Global Effect of Modifiable Risk Factors on Cardiovascular Disease and Mortality

Abstract

BACKGROUND: Five modifiable risk factors are associated with cardiovascular disease and death from any cause. Studies using individual-level data to evaluate the regional and sex-specific prevalence of the risk factors and their effect on these outcomes are lacking. METHODS: We pooled and harmonized individual-level data from 112 cohort studies conducted in 34 countries and 8 geographic regions participating in the Global Cardiovascular Risk Consortium. We examined associations between the risk factors (body-mass index, systolic blood pressure, non-high-density lipoprotein cholesterol, current smoking, and diabetes) and incident cardiovascular disease and death from any cause using Cox regression analyses, stratified according to geographic region, age, and sex. Population-attributable fractions were estimated for the 10-year incidence of cardiovascular disease and 10-year all-cause mortality. RESULTS: Among 1,518,028 participants (54.1% of whom were women) with a median age of 54.4 years, regional variations in the prevalence of the five modifiable risk factors were noted. Incident cardiovascular disease occurred in 80,596 participants during a median follow-up of 7.3 years (maximum, 47.3), and 177,369 participants died during a median follow-up of 8.7 years (maximum, 47.6). For all five risk factors combined, the aggregate global population-attributable fraction of the 10-year incidence of cardiovascular disease was 57.2% (95% confidence interval [CI], 52.4 to 62.1) among women and 52.6% (95% CI, 49.0 to 56.1) among men, and the corresponding values for 10-year all-cause mortality were 22.2% (95% CI, 16.8 to 27.5) and 19.1% (95% CI, 14.6 to 23.6). CONCLUSIONS: Harmonized individual-level data from a global cohort showed that 57.2% and 52.6% of cases of incident cardiovascular disease among women and men, respectively, and 22.2% and 19.1% of deaths from any cause among women and men, respectively, may be attributable to five modifiable risk factors. (Funded by the German Center for Cardiovascular Research (DZHK); ClinicalTrials.gov number, NCT05466825.).

Shown for reading. Its publisher allows quoting it, not republishing it.

References 36

1. 1.

   Joseph P, Leong D, McKee M, Reducing the Global Burden of Cardiovascular Disease, Part 1: The Epidemiology and Risk Factors. Circulation research 2017;121(6):677–694. (In eng). DOI:.

   Not in our library10.1161/circresaha.117.308903

2. 2.

   Yusuf S, Hawken S, Ounpuu S, Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet 2004;364(9438):937–52. DOI:.

   Not in our library10.1016/s0140-6736(04)17018-9

3. 3.

   Yusuf S, Joseph P, Rangarajan S, Modifiable risk factors, cardiovascular disease, and mortality in 155 722 individuals from 21 high-income, middle-income, and low-income countries (PURE): a prospective cohort study. Lancet 2020;395(10226):795–808. DOI:.

   Not in our library10.1016/s0140-6736(19)32008-2

4. 4.

   collaboration SwgaECr. SCORE2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in Europe. European heart journal 2021;42(25):2439–2454. (In eng). DOI:.

   Not in our library10.1093/eurheartj/ehab309

5. 5.

   Yadlowsky S, Hayward RA, Sussman JB, McClelland RL, Min YI, Basu S. Clinical Implications of Revised Pooled Cohort Equations for Estimating Atherosclerotic Cardiovascular Disease Risk. Annals of internal medicine 2018;169(1):20–29. (In eng). DOI:.

   Not in our library10.7326/m17-3011

6. 6.

   (WHO WHO. World Health Statistics. 2011. (https://web.archive.org/web/20111116011154/http://www.who.int/whosis/whostat/2011/en/).

   Not in our library

7. 7.

   Jaspers NEM, Blaha MJ, Matsushita K, Prediction of individualized lifetime benefit from cholesterol lowering, blood pressure lowering, antithrombotic therapy, and smoking cessation in apparently healthy people. European heart journal 2020;41(11):1190–1199. DOI:.

   Not in our library10.1093/eurheartj/ehz239

8. 8.

   Evans A, Salomaa V, Kulathinal S, MORGAM (an international pooling of cardiovascular cohorts). International journal of epidemiology 2005;34(1):21–7. (In eng). DOI:.

   Not in our library10.1093/ije/dyh327

9. 9.

   van Buuren S, Groothuis-Oudshoorn K. mice: Multivariate Imputation by Chained Equations in R. Journal of Statistical Software 2011;45(3):1–67. DOI:.

   Not in our library10.18637/jss.v045.i03

10. 10.

    Riley RD SL, Tierney JF. Individual Participant Data Meta-Analysis: A Handbook for Healthcare Research. Wiley Online Library 2021.

    Not in our library

11. 11.

    Korn EL, Graubard BI, Midthune D. Time-to-event analysis of longitudinal follow-up of a survey: choice of the time-scale. American journal of epidemiology 1997;145(1):72–80. (In eng). DOI:.

    Not in our library10.1093/oxfordjournals.aje.a009034

12. 12.

    Laaksonen MA, Virtala E, Knekt P, Oja H, Härkänen T. SAS Macros for Calculation of Population Attributable Fraction in a Cohort Study Design. Journal of Statistical Software 2011;43(7):1–25. DOI:.

    Not in our library10.18637/jss.v043.i07

13. 13.

    Team RC. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. (http://www.r-project.org/index.html).

    Not in our library

14. 14.

    Pencina MJ, D’Agostino RB, Sr., Larson MG, Massaro JM, Vasan RS. Predicting the 30-year risk of cardiovascular disease: the framingham heart study. Circulation 2009;119(24):3078–84. DOI:.

    Not in our library10.1161/circulationaha.108.816694

15. 15.

    Joseph P, Kutty VR, Mohan V, Cardiovascular disease, mortality, and their associations with modifiable risk factors in a multi-national South Asia cohort: a PURE substudy. European heart journal 2022. DOI:.

    Not in our library10.1093/eurheartj/ehac249

16. 16.

    Walli-Attaei M, Joseph P, Rosengren A, Variations between women and men in risk factors, treatments, cardiovascular disease incidence, and death in 27 high-income, middle-income, and low-income countries (PURE): a prospective cohort study. Lancet 2020;396(10244):97–109. DOI:.

    Not in our library10.1016/s0140-6736(20)30543-2

17. 17.

    Berry JD, Dyer A, Cai X, Lifetime risks of cardiovascular disease. The New England journal of medicine 2012;366(4):321–9. DOI:.

    Not in our library10.1056/nejmoa1012848

18. 18.

    Yusuf S, Hawken S, Ounpuu S, Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet (London, England) 2004;364(9438):937–52. (In eng). DOI:.

    Not in our library10.1016/s0140-6736(04)17018-9

19. 19.

    Ueshima H, Sekikawa A, Miura K, Cardiovascular disease and risk factors in Asia: a selected review. Circulation 2008;118(25):2702–9. DOI:.

    Not in our library10.1161/circulationaha.108.790048

20. 20.

    Lawes CM, Vander Hoorn S, Rodgers A. Global burden of blood-pressure-related disease, 2001. Lancet (London, England) 2008;371(9623):1513–8. (In eng). DOI:.

    Not in our library10.1016/s0140-6736(08)60655-8

21. 21.

    Group SR, Wright JT Jr., Williamson JD, A Randomized Trial of Intensive versus Standard Blood-Pressure Control. The New England journal of medicine 2015;373(22):2103–16. DOI:.

    Not in our library10.1056/nejmoa1511939

22. 22.
    Application of non-HDL cholesterol for population-based cardiovascular risk stratification: results from the Multinational Cardiovascular Risk Consortium · 2019

    Corrected
23. 23.

    Johannesen CDL, Langsted A, Mortensen MB, Nordestgaard BG. Association between low density lipoprotein and all cause and cause specific mortality in Denmark: prospective cohort study. Bmj 2020;371:m4266. DOI:.

    Not in our library10.1136/bmj.m4266

24. 24.

    Liu Y, Liu F, Zhang L, Association between low density lipoprotein cholesterol and all-cause mortality: results from the NHANES 1999–2014. Scientific reports 2021;11(1):22111. DOI:.

    Not in our library10.1038/s41598-021-01738-w

25. 25.

    Sabatine MS, Giugliano RP, Keech AC, Evolocumab and Clinical Outcomes in Patients with Cardiovascular Disease. The New England journal of medicine 2017;376(18):1713–1722. DOI:.

    Not in our library10.1056/nejmoa1615664

26. 26.

    Robinson JG, Farnier M, Krempf M, Efficacy and safety of alirocumab in reducing lipids and cardiovascular events. The New England journal of medicine 2015;372(16):1489–99. DOI:.

    Not in our library10.1056/nejmoa1501031

27. 27.

    van Bruggen FH, Luijendijk HJ. Evolocumab’s Long-Term Mortality Risk Unclear Due to Shortened Follow-Up of FOURIER. Am J Cardiovasc Drugs 2022;22(1):5–8. DOI:.

    Not in our library10.1007/s40256-021-00480-y

28. 28.
    Risk thresholds for alcohol consumption: combined analysis of individual-participant data for 599 912 current drinkers in 83 prospective studies · 2018

    Corrected
29. 29.

    Schraufnagel DE, Balmes JR, Cowl CT, Air Pollution and Noncommunicable Diseases: A Review by the Forum of International Respiratory Societies’ Environmental Committee, Part 2: Air Pollution and Organ Systems. Chest 2019;155(2):417–426. DOI:.

    Not in our library10.1016/j.chest.2018.10.041

30. 30.

    Basner M, Babisch W, Davis A, Auditory and non-auditory effects of noise on health. Lancet 2014;383(9925):1325–1332. DOI:.

    Not in our library10.1016/s0140-6736(13)61613-x

31. 31.

    Walli-Attaei M, Rosengren A, Rangarajan S, Metabolic, behavioural, and psychosocial risk factors and cardiovascular disease in women compared with men in 21 high-income, middle-income, and low-income countries: an analysis of the PURE study. Lancet (London, England) 2022;400(10355):811–821. (In eng). DOI:.

    Not in our library10.1016/s0140-6736(22)01441-6

32. 32.

    Blankenberg S, Salomaa V, Makarova N, Troponin I and cardiovascular risk prediction in the general population: the BiomarCaRE consortium. European heart journal 2016;37(30):2428–37. DOI:.

    Not in our library10.1093/eurheartj/ehw172

33. 33.

    Neumann JT, Twerenbold R, Ojeda F, Application of High-Sensitivity Troponin in Suspected Myocardial Infarction. The New England journal of medicine 2019;380(26):2529–2540. DOI:.

    Not in our library10.1056/nejmoa1803377

34. 34.
    Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019 · 2020

    Corrected
35. 35.

    Vaduganathan M, Mensah GA, Turco JV, Fuster V, Roth GA. The Global Burden of Cardiovascular Diseases and Risk: A Compass for Future Health. Journal of the American College of Cardiology 2022;80(25):2361–2371. DOI:.

    Not in our library10.1016/j.jacc.2022.11.005

36. 36.

    Global Burden of Metabolic Risk Factors for Chronic Diseases C, Lu Y, Hajifathalian K, Metabolic mediators of the effects of body-mass index, overweight, and obesity on coronary heart disease and stroke: a pooled analysis of 97 prospective cohorts with 1.8 million participants. Lancet 2014;383(9921):970–83. DOI:.

    Not in our library10.1016/s0140-6736(13)61836-x

Cited by papers we hold 1

• Joint association of TyG index and high sensitivity C-reactive protein with cardiovascular disease: a national cohort study · 2024
  No notice

Reads

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.