Disparities Between Ideal Cardiovascular Health Metrics and Subclinical Atherosclerotic Burden
2015; Lippincott Williams & Wilkins; Volume: 8; Issue: 1 Linguagem: Inglês
10.1161/circimaging.114.002761
ISSN1942-0080
AutoresKhurram Nasir, Ron Blankstein,
Tópico(s)Cardiac Health and Mental Health
ResumoHomeCirculation: Cardiovascular ImagingVol. 8, No. 1Disparities Between Ideal Cardiovascular Health Metrics and Subclinical Atherosclerotic Burden Free AccessEditorialPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessEditorialPDF/EPUBDisparities Between Ideal Cardiovascular Health Metrics and Subclinical Atherosclerotic BurdenMore Than Meets The Eye Khurram Nasir and Ron Blankstein Khurram NasirKhurram Nasir From the Center for Prevention and Wellness Research, Baptist Health Medical Group, Miami Beach, FL (K.N.); Miami Cardiovascular Institute (MCVI), Baptist Health South Florida, Miami Beach, FL (K.N.); The Johns Hopkins Ciccarone Center for the Prevention of Heart Disease, Baltimore, MD (K.N.); Department of Medicine, Herbert Wertheim College of Medicine (K.N.) and Department of Epidemiology, Robert Stempel College of Public Health (K.N.), Florida International University, Miami; and Non-Invasive Cardiovascular Imaging Program, Departments of Medicine (Cardiovascular Division) and Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (R.B.). and Ron BlanksteinRon Blankstein From the Center for Prevention and Wellness Research, Baptist Health Medical Group, Miami Beach, FL (K.N.); Miami Cardiovascular Institute (MCVI), Baptist Health South Florida, Miami Beach, FL (K.N.); The Johns Hopkins Ciccarone Center for the Prevention of Heart Disease, Baltimore, MD (K.N.); Department of Medicine, Herbert Wertheim College of Medicine (K.N.) and Department of Epidemiology, Robert Stempel College of Public Health (K.N.), Florida International University, Miami; and Non-Invasive Cardiovascular Imaging Program, Departments of Medicine (Cardiovascular Division) and Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (R.B.). Originally published31 Dec 2014https://doi.org/10.1161/CIRCIMAGING.114.002761Circulation: Cardiovascular Imaging. 2015;8:e002761In 2010, the American Heart Association proposed an important and welcoming paradigm shift from our decades old emphasis on reduction of cardiovascular disease (CVD) to a national goal of attaining cardiovascular health.1 This framework paved the way for an ideal cardiovascular health (ICH) metric, on the basis of simple, reproducible, and easily measurable determinants of CV health, which have been proven to have a favorable effect on long-term cardiovascular morbidity and mortality. Broadly, the focus is on 4 lifestyle factors (smoking, body weight, physical activity, and optimal diet) and 3 established risk factors (blood cholesterol, blood glucose, and blood pressure levels). Since the first formal definition of ICH, extensive investigations have conclusively demonstrated that (1) a small proportion of our population has optimal CV health status as defined by presence of ≥6 to 7 ICH metrics, (2) as a society we fare poorly on the diet, physical activity, and body mass index metrics, and (3) those who demonstrate higher frequency of ICH metrics have a substantially lower CVD and all-cause mortality.2–5See Article by Saleem et alIn recent years, there has been a significant interest in exploring associations between ICH metrics and subclinical CVD, a proposed link between healthy risk factor/lifestyle profile and improved CVD outcomes. Aatola et al6 demonstrated that arterial stiffness measured as pulse wave velocity decreased by 0.09 m/s per unit increase in patients with ideal CV health score, whereas Crichton et al7 noted that mean pulse wave velocity was significantly lower among subjects with ≥5 ICH metrics when compared with those with ≤2. A similar inverse relationship was observed between favorable CV health status and carotid intima-media thickness, a marker of atherosclerotic disease.8 Results from the Framingham offspring cohort convincingly revealed that with each additional ideal CV health metric, there was a 23% reduction in the probability of having a abnormal marker of subclinical CVD (defined as any combination of left ventricular hypertrophy, enlarged left ventricular end-systolic diameter, increased carotid intima-media thickness, peripheral arterial disease, and the presence of microalbuminuria).9In this issue of Circulation: Cardiovascular Imaging, Saleem et al10 add to the current literature by examining association between ICH metrics with the presence and burden of coronary artery calcification (CAC), arguably one of the most robust marker of subclinical CVD and prognosis. In a large sample of self-referred individuals (n=3121), the investigators categorized cardiovascular health status as favorable (4–7 metrics in ideal range), intermediate (3 metrics in ideal range), or unfavorable (0–2 metrics in ideal range). Despite the limitations that the study focused on a nonrepresentative population whose objectives were not intended to assess metrics of ideal health, the distribution of these metrics was still consistent with national estimates from multiple prospective studies. As expected, none of the participants had all 7-health metrics in ideal range. Favorable CVD status, defined as having ≥4 ICH metrics was noted in one third of the population. Conversely, nearly half (43%) were considered to have poor CVD health (0–2 ideal health CVD health metrics).The results of the study demonstrated a powerful graded relationship between the clustering of ideal health metrics and the presence and severity of coronary artery plaque, as assessed by CAC. In the current study, at least one third of the participants with unfavorable CV health metrics had CAC>100, which has been shown to be a coronary heart disease risk equivalent and as a result explains the increased risk noted in this group.11,12 In contrast, those with intermediate and favorable health metrics were 32% and 59% more likely to have no CACs (CAC=0). The strong association of favorable clustering of ideal health profile with absent coronary calcifications may explain, at least in part, the favorable influence of ideal CV health on cardiac outcomes.13–15From a ten thousand feet view, the message of the study highlighting the effect of unfavorable lifestyle behaviors and risk factor clustering on heightened risk for subclinical CVD is crystal clear. However, one must be reminded of the famous English writer and philosopher of the early 20th century, Aldous Huxley quote, "There are things known and there are things unknown, and in between are the doors of perception." A closer inspection of Figure 2, which describes the distribution of CAC scores according to CVD health status provides some intriguing insights that deserve further discussion. At the extreme spectrums of ideal health status, it may not be unrealistic for one to expect homogeneity of risk versus disease. However, we observe significant discordance. Evidence of early subclinical coronary atherosclerosis was noted in ≈40% of those perceived to attain ideal CVD health. Furthermore, ≥1 in 6 subjects with favorable CVD health showed signs of significant burden of coronary atherosclerotic disease (CAC>100). On the contrary, at least one third with unfavorable CVD health status had no signs of calcified coronary atherosclerotic disease and likely are at much lower risk than would be anticipated.Should we be surprised with this observation? Not really. In recent years, there has been growing awareness that a lower perceived risk, as defined by the absence of traditional clinical and lifestyle factors, may not equate with the absence of subclinical CVD, and vice versa. Hulten et al16 recently showed that at least one third at subjects with a low life-time risk based on optimal CV risk profile had early signs of coronary atherosclerotic disease with 15% of these young individuals showing moderate to severe degree of coronary atherosclerosis (CAC>100). Another study from the prospective Multi-Ethnic Study of Atherosclerosis corroborated these observations by showing that among participants with no traditional modifiable CVD risk factors, one third (32%) were noted to have underlying CAC.17 Furthermore, Ahmed et al18 showed that 45% of subjects with 3 to 4 favorable lifestyle metrics by the American Heart Association 2020 goals (non smokers, normal body mass index, optimal diet, and optimal physical activity level) had positive CAC scores. On the contrary, consistent with findings reported by Saleem et al,10 ≥35% to 45% of subjects with clustering of unfavorable risk factor and lifestyle metrics have been noted with signs of early atherosclerotic disease in these recent studies.16–18How can we explain these potentially unexpected but significant disparities? Blaha et al19 argues that reliance on these simple and surrogate measurements taken at single time point at a relatively late stage in life can explain this heterogeneity between actual and perceived risk. This imprecise paradigm of risk assessment likely disregards temporal as well varying exposure during the course of development and adulthood and does not account for other genetic and environmental determinants. This imprecision can be minimized by at least accounting for these metrics over a longer period of time, thus reducing the variability that is inherent when estimating the cumulative effect of being exposed to multiple factors over a lifetime. Alternatively, one can directly bypass these surrogate measurements to test for underlying preclinical disease and mitigate the imprecision in quantifying early life risk exposures. An added advantage to this approach is that it may also identify individuals who, for unclear reasons, do not develop atherosclerosis despite exposure to multiple risk factors.Do disparities in perceived risk and underlying atherosclerotic burden have any effect on patient outcomes? Unfortunately, the current study does not address this specific issue because no follow-up information on incident CVD event was available. The answer to this question can be potentially extrapolated from a recent study by Silverman et al17 that examined the interplay between atherosclerotic burden and risk factors, which provided us with some interesting findings: (1) the burden of subclinical disease allows for risk discrimination over a wider range when compared with the clustering of risk factors and accounts for a substantial amount of residual risk that is not captured by risk factors; (2) even among those with favorable risk profiles, the presence of CAC is associated with a higher event rate when compared with those who had multiple risk factors but had no underlying CAC, (3) once subclinical atherosclerosis burden was taken into account, risk factors remain associated with slightly higher relative risk; and (4) the worst outcomes are observed among those with the worst risk profile status and the highest degree of atherosclerotic burden.18Do these findings imply that there should be a lesser emphasis on these risk factor/lifestyle metrics? Absolutely not. In spite of a cautionary note of disparities in risk profile versus subclinical CVD, these studies at the same time reinforce the importance of primordial prevention, as even the presence of a single major risk factor in associated with a relatively worse outcome, irrespective of baseline atherosclerotic burden. In this regard, pursuing ideal CV health is an ideal target, especially those who have unfavorable metrics. The optimism is supported by the extensive evidence clearly demonstrating that adoption of healthy lifestyle and improving one risk profile as suggested by life simple 7 goals translates into reducing the risk of incident cardiac disease that also extends to halting development and progression of underlying subclinical cardiovascular damages. For example, Ahmed et al18 assessed the effect of a healthy lifestyle metrics, and convincingly showed that among those with absence of CAC=0, only 14% of those with favorable lifestyle score follow-up developed CAC in 2-year follow-up when compared with 22% among those who did not adhere to any of these healthy lifestyle behaviors. Furthermore, it is evident that young adults adopting healthy lifestyle changes at an early age are significantly less likely to develop subclinical atherosclerosis assessed 20 years later.20In summary, although achieving ICH metrics remain one of the most important public health goal, studies like the one by Saleem et al10 leave us with more questions, such as can we accurately classify CVD health as ideal in the presence of early subclinical damage? Although a provocative and untested concept, these findings provide enough substance for us to at least start deliberating whether there is any value in broadening our scope to embrace subclinical disease testing to assess true CVD health status. The path for adopting this change within American Heart Association 2020 goals framework although will be extremely challenging, as to date we have little information suggesting that this paradigm shift can or will have any meaningful effect in achieving our objectives. However, at the same time, this should not distract us from hard facts that substantial disparities exist between perceived health and actual disease. We have come a long way in tackling the enormous burden of CVD, and are in an exciting, yet early phase of comprehending the concept of CVD well-being. If we were betting men, not too far in future, we foresee a more decisive role of preclinical disease assessment in the framework of primordial prevention for refining the definition of ideal cardiovascular health.DisclosuresNone.FootnotesThe opinions expressed in this article are not necessarily those of the editors or of the American Heart Association.Correspondence to Khurram Nasir, MD, MPH, Center for Prevention and Wellness Research, Baptist Health Medical Group, 1691 Michigan Ave Suite 500, Miami Beach, FL 33139. E-mail [email protected]References1. Lloyd-Jones D, Adams RJ, Brown TM, Carnethon M, Dai S, De Simone G, Ferguson TB, Ford E, Furie K, Gillespie C, Go A, Greenlund K, Haase N, Hailpern S, Ho PM, Howard V, Kissela B, Kittner S, Lackland D, Lisabeth L, Marelli A, McDermott MM, Meigs J, Mozaffarian D, Mussolino M, Nichol G, Roger VL, Rosamond W, Sacco R, Sorlie P, Stafford R, Thom T, Wasserthiel-Smoller S, Wong ND, Wylie-Rosett J. Executive summary: heart disease and stroke statistics–2010 update: a report from the American Heart Association.Circulation. 2010; 121:948–954.LinkGoogle Scholar2. Bambs C, Kip KE, Dinga A, Mulukutla SR, Aiyer AN, Reis SE. Low prevalence of "ideal cardiovascular health" in a community-based population: the heart strategies concentrating on risk evaluation (Heart SCORE) study.Circulation. 2011; 123:850–857. doi: 10.1161/CIRCULATIONAHA.110.980151.LinkGoogle Scholar3. Folsom AR, Yatsuya H, Nettleton JA, Lutsey PL, Cushman M, Rosamond WD; ARIC Study Investigators. Community prevalence of ideal cardiovascular health, by the American Heart Association definition, and relationship with cardiovascular disease incidence.J Am Coll Cardiol. 2011; 57:1690–1696. doi: 10.1016/j.jacc.2010.11.041.CrossrefMedlineGoogle Scholar4. Dong C, Rundek T, Wright CB, Anwar Z, Elkind MS, Sacco RL. Ideal cardiovascular health predicts lower risks of myocardial infarction, stroke, and vascular death across whites, blacks, and hispanics: the northern Manhattan study.Circulation. 2012; 125:2975–2984. doi: 10.1161/CIRCULATIONAHA.111.081083.LinkGoogle Scholar5. Yang Q, Cogswell ME, Flanders WD, Hong Y, Zhang Z, Loustalot F, Gillespie C, Merritt R, Hu FB. Trends in cardiovascular health metrics and associations with all-cause and CVD mortality among US adults.JAMA. 2012; 307:1273–1283. doi: 10.1001/jama.2012.339.CrossrefMedlineGoogle Scholar6. Aatola H, Hutri-Kähönen N, Juonala M, Laitinen TT, Pahkala K, Mikkilä V, Telama R, Koivistoinen T, Lehtimäki T, Viikari JS, Raitakari OT, Kähönen M. Prospective relationship of change in ideal cardiovascular health status and arterial stiffness: the Cardiovascular Risk in Young Finns Study.J Am Heart Assoc. 2014; 3:e000532. doi: 10.1161/JAHA.113.000532.LinkGoogle Scholar7. Crichton GE, Elias MF, Robbins MA. Cardiovascular health and arterial stiffness: the Maine-Syracuse Longitudinal Study.J Hum Hypertens. 2014; 28:444–449. doi: 10.1038/jhh.2013.131.CrossrefMedlineGoogle Scholar8. Kulshreshtha A, Goyal A, Veledar E, McClellan W, Judd S, Eufinger SC, Bremner JD, Goldberg J, Vaccarino V. Association between ideal cardiovascular health and carotid intima-media thickness: a twin study.J Am Heart Assoc. 2014; 3:e000282. doi: 10.1161/JAHA.113.000282.LinkGoogle Scholar9. Xanthakis V, Enserro DM, Murabito JM, Polak JF, Wollert KC, Januzzi JL, Wang TJ, Tofler G, Vasan RS. Ideal cardiovascular health: associations with biomarkers and subclinical disease and impact on incidence of cardiovascular disease in the framingham offspring study.Circulation. 2014; 130:1676–1683. doi: 10.1161/CIRCULATIONAHA.114.009273.LinkGoogle Scholar10. Saleem Y, DeFina LF, Radford NB, Willis BL, Barlow CE, Gibbons LW, Khera A.Association of a favorable cardiovascular health profile with the presence of coronary artery calcification.Circ Cardiovasc Imaging. 2015; 8:e001851.LinkGoogle Scholar11. Detrano R, Guerci AD, Carr JJ, Bild DE, Burke G, Folsom AR, Liu K, Shea S, Szklo M, Bluemke DA, O'Leary DH, Tracy R, Watson K, Wong ND, Kronmal RA. Coronary calcium as a predictor of coronary events in four racial or ethnic groups.N Engl J Med. 2008; 358:1336–1345. doi: 10.1056/NEJMoa072100.CrossrefMedlineGoogle Scholar12. Erbel R, Möhlenkamp S, Moebus S, Schmermund A, Lehmann N, Stang A, Dragano N, Grönemeyer D, Seibel R, Kälsch H, Bröcker-Preuss M, Mann K, Siegrist J, Jöckel KH; Heinz Nixdorf Recall Study Investigative Group. Coronary risk stratification, discrimination, and reclassification improvement based on quantification of subclinical coronary atherosclerosis: the Heinz Nixdorf Recall study.J Am Coll Cardiol. 2010; 56:1397–1406. doi: 10.1016/j.jacc.2010.06.030.CrossrefMedlineGoogle Scholar13. Sarwar A, Shaw LJ, Shapiro MD, Blankstein R, Hoffmann U, Hoffman U, Cury RC, Abbara S, Brady TJ, Budoff MJ, Blumenthal RS, Nasir K. Diagnostic and prognostic value of absence of coronary artery calcification.JACC. Cardiovasc Imaging. 2009; 2:675–688. doi: 10.1016/j.jcmg.2008.12.031.CrossrefMedlineGoogle Scholar14. Blaha M, Budoff MJ, Shaw LJ, Khosa F, Rumberger JA, Berman D, Callister T, Raggi P, Blumenthal RS, Nasir K. Absence of coronary artery calcification and all-cause mortality.JACC. Cardiovasc Imaging. 2009; 2:692–700. doi: 10.1016/j.jcmg.2009.03.009.CrossrefMedlineGoogle Scholar15. Budoff MJ, McClelland RL, Nasir K, Greenland P, Kronmal RA, Kondos GT, Shea S, Lima JA, Blumenthal RS. Cardiovascular events with absent or minimal coronary calcification: the Multi-Ethnic Study of Atherosclerosis (MESA).Am Heart J. 2009; 158:554–561. doi: 10.1016/j.ahj.2009.08.007.CrossrefMedlineGoogle Scholar16. Hulten E, Villines TC, Cheezum MK, Berman DS, Dunning A, Achenbach S, Al-Mallah M, Budoff MJ, Cademartiri F, Callister TQ, Chang HJ, Cheng VY, Chinnaiyan K, Chow BJ, Cury RC, Delago A, Feuchtner G, Hadamitzky M, Hausleiter J, Kaufmann PA, Kim YJ, Leipsic J, Lin FY, Maffei E, Plank F, Raff GL, Shaw LJ, Min JK; CONFIRM Investigators. Calcium score, coronary artery disease extent and severity, and clinical outcomes among low Framingham risk patients with low vs high lifetime risk: results from the CONFIRM registry.J Nucl Cardiol. 2014; 21:29–37; quiz 38. doi: 10.1007/s12350-013-9819-7.CrossrefMedlineGoogle Scholar17. Silverman MG, Blaha MJ, Krumholz HM, Budoff MJ, Blankstein R, Sibley CT, Agatston A, Blumenthal RS, Nasir K. Impact of coronary artery calcium on coronary heart disease events in individuals at the extremes of traditional risk factor burden: the Multi-Ethnic Study of Atherosclerosis.Eur Heart J. 2014; 35:2232–2241. doi: 10.1093/eurheartj/eht508.CrossrefMedlineGoogle Scholar18. Ahmed HM, Blaha MJ, Nasir K, Jones SR, Rivera JJ, Agatston A, Blankstein R, Wong ND, Lakoski S, Budoff MJ, Burke GL, Sibley CT, Ouyang P, Blumenthal RS. Low-risk lifestyle, coronary calcium, cardiovascular events, and mortality: results from MESA.Am J Epidemiol. 2013; 178:12–21. doi: 10.1093/aje/kws453.CrossrefMedlineGoogle Scholar19. Blaha MJ, Silverman MG, Budoff MJ. Is there a role for coronary artery calcium scoring for management of asymptomatic patients at risk for coronary artery disease?: Clinical risk scores are not sufficient to define primary prevention treatment strategies among asymptomatic patients.Circ Cardiovasc Imaging. 2014; 7:398–408; discussion 408. doi: 10.1161/CIRCIMAGING.113.000341.LinkGoogle Scholar20. Spring B, Moller AC, Colangelo LA, Siddique J, Roehrig M, Daviglus ML, Polak JF, Reis JP, Sidney S, Liu K. Healthy lifestyle change and subclinical atherosclerosis in young adults: Coronary Artery Risk Development in Young Adults (CARDIA) study.Circulation. 2014; 130:10–17. doi: 10.1161/CIRCULATIONAHA.113.005445.LinkGoogle Scholar Previous Back to top Next FiguresReferencesRelatedDetailsCited By Fernández-Alvira J, Fuster V, Pocock S, Sanz J, Fernández-Friera L, Laclaustra M, Fernández-Jiménez R, Mendiguren J, Fernández-Ortiz A, Ibáñez B and Bueno H (2017) Predicting Subclinical Atherosclerosis in Low-Risk Individuals, Journal of the American College of Cardiology, 10.1016/j.jacc.2017.09.032, 70:20, (2463-2473), Online publication date: 1-Nov-2017. Santos I, Goulart A, Pereira A, Lotufo P and Benseñor I (2016) Association between Cardiovascular Health Score and Carotid Intima-Media Thickness: Cross-Sectional Analysis of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) Baseline Assessment, Journal of the American Society of Echocardiography, 10.1016/j.echo.2016.09.001, 29:12, (1207-1216.e4), Online publication date: 1-Dec-2016. Bensenor I, Goulart A, Santos I, Bittencourt M, Pereira A, Santos R, Nasir K, Blankstein R and Lotufo P (2016) Association between a healthy cardiovascular risk factor profile and coronary artery calcium score: Results from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), American Heart Journal, 10.1016/j.ahj.2015.12.018, 174, (51-59), Online publication date: 1-Apr-2016. Maclagan L and Tu J (2015) Using the concept of ideal cardiovascular health to measure population health, Current Opinion in Cardiology, 10.1097/HCO.0000000000000210, 30:5, (518-524), Online publication date: 1-Sep-2015. Joshi P and Nasir K (2015) Discordance between Risk Factors and Coronary Artery Calcium: Implications for Guiding Treatment Strategies in Primary Prevention Settings, Progress in Cardiovascular Diseases, 10.1016/j.pcad.2015.05.006, 58:1, (10-18), Online publication date: 1-Jul-2015. Thomas D, Divakaran S, Villines T, Nasir K, Shah N, Slim A, Blankstein R and Cheezum M (2015) Management of Coronary Artery Calcium and Coronary CTA Findings, Current Cardiovascular Imaging Reports, 10.1007/s12410-015-9334-0, 8:6, Online publication date: 1-Jun-2015. January 2015Vol 8, Issue 1 Advertisement Article InformationMetrics © 2014 American Heart Association, Inc.https://doi.org/10.1161/CIRCIMAGING.114.002761PMID: 25552494 Originally publishedDecember 31, 2014 Keywordscoronary artery calcificationEditorialssubclinical atherosclerosiscardiovascular healthPDF download Advertisement
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