OBJECTIVE: To study the relationships between artificial sweeteners, accounting for all dietary sources (total and by type of artificial sweetener) and risk of type 2 diabetes (T2D), in a large-scale prospective cohort.RESEARCH DESIGN AND METHODS: The analyses included 105,588 participants from the web-based NutriNet-Santé study (France, 2009–2022; mean age 42.5 ± 14.6 years, 79.2% women). Repeated 24-h dietary records, including brands and commercial names of industrial products, merged with qualitative and quantitative food additive composition data, enabled artificial sweetener intakes to be accurately assessed from all dietary sources. Associations between artificial sweeteners (total, aspartame, acesulfame potassium [K], and sucralose) and T2D were investigated using Cox proportional hazard models adjusted for potential confounders, including weight variation during follow-up.RESULTS: During a median follow-up of 9.1 years (946,650 person-years, 972 incident T2D), compared with nonconsumers, higher consumers of artificial sweeteners (i.e., above the sex-specific medians of 16.4 mg/day in men and 18.5 mg/day in women) had higher risks of developing T2D (hazard ratio [HR] 1.69; 95% CI 1.45–1.97; P-trend <0.001). Positive associations were also observed for individual artificial sweeteners: aspartame (HR 1.63 [95% CI 1.38–1.93], P-trend <0.001), acesulfame-K (HR 1.70 [1.42–2.04], P-trend <0.001), and sucralose (HR 1.34 [1.07–1.69], P-trend = 0.013).CONCLUSIONS: Potential for reverse causality cannot be eliminated; however, many sensitivity analyses were computed to limit this and other potential biases. These findings of positive associations between artificial sweetener intakes and increased T2D risk strengthen the evidence that these additives may not be safe sugar alternatives. This study provides important insights in the context of on-going reevaluation of artificial sweeteners by health authorities worldwide.

Background: Mixtures of food additives are daily consumed worldwide by billions of people. So far, safety assessments have been performed substance by substance due to lack of data on the effect of multiexposure to combinations of additives. Our objective was to identify most common food additive mixtures, and investigate their associations with type 2 diabetes incidence in a large prospective cohort. Methods and Findings: Participants (n = 108,643, mean follow-up = 7.7 years (standard deviation (SD) = 4.6), age = 42.5 years (SD = 14.6), 79.2% women) were adults from the French NutriNet-Santé cohort (2009–2023). Dietary intakes were assessed using repeated 24h-dietary records, including industrial food brands. Exposure to food additives was evaluated through multiple food composition databases and laboratory assays. Mixtures were identified through nonnegative matrix factorization (NMF), and associations with type 2 diabetes incidence were assessed using Cox models adjusted for potential socio-demographic, anthropometric, lifestyle and dietary confounders. A total of 1,131 participants were diagnosed with type 2 diabetes. Two out of the five identified food additive mixtures were associated with higher type 2 diabetes incidence: the first mixture included modified starches, pectin, guar gum, carrageenan, polyphosphates, potassium sorbates, curcumin, and xanthan gum (hazard ratio (HR)_{per an increment of 1SD of the NMF mixture score} = 1.08 [1.02, 1.15], p = 0.006), and the other mixture included citric acid, sodium citrates, phosphoric acid, sulphite ammonia caramel, acesulfame-K, aspartame, sucralose, arabic gum, malic acid, carnauba wax, paprika extract, anthocyanins, guar gum, and pectin (HR = 1.13 [1.08,1.18], p < 0.001). No association was detected for the three remaining mixtures: HR = 0.98 [0.91, 1.06], p = 0.67; HR = 1.02 [0.94, 1.10], p = 0.68; and HR = 0.99 [0.92, 1.07], p = 0.78. Several synergistic and antagonist interactions between food additives were detected in exploratory analyses. Residual confounding as well as exposure or outcome misclassifications cannot be entirely ruled out and causality cannot be established based on this single observational study. Conclusions: This study revealed positive associations between exposure to two widely consumed food additive mixtures and higher type 2 diabetes incidence. Further experimental research is needed to depict underlying mechanisms, including potential synergistic/antagonist effects. These findings suggest that a combination of food additives may be of interest to consider in safety assessments, and they support public health recommendations to limit nonessential additives. Trial Registration: The NutriNet-Santé cohort is registered at clinicaltrials.gov (NCT03335644). https://clinicaltrials.gov/study/NCT03335644.

Background: Epicardial adipose tissue (EAT) has anatomic and functional proximity to the heart and is considered a novel diagnostic marker and therapeutic target in cardiometabolic diseases. The aim of this study was to evaluate whether EAT volume was associated with coronary artery calcification (CAC) in people living with diabetes, independently of confounding factors. Methods: We included all consecutive patients with diabetes whose EAT volume and CAC score were measured using computed tomography between January 1, 2019 and September 30, 2020 in the Department of Diabetology-Endocrinology-Nutrition at Avicenne Hospital, France. Determinants of EAT volume and a CAC score ≥ 100 Agatston units (AU) were evaluated. Results: The study population comprised 409 patients (218 men). Mean (± standard deviation) age was 57 ± 12 years, and 318, 56 and 35 had type 2 (T2D), type 1 (T1D), or another type of diabetes, respectively. Mean body mass index (BMI) was 29 ± 6 kg/m², mean AET volume 93 ± 38 cm³. EAT volume was positively correlated with age, BMI, pack-year smoking history and triglyceridaemia, but negatively correlated with HDL-cholesterol level. Furthermore, it was lower in people with retinopathy, but higher in men, in Caucasian people, in patients on antihypertensive and lipid-lowering medication, in people with nephropathy, and finally in individuals with a CAC ≥ 100 AU (CAC < 100 vs CAC ≥ 100: 89 ± 35 vs 109 ± 41 cm³, respectively, p < 0.05). In addition to EAT volume, other determinants of CAC ≥ 100 AU (n = 89, 22%) were age, T2D, ethnicity, antihypertensive and lipid-lowering medication, cumulative tobacco consumption, retinopathy, macular edema and macrovascular disease. Multivariable analysis considering all these determinants as well as gender and BMI showed that EAT volume was independently associated with CAC ≥ 100 AU (per 10 cm³ increase: OR 1.11 [1.02–1.20]). Conclusions: EAT volume was independently associated with CAC. As it may play a role in coronary atherosclerosis in patients with diabetes, reducing EAT volume through physical exercise, improved diet and pharmaceutical interventions may improve future cardiovascular risk outcomes in this population.

Context: Some women living with type 1 diabetes complain of changes in glucose values according to the different phases of menstruation. Objective: To evaluate this variability through continuous glucose monitoring (CGM) data in type 1 diabetes patients. Design: Observational study. Setting: Ambulatory data, recruitment in 2 centers in the Paris region. Patients: Twenty-four women with type 1 diabetes having spontaneous menstrual cycles. Intervention: Collection of CGM data for 62 spontaneous menstrual cycles, with evaluation of five 3-day phases during each cycle: (1) early follicular (menstruations), (2) mid-follicular, (3) peri-ovulatory, (4) mid-luteal, and (5) late luteal. Main outcome measure: Time in range (TIR, prespecified). Results: TIR decreased for each consecutive phase (61 ± 18%; 59 ± 18%; 59 ± 20%; 57 ± 18%; and 55 ± 20%, P = 0.02). The linear mixed model highlighted a decrease in TIR in the mid-luteal (P = 0.03) and late luteal (P < 0.001) phases compared with the early follicular phase. Time above range was significantly higher during the late luteal phase than the early follicular phase (P = 0.003). Time below range was significantly higher during the mid-follicular phase than in the early follicular phase. Conclusion: In most of the study population, glucose levels rose linearly throughout the menstrual cycle, reaching a maximum in the late luteal phase. A sharp decrease was seen for most participants at the beginning of menstrual bleeding. This should be taken into consideration in daily care of type 1 diabetes patients to avoid hypoglycemia.

Background: Epicardial adipose tissue (EAT) is considered a novel diagnostic marker for cardiometabolic disease. This study aimed to evaluate whether EAT volume was associated with stress-induced myocardial ischemia in asymptomatic people living with diabetes—independently of confounding factors—and whether it could predict this condition. Methods: We included asymptomatic patients with diabetes and no coronary history, who had undergone both a stress a myocardial scintigraphy to diagnose myocardial ischemia, and a computed tomography to measure their coronary artery calcium (CAC) score. EAT volume was retrospectively measured from computed tomography imaging. Determinants of EAT volume and asymptomatic myocardial ischemia were evaluated. Results: The study population comprised 274 individuals, including 153 men. Mean (± standard deviation) age was 62 ± 9 years, and 243, 23 and 8 had type 2, type 1, or another type of diabetes, respectively. Mean body mass index was 30 ± 6 kg/m², and mean EAT volume 96 ± 36 cm³. Myocardial ischemia was detected in 32 patients (11.7%). EAT volume was positively correlated with age, body mass index and triglyceridemia, but negatively correlated with HbA1c, HDL- and LDL-cholesterol levels. Furthermore, EAT volume was lower in people with retinopathy, but higher in men, in current smokers, in patients with nephropathy, those with a CAC score > 100 Agatston units, and finally in individuals with myocardial ischemia (110 ± 37 cm³ vs 94 ± 37 cm³ in those without myocardial ischemia, p < 0.05). The association between EAT volume and myocardial ischemia remained significant after adjustment for gender, diabetes duration, peripheral macrovascular disease and CAC score. We also found that area under the ROC curve analysis showed that EAT volume (AROC: 0.771 [95% confidence interval 0.683–0.858]) did not provide improved discrimination of myocardial ischemia over the following classic factors: gender, diabetes duration, peripheral macrovascular disease, retinopathy, nephropathy, smoking, atherogenic dyslipidemia, and CAC score (AROC 0.773 [0.683–0.862]). Conclusions: EAT may play a role in coronary atherosclerosis and coronary circulation in patients with diabetes. However, considering EAT volume is not a better marker for discriminating the risk of asymptomatic myocardial ischemia than classic clinical data.

We aimed to compare pregnancy outcomes in 4665 women according to the following types of hyperglycaemia in pregnancy sub-types: (i) normoglycaemia, (ii) gestational diabetes mellitus (GDM), (iii) diabetes in pregnancy (DIP), (iv) early-diagnosed (i.e., <22 weeks of gestation) GDM (eGDM), and (v) early-diagnosed DIP (eDIP). The prevalence of normoglycaemia, eGDM, eDIP, GDM, and DIP was 76.4%, 10.8%, 0.6%, 11.7%, and 0.6%, respectively. With regard to pregnancy outcomes, gestational weight gain (11.5 ± 5.5, 9.0 ± 5.4, 8.3 ± 4.7, 10.4 ± 5.3, and 10.1 ± 5.0 kg, p < 0.0001) and insulin requirement (none, 46.0%, 88.5%, 25.5%, and 51.7%; p < 0.001) differed according to the glycaemic sub-types. eGDM and eDIP were associated with higher rates of infant malformation. After adjustment for confounders, with normoglycaemia as the reference, only GDM was associated with large-for-gestational-age infant (odds ratio 1.34 (95% interval confidence 1.01–1.78) and only DIP was associated with hypertensive disorders (OR 3.48 (1.26–9.57)). To conclude, early-diagnosed hyperglycaemia was associated with an increased risk of malformation, suggesting that it was sometimes present at conception. Women with GDM, but not those with eGDM, had an increased risk of having a large-for-gestational-age infant, possibly because those with eGDM were treated early and therefore had less gestational weight gain. Women with DIP might benefit from specific surveillance for hypertensive disorders.