AIMS:Heart failure (HF) may develop in type 2 diabetes without prior cardiovascular disease (CVD). This study aimed to identify risk factors that distinguish CVD that presents first as a HF event versus CVD that presents first as an atherosclerotic event (ASCVD), among people with type 2 diabetes. MATERIALS AND METHODS:ORIGIN and REWIND trial participants with type 2 diabetes but free of CVD (N = 6175; 64 ± 7 years, 50.1% female) were followed for ~5.8 years for incident CVD presenting first as either a HF event (HF hospitalization or HF death), ASCVD (myocardial infarction, unstable angina, stroke, or revascularization), or other cardiovascular death. Multi-state models characterised event-specific associations of risk factors with each possible first CVD event. RESULTS:HF was the first event in 16.8% of 1024 incident CVD cases. Older age, higher BMI, and higher urine albumin:creatinine ratio were more strongly associated with CVD manifesting first as HF, rather than as ASCVD or other cardiovascular death. ASCVD as the first event (65.2% of cases) was more strongly associated with worse LDL-cholesterol and HbA1c. These unique associations of risk factors with HF versus ASCVD translated to variable probabilities of HF as the first CVD event, depending on the clinical profile (32.0% for a profile enriched with HF-specific risk factors versus 5.1% for a profile enriched with ASCVD-specific risk factors). CONCLUSIONS:CVD that presents first as a HF event is common in type 2 diabetes and its risk factors are distinct from those associated with CVD that presents first as an ASCVD event.

AIMS:Magnetic resonance imaging (MRI) provides the most accurate assessments of site-specific fat accumulation, but is not readily available. Less-accurate methods, such as Dual-energy x-ray absorptiometry (DXA), bioelectrical impedance analysis (BIA), and anthropometry, have been widely used to measure overall and regional adiposity. However, the extent to which these approaches reflect MRI-derived fat depots is not fully understood. MATERIALS AND METHODS:We included 18 622 White participants from the UK Biobank imaging visit. A total of 27 indices from DXA, BIA, and anthropometry were selected to characterise overall and regional adiposity, and all indices were standardised. In subgroups stratified by age and sex, Pearson correlation coefficients were used to assess the degree of linear association between these indices and MRI-determined subcutaneous, visceral, liver, and pancreas fat. Intraclass correlation coefficients (ICC) were further calculated to evaluate the absolute agreement between the corresponding fat measures. RESULTS:Generally, correlations of adiposity indices from DXA (total, trunk, android, gynoid, arm, and leg fat), BIA (total, trunk, arm, and leg fat), and anthropometry (body mass index (BMI), waist and hip circumference) with MRI measures were strongest for subcutaneous fat, followed by visceral fat, and weakest for liver and pancreas fat. The correlation coefficients with MRI-based visceral fat were larger for indices reflecting abdominal adiposity (e.g., DXA-based visceral, android, and trunk fat, BIA-based trunk fat, and waist circumference) and for measures of total adiposity (e.g., DXA- and BIA-derived total fat). The absolute agreement with MRI-based visceral fat was highest for DXA-based visceral, trunk, and android fat (ICC = 0.73-0.94), followed by waist circumference (ICC = 0.73-0.77), and then the remaining indices. CONCLUSIONS:Indices of abdominal adiposity (as indicated by DXA-derived visceral, trunk, and android fat and waist circumference) appeared highly reflective of MRI-determined visceral fat. Considering cost and accessibility, waist circumference may serve as the most appropriate surrogate for assessing visceral fat.

Aims/hypothesisLarge-scale data on age- and sex-specific dementia mortality trends among people with diabetes remain limited, as most previous studies have been restricted to single countries or have not distinguished mortality by diabetes status. We estimated age- and sex-specific time trends in dementia mortality among individuals with and without diabetes from high-income jurisdictions.MethodsWe analysed aggregated mortality and demographic data using registries and administrative sources in Australia, Canada (Alberta and Ontario), France, Denmark, Finland and Scotland from 2000 to 2023. Poisson regression was used to estimate mortality rates for dementia as the underlying cause of death in people with and without diabetes at 60, 70, 80 and 90 years of age.ResultsA total of 114,559 and 589,706 dementia deaths were identified in over 42 and 244 million person-years of follow-up for individuals with and without diagnosed diabetes, respectively. Dementia mortality trends varied by age and jurisdiction but were generally consistent for both sexes. At younger ages (e.g. 60 and 70 years), the dementia mortality trends did not suggest any meaningful increases or decreases, except for in Scotland, which reported increasing dementia mortality over time only for those with diabetes. At older ages (e.g. 80 and 90 years), however, increases in dementia mortality were observed in most jurisdictions, ranging from 7.6% to 42.4% per 5 years. The magnitude of the increases was generally greater for those with diabetes. Mortality from dementia subtypes (e.g. Alzheimer's disease and vascular dementia) also increased over time in individuals aged 40-89 years, with greater increases in mortality rates for individuals with diabetes, specifically in Australia and Scotland.Conclusions/interpretationIncreases in dementia mortality were observed for those aged 80 years and above and were most marked for people with diabetes. These findings highlight the growing burden of dementia for health systems.

Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are widely used for the treatment of type 2 diabetes and/or obesity. The physiological actions of endogenous GLP-1, and synthetic GLP-1RAs include inhibition of gastric emptying. This has peri-procedural implications due to the potential increased risk of retained gastric contents which may result in pulmonary aspiration. There is a need for local evidence-based guidelines to best manage patients on GLP-1RAs and dual GLP-1 and glucose-dependent insulinotropic polypeptide receptor co-agonists (GLP-1/GIPRAs) presenting for surgical and medical procedures requiring sedation or anaesthesia. A panel of experts was formed to consider the peri-procedural implications of GLP-1RA and GLP-1/GIPRA use and establish best practice recommendations based on the current evidence.We recommend that all patients should be asked about glucagon-like peptide-1 receptor agonist (GLP-1RA) and dual GLP-1 and glucose-dependent insulinotropic polypeptide receptor co-agonist (GLP-1/GIPRA) use prior to anaesthesia or sedation for surgical and endoscopic procedures and be informed of the benefits and risks. We also recommend that GLP-1RAs and GLP-1/GIPRAs be continued in the peri-procedural period. Preprocedural diet modification with a 24-h clear fluid diet, followed by standard 6-h fasting, should be recommended for all patients receiving GLP-1RAs or GLP-1/GIPRAs. In patients who have not completed or are unable to have a 24-h liquid diet, risk stratification using gastric ultrasound or minimally sedated gastroscopy to assess gastric contents is recommended, as is the use of intravenous erythromycin. We cannot currently recommend using the absence of gastrointestinal symptoms for risk stratification, nor can we recommend an adequate cessation period for GLP-1RAs and GLP-1/GIPRAs to ensure gastric emptying has returned to baseline levels. This clinical guideline, developed by multiple professional bodies, outlines current best practice recommendations for patients taking GLP-1RAs and combined GLP-1/GIPRAs who require general anaesthesia, sedation and/or endoscopic procedures. The guide provides a structure for Australian and New Zealand primary health practitioners, gastroenterologists, surgeons, endocrinologists, anaesthetists and perioperative physicians to support clinical decisions in these patients.

BACKGROUND:Cardiovascular disease has historically been the most common cause of death (COD) among people with and without diabetes. However, substantial progress has been made in the management of cardiovascular disease. We conducted a multinational analysis to establish whether this trend is still the case. METHODS:In this multinational, population-based study, we assembled aggregated annual mortality data collected during routine clinical care from nationally or regionally representative administrative datasets in high-income jurisdictions between 2000 and 2023. For inclusion, datasets must have ongoing enrolment of new patients with diabetes, cause-specific death counts in people with and without diabetes, and sex-specific and age-specific data. We collected population size, counts of prevalent diabetes (type 1 and type 2), death counts, and person-years of follow-up in people with and without diagnosed diabetes by sex and 10-year age group. We estimated cause-specific trends in mortality rates, proportional mortality, and mortality rate ratios (MRR) for people with versus those without diabetes (type 1 and type 2) using Poisson models standardised for age and sex. FINDINGS:Using data from 11 jurisdictions, we identified 2·7 million deaths in people with diabetes and 11·0 million deaths in people without diabetes during a total of 1·7 billion person-years of follow-up. Cardiovascular disease mortality decreased in all jurisdictions in populations with and without diabetes. Mean 5-year declines in cardiovascular disease mortality among people with diabetes ranged from 8·3% (95% CI 5·9 to 10·7) to 25·4% (22·8 to 28·0). Mortality due to diabetes declined in most jurisdictions. Dementia mortality increased in people with and without diabetes in six (86%) of seven jurisdictions. Cancer mortality declined in people with diabetes in three (33%) of nine jurisdictions and in people without diabetes in six (67%). At the end of the observation period, cancer was the leading COD in people with diabetes in four (36%) of 11 jurisdictions. MRRs were generally stable for all CODs. Exceptions include Lithuania, where the mean 5-year change in MRR for cardiovascular disease was -7·6% (-10·1 to -5·1), indicating a more rapid fall in cardiovascular disease mortality in people with diabetes than in people without. For dementia, the MRR increased in Denmark (5-year change 8·0% [5·0 to 11·1]) and Scotland (11·4% [8·5 to 14·3]). INTERPRETATION:Mortality from cardiovascular disease and diabetes has declined among people with diabetes in most jurisdictions, whereas mortality from dementia has increased markedly, independent of age. Cardiovascular disease is no longer universally the most common COD among people with diabetes in high-income countries. FUNDING:US Centers for Disease Control and Prevention, Diabetes Australia Research Program, and Victoria State Government Operational Infrastructure Support Program.

Diet is a key factor for many diseases, yet the underlying metabolic pathways involved remain poorly understood. We analyze data from 13,335 participants across two large Australian cohorts examining comprehensive lipidomic profiles in relation to diet. We also assess the link between metabolic signatures of dietary quality with cardiometabolic health and all-cause mortality. Here, using linear models and lipid set enrichment analysis, we report characteristic lipidomic profiles associated with dairy [sphingomyelins and lipids esterified with 14:0, 15:0, 17:0 or 17:1 fatty acid], red meat and poultry [alkyl- and alkenyl-phosphatidylcholine and phosphatidylethanolamine notably, with arachidonic acid], and fish intake [higher 22:6, and lower 22:4 fatty acids]. In a Cox proportional hazard regression, metabolic signatures of diet quality showed inverse associations with all-cause mortality with hazard ratios (95% confidence intervals) of 0.89 (0.84-0.93), 0.87 (0.83-0.92), and 0.88 (0.84-0.93) for the Australian Dietary Guideline Index (DGI), the Global Diet Quality Score (DGQS), and the Mediterranean-DASH (Dietary Approaches to Stop Hypertension) Intervention for Neurodegenerative Delay (MIND) score, respectively. Additionally, the intake of nuts (β = -0.07, p = 7.92 × 10⁻¹⁸) and the MIND score (β = -0.07, p = 1.51 × 10⁻¹⁸) were inversely associated with CVD risk. Our data provide new insights into how dietary exposure relates to lipid metabolism and metabolic health, opening avenues for future mechanistic studies and dietary interventions that can inform targeted strategies for the prevention of cardiometabolic diseases.

BACKGROUND:Poor cognitive function is associated with increased mortality; however, whether these associations are consistent across different cognitive domains remains incompletely understood. METHODS:We examined associations between cognitive function and all-cause mortality in a population-based cohort of Australian adults (N = 4561, median age = 60.0 years). In addition to global cognitive function (Mini-Mental State Examination [MMSE]) and premorbid verbal ability, participants underwent clinical assessments targeting the specific cognitive domains of processing speed and memory. Cox proportional hazards models with age as the time scale estimated hazard ratios (HR) for all-cause mortality per 1-standard deviation (SD) increase in cognitive scores. Analyses were adjusted for sociodemographic (including education), lifestyle, and clinical factors. RESULTS:In this cohort with predominantly normal MMSE scores (98%), followed for a median of 11.3 years, 566 deaths occurred. Cognitive function was associated with lower mortality across most domains, as evidenced by 22% reduced mortality risk per 1-SD increase in global cognitive function (HR 0.78, 95% CI [0.67, 0.90]), 32% per 1-SD increase in processing speed (HR 0.68, [0.59, 0.78]) and 20% per 1-SD increase in memory (HR 0.80, [0.71, 0.91]), in fully adjusted models. Premorbid verbal ability was not associated with mortality (HR 0.92, [0.83, 1.02]). Associations were similar in men and women, and robust across sensitivity analyses. CONCLUSIONS:Processing speed and memory were independently associated with mortality after covariate adjustment. The presence of these associations in a cohort with mostly preserved cognitive function underscores the potential of domain-specific cognitive measures to serve as indirect prognostic markers of mortality and to inform risk stratification.

AIMS/HYPOTHESIS:Beyond longer diabetes duration, uncertainty remains regarding the factors that contribute to a higher risk of developing complications in younger vs older people with type 2 diabetes. We investigated whether younger age was associated with a more adverse risk-factor profile compared with older age among people with type 2 diabetes. METHODS:We conducted cross-sectional analyses of demographic and clinical data from individuals with type 2 diabetes participating in national health surveys from four countries: the Australian Diabetes, Obesity and Lifestyle Study (AusDiab), the US National Health and Nutrition Examination Survey (NHANES), the Mauritius Non-Communicable Diseases Survey (Mauritius Survey), and the Indian Council of Medical Research-India Diabetes (ICMR-INDIAB) study. Type 2 diabetes was defined according to each study's criteria, including previously diagnosed and newly diagnosed (screen-detected) diabetes (NDM). Individuals with normal glucose tolerance (NGT) were included for comparison. Regression analyses with natural splines assessed association between age at survey and cardiometabolic risk factors in each cohort. RESULTS:There were 903 participants with type 2 diabetes from AusDiab, 7086 from NHANES, 2682 from the Mauritius Survey and 10,151 from ICMR-INDIAB. In three of the four studies (excluding ICMR-INDIAB), BMI decreased with increasing age. Younger individuals had higher low-density lipoprotein cholesterol (in NHANES and AusDiab) and lower high-density lipoprotein cholesterol (in all studies except ICMR-INDIAB) compared with older individuals. In AusDiab, NHANES and the Mauritius Survey, triglycerides were highest in younger adults, declining with age. In AusDiab, the Mauritius Survey and ICMR-INDIAB, fasting plasma glucose (FPG) increased with age until 45-55 years, after which it declined. In NHANES, younger individuals with diabetes had higher FPG than older individuals. In all four studies, haemoglobin A1c (HbA1c) increased with age, peaking around 50-60 years, before declining. In NDM, 2 h plasma glucose did not vary across age. Systolic blood pressure (SBP) and urinary albumin/creatinine ratio (UACR) were higher in older individuals. Comparing diabetes with NGT, differences in FPG, HbA1c, triglycerides and diastolic blood pressure (DBP) were greater at younger than older ages in most cohorts. The same was observed for BMI and SBP, but only in two studies (AusDiab and NHANES). CONCLUSIONS/INTERPRETATION:Younger individuals with type 2 diabetes have higher BMI and triglycerides (observed in three out of four studies) but lower SBP and UACR than older individuals with type 2 diabetes. FPG and HbA1c peak in middle age. Differences relative to individuals without diabetes were more pronounced at younger than older ages for FPG, HbA1c, triglycerides and DBP, and were possibly greater for BMI and SBP. These age-related patterns likely influence the overall risk of diabetes-related complications.

BackgroundDiabetes is a recognized risk factor for dementia, but its impact on dementia burden across sociodemographic groups in Australia is not well characterized.ObjectiveTo compare prevalence of dementia among Australians with and without diabetes and examine variation across key sociodemographic factors.MethodsWe conducted a cross-sectional analysis of the 2021 Australian national census among respondents aged 60-99 years. Prevalence was stratified by education, income, socioeconomic disadvantage, remoteness, and country of birth.ResultsAge- and sex-standardized prevalence of dementia was higher in Australians with diabetes (3.83%) than in those without (3.33%), representing a 15% higher prevalence in the diabetes population. Women with diabetes had a higher prevalence than women without diabetes and men with diabetes. Across all sociodemographic strata, the prevalence of dementia was consistently higher among Australians with diabetes; however, the gap between Australians with and without diabetes widened in certain sociodemographic groups. The largest differences were observed among Australians with no education (6.56% versus 4.78%, 37% higher), those in remote areas (4.37% versus 3.22%, 36% higher) and those born in Vietnam (4.71% versus 3.79%, 24% higher) or China (3.81% versus 2.95%, 29% higher). Differences were also observed for those living in the most socioeconomically disadvantaged areas (4.72% versus 4.29%, 10% higher) and earning <$500/week (4.00% versus 3.47%, 15% higher). After adjusting for age and sex, the prevalence of dementia was 15% higher in the diabetes population, with this elevated risk persisting across sociodemographic strata.ConclusionsDementia is more prevalent among Australians with diabetes as compared with Australians without diabetes, particularly in socioeconomically and culturally disadvantaged populations. Addressing sociodemographic inequities is essential to reduce the burden of diabetes-related dementia in Australia's aging population.

OBJECTIVE:The aim of this study was to describe the associations of nutrition during pregnancy with childhood anthropometry among First Nations and non-First Nations women with hyperglycaemia in pregnancy. METHODS:224 women (58% First Nations women) with hyperglycaemia in pregnancy (168 gestational diabetes, 56 pre-existing type 2 diabetes) were administered food-frequency questionnaires during the third trimester. Childhood anthropometry body mass index, waist and arm circumferences and skinfold thickness) was measured at median (range) follow-up of 2.7 (1.5-5.0) years of age. Multivariable linear regression assessed associations of maternal nutrition with children's anthropometry after adjusting for age, sex, diabetes type, maternal body mass index, ethnicity, socioeconomic factors, birthweight, and breastfeeding. RESULTS:On multivariable regression, greater maternal frequency of fast-food (two or more times a week vs. weekly or less) was associated with higher body mass index (ß-coefficient 0.6 kg/m2, p=0.03), waist circumference (ß-coefficient 2.2 cm, p<0.01), arm circumference (ß-coefficient 0.7 cm, p<0.01) and sum of skinfolds (ß-coefficient 4.0 mm, p<0.01) in children. There were no associations between consumption of sugar-sweetened beverages, fruit or vegetable intake and outcomes. CONCLUSIONS:Addressing factors that support women and their families to maintain healthy diets is likely essential for improving childhood anthropometric outcomes. IMPLICATIONS FOR PUBLIC HEALTH:System-level changes focusing on food environments are essential to shift dietary patterns during pregnancy.

Type 2 diabetes disproportionately affects South Asian populations, who typically develop earlier onset disease associated with a high lifetime burden of complications. Conventional tools to predict diabetes complications, largely derived from European-ancestry cohorts and traditional clinical variables, perform suboptimally in South Asians and leave substantial residual risk unexplained. This review synthesises evidence on non-conventional predictors of microvascular and macrovascular complications in South Asian adults with type 2 diabetes. We examine life-course and early developmental determinants, ectopic fat, socioeconomic and environmental exposures, psychological and behavioural factors, non-conventional glycaemic metrics, novel organ-specific biomarkers, genetics, and artificial intelligence approaches. Although many predictors show promise, most lack validation in longitudinal South Asian cohorts and meaningful predictive value beyond existing clinical risk scores. Integrating diverse data types may enable more precise risk stratification, but robust external validation and evidence of improved patient outcomes are required before implementation in routine diabetes care.

Cardiovascular disease (CVD) is a major cause of morbidity and mortality in adults with type 2 diabetes mellitus (T2DM). Cardiac dysfunction and decreased exercise capacity are common in people with T2DM, even in those without overt heart failure. Empagliflozin, a sodium-glucose co-transporter 2 (SGLT2) inhibitor, reduces major cardiovascular events and mortality in people with T2DM and established CVD, though the underlying mechanisms are not fully elucidated. This study aimed to assess changes in cardiac function and cardiorespiratory fitness (CRF) at rest and during exercise with empagliflozin treatment in people with T2DM. This double-masked, single-centre, randomised, placebo-controlled analysis combined two studies involving adults (≥ 18 years) with T2DM comparing empagliflozin 25 mg daily vs. placebo, each over three months. VO₂ peak was measured using a ramp protocol peak exercise test on a bicycle ergometer, and echocardiography assessed changes in cardiac structure and function. Of 65 recruited participants, 57 completed the study (70.2

Background:Guideline-recommended clinical risk scores such as AusCVDRisk underestimate cardiovascular disease (CVD) risk in a substantial proportion of individuals who later experience events, with up to 65% initially classified as low or intermediate risk. This limitation is most consequential in the intermediate-risk group, where treatment decisions are uncertain and additional risk refinement could alter management. Circulating lipid species and inherited genetic variation capture complementary molecular aspects of atherosclerotic risk that are not fully reflected by conventional clinical variables, but are not routinely incorporated into primary-care risk assessment. We investigated whether selective integration of lipidomic and genomic risk signals into AusCVDRisk improves 5-year CVD prediction and reclassification, with a focus on individuals at intermediate clinical risk. Methods:A lipidomic score comprising 689 lipid species measured by liquid chromatography-tandem mass spectrometry was derived using regularised Cox regression in 8082 participants from the Australian Diabetes, Obesity and Lifestyle Study (1999-2000). A genome-wide coronary artery disease polygenic score (PGS002048; 762,124 variants) was optimised in 3328 participants from the Busselton Health Study (1994-95). Each score was adjusted for AusCVDRisk predictors to isolate independent effects and incorporated into Cox models retaining the AusCVDRisk linear predictor as a fixed offset, generating lipidomic-enhanced (L.CVDRisk), genomic-enhanced (G.CVDRisk), and combined (LG.CVDRisk) scores. Internal and external validation was performed across five Australian cohorts totalling 13,521 adults without baseline CVD. Discrimination (Harrell's concordance index; C-statistic), calibration, categorical net reclassification improvement (NRI), and decision-curve analyses were assessed. Findings:LG.CVDRisk showed modest gains in discrimination compared with AusCVDRisk (pooled ΔC among intermediate-risk individuals 0.071, 95% CI 0.033-0.109; overall 0.012, 95% CI 0.000-0.024). Risk classification improved substantially (pooled NRI in the intermediate-risk group 0.305, 95% CI 0.212-0.397; overall 0.080, 95% CI 0.031-0.129), with net event and non-event reclassification of 38.2% (95% CI 29.3-47.0%) and -6.8% (95% CI -9.3 to -4.2%) among intermediate-risk individuals. Decision-curve analysis showed the greatest net benefit when molecular profiling was selectively applied to individuals with intermediate AusCVDRisk (5-<10%). In a coronary imaging cohort, LG.CVDRisk reclassified 17 (41%) of 41 intermediate-risk individuals with extensive coronary calcification into the high-risk category. Interpretation:Selective augmentation of an established clinical risk algorithm with lipidomic and genomic information improves cardiovascular risk stratification among individuals at intermediate baseline risk. This approach supports targeted molecular testing within existing primary-care pathways to inform personalised prevention. Funding:National Heart Foundation, Australia, Australian Government Medical Research Future Fund, National Health and Medical Research Council, Victorian Government.

Traditional lipid biomarkers, such as cholesterol, HDL, LDL, and triglycerides, are frequently used to assess cardiometabolic health in clinical practice. However, these measures provide a limited view of the human lipidome, leaving clinically relevant information untapped. Lipidomic profiling using LC-MS/MS enables the measurement of hundreds of individual lipid species, yet low throughput and complex data processing have limited clinical integration. To overcome these limitations, we developed a Clinical Lipidomics Platform (CLP), a high-throughput (6 min runtime) LC-MS/MS assay measuring 270 lipid species (248 analytes + 22 internal standards) from 37 lipid subclasses in human plasma. The CLP incorporates automated data processing and normalization to an external reference material (NIST SRM 1950) to ensure reproducible and accurate data. We validated the CLP using the BioHEART-CT Discovery Cohort (n = 994) and compared lipidomic data to those from our Research Lipidomics Platform (RLP), which used a 16 min LC gradient and manual data processing to measure >800 lipids. CLP and RLP lipid measurements were highly correlated. A Lipidomic Risk Score (LRS), previously developed to model 10-year cardiovascular event risk using lipidomic, clinical, and demographic data, was calculated for each individual. CLP-derived LRS showed a strong correlation with RLP-derived LRS (R2 = 0.97). The LRS outperformed traditional risk scores, such as the Framingham Risk Score (FRS), in predicting the coronary artery calcium score (CACS), particularly in intermediate-risk individuals. These findings demonstrate the clinical utility of the CLP for cardiovascular risk assessment and its potential for broader clinical application.

BACKGROUND:The benefit of efforts to identify heart failure (HF) risk in cancer survivors is unclear. Individuals with diabetes mellitus (DM) are at elevated risk of both cancer and HF and may warrant further consideration regarding HF prevention. OBJECTIVES:To examine the incidence of HF in individuals with DM and cancer compared with DM alone. METHODS:A national cohort was established by linking the Australian National Diabetes Services Scheme (NDSS; n=792,742, aged ≥50 years) with hospital admissions, the National Death Index, and the Pharmaceutical Benefits Scheme. Cancer was defined by hospital admission or chemotherapy prescriptions. Incident HF was defined as the first HF hospitalization or HF-related death. Poisson models were adjusted for age, sex, socio-economic status, remoteness, coronary artery disease and hypertension. RESULTS:Between 2010 and 2022, 31,082 HF events will occur during 6.3 million person-years. Among 143,111 individuals with DM and cancer, HF incidence per 1,000 person-years was 10.8 (95% CI 10.47-11.04) versus 4.4 (95% CI 4.37-4.47) with DM alone (IRR 1.52, 95% CI 1.48-1.57). Risk was highest in those ≥70 years with DM and cancer (10/1,000 person-years) and those with hematologic malignancies (19/1,000 person years). Compared to DM alone, cancer admission without chemotherapy carried greater HF risk (IRR 1.76, 95% CI 1.69-1.84) than did chemotherapy exposure (IRR 1.36 95% CI 1.31-1.42), suggesting cancer itself is associated with HF. Risk was strongest when cancer was coded as a secondary diagnosis, suggesting synergy with multimorbidity. CONCLUSIONS:People with DM and cancer (especially aged ≥70 years), represent a high-risk group for HF.

Prediabetes or intermediate hyperglycaemia represents a preliminary stage in the development of type 2 diabetes mellitus (T2DM). In addition to an increased likelihood of developing T2DM, individuals with prediabetes have an elevated risk of various vascular and non-vascular complications. No consensus has been achieved on the ideal screening strategy for prediabetes, with fasting plasma glucose concentration, glycated haemoglobin (HbA1c) and the oral glucose tolerance test being the most frequently measured parameters. The two major phenotypes of prediabetes, that is, impaired fasting glucose and impaired glucose tolerance, may represent different pathophysiologies with varying natural history, risk of adverse outcomes and responsiveness to treatment. Most of the evidence for managing prediabetes focuses on lifestyle modification with or without medications in individuals with overweight or obesity and impaired glucose tolerance. Whether these interventions are beneficial in individuals with impaired fasting glucose and those of normal body weight is unclear, as is the cost-effectiveness and sustainability of pharmacotherapy for treating prediabetes. Large-scale national T2DM prevention programmes are currently under way to assess whether the benefits of interventions for prediabetes can be translated to the community setting. Prediabetes refers to individuals with blood glucose levels above the normal levels but below the thresholds for a diabetes mellitus diagnosis. In this Primer, Mohan and colleagues discuss the increasing prevalence of prediabetes, its pathophysiology and diagnosis as well as the importance of early intervention to improve adverse outcomes in patients.

Introduction and Objective: In order to achieve diabetes remission, resources to support intensive lifestyle intervention (ILI) need to be directed towards people with diabetes for whom remission is achievable, i.e. short diabetes duration, lower HbA1c. We aimed to determine if responses to ILI, other than remission, justify this resource allocation. Methods: We analyzed Look AHEAD participants 20–65 years old with BMI 27–45kg/m2. The effect of ILI was assessed after stratification for remission eligibility at baseline (diabetes duration ≤6 years, no insulin). Cox models evaluated the effect of ILI on incidence of cardiovascular disease (CVD), chronic kidney disease (CKD), and mortality, and linear models assessed the effect on weight and HbA1c. Results: There were 3,105 participants - 60% women, median age 58 years old, median follow-up 9 years. At baseline, 54% were eligible for remission. Remission eligibility status did not modify the effect of ILI on CVD, CKD or mortality. ILI led to 2.4 kg greater weight loss (-5.53 kg (95%CI -6.02, -5.03) vs -3.17 kg (95%CI -3.86, -2.49)), and 0.1% greater HbA1c reduction (-0.28% (95%CI -0.33, -0.23) vs -0.17% (95%CI -0.23, -0.11)) in eligible compared to ineligible people (Figure). Conclusion: The small additional benefit of intervention in people eligible for remission, compared to ineligible people, may not be enough to justify restricting resources to such eligible people. J.Y. Gong: None. A. Salim: None. D.J. Magliano: None. J.E. Shaw: Advisory Panel; GlaxoSmithKline plc. Speaker's Bureau; AstraZeneca, Roche Diagnostics, Boehringer-Ingelheim, Zuellig Pharma. Advisory Panel; Novo Nordisk. NHMRC (Investigator Grants and postgraduate scholarship), National Heart Foundation of Australia (postgraduate scholarship), The University of Melbourne (Rowden White scholarship)

OBJECTIVE:To explore the association between diabetes and anemia. RESEARCH DESIGN AND METHODS:We included 9,026 and 389,616 participants from the U.S. National Health and Nutrition Examination Surveys and the UK Biobank study (UKB), respectively. Multivariable logistic regression was used to examine the cross-sectional association of diabetes with anemia, as defined by hemoglobin measurement. For the UKB follow-up, multivariable Cox proportional hazards regression was performed to estimate hazard ratios (HRs) and 95% CIs of incident anemia, as defined by hemoglobin levels or diagnosis records, in relation to diabetes. We further assessed the impact of inflammation, renal dysfunction, and medication use on this association in both populations. RESULTS:Among White people aged 40-69 years in the U.S. and U.K., the adjusted odds of study participants with diagnosed diabetes also having anemia was two to four times higher than in those with normal glycemia. Over a median follow-up of 13.6 years in the UKB, 42,354 people developed anemia. The adjusted HRs for incident anemia comparing diagnosed diabetes with normal glycemia were 3.05 (95% CI 2.90-3.21) for iron deficiency anemia, 3.02 (95% CI 2.51-3.63) for anemia of chronic disease, and 4.88 (95% CI 4.23-5.63) for vitamin B12 deficiency anemia. Further adjustment for inflammation, renal dysfunction, and medication use partially attenuated these associations, but they remained strong and significant. CONCLUSIONS:Diabetes was associated with several major types of anemia. Further studies are warranted to identify the mechanisms.

AIMS:To examine the association between fat distribution and diabetes. MATERIALS AND METHODS:We included UK Biobank participants who underwent an imaging visit and did not have type 1 diabetes at the time of that visit. Exposures were four MRI-measured fat depots, including abdominal subcutaneous adipose tissue (ASAT, in litres), visceral adipose tissue (VAT, in litres), liver fat (LF, in percentages) and muscle fat infiltration (MFI, in percentages). Logistic regression was used to estimate the odds ratios for prevalent diabetes, identified through self-reported diabetes diagnosis or non-metformin glucose-lowering medication use, or diagnosis records in primary care and hospitalizations before the imaging date, while Cox proportional hazards regression was used to estimate the hazard ratios (HRs) for incident diabetes, captured by hospitalizations only. RESULTS:Of the 44 857 participants (mean age: 66 years, 52% women) included, 2428 had prevalent diabetes. Of the remaining 42 429 who were free of diabetes at the imaging visit, 252 were hospitalized with diabetes over a median follow-up of 3.6 years. In age-, sex- and ethnicity-adjusted models, ASAT, VAT, LF and MFI were all associated with a higher likelihood of having or developing diabetes. Those associations were attenuated after additional adjustment of body mass index (BMI) or other fat depots, and generally followed the ranking of VAT>LF/MFI>ASAT. The HRs for incident diabetes, per standard deviation increase, adjusted for age, sex, ethnicity and BMI, were 2.44 (95% CI: 1.91-3.11) for VAT, 1.75 (95% CI: 1.56-1.97) for LF, 1.14 (95% CI: 0.98-1.34) for MFI, and 0.80 (95% CI: 0.63-1.02) for ASAT. CONCLUSIONS:Visceral fat showed a stronger association with diabetes than did other fat depots, highlighting the central role of visceral fat in the development of diabetes.