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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
J Clin Hypertens (Greenwich). Author manuscript; available in PMC 2012 May 1.
Published in final edited form as:
PMCID: PMC3089739
NIHMSID: NIHMS246814

Impact of Type 1 Diabetes and Body Weight Status on Cardiovascular Risk Factors in Adolescent Children

Abstract

Type 1 diabetes (T1D) is a risk factor for cardiovascular disease. However, it is unclear if increased body weight amplifies that risk in T1D patients. This is a cross-sectional study, examining the presence of cardiovascular risk factors in normal and overweight children, both with and without T1D. Sixty-six children (age 16 ± 2.2) were included in one of the following groups: (T1D and normal weight, T1D and overweight, healthy and normal weight, and healthy and overweight). A fasting blood sample was analyzed for lipid profile (triglyceride, cholesterol, HDL-C, and LDL-C), apolipoprotein B (apoB) and apolipoprotein C-III (apoC-III) levels. Body composition was determined by dual energy X-ray absorptiometry and vascular elasticity by HDI/Pulsewave CR-2000. Statistical analyses examined the effect of T1D, body weight status, and their interactions on cardiovascular risk parameters. In this study we were unable to demonstrate an additive effect of body weight status and TID on cardiovascular risk profile. However, subgroup analysis of subjects with T1D revealed higher apoC-III levels in overweight subjects with T1D (p=0.0453) compared to normal weight diabetic children. Most notably, there was a direct relationship of small artery elasticity to body weight status. This seemingly paradoxical observation supports recent data and warrants further investigation.

Introduction

Type 1 diabetes (T1D) is a common disease of childhood and is increasing in prevalence worldwide 1. Cardiovascular disease occurs at a higher frequency and at a younger age in T1D compared to the general population 2, 3. Men and women with T1D have a cumulative mortality rate of 35% from coronary artery disease by the age of 55 years, compared to only 4-8% in non-diabetic people 4. Since T1D is a disease mostly occurring in childhood, afflicted patients face a lifelong cardiovascular burden. Identifying risk factors for cardiovascular disease in childhood allows for earlier intervention and possible amelioration of risk.

The Diabetes Control and Complications Trial (DCCT) examined the effect of an intensive insulin regimen compared to a conventional insulin regimen on subsequent microvascular and macrovascular complications associated with T1D. The trial demonstrated that tight control of diabetes with an intensive insulin regimen resulted in a decreased incidence of microvascular complications5. The use of intensive insulin resulted in better control of diabetes, but had some deleterious side effects, notably increased risk of hypoglycemia and increased weight gain. The prevalence of overweight, defined by body mass index (BMI) of > 27.8 kg/m2 in men and > 27.3 kg/m2 in women, is almost two fold higher in intensively treated patients compared to the patients on conventional regimen 6. However, it is still unclear if macrovascular complications that occur with weight gain 7 offset the benefits of intensive insulin therapy. The current study was done to examine the presence of cardiovascular risk factors (body composition, lipid profile, apolipoproteins B and C-III) in children with and without T1D, both normal weight and overweight, between the ages of 13 to 20 years. We hypothesized that children with T1D will have worse cardiovascular risk profile than children without TID, and that there will be a synergistic or additive effect of overweight status and TID on cardiovascular risk profile as defined by less favorable body composition, lipid profile, and decreased arterial compliance.

Methods

This was a cross-sectional study of children with and without TID between the ages of 13-20 years who were either of normal weight or were overweight. Subjects with TID were mainly recruited from our diabetes clinics and non-diabetic subjects were recruited through recruitment fliers and campus wide emails. A total of 77 children were enrolled, and 68 completed the study. Data from 2 participants were not included in the analysis: one subject was on oral contraceptive pills (inadvertently consented and screened, despite having an exclusion criterion per protocol, and the other because of markedly abnormal lipid data suggesting a possible genetic mutation in lipoprotein metabolism, also an exclusion criterion). Study subjects were defined as being overweight if their body mass index (BMI) was above the 85th percentile for age and gender and normal weight if their BMI was between the 3rd to 85th percentile for age and gender. The research protocol was approved by the Institutional Review Board at University of Oklahoma Health Sciences Center and all subjects signed an assent form prior to testing.

Inclusion criteria for children with T1D included a diagnosis of type 1 diabetes for more than 3 years and an average HbA1c between 6.5 to 10.7% for the past 6 months. To control for potentially independent effects of extreme hyperglycemia, a cut-off HbA1c level of 10.7% was selected, which represents one standard deviation above the mean HbA1c achieved in the adolescent population during the DCCT. To control for the well-described changes in the rates of diabetic complications after puberty, children who were prepubertal or early pubertal (Tanner 1 and 2) were excluded. Children were excluded from the study if they had any other coexisting endocrine, genetic or metabolic disease, if they were on any medications, including those that could affect substrate metabolism (excluding insulin), psychotropic medications, weight loss medications, and oral contraceptives for female subjects. Inclusion criteria for Tanner stage and ages were identical for non-T1D children. Children were excluded from the study if they had impaired fasting glucose or had diabetes based on fasting glucose values. Additional exclusion criteria were otherwise identical to those listed above for the group with T1D. Two children with coexisting hypothyroidism and 1 child with Addison’s disease, all well-controlled on physiological replacement hormonal therapy, were included in the study. Three diabetic participants treated for urinary microalbuminuria with angiotensin converting enzyme inhibitors (for an average of three years prior to entry into the study) were included.

After obtaining appropriate consent and assent, each child underwent a history and physical exam by a board certified pediatrician. Height and weight were used to calculate BMI, waist and hip circumference were obtained on each subject, and the presence and degree of acanthosis nigricans were noted if present. Then they underwent testing for body composition, vascular elasticity indices and a blood draw for lipid profile and apolipoprotein values. All testing was done in the morning after an overnight fast and was done by an experienced nurse assigned to the study at the General Clinical Research Center at the University of Oklahoma.

Body composition was measured using dual energy x-ray absorptiometry scan (DXA; Hologic QDR 4500, Waltham, MA). Pulse wave analysis determination was made by HDI/Pulsewave CR-2000, Hypertension Diagnostics, Eagan, MN8. This technique uses a modified Windkessel model to derive information on proximal and distal arteries by analyzing the diastolic part of the arterial wave form 9. Testing was done in fasting subjects when rested in the supine position. An average of three readings was calculated to derive the mean small artery elasticity index and large artery elasticity index. Age related norms for small artery and large artery compliance have recently been published 8.

Blood was analyzed for fasting lipids, apolipoprotein B, and apolipoprotein C-III levels. Total cholesterol, triglycerides and HDL-cholesterol were measured by standardized enzymatic procedure. VLDL-cholesterol and LDL-cholesterol were estimated by Freidewald formula and non HDL-cholesterol was calculated as total cholesterol-HDL-cholesterol.

Blood was frozen for later analysis of apolipoprotein levels. Apolipoprotein levels were measured by immunoturbidimetry as described previously10. Since heparin-manganese has a high affinity for apoB, apoC-III in the heparin manganese precipitate (HP) is apoC-III bound to apoB-containing lipoproteins, and apoC-III in the heparin-manganese supernate (HS) is apoC-III bound to apoA-containing lipoproteins. ApoC-III is measured in the total plasma sample and in the precipitate following reconstitution to the original volume to obtain apoC-III HP. The value for apoC-III HS was derived by subtracting apoC-III HP from total plasma apoC-III.

Statistical Methods

Demographic variables including age, weight, BMI, BMI centile, height, Tanner stage, and HbA1c were compared across groups using the Fisher’s Exact Test and the Kruskal-Wallis Test. Children without T1D who were overweight had a much higher BMI on the average compared to children with T1D who were overweight preventing us from doing a simple four group comparison. Thus the effect of body weight status, diabetes status and the interaction between the two on each cardiovascular variable was examined by regression analysis after controlling for age, gender and ethnicity. Least square means along with standard error for both are presented. If the interaction was not statistically significant then the final model included only the main effects (diabetes or body weight status) and control variables (age, gender and ethnicity). Additionally a subgroup analysis was conducted on just those children with T1D to examine the effect of body weight status after controlling for age, gender, and ethnicity on cardiovascular risk profile.

Secondary analyses were performed on other indices of body fat. Additional models were created as described above, with the substitution of trunk fat mass, fat free mass, total fat mass and percent fat separately in place of the main effect of overweight status. The effect of these indices of body fat was summarized in each regression model by the model coefficient pertaining to the body fat index, along with the standard error and 95% confidence interval around this coefficient. All analyses were performed using SAS (Version 9.1) software with a significance level of 0.05.

Results

Demographic information for all study subjects and groups are listed in Table 1. There were no differences in age or Tanner stages across the groups. As expected there was a significant difference in weight and BMI between overweight and normal weight groups (p<0.0001). There was no significant difference in HbA1c between the diabetic subjects (overweight and normal weight), and as expected, HbA1c values were higher in diabetic subjects compared to non-diabetic subjects (p<0.0001). There was a significant difference in ethnic distribution across all the four groups (p=0.0207). Since there were a higher proportion of Caucasian children in the T1D group compared to the other groups, the data were controlled for ethnicity. The effects of T1D, body weight status and their interaction were examined for all cardiovascular risk parameters.

Table 1
Demographics (mean ± standard deviation)

Effects of diabetes on the cardiovascular risk factors are presented in Table 2. These associations are adjusted by age, gender and ethnicity due to imbalances across groups and known clinical associations of these variables with the cardiovascular risk factors. HDL-C levels were consistently higher in TID subjects compared to non diabetic subjects (p=0.0023). None of the other lipid variables or any of the vascular measures showed a statistically significant association with diabetes status. A significant interaction was found (p < 0.05) between the effects of diabetes and body weight status for waist circumference, total fat mass, and trunk fat mass. The overweight non-diabetic subjects had higher values than the overweight diabetic subjects, whereas little differences were seen between the two normal weight groups. A significant interaction was also found (p < 0.05) for percent body fat, as the normal weight diabetic subjects had higher values than the normal weight non-diabetic subjects, whereas little difference was noted between the two overweight groups.

Table 2
Diabetes Effect on Cardiovascular Risk Factors from Multiple Regression models: Least Squares Means ± Standard Error, adjusted for age, gender and ethnicity

Effect of body weight status on the cardiovascular risk variables are presented in Table 3. As expected, waist-to-hip ratio was significantly higher in the overweight subjects than their normal weight counterparts (p=0.0001). Small arterial elastic index was higher in overweight subjects (p=0.0007). When substituting trunk fat mass, fat free mass, percent fat or total fat mass as indices of body fat for body weight status (Table 4), similar significance was found for each body fat measure with small artery elasticity index. Additionally, fat free mass was found to have a significant negative association with HDL-C levels and significant positive association with systolic blood pressure. Total fat mass and percent fat were the only body composition variable that had a significant and positive association with large artery elasticity index (p=0.0456 and p=0.0457, respectively).

Table 3
Weight Effect on Cardiovascular Risk Factors from Multiple Regression models: Least Squares Means ± Standard Error, adjusted for age, gender and ethnicity
Table 4
Effect of Body Composition Variables on Lipid Profile and Vascular Measures from Multiple Regression models: Model Coefficient ± Standard Error, adjusted for age, gender, ethnicity and diabetes status

A subgroup analysis was done to delineate the relationship between weight status and cardiovascular risk profile in children with TID (Table 5). Children with TID who were overweight had higher apoC-III levels (p=0.0453) compared to their normal weight counterparts. Also, the triglyceride and apoC-III HP levels were higher in the overweight group (p=0.0541 and p=0.0761 respectively), although this did not reach statistical significance. These findings could not be explained by diabetes duration (p=0.5877) or insulin dosage per kilogram of body weight (p=0.7400).

Table 5
Weight Effect on Cardiovascular Risk Factors from Multiple Regression models in T1D subjects: Least Squares Means ± Standard Error, adjusted for age, gender and ethnicity

Discussion

The results of this study did not support our hypothesis that cardiovascular risk factors (unfavorable body composition, lipid values and decreased arterial compliance) would be greater in T1D children, and still greater in overweight children with TID.

In our study diabetes status was not associated with higher cardiovascular risk profile. Children with T1D had consistently and paradoxically higher HDL-C levels than non-T1D subjects irrespective of their overweight status, although this is not a novel finding. Maahs et al have reported earlier the lower prevalence of decreased HDL-C levels in T1D children compared to the NHANES cohort, irrespective of their glycemic status 11. The SEARCH for Diabetes in Youth Case-Control Study has shown 12 higher LDL-C and total cholesterol levels in subjects with type 1 diabetes who were poorly controlled. It is possible that we did not see higher LDL-C levels in the children with T1D in our study because only relatively well-controlled diabetic children were included, and thus the poorly controlled patients with worse dyslipidemia were not represented.

As expected, overweight status conferred a worse body composition profile, with children who were overweight having higher waist-to-hip ratio and more fat free mass compared to non-obese children. However, in this study, overweight status was not associated with a worse lipid profile or higher blood pressure. The interaction of overweight status and T1D was significant for several body composition variables. Overweight children without T1D had higher waist circumference, total fat mass and trunk fat mass compared to overweight children with T1D and this likely can be best explained from our sample of convenience: the overweight children without T1D in our sample were somewhat more overweight than our sample of overweight children with T1D. Interestingly, normal weight TID subjects had higher percent body fat compared to normal weight non-diabetic subjects, whereas little difference was noticed between the two overweight groups.

A subgroup analysis of the children with T1D showed that overweight children with TID had significantly higher apoC-III levels compared to their normal weight counterparts. Also these children had higher triglycerides and apoC-III HP levels that trended towards significance. Various apolipoprotein abnormalities have been described in patients with T1D including elevated apoB and apolipoprotein C-III levels 13,14, and these have been postulated to be related to the increased cardiovascular risk seen even in diabetic patients having a relatively normal lipid profile. ApoC-III has been associated with the metabolic syndrome in adults 15,16 and adolescents 16, and with insulin resistance in young children and adolescents 17. Furthermore, it has been shown to be a predictor of coronary events, progression of cardiovascular disease and cardiovascular mortality 18, 19. ApoB levels also were strongly linked to cardiovascular risk in patients with T1D in a 15 year follow up study in Switzerland 20. It is unclear why we did not observe a relationship between T1D and apoB levels in our study, although it is possible that the negative consequences of diabetes on apoB may be confined to older patients.

We did not observe a statistically significant adverse effect of diabetes on arterial compliance nor an interaction between diabetes and overweight status. Other studies by Haller et al21 and Jarvisalo et al22 have demonstrated increased arterial stiffness and endothelial dysfunction respectively in children with T1D, although the apparently discordant findings between our findings and those reports may be related to differences in methods used. Haller et al. had demonstrated arterial stiffness using radial tonometry in 98 diabetes subjects compared to controls. In our study we used applanation tonometry using the HDI pulsewave analyzer to characterize arterial stiffness. Jarvisalo used flow mediated dilatation to detect endothelial dysfunction and ultrasound to measure carotid intimal thickness in children with T1D. He found endothelial dysfunction (75 diabetic children) and increased carotid artery intimal thickness compared to healthy controls. In our report, the trend for T1D subjects to have lower small and large arterial compliance compared to the non-diabetic subjects (although not statistically significant) is concerning and supports existing literature about the negative influence of T1D on vascular health.

Small artery elasticity index was higher in overweight subjects. Although surprising, these data are consistent with a reported slower pulse wave velocity measured in obese compared to control children 23. This seemingly paradoxical observation was supported further by the subgroup analysis of subjects with T1D, in that the overweight diabetic patients also tended to have higher small arterial elasticity index compared to their normal weight counterparts (p=0.0645). One might speculate whether this increased compliance might reflect a state of tonic vascular dilatation, either secondary to relative hyperinsulinemia, or simply an initial compensating mechanism for the cardiovascular burden placed by excessive weight gain. This could possibly even reflect a higher insulin sensitivity in these overweight children. We observed no effect of overweight status on large arterial elasticity index.

Limitation of Study

Despite the fact that this is a relatively small study with all the well-described limitations of a cross sectional study, several observations are key, including the lack of obvious potentiation of overweight status on risk factors in children with T1D and the seemingly improved arterial compliance in both overweight diabetic and non-diabetic children. Our study was limited by the fact that only well controlled children with T1D were included in the study; thus the observations may not apply to all children with T1D. However, the effect of poorly controlled TID on cardiovascular risk factors is already well documented. Additional longitudinal studies are needed to further delineate the interaction between overweight status and T1D, including the effect of glycemic control on these measures.

Conclusion

These data do not support the notion that well-controlled children with T1D have worse cardiovascular risk factors compared to non-diabetic children. We could not demonstrate an additive effect of TID and overweight status on cardiovascular risk profile. However, when children with T1D were considered separately, overweight diabetic children had higher apoC-III levels and tended to have higher triglyceride and apoC-III HP levels compared to their normal weight counterparts. The direct relationship of small artery elasticity to BMI in both diabetic and non-diabetic children is paradoxical, but consistent with recently published and newly-emerging vascular data, and warrants further investigation.

Acknowledgment

We would like to gratefully acknowledge the helpful contributions of Amy Wisniewski PhD, Steven D. Chernausek M.D, and Peter Alaupovic PhD to this project .

This work supported in part by, grant M01 RR14467 from the National Center for Research Resources, National Institutes of Health and by Novo-Nordisk (C7042301). AWG is supported by grants from the National Institute on Aging (R01-AG-24296), National Center on Minority Health and Health Disparities (P20-MD-000528), National Center for Research Resources (M01-RR-14467 and P20-RR-024215), and Oklahoma Center for the Advancement of Science and Technology (HR09-035). KCC is supported by research funding from the National Institutes of Health (U01-DK061230-09).

Footnotes

Statement of Financial Disclosure

The authors have no competing interests to declare. Sowmya Krishnan and David A. Fields have research support through an investigator-initiated grant from Novo-Nordisk (C7042301).

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