E. van t Riet J.M. Rijkelijkhuizen M. Alssema G.Nijpels C.D.A. Stehouwer R. J. Heine J. M. Dekker

Transcription

1 8 HbA1c is an independent predictor of nonfatal cardiovascular disease in a Caucasian population without diabetes. A 10-year follow-up of the Hoorn Study E. van t Riet J.M. Rijkelijkhuizen M. Alssema G.Nijpels C.D.A. Stehouwer R. J. Heine J. M. Dekker Eur J of Cardiac Prev and Rehab, 2010 (Epub ahead of print)

2 Chapter 8 Abstract Aims To investigate the associations of HbA1c, fasting glucose and post load plasma glucose with 10-year fatal and non-fatal cardiovascular disease (CVD) and allcause mortality in Caucasian subjects between 50 and 75 years of age without diabetes. Method and Results The 10-year risk of all-cause mortality and CVD in relation to HbA1c and glucose levels was assessed with Cox survival analysis in 1674 non-diabetic subjects of a population-based cohort (Hoorn Study). Analyses were stratified according to sex and adjustments were made for age and known CVD risk factors. After full adjustment, HbA1c levels 6.0% were significantly associated with an increased risk of non-fatal CVD compared to the lowest category of HbA1c ( 5.1%) in women [HR 2.27 ( )]. In addition, HbA1c as a continuous variable was significantly related to non-fatal CVD in both men [HR 1.40 ( )] and women [HR 2.41 ( )]. The relationships of HbA1c with fatal CVD and all-cause mortality were explained by traditional CVD risk factors in both sexes, as well as the associations between fasting or post load plasma glucose with any of the outcome measures. Conclusion In Caucasian men and especially in women between 50 and 75 years of age without diabetes, high HbA1c levels are associated with increased risk of future non-fatal CVD, independent of other CVD risk factors. 134

3 HbA1c, glucose and incident cardiovascular disease Introduction Cardiovascular disease (CVD) is one of the main complications among patients with type 2 diabetes. Compared to the general non-diabetic population, patients with type 2 diabetes have a 2 to 4 fold higher risk of death from CVD [1,2]. In general, fasting plasma glucose levels and plasma glucose levels 2-hours after a glucose tolerance test (post load glucose levels) are used for diagnosis of diabetes [3]. In addition, glycated haemoglobin (HbA1c) levels are used to monitor glycaemic control in patients with diabetes. Several large-scale studies have shown that in patients with diabetes, HbA1c is a strong predictor of CVD, after correction for other CVD risk factors (e.g. dyslipidemia, hypertension, smoking and micro-albuminuria) [4-6], such that an improved glycaemic control is associated with a delay of onset of and decline in micro and macro-vascular complications [7,8]. In addition, high fasting glucose levels and especially high post load glucose levels are also known to be related to an increased CVD risk in patients with type 2 diabetes [9,10]. Evidence on the increased risk of CVD with high HbA1c and post load glucose levels in subjects without diabetes is accumulating [9,11-16]. Levitan et al. [17], on the basis of a systematic review, concluded that blood glucose levels are associated with CVD risk in individuals without diabetes, and this association was stronger in women. However, most studies contained data on fatal CVD only. Information on the relationship between markers of hyperglycaemia and non-fatal CVD in subjects without diabetes is rare. Recent research on glycaemia in the non-diabetic range and predictors of nonfatal CVD, like intimae medial thickness [18] and coronary artery calcium [19,20], indicate that there might be an association between markers of hyperglycaemia and non-fatal CVD in subjects without diabetes. Adams et al. found an association between high HbA1c levels and self-reported CVD and stroke in 2913 adults free of diabetes [21]. 135

4 Chapter 8 Since evidence on the relation between different markers of hyperglycaemia and CVD in the general population is accumulating, research including all three markers of hyperglycaemia (fasting glucose, post load glucose and HbA1c) measured in one population is needed to establish the individual role of all these markers. In addition, studies describing hyperglycaemia in relation to well-documented non-fatal CVD are scarce. Therefore, our aim was to investigate the associations of HbA1c, fasting glucose and post load glucose with 10-year fatal and non-fatal CVD in Caucasian men and women without diabetes in the Hoorn Study. Methods Study procedure The Hoorn Study is a Dutch cohort study of diabetes and diabetes complications in the general population, which started in The cohort and the baseline measurements have been described in detail previously [22]. Briefly, a random selection of 3553 men and women of 50 to 75 years old was taken from the population register of the middle-sized Dutch town of Hoorn. A total of 2540 (71,5%) agreed to participate, and after exclusion of 56 non-caucasian participants, the Hoorn Study population consisted of 2484 men and women. For the present study we excluded 90 patients with known diabetes (based on treatment with glucose lowering medication or diet), 165 subjects with newly diagnosed diabetes at baseline (based on OGTT results using the WHO 06 criteria on glucose metabolism [3]) and 17 subjects with missing information on either HbA1c or plasma glucose values. In figure 1, a flow chart of the inclusion is presented. All participants gave their written informed consent. The study was approved by the Ethics Committee of the VU University Medical Center. 136

5 HbA1c, glucose and incident cardiovascular disease B A S E L I N E Invited at baseline N=3553 Assessed for eligibility N=2540 Refused to participate N=1013 Excluded Non-Caucasian N=56 Participants at baseline N=2484 F O L L O W U P Complete information of morbidity and mortality follow-up available N=1919 Missing information on morbidity follow-up N=541 Missing information on cause of death N= 24 Excluded A N A L Y S I S Eligible for current analysis N=1647 Known diabetes N=90 Newlydiagnosed diabetes N=165 Missing information on glycaemic measures N=17 Figure 1. Flow chart of the inclusion 137

6 Chapter 8 Baseline measurements At the baseline medical examination, a fasting blood sample was taken from all participants after overnight fast, and an oral 75-g glucose load was given. Weight and height were measured, and body mass index (BMI) was calculated as the ratio of weight and height squared. In addition, waist and hip circumference were determined, to calculate the waist-to-hip ratio. Blood pressure was measured twice on the right arm with a random-zero sphygmomanometer (Hawksley-Gelman Ltd, Lancing, UK). Hypertension was defined as systolic blood pressure 140 mm Hg, diastolic blood pressure 90 mm Hg, or when using anti-hypertensive medication. Information about use of medication, including antihypertensive medication, smoking status (non-smokers, ex-smokers and current smokers), and history of cardiovascular disease (Rose Questionnaire) were determined by a selfadministered questionnaire. Laboratory procedures Fasting and 2-hour post load plasma glucose concentrations were determined with a glucose dehydrogenase method. HbA1c levels were determined by ionexchange high performance liquid chromatography (HPLC-Biorad Diamat, Veenendaal, the Netherlands). Triglycerides, total and HDL-cholesterol were determined from fasting blood samples by enzymatic techniques (Boehringer-Mannheim, Mannheim, Germany). LDL-cholesterol was estimated with the Friedewald formula, except in subjects with triglycerides >4.5 mmol/l. Follow-up The cohort is being followed with respect to morbidity and mortality. Vital status is obtained from the population register of the city of Hoorn. Information on morbidity and mortality is continuously obtained from the local hospital, and periodically from the medical records of the general practitioners. Causes 138

7 HbA1c, glucose and incident cardiovascular disease of death were coded according to the International Classification of Diseases, Injuries and Causes of Death, ninth revision (ICD-9). Fatal cases of CVD were defined with ICD codes 390 to 459 (diseases of the circulatory system) or 798 (sudden death, cause unknown), because sudden death generally is of cardiovascular origin. Vital status until January 2000 was known for all subjects. Causes of death could not be obtained for 24 participants. Data on non-fatal CVD were complete until January From 541 participants, data on non-fatal CVD were not available (Figure 1). Missing data resulted from participants who moved out of the town of Hoorn and could not be contacted, or because the participant gave no permission to access their hospital files and/or contact their general practitioner. Participants with complete follow-up data did not differ from participants without complete follow-up on mean age, fasting glucose, 2-hour post load glucose, HbA1c, cholesterol, blood pressure and prevalent CVD at baseline (all p > 0.10). However, they had a higher mean BMI (p=0.05), were more often women (p=0.02) and contained a higher proportion of current smokers (p=0.01). The medical records of the general practitioners of all participants who gave permission were searched for non-fatal CVD events in Based on the criteria for cardiovascular disease, events were graded by a medical coder as: documented angina pectoris (chest pain followed by coronary artery bypass surgery or angioplasty, or in the presence of >50% stenosis, or ECG changes or positive exercise test), myocardial infarction (in the presence of at least 2 of the following: typical pain, elevated enzymes, or ECG changes), congestive heart failure (in the presence of at least 2 of the following: shortness of breath, cardiomegaly, or dilated neck veins, or 1 of the former in the presence of oedema or tachycardia), stroke or transient ischemic attack (sudden onset of symptoms, neurological symptoms, or change of consciousness), peripheral disease (by procedure, or typical pain accompanied by stenosis, ankle-arm blood pressure ratio < 0.90, or positive vascular stress test). In case of doubt 139

8 Chapter 8 in the grading, a medical doctor in internal medicine or cardiology was consulted. Statistical analyses Subjects were categorized according to tertiles of HbA1c, fasting glucose and post load glucose. In the highest tertiles of fasting and post load glucose, further subgroups were defined according to the cut-off points of the WHO definitions of impaired fasting glucose (fasting plasma glucose mmol/l) and impaired glucose tolerance (post load plasma glucose mmol/l) [3]. In addition, in the highest tertile of HbA1c, a subgroup representing the highest 10% of HbA1c was created. Second, baseline characteristics of the study population were compared between categories of HbA1c. Differences relative to the lowest category of Hba1c were tested using ANOVA and Chi-square tests. Then, the associations of HbA1c, fasting glucose and post load glucose with total mortality, fatal and non-fatal cardiovascular morbidity were studied with Cox proportional hazards analyses. The resulting hazard ratio s can be interpreted as relative risks. Proportional hazard assumptions were checked for every model by interpretation of the survival plots. Because of a significant interaction effect of sex in the models, analyses were stratified according to sex. In the first model we adjusted for age. The second model was additionally adjusted for known CVD risk factors, which decreased the estimated relative risks of the indicators of glycaemic exposure in bivariate analysis: hypertension (dichotomous, yes/no), smoking (dichotomous, yes/ no), LDL cholesterol (continuous), HDL cholesterol (continuous), triglycerides (continuous), waist- to- hip ratio (continuous) and self-reported history of CVD (dichotomous, yes/no). All analysis were performed using the Statistical Package for the Social Sciences (SPSS for Windows 14.0). The cut-off point for statistical significance was p<0.05 for all analysis and p<0.10 for interaction effects. 140

9 HbA1c, glucose and incident cardiovascular disease Table 1. Baseline characteristics in categories of HbA1c for men and women MEN HbA1c 5.1 HbA1c HbA1c HbA1c 6.0 (upper 10%) Number of subjects Current smokers (%) * 55.8 * Hypertension (%) * 56.3 * Age (%) 59.7 ± ± ± 7.4 * 63.6 ± 7.0 * HbA1c (%) 4.8 ± ± 0.11 * 5.7 ± 0.11 * 6.20 ± 0.24 * Fasting glucose (mmol/l) 5.4 ± ± ± 0.48 * 5.70 ± 0.50 * Post load glucose (mmol/l) 5.16 ± ± ± ± 1.72 HDL (mmol/l) 1.27 ± ± 0.30 * 1.13 ± 0.28 * 1.10 ± 0.33 * LDL (mmol/l) 4.33 ± ± ± 1.08 * 4.85 ± 1.12 * Triglycerides (mmol/l) 1.30 (0.90, 1.94) 1.40 (0.90, 2.02) 1.50 (1.10, 2.30) * 1.60 ( ) * WHR 0.94 ± ± ± ± 0.06 BMI (kg/m 2 ) 25.7 ± ± ± ± 2.67 Fasting plasma glucose * 16.2 * 18.4 * 7.0 mmol/l (%) Postload glucose * 14.0 * 6.9 * mmol/l (%) Prevalent CVD (%) * 29.6 * 27.9 * WOMEN HbA1c 5.1 HbA1c HbA1c HbA1c 6.0 (upper 10%) Number of subjects Current smokers (%) * 43.8 * Hypertension (%) * 56.3 * Age (%) 60.3 ± ± ± 7.6 * 63.5 ± 6.6 HbA1c (%) 4.8 ± ± 0.11 * 5.7 ± 0.11 * 6.14 ± 0.15 * Fasting glucose (mmol/l) 5.16 ± ± 0.49 * 5.47 ± 0.52 * 5.68± 0.58 * Postload glucose (mmol/l) 5.38 ± ± 1.63 * 5.78 ± 1.78 * 6.42 ± 2.01 * HDL (mmol/l) 1.51 ± ± ± 0.34 * 1.37 ± 0.35 * LDL (mmol/l) 4.49 ± ± 1.03 * 4.98 ± 1.19 * 4.92 ± 1.20 * Triglycerides (mmol/l) 1.20 (0.84, 1.60) 1.20 (0.90, 1.80) 1.40 (1.00, 2.10) * 1.50 ( ) * WHR 0.82 ± ± 0.07 * 0.84± 0.07 * 0.87± 0.07 * BMI (kg/m 2 ) 26.3 ± ± ± ± 3.91* Fasting plasma glucose * 14.9 * 26.3 * 7.0 mmol/l (%) Postload glucose * 13.1 * 25.0 * mmol/l (%) Prevalent CVD (%) * Results are mean ± SD, percentage or median (20,80 percentile) * Significantly different from HbA1c 5.1 using Chi-square or ANOVA. log-transformed before testing 141

10 Chapter 8 Table 2. Fasting plasma glucose (mmol/l) in relation to non-fatal CVD, fatal CVD, fatal and non-fatal CVD combined and all-cause mortality (hazard ratio s with 95% confidence interval). MEN Fasting plasma glucose mmol/l (n) < 5.2 (214) (247) (225) (110) Continuous Non-fatal CVD (n=178) Model ( ) 1.07 ( ) 1.08 ( ) 1.14 ( ) Model ( ) 0.93 ( ) 0.81 ( ) 0.93 ( ) Fatal CVD (n=76) Model ( ) 1.07 ( ) 1.49 ( ) 1.29 ( ) Model ( ) 0.83 ( ) 1.24 ( ) 1.03 ( ) Fatal and non-fatal CVD (n=217) Model ( ) 0.96 ( ) 1.17 ( ) 1.13 ( ) Model ( ) 0.80 ( ) 0.88 ( ) 0.91 ( ) All-cause mortality (n=152) Model ( ) 1.09 ( ) 1.60 ( ) 1.26 ( ) Model ( ) 0.89 ( ) 1.37 ( ) 1.03 ( ) WOMEN Fasting plasma glucose mmol/l (n) < 5.2 (328) (276) (196) (78) Continuous Non-fatal CVD (n=107) Model ( ) * 1.64 ( ) 1.71 ( ) 1.22 ( ) Model ( ) 1.39 ( ) 1.27 ( ) 1.00 ( ) Fatal CVD (n=37) Model ( ) 0.35 ( ) 0.54 ( ) 0.59 ( ) Model ( ) 0.38 ( ) 0.38 ( ) 0.45 ( ) Fatal and non-fatal CVD (n=134) Model ( ) 1.29 ( ) 1.42 ( ) 1.08 ( ) Model ( ) 1.08 ( ) 0.95 ( ) 0.85 ( ) All-cause mortality (n=100) Model ( ) 0.69 ( ) 1.27 ( ) 1.03 ( ) Model ( ) 0.64 ( ) 1.02 ( ) 0.90 ( ) Model 1: adjusted for age Model 2: additionally adjusted for hypertension, smoking, LDL-cholesterol, HDL-cholesterol, triglycerides, waist-to-hip ratio and self-reported history of CVD. * P <

11 HbA1c, glucose and incident cardiovascular disease Results Population characteristics In both men and women without diabetes, higher HbA1c levels were associated with an adverse cardiovascular risk profile, including a higher proportion of smokers and participants with hypertension, higher triglycerides and a lower HDL cholesterol (Table 1). Morbidity and mortality Until January 2000, 252 of the 1674 subjects died, 285 had at least one nonfatal cardiovascular event, 113 had a fatal cardiovascular event, and 351 had at least one fatal and/or nonfatal cardiovascular event. Fasting and post load glucose The results of the Cox regression analysis of fasting and post load glucose are presented for men in Table 2 and Table 3. Neither fasting, nor post load glucose showed statistically significant increased hazard ratios with any outcome measures in both models. Although not significant, women with a fasting glucose of mmol/l have a higher risk of developing nonfatal CVD than men, while men in that same category have a higher risk of developing fatal CVD. However, most of the elevated risk was explained by traditional CVD risk factors. HbA1c For both men and women, hazard ratios increased with increasing HbA1c levels in the age adjusted model (Table 4). In line with the findings for fasting glucose, men with higher HbA1c levels seem to have a higher risk of fatal CVD than women, while women seem to have a higher risk of developing non-fatal CVD. 143

12 Chapter 8 After adjustment for other CVD risk factors, the association between HbA1c and all-cause mortality and fatal CVD were no longer statistically significant in both men and women. In contrast, the association with non-fatal CVD remained significant in women, with a hazard ratio of 2.27 ( ) in women with a HbA1c level of 6.0 % or higher. In men, after adjustments the hazard ratio was 1.40 ( ), but no longer statistically significant. As important, the association between HbA1c as a continuous variable and nonfatal CVD remained significant in both men and women, with hazard ratios of 1.40 ( ) and 2.41 ( ) respectively for every % increase in HbA1c. Including systolic and diastolic blood pressure instead of hypertension as dichotomous variable to all multivariate models did not alter the results (data not shown). 144

13 HbA1c, glucose and incident cardiovascular disease Table 3. Postload plasma glucose (mmol/l) in relation to non-fatal CVD, fatal CVD, fatal and non-fatal CVD combined and all-cause mortality (hazard ratio s with 95% confidence interval). MEN Postload plasma glucose mmol/l (n) < 4.9 (327) (268) (131) (70) Continuous Non-fatal CVD (n=178) Model ( ) 1.24 ( ) 1.50 ( ) 1.06 ( ) Model ( ) 1.04 ( ) 1.13 ( ) 0.98 ( ) Fatal CVD (n=76) Model ( ) 0.93 ( ) 1.75 ( ) 1.08 ( ) Model ( ) 0.76 ( ) 0.79 ( ) 0.94 ( ) Fatal and non-fatal CVD (n=217) Model ( ) 1.22 ( ) 1.41 ( ) 1.06 ( ) Model ( ) 1.03 ( ) 0.99 ( ) 0.96 ( ) All-cause mortality (n=152) Model ( ) 1.28 ( ) 1.57 ( ) 1.09 ( )* Model ( ) 1.11 ( ) 1.04 ( ) 1.00 ( ) WOMEN Postload plasma glucose mmol/l (n) < 4.9 (299) (304) (172) (103) Continuous Non-fatal CVD (n=107) Model ( ) 1.41 ( ) 1.35 ( ) 1.05 ( ) Model ( ) 1.24 ( ) 0.99 ( ) 0.97 ( ) Fatal CVD (n=37) Model ( ) 1.11 ( ) 1.21 ( ) 0.94 ( ) Model ( ) 1.12 ( ) 1.07 ( ) 0.87 ( ) Fatal and non-fatal CVD (n=134) Model ( ) 1.40 ( ) 1.40 ( ) 1.05 ( ) Model ( ) 1.26 ( ) 1.08 ( ) 0.96 ( ) All-cause mortality (n=100) Model ( ) 1.12 ( ) 1.63 ( ) 1.05 ( ) Model ( ) 1.02 ( ) 1.53 ( ) 1.00 ( ) Model 1: adjusted for age Model 2: additionally adjusted for hypertension, smoking, LDL-cholesterol, HDL-cholesterol, triglycerides, waist-to-hip ratio and self-reported history of CVD. * P <

14 Chapter 8 Table 4. HbA1c in relation to non-fatal CVD, fatal CVD, fatal and non-fatal CVD combined and all-cause mortality (hazard ratio s with 95% confidence interval). MEN HbA1c % (n) HbA1c 5.1 (257) HbA1c (273) HbA1c (179) Upper 10% HbA1c 6.0 (87) Continuous Non-fatal CVD (n=178) Model ( ) 1.93 ( )* 2.10 ( )* 1.63 ( )* Model ( ) 1.35 ( ) 1.40 ( ) 1.40 ( )* Fatal CVD (n=76) Model ( ) 2.19 ( )* 2.30 ( )* 1.75 ( )* Model ( ) 1.09 ( ) 1.04 ( ) 1.21 ( ) Fatal and non-fatal CVD (n=217) Model ( )* 2.03 ( )* 2.22 ( )* 1.65 ( )* Model ( ) 1.33 ( ) 1.35 ( ) 1.37 ( )* All-cause mortality (n=152) Model ( ) 1.63 ( )* 1.71 ( )* 1.44 ( )* Model ( ) 1.17 ( ) 1.06 ( ) 1.19 ( ) WOMEN HbA1c % (n) HbA1c 5.1 (306) HbA1c (324) HbA1c (168) Upper 10% HbA1c 6.0 (80) Continuous Non-fatal CVD (n=107) Model ( ) 1.77 ( )* 3.66 ( )* 3.10 ( )* Model ( ) 1.29 ( ) 2.27 ( )* 2.41 ( )* Fatal CVD (n=37) Model ( ) 1.16 ( ) 1.26 ( ) 1.42 ( ) Model ( ) 0.94 ( ) 0.92 ( ) 1.14 ( ) Fatal and non-fatal CVD (n=134) Model ( ) 1.69 ( )* 3.66 ( )* 2.97 ( )* Model ( ) 1.20 ( ) 2.22 ( )* 2.27 ( )* All-cause mortality (n=100) Model ( ) 0.88 ( ) 1.65 ( ) 1.31 ( ) Model ( ) 0.82 ( ) 1.23 ( ) 1.19 ( ) Model 1: adjusted for age Model 2: additionally adjusted for hypertension, smoking, LDL-cholesterol, HDL-cholesterol, triglycerides, waist-to-hip ratio and self-reported history of CVD. * P <

15 HbA1c, glucose and incident cardiovascular disease Discussion To summarize, high HbA1c levels, but not high fasting or post load glucose levels, are a risk indicator of non-fatal CVD in older Caucasian individuals, stronger for women than men, and independent of other known CVD risk factors. Our results are among the first to report the association between HbA1c and non-fatal CVD. One other prospective research in 2913 Australian adults without diabetes showed that HbA1c levels 5.7% were associated with an odds ratio for new onset CVD and stroke of 1.9 ( ) after adjustment for other risk factors and that this association was stronger in women [21]. This is consistent with our findings. Moreover, our study included all 3 markers of hyperglycaemia, while earlier research only investigated the role of one [23] or two [9,24] of these measures in relation to CVD or all-cause mortality. Last, we were able to separate fatal and non-fatal CVD events, while other (prospective) research, including earlier analysis in the Hoorn Study data [11], only documented the relationship of HbA1c levels with fatal CVD only [9,11,15,16], fatal and non-fatal CVD combined [12,13] or all-cause mortality [11,15,25]. We found no significant relations between fasting and post load glucose levels and non-fatal CVD, while a significant relation between HbA1c and nonfatal CVD was detected. Although HbA1c was associated with components of the metabolic syndrome, adjusting for these factors did not explain the association. HbA1c may be related to mean daily glucose exposure, which is suggested by a recent report [26]. Mean daily glucose exposure has been found to be associated with non-fatal CVD [18]. It may therefore be suggested that the relation between HbA1c and non-fatal CVD found in this study, can be explained by the relation between mean glucose exposure and non-fatal CVD. Alternatively, glucose (fasting and post load) and HbA1c may reflect different processes. Modan et al. reported that only 2.4% of the variance 147

16 Chapter 8 of HbA1c in subjects without diabetes was explained by fasting glucose and therefore concluded that other factors may determine HbA1c [14]. The amount of glycosylation is known to vary interindividually, as suggested by Simon et al. in the Telecom Study [27]. Possible mechanisms causing these interindividual differences are genetic, as shown by twin studies [28,29], nutrition compounds in human diet [30], differences in intra-erythrocyte environments [31] and the role of racial differences [32]. In addition, recent research showed that variation in the survival of the red blood cell was large enough to cause differences in HbA1c levels for a given mean blood glucose [33] and that the glucose permeability of the red blood cell also influences HbA1c, unrelated to plasma glucose levels [34]. The Hoorn Study is a prospective study of subjects who were randomly selected from the population register of Hoorn; which limits the possibility of selection bias. In addition, possible confounders were measured at baseline, which made it possible to adjust for them in the analysis. Another strength of this study is that measurement of all three markers of glycaemia (fasting glucose, post load glucose and HbA1c) were available. Therefore, the independent contribution of all three of these markers in the association with CVD could be investigated and in addition, patients with diabetic glucose levels could be excluded from the analysis. Finally, the present study had the availability of separate data of fatal and non-fatal CVD, while in other studies only combined data of fatal and non-fatal cases were available. To investigate whether the existence of fatal cases in the Cox model with non-fatal CVD influenced the regression model (subjects without non-fatal CVD could have had fatal CVD), we temporarily censored the fatal CVD cases for this analysis. For the analysis with fatal CVD, we conducted the same procedure with the non-fatal CVD cases. Both adjustments did not influence the effects we detected. A limitation of the present study is that the Hoorn Study consists of only Caucasian individuals. A recent report by Herman et al. [32] showed that in 148

17 HbA1c, glucose and incident cardiovascular disease subjects with impaired glucose tolerance, the average HbA1c levels differ between different racial and ethnic groups, even after adjustments for factors likely to affect glycaemia [32]. If these same differences are present in subjects with a normal glucose metabolism, the interpretation of the present results for other ethnic groups should be performed with caution. Another limitation of the present study is the low event rate of fatal CVD. Other studies have documented a significant relation between glucose levels and/or HbA1c and fatal CVD [9,11-15]. Therefore, it could be suggested that the low event rate in our study prevented us from detecting an association. However, a recent study among almost 20,000 U.S adults also reported no association between HbA1c and all-cause mortality and fatal CVD in persons without diabetes [6]. Moreover, repeating our analysis for men and women together to increase the event rate did also not result in a significant association between any of the glycaemic parameters and fatal CVD (data not shown). Next, we did not have the availability of repeated measures of the main determinants and confounders of the entire study population. Therefore, we used the baseline data to predict future morbidity and mortality. Future studies may address the possible role of changes in glucose, HbA1c and other risk factors in relation to CVD. Last, only one sample of blood glucose and HbA1c was taken from each subject. It is known that especially fasting glucose and post load glucose levels have a rather high variability within individuals [35]. Therefore, it can be suggested that the better predictive properties of HbA1c levels in the present study may be due to the lower variability of the HbA1c measurement. However, earlier research showed better predictive values of post load glucose compared to HbA1c on CVD mortality [11,13], which refutes the consideration that a higher precision of the single HbA1c measurement can explain the present observation. In conclusion, in contrast to fasting and post load glucose, high Hba1c levels are related to non-fatal CVD in Caucasian individuals, independent of other CVD risk factors and especially in women. 149

18 Chapter 8 Conflict of Interest: Robert J. Heine is an employee of Eli Lilly & Company, which manufactures or is developing products that can be used in the treatment of diabetes. The other authors declared no potential conflict of interest. 150

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21 HbA1c, glucose and incident cardiovascular disease (15) Barr EL, Boyko EJ, Zimmet PZ, Wolfe R, Tonkin AM, Shaw JE. Continuous relationships between non-diabetic hyperglycaemia and both cardiovascular disease and all-cause mortality: the Australian Diabetes, Obesity, and Lifestyle (AusDiab) study. Diabetologia 2009; 52: (16) Park S, Barrett-Connor E, Wingard DL, Shan J, Edelstein S. GHb is a better predictor of cardiovascular disease than fasting or postchallenge plasma glucose in women without diabetes. The Rancho Bernardo Study. Diabetes Care 1996; 19: (17) Levitan EB, Song Y, Ford ES, Liu S. Is nondiabetic hyperglycemia a risk factor for cardiovascular disease? A meta-analysis of prospective studies. Arch Intern Med 2004; 164: (18) Alssema M, Schindhelm RK, Dekker JM, Diamant M, Kostense PJ, Teerlink T, Scheffer PG, Nijpels G, Heine RJ. Postprandial glucose and not triglyceride concentrations are associated with carotid intima media thickness in women with normal glucose metabolism: the Hoorn prandial study. Atherosclerosis 2008; 196: (19) Kramer CK, von MD, Gross JL, Laughlin GA, Barrett-Connor E. Blood pressure and fasting plasma glucose rather than metabolic syndrome predict coronary artery calcium progression: the Rancho Bernardo Study. Diabetes Care 2009; 32: (20) Nasir K, Santos RD, Tufail K, Rivera J, Carvalho JA, Meneghello R, Brady TD, Blumenthal RS. High-normal fasting blood glucose in non-diabetic range is associated with increased coronary artery calcium burden in asymptomatic men. Atherosclerosis 2007; 195: e155-e

22 Chapter 8 (21) Adams RJ, Appleton SL, Hill CL, Wilson DH, Taylor AW, Chittleborough CR, Gill TK, Ruffin RE. Independent Association of HbA(1c) and Incident Cardiovascular Disease in People Without Diabetes. Obesity (Silver Spring) 2009; 17: (22) Mooy JM, Grootenhuis PA, de Vries H, Valkenburg HA, Bouter LM, Kostense PJ, Heine RJ. Prevalence and determinants of glucose intolerance in a Dutch caucasian population. The Hoorn Study. Diabetes Care 1995; 18: (23) Khaw KT, Wareham N, Luben R, Bingham S, Oakes S, Welch A, Day N. Glycated haemoglobin, diabetes, and mortality in men in Norfolk cohort of european prospective investigation of cancer and nutrition (EPIC-Norfolk). BMJ 2001; 322: (24) Coutinho M, Gerstein HC, Wang Y, Yusuf S. The relationship between glucose and incident cardiovascular events. A metaregression analysis of published data from 20 studies of 95,783 individuals followed for 12.4 years. Diabetes Care 1999; 22: (25) Qiao Q, Dekker JM, de Vegt F, Nijpels G, Nissinen A, Stehouwer CD, Bouter LM, Heine RJ, Tuomilehto J. Two prospective studies found that elevated 2-hr glucose predicted male mortality independent of fasting glucose and HbA1c. J Clin Epidemiol 2004; 57: (26) Nathan DM, Kuenen J, Borg R, Zheng H, Schoenfeld D, Heine RJ. Translating the A1C Assay Into Estimated Average Glucose Values. Diabetes Care 2008; 31:

23 HbA1c, glucose and incident cardiovascular disease (27) Simon D, Senan C, Balkau B, Saint-Paul M, Thibult N, Eschwege E. Reproducibility of HbA1c in a healthy adult population: the Telecom Study. Diabetes Care 1999; 22: (28) Cohen RM, Snieder H, Lindsell CJ, Beyan H, Hawa MI, Blinko S, Edwards R, Spector TD, Leslie RD. Evidence for independent heritability of the glycation gap (glycosylation gap) fraction of HbA1c in nondiabetic twins. Diabetes Care 2006; 29: (29) Snieder H, Sawtell PA, Ross L, Walker J, Spector TD, Leslie RD. HbA(1c) levels are genetically determined even in type 1 diabetes: evidence from healthy and diabetic twins. Diabetes 2001; 50: (30) Vlassara H, Striker G. Glycotoxins in the diet promote diabetes and diabetic complications. Curr Diab Rep 2007; 7: (31) Gould BJ, Davie SJ, Yudkin JS. Investigation of the mechanism underlying the variability of glycated haemoglobin in non-diabetic subjects not related to glycaemia. Clin Chim Acta 1997; 260: (32) Herman WH, Ma Y, Uwaifo G, Haffner S, Kahn SE, Horton ES, Lachin JM, Montez MG, Brenneman T, Barrett-Connor E. Racial and Ethnic Differences in Hemoglobin A1c among Patients with Impaired Glucose Tolerance in the Diabetes Prevention Program. Diabetes Care 2007; 30: (33) Cohen RM, Franco RS, Khera PK, Smith EP, Lindsell CJ, Ciraolo PJ, Palascak MB, Joiner CH. Red cell lifespan heterogeneity in hematologically normal people is sufficient to alter HbA1c. Blood

24 Chapter 8 (34) Khera PK, Joiner CH, Carruthers A, Lindsell CJ, Smith EP, Franco RS, Holmes YR, Cohen RM. Evidence for interindividual heterogeneity in the glucose gradient across the human red blood cell membrane and its relationship to hemoglobin glycation. Diabetes 2008; 57: (35) Mooy JM, Grootenhuis PA, de Vries H, Kostense PJ, Popp-Snijders C, Bouter LM, Heine RJ. Intra-individual variation of glucose, specific insulin and proinsulin concentrations measured by two oral glucose tolerance tests in a general Caucasian population: the Hoorn Study. Diabetologia 1996; 39: