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Article |

Serum Lipids and Glucose Control:  The SEARCH for Diabetes in Youth Study FREE

Diana B. Petitti, MD, MPH; Giuseppina Imperatore, MD, PhD; Shana L. Palla, MS; Stephen R. Daniels, MD, PhD; Lawrence M. Dolan, MD; Ann K. Kershnar, MD; Santica Marcovina, PhD, ScD; David J. Pettitt, MD; Catherine Pihoker, MD ; for the SEARCH for Diabetes in Youth Study Group
[+] Author Affiliations

Author Affiliations: Kaiser Permanente Southern California, Pasadena (Drs Petitti, Kershnar, and Pettitt); Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Ga (Dr Imperatore); Department of Public Health Sciences, Wake Forest University Health Sciences, Winston-Salem, NC (Ms Palla); Children's Hospital Medical Center, Cincinnati, Ohio (Drs Daniels and Dolan); Northwest Research Laboratory, Seattle, Wash (Dr Marcovina); Children's Hospital and Regional Medical Center, Seattle (Dr Pihoker).


Arch Pediatr Adolesc Med. 2007;161(2):159-165. doi:10.1001/archpedi.161.2.159.
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Objective  To assess the relationship of serum lipid concentrations with glucose control in youth with diabetes mellitus.

Design  Cross-sectional analyses of data from the SEARCH for Diabetes in Youth study.

Setting  Multicenter study of youth with diabetes onset at younger than 20 years.

Patients/Participants  Nineteen hundred seventy-three SEARCH participants aged 10 years or older with hemoglobin A1c and fasting total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride measured at the SEARCH study examination.

Main Exposure  Hemoglobin A1c.

Outcome Measure  Lipid concentrations.

Results  There were significant trends of higher levels of TC, LDL-C, triglyceride, and non–HDL-C (but not HDL-C) with higher hemoglobin A1c concentrations for both diabetes types. The slopes of TC increase were 7.8 mg/dL (0.20 mmol/L) per unit increase in hemoglobin A1c for type 1 and 8.1 mg/dL (0.21 mmol/L) for type 2. Levels of TC, LDL-C, triglyceride, and non–HDL-C were all significantly higher (all P values <.001) in type 2 than in type 1 diabetes (mean differences in milligrams per deciliter [millimoles per liter], +13.6 [+0.35] for TC; +8.3 [+0.22] for LDL-C; +66.3 [+0.75] for triglyceride; +25.5 [+0.66] for non–HDL-C). Levels of HDL-C were lower in youth with type 2 diabetes (mean difference, −11.9 mg/dL [−0.31 mmol/L]). Among those with type 1 diabetes in poor glycemic control, 35%, 27%, and 12% had high concentrations of TC (≥200 mg/dL [5.17 mmol/L]), LDL-C (≥130 mg/dL [3.36 mmol/L]), and triglyceride (≥200 mg/dL [2.26 mmol/L]), respectively. In youth with type 2 diabetes in poor glycemic control, percentages with high levels of TC, LDL-C, and triglycerides were 65%, 43%, and 40%, respectively.

Conclusions  Glycemic control and lipid levels are independently associated in youth with both type 1 and type 2 diabetes.

Figures in this Article

In adults with diabetes, the risk of atherosclerotic cardiovascular disease morbidity and mortality is greatly increased. Diabetes mellitus also increases the risk of microangiopathy, which manifests itself as renal failure, retinopathy, and neuropathy. In nondiabetic youth, atherosclerosis is known to begin during childhood and adolescence.15 Many studies show that the microvascular changes and the precursors of atherosclerosis can be observed in young patients early in the course of type 1 diabetes.610

The Diabetes Control and Complications Trial (DCCT) reported in 1993 that aggressive glycemic control decreases the likelihood of microvascular complications in type 1 diabetes11 and later showed that glycemic control reduces the likelihood of subclinical and clinical macrovascular disease.12,13 In the DCCT, the benefits of stringent glycemic control extended to adolescents with type 1 diabetes.14 The benefits were long-lasting.1315 Glycemic control also reduces the likelihood of microvascular complications in adults with type 2 diabetes.16

Lipid concentrations are strongly related to the risk of macrovascular disease (coronary heart disease, stroke, and peripheral vascular disease) in adults with diabetes. Treatment with HMG-glutaryl CoA enzyme reductase inhibitors (statins), which lower low-density lipoprotein cholesterol (LDL-C) levels, prevents primary and secondary coronary events in adults with type 1 and type 2 diabetes.1719 Recent evidence suggests that lipid and lipoprotein concentrations are related to nephropathy, retinopathy, and neuropathy in type 1 diabetes.2023 In an animal model of diabetes, statin treatment prevented diabetic microangiopathy.24

Studies of the effects on cardiovascular disease outcomes of early intervention to reduce dyslipidemia in youth with either type 1 or type 2 diabetes have not been done. It also is not known whether pharmacologic intervention to manage lipid concentrations in adolescents and young adults with diabetes has a favorable benefit-to-risk ratio.25 These questions assume considerable importance in light of the high prevalence of lipid abnormalities in youth with type 1 and type 2 diabetes found by SEARCH investigators in a large, ethnically diverse population being managed under a variety of medical care models.26

SEARCH also noted a high prevalence of poor glycemic control among youth with diabetes. Data on the association between glycemic control and lipid concentrations in children and adolescents with diabetes, especially type 2 diabetes, are few. In the present analysis, SEARCH used cross-sectional data to assess the association of glycemic control with concentrations of total cholesterol (TC), LDL-C, high-density lipoprotein cholesterol (HDL-C), triglyceride, and non–HDL-C in youth aged 10 to 22 years with either type 1 or type 2 diabetes.

Data for this analysis derive from the cross-sectional component of the SEARCH for Diabetes in Youth Study. The study protocol was reviewed and approved by the local institutional review boards that had jurisdiction. All centers complied with the privacy requirements of the Health Insurance Portability and Accountability Act. Written informed consent for the study visit was obtained according to the local institutional review board requirements from patients aged 18 years or older or from a subject's parent or guardian if the subject was younger than 18 years. Written assent was also obtained from patients younger than 18 years as governed by local institutional review board instructions.

PARTICIPANTS

A detailed description of SEARCH study methods has been published elsewhere.27 In brief, SEARCH is a multicenter study that began conducting population-based ascertainment of cases of diabetes in patients younger than 20 years in 2001 at 6 centers in Ohio, Colorado, Washington, South Carolina, Hawaii, and southern California. SEARCH sought to identify all existing (prevalent) cases of nongestational diabetes in patients younger than 20 years in 2001 and all newly diagnosed (incident) cases of nongestational diabetes in the same age group in subsequent calendar years. Networks of reporting providers are the primary source of identification of incident diabetes cases. To identify 2001 prevalent cases, centers used databases and data sources that were sometimes common to all centers (eg, hospital discharge records) and sometimes unique to a specific center (eg, laboratory data on performance of hemoglobin A1c [HbA1c] tests) as well as reporting providers.

Youth with diabetes who completed the study survey, except those whose diabetes was secondary diabetes (defined as diabetes due to a chronic illness, congenital anomaly, or drug), were invited to a study visit. During the study visit, additional survey information was collected on medication use; blood was drawn for measurement of TC, LDL-C, HDL-C, triglyceride, and HbA1c; and an examination was done to measure height and weight.

Diabetes cases were considered valid if diagnosed by a health care provider. In this analysis, diabetes type is based on the clinical diagnosis made by a health care provider. This information was collected either from the health providers at the time of the diabetes case report to SEARCH or from medical records.

Eligible for this analysis were patients from the 2001 prevalent cases and 2002 incident cases who were aged 10 years or older at the time they participated in a SEARCH examination, who had their blood drawn while fasting, and whose fasting lipid measurement was completed by December 1, 2004. Cases classified clinically by a health care provider as type 1, type 1A, or type 1B were combined in a single type 1 category. Cases with another or an unknown clinical classification (13 unknown and 5 hybrid) were excluded. The 3 cases clinically classified as maturity onset diabetes of youth were analyzed with the type 2 cases because the clinical classification was not confirmed.

DATA COLLECTION

Blood samples were obtained under conditions of metabolic stability, defined as having had no episode of diabetic ketoacidosis during the previous month and having fasted for at least 8 hours. Specimens were processed locally at the sites and then shipped within 24 hours to the central laboratory (Northwest Lipid Metabolism and Diabetes Research Laboratories, University of Washington, Seattle) where they were analyzed. Measurements of TC, HDL-C, and triglyceride were performed enzymatically on a Hitachi 917 autoanalyzer (Boehringer Mannheim Diagnostics, Indianapolis, Ind). Low-density lipoprotein cholesterol was calculated by the Friedewald equation for individuals with triglyceride concentrations of less than 400 mg/dL (4.52 mmol/L)28 and by Lipid Research Clinics Beta Quantification29 for those with triglyceride concentrations of at least 400 mg/dL (4.52 mmol/L). Non–HDL-C was calculated as TC minus HDL-C. Hemoglobin A1c was measured by ion exchange, high-performance liquid chromatography (Bio-Rad Laboratories, Hercules, Calif).

Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared. The Centers for Disease Control and Prevention standards were used to estimate BMI percentile for age.30

In the analyses that categorized lipids concentrations, the cut points for elevated lipid concentration were adapted from those published by the National Cholesterol Education Program and the American Heart Association.3133 In some analyses, HbA1c was categorized in 4 groups. The lower cut point used to define the first group (<6.7%, near normal) was chosen to reflect near-normal glycemia. The upper cut point of the second group (<8.0%, good) was chosen to encompass the recommendation from the American Diabetes Association for age-specific HbA1c values in youth with type 1 diabetes (<8.0% at ages 6-12 years; <7.5% at ages 13-19 years; <7.0% at ages ≥20 years) for all ages of the SEARCH subjects included in this analysis.34 The lower cut point for the fourth group (<9.5%, poor) was chosen to reflect unacceptable glucose levels. Values of HbA1c between 8.0% and 9.5% (intermediate) comprised the third group.

ANALYSIS

All statistical analyses were conducted using SAS for Windows version 8.2 (SAS Institute Inc, Cary, NC). Descriptive characteristics of the SEARCH participants in the analysis were calculated separately for type 1 and type 2 diabetes. Means and standard deviations were calculated for continuous variables, and frequencies and percentages were calculated for categorical variables.

Analyses were performed first considering each of the lipid values and HbA1c measured on a continuous scale and then repeated where the lipids and HbA1c were considered as ordered categories. For the analyses using continuous measures, we used general linear models (linear regression) with the lipids measure treated as the outcome measure and the HbA1c measure considered as the predictor variable. Five separate models were fit, one for each lipid. Based on examining the assumptions of the linear model, the triglyceride concentration outcome was log transformed to adjust for its nonnormal distribution. Two sets of linear models were fit; the first included only HbA1c level as the predictor variable and the second included HbA1c level adjusted for age, sex, BMI percentile for age, diabetes duration, and race/ethnicity. In these linear models, diagnostics were performed to examine whether there was evidence of colinearity using the variance inflation factor and condition index statistics for linear regression models. Models were fit overall and then separately by clinically defined diabetes type. Based on these regression models, fitted lines and confidence intervals were plotted. Additional models included HbA1c levels as well as type and their interaction to determine whether the relationship between HbA1c levels for each lipid was significantly different by type. Estimates of the difference in lipid concentration between type 1 and type 2 diabetes and estimates of the slope of the change in lipid concentration with higher HbA1c level derive from these models.

Data were also analyzed with lipid values in the 4 categories of HbA1c described here: near-normal, good, intermediate, poor. In this analysis, statistical methods appropriate for categorical data were applied. Cochran-Armitage tests for trend were calculated to examine whether increasing values of HbA1c predict different lipid values. The Cochran-Mantel-Haenszel test was used to examine whether the HbA1c and lipid relationship remained significant after controlling for diabetes type. The Breslow-Day test was done to assess whether the HbA1c–lipid relationship was the same for type 1 and type 2 diabetes, that is, testing for interaction.

Methods that analyze continuous data in categories are generally less powerful statistically than methods based on linear models. The categorical analyses did not, however, lead to different conclusions about association, trend, or interaction for any lipid examined. The descriptive data from the categorical analysis are presented because the categories are clinically relevant and because the data permit conclusions about the prevalence of lipid concentration abnormalities in youth with diabetes at various HbA1c levels.

Of 7539 individuals with diabetes identified by SEARCH in 2001 and 2002 and invited for a study visit, 3215 (43%) had a study visit. Of these, 2469 were aged 10 years or older at the time of the SEARCH study examination; the 1973 youth who had data on fasting lipid concentration, diabetes type, and HbA1c are included in this analysis. Of the youth aged 10 years or older included in this analysis, 1680 were type 1 and 283 were type 2.

Table 1 lists demographic and clinical characteristics by diabetes type. Of youth with type 1 diabetes, 39% (95% confidence interval, 37% to 41%) had HbA1c concentrations less than 8% compared with 54% of youth with type 2 diabetes (95% confidence interval, 48% to 60%). Of youth with type 1 diabetes, 23% (95% confidence interval, 21% to 25%) had HbA1c concentrations of 9.5% or more compared with 31% (95% confidence interval, 26% to 37%) of those with type 2 diabetes. There were statistically significant differences in virtually all of these characteristics comparing type 1 and type 2 diabetes.

Table Graphic Jump LocationTable 1. Demographic Characteristics and Clinical Characteristics According to Clinically Diagnosed Diabetes Type

Table 2 lists the means for the lipid and HbA1c concentrations by diabetes type. The mean (SD) concentration of HbA1c was 8.6% (1.7%) in type 1 diabetes and 8.3% (2.7%) in type 2. Mean concentrations of TC, LDL-C, triglyceride, and non–HDL-C were significantly higher in type 2 diabetes, and HDL-C concentration was lower.

Table Graphic Jump LocationTable 2. Mean Hemoglobin A1c and Lipid Concentrations According to Clinically Diagnosed Diabetes Type

The Figure shows plots of the lipid value by HbA1c value using different symbols for youth with type 1 and type 2 diabetes along with lines fitted based on the regression of each lipid on HbA1c for type 1 and type 2 separately. For both type 1 and type 2 diabetes, there were statistically significant trends of higher TC, LDL-C, triglyceride, and non–HDL-C concentrations with higher HbA1c level (all P values <.001). Various terms were used as possible fits to the data; the linear term fit best. There was no significant trend for HDL-C with higher concentration of HbA1c (P = .64 for type 1; P = 48 for type 2).

Place holder to copy figure label and caption
Figure.

Plots of lipid value by hemoglobin A1c (HbA1c) concentration and fitted regression lines by diabetes type. A, Total cholesterol concentration by HbA1c concentration. B, Low-density lipoprotein (LDL) cholesterol concentration by HbA1c concentration. C, High-density lipoprotein (HDL) cholesterol concentration by HbA1c concentration. D, Triglyceride concentration by HbA1c concentration. E, Non-HDL cholesterol concentration by HbA1c concentration. Values come from the SEARCH for Diabetes in Youth Study with patients aged 10 years or older from cases in 2001 and 2002. Slope is the increase in lipid concentration in milligrams per deciliter for each 1.0 unit increase in HbA1c concentration.

Graphic Jump Location

The slope of the increase in lipid with higher values of HbA1c did not differ between type 1 and type 2 diabetes for any of the lipids (all P values >.05). The slope of the increase in TC was 7.8 mg/dL (0.20 mmol/L) per 1.0 unit increase in HbA1c in type 1 and 8.1 mg/dL (0.21 mmol/L) in type 2. For LDL-C, the slopes were 5.1 mg/dL (0.13 mmol/L) per unit increase in HbA1c for type 1 and 3.8 mg/dL (0.10 mmol/L) for type 2.

The estimated mean differences between type 1 and type 2 diabetes holding HbA1c constant were +13.6 mg/dL (+0.35 mmol/L) for TC; +8.3 mg/dL (+0.22 mmol/L) for LDL-C; +66.3 mg/dL (+0.75 mmol/L) for triglyceride; and +25.5 mg/dL (+0.66 mmol/L) for non–HDL-C (all P values <.001). Youth with type 2 diabetes had a lower concentration of HDL-C than those with type 1 diabetes (estimated mean difference, −11.9 mg/dL [−0.31 mmol/L], P<.001). After adjustment for age, sex, duration of diabetes, BMI percentile for age and sex, and race/ethnicity, the associations of higher HbA1c concentrations with higher TC, LDL-C, triglyceride, and non–HDL-C concentrations remained statistically significant for both type 1 and type 2 (Table 3). After adjustment, there was no association of higher HbA1c concentration with lower HDL-C concentration.

Table Graphic Jump LocationTable 3. Results of Multiple Linear Regression Analyses: Amount of Change in Lipid in Milligrams per Deciliter for Each 1.0 Unit Increase in Hemoglobin A1c Adjusting for Age, Sex, Race/Ethnicity, Diabetes Duration, and BMI Percentile for Age and Sex

Table 4 lists the proportions of youth in lipid categories by glycemic control category. Because lipid levels increase with increasing values of HbA1c, a very high percentage of youth are classified as having “high” TC, LDL-C, and triglyceride concentrations in the category “poor glycemic control” for both type 1 and type 2 diabetes. Among those with type 1 diabetes who were in poor glycemic control, 35%, 27%, and 12% had high concentrations of TC (≥200 mg/dL [5.17 mmol/L]), LDL-C (≥130 mg/dL [3.36 mmol/L]), and triglyceride (≥200 mg/dL [2.26 mmol/L]), respectively. In youth with type 2 diabetes who were in poor glycemic control, percentages with high TC, LDL-C, and triglyceride concentrations were 65%, 43%, and 40%, respectively.

Table Graphic Jump LocationTable 4. Percentage Distributions of Lipid Concentration in Categories by Hemoglobin A1c Category According to Clinically Diagnosed Diabetes Type*

In 1992, the DCCT reported a positive correlation between glycemic control and the concentrations of TC, LDL-C, and triglycerides at screening in 1569 patients with type 1 diabetes aged 13 to 40 years (mean age, 25.8 years for women and 27.2 years for men),35 but only 20% were younger than 18 years of age. All had type 1 diabetes, and the overwhelming majority were non-Hispanic and white. The data from the SEARCH study are important because they show that the association between poor glycemic control and higher concentrations of TC, LDL-C, and triglyceride extends to children and youth aged 10 to 22 years in all major ethnic/racial groups in the United States and characterizes both type 1 and type 2 diabetes in this age group.

In the multivariate analyses, the relationships of higher HbAlc with higher TC, triglyceride, LDL-C, and non–HDL-C concentrations were independent of BMI for age, as well as sex, duration of diabetes, and age at diagnosis, for both types of diabetes. In SEARCH, poorer glycemic control was not associated with HDL-C concentration in type 1 or type 2 diabetes. However, youth with type 2 diabetes had a lower mean concentration of HDL-C at all values of glycemic control. The DCCT analysis also reported no association of glycemic control with HDL-C in subjects with type 1 diabetes.35 In SEARCH, the lack of association of poorer glycemic control with HDL-C remained despite the inclusion of BMI percentile for age and other variables in a multivariate analysis for subjects with type 1 or with type 2 diabetes.

The cross-sectional design does not permit us to conclude that poor glycemic control caused high concentrations of TC, LDL-C, triglycerides, and non–HDL-C. It is possible that both glycemic control and lipid concentration are markers for the quality of diabetes care either at the individual level or the level of the health care system. For example, youth with limited access to health care may be those more likely to have poor glycemic control and, at the same time, may be less likely to be tested and treated for lipid abnormalities. However, other evidence suggests strongly that glycemic control affects the concentrations of TC, LDL-C, and triglycerides. Thus, data from the DCCT trial showed that intensive glucose control significantly decreased the concentrations of TC, LDL-C, and triglycerides in patients aged 13 to 40 years with type 1 diabetes.36 Similar results have been reported in studies in adults with type 2 diabetes.37

Because of the trend of higher concentrations of TC, LDL-C, and triglycerides with higher HbA1c values, a very high percentage of the SEARCH participants had HbA1c concentrations in the “poor” glycemic category. In addition, if the participants were adults, their TC, LDL-C, and triglyceride concentrations would have qualified them for pharmacologic intervention. The high prevalence of lipid abnormalities in diabetic youth with poor glycemic control underscores the importance of aggressive glucose control in children and youth with diabetes.

The American Diabetes Association has recommended pharmacologic therapy for youth with type 1 diabetes if the LDL-C level is greater than 160 mg/dL (4.14 mmol/L) and no other risk factors are present and consideration of pharmacologic therapy if the LDL-C level is between 130 and 159 mg/dL (3.36-4.11 mmol/L) based on presence of other cardiovascular risk factors.33 For adults with type 2 diabetes who are younger than 40 years, a group that encompasses some SEARCH youth, the American Diabetes Association recommends consideration of pharmacologic treatment based on risk factors if LDL-C is not optimal (LDL-C <100 mg/dL [2.59 mmol/L]).38 We have reported that very few (<1%) of the SEARCH participants were taking a lipid-lowering drug.37

Our study has important limitations. Less than half (43%) of youth with diabetes who were eligible participated in the SEARCH study visit. Nonresponse is unlikely to affect the association between glycemic control and lipid concentration. However, an unrepresentative sample would affect estimates of the prevalence of dyslipidemia and poor glycemic control if our results were generalized to all youth with diabetes. To attempt to estimate the magnitude and direction of possible bias in our prevalence estimates, we did an analysis of data on lipid and HbA1c testing and results at a SEARCH center that had access to computer-stored data on routine clinical testing, including both attendees and nonattendees at the SEARCH study examination. At this center, 1209 of 1390 youth with diabetes identified by SEARCH in 2001 or 2002 (87%) had a clinical HbA1c test in 2001 or 2002. Only 37% (n = 516) of the youth had TC and 13% (n = 185) LDL-C measured clinically in 2001 or 2002. Among those with a clinical HbA1c measurement, the mean (SD) level of HbA1c was significantly lower among participants in the study examination (8.9% [1.9]) than among nonparticipants (9.5% [2.4]; P<.05). Among those with a clinical TC or LDL-C measurement, there was no significant difference in mean concentration of TC or LDL-C between participants and nonparticipants in the study examination (both P values >.05). Analysis of nonresponse in the entire SEARCH study population showed a strong relationship between attendance at the study visit and age. Higher rates of nonresponse in older youth would lead to an underestimate of the problem both of poor glycemic control and of lipid abnormalities because both were related to older age in SEARCH.

Over the last decade, great progress has been made in our understanding of the link between glycemic control and better outcomes in type 1 and type 2 diabetes. The central role of dyslipidemia in causing progression of atherosclerosis in adults with diabetes has been elucidated. Randomized trials have shown that lipid-lowering therapy is important in the primary and secondary prevention of coronary events in adults with type 1 and type 2 diabetes. Knowledge about how best to manage cases of children and youth with diabetes has not kept pace with knowledge about diabetes management in adults. The quality of care for children and youth with diabetes has not been measured systematically. The SEARCH study results suggest that a substantial proportion of youth with diabetes are not managed optimally with regard to 2 key drivers of outcome in diabetes: glycemic control and lipids. Research on how to improve the care of children and youth with diabetes should be done in concert with further research to understand the mechanisms by which lipid concentrations are altered by diabetes.

Correspondence: Diana B. Petitti, MD, MPH, Department of Research and Evaluation, Kaiser Permanente Southern California, 393 E Walnut St, Pasadena, CA 91188 (diana.b.petitti@kp.org).

Accepted for Publication: September 7, 2006.

Author Contributions:Study concept and design: Petitti, Imperatore, Daniels, Dolan, Kershnar, Pettitt, and Pihoker. Acquisition of data: Petitti, Dolan, Kershnar, Marcovina, and Pihoker. Analysis and interpretation of data: Petitti, Imperatore, Palla, Daniels, Dolan, Kershnar, and Marcovina. Drafting of the manuscript: Petitti, Imperatore, Dolan, and Kershnar. Critical revision of the manuscript for important intellectual content: Petitti, Imperatore, Palla, Daniels, Dolan, Marcovina, Pettitt, and Pihoker. Statistical analysis: Palla. Obtained funding: Petitti, Dolan, and Pihoker. Administrative, technical, and material support: Petitti, Marcovina, and Pihoker. Study supervision: Imperatore and Dolan.

Financial Disclosure: None reported.

Funding/Support: SEARCH for Diabetes in Youth is funded by the Centers for Disease Control and Prevention (PA No. 00097 and DP-05-069) and supported by the National Institute of Diabetes and Digestive and Kidney Diseases. Center contract numbers for each state follow: California (U01 DP000246); Colorado (U01 DP000247); Hawaii (U01 DP000245); Ohio (U01 DP000248); South Carolina (U01 DP000254); Washington (U01 DP000244); and the coordinating center (U01 DP000250).

Disclaimer: The contents of this article are solely the responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention.

Acknowledgment: The SEARCH for Diabetes in Youth Study is indebted to the many youth and their families, and their health care providers, whose participation made this study possible. We acknowledge the involvement of General Clinical Research Centers at the following institutions in the SEARCH for Diabetes in Youth Study: Medical University of South Carolina (grant No. M01 RR01070); Cincinnati Children's Hospital (grant No. M01 RR08084); Children's Hospital and Regional Medical Center and the University of Washington School of Medicine (grant No. M01RR00037 and M01RR001271); and Colorado Pediatric General Clinical Research Center (grant No. M01 RR00069)

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Hadjadj  SDuly-Bouhanick  BBekherraz  A  et al.  Serum triglycerides are a predictive factor for the development and the progression of renal and retinal complications in patients with type 1 diabetes. Diabetes Metab 2004;3043- 51
PubMed Link to Article
Tesfaye  SChaturvedi  NEaton  SE  et al.  Vascular risk factors and diabetic neuropathy. N Engl J Med 2005;352341- 350
PubMed Link to Article
Casey  RGJoyce  MRoche-Nagle  GChen  GBouchier-Hayes  D Pravastatin modulates early diabetic nephropathy in an experimental model of diabetic renal disease. J Surg Res 2005;123176- 181
PubMed Link to Article
Libby  PNathan  DMAbraham  K  et al.  Report of the National Heart, Lung, and Blood Institute–National Institute of Diabetes and Digestive and Kidney Diseases Working Group on cardiovascular complications of type 1 diabetes mellitus. Circulation 2005;1113489- 3493
PubMed Link to Article
Kershnar  AKDaniels  SRImperatore  G  et al.  Lipid abnormalities are prevalent in youth with type 1 and type 2 diabetes: the SEARCH for Diabetes in Youth Study. J Pediatr 2006;149314- 319
Link to Article
SEARCH for Diabetes in Youth, A multicenter study of the prevalence, incidence and classification of diabetes mellitus in youth: The SEARCH Study Group. Control Clin Trials 2004;25458- 471
PubMed Link to Article
Friedewald  WTLevy  RIFredrickson  DS Estimation of the level of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972;18499- 502
PubMed
Hainline  A  JrMiller  DTMather  A The Coronary Drug Project: role and methods of the central laboratory. Control Clin Trials 1983;4377- 387
PubMed Link to Article
Kuczmarski  RJOgden  CLGrummer-Strawn  LM  et al.  CDC growth charts: United States. Adv Data 2000;3141- 27
PubMed
National Cholesterol Education Program (NCEP), Highlights of the report of the Expert Panel on Blood Cholesterol Levels in Children and Adolescents. Pediatrics 1992;89495- 501
PubMed
Kavey  REDaniels  SRLauer  RMAtkins  DLHayman  LLTaubert  K American Heart Association guidelines for primary prevention of atherosclerotic cardiovascular disease beginning in childhood. Circulation 2003;1071562- 1566
PubMed Link to Article
Williams  CLHayman  LLDaniels  SR  et al.  Cardiovascular health in childhood: a statement for health professionals from the Committee on Atherosclerosis, Hypertension, and Obesity in the Young (AHOY) of the Council on Cardiovascular Disease in the Young, American Heart Association. Circulation 2002;106143- 160
PubMed Link to Article
Silverstein  JKlingensmith  GCopeland  K  et al.  Care of children and adolescents with type 1 diabetes: a statement of the American Diabetes Association. Diabetes Care 2005;28186- 212
PubMed Link to Article
DCCT Research Group, Lipid and lipoprotein levels in patients with IDDM: Diabetes Control and Complications Trial Experience. Diabetes Care 1992;15886- 894
PubMed Link to Article
 Effect of intensive diabetes management on macrovascular events and risk factors in the Diabetes Control and Complications Trial. Am J Cardiol 1995;75894- 903
PubMed Link to Article
Emanuele  NAzad  NAbraira  C  et al.  Effect of intensive glycemic control on fibrinogen, lipids, and lipoproteins: Veterans Affairs Cooperative Study in Type II Diabetes Mellitus. Arch Intern Med 1998;1582485- 2490
PubMed Link to Article
American Diabetes Association, Standards of medical care in diabetes. Diabetes Care 2005;28(suppl 1)S4- S36
PubMed Link to Article

Figures

Place holder to copy figure label and caption
Figure.

Plots of lipid value by hemoglobin A1c (HbA1c) concentration and fitted regression lines by diabetes type. A, Total cholesterol concentration by HbA1c concentration. B, Low-density lipoprotein (LDL) cholesterol concentration by HbA1c concentration. C, High-density lipoprotein (HDL) cholesterol concentration by HbA1c concentration. D, Triglyceride concentration by HbA1c concentration. E, Non-HDL cholesterol concentration by HbA1c concentration. Values come from the SEARCH for Diabetes in Youth Study with patients aged 10 years or older from cases in 2001 and 2002. Slope is the increase in lipid concentration in milligrams per deciliter for each 1.0 unit increase in HbA1c concentration.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Demographic Characteristics and Clinical Characteristics According to Clinically Diagnosed Diabetes Type
Table Graphic Jump LocationTable 2. Mean Hemoglobin A1c and Lipid Concentrations According to Clinically Diagnosed Diabetes Type
Table Graphic Jump LocationTable 3. Results of Multiple Linear Regression Analyses: Amount of Change in Lipid in Milligrams per Deciliter for Each 1.0 Unit Increase in Hemoglobin A1c Adjusting for Age, Sex, Race/Ethnicity, Diabetes Duration, and BMI Percentile for Age and Sex
Table Graphic Jump LocationTable 4. Percentage Distributions of Lipid Concentration in Categories by Hemoglobin A1c Category According to Clinically Diagnosed Diabetes Type*

References

McGill  HC  JrMcMahon  CAZieske  AW  et al.  Associations of coronary heart disease risk factors with intermediate lesion of atherosclerosis in youth: the Pathobiologic Determinants of Atherosclerosis in Youth (PDAY) Research Group. Arterioscler Thromb Vasc Biol 2000;201998- 2004
PubMed Link to Article
Li  SChen  WSrinivasan  SR  et al.  Childhood cardiovascular risk factors and carotid vascular changes in adulthood: the Bogalusa Heart Study. JAMA 2003;2902271- 2276
PubMed Link to Article
Raitakari  OTJuonala  MKahonen  M  et al.  Cardiovascular risk factors in childhood and carotid artery intima-media thickness in adulthood: the Cardiovascular Risk in Young Finns Study. JAMA 2003;2902277- 2283
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Newman  WP  IIIFreedman  DSVoors  AW  et al.  Relation of serum lipoprotein levels and systolic blood pressure to early atherosclerosis: the Bogalusa Heart Study. N Engl J Med 1986;314138- 144
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Mahoney  LTBurns  TLStanford  W  et al.  Coronary risk factors measured in childhood and young adult life are associated with coronary artery calcification in young adults: the Muscatine Study. J Am Coll Cardiol 1996;27277- 284
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Jarvisalo  MJPutto-Laurila  AJartti  L  et al.  Carotid artery intima-media thickness in children with type 1 diabetes. Diabetes 2002;51493- 498
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Peppa-Patrikiou  MScordili  MAntoniou  AGiannaki  MDracopoulou  MDacou-Voutetakis  C Carotid atherosclerosis in adolescents and young adults with IDDM: relation to urinary endothelin, albumin, free cortisol, and other factors. Diabetes Care 1998;211004- 1007
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Krantz  JSMack  WJHodis  HNLiu  CRLiu  CHKaufman  FR Early onset of subclinical atherosclerosis in young persons with type 1 diabetes. J Pediatr 2004;145452- 457
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Starkman  HSCable  GHala  VHecht  HDonnelly  CM Delineation of prevalence and risk factors for early coronary artery disease by electron beam computed tomography in young adults with type 1 diabetes. Diabetes Care 2003;26433- 436
PubMed Link to Article
Svensson  MSundkvist  GArnqvist  HJ  et al.  Signs of nephropathy may occur early in young adults with diabetes despite modern diabetes management: results from the nationwide population-based Diabetes Incidence Study in Sweden (DISS). Diabetes Care 2003;262903- 2909
PubMed Link to Article
Diabetes Control and Complications Trial Research Group, The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med 1993;329977- 986
PubMed Link to Article
Nathan  DMLachin  JCleary  P  et al.  Intensive diabetes therapy and carotid intima-media thickness in type 1 diabetes mellitus. N Engl J Med 2003;3482294- 2303
PubMed Link to Article
Nathan  DMCleary  PABacklund  JY  et al.  Intensive diabetes treatment and cardiovascular disease in patients with type 1 diabetes. N Engl J Med 2005;3532643- 2653
PubMed Link to Article
White  NHCleary  PADahms  WGoldstein  DMalone  JTamborlane  WV Beneficial effects of intensive therapy of diabetes during adolescence: outcomes after the conclusion of the Diabetes Control and Complications Trial (DCCT). J Pediatr 2001;139804- 812
PubMed Link to Article
Writing Team for the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Research Group, Sustained effect of intensive treatment of type 1 diabetes mellitus on development and progression of diabetic nephropathy: the Epidemiology of Diabetes Interventions and Complications (EDIC) study. JAMA 2003;2902159- 2167
PubMed Link to Article
UK Prospective Diabetes Study (UKPDS) Group, Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). Lancet 1998;352837- 853
PubMed Link to Article
Haffner  SMAlexander  CMCook  TJ  et al. Scandinavian Simvastatin Survival Study Group, Reduced coronary events in simvastatin-treated patients with coronary heart disease and diabetes or impaired fasting glucose levels: subgroup analyses from the Scandinavian Simvastatin Survival Study. Arch Intern Med 1999;1592661- 2667
PubMed Link to Article
Goldberg  RBMellies  MJSacks  FM  et al. CARE Investigators, Cardiovascular events and their reduction with pravastatin in diabetic and glucose-intolerant myocardial infarction survivors with average cholesterol levels: subgroup analyses in the Cholesterol and Recurrent Events (CARE) trial. Circulation 1998;982513- 2519
PubMed Link to Article
Collins  RArtmitage  JParish  SSleigh  PPeto  R MRC/BHF Heart Protection Study of cholesterol-lowering with simvastatin in 5963 people with diabetes: a randomized placebo-controlled trial. Heart Protection Study Collaborative Group. Lancet 2003;3612005- 2016
PubMed Link to Article
Jenkins  AJLyons  TJZheng  D  et al.  Lipoproteins in the DCCT/EDIC cohort: associations with diabetic nephropathy. Kidney Int 2003;64817- 828
PubMed Link to Article
Lyons  TJJenkins  AJZheng  D  et al.  Diabetic retinopathy and serum lipoprotein subclasses in the DCCT/EDIC cohort. Invest Ophthalmol Vis Sci 2004;45910- 918
PubMed Link to Article
Hadjadj  SDuly-Bouhanick  BBekherraz  A  et al.  Serum triglycerides are a predictive factor for the development and the progression of renal and retinal complications in patients with type 1 diabetes. Diabetes Metab 2004;3043- 51
PubMed Link to Article
Tesfaye  SChaturvedi  NEaton  SE  et al.  Vascular risk factors and diabetic neuropathy. N Engl J Med 2005;352341- 350
PubMed Link to Article
Casey  RGJoyce  MRoche-Nagle  GChen  GBouchier-Hayes  D Pravastatin modulates early diabetic nephropathy in an experimental model of diabetic renal disease. J Surg Res 2005;123176- 181
PubMed Link to Article
Libby  PNathan  DMAbraham  K  et al.  Report of the National Heart, Lung, and Blood Institute–National Institute of Diabetes and Digestive and Kidney Diseases Working Group on cardiovascular complications of type 1 diabetes mellitus. Circulation 2005;1113489- 3493
PubMed Link to Article
Kershnar  AKDaniels  SRImperatore  G  et al.  Lipid abnormalities are prevalent in youth with type 1 and type 2 diabetes: the SEARCH for Diabetes in Youth Study. J Pediatr 2006;149314- 319
Link to Article
SEARCH for Diabetes in Youth, A multicenter study of the prevalence, incidence and classification of diabetes mellitus in youth: The SEARCH Study Group. Control Clin Trials 2004;25458- 471
PubMed Link to Article
Friedewald  WTLevy  RIFredrickson  DS Estimation of the level of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972;18499- 502
PubMed
Hainline  A  JrMiller  DTMather  A The Coronary Drug Project: role and methods of the central laboratory. Control Clin Trials 1983;4377- 387
PubMed Link to Article
Kuczmarski  RJOgden  CLGrummer-Strawn  LM  et al.  CDC growth charts: United States. Adv Data 2000;3141- 27
PubMed
National Cholesterol Education Program (NCEP), Highlights of the report of the Expert Panel on Blood Cholesterol Levels in Children and Adolescents. Pediatrics 1992;89495- 501
PubMed
Kavey  REDaniels  SRLauer  RMAtkins  DLHayman  LLTaubert  K American Heart Association guidelines for primary prevention of atherosclerotic cardiovascular disease beginning in childhood. Circulation 2003;1071562- 1566
PubMed Link to Article
Williams  CLHayman  LLDaniels  SR  et al.  Cardiovascular health in childhood: a statement for health professionals from the Committee on Atherosclerosis, Hypertension, and Obesity in the Young (AHOY) of the Council on Cardiovascular Disease in the Young, American Heart Association. Circulation 2002;106143- 160
PubMed Link to Article
Silverstein  JKlingensmith  GCopeland  K  et al.  Care of children and adolescents with type 1 diabetes: a statement of the American Diabetes Association. Diabetes Care 2005;28186- 212
PubMed Link to Article
DCCT Research Group, Lipid and lipoprotein levels in patients with IDDM: Diabetes Control and Complications Trial Experience. Diabetes Care 1992;15886- 894
PubMed Link to Article
 Effect of intensive diabetes management on macrovascular events and risk factors in the Diabetes Control and Complications Trial. Am J Cardiol 1995;75894- 903
PubMed Link to Article
Emanuele  NAzad  NAbraira  C  et al.  Effect of intensive glycemic control on fibrinogen, lipids, and lipoproteins: Veterans Affairs Cooperative Study in Type II Diabetes Mellitus. Arch Intern Med 1998;1582485- 2490
PubMed Link to Article
American Diabetes Association, Standards of medical care in diabetes. Diabetes Care 2005;28(suppl 1)S4- S36
PubMed Link to Article

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