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.

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.

Cardiovascular disease hospitalizations among women who undergo fertility treatment.

RESEARCH QUESTION: Are women who receive fertility treatment at increased risk of cardiovascular disease (CVD) hospitalization compared with women who do not? DESIGN: A retrospective cohort study of all women registered for fertility treatment at Monash IVF between 1998 and 2014. This cohort was linked to the Victorian Admitted Episodes Dataset, which contains records of all hospital admissions in the Australian state of Victoria. Age- and Index of Relative Socioeconomic Disadvantage (IRSD)-adjusted relative risks of CVD hospitalization for women who did or did not undergo fertility treatment were determined using Poisson regression. Risks were calculated overall by CVD subtype and stratified by area-based social disadvantage using IRSD fifths, number of stimulated cycles and mean oocytes per cycle. RESULTS: Of 27,262 women registered for fertility treatment, 24,131 underwent treatment and 3131 did not. No significant difference was found in risk of CVD hospitalization between treated and untreated women overall (adjusted RR 0.93, 95% 0.82 to 1.05) or by CVD subtype. The admission risk for CVD was significantly lower in treated women who had a mean of fewer than five oocytes per cycle (adjusted RR 0.80, 95% CI 0.70 to 0.92) compared with untreated women. Treated women residing in areas within the second IRSD fifth were less likely to be hospitalized for CVD compared with untreated women (age-adjusted RR 0.66, 95% CI 0.49 to 0.89). CONCLUSIONS: Fertility treatment is not associated with increased risk of CVD hospitalization. Lower risk among some subgroups of treated women may be explained by social disadvantage.

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.

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.

Validation of serum non-invasive tests of liver fibrosis as prognostic markers of clinical outcomes in people with fatty liver disease in Australia.

BACKGROUND AND AIM: The validity of non-invasive tests (NITs) of liver fibrosis for the prediction of liver and mortality outcomes in an Australian cohort is unknown. We aimed to verify the utility of available NITs to predict overall and cause-specific mortality and major adverse liver outcome (MALO). METHODS: This was an analysis from the Crossroads 1 clinic sub-study of a randomly sampled adult cohort from regional Australia between 2001 and 2003. Baseline variables included demographic details, anthropometry, health and lifestyle data, and laboratory tests. Non-alcoholic fatty liver disease (NAFLD) and metabolic-(dysfunction) associated fatty liver disease (MAFLD) were defined by fatty liver index ≥ 60 and other accepted criteria. Outcomes were defined by the International Statistical Classification of Diseases and Related Health Problems 10th Revision codes for linked hospitalization and death registry data. Available serum-based NITs were analyzed as predictors of overall, cardiovascular disease-related, and cancer-related mortality and MALO in those with fatty liver disease (FLD). RESULTS: In total, 1324 and 1444 participants were included for NAFLD and MAFLD analysis (prevalence 35.4% and 40.7%, respectively). There were 298 deaths (89 cardiovascular disease-related and 98 cancer-related) and 24 MALO over a median 19.7 years of follow-up time. In both forms of FLD, fibrosis-4 index, Steatosis-Associated Fibrosis Estimator score, and Forns fibrosis score consistently had the highest area under the receiver operating characteristic curve (AUROC) for overall and cause-specific mortality, with AUROC > 0.70 for each outcome. However, all had poor discriminatory ability for determining MALO in each FLD. CONCLUSIONS: Several liver fibrosis NITs perform similarly reasonably well in predicting the risk of mortality outcomes in those with FLD but are poorly discriminatory for MALO prediction.

Special Issue: "New Trends in Diabetes, Hypertension, and Cardiovascular Diseases".

Cardiovascular disease (CVD) encompasses a range of disorders affecting the heart and blood vessels, including coronary heart disease and cerebrovascular disease [...].

Global trends in the incidence of hospital admissions for diabetes-related foot disease and amputations: a review of national rates in the 21st century.

AIMS/HYPOTHESIS: Diabetic foot disease (DFD) is a leading cause of hospital admissions and amputations. Global trends in diabetes-related amputations have been previously reviewed, but trends in hospital admissions for multiple other DFD conditions have not. This review analysed the published incidence of hospital admissions for DFD conditions (ulceration, infection, peripheral artery disease [PAD], neuropathy) and diabetes-related amputations (minor and major) in nationally representative populations. METHODS: PubMed and Embase were searched for peer-reviewed publications between 1 January 2001 and 5 May 2022 using the terms 'diabetes', 'DFD', 'amputation', 'incidence' and 'nation'. Search results were screened and publications reporting the incidence of hospital admissions for a DFD condition or a diabetes-related amputation among a population representative of a country were included. Key data were extracted from included publications and initial rates, end rates and relative trends over time summarised using medians (ranges). RESULTS: Of 2527 publications identified, 71 met the eligibility criteria, reporting admission rates for 27 countries (93% high-income countries). Of the included publications, 14 reported on DFD and 66 reported on amputation (nine reported both). The median (range) incidence of admissions per 1000 person-years with diabetes was 16.3 (8.4-36.6) for DFD conditions (5.1 [1.3-7.6] for ulceration; 5.6 [3.8-9.0] for infection; 2.5 [0.9-3.1] for PAD) and 3.1 (1.4-10.3) for amputations (1.2 [0.2-4.2] for major; 1.6 [0.3-4.3] for minor). The proportions of the reported populations with decreasing, stable and increasing admission trends were 80%, 20% and 0% for DFD conditions (50%, 0% and 50% for ulceration; 50%, 17% and 33% for infection; 67%, 0% and 33% for PAD) and 80%, 7% and 13% for amputations (80%, 17% and 3% for major; 52%, 15% and 33% for minor), respectively. CONCLUSIONS/INTERPRETATION: These findings suggest that hospital admission rates for all DFD conditions are considerably higher than those for amputations alone and, thus, the more common practice of reporting admission rates only for amputations may substantially underestimate the burden of DFD. While major amputation rates appear to be largely decreasing, this is not the case for hospital admissions for DFD conditions or minor amputation in many populations. However, true global conclusions are limited because of a lack of consistent definitions used to identify admission rates for DFD conditions and amputations, alongside a lack of data from low- and middle-income countries. We recommend that these areas are addressed in future studies. REGISTRATION: This review was registered in the Open Science Framework database ( https://doi.org/10.17605/OSF.IO/4TZFJ ).

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.

Long-term cost-effectiveness of implementing a lifestyle intervention during pregnancy to reduce the incidence of gestational diabetes and type 2 diabetes.

AIMS/HYPOTHESIS: The aim of this study was to determine the long-term cost-effectiveness and return on investment of implementing a structured lifestyle intervention to reduce excessive gestational weight gain and associated incidence of gestational diabetes mellitus (GDM) and type 2 diabetes mellitus. METHODS: A decision-analytic Markov model was used to compare the health and cost-effectiveness outcomes for (1) a structured lifestyle intervention during pregnancy to prevent GDM and subsequent type 2 diabetes; and (2) current usual antenatal care. Life table modelling was used to capture type 2 diabetes morbidity, mortality and quality-adjusted life years over a lifetime horizon for all women giving birth in Australia. Costs incorporated both healthcare and societal perspectives. The intervention effect was derived from published meta-analyses. Deterministic and probabilistic sensitivity analyses were used to capture the impact of uncertainty in the model. RESULTS: The model projected a 10% reduction in the number of women subsequently diagnosed with type 2 diabetes through implementation of the lifestyle intervention compared with current usual care. The total net incremental cost of intervention was approximately AU$70 million, and the cost savings from the reduction in costs of antenatal care for GDM, birth complications and type 2 diabetes management were approximately AU$85 million. The intervention was dominant (cost-saving) compared with usual care from a healthcare perspective, and returned AU$1.22 (95% CI 0.53, 2.13) per dollar invested. The results were robust to sensitivity analysis, and remained cost-saving or highly cost-effective in each of the scenarios explored. CONCLUSIONS/INTERPRETATION: This study demonstrates significant cost savings from implementation of a structured lifestyle intervention during pregnancy, due to a reduction in adverse health outcomes for women during both the perinatal period and over their lifetime.

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.

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.

Dairy Product Consumption and Incident Prediabetes in the Australian Diabetes, Obesity, and Lifestyle Study With 12 Years of Follow-Up.

BACKGROUND: Investigating modifiable risk factors for the early stages of the development of type 2 diabetes is essential for effective prevention. Some studies show protective associations between dairy and prediabetes; however, associations are heterogeneous by the type and fat content of dairy foods. OBJECTIVE: To examine the relationship between the consumption of dairy, including different types of dairy products and risk of prediabetes. METHODS: The study included 4891 participants with normal glucose tolerance (aged 49.0 ± 12.3 y, 57% female) of the Australian Diabetes, Obesity, and Lifestyle (AusDiab) study, a longitudinal population-based study. Dairy intake was measured at baseline using a food frequency questionnaire. Prediabetes at the 5-y and 12-y follow-ups was defined according to the WHO criteria as fasting plasma glucose levels of 110-125 mg/dL or 2-h plasma glucose levels of 140-199 mg/dL. Associations were analyzed using Poisson regression, adjusted for social demographics, lifestyle behaviors, a family history of diabetes, and food group intake. RESULTS: In total, 765 (15.6%) incident cases of prediabetes were observed. The mean intake of dairy foods was 2.4 ± 1.2 servings/d, mostly consisting of low-fat milk (0.70 ± 0.78 servings/d) and high-fat milk (0.47 ± 0.72 servings/d). A higher intake of high-fat dairy (RRservings/d: 0.92; 95% CI: 0.85, 1.00), high-fat milk (0.89; 95% CI: 0.80, 0.99), and total cheese (0.74; 95% CI: 0.56, 0.96) was associated with a lower risk of prediabetes. Low-fat milk intake was associated nonlinearly with prediabetes risk. Low-fat dairy foods, total milk, yogurt, low-fat cheese, and ice cream were not associated with prediabetes risk. CONCLUSION: In this large Australian cohort, protective associations were found for high-fat dairy types, whereas neutral associations were seen for low-fat dairy types. Studies with more detail on sugar content of types of dairy foods and products eaten with dairy foods (e.g., cereals or jam), and studies into potential causal mechanisms of the health effects of dairy intake are required.

The T1D Index: Implications of Initial Results, Data Limitations, and Future Development.

PURPOSE OF THE REVIEW: Current global information on incidence, prevalence, and mortality of type 1 diabetes (T1D) is limited, particularly in low- and middle-income countries. To address this gap in evidence, JDRF, Life for a Child, International Society for Pediatric and Adolescent Diabetes, and International Diabetes Federation have developed the T1D Index, which uses a Markov mathematical model, and machine learning and all available data to provide global estimates of the burden on T1D. This review assesses the methodology, limitations, current findings, and future directions of the Index. RECENT FINDINGS: Global prevalence was estimated at 8.4 million in 2021, with 1.5 million <20 years (y). T1D prevalence varied from 1.5 to 534 per 100,000, with T1D accounting for <0.1-17.8% of all diabetes in different countries. A total of 35,000 young people <25 y are estimated to have died at clinical onset of T1D from non-diagnosis. An estimated 435,000 people <25 y were receiving "minimal care." Health-adjusted life years (HALYs) lost for individuals diagnosed with T1D at age 10 y in 2021 ranged from 14 to 55 y. These results show that interventions to reduce deaths from non-diagnosis, and improve access to at least an intermediate care level, are needed to reduce projected life years lost. The results have significant uncertainties due to incomplete data across the required inputs. Obtaining recent incidence, prevalence, and mortality data, as well as addressing data quality issues, misdiagnoses, and the lack of adult data, is essential for maintaining and improving accuracy. The index will be updated regularly as new data become available.

Correction: High-coverage plasma lipidomics reveals novel sex-specific lipidomic fingerprints of age and BMI: Evidence from two large population cohort studies.

[This corrects the article DOI: 10.1371/journal.pbio.3000870.].