Household food insecurity and associations with hemoglobin A1c and acute diabetes-related complications in youth and young adults with type 1 diabetes: The SEARCH for Diabetes in Youth study.

AIMS: To examine, among youth and young adults (YYA) with type 1 diabetes (T1D), the association of household food insecurity (HFI) with: 1) HbA1c and 2) episodes of diabetic ketoacidosis (DKA) and severe hypoglycemia. METHODS: HFI was assessed using the U.S. Household Food Security Survey Module in SEARCH for Diabetes in Youth participants with T1D between 2016 and 2019. Linear and logistic regression models adjusted for age, diabetes duration, sex, race, ethnicity, clinic site, parent/participant education, household income, health insurance, and diabetes technology use. RESULTS: Of 1830 participants (mean age 20.8 ± 5.0 years, 70.0 % non-Hispanic White), HbA1c was collected for 1060 individuals (mean HbA1c 9.2 % ± 2.0 %). The prevalence of HFI was 16.4 %. In the past 12 months, 18.2 % and 9.9 % reported an episode of DKA or severe hypoglycemia, respectively. Compared to participants who were food secure, HFI was associated with a 0.33 % (95 % CI 0.003, 0.657) higher HbA1c level. Those with HFI had 1.58 (95 % CI 1.13, 2.21) times the adjusted odds of an episode of DKA and 1.53 (95 % CI 0.99, 2.37) times the adjusted odds of an episode of severe hypoglycemia as those without HFI. CONCLUSIONS: HFI is associated with higher HbA1c levels and increased odds of DKA in YYA with T1D.

Diabetes Stigma and Clinical Outcomes in Adolescents and Young Adults: The SEARCH for Diabetes in Youth Study.

OBJECTIVE: To examine the association between diabetes stigma and HbA1c, treatment plan and acute and chronic complications in adolescents and young adults (AYAs) with type 1 or type 2 diabetes. RESEARCH DESIGN AND METHODS: The SEARCH for Diabetes in Youth study is a multicenter cohort study that collected questionnaire, laboratory, and physical examination data about AYAs with diabetes diagnosed in childhood. A five-question survey assessed frequency of perceived diabetes-related stigma, generating a total diabetes stigma score. We used multivariable linear modeling, stratified by diabetes type, to examine the association of diabetes stigma with clinical factors, adjusting for sociodemographic characteristics, clinic site, diabetes duration, health insurance, treatment plan, and HbA1c. RESULTS: Of 1,608 respondents, 78% had type 1 diabetes, 56% were female, and 48% were non-Hispanic White. The mean (SD) age at study visit was 21.7 (5.1) years (range, 10-24.9). The mean (SD) HbA1c was 9.2% (2.3%; 77 mmol/mol [2.0 mmol/mol]). Higher diabetes stigma scores were associated with female sex and higher HbA1c (P < 0.01) for all participants. No significant association between diabetes stigma score and technology use was observed. In participants with type 2 diabetes, higher diabetes stigma scores were associated with insulin use (P = 0.04). Independent of HbA1c, higher diabetes stigma scores were associated with some acute complications for AYAs with type 1 diabetes and some chronic complications for AYAs with type 1 or type 2 diabetes. CONCLUSIONS: Diabetes stigma in AYAs is associated with worse diabetes outcomes and is important to address when providing comprehensive diabetes care.

A longitudinal assessment of diabetes autoantibodies in the SEARCH for diabetes in youth study.

To assess changes in diabetes autoantibodies (DAs) over time in children and young adults with diabetes and determine whether observed changes were associated with demographic characteristics, clinical parameters and diabetes complications. Participants had DAs measured at baseline (10.3 ± 7.1 months after diabetes diagnosis) and at 12, 24 months and ≥5 years after the baseline measurement. At the ≥5-year follow-up, the presence of diabetes complications was assessed. We examined the associations between change in number of positive DAs and changes in individual DA status with the participants' characteristics and clinical parameters over time. Out of 4179 participants, 62% had longitudinal DA data and 51% had complications and longitudinal DA data. In participants with ≥1 baseline positive DA (n = 1699), 83.4% remained positive after 7.3 ± 2.3 years duration of diabetes. Decrease in number of positive DAs was associated with longer diabetes duration (p = 0.003 for 1 baseline positive DA; p < 0.001 for 2 baseline positive DAs) and younger age at diagnosis (p < 0.001 for 2 baseline positive DAs). No associations were found between change in number of positive DAs in participants with ≥1 baseline positive DA (n = 1391) and HbA1c, insulin dose, acute, or chronic complications after 7.7 ± 1.9 years duration of diabetes. DA status likely remains stable in the first 7 years after diabetes diagnosis. Younger age at diabetes diagnosis and longer duration were associated with less persistence of DAs. Measuring DAs after initial presentation may aid in diabetes classification but not likely in predicting the clinical course.

Disparities in Hemoglobin A1c Testing During the Transition to Adulthood and Association With Diabetes Outcomes in Youth-Onset Type 1 and Type 2 Diabetes: The SEARCH for Diabetes in Youth Study.

OBJECTIVE: To identify correlates of hemoglobin A1c (HbA1c) testing frequency and associations with HbA1c levels and microvascular complications in youth-onset diabetes. RESEARCH DESIGN AND METHODS: The SEARCH for Diabetes in Youth study collected data from individuals diagnosed with diabetes before age 20 at 8 years (n=1,885 type 1, n=230 type 2) and 13 years (n=649 type 1, n = 84 type 2) diabetes duration. We identified correlates of reporting ≥3 HbA1c tests/year using logistic regression. We examined associations of HbA1c testing with HbA1c levels and microvascular complications (retinopathy, neuropathy, or nephropathy) using sequentially adjusted linear and logistic regression. RESULTS: For type 1 diabetes, odds of reporting ≥3 HbA1c tests/year at 8 and 13 years diabetes duration decreased with older age at diagnosis (odds ratio [OR] 0.91 [95% CI 0.88-0.95]), longer duration of diabetes (OR 0.90 [0.82-0.99]), not having a personal doctor (OR 0.44 [0.30-0.65]), and lapses in health insurance (OR 0.51 [0.27-0.96]). HbA1c testing ≥3 times/year over time was associated with lower HbA1c levels (OR -0.36% [-0.65 to -0.06]) and lower odds of microvascular complications (OR 0.64 [0.43-0.97]) at 13 years duration, but associations were attenuated after adjustment for HbA1c testing correlates (OR -0.17 [-0.46 to 0.13] and 0.70 [0.46-1.07], respectively). For type 2 diabetes, not seeing an endocrinologist decreased the odds of reporting ≥3 HbA1c tests/year over time (OR 0.19 [0.06-0.63]), but HbA1c testing frequency was not associated with HbA1c levels or microvascular complications. CONCLUSIONS: We observed disparities in HbA1c testing frequency predominately by health care-related factors, which were associated with diabetes outcomes in type 1 diabetes.

Genetic Tools for Coronary Risk Assessment in Type 2 Diabetes: A Cohort Study From the ACCORD Clinical Trial.

OBJECTIVE: We evaluated whether the increasing number of genetic loci for coronary artery disease (CAD) identified in the general population could be used to predict the risk of major CAD events (MCE) among participants with type 2 diabetes at high cardiovascular risk. RESEARCH DESIGN AND METHODS: A weighted genetic risk score (GRS) derived from 204 variants representative of all the 160 CAD loci identified in the general population as of December 2017 was calculated in 5,360 and 1,931 white participants in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) and Outcome Reduction With Initial Glargine Intervention (ORIGIN) studies, respectively. The association between GRS and MCE (combining fatal CAD events, nonfatal myocardial infarction, and unstable angina) was assessed by Cox proportional hazards regression. RESULTS: The GRS was associated with MCE risk in both ACCORD and ORIGIN (hazard ratio [HR] per SD 1.27, 95% CI 1.18-1.37, P = 4 × 10-10, and HR per SD 1.35, 95% CI 1.16-1.58, P = 2 × 10-4, respectively). This association was independent from interventions tested in the trials and persisted, though attenuated, after adjustment for classic cardiovascular risk predictors. Adding the GRS to clinical predictors improved incident MCE risk classification (relative integrated discrimination improvement +8%, P = 7 × 10-4). The performance of this GRS was superior to that of GRS based on the smaller number of CAD loci available in previous years. CONCLUSIONS: When combined into a GRS, CAD loci identified in the general population are associated with CAD also in type 2 diabetes. This GRS provides a significant improvement in the ability to correctly predict future MCE, which may increase further with the discovery of new CAD loci.

Prevalence of and disparities in barriers to care experienced by youth with type 1 diabetes.

OBJECTIVE: To describe the prevalence of access and process barriers to health care and to examine their relationship to sociodemographic and disease factors in a large and diverse cohort of US youth with type 1 diabetes. STUDY DESIGN: A cross-sectional analysis of 780 youth who participated in the SEARCH for Diabetes in Youth Study and were diagnosed with type 1 diabetes in 2002-2005. Experience of barriers to care was collected from parent report on questionnaires. Analyses included multivariate regression models to predict the presence of specific barriers to care. RESULTS: Overall, 81.7% of participants reported at least one barrier; the 3 most common were costs (47.5%), communication (43.0%), and getting needed information (48.4%). Problems with access to care, not having a regular provider, and receiving contextual care (care that takes into account personal and family context) were associated with poorer glycated hemoglobin levels. Adjusted multivariate models indicated that barriers related to access (regular provider, cost) were most likely for youth with low family income and those without public health insurance. Barriers associated with the processes of quality care (contextual care, communication) were more likely for Hispanic youth and those whose parents had less education. CONCLUSIONS: This study indicates that a large proportion of youth with type 1 diabetes experience substantial barriers to care. Barriers to access and those associated with processes of quality care differed by sociodemographic characteristics. Future investigators should expand knowledge of the systemic processes that lead to disparate outcomes for some youth with diabetes and assess potential solutions.

The burden of diabetes mellitus among US youth: prevalence estimates from the SEARCH for Diabetes in Youth Study.

OBJECTIVE: Our goal was to estimate the prevalence of diabetes mellitus in youth <20 years of age in 2001 in the United States, according to age, gender, race/ethnicity, and diabetes type. METHODS: The SEARCH for Diabetes in Youth Study is a 6-center observational study conducting population-based ascertainment of physician-diagnosed diabetes in youth. Census-based denominators for 4 geographically based centers and enrollment data for 2 health plan-based centers were used to calculate prevalence. Age-, gender-, and racial/ethnic group-specific prevalence rates were multiplied by US population counts to estimate the total number of US youth with diabetes. RESULTS: We identified 6379 US youth with diabetes in 2001, in a population of approximately 3.5 million. Crude prevalence was estimated as 1.82 cases per 1000 youth, being much lower for youth 0 to 9 years of age (0.79 cases per 1000 youth) than for those 10 to 19 years of age (2.80 cases per 1000 youth). Non-Hispanic white youth had the highest prevalence (1.06 cases per 1000 youth) in the younger group. Among 10- to 19-year-old youth, black youth (3.22 cases per 1000 youth) and non-Hispanic white youth (3.18 cases per 1000 youth) had the highest rates, followed by American Indian youth (2.28 cases per 1000 youth), Hispanic youth (2.18 cases per 1000 youth), and Asian/Pacific Islander youth (1.34 cases per 1000 youth). Among younger children, type 1 diabetes accounted for > or = 80% of diabetes; among older youth, the proportion of type 2 diabetes ranged from 6% (0.19 cases per 1000 youth for non-Hispanic white youth) to 76% (1.74 cases per 1000 youth for American Indian youth). We estimated that 154,369 youth had physician-diagnosed diabetes in 2001 in the United States. CONCLUSIONS: The overall prevalence estimate for diabetes in children and adolescents was approximately 0.18%. Type 2 diabetes was found in all racial/ethnic groups but generally was less common than type 1, except in American Indian youth.

A critical evaluation of the role of Lp(a) in cardiovascular disease: can Lp(a) be useful in risk assessment?

Lp(a) is a structurally complex particle which resembles LDL, but which also contains the distinctive glycoprotein apo(a). Apo(a) is characterized by a variable number of repeated kringle domains, which gives rise to differently-sized Lp(a) isoforms in the population. Although epidemiological studies indicate that elevated Lp(a) concentration and/or small apo(a) isoform sizes increase the risk of coronary heart disease (CHD), a causal role for Lp(a) in CHD remains unproven. This is largely due to the difficulty in establishing a relevant animal model to probe Lp(a) function, and the lack of intervention studies in which Lp(a) concentrations are lowered and outcomes followed. The accumulation of apo(a)/Lp(a) in arterial lesions has provided the rationale for numerous in vitro studies aimed at dissecting its function in this milieu. These studies have resulted in the proposal of numerous proatherogenic, prothrombotic and antifibrinolytic roles for both native and modified apo(a)/Lp(a). Although characterization of Lp(a) in the general population is not presently justified, Lp(a) analysis in patients at risk for CHD may be warranted.