Matthew J Gurka1, Sherita H Golden2,3, Solomon K Musani4, Mario Sims4, Abhishek Vishnu1,5, Yi Guo1, Michelle Cardel1, Thomas A Pearson6, Mark D DeBoer7. 1. Department of Health Outcomes and Policy, College of Medicine, University of Florida, Gainesville, FL, USA. 2. Department of Medicine, Johns Hopkins University, Baltimore, MD, USA. 3. Department of Epidemiology, Johns Hopkins University, Baltimore, MD, USA. 4. Department of Medicine, Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS, USA. 5. Icahn School of Medicine at Mount Sinai, New York, NY, USA. 6. Department of Epidemiology, College of Medicine, University of Florida, Gainesville, FL, USA. 7. Department of Pediatrics, Division of Pediatric Endocrinology, University of Virginia, 409 Lane Road, Room 2017, PO Box 800386, Charlottesville, VA, 22908, USA. deboer@virginia.edu.
Abstract
AIMS/HYPOTHESIS: The study aimed to assess for an association between the degree of severity of the metabolic syndrome and risk of type 2 diabetes beyond that conferred by the individual components of the metabolic syndrome. METHODS: We assessed HRs for an Adult Treatment Panel III (ATP-III) metabolic syndrome score (ATP-III MetS) and a sex- and race-specific continuous metabolic syndrome severity z score related to incident diabetes over a median of 7.8 years of follow-up among participants of two observational cohorts, the Atherosclerosis Risk in Communities study (n = 10,957) and the Jackson Heart Study (n = 2137). RESULTS: The ATP-III MetS had an HR for incident diabetes of 4.36 (95% CI 3.83, 4.97), which was attenuated in models that included the individual metabolic syndrome components. By contrast, participants in the fourth quartile of metabolic syndrome severity (compared with the first quartile) had an HR of 17.4 (95% CI 12.6, 24.1) for future diabetes; in models that also included the individual metabolic syndrome components, this remained significant, with an HR of 3.69 (95% CI 2.42, 5.64). There was a race × metabolic syndrome interaction in these models such that HR was greater for black participants (5.30) than white participants (2.24). When the change in metabolic syndrome severity score was included in the hazard models, this conferred a further association, with changes in metabolic syndrome severity score of ≥0.5 having a HR of 2.66 compared with changes in metabolic syndrome severity score of ≤0. CONCLUSIONS/ INTERPRETATION: Use of a continuous sex- and race-specific metabolic syndrome severity z score provided an additional prediction of risk of diabetes beyond that of the individual metabolic syndrome components, suggesting an added risk conferred by the processes underlying the metabolic syndrome. Increases in this score over time were associated with further risk, supporting the potential clinical utility of following metabolic syndrome severity over time.
AIMS/HYPOTHESIS: The study aimed to assess for an association between the degree of severity of the metabolic syndrome and risk of type 2 diabetes beyond that conferred by the individual components of the metabolic syndrome. METHODS: We assessed HRs for an Adult Treatment Panel III (ATP-III) metabolic syndrome score (ATP-IIIMetS) and a sex- and race-specific continuous metabolic syndrome severity z score related to incident diabetes over a median of 7.8 years of follow-up among participants of two observational cohorts, the Atherosclerosis Risk in Communities study (n = 10,957) and the Jackson Heart Study (n = 2137). RESULTS: The ATP-IIIMetS had an HR for incident diabetes of 4.36 (95% CI 3.83, 4.97), which was attenuated in models that included the individual metabolic syndrome components. By contrast, participants in the fourth quartile of metabolic syndrome severity (compared with the first quartile) had an HR of 17.4 (95% CI 12.6, 24.1) for future diabetes; in models that also included the individual metabolic syndrome components, this remained significant, with an HR of 3.69 (95% CI 2.42, 5.64). There was a race × metabolic syndrome interaction in these models such that HR was greater for black participants (5.30) than white participants (2.24). When the change in metabolic syndrome severity score was included in the hazard models, this conferred a further association, with changes in metabolic syndrome severity score of ≥0.5 having a HR of 2.66 compared with changes in metabolic syndrome severity score of ≤0. CONCLUSIONS/ INTERPRETATION: Use of a continuous sex- and race-specific metabolic syndrome severity z score provided an additional prediction of risk of diabetes beyond that of the individual metabolic syndrome components, suggesting an added risk conferred by the processes underlying the metabolic syndrome. Increases in this score over time were associated with further risk, supporting the potential clinical utility of following metabolic syndrome severity over time.
Entities:
Keywords:
Insulin resistance; Metabolic syndrome; Risk; Type 2 diabetes mellitus
Authors: David C Goff; Donald M Lloyd-Jones; Glen Bennett; Sean Coady; Ralph B D'Agostino; Raymond Gibbons; Philip Greenland; Daniel T Lackland; Daniel Levy; Christopher J O'Donnell; Jennifer G Robinson; J Sanford Schwartz; Susan T Shero; Sidney C Smith; Paul Sorlie; Neil J Stone; Peter W F Wilson; Harmon S Jordan; Lev Nevo; Janusz Wnek; Jeffrey L Anderson; Jonathan L Halperin; Nancy M Albert; Biykem Bozkurt; Ralph G Brindis; Lesley H Curtis; David DeMets; Judith S Hochman; Richard J Kovacs; E Magnus Ohman; Susan J Pressler; Frank W Sellke; Win-Kuang Shen; Sidney C Smith; Gordon F Tomaselli Journal: Circulation Date: 2013-11-12 Impact factor: 29.690
Authors: Salvatore Mottillo; Kristian B Filion; Jacques Genest; Lawrence Joseph; Louise Pilote; Paul Poirier; Stéphane Rinfret; Ernesto L Schiffrin; Mark J Eisenberg Journal: J Am Coll Cardiol Date: 2010-09-28 Impact factor: 24.094
Authors: Mark D DeBoer; Matthew J Gurka; Sherita Hill Golden; Solomon K Musani; Mario Sims; Abhishek Vishnu; Yi Guo; Thomas A Pearson Journal: J Am Coll Cardiol Date: 2017-03-07 Impact factor: 24.094
Authors: Michelle I Cardel; Yi Guo; Mario Sims; Akilah Dulin; Darci Miller; Xiaofei Chi; Gregory Pavela; Mark D DeBoer; Matthew J Gurka Journal: Psychoneuroendocrinology Date: 2020-04-26 Impact factor: 4.905
Authors: Jenna Sopfe; Laura Pyle; Amy K Keating; Kristen Campbell; Arthur K Liu; R Paul Wadwa; Michael R Verneris; Roger H Giller; Gregory P Forlenza Journal: Blood Adv Date: 2019-02-12
Authors: H Matthew Lehrer; Mary A Steinhardt; Susan K Dubois; Mark L Laudenslager Journal: Psychoneuroendocrinology Date: 2019-11-10 Impact factor: 4.905
Authors: Mark D DeBoer; Stephanie L Filipp; Solomon K Musani; Mario Sims; Mark D Okusa; Matthew Gurka Journal: Kidney Blood Press Res Date: 2018-04-06 Impact factor: 2.687