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Approximately 347 million persons were estimated to have diabetes worldwide in 2008, an increase of 194 million cases from 1980. Diabetes now affects both high- and low-income countries, with low-income countries bearing the majority of the burden. The epidemiologic transition from traditional health risks, such as poor hygiene, to modern health risks, such as sedentary lifestyle, has facilitated the increase in incidence in diabetes, especially in developing countries. The effect of these risk factors may be especially pronounced in some racial and ethnic populations. Increased surveillance for diabetes has contributed to increased diabetes prevalence in higher-income countries. Survival with and some risk factors for diabetes have improved in developed countries, but global diabetes mortality has increased by 20 % since 1990. Population growth and aging will only increase the burden of diabetes, and public health interventions are needed to address diabetes risk factors to stem the tide of this epidemic.

Evidence shows that both biological and nonbiological factors contribute to health disparities. Genetics, in particular, plays a part in how common diseases manifest themselves. Today, unprecedented advances in genetically based diagnoses and treatments provide opportunities for personalized medicine. However, disadvantaged groups may lack access to these advances, and treatments based on research on non-Hispanic whites might not be generalizable to members of minority groups. Unless genetic technologies become universally accessible, existing disparities could be widened. Addressing this issue will require integrated strategies, including expanding genetic research, improving genetic literacy, and enhancing access to genetic technologies among minority populations in a way that avoids harms such as stigmatization.

IntroductionDiet is a critical aspect of the management of adults with diabetes. This paper aims to compare dietary intakes of key macronutrients and micronutrients of US adults with and without diabetes and across the spectrum of diabetes.Research design and methodsWe compared absolute and energy-adjusted dietary intake of major macronutrients and micronutrients among those with and without diabetes and across the spectrum of glycemic control using a 24-hour dietary recall from a cross-sectional, nationally representative sample of 9939 US adults, 20+ years old (National Health and Nutrition Examination Survey 2013–2016). Diabetes was defined as an glycohemoglobin A1c (HbA1c)≥6.5%, fasting glucose ≥126 mg/dL, serum glucose at 2 hours following a 75 g glucose load (oral glucose tolerance test) ≥200 mg/dL, any diagnosis of diabetes or use of diabetes medication (self-reported).ResultsPercent of calories from macronutrients was similar for those with and without diabetes (p>0.05, energy adjusted and adjusted for age, race, and sex). In both groups, sugar accounted for about 20% of calories. Those with diabetes consumed about 7% more calcium (p=0.033), about 5% more sodium (p=0.026), and had lower diet quality (Healthy Eating Index-2015, p=0.021) than those without diabetes. Among those with diabetes, those with an HbA1c>9.0% consumed about 4% less magnesium (p-analysis of variance=0.007) than those with an HbA1c<6.5%. Results were similar within strata of age, race, and sex. Macronutrient intake did not vary consistently by HbA1c level.ConclusionsIn this nationally representative sample, there were no substantial or consistent differences in the dietary intake of macronutrients or micronutrients between US adults with and without diabetes. Improving the diets of those with diabetes will likely require enhanced targeted efforts to improve the dietary intake of persons with diabetes, as well as broad efforts to improve the dietary intake of the general population.

To investigate the feasibility and utility of the Analytic Hierarchy Process (AHP) for medication decision-making in type 2 diabetes. We conducted an AHP with nine diabetes experts using structured interviews to rank add-on therapies (to metformin) for type 2 diabetes. During the AHP, participants compared treatment alternatives relative to eight outcomes (hemoglobin A1c-lowering and seven potential harms) and the relative importance of the different outcomes. The AHP model and instrument were pre-tested and pilot-tested prior to use. Results were discussed and an evaluation of the AHP was conducted during a group session. We conducted the quantitative analysis using Expert Choice software with the ideal mode to determine the priority of treatment alternatives. Participants judged exenatide to be the best add-on therapy followed by sitagliptin, sulfonylureas, and then pioglitazone. Maximizing benefit was judged 21% more important than minimizing harm. Minimizing severe hypoglycemia was judged to be the most important harm to avoid. Exenatide was the best overall alternative if the importance of minimizing harms was prioritized completely over maximizing benefits. Participants reported that the AHP improved transparency, consistency, and an understanding of others' perspectives and agreed that the results reflected the views of the group. The AHP is feasible and useful to make decisions about diabetes medications. Future studies which incorporate stakeholder preferences should evaluate other decision contexts, objectives, and treatments.

BackgroundSodium-glucose cotransporter-2 inhibitors (SGLT2Is) are a recent class of medication approved for the treatment of type 2 diabetes (T2D). Previous meta-analyses have quantified the benefits and harms of SGLT2Is; however, these analyses have been limited to specific outcomes and comparisons and included trials of short duration. We comprehensively reviewed the longer-term benefits and harms of SGLT2Is compared to placebo or other anti-hyperglycemic medications.MethodsWe searched PubMed, Scopus, and clinicaltrials.gov from inception to July 2019 for randomized controlled trials of minimum 52 weeks’ duration that enrolled adults with T2D, compared an SGLT2I to either placebo or other anti-hyperglycemic medications, and reported at least one outcome of interest including cardiovascular risk factors, microvascular and macrovascular complications, mortality, and adverse events. We conducted random effects meta-analyses to provide summary estimates using weighted mean differences (MD) and pooled relative risks (RR). The study was registered a priori with PROSPERO (CRD42018090506).ResultsFifty articles describing 39 trials (vs. placebo, n = 28; vs. other anti-hyperglycemic medication, n = 12; vs. both, n = 1) and 112,128 patients were included in our analyses. Compared to placebo, SGLT2Is reduced cardiovascular risk factors (e.g., hemoglobin A1c, MD − 0.55%, 95% CI − 0.62, − 0.49), macrovascular outcomes (e.g., hospitalization for heart failure, RR 0.70, 95% CI 0.62, 0.78), and mortality (RR 0.87, 95% CI 0.80, 0.94). Compared to other anti-hyperglycemic medications, SGLT2Is reduced cardiovascular risk factors, but insufficient data existed for other outcomes. About a fourfold increased risk of genital yeast infections for both genders was observed for comparisons vs. placebo and other anti-hyperglycemic medications.DiscussionWe found that SGLT2Is led to durable reductions in cardiovascular risk factors compared to both placebo and other anti-hyperglycemic medications. Reductions in macrovascular complications and mortality were only observed in comparisons with placebo, although trials comparing SGLT2Is vs. other anti-hyperglycemic medications were not designed to assess longer-term outcomes.

The American Diabetes Association and the European Association for the Study of Diabetes convened a panel to update the previous consensus statements on the management of hyperglycaemia in type 2 diabetes in adults, published since 2006 and last updated in 2019. The target audience is the full spectrum of the professional healthcare team providing diabetes care in the USA and Europe. A systematic examination of publications since 2018 informed new recommendations. These include additional focus on social determinants of health, the healthcare system and physical activity behaviours including sleep. There is a greater emphasis on weight management as part of the holistic approach to diabetes management. The results of cardiovascular and kidney outcomes trials involving sodium–glucose cotransporter-2 inhibitors and glucagon-like peptide-1 receptor agonists, including assessment of subgroups, inform broader recommendations for cardiorenal protection in people with diabetes at high risk of cardiorenal disease. After a summary listing of consensus recommendations, practical tips for implementation are provided.

Aims/hypothesis SLC30A8 encodes a zinc transporter in the beta cell; individuals with a common missense variant (rs13266634; R325W) in SLC30A8 demonstrate a lower early insulin response to glucose and an increased risk of type 2 diabetes. We hypothesised that zinc supplementation may improve insulin secretion in a genotype-dependent manner. Methods We evaluated the early insulin response to glucose (using frequently sampled intravenous glucose tolerance testing) by R325W genotype before and after 14 days of supplementation with oral zinc acetate (50 mg elemental zinc) twice daily in healthy non-diabetic Amish individuals ( N  = 55). Results Individuals with RW/WW genotypes ( n  = 32) had the lowest insulin response to glucose at 5 and 10 min at baseline (vs RR homozygotes [ n  = 23]). After zinc supplementation, the RW/WW group experienced 15% and 14% increases in the insulin response to glucose at 5 and 10 min, respectively ( p  ≤ 0.04), and, compared with RR homozygotes, experienced a 26% ( p  = 0.04) increase in insulin at 5 min. We observed reciprocal decreases in proinsulin:insulin in the RW/WW ( p  = 0.002) vs RR group ( p  = 0.048), suggesting a genotype-specific improvement in insulin processing. Conclusions/interpretation Zinc supplementation appears to affect the early insulin response to glucose differentially by rs13266634 genotype and could be beneficial for diabetes prevention and/or treatment for some individuals based on SLC30A8 variation. Trial registration: ClinicalTrials.gov NCT00981448

1,5-anhydroglucitol (1,5-AG) is a biomarker of hyperglycemic excursions associated with diabetic complications. Because of its structural similarity to glucose, genetic studies of 1,5-AG can deliver complementary insights into glucose metabolism. We conducted genome-wide association studies of serum 1,5-AG concentrations in 7,550 European ancestry (EA) and 2,030 African American participants (AA) free of diagnosed diabetes from the ARIC Study. Seven loci in/near EFNA1 / SLC50A1 , MCM6 / LCT , SI , MGAM , MGAM2 , SLC5A10 , and SLC5A1 showed genome-wide significant associations ( P  < 5 × 10 −8 ) among EA participants, five of which were novel. Six of the seven loci were successfully replicated in 8,790 independent EA individuals, and MCM6 / LCT and SLC5A10 were also associated among AA. Most of 1,5-AG-associated index SNPs were not associated with the clinical glycemic markers fasting glucose or the  HbA1c, and vice versa. Only the index variant in SLC5A1 showed a significant association with fasting glucose in the expected opposing direction. Products of genes in all 1,5-AG-associated loci have known roles in carbohydrate digestion and enteral or renal glucose transport, suggesting that genetic variants associated with 1,5-AG influence its concentration via effects on glucose metabolism and handling.

Prediabetes affects 1 in 3 US adults. Most are not receiving evidence-based interventions, so understanding how providers discuss prediabetes with patients will inform how to improve their care. This study aimed to develop a natural language processing (NLP) algorithm using machine learning techniques to identify discussions of prediabetes in narrative documentation. We developed and applied a keyword search strategy to identify discussions of prediabetes in clinical documentation for patients with prediabetes. We manually reviewed matching notes to determine which represented actual prediabetes discussions. We applied 7 machine learning models against our manual annotation. Machine learning classifiers were able to achieve classification results that were close to human performance with up to 98% precision and recall to identify prediabetes discussions in clinical documentation. We demonstrated that prediabetes discussions can be accurately identified using an NLP algorithm. This approach can be used to understand and identify prediabetes management practices in primary care, thereby informing interventions to improve guideline-concordant care.

Plasma soluble Receptor for Advanced Glycation End-products (sRAGE) is a strong marker of vascular outcomes although evidence on the direction of association is mixed. Compared to whites, blacks have lower levels of sRAGE. We hypothesized that genetic determinants of sRAGE would help clarify the causal role of sRAGE and the black-white difference in sRAGE levels. We conducted a genome-wide analysis of sRAGE in whites and blacks from the Atherosclerosis Risk in Communities Study. Median plasma sRAGE levels were lower in blacks than whites (728 vs. 1067 pg/ml; P<0.0001). The T (vs. C) allele of rs2070600, a missense variant in AGER, the gene encoding RAGE, was associated with approximately 50% lower sRAGE levels in both whites (N = 1,737; P = 7.26x10-16; minor allele frequency (MAF) = 0.04) and blacks (N = 581; P = 0.02; MAF = 0.01). In blacks, the T (vs. C) allele of rs2071288, intronic to AGER, was associated with 43% lower sRAGE levels (P = 2.22x10-8; MAF = 0.10) and was nearly absent in whites. These AGER SNPs explained 21.5% and 26% of the variation in sRAGE in blacks and whites, respectively, but did not explain the black-white difference in sRAGE. These SNPs were not significantly associated with incident death, coronary heart disease, diabetes, heart failure, or chronic kidney disease in whites (N = 8,130-9,017) or blacks (N = 2,293-2,871) (median follow up ~20 years). We identified strong genetic determinants of sRAGE that did not explain the large black-white difference in sRAGE levels or clearly influence risk of clinical outcomes, suggesting that sRAGE may not be a causal factor in development of these outcomes.