The Environmental Determinants of Diabetes in the Young (TEDDY) study followed 7,522 genetically high-risk children in Sweden, Finland, Germany, and the U.S. from birth for a median of 9.0 years (interquartile range 5.7–10.6) with available growth data. Of these, 761 (10.1%) children developed IA and 290 (3.9%) children were diagnosed with T1D. Bayesian two-phase piecewise linear mixed models with a random change point were used to estimate children’s individual growth trajectories. Cox proportional hazards models were used to assess the effects of associated growth parameters on the risks of IA and progression to T1D.

A higher rate of weight gain in infancy was associated with increased IA risk (hazard ratio [HR] 1.09 [95% CI 1.02, 1.17] per 1 kg/year). A height growth pattern with a lower rate in infancy (HR 0.79 [95% CI 0.70, 0.90] per 1 cm/year), higher rate in early childhood (HR 1.48 [95% CI 1.22, 1.79] per 1 cm/year), and younger age at the phase transition (HR 0.76 [95% CI 0.58, 0.99] per 1 month) was associated with increased risk of progression from IA to T1D. A higher rate of weight gain in early childhood was associated with increased risk of progression from IA to T1D (HR 2.57 [95% CI 1.34, 4.91] per 1 kg/year) in children with first-appearing GAD autoantibody only.

Growth patterns in early life better clarify how specific growth phases are associated with the development of T1D.

Data on health care resource utilization from 100,391 people with type 2 diabetes were extracted from the electronic database used at the Catalan Health Institute. Multivariate regression models were carried out to test the impact of glycemic control (HbA_1c) on total health care, hospital admission, and medication costs; model 1 adjusted for a variety of covariates, and model 2 also included micro- and macrovascular complications. Glycemic control was classified as good for HbA_1c <7%, fair for ≥7% to <8%, poor for ≥8% to <10%, and very poor for ≥10%.

Mean per patient annual direct medical costs were 3,039 ± SD 6,581. Worse glycemic control was associated with higher total health care costs: compared with good glycemic control, health care costs increased by 18% (509.82) and 23% (661.35) in patients with very poor and poor glycemic control, respectively, when unadjusted and by 428.3 and 395.1, respectively, in model 2. Medication costs increased by 12% in patients with fair control and by 28% in those with very poor control (model 2). Patients with poor control had a higher probability of hospitalization than those with good control (5% in model 2) and a greater average cost when hospitalization occurred (811).

Poor glycemic control was directly related to higher total health care, hospitalization, and medication costs. Preventive strategies and good glycemic control in people with type 2 diabetes could reduce the economic impact associated with this disease.

We analyzed data from a large representative sample of adults with T1D (N = 5,558). We assessed the presence of symptomatic neuropathy using the dichotomized (≥4) Michigan Neuropathy Screening Instrument Patient Questionnaire score. Logistic regression models were used to investigate associations between DPN and risk factors, as well as with other complications.

The burden of DPN is substantial with 13% prevalence overall. Adjusting for attained age, diabetes duration, and sex, the odds of DPN increased mainly with waist-to-hip ratio, lipids, poor glycemic control (odds ratio 1.51 [95% CI 1.21–1.89] for levels of 75 vs. 53 mmol/mol), ever versus never smoking (1.67 [1.37–2.03]), and worse renal function (1.96 [1.03–3.74] for estimated glomerular filtration rate levels <30 vs. ≥90 mL/min/1.73 m²). The odds significantly decreased with higher HDL cholesterol (0.77 [0.66–0.89] per mmol/L). Living in more deprived areas was associated with DPN (2.17 [1.78–2.65]) for more versus less deprived areas adjusted for other risk factors. Finally, individuals with prevalent DPN were much more likely than others to have other diabetes complications.

Diabetic neuropathy remains substantial, particularly affecting those in the most socioeconomically deprived groups. Those with clinically manifest neuropathy also have a higher burden of other complications and elevated levels of modifiable risk factors. These data suggest that there is considerable scope to reduce neuropathy rates and narrow the socioeconomic differential by better risk factor control.

A post hoc analysis was performed of the SWITCH (SWITCH 1: n = 501, type 1 diabetes; SWITCH 2: n = 721, type 2 diabetes) and DEVOTE (n = 7,637, type 2 diabetes) trials utilizing the IHSG low glucose definitions. Patients in all trials were randomized to either insulin degludec or insulin glargine 100 units/mL. In the main analysis, the following definitions were compared: 1) American Diabetes Association (ADA) 2005 (plasma glucose [PG] confirmed ≤3.9 mmol/L with symptoms); and 2) IHSG level 2 (PG confirmed <3.0 mmol/L, independent of symptoms).

In SWITCH 2, the estimated rate ratios of hypoglycemic events indicated increasing differences between treatments with decreasing PG levels until 3.0 mmol/L, following which no additional treatment differences were observed. Similar results were observed for the SWITCH 1 trial. In SWITCH 2, the IHSG level 2 definition produced a rate ratio that was lower than the ADA 2005 definition.

The IHSG level 2 definition was validated in a series of clinical trials, demonstrating its ability to discriminate between basal insulins. This definition is therefore recommended to be uniformly adopted by regulatory bodies and used in future clinical trials.

We employed a transethnic approach with a cohort of Asian origin (Singapore) (N = 2,061) and a cohort of European origin (France) (N = 1,438) included in the study. We used survival analyses to study the association of urine haptoglobin with risk of all-cause and cause-specific mortality.

A total of 365 and 525 deaths were registered in the Singapore cohort (median follow-up 7.5 years [interquartile range 3.5–12.8]) and French SURDIAGENE cohort (median follow-up 6.8 years [interquartile range 4.3–10.5], respectively. Singapore participants with urine haptoglobin in quartiles 2 to 4 had higher risk for all-cause mortality compared with quartile 1 (unadjusted hazard ratio [HR] 1.47 [95% CI 1.02–2.11], 2.28 [1.62–3.21], and 4.64 [3.39–6.35], respectively). The association remained significant in quartile 4 after multiple adjustments (1.68 [1.15–2.45]). Similarly, participants in the French cohort with haptoglobin in quartile 4 had significantly higher hazards for all-cause mortality compared with quartile 1 (unadjusted HR 2.67 [2.09–3.42] and adjusted HR 1.49 [1.14–1.96]). In both cohorts, participants in quartile 4 had a higher risk of mortality attributable to cardiovascular disease and infection but not malignant tumor.

Urine haptoglobin predicts risk of mortality independent of traditional risk factors, suggesting that it may potentially be a novel biomarker for risk of mortality in patients with type 2 diabetes.

We retrospectively analyzed records of patients presenting with a first type 1 MI at age ≤50 years from 2000 to 2016. Diabetes was defined as a hemoglobin A_1c ≥6.5% (48 mmol/mol) or a documented diagnosis of or treatment for diabetes. Vital status was ascertained for all patients, and cause of death was adjudicated.

Among 2,097 young patients who had a type 1 MI (mean age 44.0 ± 5.1 years, 19.3% female, 73% white), diabetes was present in 416 (20%), of whom 172 (41%) were receiving insulin. Over a median follow-up of 11.2 years (interquartile range 7.3–14.2 years), diabetes was associated with a higher all-cause mortality (hazard ratio 2.30; P < 0.001) and cardiovascular mortality (2.68; P < 0.001). These associations persisted after adjusting for baseline covariates (all-cause mortality: 1.65; P = 0.008; cardiovascular mortality: 2.10; P = 0.004).

Diabetes was present in 20% of patients who presented with their first MI at age ≤50 years and was associated with worse long-term all-cause and cardiovascular mortality. These findings highlight the need for implementing more-aggressive therapies aimed at preventing future adverse cardiovascular events in this population.

Patients with type 1 diabetes receiving regular care were recruited in this observational cross-sectional study and divided into four groups according to their Lp(a) levels in nmol/L (very low <10, low 10–30, intermediate 30–120, high >120). Prevalence of vascular complications was compared between the groups. In addition, the association between metabolic control, measured as HbA_1c, and Lp(a) was studied.

The patients (n = 1,860) had a median age of 48 years, diabetes duration of 25 years, and HbA_1c of 7.8% (61 mmol/mol). The median Lp(a) was 19 (interquartile range 10–71) nmol/L. No significant differences between men and women were observed, but Lp(a) levels increased with increasing age. Patients in the high Lp(a) group had higher prevalence of complications than patients in the very low Lp(a) group. The age- and smoking-status–adjusted relative risk ratio of having any macrovascular disease was 1.51 (95% CI 1.01–2.28, P = 0.048); coronary heart disease, 1.70 (95% CI 0.97–3.00, P = 0.063); albuminuria, 1.68 (95% CI 1.12–2.50, P = 0.01); and calcified aortic valve disease, 2.03 (95% CI 1.03–4.03; P = 0.042). Patients with good metabolic control, HbA_1c <6.9% (<52 mmol/mol), had significantly lower Lp(a) levels than patients with poorer metabolic control, HbA_1c >6.9% (>52 mmol/mol).

Lp(a) is a significant risk factor for macrovascular disease, albuminuria, and calcified aortic valve disease in patients with type 1 diabetes. Poor metabolic control in patients with type 1 diabetes is associated with increased Lp(a) levels.

FPG and urinary biomarkers of oxidative DNA damage (8-hydroxy-deoxyguanosine [8-OHdG]), lipid peroxidation (8-iso-prostaglandin-F2α [8-iso-PGF2α]), and acrylamide exposure (N-acetyl-S-[2-carbamoylethyl]-l-cysteine [AAMA], N-acetyl-S-[2-carbamoyl-2-hydroxyethyl]-l-cysteine [GAMA]) were measured for 3,270 general adults from the Wuhan-Zhuhai cohort. The associations of urinary acrylamide metabolites with 8-OHdG, 8-iso-PGF2α, and FPG were assessed by linear mixed models. The mediating roles of 8-OHdG and 8-iso-PGF2α were evaluated by mediation analysis.

We found significant linear positive dose-response relationships of urinary acrylamide metabolites with 8-OHdG, 8-iso-PGF2α, and FPG (except GAMA with FPG) and 8-iso-PGF2α with FPG. Each 1-unit increase in log-transformed level of AAMA, AAMA + GAMA (UAAM), or 8-iso-PGF2α was associated with a 0.17, 0.15, or 0.23 mmol/L increase in FPG, respectively (P and/or P trend < 0.05). Each 1% increase in AAMA, GAMA, or UAAM was associated with a 0.19%, 0.27%, or 0.22% increase in 8-OHdG, respectively, and a 0.40%, 0.48%, or 0.44% increase in 8-iso-PGF2α, respectively (P and P trend < 0.05). Increased 8-iso-PGF2α rather than 8-OHdG significantly mediated 64.29% and 76.92% of the AAMA- and UAAM-associated FPG increases, respectively.

Exposure of the general adult population to acrylamide was associated with FPG elevation, oxidative DNA damage, and lipid peroxidation, which in turn partly mediated acrylamide-associated FPG elevation.

A total of 4,699 people with diabetes who enrolled in the National Health and Nutrition Examination Survey from 2003 to 2014 were recruited for this study. Energy and macronutrient intake was measured by a 24-h dietary recall. The differences () in energy and macronutrient intake between dinner and breakfast ( = dinner – breakfast) were categorized into quintiles. Death information was obtained from the National Death Index until 2015. Cox proportional hazards regression models were developed to evaluate the survival relationship between and diabetes, cardiovascular disease (CVD), and all-cause mortality.

Among the 4,699 participants, 913 deaths, including 269 deaths due to diabetes and 314 deaths due to CVD, were documented. After adjustment for potential confounders, compared with participants in the lowest quintile of in terms of total energy and protein, participants in the highest quintile were more likely to die due to diabetes (hazard ratio [HR]_energy 1.92, 99% CI 1.08–3.42; HR_protein 1.92, 99% CI 1.06–3.49) and CVD (HR_energy 1.69, 99% CI 1.02–2.80; HR_protein 1.96, 99% CI 1.14–3.39). The highest quintile of total fat was related to CVD mortality (HR 1.67, 99% CI 1.01–2.76). Isocalorically replacing 5% of total energy at dinner with breakfast was associated with 4% and 5% lower risk of diabetes (HR 0.96, 95% CI 0.94–0.98) and CVD (HR 0.95, 95% CI 0.93–0.97) mortality, respectively.

Higher intake of energy, total fat, and protein from dinner than breakfast was associated with greater diabetes, CVD, and all-cause mortality in people with diabetes.

A total of 291 subjects aged 35–60 years with normal glucose tolerance (NGT), newly diagnosed impaired fasting glucose or glucose tolerance (IFG/IGT), or type 2 diabetes were screened by a standard 2-h oral glucose tolerance test (OGTT) with the use of traditional measures to evaluate β-cell function. From these participants, 74 subjects were recruited for an oral minimal model test, and β-cell function was assessed with model-derived indices. Circulating RBP4 levels were measured by a commercially available ELISA kit.

Circulating RBP4 levels were significantly and inversely correlated with β-cell function indicated by the Stumvoll first-phase and second-phase insulin secretion indices, but not with HOMA of β-cell function, calculated from the 2-h OGTT in 291 subjects across the spectrum of glycemia. The inverse association was also observed in subjects involved in the oral minimal model test with β-cell function assessed by both direct measures and model-derived measures, after adjustment for potential confounders. Moreover, RBP4 emerged as an independent factor of the disposition index-total insulin secretion.

Circulating RBP4 levels are inversely and independently correlated with β-cell function across the spectrum of glycemia, providing another possible explanation of the linkage between RBP4 and the pathogenesis of type 2 diabetes.

This retrospective cohort study analyzed patients from Tayside and Fife in the Scottish Care Information–Diabetes Collaboration (SCI-DC) who were observable from the diagnosis of diabetes and had at least five HbA_1c measurements before the outcomes were evaluated. We used the previously reported HbA_1c variability score (HVS), calculated as the percentage of the number of changes in HbA_1c >0.5% (5.5 mmol/mol) among all HbA_1c measurements within an individual. The association between HVS and 10 outcomes was assessed using Cox proportional hazards models.

We included 13,111–19,883 patients in the analyses of each outcome. The patients with HVS >60% were associated with elevated risks of all outcomes compared with the lowest quintile (for example, HVS >80 to ≤100 vs. HVS ≥0 to ≤20, hazard ratio 2.38 [95% CI 1.61–3.53] for major adverse cardiovascular events, 2.4 [1.72–3.33] for all-cause mortality, 2.4 [1.13–5.11] for atherosclerotic cardiovascular death, 2.63 [1.81–3.84] for coronary artery disease, 2.04 [1.12–3.73] for ischemic stroke, 3.23 [1.76–5.93] for heart failure, 7.4 [3.84–14.27] for diabetic retinopathy, 3.07 [2.23–4.22] for diabetic peripheral neuropathy, 5.24 [2.61–10.49] for diabetic foot ulcer, and 3.49 [2.47–4.95] for new-onset chronic kidney disease). Four sensitivity analyses, including adjustment for time-weighted average HbA_1c, confirmed the robustness of the results.

Our study shows that higher HbA_1c variability is associated with increased risks of all-cause mortality, cardiovascular events, and microvascular complications of diabetes independently of high HbA_1c.

We identified 8,528 patients with diabetes (self-report, medication use, or electronic medical record diagnosis) from the Henry Ford Exercise Testing Project (FIT Project). Patients with a BMI <18.5 kg/m² or cancer were excluded. Fitness was measured as the METs achieved during a physician-referred treadmill stress test and categorized as low (<6), moderate (6–9.9), or high (≥10). Adjusted hazard ratios for mortality were calculated using standard BMI (kilograms per meter squared) cutoffs of normal (18.5–24.9), overweight (25–29.9), and obese (≥30). Adjusted splines centered at 22.5 kg/m² were used to examine BMI as a continuous variable.

Patients had a mean age of 58 ± 11 years (49% women) with 1,319 deaths over a mean follow-up of 10.0 ± 4.1 years. Overall, obese patients had a 30% lower mortality hazard (P < 0.001) compared with normal-weight patients. In adjusted spline modeling, higher BMI as a continuous variable was predominantly associated with a lower mortality risk in the lowest fitness group and among patients with moderate fitness and BMI ≥30 kg/m². Compared with the lowest fitness group, patients with higher fitness had an ~50% (6–9.9 METs) and 70% (≥10 METs) lower mortality hazard regardless of BMI (P < 0.001).

Among patients with diabetes, the obesity paradox was less pronounced for patients with the highest fitness level, and these patients also had the lowest risk of mortality.