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In a nationwide study of 3818 charts from patients with fatal COVID-19, we found that geographical differences in Dipeptidyl peptidase 4 (DPP4) inhibitors use did not correlate with diabetes prevalence among COVID-19 deaths, thus not supporting the hypothesis of a clinically relevant involvement of DPP4 inhibition in COVID-19 development and progression.

Secular trends in diabetes prevalence vary globally. We compared the prevalence of diabetes in two surveys 15 years apart in rural Australia.Two cross-sectional household surveys and clinics (biomedical assessments including oral glucose tolerance tests (OGTTs)) in 2001-2003 (Crossroads) and 2016-2018 (Crossroads-II).Four rural Victorian towns.Residents of randomly selected households (Crossroads (n = 5258), Crossroads-II (n = 2649)) with nested clinic assessments for randomly selected participants (n = 1048 and 736 respectively). Response rate 61%.Self-reported diagnosed diabetes, screening history, and diabetes defined by OGTT.The age standardised prevalence of diagnosed diabetes increased from 5.0(4.4-5.7)% to 7.7(6.7-8.6)%, with crude prevalence increasing overall (5.4 to 10.4% p 0.001), in the smaller towns (5.4 to 11.1% p = 0.001) and, the regional centre (4.1 to 7.3% p 0.001). Screening for diabetes over the previous two years increased (rural towns 49.8 to 63.8%; regional centre 44.9 to 63.6%; both p 0.001). The proportion of undiagnosed diabetes was 23.2% in 2003 and 13.7% in 2018. The age and sex adjusted change in total diabetes was (1.15(0.84-1.59)). Central obesity (adjusted odd ratio 1.28(1.00-1.64)) but not overall obesity (adjusted odd ratio 1.17(0.95-1.46)) increased over time.Over 15 years, the crude prevalence of diagnosed diabetes increased while the age and sex adjusted total diabetes prevalence did not change significantly. The epidemic may be slowing in some settings.

The Bedouins are an Arab population living in Israel severely impacted by diabetes and obesity. The aim of this research was to update the prevalence of diabetes among Bedouins in the Negev and to observe differences in this population in comparison with non-Bedouins in Israel.A cross-sectional study was performed using the Clalit Health Services database. Diabetes prevalence among Bedouins was compared with non-Arabs and non-Bedouin Arabs in Israel. Differences in sexes and among Bedouins living in planned cities and unrecognized villages were observed.The age-adjusted prevalence of diabetes was 12.3% in the Bedouin population versus 8.2% in the non-Arab population in southern Israel (p 0.0001). Diabetes prevalence among Bedouins and all Arabs in Israel was similar (12.0%). In all of Israel, age-adjusted diabetes prevalence was 8.8% for men and 7.5% in women (p 0.0001) compared to 12.0% for men and 12.5% for women in the Bedouin population (p = 0.0008). In the Bedouin population in planned cities, age-adjusted diabetes prevalence was 12.5% versus 10.5% in the Bedouin population in unrecognized villages (p 0.0001).This study shows that the prevalence of diabetes among Bedouins is higher than non-Bedouins in Israel. Increasing urbanization of the Bedouin population with their higher diabetes prevalence indicates the need for increased medical intervention as well as continuing investigation into the causes.

The purpose of this study was to investigate trends in diabetic prevalence over the past 11 years using Korea National Health and Nutrition Examination Survey (KNHANES) data. In addition, we aimed to examine trends in diagnosed and undiagnosed diabetes after stratification.We used data from the KNHANES III (2005), IV (2007-2009), V (2010-2012), and VI (2013-2015). 46,157 participants were included in this study. Diabetes was defined as follows: (1) an answer of 'yes' to whether the participants had ever been diagnosed with diabetes by a physician, (2) fasting plasma glucose (FPG) ≥126 mg/dL, or (3) taking oral hypoglycemic agents or insulin. All sampling and weight variables were stratified, and analysis to account for the complex sampling design. The prevalence of diabetes was standardized by the 2005 Korean Housing Census.In men, the crude prevalence of total and undiagnosed diabetes were significantly increased with KNHANES phase (P for trend = 0.002 and 0.004, respectively). The age-standardized prevalence of total, diagnosed and undiagnosed diabetes of both sexes increased with the KNHANES phase (all P for trend 0.001). Compared with the KNHANES III, the age-adjusted odds ratios (ORs) for the crude-prevalence of undiagnosed diabetes in KNHANES IV, V, and VI were 1.00 (0.72-1.41), 1.08 (0.78-1.51), and 1.42 (1.04-1.96) for men.The prevalence of total, diagnosed and undiagnosed diabetes steadily increased and public efforts should focus on screening for the detection of diabetes, especially in men.

Introduction Since the year 2000, IDF has been measuring the prevalence of diabetes nationally, regionally and globally. Aim To produce estimates of the global burden of diabetes and its impact for 2017 and projections for 2045. Methods A systematic literature review was conducted to identify published studies on the prevalence of diabetes, impaired glucose tolerance and hyperglycaemia in pregnancy in the period from 1990 to 2016. The highest quality studies on diabetes prevalence were selected for each country. A logistic regression model was used to generate age-specific prevalence estimates or each country. Estimates for countries without data were extrapolated from similar countries. Results It was estimated that in 2017 there are 451 million (age 18–99 years) people with diabetes worldwide. These figures were expected to increase to 693 million) by 2045. It was estimated that almost half of all people (49.7%) living with diabetes are undiagnosed. Moreover, there was an estimated 374 million people with impaired glucose tolerance (IGT) and it was projected that almost 21.3 million live births to women were affected by some form of hyperglycaemia in pregnancy. In 2017, approximately 5 million deaths worldwide were attributable to diabetes in the 20–99 years age range. The global healthcare expenditure on people with diabetes was estimated to be USD 850 billion in 2017. Conclusion The new estimates of diabetes prevalence, deaths attributable to diabetes and healthcare expenditure due to diabetes present a large social, financial and health system burden across the world.

Aims To examine and forecast the patterns of diabetes prevalence in synergy with obesity. Methods Prophet models were employed to forecast the prevalence of diabetes and obesity in 2030 using time-series data from the WHO Global Health Observatory data repository. K-means clustering models and self-organising maps were used to identify the patterns (clusters) of diabetes prevalence in association with obesity among 183 countries. Results Three patterns of diabetes prevalence were identified, countries in cluster three were estimated to have the highest obesity (44.9%, 26.2–65.8%) and diabetes prevalence (25.3%, 18.3–32.6%) in 2030. By 2030, countries in the Eastern Mediterranean and Upper-middle-income are projected to have the highest prevalence of diabetes. Overall, Niue is likely to have the biggest impact of diabetes. Liberia is projected to experience the largest rise in the prevalence of diabetes, with over 100% growth from 2014 to 2030. Libya, Kuwait, UK, USA, Argentina, and Nauru are estimated to have the peak prevalence of obesity on their respective continents. There is no decline in the influence of obesity in 185 countries by 2030. Globally, the prevalence of diabetes is projected to increase in 2030. Conclusion These estimates of diabetes prevalence in adults confirm continuity in the “diabetes crisis”.

Aims To provide global estimates of diabetes prevalence for 2019 and projections for 2030 and 2045. Methods A total of 255 high-quality data sources, published between 1990 and 2018 and representing 138 countries were identified. For countries without high quality in-country data, estimates were extrapolated from similar countries matched by economy, ethnicity, geography and language. Logistic regression was used to generate smoothed age-specific diabetes prevalence estimates (including previously undiagnosed diabetes) in adults aged 20–79 years. Results The global diabetes prevalence in 2019 is estimated to be 9.3% (463 million people), rising to 10.2% (578 million) by 2030 and 10.9% (700 million) by 2045. The prevalence is higher in urban (10.8%) than rural (7.2%) areas, and in high-income (10.4%) than low-income countries (4.0%). One in two (50.1%) people living with diabetes do not know that they have diabetes. The global prevalence of impaired glucose tolerance is estimated to be 7.5% (374 million) in 2019 and projected to reach 8.0% (454 million) by 2030 and 8.6% (548 million) by 2045. Conclusions Just under half a billion people are living with diabetes worldwide and the number is projected to increase by 25% in 2030 and 51% in 2045.

Aims Although diabetes mellitus at the end of life is associated with complex care, its end-of-life prevalence is uncertain. Our aim is to estimate diabetes prevalence in the end-of-life population, to evaluate which medical register has the largest added value to cause-of-death data in detecting diabetes cases, and to assess the extent to which reporting of diabetes as a cause of death is associated with disease severity. Methods Our study population consisted of deaths in the Netherlands (2015–2016) included in Nivel Primary Care Database (Nivel-PCD; N = 18,162). The proportion of deaths with diabetes (Type 1 or 2) within the last two years of life was calculated using individually linked cause-of-death, general practice, medication, and hospital discharge data. Severity status of diabetes was defined with dispensed medicines. Results According to all data sources combined, 28.7% of the study population had diabetes at the end of life. The estimated end-of-life prevalence of diabetes was 7.7% using multiple cause-of-death data only. Addition of general practice data increased this estimate the most (19.7%-points). Of the cases added by primary care data, 76.3% had a severe or intermediate status. Conclusions More than one fourth of the Dutch end-of-life population has diabetes. Cause-of-death data are insufficient to monitor this prevalence, even of severe cases of diabetes, but could be enriched particularly with general practice data.

Aims To find diabetes prevalence of diagnosed cases, stratified by gender, age, and urban/rural municipalities in the Republic of Macedonia, based on data derived from the National eHealth System. Methods The National eHealth System was searched for all patients with ICD-10 diagnoses E10–E14 in their electronic healthcare records. Data records from the National eHealth System contained patient’s gender, date of birth, place of living, and ICD-10 code. Results Total number of diagnosed diabetes cases was 84,568: 36,119 males (42.7%) and 48,449 females (57.3%). Diabetes prevalence of diagnosed cases in population 20–79 years was 5.0% (n = 78,233; N = 1,562,203), prevalence was higher in females than in males (4.6% vs 3.4%); in rural than in urban municipalities (5.6% vs 3.6%), and was highest in the age group 60–79 years (14.6%). Conclusion These were the first findings on diabetes prevalence of diagnosed cases in the Republic of Macedonia derived from the National eHealth System, stratified by age, gender, and urban/rural municipalities. These data could enable more precise estimations of the total diabetes prevalence in the country, including both diagnosed and undiagnosed cases, and further analysis of the risk factors leading to higher diabetes prevalence in females and rural municipalities in the Republic of Macedonia.

Aim To validate the New Zealand Ministry of Health (MoH) Virtual Diabetes Register (VDR) using longitudinal laboratory results and to develop an improved algorithm for estimating diabetes prevalence at a population level. Methods The assigned diabetes status of individuals based on the 2014 version of the MoH VDR is compared to the diabetes status based on the laboratory results stored in the Auckland regional laboratory result repository (TestSafe) using the New Zealand diabetes diagnostic criteria. The existing VDR algorithm is refined by reviewing the sensitivity and positive predictive value of the each of the VDR algorithm rules individually and as a combination. Results The diabetes prevalence estimate based on the original 2014 MoH VDR was 17% higher (n = 108,505) than the corresponding TestSafe prevalence estimate (n = 92,707). Compared to the diabetes prevalence based on TestSafe, the original VDR has a sensitivity of 89%, specificity of 96%, positive predictive value of 76% and negative predictive value of 98%. The modified VDR algorithm has improved the positive predictive value by 6.1% and the specificity by 1.4% with modest reductions in sensitivity of 2.2% and negative predictive value of 0.3%. At an aggregated level the overall diabetes prevalence estimated by the modified VDR is 5.7% higher than the corresponding estimate based on TestSafe. Conclusion The Ministry of Health Virtual Diabetes Register algorithm has been refined to provide a more accurate diabetes prevalence estimate at a population level. The comparison highlights the potential value of a national population long term condition register constructed from both laboratory results and administrative data.

WHO, IDF and ADA recommend HbA(1c) ≥6.5% (48 mmol/mol) for diagnosis of diabetes with pre-diabetes 6.0% (42 mmol/mol) [WHO] or 5.7% (39 mmol/mol) [ADA] to 6.4% (47 mmol/mol). We have compared HbA(1c) from several methods for research relating glycaemic markers.HbA1c was measured in EDTA blood from 128 patients with diabetes on IE HPLC analysers (Bio-Rad Variant II NU, Menarini HA8160 and Tosoh G8), point of care systems, POCT, (A1cNow+ disposable cartridges and DCA 2000(®)+ analyser), affinity chromatography (Primus Ultra2) and the IFCC secondary reference method (Menarini HA8160 calibrated using IFCC SRM protocol).Median (IQ range) on IFCC SRM was 7.5% (6.8-8.4) (58(51-68) mmol/mol) HbA(1c) with minimum 5.3%(34 mmol/mol)/maximum 11.9%(107 mmol/mol). There were positive offsets between IFCC SRM and Bio-Rad Variant II NU, mean difference (1SD), +0.33%(0.17) (+3.6(1.9) mmol/mol), r(2)=0.984, p0.001 and Tosoh G8, +0.22%(0.20) (2.4(2.2) mmol/mol), r(2)=0.976, p0.001 with a very small negative difference -0.04%(0.11) (-0.4(1.2) mmol/mol), r(2)=0.992, p0.001 for Menarini HA8160. POCT methods were less precise with negative offsets for DCA 2000(®)+ analyser -0.13%(0.28) (-1.4(3.1) mmol/mol), r(2)=0.955, p0.001 and A1cNow+ cartridges -0.70%(0.67) (-7.7(7.3) mmol/mol), r(2)=0.699, p0.001 (n=113). Positive biases for Tosoh and Bio-Rad (compared with IFCC SRM) have been eliminated by subsequent revision of calibration.Small differences observed between IFCC-calibrated and NGSP certified methods across a wide HbA(1c) range were confirmed by quality control and external quality assurance. As these offsets affect estimates of diabetes prevalence, the analyser (and calibrator) employed should be considered when evaluating diagnostic data.

Objective To estimate the burden of diabetes mellitus and pre-diabetes in tribal populations of India. Methods The authors reviewed studies from 2000 to 2011 that documented the prevalence of diabetes mellitus in various tribal populations of India. The search was performed using electronic and manual methods. Meta-analysis of data on point prevalence was performed. Results A total of seven studies were retrieved. The prevalence of diabetes mellitus ranged from 0.7% to 10.1%. The final estimate of diabetes prevalence obtained after pooling of data from individual studies, was 5.9% (95% CI; 3.1–9.5%). The prevalence for impaired fasting glucose (IFG) varied from 5.1% to 13.5% and impaired glucose tolerance (IGT), from 6.6% to 12.9%. Conclusion Chronic disease research in tribal populations is limited. The reported prevalence of IFG/IGT was higher than the prevalence of diabetes and this observation could be suggestive of a potential increase in diabetes in the coming years. Given that lifestyle changes have occurred in the tribal populations, there is a need to synthesize evidence(s) relating to diabetes and other chronic diseases in these marginalized populations and inform policy makers.

Diabetes rates are increasing dramatically, and certain populations are at greater risk. Low income status is associated with higher diabetes prevalence and higher mortality. The effect of income on diabetes incidence is less well understood.Using a validated, population-based diabetes registry and census data from Ontario, Canada, we compared the rate of new diabetes cases among persons aged 20 years or older between April 1st 2006 and March 31st 2007 between neighborhood income quintiles, and assessed for age- and sex-based differences.There were 88,886 new cases of diabetes in Ontario adults during our study period (incidence rate 8.26/1000, 95% confidence interval, CI 8.20-8.31). Rates increased with age and were higher in males versus females. Increasing income quintile was associated with a significantly decreased diabetes incidence (8.70/1000, 95% CI 8.57-8.82 in the lowest quintile, vs. 7.25/1000, 95% CI 7.14-7.36 in the highest quintile, p0.0001). Significant interactions were found between income quintile (1, 2, and 3 vs. 5) and age groups (20-39, 40-59 vs. 80+ years) (p0.01) and sex (p0.01), such that the impact of income was more pronounced in younger compared to older age groups and in females versus males.This population-based study found that diabetes risk is significantly higher in lower compared to higher income groups, and that this income gap was widest in younger persons and females. Greater diabetes preventive efforts directed toward younger and female lower-income populations are necessary, in order to lessen the lifelong burden of diabetes for an already disadvantaged population.

The aim of this study was to obtain an accurate estimate of diabetes prevalence in Croatia and additional estimates of impaired fasting glucose (IFG), undiagnosed diabetes, and insulin resistance. The study was part of the First Croatian Health Project. Field work included a questionnaire, anthropological measurements, and blood sampling. A nationally representative sample of 1653 subjects aged 18-65 years was analyzed. A total of 100 participants with diabetes were detected, among them 42 with previously unknown diabetes. The prevalence was 6.1% (95% CI: 4.59-7.64), with a significant difference by age. IFG prevalence (WHO-criteria) was 11.3%. The ratio of undiagnosed/diagnosed diabetes was 72/100, unevenly distributed by the regions. HOMA-IR was >1 in 40.4% of the subjects. This survey revealed a higher prevalence of diabetes than previously estimated, whereas that of IFG was as expected. A significant difference in the proportion of undiagnosed diabetes among the regions warrants attention.

We assessed the prevalence of Type 1 diabetes mellitus and determined how the targets established in the guidelines for patients with Type 1 diabetes mellitus were achieved in clinical practice in North Karelia, Finland.All adult Type 1 diabetes mellitus patients (n=1075) were identified from the regional electronic patient database. The data for HbA1c and LDL cholesterol measurements during the years 2013 and 2014 were obtained from medical records.The prevalence of Type 1 diabetes mellitus in the adult population in North Karelia was 0.8%, which is among the highest worldwide. HbA1c and LDL cholesterol were measured in 93% and 90% of participants, respectively. Nineteen percent of patients reached the HbA1c target of7.0% (53mmol/mol) and 45% attained LDL cholesterol2.5mmol/l. Overall, 26% of patients over 60 years old with diabetes achieved glycaemic control targets compared with 13-16% of younger patients with diabetes.Glycaemic control was in line with the recommendations in only one-fifth of Type 1 diabetes mellitus patients and less than half of them had LDL cholesterol levels within the target range. Interestingly, older Type 1 diabetes mellitus patients met the glycaemic control target more often than younger patients with diabetes. The targets established for patients with Type 1 diabetes mellitus are not achieved satisfactorily in daily practice.

There was no significant association between diabetes prevalence and income levels for either sex in 1998. However, the high income level in men and the low income level in women positively related to the odds of diabetes in 2011-2012. Preventive strategies for diabetes should consider the gender-specific economic discrepancy.

Purpose To compare the age-specific prevalence of diabetes and diabetic retinopathy (DR) over 6 years. Methods The Blue Mountains Eye Study (BMES) examined 3654 residents (82.4% response) aged >49 years in BMES I (1992–1994). Survivors ( n = 2335) and newly eligible residents ( n = 1174) were examined in BMES II (1997–2000). Diabetes was defined by history or fasting plasma glucose ≥7.0 mmol/L. DR was graded from 6-field retinal photographs using the Airlie House Classification. Age-specific prevalence in 5-year intervals was compared, as samples of each age group were independent. Results The overall diabetes prevalence increased from 7.8 to 9.9% ( p = 0.002) while the age-specific prevalence increased in age groups 60–74 years, over 6 years. A slightly higher prevalence of mild levels of DR ( p = 0.018) but lower prevalence of moderate–severe levels of DR ( p = 0.049) was evident in BMES II compared to BMES I. Factors significantly associated with DR prevalence were diabetes duration ≥20 years (BMES I, OR 7.6 [2.9–20.5]; BMES II, OR 6.1 [2.5–15.4]) and blood glucose level (BMES I, OR 1.1 [1.0–1.2]; BMES II, OR 1.2 [1.1–1.3] per mmol/L increase). Conclusions An increased prevalence of diabetes, but decreased prevalence of severe levels of DR, was documented in two survey samples from the same region over 6 years.

AIMS: To systematically review trends in diabetes mellitus (DM) prevalence in adults in China over the last 10 years and to identify the determinants of these trends. METHODS: A systematic search was conducted for studies published between 2000 and 2010. Studies reporting DM prevalence were included if they met the pre-determined criteria. The prevalence estimates and reported determinants of these studies were compared. RESULTS: Twenty-five manuscripts, reporting on 22 studies, were selected for inclusion in the review. There has been an increase in DM prevalence from 2.6% to 9.7% in China over the past decade. DM prevalence is strongly associated with age and is higher in urban residents compared with rural populations. Some studies found a difference in DM prevalence between males and females, but this finding was not consistent. Other commonly reported associations with DM included family history, obesity and hypertension. CONCLUSION: Over the period of 2000-2010, we identify a significant increase in DM prevalence at the national level. It is important for all levels of government to develop more effective strategies to prevent and manage this rising diabetes epidemic. There is also an important need for more large-scale studies of diabetes in the western and central regions of China.

Objective: To estimate the prevalence of diabetes in the Maltese Islands from data regarding drug consumption, and to assess the prescribing habits and management attitudes of local doctors. Methodology: The prescribed average daily dose of each type of anti-diabetic drug was calculated from random representative samples of patients (total 1,444) attending the Health Department's primary and secondary health centres as well as of patients seeing their private practitioners. This constituted circa 16% of the total estimated number of diabetics on drug therapy in Malta. The quantities of drugs consumed were obtained both from Government and private industry sources, whilst relevant data on therapy modalities, including proportions of patients on a combination of anti-diabetic preparations, were obtained from records held at the Dept. of Health. Results: Applying the appropriate formulae (as proposed by Eurodiab. subarea C 1989 programme) the global prevalence of diabetes worked out to be 5.22%, an underestimate of circa 12% of the figure extrapolated from the recent population based epidemiological studies. Overall 51% of cases were treated with ‘diet only’, whilst less than 10% of subjects were managed with insulin. Compared to patients attending the better staffed and equipped health centres, those seeing their private physicians were proportionately less frequently put on insulin (5.7% vs 11.7%), and were prescribed a slightly higher mean daily dose (1.7 vs. 1.4 tab) of glibenclamide suggesting the need of better education of the patient (and probably also of the physician). Conclusion: This type of study proved to be relatively simple and inexpensive to perform. Although it cannot replace epidemiological field surveys it can still give a reasonably fair (albeit with limitations) estimate of diabetes prevalence in a population. Moreover it permits an important insight into local public health indicating ways to improve diabetes care.

A cross-sectional study using the US national 2009 Behavioral-Risk-Factor-Surveillance-System data ( n =425,846) demonstrates that diabetes prevalence was significantly increased after age 35 in ever smokers, irrespective of gender. Diabetes prevalence was significantly increased in white or Hispanic ever smokers after age 25, and in black ever smokers after age 35.

The extent to which random plasma glucose levels underestimate the true prevalence of diabetes has been determined in Micronesian Nauruans. In 337 individuals who were screened on the basis of their random plasma glucose levels, the age-standardised prevalence based on a cut-off of 11.1 mmol/l underestimated the population prevalence based on a complete oral glucose tolerance test by 42% in males and 63% in females. At a cut-off level of 7.8 mmol/l the true age-standardised prevalence was underestimated by 16 and 38%, in males and females, respectively. The use of random plasma glucose concentrations to determine the prevalence of diabetes, as currently defined, seems inappropriate. Performing oral glucose tolerance tests on smaller representative population samples should provide more accurate data at less expense than through large-scale screening utilizing random glucose levels.

The prevalence of diabetes and impaired glucose tolerance has been determined in an Asian Muslim community in Dar-es-Salaam, Tanzania. Two-h oral glucose (75 g) tolerance tests were performed on 1049 subjects over 14 years old, who were fasting, from a random sample of families. The overall age and sex-adjusted prevalence of diabetes was 7.1% (4.4% known, 2.7% previously undiagnosed) with a steady increase from 0.8% at 15–24 years and 3.0% at 25–34 years, to 24.9% for 65 years and over. Impaired glucose tolerance (IGT) rates ranged from 11.4% (15–24 years) to 22.3% (over 64 years). The overall age-adjusted prevalence of IGT was 21.5%. The mean body indices (BMIs) were 24.3 and 26.4 for males and females, respectively, but age-adjusted diabetes rates were similar in the two sexes (7.0% and 7.6%, respectively). Diabetes and IGT were commoner in those with BMI > 25 only in the older age groups. Diabetes and IGT were commoner in those with a family history of diabetes. Increasing parity was also associated with a higher diabetes prevalence. Diabetes and IGT are thus common in Asians in Tanzania, in contrast to the indigenous community. Rates are indeed higher than in most other immigrant Asian communities.

The Australian Diabetes, Obesity and Lifestyle Study (AusDiab) addresses the urgent need for data on diabetes prevalence, risk factors and associated conditions in Australia. Here we describe the methods used and the response rates obtained. AusDiab was a population-based cross-sectional survey of national diabetes mellitus prevalence and associated risk factors in people aged > or =25 years, conducted between May 1999 and December 2000 in the six states and the Northern Territory of Australia. The study involved an initial household interview, followed by a biomedical examination that included an oral glucose tolerance test (OGTT), standard anthropometric tests, blood pressure measurements and the administration of questionnaires. Of the 20347 eligible people (aged > or =25 years and resident at the address for > or =6 months) who completed a household interview, 11247 (55.3%) attended for the biomedical examination. Of those who completed the biomedical examination 55.1% were female. Comparisons with the 1998 Australian population estimates showed that younger age responders were under-represented at the biomedical examination, while the middle-aged and older age groups were over-represented. Weighting of the AusDiab data for age and gender have corrected for this bias. AusDiab, which is the largest national diabetes prevalence study undertaken in a developed nation to have used an OGTT, provides a valuable national resource for the study of the prevalence and possible causes of diabetes, as well as identifying possible risk factors that may lead to diabetes. Furthermore, it generates the baseline data for a prospective 5-year cohort study. The data will be important for national and regional public health and lifestyle education and health promotion programs.

Based on oral glucose tolerance testing, the prevalence of diabetes in Australian adults has ranged from 2.3% in Europids in 1966 to 20% in small surveys of Aborigines. We have surveyed Aborigines and Europids simultaneously for further comparison of diabetes prevalence between these population groups. The samples were drawn from two adjacent country towns in south-eastern Australia, where Aborigines and Europids have been in contact for 150 years. By the 2-h (post-75 g oral glucose load) criterion (venous plasma glucose greater than or equal to 11.1 mmol/l), the crude prevalence of diabetes among 306 Aborigines was 7.8%, significantly higher than the 3.4% among 553 Europids (P less than 0.01). The prevalence of impaired glucose tolerance was similar in both groups (6.9% in Aborigines, 6.0% in Europids, no significant difference). Adjustment for the marked differences in age distribution between Aborigines and Europids by direct standardization to the 1980 world population increased the apparent differences, with the finding of a four-fold greater prevalence among Aborigines (8.1% compared with 1.9%). The greater frequency of glucose intolerance among Aborigines appears to persist despite the higher proportion of Europid genetic mix with these urbanized south-eastern groups than with Aborigines from remote settings.

Asian Indian migrants have a strikingly high diabetes prevalence but prevalence in India has been considered to be relatively low. However, there have been few recent studies, especially in rural India. A house-to-house survey was undertaken in a defined area of Eluru, a small town in South India, and in four adjoining villages. A total of 9563 subjects (4729 male, 4834 female) were surveyed, of whom 5699 lived in Eluru and 3864 in the four villages. Enquiry was made for known diabetes in each household. In all, 157 known diabetic subjects (89 male, 68 female) were ascertained. The prevalence of known diabetes was 6.1% in all subjects aged 40 or over and rose to 13.3% in the age group 50–59 years. The overall crude prevalence of known diabetes was 1.6% (1.9% male, 1.4% female). The prevalence in Eluru (1.5%) was similar to that in the four villages (1.9%). The age-adjusted rates for known diabetes in the middle-aged and elderly subjects are unexpectedly high, considering the poor socio-economic circumstances, decreased health awareness and decreased access to medical facilities, and are comparable with those of similar surveys in relatively affluent Delhi, and in Southall, London. The prevalence in rural (as well as urban) India may be much higher than previously realised. Large formal prevalence studies are urgently required.