The Prevalence and Determinants of Undiagnosed and Diagnosed Type 2 Diabetes in Middle-Aged Irish Adults

Transcription

1 The Prevalence and Determinants of Undiagnosed and Diagnosed Type 2 Diabetes in Middle-Aged Irish Adults Seán R. Millar, Jennifer M. O Connor, Claire M. Buckley, Patricia M. Kearney, Ivan J. Perry s.millar@ucc.ie

2 Background Type 2 Diabetes mellitus (T2DM) Obesity Dyslipidaemia Hypertension Chronic Hyperglycaemia

3 Background Diabetes Complications Source: Saltiel & Olefsky (2001)

4 Background There is a lack of research relating to diabetes in Ireland although a recent Institute of Public Health report, using data from the 2007 SLÁN survey, suggested 135,000 cases in adults 45+ (8.9%). Approximately one-third of these were undiagnosed. Subjects with undiagnosed T2DM are at high-risk of diabetes complications.

5 Background There is an ongoing need for contemporary data on the prevalence of T2DM within Ireland. This could help formulate strategies that further develop effective diabetes prevention, detection and management.

6 Study Aims The aim of this study was to assess the prevalence of undiagnosed and diagnosed T2DM in middle-aged Irish adults and compare features in order to investigate why certain individuals remain undetected. In particular, we determined the extent to which the probability of diagnosis is influenced by access to primary care as defined by health insurance status.

7 Study Design The Cork and Kerry Diabetes and Heart Disease Study (Phase II) was a single centre, cross-sectional study conducted between 2010 and 2011, based on a population representative random sample of 2,047 men and women aged between years (49.2% male).

8 Methods: Biochemical Classifications All study participants attended the clinic in the morning after an overnight fast and blood samples were taken on arrival. Lipid and lipoprotein measurements were classified according to International Diabetes Federation guidelines: High triglycerides >1.7 mmol/l Low HDL-C <1.03 mmol/l in males <1.29 mmol/l in females

9 Methods: Biochemical Classifications Dyslipidaemia Both high triglyceride and low HDL-C levels. Undiagnosed diabetes Subjects without a history of diabetes but with HbA 1c levels >6.5% (>48 mmol/mol). Diagnosed diabetes Self-reported physician diagnosis or medication use.

10 Methods: Anthropometric Measurements Weight and height were measured to the nearest 0.1 kg and 0.1 cm respectively. Body mass index (BMI) was calculated as weight divided by the square of height. <25 normal weight overweight >30 obese

11 Methods: Lifestyle Data Data on age, gender, education level, morbidity, prescription (Rx) medication use, smoking/alcohol behaviours and health insurance status were gathered through a self-completed General Health Questionnaire (GHQ). Physical activity levels were assessed using the validated International Physical Activity Questionnaire (IPAQ).

12 Statistical Analysis Stepwise forwards and backwards entry elimination logistic regressions were performed to explore socioeconomic, metabolic and other health-related variable associations with undiagnosed and diagnosed T2DM. Model stability was determined using the likelihood ratio. The discriminatory properties of clinically relevant predictor variables identified in regression analyses were assessed using the receiver operating characteristic curve. Two-tailed P value <0.05 considered to indicate statistical significance.

13 RESULTS The total prevalence of T2DM was 8.5% (95% CI: 7.4%-8.8%). The prevalence of undiagnosed diabetes was 3.5% (95% CI: 2.8%-4.4%), representing 41% of all T2DM cases. A significantly greater proportion of male subjects (11.1%) had T2DM compared to females (6.0%, P <0.001).

14 Odds ratios (95% CI) of having undiagnosed or diagnosed type 2 diabetes compared to no diabetes Obesity, dyslipidaemia and having a family diabetes history were positively associated with both undiagnosed and diagnosed T2DM. The association between means-tested state health insurance and undiagnosed diabetes implies a correlation between lower socio-economic status and T2DM. The relationship between no health insurance and undiagnosed diabetes suggests a sub-category of people at risk that do not qualify for state insurance and who cannot afford private insurance.

15 Odds ratios (95% CI) of having undiagnosed compared to diagnosed diabetes When compared to diagnosed subjects, study participants with undiagnosed diabetes were significantly more likely to have low levels of physical activity, and were less likely to be on treatment for diabetes-related conditions or to have private medical insurance.

16 Receiver operating characteristic curves for models to discriminate undiagnosed and diagnosed diabetes Undiagnosed T2DM Diagnosed T2DM Models including health insurance, physical activity and BMI displayed a higher discriminatory capacity to detect undiagnosed T2DM, suggesting that use of these variables in screening programmes may help identify a subset of diabetes cases.

17 Discussion Results from this study and the SLÁN survey suggest that between one-third and almost 50% of middle-aged adults with T2DM in Ireland are unaware of their condition.

18 Discussion Societal failure Despite policies and continued investment in services which promote awareness and knowledge of a disease that is largely preventable, over two-thirds of middle-aged Irish adults are overweight or obese. Equitable access to primary healthcare is needed. Clinical failure A majority of undiagnosed subjects did have health insurance. Better detection methods are needed.

19 Limitations Cross-sectional data precludes examination of the temporal relationships between risk features and T2DM. Single primary care based sample. Modest sample size. Results should be considered preliminary and exploratory. Future studies may find other relationships.

20 Recommendations Individuals from lower socio-economic backgrounds should be targeted. Observed low levels of physical activity, obesity assessment and recognition of untreated cardiometabolic conditions may improve detection of diabetes cases within clinical practice. A strategic approach that identifies subjects without access to primary health services, and which furthers efforts to promote affordable and equitable healthcare, is also needed to prevent predictable sequelae for affected individuals.

21 Thank You Acknowledgements Many thanks to my co-authors: Ms. Jennifer O Connor Dr. Claire Buckley Prof. Patricia Kearney Prof. Ivan Perry