Impaired glucose tolerance and impaired fasting glycaemia: the current status on definition and intervention

Diabetic MedicineVolume 19, Issue 9 p. 708-723 Free Access Impaired glucose tolerance and impaired fasting glycaemia: the current status on definition and intervention Writing committee, Writing committee Diabetes and Metabolism, School of Clinical Medical Sciences, Urniversity of Newcastle, UK,Search for more papers by this authorN. Unwin, Corresponding Author N. Unwin Diabetes and Metabolism, School of Clinical Medical Sciences, Urniversity of Newcastle, UK,: Nigel Unwin or George Alberti, Diabetes & Metabolism, University of Newcastle upon Tyne, Medical School, Framlington Place, Newcastle NE2 4HH, UK.Search for more papers by this authorJ. Shaw, J. Shaw Diabetes and Metabolism, School of Clinical Medical Sciences, Urniversity of Newcastle, UK, International Diabetes Institute, Melbourne, AustraliaSearch for more papers by this authorP. Zimmet, P. Zimmet Diabetes and Metabolism, School of Clinical Medical Sciences, Urniversity of Newcastle, UK, International Diabetes Institute, Melbourne, AustraliaSearch for more papers by this authorK. G. M. M. Alberti, K. G. M. M. Alberti Diabetes and Metabolism, School of Clinical Medical Sciences, Urniversity of Newcastle, UK,Search for more papers by this author Writing committee, Writing committee Diabetes and Metabolism, School of Clinical Medical Sciences, Urniversity of Newcastle, UK,Search for more papers by this authorN. Unwin, Corresponding Author N. Unwin Diabetes and Metabolism, School of Clinical Medical Sciences, Urniversity of Newcastle, UK,: Nigel Unwin or George Alberti, Diabetes & Metabolism, University of Newcastle upon Tyne, Medical School, Framlington Place, Newcastle NE2 4HH, UK.Search for more papers by this authorJ. Shaw, J. Shaw Diabetes and Metabolism, School of Clinical Medical Sciences, Urniversity of Newcastle, UK, International Diabetes Institute, Melbourne, AustraliaSearch for more papers by this authorP. Zimmet, P. Zimmet Diabetes and Metabolism, School of Clinical Medical Sciences, Urniversity of Newcastle, UK, International Diabetes Institute, Melbourne, AustraliaSearch for more papers by this authorK. G. M. M. Alberti, K. G. M. M. Alberti Diabetes and Metabolism, School of Clinical Medical Sciences, Urniversity of Newcastle, UK,Search for more papers by this author First published: 06 September 2002 https://doi.org/10.1046/j.1464-5491.2002.00835.xCitations: 763AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Glossary of abbreviations BMI Body mass index CHD Coronary heart disease CVD Cardiovascular disease DECODA D iabetes E pidemiology: C ollaborative analysis O f D iagnostic criteria in A sia DECODE D iabetes E pidemiology: C ollaborative analysis O f D iagnostic criteria in E urope DPP D iabetes P revention P rogramme DREAM D iabetes Re duction A ssessment with Ramipril and Rosiglitazone M edication HGO Hepatic glucose output FDPS Finnish Diabetes Prevention Study GDM Gestational diabetes mellitus IFG Impaired fasting glycaemia IGT Impaired glucose tolerance NAVIGATOR N ateglinide and V alsartan in I mpaired G lucose T olerance O utcomes R esearch OGTT Oral glucose tolerance test RIAD R isk factors in I GT for A therosclerosis and D iabetes STOP-NIDDM S tudy TO P revent NIDDM 2-HPG 2-h plasma glucose value in an oral glucose tolerance test TRIPOD Tr oglitzaone i n the P revention o f D iabetes Introduction The majority of deaths in persons with diabetes result from accelerated cardiovascular and cerebrovascular atherosclerosis. Mortality attributable to cardiovascular disease (CVD) is increased 1.5–4.5-fold, and all-cause mortality is increased 1.5–2.7-fold. Diabetes has been identified as an independent risk factor for CVD mortality, even though other risk factors such as central obesity, hypertension and dyslipidaemia frequently coexist in persons with diabetes. Evidence is accumulating that macrovascular disease is associated with lesser degrees of hyperglycaemia than is microvascular disease. The heightened risk of CVD extends to the impaired glucose tolerance (IGT) category, and as with diabetes, IGT is often associated with the metabolic syndrome (insulin resistance syndrome), the components of which explain some, but not all of the excessive CVD risk seen in IGT and diabetes. Both IGT and impaired fasting glycaemia (IFG) are very strong risk markers for the development of diabetes. Both IGT and IFG are associated with increased CVD risk, and the question therefore arises, why they are not considered to be disease states rather than risk factors. Aim and objectives of the workshop The Consensus Workshop was convened by the International Diabetes Federation (IDF) to review information relating to IGT and IFG with the objective of considering: • Their significance with regard to future risk of both diabetes and CVD; and • Whether intervention strategies are indicated. Specifically the workshop participants were set the task of addressing the following questions: (i) are the current definitions of IGT and IFG appropriate? (ii) are IGT and IFG risk factors, risk markers or actually disease states? (iii) are interventions indicated for IGT and IFG and if so, how? With respect to the second question, the term 'risk marker' is used simply to indicate that an association exists between either IGT or IFG and a specified outcome [1]. The term 'risk factor' is used where such an association has been found to be independent of known confounders and the evidence suggests that intervention to reduce it will lead to a reduction in the outcomes it is associated with. This is a useful distinction, even though in practice it is often a difficult one to make. Structure of the report The report is divided into two main sections. The first section, the background, provides an overview of the data that were presented and considered by participants at the meeting. The second section summarizes the consensus reached and the recommendations arising. Background The origin and nature of IGT and IFG categories IGT was first introduced in 1979 to replace 'borderline' diabetes and other categories of hyperglycaemia that did not appear to carry a risk of microvascular complications [2,3]. It was considered as a clinical class of glucose intolerance in the 1985 WHO classification [4]. It is now, in the latest reports from WHO and the American Diabetes Association (ADA), categorized as a stage in the natural history of disordered carbohydrate metabolism. It was only in the most recent reports that a category of non-diabetic fasting hyperglycaemia was defined and given the name impaired fasting glycaemia (IFG) [5,6]. This indicates glucose concentrations that are clearly above normal but fall short of the diagnostic value for diabetes. At present neither IFG nor IGT are considered clinical entities in their own right, but as risk categories for the future development of diabetes and CVD. They represent metabolic states intermediate between normal glucose homeostasis and diabetic hyperglycaemia. Individuals who meet the criteria for IGT or IFG usually have HbA1c values that are within or only just above the normal range. However, as discussed below, even this degree of hyperglycaemia is clearly associated with other metabolic and cardiovascular abnormalities. IGT and IFG are often components of the metabolic syndrome, thereby heightening the risk of cardiovascular disease. The metabolic determinants of fasting (FPG) and 2-h plasma glucose (2-HPG) values in an oral glucose tolerance test are somewhat different [7–9]. This means the categorization of an individual on a fasting value may differ from that on a 2-HPG value. Normal control of fasting glucose depends on the ability to maintain adequate basal insulin secretion, and on appropriate levels of insulin sensitivity in the liver to control hepatic glucose output. Abnormalities of these metabolic functions characterize IFG. During an oral glucose tolerance test (OGTT), the normal response to the absorption of the carbohydrate load is both to suppress hepatic glucose output (HGO) and to enhance glucose uptake in the muscle and liver. This requires a prompt increase in insulin secretion, and adequate hepatic and muscle sensitivity to insulin. In particular, IGT is associated with peripheral insulin resistance, most importantly at the level of skeletal muscle (the main depot for glucose disposal post-prandially). In short, the physiological bases of IFG and IGT are somewhat different. Finally, it must be remembered that measurement error preceding carbohydrate intake and biological variability can all lead to different classifications of an individual when tested on more than one occasion. An illustration of the effect of random error on the classification of individuals is given using data from the AusDiab (Australian national study [10]). The FPG and 2-HPG results of each individual were changed at random, up to a maximum of ±5% of the recorded value. When this was done, 22% of the individuals who were classified as IFG on the recorded value, and 10% of those with IGT, were reclassified to another category (J. Shaw, personal communication). Definitions Table 1 shows the plasma and blood glucose values for the categories of diabetes, IFG and IGT [ 6 ]. The category in which an individual is placed may depend on whether only fasting glucose is measured or fasting and 2-h glucose values are obtained. For example, an individual falling into the IFG category on the fasting result may also have IGT on the 2-h value, or indeed diabetes. If an individual falls into two different categories, the higher one applies. Table 1. Values for diagnosis of diabetes mellitus and other categories of hyperglycaemia [ 6 ] Glucose concentration, mmol/l (mg/dl) Plasma Whole blood Venous Venous Capillary Diabetes mellitus Fasting and/or ≥ 7.0 (126) ≥ 6.1 (110) ≥ 6.1 (110) 2-h post-glucose load ≥ 11.1 (200) ≥ 10.0 (180) ≥ 11.1 (200) Impaired glucose tolerance Fasting concentration (if measured) and < 7.0 (126) < 6.1 (110) < 6.1 (110) 2-h post-glucose load 7.8–11.0 (140–199) 6.7–9.9 (120–179) 7.8–11.0 (140–199) Impaired fasting glucose Fasting and 6.1–6.9 (110–125) 5.6–6.0 (100–109) 5.6–6.0 (100–109) 2-h (if measured) < 7.8 (140) < 6.7 (120) < 7.8 (140) Descriptive epidemiology of IGT and IFG Prevalence and overlap between IGT and IFG As discussed above, IGT and IFG are not equivalent metabolically, and it is therefore not surprising that there are differences in their prevalence and in the people categorized as having one or the other. In most populations, IGT is considerably more prevalent than IFG. Furthermore, there is limited overlap between the categories—the majority of people with IGT do not have IFG, and the majority with IFG do not have IGT. Hence the terminology of 'isolated IGT' and 'isolated IFG'. Figure 1 shows the different subcategories of IGT and IFG within the American NHANES III study. This demonstrates how little overlap there exists between the categories, and that the largest subgroup is isolated IGT (I-IGT) (FPG < 6.1 mmol/l and 2-HPG 7.8–11.0 mmol/l). Table 2 shows data from a variety of populations demonstrating that this picture of highest prevalence of I-IGT and limited overlap between IGT and IFG is found in most of them. Thus, IFG and IGT identify substantially different segments of the population with impaired glucose regulation. Figure 1Open in figure viewerPowerPoint Prevalence of impaired glucose tolerance (IGT) and impaired fasting glycaemia (IFG) in 2662 persons aged 40–74 years without previously diagnosed diabetes by 1985 WHO criteria, NHANES III study. (From Harris MI et al . Diabetes Care 1997; 20: 1859–1862.) Table 2. The prevalence (percentages) of impaired glucose tolerance (IGT) and impaired fasting glycaemia (IFG) in different adult populations Age (size of study population) Total IGT Total IFG *I-IGT *I-IFG IGT/IFG Mauritius [11] 25–74 (3713) 17.2 7.5 13.9 4.2 3.3 Pima [12] ≥ 15 (5023) 13.2 4.4 10.7 1.9 2.5 Sweden [13] 55–57 (1843) 27.9 17.3 20.3 9.7 7.6 NHANES III [15] 40–74 (2844) 14.9 8.3 11.0 4.4 3.9 Australia [10] ≥ 25 (11 247) 10.6 8.3 8.0 5.7 2.6 Hong Kong [16] 18–66 (1486) 7.2 2.0 6.1 0.9 1.1 DECODE [17] ≥ 30 (25 364) 11.9 10.0 8.8 6.9 3.1 * Isolated IGT and IFG, respectively. Age and sex distribution of IGT and IFG In addition to differences in the overall prevalence between IGT and IFG, there is now clear evidence of differences in phenotype between the two categories. The most robust evidence for this comes from the analyses of the DECODE [18,19] and DECODA [20,21] study groups, which include data from 13 European and 10 Asian studies, respectively. Their findings are summarized in Table 3. The most consistent and statistically significant difference is that IFG is commoner in men than women in virtually all age groups, typically being 1.5–3 times higher, but up to seven or eight times higher in Europeans aged 50–70 years. Conversely, the prevalence of IGT is higher in women than men in all age groups except over the age of 60 in Asian populations and over the age of 80 in the European. However, these findings are less statistically robust than those for IFG, being significant only in Europeans aged 30–39 and 70–79 years. Finally, the prevalence of IGT tends to increase across all age groups, but that of IFG tends to plateau in middle age, and in European men in particular falls in older age groups. In making the generalizations summarized in Table 3 it must be remembered that there are differences between individual studies, particularly in the relationship between age and IFG and IGT prevalence. It can not be determined from these cross-sectional data what these differences represent. For example, the combined effects of age-specific incidence (the rate at which new cases enter the category) and the rate at which people leave the category (through death or progression to diabetes) will determine current age-specific prevalence. In addition, cross-sectional findings may reflect the differing experience of different age cohorts (likely to be particularly important in populations undergoing rapid lifestyle change), and relationships found cross-sectionally may not apply longitudinally. Table 3. Summary of the age and sex distribution of impaired fasting glycaemia (IFG) and impaired glucose tolerance (IGT) in European and Asian populations aged 30–89 years * Age IFG : Prevalence plateaus in middle age (40–50 years), with the exception of European women where it rises until 70 years IGT : Prevalence rises with age, although exceptions exist in a few populations where it plateaus in middle age Sex Men > women for IFG in all age groups with the exception of 70–79 years in Europeans and 80–89 years in Asians Women > men for IGT in all age groups in Europeans (but not Asians) with the exception of 80–89 years IFG:IGT ratio by age and sex IGT > IFG in all age groups in Asian men and women and in European women and in European men aged ≥ 70 years IFG > IGT in European men up to the age of 60 years * Based on DECODE and DECODA data and analyses. The predictive properties of IFG and IGT—methodological considerations In common with most other risk factors and risk markers for diabetes and CVD, glucose is usually found to have a continuous relationship with risk of future diabetes, CVD and total mortality [22]. The categories of IFG and IGT therefore represent largely arbitrary sections on the continuum of risk between these outcomes and FPG and 2-HPG, respectively. Inevitably therefore, the findings of studies that quantify the risks associated with IFG or IGT using relative risk or an odds ratio are highly dependent on the reference category that is used, i.e. whether it is: FPG < 6.1 mmol/l; or 2-HPG < 7.8 mmol/l; or FPG < 6.1 mmol/l and 2-HPG < 7.8 mmol/l. Hence, even if fasting and 2-HPG carried equivalent risk of an outcome, the relative risk of IFG compared with FPG < 6.1 mmol/l could be quite different from the relative risk of IGT compared with 2-HPG < 7.8 mmol/l. Many prospective studies that have examined glucose as an independent risk factor for CVD or total mortality have been under-powered, and this is likely to be a major reason for conflicting findings from different studies. One approach to overcome the low power of individual prospective studies is to combine the data from them. This approach has been taken by the DECODE investigators [17]. While such data sets have considerable power, there is an important limit to their precision with regard to glucose measurements. Differences in the methodology of glucose assessment between studies, such as in the type of blood sample (whole blood vs. plasma or capillary) and glucose assay method, inevitably introduce imprecision into an assessment of the relationship between glucose level or category and outcomes. Finally, although interest usually focuses on whether a relationship between glucose and outcomes is independent of known or potential confounders (such as other CVD risk factors), both unadjusted and adjusted relationships between glucose and outcomes have utility. For example, glucose may have value as a risk marker for CVD even if this relationship is mediated through its association with other cardiovascular risk factors. A special example of this is whether the relationship between fasting glucose and outcomes is independent of 2-HPG and vice versa. Predictive properties of IGT and IFG for diabetes The diagnostic cut-offs for diabetes appear to identify genuine thresholds below which there is virtually no risk of diabetic retinopathy, whilst above it the risk starts to rise substantially [5,6]. The same does not apply to the lower cut-offs of IFG or IGT, which were based on consensus rather than evidence. The risk for CVD or future diabetes appears to be continuous across the glucose range, and the cut-offs merely represent a convenient point at which the risk can be deemed to be 'excessive' and worthy of labelling. This is of undoubted convenience in clinical and public health settings, but has obvious limitations. Indeed, in epidemiological studies, using a single OGTT, a continuous and curvilinear relationship exists between current glucose levels (either fasting or 2 h) and the risk of future diabetes (illustrated in Fig. 2 using data from the Pima Indians [23]). Such data indicate that the predictive abilities for diabetes of fasting and 2-h glucose (when considered as continuous variables) are similar. Figure 2Open in figure viewerPowerPoint Incidence of diabetes (1999 WHO criteria) in Pima Indians by 5-percentile intervals of baseline fasting plasma glucose (FPG) and 2-h plasma glucose (2-HPG) value in an oral glucose tolerance test. ––––, FPG; - - - -, 2-HPG. (From Gabir MM et al. Diabetes Care 2000; 23: 1108–1112.) A number of studies have recently tried to determine whether IGT or IFG is a better predictor of future diabetes. The findings from six studies are summarized in Table 4. Although there are some differences between the studies, the following general conclusions may be drawn. The incidence of subsequent diabetes is highest in individuals with combined IGT and IFG. It tends to be similar in those with isolated IFG (I-IFG) and I-IGT, although there may be differences in some populations, with data from Pima Indians suggesting a higher incidence in those with I-IFG. However, because in most populations I-IGT is much commoner than I-IFG, it identifies a greater proportion of those who will develop diabetes. A substantial minority, well over a third, of individuals who develop diabetes have normal glucose tolerance at baseline. This latter proportion will be largely dependent on the time interval between glucose measurements. This is probably the main explanation for over 60% of those with diabetes having normal glucose tolerance at baseline in the Italian study, where the follow-up after initial assessment of glucose status was > 11 years. This highlights the fact that the intermittent measurement of FPG and 2-HPG is of limited utility in identifying all those within a population at future risk of developing diabetes. Taking into account additional risk factors may improve this, and this is considered later. Table 4. The predictive power of impaired fasting glycaemia (IFG) and impaired glucose tolerance (IGT) for future diabetes Study Number, follow-up, definition of diabetes Glucose tolerance category (n) Percentage (n) developing diabetes Percentage of all incident diabetes in population Hoorn study (white), men and women 50–75 years [14] 1342 without DM. Mean follow up 5.8–6.5 years. WHO 1999 NGT (1125) 4.5 (51) 38.3 I-IFG (106) 33.0 (35) 26.3 I-IGT (80) 33.8 (27) 20.3 IGT and IFG (31) 64.5 (20) 15.0 Pima Indian population, men and women ≥ 15 years [12] 5023 without DM. Five years follow-up*. WHO 1999 NGT (3499) 3.6 40.1 I-IFG (93) 31.0 9.2 I-IGT (537) 19.9 34.1 IGT and IFG (126) 41.2 16.6 Mauritians (multiethnic), men and women 25–74 years [11] 3229 without DM. Five years follow-up. WHO 1999 NGT (2474) 4.7 (117) 39.4 I-IFG (148) 21.6 (32) 10.8 I-IGT (489) 20.8 (103) 34.7 IGT and IFG (118) 38.1 (45) 15.2 Italian (white) men and women, 40–59 years [24] 560 without DM. 11.5 years follow-up. ADA 1997 NGT (500) 7.2 (36) 66.7 I-IFG (11) 9.1 (1) 1.9 I-IGT (40) 32.5 (13) 24.1 IGT and IFG (9) 44.4 (4) 7.4 Ely, UK (white) men and women 40–65 years at baseline [25]† 908 without DM. 4.5 years follow-up. WHO 1999 NGT (604) 0.3 (2) 8.3 I-IFG (149) 4.7 (7) 29.2 I-IGT (84) 7.1 (6) 25.0 IGT and IFG (71) 12.7 (9) 37.5 Brazilian-Japanese, 40–79 years [26]† 314 without DM. Seven years follow-up. WHO 1999 NGT (252) 20.2 (51) 54.8 I-IFG (14) 64.3 (9) 9.7 I-IGT (37) 67.6 (25) 26.9 IGT and IFG (11) 72.7 (8) 8.6 Paris Prospective Study (white), men, 44–55 years [27] 5139 without DM. 30-month follow-up. WHO 1999 NGT or I-IFG‡ (4615) 2.7 (129) 75.4 I-IGT 5.4 (14) 8.1 IGT and IFG 14.9 (28) 16.4 * Five-year cumulative incidence was calculated using the Kaplan–Meier method. † The analyses presented here were provided specifically for this report by Dr N. Wareham and Dr L. Franco, respectively. ‡ Data were not available for isolated-IFG alone. A fasting plasma glucose of 5.7 mmol/l has been found to be closer to a 2-h cut-off of 7.8 mmol/l (the lower cut point for IGT) both in terms of the sensitivity for future diabetes and in defining a category of similar prevalence to IGT. This has been shown in the data from Mauritius [11] and Pima Indians [23]. Thus, when looking at each of these populations, reducing the lower limit for IFG to 5.7 mmol/l yielded a group that was approximately the same proportion of the population as the IGT group, and identified a similar number of future cases of diabetes. However, given the differences in the distribution of IFG and IGT by age, sex and ethnicity described above, the ideal lower limit for IFG (ideal at least in terms of equal to IGT in prevalence and risk) will vary by these parameters and thus be population-specific. There is no a priori reason why the prevalence of IGT and IFG should be the same. Predictive properties of IGT and IFG for CVD and total mortality Glucose and its association with other CVD risk factors Both IFG and IGT are associated with CVD risk factors, including hypertension, dyslipidaemia, and other features of the metabolic syndrome (e.g. hyperinsulinaemia, microalbuminuria, inflammatory and haemostatic markers). Given the somewhat different physiological bases of IFG and IGT referred to earlier, differences in their association with other cardiovascular risk factors might be expected. However, published data presenting these associations are limited and often not population-based. Further data comparing CVD risk factors across these groups from a variety of populations are desirable. Those that are available suggest little difference between individuals with I-IFG and I-IGT in lipid levels or blood pressure, with higher levels in individuals with both IFG and IGT [9,13,28,29]. The intima-media thickness (IMT) of the common carotid artery is considered a valid marker of atherosclerosis. In the Risk factors in IGT for Atherosclerosis and Diabetes (RIAD) study the IMT in individuals with isolated IFG was no different from controls with normal glucose tolerance (NGT) matched for age, sex and body mass index (BMI). However, IMT was significantly higher in the group with combined IFG–IGT, with the I-IGT group having levels intermediate between the two [29]. Further analyses demonstrated that below a fasting plasma glucose of 7.0 mmol/l fasting glucose level was not related to IMT, but 2-h glucose level was predictive of IMT at fasting glucose levels of both 6.1–7.0 mmol/l, and < 6.1 mmol/l [30]. The relationship between glucose and CVD and total mortality The nature of the relationship between non-diabetic glucose levels and total and CVD mortality has been a subject of investigation for at least the past two decades, but until recently has remained relatively poorly defined. A major part of the reason for this has been the limited statistical power of most studies. In order to overcome this limitation two recent initiatives have pooled results or data from several studies and thus provided much greater statistical power for defining this relationship. In analyses unadjusted for other risk factors both fasting and 2-HPG are associated with total and CVD mortality. A meta-regression analysis was undertaken in which data relating glucose to CVD events (the vast majority of which were deaths) were combined from 20 studies with a mean follow-up of 12 years [22]. This found a continuous positive relationship between initial fasting and 2-HPG and CVD events that extended below the current thresholds for IFG and IGT. For example, using a reference plasma glucose value of 4.2 mmol/l, a fasting plasma glucose value of 6.1 mmol/l was associated with a relative risk of 1.33 (95% CIs 1.06–1.67), and a 2-HPG value of 7.8 mmol/l was associated with a relative risk of 1.58 (1.19–2.10). Analyses from the DECODE data set have also demonstrated an unadjusted association between both fasting and 2-h glucose and mortality, but with 2-h glucose being more predictive than fasting. Thus, in an analysis combining 13 prospective European studies [17] the hazard ratio for all-cause mortality (adjusted only for age, sex and study centre) compared with the group with normal fasting and 2-h glucose tolerance was 1.20 (95% CI 1.04–1.38) for IFG and 1.50 (1.33–1.69) for IGT. A significant association with fasting glucose categories was found only in those with normal 2-HPG (Fig. 3). Indeed, the relationship between fasting glucose and mortality was not independent of 2-HPG, but the relationship with 2-HPG was independent of fasting glucose. Figure 3Open in figure viewerPowerPoint Hazard ratios for all-cause mortality by fasting and 2-h plasma glucose. *95% CIs do not cross 1. (From DECODE Study Group. Lancet 1999; 354: 617–621.) Further analyses of the DECODE data set have examined the association between glucose tolerance categories and CHD, stroke, all CVD a