T A Welborn

Sir Charles Gairdner Hospital, Perth City, Western Australia, Australia

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Publications (82)340.06 Total impact

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    Satvinder S Dhaliwal, Timothy A Welborn, Peter A Howat
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    ABSTRACT: To assess the role of body adiposity index (BAI) in predicting cardiovascular disease (CVD) and coronary heart disease (CHD) mortality, in comparison with body mass index (BMI), waist circumference (WC), and the waist circumference to hip circumference ratio (WHR). This study was a prospective 15 year mortality follow-up of 4175 Australian males, free of heart disease, diabetes and stroke. The Framingham Risk Scores (FRS) for CHD and CVD death were calculated at baseline for all subjects. Multivariable logistic regression was used to assess the effects of the measures of obesity on CVD and CHD mortality, before adjustment and after adjustment for FRS. The predictive ability of BAI, though present in the unadjusted analyses, was generally not significant after adjustment for age and FRS for both CVD and CHD mortality. BMI behaved similarly to BAI in that its predictive ability was generally not significant after adjustments. Both WC and WHR were significant predictors of CVD and CHD mortality and remained significant after adjustment for covariates. BAI appeared to be of potential interest as a measure of % body fat and of obesity, but was ineffective in predicting CVD and CHD.
    PLoS ONE 01/2014; 9(4):e94560. · 3.53 Impact Factor
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    ABSTRACT: It is important to ascertain which anthropometric measurements of obesity, general or central, are better predictors of cardiovascular disease (CVD) risk in women. 10-year CVD risk was calculated from the Framingham risk score model, SCORE risk chart for high-risk regions, general CVD and simplified general CVD risk score models. Increase in CVD risk associated with 1 SD increment in each anthropometric measurement above the mean was calculated, and the diagnostic utility of obesity measures in identifying participants with increased likelihood of being above the treatment threshold was assessed. Cross-sectional data from the National Heart Foundation Risk Factor Prevalence Study. Population-based survey in Australia. 4487 women aged 20-69 years without heart disease, diabetes or stroke. Anthropometric obesity measures that demonstrated the greatest increase in CVD risk as a result of incremental change, 1 SD above the mean, and obesity measures that had the greatest diagnostic utility in identifying participants above the respective treatment thresholds of various risk score models. Waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-stature ratio had larger effects on increased CVD risk compared with body mass index (BMI). These central obesity measures also had higher sensitivity and specificity in identifying women above and below the 20% treatment threshold than BMI. Central obesity measures also recorded better correlations with CVD risk compared with general obesity measures. WC and WHR were found to be significant and independent predictors of CVD risk, as indicated by the high area under the receiver operating characteristic curves (>0.76), after controlling for BMI in the simplified general CVD risk score model. Central obesity measures are better predictors of CVD risk compared with general obesity measures in women. It is equally important to maintain a healthy weight and to prevent central obesity concurrently.
    BMJ Open 01/2014; 4(2):e004138. · 1.58 Impact Factor
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    ABSTRACT: Although elevated cardiovascular disease (CVD) risk factors are associated with a higher risk of developing heart conditions across all ethnic groups, variations exist between groups in the distribution and association of risk factors, and also risk levels. This study assessed the 10-year predicted risk in a multiethnic cohort of women and compared the differences in risk between Asian and Caucasian women. Information on demographics, medical conditions and treatment, smoking behavior, dietary behavior, and exercise patterns were collected. Physical measurements were also taken. The 10-year risk was calculated using the Framingham model, SCORE (Systematic COronary Risk Evaluation) risk chart for low risk and high risk regions, the general CVD, and simplified general CVD risk score models in 4,354 females aged 20-69 years with no heart disease, diabetes, or stroke at baseline from the third Australian Risk Factor Prevalence Study. Country of birth was used as a surrogate for ethnicity. Nonparametric statistics were used to compare risk levels between ethnic groups. Asian women generally had lower risk of CVD when compared to Caucasian women. The 10-year predicted risk was, however, similar between Asian and Australian women, for some models. These findings were consistent with Australian CVD prevalence. In summary, ethnicity needs to be incorporated into CVD risk assessment. Australian standards used to quantify risk and treat women could be applied to Asians in the interim. The SCORE risk chart for low-risk regions and Framingham risk score model for incidence are recommended. The inclusion of other relevant risk variables such as obesity, poor diet/nutrition, and low levels of physical activity may improve risk estimation.
    International Journal of Women's Health 01/2014; 6:259-67.
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    ABSTRACT: The objectives of this study were to determine whether the cross-sectional associations between anthropometric obesity measures, body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR), and calculated 10-year cardiovascular disease (CVD) risk using the Framingham and general CVD risk score models, are the same for women of Australian, UK and Ireland, North European, South European and Asian descent. This study would investigate which anthropometric obesity measure is most predictive at identifying women at increased CVD risk in each ethnic group.
    BMJ Open 01/2014; 4(5):e004702. · 1.58 Impact Factor
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    Satvinder S Dhaliwal, Timothy A Welborn, Peter A Howat
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    ABSTRACT: The role of physical activity in preventing CVD has been highlighted by Professor Jerry Morris in the 1950's. We report outcome of a 15-year prospective study with the aim to identify whether physical activity showed cardiovascular benefit independent of common risk factors and of central obesity. Baseline data of 8662 subjects, with no previous history of heart disease, diabetes or stroke, were obtained from an age- and gender- stratified sample of adults in Australian capital cities and were linked with the National Death Index to determine the causes of death of 610 subjects who had died to 31 December 2004. The study consisted of 4175 males (age 42.3±13.1 years) and 4487 females (age 42.8±13.2 years). Fasting serum lipid levels, systolic and diastolic blood pressure and smoking habits at baseline were recorded. The Framingham Risk Scores of 15-year mortality due to CHD and CVD were calculated using established equations. Subjects were also asked if they engaged in vigorous exercise, less vigorous exercise or walk for recreation and exercise in the past 2 weeks. Subjects in the high recreational physical activity category were 0.16 (0.06-0.43; p<0.001) and 0.12 (0.03-0.48; p = 0.003) times as likely as subjects in the low category for CVD and CHD mortality respectively. After adjusting for both the Framingham Risk Score and central obesity (Waist circumference to Hip circumference Ratio), those in the high recreational physical activity group were 0.35 (0.13-0.98) times less likely compared to the low category for CVD mortality. Recreational physical activity independently predicted reduced cardiovascular mortality over fifteen years. A public health focus on increased physical activity and preventing obesity is required to reduce the risk of CVD and CHD.
    PLoS ONE 01/2013; 8(12):e83435. · 3.53 Impact Factor
  • Timothy A Welborn, Satvinder S Dhaliwal
    The Medical journal of Australia 04/2011; 194(8):429-30. · 2.85 Impact Factor
  • Timothy A Welborn, Satvinder S Dhaliwal
    New England Journal of Medicine 02/2011; 364(8):781; author reply 782-3. · 51.66 Impact Factor
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    ABSTRACT: To assess the adequacy of self-reported weight and height as indicators for BMI in community-based obesity control programs. Self-reported and measured weight and height and calculated BMI in 6979 adults were assessed using analysis of covariance. Prevalence of obesity (BMI > 25 kg/m(2)) and overweight (25-29.9 kg/m(2)) was lower using self-reported values by 3.2% and 5.0%, respectively. Females underreported BMI more than males did; and older subjects, more than younger subjects. Self-reported weight and height measurements may be used for the evaluation of community-based obesity control programs with the application of correction factors. This will minimize costs associated with physical measurements.
    American journal of health behavior 04/2010; 34(4):489-99. · 1.31 Impact Factor
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    ABSTRACT: We assessed whether the relationships between insulin sensitivity and all-cause mortality as well as fatal or non-fatal cardiovascular disease (CVD) events are independent of elevated blood glucose, high blood pressure, dyslipidaemia and body composition in individuals without diagnosed diabetes. Between 1999 and 2000, baseline fasting insulin, glucose and lipids, 2 h plasma glucose, HbA(1c), anthropometrics, blood pressure, medication use, smoking and history of CVD were collected from 8,533 adults aged >35 years from the population-based Australian Diabetes, Obesity and Lifestyle study. Insulin sensitivity was estimated by HOMA of insulin sensitivity (HOMA-%S). Deaths and fatal or non-fatal CVD events were ascertained through linkage to the National Death Index and medical records adjudication. After a median of 5.0 years there were 277 deaths and 225 CVD events. HOMA-%S was not associated with all-cause mortality. Compared with the most insulin-sensitive quintile, the combined fatal or non-fatal CVD HR (95% CI) for quintiles of decreasing HOMA-%S were 1.1 (0.6-1.9), 1.4 (0.9-2.3), 1.6 (1.0-2.5) and 2.0 (1.3-3.1), adjusting for age and sex. Smoking, CVD history, hypertension, lipid-lowering medication, total cholesterol and waist-to-hip ratio moderately attenuated this relationship. However, the association was rendered non-significant by adding HDL. Fasting plasma glucose, but not HOMA-%S significantly improved the prediction of CVD, beyond that seen with other risk factors. In this cohort, HOMA-%S showed no association with all-cause mortality and only a modest association with CVD events, largely explained by its association with HDL. Fasting plasma glucose was a better predictor of CVD than HOMA-%S.
    Diabetologia 11/2009; 53(1):79-88. · 6.49 Impact Factor
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    ABSTRACT: To provide an estimate of the morbidity and mortality resulting from abdominal overweight and obesity in the Australian population. Prospective, national, population-based study (the Australian Diabetes, Obesity and Lifestyle [AusDiab] study). 6072 men and women aged>or=25 years at study entry between May 1999 and December 2000, and aged<or=75 years, not pregnant and for whom there were waist circumference data at the follow-up survey between June 2004 and December 2005. Incident health outcomes (type 2 diabetes, hypertension, dyslipidaemia, the metabolic syndrome and cardiovascular diseases) at 5 years and mortality at 8 years. Comparison of outcome measures between those classified as abdominally overweight or obese and those with a normal waist circumference at baseline, and across quintiles of waist circumference, and (for mortality only) waist-to-hip ratio. Abdominal obesity was associated with odds ratios of between 2 and 5 for incident type 2 diabetes, dyslipidaemia, hypertension and the metabolic syndrome. The risk of myocardial infarction among obese participants was similarly increased in men (hazard ratio [HR], 2.75; 95% CI, 1.08-7.03), but not women (HR, 1.43; 95% CI, 0.37-5.50). Abdominal obesity-related population attributable fractions for these outcomes ranged from 13% to 47%, and were highest for type 2 diabetes. No significant associations were observed between all-cause mortality and increasing quintiles of abdominal obesity. Our findings confirm that abdominal obesity confers a considerably heightened risk for type 2 diabetes, the metabolic syndrome (as well as its components) and cardiovascular disease, and they provide important information that enables a more precise estimate of the burden of disease attributable to obesity in Australia.
    The Medical journal of Australia 09/2009; 191(4):202-8. · 2.85 Impact Factor
  • Satvinder S Dhaliwal, Timothy A Welborn
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    ABSTRACT: Our objective is to develop a parsimonious model to predict coronary heart disease (CHD) and cardiovascular disease (CVD) deaths using individual components of the Framingham risk score plus measures of central obesity. 15 year mortality follow-up of 8662 representative Australian adults in the National Heart Foundation Risk Factor Prevalence Survey of 1989, excluding those with a baseline history of heart disease, stroke or diabetes. Measures included blood pressure, fasting lipids, smoking history, body mass index (BMI), waist circumference (WC) and waist to hip ratio (WHR). Multivariable logistic regression was used to assess the effects of the Framingham risk variables and central obesity variables on cardiovascular disease mortality. Smoking status, high density lipoprotein cholesterol (HDL-C) and the total cholesterol (TC) to HDL-C ratio were significant univariate predictors of CHD deaths. These together with systolic blood pressure were significant predictors of CVD deaths. The obesity measures of WC and WHR were significant univariate predictors but BMI was not. In multivariable analyses, only smoking status and waist to hip ratio were identified as key independent risk factors for CHD and CVD deaths, although TC to HDL-C ratio contributed minimally to CHD deaths. Receiver operator characteristic (ROC) curves for the Framingham risk score in comparison to the WHR plus smoking model were virtually identical, with no added effect of the lipid ratio. The preferred model for predicting CHD and CVD deaths uses central obesity plus smoking with no added influence of measured lipids or blood pressure. A public health focus on identifying and modifying central obesity is at least as important as the measurement and treatment of lipids and hypertension.
    Preventive Medicine 09/2009; 49(2-3):153-7. · 3.50 Impact Factor
  • Satvinder S Dhaliwal, Timothy A Welborn
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    ABSTRACT: Methods of estimating central obesity are important because of the increasing frequency of obesity related diseases worldwide. Here we evaluate the precision of measuring waist circumference and the waist to hip ratio with comparisons across ethnic groups. The third Australian Risk Factor Prevalence Study (1989) of 9279 adults recorded height, weight, and Body Mass Index together with duplicate measurements of the waist and hip circumferences, the waist to hip ratio, and blood pressure levels using clearly defined survey techniques. Measurement error and precision for these variables were calculated, and comparisons were made across ethnic groups. Coefficients of variation for the waist circumference and the waist to hip ratio were less than 1% indicating good precision in comparison with quite large variability for systolic and diastolic pressure readings. Waist circumference showed increased variability in subjects with larger body build in comparison with waist to hip ratio. Equivalence tests across ethnic groups indicated that the waist to hip ratio was independent of ethnicity. Waist to hip ratio provides a superior measure of central obesity with low measurement error, high precision, and no bias over a wide range of ethnic groups. We believe that it is essential to standardize methods in the assessment of central obesity. Assessment criteria should be based on waist to hip ratio rather than waist circumference.
    Preventive Medicine 08/2009; 49(2-3):148-52. · 3.50 Impact Factor
  • Satvinder S Dhaliwal, Timothy A Welborn
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    ABSTRACT: To evaluate the role of measurements of central obesity in the multivariable prediction of cardiovascular risk using the Framingham risk scores, we studied 4,175 representative men from Australian cities, free of heart disease, stroke, and diabetes in 1989, and followed the cohort for mortality to 2004. Baseline lipids, blood pressure, and current cigarette smoking were recorded. Obesity was assessed by body mass index, waist circumference (WC), and waist-to-hip ratio (WHR) by strictly standardized methods. The Framingham equations were strong predictors of coronary heart disease (CHD) and cardiovascular disease (CVD) deaths. Of the obesity measurements, WHR and WC predicted deaths using Cox proportional hazards regression but body mass index did not. In the multivariable analyses, WHR was an independent predictor of CHD deaths, and WHR and WC were independent predictors of CVD deaths. There was little or no attenuation of hazard ratios for WHR and WC after correction for the Framingham scores. The 2 measurements of central obesity were more strongly predictive of CHD and CVD deaths in subjects at the lower levels of Framingham risk. In contrast, cigarette smoking risk appeared to contribute more in the higher Framingham risk categories. In conclusion, central obesity significantly and independently contributes to cardiovascular outcomes and to residual risk after accounting for the Framingham equations.
    The American journal of cardiology 06/2009; 103(10):1403-7. · 3.58 Impact Factor
  • E L M Barr, A M Tonkin, T A Welborn, J E Shaw
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    ABSTRACT: Epidemiological studies often rely on self-reported cardiovascular disease (CVD) information, but this may be inaccurate. We investigated the accuracy of self-reported CVD (myocardial infarction, stroke, coronary artery bypass surgery and coronary artery angioplasty) during the follow up of the Australian Diabetes, Obesity and Lifestyle (AusDiab) study. Self-reported CVD events, including the date of the event and hospital admission details, were collected with an interviewer-administered questionnaire. Of the 276 self-reported CVD events, 188 (68.1%) were verified by adjudication of medical records. Furthermore, linkage to the statewide Western Australian Hospital Morbidity Database (WAHMD) showed that CVD events were unlikely to be missed, with only 0.2% of those denying any CVD event being recorded as having had an event on the WAHMD. The adjudication of medical records was as accurate as record linkage to the WAHMD for validation of self-reported CVD, but combining the results from both methods of ascertainment improved CVD event identification.
    Internal Medicine Journal 02/2009; 39(1):49-53. · 1.82 Impact Factor
  • Diabetes Care 05/2008; 31(5):1007-14. · 7.74 Impact Factor
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    ABSTRACT: To determine the extent of gender-related differences in the prevalence of glucose intolerance for the Australian population and whether body size may explain such differences. Cross-sectional data were collected from a national cohort of 11 247 Australians aged > or = 25 years. Glucose tolerance status was assessed according to both fasting plasma glucose (FPG) and 2-h plasma glucose (2hPG) levels following a 75-g oral glucose tolerance test (OGTT). Anthropometric and glycated haemoglobin measurements were also made. Undiagnosed diabetes and non-diabetic glucose abnormalities were more prevalent among men than women when based only on the FPG results (diabetes: men 2.2%, women 1.6%, P = 0.02; impaired fasting glycaemia: men 12.3%, women 6.6%, P < 0.001). In contrast 16.0% of women and 13.0% of men had a 2hPG abnormality (either diabetes or impaired glucose tolerance, P = 0.14). Women had a mean FPG 0.3 mmol/l lower than men (P < 0.001), but 2hPG 0.3 mmol/l higher (P = 0.002) and FPG-2hPG increment 0.5 mmol/l greater (P < 0.001). The gender difference in mean 2hPG and FPG-2hPG increment disappeared following adjustment for height. For both genders, those in the shortest height quartile had 2hPG levels 0.5 mmol/l higher than the tallest quartile, but height showed almost no relationship with the FPG. Men and women had different glycaemic profiles; women had higher mean 2hPG levels, despite lower fasting levels. It appeared that the higher 2hPG levels for women related to lesser height and may be a consequence of using a fixed glucose load in the OGTT, irrespective of body size.
    Diabetic Medicine 03/2008; 25(3):296-302. · 3.24 Impact Factor
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    ABSTRACT: To compare the ability of the metabolic syndrome (MetS), a diabetes prediction model (DPM), a noninvasive risk questionnaire and individual glucose measurements to predict future diabetes. Five-year longitudinal cohort study. Tools tested included MetS definitions [World Health Organization, International Diabetes Federation, ATPIII and European Group for the study of Insulin Resistance (EGIR)], the FINnish Diabetes RIsk SCore risk questionnaire, the DPM, fasting and 2-h post load plasma glucose. Adult Australian population. A total of 5842 men and women without diabetes > or =25 years. Response 58%. A total of 224 incident cases of diabetes. In receiver operating characteristic curve analysis, the MetS was not a better predictor of incident diabetes than the DPM or measurement of glucose. The risk for diabetes among those with prediabetes but not MetS was almost triple that of those with MetS but not prediabetes (9.0% vs. 3.4%). Adjusted for component parts, the MetS was not a significant predictor of incident diabetes, except for EGIR in men [OR 2.1 (95% CI 1.2-3.7)]. A single fasting glucose measurement may be more effective and efficient than published definitions of the MetS or other risk constructs in predicting incident diabetes. Diagnosis of the MetS did not confer increased risk for incident diabetes independent of its individual components, with an exception for EGIR in men. Given these results, debate surrounding the public health utility of a MetS diagnosis, at least for identification of incident diabetes, is required.
    Journal of Internal Medicine 02/2008; 264(2):177-86. · 6.46 Impact Factor
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    T A Welborn, S S Dhaliwal
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    ABSTRACT: To define the clinical measures of obesity that best predict all cause mortality and cardiovascular disease (CVD) mortality. Eleven-year mortality follow-up of an Australian urban population sample of 9309 adults aged 20-69 years in 1989. Baseline measures of obesity included body mass index (BMI), waist circumference (WC), waist-to-stature ratio and the waist-to-hip ratio. The age-standardized hazard ratios for mortality were calculated for 1 s.d. above the mean for each measure of obesity using Cox regression analysis. We constructed receiver operator characteristic (ROC) curves to assess sensitivity and specificity of the measures and to identify approximate cut-points for the prediction of risk. Waist-to-hip ratio was superior by magnitude and significance in predicting all cause mortality (male hazard ratio 1.25, P=0.003, female hazard ratio 1.24, P=0.003) and CVD mortality (male hazard ratio 1.62, P<0.001, female hazard ratio 1.59, P<0.001). Waist-to-stature ratio and WC were highly significant but less powerful predictors for CVD mortality. ROC analysis showed higher 'area under the curve' values for waist-related measures in males, with similar less marked trends in females. The ROC cut-points yielded values that corresponded to current promulgated criteria. The waist-to-hip ratio is the preferred clinical measure of obesity for predicting all cause and CVD mortality. WC is a practical alternative. Waist-to-stature ratio is not more useful than WC alone.
    European Journal of Clinical Nutrition 01/2008; 61(12):1373-9. · 2.76 Impact Factor
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    ABSTRACT: Framingham risk functions are widely used for prediction of future cardiovascular disease events. They do not, however, include anthropometric measures of overweight or obesity, now considered a major cardiovascular disease risk factor. We aimed to establish the most appropriate anthropometric index and its optimal cutoff point for use as an ancillary measure in clinical practice when identifying people with increased absolute cardiovascular risk estimates. Analysis of a population-based, cross-sectional survey was carried out. The 1991 Framingham prediction equations were used to compute 5 and 10-year risks of cardiovascular or coronary heart disease in 7191 participants from the Australian Diabetes, Obesity and Lifestyle Study (1999-2000). Receiver operating characteristic curve analysis was used to compare measures of body mass index (BMI), waist circumference, and waist-to-hip ratio in identifying participants estimated to be at 'high', or at 'intermediate or high' absolute risk. After adjustment for BMI and age, waist-to-hip ratio showed stronger correlation with absolute risk estimates than waist circumference. The areas under the receiver operating characteristic curve for waist-to-hip ratio (0.67-0.70 in men, 0.64-0.74 in women) were greater than those for waist circumference (0.60-0.65, 0.59-0.71) or BMI (0.52-0.59, 0.53-0.66). The optimal cutoff points of BMI, waist circumference and waist-to-hip ratio to predict people at 'high', or at 'intermediate or high' absolute risk estimates were 26 kg/m2, 95 cm and 0.90 in men, and 25-26 kg/m2, 80-85 cm and 0.80 in women, respectively. Measurement of waist-to-hip ratio is more useful than BMI or waist circumference in the identification of individuals estimated to be at increased risk for future primary cardiovascular events.
    European Journal of Cardiovascular Prevention and Rehabilitation 01/2008; 14(6):740-5. · 2.63 Impact Factor

Publication Stats

4k Citations
340.06 Total Impact Points

Institutions

  • 1979–2014
    • Sir Charles Gairdner Hospital
      Perth City, Western Australia, Australia
  • 2009–2010
    • Curtin University Australia
      • School of Public Health
      Bentley, Western Australia, Australia
    • Baker IDI Heart and Diabetes Institute
      • Clinical Diabetes and Epidemiology Research Group
      Melbourne, Victoria, Australia
  • 1985–2009
    • University of Western Australia
      • School of Population Health
      Perth City, Western Australia, Australia
  • 2003–2008
    • Diabetes Australia, Victoria
      Melbourne, Victoria, Australia
  • 2002–2006
    • Monash University (Australia)
      • Department of Epidemiology and Preventive Medicine
      Melbourne, Victoria, Australia
    • Monash University (Malaysia)
      Labuan, Labuan, Malaysia
  • 1981–2000
    • The Queen Elizabeth Hospital
      • Department of Ophthalmology
      Tarndarnya, South Australia, Australia
  • 1999
    • Canterbury District Health Board
      • Lipid and Diabetes Research Group
      Christchurch, Canterbury, New Zealand