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Aims/hypothesis: Dietary patterns characterised by high intakes of vegetables may lower the risk of pre-eclampsia and premature birth in the general population. The effect of dietary patterns in women with type 1 diabetes, who have an increased risk of complications in pregnancy, is not known. The aim of this study was to investigate the relationship between dietary patterns and physical activity during pregnancy and maternal complications and birth outcomes in women with type 1 diabetes. We also compared dietary patterns in women with and without type 1 diabetes., Methods: Diet was assessed in the third trimester using a validated food frequency questionnaire in participants followed prospectively in the multi-centre Environmental Determinants of Islet Autoimmunity (ENDIA) study. Dietary patterns were characterised by principal component analysis. The Pregnancy Physical Activity Questionnaire was completed in each trimester. Data for maternal and birth outcomes were collected prospectively., Results: Questionnaires were completed by 973 participants during 1124 pregnancies. Women with type 1 diabetes (n=615 pregnancies with dietary data) were more likely to have a 'fresh food' dietary pattern than women without type 1 diabetes (OR 1.19, 95% CI 1.07, 1.31; p=0.001). In women with type 1 diabetes, an increase equivalent to a change from quartile 1 to 3 in 'fresh food' dietary pattern score was associated with a lower risk of pre-eclampsia (OR 0.37, 95% CI 0.17, 0.78; p=0.01) and premature birth (OR 0.35, 95% CI 0.20, 0.62, p<0.001). These associations were mediated in part by BMI and HbA 1c . The 'processed food' dietary pattern was associated with an increased birthweight (β coefficient 56.8 g, 95% CI 2.8, 110.8; p=0.04). Physical activity did not relate to outcomes., Conclusions/interpretation: A dietary pattern higher in fresh foods during pregnancy was associated with sizeable reductions in risk of pre-eclampsia and premature birth in women with type 1 diabetes., (© 2024. The Author(s).)

Objective: Continuous glucose monitoring (CGM) can detect early dysglycemia in older children and adults with presymptomatic type 1 diabetes (T1D) and predict risk of progression to clinical onset. However, CGM data for very young children at greatest risk of disease progression are lacking. This study aimed to investigate the use of CGM data measured in children being longitudinally observed in the Australian Environmental Determinants of Islet Autoimmunity (ENDIA) study from birth to age 10 years., Research Design and Methods: Between January 2021 and June 2023, 31 ENDIA children with persistent multiple islet autoimmunity (PM Ab+) and 24 age-matched control children underwent CGM assessment alongside standard clinical monitoring. The CGM metrics of glucose SD (SDSGL), coefficient of variation (CEV), mean sensor glucose (SGL), and percentage of time >7.8 mmol/L (>140 mg/dL) were determined and examined for between-group differences., Results: The mean (SD) ages of PM Ab+ and Ab- children were 4.4 (1.8) and 4.7 (1.9) years, respectively. Eighty-six percent of eligible PM Ab+ children consented to CGM wear, achieving a median (quartile 1 [Q1], Q3) sensor wear period of 12.5 (9.0, 15.0) days. PM Ab+ children had higher median (Q1, Q3) SDSGL (1.1 [0.9, 1.3] vs. 0.9 [0.8, 1.0] mmol/L; P < 0.001) and CEV (17.3% [16.0, 20.9] vs. 14.7% [12.9, 16.6]; P < 0.001). Percentage of time >7.8 mmol/L was greater in PM Ab+ children (median [Q1, Q3] 8.0% [4.4, 13.0] compared with 3.3% [1.4, 5.3] in Ab- children; P = 0.005). Mean SGL did not differ significantly between groups (P = 0.10)., Conclusions: CGM is feasible and well tolerated in very young children at risk of T1D. Very young PM Ab+ children have increased SDSGL, CEV, and percentage of time >7.8 mmol/L, consistent with prior studies involving older participants., (© 2024 by the American Diabetes Association.)

Background: Cystic fibrosis (CF) related diabetes affects up to half of all adults with CF and is associated with higher morbidity and mortality. Our aim is to codevelop an ideal model of care that integrates diabetes technology and better meets the needs of adults living with the condition to improve attendance, engagement, service satisfaction, and clinical outcomes., Methods: Using qualitative research methods, we evaluated disease perceptions, barriers, and enablers to optimal CF-related diabetes management and service delivery. Integration of continuous glucose monitoring (CGM) was also explored. An initial broad purposive consumer survey was followed by focus groups with end-users. Grounded theory approach was utilized with major problem areas identified then explored, coded, and grouped into requisites for an "ideal model of care" for adults living with CF-related diabetes., Results: Two key themes emerged (i) an ideal model of care consisted of a dual-specialty service co-led by endocrinology and CF physicians and supported by diabetes educator and CF dietitian with a goal to provide consistent and personalized diabetes management and (ii) CGM was acceptable for use in adults with CF-related diabetes with many perceived benefits and should be integrated into the model of care. Barriers to optimizing glycemic control included diet, finger-prick testing, reduced access to CGM, and pulmonary exacerbations. End-user feedback on CGM was overwhelmingly positive with regard to operability. CGM was also identified as a tool that could be used to engage, educate, and empower adults living with CF-related diabetes and facilitate constructive and personalized clinical decision-making by healthcare providers., Conclusion: For adults living with CF, a diagnosis of diabetes is associated with increased treatment burden. Our findings suggest an "ideal model of care" for CF-related diabetes would be co-led by endocrinology services integrated within a pre-existing CF service, incorporating CGM., (© 2024 The Authors. Pediatric Pulmonology published by Wiley Periodicals LLC.)

Introduction: The Environmental Determinants of Islet Autoimmunity (ENDIA) Study is an ongoing Australian prospective cohort study investigating how modifiable prenatal and early-life exposures drive the development of islet autoimmunity and type 1 diabetes (T1D) in children. In this profile, we describe the cohort's parental demographics, maternal and neonatal outcomes and human leukocyte antigen (HLA) genotypes., Research Design and Methods: Inclusion criteria were an unborn child, or infant aged less than 6 months, with a first-degree relative (FDR) with T1D. The primary outcome was persistent islet autoimmunity, with children followed until a T1D diagnosis or 10 years of age. Demographic data were collected at enrollment. Lifestyle, clinical and anthropometric data were collected at each visit during pregnancy and clinical pregnancy and birth data were verified against medical case notes. Data were compared between mothers with and without T1D. HLA genotyping was performed on the ENDIA child and all available FDRs., Results: The final cohort comprised 1473 infants born to 1214 gestational mothers across 1453 pregnancies, with 80% enrolled during pregnancy. The distribution of familial T1D probands was 62% maternal, 28% paternal and 11% sibling. The frequency of high-risk HLA genotypes was highest in T1D probands, followed by ENDIA infants, and lowest among unaffected family members. Mothers with T1D had higher rates of pregnancy complications and perinatal intervention, and larger babies of shorter gestation. Parent demographics were comparable to the Australian population for age, parity and obesity. A greater percentage of ENDIA parents were Australian born, lived in a major city and had higher socioeconomic advantage and education., Conclusions: This comprehensive profile provides the context for understanding ENDIA's scope, methodology, unique strengths and limitations. Now fully recruited, ENDIA will provide unique insights into the roles of early-life factors in the development of islet autoimmunity and T1D in the Australian environment., Trial Registration Number: ACTRN12613000794707., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)