Pitavastatin treatment remodels the HDL subclass lipidome and proteome in hypertriglyceridemia.

HDL particles vary in lipidome and proteome, which dictate their individual physicochemical properties, metabolism, and biological activities. HDL dysmetabolism in nondiabetic hypertriglyceridemia (HTG) involves subnormal HDL-cholesterol and apoAI levels. Metabolic anomalies may impact the qualitative features of both the HDL lipidome and proteome. Whether particle content of bioactive lipids and proteins may differentiate HDL subclasses (HDL2b, 2a, 3a, 3b, and 3c) in HTG is unknown. Moreover, little is known of the effect of statin treatment on the proteolipidome of hypertriglyceridemic HDL and its subclasses. Nondiabetic, obese, HTG males (n = 12) received pitavastatin calcium (4 mg/day) for 180 days in a single-phase, unblinded study. ApoB-containing lipoproteins were normalized poststatin. Individual proteolipidomes of density-defined HDL subclasses were characterized prestatin and poststatin. At baseline, dense HDL3c was distinguished by marked protein diversity and peak abundance of surface lysophospholipids, amphipathic diacylglycerol and dihydroceramide, and core cholesteryl ester and triacylglycerol, (normalized to mol phosphatidylcholine), whereas light HDL2b showed peak abundance of free cholesterol, sphingomyelin, glycosphingolipids (monohexosylceramide, dihexosylceramide, trihexosylceramide, and anionic GM3), thereby arguing for differential lipid transport and metabolism between subclasses. Poststatin, bioactive lysophospholipid (lysophosphatidylcholine, lysoalkylphosphatidylcholine, lysophosphatidylethanolamine, and lysophosphatidylinositol) cargo was preferentially depleted in HDL3c. By contrast, baseline lipidomic profiles of ceramide, dihydroceramide and related glycosphingolipids, and GM3/phosphatidylcholine were maintained across particle subclasses. All subclasses were depleted in triacylglycerol and diacylglycerol/phosphatidylcholine. The abundance of apolipoproteins CI, CII, CIV, and M diminished in the HDL proteome. Statin treatment principally impacts metabolic remodeling of the abnormal lipidome of HDL particle subclasses in nondiabetic HTG, with lesser effects on the proteome.

Acculturation and glycaemic control in Arab immigrants with type 2 diabetes in Australia.

AIMS/HYPOTHESIS: This study aimed to investigate acculturation's direct and mediated effects on HbA1c levels in individuals with type 2 diabetes from Arabic-speaking countries that are members of the Arab League who have emigrated to Australia. METHODS: In this multicentre cross-sectional study, we recruited 382 Arabic-speaking immigrants who were born in any of the 22 countries of the Arab League and who had type 2 diabetes from different healthcare settings in Australia. HbA1c levels were retrieved from medical records. A validated self-report questionnaire was used to assess behavioural and psychosocial outcomes. Acculturation was measured using the General Acculturation Index and the Adherence to Traditional Values tool. We used structural equation modelling to test mediation hypotheses. RESULTS: Participants had a mean HbA1c value of 63.9 mmol/mol (8.0%), a low acculturation level (mean±SD: 1.9±0.6; range: 1-5) and highly adhered to traditional values (mean General Acculturation Index value: 3.7±0.7; range: 1-5). Higher HbA1c was associated with lower acculturation levels (Pearson correlation coefficient [r] = -0.32, p<0.01) and higher adherence to traditional values (r=0.35, p<0.01). Self-efficacy, health literacy and self-care activities partially mediated the relationship between acculturation and HbA1c. CONCLUSIONS/INTERPRETATION: Among Arab immigrants in Australia with type 2 diabetes, the degree of acculturation is related to glycaemic control, suggesting possible avenues for new interventions.

Improving health outcomes of people with diabetes: target setting for the WHO Global Diabetes Compact.

The Global Diabetes Compact is a WHO-driven initiative uniting stakeholders around goals of reducing diabetes risk and ensuring that people with diabetes have equitable access to comprehensive, affordable care and prevention. In this report we describe the development and scientific basis for key health metrics, coverage, and treatment targets accompanying the Compact. We considered metrics across four domains: factors at a structural, system, or policy level; processes of care; behaviours and biomarkers such as glycated haemoglobin (HbA1c); and health events and outcomes; and three risk tiers (diagnosed diabetes, high risk, or whole population), and reviewed and prioritised them according to their health importance, modifiability, data availability, and global inequality. We reviewed the global distribution of each metric to set targets for future attainment. This process led to five core national metrics and target levels for UN member states: (1) of all people with diabetes, at least 80% have been clinically diagnosed; and, for people with diagnosed diabetes, (2) 80% have HbA1c concentrations below 8·0% (63·9 mmol/mol); (3) 80% have blood pressure lower than 140/90 mm Hg; (4) at least 60% of people 40 years or older are receiving therapy with statins; and (5) each person with type 1 diabetes has continuous access to insulin, blood glucose meters, and test strips. We also propose several complementary metrics that currently have limited global coverage, but warrant scale-up in population-based surveillance systems. These include estimation of cause-specific mortality, and incidence of end-stage kidney disease, lower-extremity amputations, and incidence of diabetes. Primary prevention of diabetes and integrated care to prevent long-term complications remain important areas for the development of new metrics and targets. These metrics and targets are intended to drive multisectoral action applied to individuals, health systems, policies, and national health-care access to achieve the goals of the Global Diabetes Compact. Although ambitious, their achievement can result in broad health benefits for people with diabetes.

Urine Albumin-Creatinine Ratio Variability in People With Type 2 Diabetes: Clinical and Research Implications.

RATIONALE & OBJECTIVE: Evidence has demonstrated that albuminuria is a key diagnostic and prognostic marker of diabetic chronic kidney disease, but the impact of its day-to-day variability has not been adequately considered. This study quantified within-individual variability of albuminuria in people with type 2 diabetes to inform clinical albuminuria monitoring. STUDY DESIGN: Descriptive cross-sectional analysis. SETTING & PARTICIPANTS: People with type 2 diabetes (n=826, 67.1 [IQR, 60.3-72.4] years, 64.9% male) participating in the Progression of Diabetic Complications (PREDICT) cohort study. EXPOSURE: Four spot urine collections for measurement of urinary albumin-creatinine ratio (UACR) within 4 weeks. OUTCOME: Variability of UACR. ANALYTICAL APPROACH: We characterized within-individual variability (coefficient of variation [CV], 95% limits of random variation, intraclass correlation coefficient), developed a calculator displaying probabilities that any observed difference between a pair of UACR values truly exceeded a 30% difference, and estimated the ranges of diagnostic uncertainty to inform a need for additional UACR collections to exclude or confirm albuminuria. Multiple linear regression examined factors influencing UACR variability. RESULTS: We observed high within-individual variability (CV 48.8%; 95% limits of random variation showed a repeated UACR to be as high/low as 3.78/0.26 times the first). If a single-collection UACR increased from 2 to 5mg/mmol, the probability that UACR actually increased by at least 30% was only 50%, rising to 97% when 2 collections were obtained at each time point. The ranges of diagnostic uncertainty were 2.0-4.0mg/mmol after an initial UACR test, narrowing to 2.4-3.2 and 2.7-2.9mg/mmol for the mean of 2 and 3 collections, respectively. Some factors correlated with higher (female sex; moderately increased albuminuria) or lower (reduced estimated glomerular filtration rate and sodium-glucose cotransporter 2 inhibitor/angiotensin-converting enzyme inhibitor/angiotensin receptor blocker treatment) within-individual UACR variability. LIMITATIONS: Reliance on the mean of 4 UACR collections as the reference standard for albuminuria. CONCLUSIONS: UACR demonstrates a high degree of within-individual variability among individuals with type 2 diabetes. Multiple urine collections for UACR may improve capacity to monitor changes over time in clinical and research settings but may not be necessary for the diagnosis of albuminuria. PLAIN-LANGUAGE SUMMARY: Albuminuria (albumin in urine) is a diagnostic and prognostic marker of diabetic chronic kidney disease. However, albuminuria can vary within an individual from day to day. We compared 4 random spot urinary albumin-creatinine ratio (UACR) samples from 826 participants. We found that a second UACR collection may be as small as a fourth or as large as almost 4 times the first sample's UACR level. This high degree of variability presents a challenge to our ability to interpret changes in albuminuria. Multiple collections have been suggested as a solution. We have constructed tools that may aid clinicians in deciding how many urine collections are required to monitor and diagnose albuminuria. Multiple urine collections may be required for individual monitoring but not necessarily for diagnosis.

Trends in rates of hospitalisation for infection in people with diabetes and the general population.

AIM: To describe the trends of hospitalisation for infections in people with diabetes and in the general population. METHODS: People with diabetes were identified from the Australian National Diabetes Services Scheme linked to hospitalisation datasets from 2010/11 to 2018/19. Data on hospitalisations in the general population were obtained from the Australian Institute of Health and Welfare. Joinpoint regression software was used to calculate the annual percentage change (APC) of rates. RESULTS: The rate of hospitalisation for total infections increased with an APC of 2.6% (95% CI: 1.5, 3.7) among people with type 1 diabetes, 3.6% (2.6, 4.6) among people with type 2 diabetes, and 2.5% (1.3, 3.9) in the general population. Increasing rates were observed for sepsis, influenza, kidney infections, osteomyelitis, cellulitis, and foot infections in all groups. The rate of hospitalisation for urinary tract infection declined among people with type 2 diabetes though it was stable in other groups. The rate of hospitalisation for respiratory tract infections was stable among people with type 1 diabetes but increased in other groups. The rate of hospitalisation for gastrointestinal infection was stable in all cohorts. CONCLUSION: Hospitalisation rates for infection have increased more rapidly over time in people with diabetes than in the general population.

Causes of death among Australians with type 1 or type 2 diabetes, 2002-2019.

AIMS: This population-based study sought to explore in detail the conditions driving the diversification in causes of death among people with diabetes. METHODS: We linked Australians with type 1 or type 2 diabetes of all ages on the National Diabetes Services Scheme to the National Death Index for 2002-2019. We investigated the proportional contributions of different causes of death to total deaths over time across eight categories of causes of death, stratified by sex and diabetes type. The underlying causes of death were classified according to the International Classification of Diseases, Tenth Revision codes. RESULTS: Between 2002 and 2019, there was a shift in the causes of death among Australians with diabetes away from cardiovascular disease. The proportion of deaths attributed to cardiovascular disease declined in both sexes (ptrend <0.001), most substantially among women with type 2 diabetes from 48.2% in 2002 to 30.7% in 2019. Among men with type 2 diabetes, cancer replaced cardiovascular disease as the leading cause of death. The proportion of deaths due to dementia increased overall, from 2% in 2002 to over 7% in 2019, and across all age groups, notably from 1% to 4% in those aged 70-79. The proportion of deaths due to falls and Parkinson's disease also increased. CONCLUSIONS: There has been a shift of causes of death among those with diabetes away from cardiovascular disease. The proportion of deaths due to conditions such as dementia and falls is increasing among those with diabetes, which will require consideration when planning future resource allocation.

Reasons for hospitalisation in youth with type 1 diabetes, 2010-2019.

AIMS: To determine the incidence of hospitalisation for all diagnoses among Australian youth with type 1 diabetes. METHODS: We linked Australians aged under 20 years with type 1 diabetes on the National Diabetes Services Scheme (n = 45,685) to hospital admission data from 2010 to 2019. We determined relative risks (RR) of hospitalisation among those with type 1 diabetes in the states of Victoria and Queensland (n = 21,898) compared to the general population for 2010-2017 using Poisson regression. RESULTS: Australian youth with type 1 diabetes had increased risk for almost all reasons for hospitalisation compared to the general population, especially infections such as anogenital herpesviral infections (RR 54.83, 95% CI 33.21-90.53), and mental health disorders including personality disorders (RR 9.70, 95% CI 8.02-11.72). Among those with type 1 diabetes, over 60% of hospitalisations were directly related to diabetes, almost half of which were for ketoacidosis. Approximately 15% of ketoacidosis admissions occurred within 3 months of diabetes diagnosis. One quarter of those with admissions for ketoacidosis were readmitted for ketoacidosis within 12 months. Residence in areas of high socio-economic disadvantage was an independent risk factor for admission and readmission for ketoacidosis. CONCLUSIONS: Youth with type 1 diabetes are susceptible to a wide range of complications. Clinicians should consider screening and prevention for conditions such as infections and mental health disorders. Targeted support and education around glycaemic management should be considered in those at high risk for ketoacidosis admission including those living in areas of high socio-economic disadvantage.

Hospital admissions among people with diabetes: A systematic review.

OBJECTIVE: To describe the reasons for hospital admission among people with diabetes. METHODS: We searched Emcare, Embase, Medline and Google Scholar databases for population-based studies describing the causes of hospitalisation among people with diabetes. We included articles published in English from 1980 to 2022. For each study, we determined the most frequent reasons for admission. Studies were assessed for quality using the Newcastle Ottawa quality assessment tool. RESULTS: 6920 research articles were retrieved from the search of all sources. After screening the titles and abstracts of these, we reviewed the full text of 135 papers and finally included data from 42 studies. Admissions among the total diabetes were reported in 25 papers: 5 articles reported type 1 diabetes alone, 10 articles reported type 2 diabetes alone and the remaining 2 articles reported type 1 and type 2 diabetes separately. Among the 25 total and type 2 diabetes studies that reported the distribution of hospitalisations in broad categories, cardiovascular diseases (CVD) were the leading cause of admission in 19/25 (76%) of studies. Among the 19 studies that reported CVD admissions by subcategories, ischaemic or coronary heart disease was the leading subtype of CVD in 58% of studies. The other common causes of admissions were infections, renal disorders, endocrine, nutritional, metabolic and immunity disorders. In people with type 1 diabetes, acute diabetes complications were the leading cause of admission. CONCLUSION: CVD are the leading cause of hospital admission for people with diabetes, with ischaemic or coronary heart disease as the predominant subtype.

Evaluating the incidence of complications among people with diabetes according to age of onset: Findings from the UK Biobank.

AIMS: To examine the impact of current age, age at diagnosis, and duration of diabetes on the incidence rate of complications among people with type 2 diabetes. METHODS: Baseline data from 19,327 individuals with type 2 diabetes in the UK Biobank were analysed. Poisson regression was used to model incidence rates by current age, age at diagnosis, and duration of diabetes for the following outcomes: myocardial infarction (MI), heart failure (HF), stroke, end-stage kidney diseases (ESKD), chronic kidney diseases (CKD), liver diseases, depression, and anxiety. RESULTS: The mean age at baseline was 60.2 years, and median follow-up was 13.9 years. Diabetes duration was significantly longer among those with younger-onset type 2 diabetes (diagnosed at <40 years) compared to later-onset type 2 diabetes (diagnosed at ≥40 years), 16.2 and 5.3 years, respectively. Incidence rates of MI, HF, stroke, and CKD had strong positive associations with age and duration of diabetes, whereas incidence rates of ESKD liver diseases, and anxiety mainly depended on duration of diabetes. The incidence rates of depression showed minor variation by age and duration of diabetes and were highest among those diagnosed at earlier ages. No clear evidence of an effect of age of onset of diabetes on risk of complications was apparent after accounting for current age and duration of diabetes. CONCLUSIONS: Our study indicates age at diagnosis of diabetes does not significantly impact the incidence of complications, independently of the duration of diabetes. Instead, complications are primarily influenced by current age and diabetes duration.

A novel approach to accurately measuring the burden of hospitalisations for cardiovascular disease in people with diabetes: A pilot study.

AIM: To determine the reliability of hospital discharge codes for heart failure (HF), acute myocardial infarction (AMI) and stroke compared with adjudicated diagnosis, and to pilot a scalable approach to adjudicate records on a population-based sample. METHODS: A population-based sample of 685 people with diabetes admitted (1274 admissions) to one of three Australian hospitals during 2018-2020 were randomly selected for this study. All medical records were reviewed and adjudicated. RESULTS: Cardiovascular diseases were the most common primary reason for hospitalisation in people with diabetes, accounting for ~17% (215/1274) of all hospitalisations, with HF as the leading cause. ICD-10 codes substantially underestimated HF prevalence and had the lowest agreement with the adjudicated diagnosis of HF (Kappa = 0.81), compared with AMI and stroke (Kappa ≥ 0.91). While ICD-10 codes provided suboptimal sensitivity (72%) for HF, the performance was better for AMI (sensitivity 84%; specificity 100%) and stroke (sensitivity 85%; specificity 100%). A novel approach to screen possible HF cases only required adjudicating 8% (105/1274) of records, correctly identified 78/81 of HF admissions and yielded 96% sensitivity and 98% specificity. CONCLUSIONS: While ICD-10 codes appear reliable for AMI or stroke, a more complex diagnosis such as HF benefits from a two-stage process to screen for suspected HF cases that need adjudicating. The next step is to validate this novel approach on large multi-centre studies in diabetes.

Liver disease mortality and hospitalisations among people with type 2 diabetes mellitus: A population-based study.

BACKGROUND AND AIMS: The burden of liver disease among people with diabetes at a population level is unknown. We explored the burden and trends of liver disease mortality and hospitalisations among Australians with diabetes. METHODS: We linked Australians with type 2 diabetes on the National Diabetes Services Scheme to the National Death Index for 2002-2019 to determine trends in the proportion of deaths due to liver disease, overall and by subcategory. We also determined the leading reasons and risk factors for liver disease hospitalisations in those with diabetes over this period. Finally, we compared the burden of liver disease hospitalisations among those with diabetes to the general population using excess hospitalisations per 100 000 person-years. RESULTS: Among Australians with type 2 diabetes (n = 1 122 431) liver diseases accounted for between 1.5% and 1.9% of deaths between 2002 and 2019, roughly one-third of the proportion of deaths caused by kidney disease. The proportion of deaths due to inflammatory liver diseases among those with diabetes increased from .08% in 2002 to .27% in 2019. Alcohol-related liver disease accounted for the greatest share (22.7%) of liver disease hospitalisation in those with diabetes, but the number of hospitalisations for this condition declined over time. Compared to the general population, men (RR 3.63, 95% CI 3.44-3.84) and women (RR 4.49, 4.21-4.78) with diabetes were at higher risk of hospitalisation for fibrosis and cirrhosis; however, this did not translate to a substantial excess risk per 100 000 population. CONCLUSIONS: Better screening methods for liver disease among people with diabetes should be developed and implemented into practice.

The association of glycaemic risk factors and diabetes duration with risk of heart failure in people with type 2 diabetes: A systematic review and meta-analysis.

AIMS: To conduct a systematic review in order to better understand the association of glycaemic risk factors and diabetes duration with risk of heart failure (HF) in individuals with type 2 diabetes (T2D). METHODS: We identified longitudinal studies investigating the association of glycaemic factors (glycated haemoglobin [HbA1c], HbA1c variability, and hypoglycaemia) and diabetes duration with HF in individuals with T2D. Hazard ratios and odds ratios were extracted and meta-analysed using a random-effects model where appropriate. Risk of bias assessment was carried out using a modified Newcastle-Ottawa Scale. Egger's test along with the trim-and-fill method were used to assess and account for publication bias. RESULTS: Forty studies representing 4 102 589 people met the inclusion criteria. The risk of developing HF significantly increased by 15% for each percentage point increase in HbA1c, by 2% for each additional year of diabetes duration, and by 43% for having a history of severe hypoglycaemia. Additionally, variability in HbA1c levels was associated with a 20%-26% increased risk of HF for each unit increase in the metrics of variability (HbA1c standard deviation, coefficient of variation, and average successive variability). All included studies scored high in the risk of bias assessment. Egger's test suggested publication bias, with trim-and-fill analyses revealing a significant 14% increased risk of HF per percentage point increase in HbA1c. CONCLUSIONS: Glycaemic risk factors and diabetes duration significantly contribute to the heightened risk of HF among individuals with T2D. A reduction in risk of HF is anticipated with better management of glycaemic risk factors.

The Determination of Diabetes Utilities, Costs, and Effects Model: A Cost-Utility Tool Using Patient-Level Microsimulation to Evaluate Sensor-Based Glucose Monitoring Systems in Type 1 and Type 2 Diabetes: Comparative Validation.

OBJECTIVES: To assess the accuracy and validity of the Determination of Diabetes Utilities, Costs, and Effects (DEDUCE) model, a Microsoft-Excel-based tool for evaluating diabetes interventions for type 1 and type 2 diabetes. METHODS: The DEDUCE model is a patient-level microsimulation, with complications predicted based on the Sheffield and Risk Equations for Complications Of type 2 diabetes models for type 1 and type 2 diabetes, respectively. For this tool to be useful, it must be validated to ensure that its complication predictions are accurate. Internal, external, and cross-validation was assessed by populating the DEDUCE model with the baseline characteristics and treatment effects reported in clinical trials used in the Fourth, Fifth, and Ninth Mount Hood Diabetes Challenges. Results from the DEDUCE model were evaluated against clinical results and previously validated models via mean absolute percentage error or percentage error. RESULTS: The DEDUCE model performed favorably, predicting key outcomes, including cardiovascular disease in type 1 diabetes and all-cause mortality in type 2 diabetes. The model performed well against other models. In the Mount Hood 9 Challenge comparison, error was below the mean reported from comparator models for several outcomes, particularly for hazard ratios. CONCLUSIONS: The DEDUCE model predicts diabetes-related complications from trials and studies well when compared with previously validated models. The model may serve as a useful tool for evaluating the cost-effectiveness of diabetes technologies.

Changes in the incidence of type 2 diabetes in Australia, 2005-2019, overall and by socio-demographic characteristics: a population-based study.

OBJECTIVES: To estimate changes in the incidence of clinically diagnosed type 2 diabetes in Australia, overall and by age, sex, socio-economic disadvantage, geographic remoteness, and country of birth. STUDY DESIGN: Population-based study; analysis of National Diabetes Services Scheme (NDSS) data (age-period-cohort models). SETTING, PARTICIPANTS: Data were extracted for incident cases of type 2 diabetes, 1 January 2005 to 31 December 2019, in residents of the Australian Capital Territory, New South Wales, Queensland, and Victoria aged 20 years or older registered with the NDSS. The numbers of people at risk were obtained from the Australian Bureau of Statistics. MAIN OUTCOME MEASURES: Changes in the incidence of type 2 diabetes, 2005-2019, by age, postcode-level socio-economic disadvantage (Index of Relative Socioeconomic Disadvantage) and remoteness (major city, inner regional, outer regional/remote/very remote), and country of birth, stratified by sex. RESULTS: During 2005-2019, 741 535 people aged 20 years or older with incident type 2 diabetes were registered with the NDSS; 421 190 were men (56.8%). Overall, the incidence of type 2 diabetes increased with age (until about age 70 years) and socio-economic disadvantage for both sexes; it was higher in inner regional areas than in major cities or outer regional/remote/very remote areas during 2005-2015, but highest among people in major cities after 2015. The age-standardised incidence of type 2 diabetes increased during 2005-2010, both among men (annual percentage change [APC], 4.4%; 95% confidence interval [CI], 3.6-5.2%) and women (APC, 2.9%; 95% CI, 2.2-3.7%); it declined during 2010-2019 among both men (APC, -5.2%; 95% CI, -5.4% to -4.9%) and women (APC, -6.5%; 95% CI, -6.8% to -6.2%). In general, similar patterns (but of differing magnitude) applied to all age, sex, socio-economic disadvantage, and remoteness groups. However, the incidence of type 2 diabetes increased during 2011-2019 among people born in Asia, North Africa and the Middle East, and the Pacific Islands. CONCLUSIONS: The incidence of type 2 diabetes in Australian adults declined during 2010-2019 across all age, sex, socio-economic disadvantage, and remoteness groups, but increased among people from Asia, North Africa and the Middle East, and the Pacific Islands.

Projecting the incidence and costs of major cardiovascular and kidney complications of type 2 diabetes with widespread SGLT2i and GLP-1 RA use: a cost-effectiveness analysis.

AIMS/HYPOTHESIS: Whether sodium-glucose co-transporter 2 inhibitors (SGLT2is) or glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are cost-effective based solely on their cardiovascular and kidney benefits is unknown. We projected the health and economic outcomes due to myocardial infarction (MI), stroke, heart failure (HF) and end-stage kidney disease (ESKD) among people with type 2 diabetes, with and without CVD, under scenarios of widespread use of these drugs. METHODS: We designed a microsimulation model using real-world data that captured CVD and ESKD morbidity and mortality from 2020 to 2040. The populations and transition probabilities were derived by linking the Australian Diabetes Registry (1.1 million people with type 2 diabetes) to hospital admissions databases, the National Death Index and the ESKD Registry using data from 2010 to 2019. We modelled four interventions: increase in use of SGLT2is or GLP-1 RAs to 75% of the total population with type 2 diabetes, and increase in use of SGLT2is or GLP-1 RAs to 75% of the secondary prevention population (i.e. people with type 2 diabetes and prior CVD). All interventions were compared with current use of SGLT2is (20% of the total population) and GLP-1 RAs (5% of the total population). Outcomes of interest included quality-adjusted life years (QALYs), total costs (from the Australian public healthcare perspective) and the incremental cost-effectiveness ratio (ICER). We applied 5% annual discounting for health economic outcomes. The willingness-to-pay threshold was set at AU$28,000 per QALY gained. RESULTS: The numbers of QALYs gained from 2020 to 2040 with increased SGLT2i and GLP-1 RA use in the total population (n=1.1 million in 2020; n=1.5 million in 2040) were 176,446 and 200,932, respectively, compared with current use. Net cost differences were AU$4.2 billion for SGLT2is and AU$20.2 billion for GLP-1 RAs, and the ICERs were AU$23,717 and AU$100,705 per QALY gained, respectively. In the secondary prevention population, the ICERs were AU$8878 for SGLT2is and AU$79,742 for GLP-1 RAs. CONCLUSIONS/INTERPRETATION: At current prices, use of SGLT2is, but not GLP-1 RAs, would be cost-effective when considering only their cardiovascular and kidney disease benefits for people with type 2 diabetes.

Risk of kidney disease following a pregnancy complicated by diabetes: a longitudinal, population-based data-linkage study among Aboriginal women in the Northern Territory, Australia.

AIMS/HYPOTHESIS: The aim of this work was to investigate the risk of developing chronic kidney disease (CKD) or end-stage kidney disease (ESKD) following a pregnancy complicated by gestational diabetes mellitus (GDM) or pre-existing diabetes among Aboriginal women in the Northern Territory (NT), Australia. METHODS: We undertook a longitudinal study of linked healthcare datasets. All Aboriginal women who gave birth between 2000 and 2016 were eligible for inclusion. Diabetes status in the index pregnancy was as recorded in the NT Perinatal Data Collection. Outcomes included any stage of CKD and ESKD as defined by ICD-10 coding in the NT Hospital Inpatient Activity dataset between 2000 and 2018. Risk was compared using Cox proportional hazards regression. RESULTS: Among 10,508 Aboriginal women, the mean age was 23.1 (SD 6.1) years; 731 (7.0%) had GDM and 239 (2.3%) had pre-existing diabetes in pregnancy. Median follow-up was 12.1 years. Compared with women with no diabetes during pregnancy, women with GDM had increased risk of CKD (9.2% vs 2.2%, adjusted HR 5.2 [95% CI 3.9, 7.1]) and ESKD (2.4% vs 0.4%, adjusted HR 10.8 [95% CI 5.6, 20.8]). Among women with pre-existing diabetes in pregnancy, 29.1% developed CKD (adjusted HR 10.9 [95% CI 7.7, 15.4]) and 9.9% developed ESKD (adjusted HR 28.0 [95% CI 13.4, 58.6]). CONCLUSIONS/INTERPRETATION: Aboriginal women in the NT with GDM or pre-existing diabetes during pregnancy are at high risk of developing CKD and ESKD. Pregnancy presents an important opportunity to identify kidney disease risk. Strategies to prevent kidney disease and address the social determinants of health are needed.

The future burden of oesophageal and stomach cancers attributable to modifiable behaviours in Australia: a pooled cohort study.

BACKGROUND: We quantified the individual and joint contribution of contemporaneous causal behavioural exposures on the future burden of oesophageal and stomach cancers and their subtypes and assessed whether these burdens differ between population groups in Australia, as such estimates are currently lacking. METHODS: We combined hazard ratios from seven pooled Australian cohorts (N = 367,058) linked to national cancer and death registries with exposure prevalence from the 2017-2018 National Health Survey to estimate Population Attributable Fractions (PAFs) with 95% confidence intervals (CIs), accounting for competing risk of death. RESULTS: Current and past smoking explain 35.2% (95% CI = 11.7-52.4%), current alcohol consumption exceeding three drinks/day 15.7% (95% CI = 0.9-28.4%), and these exposures jointly 41.4% (95% CI = 19.8-57.3%) of oesophageal squamous cell carcinomas in Australia. Current and past smoking contribute 38.2% (95% CI = 9.4-57.9%), obesity 27.0% (95% CI = 0.6-46.4%), and these exposures jointly 54.4% (95% CI = 25.3-72.1%) of oesophageal adenocarcinomas. Overweight and obesity explain 36.1% (95% CI = 9.1-55.1%), current and past smoking 24.2% (95% CI = 4.2-40.0%), and these exposures jointly 51.2% (95% CI = 26.3-67.8%) of stomach cardia cancers. Several population groups had a significantly higher smoking-attributable oesophageal cancer burden, including men and those consuming excessive alcohol. CONCLUSIONS: Smoking is the leading preventable behavioural cause of oesophageal cancers and overweight/obesity of stomach cancers.

Association between maternal hyperglycemia in pregnancy and offspring anthropometry in early childhood: the pandora wave 1 study.

BACKGROUND: In-utero hyperglycemia exposure influences later cardiometabolic risk, although few studies include women with pre-existing type 2 diabetes (T2D) or assess maternal body mass index (BMI) as a potential confounder. OBJECTIVE: To explore the association of maternal T2D and gestational diabetes mellitus (GDM) with childhood anthropometry, and the influence of maternal BMI on these associations. METHODS: The PANDORA cohort comprises women (n = 1138) and children (n = 1163). Women with GDM and T2D were recruited from a hyperglycemia in pregnancy register, and women with normoglycemia from the community. Wave 1 follow-up included 423 children, aged 1.5-5 years (median follow-up age 2.5 years). Multivariable linear regression assessed associations between maternal antenatal variables, including BMI and glycemic status, with offspring anthropometry (weight, height, BMI, skinfold thicknesses, waist, arm and head circumferences). RESULTS: Greater maternal antenatal BMI was associated with increased anthropometric measures in offspring independent of maternal glycemic status. After adjustment, including for maternal BMI, children exposed to maternal GDM had lower mean weight (-0.54 kg, 95% CI: -0.99, -0.11), BMI (-0.55 kg/m2, 95% CI: -0.91, -0.20), head (-0.52 cm, 95% CI: -0.88, -0.16) and mid-upper arm (-0.32 cm, 95% CI: -0.63, -0.01) circumferences, and greater mean suprailiac skinfold (0.78 mm, 95% CI: 0.13, 1.43), compared to children exposed to normoglycemia. Adjustment for maternal BMI strengthened the negative association between GDM and child weight, BMI and circumferences. Children exposed to maternal T2D had smaller mean head circumference (-0.82 cm, 95% CI: -1.33, -0.31) than children exposed to normoglycemia. Maternal T2D was no longer associated with greater child mean skinfolds (p = 0.14) or waist circumference (p = 0.18) after adjustment for maternal BMI. CONCLUSIONS: Children exposed to GDM had greater suprailiac skinfold thickness than unexposed children, despite having lower mean weight, BMI and mid-upper arm circumference, and both GDM and T2D were associated with smaller mean head circumference. Future research should assess whether childhood anthropometric differences influence lifetime cardiometabolic and neurodevelopmental risk.

Trends in the Incidence of End-Stage Kidney Disease in Type 1 and Type 2 Diabetes in Australia, 2010-2019.

RATIONALE & OBJECTIVE: Trends in end-stage kidney disease (ESKD) among people with diabetes may inform clinical management and public health strategies. We estimated trends in the incidence of ESKD among people with type 1 and type 2 diabetes in Australia from 2010-2019 and evaluated their associated factors. STUDY DESIGN: Cohort study. SETTING & PARTICIPANTS: 71,700 people with type 1 and 1,112,690 people with type 2 diabetes registered on the Australian National Diabetes Services Scheme (NDSS). We estimated the incidence of kidney replacement therapy (KRT) via linkage to the Australia and New Zealand Dialysis and Transplant Registry (ANZDATA) and the incidence of KRT or death from ESKD by linking the NDSS to the ANZDATA and the National Death Index for Australia. PREDICTORS: Calendar time, sex, age, and duration of diabetes. OUTCOME: Incidence of KRT and KRT or death from ESKD. ANALYTICAL APPROACH: Incidence of ESKD, trends over time, and associations with factors related to these trends were modeled using Poisson regression stratified by diabetes type and sex. RESULTS: The median duration of diabetes increased from 15.3 to 16.8 years in type 1 diabetes, and from 7.6 to 10.2 years in type 2 diabetes between 2010 and 2019. The incidence of KRT and KRT or death from ESKD did not significantly change over this time interval among people with type 1 diabetes. Conversely, the age-adjusted incidence of KRT and KRT or death from ESKD increased among males with type 2 diabetes (annual percent changes [APCs]: 2.52% [95% CI, 1.54 to -3.52] and 1.27% [95% CI, 0.53 2.03], respectively), with no significant change among females (0.67% [95% CI, -0.68 to 2.04] and 0.07% [95% CI, -0.81 to 0.96], respectively). After further adjustment for duration of diabetes, the incidence of ESKD fell between 2010 and 2019, with APCs of-0.09% (95% CI, -1.06 to 0.89) and-2.63% (95% CI, -3.96 to-1.27) for KRT and-0.97% (95% CI, -1.71 to-0.23) and-2.75% (95% CI, -3.62 to-1.87) for KRT or death from ESKD among males and females, respectively. LIMITATIONS: NDSS only captures 80%-90% of people with diabetes; lack of clinical covariates limits understanding of trends. CONCLUSIONS: While the age-adjusted incidence of ESKD increased for males and was stable for females over the last decade, after adjusting for increases in duration of diabetes the risk of developing ESKD has decreased for both males and females. PLAIN-LANGUAGE SUMMARY: Previous studies showed an increase in new cases of kidney failure among people with type 2 diabetes, but more recent data have not been available. Here, we report trends in the rate of kidney failure for people with type 2 diabetes from 2010 to 2019 and showed that while more people with type 2 diabetes are developing kidney failure, accounting for the fact that they are also surviving longer (and therefore have a higher chance of kidney failure) the growth in this population is not caused by a higher risk of kidney failure. Nevertheless, more people are getting kidney failure than before, which will impact health care systems for years to come.

Postpartum uptake of diabetes screening tests in women with gestational diabetes: The PANDORA study.

AIMS: To determine rates and predictors of postpartum diabetes screening among Aboriginal and/or Torres Strait Islander and non-Indigenous women with gestational diabetes mellitus (GDM). METHODS: PANDORA is a prospective longitudinal cohort of women recruited in pregnancy. Postpartum diabetes screening rates at 12 weeks (75-g oral glucose tolerance test (OGTT)) and 6, 12 and 18 months (OGTT, glycated haemoglobin [HbA1C ] or fasting plasma glucose) were assessed for women with GDM (n = 712). Associations between antenatal factors and screening with any test (OGTT, HbA1C , fasting plasma glucose) by 6 months postpartum were examined using Cox proportional hazards regression. RESULTS: Postpartum screening rates with an OGTT by 12 weeks and 6 months postpartum were lower among Aboriginal and/or Torres Strait Islander women than non-Indigenous women (18% vs. 30% at 12 weeks, and 23% vs. 37% at 6 months, p < 0.001). Aboriginal and/or Torres Strait Islander women were more likely to have completed a 6-month HbA1C compared to non-Indigenous women (16% vs. 2%, p < 0.001). Screening by 6 months postpartum with any test was 41% for Aboriginal and/or Torres Strait Islander women and 45% for non-Indigenous women (p = 0.304). Characteristics associated with higher screening rates with any test by 6 months postpartum included, insulin use in pregnancy, first pregnancy, not smoking and lower BMI. CONCLUSIONS: Given very high rates of type 2 diabetes among Aboriginal and Torres Strait Islander women, early postpartum screening with the most feasible test should be prioritised to detect prediabetes and diabetes for intervention.