- About this Journal ·
- Abstracting and Indexing ·
- Advance Access ·
- Aims and Scope ·
- Annual Issues ·
- Article Processing Charges ·
- Articles in Press ·
- Author Guidelines ·
- Bibliographic Information ·
- Citations to this Journal ·
- Contact Information ·
- Editorial Board ·
- Editorial Workflow ·
- Free eTOC Alerts ·
- Publication Ethics ·
- Reviewers Acknowledgment ·
- Submit a Manuscript ·
- Subscription Information ·
- Table of Contents
International Journal of Endocrinology
Volume 2013 (2013), Article ID 613475, 9 pages
Effects of Age and Sex on Estimated Diabetes Prevalence Using Different Diagnostic Criteria: The Tromsø OGTT Study
1Tromsø Endocrine Research Group, Department of Clinical Medicine, University of Tromsø, 9037 Tromsø, Norway
2Division of Internal Medicine, University Hospital of North Norway, 9038 Tromsø, Norway
3Department of Community Medicine, University of Tromsø, 9037 Tromsø, Norway
4Department of Medical Biology, University of Tromsø, 9037 Tromsø, Norway
5Division of Laboratory Medicine, University Hospital of North Norway, 9038 Tromsø, Norway
Received 27 September 2012; Revised 4 December 2012; Accepted 5 December 2012
Academic Editor: Mario Maggi
Copyright © 2013 Moira Strand Hutchinson et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Hb 6.5% has recently been recommended as an alternative diagnostic criterion for diabetes. The aims of the study were to evaluate the effects of age, sex, and other factors on prevalence of diabetes and to compare risk profiles of subjects with diabetes when defined by Hb and glucose criteria. Subjects were recruited among participants in the longitudinal population-based Tromsø Study. Hb, fasting plasma glucose, and 2-hour plasma glucose were measured in 3,476 subjects. In total, 294 subjects met one or more of the diagnostic criteria for diabetes; 95 met the Hb criterion only, 130 met the glucose criteria only, and 69 met both. Among subjects with diabetes detected by glucose criteria (regardless of Hb), isolated raised 2-hour plasma glucose was more common in subjects aged ≥ 60 years as compared to younger subjects and in elderly women as compared to elderly men. Subjects with diabetes detected by glucose criteria only had worse cardiometabolic risk profiles than those detected by Hb only. In conclusion, the current Hb and glucose criteria defined different subjects with diabetes with only modest overlap. Among a substantial proportion of elderly subjects, and especially elderly women, the 2-hour plasma glucose was the only abnormal value.
Criteria for the diagnosis of diabetes are based on measurements of fasting plasma glucose (FPG), 2-hour plasma glucose (2hPG), or haemoglobin (Hb). Single raised values with symptoms or raised values on two occasions of any one of these tests, or a combination of these tests can be used for diagnosis of diabetes [1, 2]. The most commonly used test is the FPG as it is simple and inexpensive. The 2hPG is measured in combination with FPG in the oral glucose tolerance test (OGTT), where plasma glucose is measured in the morning after an overnight fast and 2 hours after oral ingestion of 75 g glucose. Hb was recently introduced as a diagnostic test for diabetes. Compared to glucose measurements, Hb has better sample stability, lower within-person variation and is independent of acute factors such as illness, recent food ingestion, stress, or exercise .
Diagnostic levels of FPG, 2hPG, and Hb are based on thresholds for increased risk of micro- and macrovascular disease, in particular retinopathy [1, 4]. In the DETECT-2 study, sensitivity and specificity for prediction of prevalent retinopathy were almost equal when comparing FPG, 2hPG and Hb . Several recent studies have shown that both the prevalence of diabetes and the subjects diagnosed with diabetes vary when different diagnostic criteria for diabetes are applied [6–11]. According to current guidelines, clinicians can choose freely among FPG, OGTT, and Hb when testing a patient for diabetes [1, 2]. As Hb and glucose criteria have been shown to identify different subjects with diabetes with relatively modest overlap, the choice of test may affect the test outcome [6, 7, 9]. This is important both at the individual level, where correct diagnosis, treatment, and prevention of later complications are in focus, and at the population level where early identification of the “correct” individuals at risk of developing complications is important for cost-effective utilisation of resources. Furthermore, race, age, and sex have been reported to affect the outcome of diabetes testing with different diagnostic criteria [6–8, 12, 13]. This could have implications for the preferred choice of test in subgroups of patients. In Tromsø we have recently performed a large health survey where we measured Hb, FPG, and 2hPG in 3,476 subjects without previously diagnosed diabetes. These data enabled us to study the effect of age, sex, and other factors on diabetes defined by different diagnostic criteria and to compare cardiometabolic risk profiles of subjects with diabetes defined by different criteria.
2. Materials and Methods
Subjects were recruited from the sixth survey of the longitudinal population-based Tromsø Study performed by the University of Tromsø from October 2007 to December 2008, where Hb was measured in 12,769 participants. All subjects without self-reported diabetes and with Hb in the range 5.8–6.9% and a random sample of approximately 200 subjects with Hb 5.3% and 5.4% and 100 subjects with Hb 5.5%, 5.6%, and 5.7%, respectively, were invited to participate in the Tromsø OGTT Study. Race was not registered, but practically all subjects were Caucasian.
Waist and hip circumference, height, weight, and blood pressure were measured, body mass index (BMI) was defined, and physical activity score (PAS) was calculated as previously described . Hb was determined by high performance liquid chromatography (HPLC) using an automated analyser (Variant II, Bio-Rad Laboratories Inc., Hercules, CA, USA). The reference interval was 4.3–6.1%. This analysis has been certified by the National Glycohemoglobin Standardization Program (NGSP) as having documented traceability to the Diabetes Control and Complication Trial (DCCT) reference method . Haemoglobin (Hb) was measured by photometry using an automated analyser (reference intervals 11.5–16.0 g/dL for women and 13.0–17.0 g/dL for men). Plasma glucose, serum insulin, and serum C-peptide were measured and analysed as previously described . Serum triglyceride (TG) was analysed with an enzymatic colorimetric assay using an automated clinical chemistry analyser (reference interval 0.5–2.6 mmol/L). Estimates of insulin sensitivity in the fasting state were calculated using homeostasis model assessment (HOMA-IR) and the Quantitative Insulin-Sensitivity Check Index (QUICKI) [16, 17], and insulin sensitivity including the 2-hour values for glucose and insulin with the insulin sensitivity index (ISI0.120) according to the formula by Gutt et al. [(/MPG)/log MSI, where = (75 000 mg + [fasting glucose (mg/dL) − 2-h glucose (mg/dL)] × 0.19 × body weight (kg))/120 min, MPG = mean of fasting and 2-h glucose concentrations (mmol/L); MSI = mean of fasting and 2-h insulin concentrations (milliunits per liter)] .
OGTTs were performed from February 2008 until August 2010 as previously described . All OGTTs were performed in the morning after an overnight fast. To minimize time between OGTT and Hb, the latter was measured simultaneously with the OGTT from September 2008 onwards. Hb from the Tromsø Study 2007-2008 was used for the 932 participants who completed OGTT before September 2008. Mean change in Hb for the 2,544 subjects who measured Hb on both occasions was %. For the purpose of this study, we chose to classify subjects with a single value of FPG ≥ 7.0 mmol/L, 2hPG ≥ 11.1 mmol/L, and/or Hb ≥ 6.5% as having diabetes, even though subjects were asymptomatic. Subjects with diabetes were subdivided into diabetes detected by Hb only, by OGTT (raised FPG and/or 2hPG) only and by both. Furthermore, subjects with diabetes detected by OGTT (regardless of Hb) were subdivided into diabetes detected by FPG (regardless of 2hPG) and by isolated raised 2hPG.
Normal distribution was evaluated by visual inspection of histograms and determination of skewness and kurtosis, and after natural log transformation of TG, PAS, QUICKI, HOMA-IR, and ISI0.120, all variables except the PAS (where several subjects had “0” values) were considered normally distributed. Ln values were used when these variables were dependent variables. Pearson Chi-square test was used for subgroup analysis in Table 2. Comparisons between groups were performed with logistic regression for categorical variables and univariate analysis of variance with Bonferroni post hoc adjustment or Mann Whitney U test for continuous variables in Table 3. Venn diagrams were constructed to illustrate overlap between diagnostic criteria and scatterplots to illustrate the distribution of FPG and 2hPG values in relation to Hb. Unless otherwise stated, data are expressed as mean ± SD for normally distributed values and as median (5, 95 percentile) for non-normally distributed values. All tests were two-sided, and value < 0.05 was considered statistically significant. The Statistical Package for Social Sciences version 17.0 was used for all statistical analyses (SPSS Inc., Chicago, IL, USA).
Among the 4,393 subjects who were invited, 3,520 attended and 3,476 completed the OGTT. The number of subjects planned to participate, invited to OGTT, and attended at different Hb levels, as measured in the Tromsø Study 2007-2008, is presented in Table 1. In total, 294 (8.5%) subjects met one or more of the diagnostic criteria for diabetes. Mean age was 61 years and 49.5% were women.
3.1. Prevalence of Diabetes Defined by Different Diagnostic Criteria
Among those who completed OGTT, 164 (4.7%) met the Hb criterion, 119 (3.4%) met the FPG criterion, and 126 (3.6%) met the 2hPG criterion. In total 199 (5.7%) met the OGTT (FPG and/or 2hPG) criteria. As presented in Table 2, 95 (32.3%) of those with diabetes met the Hb criterion only, 130 (44.2%) met the OGTT criteria only, and 69 (23.5%) met both criteria. The overlap between subjects with diabetes defined by Hb and OGTT varied between 10–35% in different subgroups.
Hb alone detected more subjects with diabetes as compared to OGTT alone in those with BMI < 25 kg/m2, TG < 1.2 mmol/L, and high PAS, but there were no significant differences in subgroup analysis of age and sex (Table 2). Among those with diabetes detected by OGTT (regardless of Hb), isolated raised 2hPG was more common in subjects aged ≥ 60 years and women (Table 2). This effect of age and sex was not due to differences in BMI. Stratification for age showed that the sex difference was significant only in those aged ≥ 60 years, where 58% of women and 36% of men had isolated raised 2hPG (). Mean age and BMI did not differ significantly between men and women. Furthermore, the sex difference was significant only in the two lower BMI groups () and in the lowest PAS tertile ().
The distribution of subjects with diabetes detected by Hb only, OGTT only, and both, as well as by OGTT components (FPG and isolated raised 2hPG) is illustrated stratified for age and sex in Figure 1. The overlap between subjects with diabetes defined by Hb and OGTT was relatively consistent, but prevalence of isolated raised 2hPG was higher in subjects aged ≥ 60 years as compared to younger subjects, and in elderly women as compared to elderly men. In subjects aged ≥ 60 years the distribution of 2hPG values in relation to Hb values was more scattered as compared to younger subjects (Figure 2), illustrating that for many subjects in this age group an Hb value < 6.5% did not exclude a 2hPG value above the cut off point for diabetes.
3.2. Characteristics of Subjects with Diabetes Defined by Different Diagnostic Criteria
As presented in Table 3, subjects with diabetes detected by Hb only had lower TG, lower systolic blood pressure, higher insulin sensitivity and were less insulin resistant and more physically active as compared to subjects with diabetes detected by OGTT only. Among subjects with diabetes detected by OGTT (regardless of Hb), those with raised FPG differed from those with isolated raised 2hPG by being younger, predominantly men and more insulin resistant (Table 3).
4.1. Prevalence of Diabetes Defined by Different Diagnostic Criteria
In our population, we found prevalence of diabetes detected by OGTT only to be higher than prevalence of diabetes detected by Hb only. The present study also confirmed results from recent studies showing that Hb and OGTT define different subjects with diabetes with relatively modest overlap, which in our study was only 23.5% [6, 7, 9]. Prevalence of diabetes defined by Hb and OGTT, and overlap between these, differs in previous studies, probably due to differences in age, race, and sex composition of the populations and/or lack of standardisation of Hb and glucose measurements [7, 8, 12, 13, 19].
Race, age, and sex have been reported to affect the outcome of diabetes testing with different diagnostic criteria [6–8, 12, 13]. Our study population did not allow us to study the effect of race as practically all subjects were Caucasian. When comparing subjects aged ≥ 60 years with younger subjects, we found no difference in prevalence of diabetes detected by Hb only and OGTT only. Among those with diabetes detected by OGTT (regardless of Hb), prevalence of isolated raised 2hPG was higher in older (≥60 years) as compared to younger subjects. Furthermore, we found that among subjects aged ≥ 60 years, having a 2hPG in the diabetic range but a nondiabetic Hb value was more common as compared to younger subjects. Similarly, in the Finnish population-based cross sectional FIN-D2D study including 2,826 men and women aged 45–74 years, any given Hb value was found to imply a much higher 2hPG and slightly lower FPG in elderly as compared to middle aged subjects . The 2hPG is known to increase more with age than FPG [20, 21]. Possible explanations for the increased prevalence of isolated raised 2hPG among elderly subjects could be reduced basal insulin secretion , delayed insulin response after oral glucose intake , physical inactivity, and/or weight gain .
In our data, there was no sex difference in diabetes detected by Hb only and OGTT only. However, we found that among those with diabetes detected by OGTT (regardless of Hb), isolated raised 2hPG was more common in elderly women as compared to elderly men, a difference that could not be explained by differences in age or BMI. Similarly, the FIN-D2D study reported that Hb tends to miss more elderly diabetic people and especially women . Previous studies have suggested that differences in FPG and Hb levels are likely to reflect sex-specific differences in glucose regulation as they, unlike differences in 2hPG, remained after adjusting for height and body composition [24, 25]. We also found that Hb alone detected more subjects with diabetes as compared to OGTT alone in subjects with BMI < 25 kg/m2 as compared to those with higher BMI. In a recently published paper, we reported that a particular Hb value implied relatively higher 2hPG and FPG in subjects with high BMI compared to subjects with lower BMI . As very few reports have addressed this issue, it remains uncertain whether BMI has an effect on diagnosis of diabetes by different criteria.
4.2. Characteristics of Subjects with Diabetes Defined by Different Diagnostic Criteria
In our population, subjects with diabetes detected by OGTT only had a worse cardiometabolic risk profile than those detected by Hb only. Previous studies have shown conflicting results; some have found the worst risk profiles in subjects with diabetes defined by OGTT [6, 8, 9], some in subjects with diabetes defined by Hb , and some have found the two groups to have equally unfavourable risk profiles [8, 10]. In the international A1C-Derived Average Glucose study including 427 subjects with diabetes, Hb, FPG, and 2hPG were all associated with CVD risk factors, but the strongest association was seen with Hb . We did not have data to evaluate the risk of diabetes complications in the different groups. Although both Hb and 2hPG have been shown to be independent risk factors for cardiovascular morbidity and mortality, the added prognostic information may be marginal as compared to standard nonglycaemic risk factors [28–30]. In a prospective study based on the Norwegian population-based longitudinal HUNT study, the risk of macrovascular complications in subjects with relatively low Hb values was found to be mainly related to conventional risk factors .
The strength of our study is that OGTT was performed in a large number of subjects recruited from a population representative of the general population in our area. The main shortcomings of our study are that only subjects with Hb in the range of 5.3–6.9% were invited to participate and that subjects included at an early stage of the study did not have Hb measured simultaneously with the OGTT, but were included in the analysis with the Hb value measured in the Tromsø Study 2007-2008. We chose to include these subjects in the analysis as we found that change in Hb from the Tromsø Study to the OGTT visit was negligible for those who had Hb measured at both occasions. Furthermore, in the absence of clear symptoms, diagnosis of diabetes requires raised values of Hb, FPG, or 2hPG on two occasions. For practical reasons, we did not repeat either Hb, or the OGTTs, but chose to classify subjects with a single raised value of Hb, FPG, or 2hPG as having diabetes. As FPG, and especially 2hPG, are known to have high within-person variation, repeating the OGTTs to confirm the diagnosis would probably have reduced the number of subjects with diabetes detected by OGTT . Hb is known to be affected by anaemia. Hb was measured in the Tromsø Study 2007-2008, but not simultaneously as OGTT. However, anaemia is not a source of error when analysing Hb with the HPLC method used in our study as the analysis is not performed if there are too few or too many erythrocytes in the sample. Haemolytic anaemia could result in falsely low Hb, but the condition is rare in our population and is not likely to affect the results. Other shortcomings are that we did not have information about retinopathy or other end organ diseases, and that we did not differentiate between type 1 and type 2 diabetes. However, as subjects in our study did not have previously diagnosed diabetes and age ranged from 30–87 years, most diabetes cases were likely to be type 2 diabetes. The cross-sectional study design is a major limitation when evaluating the impact of using different diagnostic criteria for diabetes. Prospective studies are needed to clarify which test detects the population with the highest risk of disease progression and complications of diabetes.
The current Hb and glucose criteria for diabetes defined different subjects with only modest overlap. Among those with diabetes detected by OGTT (regardless of Hb), isolated raised 2-hour plasma glucose was more common in subjects aged ≥ 60 years as compared to younger subjects, and in elderly women as compared to elderly men. As race, age, sex, and possibly BMI seem to affect Hb, FPG, and 2hPG and the relationship between these, creating an algorithm for choice of diagnostic test in different subgroups is a possibility and may be beneficial. If the aim is to detect as many patients with diabetes as possible, our data suggest that OGTT would be preferable for those aged ≥ 60 years, and especially women, while Hb would be preferable for the younger and those with low BMI. However, in order to decide which diagnostic test should be preferred, and whether race, age, sex, and/or BMI specific guidelines should be considered, prospective studies with micro- and macrovascular end-points are needed.
|OGTT:||Oral glucose tolerance test|
|FPG:||Fasting plasma glucose|
|2hPG:||2-hour plasma glucose|
|HPLC:||High precision liquid chromatography|
|BMI:||Body mass index|
|HOMA-IR:||Homeostasis model assessment-insulin resistance|
|QUICKI:||Quantitative insulin-sensitivity check index|
|:||Insulin sensitivity index,|
|PAS:||Physical activity score|
The study was approved by the Regional Committee for Medical and Health Research Ethics, North Norway. All participants gave written informed consent prior to the study.
Conflict of Interests
No potential conflict of interests relevant to this paper was reported.
M. S. Hutchinson gathered and researched data and wrote the paper. R. M. Joakimsen contributed to the discussion and reviewed the paper. I. Njølstad was responsible for the Tromsø Study data and reviewed the paper. H. Schirmer contributed to the discussion and reviewed the paper. Y. Figenschau was responsible for the laboratory analyses and reviewed the paper. J. Svartberg contributed to the discussion and reviewed the paper. R. Jorde led the Tromsø OGTT Study, contributed to the discussion and reviewed the paper.
The superb assistance provides by study nurse Anita Korsberg and the staff at the Clinical Research Unit at the University Hospital of North Norway as well as the staff at the Division of Laboratory Medicine, University Hospital of North Norway, is gratefully acknowledged. The present study was supported by a grant from The Northern Norway Regional Health Authority and the Research Council of Norway.
- World Health Organization, Use of Glycated Haemoglobin (HbA1c) in the Diagnosis of Diabetes Mellitus: Abbreviated Report of a WHO Consultation, World Health Organization, Geneva, Switzerland, 2011.
- American Diabetes Association, “Diagnosis and classification of diabetes mellitus,” Diabetes Care, vol. 35, supplement 1, pp. S64–S71, 2012.
- D. B. Sacks, “A1C versus glucose testing: a comparison,” Diabetes Care, vol. 34, no. 2, pp. 518–523, 2011.
- “Report of the expert committee on the diagnosis and classification of diabetes mellitus,” Diabetes Care, vol. 20, no. 7, pp. 1183–1197, 1997.
- S. Colagiuri, C. M. Y. Lee, T. Y. Wong, B. Balkau, J. E. Shaw, and K. Borch-Johnsen, “Glycemic thresholds for diabetes-specific retinopathy: implications for diagnostic criteria for diabetes,” Diabetes Care, vol. 34, no. 1, pp. 145–150, 2011.
- W. Rathmann, B. Kowall, T. Tamayo, et al., “Hemoglobin A1c and glucose criteria identify different subjects as having type 2 diabetes in middle-aged and older populations: The KORA S4/F4 Study,” Annals of Internal Medicine, vol. 44, no. 2, pp. 170–177, 2012.
- C. C. Cowie, K. F. Rust, D. D. Byrd-Holt et al., “Prevalence of diabetes and high risk for diabetes using A1C criteria in the U.S. population in 1988–2006,” Diabetes Care, vol. 33, no. 3, pp. 562–568, 2010.
- R. Borg, D. Vistisen, D. R. Witte, and K. Borch-Johnsen, “Comparing risk profiles of individuals diagnosed with diabetes by OGTT and HbA1cThe Danish Inter99 study,” Diabetic Medicine, vol. 27, no. 8, pp. 906–910, 2010.
- S. A. Mostafa, M. J. Davies, D. Webb et al., “The potential impact of using glycated haemoglobin as the preferred diagnostic tool for detecting Type 2 diabetes mellitus,” Diabetic Medicine, vol. 27, no. 7, pp. 762–769, 2010.
- E. Cosson, M. T. Nguyen, E. Hamo-Tchatchouang et al., “What would be the outcome if the American Diabetes Association recommendations of 2010 had been followed in our pratice in 1998–2006?” Diabetic Medicine, vol. 28, no. 5, pp. 567–574, 2011.
- C. Lorenzo and S. M. Haffner, “Performance characteristics of the new definition of diabetes: the insulin resistance atherosclerosis study,” Diabetes Care, vol. 33, no. 2, pp. 335–337, 2010.
- D. L. Christensen, D. R. Witte, L. Kaduka et al., “Moving to an A1C-based diagnosis of diabetes has a different impact on prevalence in different ethnic groups,” Diabetes Care, vol. 33, no. 3, pp. 580–582, 2010.
- J. T. Saltevo, H. Kautiainen, L. Niskanen, et al., “Ageing and associations of fasting plasma glucose and 2h plasma glucose with HbA(1C) in apparently healthy population., “FIN-D2D” study,” Diabetes Research and Clinical Practice Journal, vol. 93, pp. 344–349, 2011.
- M. S. Hutchinson, R. M. Joakimsen, I. Njolstad, H. Schirmer, Y. Figenschau, and R. Jorde, “Haemoglobin A1c in diagnosis of diabetes mellitus and pre-diabetes, validation by oral glucose tolerance test. The Tromso OGTT Study,” Journal of Endocrinological Investigation, vol. 35, no. 9, pp. 835–840, 2012.
- R. R. Little, C. L. Rohlfing, and D. B. Sacks, “Status of hemoglobin A1c measurement and goals for improvement: from Chaos to order for improving diabetes care,” Clinical Chemistry, vol. 57, no. 2, pp. 205–214, 2011.
- A. Katz, S. S. Nambi, K. Mather et al., “Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans,” Journal of Clinical Endocrinology and Metabolism, vol. 85, no. 7, pp. 2402–2410, 2000.
- D. R. Matthews, J. P. Hosker, A. S. Rudenski, B. A. Naylor, D. F. Treacher, and R. C. Turner, “Homeostasis model assessment: Insulin resistance and β-cell function from fasting plasma glucose and insulin concentrations in man,” Diabetologia, vol. 28, no. 7, pp. 412–419, 1985.
- M. Gutt, C. L. Davis, S. B. Spitzer et al., “Validation of the insulin sensitivity index (ISI0,120): comparison with other measures,” Diabetes Research and Clinical Practice, vol. 47, no. 3, pp. 177–184, 2000.
- “International Expert Committee report on the role of the A1C assay in the diagnosis of diabetes,” Diabetes Care, vol. 32, pp. 1327–1334, 2009.
- “Consequences of the new diagnostic criteria for diabetes in older men and women: The DECODE Study (Diabetes Epidemiology: Collaborative Analysis of Diagnostic Criteria in Europe),” Diabetes Care, vol. 22, no. 10, pp. 1667–1671, 1999.
- M. B. Davidson, “The effect of aging on carbohydrate metabolism: a review of the English literature and a practical approach to the diagnosis of diabetes mellitus in the elderly,” Metabolism: Clinical and Experimental, vol. 28, no. 6, pp. 688–705, 1979.
- P. Iozzo, H. Beck-Nielsen, M. Laakso, U. Smith, H. Yki-Järvinen, and E. Ferrannini, “Independent influence of age on basal insulin secretion in nondiabetic humans,” Journal of Clinical Endocrinology and Metabolism, vol. 84, no. 3, pp. 863–868, 1999.
- P. Imbeault, J. B. Prins, M. Stolic et al., “Aging per se does not influence glucose homeostasis: in vivo and in vitro evidence,” Diabetes Care, vol. 26, no. 2, pp. 480–484, 2003.
- K. Færch, K. Borch-Johnsen, A. Vaag, T. Jørgensen, and D. R. Witte, “Sex differences in glucose levels: a consequence of physiology or methodological convenience? the Inter99 study,” Diabetologia, vol. 53, no. 5, pp. 858–865, 2010.
- R. A. Sicree, P. Z. Zimmet, D. W. Dunstan, A. J. Cameron, T. A. Welborn, and J. E. Shaw, “Differences in height explain gender differences in the response to the oral glucose tolerance test—The AusDiab study,” Diabetic Medicine, vol. 25, no. 3, pp. 296–302, 2008.
- M. Boronat, P. Saavedra, L. Lopez-Rios, M. Riano, A. M. Wagner, and F. J. Nóvoa, “Differences in cardiovascular risk profile of diabetic subjects discordantly classified by diagnostic criteria based on glycated hemoglobin and oral glucose tolerance test,” Diabetes Care, vol. 33, no. 12, pp. 2671–2673, 2010.
- R. Borg, J. C. Kuenen, B. Carstensen et al., “HbA1cand mean blood glucose show stronger associations with cardiovascular disease risk factors than do postprandial glycaemia or glucose variability in persons with diabetes: The A1C-Derived Average Glucose (ADAG) study,” Diabetologia, vol. 54, no. 1, pp. 69–72, 2011.
- K. T. Khaw, N. Wareham, S. Bingham, R. Luben, A. Welch, and N. Day, “Association of hemoglobin A1c with cardiovascular disease and mortality in adults: The European prospective investigation into cancer in Norfolk,” Annals of Internal Medicine, vol. 141, no. 6, pp. 413–420, 2004.
- J. B. Meigs, D. M. Nathan, R. B. D'Agostino, and P. W. F. Wilson, “Fasting and postchallenge glycemia and cardiovascular disease risk: the framingham offspring study,” Diabetes Care, vol. 25, no. 10, pp. 1845–1850, 2002.
- The DECODE Study Group, “Glucose tolerance and cardiovascular mortality: comparison of fasting and 2-hour diagnostic criteria,” Archives of Internal Medicine, vol. 161, pp. 397–405, 2001.
- A. C. Dale, K. Midthjell, T. I. Nilsen, R. Wiseth, and L. J. Vatten, “Glycaemic control in newly diagnosed diabetes patients and mortality from ischaemic heart disease: 20-year follow-up of the HUNT Study in Norway,” European Heart Journal, vol. 30, no. 11, pp. 1372–1377, 2009.
- E. Selvin, C. M. Crainiceanu, F. L. Brancati, and J. Coresh, “Short-term variability in measures of glycemia and implications for the classification of diabetes,” Archives of Internal Medicine, vol. 167, no. 14, pp. 1545–1551, 2007.