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Advances in Exercise and Nutrition as Therapy in Diabetes

2023; Mary Ann Liebert, Inc.; Volume: 25; Issue: S1 Linguagem: Inglês

10.1089/dia.2023.2509

1557-8593

Dessi P. Zaharieva, Michael C. Riddell,

Obesity, Physical Activity, Diet

Diabetes Technology & TherapeuticsVol. 25, No. S1 Original ArticlesFree AccessAdvances in Exercise and Nutrition as Therapy in DiabetesDessi P. Zaharieva and Michael C. RiddellDessi P. ZaharievaDepartment of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.Search for more papers by this author and Michael C. RiddellSchool of Kinesiology and Health Science, Faculty of Health, Muscle Health Research Centre, York University, Toronto, Ontario, Canada.LMC Diabetes & Endocrinology, Toronto, Ontario, Canada.Search for more papers by this authorPublished Online:20 Feb 2023https://doi.org/10.1089/dia.2023.2509AboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail IntroductionThis year, we screened over 1800 potentially eligible titles on search engines, including PubMed and Google Scholar, between July 1, 2021, and June 30, 2022. We shortlisted 72 original peer-reviewed manuscripts that focused on exercise, nutrition, and diabetes mellitus and ultimately selected 11 papers to represent this research field.The search this year was packed with new nutrition and exercise-related research with a heavy focus on manipulating the macronutrient composition of the diet and/or adding various micronutrients to the diet for diabetes prevention and management. In the physical activity research space, lifestyle interventions continue to show the beneficial metabolic effects of regular exercise in persons at risk for developing type 2 diabetes and for people already diagnosed with diabetes (type 1 or type 2). Studies continue to refine our knowledge of the appropriate volumes and intensities of exercise for health and metabolic disease treatment. Research also remains focused on how to manage exercise-related dysglycemia using technology-driven solutions.Key Articles ReviewedEffect of Low Glycaemic Index or Load Dietary Patterns on Glycaemic Control and Cardiometabolic Risk Factors in Diabetes: Systematic Review and Meta-Analysis of Randomised Controlled TrialsChiavaroli L, Lee D, Ahmed A, Cheung A, Khan TA, Blanco Mejia S, Mirrahimi A, Jenkins DJA, Livesey G, Wolever TMS, Rahelić D, Kahleová H, Salas-Salvadó J, Kendall CWC, Sievenpiper JLBMJ 2021;374: n1651Dose-Dependent Associations of Dietary Glycemic Index, Glycemic Load, and Fiber with 3-Year Weight Loss Maintenance and Glycemic Status in a High-Risk Population: a Secondary Analysis of the Diabetes Prevention Study PreviewZhu R, Larsen TM, Fogelholm M, Poppitt SD, Vestentoft PS, Silvestre MP, Jalo E, Navas-Carretero S, Huttunen-Lenz M, Taylor MA, Stratton G, Swindell N, Drummen M, Adam TC, Ritz C, Sundvall J, Valsta LM, Muirhead R, Brodie S, Handjieva-Darlenska T, Handjiev S, Martinez JA, Macdonald IA, Westerterp-Plantenga MS, Brand-Miller J, Raben ADiabetes Care 2021;44: 1672–1681Dietary Calcium Intake in Relation to Type-2 Diabetes and Hyperglycemia in Adults: a Systematic Review and Dose-Response Meta-Analysis of Epidemiologic StudiesHajhashemy Z, Rouhani P, Saneei PSci Rep 2022;12: 1050For a High Fat, High Protein Breakfast, Preprandial Administration of 125% of the Insulin Dose Improves Postprandial Glycaemic Excursions in People with Type 1 Diabetes Using Multiple Daily Injections: a Cross-Over TrialSmith TA, Smart CE, Howley PP, Lopez PE, King BRDiabet Med 2021;38: e14512Prediction of Personal Glycemic Responses to Food for Individuals with Type 1 Diabetes Through Integration of Clinical and Microbial DataShilo S, Godneva A, Rachmiel M, Korem T, Kolobkov D, Karady T, Bar N, Wolf BC, Glantz-Gashai Y, Cohen M, Zuckerman Levin N, Shehadeh N, Gruber N, Levran N, Koren S, Weinberger A, Pinhas-Hamiel O, Segal EDiabetes Care 2022;45: 502–511Activity Detection and Classification from Wristband Accelerometer Data Collected on People with Type 1 Diabetes in Free-Living ConditionsCescon M, Choudhary D, Pinsker JE, Dadlani V, Church MM, Kudva YC, Doyle III FJ, Dassau EComput Biol Med 2021;135: 104633Different Effects of Lifestyle Intervention in High- and Low-Risk Prediabetes: Results of the Randomized Controlled Prediabetes Lifestyle Intervention Study (PLIS)Fritsche A, Wagner R, Heni M, Kantartzis K, Machann J, Schick F, Lehmann R, Peter A, Dannecker C, Fritsche L, Valenta V, Schick R, Nawroth PP, Kopf S, Pfeiffer AFH, Kabisch S, Dambeck U, Stumvoll M, Blüher M, Birkenfeld AL, Schwarz P, Hauner H, Clavel J, Seißler J, Lechner A, Müssig K, Weber K, Laxy M, Bornstein S, Schürmann A, Roden M, de Angelis MH, Stefan N, Häring HUDiabetes 2021;70: 2785–2795A Randomized Crossover Trial Comparing Glucose Control During Moderate-Intensity, High-Intensity, and Resistance Exercise with Hybrid Closed-Loop Insulin Delivery While Profiling Potential Additional Signals in Adults with Type 1 DiabetesPaldus B, Morrison D, Zaharieva DP, Lee MH, Jones H, Obeyesekere V, Lu J, Vogrin S, La Gerche A, McAuley SA, MacIsaac RJ, Jenkins AJ, Ward GM, Colman P, Smart CEM, Seckold R, King BR, Riddell MC, O'Neal DNDiabetes Care 2022;45: 194–203Comparable Glucose Control with Fast-Acting Insulin Aspart Versus Insulin Aspart Using a Second-Generation Hybrid Closed-Loop System During ExerciseMorrison D, Zaharieva DP, Lee MH, Paldus B, Vogrin S, Grosman B, Roy A, Kurtz N, O'Neal DNDiabetes Technol Ther 2022;24: 93–101Anticipated Basal Insulin Reduction To Prevent Exercise-Induced Hypoglycemia in Adults and Adolescents Living with Type 1 DiabetesTagougui S, Legault L, Heyman E, Messier V, Suppere C, Potter KJ, Pigny P, Berthoin S, Taleb N, Rabasa-Lhoret RDiabetes Technol Ther 2022;24: 307–315No More Hypoglycaemia on Days with Physical Activity and Unrestricted Diet when Using a Closed-Loop System for 12 Weeks: a Post Hoc Secondary Analysis of the Multicentre, Randomized Controlled Diabeloop WP7 TrialFranc S, Benhamou PY, Borot S, Chaillous L, Delemer B, Doron M, Guerci B, Hanaire H, Huneker E, Jeandidier N, Amadou C, Renard E, Reznik Y, Schaepelynck P, Simon C, Thivolet C, Thomas C, Hannaert P, Charpentier GDiabetes Obes Metab 2021;23: 2170–2176MACRONUTRIENTSEffect of Low Glycaemic Index or Load Dietary Patterns on Glycaemic Control and Cardiometabolic Risk Factors in Diabetes: Systematic Review and Meta-Analysis of Randomised Controlled TrialsChiavaroli L1,2, Lee D1,2, Ahmed A1,2, Cheung A1,2, Khan TA1,2, Blanco Mejia S1,2, Mirrahimi A1,2,3,5, Jenkins DJA1,2,3,4,6, Livesey G7, Wolever TMS1,3,8, Rahelić D9,10,11, Kahleová H12,13, Salas-Salvadó J14,15,16, Kendall CWC1,2,17, Sievenpiper JL1,2,3,4,61Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada; 2Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Centre, St Michael's Hospital, Toronto, ON, Canada; 3Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada; 4Department of Medical Imaging, Faculty of Medicine, University of Toronto, Toronto, ON, Canada; 5Division of Endocrinology and Metabolism, Department of Medicine, St Michael's Hospital, Toronto, ON, Canada; 6Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, ON, Canada; 7Independent Nutrition Logic, Wymondham, UK; 8INQUIS Clinical Research, Toronto, ON, Canada; 9Vuk Vrhovac University Clinic for Diabetes, Endocrinology and Metabolic Diseases, Merkur University Hospital, Zagreb, Croatia; 10School of Medicine, University of Zagreb, Zagreb, Croatia; 11School of Medicine, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia; 12Institute for Clinical and Experimental Medicine, Diabetes Centre, Prague, Czech Republic; 13Physicians Committee for Responsible Medicine, Washington, DC; 14Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Reus, Spain; 15Institut d'Investigació Sanitària Pere Virgili, Hospital Universitari San Joan de Reus, Reus, Spain; 16Consorcio CIBER, MP Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain; 17College of Pharmacy and Nutrition, University of Saskatchewan, SK, CanadaBMJ 2021;374: n1651BackgroundPrevious randomized control trials (RCTs) and meta-analyses have demonstrated that a low glycemic index (GI) or low glycemic load (GL) diet improves glycemia and cardiometabolic risk in people living with diabetes (1,2). This systematic review and meta-analysis, conducted in the spring of 2021, was the first to provide a research grading system on all relevant RCTs for GI/GL diets to help update the European Association for the Study of Diabetes (EASD) clinical practice guidelines for nutrition therapy for people living with diabetes.MethodsInvestigators independently extracted data and assessed risk of bias from published studies (Medline, Embase, Cochrane Library) up until May 13, 2021, and GRADE (Grading of Recommendations Assessment, Development, and Evaluation) was used to assess the certainty of evidence for prescribing three or more weeks of low GI/ GL in type 1 (T1D) or type 2 diabetes (T2D). The primary outcome was glycated hemoglobin (HbA1c) with secondary outcomes for various other markers of glycemic control, lipids, body composition, blood pressure, and inflammation also included.ResultsFrom a total of 9596 reports published, 29 trials involving a total of 1617 participants with diabetes were included in the final analyses, with most trials conducted in Canada (21%), Australia (17%), and France (10%). Median follow-up duration was 12 weeks; studies often had a crossover design (45% of RCTs), with or without a washout, and a reasonable distribution of women (47%) and men (53%). In general, study participants were middle aged (median age 56 years) and most (90%) were living with T2D, with the remainder having T1D. The median GI values achieved within the intervention and control diets were 49 (range 38–58) and 63 (range 51–86), respectively. (See comment below on what this score is). The median (range) GL achieved in the intervention and control diets were 102 (33–176) and 138 (39–175), respectively. The median percent contribution of energy from carbohydrate in the diets did not differ (49% in the intervention and 48% in the control diets). Most studies (90%) did not initiate a caloric restrictive diet, and most trials were judged as having a low or unclear risk of bias across the GRADE domains. Pooled analyses demonstrated that low GI/GL diets led to a small but clinically meaningful reduction in HbA1c compared with the various control diets (mean difference −0.31% [95% CI, −0.42% to −0.19%]). Low GI/GL diets also showed modest reductions in non-HDL cholesterol (mean difference −0.20 [95% CI, −0.33 to −0.07] mmol/L), LDL cholesterol (−0.17 [95% CI, −0.25 to −0.08] mmol/L), apo B (−0.05 [95% CI, −0.09 to −0.01] g/L), triglycerides (−0.09 [95% CI, −0.17 to −0.01] mmol/L), body weight (−0.66 [95% CI, −0.90 to −0.42] kg), body mass index (−0.38 [95% CI, −0.64 to −0.13]), and small reductions in fasting blood glucose (−0.36 [95% CI, −0.42 to −0.19] mmol/L) and C-reactive protein (−0.41 [95% CI, −0.78 to −0.04] mg/L). The evidence was graded as "high" for the primary outcome (HbA1c improvement), while the evidence for most secondary outcomes was graded as "moderate" owing to downgrades for either inconsistency, imprecision, or evidence of publication bias from small study effects.ConclusionThis new systematic review and meta-analysis showed that low GI/GL dietary patterns, in comparison with higher GI/GL control diets, provide small but important benefits for glycemic management and other established cardiometabolic risk factors in people living with diabetes over a median follow-up of ∼12 weeks.Dose-Dependent Associations of Dietary Glycemic Index, Glycemic Load, and Fiber with 3-Year Weight Loss Maintenance and Glycemic Status in a High-Risk Population: a Secondary Analysis of the Diabetes Prevention Study PreviewZhu R1, Larsen TM1, Fogelholm M2, Poppitt SD3, Vestentoft PS1, Silvestre MP3,4, Jalo E2, Navas-Carretero S5,6,7, Huttunen-Lenz M8, Taylor MA9, Stratton G10, Swindell N10, Drummen M11, Adam TC11, Ritz C1, Sundvall J12, Valsta LM13, Muirhead R14, Brodie S14, Handjieva-Darlenska T15, Handjiev S15, Martinez JA6,7,16,17, Macdonald IA18, Westerterp-Plantenga MS11, Brand-Miller J14, Raben A1,191Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark; 2Department of Food and Nutrition, University of Helsinki, Helsinki, Finland; 3Human Nutrition Unit, School of Biological Sciences, Department of Medicine, University of Auckland, Auckland, New Zealand; 4CINTESIS, Nova Medical School, Universidade Nova de Lisboa, Lisboa, Portugal, 5Centre for Nutrition Research, University of Navarra, Pamplona, Spain, 6Centro de Investigacion Biomedica en Red Area de Fisiologia de la Obesidad y la Nutricion (CIBEROBN), Madrid, Spain; 7IdisNA Instituto for Health Research, Pamplona, Spain, 8Institute for Nursing Science, University of Education Schwäbisch Gmünd, Schwäbisch Gmünd, Germany; 9Division of Physiology, Pharmacology and Neuroscience, School of Life Sciences, Queen's Medical Centre, Nottingham, UK; 10Applied Sports, Technology, Exercise and Medicine (A-STEM) Research Centre, Swansea University, Swansea, UK; 11Department of Nutrition and Movement Sciences, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, the Netherlands; 12Department of Government Services, Forensic Toxicology Unit, Biochemistry Laboratory, Finnish Institute for Health and Welfare, Helsinki, Finland; 13Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland; 14School of Life and Environmental Sciences and Charles Perkins Centre, University of Sydney, Sydney, Australia; 15Department of Pharmacology and Toxicology, Medical University of Sofia, Sofia, Bulgaria; 16Department of Nutrition and Physiology, University of Navarra, Pamplona, Spain; 17Precision Nutrition and Cardiometabolic Health Program, IMDEA-Food Institute (Madrid Institute for Advanced Studies), CEI UAM + CSIC, Madrid, Spain; 18Division of Physiology, Pharmacology and Neuroscience, School of Life Sciences, Queen's Medical Centre, MRC/ARUK Centre for Musculoskeletal Ageing Research, ARUK Centre for Sport, Exercise and Osteoarthritis, National Institute for Health Research Nottingham Biomedical Research Centre, Nottingham, UK; 19Steno Diabetes Center Copenhagen, Gentofte, DenmarkDiabetes Care 2021;44: 1672–1681BackgroundType 2 diabetes (T2D) is thought to be preventable, at least to some degree, in people with prediabetes who undertake lifestyle intervention with regular exercise and caloric restriction. Low-energy diets (LED), with either total or partial meal replacements, are effective in promoting rapid weight loss and improving insulin sensitivity in overweight and obese men and women with prediabetes (3), but weight regain is a common problem after about 1 year of most interventions (4). The PREVIEW (PREVention of diabetes through lifestyle Intervention and population studies in Europe and around the World) project was initiated in 2013 to find the most effective lifestyle (diet and physical activity) approach for the prevention of T2D in overweight and obese participants with increased risk for the disease (5). This 3-year randomized control trial (RCT) with four different intervention arms compared the impact of a high-protein, low-glycemic index (GI) diet with a moderate protein, moderate-GI diet in combination with moderate or high-intensity physical activity levels on the incidence of T2D and its related clinical endpoints (6). The primary goal of this secondary analysis of PREVIEW was to examine the longitudinal and dose-dependent associations of dietary GI, glycemic load (GL), and fiber with body weight and glycemic status during the 3-year weight loss maintenance (WLM) phase of the PREVIEW study participants, irrespective of the original four randomization groups.MethodsThis was a secondary analysis of pooled data from the previously published PREVIEW trial (6) to examine the impact of a low GI diet or a low GL diet or a high fiber diet on weight rebound after study intervention. A total of 1279 participants who were either overweight or obese (age 25–70 years and BMI ≥25 kg·m−2) and living with prediabetes at baseline were included. Multiadjusted linear mixed models with repeated measurements were used to assess longitudinal and dose-dependent associations with various dietary substrategies by merging the participants into one group and dividing them into GI, GL, and fiber tertiles, respectively.ResultsThe main findings from this analysis were that each 10-unit increment in GI was associated with a greater regain of weight (0.46 kg/year; 95% CI, 0.23 to 0.68 kg/year; P < .001) and a greater increase in HbA1c level. Each 20-unit increment in GL was also associated with a greater regain of weight (0.49 kg/year; 95% CI, 0.24 to 0.75 kg/year; P<.001) and increase in HbA1c. Compared with those in the lowest tertiles, participants in the highest GI and GL tertiles had significantly greater weight regain and increases in HbA1c. The associations of GI and GL with HbA1c were independent of weight change. Fiber intake was inversely associated with increases in waist circumference but did not associate with weight regain and/or glycemic status.ConclusionThis secondary analysis of individuals with a high risk of type 2 diabetes from the large international, multiethnic PREVIEW cohort found that higher cumulative average GI and GL intakes are associated with increases in body weight regain after lifestyle intervention and various markers of deteriorated glycemic status. However, fiber intake status, per se, did not appear to impact weight regain or glycemic status.CommentsAccording to our 2021–2022 ATTD Yearbook search, several new and important randomized control trials (RCTs) and meta-analyses were conducted to examine the effectiveness of manipulating macronutrient content of a diet to prevent or treat type 2 diabetes (T2D) and to manage glycemic levels in type 1 diabetes (T1D). One common nutritional approach for diabetes management, in general, is to allow relatively liberal carbohydrate intake (i.e., up to 60% of the total energy intake) but change the carbohydrate composition of the diet by decreasing the amount of high glycemic index (GI) foods and increasing the amount of low GI foods consumed in the diet. The GI is a carbohydrate ranking tool that ranks a carbohydrate containing food according to the amount by which it raises blood glucose levels after it is consumed in comparison with reference food such as pure glucose or white bread (7). In this ranking method, a carbohydrate food with a GI of ≤55 is considered low, 56–69 is considered medium, and ≥70 is considered high, based on a glucose scale. The glycemic load (GL) of a food is the GI multiplied by the available carbohydrate (g) in the serving, divided by 100, which is useful since the volume (amount) of carbohydrate also affects the glucose excursion at a meal and the dietary insulin need. For example, an apple that has a GI of 38 and contains ∼15 grams of available carbohydrate has a GL of ∼6 grams.In the first paper in this section, by Chiavaroli and colleagues, is a new meta-analysis that found that the consumption of low a GI/GL diet, without reducing actual amounts of carbohydrate intake, lowers HbA1c levels by 0.31% in those with diabetes (T1D and T2D studies were pooled). The researchers also demonstrated that there is a significant positive linear dose-response gradient for differences in GL on HbA1c levels in diabetes, showing a net reduction of 0.04% HbA1c units per 10-unit reduction in GL. This analysis is important since some individuals with diabetes cannot adhere to a low carbohydrate diet for very long, even though carbohydrate restriction also lowers HbA1c levels very effectively in both T1D (8) and T2D (9,10), as was shown nicely in several other new papers in this same ATTD yearbook search period. The key is that while both dietary manipulations work, the low carbohydrate diet may be less sustainable for many individuals while the low GI/GL diet may be somewhat more sustainable. Indeed, the second paper, by Zhu et al., showed that once weight loss and improvement in HbA1c are achieved with intensive lifestyle intervention over a period of 8 weeks in persons with prediabetes, as was achieved in the previously published PREVIEW study primary paper (6), it is much easier to sustain that weight loss and improvement in glycemia if foods low in GI and/or low in GL are consumed after the intensive lifestyle intervention ends. This information is important to share, given that the two types of diets consumed in the original PREVIEW study (i.e., high protein and low GI diet vs moderate protein and moderate GI) did not appear to differ in their success for preventing T2D (both dietary types had equal effectiveness). Collectively, all these studies strengthen the notion that carbohydrate quality and quantity are likely critical considerations for lifestyle interventions for prediabetes and T2D and that most of us who are at risk for diabetes, or already have it, should probably be striving toward a diet low in GI foods, particularly if we find that reducing our carbohydrate intake altogether is too difficult to sustain. It should also be noted that using the GI as a rating system for all carbohydrate containing foods comes with risk, since it tends to make people believe that foods are either "good" or "bad" for their diabetes (or health), which is an oversimplification (11).MICRONUTRIENTS AND NUTRACEUTICALSDietary Calcium Intake in Relation to Type-2 Diabetes and Hyperglycemia in Adults: a Systematic Review and Dose-Response Meta-Analysis of Epidemiologic StudiesHajhashemy Z1,2, Rouhani P1,2, Saneei P21Students' Research Committee, Isfahan University of Medical Sciences, Isfahan, Iran; 2Department of Community Nutrition, School of Nutrition and Food Science, Isfahan University of Medical Sciences, Isfahan, IranSci Rep 2022;12: 1050BackgroundWhile several modifiable and nonmodifiable risk factors are thought to be linked to the development of type 2 diabetes (T2D), including age, sex, genetic background, race/ethnicity, body weight, physical activity levels, and dietary patterns, some debate exists for the role of micronutrients in the disease etiology. One nutrient that gets regular attention for its possible link with T2D development is dietary calcium (Ca) (12–14). The aim of this study was to conduct a systematic review and meta-analysis to determine whether higher dietary calcium intake is associated with a lower risk of T2D or hyperglycemia in adults.MethodsThe investigators examined all published articles found in MEDLINE (Pubmed), Web of Science, and Scopus electronic databases as well as in Google Scholar up to May 2021. All published papers were included in the meta-analysis if they (1) had a cohort, cross-sectional, or case-control design; (2) investigated an adult population (≥18 years), regardless of their health status; (3) considered dietary Ca intake as the exposure and reported the risk for abnormal glucose homeostasis, including T2D, prediabetes or hyperglycemia as the outcomes of interest; (4) reported relative risks (RRs), hazard ratios (HR), or odds ratios (ORs), with 95% confidence intervals (CIs) for the association of dietary calcium intake and abnormal glucose homeostasis.ResultsApproximately 4000 papers were initially screened, with ∼100 reports retrieved in full for further screening; 17 eligible studies were included in the final meta-analysis (8 prospective, 9 cross-sectional). The assessment of dietary Ca intake was performed using food frequency questionnaires (FFQs) in 12 reports, food recall in four investigations, and food record in one study. Nine of the included studies considered T2D as the outcome, and the others reported high blood glucose (HBG) or hyperglycemia (fasting blood glucose [FBG] ≥ 100 or 110 mg/dL) as the outcome of interest. Among the 17 studies, 12 were deemed as "high-quality" (score of 8 or more out of a 10-point scale), while the remaining studies were classified as "low-quality". Results from 7 cohort studies (representing 255,744 adults) showed that individuals in the highest category of Ca intake, in comparison with the lowest category of Ca intake, had 18% lower risk of developing T2D (RR, 0.82; 95% CI, 0.74 to 0.92) but the heterogeneity between studies was deemed as "moderate" (I2 = 53.6, PQ-test = 0.02). Interestingly, the Ca intake—T2D relation was significant only in Asian countries (RR, 0.75; 95% CI, 0.69 to 0.82) and there was no significant relation in non-Asian regions (RR, 0.98; 95% CI, 0.87 to 1.11). Among participants with a mean age ≥50 years and those in developing countries, higher dietary Ca intake was protectively associated with lower risk of T2D in subgroups of women, high-quality studies, and investigations with an adjustment for magnesium intake. Based on eight studies that had a dose response examination, a 300, 600, and 1000 mg/day increase in dietary Ca intake was significantly related to a 7%, 13%, and 20% decrease in risk of T2D (RR, 0.93; 95% CI 0.89 to 0.98), (RR, 0.87; 95% CI 0.79 to 0.97) and (RR, 0.80; 95% CI 0.67 to 0.95), respectively. There was no significant relation between dietary Ca intake above 750 mg/d and risk of developing T2D, however.ConclusionThis new meta-analysis demonstrates that increasing Ca intake from less than 300 mg/day to amounts up to ∼750 mg/day is associated with a stepwise reduction in the relative risk for developing T2D in adults over the age of 50 years.CommentsSeveral papers this year focused on fortifying diets with micronutrients like vitamins, minerals, and nutraceuticals (e.g., dairy products, certain types of long chain fatty acids, food extracts, etc.). A nutraceutical is defined as any substance that is a whole food, or part of a food, that has a beneficial physiologic effect and provides medicinal or health benefits, including the prevention and treatment of various diseases like cancer, heart disease, Alzheimer disease, or diabetes. In papers published this year, for example, all the following dietary supplements were shown to influence either diabetes development or glucose management in persons with diabetes: linoleic acid (15); coffee (16); whey protein (17); ginger (18); saffron (19,20); omega 3 fatty acids (21,22); Morus Alba leaf extract (23); vitamin K1 (24); branched chain amino acids (25); red raspberry (26); and Artemisia vulgaris (a type of flowering plant also known as mugwort) (27). We selected the paper reviewed in this section from this long list of articles on potential dietary supplements because Ca intake levels in adults have long been linked to changing risk for a number of chronic disease processes, including type 2 diabetes, but excessive Ca intake (without coadministered vitamin D) might also increase the risk for myocardial infarction (28). A previous meta-analysis demonstrated a possible link between Ca consumption and T2D development, but this relationship was confounded by magnesium intake (29). This latest meta-analysis shows clearly that an inverse association exists between dietary Ca intake and risk of T2D in the general adult populations in a dose-response manner, with the intake of 750 mg/day sufficient to reduce the risk of developing T2D. It is also an important finding that more is not better for diabetes prevention, since the consumption of >900 mg/d appears to increase the risk for cardiovascular disease mortality and all-cause mortality (30). In addition, Ca is also important for bone health in diabetes (31). So, for now, we should all try to achieve this ∼750 mg/day threshold for calcium intake in some way, whether through supplements, plant-based foods, animal-based foods, or some combination of these. A list of foods enriched in calcium can be found here: www.bonehealthandosteoporosis.org/patients/treatment/calciumvitamin-d/a-guide-to-calcium-rich-foods/INSULIN DOSING STRATEGIES FOR COMPLEX MEALSFor a High Fat, High Protein Breakfast, Preprandial Administration of 125% of the Insulin Dose Improves Postprandial Glycaemic Excursions in People with Type 1 Diabetes Using Multiple Daily Injections: a Cross-Over TriaSmith TA1,2, Smart CE1,2,3, Howley PP4, Lopez PE1,2,3, King BR1,2,31Faculty of Health and Medicine, University of Newcastle, Callaghan, Australia; 2Hunter Medical Research Institute, New Lambton Heights, Australia; 3Department of Paediatric Endocrinology, John Hunter Children's Hospital, New Lambton Heights, Australia; 4Faculty of Science, University of Newcastle, Callaghan, AustraliaDiabet Med 2021;38: e14512BackgroundA major challenge for individuals living with type 1 diabetes (T1D) is controlling glycemia after meals that have significant amounts of carbohydrates and are mixed with high fat or high protein foods (32). Adding protein and fat to meals with carbohydrate increases peak glucose levels and extends the glucose profile (32,33), suggesting that more insulin may be needed at meal time and perhaps later as well (32). To increase the time action of prandial insulin for individuals on insulin pumps, a modified bolus profile can be given (e.g., dual wave or square wave bolus), but those on multiple daily injections (MDI) of insulin do not have this ability. For the latter group, the use of regular insulin may be advantageous in these situations, since the time action profile is much longer for regular insulin than for rapid-acting insulin analogues.MethodsIndividuals with T1D (N=24, ages 9–35 years old) using MDI therapy consumed a high fat, high protein "test" breakfast. Researchers compared preprandial insulin-dosing based on the study participant's unique insulin-to-car