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01-12-2021 | Stroke | Research article

Association between cardiometabolic disease multimorbidity and all-cause mortality in 2 million women and men registered in UK general practices

Authors: Dexter Canoy, Jenny Tran, Mariagrazia Zottoli, Rema Ramakrishnan, Abdelaali Hassaine, Shishir Rao, Yikuan Li, Gholamreza Salimi-Khorshidi, Robyn Norton, Kazem Rahimi

Published in: BMC Medicine | Issue 1/2021

Abstract

Background

Myocardial infarction (MI), stroke and diabetes share underlying risk factors and commonalities in clinical management. We examined if their combined impact on mortality is proportional, amplified or less than the expected risk separately of each disease and whether the excess risk is explained by their associated comorbidities.

Methods

Using large-scale electronic health records, we identified 2,007,731 eligible patients (51% women) and registered with general practices in the UK and extracted clinical information including diagnosis of myocardial infarction (MI), stroke, diabetes and 53 other long-term conditions before 2005 (study baseline). We used Cox regression to determine the risk of all-cause mortality with age as the underlying time variable and tested for excess risk due to interaction between cardiometabolic conditions.

Results

At baseline, the mean age was 51 years, and 7% (N = 145,910) have had a cardiometabolic condition. After a 7-year mean follow-up, 146,994 died. The sex-adjusted hazard ratios (HR) (95% confidence interval [CI]) of all-cause mortality by baseline disease status, compared to those without cardiometabolic disease, were MI = 1.51 (1.49–1.52), diabetes = 1.52 (1.51–1.53), stroke = 1.84 (1.82–1.86), MI and diabetes = 2.14 (2.11–2.17), MI and stroke = 2.35 (2.30–2.39), diabetes and stroke = 2.53 (2.50–2.57) and all three = 3.22 (3.15–3.30). Adjusting for other concurrent comorbidities attenuated these estimates, including the risk associated with having all three conditions (HR = 1.81 [95% CI 1.74–1.89]). Excess risks due to interaction between cardiometabolic conditions, particularly when all three conditions were present, were not significantly greater than expected from the individual disease effects.

Conclusion

Myocardial infarction, stroke and diabetes were associated with excess mortality, without evidence of any amplification of risk in people with all three diseases. The presence of other comorbidities substantially contributed to the excess mortality risks associated with cardiometabolic disease multimorbidity.

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Diederichs C, Berger K, Bartels DB. The measurement of multiple chronic diseases--a systematic review on existing multimorbidity indices. J Gerontol A Biol Sci Med Sci. 2011;66(3):301–11. https://doi.org/10.1093/gerona/glq208.CrossRefPubMed

The Academy of Medical Sciences. Multimorbidity: a priority for global health research: The Academy of Medical Sciences; 2018.

Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet. 2012;380(9836):37–43. https://doi.org/10.1016/S0140-6736(12)60240-2.CrossRefPubMed

Tran J, Norton R, Conrad N, Rahimian F, Canoy D, Nazarzadeh M, et al. Patterns and temporal trends of comorbidity among adult patients with incident cardiovascular disease in the UK between 2000 and 2014: a population-based cohort study. PLoS Med. 2018;15(3):e1002513. https://doi.org/10.1371/journal.pmed.1002513.CrossRefPubMedPubMedCentral

Global Burden of Metabolic Risk Factors for Chronic Diseases Collaboration. Cardiovascular disease, chronic kidney disease, and diabetes mortality burden of cardiometabolic risk factors from 1980 to 2010: a comparative risk assessment. Lancet Diabetes Endocrinol. 2014;2(8):634–47. https://doi.org/10.1016/S2213-8587(14)70102-0.CrossRef

World Health Organization: The top 10 causes of death https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death (2020). Accessed 2 Apr 2021.

Ostgren CJ, Lindblad U, Melander A, Rastam L. Survival in patients with type 2 diabetes in a Swedish community: Skaraborg hypertension and diabetes project. Diabetes Care. 2002;25(8):1297–302. https://doi.org/10.2337/diacare.25.8.1297.CrossRefPubMed

Hu G, Jousilahti P, Qiao Q, Katoh S, Tuomilehto J. Sex differences in cardiovascular and total mortality among diabetic and non-diabetic individuals with or without history of myocardial infarction. Diabetologia. 2005;48(5):856–61. https://doi.org/10.1007/s00125-005-1730-6.CrossRefPubMed

Lee TA, Shields AE, Vogeli C, Gibson TB, Woong-Sohn M, Marder WD, et al. Mortality rate in veterans with multiple chronic conditions. J Gen Intern Med. 2007;22(Suppl 3):403–7. https://doi.org/10.1007/s11606-007-0277-2.CrossRefPubMedPubMedCentral

10.

Glynn LG, Buckley B, Reddan D, Newell J, Hinde J, Dinneen SF, et al. Multimorbidity and risk among patients with established cardiovascular disease: a cohort study. Br J Gen Pract. 2008;58(552):488–94. https://doi.org/10.3399/bjgp08X319459.CrossRefPubMedPubMedCentral

11.

Schramm TK, Gislason GH, Kober L, Rasmussen S, Rasmussen JN, Abildstrom SZ, et al. Diabetes patients requiring glucose-lowering therapy and nondiabetics with a prior myocardial infarction carry the same cardiovascular risk: a population study of 3.3 million people. Circulation. 2008;117(15):1945–54. https://doi.org/10.1161/CIRCULATIONAHA.107.720847.CrossRefPubMed

12.

Caughey GE, Ramsay EN, Vitry AI, Gilbert AL, Luszcz MA, Ryan P, et al. Comorbid chronic diseases, discordant impact on mortality in older people: a 14-year longitudinal population study. J Epidemiol Community Health. 2010;64(12):1036–42. https://doi.org/10.1136/jech.2009.088260.CrossRefPubMed

13.

Schmidt M, Jacobsen JB, Lash TL, Botker HE, Sorensen HT. 25 year trends in first time hospitalisation for acute myocardial infarction, subsequent short and long term mortality, and the prognostic impact of sex and comorbidity: a Danish nationwide cohort study. BMJ. 2012;344(jan25 2):e356. https://doi.org/10.1136/bmj.e356.CrossRefPubMedPubMedCentral

14.

Schmidt M, Jacobsen JB, Johnsen SP, Botker HE, Sorensen HT. Eighteen-year trends in stroke mortality and the prognostic influence of comorbidity. Neurology. 2014;82(4):340–50. https://doi.org/10.1212/WNL.0000000000000062.CrossRefPubMed

15.

Emerging Risk Factors Collaboration, Di Angelantonio E, Kaptoge S, Wormser D, Willeit P, Butterworth AS, et al. Association of cardiometabolic multimorbidity with mortality. JAMA. 2015;314(1):52–60.CrossRef

16.

Rashid M, Kwok CS, Gale CP, Doherty P, Olier I, Sperrin M, et al. Impact of co-morbid burden on mortality in patients with coronary heart disease, heart failure, and cerebrovascular accident: a systematic review and meta-analysis. Eur Heart J Qual Care Clin Outcomes. 2017;3(1):20–36. https://doi.org/10.1093/ehjqcco/qcw025.CrossRefPubMed

17.

Kang YM, Cho YK, Lee SE, Park JY, Lee WJ, Kim YJ, et al. Cardiovascular diseases and life expectancy in adults with type 2 diabetes: a Korean national sample cohort study. J Clin Endocrinol Metab. 2017;102(9):3443–51. https://doi.org/10.1210/jc.2017-00643.CrossRefPubMed

18.

Hall M, Dondo TB, Yan AT, Mamas MA, Timmis AD, Deanfield JE, et al. Multimorbidity and survival for patients with acute myocardial infarction in England and Wales: latent class analysis of a nationwide population-based cohort. PLoS Med. 2018;15(3):e1002501. https://doi.org/10.1371/journal.pmed.1002501.CrossRefPubMedPubMedCentral

19.

Gallacher KI, McQueenie R, Nicholl B, Jani BD, Lee D, Mair FS. Risk factors and mortality associated with multimorbidity in people with stroke or transient ischaemic attack: a study of 8,751 UK Biobank participants. J Comorb. 2018;8(1):1–8. https://doi.org/10.15256/joc.2018.8.129.CrossRefPubMedPubMedCentral

20.

Zhang D, Tang X, Shen P, Si Y, Liu X, Xu Z, et al. Multimorbidity of cardiometabolic diseases: prevalence and risk for mortality from one million Chinese adults in a longitudinal cohort study. BMJ Open. 2019;9(3):e024476. https://doi.org/10.1136/bmjopen-2018-024476.CrossRefPubMedPubMedCentral

21.

Nunes BP, Flores TR, Mielke GI, Thume E, Facchini LA. Multimorbidity and mortality in older adults: a systematic review and meta-analysis. Arch Gerontol Geriatr. 2016;67:130–8. https://doi.org/10.1016/j.archger.2016.07.008.CrossRefPubMed

22.

Woo J, Leung J. Multi-morbidity, dependency, and frailty singly or in combination have different impact on health outcomes. Age (Dordr). 2014;36(2):923–31. https://doi.org/10.1007/s11357-013-9590-3.CrossRef

23.

St John PD, Tyas SL, Menec V, Tate R. Multimorbidity, disability, and mortality in community-dwelling older adults. Can Fam Physician. 2014;60(5):e272–80.PubMedPubMedCentral

24.

Jani BD, Hanlon P, Nicholl BI, McQueenie R, Gallacher KI, Lee D, et al. Relationship between multimorbidity, demographic factors and mortality: findings from the UK Biobank cohort. BMC Med. 2019;17(1):74. https://doi.org/10.1186/s12916-019-1305-x.CrossRefPubMedPubMedCentral

25.

Singh K, Patel SA, Biswas S, Shivashankar R, Kondal D, Ajay VS, et al. Multimorbidity in South Asian adults: prevalence, risk factors and mortality. J Public Health (Oxf). 2019;41(1):80–9. https://doi.org/10.1093/pubmed/fdy017.CrossRef

26.

Tancredi M, Rosengren A, Svensson AM, Kosiborod M, Pivodic A, Gudbjornsdottir S, et al. Excess mortality among persons with type 2 diabetes. N Engl J Med. 2015;373(18):1720–32. https://doi.org/10.1056/NEJMoa1504347.CrossRefPubMed

27.

Turner RC, Millns H, Neil HA, Stratton IM, Manley SE, Matthews DR, et al. Risk factors for coronary artery disease in non-insulin dependent diabetes mellitus: United Kingdom Prospective Diabetes Study (UKPDS: 23). BMJ. 1998;316(7134):823–8. https://doi.org/10.1136/bmj.316.7134.823.CrossRefPubMedPubMedCentral

28.

Clinical Practice Research Datalink https://www.cprd.com/ (2020). Accessed 21 Jun 2021.

29.

Herrett E, Gallagher AM, Bhaskaran K, Forbes H, Mathur R, van Staa T, et al. Data Resource Profile: Clinical Practice Research Datalink (CPRD). Int J Epidemiol. 2015;44(3):827–36. https://doi.org/10.1093/ije/dyv098.CrossRefPubMedPubMedCentral

30.

NHS Digital: Hospital Episode Statistics (HES) https://digital.nhs.uk/data-and-information/data-tools-and-services/data-services/hospital-episode-statistics (2020). Accessed 12 Apr 2021.

31.

NHS Digital: Linked HES-ONS mortality data https://digital.nhs.uk/data-and-information/data-tools-and-services/data-services/linked-hes-ons-mortality-data#ons-mortality-data (2020). Accessed 12 Apr 2021.

32.

Smith T, Noble M, Wright G, McLennan D, Plunkett E: The English indices of deprivation 2015 https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/464597/English_Indices_of_Deprivation_2015_-_Research_Report.pdf (2015). Accessed 8 Mar 2021.

33.

Herrett E, Thomas SL, Schoonen WM, Smeeth L, Hall AJ. Validation and validity of diagnoses in the General Practice Research Database: a systematic review. Br J Clin Pharmacol. 2010;69(1):4–14. https://doi.org/10.1111/j.1365-2125.2009.03537.x.CrossRefPubMedPubMedCentral

34.

Khan NF, Harrison SE, Rose PW. Validity of diagnostic coding within the General Practice Research Database: a systematic review. Br J Gen Pract. 2010;60(572):e128–36. https://doi.org/10.3399/bjgp10X483562.CrossRefPubMedPubMedCentral

35.

Lewis JD, Bilker WB, Weinstein RB, Strom BL. The relationship between time since registration and measured incidence rates in the General Practice Research Database. Pharmacoepidemiol Drug Saf. 2005;14(7):443–51. https://doi.org/10.1002/pds.1115.CrossRefPubMed

36.

Roland M. Linking physicians’ pay to the quality of care--a major experiment in the United Kingdom. N Engl J Med. 2004;351(14):1448–54. https://doi.org/10.1056/NEJMhpr041294.CrossRefPubMed

37.

Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–83. https://doi.org/10.1016/0021-9681(87)90171-8.CrossRefPubMed

38.

US Department of Health and Human Services Office of the Assistant Secretary for Health: HHS Initiative on multiple chronic conditions https://www.hhs.gov/ash/about-ash/multiple-chronic-conditions/index.html (2015). Accessed 18 Feb 2020.

39.

Benson T. The history of the Read codes: the inaugural James Read Memorial Lecture. J Innov Health Inform. 2011;2011(3):173–82. https://doi.org/10.14236/jhi.v19i3.811.CrossRef

40.

Rothman KJ, Greenland S, Lash TL. Modern epidemiology. In: Modern Epidemiology. 3rd ed. Philadelphia, PA: Lippincott Williams & Wilkins; 2011.

41.

VanderWeele TJ. Sufficient cause interactions and statistical interactions. Epidemiology. 2009;20(1):6–13. https://doi.org/10.1097/EDE.0b013e31818f69e7.CrossRefPubMed

42.

de Mutsert R, Jager KJ, Zoccali C, Dekker FW. The effect of joint exposures: examining the presence of interaction. Kidney Int. 2009;75(7):677–81. https://doi.org/10.1038/ki.2008.645.CrossRefPubMed

43.

Core R. Team: R: a language and environment for statistical computing. In. Vienna, Austria: R Foundation for Statistical. Computing. 2017.

44.

Plummer M. Improved estimates of floating absolute risk. Stat Med. 2004;23(1):93–104. https://doi.org/10.1002/sim.1485.CrossRefPubMed

45.

Lagu T, Weiner MG, Hollenbeak CS, Eachus S, Roberts CS, Schwartz JS, et al. The impact of concordant and discordant conditions on the quality of care for hyperlipidemia. J Gen Intern Med. 2008;23(8):1208–13. https://doi.org/10.1007/s11606-008-0647-4.CrossRefPubMedPubMedCentral

46.

Magnan EM, Palta M, Johnson HM, Bartels CM, Schumacher JR, Smith MA. The impact of a patient’s concordant and discordant chronic conditions on diabetes care quality measures. J Diabetes Complicat. 2015;29(2):288–94. https://doi.org/10.1016/j.jdiacomp.2014.10.003.CrossRef

47.

Min LC, Wenger NS, Fung C, Chang JT, Ganz DA, Higashi T, et al. Multimorbidity is associated with better quality of care among vulnerable elders. Med Care. 2007;45(6):480–8. https://doi.org/10.1097/MLR.0b013e318030fff9.CrossRefPubMed

48.

Redelmeier DA, Tan SH, Booth GL. The treatment of unrelated disorders in patients with chronic medical diseases. N Engl J Med. 1998;338(21):1516–20. https://doi.org/10.1056/NEJM199805213382106.CrossRefPubMed

49.

Boyd CM, Darer J, Boult C, Fried LP, Boult L, Wu AW. Clinical practice guidelines and quality of care for older patients with multiple comorbid diseases: implications for pay for performance. JAMA. 2005;294(6):716–24. https://doi.org/10.1001/jama.294.6.716.CrossRefPubMed

50.

Piette JD, Kerr EA. The impact of comorbid chronic conditions on diabetes care. Diabetes Care. 2006;29(3):725–31. https://doi.org/10.2337/diacare.29.03.06.dc05-2078.CrossRefPubMed

51.

Panagioti M, Blakeman T, Hann M, Bower P. Patient-reported safety incidents in older patients with long-term conditions: a large cross-sectional study. BMJ Open. 2017;7(5):e013524. https://doi.org/10.1136/bmjopen-2016-013524.CrossRefPubMedPubMedCentral

Title: Association between cardiometabolic disease multimorbidity and all-cause mortality in 2 million women and men registered in UK general practices
Authors: Dexter Canoy
Jenny Tran
Mariagrazia Zottoli
Rema Ramakrishnan
Abdelaali Hassaine
Shishir Rao
Yikuan Li
Gholamreza Salimi-Khorshidi
Robyn Norton
Kazem Rahimi
Publication date: 01-12-2021
Publisher: BioMed Central
Keywords: Stroke
Myocardial Infarction
Published in: BMC Medicine / Issue 1/2021
Electronic ISSN: 1741-7015
DOI: https://doi.org/10.1186/s12916-021-02126-x

At a glance: The STEP trials

Springer Medicine

Association between cardiometabolic disease multimorbidity and all-cause mortality in 2 million women and men registered in UK general practices

Abstract

Background

Methods

Results

Conclusion

At a glance: The STEP trials

Springer Medicine

Abstract

Background

Methods

Results

Conclusion

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