Multimorbidity, mortality, and HbA1c in type 2 diabetes: A cohort study with UK and Taiwanese cohorts

Autoři: Jason I. Chiang aff001;  Peter Hanlon aff002;  Tsai-Chung Li aff003;  Bhautesh Dinesh Jani aff002;  Jo-Anne Manski-Nankervis aff001;  John Furler aff001;  Cheng-Chieh Lin aff004;  Shing-Yu Yang aff003;  Barbara I. Nicholl aff002;  Sharmala Thuraisingam aff001;  Frances S. Mair aff002
Působiště autorů: Department of General Practice, University of Melbourne, Melbourne, Australia aff001;  General Practice and Primary Care, Institute of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom aff002;  Department of Public Health, College of Public Health, China Medical University, Taichung, Taiwan aff003;  Department of Family Medicine, China Medical University Hospital, Taichung, Taiwan aff004
Vyšlo v časopise: Multimorbidity, mortality, and HbA1c in type 2 diabetes: A cohort study with UK and Taiwanese cohorts. PLoS Med 17(5): e32767. doi:10.1371/journal.pmed.1003094
Kategorie: Research Article
doi: 10.1371/journal.pmed.1003094



There is emerging interest in multimorbidity in type 2 diabetes (T2D), which can be either concordant (T2D related) or discordant (unrelated), as a way of understanding the burden of disease in T2D. Current diabetes guidelines acknowledge the complex nature of multimorbidity, the management of which should be based on the patient’s individual clinical needs and comorbidities. However, although associations between multimorbidity, glycated haemoglobin (HbA1c), and mortality in people with T2D have been studied to some extent, significant gaps remain, particularly regarding different patterns of multimorbidity, including concordant and discordant conditions. This study explores associations between multimorbidity (total condition counts/concordant/discordant/different combinations of conditions), baseline HbA1c, and all-cause mortality in T2D.

Methods and findings

We studied two longitudinal cohorts of people with T2D using the UK Biobank (n = 20,569) and the Taiwan National Diabetes Care Management Program (NDCMP) (n = 59,657). The number of conditions in addition to T2D was used to quantify total multimorbidity, concordant, and discordant counts, and the effects of different combinations of conditions were also studied. Outcomes of interest were baseline HbA1c and all-cause mortality. For the UK Biobank and Taiwan NDCMP, mean (SD) ages were 60.2 (6.8) years and 60.8 (11.3) years; 7,579 (36.8%) and 31,339 (52.5%) were female; body mass index (BMI) medians (IQR) were 30.8 (27.7, 34.8) kg/m2 and 25.6 (23.5, 28.7) kg/m2; and 2,197 (10.8%) and 9,423 (15.8) were current smokers, respectively. Increasing total and discordant multimorbidity counts were associated with lower HbA1c and increased mortality in both datasets. In Taiwan NDCMP, for those with four or more additional conditions compared with T2D only, the mean difference (95% CI) in HbA1c was −0.82% (−0.88, −0.76) p < 0.001. In UK Biobank, hazard ratios (HRs) (95% CI) for all-cause mortality in people with T2D and one, two, three, and four or more additional conditions compared with those without comorbidity were 1.20 (0.91–1.56) p < 0.001, 1.75 (1.35–2.27) p < 0.001, 2.17 (1.67–2.81) p < 0.001, and 3.14 (2.43–4.03) p < 0.001, respectively. Both concordant/discordant conditions were significantly associated with mortality; however, HRs were largest for concordant conditions. Those with four or more concordant conditions had >5 times the mortality (5.83 [4.28–7.93] p <0.001). HRs for NDCMP were similar to those from UK Biobank for all multimorbidity counts. For those with two conditions in addition to T2D, cardiovascular diseases featured in 18 of the top 20 combinations most highly associated with mortality in UK Biobank and 12 of the top combinations in the Taiwan NDCMP. In UK Biobank, a combination of coronary heart disease and heart failure in addition to T2D had the largest effect size on mortality, with a HR (95% CI) of 4.37 (3.59–5.32) p < 0.001, whereas in the Taiwan NDCMP, a combination of painful conditions and alcohol problems had the largest effect size on mortality, with an HR (95% CI) of 4.02 (3.08–5.23) p < 0.001. One limitation to note is that we were unable to model for changes in multimorbidity during our study period.


Multimorbidity patterns associated with the highest mortality differed between UK Biobank (a population predominantly comprising people of European descent) and the Taiwan NDCMP, a predominantly ethnic Chinese population. Future research should explore the mechanisms underpinning the observed relationship between increasing multimorbidity count and reduced HbA1c alongside increased mortality in people with T2D and further examine the implications of different patterns of multimorbidity across different ethnic groups. Better understanding of these issues, especially effects of condition type, will enable more effective personalisation of care.

Klíčová slova:

Alcohols – Death rates – diabetes mellitus – HbA1c – Chronic liver disease – Chronic obstructive pulmonary disease – Taiwan – Type 2 diabetes


1. 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. Epub 2019/04/11. doi: 10.1186/s12916-019-1305-x 30967141; PubMed Central PMCID: PMC6456941.

2. Australian Bureau of Statistics. National Health Survey: First Result, 2014–15. Canberra, Australia: Australian Bureau of Statistics; 2015.

3. Mair FS, May CR. Thinking about the burden of treatment. Bmj. 2014;349:g6680. doi: 10.1136/bmj.g6680 25385748.

4. Harris MF, Dennis S, Pillay M. Multimorbidity: Negotiating priorities and making progress. AFP. 2013;42(12):850–4. 24324984

5. Piette JD, Kerr EA. The impact of comorbid chronic conditions on diabetes care. Diabetes care. 2006;29(3):725–31. doi: 10.2337/diacare.29.03.06.dc05-2078 16505540.

6. UK Prospective Diabetes Study Group. Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). UK Prospective Diabetes Study (UKPDS) Group. Lancet. 1998;352(9131):837–53. Epub 1998/09/22. 9742976.

7. Chiang JI, Jani BD, Mair FS, Nicholl BI, Furler J, O'Neal D, et al. Associations between multimorbidity, all-cause mortality and glycaemia in people with type 2 diabetes: A systematic review. PLoS ONE. 2018;13(12):e0209585. Epub 2018/12/27. doi: 10.1371/journal.pone.0209585 30586451; PubMed Central PMCID: PMC6306267.

8. Lynch CP, Gebregziabher M, Zhao Y, Hunt KJ, Egede LE. Impact of medical and psychiatric multi-morbidity on mortality in diabetes: emerging evidence. BMC endocrine disorders. 2014;14:68. doi: 10.1186/1472-6823-14-68 25138206; PubMed Central PMCID: PMC4144689.

9. Walker RJ, Smalls BL, Egede LE. Social determinants of health in adults with type 2 diabetes—Contribution of mutable and immutable factors. Diabetes Research & Clinical Practice. 2015;110(2):193–201. doi: 10.1016/j.diabres.2015.09.007 26411692.

10. Monami M, Lambertucci L, Lamanna C, Lotti E, Marsili A, Masotti G, et al. Are comorbidity indices useful in predicting all-cause mortality in Type 2 diabetic patients? Comparison between Charlson index and disease count. Aging-Clinical & Experimental Research. 2007;19(6):492–6. doi: 10.1007/bf03324736 18172372.

11. Sudlow C, Gallacher J, Allen N, Beral V, Burton P, Danesh J, et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 2015;12(3):e1001779. doi: 10.1371/journal.pmed.1001779 25826379; PubMed Central PMCID: PMC4380465.

12. Chang RE, Lin SP, Aron DC. A pay-for-performance program in Taiwan improved care for some diabetes patients, but doctors may have excluded sicker ones. Health Aff (Millwood). 2012;31(1):93–102. Epub 2012/01/11. doi: 10.1377/hlthaff.2010.0402 22232099.

13. Eastwood SV, Mathur R, Atkinson M, Brophy S, Sudlow C, Flaig R, et al. Algorithms for the Capture and Adjudication of Prevalent and Incident Diabetes in UK Biobank. PLoS ONE. 2016;11(9):e0162388. doi: 10.1371/journal.pone.0162388 27631769; PubMed Central PMCID: PMC5025160.

14. Adams J, Ryan V, White M. How accurate are Townsend Deprivation Scores as predictors of self-reported health? A comparison with individual level data. Journal of public health. 2005;27(1):101–6. doi: 10.1093/pubmed/fdh193 15564276.

15. Holman R, Paul SK, Bethel MA, Matthews DR, Neil HAW. 10-year follow-up of intensive glucose control in type 2 diabetes. New England Journal of Medicine. 2008;359:1577–89. doi: 10.1056/NEJMoa0806470 18784090

16. Gerstein HC, Miller ME, Byington RP, Goff DC Jr., Bigger JT, Buse JB, et al. Effects of intensive glucose lowering in type 2 diabetes. The New England journal of medicine. 2008;358(24):2545–59. Epub 2008/06/10. doi: 10.1056/NEJMoa0802743 18539917; PubMed Central PMCID: PMC4551392.

17. Abdelhafiz AH, Sinclair AJ. Low HbA1c and Increased Mortality Risk-is Frailty a Confounding Factor? Aging Dis. 2015;6(4):262–70. Epub 2015/08/04. doi: 10.14336/AD.2014.1022 26236548; PubMed Central PMCID: PMC4509475.

18. Higashi T, Wenger NS, Adams JL, Fung C, Roland M, McGlynn EA, et al. Relationship between number of medical conditions and quality of care. The New England journal of medicine. 2007;356(24):2496–504. doi: 10.1056/NEJMsa066253 17568030.

19. Clark NG, Pawlson G. Change in HbA1c as a Measure of Quality of Diabetes Care. Diabetes care. 2006;29(5):1184. doi: 10.2337/dc06-0096

20. 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. doi: 10.1001/jama.294.6.716 16091574.

21. Jaen CR, Stange KC, Nutting PA. Competing demands of primary care: a model for the delivery of clinical preventive services. The Journal of family practice. 1994;38(2):166–71. 8308509.

22. Di Angelantonio E, Kaptoge S, Wormser D, Willeit P, Butterworth AS, Bansal N, et al. Association of Cardiometabolic Multimorbidity With Mortality. JAMA: Journal of the American Medical Association. 2015;314(1):52–60. doi: 10.1001/jama.2015.7008 26151266.

23. Tromp J, Tay WT, Ouwerkerk W, Teng T-HK, Yap J, MacDonald MR, et al. Multimorbidity in patients with heart failure from 11 Asian regions: A prospective cohort study using the ASIAN-HF registry. PLoS Med. 2018;15(3):e1002541. doi: 10.1371/journal.pmed.1002541 29584721

24. National Institute for Health and Care Excellence. Type 2 diabetes in adults: management. NICE Guideline (NG28). United Kingdom: NICE; 2017.

25. Hoffmann T, Jansen J, Glasziou P. The importance and challenges of shared decision making in older people with multimorbidity. PLoS Med. 2018;15(3):e1002530. doi: 10.1371/journal.pmed.1002530 29534067

26. Fry A, Littlejohns T, Sudlow C, Doherty N, Allen N. OP41 The representativeness of the UK Biobank cohort on a range of sociodemographic, physical, lifestyle and health-related characteristics. Journal of Epidemiology and Community Health. 2016;70(Suppl 1):A26–A. doi: 10.1136/jech-2016-208064.41

27. Ferrari AJ, Somerville AJ, Baxter AJ, Norman R, Patten SB, Vos T, et al. Global variation in the prevalence and incidence of major depressive disorder: a systematic review of the epidemiological literature. Psychological Medicine. 2013;43(3):471–81. Epub 2012/07/25. doi: 10.1017/S0033291712001511 22831756

28. Gopalkrishnan N. Cultural Diversity and Mental Health: Considerations for Policy and Practice. Front Public Health. 2018;6:179. doi: 10.3389/fpubh.2018.00179 29971226.

29. Holt RI, de Groot M, Golden SH. Diabetes and depression. Curr Diab Rep. 2014;14(6):491. Epub 2014/04/20. doi: 10.1007/s11892-014-0491-3 24743941; PubMed Central PMCID: PMC4476048.

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