P Zimmet

Baker IDI Heart and Diabetes Institute, Melbourne, Victoria, Australia

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Publications (627)3655.59 Total impact

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    ABSTRACT: De Taskforce Epidemiologie en Preventie van de International Diabetes Federation heeft een consensus-werkgroep bijeengebracht bestaande uit diabetologen, endocrinologen, chirurgen en epidemiologen om te beoordelen welke rol bariatrische chirurgie en andere gastrointestinale interventies horen te krijgen in de behandeling en preventie van type 2 diabetes.
    12/2015; 10(4):195-196. DOI:10.1007/s12467-012-0146-4
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    ABSTRACT: The prevalence of diabetes has risen rapidly in the Middle East, and in the Gulf Region in particular. However, some of the prevalence estimates have not fully accounted for the large migrant worker populations, and have focused on the minority indigenous populations. The objectives of the UAE National Diabetes and Lifestyle Study are to: define the prevalence of, and risk factors for, type 2 diabetes; describe the distribution and determinants of risk factors for type 2 diabetes (e.g. obesity, hypertension, physical activity, age, diet, smoking, serum lipids); study health knowledge, attitudes and behaviors, including patterns of health services utilization; identify gene-environment interactions in our multiethnic communities; and develop baseline data for evaluation of future intervention programs. Given the high burden of diabetes in the region and the absence of accurate data on non-UAE nationals in the UAE, a representative sample of the non-UAE nationals was essential. We employed an innovative methodology in which non-UAE nationals were sampled when attending the mandatory bi-annual health check that is required for visa renewal. Such an approach could also be used in other countries in the region. This novel methodology could provide insights for epidemiological studies in the UAE and other Gulf States particularly for expatriates. This article is protected by copyright. All rights reserved.
    Journal of Diabetes 01/2015; DOI:10.1111/1753-0407.12270 · 2.35 Impact Factor
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    ABSTRACT: Current computational methods used to analyze changes in DNA methylation and chromatin modification rely on sequenced genomes. Here we describe a pipeline for the detection of these changes from short-read sequence data that does not require a reference genome. Open source software packages were used for sequence assembly, alignment, and measurement of differential enrichment. The method was evaluated by comparing results with reference-based results showing a strong correlation between chromatin modification and gene expression. We then used our de novo sequence assembly to build the DNA methylation profile for the non-referenced Psammomys obesus genome. The pipeline described uses open source software for fast annotation and visualization of unreferenced genomic regions from short-read data.
    Epigenetics: official journal of the DNA Methylation Society 10/2014; 9(10):1329-38. DOI:10.4161/15592294.2014.969610 · 5.11 Impact Factor
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    ABSTRACT: AimsTo investigate if consumption of pulses was associated with a reduced risk of developing abnormal glucose metabolism, increases in body weight and increases in waist circumference in a multi-ethnic cohort in Mauritius.Methods Population-based surveys were performed in Mauritius in 1992 and in 1998. Pulse consumption was estimated from a food frequency questionnaire in 1992 and outcomes were measured in 1998. At both time points, anthropometry was undertaken and an oral glucose tolerance test was performed.ResultsMauritian women with the highest consumption of pulses (highest tertile) had a reduced risk of developing abnormal glucose metabolism [odds ratio 0.52; 95% CI 0.27, 0.99) compared with those with the lowest consumption, and also after multivariable adjustments. In women, a high consumption of pulses was associated with a smaller increase in BMI.Conclusions High consumption of pulses was associated with a reduced risk of abnormal glucose metabolism and a smaller increase in BMI in Mauritian women. Promotion of pulse consumption could be an important dietary intervention for the prevention of Type 2 diabetes and obesity in Mauritius and should be examined in other populations and in clinical trials.This article is protected by copyright. All rights reserved.
    Diabetic Medicine 10/2014; 32(4). DOI:10.1111/dme.12618 · 3.06 Impact Factor
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    Adrian J Cameron, Paul Z Zimmet
    The Medical journal of Australia 07/2014; 201(1):25-26. DOI:10.5694/mja14.00553 · 3.79 Impact Factor
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    ABSTRACT: It is believed that diabetes risk scores need to be ethnic specific. However, this prerequisite has not been tested. We examined the performance of several risk models, developed in various populations, in a Europid and a South Asian population. The performance of 14 published risk prediction models were tested in two prospective studies: the Australian Diabetes, Obesity and Lifestyle (AusDiab) study and the Mauritius non-communicable diseases survey. Eight models were developed in Europid populations; the remainder in various non-Europid populations. Model performance was assessed using area under the receiver operating characteristic curves (discrimination), Hosmer-Lemeshow tests (goodness-of-fit) and Brier scores (accuracy). In both AusDiab and Mauritius, discrimination was highest for a model developed in a mixed population (non-Hispanic white and African American) and lowest for a model developed in a Europid population. Discrimination for all scores was higher in AusDiab than in Mauritius. For almost all models, goodness-of-fit was poor irrespective of the ethnicity of the development cohort, and accuracy was higher in AusDiab compared to Mauritius. Our results suggest that similarity of ethnicity or similarity of diabetes risk may not be the best way of identifying models that will perform well in another population. Differences in study methodology likely account for much of the difference in the performance. Thus, identifying models which use measurements that are clearly described and easily reproducible for both research and clinical settings may be more important.
    Acta Diabetologica 07/2014; 52(1). DOI:10.1007/s00592-014-0607-x · 3.68 Impact Factor
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    ABSTRACT: Context: Adipokines actuate chronic, low-grade inflammation through a complex network of immune markers but the current understanding of these networks is incomplete. The soluble isoform of the interleukin-1 receptor accessory protein (sIL1RAP) occupies an important position in the inflammatory pathways involved in obesity. The pathogenetic and clinical influences of sIL1RAP are unknown. Objective: To elucidate whether plasma levels of sIL1RAP are reduced in obesity, using affluent clinical, biochemical and genetic data from two diverse cohorts. Design, Setting and Participants: The study was conducted in two cohorts - the San Antonio Family Heart Study (n = 1,397 individuals from 42 families) and South Asians living in Mauritius n = 230). Main outcome measures: Plasma sIL1RAP levels were measured using an enzyme-linked immunosorbent assay. The genetic basis of sIL1RAP levels were investigated using both a large scale gene expression profiling study and a genome-wide association study. Results: A significant decrease in plasma sIL1RAP levels were observed in obese subjects even after adjustment for age and sex. sIL1RAP levels demonstrated a strong inverse association with obesity measures in both populations. All associations were more significant in females. Plasma sIL1RAP levels were significantly heritable, correlated with IL1RAP transcript levels (NM 134470), showed evidence for shared genetic influences with obesity measures and were significantly associated with the rs2885373 SNP (p=6.7 x 10(-23)) within the IL1RAP gene. Conclusions: Plasma sIL1RAP levels are reduced in obesity and can potentially act as biomarkers of obesity. Mechanistic studies are required to understand the exact contribution of sIL1RAP to pathogenesis of obesity.
    Journal of Clinical Endocrinology &amp Metabolism 06/2014; 99(9):jc20134475. DOI:10.1210/jc.2013-4475 · 6.31 Impact Factor
  • 35th Annual Scientific Meeting of the; 06/2014
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    ABSTRACT: Background: Bioelectrical impedance (BIA) represents a simple, inexpensive and non-invasive method that is often used to assess fat-mass (FM) and fat-free mass (FFM) in large population-based cohorts. Objective: The aim of this study was to describe the reference ranges and examine the influence of age and gender on FM, FFM and skeletal muscle mass (SMM) as well as height-adjusted estimates of FM [fat mass index (FMI)], FFM [fat-free mass index (FFMI)] and SMM [SMM index (SMI)] in a national, population-based cohort of Australian adults. Design and Participants: The analytical sample included a total of 8,582 adults aged 25-91 years of Europid origin with complete data involved in the cross-sectional 1999-2000 Australian, Diabetes, Obesity and Lifestyle (AusDiab) Study. Measurements: Bioelectrical impedance analysis was used to examine components of body composition. Demographic information was derived from a household interview. Results: For both genders, FFM, SMM and SMI decreased linearly from the age of 25 years, with the exception that in men SMI was not related to age and FFM peaked at age 38 years before declining thereafter. The relative loss from peak values to ≥75 years in FFM (6-8%) and SMM (11-15%) was similar between men and women. For FM and FMI, there was a curvilinear relationship with age in both genders, but peak values were detected 6-7 years later in women with a similar relative loss thereafter. For FFMI there was no change with age in men and a modest increase in women. Conclusion: In Australian adults there is heterogeneity in the age of onset, pattern and magnitude of changes in the different measures of muscle and fat mass derived from BIA, but overall the age-related losses were similar between men and women.
    The Journal of Nutrition Health and Aging 05/2014; 18(5):540-546. DOI:10.1007/s12603-014-0464-x · 2.66 Impact Factor
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    ABSTRACT: To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.
    Nature Genetics 03/2014; 46(3):234-244. DOI:10.1038/ng.2897 · 29.65 Impact Factor
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    ABSTRACT: Cardiovascular disease poses a major challenge for the 21st century, exacerbated by the pandemics of obesity, metabolic syndrome and type 2 diabetes. While best standards of care, including high-dose statins, can ameliorate the risk of vascular complications, patients remain at high risk of cardiovascular events. The Residual Risk Reduction Initiative (R3i) has previously highlighted atherogenic dyslipidaemia, defined as the imbalance between proatherogenic triglyceride-rich apolipoprotein B-containing-lipoproteins and antiatherogenic apolipoprotein A-I-lipoproteins (as in high-density lipoprotein, HDL), as an important modifiable contributor to lipid-related residual cardiovascular risk, especially in insulin-resistant conditions. As part of its mission to improve awareness and clinical management of atherogenic dyslipidaemia, the R3i has identified three key priorities for action: i) to improve recognition of atherogenic dyslipidaemia in patients at high cardiometabolic risk with or without diabetes; ii) to improve implementation and adherence to guideline-based therapies; and iii) to improve therapeutic strategies for managing atherogenic dyslipidaemia. The R3i believes that monitoring of non-HDL cholesterol provides a simple, practical tool for treatment decisions regarding the management of lipid-related residual cardiovascular risk. Addition of a fibrate, niacin (North and South America), omega-3 fatty acids or ezetimibe are all options for combination with a statin to further reduce non-HDL cholesterol, although lacking in hard evidence for cardiovascular outcome benefits. Several emerging treatments may offer promise. These include the next generation peroxisome proliferator-activated receptoralpha agonists, cholesteryl ester transfer protein inhibitors and monoclonal antibody therapy targeting proprotein convertase subtilisin/kexin type 9. However, long-term outcomes and safety data are clearly needed. In conclusion, the R3i believes that ongoing trials with these novel treatments may help to define the optimal management of atherogenic dyslipidaemia to reduce the clinical and socioeconomic burden of residual cardiovascular risk.
    Cardiovascular Diabetology 01/2014; 13(1):26. DOI:10.1186/1475-2840-13-26 · 3.71 Impact Factor
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    ABSTRACT: To assess in a single cohort whether annual weight and waist circumference (WC) change has varied over time. Longitudinal cohort study with three surveys (1) 1999/2000; (2) 2004/2005 and (3) 2011/2012. Generalised linear mixed models with random effects were used to compare annualised weight and WC change between surveys 1 and 2 (period 1) with that between surveys 2 and 3 (period 2). Models were adjusted for age to analyse changes with time rather than age. Models were additionally adjusted for sex, education status, area-level socioeconomic disadvantage, ethnicity, body mass index, diabetes status and smoking status. The Australian Diabetes, Obesity and Lifestyle study (AusDiab)-a population-based, stratified-cluster survey of 11247 adults aged ≥25 years. 3351 Australian adults who attended each of three surveys and had complete measures of weight, WC and covariates. Weight and WC were measured at each survey. Change in weight and WC was annualised for comparison between the two periods. Mean weight and WC increased in both periods (0.34 kg/year, 0.43 cm/year period 1; 0.13 kg/year, 0.46 cm/year period 2). Annualised weight gain in period 2 was 0.11 kg/year (95% CI 0.06 to 0.15) less than period 1. Lesser annual weight gain between the two periods was not seen for those with greatest area-level socioeconomic disadvantage, or in men over the age of 55. In contrast, the annualised WC increase in period 2 was greater than period 1 (0.07 cm/year, 95% CI 0.01 to 0.12). The increase was greatest in men aged 55+ years and those with a greater area-level socioeconomic disadvantage. Between 2004/2005 and 2011/2012, Australian adults in a national study continued to gain weight, but more slowly than 1999/2000-2004/2005. While weight gain may be slowing, this was not observed for older men or those in more disadvantaged groups, and the same cannot be said for WC.
    BMJ Open 01/2014; 4(1):e003667. DOI:10.1136/bmjopen-2013-003667 · 2.06 Impact Factor
  • K George M M Alberti, Paul Z Zimmet
    01/2014; 2(1):e1-2. DOI:10.1016/S2213-8587(13)70187-6
  • BMC Health Services Research 01/2014; 14(Suppl 2):P33. DOI:10.1186/1472-6963-14-S2-P33 · 1.66 Impact Factor
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    ABSTRACT: The number of people with diabetes worldwide has more than doubled during the past 20 years. One of the most worrying features of this rapid increase is the emergence of type 2 diabetes in children, adolescents, and young adults. Although the role of traditional risk factors for type 2 diabetes (eg, genetic, lifestyle, and behavioural risk factors) has been given attention, recent research has focused on identifying the contributions of epigenetic mechanisms and the effect of the intrauterine environment. Epidemiological data predict an inexorable and unsustainable increase in global health expenditure attributable to diabetes, so disease prevention should be given high priority. An integrated approach is needed to prevent type 2 diabetes, taking into account its many origins and heterogeneity. Thus, research needs to be directed at improved understanding of the potential role of determinants such as the maternal environment and other early life factors, as well as changing trends in global demography, to help shape disease prevention programmes.
    01/2014; 2(1):56-64. DOI:10.1016/S2213-8587(13)70112-8
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    ABSTRACT: Diabetes in pregnancy carries an increased risk of adverse pregnancy outcomes for both the mother and foetus, but it also provides an excellent early opportunity for intervention in the life course for both mother and baby. In the context of the escalating epidemic of chronic diseases among Indigenous Australians, it is vital that this risk is reduced as early as possible in the life course of the individual. The aims of the PANDORA Study are to: (i) accurately assess rates of diabetes in pregnancy in the Northern Territory (NT) of Australia, where 38% of babies are born to Indigenous mothers; (ii) assess demographic, clinical, biochemical, anthropometric, socioeconomic and early life development factors that may contribute to key maternal and neonatal birth outcomes associated with diabetes in pregnancy; and (iii) monitor relevant post-partum clinical outcomes for both the mothers and their babies.Methods/design: Eligible participants are all NT women with diabetes in pregnancy aged 16 years and over. Information collected includes: standard antenatal clinical information, diagnosis and management of diabetes in pregnancy, socio-economic status, standard clinical birth information (delivery, gestational age, birth weight, adverse antenatal and birth outcomes). Cord blood is collected at the time of delivery and detailed neonatal anthropometric measurements performed within 72 hours of birth. Information will also be collected regarding maternal post-partum glucose tolerance and cardio-metabolic risk factor status, breastfeeding and growth of the baby up to 2 years post-partum in the first instance. This study will accurately document rates and outcomes of diabetes in pregnancy in the NT of Australia, including the high-risk Indigenous Australian population. The results of this study should contribute to policy and clinical guidelines with the goal of reducing the future risk of obesity and diabetes in both mothers and their offspring.
    BMC Pregnancy and Childbirth 12/2013; 13(1):221. DOI:10.1186/1471-2393-13-221 · 2.15 Impact Factor
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    ABSTRACT: India currently has more than 60 million people with Type 2 Diabetes Mellitus (T2DM) and this is predicted to increase by nearly two-thirds by 2030. While management of those with T2DM is important, preventing or delaying the onset of the disease, especially in those individuals at 'high risk' of developing T2DM, is urgently needed, particularly in resource-constrained settings. This paper describes the protocol for a cluster randomised controlled trial of a peer-led lifestyle intervention program to prevent diabetes in Kerala, India.Methods/designA total of 60 polling booths are randomised to the intervention arm or control arm in rural Kerala, India. Data collection is conducted in two steps. Step 1 (Home screening): Participants aged 30--60 years are administered a screening questionnaire. Those having no history of T2DM and other chronic illnesses with an Indian Diabetes Risk Score value of >=60 are invited to attend a mobile clinic (Step 2). At the mobile clinic, participants complete questionnaires, undergo physical measurements, and provide blood samples for biochemical analysis. Participants identified with T2DM at Step 2 are excluded from further study participation. Participants in the control arm are provided with a health education booklet containing information on symptoms, complications, and risk factors of T2DM with the recommended levels for primary prevention. Participants in the intervention arm receive: (1) eleven peer led small group sessions to motivate, guide and support in planning, initiation and maintenance of lifestyle changes; (2) two diabetes prevention education sessions led by experts to raise awareness on T2DM risk factors, prevention and management; (3) a participant handbook containing information primarily on peer support and its role in assisting with lifestyle modification; (4) a participant workbook to guide self-monitoring of lifestyle behaviours, goal setting and goal review; (5) the health education booklet that is given to the control arm. Follow-up assessments are conducted at 12 and 24 months. The primary outcome is incidence of T2DM. Secondary outcomes include behavioural, psychosocial, clinical, and biochemical measures. An economic evaluation is planned. Results from this trial will contribute to improved policy and practice regarding lifestyle intervention programs to prevent diabetes in India and other resource-constrained settings.Trial registrationAustralia and New Zealand Clinical Trials Registry: ACTRN12611000262909.
    BMC Public Health 11/2013; 13(1):1035. DOI:10.1186/1471-2458-13-1035 · 2.32 Impact Factor
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    ABSTRACT: A significant proportion of individuals with diabetes or impaired glucose tolerance have fasting plasma glucose less than 6.1 mmol/L and so are not identified with fasting plasma glucose measurements. In this study, we sought to evaluate the utility of plasma lipids to improve on fasting plasma glucose and other standard risk factors for the identification of type 2 diabetes or those at increased risk (impaired glucose tolerance). Our diabetes risk classification model was trained and cross-validated on a cohort 76 individuals with undiagnosed diabetes or impaired glucose tolerance and 170 gender and body mass index matched individuals with normal glucose tolerance, all with fasting plasma glucose less than 6.1 mmol/L. The inclusion of 21 individual plasma lipid species to triglycerides and HbA1c as predictors in the diabetes risk classification model resulted in a statistically significant gain in area under the receiver operator characteristic curve of 0.049 (p<0.001) and a net reclassification improvement of 10.5% (p<0.001). The gain in area under the curve and net reclassification improvement were subsequently validated on a separate cohort of 485 subjects. Plasma lipid species can improve the performance of classification models based on standard lipid and non-lipid risk factors.
    PLoS ONE 10/2013; 8(10):e76577. DOI:10.1371/journal.pone.0076577 · 3.53 Impact Factor
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    ABSTRACT: The relationship between lipid metabolism with prediabetes (impaired fasting glucose and impaired glucose tolerance) and type 2 diabetes mellitus is poorly defined. We hypothesized that a lipidomic analysis of plasma lipids might improve the understanding of this relationship. We performed lipidomic analysis measuring 259 individual lipid species, including sphingolipids, phospholipids, glycerolipids and cholesterol esters, on fasting plasma from 117 type 2 diabetes, 64 prediabetes and 170 normal glucose tolerant participants in the Australian Diabetes, Obesity and Lifestyle Study (AusDiab) then validated our findings on 1076 individuals from the San Antonio Family Heart Study (SAFHS). Logistic regression analysis of identified associations with type 2 diabetes (135 lipids) and prediabetes (134 lipids), after adjusting for multiple covariates. In addition to the expected associations with diacylglycerol, triacylglycerol and cholesterol esters, type 2 diabetes and prediabetes were positively associated with ceramide, and its precursor dihydroceramide, along with phosphatidylethanolamine, phosphatidylglycerol and phosphatidylinositol. Significant negative associations were observed with the ether-linked phospholipids alkylphosphatidylcholine and alkenylphosphatidylcholine. Most of the significant associations in the AusDiab cohort (90%) were subsequently validated in the SAFHS cohort. The aberration of the plasma lipidome associated with type 2 diabetes is clearly present in prediabetes, prior to the onset of type 2 diabetes. Lipid classes and species associated with type 2 diabetes provide support for a number of existing paradigms of dyslipidemia and suggest new avenues of investigation.
    PLoS ONE 09/2013; 8(9):e74341. DOI:10.1371/journal.pone.0074341 · 3.53 Impact Factor
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    ABSTRACT: The relationships between smoking and glycaemic variables have not been well explored. We compared HbA1c, fasting plasma glucose (FPG) and 2 h plasma glucose (2H-PG) in current, ex- and never-smokers. This meta-analysis used individual data from 16,886 men and 18,539 women without known diabetes in 12 DETECT-2 consortium studies and in the French Data from an Epidemiological Study on the Insulin Resistance Syndrome (DESIR) and Telecom studies. Means of three glycaemic variables in current, ex- and never-smokers were modelled by linear regression, with study as a random factor. The I (2) statistic was used to evaluate heterogeneity among studies. HbA1c was 0.10% (95% CI 0.08, 0.12) (1.1 mmol/mol [0.9, 1.3]) higher in current smokers and 0.03% (0.01, 0.05) (0.3 mmol/mol [0.1, 0.5]) higher in ex-smokers, compared with never-smokers. For FPG, there was no significant difference between current and never-smokers (-0.004 mmol/l [-0.03, 0.02]) but FPG was higher in ex-smokers (0.12 mmol/l [0.09, 0.14]). In comparison with never-smokers, 2H-PG was lower (-0.44 mmol/l [-0.52, -0.37]) in current smokers, with no difference for ex-smokers (0.02 mmol/l [-0.06, 0.09]). There was a large and unexplained heterogeneity among studies, with I (2) always above 50%; I (2) was little changed after stratification by sex and adjustment for age and BMI. In this study population, current smokers had a prevalence of diabetes that was 1.30% higher as screened by HbA1c and 0.52% lower as screened by 2H-PG, in comparison with never-smokers. Across this heterogeneous group of studies, current smokers had a higher HbA1c and lower 2H-PG than never-smokers. This will affect the chances of smokers being diagnosed with diabetes.
    Diabetologia 09/2013; 57(1). DOI:10.1007/s00125-013-3058-y · 6.88 Impact Factor

Publication Stats

49k Citations
3,655.59 Total Impact Points


  • 2008–2014
    • Baker IDI Heart and Diabetes Institute
      • Clinical Diabetes and Epidemiology Research Group
      Melbourne, Victoria, Australia
    • Aintree University Hospital NHS Foundation Trust
      Liverpool, England, United Kingdom
    • Royal Prince Alfred Hospital
      Camperdown, New South Wales, Australia
    • The George Institute for Global Health
      Sydney, New South Wales, Australia
    • University of Wisconsin, Madison
      • Department of Ophthalmology and Visual Sciences
      Mississippi, United States
    • University of Western Australia
      Perth City, Western Australia, Australia
    • Umeå University
      • Department of Public Health and Clinical Medicine
      Umeå, Västerbotten, Sweden
    • Université du Droit et de la Santé Lille 2
      Lille, Nord-Pas-de-Calais, France
  • 2012–2013
    • The Kings College
      Denmark, South Carolina, United States
  • 1992–2012
    • University of Vic
      Vic, Catalonia, Spain
  • 1989–2012
    • Monash University (Australia)
      • • Department of Epidemiology and Preventive Medicine
      • • School of Public Health and Preventive Medicine
      • • Department of Biochemistry and Molecular Biology
      Melbourne, Victoria, Australia
    • Papua New Guinea Institute of Medical Research
      New Garoka, Eastern Highlands, Papua New Guinea
  • 2007–2011
    • University of Queensland 
      • Cancer Prevention Research Centre
      Brisbane, Queensland, Australia
    • Baker College, Australia
      Hornsby, New South Wales, Australia
  • 1999–2011
    • University of Melbourne
      • • Department of Medicine
      • • Department of Rural Health
      Melbourne, Victoria, Australia
  • 1996–2010
    • Melbourne Institute of Technology
      Melbourne, Victoria, Australia
    • Hospital Clínico San Carlos
      Madrid, Madrid, Spain
  • 2009
    • Singapore Eye Research Institute
      Tumasik, Singapore
  • 1999–2009
    • Newcastle University
      Newcastle-on-Tyne, England, United Kingdom
  • 1992–2009
    • University of Sydney
      • School of Public Health
      Sydney, New South Wales, Australia
  • 1982–2008
    • Diabetes Australia, Victoria
      Melbourne, Victoria, Australia
  • 2006–2007
    • Imperial College Healthcare NHS Trust
      Londinium, England, United Kingdom
    • Imperial College London
      Londinium, England, United Kingdom
  • 1998–2006
    • Deakin University
      • • School of Exercise and Nutrition Sciences
      • • School of Health and Social Development
      Geelong, Victoria, Australia
    • Western Australia Health
      Perth City, Western Australia, Australia
    • University of Minnesota Duluth
      Duluth, Minnesota, United States
  • 2005
    • The Queen Elizabeth Hospital
      Tarndarnya, South Australia, Australia
    • Southwest Foundation For Biomedical Research
      San Antonio, Texas, United States
    • Mount Sinai Hospital
      New York City, New York, United States
  • 2004
    • Prince of Wales Hospital and Community Health Services
      Sydney, New South Wales, Australia
  • 2003
    • National Institutes of Health
      Maryland, United States
    • Melbourne Pathology
      Melbourne, Victoria, Australia
  • 2002
    • Sir Charles Gairdner Hospital
      Perth City, Western Australia, Australia
    • Sahlgrenska University Hospital
      Goeteborg, Västra Götaland, Sweden
  • 1988–1996
    • National Public Health Institute
      Helsinki, Southern Finland Province, Finland
  • 1995
    • University of Tasmania
      • Menzies Research Institute
      Hobart Town, Tasmania, Australia
    • Mahidol University
      Krung Thep, Bangkok, Thailand
    • Victoria University Melbourne
      Melbourne, Victoria, Australia
  • 1988–1990
    • Melbourne Water
      Melbourne, Victoria, Australia
  • 1979–1989
    • Royal Melbourne Hospital
      Melbourne, Victoria, Australia
  • 1987
    • Australian National University
      Canberra, Australian Capital Territory, Australia
  • 1984
    • St. Vincent's Hospital Melbourne
      Melbourne, Victoria, Australia
    • University of Kuopio
      Kuopio, Eastern Finland Province, Finland
  • 1978–1981
    • Alfred Hospital
      Melbourne, Victoria, Australia