Disparities in glycaemic control, monitoring, and treatment of type 2 diabetes in England: A retrospective cohort analysis
Autoři:
Martin B. Whyte aff001; William Hinton aff001; Andrew McGovern aff001; Jeremy van Vlymen aff001; Filipa Ferreira aff001; Silvio Calderara aff002; Julie Mount aff002; Neil Munro aff001; Simon de Lusignan aff001
Působiště autorů:
Department of Clinical and Experimental Medicine, University of Surrey, Guildford, United Kingdom
aff001; Eli Lilly, Basingstoke, United Kingdom
aff002
Vyšlo v časopise:
Disparities in glycaemic control, monitoring, and treatment of type 2 diabetes in England: A retrospective cohort analysis. PLoS Med 16(10): e32767. doi:10.1371/journal.pmed.1002942
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pmed.1002942
Souhrn
Background
Disparities in type 2 diabetes (T2D) care provision and clinical outcomes have been reported in the last 2 decades in the UK. Since then, a number of initiatives have attempted to address this imbalance. The aim was to evaluate contemporary data as to whether disparities exist in glycaemic control, monitoring, and prescribing in people with T2D.
Methods and findings
A T2D cohort was identified from the Royal College of General Practitioners Research and Surveillance Centre dataset: a nationally representative sample of 164 primary care practices (general practices) across England. Diabetes healthcare provision and glucose-lowering medication use between 1 January 2012 and 31 December 2016 were studied. Healthcare provision included annual HbA1c, renal function (estimated glomerular filtration rate [eGFR]), blood pressure (BP), retinopathy, and neuropathy testing. Variables potentially associated with disparity outcomes were assessed using mixed effects logistic and linear regression, adjusted for age, sex, ethnicity, and socioeconomic status (SES) using the Index of Multiple Deprivation (IMD), and nested using random effects within general practices. Ethnicity was defined using the Office for National Statistics ethnicity categories: White, Mixed, Asian, Black, and Other (including Arab people and other groups not classified elsewhere). From the primary care adult population (n = 1,238,909), we identified a cohort of 84,452 (5.29%) adults with T2D. The mean age of people with T2D in the included cohort at 31 December 2016 was 68.7 ± 12.6 years; 21,656 (43.9%) were female. The mean body mass index was 30.7 ± SD 6.4 kg/m2. The most deprived groups (IMD quintiles 1 and 2) showed poorer HbA1c than the least deprived (IMD quintile 5). People of Black ethnicity had worse HbA1c than those of White ethnicity. Asian individuals were less likely than White individuals to be prescribed insulin (odds ratio [OR] 0.86, 95% CI 0.79–0.95; p < 0.01), sodium-glucose cotransporter-2 (SGLT2) inhibitors (OR 0.68, 95% CI 0.58–0.79; p < 0.001), and glucagon-like peptide-1 (GLP-1) agonists (OR 0.37, 95% CI 0.31–0.44; p < 0.001). Black individuals were less likely than White individuals to be prescribed SGLT2 inhibitors (OR 0.50, 95% CI 0.39–0.65; p < 0.001) and GLP-1 agonists (OR 0.45, 95% CI 0.35–0.57; p < 0.001). Individuals in IMD quintile 5 were more likely than those in the other IMD quintiles to have annual testing for HbA1c, BP, eGFR, retinopathy, and neuropathy. Black individuals were less likely than White individuals to have annual testing for HbA1c (OR 0.89, 95% CI 0.79–0.99; p = 0.04) and retinopathy (OR 0.82, 95% CI 0.70–0.96; p = 0.011). Asian individuals were more likely than White individuals to have monitoring for HbA1c (OR 1.10, 95% CI 1.01–1.20; p = 0.023) and eGFR (OR 1.09, 95% CI 1.00–1.19; p = 0.048), but less likely for retinopathy (OR 0.88, 95% CI 0.79–0.97; p = 0.01) and neuropathy (OR 0.88, 95% CI 0.80–0.97; p = 0.01). The study is limited by the nature of being observational and defined using retrospectively collected data. Disparities in diabetes care may show regional variation, which was not part of this evaluation.
Conclusions
Our findings suggest that disparity in glycaemic control, diabetes-related monitoring, and prescription of newer therapies remains a challenge in diabetes care. Both SES and ethnicity were important determinants of inequality. Disparities in glycaemic control and other areas of care may lead to higher rates of complications and adverse outcomes for some groups.
Klíčová slova:
Ethnic epidemiology – Ethnicities – Neuropathy – Primary care – Socioeconomic aspects of health
Zdroje
1. Public Health England. Diabetes prevalence model. London: Public Health England; 2016 [cited 2019 Jul 16]. Available from: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/612306/Diabetesprevalencemodelbriefing.pdf.
2. UK government. Population of England and Wales. London: UK government; 2018 [2019 Jul 16]. Available from: https://www.ethnicity-facts-figures.service.gov.uk/uk-population-by-ethnicity/national-and-regional-populations/population-of-england-and-wales/1.4.
3. Agardh E, Allebeck P, Hallqvist J, Moradi T, Sidorchuk A. Type 2 diabetes incidence and socio-economic position: a systematic review and meta-analysis. Int J Epidemiol. 2011;40(3):804–18. doi: 10.1093/ije/dyr029 21335614
4. Moody A. Adult anthropometric measures, overweight and obesity. In: Craig R, Mindell J, eds. Health survey for England 2013. Leeds: Health and Social Care Information Centre; 2014.
5. Moody A, Cowley G, Ng Fat L, Mindell JS. Social inequalities in prevalence of diagnosed and undiagnosed diabetes and impaired glucose regulation in participants in the Health Surveys for England series. BMJ Open. 2016;6(2):e010155. doi: 10.1136/bmjopen-2015-010155 26857106
6. American Diabetes Association. 1. Promoting health and reducing disparities in populations. Diabetes Care. 2017;40(Suppl 1):S6–10. doi: 10.2337/dc17-S004 27979888
7. Emerging Risk Factors Collaboration, Sarwar N, Gao P, Seshasai SR, Gobin R, Kaptoge S, et al. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies. Lancet. 2010;375(9733):2215–22. doi: 10.1016/S0140-6736(10)60484-9 20609967
8. Liew G, Michaelides M, Bunce C. A comparison of the causes of blindness certifications in England and Wales in working age adults (16–64 years), 1999–2000 with 2009–2010. BMJ Open. 2014;4(2):e004015. doi: 10.1136/bmjopen-2013-004015 24525390
9. UK Renal Registry. UK Renal Registry 21st annual report. Bristol: UK Renal Registry; 2017 [cited 2019 Aug 6]. Available from: https://www.renalreg.org/reports/data_to_end_2017/.
10. Hex N, Bartlett C, Wright D, Taylor M, Varley D. Estimating the current and future costs of type 1 and type 2 diabetes in the UK, including direct health costs and indirect societal and productivity costs. Diabet Med. 2012;29(7):855–62. doi: 10.1111/j.1464-5491.2012.03698.x 22537247
11. Liebl A, Khunti K, Orozco-Beltran D, Yale JF. Health economic evaluation of type 2 diabetes mellitus: a clinical practice focused review. Clin Med Insights Endocrinol Diabetes. 2015;8:13–9. doi: 10.4137/CMED.S20906 25861233
12. James GD, Baker P, Badrick E, Mathur R, Hull S, Robson J. Ethnic and social disparity in glycaemic control in type 2 diabetes; cohort study in general practice 2004–9. J R Soc Med. 2012;105(7):300–8. doi: 10.1258/jrsm.2012.110289 22396467
13. James GD, Baker P, Badrick E, Mathur R, Hull S, Robson J. Type 2 diabetes: a cohort study of treatment, ethnic and social group influences on glycated haemoglobin. BMJ Open. 2012;2(5):e001477. doi: 10.1136/bmjopen-2012-001477 23087015
14. Negandhi PH, Ghouri N, Colhoun HM, Fischbacher CM, Lindsay RS, McKnight JA, et al. Ethnic differences in glycaemic control in people with type 2 diabetes mellitus living in Scotland. PLoS ONE. 2013;8(12):e83292. doi: 10.1371/journal.pone.0083292 24358273
15. Xiao M, O’Neill C. Detection and management of diabetes in England: results from the Health Survey for England. Diabetes Ther. 2017;8(5):1163–74. doi: 10.1007/s13300-017-0300-5 28948483
16. Department of Health and Social Security. Inequalities in health: report of a research working group. London: Department of Health and Social Security; 1980.
17. Department of Health. Tackling health inequalities: a programme for action. London: Department of Health; 2003.
18. 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. doi: 10.1056/NEJMhpr041294 15459308
19. Alshamsan R, Majeed A, Ashworth M, Car J, Millett C. Impact of pay for performance on inequalities in health care: systematic review. J Health Serv Res Policy. 2010;15(3):178–84. doi: 10.1258/jhsrp.2010.009113 20555042
20. Dixon A KA, Wallace A, Peckham S, Boyce T, Gillam S. Impact of Quality and Outcomes Framework on health inequalities. London: King’s Fund; 2011.
21. Guthrie B, Emslie-Smith A, Morris AD. Which people with type 2 diabetes achieve good control of intermediate outcomes? Population database study in a UK region. Diabet Med. 2009;26(12):1269–76. doi: 10.1111/j.1464-5491.2009.02837.x 20002480
22. Lowrie R, McConnachie A, Williamson AE, Kontopantelis E, Forrest M, Lannigan N, et al. Incentivised chronic disease management and the inverse equity hypothesis: findings from a longitudinal analysis of Scottish primary care practice-level data. BMC Med. 2017;15(1):77. doi: 10.1186/s12916-017-0833-5 28395660
23. Alshamsan R, Lee JT, Majeed A, Netuveli G, Millett C. Effect of a UK pay-for-performance program on ethnic disparities in diabetes outcomes: interrupted time series analysis. Ann Fam Med. 2012;10(3):228–34. doi: 10.1370/afm.1335 22585887
24. Dalton AR, Alshamsan R, Majeed A, Millett C. Exclusion of patients from quality measurement of diabetes care in the UK pay-for-performance programme. Diabet Med. 2011;28(5):525–31. doi: 10.1111/j.1464-5491.2011.03251.x 21294767
25. Hamilton FL, Bottle A, Vamos EP, Curcin V, Ng A, Molokhia M, et al. Impact of a pay-for-performance incentive scheme on age, sex, and socioeconomic disparities in diabetes management in UK primary care. J Ambul Care Manage. 2010;33(4):336–49. doi: 10.1097/JAC.0b013e3181f68f1d 20838113
26. Millett C, Netuveli G, Saxena S, Majeed A. Impact of pay for performance on ethnic disparities in intermediate outcomes for diabetes: a longitudinal study. Diabetes Care. 2009;32(3):404–9. doi: 10.2337/dc08-0912 19073759
27. Fleetcroft R, Asaria M, Ali S, Cookson R. Outcomes and inequalities in diabetes from 2004/2005 to 2011/2012: English longitudinal study. Br J Gen Pract. 2017;67(654):e1–9. doi: 10.3399/bjgp16X688381 27919938
28. Health and Social Care Act 2012. UK Public General Act 2012 c.7. 2012 Mar 27.
29. NHS England. Action plan health inequalities. London: NHS England; 2018 [cited 2019 Mar 12]. Available from: https://www.england.nhs.uk/wp-content/uploads/2018/05/07a-pb-24-05-2018-health-inequalities-action-plan.pdf.
30. Currie J, Guzman Castillo M, Adekanmbi V, Barr B, O’Flaherty M. Evaluating effects of recent changes in NHS resource allocation policy on inequalities in amenable mortality in England, 2007–2014: time-series analysis. J Epidemiol Community Health. 2019;73(2):162–7. doi: 10.1136/jech-2018-211141 30470698
31. Nishino Y, Gilmour S, Shibuya K. Inequality in diabetes-related hospital admissions in England by socioeconomic deprivation and ethnicity: facility-based cross-sectional analysis. PLoS ONE. 2015;10(2):e0116689. doi: 10.1371/journal.pone.0116689 25705895
32. Hippisley-Cox J, O’Hanlon S, Coupland C. Association of deprivation, ethnicity, and sex with quality indicators for diabetes: population based survey of 53,000 patients in primary care. BMJ. 2004;329(7477):1267–9. doi: 10.1136/bmj.38279.588125.7C 15548561
33. Correa A, Hinton W, McGovern A, van Vlymen J, Yonova I, Jones S, et al. Royal College of General Practitioners Research and Surveillance Centre (RCGP RSC) sentinel network: a cohort profile. BMJ Open. 2016;6(4):e011092. doi: 10.1136/bmjopen-2016-011092 27098827
34. McGovern A, Hinton W, Calderara S, Munro N, Whyte M, de Lusignan S. A class comparison of medication persistence in people with type 2 diabetes: a retrospective observational study. Diabetes Ther. 2018;9(1):229–42. doi: 10.1007/s13300-017-0361-5 29302934
35. McGovern A, Hinton W, Correa A, Munro N, Whyte M, de Lusignan S. Real-world evidence studies into treatment adherence, thresholds for intervention and disparities in treatment in people with type 2 diabetes in the UK. BMJ Open. 2016;6(11):e012801. doi: 10.1136/bmjopen-2016-012801 27884846
36. de Lusignan S, Khunti K, Belsey J, Hattersley A, van Vlymen J, Gallagher H, et al. A method of identifying and correcting miscoding, misclassification and misdiagnosis in diabetes: a pilot and validation study of routinely collected data. Diabet Med. 2010;27(2):203–9. doi: 10.1111/j.1464-5491.2009.02917.x 20546265
37. de Lusignan S, Sadek N, Mulnier H, Tahir A, Russell-Jones D, Khunti K. Miscoding, misclassification and misdiagnosis of diabetes in primary care. Diabet Med. 2012;29(2):181–9. doi: 10.1111/j.1464-5491.2011.03419.x 21883428
38. Office for National Statistics. Ethnic group, national identity and religion. London: Office for National Statistics; 2018 [cited 2018 Dec 17]. Available from: https://www.ons.gov.uk/methodology/classificationsandstandards/measuringequality/ethnicgroupnationalidentityandreligion.
39. Tippu Z, Correa A, Liyanage H, Burleigh D, McGovern A, Van Vlymen J, et al. Ethnicity recording in primary care computerised medical record systems: an ontological approach. J Innov Health Inform. 2017;23(4):920. doi: 10.14236/jhi.v23i4.920 28346128
40. Grintsova O, Maier W, Mielck A. Inequalities in health care among patients with type 2 diabetes by individual socio-economic status (SES) and regional deprivation: a systematic literature review. Int J Equity Health. 2014;13:43. doi: 10.1186/1475-9276-13-43 24889694
41. Heald AH, Livingston M, Malipatil N, Becher M, Craig J, Stedman M, et al. Improving type 2 diabetes mellitus glycaemic outcomes is possible without spending more on medication: lessons from the UK National Diabetes Audit. Diabetes Obes Metab. 2018;20(1):185–94. doi: 10.1111/dom.13067 28730750
42. Wright CE, Yeung S, Knowles H, Woodhouse A, Barron E, Evans S. Factors influencing variation in participation in the National Diabetes Audit and the impact on the Quality and Outcomes Framework indicators of diabetes care management. BMJ Open Diabetes Res Care. 2018;6(1):e000554. doi: 10.1136/bmjdrc-2018-000554 30397490
43. Victora CG, Vaughan JP, Barros FC, Silva AC, Tomasi E. Explaining trends in inequities: evidence from Brazilian child health studies. Lancet. 2000;356(9235):1093–8. doi: 10.1016/S0140-6736(00)02741-0 11009159
44. Downing A, Rudge G, Cheng Y, Tu YK, Keen J, Gilthorpe MS. Do the UK government’s new Quality and Outcomes Framework (QOF) scores adequately measure primary care performance? A cross-sectional survey of routine healthcare data. BMC Health Serv Res. 2007;7:166. doi: 10.1186/1472-6963-7-166 17941984
45. Doran T, Fullwood C, Kontopantelis E, Reeves D. Effect of financial incentives on inequalities in the delivery of primary clinical care in England: analysis of clinical activity indicators for the quality and outcomes framework. Lancet. 2008;372(9640):728–36. doi: 10.1016/S0140-6736(08)61123-X 18701159
46. Brown MJ. Hypertension and ethnic group. BMJ. 2006;332(7545):833–6. doi: 10.1136/bmj.332.7545.833 16601044
47. Schofield P, Saka O, Ashworth M. Ethnic differences in blood pressure monitoring and control in south east London. Br J Gen Pract. 2011;61(585):e190–6.
48. Sivaprasad S, Gupta B, Gulliford MC, Dodhia H, Mohamed M, Nagi D, et al. Ethnic variations in the prevalence of diabetic retinopathy in people with diabetes attending screening in the United Kingdom (DRIVE UK). PLoS ONE. 2012;7(3):e32182. doi: 10.1371/journal.pone.0032182 22412857
49. Strutton R, Du Chemin A, Stratton IM, Forster A. System-level and patient-level explanations for nonattendance at diabetic retinopathy screening in Sutton and Merton (London, UK): a qualitative analysis of a service evaluation. BMJ Open. 2016;6:e010952. doi: 10.1136/bmjopen-2015-010952 27194319
50. Abbott CA, Malik RA, van Ross ER, Kulkarni J, Boulton AJ. Prevalence and characteristics of painful diabetic neuropathy in a large community-based diabetic population in the U.K. Diabetes Care. 2011;34(10):2220–4. doi: 10.2337/dc11-1108 21852677
51. Marso SP, Daniels GH, Brown-Frandsen K, Kristensen P, Mann JF, Nauck MA, et al. Liraglutide and cardiovascular outcomes in type 2 diabetes. N Engl J Med. 2016;375(4):311–22. doi: 10.1056/NEJMoa1603827 27295427
52. Neal B, Perkovic V, Mahaffey KW, de Zeeuw D, Fulcher G, Erondu N, et al. Canagliflozin and cardiovascular and renal events in type 2 diabetes. N Engl J Med. 2017;377(7):644–57. doi: 10.1056/NEJMoa1611925 28605608
53. Wiviott SD, Raz I, Bonaca MP, Mosenzon O, Kato ET, Cahn A, et al. Dapagliflozin and cardiovascular outcomes in type 2 diabetes. N Engl J Med. 2019;380(4):347–57. doi: 10.1056/NEJMoa1812389 30415602
54. Zinman B, Wanner C, Lachin JM, Fitchett D, Bluhmki E, Hantel S, et al. Empagliflozin, cardiovascular outcomes, and mortality in type 2 diabetes. N Engl J Med. 2015;373(22):2117–28. doi: 10.1056/NEJMoa1504720 26378978
55. Hippisley-Cox J, Coupland C. Development and validation of risk prediction equations to estimate future risk of blindness and lower limb amputation in patients with diabetes: cohort study. BMJ. 2015;351:h5441. doi: 10.1136/bmj.h5441 26560308
56. NHS England. Action on diabetes. London: NHS England; 2014.
Štítky
Interní lékařstvíČlánek vyšel v časopise
PLOS Medicine
2019 Číslo 10
- Příznivý vliv Armolipidu Plus na hladinu cholesterolu a zánětlivé parametry u pacientů s chronickým subklinickým zánětem
- Léčba bolesti u seniorů
- Co lze v terapii hypertenze očekávat od přidání perindoprilu k bisoprololu?
- Nefarmakologická léčba dyslipidémií
- Flexofytol® – přírodní revoluce v boji proti osteoartróze kloubů
Nejčtenější v tomto čísle
- Characterization of Parkinson’s disease using blood-based biomarkers: A multicohort proteomic analysis
- Preconception diabetes mellitus and adverse pregnancy outcomes in over 6.4 million women: A population-based cohort study in China
- Association of preterm birth with lipid disorders in early adulthood: A Swedish cohort study
- mHealth intervention “ImTeCHO” to improve delivery of maternal, neonatal, and child care services—A cluster-randomized trial in tribal areas of Gujarat, India