Cardiovascular Disease Projections in the United States Based on the 2020 Census Estimates
Open accessAbstract
Background Understanding trends in cardiovascular (CV) risk factors and CV disease according to age, sex, race, and ethnicity is important for policy planning and public health interventions. Objectives The goal of this study was to project the number of people with CV risk factors and disease and further explore sex, race, and ethnical disparities. Methods The prevalence of CV risk factors (diabetes mellitus, hypertension, dyslipidemia, and obesity) and CV disease (ischemic heart disease, heart failure, myocardial infarction, and stroke) according to age, sex, race, and ethnicity was estimated by using logistic regression models based on 2013-2018 National Health and Nutrition Examination Survey data and further combining them with 2020 U.S. Census projection counts for years 2025-2060. Results By the year 2060, compared with the year 2025, the number of people with diabetes mellitus will increase by 39.3% (39.2 million [M] to 54.6M), hypertension by 27.2% (127.8M to 162.5M), dyslipidemia by 27.5% (98.6M to 125.7M), and obesity by 18.3% (106.3M to 125.7M). Concurrently, projected prevalence will similarly increase compared with 2025 for ischemic heart disease by 31.1% (21.9M to 28.7M), heart failure by 33.0% (9.7M to 12.9M), myocardial infarction by 30.1% (12.3M to 16.0M), and stroke by 34.3% (10.8M to 14.5M). Among White individuals, the prevalence of CV risk factors and disease is projected to decrease, whereas significant increases are projected in racial and ethnic minorities. Conclusions Large future increases in CV risk factors and CV disease prevalence are projected, disproportionately affecting racial and ethnic minorities. Future health policies and public health efforts should take these results into account to provide quality, affordable, and accessible health care.
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Cardiovascular risk factors are predicted to increase and only a minority of people with type 2 diabetes achieve recommended risk factor goals and are treated with guideline-recommended therapy.
“Despite these encouraging opportunities to reduce morbidity and mortality, cardiovascular risk factors are predicted to increase and only a minority of people with type 2 diabetes achieve recommended risk factor goals and are treated with guideline-recommended therapy (7)(8)(9).”
From 10. Cardiovascular Disease and Risk Management: Standards of Care in Diabetes—2025 (2025) · cites this paper as [7]
The Results (CV Risk Factors; page not provided) project increases in several cardiovascular risk factors in the U.S. through 2060. The paper does not report what proportion of people with type 2 diabetes meet recommended risk-factor goals or receive guideline-recommended therapy. (LLM, conf=0.88)
Experimental — accuracy not yet measuredCardiovascular disease and chronic kidney disease are projected to rise and disproportionately impact racial and ethnic minority populations in the US.
“cardiovascular disease and chronic kidney disease are projected to rise and disproportionately impact racial and ethnic minority populations in the US.30,31”
From Race and ethnicity and pharmacy dispensing of SGLT2 inhibitors and GLP-1 receptor agonists in type 2 diabetes (2024) · cites this paper as [30]
The Discussion projects that cardiovascular disease will rise in the United States and disproportionately affect racial and ethnic minority populations; the Results specify increases particularly among Black and Hispanic populations. The paper does not project chronic kidney disease, so that part of the sentence is not supported by this source. (LLM, conf=0.90)
Experimental — accuracy not yet measuredOnly a minority of people with type 2 diabetes achieve recommended risk factor goals and are treated with guideline-recommended therapy.
“only a minority of people with type 2 diabetes achieve recommended risk factor goals and are treated with guideline-recommended therapy (7–9).”
From 10. Cardiovascular Disease and Risk Management: Standards of Care in Diabetes—2026 (2026) · cites this paper as [7]
The Results section projects diabetes prevalence, while the Methods section defines diabetes for that analysis; neither reports how many people with type 2 diabetes meet risk-factor goals or receive guideline-recommended therapy. A search for those terms and related treatment-and-control language found no passage addressing the claim in our copy. Page numbers were not available for these passages. (LLM, conf=0.75)
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Cites
Global estimates of diabetes prevalence for 2013 and projections for 2035
Guariguata, L., Whiting, D. R., Hambleton, I., Beagley, J., Linnenkamp, U., & Shaw, J. E. (2014) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2013.11.002 · Cited by 4,642 · see citing works
Heidenreich, P. A., Trogdon, J. G., Khavjou, O. A., Butler, J., Dracup, K., Ezekowitz, M. D., Finkelstein, E. A., Hong, Y., Johnston, S. C., Khera, A., et al. (2011) · Circulation · doi:10.1161/cir.0b013e31820a55f5 · Cited by 3,208 · see citing works
Grundy, S. M., Stone, N. J., Bailey, A. L., Beam, C., Birtcher, K. K., Blumenthal, R. S., Braun, L. T., de Ferranti, S., Faiella-Tommasino, J., Forman, D. E., et al. (2019) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.11.003 · Cited by 2,691 · see citing works
He, J., Ogden, L. G., Bazzano, L. A., Vupputuri, S., Loria, C., & Whelton, P. K. (2001) · Archives of Internal Medicine · doi:10.1001/archinte.161.7.996 · Cited by 1,172 · see citing works
Flagged first, then by citations
Research works printed but not linked: 33
- [1]Mackenbach JP. The epidemiologic transition theory. J Epidemiol Commun Health. 1994; 48(4): 329. PMC1059977 7964327
- [2]Olshansky SJ, Ault AB. The fourth stage of the epidemiologic transition: the age of delayed degenerative diseases. Milbank Q. 1986: 355– 391. 3762504
- [3]Ogden CL, Carroll MD, Curtin LR, Lamb MM, Flegal KM. Prevalence of high body mass index in US children and adolescents, 2007–2008. JAMA. 2010; 303(3): 242– 249. 20071470
- [4]Magliano DJ, Islam RM, Barr ELM, Trends in incidence of total or type 2 diabetes: systematic review. BMJ. 2019; 366: l5003. 10.1136/bmj.l5003 31511236 PMC6737490 · DOI · Paper page
- [5]Virani SS, Alonso A, Aparicio HJ, Heart disease and stroke statistics—2021 update: a report from the American Heart Association. Circulation. 2021; 143(8): e254– e743. 10.1161/CIR.0000000000000950 33501848 PMC13036842 · DOI · Paper page
- [6]Havranek EP, Mujahid MS, Barr DA, Social determinants of risk and outcomes for cardiovascular disease: a scientific statement from the American Heart Association. Circulation. 2015; 132(9): 873– 898. 10.1161/CIR.0000000000000228 26240271 · DOI · Paper page
- [10]Lawrence JM, Divers J, Isom S, Trends in prevalence of type 1 and type 2 diabetes in children and adolescents in the US, 2001–2017. JAMA. 2021; 326(8): 717– 727. 10.1001/jama.2021.11165 34427600 PMC8385600 · DOI
- [11]Deputy NP, Kim SY, Conrey EJ, Bullard KM. Prevalence and changes in preexisting diabetes and gestational diabetes among women who had a live birth—United States, 2012–2016. MMWR Morb Mortal Wkly Rep. 2018; 67(43): 1201– 1207. 10.15585/mmwr.mm6743a2 PMC6319799 30383743 · DOI
- [12]Thayer KA, Heindel JJ, Bucher JR, Gallo MA. Role of environmental chemicals in diabetes and obesity: a National Toxicology Program workshop review. Environ Health Perspect. 2012; 120(6): 779– 789. 10.1289/ehp.1104597 22296744 PMC3385443 · DOI
- [13]Foti K, Wang D, Appel LJ, Selvin E. Hypertension awareness, treatment, and control in US adults: trends in the hypertension control cascade by population subgroup (National Health and Nutrition Examination Survey, 1999–2016). Am J Epidemiol. 2019; 188(12): 2165– 2174. 10.1093/aje/kwz177 31504121 PMC7212399 · DOI
- [16]Ward ZJ, Bleich SN, Cradock AL, Projected U.S. state-level prevalence of adult obesity and severe obesity. N Engl J Med. 2019; 381(25): 2440– 2450. 10.1056/NEJMsa1909301 31851800 · DOI · Paper page
- [17]Carnethon MR, Pu J, Howard G, Cardiovascular health in African Americans: a scientific statement from the American Heart Association. Circulation. 2017; 136(21): e393– e423. 10.1161/CIR.0000000000000534 29061565 · DOI · Paper page
- [18]Azam TU, Colvin MM. Representation of Black patients in heart failure clinical trials. Curr Opin Cardiol. 2021; 36(3): 329– 334. 10.1097/HCO.0000000000000849 33818547 · DOI
- [19]Lewsey SC, Breathett K. Racial and ethnic disparities in heart failure: current state and future directions. Curr Opin Cardiol. 2021; 36(3): 320– 328. 10.1097/HCO.0000000000000855 33741769 PMC8130651 · DOI
- [20]Kamel H, Zhang C, Kleindorfer DO, Association of black race with early recurrence after minor ischemic stroke or transient ischemic attack: secondary analysis of the POINT randomized clinical trial. JAMA Neurol. 2020; 77(5): 601– 605. 10.1001/jamaneurol.2020.0010 32091536 PMC7042873 · DOI
- [22]Huffman MD, Capewell S, Ning H, Shay CM, Ford ES, Lloyd-Jones DM. Cardiovascular health behavior and health factor changes (1988–2008) and projections to 2020: results from the National Health and Nutrition Examination Surveys. Circulation. 2012; 125(21): 2595– 2602. 10.1161/CIRCULATIONAHA.111.070722 22547667 PMC3914399 · DOI · Paper page
- [23]Pandya A, Gaziano TA, Weinstein MC, Cutler D. More Americans living longer with cardiovascular disease will increase costs while lowering quality of life. Health Aff (Millwood). 2013; 32(10): 1706– 1714. 10.1377/hlthaff.2013.0449 24101059 PMC3894660 · DOI
- [24]Essien UR, Dusetzina SB, Gellad WF. A policy prescription for reducing health disparities—achieving pharmacoequity. JAMA. 2021; 326(18): 1793– 1794. 10.1001/jama.2021.17764 34677579 · DOI
- [25]Schultz WM, Kelli HM, Lisko JC, Socioeconomic status and cardiovascular outcomes: challenges and interventions. Circulation. 2018; 137(20): 2166– 2178. 10.1161/CIRCULATIONAHA.117.029652 29760227 PMC5958918 · DOI · Paper page
- [26]Bailey ZD, Krieger N, Agénor M, Graves J, Linos N, Bassett MT. Structural racism and health inequities in the USA: evidence and interventions. Lancet. 2017; 389(10077): 1453– 1463. 10.1016/s0140-6736(17)30569-x 28402827 · DOI · Paper page
- [28]Huovinen E, Harkanen T, Martelin T, Koskinen S, Aromaa A. Predicting coronary heart disease mortality—assessing uncertainties in population forecasts and death probabilities by using Bayesian inference. Int J Epidemiol. 2006; 35(5): 1246– 1252. 10.1093/ije/dyl128 16844770 · DOI
- [29]Odden MC, Coxson PG, Moran A, Lightwood JM, Goldman L, Bibbins-Domingo K. The impact of the aging population on coronary heart disease in the United States. Am J Med. 2011; 124(9): 827– 833. 10.1016/j.amjmed.2011.04.010. e5. 21722862 PMC3159777 · DOI · Paper page
- [30]Huffman MD, Lloyd-Jones DM, Ning H, Quantifying options for reducing coronary heart disease mortality by 2020. Circulation. 2013; 127(25): 2477– 2484. 10.1161/CIRCULATIONAHA.112.000769 23661723 PMC3795417 · DOI
- [31]Heidenreich PA, Albert NM, Allen LA, Forecasting the impact of heart failure in the United States: a policy statement from the American Heart Association. Circ Heart Fail. 2013; 6(3): 606– 619. 10.1161/HHF.0b013e318291329a 23616602 PMC3908895 · DOI
- [32]Ovbiagele B, Goldstein LB, Higashida RT, Forecasting the future of stroke in the United States: a policy statement from the American Heart Association and American Stroke Association. Stroke. 2013; 44(8): 2361– 2375. 10.1161/STR.0b013e31829734f2 23697546 · DOI
- [35]Tai DBG, Shah A, Doubeni CA, Sia IG, Wieland ML. The disproportionate impact of COVID-19 on racial and ethnic minorities in the United States. Clin Infect Dis. 2021; 72(4): 703– 706. 10.1093/cid/ciaa815 32562416 PMC7337626 · DOI
- [36]Lu Y, Liu Y, Dhingra LS, National trends in racial and ethnic disparities in antihypertensive medication use and blood pressure control among adults with hypertension, 2011–2018. Hypertension. 2022; 79(1): 207– 217. 10.1161/HYPERTENSIONAHA.121.18381 34775785 · DOI
- [37]Rethy L, Petito LC, Vu THT, Trends in the prevalence of self-reported heart failure by race/ethnicity and age from 2001 to 2016. JAMA Cardiol. 2020; 5(12): 1425– 1429. 10.1001/jamacardio.2020.3654 32876652 PMC7489385 · DOI
- [39]Gartside PS, Wang P, Glueck CJ. Prospective assessment of coronary heart disease risk factors: the NHANES I Epidemiologic Follow-Up Study (NHEFS) 16-year follow-up. J Am Coll Nutr. 1998; 17(3): 263– 269. 10.1080/07315724.1998.10718757 9627913 · DOI
- [40]Saydah S, Bullard KM, Cheng Y, Trends in cardiovascular disease risk factors by obesity level in adults in the United States, NHANES 1999–2010. Obesity (Silver Spring). 2014; 22(8): 1888– 1895. 10.1002/oby.20761 24733690 PMC4560453 · DOI
- [41]Guo F, Garvey WT. Trends in cardiovascular health metrics in obese adults: National Health and Nutrition Examination Survey (NHANES), 1988–2014. J Am Heart Assoc. 2016; 5(7). 10.1161/JAHA.116.003619 PMC5015398 27413039 · DOI
- [42]Ford ES. Trends in mortality from all causes and cardiovascular disease among hypertensive and nonhypertensive adults in the United States. Circulation. 2011; 123(16): 1737– 1744. 10.1161/CIRCULATIONAHA.110.005645 21518989 · DOI
- [43]St Clair P, Gaudette E, Zhao H, Tysinger B, Seyedin R, Goldman DP. Using self-reports or claims to assess disease prevalence: it’s complicated. Med Care. 2017; 55(8): 782– 788. 10.1097/MLR.0000000000000753 28617703 PMC5507726 · DOI
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Ng, M., Gakidou, E., Lo, J., Abate, Y. H., Abbafati, C., Abbas, N., Abbasian, M., Abd ElHafeez, S., Abdel-Rahman, W. M., Abd-Elsalam, S., et al. (2025) · The Lancet · doi:10.1016/s0140-6736(25)00355-1 · Cited by 1,151 · see citing works
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American Diabetes Association Professional Practice Committee, ElSayed, N. A., McCoy, R. G., Aleppo, G., Balapattabi, K., Beverly, E. A., Briggs Early, K., Bruemmer, D., Das, S. R., Echouffo-Tcheugui, J. B., et al. (2025) · Diabetes Care · doi:10.2337/dc25-s010 · Cited by 339 · see citing works
Maddox, T. M., Januzzi, J. L., Allen, L. A., Breathett, K., Brouse, S., Butler, J., Davis, L. L., Fonarow, G. C., Ibrahim, N. E., Lindenfeld, J., et al. (2024) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2023.12.024 · Cited by 362 · see citing works
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Mozaffarian, D., Aspry, K. E., Garfield, K., Kris-Etherton, P., Seligman, H., Velarde, G. P., Williams, K., & Yang, E. (2024) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2023.12.023 · Cited by 219 · see citing works
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American Diabetes Association Professional Practice Committee for Diabetes*, Bajaj, M., McCoy, R. G., Balapattabi, K., Bannuru, R. R., Bellini, N. J., Bennett, A. K., Beverly, E. A., Briggs Early, K., ChallaSivaKanaka, S., et al. (2026) · Diabetes Care · doi:10.2337/dc26-s010 · Cited by 107 · see citing works
Laddu, D., Neeland, I. J., Carnethon, M., Stanford, F. C., Mongraw-Chaffin, M., Barone Gibbs, B., Ndumele, C. E., Longenecker, C. T., Chung, M. L., Rao, G., et al. (2024) · Circulation · doi:10.1161/cir.0000000000001221 · Cited by 62 · see citing works
Rodriguez, L. A., Finertie, H., Neugebauer, R. S., Gosiker, B., Thomas, T. W., Karter, A. J., Gilliam, L. K., Oshiro, C., An, J., Simonson, G., et al. (2024) · The Lancet Regional Health - Americas · doi:10.1016/j.lana.2024.100759 · Cited by 31 · see citing works
“30,31 Our work supports prior fi ndings 5,6 and highlights the need to evaluate approaches to increase the use of these cardiorenal protective drugs in patients from racial and ethnic minority groups with type 2 diabetes to reduce adverse car-diorenal outcomes and improve health equity.”
- Authors
- Mohebi, R., Chen, C., Ibrahim, N. E., McCarthy, C. P., Gaggin, H. K., Singer, D. E., Hyle, E. P., Wasfy, J. H., & Januzzi, J. L.
- Affiliations
- Harvard University (US)
- Inova Fairfax Hospital (US)
- Corresponding author
- Januzzi, James L.
- ORCID
- Venue
- Journal of the American College of Cardiology
- Publisher
- Elsevier BV
- Published
- 2022-08
- Volume
- 80
- Issue
- 6
- Pages
- 565-578
- ISSN
- 0735-1097 (ISSN-L)
- PMC
- PMC9396356
- OpenAlex
- W4289262214
- Cited by
- 319
- References
- 4
- Citations by year
- 2026: 49 · 2025: 98 · 2024: 104 · 2023: 54 · 2022: 14
- FWCI
- 47.01
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of the American College of Cardiology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Aging (R01AG069575)
- National Heart, Lung, and Blood Institute (T32HL094301)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
- Health Sciences › Medicine › Epidemiology › Healthcare Systems and Public Health
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
- Keywords
- cardiovascular risk factors, diabetes mellitus, hypertension, dyslipidemia, obesity, ischemic heart disease, heart failure, myocardial infarction, stroke, racial and ethnic disparities, sex disparities, population projections, health policy
- MeSH terms
- Cardiovascular Diseases, Diabetes Mellitus, Heart Failure, Humans, Hypertension, Myocardial Infarction, Nutrition Surveys, Obesity, United States, Prevalence, Myocardial Ischemia, Censuses, Stroke, Dyslipidemias
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