IMPORTANCE Sugar-sweetened beverages (SSBs) are associated with increased risk of metabolic syndrome (MetS). However, the role of other important food sources of fructose-containing sugars in the development of MetS remains unclear. OBJECTIVE To examine the association of major food sources of fructose-containing sugars with incident MetS. DATA SOURCES MEDLINE, Embase, and Cochrane Library were searched from database inception to March 24, 2020, in addition to manual searches of reference lists from included studies using the following search terms: sugar-sweetened beverages, fruit drink, yogurt, metabolic syndrome, and prospective study. STUDY SELECTION Inclusion criteria included prospective cohort studies of 1 year or longer that investigated the association of important food sources of fructose-containing sugars with incident MetS in participants free of MetS at the start of the study. DATA EXTRACTION AND SYNTHESIS Study quality was assessed using the Newcastle-Ottawa Scale. Extreme quantile risk estimates for each food source with MetS incidence were pooled using a random-effects meta-analysis. Interstudy heterogeneity was assessed (Cochran Q statistic) and quantified (I 2 statistic). Dose-response analyses were performed using a 1-stage linear mixed-effects model. The certainty of the evidence was assessed using GRADE (Grading of Recommendations, Assessment, Development, and Evaluation). Results were reported according to the Meta-analysis of Observational Studies in Epidemiology (MOOSE) and Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines. MAIN OUTCOMES AND MEASURES Pooled risk ratio (RR) of incident MetS (pairwise and dose response). RESULTS Thirteen prospective cohort studies (49 591 participants [median age, 51 years; range, 6-90 years]; 14 205 with MetS) that assessed 8 fructose-containing foods and MetS were included. An adverse linear dose-response association for SSBs (RR for 355 mL/d, 1.14; 95% CI, 1.05-1.23) and an L-shaped protective dose-response association for yogurt (RR for 85 g/d, 0.66; 95% CI, 0.58-0.76) and fruit (RR for 80 g/d, 0.82; 95% CI, 0.78-0.86) was found. Fruit juices (mixed and 100%) had a U-shaped dose-response association with protection at moderate doses (mixed fruit juice: RR for 125 mL/d, 0.58; 95% CI, 0.42-0.79; 100% fruit juice: RR for 125 mL/d, 0.77; 95% CI, 0.61-0.97). Honey, ice cream, and confectionary had no association with MetS incidence. The certainty of the evidence (continued) Key Points Question What is the association of major food sources of fructose-Author affiliations and article information are listed at the end of this article.

The Precision Medicine in Diabetes Initiative (PMDI) was launched in 2018 by the American Diabetes Association (ADA) in collaboration with the European Association for the Study of Diabetes (EASD). The PMDI has subsequently partnered with other organizations including the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), JDRF, and the Diabetes Technology Society. The mandate of the PMDI is to establish consensus on the viability and ultimate clinical implementation of precision medicine for the diagnosis, prevention, treatment, prognosis, and monitoring of diabetes. This process is designed to take place through systematic evaluation of available scientific evidence, expert consultation, and broad stakeholder engagement (Fig. 1). The mandate of the PMDI is pursued with the overarching goal of facilitating longer, healthier lives for people living with diabetes, identifying those at risk, and preventing diabetes through multiple interventional approaches.The PMDI held its first international scientific conference in Madrid, Spain, in October 2019. Approximately 100 delegates participated, with attendees from North America, Europe, the Middle East, Asia, and Africa, with diverse representation (including academia, industry, funders, and people with diabetes). The conference provided the foundation and framework from which a first Consensus Report on precision medicine in diabetes was developed and published in 2020 (1). The Consensus Report named five key pillars, or domains, of precision diabetes medicine: precision diagnostics, precision prevention, precision treatment, precision prognostics, and precision monitoring. Across each domain, the article also identified critical gaps in knowledge and evidence required for the scientific advancement, implementation, and ongoing evaluation of precision medicine in diabetes. Newly formed PMDI working groups (composed of 175 internationally leading clinicians and researchers in precision diabetes medicine [Supplementary Appendix]) have since initiated multiple, ongoing evidence-based evaluations in diabetes related to the five key domains.The second international scientific conference organized by the PMDI was held in April 2021 (www.pdm2021.org). This meeting, hosted virtually owing to the coronavirus disease 2019 (COVID-19) pandemic, included more than 3,000 participants from 67 countries. Building on the foundation and framework established at the first conference, diverse stakeholders in the development and implementation of precision diabetes medicine exchanged new data, ideas, and opinions. Over 3 days, the meeting delivered interactive state-of-the-science overviews of all key domains of precision diabetes medicine in research and practice. The PMDI working groups undertaking systematic reviews provided progress updates and summaries of existing evidence and identified critical gaps in current scientific knowledge. Plenary presentations discussed the interface of precision medicine in diabetes with the social determinants of health and dispa...

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ObjectiveTo evaluate multiple determinants of the longitudinal change in insulin clearance (IC) in subjects at high risk for type 2 diabetes (T2D).Research design and methodsAdults (n=492) at risk for T2D in the Prospective Metabolism and Islet Cell Evaluation cohort, a longitudinal observational cohort, had four visits over 9 years. Values from oral glucose tolerance tests collected at each assessment were used to calculate the ratios of both fasting C peptide-to-insulin (ICFASTING) and areas under the curve of C peptide-to-insulin (ICAUC). Generalized estimating equations (GEE) evaluated multiple determinants of longitudinal changes in IC.ResultsIC declined by 20% over the 9-year follow-up period (p<0.05). Primary GEE results indicated that non-European ethnicity, as well as increases in baseline measures of waist circumference, white cell count, and alanine aminotransferase, was associated with declines in ICFASTING and ICAUC over time (all p<0.05). There were no significant associations of IC with sex, age, physical activity, smoking, or family history of T2D. Both baseline and longitudinal IC were associated with incident dysglycemia.ConclusionsOur findings suggest that non-European ethnicity and components of the metabolic syndrome, including central obesity, non-alcoholic fatty liver disease, and subclinical inflammation, may be related to longitudinal declines in IC.