Type 1 Diabetes Exchange Clinic Registry Research Articles

Environmental exposures and blood pressure in adolescents and adults in the T1D exchange clinic registry

AimsTo examine the associations between environmental determinants of health and blood pressure and whether age, sex, or race moderated the associations among 18,754 adolescents and adults from the type 1 diabetes (T1D) Exchange Clinic Registry. MethodsWe used multivariable linear regression. Environmental determinants included exposure to ambient fine particulate matter (PM2.5, obtained from an integrated model), nitrogen dioxide (NO2), noise and light pollution, and the normalized difference vegetation index (NDVI, a marker of green space) at the ZIP code level of residence. ResultsHigher exposure to PM2.5 and NO2, and lower NDVI, was associated with higher systolic and diastolic blood pressure, and higher light pollution exposure were similarly associated with higher diastolic blood pressure. These associations between environmental exposures and blood pressure remained significant after accounting for other covariates (age, sex, race/ethnicity, BMI, and T1D duration). With aging, the negative association between NDVI and blood pressure weakened. ConclusionsThese findings emphasize the significance of minimizing exposure to environmental pollutants, including PM2.5 and NO2, as well as ensuring access to areas with higher NDVI, to promote cardiovascular health in individuals with T1D.

Disparities in Continuous Glucose Monitoring Use Among Women of Reproductive Age with Type 1 Diabetes in the T1D Exchange.

We identified characteristics associated with continuous glucose monitoring (CGM) use in women of reproductive age with type 1 diabetes (T1D) in the T1D Exchange clinic registry from 2015 to 2018. Among 6643 assessed women, the frequency of CGM increased from 2015 to 2018 (20.6% vs. 30.0%; adjusted odds ratios [aOR]: 1.72; confidence interval [95% CI]: 1.51-1.95) and was more likely with recent pregnancy (45.3% vs. 25.8%; aOR: 1.63; 95% CI: 1.23-2.16). Non-Hispanic Black and Hispanic race and ethnicity, younger age, lower educational attainment, lower income, and Medicaid insurance were associated with lower odds of CGM. The use of CGM was associated with lower odds of diabetic ketoacidosis and lower hemoglobin A1c without any difference in the odds of symptomatic severe hypoglycemia. In conclusion, although CGM use was associated with better glycemic control, the majority of reproductive-age women still did not use it. Those who did not use CGM were more likely to be those at greatest risk of adverse pregnancy outcomes.

Socioeconomic deprivation and cardiometabolic risk factors in individuals with type 1 diabetes: T1D exchange clinic registry

AimsSocial determinants of health (SDOH) influence cardiovascular health in the general population; however, the degree to which this occurs in individuals with type 1 diabetes (T1D) is not well understood. We evaluated associations among socioeconomic deprivation and cardiometabolic risk factors (hemoglobin A1c, low-density lipoprotein, blood pressure, body mass index, physical activity) in individuals with T1D from the T1D Clinic Exchange Registry. MethodsWe evaluated the association between the social deprivation index (SDI) and cardiometabolic risk factors using multivariable and logistic regression among 18,754 participants ages 13 – 90 years (mean 29.2 ± 17) in the T1D Exchange clinic registry from 6,320 zip code tabulation areas (2007–2017). ResultsSDI was associated with multiple cardiometabolic risk factors even after adjusting for covariates (age, biological sex, T1D duration, and race/ethnicity) in the multivariable linear regression models. Those in the highest socially deprived areas had 1.69 (unadjusted) and 1.78 (adjusted) times odds of a triple concomitant risk burden of poor glycemia, dyslipidemia, and hypertension. ConclusionsPersistent SDOH differences could account for a substantial degree of poor achievement of cardiometabolic targets in individuals with T1D. Our results suggest the need for a broader framework to understand the association between T1D and adverse cardiometabolic outcomes.

Effects of Adjuvant Medications on A1C, Body Mass Index, and Insulin Requirements among Patients with Type 1 Diabetes.

Randomized controlled trials have demonstrated that noninsulin medications used to treat type 2 diabetes can improve health outcomes among patients with type 1 diabetes (T1D). This study assessed the effects of adjuvant diabetes medications on glycated hemoglobin (A1C), body mass index (BMI), or total daily insulin (TDI) among patients with T1D in a real-world setting. This was an analysis of the T1D Exchange Clinic Registry, using the study periods of 2010–2012, 2015–2016, and 2016–2017, to assess differences in A1C, BMI, and TDI between patients with and without adjuvant medications. The relationships between characteristics and A1C in 2015–2016 and 2016–2017 were determined. Analysis included 517 patients in the adjuvant medication cohort and 4968 in the insulin-only cohort. No significant improvement in A1C was observed. A significant difference in BMI and TDI between the insulin-only (median BMI: 25.5, 26.2, 26.4 and median TDI: 45, 44 units) and adjuvant medication cohorts (median BMI: 29.8, 30.5, 30.5 and median TDI: 51, 52 units) (p < 0.001) was observed. Patients with a continuous glucose monitor (CGM), higher education level, higher annual income, and older age were associated with lower A1C (p ≤ 0.001). Higher BMI and self-description as African American/Black were associated with higher A1C (p ≤ 0.01). Insulin pump use was associated with lower A1C (p < 0.01) in 2015–2016. Patients who used adjuvant medications did not demonstrate significant improvement in disease control. These data suggest that findings from well-designed research studies may not be consistently reproducible in real-world settings, due to patient-specific factors.

Symptomatic diabetic autonomic neuropathy in type 1 diabetes (T1D): Findings from the T1D exchange

AimsWe aimed to evaluate the contemporary prevalence of and risk factors for symptomatic diabetic autonomic neuropathy (DAN) in participants with type 1 diabetes (T1D) enrolled in the T1D Exchange Clinic Registry. MethodsDAN symptoms and severity were assessed with the Survey of Autonomic Symptoms (SAS) in adults with ≥5 years of T1D participating in the T1D Exchange from years 2010–2017. Associations of demographic, clinical, and laboratory factors with symptomatic DAN were assessed. ResultsOf the 4919 eligible T1D participants, 965 (20%) individuals completed the SAS questionnaire [mean age 40 ± 17 years, median diabetes duration 20 years (IQR: 13,34), 64% female, 90% non-Hispanic White, and 82% with private insurance]. DAN symptoms were present in 166 (17%) of responders with 72% experiencing moderate severity symptoms or worse. Symptomatic DAN participants had higher hemoglobin A1c (p = 0.03), longer duration (p = 0.004), were more likely to be female (p = 0.03), and more likely to have lower income (p = 0.03) versus no DAN symptoms. Symptomatic DAN was associated with diabetic peripheral neuropathy (p < 0.0001), smoking (p = 0.002), cardiovascular disease (p = 0.02), depression (p < 0.001), and opioid use (p = 0.004). ConclusionsDAN symptoms are common in T1D. Socioeconomic factors and psychological comorbidities may contribute to DAN symptoms and should be explored further.

573-P: Insulin and Supply Rationing in Emerging Adults with Type 1 Diabetes

Over 25% of adults with diabetes have reported rationing insulin in the United States. Emerging adults, ages 18-25, may be even more vulnerable to rationing as they grapple with financial instability during this developmental period of increasing independence coupled with the rising cost of healthcare. The purpose of this study was to explore factors related to insulin and diabetes supply rationing in a sample of emerging adults with type 1 diabetes (T1D). Content analysis was used to examine a single open-ended response to the question, “Please tell me about your experiences rationing insulin or diabetes supplies,” in a parent cross-sectional study. The parent study explored financial stress factors, psychological factors, and self-management outcomes in 413 emerging adults from the T1D Exchange Clinic Registry. Chi-square tests were utilized to understand if rationing (yes or no) differed based on gender, race/ethnicity, employment status, type of health insurance, insulin pump usage, CGM usage, and A1c level (&amp;lt;8.9% or &amp;gt;9.0%). Alpha was set at .05. A total of 268 participants responded to the open-ended question about rationing. Over one-third of respondents (N=99, 36.9%) reported rationing insulin or diabetes supplies. Lack of private health insurance X2(3, N=224)=8.38, p&amp;lt;.05, racial/ethnic diversity (non-white, Hispanic) race/ethnicity X2(6, N=224)=13.54, p&amp;lt;.05 and no CGM usage X2(1, N=224)=9.75, p&amp;lt;.01 had significant relationships with rationing. Gender, employment status, A1C level, and insulin pump usage were not associated with rationing. A considerable number of emerging adults with T1D have experience rationing. Diabetes providers should routinely assess for insulin and diabetes supply rationing in this population. Attention should be paid to emerging adults who are racially/ethnically diverse, lack private insurance, and do not use CGM. Policy changes are necessary in order to improve access to affordable diabetes management tools in this vulnerable population. Disclosure J. E. Blanchette: Board Member; Self; JDRF, Consultant; Self; Insulet Corporation, Other Relationship; Self; Insulet Corporation, Tandem Diabetes Care, Research Support; Self; Association of Diabetes Care and Education Specialists. V. B. Toly: None. J. R. Wood: Research Support; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Insulet Corporation, Speaker’s Bureau; Self; Xeris Pharmaceuticals, Inc. M. L. Litchman: Research Support; Self; Abbott Diabetes. Funding Sigma Theta Tau Alpha Mu; Frances Payne Bolton School of Nursing

1624-P: Family History of Type 1 Diabetes (T1D) and Comorbidity Status in Individuals with T1D: A Computational Deep Exploratory Data Mining Approach

T1D is a progressive, autoimmune-mediated condition associated with numerous comorbidities and significant premature mortality. The offspring of fathers diagnosed with T1D exhibit a 2-3 times higher risk of developing T1D than the offspring of mothers diagnosed with T1D. Individuals with T1D who have an affected father present with a more aggressive disease phenotype at diagnosis. Yet the impact of paternal T1D (P-T1D) vs. maternal T1D (M-T1D) on health outcomes in individuals with T1D is unknown. We previously developed and validated a subgroup discovery algorithm that identifies highly contrasted patterns occurring with a significant difference in prevalence between two subgroups (e.g., P-T1D vs. M-T1D). Here we used this computational deep exploratory data mining method to analyze publicly-accessible data from the T1D Exchange Clinic Registry (2010-12; 2015-17). We used an Apache Spark high performance computing environment to apply our algorithm to family history, gender, and medical conditions data in the Registry. We identified multiple phenotypic contrasts between individuals with P-T1D (2010-12 data: n = 1011; 2015-17 data: n = 652) vs. M-T1D (2010-12 data: n = 528; 2015-17 data: n = 342). Using Fisher’s exact tests to determine statistical significance, P-T1D associated with hypothyroidism and male gender in 7.2% of cases (47/652), compared to 3.2% of cases (11/342) of M-T1D (p = 0.01). M-T1D was associated with hypertension (HTN) in 36.0% of cases (123/342), compared to 22.3% of cases (146/652) in P-T1D (p &amp;lt; 0.001). M-T1D was associated with diabetes-related neuropathy and HTN in 10.8% of cases (37/342), compared to 4.9% of cases (32/652) in P-T1D (p = 0.001). Complex patterns generated with this algorithm may yield contrast patterns that provide insights about personalized interventions to improve health outcomes. Whether contrast mining can be used to predict health trajectories of individuals with T1D remains to be determined. Disclosure E.M. Tallon: None. M.A. Clements: Consultant; Self; Glooko, Inc. Other Relationship; Self; Glooko, Inc. D. Liu: None. K. Boles: None. R.A. Stuck: None. C. Shyu: None. Funding National Institutes of Health (5T32LM012410)

1360-P: Infertility Is Not Associated with Clinical Factors in Women with Type 1 Diabetes (T1D)

Previous studies have shown adolescents with T1D diagnosed prior to menarche have an older age of menarche compared with those diagnosed after menarche and to the general population, and menstrual irregularity in women with T1D is more common than in those without T1D, suggesting that T1D may be associated with reproductive abnormalities. In this study, multiple regression models were used to explore the relationship between clinical factors and markers of reproductive health in 3528 women &amp;gt;18 years (mean age 39±17 years) in the T1D Exchange Clinic Registry who had a 5-year follow-up. Average age of menarche was 13±2 years, and 13% reported irregular menstrual periods unrelated to pregnancy or menopause. Younger age at T1D diagnosis was significantly associated with older age at menarche (p=0.001) after adjustment for race/ethnicity, current BMI, and report of severe hypoglycemia (SH). Having an evaluation for infertility was reported by 6% of participants and was associated with lower mean hemoglobin A1c (A1c; OR 0.79, 95% CI 0.67-0.91 for a 1% increase in A1c) and current use of continuous glucose monitoring (CGM, OR 1.58, 95% CI 1.16-2.16). Seeking an infertility evaluation was not significantly associated with age at T1D diagnosis, autoantibody status, or current menstrual regularity. Additionally, having an abnormal infertility evaluation was not associated with mean A1c (OR 0.85, 95% CI 0.62-1.17) or current use of CGM (OR 1.62, 95% CI 0.91-2.91). There were also no factors that were both clinically and statistically significantly associated with miscarriage or problems conceiving a child. These results suggest that women with T1D who are likely to seek infertility evaluations may be more determined to maintain optimal glycemic control with technology such as CGM, or that concern about fertility may drive the decision to use CGM and lower A1c. This study highlights the need for prospective studies to assess the impact of T1D on fertility in women. Disclosure A. Erkin-Cakmak: None. R. Bailey: None. P. Calhoun: Stock/Shareholder; Self; Dexcom, Inc. H. Cakmak: None. J.C. Wong: Consultant; Self; pH Pharma. Research Support; Self; Dexcom, Inc. Funding The Leona M. and Harry B. Helmsley Charitable Trust (G-2016PG-T1D053)

194-LB: T1D Exchange Registry: Current Data Insights and Future Impact

In a previous T1D Exchange led initiative, the T1D Exchange Clinic Registry encompassed 25,000 participants from 81 clinic sites across the U.S. who drove type 1 diabetes (T1D) research and produced real-world data on T1D. Upon the Clinic Registry’s closing, T1D Exchange launched the online T1D Exchange Registry in June of 2019 to lower barriers to research, increase participation, and strive to develop a more diverse population. The Registry is currently recruiting adults with T1D and parents/guardians of children who have T1D, living in the U.S. The Registry is a streamlined platform where participants enroll by completing screening questions, signing consent, and answering an initial questionnaire. Participants then complete an annual questionnaire to track health, disease management, and changes in outcomes over time. As of March 2020, there are over 5,300 participants enrolled in the Registry, with over 56% having completed their initial questionnaire. Currently, 10.9% of participants are between the ages of 1-17 years, 70.2% are between 18-55 years, and 18.9% are 56 years or above. This cohort represents a wide range of years since diagnosis, with 23.4% diagnosed within the past 5 years and 24.8% diagnosed more than 30 years ago. The majority identify as Caucasian (94.1%) and female (70.2%), with geographic representation from every U.S. state and territory. Among the pediatric cohort (&amp;lt;18 years), 24% reported A1C below 7.0%, whereas 36.1% of adults between 18-55 years reported A1C below 7.0%; 77.8% of adults 56 years or above reported A1C lower than 7.5%. The Registry cohort appears to be more technology-skilled than other T1D cohorts reported in the U.S., with 77.0% of participants currently using a CGM, and 67.2% using an insulin pump. Future projects for the Registry include analyzing longitudinal data, linking device data, sharing clinical trial opportunities, and providing additional research opportunities to participants. Disclosure K. LaFerriere: None. J. Liu: None. A. Hughes: None. W. Wolf: None. Funding The Leona M. and Harry B. Helmsley Charitable Trust (G-2018PG-T1D074)

Cognitions Associated With Hypoglycemia Awareness Status and Severe Hypoglycemia Experience in Adults With Type 1 Diabetes.

Impaired awareness of hypoglycemia (IAH) and recurrent severe hypoglycemia (RSH) remain problematic for people with type 1 diabetes (T1D), despite major therapeutic advances. We explored beliefs around hypo- and hyperglycemia in adults with T1D with, and without, IAH and RSH. A cross-sectional U.S. multicenter survey included Attitudes to Awareness of Hypoglycemia (A2A; a 19-item questionnaire concerning beliefs about hypoglycemia), the Gold score (single item: awareness of hypoglycemia), and a question about severe hypoglycemia over the preceding year. The survey was emailed to 6,200 adult participants of the annual T1D Exchange clinic registry data collection. A2A data were subjected to principal component analysis with varimax rotation. Among 1,978 respondents (response rate 32%), 61.7% were women, mean ± SD age was 39.6 ± 16.3 years, and T1D duration was 23.1 ± 13.8 years. Thirty-seven percent reported IAH, 16% RSH, and 9% both. A2A items segregated into three factors, differently distributed by hypoglycemia experience. Respondents with IAH or RSH expressed appropriate concern about hypoglycemia, but those with IAH were more likely to prioritize hyperglycemia concerns than those with intact awareness (P = 0.002). Those with RSH showed greater normalization of asymptomatic hypoglycemia than those without (P = 0.019) and trended toward prioritizing hyperglycemia concerns (P = 0.097), driven by those with both IAH and RSH. Adults with T1D with IAH and RSH report specific cognitions about hypoglycemia and hyperglycemia, which may act as barriers to hypoglycemia avoidance and recovery of awareness. These may be modifiable and present a target for enhancing engagement of vulnerable people with strategies to avoid future hypoglycemia.

836-P: Cannabis Use in Adults with Type 1 Diabetes (T1D) Is Associated with Poor Glycemic Control and Increased Risk for Diabetic Ketoacidosis (DKA)

Cannabis has been legalized for medical or recreational use in 33 states and usage is increasing in adults. A prior study from Colorado showed a two-fold increased DKA risk among adults with T1D using cannabis. This study was aimed to evaluate glycemic control and DKA risk among adults with T1D who use cannabis from the T1D Exchange Clinic Registry (T1DX). The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) questionnaire was emailed to 4311 adults at 69 T1DX clinic registry centers. Total Substance Score (TSC) for cannabis was used to classify adults with T1D requiring no intervention (TSC score 0-3), a brief intervention (TSC 4-26), and more intensive intervention (&amp;gt;26). A total of 932 adults with T1D completed the survey (61% female, 90% non-Hispanic white, mean age 38±16 years). The prevalence of cannabis use was 17.8%; prevalence was higher in states where cannabis is legal. Compared to participants categorized as ‘no intervention’ (n=871), cannabis users ‘brief intervention’ (n=61) were younger, had a younger age at T1D diagnosis, had higher A1c, and had similar use of insulin pumps and CGMs. Cannabis use (TSC &amp;gt;4) was associated with increased DKA risk (OR 2.5, 1.0-5.9) after adjusting for age, sex and A1c [Figure]. With the growing use of cannabis among adults with T1D, physicians should be aware of an association between cannabis use and a risk for DKA. Disclosure V.N. Shah: Advisory Panel; Self; Sanofi US. Consultant; Self; Dexcom, Inc. D.D. Taylor: None. N.C. Foster: None. R. Beck: Other Relationship; Self; Abbott Laboratories, Ascensia Diabetes Care, Bigfoot Biomedical, Dexcom, Inc., Insulet Corporation, Lilly Diabetes, Roche Diabetes Care, Tandem Diabetes Care. H.K. Akturk: Advisory Panel; Self; Sanofi. Research Support; Self; Eli Lilly and Company, MannKind Corporation, REMD Biotherapeutics. Speaker's Bureau; Self; MannKind Corporation. G.L. Kinney: None. Funding The Leona M. and Harry B. Helmsley Charitable Trust

1424-P: Changes in Device Uptake and Glycemic Control among Pregnant Women with Type 1 Diabetes: Data from the T1D Exchange

We examined characteristics of pregnant women aged 16-40 years with type 1 diabetes (T1D) enrolled in the T1D Exchange clinic registry. We compared characteristics of 3 cohorts of women with data collection periods from: 2010-12 (N=4651), 2011-13 (N=3355), and 2016-18 (N=2818). 2.9%, 2.2%, and 1.7% of women reported being pregnant during 2010-12, 2011-13, and 2016-18, respectively. For pregnant women, there was a trend for a decrease in HbA1c over the 3 time periods from 6.8% to 6.7% to 6.4% (P=0.13 adjusted for age, race/ethnicity, frequency of glucose monitoring, and use of CGM). Self-reported use of CGM while pregnant increased more than 2-fold over the time period (P=0.001 adjusted for age, duration, race/ethnicity, insurance status, and use of pump); conversely, self-reported pump use while pregnant remained unchanged (adjusted P=0.38) (Table). Severe hypoglycemia (seizure/loss of consciousness) was similar across cohorts (adjusted P=0.38).We found in a real-world population of pregnant women in the U.S., lower HbA1c levels compared to those pregnant 5-6 years ago. CGM use in pregnancy appears to have increased over time, with relatively low but stable participant-reported insulin pump use. Further explorations of these findings, ongoing assessment of real-world pregnancy outcomes and comparisons with data on T1D pregnant women from other large registries are needed. Disclosure C.J. Levy: Advisory Panel; Self; Novo Nordisk A/S, Sanofi. Employee; Spouse/Partner; Allergan. N.C. Foster: None. S. DuBose: None. S. Agarwal: None. S. Lyons: None. A.L. Peters: Advisory Panel; Self; Abbott, Becton, Dickinson and Company, Bigfoot Biomedical, Eli Lilly and Company, Lexicon Pharmaceuticals, Inc., Livongo Health, MannKind Corporation, Medscape, Merck &amp; Co., Inc., Omada Health, Inc., OptumRx, Inc., Sanofi US, Zafgen, Inc. Research Support; Self; AstraZeneca, Dexcom, Inc., Jaeb Center for Health Research, MannKind Corporation, National Institute of Diabetes and Digestive and Kidney Diseases. Speaker's Bureau; Self; Novo Nordisk Inc. G.I. Uwaifo: None. L. DiMeglio: Research Support; Self; Amgen Inc., Caladrius Biosciences, Inc., Janssen Research &amp; Development, Medtronic, Sanofi. Other Relationship; Self; Dexcom, Inc. J. Sherr: Advisory Panel; Self; Bigfoot Biomedical, Eli Lilly and Company, Insulet Corporation. Consultant; Self; Lexicon Pharmaceuticals, Inc., Medtronic, Sanofi. Research Support; Self; Dexcom, Inc., Insulet Corporation. S. Polsky: Consultant; Self; Jaeb Center for Health Research. Research Support; Self; Barbara Davis Center for Diabetes, Children's Diabetes Foundation, Dexcom, Inc., Eli Lilly and Company, JDRF, Leona &amp; Harry Helmsley Charitable Trust, National Institute of Diabetes and Digestive and Kidney Diseases, Sanofi US. Funding The Leona M. and Harry B. Helmsley Charitable Trust

429-P: Therapeutic Inertia: Gap between Goals and Achievement between the T1DX and DPV Registries

Despite increased cardiovascular (CV) mortality in people with type 1 diabetes (T1D), treatment of CV risk factors may not be optimized. International registry comparisons highlight opportunities to improve clinical care and improve outcomes. We analyzed data from 28,494 patients from the German/Austrian DPV registry and 19,442 patients from the U.S. T1D Exchange (T1DX) Clinic registry with data between 01/2016 and 03/2018. Percent of patients by age category with HbA1c &amp;lt;7.5%, hypertension (HTN) and its treatment, dyslipidemia and its treatment, urine albumin to creatinine ratio &amp;gt;30 mg/g, BMI &amp;gt;30 kg/m2, and current smoking are reported. Logistic regression models by age group adjusted for sex and diabetes duration were used to calculate whether registry differences existed. The prevalence of obesity is lower in the DPV than the T1DX registry (Table). In those age &amp;lt;26 years more DPV than T1DX patients had A1c &amp;lt;7.5%. Hypertension was more prevalent in the DPV for those &amp;lt;26 years, but less prevalent for those &amp;gt;50 years. Dyslipidemia was more prevalent in DPV for those &amp;lt;50 years, but less for those &amp;lt;50 years. Elevated ACR and smoking are higher and HTN and dyslipidemia treatment are lower in the DPV than in the T1DX. Vascular disease remains the leading cause of morbidity and mortality in T1D. Comparison of risk factors and their treatment in these registries highlights opportunities to improve care and outcomes. Disclosure D.M. Maahs: Advisory Panel; Self; Novo Nordisk Inc. Consultant; Self; Abbott, Sanofi. Research Support; Self; Dexcom, Inc., Tandem Diabetes Care. J. Hermann: None. N.C. Foster: None. W. Karges: None. K. Miller: None. A. Dost: None. R.S. Weinstock: Consultant; Self; Insulogic LLC. Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Jaeb Center for Health Research, Kowa Pharmaceutical Europe Co. Ltd., Medtronic MiniMed, Inc., Oramed Pharmaceuticals. Other Relationship; Self; Unitio, Inc. M. Pavel: None. V.N. Shah: Advisory Panel; Self; Sanofi US. Consultant; Self; Dexcom, Inc. R.W. Holl: None. Funding The Leona M. and Harry B. Helmsley Charitable Trust; German Center for Diabetes Research; German Diabetes Association; European Foundation for the Study of Diabetes; INNODIA

2418-PUB: Incident Diabetes Complications among Women with T1D Based on Parity

We aimed to assess the association between pregnancy and occurrence of diabetes-related complications in women with type 1 diabetes (T1D). Females 16-40 years old in the T1D Exchange clinic registry completing an initial questionnaire during 2011-13 and repeating it between 2016-18 (N=497; age 22±5 years, duration 12 [6,17] years, 87% non-Hispanic White) were categorized into 2 cohorts: first pregnancy during 2011-13 (preg; n=28) and never pregnant (never; n=469). No participants had complications reported at baseline. Funduscopic exam data were not uniformly available. There was a trend for lower HbA1c 5 years after study enrollment in the preg group (7.3%±1.3%) compared with the never group (7.9%±1.4%), P=0.14 adjusted for age, race/ethnicity, and body mass index. Both albuminuria and nephropathy within 5 years of study enrollment were found at higher frequency in the women who had never been pregnant (Table). Rates of neuropathy within 5 years of enrollment were similar between the groups. While rates of cardiovascular disease within 5 years of study enrollment were low for both groups (0 in preg group and 2 participants in never group), the pregnant cohort despite having lower A1c had higher frequency of some cardiovascular disease risk factors (e.g., obesity). In persons with T1D without reported complications at enrollment, pregnancy was not associated with new complication development 5 years after delivery. Disclosure S. Polsky: Consultant; Self; Jaeb Center for Health Research. Research Support; Self; Barbara Davis Center for Diabetes, Children's Diabetes Foundation, Dexcom, Inc., Eli Lilly and Company, JDRF, Leona &amp; Harry Helmsley Charitable Trust, National Institute of Diabetes and Digestive and Kidney Diseases, Sanofi US. N.C. Foster: None. S. DuBose: None. S. Agarwal: None. S. Lyons: None. A.L. Peters: Advisory Panel; Self; Abbott, Becton, Dickinson and Company, Bigfoot Biomedical, Eli Lilly and Company, Lexicon Pharmaceuticals, Inc., Livongo Health, MannKind Corporation, Medscape, Merck &amp; Co., Inc., Omada Health, Inc., OptumRx, Inc., Sanofi US, Zafgen, Inc. Research Support; Self; AstraZeneca, Dexcom, Inc., Jaeb Center for Health Research, MannKind Corporation, National Institute of Diabetes and Digestive and Kidney Diseases. Speaker's Bureau; Self; Novo Nordisk Inc. G.I. Uwaifo: None. L. DiMeglio: Research Support; Self; Amgen Inc., Caladrius Biosciences, Inc., Janssen Research &amp; Development, Medtronic, Sanofi. Other Relationship; Self; Dexcom, Inc. J. Sherr: Advisory Panel; Self; Bigfoot Biomedical, Eli Lilly and Company, Insulet Corporation. Consultant; Self; Lexicon Pharmaceuticals, Inc., Medtronic, Sanofi. Research Support; Self; Dexcom, Inc., Insulet Corporation. C.J. Levy: Advisory Panel; Self; Novo Nordisk A/S, Sanofi. Employee; Spouse/Partner; Allergan. Funding The Leona M. and Harry B. Helmsley Charitable Trust

OR14-3 The Association of Glycemic Control and Glycemic Variability with Treatment Patterns and Diabetes-Related Events in the Adult Patients (Pts) with Type 1 Diabetes (T1D): Results from the T1D Exchange Clinic Registry

This cross-sectional analysis evaluated the association of A1C control/variability with treatment patterns and outcomes in adult pts with T1D.The association of A1C control (categorized into <7.0%; 7.0-8.0%; 8.0-9.0%; and ≥9.0%) and variability (defined as intrapersonal mean [M] and adjusted standard deviation [SD] of A1C values, categorized into low M/low SD = low; low M/high SD = medium; high M/low SD = high; and high M/high SD = very high) with pt characteristics, treatment patterns, and diabetes-related events (e.g. diabetic ketoacidosis [DKA], hypoglycemia, and comorbidities) were evaluated using T1D Exchange Clinic Registry data (05-01-2016 to 07-31-2017). Pts were required to have A1C values and key outcomes at exam, and ≥4 A1C values measured within 1 year from exam date for A1C variability analysis. Pts with a history of pancreas or islet cell transplant or currently pregnant were excluded. The association between A1C control/variability and diabetes-related outcomes were evaluated using multiple logistic regression adjusting for covariates.8331 and 2466 pts were included for A1C control and A1C variability analysis, respectively. The majority of the adult T1D pts did not achieve A1C<7.0% (78% pts had A1C≥7.0%) and had increased A1C variability (65% pts in medium to very high groups).Compared with the A1C<7.0% group, pts in the A1C≥9.0% group were significantly younger (29 vs 43 years) and with significantly shorter T1D duration (16 vs 25 years); both p<0.001. Ethnic minorities, lower socioeconomic status, being single, and smoking were also associated with poor A1C control; all p<0.001. Pts on pump or other adjunctive treatment (non-insulin injection, statin use, continuous glucose monitoring [CGM] use) were more likely to have better A1C control (all p<0.001). Poor A1C control (≥9.0%) was significantly associated with greater risk for DKA (adjusted odds ratio [aOR] of 5.7 for the A1C≥9.0% group vs <7.0%), retinopathy (aOR 2.5), neuropathy (aOR 1.8), micro nephropathy (aOR 1.9), and renal disease (aOR 1.9); all p<0.01.Similar associations were observed between A1C variability and pt demographics and disease duration. Pts on pump, statin use, or CGM use were more likely to have low A1C variability; all p<0.001. The very high A1C variability group (high M/high SD) was significantly associated with greater risk for DKA (aOR of 13.5 vs the low A1C variability group), severe hypoglycemia (aOR 4.8), neuropathy (aOR 2.2), micro nephropathy (aOR 2.3), and renal disease (aOR 2.8); all p<0.05.Lack of glycemic control and stability are associated with younger age, shorter disease duration, ethnic minorities, and low socioeconomic status. This study confirms the previously established association between glycemic control and diabetes-related complications and highlights the association of glycemic variability across both acute and long-term diabetes-related complications.

Test of the modified dual pathway model of eating disorders in individuals with type 1 diabetes

Adolescents and young adults with type 1 diabetes (T1D) demonstrate high rates of disordered eating behaviors (DEBs) and may experience physiological and psychological vulnerabilities not currently included in established risk models of DEBs. This study examined associations among constructs included in the recently proposed T1D-specific modified dual pathway model and examined age as a moderator of these associations. Participants included adolescents (n = 307; age M = 15.71, SD = 1.33), young adults (n = 313; age M = 21.20, SD = 2.10), and adults (n = 198; age M = 30.51, SD = 2.81) recruited via the T1D Exchange Clinic Registry. Data were collected from participants' medical records and from self-report questionnaires assessing dietary regimen, dietary restraint, body dissatisfaction, hunger/satiety, diabetes-specific negative affect, and DEBs. Multiple group path modeling was used to test hypotheses. Approximately 31% of participants were at risk for an eating disorder. The original modified dual pathway model had poor model fit. The addition of three empirically defensible paths improved model fit. Diabetes-specific dietary regimen, diabetes-specific negative affect, and hunger/satiety disruption all were associated with DEBs. A fully varying multiple group model by age fit best; however, only the dietary restraint to DEBs pathway demonstrated a distinct pattern across age cohort, which attenuated from the adolescent to the adult cohort. This study provides preliminary support for associations proposed in the modified dual pathway model and suggests potential for intervening on disease-specific risk factors of DEBs in a T1D population.

Stressful Life Events in Young Adults With Type 1 Diabetes in the U.S. T1D Exchange Clinic Registry.

The purpose was to test associations among stressful life events, frequency of missed insulin doses, and glycemic control in young adults with type 1 diabetes (T1D). The study was a cross-sectional descriptive secondary analysis. Data from 2,921 participants (ages 18-26 years) in the U.S. T1D Exchange Clinic Registry were analyzed. Report of a stressful life event was defined as one or more positive responses on a 17-item stressful life events index and defined as a dichotomous variable (yes or no). Frequency of missed insulin doses was measured using a single self-report item and collapsed into two levels (fewer than three times a week, three or more times a week). The glycosylated hemoglobin (A1c) level recorded at the time of enrollment was used to assess glycemic control. Nearly half (48.6%) of the participants reported having a stressful life event during the previous year. The most frequently reported stressful life events were problems at work or school (16.1%), serious arguments with family members or a close friend (15.2%), and financial problems in the family (13.8%). Compared to the participants not reporting stressful life events, those who reported stressful life events were more likely to be older, female, with a higher educational attainment level, and not working or unemployed. Those who reported a stressful life event were more likely than those who did not to say they typically missed insulin doses at least three times a week and less likely to say they typically missed insulin doses fewer than three times a week (p < .001 adjusted for age, sex, race or ethnicity, educational attainment level, duration of T1D diagnosis, and insulin delivery method). Mean A1c level was higher for the group who reported having a stressful life event in the past 12 months compared to the group who did not (8.7 ± 1.8% vs. 8.2 ± 1.6%; adjusted p < .001). The results of a mediation analysis suggest that the measure of frequency of missed insulin doses may be a mediator of the relationship between recent stressful life events and glycemic control (Sobel test: ab = .841, 95% confidence interval = 0.064-1.618). These findings suggest that, for young adults with T1D, the experience of stressful life events may increase their risk for poorer glycemic control, possibly by disrupting adherence with insulin doses. Further exploration of these relationships may allow for the potential for identifying those at risk and assisting them with more positive approaches to managing stressful events.

Diabetes Technology Use Among Pregnant and Nonpregnant Women with T1D in the T1D Exchange.

Gestational tight glycemic control is critical for women with type 1 diabetes (T1D). Limited data exist on the adoption and retention of diabetes technologies among women in different parity strata. We compared T1D management between T1D Exchange clinic registry participants (mean age 28 ± 9 years, 84% white non-Hispanic, and median T1D duration 13 years) who were pregnant at enrollment or year 1 follow-up ("recently pregnant" between 2010 and 2013, n = 214), ever (but not recently) pregnant (n = 1540), and never pregnant (n = 2586). We examined self-reported maternal and fetal outcomes in 130 women who delivered a baby within the last year. Recently pregnant women had the lowest hemoglobin A1c (6.5% pregnant vs. 7.8% ever pregnant vs. 8.0% never pregnant, P < 0.001). Recently pregnant women reported the highest use of continuous subcutaneous insulin infusion (74% vs. 60% vs. 58%, adjusted P < 0.001) and continuous glucose monitor (CGM) (36% vs.17% vs. 12%, adjusted P < 0.001) therapies compared with ever or never pregnant women, respectively, after adjusting for age, diabetes duration, and socioeconomic status. Among women 18-25 years old, CGM use was highest among recently pregnant women (adjusted P = 0.0022). Never pregnant women 26-45 years old had a higher use of CGM compared with younger counterparts (adjusted P < 0.001). Adverse maternal and fetal outcomes were common. Despite high uptake levels of advanced diabetes technologies among pregnant women, rates of adverse maternal and fetal outcomes remain high. More studies are needed to determine how these technologies could be best used in pregnancy and postpartum to improve health outcomes among women with T1D.

Impact of Target HbA1c Change in Pediatric Participants in the T1D Exchange Clinic Registry

In 2014, the American Diabetes Association lowered its recommended HbA1c target for children with type 1 diabetes (T1D) from &amp;lt;8.5% for &amp;lt;6 years, &amp;lt;8.0% for 6-&amp;lt;13 years, and &amp;lt;7.5 for 13-&amp;lt;18 years to &amp;lt;7.5% for all ages. To determine if HbA1c changed in response, we compared two cross-sectional cohorts of T1D participants in the United States aged &amp;lt;18 years with T1D duration ≥1 year from the T1D Exchange Clinic Registry. The first cohort (PRE) were participants who enrolled between 2010 and 2012 (n=11,788). The second cohort (POST) were participants with an update between 2016 and 2017 (n=9,234). For each age group, mean HbA1c was compared between the cohorts using a linear regression model adjusted for age, T1D duration, and socioeconomic status (SES). A comparison of the cohorts can be found in Table 1. Demographic and SES characteristics were similar between the cohorts. More participants in the POST cohort were using insulin pumps and CGMs. Mean HbA1c was similar between the two cohorts for those &amp;lt;6 years, though more participants in the POST cohort met the current HbA1c target. For the 6-&amp;lt;13 and 13-&amp;lt;18 age groups, those in the POST cohort had higher mean HbA1c, with fewer meeting the current HbA1c target (p&amp;lt;0.01). Thus, despite the lowering of HbA1c targets, glycemic control remains suboptimal in this population. Disclosure J. Wood: None. C. Boyle: None. M. Quinn: None. J.C. Wong: Research Support; Self; Dexcom, Inc.. Other Relationship; Self; Tidepool Project. M.J. Haller: None. B.A. Nelson: Speaker's Bureau; Self; Dexcom, Inc.. M.J. Haller: None. D. Schatz: None. W.V. Tamborlane: Consultant; Self; AstraZeneca, Boehringer Ingelheim GmbH, Eli Lilly and Company, Medtronic MiniMed, Inc., Novo Nordisk Inc., Sanofi, Takeda Pharmaceuticals U.S.A., Inc.. L. Fox: None. P. Prahalad: None. S. Corathers: None. D.M. Maahs: Advisory Panel; Self; Insulet Corporation. Consultant; Self; Abbott. Research Support; Self; Medtronic, Bigfoot Biomedical, Dexcom, Inc., Insulet Corporation, Roche Diabetes Care Health and Digital Solutions. G.T. Alonso: None. D.J. DeSalvo: Consultant; Self; Dexcom, Inc.. Speaker's Bureau; Self; Insulet Corporation. R. Wadwa: Advisory Panel; Self; Eli Lilly and Company. Research Support; Self; Dexcom, Inc., Xeris Pharmaceuticals, Inc., Novo Nordisk Inc., MannKind Corporation, Bigfoot Biomedical. L. DiMeglio: Advisory Panel; Self; Eli Lilly and Company. Research Support; Self; Dexcom, Inc., Medtronic, Sanofi, Caladrius Biosciences, Inc., Janssen Research &amp; Development, Xeris Pharmaceuticals, Inc., Sanofi.

Longitudinal Changes in Depression and Glycemia in Adults with Type 1 Diabetes

To assess change in depression over ≥4 years in adults with type 1 diabetes (T1D) and the association between change in depression and glycemic outcomes, we examined PHQ-8 data in adults in the T1D Exchange Clinic Registry with T1D duration ≥ 1 year (N= 2547; 57% female, 92% non-Hispanic white, year 1 age 43±16 years). PHQ-8 score ≥10 defined “depressed.” Linear regression was used to assess association of continuous outcomes and depression; logistic regression was used for categorical outcomes. At year 1/year 5, 9%/11% were depressed. In this sample, 126 (5%) had Persistent Depression (depressed at year 1 and year 5), 112 (4%) Resolved Depression (depressed at year 1, not at year 5), 148 (6%) New Year 5 Depression (not depressed at year 1, depressed at year 5), and 2161 (85%) Not Depressed at year 1/year 5. Of those depressed at year 1, 53% were depressed at year 5; of those not depressed at year 1, 6% were depressed at year 5. Participants with persistent depression/new year 5 depression had a significant increase (↑) in A1c [adj mean ↑ 0.5± 0.2/0.5± 0.2; adj mean 8.1±0.1 for both; adj P’s=0.001]; those not depressed at year 1/year 5 showed a trend in ↑A1c [0.3±0.1; adj mean 7.8±0.1; adj P=0.04]. Those with resolved depression did not show change in A1c [0.2±0.2; adj mean 7.7±0.2; adj P=0.28]. Those with persistent depression/new year 5 depression were more likely to report new year 5 DKA (DKA year 5 | no DKA year 1) than those not depressed at year 1/year 5 (adj P’s=0.03/0.04). There were trends for those with persistent depression to be more likely to report new year 5 severe hypoglycemia (SH) than those not depressed (11.1% vs. 4.8%); and for those with resolved depression to be less likely to report new year 5 SH (3.6 vs. 4.8%, adj P’s=0.09/0.11). Depression category was not associated with change in BMI (adj P=0.80). As a continuous variable, ↑in PHQ-8 was associated with ↑ in A1c (adj P&amp;lt;0.001), but not with new year 5 SH or BMI change (adj P&amp;gt;0.50). Depression (persistent or new year 5) has a negative impact on glycemic control over time. Adults with T1D should be screened and treated for depression. Disclosure P.M. Trief: Research Support; Self; National Institute of Diabetes and Digestive and Kidney Diseases. N.C. Foster: None. N. Chaytor: None. M.E. Hilliard: None. J. Kittelsrud: None. S. Jaser: None. S. Majidi: None. S. Corathers: None. S. Bzdick: None. D. Adkins: None. R.S. Weinstock: Research Support; Self; Medtronic MiniMed, Inc., Mylan, Kowa Pharmaceuticals America, Inc., Diasome Pharmaceuticals, Inc., Calibra Medical, Dexcom, Inc., Ultradian Diagnostics LLC., JAEB Center For Health Research, JDRF, National Institute of Diabetes and Digestive and Kidney Diseases.