Obesity and Diabetes
2023; Mary Ann Liebert, Inc.; Volume: 25; Issue: S1 Linguagem: Inglês
10.1089/dia.2023.2515
ISSN1557-8593
AutoresViral N. Shah, Francesco Prattichizzo, Antonio Ceriello,
Tópico(s)Diet and metabolism studies
ResumoDiabetes Technology & TherapeuticsVol. 25, No. S1 Original ArticlesFree AccessObesity and DiabetesViral N. Shah, Francesco Prattichizzo, and Antonio CerielloViral N. ShahBarbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.Search for more papers by this author, Francesco PrattichizzoIRCCS MultiMedica, Milan, Italy.Search for more papers by this author, and Antonio CerielloIRCCS MultiMedica, Milan, Italy.Search for more papers by this authorPublished Online:20 Feb 2023https://doi.org/10.1089/dia.2023.2515AboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail IntroductionThe prevalence of obesity is increasing worldwide, and it has become a significant public health problem. Obesity is associated with increased insulin resistance and higher risk for type 2 diabetes (T2D), cardiovascular disease (CVD), and nonalcoholic fatty liver diseases (NAFLD). Unfortunately, obesity is also increasing among people with type 1 diabetes (T1D), leading to suboptimal glycemic control and increased risk for CVD. Therefore, we introduce this new article to the ATTD Yearbook to provide readers with highlights of recently published significant research articles in this field.In this article, we have reviewed published literature (PubMed) in the last year (July 1, 2021, to June 9, 2022) by using the following search criteria: overweight [tiab] AND obesity [tiab] AND diabetes [title] for articles related to obesity and diabetes and nonalcoholic fatty liver disease [tiab] OR non-alcoholic steatohepatitis [tiab] AND diabetes [title] for diabetes and NFLD related articles. Only human studies that were published in the English language were reviewed. For the diabetes and NFLD articles, selection was focused on randomized controlled trials of therapeutics agents to treat fatty liver disease. Of 305 research articles, we selected five best articles in the field of "Obesity and Diabetes" and five articles related to "Diabetes and NFALD." These research articles are summarized below.Key Articles ReviewedBody-Mass Index and Diabetes Risk in Fifty-Seven Low-Income and Middle-Income Countries: A Cross-Sectional Study of Nationally Representative, Individual-Level Data in 685,616 AdultsTeufel F, Seiglie JA, Geldsetzer P, Theilmann M, Marcus ME, Ebert C, Arboleda WAL, Agoudavi K, Andall-Brereton G, Aryal KK, Bicaba BW, Brian G, Bovet P, Dorobantu M, Gurung MS, Guwatudde D, Houehanou C, Houinato D, Jorgensen JMA, Kagaruki GB, Karki KB, Labadarios D, Martins JS, Mayige MT, McClure RW, Mwangi JK, Mwalim O, Norov B, Crooks S, Farzadfar F, Moghaddam SS, Silver BK, Sturua L, Wesseh CS, Stokes AC, Essien UR, De Neve JW, Atun R, Davies JI, Vollmer S, Bärnighausen TW, Ali MK, Meigs JB, Wexler DJ, Manne-Goehler JLancet 2021;398(10296): 238–248Childhood Body Size Directly Increases Type 1 Diabetes Risk Based on a Lifecourse Mendelian Randomization ApproachRichardson TG, Crouch DJM, Power GM, Morales-Berstein F, Hazelwood E, Fang S, Cho Y, Inshaw JRJ, Robertson CC, Sidore C, Cucca F, Rich SS, Todd JA, Davey Smith GNat Commun 2022;13: 2337Obesity in People Living with Type 1 DiabetesVan der Schueren B, Ellis D, Faradji RN, Al-Ozairi E, Rosen J, Mathieu CLancet Diabetes Endocrinol 2021;9: 776–785Effect of Weekly Subcutaneous Semaglutide vs Daily Liraglutide on Body Weight in Adults with Overweight or Obesity Without Diabetes: The STEP 8 Randomized Clinical TrialRubino DM, Greenway FL, Khalid U, O'Neil PM, Rosenstock J, Sørrig R, Wadden TA, Wizert A, Garvey W for the STEP 8 InvestigatorsJAMA 2022;327: 138–150Dose-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: 1672–1681The Effects of Dapagliflozin on Hepatic and Visceral Fat in Type 2 Diabetes Patients with Non-Alcoholic Fatty Liver DiseasePhrueksotsai S, Pinyopornpanish K, Euathrongchit J, Leerapun A, Phrommintikul A, Buranapin S, Chattipakorn N, Thongsawat SJ Gastroenterol Hepatol 2021;36: 2952–2959A Placebo-Controlled Trial of Subcutaneous Semaglutide in Nonalcoholic SteatohepatitisNewsome PN, Buchholtz K, Cusi K, Linder M, Okanoue T, Ratziu V, Sanyal AJ, Sejling AS, Harrison SA, on behalf of the NN9931-4296 InvestigatorsN Engl J Med 2021;384: 1113–1124Pioglitazone Even at Low Dosage Improves NAFLD in Type 2 Diabetes: Clinical and Pathophysiological Insights from a Subgroup of the TOSCA.IT Randomised Trial.Della Pepa G, Russo M, Vitale M, Carli F, Vetrani C, Masulli M, Riccardi G, Vaccaro O, Gastaldelli A, Rivellese AA, Bozzetto LDiabetes Res Clin Pract 2021;178: 108984Emerging Therapeutic Approaches for the Treatment of NAFLD and Type 2 Diabetes MellitusFerguson D, Finck BNNat Rev Endocrinol 2021;17: 484–495American Association of Clinical Endocrinology Clinical Practice Guideline for the Diagnosis and Management of Nonalcoholic Fatty Liver Disease in Primary Care and Endocrinology Clinical Settings: Co-Sponsored by the American Association for the Study of Liver Diseases (AASLD)Cusi K, Isaacs S, Barb D, Basu R, Caprio S, Garvey WT, Kashyap S, Mechanick JI, Mouzaki M, Nadolsky K, Rinella ME, Vos MB, Younossi ZEndocr Pract 2022;28: 528–562OBESITY AND DIABETESBody-Mass Index and Diabetes Risk in Fifty-Seven Low-Income and Middle-Income Countries: A Cross-Sectional Study of Nationally Representative, Individual-Level Data In 685,616 AdultsTeufel F1, Seiglie JA2,5, Geldsetzer P1,7, Theilmann M1, Marcus ME8, Ebert C9, Arboleda WAL1, Agoudavi K10, Andall-Brereton G11, Aryal KK12, Bicaba BW13, Brian G14, Bovet P15,16, Dorobantu M17, Gurung MS18, Guwatudde D19, Houehanou C20, Houinato D20, Jorgensen JMA21, Kagaruki GB22, Karki KB23, Labadarios D24, Martins JS26, Mayige MT22, McClure RW27, Mwangi JK28,29, Mwalim O30, Norov B31, Crooks S11, Farzadfar F32, Moghaddam SS33, Silver BK34, Sturua L35,36, Wesseh CS37, Stokes AC38, Essien UR39,40, De Neve JW1, Atun R41,42, Davies JI25,43,44, Vollmer S8, Bärnighausen TW1,41,45, Ali MK46,47, Meigs JB3,5, Wexler DJ2,5, Manne-Goehler J4,5,61Heidelberg Institute of Global Health, Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg, Germany; 2Diabetes Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA; 3Department of General Internal Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA; 4Medical Practice Evaluation Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA; 5Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; 6Division of Infectious Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; 7Division of Primary Care and Population Health, Department of Medicine, Stanford University, Stanford, CA; 8Department of Economics and Centre for Modern Indian Studies, University of Goettingen, Göttingen, Germany; 9RWI-Leibniz Institute for Economic Research, Essen (Berlin Office), Germany; 10Togo Ministry of Health, Lome, Togo; 11Caribbean Public Health Agency, Port of Spain, Trinidad and Tobago; 12Nepal Health Sector Programme 3, Monitoring Evaluation and Operational Research Project, Abt Associates, Kathmandu, Nepal; 13Institut National de Santé Ouagadougou, Burkina Faso; 14The Fred Hollows Foundation New Zealand, Auckland, New Zealand; 15Ministry of Health, Victoria, Seychelles; 16University Center for Primary Care and Public Health, Lausanne, Switzerland; 17University of Medicine and Pharmacy Carol Davila, Bucharest, Romania; 18Health Research and Epidemiology Unit, Ministry of Health, Bhutan; 19Department of Epidemiology and Biostatistics, School of Public Health, Makerere University, Kampala, Uganda; 20Laboratory of Epidemiology of Chronic and Neurological Diseases, Faculty of Health Sciences, University of Abomey-Calavi, Benin; 21Dept of Public Health, University of Copenhagen, Copenhagen, Denmark; 22National Institute for Medical Research, Dar es Salaam, Tanzania; 23Department of Community Medicine and Public Health, Institute of Medicine, Tribhuvan University, Kathmandu, Nepal; 24Faculty of Medicine and Health Sciences, Stellenbosch University, South Africa; 25Department of Global Health, Centre for Global Surgery, Stellenbosch University, South Africa; 26Faculty of Medicine and Health Sciences, National University of East Timor, Rua Jacinto Candido, Dili, Timor-Leste; 27Epidemiology Office and Surveillance, Caja Costarricense de Seguro Social, San Jose, Costa Rica; 28Division of Non-Communicable Diseases, Ministry of Health, Nairobi, Kenya; 29Faculté de Médecine, Université de Genève, Geneva, Switzerland; 30Zanzibar Ministry of Health, Mnazi Mmoja, Zanzibar; 31National Center for Public Health, Ulaanbaatar, Mongolia; 32NonCommunicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran; 33Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran; 34St. Francis Hospital, Nsambya, Kampala, Uganda; 35NonCommunicable Diseases Department, National Center for Disease Control and Public Health, Tbilisi, Georgia; 36Petre Shotadze Tbilisi Medical Academy, Tbilisi, Georgia; 37Liberia Ministry of Health, Monrovia, Liberia; 38Department of Global Health, Boston University School of Public Health, Boston, MA; 39Division of General Internal Medicine, University of Pittsburgh, Pittsburgh, PA; 40Center for Health Equity Research and Promotion, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA; 41Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA; 42Department of Global Health and Social Medicine, Harvard Medical School, Harvard University, Boston, MA; 43MRC/Wits Rural Public Health and Health Transitions Research Unit, School of Public Health, University of Witwatersrand, Johannesburg, South Africa; 44Institute of Applied Health Research, University of Birmingham, Birmingham, UK; 45Africa Health Research Institute, Somkhele, South Africa; 46Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA; 47Departments of Family and Preventive Medicine, School of Medicine, Emory University, Atlanta, GALancet 2021;398(10296): 238–248BackgroundIn low-income and middle-income countries (LMICs), overweight, obesity, and diabetes are rapidly becoming more prevalent. However, there are insufficient data on the association between body-mass index (BMI) and diabetes in these settings.MethodsIn this cross-sectional study, we pooled individual-level data from nationally representative surveys across 57 LMICs. We identified all countries in which a World Health Organization (WHO) Stepwise Approach to Surveillance (STEPS) survey had been done during a year in which the country fell into an eligible World Bank income group category. For LMICs that did not have a STEPS survey, did not have valid contact information, or declined our request for data, we did a systematic search for survey datasets. Eligible surveys were done during or after 2008; had individual-level data; were done in a low-income, lower-middle-income, or upper-middle-income country; were nationally representative; had a response rate of 50% or higher; contained a diabetes biomarker (either a blood glucose measurement or glycated hemoglobin [HbA1c]); and contained data on height and weight. Diabetes was defined biologically as a fasting plasma glucose concentration of 7.0 mmol/L (126.0 mg/dL) or higher; a random plasma glucose concentration of 11.1 mmol/L (200.0 mg/dL) or higher; an HbA1c of 6.5% (48.0 mmol/mol) or higher; or by self-reported use of diabetes medication. We included individuals aged 25 years or older with complete data on sex, age, diabetes status, and BMI (defined as normal [18.5–22.9], upper-normal [23.0–24.9], overweight [25.0–29.9], or obese [≥30.0]). Countries were categorized into six geographical regions: Latin America and the Caribbean; Europe and central Asia; east, south, and southeast Asia; sub-Saharan Africa, Middle East, and north Africa; and Oceania. We estimated the association between BMI and diabetes risk by multivariable Poisson regression and receiver operating curve analyses, stratified by sex and geographical region.FindingsThere were 685,616 individuals in the pooled dataset, which was composed of 58 nationally representative surveys from 57 LMICs. The overall prevalence of overweight was 27.2% (95% CI, 26.6%–27.8%), of obesity was 21.0% (95% CI, 19.6%–22.5%), and of diabetes was 9.3% (95% CI, 8.4%–10.2%). In the pooled analysis, higher risk of diabetes was observed at a BMI of 23 or higher than at BMI 18.5–22.9, with a 43% greater risk of diabetes for men and a 41% greater risk for women. Diabetes risk also increased steeply in individuals aged 35–44 years and in men aged 25–34 years in sub-Saharan Africa. In the stratified analyses, there was considerable regional variability in this association. Optimal BMI thresholds for diabetes screening ranged from 23.8 among men in east, south, and southeast Asia to 28.3 among women in the Middle East and north Africa and in Latin America and the Caribbean.InterpretationRegional variability exists in the association between BMI and risk of diabetes in LMICs. The BMI thresholds and age for diabetes risk were lower in this study than they are in current BMI guidelines for assessing such risk. These results can be used to modify context-specific screening guidelines.Childhood Body Size Directly Increases Type 1 Diabetes Risk Based on a Lifecourse Mendelian Randomization ApproachRichardson TG1,2, Crouch DJM3, Power GM1, Morales-Berstein F1, Hazelwood E1, Fang S1, Cho Y1, Inshaw JRJ3, Robertson CC4, Sidore C5, Cucca F5, Rich SS4, Todd JA3, Davey Smith G11MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK; 2Novo Nordisk Research Centre Oxford, Old Road Campus, Oxford, UK; 3JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Oxford, UK; 4Center for Public Health Genomics, University of Virginia, Charlottesville, VA; 5Institute for Research in Genetics and Biomedicine (IRGB), Sardinia, ItalyNat Commun 2022;13: 2337AbstractThe rising prevalence of childhood obesity has been postulated as an explanation for the increasing rate of individuals diagnosed with type 1 diabetes (T1D). In this study, we used Mendelian randomization (MR) to provide evidence that childhood body size has an effect on T1D risk (OR, 2.05 per change in body size category; 95% CI, 1.20 to 3.50; P=.008), which remains after accounting for body size at birth and during adulthood using multivariable MR (OR, 2.32; 95% CI, 1.21 to 4.42; P=.013). We validate this direct effect of childhood body size using data from a large-scale T1D meta-analysis based on 15,573 cases and 158,408 controls (OR, 1.94; 95% CI, 1.21 to 3.12; P=.006). We also provide evidence that childhood body size influences risk of asthma, eczema, and hypothyroidism, although multivariable MR suggested that these effects are mediated by body size in later life. The results of this study indicate that a large body size during childhood causes an increased risk of T1D development. However, for other immune-associated diseases, the likely cause is having been overweight for several years over the course of a lifetime and not directly related to a large body size during childhood.Obesity in People Living with Type 1 DiabetesVan der Schueren B1,2, Ellis D2, Faradji RN3,4, Al-Ozairi E5, Rosen J6, Mathieu C1,21Department of Endocrinology, University Hospitals Leuven, Leuven, Belgium; 2Laboratory of Clinical and Experimental Endocrinology, University of Leuven, Leuven, Belgium; 3Endocrinology and Diabetes, Clinica EnDi, Mexico City, Mexico; 4Centro Medico ABC, Mexico City, Mexico; 5Department of Clinical Research and Clinical Trials, Dasman Diabetes Institute, Dasman, Kuwait; 6JDRF International, New York, NYLancet Diabetes Endocrinol 2021;9: 776–785AbstractHistorically, type 1 diabetes has typically been thought to occur in lean people. However, an increasing number of people with type 1 diabetes have overweight or obesity. Nonphysiological insulin replacement that causes peripheral hyperinsulinemia, insulin profiles that do not match basal and mealtime insulin needs, defensive snacking to avoid hypoglycemia, or a combination of these are believed to affect body composition and drive excessive accumulation of body fat in people with type 1 diabetes. The consequences of overweight or obesity in people with type 1 diabetes are of particular concern, as they increase the risk of both diabetes-related and obesity-related complications, including cardiovascular disease, stroke, and various types of cancer. In this review, we summarize the current understanding of the etiology and consequences of excessive body weight in people with type 1 diabetes and highlight the need to optimize future prevention and treatment strategies in this population. Effect of Weekly Subcutaneous Semaglutide vs Daily Liraglutide on Body Weight in Adults with Overweight or Obesity Without Diabetes: The STEP 8 Randomized Clinical TrialRubino DM1, Greenway FL2, Khalid U3, O'Neil PM4, Rosenstock J5, Sørrig R3, Wadden TA6, Wizert A3, Garvey WT7 for the STEP 8 Investigators1Washington Center for Weight Management and Research, Arlington, VA; 2Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA; 3Novo Nordisk A/S, Søborg, Denmark; 4Weight Management Center, Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC; 5Dallas Diabetes Research Center at Medical City, Dallas, TX; 6Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; 7Department of Nutrition Sciences, University of Alabama at Birmingham, ALJAMA 2022;327: 138–150ImportanceThus far, semaglutide and liraglutide have not been compared for weight management in phase 3 trials.ObjectiveTo compare a once-weekly 2.4-mg dose of subcutaneous semaglutide with once-daily 3.0-mg dose of subcutaneous liraglutide in individuals with overweight or obesity when all individuals receive counseling for diet and physical activity.Design, Setting, and ParticipantsRandomized, open-label, 68-week, phase 3b trial conducted at 19 US sites from September 2019 (enrollment: September 11 to November 26) to May 2021 (end of follow-up: May 11) in adults without diabetes with body mass index of 1) 30 or greater or 2) 27 or greater with one or more weight-related comorbidities (N=338).InterventionsParticipants were randomized (3:1:3:1) to receive once-weekly subcutaneous 2.4-mg semaglutide (16-week escalation; n=126) or matching placebo or to receive once-daily subcutaneous 3.0-mg liraglutide (4-week escalation; n=127) or matching placebo; diet and physical activity were assigned for all groups. Participants unable to tolerate 2.4 mg of semaglutide could receive 1.7 mg; participants unable to tolerate 3.0 mg of liraglutide discontinued treatment and could restart the 4-week titration. Placebo groups were pooled (n=85).Main Outcomes and MeasuresThe primary endpoint was percentage change in body weight, and confirmatory secondary endpoints were achievement of 10% or more, 15% or more, and 20% or more weight loss, assessed for semaglutide and liraglutide at week 68. Semaglutide-vs-liraglutide comparisons were open-label, with active treatment groups double-blinded against matched placebo groups. Comparisons of active treatments with pooled placebo were supportive secondary endpoints.ResultsOf 338 randomized participants (mean [SD] age, 49 [13] years; 265 women [78.4%]; mean [SD] body weight, 104.5 [23.8] kg; mean [SD] body mass index, 37.5 [6.8]), 319 (94.4%) completed the trial, and 271 (80.2%) completed treatment. The mean weight change from baseline was −15.8% with semaglutide and −6.4% with liraglutide (difference, −9.4 percentage points [95% CI, −12.0 to −6.8]; P<.001); weight change with pooled placebo was −1.9%. Participants had significantly greater odds of achieving 10% or more, 15% or more, and 20% or more weight loss with semaglutide than with liraglutide (70.9% of participants vs 25.6% [odds ratio, 6.3 {95% CI, 3.5 to 11.2}]; 55.6% vs 12.0% [odds ratio, 7.9 {95% CI, 4.1 to 15.4}]; and 38.5% vs 6.0% [odds ratio, 8.2 {95% CI, 3.5 to 19.1}], respectively; all P<.001). Proportions of participants discontinuing treatment for any reason were 13.5% with semaglutide and 27.6% with liraglutide. Gastrointestinal adverse events were reported by 84.1% with semaglutide and 82.7% with liraglutide.Conclusions and RelevanceSignificantly greater weight loss at 68 weeks was seen for once-weekly semaglutide than for once-daily liraglutide in adults who had overweight or obesity but not diabetes and were receiving counseling for diet and physical activity.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: 1672–1681ObjectiveTo assess dietary glycemic index (GI), glycemic load (GL), and fiber for longitudinal and dose-dependent associations with body weight and glycemic status in adults with high risk for type 2 diabetes who were participating in a 3-year weight loss maintenance program.Research Design and MethodsIn this secondary analysis, we used pooled data from PREVIEW (PREVention of diabetes through lifestyle Intervention and population studies in Europe and around the World), a randomized controlled trial that was designed to test the effects of four diet and physical activity interventions. A total of 1279 participants with overweight or obesity (age 25–70 years and BMI ≥25) and prediabetes at baseline were included. We used multiadjusted linear mixed models with repeated measurements to assess longitudinal and dose-dependent associations by merging the participants into one group and dividing them into GI, GL, and fiber tertiles, respectively.ResultsIn the available-case analysis, each 10-unit increment in GI was associated with a greater regain of weight (0.46 kg/year; 95% CI, 0.23–0.68; P<0.001) and increase in HbA1c. Each 20-unit increment in GL was associated with a greater regain of weight (0.49 kg/year; 95% CI, 0.24–0.75; P<0.001) and increase in HbA1c. The associations of GI and GL with HbA1c were independent of weight change. Compared with those in the lowest tertiles, participants in the highest GI and GL tertiles had significantly greater weight regain and increases in HbA1c. Fiber was inversely associated with increases in waist circumference, but the associations with weight regain and glycemic status did not remain robust in different analyses.ConclusionsWeight gain and deteriorating glycemic status each directly correlated with both dietary GI and GL. More data are needed regarding the role of fiber.CommentsObesity is a major risk factor for the development type 2 diabetes (T2D). The incidence and prevalence of both conditions are steadily increasing worldwide and numerous, dramatic estimates of future trend are continuously published. In one large cross-sectional study, the authors summarize the prevalence of overweight and obesity in 57 low-income and middle-income countries (LMICs), showing that the overall prevalence of overweight was 27.2% (95% CI, 26.6%–27.8%), of obesity was 21.0% (95% CI, 19.6%–22.5%), and of diabetes was 9.3% (95% CI, 8.4%–10.2%). More importantly, they demonstrate that the risk of diabetes in these LMICs is increased at a BMI of 23, a threshold substantially lower than the cut-off suggested by the majority of guidelines, which are, in most cases, based on studies performed in Western countries. Optimal BMI thresholds for diabetes screening differed according to regional areas, suggesting that screening guidelines should be context specific.Obesity in infants and adolescent is already recognized as a key risk factor for early T2D. However, the relevance of childhood body size for the development of type 1 diabetes (T1D) is more debated. In a Mendelian randomization (MR) study, the authors provide evidence that childhood body size has an effect on T1D risk, which remains significant after accounting for body size at birth and during adulthood; overall, this finding suggests a causal role for higher childhood body size on risk of being diagnosed with T1D. More broadly, the importance of managing obesity in T1D is underrecognized. Indeed, since T1D patients have an immune disease impeding proper insulin secretion, they might be seen as lean patients not requiring the management of multiple risk factors. In an intriguing review paper encompassing all the current knowledge on the topic, Van der Schueren and colleagues summarize the current understanding of the etiology and consequences of excessive body weight in people with type 1 diabetes and highlight the need to optimize future prevention and treatment strategies in this population. In particular, they emphasize that body composition and fat accumulation in T1D might be driven by nonphysiological insulin replacement that causes peripheral hyperinsulinemia, insulin profiles that do not match basal and mealtime insulin needs, defensive snacking to avoid hypoglycemia, or a combination of these. The consequences of obesity in T1D are the same as in the general population. Thus, this risk factor in this population should also be properly managed.The first approach to prevent or revert obesity is always based on lifestyle changes. However, when interventions based on physical activity or diet regimens do not suffice, pharmacological or surgical approaches are needed. In the last year, new classes of glucose-lowering drugs—in particular, GLP-1 receptor agonists—have demonstrated a clear benefit in terms of weight loss. Many trials have tested and are still assessing the effect of this class on weight reduction, with outstanding results both in patients with and in those without diabetes. One such trial compared the effect of weekly subcutaneous semaglutide with that of daily liraglutide on body weight in obese patients without diabetes. Highly consistent weight reductions were obtained with both drugs, with weekly semaglutide outperforming the comparator. These effects were observed after 68 weeks, meaning that the weight-reducing effect of these drugs is sustained. More trials with this or similar design have been or are being published, with new drugs adding other mechanis
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