title: Association of cardiac and non-cardiac chronic disease comorbidity on glycaemic control in a multi-ethnic population with type 1 and type 2 diabetes.
abstract: OBJECTIVE
  To determine the prevalence of chronic disease comorbidity in south Asians (SAs) and white Europeans (WEs) with diabetes and to quantify the relationship of cardiac disease comorbidity (CDCM) and non-cardiac disease comorbidity (NCCM) to glycaemic control in SAs and WEs with type 1 and type 2 diabetes mellitus.
  
  
  METHODS
  A cross-sectional study using a database of patients of SA (25.5%) and WE (74.5%) origin attending a specialist diabetes clinic in the UK between 2003 and 2005 (n=5664).
  
  
  RESULTS
  The prevalence of SAs and WEs with type 1 diabetes was 12% and 88%, respectively; for those with type 2 diabetes the prevalence was 30% and 70%, respectively. Overall, the prevalence of comorbidity in people with type 1 diabetes was 25.5% and with type 2 diabetes was 47%. NCCM was more prevalent in WEs than SAs (17.6% vs 12.8%, p<0.001). In type 2 diabetes, the prevalence of suboptimal glycaemic control was significantly greater in SAs compared to WEs with NCCM and CDCM (79% vs 62%, p<0.001; 78% vs 65%, p<0.001, respectively). SAs with type 2 diabetes and comorbidity had excess odds of suboptimal glycaemic control compared to WEs: OR 2.27 (95% CI 1.50 to 3.43) for those with NCCM and OR 1.91 (95% CI 1.49 to 2.44) for those with CDCM.
  
  
  CONCLUSIONS
  The prevalence of CDCM is higher in SAs compared to WEs with type 2 diabetes, whereas the prevalence of NCCM is higher in WEs compared to SAs. Taking into account comorbidities, SAs (compared to WEs) with type 2 diabetes had an excess risk of having HbA1c ≥7% ranging from 1.86- to 2.27-fold. Further research is needed to identify the reasons for unfavourable metabolic conditions in SAs and also develop and evaluate interventions.
authors.affiliation: Department of Health Sciences, University of Leicester, 22-28 Princess Road West, Leicester, UK. rlm17@le.ac.uk
authors.forename: R L
authors.initials: RL
authors.lastname: Mehta
authors.forename: M J
authors.initials: MJ
authors.lastname: Davies
authors.forename: S
authors.initials: S
authors.lastname: Ali
authors.forename: N A
authors.initials: NA
authors.lastname: Taub
authors.forename: M A
authors.initials: MA
authors.lastname: Stone
authors.forename: R
authors.initials: R
authors.lastname: Baker
authors.forename: P G
authors.initials: PG
authors.lastname: McNally
authors.forename: I G
authors.initials: IG
authors.lastname: Lawrence
authors.forename: K
authors.initials: K
authors.lastname: Khunti
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D044466:Asian People; D001786:Blood Glucose / Q000378:metabolism*; D015897:Comorbidity; D003430:Cross-Sectional Studies; D003922:Diabetes Mellitus, Type 1 / Q000097:blood / Q000208:ethnology*; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000208:ethnology*; D005260:Female; D006331:Heart Diseases / Q000097:blood / Q000208:ethnology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D012307:Risk Factors; D018709:Statistics, Nonparametric; D013997:Time Factors; D006113:United Kingdom / Q000453:epidemiology; D044465:White People
chemical_list: D001786:Blood Glucose