The relationship between socioeconomic deprivation and metabolic/cardiovascular risk factors in a cohort of patients with type 2 diabetes mellitus.
OBJECTIVE
There is conflicting information on the impact of socioeconomic deprivation on outcomes in diabetes. Our aim was to study the relationship between socioeconomic deprivation and clinical outcome indicators in a patient cohort with type 2 diabetes mellitus [T2DM].


METHODS
We recruited a random sample of 446 patients with T2DM [57% male] stratified by Income Deprivation Measure. Data on patient specific socioeconomic status, educational attainment, behaviour and attitudes were gathered by patient interview. Data analysis was by logistic and linear regression with correction for age, gender and duration of diabetes.


RESULTS
The study cohort showed high levels of deprivation with 80% reporting a household annual income of <£20,000 and 69.5% having no formal educational qualification. The cohort was actively managed with high usage of lipid lowering [90.1%], antihypertensive [80.6%] and antiplatelet agents [78%] and correspondingly good control of modifiable risk factors: HbA1c 7.6 [1.4]%, systolic blood pressure 134.2 [20.6], diastolic blood pressure 72.7 [11.2]mmHg, total cholesterol 4.0 [0.9]mmol/L. Socioeconomic disadvantage was strongly related to measures of integration and attitude to diabetes. Despite this there were no significant or consistent relationships between Income Deprivation Measure/self-reported annual household income/educational attainment on metabolic or cardiovascular risk factors.


CONCLUSIONS
Successful management of modifiable risk factors can be achieved in a way that is independent of socioeconomic position.
O'Kane
Maurice J
MJ
Diabetes Clinic, Altnagelvin Hospital, Londonderry, Northern Ireland, United Kingdom. Maurice.OKane@westerntrust.hscni.net
McMenamin
Mary
M
Bunting
Brendan P
BP
Moore
Adrian
A
Coates
Vivien E
VE
D000959:Antihypertensive Agents / Q000627:therapeutic use; D015415:Biomarkers / Q000097:blood; D001794:Blood Pressure; D002318:Cardiovascular Diseases / Q000097:blood / Q000453:epidemiology / Q000503:physiopathology / Q000517:prevention & control*; D002784:Cholesterol / Q000097:blood; D015331:Cohort Studies; D003430:Cross-Sectional Studies; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000188:drug therapy* / Q000453:epidemiology / Q000503:physiopathology; D005260:Female; D006442:Glycated Hemoglobin / Q000032:analysis; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D007004:Hypoglycemic Agents / Q000627:therapeutic use; D000960:Hypolipidemic Agents / Q000627:therapeutic use; D016014:Linear Models; D016015:Logistic Models; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood / Q000188:drug therapy* / Q000453:epidemiology / Q000503:physiopathology; D009660:Northern Ireland / Q000453:epidemiology; D010044:Outpatient Clinics, Hospital; D010975:Platelet Aggregation Inhibitors / Q000627:therapeutic use; D011203:Poverty; D012042:Registries; D018570:Risk Assessment; D012307:Risk Factors; D012959:Socioeconomic Factors
D000959:Antihypertensive Agents; D015415:Biomarkers; D002784:Cholesterol; D006442:Glycated Hemoglobin; D007004:Hypoglycemic Agents; D000960:Hypolipidemic Agents; D010975:Platelet Aggregation Inhibitors; C517652:hemoglobin A1c protein, human