Cohort profile: The MULTI sTUdy Diabetes rEsearch (MULTITUDE) consortium

Purpose Globally, the age-standardised prevalence of type 2 diabetes mellitus (T2DM) has nearly doubled from 1980 to 2014, rising from 4.7% to 8.5% with an estimated 422 million adults living with the chronic disease. The MULTI sTUdy Diabetes rEsearch (MULTITUDE) consortium was recently established to harmonise data from 17 independent cohort studies and clinical trials and to facilitate a better understanding of the determinants, risk factors and outcomes associated with T2DM. Participants Participants range in age from 3 to 88 years at baseline, including both individuals with and without T2DM. MULTITUDE is an individual-level pooled database of demographics, comorbidities, relevant medications, clinical laboratory values, cardiac health measures, and T2DM-associated events and outcomes across 45 US states and the District of Columbia. Findings to date Among the 135 156 ongoing participants included in the consortium, almost 25% (33 421) were diagnosed with T2DM at baseline. The average age of the participants was 54.3, while the average age of participants with diabetes was 64.2. Men (55.3%) and women (44.6%) were almost equally represented across the consortium. Non-whites accounted for 31.6% of the total participants and 40% of those diagnosed with T2DM. Fewer individuals with diabetes reported being regular smokers than their non-diabetic counterparts (40.3% vs 47.4%). Over 85% of those with diabetes were reported as either overweight or obese at baseline, compared with 60.7% of those without T2DM. We observed differences in all-cause mortality, overall and by T2DM status, between cohorts. Future plans Given the wide variation in demographics and all-cause mortality in the cohorts, MULTITUDE consortium will be a unique resource for conducting research to determine: differences in the incidence and progression of T2DM; sequence of events or biomarkers prior to T2DM diagnosis; disease progression from T2DM to disease-related outcomes, complications and premature mortality; and to assess race/ethnicity differences in the above associations.

[1]  Parminder Raina,et al.  Maelstrom Research guidelines for rigorous retrospective data harmonization , 2016, International journal of epidemiology.

[2]  N. Wong,et al.  Evaluating the Quality of Comprehensive Cardiometabolic Care for Patients With Type 2 Diabetes in the U.S.: The Diabetes Collaborative Registry , 2016, Diabetes Care.

[3]  M. Roden,et al.  Cohort profile: the German Diabetes Study (GDS) , 2016, Cardiovascular Diabetology.

[4]  C. Escobar Cervantes,et al.  [A randomized trial of intensive versus standard blood pressure control]. , 2016, Semergen.

[5]  Ramachandran S Vasan,et al.  Cohort Profile: The Framingham Heart Study (FHS): overview of milestones in cardiovascular epidemiology. , 2015, International journal of epidemiology.

[6]  Dan J Stein,et al.  Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013 , 2015, BDJ.

[7]  A. Dyer,et al.  Data Resource Profile Data Resource Profile : The Cardiovascular Disease Lifetime Risk Pooling Project , 2015 .

[8]  H. Yamashita,et al.  Cohort profile: The Japan diabetes complications study: a long-term follow-up of a randomised lifestyle intervention study of type 2 diabetes. , 2014, International journal of epidemiology.

[9]  Markus Perola,et al.  Data harmonization and federated analysis of population-based studies: the BioSHaRE project , 2013, Emerging Themes in Epidemiology.

[10]  P. Kearney,et al.  Cohort profile: The Cork and Kerry Diabetes and Heart Disease Study. , 2013, International journal of epidemiology.

[11]  L. Balluz,et al.  Trends in Cigarette Smoking Rates and Quit Attempts Among Adults With and Without Diagnosed Diabetes, United States, 2001–2010 , 2013, Preventing chronic disease.

[12]  Kaarin J Anstey,et al.  COSMIC (Cohort Studies of Memory in an International Consortium): An international consortium to identify risk and protective factors and biomarkers of cognitive ageing and dementia in diverse ethnic and sociocultural groups , 2013, Alzheimer's & Dementia.

[13]  A. Fan Trends in Cigarette Smoking Rates and Quit Attempts Among Adults With and Without Diagnosed Diabetes: Findings From 2001 to 2010 Behavioral Risk Factors Surveillance System , 2013 .

[14]  Parminder Raina,et al.  Facilitating collaborative research: Implementing a platform supporting data harmonization and pooling , 2012 .

[15]  R. Ness-Abramof,et al.  A Two-Year Randomized Trial of Obesity Treatment in Primary Care Practice , 2012 .

[16]  B. Chaitman,et al.  Liberal or restrictive transfusion in high-risk patients after hip surgery. , 2011, The New England journal of medicine.

[17]  A. Alwan Global status report on noncommunicable diseases 2010. , 2011 .

[18]  Peter A. Bath,et al.  The harmonisation of longitudinal data: a case study using data from cohort studies in The Netherlands and the United Kingdom , 2010, Ageing and Society.

[19]  Maria Mori Brooks,et al.  A randomized trial of therapies for type 2 diabetes and coronary artery disease. , 2009, The New England journal of medicine.

[20]  W. Cushman,et al.  Prevention of cardiovascular disease in persons with type 2 diabetes mellitus: current knowledge and rationale for the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. , 2007, The American journal of cardiology.

[21]  Ralph B D'Agostino,et al.  Prediction of incident diabetes mellitus in middle-aged adults: the Framingham Offspring Study. , 2007, Archives of internal medicine.

[22]  J. Manson,et al.  Ethnicity, Obesity, and Risk of Type 2 Diabetes in Women , 2006, Diabetes Care.

[23]  Vittorio Krogh,et al.  Methods for pooling results of epidemiologic studies: the Pooling Project of Prospective Studies of Diet and Cancer. , 2006, American journal of epidemiology.

[24]  B. Rosner,et al.  Rationale and design of the Optimal Macro-Nutrient Intake Heart Trial to Prevent Heart Disease (OMNI-Heart) , 2005, Clinical trials.

[25]  R. D'Agostino,et al.  The Cardiovascular Outcomes with Renal Atherosclerotic Lesions (CORAL) study: rationale and methods. , 2005, Journal of vascular and interventional radiology : JVIR.

[26]  R. Holman,et al.  A model to estimate the lifetime health outcomes of patients with Type 2 diabetes: the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model (UKPDS no. 68) , 2004, Diabetologia.

[27]  Muin J Khoury,et al.  The case for a global human genome epidemiology initiative , 2004, Nature Genetics.

[28]  David M Eddy,et al.  Archimedes: a trial-validated model of diabetes. , 2003, Diabetes care.

[29]  Stephen W. Sorensen,et al.  Lifetime risk for diabetes mellitus in the United States. , 2003, JAMA.

[30]  B. Davis,et al.  Major outcomes in high-risk hypertensive patients randomized to angiotensin-converting enzyme inhibitor or calcium channel blocker vs diuretic: The Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). , 2002, JAMA.

[31]  A L Waldo,et al.  A comparison of rate control and rhythm control in patients with atrial fibrillation. , 2002, The New England journal of medicine.

[32]  A. Morris,et al.  Considerations in assessing effectiveness and costs of diabetes care: lessons from DARTS , 2002, Diabetes/metabolism research and reviews.

[33]  G. Berenson Bogalusa Heart Study: A Long‐Term Community Study of a Rural Biracial (Black/White) Population , 2001, The American journal of the medical sciences.

[34]  S. Wannamethee,et al.  Smoking as a modifiable risk factor for type 2 diabetes in middle-aged men. , 2001, Diabetes care.

[35]  J. de Irala,et al.  Intervention study for smoking cessation in diabetic patients: a randomized controlled trial in both clinical and primary care settings. , 2000, Diabetes care.

[36]  T. Manolio,et al.  Overview of the Jackson Heart Study: a study of cardiovascular diseases in African American men and women. , 1999, The American journal of the medical sciences.

[37]  Obesity and cardiovascular disease risk factors in black and white girls: the NHLBI Growth and Health Study. , 1992, American journal of public health.

[38]  Aric Invest The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. The ARIC investigators , 1989 .

[39]  A. Folsom,et al.  The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. The ARIC investigators. , 1989, American journal of epidemiology.