[ Diabetes Type 2 ]

The Association between HbA1c and Cardiovascular Disease Markers in a Remote Indigenous Australian Community with

Australian diabetes expert, Professor Paul Zimmet AO, was elected Honorary President of the International Diabetes Federation (IDF) at the World Diabetes Congress in Dubai at the weekend. The Programme Organising Committee consisted of members from all three societies and endeavoured to present you with the latest and most exciting data from these respective fields with a range of international and national leading speakers. We recommend taking the time to read the Language for Diabetes Position Paper:. Diabetes NSW will manage all event logistics. The likelihood that a patient will develop the complications associated with diabetes increases across the range of fasting glucoses and therefore it is not unreasonable that different bodies might decide on different cut-offs. Methods. Professor Zimmet has devoted his life to the research, education and care of people with diabetes, with his research and advocacy attracting international recognition in raising awareness of diabetes as an international public health epidemic.

The participants were stratified by HbA1c into 5 groups using cut-off points recommended by international organisations. As part of the initiative, eight of the partner organisations have signed a consensus statement with a series of recommendations around tackling the over consumption of sugar-sweetened beverages. Activities for the kids include getting up and close with animals from a petting zoo, face painting, karaoke, jumping castle, kids disco, sports, arts and crafts, games and competitions – plus more! Members of the RCPA Chemical Pathology Advisory Committee are: Dr G.R.D. Individuals with higher HbA1c levels were more likely to have albuminuria (OR 3.14, 95% CI 1.26–7.82) and dyslipidaemia (OR 2.37, 95% CI 1.29–4.34) and visited the clinic more often (OR 2.52, 95% CI 1.26–4.99). Almost all traditional CVD risk factors showed a positive association with HbA1c. Conclusions.

Screening in this remote Indigenous Australian community highlights the high proportion of individuals who are at high risk of diabetes as indicated by HbA1c and who also had an accentuated cardiovascular risk profile. This event is aimed at all people living with diabetes and coincides with National Diabetes Week. Barker, Dr K.N. Some Indigenous communities are up to 10 times more likely to have diabetes than the general population and 2 times more than other remote Indigenous communities [3, 4]. This further disadvantage for individuals living in remote communities requires continued efforts. Many previous studies report the burden of diabetes based on diabetes incidence, prevalence, or microvascular and macrovascular complications associated with diabetes [5–7]. It is also important to investigate the burden of this disease in remote Indigenous Australians before they are diagnosed with diabetes.

The risk of, and progression of, type 2 diabetes is on a continuum, so the earliest identification of these high-risk individuals would increase the chance to delay or prevent diabetes development. Use of glycosylated haemoglobin (HbA1c) may be a successful screening option to investigate the burden of diabetes in these remote Indigenous Australian communities. HbA1c is currently recommended for diabetes diagnosis in clinical practice in the United Kingdom, New Zealand, United States, and Australian [8–11] general populations. HbA1c has also been shown to successfully screen urban Indigenous Australians [12] and more recently remote Indigenous Australian communities for diabetes [13]. In addition to diagnosing diabetes, HbA1c could also identify individuals at high risk of developing diabetes. An International Expert Committee recommended a 6.0–6.4% (42–46 mmol/mol) HbA1c category to identify those at high risk of diabetes [14], while the American Diabetes Association (ADA) recommends a 5.7–6.4% (39–46 mmol/mol) HbA1c category [9]. Although diabetes risk is a continuum, these categories are a starting point for health services to focus on prevention and early identification of those at high risk of diabetes.

Although high-risk categories have been recommended in general populations, it is unknown what level of HbA1c would be most appropriate in the Indigenous Australian context. This study aims to investigate the cardiovascular risk profile of people in a remote Indigenous Australian community across a wide range of HbA1c levels. We also compare the differences between groups with and without diabetes to highlight how the burden of cardiovascular risk markers changes as risk of diabetes increases based on increased HbA1c. Health screening examinations were offered between 2004 and 2006 to every individual of a remote Indigenous Australian community in the Northern Territory who were ambulatory. People in old age care, in hospital, on dialysis, resident elsewhere, or out of community on the screening occasion did not participate. All participants provided written informed consent. Blood and urine samples were collected, anthropometric measurements and lifestyle questions were recorded, and medical records were reviewed.

Blood samples were only taken from participants over 15 years old. There were 1,554 who participated in the health screening examinations and 79 percent were aged between 15 and 82 years, which represented 70% of the (1,757) total age-eligible population, based on the 2006 Census. Participants were excluded from the current analysis if they did not identify themselves as Indigenous Australian or did not have a blood sample taken. Urine and blood samples collected from participants were sent to Westerns Pathology in Darwin. All assays were performed using the Roche Integra I800. Urinary albumin was measured by immunoturbidimetry using the Beckmann Array (Beckman Instruments, Brea, CA). Urinary creatinine was measured using the kinetic method with an alkaline picrate reagent.

Samples were analysed within 48 hours of collection, with interim storage at 4°C. Microalbuminuria and macroalbuminuria were classified by a urinary albumin/creatinine ratio (ACR) of 3.4–33 g/mol and ≥34 g/mol, respectively [15]. Blood pressure was measured on the right arm in a seated position after participants had rested for at least 5 minutes using an automated BP device (Welch Allyn, Skaneateles Falls, NY) and appropriate cuffs for arm size. Hypertension was defined if the participant had a previous diagnosis of hypertension in their health records, was taking antihypertensive medication, or had elevated levels in the baseline examination (≥140 mmHg systolic, ≥90 mmHg diastolic). Estimated glomerular filtration rate (eGFR) was calculated using the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) formula as validated (without adjustment for African American status) in Indigenous Australian populations by Maple-Brown et al. [16]. Triglyceride levels were measured using lipase/glycerol kinase/GPO-PAP assays.

Total cholesterol concentration was measured using cholesterol oxidase/peroxidase reagents. HDL cholesterol levels were measured using cyclodextrin sulphate/PEG modified enzymes. Dyslipidaemia was defined by a previous diagnosis of high cholesterol, taking cholesterol management medication, or having total cholesterol ≥ 5.5 mmol/L or HDL < 1.0 mmol/L at the screening examination as per the Australian Diabetes, Obesity, and Lifestyle Study (AusDiab) [17]. High sensitivity CRP was analysed using immunoturbidimetric CRP assay on a Hitachi 917 analyser (Roche Diagnostics, Australia) with a detection limit of 0.03 mg/L. The assay’s analytical range was from 0.1 to 20 mg/L. CRP concentrations greater than 20 mg/L were measured using diluted samples. The imprecision of the assay is less than 5% [18]. Waist circumference (WC) was measured at the narrowest point below the ribs or halfway between the lower border of the ribs and the iliac crest in centimetres. Participants in the highest quartile for WC based on age- and sex-adjusted z-scores were defined as having high WC. Body mass index (BMI) was calculated by dividing the individual’s weight in kilograms by their height in metres-squared (kg/m2). Smoking status was self-reported in the health screening interview. The number of clinic visits in the last year was counted through the clinic records for each individual in the past 12 months prior to their health screening examination. A history of CVD was determined if the participant had hospitalisation associated with CVD in the last 12 years prior to their health screening examination. The number of cardiovascular risk factors was the total score of the following possible risk factors: micro/macroalbuminuria, hypertension, dyslipidaemia, current smoking, and high WC.

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