Giuseppina Imperatore

Improvements in diabetes processes of care and intermediate outcomes: United States, 1988-2002.

Context As the target of many quality improvement programs, positive change in diabetes care is a good marker for progress toward better health care. Content The authors analyzed measures of diabetes care from national population-based surveys that were conducted between 1988 and 2002. Improvements occurred in the proportion of patients with hemoglobin A1c between 6% and 8%, low-density lipoprotein (LDL) cholesterol levels less than 3.4 mmol/L (<130 mg/dL), annual influenza vaccination, and aspirin use. Blood pressure did not change. Substantial proportions of patients still had poor control of LDL cholesterol levels, glycemia, and blood pressure. Implications Despite some progress, population-based measurements show that care for many Americans with diabetes falls far short of targets. The Editors Diabetes currently affects 20.8 million people in the United States (1), and that number is projected to reach 39 million by the year 2050 (2). If current trends continue, 1 in 3 Americans will develop diabetes sometime in his or her lifetime, and those with diabetes will lose, on average, 10 to 15 life-years (3). In 2002, diabetes cost the nation an estimated

The Evolving Diabetes Burden in the United States

132 billion in direct and indirect costs (4). There is, however, a growing array of effective and cost-effective treatments to help prevent or delay diabetes complications and also diabetes itself (5-17). Diabetes care has been suboptimal and varied in the United States (18-21). The National Diabetes Quality Improvement Project, founded in 1997, developed a comprehensive set of measures of diabetes quality of care (22). These measures have been incorporated into the Health Plan Employer Data and Information Set, the American Diabetes Association Provider Recognition Program, the American Medical Association Diabetes Measures Group, the Veterans Administration performance monitoring program, and other activities. The Diabetes Quality Improvement Project partners now continue their work as a coalition of 13 influential private and public national organizations called the National Diabetes Quality Improvement Alliance. The Alliance develops, maintains, and promotes the use of an updated standardized measurement set (the Alliance measures) for quality of diabetes care (23). We previously established a national benchmark for diabetes quality of care in the United States for the years 1988 to 1995 by using the standard measurements recommended by the Diabetes Quality Improvement Project (18). On the basis of nationally representative data collected in 1999 to 2002, we report the changes in the quality of diabetes care from the 1990s to 2000s by using the standardized Alliance measures for both time periods. Methods Surveys We used data from 2 federally funded, nationally representative surveys: the National Health and Nutrition Examination Survey, 19881994 (NHANES III) and 19992002 (NHANES 19992002), and the Behavioral Risk Factor Surveillance System, 1995 (BRFSS 1995) and 2002 (BRFSS 2002). As previously explained (18), we used both BRFSS and NHANES to obtain data on all the process and intermediate outcome measures needed for the analysis. In our report, we refer to NHANES III and BRFSS 1995 as baseline surveys and NHANES 19992002 and BRFSS 2002 as recent surveys. We analyzed data from each survey separately. Table 1 presents the indicators used and their respective data source. Table 1. National Diabetes Quality Improvement Alliance and Additional Indicators of Diabetes Processes and Outcomes of Care National Health and Nutrition Examination Survey The NHANES consists of nationally representative samples of the U.S. civilian, noninstitutionalized population. Samples were obtained by using a stratified multistage probability design with planned oversampling of older and minority groups. Household interviews were conducted to ascertain sociodemographic characteristics and medical and family history. After the household interview, clinical examinations were conducted at a mobile examination center. Detailed descriptions of the design and data collection of each survey have been published elsewhere (24-27). Data from NHANES were self-reported (demographic characteristics and clinical variables) or were obtained during the clinical examination (hemoglobin A1c, cholesterol level, triglycerides level, and blood pressure level). Hemoglobin A1c measurements were standardized to the Diabetes Control and Complications Trial. Cholesterol levels were standardized by using the criteria established by the Centers for Disease Control and Prevention and the National Heart, Lung, and Blood Institute Lipid Standardization Program II. For persons who fasted for more than 8 hours and had triglyceride levels less than 4.5 mmol/L (<400 mg/dL), the Friedewald equation was applied to calculate low-density lipoprotein (LDL) cholesterol level. We log-transformed triglyceride levels because data were not normally distributed. We used the average of each persons blood pressure readings that were taken in the seated position during the clinical examination. Because we did not have data on annual testing for microalbuminuria, we assessed the absence of microalbuminuria, defined as albumin-to-creatinine ratio greater than 30 g/mg in spot urine collection (28). We analyzed the data for all indicators regardless of respective treatment status. Behavioral Risk Factor Surveillance System The BRFSS is an ongoing random-digit telephone survey of the noninstitutionalized U.S. adult population in each of the 50 states and the District of Columbia. Detailed descriptions of the design and data collection of the BRFSS have been published elsewhere (29). We used the diabetes-specific module that contains questions on clinical and preventive care practices to collect information from the participants with diabetes. Participants We included adults 18 to 75 years of age who reported a previous diagnosis of diabetes by a health care professional. We excluded women with gestational diabetes. We analyzed data from 1024 participants in NHANES III and 750 participants in NHANES 19992002 who selfreported a diagnosis of diabetes and who completed the clinical examination. We analyzed data from 3065 persons in BRFSS 1995 and 13078 persons in BRFSS 2002 who identified themselves as having diabetes. Participants reporting diabetes in all surveys were similar in age, sex, education, smoking, and insurance status at each point of time. Among participants of the recent surveys compared with those of the baseline surveys, the proportion of women and non-Hispanic white persons was lower and the proportion of participants with more than a high school education and an annual household income of

Achievement of Goals in U.S. Diabetes Care, 1999–2010

20000 or more was higher (Table 2). The proportion of people with diabetes who use insulin was also lower in the recent surveys but was statistically significant only in BRFSS 2002. Table 2. Characteristics of Participants 18 to 75 Years of Age with Self-Reported Diabetes in the National Health and Nutrition Examination Survey, 19881994 and 19992002, and Behavioral Risk Factors Surveillance System, 1995 and 2002 Performance Measurement Set We assessed the quality of diabetes care by using the Alliance measurement set (22) (Table 1). We used the Alliance measures of diabetes care wherever data were available, and we also examined additional measures that may be indicators of quality care in the future: pneumococcal vaccination, diabetes education, annual dental examination, and self-monitoring of blood glucose level. The BRFSS did not have a question about smoking counseling. We, therefore, used the proportion of smokers who tried to quit smoking. Questions about aspirin use were asked only every other year, so we used data from BRFSS 1996 for this variable. Statistical Analysis We conducted statistical analyses by using SAS for Windows software, version 7.0 (SAS Institute, Inc., Cary, North Carolina), for data management. We used SUDAAN software (Research Triangle Institute, Research Triangle Park, North Carolina) to obtain point estimates and SEs based on sampling weights to produce national estimates accounting for the complex survey design. We used Taylor series linearization for variance estimation. We computed the percentage of respondents who reported receipt of each measure. We examined the diabetes care measures by age, sex, race or ethnicity, education, insulin use, and health insurance status because our previous analysis had variations by these factors (18). However, insulin users were not asked to fast; hence, we did not examine LDL levels by insulin use. We used multiple logistic regression and predictive margins to estimate the probability of receiving or meeting the care measure after controlling for all known potential confounders. Predictive margins are a type of direct standardization, where the predicted values from the logistic regression models are averaged over the covariate distribution in the population (30). This statistic has several advantages over the odds ratio: It is not influenced if the outcome is not rare; a comparison group is not required; and it provides a measure of absolute difference rather than relative difference. We included an interaction term between time and each measure in the models to allow estimation of the probability for each period. To assess the difference in the percentage change between the 2 comparison groups, we tested the interaction term of each demographic characteristic and clinical variable (age, sex, race or ethnicity, education, insulin use, and health insurance status) with time. Role of the Funding Source No funding was received for this study. Results Half of the quality care measures that we analyzed improved between the baseline and recent surveys, and the only measure that worsened was the proportion of participants with hemoglobin A1c < 6%. We observed absolute increases for LDL levels less than 3.4 mmol/L (<130 mg/dL) (22 percentage points), annual lipid profil

The SEARCH for Diabetes in Youth study: rationale, findings, and future directions.

Diabetes was first described in ancient times with the cardinal symptoms of polyuria, polydipsia, and polyphagia (1). The use of uniform diagnostic criteria provided a means to reliably track the disease and unveiled a worldwide epidemic that emerged during the second half of the 20th century and is now extending into the 21st century (2-4). This report examines the evolution of the diabetes epidemic in the United States and the burden imposed by its complications. Classification of Diabetes Mellitus There are 3 major types of diabetes (5). Type 1 diabetes usually involves children and was previously called insulin-dependent diabetes mellitus or juvenile-onset diabetes. It develops when the bodys immune system destroys pancreatic cells, which make insulin. Type 1 diabetes accounts for 5% to 10% of all diagnosed cases of diabetes in the United States. Type 2 diabetes, previously called noninsulin-dependent diabetes mellitus or adult-onset diabetes, usually begins as insulin resistance, in which target tissues do not use insulin properly. It accounts for approximately 90% to 95% of all diagnosed cases of diabetes. Gestational diabetes is glucose intolerance diagnosed during pregnancy with return to a normal metabolic state after delivery. Other, lesser types of diabetes result from specific genetic conditions (such as maturity-onset diabetes of youth), surgery, drugs, malnutrition, infections, and other illnesses; these account for 1% to 5% of all diagnosed cases of diabetes (5). Diagnosis of Diabetes Uniform diagnostic criteria for diabetes were first recommended by the American Diabetes Association and the World Health Organization in 1979 and 1980 and were updated in the late 1990s (5, 6). Currently, when typical symptoms of diabetes are present (for example, polyuria, polydipsia, or unexplained weight loss), a casual (that is, at any time without regard to the last meal) plasma glucose level of 11.1 mmol/L (200 mg/dL) or greater confirms the diagnosis. In addition, the diagnosis can be made with a fasting plasma glucose level of 7.0 mmol/L (126 mg/dL) or greater or an oral glucose tolerance test with a 2-hour value of 11.0 mmol/L (200 mg/dL) or greater. A positive diagnostic test result should be followed by a repeated test on a different day to confirm the clinical diagnosis. In contrast, for epidemiologic studies, a single fasting plasma glucose or 2-hour oral glucose tolerance test measurement is used to estimate the prevalence of diabetes in a population. Tracking the Diabetes Epidemic Currently, 3 periodic national surveys track diabetes prevalence in the United States. The National Health Interview Survey and National Health and Nutrition Examination Survey (NHANES) use national population-based samples and query persons in face-to-face interviews about whether they have been told by their health care provider that they have diabetes. A third survey, the Behavioral Risk Factors Surveillance System, asks a similar question of state-based population samples during telephone interviews of residents. Unlike the other 2 surveys, NHANES includes a laboratory-based examination that measures glucose levels and identifies persons with undiagnosed diabetes. All 3 surveys provide national estimates of the prevalence of diagnosed diabetes. Only the Behavioral Risk Factors Surveillance System provides state-based estimates, and only NHANES provides estimates of undiagnosed diabetes. Prevalence In 2002, an estimated 6.3% of the U.S. population (about 18.2 million persons) had diabetes (7). Diabetes affects various sociodemographic groups unequally. According to data from the National Health Interview Survey, persons 65 years of age or older make up almost 40% of all persons with diagnosed diabetes, and the prevalence in this age group is more than 10 times that in persons younger than 45 years of age (8). Minority race and ethnic groups, including black persons, Hispanic persons, and Native Americans, are disproportionately affected; the prevalence of diagnosed diabetes is generally 2 to 4 times higher in these groups than in the majority population (Figure 1) (7, 8). Figure 1. Prevalence of diagnosed diabetes in people 20 years of age and older by age and race or ethnicity, United States, 2002. The longest running of the surveys, the National Health Interview Survey, found a 4- to 8-fold increase over the last half-century in the number of persons who received a diagnosis of diabetes (1.6 million in 1958 and 12.1 million in 2000) and the prevalence of diagnosed diabetes in the United States (0.9% in 1958 and 4.4% in 2000) (Figure 2) (8, 9). Increases occurred across all demographic categories, including sex, race or ethnicity, and age (8). Between 1990 and 2001, data from the Behavioral Risk Factors Surveillance System indicate that the largest relative increases in diagnosed diabetes occurred in persons 30 to 39 and 40 to 49 years of age (95% and 83%, respectively); increases in other age groups were 40% in persons 18 to 29 years of age, 49% in persons 50 to 59 years of age, 42% in persons 60 to 69 years of age, and 33% in persons 70 years of age or older (10, 11). Although the magnitude of the increase varied, the prevalence of diagnosed diabetes among adults increased in every state in the United States (Figure 3). Trends are also disturbing in children and adolescents, in whom type 2 diabetes is increasingly being recognized, but as yet less commonly than type 1 diabetes (12). Studies of estimates of the incidence of type 1 diabetes in the United States, which are limited by sparse data, do not find a consistent patternsome show an increase, some show a decrease, and some remain unchanged (13). Figure 2. Prevalence of diagnosed diabetes and the number of people with diagnosed diabetes in the United States, 1958 to 2000. Figure 3. Prevalence of diagnosed diabetes (including gestational diabetes) by state in the United States, 1990 to 2001. The NHANES found that diabetes is undiagnosed in approximately one third of all persons with diabetes and that this fraction has changed little over time (14). Many factors may have affected these uptrends in the prevalence of diabetes, including changes in diagnostic criteria, improved or enhanced detection, decreasing mortality, changes in demographic characteristics of the population (for example, aging), and growth in minority populations in whom the prevalence and incidence of diabetes are increasing. Diabetes Complications Morbidity Cardiovascular Disease Data on cardiovascular disease among the diabetic population are scant. However, in 2000, 37.2% of diabetic persons age 35 years and older reported receiving a diagnosis of a cardiovascular disease (8). Prevalence of ischemic heart disease among persons with diabetes was about 14 times the rate among those without diabetes in persons 18 to 44 years of age (2.7% vs. 0.2 %), 3 times as high in persons 45 to 64 years of age (14.3% vs. 4.7%), and almost twice as high in those 65 years of age or older (20% vs. 12%) (15). Other studies have shown that the absolute rates of cardiovascular disease in persons with diabetes are higher in men than in women (as in the general population), but the relative risk (comparing those with and without diabetes) is higher in women than in men (relative risk, 2 to 4 for women and 1.5 to 2.5 for men) (16, 17). Eye, Kidney, and Lower-Extremity Disease Visual impairment and blindness are major disabling complications of diabetes. Diabetic retinopathy, the leading cause of blindness (visual acuity 20/200) in persons age 20 to 64 years, accounts for 12% of all new cases of blindness and leads to 12 000 to 24 000 new cases each year in the United States (18). Considerable visual impairment (best corrected [for example, with glasses] visual acuity in either eye < 20/40) among persons with diabetes is much more common than blindness and is associated with reduced functional status. A national population-based survey based on self-reports found that 25% of all persons with diabetes had considerable visual impairment, approximately double the proportion among persons without diabetes (19). Impairment among persons with diabetes can have several causes. Some are specific to diabetes, such as macular edema and diabetic retinopathy, and others are not specific to diabetes but occur more commonly in diabetic than in nondiabetic persons. Examples of conditions not specific to diabetes are cataracts (32% vs. 20% in persons 65 to 74 years of age) and glaucoma (6.0% vs. 2.3% in persons 65 to 74 years of age) (20-23). In the United States in 2000, diabetic nephropathy accounted for more than 40% of new cases of end-stage renal disease (that is, kidney failure that requires dialysis or transplantation) (8). Persons with diabetes are the fastest-growing group of recipients of dialysis and transplantation (8). Several factors may account for the increase in incidence, including greater recognition of the etiologic role of diabetes, more use of treatments for end-stage renal disease, a true increase in the incidence of diabetes-related end-stage renal disease, or a combination of these factors. Lower-extremity disease, which includes peripheral neuropathy and peripheral arterial disease or both, results in elevated rates of lower-extremity amputations among persons with diabetes. An estimated 15% of persons with diabetes will have a diabetic foot ulcer during their lifetime (24); of these, 6% to 43% will ultimately undergo a lower-extremity amputation (25). Among persons with diabetes who have had an amputation, as many as 85% may have had a preceding foot ulcer (25). Currently, more than half of all nontraumatic lower-extremity amputations in the United States occur among people with diagnosed diabetes (8). An analysis of the 1999 to 2000 NHANES found that an estimated 8.1% of the diabetic population age 40 years or older have peripheral arterial disease (defined as an ankle to brachial artery blood pressure ra

Glycemic control in youth with diabetes: the SEARCH for diabetes in Youth Study.

BACKGROUND Tracking national progress in diabetes care may aid in the evaluation of past efforts and identify residual gaps in care. METHODS We analyzed data for adults with self-reported diabetes from the National Health and Nutrition Examination Survey and the Behavioral Risk Factor Surveillance System to examine risk-factor control, preventive practices, and risk scores for coronary heart disease over the 1999-2010 period. RESULTS From 1999 through 2010, the weighted proportion of survey participants who met recommended goals for diabetes care increased, by 7.9 percentage points (95% confidence interval [CI], 0.8 to 15.0) for glycemic control (glycated hemoglobin level <7.0%), 9.4 percentage points (95% CI, 3.0 to 15.8) for individualized glycemic targets, 11.7 percentage points (95% CI, 5.7 to 17.7) for blood pressure (target, <130/80 mm Hg), and 20.8 percentage points (95% CI, 11.6 to 30.0) for lipid levels (target level of low-density lipoprotein [LDL] cholesterol, <100 mg per deciliter [2.6 mmol per liter]). Tobacco use did not change significantly, but the 10-year probability of coronary heart disease decreased by 2.8 to 3.7 percentage points. However, 33.4 to 48.7% of persons with diabetes still did not meet the targets for glycemic control, blood pressure, or LDL cholesterol level. Only 14.3% met the targets for all three of these measures and for tobacco use. Adherence to the recommendations for annual eye and dental examinations was unchanged, but annual lipid-level measurement and foot examination increased by 5.5 percentage points (95% CI, 1.6 to 9.4) and 6.8 percentage points (95% CI, 4.8 to 8.8), respectively. Annual vaccination for influenza and receipt of pneumococcal vaccination for participants 65 years of age or older rose by 4.5 percentage points (95% CI, 0.8 to 8.2) and 6.9 percentage points (95% CI, 3.4 to 10.4), respectively, and daily glucose monitoring increased by 12.7 percentage points (95% CI, 10.3 to 15.1). CONCLUSIONS Although there were improvements in risk-factor control and adherence to preventive practices from 1999 to 2010, tobacco use remained high, and almost half of U.S. adults with diabetes did not meet the recommended goals for diabetes care.

Projections of type 1 and type 2 diabetes burden in the U.S. population aged <20 years through 2050: dynamic modeling of incidence, mortality, and population growth.

The SEARCH for Diabetes in Youth (SEARCH) study was initiated in 2000, with funding from the Centers for Disease Control and Prevention and support from the National Institute of Diabetes and Digestive and Kidney Diseases, to address major knowledge gaps in the understanding of childhood diabetes. SEARCH is being conducted at five sites across the U.S. and represents the largest, most diverse study of diabetes among U.S. youth. An active registry of youth diagnosed with diabetes at age <20 years allows the assessment of prevalence (in 2001 and 2009), annual incidence (since 2002), and trends by age, race/ethnicity, sex, and diabetes type. Prevalence increased significantly from 2001 to 2009 for both type 1 and type 2 diabetes in most age, sex, and race/ethnic groups. SEARCH has also established a longitudinal cohort to assess the natural history and risk factors for acute and chronic diabetes-related complications as well as the quality of care and quality of life of persons with diabetes from diagnosis into young adulthood. Many youth with diabetes, particularly those from low-resourced racial/ethnic minority populations, are not meeting recommended guidelines for diabetes care. Markers of micro- and macrovascular complications are evident in youth with either diabetes type, highlighting the seriousness of diabetes in this contemporary cohort. This review summarizes the study methods, describes key registry and cohort findings and their clinical and public health implications, and discusses future directions.

Presence of Diabetic Ketoacidosis at Diagnosis of Diabetes Mellitus in Youth: The Search for Diabetes in Youth Study

OBJECTIVE To assess correlates of glycemic control in a diverse population of children and youth with diabetes. STUDY DESIGN This was a cross-sectional analysis of data from a 6-center US study of diabetes in youth, including 3947 individuals with type 1 diabetes (T1D) and 552 with type 2 diabetes (T2D), using hemoglobin A(1c) (HbA(1c)) levels to assess glycemic control. RESULTS HbA(1c) levels reflecting poor glycemic control (HbA(1c) >or= 9.5%) were found in 17% of youth with T1D and in 27% of those with T2D. African-American, American Indian, Hispanic, and Asian/Pacific Islander youth with T1D were significantly more likely to have higher HbA(1c) levels compared with non-Hispanic white youth (with respective rates for poor glycemic control of 36%, 52%, 27%, and 26% vs 12%). Similarly poor control in these 4 racial/ethnic groups was found in youth with T2D. Longer duration of diabetes was significantly associated with poorer glycemic control in youth with T1D and T2D. CONCLUSIONS The high percentage of US youth with HbA(1c) levels above the target value and with poor glycemic control indicates an urgent need for effective treatment strategies to improve metabolic status in youth with diabetes.

Prevalence of Cardiovascular Disease Risk Factors in U.S. Children and Adolescents With Diabetes The SEARCH for Diabetes in Youth Study

OBJECTIVE To forecast the number of U.S. individuals aged <20 years with type 1 diabetes mellitus (T1DM) or type 2 diabetes mellitus (T2DM) through 2050, accounting for changing demography and diabetes incidence. RESEARCH DESIGN AND METHODS We used Markov modeling framework to generate yearly forecasts of the number of individuals in each of three states (diabetes, no diabetes, and death). We used 2001 prevalence and 2002 incidence of T1DM and T2DM from the SEARCH for Diabetes in Youth study and U.S. Census Bureau population demographic projections. Two scenarios were considered for T1DM and T2DM incidence: 1) constant incidence over time; 2) for T1DM yearly percentage increases of 3.5, 2.2, 1.8, and 2.1% by age-groups 0–4 years, 5–9 years, 10–14 years, and 15–19 years, respectively, and for T2DM a yearly 2.3% increase across all ages. RESULTS Under scenario 1, the projected number of youth with T1DM rises from 166,018 to 203,382 and with T2DM from 20,203 to 30,111, respectively, in 2010 and 2050. Under scenario 2, the number of youth with T1DM nearly triples from 179,388 in 2010 to 587,488 in 2050 (prevalence 2.13/1,000 and 5.20/1,000 [+144% increase]), with the greatest increase in youth of minority racial/ethnic groups. The number of youth with T2DM almost quadruples from 22,820 in 2010 to 84,131 in 2050; prevalence increases from 0.27/1,000 to 0.75/1,000 (+178% increase). CONCLUSIONS A linear increase in diabetes incidence could result in a substantial increase in the number of youth with T1DM and T2DM over the next 40 years, especially those of minority race/ethnicity.

TYPE 2 DIABETES IN CHILDREN

OBJECTIVE. The purpose of this work was to determine the prevalence and predictors of diabetic ketoacidosis at the diagnosis of diabetes in a large sample of youth from the US population. PATIENTS AND METHODS. The Search for Diabetes in Youth Study, a multicenter, population-based registry of diabetes with diagnosis before 20 years of age, identified 3666 patients with new onset of diabetes in the study areas in 2002–2004. Medical charts were reviewed in 2824 (77%) of the patients in a standard manner to abstract the results of laboratory tests and to ascertain diabetic ketoacidosis at the time of diagnosis. Diabetic ketoacidosis was defined by blood bicarbonate <15 mmol/L and/or venous pH < 7.25 (arterial/capillary pH < 7.30), International Classification of Diseases, Ninth Revision, code 250.1, or listing of diabetic ketoacidosis in the medical chart. RESULTS. More than half (54%) of the patients were hospitalized at diagnosis, including 93% of those with diabetic ketoacidosis and 41% without diabetic ketoacidosis. The prevalence of diabetic ketoacidosis at the diagnosis was 25.5%. The prevalence decreased with age from 37.3% in children aged 0 to 4 years to 14.7% in those aged 15 to 19 years. Diabetic ketoacidosis prevalence was significantly higher in patients with type 1 (29.4%) rather than in those with type 2 diabetes (9.7%). After adjusting for the effects of center, age, gender, race or ethnicity, diabetes type, and family history of diabetes, diabetic ketoacidosis at diagnosis was associated with lower family income, less desirable health insurance coverage, and lower parental education. CONCLUSION. At the time of diagnosis, 1 in 4 youth presents with diabetic ketoacidosis. Those with diabetic ketoacidosis were more likely to be hospitalized. Diabetic ketoacidosis was a presenting feature of <10% of youth with type 2. Young and poor children are disproportionately affected.

Prevalence of impaired fasting glucose and its relationship with cardiovascular disease risk factors in US adolescents, 1999-2000.

OBJECTIVE—The purpose of this study was to determine the prevalence and correlates of selected cardiovascular disease (CVD) risk factors among youth aged <20 years with diabetes. RESEARCH DESIGN AND METHODS—The analysis included 1,083 girls and 1,013 boys examined as part of the SEARCH for Diabetes in Youth study, a multicenter, population-based study of youth 0–19 years of age with diabetes. Diabetes type was determined by a biochemical algorithm based on diabetes antibodies and fasting C-peptide level. CVD risk factors were defined as follows: HDL cholesterol <40 mg/dl; age- and sex-specific waist circumference >90th percentile; systolic or diastolic blood pressure >90th percentile for age, sex, and height or taking medication for high blood pressure; and triglycerides >110 mg/dl. RESULTS—The prevalence of having at least two CVD risk factors was 21%. The prevalence was 7% among children aged 3–9 years and 25% in youth aged 10–19 years (P < 0.0001), 23% among girls and 19% in boys (P = 0.04), 68% in American Indians, 37% in Asian/Pacific Islanders, 32% in African Americans, 35% in Hispanics, and 16% in non-Hispanic whites (P < 0.0001). At least two CVD risk factors were present in 92% of youth with type 2 and 14% of those with type 1A diabetes (P < 0.0001). In multivariate analyses, age, race/ethnicity, and diabetes type were independently associated with the odds of having at least two CVD risk factors (P < 0.0001). CONCLUSIONS—Many youth with diabetes have multiple CVD risk factors. Recommendations for weight, lipid, and blood pressure control in youth with diabetes need to be followed to prevent or delay the development of CVD as these youngsters mature.