Medical resource use data and responses to the EuroQol 5-Dimension (EQ-5D) instrument were collected at baseline and throughout the trial. Medical resources and medications were assigned values by using U.S. Medicare payments and wholesale acquisition costs, respectively. Secondary analyses used English costs.

Patients were followed for an average of 3.3 years, during which time those randomized to EQW experienced 0.41 fewer inpatient days (7.05 vs. 7.46 days; relative rate ratio 0.91; P = 0.05). Rates of outpatient medical visits were similar, as were total inpatient and outpatient costs. Mean costs for nonstudy diabetes medications over the study period were ~$1,600 lower with EQW than with placebo (P = 0.01). Total within-study costs, excluding study medication, were lower in the EQW arm than in the placebo arm ($28,907 vs. $30,914; P ≤ 0.01). When including the estimated cost of EQW, total mean costs were significantly higher in the EQW group than in the placebo group ($42,697 vs. $30,914; P < 0.01). With English costs applied, mean total costs, including exenatide costs, were £1,670 higher in the EQW group than the placebo group (£10,874 vs. £9,204; P < 0.01). There were no significant differences in EQ-5D health utilities between arms over time.

Medical costs were lower in the EQW arm than the placebo arm, but total costs were significantly higher once the cost of branded exenatide was incorporated.

We studied 706 single autoantibody–positive pediatric TrialNet participants (ages 1.6–18.6 years at baseline). Cumulative excess BMI (ceBMI) was calculated for each participant based on longitudinally accumulated BMI ≥85th age- and sex-adjusted percentile. Recursive partitioning analysis and multivariable modeling defined the age cut point differentiating the risk for progression to multiple positive autoantibodies.

At baseline, 175 children (25%) had a BMI ≥85th percentile. ceBMI range was –9.2 to 15.6 kg/m² (median –1.91), with ceBMI ≥0 kg/m² corresponding to persistently elevated BMI ≥85th percentile. Younger age increased the progression to multiple autoantibodies, with age cutoff of 9 years defined by recursive partitioning analysis. Although ceBMI was not significantly associated with progression from single to multiple autoantibodies overall, there was an interaction with ceBMI ≥0 kg/m², age, and HLA (P = 0.009). Among children ≥9 years old without HLA DR3-DQ2 and DR4-DQ8, ceBMI ≥0 kg/m² increased the rate of progression from single to multiple positive autoantibodies (hazard ratio 7.32, P = 0.004) and conferred a risk similar to that in those with T1D-associated HLA haplotypes. In participants <9 years old, the effect of ceBMI on progression to multiple autoantibodies was not significant regardless of HLA type.

These data support that elevated BMI may exacerbate islet autoimmunity prior to clinical T1D, particularly in children with lower risk based on age and HLA. Interventions to maintain normal BMI may prevent or delay the progression of islet autoimmunity.

We monitored 4,372 women with a history of GDM participating in the Nurses’ Health Study II for incident type 2 diabetes over 25 years up to 2017. Lactation history was obtained through follow-up questionnaires to calculate lactation duration. Follow-up blood samples were collected from a subset of these women at median age of 58 years through the Diabetes & Women’s Health Study.

We documented 873 incident cases of type 2 diabetes during 87,411 person-years of follow-up. Longer duration of lactation was associated with lower risk of type 2 diabetes for both total lactation (hazard ratio 1.05 [95% CI 0.83–1.34] for up to 6 months, 0.91 [0.72–1.16] for 6–12 months, 0.85 [0.67–1.06] for 12–24 months, and 0.73 [0.57–0.93] for >24 months, compared with 0 months; P-trend = 0.003) and exclusive breastfeeding (P-trend = 0.002) after adjustment for age, ethnicity, family history of diabetes, parity, age at first birth, smoking, diet quality, physical activity, and prepregnancy BMI. Longer duration of lactation was also associated with lower HbA_1c, fasting plasma insulin, and C-peptide concentrations among women without type 2 diabetes at follow-up (all adjusted P-trend ≤0.04).

Longer duration of lactation is associated with a lower risk of type 2 diabetes and a favorable glucose metabolic biomarker profile among women with a history of GDM. The underlying mechanisms and impact on diabetes complications, morbidity, and mortality remain to be determined.

We included 17,026 adults (8,346 men and 8,680 women) who were part of the China Health and Nutrition Survey (1991–2015) prospective cohort. Dietary intake was measured by three consecutive 24-h dietary recalls combined with a household food inventory. Diabetes cases were identified through a questionnaire. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% CIs.

A total of 547 men and 577 women developed diabetes during 202,138 person-years of follow-up. For men, the adjusted HRs (95% CIs) for quintiles of nonheme iron intake were 1.00, 0.77 (0.58–1.02), 0.72 (0.54–0.97), 0.63 (0.46–0.85), and 0.87 (0.64–1.19) (P-nonlinearity = 0.0015). The corresponding HRs (95% CIs) for women were 1.00, 0.63 (0.48–0.84), 0.57 (0.43–0.76), 0.58 (0.43–0.77), and 0.67 (0.49–0.91) (P-nonlinearity < 0.0001). The dose-response curves for the association between nonheme iron and total iron intake and diabetes followed a reverse J shape in men and an L shape in women. No significant associations were observed between heme iron intake and diabetes risk.

Total iron and nonheme iron intake was associated with diabetes risk, following a reverse J-shaped curve in men and an L-shaped curve in women. Sufficient intake of nonheme or total iron might be protective against diabetes, while excessive iron intake might increase the risk of diabetes among men.

We pooled individual-level data from 29 nationally representative surveys conducted between 2008 and 2016, totaling 588,574 participants aged ≥25 years. Diabetes prevalence and the subset with undiagnosed diabetes was calculated overall and by country, World Bank income group (WBIG), and geographic region. Multivariable Poisson regression models were used to estimate relative risk (RR).

Overall, prevalence of diabetes in 29 LMICs was 7.5% (95% CI 7.1–8.0) and of undiagnosed diabetes 4.9% (4.6–5.3). Diabetes prevalence increased with increasing WBIG: countries with low-income economies (LICs) 6.7% (5.5–8.1), lower-middle-income economies (LMIs) 7.1% (6.6–7.6), and upper-middle-income economies (UMIs) 8.2% (7.5–9.0). Compared with no formal education, greater educational attainment was associated with an increased risk of diabetes across WBIGs, after adjusting for BMI (LICs RR 1.47 [95% CI 1.22–1.78], LMIs 1.14 [1.06–1.23], and UMIs 1.28 [1.02–1.61]).

Among 29 LMICs, diabetes prevalence was substantial and increased with increasing WBIG. In contrast to the association seen in high-income countries, diabetes risk was highest among those with greater educational attainment, independent of BMI. LMICs included in this analysis may be at an advanced stage in the nutrition transition but with no reversal in the socioeconomic gradient of diabetes risk.

Chromosome 6 was imputed using SNP2HLA, with conditional analysis performed in type 1 diabetes case subjects (n = 1,985) and control subjects (n = 2,219). The same approach was applied to a LADA cohort (n = 1,428) using population-based control subjects (n = 2,850) and in a separate replication cohort (656 type 1 diabetes case, 823 LADA case, and 3,218 control subjects).

The strongest associations in the MHC class II region (rs3957146, β [SE] = 1.44 [0.05]), as well as the independent effect of MHC class I genes, on type 1 diabetes risk, particularly HLA-B*39 (β [SE] = 1.36 [0.17]), were confirmed. The conditional analysis in LADA versus control subjects showed significant association in the MHC class II region (rs3957146, β [SE] = 1.14 [0.06]); however, we did not observe significant independent effects of MHC class I alleles in LADA.

In LADA, the independent effects of MHC class I observed in type 1 diabetes were not observed after conditioning on the leading MHC class II associations, suggesting that the MHC class I association may be a genetic discriminator between LADA and childhood-onset type 1 diabetes.

Urinary samples of 87 children (44 girls) aged 8.5–17.9 years with obesity (BMI >97th percentile) were quantified for 31 steroid metabolites by GC-MS. Defined as HOMA-IR >95th percentile and fasting glucose-to-insulin ratio >0.3, IR was diagnosed in 20 (of 87 [23%]) of the examined patients. The steroidal fingerprints of subjects with IR were compared with those of obese children without IR (non-IR). The steroidal signature of IR was created from the product of IR – non-IR for each of the 31 steroids.

IR and non-IR groups of children had comparable mean age (13.7 ± 1.9 and 14.6 ± 2.4 years, respectively) and z score BMI (2.7 ± 0.5 and 2.7 ± 0.5, respectively). The steroidal signature of IR was characterized by high adrenal androgens, glucocorticoids, and mineralocorticoid metabolites; higher 5α-reductase (An/Et) (P = 0.007) and 21-hydroxylase [(THE + THF + αTHF)/PT] activity (P = 0.006); and lower 11βHSD1 [(THF + αTHF)/THE] activity (P = 0.012).

The steroidal metabolomic signature of IR in obese children is characterized by enhanced secretion of steroids from all three adrenal pathways. As only the fasciculata and reticularis are stimulated by ACTH, these findings suggest that IR directly affects the adrenals. We suggest a vicious cycle model, whereby glucocorticoids induce IR, which could further stimulate steroidogenesis, even directly. We do not know whether obese children with IR and the new signature may benefit from amelioration of their hyperadrenalism.