Subclinical Vascular Disease Burden and Premature Mortality Among Middle-aged Adults: the Atherosclerosis Risk in Communities Study

Abstract

Background

Whether high burden of subclinical vascular disease (SVD) is associated with increased premature mortality among middle-aged adults is not adequately understood. The association of midlife SVD burden with premature mortality among middle-aged adults free of clinical cardiovascular disease (CVD) could provide further insights into stratifying premature death beyond clinical CVD.

Objective

To determine whether high burden of subclinical vascular disease is associated with increased premature mortality among middle-aged adults.

Design

We leveraged data from the Atherosclerosis Risk in Communities Study.

Participants

Thirteen thousand eight hundred seventy-six community-dwelling blacks and whites aged 45–64 years from the Atherosclerosis Risk in Communities Study.

Main Measures

Each SVD measure—ankle-brachial index, carotid intima-media thickness, and electrocardiogram—was scored 0 (no abnormalities), 1 (minor abnormalities), or 2 (major abnormalities). An index was constructed as the sum of three measures, ranging from 0 (lowest burden) to 6 (highest burden). We used the Cox proportional-hazards model to determine the association of SVD burden with premature mortality (death before age 70) among persons free of clinical CVD. We then tested the difference in point estimates between SVD and clinical CVD.

Key Results

Among persons without CVD, the premature death was 1.7, 2.1, 2.5, and 3.8 per 1000 person-years among those with an SVD score of 0 (lowest burden), 1, 2, and 3–6 (highest burden), respectively. After multivariable-adjustment, highest SVD burden (score = 3–6; HR = 1.47) was significantly associated with premature death among persons initially without CVD. In the model where persons with and without CVD were included, high SVD burden (score: 3–6 vs. 0) and CVD did not have hugely different association with premature death (HR = 1.49 vs. 1.68; P = 0.32 for comparison).

Conclusions

Midlife SVD burden was associated with premature mortality and it could stratify premature death beyond clinical CVD. It is important to take SVD into account when designing interventions for reducing premature mortality.

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References

  1. 1.

    Norheim, O. F. et al. Avoiding 40% of the Premature Deaths in Each Country, 2010-30: Review of National Mortality Trends to Help Quantify the UN Sustainable Development Goal for Health. Lancet 385, 239–252 (2015).

    Article  Google Scholar 

  2. 2.

    Bennett, J. E. et al. NCD Countdown 2030: worldwide trends in non-communicable disease mortality and progress towards Sustainable Development Goal target 3.4. Lancet, 392, 1072–1088 (2018).

    Article  Google Scholar 

  3. 3.

    “Cardiovascular Diseases.” February 28, 2020. https://www.who.int/westernpacific/health-topics/cardiovascular-diseases.

  4. 4.

    “Heart Disease and Stroke,” April 1, 2019. https://www.cdc.gov/chronicdisease/resources/publications/factsheets/heart-disease-stroke.htm.

  5. 5.

    Newman, A. B. et al. Associations of subclinical cardiovascular disease with frailty. J Gerontol A Biol Sci Med Sci. 56, M158–166 (2001).

    CAS  Article  Google Scholar 

  6. 6.

    Odden, M. C. et al. Subclinical vascular disease burden and longer survival. J Am Geriatr Soc. 62, 1692–1698, doi:https://doi.org/10.1111/jgs.13018 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Inzitari, M. et al. Subclinical vascular disease burden and risk for death and cardiovascular events in older community dwellers. J Gerontol Ser A: Biomed Sci Med Sci. 66, 986–993 (2011).

    Article  Google Scholar 

  8. 8.

    Newman, A. B. et al. Ankle-arm index as a predictor of cardiovascular disease and mortality in the Cardiovascular Health Study. Arterioscler Thromb Vasc Biol. 19, 538–545 (1999).

    CAS  Article  Google Scholar 

  9. 9.

    Newman, A. B. et al. “Successful aging”: effect of subclinical cardiovascular disease. Arch Intern Med. 163, 2315–2322, doi:https://doi.org/10.1001/archinte.163.19.2315 (2003).

    Article  PubMed  Google Scholar 

  10. 10.

    Newman, A. B., Boudreau, R. M., Naydeck, B. L., Fried, L. F. & Harris, T. B. A physiologic index of comorbidity: relationship to mortality and disability. J Gerontol Ser A: Biol Sci Med Sci 63, 603–609 (2008).

    Article  Google Scholar 

  11. 11.

    Wu, C., Smit, E., Sanders, J. L., Newman, A. B. & Odden, M. C. A Modified Healthy Aging Index and Its Association with Mortality: The National Health and Nutrition Examination Survey, 1999-2002. J Gerontol A Biol Sci Med Sci. 72, 1437–1444, doi:https://doi.org/10.1093/gerona/glw334 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Chaves, P. H. et al. Subclinical cardiovascular disease in older adults: insights from the Cardiovascular Health Study. Am J Geriatr Cardiol. 13, 137–151 (2004).

    Article  Google Scholar 

  13. 13.

    Kuller, L. H. et al. Subclinical disease as an independent risk factor for cardiovascular disease. Circulation 92, 720–726 (1995).

    CAS  Article  Google Scholar 

  14. 14.

    Kuller, L. H. et al. Diabetes mellitus: subclinical cardiovascular disease and risk of incident cardiovascular disease and all-cause mortality. Arterioscler Thromb Vasc Biol. 20, 823–829 (2000).

    CAS  Article  Google Scholar 

  15. 15.

    Benjamin, E. J. et al. Heart disease and stroke statistics—2017 update: a report from the American Heart Association. Circulation 135, e146–e603 (2017).

    Article  Google Scholar 

  16. 16.

    The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. The ARIC investigators. Am J Epidemiol. 1989;129:687–702.

  17. 17.

    Mundt, K. A., Chambless, L. E., Burnham, C. B. & Heiss, G. Measuring ankle systolic blood pressure: validation of the Dinamap 1846 SX. Angiology 43, 555–566, doi:https://doi.org/10.1177/000331979204300703 (1992).

    CAS  Article  PubMed  Google Scholar 

  18. 18.

    Pignoli, P., Tremoli, E., Poli, A., Oreste, P. & Paoletti, R. Intimal plus medial thickness of the arterial wall: a direct measurement with ultrasound imaging. Circulation 74, 1399-1406 (1986).

    CAS  Article  Google Scholar 

  19. 19.

    High-resolution B-mode ultrasound reading methods in the Atherosclerosis Risk in Communities (ARIC) cohort. The ARIC Study Group. J Neuroimaging. 1991;1:168–172.

  20. 20.

    Chambless, L. E. et al. Association of coronary heart disease incidence with carotid arterial wall thickness and major risk factors: the Atherosclerosis Risk in Communities (ARIC) Study, 1987-1993. Am J Epidemiol. 146, 483–494 (1997).

    CAS  Article  Google Scholar 

  21. 21.

    Prineas RJ, Crow R, Blackburn HW. The Minnesota Code Manual of Electrocardiographic Findings: Standards and Procedures for Measurement and Classification. J. Wright; Boston, MA: 1982.

    Google Scholar 

  22. 22.

    Vitelli, L. L. et al. Electrocardiographic findings in a healthy biracial population. Atherosclerosis Risk in Communities (ARIC) Study Investigators. Am J Cardiol. 81, 453–459 (1998).

    CAS  Article  Google Scholar 

  23. 23.

    Inzitari, M. et al. Subclinical vascular disease burden and risk for death and cardiovascular events in older community dwellers. J Gerontol A Biol Sci Med Sci. 66, 986–993, doi:https://doi.org/10.1093/gerona/glr069 (2011).

    Article  PubMed  Google Scholar 

  24. 24.

    Rosamond, W.D. et al. Trends in the incidence of myocardial infarction and in mortality due to coronary heart disease, 1987 to 1994. N Engl J Med. 339, 861–867 (1998).

    CAS  Article  Google Scholar 

  25. 25.

    Rosamond, W.D. et al. Classification of heart failure in the Atherosclerosis Risk in Communities (ARIC) study: a comparison of diagnostic criteria. Circ Heart Fail. 5, 152–159 (2012).

    Article  Google Scholar 

  26. 26.

    Jones, S.A. et al. Validity of hospital discharge diagnosis codes for stroke: the Atherosclerosis Risk in Communities Study. Stroke 45, 3219–3225 (2014).

    Article  Google Scholar 

  27. 27.

    Carson, A. P. et al. Cumulative socioeconomic status across the life course and subclinical atherosclerosis. Ann Epidemiol. 17, 296–303, doi:https://doi.org/10.1016/j.annepidem.2006.07.009 (2007).

    Article  PubMed  Google Scholar 

  28. 28.

    Nieto, F. J., Diez-Roux, A., Szklo, M., Comstock, G. W. & Sharrett, A. R. Short- and long-term prediction of clinical and subclinical atherosclerosis by traditional risk factors. J Clin Epidemiol. 52, 559–567 (1999).

    CAS  Article  Google Scholar 

  29. 29.

    Diez Roux, A. V. et al. Long-term exposure to ambient particulate matter and prevalence of subclinical atherosclerosis in the Multi-Ethnic Study of Atherosclerosis. Am J Epidemiol. 167, 667–675, doi:https://doi.org/10.1093/aje/kwm359 (2008).

    Article  PubMed  Google Scholar 

  30. 30.

    Psaty, B. M. et al. Association between levels of blood pressure and measures of subclinical disease multi-ethnic study of atherosclerosis. Am J Hypertens. 19, 1110–1117, doi:https://doi.org/10.1016/j.amjhyper.2006.04.002 (2006).

    Article  PubMed  Google Scholar 

  31. 31.

    Allison, M. A. et al. Prevalence of and risk factors for subclinical cardiovascular disease in selected US Hispanic ethnic groups: the Multi-Ethnic Study of Atherosclerosis. Am J Epidemiol. 167, 962–969, doi:https://doi.org/10.1093/aje/kwm402 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Lutsey, P. L. et al. Associations of acculturation and socioeconomic status with subclinical cardiovascular disease in the multi-ethnic study of atherosclerosis. Am J Public Health. 98, 1963–1970, doi:https://doi.org/10.2105/AJPH.2007.123844 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Steyerberg, E. W. et al. Assessing the performance of prediction models: a framework for traditional and novel measures. Epidemiology 21, 128–138, doi:https://doi.org/10.1097/EDE.0b013e3181c30fb2 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgments

The Atherosclerosis Risk in Communities Study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C) with the ARIC carotid MRI examination funded by U01HL075572-01. The authors thank the staff and participants of the ARIC Study for their important contributions. Dr. Chenkai Wu is supported by the Suzhou Municipal Science and Technology Bureau (SS2019069).

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Correspondence to Chenkai Wu Ph.D., M.P.H., M.S..

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Conflict of Interest

Dr. Chenkai Wu provides paid consultant services to HealthKeeperS, a health data analytics company in China. Dr. Michelle Odden provides paid consultant services to Cricket Health, Inc., a kidney care company in the USA.

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Wu, C., Zhang, K., Odden, M.C. et al. Subclinical Vascular Disease Burden and Premature Mortality Among Middle-aged Adults: the Atherosclerosis Risk in Communities Study. J GEN INTERN MED (2021). https://doi.org/10.1007/s11606-020-06398-6

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KEY WORDS

  • atherosclerosis
  • cardiovascular diseases
  • vascular diseases
  • premature mortality