Diabetic ketoacidosis at diagnosis among youth with type 1 and type 2 diabetes: Results from SEARCH (United States) and YDR (India) registries.

BACKGROUND: There is significant global variation in the prevalence of diabetic ketoacidosis (DKA) at diagnosis among youth with type 1 diabetes (T1D). However, data for youth with type 2 diabetes (T2D) are limited, even in developed countries. We compared the prevalence of DKA at diagnosis among individuals with T1D and T2D from the SEARCH for Diabetes in Youth (SEARCH) and the Registry of Youth Onset Diabetes in India (YDR) registries. METHODS: We harmonized the SEARCH and YDR registries to the structure and terminology in the Observational Medical Outcome Partnership Common Data Model. Data used were from youth with T1D and T2D diagnosed before 20 years and newly diagnosed between 2006 and 2012 in YDR and 2009 and 2012 in SEARCH. RESULTS: There were 5366 US youth (4078 with T1D, 1288 with T2D) and 2335 Indian youth (2108 with T1D, 227 with T2D). More than one third of T1D youth enrolled in SEARCH had DKA at diagnosis which was significantly higher than in YDR (35.3% vs 28.7%, P < .0001). The burden of DKA in youth with T1D was significantly higher among younger age groups; this relationship was similar across registries (P = .4). The prevalence of DKA among T2D in SEARCH and YDR were 5.5% and 6.6% respectively (P = .4). CONCLUSIONS: There is significant burden of DKA at diagnosis with T1D among youth from United States and India, especially among the younger age groups. The reasons for this high prevalence are largely unknown but are critical to developing interventions to prevent DKA at diagnosis.

Clinical profile at diagnosis with youth-onset type 1 and type 2 diabetes in two pediatric diabetes registries: SEARCH (United States) and YDR (India).

BACKGROUND: Over the last decades, diabetes in youth has increased in both India and the United States, along with the burden of long-term complications and healthcare costs. However, there are limited standardized population-based data in contemporary youth cohorts for comparison of clinical and demographic characteristics of diabetes for both type 1 (T1D) and type 2 (T2D). METHODS: In partnership, we harmonized demographic and clinical data from the SEARCH for Diabetes in Youth (SEARCH) registry in the United States and the Registry of People with Diabetes with Youth Age at Onset (YDR) in India to the structure and terminology of the Observational Medical Outcomes Partnership Common Data Model. Data were from youth with T1D and T2D, aged <20 years and newly diagnosed between 2006 and 2010. We compared key characteristics across registries using χ2 tests and t-tests. RESULTS: In total, there were 9650 youth with T1D and 2406 youth with T2D from 2006 to 2012. SEARCH youth were diagnosed at younger ages than YDR youth for T1D and T2D (10.0 vs 10.5 years, P < .001 and 14.7 vs 16.1 years, P < .001, respectively). For T2D, SEARCH had a higher proportion of females and significantly lower proportion of youth of high socioeconomic status compared to YDR. For T1D and T2D, SEARCH youth had higher BMI, lower blood pressure, and lower A1c compared to YDR youth. CONCLUSIONS: These data offer insights into the demographic and clinical characteristics of diabetes in youth across the two countries. Further research is needed to better understand why these differences exist.

Treatment regimens and glycosylated hemoglobin levels in youth with Type 1 and Type 2 diabetes: Data from SEARCH (United States) and YDR (India) registries.

OBJECTIVE: To compare treatment regimens and glycosylated hemoglobin (A1c) levels in Type 1 (T1D) and Type 2 diabetes (T2D) using diabetes registries from two countries-U.S. SEARCH for Diabetes in Youth (SEARCH) and Indian Registry of youth onset diabetes in India (YDR). METHODS: The SEARCH and YDR data were harmonized to the structure and terminology in the Observational Medical Outcomes Partnership Common Data Model. Data used were from T1D and T2D youth diagnosed <20 years between 2006-2012 for YDR, and 2006, 2008, and 2012 for SEARCH. We compared treatment regimens and A1c levels across the two registries. RESULTS: There were 4003 T1D (SEARCH = 1899; YDR = 2104) and 611 T2D (SEARCH = 384; YDR = 227) youth. The mean A1c was higher in YDR compared to SEARCH (T1D:11.0% ± 2.9% vs 7.8% ± 1.7%, P < .001; T2D:9.9% ± 2.8% vs 7.2% ± 2.1%, P < .001). Among T1D youth in SEARCH, 65.1% were on a basal/bolus regimen, whereas in YDR, 52.8% were on once/twice daily insulin regimen. Pumps were used by 16.2% of SEARCH and 1.5% of YDR youth with T1D. Among T2D youth, in SEARCH and YDR, a majority were on metformin only (43.0% vs 30.0%), followed by insulin + any oral hypoglycemic agents (26.3% vs 13.7%) and insulin only (12.8% vs 18.9%), respectively. CONCLUSION: We found significant differences between SEARCH and YDR in treatment patterns in T1D and T2D. A1c levels were higher in YDR than SEARCH youth, for both T1D and T2D, irrespective of the regimens used. Efforts to achieve better glycemic control for youth are urgently needed to reduce the risk of long-term complications.

Comparison of the incidence of diabetes in United States and Indian youth: An international harmonization of youth diabetes registries.

OBJECTIVE: Incidence of youth-onset diabetes in India has not been well described. Comparison of incidence, across diabetes registries, has the potential to inform hypotheses for risk factors. We sought to compare the incidence of diabetes in the U.S.-based registry of youth onset diabetes (SEARCH) to the Registry of Diabetes with Young Age at Onset (YDR-Chennai and New Delhi regions) in India. METHODS: We harmonized data from both SEARCH and YDR to the Observational Medical Outcomes Partnership (OMOP) Common Data Model. Data were from youth registered with incident diabetes (2006-2012). Denominators were from census and membership data. We calculated diabetes incidence by averaging the total cases across the entire follow-up period and dividing this by the estimated census population corresponding to the source population for case ascertainment. Incidence was calculated for each of the registries and compared by type and within age and sex categories using a 2-sided, skew-corrected inverted score test. RESULTS: Incidence of type 1 was higher in SEARCH (21.2 cases/100 000 [95% CI: 19.9, 22.5]) than YDR (4.9 cases/100 000 [95% CI: 4.3, 5.6]). Incidence of type 2 diabetes was also higher in SEARCH (5.9 cases/100 000 [95% CI: 5.3, 6.6] in SEARCH vs 0.5/cases/100 000 [95% CI: 0.3, 0.7] in YDR). The age distribution of incident type 1 diabetes cases was similar across registries, whereas type 2 diabetes incidence was higher at an earlier age in SEARCH. Sex differences existed in SEARCH only, with a higher rate of type 2 diabetes among females. CONCLUSION: The incidence of youth-onset type 1 and 2 diabetes was significantly different between registries. Additional data are needed to elucidate whether the differences observed represent diagnostic delay, differences in genetic susceptibility, or differences in distribution of risk factors.

Urine tungsten and chronic kidney disease in rural Colorado.

BACKGROUND: Chronic kidney disease (CKD) is a cause of global morbidity and mortality in agricultural communities. The San Luis Valley (SLV) is a rural agricultural community in southern Colorado with geographic and sociodemographic risk factors for CKD, including a water supply contaminated by heavy metals. METHODS: We obtained pre-existing sociodemographic, clinical, and urine trace metal data for 1659 subjects from the San Luis Valley Diabetes Study, a prospective cohort study. We assessed prospective associations between urine tungsten (W) and time-to-CKD using accelerated failure time models (n = 1659). Additionally, logistic models were used to assess relationships between urine W and renal injury markers (NGAL, KIM1) using Tobit regression (n = 816), as well as epidemiologically-defined CKD of unknown origin (CKDu) using multiple logistic regression (n = 620). RESULTS: Elevated urine W was strongly associated with decreased time-to-CKD, even after controlling for hypertension and diabetes. Depending on how CKD was defined, a doubling of urine W was associated with a 27% (95% CI 11%, 46%) to 31% (14%, 51%) higher odds of developing CKD within 5 years. The relationship between urine W and select renal injury markers was not significant, although urine NGAL was modified by diabetes status. Elevated (>95%ile) urinary W was significantly associated with CKDu (OR 5.93, 1.83, 19.21) while adjusting for known CKD risk factors. CONCLUSIONS: Our data suggest that increased exposure to W is associated with decreased time-to-CKD and may be associated with CKDu. Given persistence of associations after controlling for diabetes and hypertension, W may exert a primary effect on the kidney, although this needs to be evaluated further in future studies.

Trends in Prevalence of Type 1 and Type 2 Diabetes in Children and Adolescents in the US, 2001-2017.

Importance: Changes in the prevalence of youth-onset diabetes have previously been observed. Objective: To estimate changes in prevalence of type 1 and type 2 diabetes in youths in the US from 2001 to 2017. Design, Setting, and Participants: In this cross-sectional observational study, individuals younger than 20 years with physician-diagnosed diabetes were enumerated from 6 areas in the US (4 geographic areas, 1 health plan, and select American Indian reservations) for 2001, 2009, and 2017. Exposures: Calendar year. Main Outcomes and Measures: Estimated prevalence of physician-diagnosed type 1 and type 2 diabetes overall and by race and ethnicity, age, and sex. Results: Among youths 19 years or younger, 4958 of 3.35 million had type 1 diabetes in 2001, 6672 of 3.46 million had type 1 diabetes in 2009, and 7759 of 3.61 million had type 1 diabetes in 2017; among those aged 10 to 19 years, 588 of 1.73 million had type 2 diabetes in 2001, 814 of 1.85 million had type 2 diabetes in 2009, and 1230 of 1.85 million had type 2 diabetes in 2017. The estimated type 1 diabetes prevalence per 1000 youths for those 19 years or younger increased significantly from 1.48 (95% CI, 1.44-1.52) in 2001 to 1.93 (95% CI, 1.88-1.98) in 2009 to 2.15 (95% CI, 2.10-2.20) in 2017, an absolute increase of 0.67 per 1000 youths (95%, CI, 0.64-0.70) and a 45.1% (95% CI, 40.0%-50.4%) relative increase over 16 years. The greatest absolute increases were observed among non-Hispanic White (0.93 per 1000 youths [95% CI, 0.88-0.98]) and non-Hispanic Black (0.89 per 1000 youths [95% CI, 0.88-0.98]) youths. The estimated type 2 diabetes prevalence per 1000 youths aged 10 to 19 years increased significantly from 0.34 (95% CI, 0.31-0.37) in 2001 to 0.46 (95% CI, 0.43-0.49) in 2009 to 0.67 (95% CI, 0.63-0.70) in 2017, an absolute increase of 0.32 per 1000 youths (95% CI, 0.30-0.35) and a 95.3% (95% CI, 77.0%-115.4%) relative increase over 16 years. The greatest absolute increases were observed among non-Hispanic Black (0.85 per 1000 youths [95% CI, 0.74-0.97]) and Hispanic (0.57 per 1000 youths [95% CI, 0.51-0.64]) youths. Conclusions and Relevance: In 6 areas of the US from 2001 to 2017, the estimated prevalence of diabetes among children and adolescents increased for both type 1 and type 2 diabetes.

Trends in Incidence of Type 1 and Type 2 Diabetes Among Youths - Selected Counties and Indian Reservations, United States, 2002-2015.

Diabetes is one of the most common chronic diseases among persons aged <20 years (1). Onset of diabetes in childhood and adolescence is associated with numerous complications, including diabetic kidney disease, retinopathy, and peripheral neuropathy, and has a substantial impact on public health resources (2,3). From 2002 to 2012, type 1 and type 2 diabetes incidence increased 1.4% and 7.1%, respectively, among U.S. youths (4). To assess recent trends in incidence of diabetes in youths (defined for this report as persons aged <20 years), researchers analyzed 2002-2015 data from the SEARCH for Diabetes in Youth Study (SEARCH), a U.S. population-based registry study with clinical sites located in five states. The incidence of both type 1 and type 2 diabetes in U.S. youths continued to rise at constant rates throughout this period. Among all youths, the incidence of type 1 diabetes increased from 19.5 per 100,000 in 2002-2003 to 22.3 in 2014-2015 (annual percent change [APC] = 1.9%). Among persons aged 10-19 years, type 2 diabetes incidence increased from 9.0 per 100,000 in 2002-2003 to 13.8 in 2014-2015 (APC = 4.8%). For both type 1 and type 2 diabetes, the rates of increase were generally higher among racial/ethnic minority populations than those among whites. These findings highlight the need for continued surveillance for diabetes among youths to monitor overall and group-specific trends, identify factors driving these trends, and inform health care planning.

The accuracy of provider diagnosed diabetes type in youth compared to an etiologic criteria in the SEARCH for Diabetes in Youth Study.

BACKGROUND: Although surveillance for diabetes in youth relies on provider-assigned diabetes type from medical records, its accuracy compared to an etiologic definition is unknown. METHODS: Using the SEARCH for Diabetes in Youth Registry, we evaluated the validity and accuracy of provider-assigned diabetes type abstracted from medical records against etiologic criteria that included the presence of diabetes autoantibodies (DAA) and insulin sensitivity. Youth who were incident for diabetes in 2002-2006, 2008, or 2012 and had complete data on key analysis variables were included (n = 4001, 85% provider diagnosed type 1). The etiologic definition for type 1 diabetes was ≥1 positive DAA titer(s) or negative DAA titers in the presence of insulin sensitivity and for type 2 diabetes was negative DAA titers in the presence of insulin resistance. RESULTS: Provider diagnosed diabetes type correctly agreed with the etiologic definition of type for 89.9% of cases. Provider diagnosed type 1 diabetes was 96.9% sensitive, 82.8% specific, had a positive predictive value (PPV) of 97.0% and a negative predictive value (NPV) of 82.7%. Provider diagnosed type 2 diabetes was 82.8% sensitive, 96.9% specific, had a PPV and NPV of 82.7% and 97.0%, respectively. CONCLUSION: Provider diagnosis of diabetes type agreed with etiologic criteria for 90% of the cases. While the sensitivity and PPV were high for youth with type 1 diabetes, the lower sensitivity and PPV for type 2 diabetes highlights the value of DAA testing and assessment of insulin sensitivity status to ensure estimates are not biased by misclassification.

Evaluating Community-Based Translational Interventions Using Historical Controls: Propensity Score vs. Disease Risk Score Approach.

Many community-based translations of evidence-based interventions are designed as one-arm studies due to ethical and other considerations. Evaluating the impacts of such programs is challenging. Here, we examine the effectiveness of the lifestyle intervention implemented by the Special Diabetes Program for Indians Diabetes Prevention (SDPI-DP) demonstration project, a translational lifestyle intervention among American Indian and Alaska Native communities. Data from the landmark Diabetes Prevention Program placebo group was used as a historical control. We compared the use of propensity score (PS) and disease risk score (DRS) matching to adjust for potential confounder imbalance between groups. The unadjusted hazard ratio (HR) for diabetes risk was 0.35 for SDPI-DP lifestyle intervention vs. control. However, when relevant diabetes risk factors were considered, the adjusted HR estimates were attenuated toward 1, ranging from 0.56 (95% CI 0.44-0.71) to 0.69 (95% CI 0.56-0.96). The differences in estimated HRs using the PS and DRS approaches were relatively small but DRS matching resulted in more participants being matched and smaller standard errors of effect estimates. Carefully employed, publicly available randomized clinical trial data can be used as a historical control to evaluate the intervention effectiveness of one-arm community translational initiatives. It is critical to use a proper statistical method to balance the distributions of potential confounders between comparison groups in this kind of evaluations.

Distribution and predictors of urinary concentrations of phthalate metabolites and phenols among pregnant women in the Healthy Start Study.

BACKGROUND: Phthalates and phenols are suspected endocrine disrupting chemicals that may adversely impact fetal outcomes following in utero exposure. Understanding predictors of exposure to phthalates and phenols during the prenatal period is important. METHODS: We measured urinary concentrations of 15 phthalate metabolites and 11 phenols in 446 pregnant women enrolled in the Healthy Start pre-birth cohort. Creatinine-adjusted geometric means (GM) for each urinary biomarker were compared across categories of potential sociodemographic and dietary predictors. To assess the independent relationship between each significant food group predictor and biomarker we used multivariable models, adjusted for sociodemographic predictors. RESULTS: The phthalate metabolites with the highest concentrations were monoethyl phthalate (GM: 41.1µg/g creatinine) and monocarboxyisooctyl phthalate (GM: 20.5µg/g creatinine). Benzophenone-3 (GM: 124.6µg/g creatinine) and methyl paraben (GM: 119.9µg/g creatinine) were the phenols with the highest concentrations. Concentrations of the metabolites of di-n-butyl phthalate and di(2-ethylhexyl) phthalate were significantly higher in younger, unmarried or unemployed mothers, those who were overweight or obese, those with lower educational attainment, or those of minority race/ethnicity (p-values < 0.05). Metabolites of di-n-butyl phthalate concentrations were 18% lower in those who consumed milk ≥ 7 times per week (95% CI: 30-4%). Benzophenone-3 and triclosan concentrations were significantly higher in older, married, or employed mothers, those with normal body mass index, higher educational attainment, higher household income, or who were non-Hispanic white (p-values < 0.05). Benzophenone-3 concentrations were 62% higher in those who consumed seafood ≥ 5 times per month (95% CI: 16-127%). CONCLUSIONS: We observed differences in urinary concentrations of phthalates and phenol biomarkers by sociodemographic predictors in an ethnically diverse cohort of pregnant women. These results and future analyses from this prospective cohort will help inform targeted interventions to reduce exposure to these potential endocrine disrupting chemicals during pregnancy.

Replication of the Association of BDNF and MC4R Variants With Dietary Intake in the Diabetes Prevention Program.

OBJECTIVE: Genomewide association studies (GWAS) have identified consistent associations with obesity, with a number of studies implicating eating behavior as a primary mechanism. Few studies have replicated genetic associations with dietary intake. This study evaluates the association between obesity susceptibility loci and dietary intake. METHODS: Data were obtained as part of the Diabetes Prevention Program (DPP), a clinical trial of diabetes prevention in persons at high risk of diabetes. The association of 31 genomewide association studies identified obesity risk alleles with dietary intake, measured through a food frequency questionnaire, was investigated in 3,180 participants from DPP at baseline. RESULTS: The minor allele at BDNF, identified as protective against obesity, was associated with lower total caloric intake (ß = -106.06, SE = 33.13; p = .0014) at experimentwide statistical significance (p = .0016), whereas association of MC4R rs571312 with higher caloric intake reached nominal significance (ß = 61.32, SE = 26.24; p = .0194). Among non-Hispanic white participants, the association of BDNF rs2030323 with total caloric intake was stronger (ß = -151.99, SE = 30.09; p < .0001), and association of FTO rs1421085 with higher caloric intake (ß = 56.72, SE = 20.69; p = .0061) and percentage fat intake (ß = 0.37, SE = 0.08; p = .0418) was also observed. CONCLUSIONS: These results demonstrate with the strength of independent replication that BDNF rs2030323 is associated with 100 to 150 greater total caloric intake per allele, with additional contributions of MC4R and, in non-Hispanic white individuals, FTO. As it has been argued that an additional 100 kcal/d could account for the trends in weight gain, prevention focusing on genetic profiles with high dietary intake may help to quell adverse obesity trends. CLINICAL TRIAL REGISTRATION: Clinicaltrials.gov,NCT00004992.

Association of Type 1 Diabetes vs Type 2 Diabetes Diagnosed During Childhood and Adolescence With Complications During Teenage Years and Young Adulthood.

Importance: The burden and determinants of complications and comorbidities in contemporary youth-onset diabetes are unknown. Objective: To determine the prevalence of and risk factors for complications related to type 1 diabetes vs type 2 diabetes among teenagers and young adults who had been diagnosed with diabetes during childhood and adolescence. Design, Setting, and Participants: Observational study from 2002 to 2015 in 5 US locations, including 2018 participants with type 1 and type 2 diabetes diagnosed at younger than 20 years, with single outcome measures between 2011 and 2015. Exposures: Type 1 and type 2 diabetes and established risk factors (hemoglobin A1c level, body mass index, waist-height ratio, and mean arterial blood pressure). Main Outcomes and Measures: Diabetic kidney disease, retinopathy, peripheral neuropathy, cardiovascular autonomic neuropathy, arterial stiffness, and hypertension. Results: Of 2018 participants, 1746 had type 1 diabetes (mean age, 17.9 years [SD, 4.1]; 1327 non-Hispanic white [76.0%]; 867 female patients [49.7%]), and 272 had type 2 (mean age, 22.1 years [SD, 3.5]; 72 non-Hispanic white [26.5%]; 181 female patients [66.5%]). Mean diabetes duration was 7.9 years (both groups). Patients with type 2 diabetes vs those with type 1 had higher age-adjusted prevalence of diabetic kidney disease (19.9% vs 5.8%; absolute difference [AD], 14.0%; 95% CI, 9.1%-19.9%; P < .001), retinopathy (9.1% vs 5.6%; AD, 3.5%; 95% CI, 0.4%-7.7%; P = .02), peripheral neuropathy (17.7% vs 8.5%; AD, 9.2%; 95% CI, 4.8%-14.4%; P < .001), arterial stiffness (47.4% vs 11.6%; AD, 35.9%; 95% CI, 29%-42.9%; P < .001), and hypertension (21.6% vs 10.1%; AD, 11.5%; 95% CI, 6.8%-16.9%; P < .001), but not cardiovascular autonomic neuropathy (15.7% vs 14.4%; AD, 1.2%; 95% CI, -3.1% to 6.5; P = .62). After adjustment for established risk factors measured over time, participants with type 2 diabetes vs those with type 1 had significantly higher odds of diabetic kidney disease (odds ratio [OR], 2.58; 95% CI, 1.39-4.81; P=.003), retinopathy (OR, 2.24; 95% CI, 1.11-4.50; P = .02), and peripheral neuropathy (OR, 2.52; 95% CI, 1.43-4.43; P = .001), but no significant difference in the odds of arterial stiffness (OR, 1.07; 95% CI, 0.63-1.84; P = .80) and hypertension (OR, 0.85; 95% CI, 0.50-1.45; P = .55). Conclusions and Relevance: Among teenagers and young adults who had been diagnosed with diabetes during childhood or adolescence, the prevalence of complications and comorbidities was higher among those with type 2 diabetes compared with type 1, but frequent in both groups. These findings support early monitoring of youth with diabetes for development of complications.

Change in adiposity minimally affects the lipid profile in youth with recent onset type 1 diabetes.

OBJECTIVE: Dyslipidemia contributes to the increased risk of cardiovascular disease in persons with type 1 diabetes (T1D). Weight control is commonly recommended as a treatment for dyslipidemia. However, the extent to which decreases in weight affect the lipid profile in youth with T1D is not known. Therefore, we tested the hypothesis that decreases in body mass index z-score (BMIz) were associated with concomitant changes in the lipid profile in youth with T1D. STUDY DESIGN: We studied 1142 youth with incident T1D, who had at least two fasting lipid measurements over 2 yr (initial visit mean: age = 10.8 ± 3.9 yr, BMIz = 0.55 ± 0.97, T1D duration = 10.7 ± 7.6 months; 47.5% female, 77.9% non-Hispanic white) in the SEARCH for Diabetes in Youth Study. Longitudinal mixed models were used to examine the relationships between changes in BMIz and changes in total, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), non-HDL cholesterol, and log triglycerides (TG) adjusted for initial age, sex, race/ethnicity, clinical site, season of study visit, T1D duration, and glycated hemoglobin A1c (HbA1c). RESULTS: We found that over 2 yr all lipid levels, except LDL-C, increased significantly (p < 0.05). Decreases in BMIz were associated with favorable changes in HDL-C and TG only and the magnitude of these changes depended on the initial BMIz value (interaction p < 0.05), so that greater improvements were seen in those with higher BMIz. CONCLUSIONS: Our data suggest that weight loss may be an effective, but limited, therapeutic approach for dyslipidemia in youth with T1D.

Arterial stiffness in adolescents and young adults with and without type 1 diabetes: the SEARCH CVD study.

BACKGROUND: Arterial stiffness is a useful parameter to predict future cardiovascular disease. OBJECTIVE: We sought to compare arterial stiffness in adolescents and young adults with and without type 1 diabetes (T1D) and explore the risk factors associated with the differences observed. SUBJECTS AND METHODS: Carotid-femoral pulse wave velocity (PWV), augmentation index (AI75), and brachial distensibility (BrachD) were measured in 402 adolescents and young adults with T1D (age 18.8 ± 3.3 yr, T1D duration 9.8 ± 3.8 yr) and 206 non-diabetic controls that were frequency-matched by age, sex, and race/ethnicity in a cross-sectional study. General linear models were used to explore variables associated with an increase in arterial stiffness after adjustment for demographic and metabolic covariates. RESULTS: T1D status was associated with a higher PWV (5.9 ± 0.05 vs. 5.7 ± 0.1 m/s), AI75 (1.3 ± 0.6 vs. -1.9 ± 0.7%), and lower BrachD (6.2 ± 0.1 vs. 6.5 ± 0.1%Δ/mmHg), all p < 0.05. In multivariate models, age, sex, race, adiposity, blood pressure, lipids, and the presence of microalbuminuria were found to be independent correlates of increased arterial stiffness. After adjustment for these risk factors, T1D status was still significantly associated with arterial stiffness (p < 0.05). CONCLUSIONS: Peripheral and central subclinical vascular changes are present in adolescents and young adults with T1D compared to controls. Increased cardiovascular risk factors alone do not explain the observed differences in arterial stiffness among cases and controls. Identifying other risk factors associated with increased arterial stiffness in youth with T1D is critical to prevent future vascular complications.

Lipoprotein lipase gene sequencing and plasma lipid profile.

Lipoprotein lipase (LPL) plays a crucial role in lipid metabolism by hydrolyzing triglyceride (TG)-rich particles and affecting HDL cholesterol (HDL-C) levels. In this study, the entire LPL gene plus flanking regions were resequenced in individuals with extreme HDL-C/TG levels (n = 95), selected from a population-based sample of 623 US non-Hispanic White (NHW) individuals. A total of 176 sequencing variants were identified, including 28 novel variants. A subset of 64 variants [common tag single nucleotide polymorphisms (tagSNP) and selected rare variants] were genotyped in the total sample, followed by association analyses with major lipid traits. A gene-based association test including all genotyped variants revealed significant association with HDL-C (P = 0.024) and TG (P = 0.006). Our single-site analysis revealed seven independent signals (P < 0.05; r² < 0.40) with either HDL-C or TG. The most significant association was for the SNP rs295 exerting opposite effects on TG and HDL-C levels with P values of 7.5.10⁻4 and 0.002, respectively. Our work highlights some common variants and haplotypes in LPL with significant associations with lipid traits; however, the analysis of rare variants using burden tests and SKAT-O method revealed negligible effects on lipid traits. Comprehensive resequencing of LPL in larger samples is warranted to further test the role of rare variants in affecting plasma lipid levels.

Validation of pediatric diabetes case identification approaches for diagnosed cases by using information in the electronic health records of a large integrated managed health care organization.

We explored the utility of different algorithms for diabetes case identification by using electronic health records. Inpatient and outpatient diagnosis codes, as well as data on laboratory results and dispensing of antidiabetic medications were extracted from electronic health records of Kaiser Permanente Southern California members who were less than 20 years of age in 2009. Diabetes cases were ascertained by using the SEARCH for Diabetes in Youth Study protocol and comprised the "gold standard." Sensitivity, specificity, positive and negative predictive values, accuracy, and the area under the receiver operating characteristic curve (AUC) were compared in 1,000 bootstrapped samples. Based on data from 792,992 youth, of whom 1,568 had diabetes (77.2%, type 1 diabetes; 22.2%, type 2 diabetes; 0.6%, other), case identification accuracy was highest in 75% of bootstrapped samples for those who had 1 or more outpatient diabetes diagnoses or 1 or more insulin prescriptions (sensitivity, 95.9%; positive predictive value, 95.5%; AUC, 97.9%) and in 25% of samples for those who had 2 or more outpatient diabetes diagnoses and 1 or more antidiabetic medications (sensitivity, 92.4%; positive predictive value, 98.4%; AUC, 96.2%). Having 1 or more outpatient type 1 diabetes diagnoses (International Classification of Diseases, Ninth Revision, Clinical Modification, code 250.x1 or 250.x3) had the highest accuracy (94.4%) and AUC (94.1%) for type 1 diabetes; the absence of type 1 diabetes diagnosis had the highest accuracy (93.8%) and AUC (93.6%) for identifying type 2 diabetes. Information in the electronic health records from managed health care organizations provides an efficient and cost-effective source of data for childhood diabetes surveillance.

Smoking and arterial stiffness in youth with type 1 diabetes: the SEARCH Cardiovascular Disease Study.

OBJECTIVE: To evaluate the effects of smoking on early markers of cardiovascular disease (arterial stiffness) in adolescents with and without type 1 diabetes (T1D) in the SEARCH Cardiovascular Disease Study. STUDY DESIGN: Participants included 606 youth (18.9 ± 3.3 years, 83% non-Hispanic white; 50% male). Six groups were defined: (1) smokers with T1D (n = 80); (2) former smokers with T1D (n = 88); (3) nonsmokers with T1D (n = 232); (4) smokers without T1D (n = 40); (5) former smokers without T1D former (n = 51); and (6) nonsmokers without T1D (n = 115). Arterial stiffness measurements included pulse wave velocity (PWV), augmentation index, and brachial distensibility. Multivariate linear regression was used to assess the independent and joint effects of T1D and smoking on arterial stiffness. RESULTS: Nearly 20% of both youth with and without T1D and T1D were smokers. In youth without T1D, smokers had higher trunk and arm PWV. After adjustment for potential confounders, T1D, but not smoking, was an independent predictor of PWV (P < .05). Moreover, smoking status did not modify the association between T1D and increased arterial stiffness. CONCLUSIONS: We found a high prevalence of smoking among youth with and without T1D; however, smoking status was not independently associated with increased arterial stiffness in youth with T1D.

Use of administrative and electronic health record data for development of automated algorithms for childhood diabetes case ascertainment and type classification: the SEARCH for Diabetes in Youth Study.

BACKGROUND: The performance of automated algorithms for childhood diabetes case ascertainment and type classification may differ by demographic characteristics. OBJECTIVE: This study evaluated the potential of administrative and electronic health record (EHR) data from a large academic care delivery system to conduct diabetes case ascertainment in youth according to type, age, and race/ethnicity. SUBJECTS: Of 57 767 children aged <20 yr as of 31 December 2011 seen at University of North Carolina Health Care System in 2011 were included. METHODS: Using an initial algorithm including billing data, patient problem lists, laboratory test results, and diabetes related medications between 1 July 2008 and 31 December 2011, presumptive cases were identified and validated by chart review. More refined algorithms were evaluated by type (type 1 vs. type 2), age (<10 vs. ≥10 yr) and race/ethnicity (non-Hispanic White vs. 'other'). Sensitivity, specificity, and positive predictive value were calculated and compared. RESULTS: The best algorithm for ascertainment of overall diabetes cases was billing data. The best type 1 algorithm was the ratio of the number of type 1 billing codes to the sum of type 1 and type 2 billing codes ≥0.5. A useful algorithm to ascertain youth with type 2 diabetes with 'other' race/ethnicity was identified. Considerable age and racial/ethnic differences were present in type-non-specific and type 2 algorithms. CONCLUSIONS: Administrative and EHR data may be used to identify cases of childhood diabetes (any type), and to identify type 1 cases. The performance of type 2 case ascertainment algorithms differed substantially by race/ethnicity.

Cardiovascular health in adolescents with type 1 diabetes: the SEARCH CVD study.

OBJECTIVE: In their Strategic Impact Goal Statement, the American Heart Association focused on primordial prevention of cardiovascular risk factors by defining metrics for ideal cardiovascular health (ICH). The prevalence of ICH among youth with type 1 diabetes is unknown. Youth with type 1 diabetes face an increased risk of cardiovascular disease (CVD) as they age. The purpose of this report was to examine the prevalence of ICH in a population of youth with type 1 diabetes and to examine the association of ICH with measures of cardiovascular structure and function. RESEARCH DESIGN AND METHODS: This report is based on SEARCH CVD an ancillary study to the SEARCH for Diabetes in Youth. A total of 190 adolescents with type 1 diabetes had complete data on all of the ICH metrics at baseline and had measures of arterial stiffness [pulse wave velocity (PWV), brachial distensibility (BrachD), and augmentation index (AIx)] and carotid intima-media thickness completed at a follow-up visit [on average 5 yr after baseline (interquartile range 4-5)]. RESULTS: No subjects met the ICH criteria for all 7 metrics. Meeting an increasing number of ICH metrics was significantly associated with lower arterial stiffness [lower PWV of the trunk (ß = -0.02 ±0.01; p = 0.004) and AIx (ß = -2.2 ±0.66; p = 0.001), and increased BrachD (ß = 0.14 ±0.07; p = 0.04)]. CONCLUSIONS: Increasing number of ICH metrics was significantly associated with decreased arterial stiffness, but prevalence of ICH in this population was low. Youth with type 1 diabetes could benefit from improvements in their cardiovascular health.

Impairment of executive cognitive control in type 2 diabetes, and its effects on health-related behavior and use of health services.

We evaluated whether, among persons with type 2 diabetes: (1) impaired executive cognitive functioning (ECF) is more common than among people without diabetes; (2) ECF is associated with the capacity to engage in instrumental health-related behaviors; and (3) worse ECF is associated with increased health services utilization. A population-based sample of 1,063 older people was interviewed regarding medical history and health services utilization; participants were administered the Mini Mental State Exam and the Behavioral Dyscontrol Scale, a measure of ECF. Participants with diabetes performed more poorly on cognitive measures than those without diabetes. Among those with diabetes, lower ECF was associated with more outpatient care and with ever having been in a nursing home. Impaired behavioral self-regulation may affect the capacity to engage in behaviors that could improve clinical status, resulting in greater health services use. The findings suggest the possibility of a positive feedback loop, with ECF deficits adversely affecting adherence, in turn leading to greater cognitive impairment-an issue for future research.