Background: Tobacco smoking and diabetes mellitus contribute significantly to the overall health burden and mortality of Australians. We aimed to assess the relationship of smoking with glycemic control, metabolic profile and complications in Australian patients living with diabetes.Methods: We analysed the 2011-2017 biennial Australian National Diabetes Audit cross-sectional data. Patients were classified as current, past or never smokers. Linear (or quantile) and logistic regression models were used to assess for associations.Results: Data from 15,352 patients were analysed, including 72.2% with type 2 diabetes. Current smokers comprised 13.5% of the study population. Current and past smokers had a median HbA1c that was 0.49% and 0.14% higher than never smokers, respectively, as well as higher triglyceride and lower HDL levels (p <0.0001 for all). Compared to never smokers, current smokers had higher odds of severe hypoglycaemia and current and past smokers had higher odds of myocardial infarction, stroke, peripheral vascular disease, lower limb amputation, erectile dysfunction and peripheral neuropathy (all p values ≤0.001), with no significant change over time. Conclusion:When compared to never smokers, current and past smokers had poorer glycemic and lipid control and higher odds of macrovascular and microvascular complications. Despite this, current smoking remains prevalent among Australians with diabetes.

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Aim To investigate temporal changes in glycaemic control and the use of antihyperglycaemic therapies in females and males with type 2 diabetes from 2013 to 2019. Methods Data from adult patients with type 2 diabetes (n = 11 930; 44.9% females, mean [SD] age of 62.9 [12.9] years) were analysed from the 2013 to 2019 biennial cross‐sectional Australian National Diabetes Audit. Results Mean HbA1c remained similar throughout the years examined and between the sexes (7.8%‐8.3%, 62‐67 mmol/mol; P > .05). The number of antihyperglycaemic agents used by both sexes increased from 2013 to 2019 (P < .001), with more agents used by males (P = .014). From 2013 to 2019, there were increasing proportions of both sexes using dipeptidyl peptidase‐4 inhibitors (females: 11.7%‐25.7%, P = .045; males: 11.6%‐29.5%, P = .036) and glucagon‐like peptide‐1 receptor agonists (females: 5.9%‐15.3%; males: 4.9%‐11.1%; P = .043 for both). Sodium‐glucose co‐transporter‐2 inhibitors were not available in 2013; however, their use increased substantially from 2015 to 2019 in both females (4.9%‐26.3%, P = .013) and males (4.7%‐32.2%, P = .019). Conclusions From 2013 to 2019, mean HbA1c levels remained unchanged despite a concurrent increase in the number of antihyperglycaemic medications used. Overall, there was a trend towards preferencing newer agents with some differences in treatment regimens relating to sex and renal function.

Background Increasing global diabetes incidence has profound implications for health systems and for people living with diabetes. Guidelines have established clinical targets but there may be variation in clinical outcomes including HbA1c, based on location and practice size. Investigating this variation may help identify factors amenable to systemic improvement interventions. The aims of this study were to identify centre-specific and patient-specific factors associated with variation in HbA1c levels and to determine how these associations contribute to variation in performance across diabetes centres. Methods This cross-sectional study analysed data for 5,872 people with type 1 (n = 1,729) or type 2 (n = 4,143) diabetes mellitus collected through the Australian National Diabetes Audit (ANDA). A linear mixed-effects model examined centre-level and patient-level factors associated with variation in HbA1c levels. Results Mean age was: 43±17 years (type 1), 64±13 (type 2); median disease duration: 18 years (10,29) (type 1), 12 years (6,20) (type 2); female: 52% (type 1), 45% (type 2). For people with type 1 diabetes, volume of patients was associated with increases in HbA1c (p = 0.019). For people with type 2 diabetes, type of centre was associated with reduction in HbA1c (p <0.001), but location and patient volume were not. Associated patient-level factors associated with increases in HbA1c included past hyperglycaemic emergencies (type 1 and type 2, p<0.001) and Aboriginal and Torres Strait Islander status (type 2, p<0.001). Being a non-smoker was associated with reductions in HbA1c (type 1 and type 2, p<0.001). Conclusions Centre-level and patient-level factors were associated with variation in HbA1c, but patient-level factors had greater impact. Interventions targeting patient-level factors conducted at a centre level including sick-day management, smoking cessation programs and culturally appropriate diabetes education for and Aboriginal and Torres Strait Islander peoples may be more important for improving glycaemic control than targeting factors related to the Centre itself.