with high predicted lifetime risk, we determined the association between participant characteristics and underestimation of lifetime risk for CVD (perceived < predicted; Figure 1)All models were adjusted for age, gender, race, education level, body mass index, systolic blood pressure, total cholesterol, current smoking, presence or absence of diabetes, presence or absence of family history of premature MI, and perceived levels of stress and health. These variables were selected in an effort to compare basic demographics, components of the Framingham and lifetime risk for CVD estimates, or because they were significantly different across levels of perceived lifetime risk. All reported p values are 2-sided at a significance level of 5%. Statistical analyses were performed using SAS for Windows (release 9.2; SAS Institute, Inc., Cary, North Carolina). Chi-square statistics were included to facilitate comparison of both categorical and continuous variables in determining risk perception.ResultsMost of the study participants had a high predicted lifetime risk for CVD. Of the 2,998 participants, 64.8% (n = 1,942) had a high predicted lifetime risk for CVD, whereas 35.2% (n = 1,056) had a low predicted lifetime risk for CVD (Supplementary Table 1). The average perceived lifetime risk for CVD in the DHS was 2.6 on a scale from 1 (least likely) to 5 (most likely; Table 1). There was a significant discordance between perceived and predicted lifetime risk for CVD. For example, of 736 participants with the lowest perceived lifetime risk (score = 1, least likely), 42% had a high predicted lifetime risk and therefore appeared to underestimate their lifetime risk (perceived < predicted). Similarly, of 312 participants with the highest perceived lifetime risk (score = 5, most likely), about 1/2 (49%) actually had a low predicted lifetime risk and therefore overestimated their lifetime risk for CVD (perceived > predicted; Table 1). Factors associated with higher perceived lifetime risk for CVD were older age, traditional CVD risk factors, positive family history of premature MI, higher levels of perceived stress, and lower levels of perceived health (Table 1).Table 1Baseline characteristics of Dallas Heart Study participants stratified according to level of perceived lifetime risk∗Perceived lifetime risk was determined by the response to the survey question "On a scale of 1-5, how likely is it that you will have a heart attack in your lifetime?" Those who selected "1 (least likely)" were defined as having low perceived lifetime risk for CVD, whereas those who selected "5 (most likely)" were defined as having high perceived lifetime risk for CVD. for cardiovascular disease (n = 2,998)VariableLeast Likely2(n = 772)3(n = 806)4(n = 372)Most Likelyp-Value1(n = 736)5(n = 312)Age (years)42 ± 1043 ± 1044 ± 1045 ± 944 ± 10<0.001Men339 (46%)317 (41%)363 (45%)175 (47%)128 (41%)0.665Race Black464 (63%)340 (44%)347 (43%)167 (45%)162 (52%)<0.0001 White110 (15%)239 (31%)298 (37%)167 (45%)97 (31%)<0.0001 Hispanic147 (20%)170 (22%)145 (18%)34 (9%)44 (14%)<0.0001 Other15 (2%)23 (3%)16 (2%)4 (1%)9 (3%)0.926Family history of premature MI52 (7%)62 (8%)73 (9%)56 (15%)66 (21%)<0.001Systolic blood pressure (mm Hg)123 ± 18122 ± 17124 ± 18127 ± 18127 ± 20<0.001Diabetes mellitus66 (9%)62 (8%)73 (9%)56 (15%)53 (17%)<0.001Total cholesterol (mg/dl)176 ± 38180 ± 37182 ± 38184 ± 41183 ± 460.001Body mass index (kg/m2)30 ± 730 ± 830 ± 731 ± 732 ± 80.0002Current smoker191 (26%)178 (23%)234 (29%)130 (35%)100 (32%)0.0001Low predicted lifetime risk for CVD427 (58%)425 (55%)419 (52%)182 (49%)153 (49%)0.0002High predicted lifetime risk for CVD309 (42%)347 (45%)387 (48%)190 (51%)159 (51%)0.0002Stress level None132 (18%)62 (8%)40 (5%)15 (4%)16 (5%)<0.0001 Extremely high44 (6%)46 (6%)73 (9%)45 (12%)69 (22%)<0.0001Perceived health Excellent162 (22%)100 (13%)81 (10%)26 (7%)19 (6%)<0.0001 Poor7 (1%)15 (2%)16 (2%)22 (6%)34 (11%)<0.0001Education level < High school179 (24%)153 (20%)128 (16%)51 (14%)74 (24%)0.013 High school247 (34%)214 (28%)232 (29%)115 (31%)112 (36%)0.656 Some college202 (27%)221 (29%)223 (28%)114 (31%)82 (26%)0.905 College +107 (15%)184 (24%)223 (28%)92 (25%)44 (14%)0.078∗ Perceived lifetime risk was determined by the response to the survey question "On a scale of 1-5, how likely is it that you will have a heart attack in your lifetime?" Those who selected "1 (least likely)" were defined as having low perceived lifetime risk for CVD, whereas those who selected "5 (most likely)" were defined as having high perceived lifetime risk for CVD. Open table in a new tab After multivariable adjustment, these associations persisted, with particularly strong associations for family history of premature MI, high perceived stress, and low perceived health. However, the association between traditional CVD risk factors and high perceived lifetime risk was more modest (Figure 2).Figure 2Multivariable-adjusted odds ratios (95% confidence intervals) comparing participant characteristics and the probability of having high perceived lifetime risk for CVD (n = 2,998). In this figure, high perceived lifetime risk is defined as having a perceived lifetime risk score of 5; lower perceived lifetime risk is defined as having a perceived lifetime risk score of 1 to 4 (see Methods for details). Odds ratios are multivariable adjusted for all covariates listed.View Large Image Figure ViewerDownload Hi-res image Download (PPT)We further examined the factors that were associated with misperception of lifetime risk for CVD. In participants with a low predicted lifetime risk for CVD (n= 1,056), 751 did not perceive their risk level to be low or "1 (least likely)," but instead rated their perceived risk level to be higher with scores from 2 to 5. The determinants of overestimated risk (perceived > predicted) included older age (odds ratio [OR] 1.23, 95% confidence interval [CI] 1.03 to 1.47), white race (OR 2.42, 95% CI 1.66 to 3.50), high education level (OR 1.56, 95% CI 1.09 to 2.23), elevated body mass index (OR 1.10, 95% CI 1.02 to 1.18), family history of premature MI (OR 2.16, 95% CI 1.15 to 4.05), high perceived stress (OR 1.87, 95% CI 1.27 to 2.76), and low perceived health (OR 2.05, 95% CI 1.34 to 3.12).Similarly, of participants with high predicted lifetime risk for CVD (n = 1,942), 1,704 did not perceive their risk level to be high or "5 (most likely)," but instead rated their perceived risk level to be lower with scores from 1 to 4. The determinants of underestimated risk (perceived < predicted) included participants without a family history of premature MI (OR 1.76, 95% CI 1.20 to 2.58), with low perceived stress (OR 2.13, 95% CI 1.57 to 2.90), and with high perceived health (OR 2.68, 95% CI 1.99 to 3.62).Finally, because perceived lifetime risk was measured on a relative scale of survey responses, we chose a priori to study those at the extremes of perceived risk (i.e., score of 1 vs 5). After additional sensitivity analyses in which we varied the threshold for low perceived lifetime risk (i.e., a score of 1, 1 or 2, and 1 to 3 were considered to be low perceived lifetime risk in separate analyses), we observed a consistent pattern of results, suggesting that our findings were independent of the threshold (data not shown).DiscussionTo our knowledge, the present study represents the first report of the perceived lifetime risk for CVD in the general population. Our findings demonstrate that the perception of lifetime risk for CVD varies considerably and is often inaccurate. In addition, our findings demonstrate that the perception of CVD risk is influenced more by personal factors (i.e., subjective perception of stress and personal health) than traditional CVD risk factors. Therefore, patients and health-care providers have different perspectives regarding estimation of lifetime risk for CVD. These findings have implications for primary prevention practice, emphasizing the importance of more effective risk communication regarding the role of established traditional risk factors in determining the lifetime risk for CVD.Several previous studies have examined the association between short-term perceived and predicted risk for CVD.13Avis N.E. Smith K.W. McKinlay J.B. Accuracy of perceptions of heart attack risk: what influences perceptions and can they be changed?.Am J Public Health. 1989; 79: 1608-1612Crossref PubMed Scopus (156) Google Scholar, 14Kreuter M.W. Strecher V.J. Changing inaccurate perceptions of health risk: results from a randomized trial.Health Psychol. 1995; 14: 56-63Crossref PubMed Scopus (240) Google Scholar, 15Marteau T.M. Kinmonth Ann-Louise Pyke Stephen Thompson Simon G. Family Heart Study GroupReadiness for lifestyle advice: self-assessments of coronary risk prior to screening in the British family heart study.Br J Gen Pract. 1995; 45: 5-8PubMed Google Scholar, 16van der Weijden T. Bos L.B. Koelewijn-van Loon M.S. Primary care patients' recognition of their own risk for cardiovascular disease: implications for risk communication in practice.Curr Opin Cardiol. 2008; 23: 471-476Crossref PubMed Scopus (35) Google Scholar Most of these studies use data derived from primary care physician practices and/or use self-reported risk factors to create predicted risk estimates. Despite these methodologic differences, these previous studies also observed that incorrect perception of short-term CVD risk was not uncommon and was associated with race, socioeconomic status, family history of CVD, and perceived health. Interestingly, a study of women's awareness of CVD demonstrated that although general knowledge of CVD as a leading cause of death has increased over the last decade, this knowledge has not translated into an accurate perception of personal risk for CVD.17Kling J.M. Miller V.M. Mankad R. Wilansky S. Wu Q. Zais T.G. Zarling K.K. Allison T.G. Mulvagh S.L. Go Red for Women cardiovascular health-screening evaluation: the dichotomy between awareness and perception of cardiovascular risk in the community.J Womens Health (Larchmt). 2013; 22: 210-218Crossref PubMed Scopus (29) Google Scholar There exists an "optimism bias," in which people generally underestimate their own personal risk for CVD.18Webster R. Heeley E. Perceptions of risk: understanding cardiovascular disease.Risk Manag Healthc Policy. 2010; 3: 49-60Crossref PubMed Scopus (72) Google ScholarIn the present study, we extend these previous observations in several important ways. First, we provide the first reported description of perceived lifetime, rather than short-term, risk for CVD and its associated demographic, personal, and risk factor characteristics in a large, multiethnic, population-based sample of United States adults. Second, using measured baseline risk factors and our previously published lifetime risk prediction algorithm we were able to compare the perceived lifetime risk with a reliable estimate of the predicted lifetime risk for CVD.We found that despite the fact that most of our study participants (64%) are at high predicted lifetime risk for CVD, most do not perceive themselves as having hi
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