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Disordered eating (DE) in type 1 diabetes (T1D) includes insulin restriction for weight loss with serious complications. Gut microbiota-derived short chain fatty acids (SCFA) may benefit host metabolism but are reduced in T1D. We evaluated the hypothesis that DE and insulin restriction were associated with reduced SCFA-producing gut microbes, SCFA, and intestinal microbial diversity in adults with T1D.We collected stool samples at four timepoints in a hypothesis-generating gut microbiome pilot study ancillary to a weight management pilot in young adults with T1D. 16S ribosomal RNA gene sequencing measured the normalized abundance of SCFA-producing intestinal microbes. Gas-chromatography mass-spectrometry measured SCFA (total, acetate, butyrate, and propionate). The Diabetes Eating Problem Survey-Revised (DEPS-R) assessed DE and insulin restriction. Covariate-adjusted and Bonferroni-corrected generalized estimating equations modeled the associations. COVID-19 interrupted data collection, so models were repeated restricted to pre-COVID-19 data. Data were available for 45 participants at 109 visits, which included 42 participants at 65 visits pre-COVID-19. Participants reported restricting insulin "At least sometimes" at 53.3% of visits. Pre-COVID-19, each 5-point DEPS-R increase was associated with a -0.34 (95% CI -0.56, -0.13, p = 0.07) lower normalized abundance of genus Anaerostipes; and the normalized abundance of Lachnospira genus was -0.94 (95% CI -1.5, -0.42), p = 0.02 lower when insulin restriction was reported "At least sometimes" compared to "Rarely or Never".DE and insulin restriction were associated with a reduced abundance of SCFA-producing gut microbes pre-COVID-19. Additional studies are needed to confirm these associations to inform microbiota-based therapies in T1D.

OBJECTIVE To describe temporal trends and correlates of glycemic control in youth and young adults (YYA) with youth-onset diabetes. RESEARCH DESIGN AND METHODS The study included 6,369 participants with type 1 or type 2 diabetes from the SEARCH for Diabetes in Youth study. Participant visit data were categorized into time periods of 2002–2007, 2008–2013, and 2014–2019, diabetes durations of 1–4, 5–9, and ≥10 years, and age groups of 1–9, 10–14, 15–19, 20–24, and ≥25 years. Participants contributed one randomly selected data point to each duration and age group per time period. Multivariable regression models were used to test differences in hemoglobin A1c (HbA1c) over time by diabetes type. Models were adjusted for site, age, sex, race/ethnicity, household income, health insurance status, insulin regimen, and diabetes duration, overall and stratified for each diabetes duration and age group. RESULTS Adjusted mean HbA1c for the 2014–2019 cohort of YYA with type 1 diabetes was 8.8 ± 0.04%. YYA with type 1 diabetes in the 10–14-, 15–19-, and 20–24-year-old age groups from the 2014–2019 cohort had worse glycemic control than the 2002–2007 cohort. Race/ethnicity, household income, and treatment regimen predicted differences in glycemic control in participants with type 1 diabetes from the 2014–2019 cohort. Adjusted mean HbA1c was 8.6 ± 0.12% for 2014–2019 YYA with type 2 diabetes. Participants aged ≥25 years with type 2 diabetes had worse glycemic control relative to the 2008–2013 cohort. Only treatment regimen was associated with differences in glycemic control in participants with type 2 diabetes. CONCLUSIONS Despite advances in diabetes technologies, medications, and dissemination of more aggressive glycemic targets, many current YYA are less likely to achieve desired glycemic control relative to earlier cohorts.

The gut microbiome is emerging as a key modulator of host energy balance1. We conducted a quantitative bioenergetics study aimed at understanding microbial and host factors contributing to energy balance. We used a Microbiome Enhancer Diet (MBD) to reprogram the gut microbiome by delivering more dietary substrates to the colon and randomized healthy participants into a within-subject crossover study with a Western Diet (WD) as a comparator. In a metabolic ward where the environment was strictly controlled, we measured energy intake, energy expenditure, and energy output (fecal, urinary, and methane)2. The primary endpoint was the within-participant difference in host metabolizable energy between experimental conditions. The MBD led to an additional 116 ± 56 kcals lost in feces daily and thus, lower metabolizable energy for the host by channeling more energy to the colon and microbes. The MBD drove significant shifts in microbial biomass, community structure, and fermentation, with parallel alterations to the host enteroendocrine system and without altering appetite or energy expenditure. Host metabolizable energy on the MBD had quantitatively significant interindividual variability, which was associated with differences in the composition of the gut microbiota experimentally and colonic transit time and short-chain fatty acid absorption in silico. Our results provide key insights into how a diet designed to optimize the gut microbiome lowers host metabolizable energy in healthy humans.

Co-management of weight and glycaemia is critical yet challenging in type 1 diabetes (T1D). We evaluated the effect of a hypocaloric low carbohydrate, hypocaloric moderate low fat, and Mediterranean diet without calorie restriction on weight and glycaemia in young adults with T1D and overweight or obesity.We implemented a 9-month Sequential, Multiple Assignment, Randomized Trial pilot among adults aged 19-30 years with T1D for ≥1 year and body mass index 27-39.9 kg/mAdjusted weight and HbA1c (n = 38) changed by -2.7 kg (95% CI -3.8, -1.5, P .0001) and -0.91 percentage points (95% CI -1.5, -0.30, P = .005), respectively, while adjusted body fat percentage remained stable, on average (P = .21). Hypoglycaemia indices remained unchanged following adjustment (n = 28, P .05). Variability in all outcomes, including weight change, was considerable (57.9% were re-randomized primarily due to loss of2% body weight). No outcomes varied by diet.Three months of a diet, irrespective of macronutrient distribution or caloric restriction, resulted in weight loss while improving or maintaining HbA1c levels without increasing hypoglycaemia in adults with T1D.

BACKGROUND: Individuals with diabetes require extensive self-management. Little is known about how Hurricane Matthew (Matthew) or Hurricane Florence (Florence) impacted diabetes self-management and outcomes in Robeson County, North Carolina. METHODS: Mixed methods were used to assess the impact of hurricanes on diabetes self-management and outcomes. Individuals with diabetes were recruited for focus groups to understand the perceived impact on diabetes self-management. Health care providers were recruited for parallel key informant interviews. Mean hemoglobin A1c (HbA1c) and frequency of diabetic ketoacidosis (DKA) from hospital data six months before and after Matthew were compared using Student t-tests. RESULTS: A demographic breakdown of 34.25% white, 21.70% Black or African American, and 21.38% American Indian or Alaska Native was observed from focus groups. Qualitative results highlight a limited access to a balanced diet and medications. No significant differences were found between mean HbA1c values before and after Matthew (before Matthew: mean HbA1c 8.34 ± 1.87%; after Matthew: mean HbA1c 8.31 ± 1.93 %; P = .366). The period prevalence (PP) of DKA was higher after Matthew than before (before Matthew: 39 cases out of 4,025 visits, PP = .010; after Matthew: 87 cases out of 3,779 visits, PP = .023; P

The ACT1ON pilot study evaluated the feasibility of three dietary strategies to optimize weight and glycemic management among young adults with T1D and overweight or obesity. As a secondary measure, self-reported physical activity (PA) was collected at baseline, 3-, 6-, and 9-months from 68 young adults with T1D (age 25.5 ± 3.1 years, 72.1% female, HbA1c 7.9 ± 1.8%, BMI 30.4 (27.9 - 33.9)) . Using the Global Physical Activity Questionnaire (GPAQ, n=195) and Previous Day Physical Activity Recalls (PDPAR, n=123) , we estimated weekly minutes of moderate-to-vigorous physical activity (MVPA) . Following the COVID-19 outbreak, a subset of participants wore Garmin Vivosmart4® PA trackers for two weeks at each visit (44 measurements from 27 participants) . Mixed effects regression models assessed the relationship between weekly minutes of MVPA and HbA1c using each PA measure. Median weekly minutes of MVPA were 33% lower following the COVID-19 outbreak compared to pre-pandemic PA levels (p=0.02) per the GPAQ, but not PDPAR (-7.7%, p=0.34) . After adjusting for design, demographic, clinical, and dietary variables, a 1 standard deviation increase in weekly minutes of MVPA (GPAQ) was associated with an absolute increase of 0.27% HbA1c (p>0.001) . A small, statistically non-significant association was observed for PDPAR (β=0.13, p=0.19) ; however, we observed a borderline statistically significant association using the PA tracker data (β=0.231, p=0.08) , despite a smaller sample size (n=44) . These results suggest that among young adults with T1D and overweight and obesity, higher levels of PA may lead to challenges in achieving optimal glycemia. Future work is needed to determine how to best support young adults with T1D and overweight and obesity in attaining both their PA and glycemic management goals. Disclosure F. R. Muntis: None. R. E. Pratley: Other Relationship; Bayer AG, Corcept Therapeutics, Dexcom, Inc., Hanmi Pharm. Co., Ltd., Merck & Co., Inc., Metavention, Novo Nordisk, Pfizer Inc., Poxel SA, Sanofi, Scohia Pharma Inc., Sun Pharmaceutical Industries Ltd. K. Corbin: None. E. J. Mayer-davis: None. D. P. Zaharieva: Research Support; Insulet Corporation, International Society for Pediatric and Adolescent Diabetes, Leona M. and Harry B. Helmsley Charitable Trust. D. Igudesman: None. A. Cristello: None. J. Thomas: None. N. Arrizon- ruiz: None. J. Hooper: None. A. Addala: None. J. Crandell: n/a. D. M. Maahs: Advisory Panel; Abbott Diabetes, Eli Lilly and Company, Medtronic, Novo Nordisk, Sanofi, Consultant; Aditx Therapeutics, Inc., Biospex. Funding National Institutes of Health (1DP3DK113358-01)

Background: Sequential Multiple Assignment Randomized Trials (SMARTs) efficiently address practical treatment comparison questions and adapt dynamically based on response. They may be useful for development of approaches to co-manage weight and glycemia T1D, which is critical yet challenging. Methods: Our SMART pilot with three diet periods enrolled young adults with T1D (BMI 27-39.9 kg/m²) . Participants were re-randomized after ∼3 months on the hypocaloric Look AHEAD (Low Fat) or Low Carbohydrate (Low Carb) ; or Mediterranean (Med, not calorie restricted) diet if Results: The proportion re-randomized was 57.9% and did not vary by diet. Weight was lost overall but insufficient weight loss was the most common reason for re-randomization for Low Fat and Med. An HbA1c increase ≥0.5% was most common on Med. Low diet acceptability was the most common reason for re-randomization on Low Carb. Conclusions: We achieved safe weight loss among young adults with T1D but observed heterogeneity in reasons for re-randomization by diet, although differences were not statistically significant. A fully-powered efficacy trial may confirm our findings. Disclosure D.Igudesman: None. R.E.Pratley: Other Relationship; Bayer AG, Corcept Therapeutics, Dexcom, Inc., Hanmi Pharm. Co., Ltd., Merck & Co., Inc., Metavention, Novo Nordisk, Pfizer Inc., Poxel SA, Sanofi, Scohia Pharma Inc., Sun Pharmaceutical Industries Ltd. M.R.Kosorok: n/a. D.M.Maahs: Advisory Panel; Abbott Diabetes, Eli Lilly and Company, Medtronic, Novo Nordisk, Sanofi, Consultant; Aditx Therapeutics, Inc., Biospex. E.J.Mayer-davis: None. J.Crandell: n/a. T.Pokaprakarn: None. K.Corbin: None. D.P.Zaharieva: Research Support; Insulet Corporation, International Society for Pediatric and Adolescent Diabetes, Leona M. and Harry B. Helmsley Charitable Trust. A.Addala: None. J.Thomas: None. A.Casu: None. M.Riddell: Advisory Panel; Zealand Pharma A/S, Zucara Therapeutics, Consultant; Eli Lilly and Company, Jaeb Center for Health Research, Speaker's Bureau; Dexcom, Inc., Eli Lilly and Company, Novo Nordisk. Funding National Institutes of Health 1DP3DK113358

Young adults with type 1 diabetes (T1D) often have difficulty co-managing weight and glycemia. The prevalence of overweight and obesity among individuals with T1D now parallels that of the general population and contributes to dyslipidemia, insulin resistance, and risk for cardiovascular disease. There is a compelling need to develop a program of research designed to optimize two key outcomes–weight management and glycemia–and to address the underlying metabolic processes and behavioral challenges unique to people with T1D. For an intervention addressing these dual outcomes to be effective, it must be appropriate to the unique metabolic phenotype of T1D, and to biological and behavioral responses to glycemia (including hypoglycemia) that relate to weight management. The intervention must also be safe, feasible, and accepted by young adults with T1D. In 2015, we established a consortium called ACT1ON: Advancing Care for Type 1 Diabetes and Obesity Network, a transdisciplinary team of scientists at multiple institutions. The ACT1ON consortium designed a multi-phase study which, in parallel, evaluated the mechanistic aspects of the unique metabolism and energy requirements of individuals with T1D, alongside a rigorous adaptive behavioral intervention to simultaneously facilitate weight management while optimizing glycemia. This manuscript describes the design of our integrative study—comprised of an inpatient mechanistic phase and an outpatient behavioral phase—to generate metabolic, behavioral, feasibility, and acceptability data to support a future, fully powered sequential, multiple assignment, randomized trial to evaluate the best approaches to prevent and treat obesity while co-managing glycemia in people with T1D. Clinicaltrials.gov identifiers: NCT03651622 and NCT03379792. The present study references can be found here: https://clinicaltrials.gov/ct2/show/NCT03651622 https://clinicaltrials.gov/ct2/show/NCT03379792?term=NCT03379792&draw=2&rank=1 Submission Category: “Study Design, Statistical Design, Study Protocols”.

OBJECTIVE: To assess the relationship between mindfulness and glycemia among adolescents with type 1 diabetes (T1D) with suboptimal glycemia, and evaluate the potential mediation by ingestive behaviors, including disordered eating, and impulsivity. METHODS: We used linear mixed models for hemoglobin A1c (HbA1c) and linear regression for continuous glucose monitoring (CGM) to study the relationship of mindfulness [Child and Adolescent Mindfulness Measure (CAMM)] and glycemia in adolescents with T1D from the 18-month Flexible Lifestyles Empowering Change (FLEX) trial. We tested for mediation of the mindfulness-glycemia relationship by ingestive behaviors, including disordered eating (Diabetes Eating Problem Survey – Revised), restrained eating, and emotional eating (Dutch Eating Behavior Questionnaire); and impulsivity (total, attentional, and motor, Barrett Impulsiveness Scale). RESULTS: At baseline, participants (n=152) had a mean age of 14.9 ± 1.1 years and HbA1c of 9.4 ± 1.2% [79±13 mmol/mol]. The majority of adolescents were non-Hispanic white (83.6%), 50.7% were female, and 73.0% used insulin pumps. From adjusted mixed models, a 5-point increase in mindfulness scores was associated with a −0.19% (95%CI −0.29, −0.08, p=0.0006) reduction in HbA1c. We did not find statistically significant associations between mindfulness and CGM metrics. Mediation of the relationship between mindfulness and HbA1c by ingestive behaviors and impulsivity was not found to be statistically significant. CONCLUSIONS: Among adolescents with T1D and suboptimal glycemia, increased mindfulness was associated with lower HbA1c levels. Future studies may consider mindfulness-based interventions as a component of treatment for improving glycemia among adolescents with T1D, though more data are needed to assess feasibility and efficacy.

OBJECTIVES: To describe temporal trends and correlates of glycemic control in youth and young adults (YYA) with youth-onset diabetes. RESEARCH DESIGN AND METHODS: The study included 6,492 participants with type 1 or type 2 diabetes from the SEARCH for Diabetes in Youth study. Participant visit data were categorized into time periods 2002-2007, 2008-2013 and 2014-2019, diabetes durations of 1-4, 5-9, and 10+ years, and age groups 1-9, 10-14, 15-19, 20-24, 25+ years. Participants contributed one randomly selected data point to each duration and age group per time period. Multivariable regression models were used to test differences in hemoglobin A1c (HbA1c) over time by diabetes type. Models were adjusted for site, age, sex, race/ethnicity, household income, health insurance status, insulin regimen and diabetes duration, overall and stratified for each duration and age group. RESULTS: Adjusted mean HbA1c for the 2014-2019 cohort of YYA with type 1 diabetes was 8.8%±0.04%. YYA with type 1 diabetes in the 10-14, 15-19, and 20-24 age groups from the 2014-2019 cohort had worse glycemic control than the 2002-2007 cohort. Race/ethnicity, household income and treatment regimen predicted differences in glycemic control in 2014-2019 type 1 diabetes participants. Adjusted mean HbA1c was 8.6%±0.12% for 2014-2019 YYA with type 2 diabetes. Participants age 25+ with type 2 diabetes had worse glycemic control relative to the 2008-2013 cohort. Only treatment regimen was associated with differences in glycemic control in type 2 diabetes participants. CONCLUSIONS: Despite advances in diabetes technologies, medications, and dissemination of more aggressive glycemic targets, many current YYA are less likely to achieve desired glycemic control relative to earlier cohorts.

Despite the widespread clinical perception that hypoglycemia may drive weight gain in youth with type 1 diabetes (T1D), there is an absence of published evidence supporting this hypothesis.We estimated the body fat percentage (eBFP) of 211 youth (HbA1c 8.0-13.0%, age 13-16) at baseline, 6, and 18 months of the Flexible Lifestyles Empowering Change trial using validated equations. Group-based trajectory modeling assigned adolescents to sex-specific eBFP groups. Using baseline 7-day blinded continuous glucose monitoring data, "more" vs. "less" percent time spent in hypoglycemia was defined by cut-points using sample median split and clinical guidelines. Adjusted logistic regression estimated the odds of membership in an increasing eBFP group comparing youth with more vs. less baseline hypoglycemia.More time spent in clinical hypoglycemia (defined by median split) was associated with 0.29 the odds of increasing eBFP in females (95% CI: 0.12, 0.69; p = 0.005), and 0.33 the odds of stable/increasing eBFP in males (95% CI: 0.14, 0.78; p = 0.01).Hypoglycemia may not be a major driver of weight gain in US youth with T1D and HbA1c ≥8.0. Further studies in different sub-groups are needed to clarify for whom hypoglycemia may drive weight gain and focus future etiological studies and interventions.We contribute epidemiological evidence that hypoglycemia may not be a major driver of weight gain in US youth with type 1 diabetes and HbA1c ≥8.0% and highlight the need for studies to prospectively test this hypothesis rooted in clinical perception. Future research should examine the relationship between hypoglycemia and adiposity together with psychosocial, behavioral, and other clinical factors among sub-groups of youth with type 1 diabetes (i.e., who meet glycemic targets or experience a frequency/severity of hypoglycemia above a threshold) to further clarify for whom hypoglycemia may drive weight gain and progress etiological understanding of and interventions for healthy weight maintenance.

BACKGROUND & AIMS: Research quantifying dietary intake in individuals with bulimia nervosa and binge-eating disorder (i.e., binge-type eating disorders) is surprisingly scant. We assessed the dietary intake of women and men with binge-type eating disorders in a large case-control study and compared them with healthy controls. We also evaluated the extent to which their dietary intake adhered to the Nordic Nutrition Recommendations. Among cases, we assessed the relationship of binge eating frequency with energy and macronutrient intake. METHODS: We derived the total daily energy, macro-, and micronutrient intake of 430 cases with binge-type eating disorders (women: n=391, men: n=39) and 1,227 frequency-matched controls (women: n=1,213, men: n=14) who completed the MiniMeal-Q, a validated food frequency questionnaire. We calculated mean intake for men and women and, in women, compared mean intake of energy and nutrients between cases and controls using linear regression. We calculated the proportion of women and men who met the recommended intake levels from the NNR, and compared these proportions in female cases and controls using logistic regression. We used linear regression to examine energy and macronutrient intake of women with varying frequencies of current binge-eating. RESULTS: Female, but not male cases, had a higher mean intake of total energy/day compared with controls and higher intake than recommended. The majority in all groups (male and female cases and controls) exceeded saturated fat recommendations, and did not meet recommendations for omega-3 fatty acid intake. Among all groups, adherence was low for vitamin D, selenium, and salt. Iron and folate intake was low among the majority of women, especially controls. Female cases with ≥4 binge-eating episodes in the past 28 days had higher intake of energy and percent carbohydrates, and lower intake of percent fat, compared to cases with no binge-eating episodes in the past month. CONCLUSIONS: Higher than recommended total daily energy intake among women with binge-type eating disorders may lead to weight gain and downstream health complications, if persistent. In most women, iron and folate intake was insufficient, which may have negative consequences for reproductive health. We found suboptimal adherence for key nutrients that are important to limit (saturated fat and salt) or meet (omega-3 fatty acids) for cardiovascular and overall health in all groups. Nutrition counseling should form an important pillar of treatment to assist with normalization of eating patterns and may also benefit individuals without eating disorders to optimize nutrient intake for long term health promotion.

Anorexia nervosa has poor prognosis and treatment outcomes and is influenced by genetic, metabolic, and psychological factors. Gut microbes interact with gut physiology to influence metabolism and neurobiology, although potential therapeutic benefits remain unknown. Type 1 diabetes is linked to anorexia nervosa through energy dysregulation, which in both disease states is related to the gut microbiota, disordered eating, and genetics.

Background The impact of weight management in persons with type 1 diabetes (T1D) from childhood into adulthood has not been well described. The purpose of the study was to explore qualitative themes presented by young adults with T1D with respect to the dual management of weight and T1D. Methods We analyzed focus group data from 17 young adults with T1D (65% female, age 21.7 ± 2.1 years, HbA1c 8.1% ± 1.5) via inductive qualitative analysis methods. Major themes were compared to themes presented by youth with T1D ages 13-16 years in previously published study in order to categorize thematic progression from early adolescence through adulthood. Results Themes from young adults with T1D, when compared to those from youth were categorized as: (a) persistent and unchanged themes, (b) evolving themes, and (c) newly reported themes. Hypoglycemia and a sense of futility around exercise was an unchanged theme. Importance of insulin usage and a healthy relationship with T1D evolved to gather greater conviction. Newly reported themes are unique to integration of adulthood into T1D, such as family planning and managing T1D with work obligations. Young adults also reported negative experiences with providers in their younger years and desire for more supportive provider relationships. Conclusions Issues identified by youth regarding the dual management of T1D and weight rarely resolve, but rather, persist or evolve to integrate other aspects of young adulthood. Individualized and age-appropriate clinical support and practice guidelines are warranted to facilitate the dual management of weight and T1D in persons with T1D.

BACKGROUND: Comanagement of glycemia and adiposity is the cornerstone of cardiometabolic risk reduction in type 1 diabetes (T1D), but targets are often not met. The intestinal microbiota and microbiota-derived short-chain fatty acids (SCFAs) influence glycemia and adiposity but have not been sufficiently investigated in longstanding T1D. OBJECTIVES: We evaluated the hypothesis that an increased abundance of SCFA-producing gut microbes, fecal SCFAs, and intestinal microbial diversity were associated with improved glycemia but increased adiposity in young adults with longstanding T1D. METHODS: Participants provided stool samples at ≤4 time points (NCT03651622: https://clinicaltrials.gov/ct2/show/NCT03651622). Sequencing of the 16S ribosomal RNA gene measured abundances of SCFA-producing intestinal microbes. GC-MS measured total and specific SCFAs (acetate, butyrate, propionate). DXA (body fat percentage and percentage lean mass) and anthropometrics (BMI) measured adiposity. Continuous glucose monitoring [percentage of time in range (70-180 mg/dL), above range (>180 mg/dL), and below range (54-69 mg/dL)] and glycated hemoglobin (i.e., HbA1c) assessed glycemia. Adjusted and Bonferroni-corrected generalized estimating equations modeled the associations of SCFA-producing gut microbes, fecal SCFAs, and intestinal microbial diversity with glycemia and adiposity. COVID-19 interrupted data collection, so models were repeated restricted to pre-COVID-19 visits. RESULTS: Data were available for ≤45 participants at 101 visits (including 40 participants at 54 visits pre-COVID-19). Abundance of Eubacterium hallii was associated inversely with BMI (all data). Pre-COVID-19, increased fecal propionate was associated with increased percentage of time above range and reduced percentage of time in target and below range; and abundances of 3 SCFA-producing taxa (Ruminococcus gnavus, Eubacterium ventriosum, and Lachnospira) were associated inversely with body fat percentage, of which two microbes were positively associated with percentage lean mass. Abundance of Anaerostipes was associated with reduced percentage of time in range (all data) and with increased body fat percentage and reduced percentage lean mass (pre-COVID-19). CONCLUSIONS: Unexpectedly, fecal propionate was associated with detriment to glycemia, whereas most SCFA-producing intestinal microbes were associated with benefit to adiposity. Future studies should confirm these associations and determine their potential causal linkages in T1D.This study is registered at clinical.trials.gov (NCT03651622; https://clinicaltrials.gov/ct2/show/NCT03651622).

Diabetes mellitus is a collection of endocrine disorders that involve insufficient or dysfunctional insulin production. Their causes include genetic and environmental factors that vary from one individual to another, and across populations. Trends in incidence and prevalence of diabetes and its complications also vary by geographic region, and by demographic factors such as gender, race, and ethnicity. While type 1 and type 2 diabetes onset tend to occur more frequently in children and adults, respectively, relative proportions of the two may be difficult to measure accurately in middle- and low-income countries. Gestational diabetes is a third diabetes type that is on the rise, partially due to increases in obesity among women of childbearing age. Prevention and treatment efforts should include a combination of pharmacologic and lifestyle interventions, and should be targeted based upon resource availability and feasibility. Economic impact is discussed both nationally and internationally.

Objective: To determine whether glycemia early in the course of type 1 diabetes changed between 2002 and 2016 across discrete youth cohorts. Research Design and Methods: Data from 3,956 youth in the SEARCH for Diabetes in Youth study were used to test whether glycemia worsened between 2002 and 2016 among successive cohorts of youth with type 1 diabetes examined within 30 months of diagnosis. We used linear regression for hemoglobin A1c (HbA1c) and logistic regression for poor glycemic control (HbA1c>9%) stratified by diabetes duration ( Results: Fully adjusted models revealed that mean HbA1c and frequency of poor glycemic control remained stable over time across successive youth cohorts with type 1 diabetes. Overall mean unadjusted HbA1c was 7.9% ± 1.5 (63 mmol/mol ± 16.4) in 2002 and 7.8% ± 2.4 (62 mmol/mol ± 26.2) in 2016, p=0.6 for trend. Estimates from weighted linear regression models found no overall change in HbA1c with index year, but a small linear reduction in HbA1c with each index year in the Conclusions: HbA1c levels remained stable but higher than recommended across discrete cohorts of SEARCH youth with type 1 diabetes duration ≤ 30 months, particularly among non-white youth. Future studies should elucidate predictors of elevated glycemia among youth early in the course of type 1 diabetes. Disclosure D. Igudesman: None. F. Malik: None. E. J. Mayer-davis: None. B. A. Reboussin: None. K. J. Souris: None. C. Pihoker: None. L. M. Dolan: None. S. Saydah: None. D. Dabelea: None. N. Clouet-foraison: None. S. M. Marcovina: None. Funding National Institute for Health Research (1UC4DK108173-01); Centers for Disease Control and Prevention (RFPDP15-002); Kaiser Permanente Southern California (U18DP006133, U48/CCU919219, U01DP000246, U18DP002714); University of Colorado Denver (U18DP006139, U48/CCU819241-3, U01DP000247, U18DP000247-06A1); Cincinnati Children’s Hospital Medical Center (U18DP006134, U48/CCU519239, U01DP000248, 1U18DP002709); University of North Carolina at Chapel Hill (U18DP006138, U48/CCU419249, U01DP000254, U18DP002708); Seattle Children’s Hospital (U18DP006136, U58/CCU019235-4, U01DP000244, U18DP002710-01); Wake Forest University School of Medicine (U18DP006131, U48/CCU919219, U01DP000250, 200-2010-35171); South Carolina Clinical and Translational Research Institute at the Medical University of South Carolina (UL1TR001450); Seattle Children’s Hospital and the University of Washington (UL1TR00423); University of Colorado Pediatric Clinical and Translational Research Center (UL1TR000154); Barbara Davis Center for Diabetes at the University of Colorado Denver (P30-DK-57516); University of Cincinnati (UL1TR001425); Ohio Department of Health

OBJECTIVE: To address a common perception that hypoglycemia is associated with increased dietary intake, we examined calorie and carbohydrate consumption on days with and without hypoglycemia among adolescents with type 1 diabetes (T1D). METHODS: Days (N=274) with 24-hour dietary recalls and continuous glucose monitoring were available for 122 adolescents with T1D in the Flexible Lifestyle Empowering Change trial (age 13–16 years, diabetes duration >1 year, hemoglobin A1c 8–13%). Days with no hypoglycemia, clinical hypoglycemia (54–69 mg/dL) or clinically serious hypoglycemia (

BACKGROUND & AIMS: Increasing dietary intake of n-3 EPA+DHA and lowering dietary n-6 LA is under investigation as a therapeutic diet for improving chronic pain syndromes as well as other health outcomes. Herein we describe the diet methodology used to modulate intake of n-3 and n-6 PUFA in a free living migraine headache population and report on nutrient intake, BMI and diet acceptability achieved at week 16 of the intensive diet intervention and week 22 follow-up time-point. METHODS: A total of 178 participants were randomized and began one of three diet interventions: 1) a high n-3 PUFA, average n-6 PUFA (H3) diet targeting 1500 mg EPA+DHA/day and 7% of energy (en%) from n-6 linoleic acid (LA), 2) a high-n-3 PUFA, low-n-6 PUFA (H3L6) targeting 1500 mg EPA+DHA/day and

Research on eating patterns in T1D is scarce, especially in youth. This population is in particular need of effective behavioral strategies during adolescence when HbA1c peaks and lifelong behaviors form. Case studies from pediatric T1D clinics suggest SE (consistent frequency, timing and spacing of meals, snacks and macronutrients throughout the day) is helpful for meeting glycemic targets, yet the health impacts and feasibility of SE as a clinical guideline are not well documented. We developed SE variables and used linear mixed effects models to explore associations between individual SE behaviors and CGM metrics in 24-hr dietary recall and 7-day CGM data of adolescents (n=319, 13-16 yrs, HbA1c 8-13%) from the Flexible Lifestyles Empowering Change (FLEX) intervention. We also conducted a small pilot (n=9, 13-16 yrs, HbA1c 8-13%), “MyPlan”, to explore acceptability of SE. In FLEX, SE behaviors were associated with favorable CGM profile, including time in range (Table 1). In MyPlan, acceptability of SE (scale 0-8) was high among adolescents (mean: 6.8; SE:1.6) and their parents (mean: 7.1 SE: 1.2). Our preliminary evidence suggests benefit and feasibility of SE in adolescents. To inform future trials and ultimately, clinical guidelines, further analyses in diverse samples are needed to more specifically characterize SE patterns and understand their role in T1D health outcomes. Disclosure A. Cristello: None. A.R. Kahkoska: Other Relationship; Self; Novo Nordisk A/S. C.E. Smart: None. S.C. Couch: None. D. Igudesman: None. L. Kager: None. E.J. Mayer-Davis: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (1UC4DK101132)

Through their effects on the intestinal epithelium and immunity, gut microbes and their fermentative byproducts can influence metabolic and psychological health parameters in patients with AN. Integrative therapies that restore gut microbial health may also benefit individuals with conditions in which gut microbial dysbiosis manifests, as in T1D, as individuals in this population experience difficulties with weight stabilization and altered metabolic traits and are vulnerable to developing symptoms of disordered eating. Although the clinical implications of the brain-gut-microbiota axis are not yet fully understood in AN, targeted pro- and antibiotics represent two mechanisms by which augmenting the gut microbiota can serve as an ancillary therapy for lessening severity of bloating and discomfort during treatment. Specifically, antibiotics could be used to eliminate known pathogens that disrupt intestinal integrity, while targeted probiotics may help to restore beneficial species known to promote gut epithelial health. Thus, we conclude that controlled studies investigating use of such novel therapies, including FMT, should be undertaken as part of an interdisciplinary approach to address metabolic and psychological factors that influence acute and long-term health outcomes in AN and T1D. We highlight again that work on the role of the intestinal microbiota in eating disorders is both limited and confined to AN. As is commonly the case, biological research in eating disorders starts with AN before progressing to the other eating disorders presentations. Yet, in many ways, eating disorders are model conditions on in which to explore the gut-brain axis given the centrality of eating and metabolic factors to the illnesses. We encourage investigators to expand on this early work by conducting studies on the other eating disorders (both in youth and adults) to develop a more comprehensive picture of the role that the intestinal microbiota plays in the development and maintenance of and recovery from these debilitating illnesses.

Intensive insulin therapy may have the unintended consequence of increased adiposity, contributing to the high prevalence of overweight and obesity in people with T1D. We examined the longitudinal association of insulin intensification with estimated body fat percentage (eBFP) among 746 individuals with T1D (age 10-21 years at initial visit) in the SEARCH for Diabetes in Youth study. eBFP was calculated using validated, published sex and race/ethnic specific formulae incorporating age and anthropometrics. Insulin intensification was defined as more intense, less intense or no change, in which “more intense” was an increased number of injections or addition of long-acting insulin, or a change from injections to an insulin pump. Sex-specific, linear mixed effects models used continuous eBFP at each available visit (baseline, and 1-4 follow-up visits; median T1D duration at the last visit, 8 years). Interaction terms between time and insulin intensification relative to change in eBFP tested the study hypothesis. Mean diagnosis age was 12.7 years ± 2.5, 47% were female, 80% non-Hispanic white. At baseline, mean BMIz score was 0.51 ± 0.93, with 32% overweight or with obesity. Although BMIz and weight status did not differ by sex, eBFP was significantly higher in females compared to males (32.4% ± 5.3 and 25.3% ± 5.9 respectively; p Disclosure E. Mayer-Davis: None. B.A. Reboussin: None. C. Pihoker: None. A.R. Kahkoska: None. D. Dabelea: None. L.M. Dolan: None. E.T. Jensen: None. D. Igudesman: None. J.M. Lawrence: None. S. Saydah: None. R. Wadwa: Advisory Panel; Self; Eli Lilly and Company. Research Support; Self; Beta Bionics, MannKind Corporation, Novo Nordisk Inc., Tandem Diabetes Care, Xeris Pharmaceuticals, Inc. Other Relationship; Self; Dexcom, Inc. Funding Centers for Disease Control and Prevention; National Institutes of Health

The impact of weight management in persons with type 1 diabetes (T1D) from childhood into adulthood is not well described. The purpose of the study is to explore qualitative themes presented by young adults on both weight and T1D management. We analyzed focus group data from 17 young adults with T1D via inductive qualitative analysis. Major themes were compared to published themes presented by youth with T1D to categorize thematic progression from youth to adulthood. Themes from young adults with T1D, when compared to youth, are categorized as: unchanged, evolving, and newly reported. Hypoglycemia and a sense of futility around exercise was an unchanged theme. Importance of insulin usage and a need for a healthy personal relationship with T1D evolved to gather greater conviction. Newly reported themes are unique to integration of adulthood into T1D, such as family planning and work-diabetes balance. Young adults also newly reported negative experiences with providers in their younger years and desire for more supportive provider relationships. Issues identified by youth regarding the dual management of T1D and weight rarely resolve, but rather, persist unchanged or integrate other aspects of young adulthood via evolving or newly emerged themes. Individualized and age-appropriate clinical support and practice guidelines are warranted to facilitate the dual management of weight and T1D in persons with T1D Disclosure A. Addala: None. D. Igudesman: None. A.R. Kahkoska: None. F.R. Muntis: None. K.J. Souris: None. K.J. Whitaker: None. R.E. Pratley: Consultant; Self; Sanofi US. Other Relationship; Self; AstraZeneca, Eli Lilly and Company, GlaxoSmithKline plc., Janssen Global Services, LLC., Janssen Research & Development, Lexicon Pharmaceuticals, Inc., Ligand Pharmaceuticals, Inc., Merck Sharp & Dohme Corp., Mundipharma, Novo Nordisk Inc., Pfizer Inc., Sanofi, Takeda Development Center Americas, Inc. E. Mayer-Davis: None.

OBJECTIVES: Examine the relationship between household food insecurity (HFS; i.e., access to nutritionally adequate and safe food) and disordered eating behaviors (i.e., restriction, bingeing, insulin manipulation, etc.) among a sample of young adults with youth-onset type 1 (T1D) or type 2 diabetes (T2D). METHODS: We used cross-sectional data from the SEARCH for Diabetes in Youth Study. Individuals (n = 792) ages ≥18 years completed the U.S. Household Food Security Survey Module and the Diabetes Eating Problem Survey-Revised (DEPS-R) between 2016 and 2019. We converted HFS scores to a 10-point scale and dichotomized scores into food secure (HFS ≤ 2.2) vs. food insecure (HFS > 2.2). Multivariable linear regression was used to evaluate the association of HFS with continuous DEPS-R score (i.e., 0–80, with a greater score indicating greater symptoms of disordered eating), adjusting for potential confounders (i.e., sex, age, race/ethnicity, education, household income, insurance, depressive symptoms, and duration of diabetes). We further stratified analyses by diabetes type. RESULTS: Participants were on average 23.8 ± 3.7 years, 59.6% female, 49.6% non-Latino white, and had a mean diabetes duration of 11.5 ± 3.1 years. The overall mean DEPS-R score was 17.3 ± 10.0 points. Mean DEPS-R scores in individuals living in food secure households (n = 709) and food insecure households (n = 83) were 16.6 ± 9.45 and 23.4 ± 12.4, respectively. The adjusted DEPS-R scores were 3.6 points (95% CI = 1.5, 5.7; P 0.05). CONCLUSIONS: Lower household food security in young adults with T1D, but not T2D, is associated with increased disordered eating scores. These results may allow clinicians and other public health professionals to target individuals with low household food security as being at higher risk for potential disordered eating, particularly those with T1D. FUNDING SOURCES: NIDDK & CDC.