OBJECTIVE: To estimate lifetime incremental medical spending attributed to incident type 2 diabetes (T2D) among Medicare beneficiaries by age at diagnosis, sex, and race/ethnicity. RESEARCH DESIGN AND METHODS: We used the 1999-2019 100% Medicare fee-for-service claims database to identify a cohort of beneficiaries with newly diagnosed T2D in 2001-2003 using ICD codes. We matched this cohort with a nondiabetes cohort using a propensity score method and then followed the two cohorts until death, disenrollment, or the end of 2019. Lifetime medical spending for each cohort was the sum of expected annual spending, a product of actual annual spending multiplied by the annual survival rate, from the age at T2D diagnosis to death. Lifetime incremental medical spending was calculated as the difference in lifetime medical spending between the two cohorts. All spending was standardized to 2019 U.S. dollars. RESULTS: Medicare beneficiaries with newly diagnosed T2D, despite having a shorter life expectancy, had 36-40% higher lifetime medical spending compared with a comparable group without diabetes. Lifetime incremental medical spending ranged from $16,115 to $122,146, depending on age at diagnosis, sex, and race/ethnicity, declining with age at diagnosis, and being highest for Asian/Pacific Islander and non-Hispanic Black beneficiaries. CONCLUSIONS: The large lifetime incremental medical spending associated with incident T2D underscores the need for preventing T2D among Medicare beneficiaries. Our results could be used to estimate the potential financial benefit of T2D prevention programs both overall and among subgroups of beneficiaries.

OBJECTIVE: To compare total and out-of-pocket (OOP) medical expenditures between pre-COVID-19 (March 2019 to February 2020) and COVID-19 (March 2020 to February 2022) periods among Medicare beneficiaries with diabetes. RESEARCH DESIGN AND METHODS: Data were from 100% Medicare fee-for-service claims. Diabetes was identified using ICD-10 codes. We calculated quarterly total and OOP medical expenditures at the population and per capita level in total and by service type. Per capita expenditures were calculated by dividing the population expenditure by the number of beneficiaries with diabetes in the same quarter. Changes in expenditures were calculated as the differences in the same quarters between the prepandemic and pandemic years. RESULTS: Population total expenditure fell to $33.6 billion in the 1st quarter of the pandemic from $41.7 billion in the same prepandemic quarter; it then bounced back to $36.8 billion by the 4th quarter of the 2nd pandemic year. The per capita total expenditure fell to $5,356 in the 1st quarter of the pandemic from $6,500 in the same prepandemic quarter. It then increased to $6,096 by the 4th quarter of the 2nd pandemic year, surpassing the same quarter in the prepandemic year ($5,982). Both population and per capita OOP expenditures during the pandemic period were lower than the prepandemic period. Changes in per capita expenditure between the pre-COVID-19 and COVID-19 periods by service type varied. CONCLUSIONS: COVID-19 had a significant impact on both total and per capita medical expenditures among Medicare beneficiaries with diabetes. The COVID-19 pandemic was associated with lower OOP expenditures.

INTRODUCTION: Traditional survey-based surveillance is costly, limited in its ability to distinguish diabetes types and time-consuming, resulting in reporting delays. The Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network seeks to advance diabetes surveillance efforts in youth and young adults through the use of large-volume electronic health record (EHR) data. The network has two primary aims, namely: (1) to refine and validate EHR-based computable phenotype algorithms for accurate identification of type 1 and type 2 diabetes among youth and young adults and (2) to estimate the incidence and prevalence of type 1 and type 2 diabetes among youth and young adults and trends therein. The network aims to augment diabetes surveillance capacity in the USA and assess performance of EHR-based surveillance. This paper describes the DiCAYA Network and how these aims will be achieved. METHODS AND ANALYSIS: The DiCAYA Network is spread across eight geographically diverse US-based centres and a coordinating centre. Three centres conduct diabetes surveillance in youth aged 0-17 years only (component A), three centres conduct surveillance in young adults aged 18-44 years only (component B) and two centres conduct surveillance in components A and B. The network will assess the validity of computable phenotype definitions to determine diabetes status and type based on sensitivity, specificity, positive predictive value and negative predictive value of the phenotypes against the gold standard of manually abstracted medical charts. Prevalence and incidence rates will be presented as unadjusted estimates and as race/ethnicity, sex and age-adjusted estimates using Poisson regression. ETHICS AND DISSEMINATION: The DiCAYA Network is well positioned to advance diabetes surveillance methods. The network will disseminate EHR-based surveillance methodology that can be broadly adopted and will report diabetes prevalence and incidence for key demographic subgroups of youth and young adults in a large set of regions across the USA.

INTRODUCTION: Screening for prediabetes and type 2 diabetes may allow earlier detection, diagnosis, and treatment. The US Preventive Services Task Force recommends screening every 3 years for abnormal blood glucose among adults aged 40 to 70 years with overweight or obesity. Using IQVIA Ambulatory Electronic Medical Records, we estimated the proportion of adults aged 40 to 70 years with overweight or obesity who received blood glucose testing within 3 years from baseline in 2016. METHODS: We identified 1,338,509 adults aged 40 to 70 years with overweight or obesity in 2016 and without pre-existing diabetes. We included adults whose records were present in the data set for at least 2 years before their index body mass index (BMI) in 2016 and 3 years after the index BMI (2017-2019), during which we examined the occurrence of blood glucose testing. We calculated the unadjusted and adjusted prevalence of receiving blood glucose testing. RESULTS: The unadjusted prevalence of receiving blood glucose testing was 33.4% when it was defined as having a hemoglobin A(1c) or fasting plasma glucose measure. The unadjusted prevalence was 74.3% when we expanded the definition of testing to include random plasma glucose and unspecified glucose measures. Adults with obesity were more likely to receive the test than those with overweight. Men (vs women) and adults aged 50 to 59 years (vs other age groups) had higher testing rates. CONCLUSION: Our findings could inform clinical and public health promotion efforts to improve screening for blood glucose levels among adults with overweight or obesity.

BACKGROUND: Household food insecurity has been linked to adverse health outcomes, but pathways driving these associations are not well understood. The stress experienced by those in food insecure households and having to prioritize between food and other essential needs could lead to physiological dysregulations (i.e., allostatic load [AL]) and, as a result, adversely impact their health. OBJECTIVE: To assess the association between household food security status and AL and differences by gender, race and ethnicity, and Supplemental Nutrition Assistance Program (SNAP) participation. METHODS: We used data from 7640 US adults in the 2015-2016 and 2017-March 2020 National Health and Nutrition Examination Survey to estimate means and prevalence ratios (PR) for AL scores (based on cardiovascular, metabolic, and immune biomarkers) associated with self-reported household food security status from multivariable linear and logistic regression models. RESULTS: Adults in marginally food secure (mean = 3.09, SE = 0.10) and food insecure households (mean = 3.05, SE = 0.08) had higher mean AL than those in food secure households (mean = 2.70, SE = 0.05). Compared to adults in food secure households in the same category, those more likely to have an elevated AL included: SNAP participants (PR = 1.12; 95% confidence interval, CI = 1.03, 1.22) and Hispanic women (PR = 1.20; 95% CI = 1.05, 1.37) in marginally food secure households; and non-Hispanic Black women (PR = 1.14; 95% CI = 1.03, 1.26), men (PR = 1.13; 95% CI = 1.02, 1.26), and non-SNAP non-Hispanic White adults (PR = 1.22; 95% CI = 1.08, 1.39) in food insecure households. CONCLUSIONS: AL may be one pathway by which household food insecurity affects health and may vary by gender, race and ethnicity, and SNAP participation.

Fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) are both used to diagnose diabetes, but these measurements can identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening, had elevated FPG, HbA1c or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardized proportion of diabetes that was previously undiagnosed and detected in survey screening ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the age-standardized proportion who had elevated levels of both FPG and HbA1c was 29-39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c was more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global shortfall in diabetes diagnosis and surveillance.

The epidemic of diabetes continues to exert great burden and cost on affected people, their families, and society. Current estimates of the burden of prediabetes and diabetes in youth and adults for the U.S. are made available through the Centers for Disease Control and Prevention (CDC) (https://www.cdc.gov/diabetes/data/statistics-report/index.html and https://gis.cdc.gov/grasp/diabetes/DiabetesAtlas.html) and for regions of the world by the International Diabetes Federation (https://diabetesatlas.org/2022-reports/). These data are typically updated every year or two. | | CDC’s estimates for the prevalence of both diagnosed and undiagnosed diabetes, prevalence of prediabetes among adults, incidence of newly diagnosed diabetes, risk factors for diabetes-related complications, and burden of coexisting conditions and complications provide valuable information, but many questions are not addressed in these national data. Therefore, commencing with this month’s issue, Diabetes Care and CDC begin a partnership to enhance knowledge among the journal’s readership by highlighting important aspects of the national burden of diabetes that expand upon the data and information provided on the CDC’s website. Through this collaboration, we will at least twice a year publish in Diabetes Care in-depth explorations of timely and clinically significant topics authored by members of CDC. As with all original manuscripts submitted to Diabetes Care, they will undergo peer review to ensure they are scientifically rigorous and informative.

Aims. Celiac disease (CD) in adults with type 1 diabetes has been associated with increased cardiovascular risk and the earlier occurrence of diabetes-associated complications. In the Search for Diabetes in Youth study, we aimed to assess the frequency of CD and the potential for undiagnosed CD among youth with childhood onset type 1 diabetes. In addition, we assessed the burden of cardiovascular risk factors and diabetes-associated complications in youth with type 1 diabetes by CD status and IgA tissue transglutaminase autoantibody (tTGA) levels. Methods. 2,444 youths with type 1 diabetes completed a CD questionnaire and underwent tTGA testing. Integrating the celiac disease questionnaire and tTGA results for this cross-sectional analysis, participants were categorized as follows: (1) reported CD; (2) seropositive for CD (no reported CD and seropositive tTGA); and (3) type 1 diabetes only (comparison group: no reported CD and seronegative tTGA). Subanalyses were performed on those with no reported CD and tTGA ≥10x ULN, designated potentially undiagnosed CD. Cardiovascular risk factors and diabetes-associated complications were evaluated by CD status and tTGA levels utilizing a Poisson model to estimate relative risk. Results. Reported CD in youths with type 1 diabetes was 7%. Seropositivity for tTGA with no reported CD was present in 4%, and 1.2% had potentially undiagnosed CD. Youths with potentially undiagnosed CD had a 2.69x higher risk of diabetic retinopathy than comparison group. In addition, CD with tTGA <0.05 (controlled CD) was associated with lower HbA1c. Conclusions. Undiagnosed CD is likely present in youths with type 1 diabetes and potentially undiagnosed CD is associated with a higher risk of diabetic retinopathy. These findings indicate the importance of routine screening for CD in type 1 diabetes in youths. © 2023 Ryan P. Brady et al.

INTRODUCTION: The American Diabetes Association (ADA) recommends screening for prediabetes and diabetes (dysglycemia) starting at age 35, or younger than 35 years among adults with overweight or obesity and other risk factors. Diabetes risk differs by sex, race, and ethnicity, but performance of the recommendation in these sociodemographic subgroups is unknown. METHODS: Nationally representative data from the National Health and Nutrition Examination Surveys (2015-March 2020) were analyzed from 5,287 nonpregnant US adults without diagnosed diabetes. Screening eligibility was based on age, measured body mass index, and the presence of diabetes risk factors. Dysglycemia was defined by fasting plasma glucose ≥100mg/dL (≥5.6 mmol/L) or haemoglobin A1c ≥5.7% (≥39mmol/mol). The sensitivity, specificity, and predictive values of the ADA screening criteria were examined by sex, race, and ethnicity. RESULTS: An estimated 83.1% (95% CI=81.2-84.7) of US adults were eligible for screening according to the 2023 ADA recommendation. Overall, ADA's screening criteria exhibited high sensitivity [95.0% (95% CI=92.7-96.6)] and low specificity [27.1% (95% CI=24.5-29.9)], which did not differ by race or ethnicity. Sensitivity was higher among women [97.8% (95% CI=96.6-98.6)] than men [92.4% (95% CI=88.3-95.1)]. Racial and ethnic differences in sensitivity and specificity among men were statistically significant (P=0.04 and P=0.02, respectively). Among women, guideline performance did not differ by race and ethnicity. DISCUSSION: The ADA screening criteria exhibited high sensitivity for all groups and was marginally higher in women than men. Racial and ethnic differences in guideline performance among men were small and unlikely to have a significant impact on health equity. Future research could examine adoption of this recommendation in practice and examine its effects on treatment and clinical outcomes by sex, race, and ethnicity.

Successful transition from a pediatric to adult diabetes care provider is associated with reduced ambulatory diabetes care visits and increased acute complications. This study aimed to determine whether the degree of independence in diabetes care and the rate of acute complications after transition to adult diabetes care were associated with individuals' student or employment status. Nonstudents were found to be less likely than students to be independent with diabetes care, and employed nonstudents were at lower risk of diabetic ketoacidosis than unemployed nonstudents. Additional support may be needed for young adults who are not students or are unemployed to improve independence and reduce the risk for acute complications.

INTRODUCTION: This study examined national trends in age, sex, racial and ethnic, and socioeconomic inequalities for diagnosed diabetes prevalence and incidence among US adults from 2008-2021. METHODS: Adults (≥18 years) were from the National Health Interview Survey (2008-2021). The annual between-group variance (BGV) for sex, race, and ethnicity, and the slope index of inequality (SII) for age, education, and poverty-to-income ratio (PIR) along with the average annual percent change (AAPC) were estimated in 2023 to assess trends in inequalities over time in diabetes prevalence and incidence. For BGV and SII, a value of 0 represents no inequality while a value further from 0 represents greater inequality. RESULTS: On average over time, PIR inequalities in diabetes prevalence worsened (SII: -8.24 in 2008 and -9.80 in 2021; AAPC for SII: -1.90%, p=0.003) while inequalities in incidence for age (SII: 17.60 in 2008 and 8.85 in 2021; AAPC for SII: -6.47%, p<0.001), sex (BGV: 0.09 in 2008, 2.05 in 2009, 1.24 in 2010, and 0.27 in 2021; AAPC for BGV: -12.34%, p=0.002), racial and ethnic (BGV: 4.80 in 2008 and 2.17 in 2021; AAPC for BGV: -10.59%, p=0.010), and education (SII: -9.89 in 2008 and -2.20 in 2021; AAPC for SII: 8.27%, p=0.001) groups improved. CONCLUSIONS: From 2008-2021, age, sex, racial and ethnic, and education inequalities in the incidence of diagnosed diabetes improved but persisted. Income-related diabetes prevalence inequalities worsened over time. To close these gaps, future research could focus on identifying factors driving these trends including the contribution of morbidity and mortality.

Background Growing evidence suggests incident cardiovascular disease (CVD) may be a long-term outcome of COVID-19 infection, and chronic diseases, such as diabetes, may influence CVD risk associated with COVID-19. We evaluated the postacute risk of CVD >30 days after a COVID-19 diagnosis by diabetes status. Methods and Results We included adults ≥20 years old with a COVID-19 diagnosis from March 1, 2020 through December 31, 2021 in a retrospective cohort study from the IQVIA PharMetrics Plus insurance claims database. A contemporaneous control group comprised adults without recorded diagnoses for COVID-19 or other acute respiratory infections. Two historical control groups comprised patients with or without an acute respiratory infection. Cardiovascular outcomes included cerebrovascular disorders, dysrhythmia, inflammatory heart disease, ischemic heart disease, thrombotic disorders, other cardiac disorders, major adverse cardiovascular events, and any CVD. The total sample comprised 23 824 095 adults (mean age, 48.4 years [SD, 15.7 years]; 51.9% women; mean follow-up, 8.5 months [SD, 5.8 months]). In multivariable Cox regression models, patients with a COVID-19 diagnosis had a significantly greater risk of all cardiovascular outcomes compared with patients without a diagnosis of COVID-19 (hazard ratio [HR], 1.66 [1.62-1.71], with diabetes; HR, 1.75 [1.73-1.78], without diabetes). Risk was attenuated but still significant for the majority of outcomes when comparing patients with COVID-19 to both historical control groups. Conclusions In patients with COVID-19 infection, postacute risk of incident cardiovascular outcomes is significantly higher than among controls without COVID-19, regardless of diabetes status. Therefore, monitoring for incident CVD may be essential beyond the first 30 days after a COVID-19 diagnosis.

IMPORTANCE: The coronavirus 2019 (COVID-19) pandemic abruptly impacted health care service delivery and utilization. However, the impact on older adults with diabetes in the United States is unclear. OBJECTIVE: To estimate changes in health care utilization among older adults with diabetes during the initial 2 years of the COVID-19 pandemic compared to the 2 years before, and to examine the variation in utilization changes by demographic and socioeconomic characteristics. DESIGN SETTING AND PARTICIPANTS: In this study, we analyzed changes in utilization, measured by the average use of health care services per 1,000 persons with diabetes, using medical claims for Medicare fee-for-service beneficiaries aged 67 years and above. Utilization changes by setting (acute inpatient, emergency room [ER], hospital outpatient, physician office, and ambulatory surgery center [ASC]) and by media (telehealth and in-person) were examined for 22 months of the pandemic (03/2020-12/2021) compared with pre-pandemic period (03/2018-12/2019). We also estimated utilization changes by beneficiaries' age group, sex, race/ethnicity, and residential urbanicity. RESULTS: The study sample consisted of approximately 6 million beneficiaries with diabetes each month. In the first 2 years of the pandemic, the average use of health care services by setting was 5-17% lower than the pre-pandemic level for all types of services. Phase 1 (03/2020-05/2020) had the largest decrease in utilization: physician office visits changed by -51.2% (95% CI, -55.0% to -47.5%), ASC procedures by -45.1% (95% CI, -49.8% to -40.4%), ER visits by -36.9% (95% CI, -39.0% to -34.7%), acute inpatient stays by -31.5% (95% CI, -33.6% to -29.3%), and hospital outpatient visits by -27% (95% CI, -29.3% to -24.8%). The reduction in utilization varied by sociodemographic subgroup. During the pandemic, the use of telehealth visits increased by 511.1% (95% CI, 502.2% to 520.0%) compared to the pre-pandemic period. The increase was smaller among rural residents. CONCLUSIONS AND RELEVANCE: Medicare beneficiaries with diabetes experienced a reduction in the use of health care services during the COVID-19 pandemic, some of which persisted through two years into the pandemic. Telehealth visits increased, but not enough to overcome decreases in in-person visits. Understanding these patterns may help to optimize the use of health care resources for diabetes management in the post-pandemic era and during future emergencies.

INTRODUCTION: In 2021, the U.S. Preventive Services Task Force (USPSTF) recommended prediabetes and diabetes screening for asymptomatic adults aged 35-70 years with overweight/obesity, lowering the age from 40 years in its 2015 recommendation. The USPSTF suggested considering earlier screening in racial and ethnic groups with high diabetes risk at younger ages or lower BMI. This study examined the clinical performance of these USPSTF screening recommendations as well as alternative age and BMI cutoffs in the U.S. adult population overall, and separately by race and ethnicity. METHODS: Nationally representative data were collected from 3,243 nonpregnant adults without diagnosed diabetes in January 2017-March 2020 and analyzed from 2021 to 2022. Screening eligibility was based on age and measured BMI. Collectively, prediabetes and undiagnosed diabetes were defined by fasting plasma glucose ≥100 mg/dL or hemoglobin A(1c) ≥5.7%. The sensitivity, specificity, and predictive values of alternate screening criteria were examined overall, and by race and ethnicity. RESULTS: The 2021 criteria exhibited marginally higher sensitivity (58.6%, 95% CI=55.5, 61.6 vs 52.9%, 95% CI=49.7, 56.0) and lower specificity (69.3%, 95% CI=65.7, 72.2 vs 76.4%, 95% CI=73.3, 79.2) than the 2015 criteria overall, and within each racial and ethnic group. Screening at lower age and BMI thresholds resulted in even greater sensitivity and lower specificity, especially among Hispanic, non-Hispanic Black, and Asian adults. Screening all adults aged 35-70 years regardless of BMI yielded the most equitable performance across all racial and ethnic groups. CONCLUSIONS: The 2021 USPSTF screening criteria will identify more adults with prediabetes and diabetes in all racial and ethnic groups than the 2015 criteria. Screening all adults aged 35-70 years exhibited even higher sensitivity and performed most similarly by race and ethnicity, which may further improve early detection of prediabetes and diabetes in diverse populations.

We thank Manicardi et al. (1) for their insightful discussion of potential factors affecting our study of cardiovascular disease (CVD) mortality trends in the population with diabetes (2). Changes in diagnostic criteria and early detection of diabetes could indeed have affected the risk level and changes in rates of CVD differentially over time. We further agree that the population today is likely much different from that in the 1980s, perhaps due to the significant increases in obesity among the population with diabetes, which could influence risk as well. However, we caution that there is limited direct evidence that significant increases in detection have led to a healthier population or that the risk level at diagnosis has changed at a rate higher than the risk level of the underlying population (3). The impact of the 1997 change in diabetes definition and early detection of diabetes is also unknown but unlikely to explain the steady 12-year increase in incidence that occurred after that. Although we lack the appropriate data to quantify the impact of changing underlying risk directly, our indirect sensitivity analyses of these effects in the current report suggest that the impact of any lead-time bias on these trends was modest in comparison with the reductions that occurred (2). That said, the points raised by Manicardi et al. are important and underscore the need for more comprehensive epidemiologic data to understand the transitions underway in diabetes complications.

This article describes a significant decline in emergency department visits for acute life-threatening conditions during the COVID-19 pandemic, suggesting that patients may be delaying or avoiding care or unable to access care during the pandemic.

AIMS: The overall prevalence of diabetes has increased over the past two decades in the United States, disproportionately affecting low-income populations. We aimed to examine the trends in income-related inequalities in diabetes prevalence and to identify the contributions of determining factors. METHODS: We estimated income-related inequalities in diagnosed diabetes during 2001-2018 among US adults aged 18 years or older using data from the National Health Interview Survey (NHIS). The concentration index was used to measure income-related inequalities in diabetes and was decomposed into contributing factors. We then examined temporal changes in diabetes inequality and contributors to those changes over time. RESULTS: Results showed that income-related inequalities in diabetes, unfavorable to low-income groups, persisted throughout the study period. The income-related inequalities in diabetes decreased during 2001-2011 and then increased during 2011-2018. Decomposition analysis revealed that income, obesity, physical activity levels, and race/ethnicity were important contributors to inequalities in diabetes at almost all time points. Moreover, changes regarding age and income were identified as the main factors explaining changes in diabetes inequalities over time. CONCLUSIONS: Diabetes was more prevalent in low-income populations. Our study contributes to understanding income-related diabetes inequalities and could help facilitate program development to prevent type 2 diabetes and address modifiable factors to reduce diabetes inequalities.

Background: Youth with excess weight are at risk of developing type 2 diabetes (T2DM). Guidelines recommend screening for prediabetes and/or T2DM after 10 years of age or after puberty in youth with excess weight who have ≥1 risk factor(s) for T2DM. Electronic health records (EHRs) offer an opportunity to study the use of tests to detect diabetes in youth. Methods: We examined the frequency of (1) diabetes testing and (2) elevated test results among youth aged 10-19 years with at least one BMI measurement in an EHR from 2019 to 2021. We examined the presence of hemoglobin A1C (A1C), fasting plasma glucose (FPG), or oral glucose tolerance test (2-hour plasma glucose [2-hrPG]) results and, among those tested, the frequency of elevated values (A1C ≥6.5%, FPG ≥126 mg/dL, or 2-hrPG ≥200 mg/dL). Patients with pre-existing diabetes (n = 6793) were excluded. Results: Among 1,024,743 patients, 17% had overweight, 21% had obesity, including 8% with severe obesity. Among patients with excess weight, 10% had ≥1 glucose test result. Among those tested, elevated values were more common in patients with severe obesity (27%) and obesity (22%) than in those with healthy weight (8%), and among Black youth (30%) than White youth (13%). Among patients with excess weight, >80% of elevated values fell in the prediabetes range. Conclusions: In youth with excess weight, the use of laboratory tests for prediabetes and T2DM was infrequent. Among youth with test results, elevated FPG, 2hrPG, or A1C levels were most common in those with severe obesity and Black youth.

BACKGROUND: The incidence of diabetes is increasing in children and young people. We aimed to describe the incidence of type 1 and type 2 diabetes in children and young people aged younger than 20 years over a 17-year period. METHODS: The SEARCH for Diabetes in Youth study identified children and young people aged 0-19 years with a physician diagnosis of type 1 or type 2 diabetes at five centres in the USA between 2002 and 2018. Eligible participants included non-military and non-institutionalised individuals who resided in one of the study areas at the time of diagnosis. The number of children and young people at risk of diabetes was obtained from the census or health plan member counts. Generalised autoregressive moving average models were used to examine trends, and data are presented as incidence of type 1 diabetes per 100 000 children and young people younger than 20 years and incidence of type 2 diabetes per 100 000 children and young people aged between 10 years and younger than 20 years across categories of age, sex, race or ethnicity, geographical region, and month or season of diagnosis. FINDINGS: We identified 18 169 children and young people aged 0-19 years with type 1 diabetes in 85 million person-years and 5293 children and young people aged 10-19 years with type 2 diabetes in 44 million person-years. In 2017-18, the annual incidence of type 1 diabetes was 22·2 per 100 000 and that of type 2 diabetes was 17·9 per 100 000. The model for trend captured both a linear effect and a moving-average effect, with a significant increasing (annual) linear effect for both type 1 diabetes (2·02% [95% CI 1·54-2·49]) and type 2 diabetes (5·31% [4·46-6·17]). Children and young people from racial and ethnic minority groups such as non-Hispanic Black and Hispanic children and young people had greater increases in incidence for both types of diabetes. Peak age at diagnosis was 10 years (95% CI 8-11) for type 1 diabetes and 16 years (16-17) for type 2 diabetes. Season was significant for type 1 diabetes (p=0·0062) and type 2 diabetes (p=0·0006), with a January peak in diagnoses of type 1 diabetes and an August peak in diagnoses of type 2 diabetes. INTERPRETATION: The increasing incidence of type 1 and type 2 diabetes in children and young people in the USA will result in an expanding population of young adults at risk of developing early complications of diabetes whose health-care needs will exceed those of their peers. Findings regarding age and season of diagnosis will inform focused prevention efforts. FUNDING: US Centers for Disease Control and Prevention and US National Institutes of Health.

INTRODUCTION: Inequitable access to leisure-time physical activity (LTPA) resources may explain geographic disparities in type 2 diabetes (T2D). We evaluated whether the neighborhood socioeconomic environment (NSEE) affects T2D through the LTPA environment. RESEARCH DESIGN AND METHODS: We conducted analyses in three study samples: the national Veterans Administration Diabetes Risk (VADR) cohort comprising electronic health records (EHR) of 4.1 million T2D-free veterans, the national prospective cohort REasons for Geographic and Racial Differences in Stroke (REGARDS) (11 208 T2D free), and a case-control study of Geisinger EHR in Pennsylvania (15 888 T2D cases). New-onset T2D was defined using diagnoses, laboratory and medication data. We harmonized neighborhood-level variables, including exposure, confounders, and effect modifiers. We measured NSEE with a summary index of six census tract indicators. The LTPA environment was measured by physical activity (PA) facility (gyms and other commercial facilities) density within street network buffers and population-weighted distance to parks. We estimated natural direct and indirect effects for each mediator stratified by community type. RESULTS: The magnitudes of the indirect effects were generally small, and the direction of the indirect effects differed by community type and study sample. The most consistent findings were for mediation via PA facility density in rural communities, where we observed positive indirect effects (differences in T2D incidence rates (95% CI) comparing the highest versus lowest quartiles of NSEE, multiplied by 100) of 1.53 (0.25, 3.05) in REGARDS and 0.0066 (0.0038, 0.0099) in VADR. No mediation was evident in Geisinger. CONCLUSIONS: PA facility density and distance to parks did not substantially mediate the relation between NSEE and T2D. Our heterogeneous results suggest that approaches to reduce T2D through changes to the LTPA environment require local tailoring.

AIMS: Recent USPSTF and ADA guidelines expanded criteria of whom to test to identify prediabetes and diabetes. We described which Americans are eligible and report receiving glucose testing by USPSTF 2015 and 2021 as well as ADA 2003 and 2022 recommendations, and performance of each guideline. METHODS: We analyzed cross-sectional data from 6,007 non-pregnant U.S. adults without diagnosed diabetes in the 2013-2018 National Health and Nutrition Examination Surveys. We reported proportions of adults who met each guideline's criteria for glucose testing and reported receiving glucose testing in the past three years, overall and by key population subgroups,. Defining prediabetes (FPG 100-125mg/dL and/or HbA1c 5.7-6.4%) or previously undiagnosed diabetes (FPG≥126mg/dL and/or HbA1c≥6.5%), we assessed sensitivity and specificity. RESULTS: During 2013-2018, 76.7 million, 90.4 million, 157.7 million, and 169.5 million US adults met eligibility for glucose testing by USPSTF 2015, 2021, and ADA 2003 and 2022 guidelines, respectively. On average, 52% of adults reported receiving glucose testing within the past 3 years. Likelihood of receiving glucose testing was lower among younger adults, men, Hispanic adults, those with less than high school completion, those living in poverty, and those without health insurance or a usual place of care than their respective counterparts. ADA recommendations were most sensitive (range: 91.0% to 100.0%) and least specific (range: 18.3% to 35.3%); USPSTF recommendations exhibited lower sensitivity (51.9% to 66.6%), but higher specificity (56.6% to 74.5%). CONCLUSIONS: An additional 12-14 million US adults are eligible for diabetes screening. USPSTF 2021 criteria provide balanced sensitivity and specificity while ADA 2022 criteria maximize sensitivity. Glucose testing does not align with guidelines and disparities remain.

BACKGROUND: Incidence is one of the most important epidemiologic indices in surveillance. However, determining incidence is complex and requires time-consuming cohort studies or registries with date of diagnosis. Estimating incidence from prevalence using mathematical relationships may facilitate surveillance efforts. The aim of this study was to examine whether a partial differential equation (PDE) can be used to estimate diabetes incidence from prevalence in youth. METHODS: We used age-, sex-, and race/ethnicity-specific estimates of prevalence in 2001 and 2009 as reported in the SEARCH for Diabetes in Youth study. Using these data, a PDE was applied to estimate the average incidence rates of type 1 and type 2 diabetes for the period between 2001 and 2009. Estimates were compared to annual incidence rates observed in SEARCH. Precision of the estimates was evaluated using 95% bootstrap confidence intervals. RESULTS: Despite the long period between prevalence measures, the estimated average incidence rates mirror the average of the observed annual incidence rates. Absolute values of the age-standardized sex- and type-specific mean relative errors are below 8%. CONCLUSIONS: Incidence of diabetes can be accurately estimated from prevalence. Since only cross-sectional prevalence data is required, employing this methodology in future studies may result in considerable cost savings.

OBJECTIVE: Adults with diabetes are at risk for cardiovascular (CV) events, possibly due to increased arterial stiffness (AS) and cardiac autonomic neuropathy (CAN). We sought to determine whether 1) AS is associated with cardiac target organ damage in young adults with youth-onset diabetes, 2) whether CAN is associated with AS, as one possible etiology for increased AS in this cohort, and 3) whether these relationships differ by type of diabetes. RESEARCH DESIGN AND METHODS: Participants from the SEARCH for Diabetes in Youth Study (type 1 diabetes [T1D], n = 222; type 2 diabetes [T2D], n = 177; mean age 23 years) had clinical, echocardiographic, AS, and CAN assessed. Linear regression was performed to determine whether AS was associated with cardiac changes and CAN and whether relationships differed by diabetes type. RESULTS: AS was significantly associated with cardiac structure (left ventricular mass index, P < 0.0001), systolic function (ejection fraction, P = 0.03) and diastolic function (transmitral peak early [E]/atrial [A] wave velocities ratio, P = 0.008; early [e']/atrial [a'] waves, P = 0.02) after adjustments for CV risk factors. The association between AS and CAN was not significant when other important covariates were added. These relationships were mostly similar in both T1D and T2D. CONCLUSIONS: AS is associated with cardiac changes in young adults with diabetes. CAN-induced AS does not appear to be an etiology for cardiac abnormalities in this cohort.

OBJECTIVE: To project the prevalence and number of youths with diabetes and trends in racial and ethnic disparities in the U.S. through 2060. RESEARCH DESIGN AND METHODS: Based on a mathematical model and data from the SEARCH for Diabetes in Youth study for calendar years 2002-2017, we projected the future prevalence of type 1 and type 2 diabetes among youth aged <20 years while considering different scenarios of future trends in incidence. RESULTS: The number of youths with diabetes will increase from 213,000 (95% CI 209,000; 218,000) (type 1 diabetes 185,000, type 2 diabetes 28,000) in 2017 to 239,000 (95% CI 209,000; 282,000) (type 1 diabetes 191,000, type 2 diabetes 48,000) in 2060 if the incidence remains constant as observed in 2017. Corresponding relative increases were 3% (95% CI -9%; 21%) for type 1 diabetes and 69% (95% CI 43%; 109%) for type 2 diabetes. Assuming that increasing trends in incidence observed between 2002 and 2017 continue, the projected number of youths with diabetes will be 526,000 (95% CI 335,000; 893,000) (type 1 diabetes 306,000, type 2 diabetes 220,000). Corresponding relative increases would be 65% (95% CI 12%; 158%) for type 1 diabetes and 673% (95% CI 362%; 1,341%) for type 2 diabetes. In both scenarios, substantial widening of racial and ethnic disparities in type 2 diabetes prevalence are expected, with the highest prevalence among non-Hispanic Black youth. CONCLUSIONS: The number of youths with diabetes in the U.S. is likely to substantially increase in future decades, which emphasizes the need for prevention to attenuate this trend.

OBJECTIVE: To estimate medical costs associated with 17 diabetes complications and treatment procedures among Medicare beneficiaries aged ≥65 years with type 1 diabetes. RESEARCH DESIGN AND METHODS: With use of the 2006-2017 100% Medicare claims database for beneficiaries enrolled in fee-for-service plans and Part D, we estimated the annual cost of 17 diabetes complications and treatment procedures. Type 1 diabetes and its complications and procedures were identified using ICD-9/ICD-10, procedure, and diagnosis-related group codes. Individuals with type 1 diabetes were followed from the year when their diabetes was initially identified in Medicare (2006-2015) until death, discontinuing plan coverage, or 31 December 2017. Fixed-effects regression was used to estimate costs in the complication occurrence year and subsequent years. The cost proportion of a complication was equal to the total cost of the complication, calculated by multiplying prevalence by the per-person cost divided by the total cost for all complications. All costs were standardized to 2017 U.S. dollars. RESULTS: Our study included 114,879 people with type 1 diabetes with lengths of follow-up from 3 to 10 years. The costliest complications per person were kidney failure treated by transplant ($77,809 in the occurrence year and $13,556 in subsequent years), kidney failure treated by dialysis ($56,469 and $41,429), and neuropathy treated by lower-extremity amputation ($40,698 and $7,380). Sixteen percent of the total medical cost for diabetes complications was for treating congestive heart failure. CONCLUSIONS: Costs of diabetes complications were large and varied by complications. Our results can assist in cost-effectiveness analysis of treatments and interventions for preventing or delaying diabetes complications in Medicare beneficiaries aged ≥65 years with type 1 diabetes.

Evaluation of geographic disparities in type 2 diabetes (T2D) onset requires multidimensional approaches at a relevant spatial scale to characterize community types and features that could influence this health outcome. Using Geisinger electronic health records (2008-2016), we conducted a nested case-control study of new onset T2D in a 37-county area of Pennsylvania. The study included 15,888 incident T2D cases and 79,435 controls without diabetes, frequency-matched 1:5 on age, sex, and year of diagnosis or encounter. We characterized patients' residential census tracts by four dimensions of social determinants of health (SDOH) and into a 7-category SDOH census tract typology previously generated for the entire United States by dimension reduction techniques. Finally, because the SDOH census tract typology classified 83% of the study region's census tracts into two heterogeneous categories, termed rural affordable-like and suburban affluent-like, to further delineate geographies relevant to T2D, we subdivided these two typology categories by administrative community types (U.S. Census Bureau minor civil divisions of township, borough, city). We used generalized estimating equations to examine associations of 1) four SDOH indexes, 2) SDOH census tract typology, and 3) modified typology, with odds of new onset T2D, controlling for individual-level confounding variables. Two SDOH dimensions, higher socioeconomic advantage and higher mobility (tracts with fewer seniors and disabled adults) were independently associated with lower odds of T2D. Compared to rural affordable-like as the reference group, residence in tracts categorized as extreme poverty (odds ratio [95% confidence interval] = 1.11 [1.02, 1.21]) or multilingual working (1.07 [1.03, 1.23]) were associated with higher odds of new onset T2D. Suburban affluent-like was associated with lower odds of T2D (0.92 [0.87, 0.97]). With the modified typology, the strongest association (1.37 [1.15, 1.63]) was observed in cities in the suburban affluent-like category (vs. rural affordable-like-township), followed by cities in the rural affordable-like category (1.20 [1.05, 1.36]). We conclude that in evaluating geographic disparities in T2D onset, it is beneficial to conduct simultaneous evaluation of SDOH in multiple dimensions. Associations with the modified typology showed the importance of incorporating governmentally, behaviorally, and experientially relevant community definitions when evaluating geographic health disparities.

OBJECTIVE: To estimate medical costs associated with 17 major diabetes-related complications and treatment procedures among Medicare beneficiaries aged ≥65 years with type 2 diabetes. RESEARCH DESIGN AND METHODS: Claims data from 100% of Medicare beneficiaries enrolled in fee-for-service plans from 2006 to 2017 were analyzed. Records with type 2 diabetes and complications were identified using ICD-9, ICD-10, and diagnosis-related group codes. The index year was the year when a person was first identified as having diabetes with an inpatient claim or an outpatient claim plus another inpatient/outpatient claim in the 2 years following the first claim in Medicare. Included individuals were followed from index years until death, discontinuation of plan coverage, or 31 December 2017. Fixed-effects regression was used to estimate the cost in years when the complication event occurred and in subsequent years. The total cost for each complication was calculated for 2017 by multiplying the complication prevalence by the cost estimate. All costs were standardized to 2017 U.S. dollars. RESULTS: Our study included 10,982,900 beneficiaries with type 2 diabetes. Follow-up ranged from 3 to 10 years. The three costliest complications were kidney failure treated by transplant (occurring year $79,045, subsequent years $17,303), kidney failure treated by dialysis ($54,394, $38,670), and lower-extremity amputation ($38,982, $8,084). Congestive heart failure accounted for the largest share (18%) of total complication costs. CONCLUSIONS: Costs associated with diabetes complications were substantial. Our cost estimates provide essential information needed for conducting economic evaluation of treatment and programs to prevent and delay diabetes complications in Medicare beneficiaries.

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.

INTRODUCTION: More information is needed to understand the clinical epidemiology of youth hospitalized with diabetes and COVID-19. We describe the demographic and clinical characteristics of patients <21years old hospitalized with COVID-19 and either Type 1 or Type 2 Diabetes Mellitus (T1DM or T2DM) during peak incidence of SARS-CoV-2 infection with the B.1.617.2 (Delta) variant. METHODS: This is a descriptive sub-analysis of a retrospective chart review of patients aged <21years hospitalized with COVID-19 in six US children's hospitals during July-August 2021. Patients with COVID-19 and either newly diagnosed or known T1DM or T2DM were described using originally collected data and diabetes-related data specifically collected on these patients. RESULTS: Of the 58 patients hospitalized with COVID-19 and diabetes, 34 had T1DM and 24 had T2DM. Of those with T1DM and T2DM, 26% (9/34) and 33% (8/24), respectively, were newly diagnosed. Among those >12years old and eligible for COVID-19 vaccination, 93% were unvaccinated (42/45). Among patients with T1DM, 88% had diabetic ketoacidosis (DKA) and 6% had COVID-19 pneumonia; of those with T2DM, 46% had DKA and 58% had COVID-19 pneumonia. Of those with T1DM or T2DM, 59% and 46%, respectively, required ICU admission. CONCLUSION: Our findings highlight the importance of considering diabetes in the evaluation of youth presenting with COVID-19; the challenges of managing young patients who present with both COVID-19 and diabetes, particularly T2DM; and the importance of preventive actions like COVID-19 vaccination to prevent severe illness among those eligible with both COVID-19 and diabetes. This article is protected by copyright. All rights reserved.

OBJECTIVE: We compared arterial stiffness and heart rate variability (HRV) over time by diabetes type and determined the risk factors associated with worsening arterial stiffness and HRV in young adults with youth-onset diabetes. RESEARCH DESIGN AND METHODS: Arterial stiffness (pulse wave velocity, augmentation index) and six indices of heart rate variability were measured twice, 4.5 years apart, among participants with either youth-onset type 1 or type 2 diabetes in the SEARCH for Diabetes in Youth study. Multivariable linear regression models were used to assess risk factors associated with arterial stiffness and HRV at follow-up. RESULTS: Of 1,159 participants studied, 949 had type 1 diabetes (mean age 17.1 ± 4.7 years, 60.3% non-Hispanic White, 55% female) and 210 had type 2 diabetes (mean age 22.1 ± 3.5 years, 23.8% non-Hispanic White, 71% female) at initial assessment when diabetes duration was 7.9 years (both groups). Participants with type 2 versus type 1 diabetes had greater arterial stiffness and more abnormalities in HRV at initial and follow-up assessment and a greater change over time (all P < 0.05). Risk factors associated with worse arterial stiffness and HRV at follow-up in both types of diabetes included higher blood pressure, hemoglobin A1c, waist circumference and triglycerides overtime and longer diabetes duration. CONCLUSIONS: Arterial stiffness and HRV worsened over time with greater changes among participants with type 2 versus type 1 diabetes and among those with features of the metabolic syndrome. The risk factor profile documents potentially modifiable pathways to prevent or limit cardiovascular complications in young adults with youth-onset diabetes.