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Domalpally A, Whittier SA, Pan Q, Dabelea DM, Darwin CH, Knowler WC, Lee CG, Luchsinger JA, White NH, Chew EY, Gadde KM, Culbert IW, Arceneaux J, Chatellier A, Dragg A, Champagne CM, Duncan C, Eberhardt B, Greenway F, Guillory FG, Herbert AA, Jeffirs ML, Kennedy BM, Levy E, Lockett M, Lovejoy JC, Morris LH, Melancon LE, Ryan DH, Sanford DA, Smith KG, Smith LL, St.Amant JA, Tulley RT, Vicknair PC, Williamson D, Zachwieja JJ, Polonsky KS, Tobian J, Ehrmann DA, Matulik MJ, Temple KA, Clark B, Czech K, DeSandre C, Dotson B, Hilbrich R, McNabb W, Semenske AR, Caro JF, Furlong K, Goldstein BJ, Watson PG, Smith KA, Mendoza J, Simmons M, Wildman W, Liberoni R, Spandorfer J, Pepe C, Donahue RP, Goldberg RB, Prineas R, Calles J, Giannella A, Rowe P, Sanguily J, Cassanova-Romero P, Castillo-Florez S, Florez HJ, Garg R, Kirby L, Lara O, Larreal C, McLymont V, Mendez J, Perry A, Saab P, Veciana B, Haffner SM, Hazuda HP, Montez MG, Hattaway K, Isaac J, Lorenzo C, Martinez A, Salazar M, Walker T, Hamman RF, Nash PV, Steinke SC, Testaverde L, Truong J, Anderson DR, Ballonoff LB, Bouffard A, Bucca B, Calonge BN, Delve L, Farago M, Hill JO, Hoyer SR, Jenkins T, Jortberg BT, Lenz D, Miller M, Nilan T, Perreault L, Price DW, Regensteiner JG, Schroeder EB, Seagle H, Smith CM, VanDorsten B, Horton ES, Munshi M, Lawton KE, Jackson SD, Poirier CS, Swift K, Arky RA, Bryant M, Burke JP, Caballero E, Callaphan KM, Fargnoli B, Franklin T, Ganda OP, Guidi A, Guido M, Jacobsen AM, Kula LM, Kocal M, Lambert L, Ledbury S, Malloy MA, Middelbeek RJ, Nicosia M, Oldmixon CF, Pan J, Quitingon M, Rainville R, Rubtchinsky S, Seely EW, Sansoucy J, Schweizer D, Simonson D, Smith F, Solomon CG, Spellman J, Warram J, Kahn SE, Fattaleh B, Montgomery BK, Colegrove C, Fujimoto W, Knopp RH, Lipkin EW, Marr M, Morgan-Taggart I, Murillo A, O’Neal K, Trence D, Taylor L, Thomas A, Tsai EC, Dagogo-Jack S, Kitabchi AE, Murphy ME, Taylor L, Dolgoff J, Applegate WB, Bryer-Ash M, Clark D, Frieson SL, Ibebuogu U, Imseis R, Lambeth H, Lichtermann LC, Oktaei H, Ricks H, Rutledge LM, Sherman AR, Smith CM, Soberman JE, Williams-Cleaves B, Patel A, Nyenwe EA, Hampton EF, Metzger BE, Molitch ME, Johnson MK, Adelman DT, Behrends C, Cook M, Fitzgibbon M, Giles MM, Heard D, Johnson CK, Larsen D, Lowe A, Lyman M, McPherson D, Penn SC, Pitts T, Reinhart R, Roston S, Schinleber PA, Wallia A, Nathan DM, McKitrick C, Turgeon H, Larkin M, Mugford M, Abbott K, Anderson E, Bissett L, Bondi K, Cagliero E, Florez JC, Delahanty L, Goldman V, Grassa E, Gurry L, D’Anna K, Leandre F, Lou P, Poulos A, Raymond E, Ripley V, Stevens C, Tseng B, Olefsky JM, Barrett-Connor E, Mudaliar S, Araneta MR, Carrion-Petersen ML, Vejvoda K, Bassiouni S, Beltran M, Claravall LN, Dowden JM, Edelman SV, Garimella P, Henry RR, Horne J, Lamkin M, Janesch SS, Leos D, Polonsky W, Ruiz R, Smith J, Torio-Hurley J, Pi-Sunyer FX, Lee JE, Hagamen S, Allison DB, Agharanya N, Aronoff NJ, Baldo M, Crandall JP, Foo ST, Luchsinger JA, Pal C, Parkes K, Pena MB, Rooney ES, Van Wye GE, Viscovich KA, de Groot M, Marrero DG, Mather KJ, Prince MJ, Kelly SM, Jackson MA, McAtee G, Putenney P, Ackermann RT, Cantrell CM, Dotson YF, Fineberg ES, Fultz M, Guare JC, Hadden A, Ignaut JM, Kirkman MS, Phillips EO, Pinner KL, Porter BD, Roach PJ, Rowland ND, Wheeler ML, Aroda V, Magee M, Ratner RE, Youssef G, Shapiro S, Andon N, Bavido-Arrage C, Boggs G, Bronsord M, Brown E, Love Burkott H, Cheatham WW, Cola S, Evans C, Gibbs P, Kellum T, Leon L, Lagarda M, Levatan C, Lindsay M, Nair AK, Park J, Passaro M, Silverman A, Uwaifo G, Wells-Thayer D, Wiggins R, Saad MF, Watson K, Budget M, Jinagouda S, Botrous M, Sosa A, Tadros S, Akbar K, Conzues C, Magpuri P, Ngo K, Rassam A, Waters D, Xapthalamous K, Santiago JV, Brown AL, Das S, Khare-Ranade P, Stich T, Santiago A, Fisher E, Hurt E, Jones T, Kerr M, Ryder L, Wernimont C, Golden SH, Saudek CD, Bradley V, Sullivan E, Whittington T, Abbas C, Allen A, Brancati FL, Cappelli S, Clark JM, Charleston JB, Freel J, Horak K, Greene A, Jiggetts D, Johnson D, Joseph H, Loman K, Mathioudakis N, Mosley H, Reusing J, Rubin RR, Samuels A, Shields T, Stephens S, Stewart KJ, Thomas L, Utsey E, Williamson P, Schade DS, Adams KS, Canady JL, Johannes C, Hemphill C, Hyde P, Atler LF, Boyle PJ, Burge MR, Chai L, Colleran K, Fondino A, Gonzales Y, Hernandez-McGinnis DA, Katz P, King C, Middendorf J, Rubinchik S, Senter W, Crandall J, Shamoon H, Brown JO, Trandafirescu G, Powell D, Adorno E, Cox L, Duffy H, Engel S, Friedler A, Goldstein A, Howard-Century CJ, Lukin J, Kloiber S, Longchamp N, Martinez H, Pompi D, Scheindlin J, Violino E, Walker EA, Wylie-Rosett J, Zimmerman E, Zonszein J, Orchard T, Venditti E, Wing RR, Jeffries S, Koenning G, Kramer MK, Smith M, Barr S, Benchoff C, Boraz M, Clifford L, Culyba R, Frazier M, Gilligan R, Guimond S, Harrier S, Harris L, Kriska A, Manjoo Q, Mullen M, Noel A, Otto A, Pettigrew J, Rockette-Wagner B, Rubinstein D, Semler L, Smith CF, Weinzierl V, Williams KV, Wilson T, Mau MK, Baker-Ladao NK, Melish JS, Arakaki RF, Latimer RW, Isonaga MK, Beddow R, Bermudez NE, Dias L, Inouye J, Mikami K, Mohideen P, Odom SK, Perry RU, Yamamoto RE, Anderson H, Cooeyate N, Dodge C, Hoskin MA, Percy CA, Enote A, Natewa C, Acton KJ, Andre VL, Barber R, Begay S, Bennett PH, Benson MB, Bird EC, Broussard BA, Bucca BC, Chavez M, Cook S, Curtis J, Dacawyma T, Doughty MS, Duncan R, Edgerton C, Ghahate JM, Glass J, Glass M, Gohdes D, Grant W, Hanson RL, Horse E, Ingraham LE, Jackson M, Jay P, Kaskalla RS, Kavena K, Kessler D, Kobus KM, Krakoff J, Kurland J, Manus C, McCabe C, Michaels S, Morgan T, Nashboo Y, Nelson JA, Poirier S, Polczynski E, Piromalli C, Reidy M, Roumain J, Rowse D, Roy RJ, Sangster S, Sewenemewa J, Smart M, Spencer C, Tonemah D, Williams R, Wilson C, Yazzie M, Bain R, Fowler S, Temprosa M, Larsen MD, Brenneman T, Edelstein SL, Abebe S, Bamdad J, Barkalow M, Bethepu J, Bezabeh T, Bowers A, Butler N, Callaghan J, Carter CE, Christophi C, Dwyer GM, Foulkes M, Gao Y, Gooding R, Gottlieb A, Grimes KL, Grover-Fairchild N, Haffner L, Hoffman H, Jablonski K, Jones S, Jones TL, Katz R, Kolinjivadi P, Lachin JM, Ma Y, Mucik P, Orlosky R, Reamer S, Rochon J, Sapozhnikova A, Sherif H, Stimpson C, Hogan Tjaden A, Walker-Murray F, Venditti EM, Kriska AM, Weinzierl V, Marcovina S, Aldrich FA, Harting J, Albers J, Strylewicz G, Eastman R, Fradkin J, Garfield S, Lee C, Gregg E, Zhang P, O’Leary D, Evans G, Budoff M, Dailing C, Stamm E, Schwartz A, Navy C, Palermo L, Rautaharju P, Prineas RJ, Alexander T, Campbell C, Hall S, Li Y, Mills M, Pemberton N, Rautaharju F, Zhang Z, Soliman EZ, Hu J, Hensley S, Keasler L, Taylor T, Blodi B, Danis R, Davis M, Hubbard* L, Endres** R, Elsas** D, Johnson** S, Myers** D, Barrett N, Baumhauer H, Benz W, Cohn H, Corkery E, Dohm K, Gama V, Goulding A, Ewen A, Hurtenbach C, Lawrence D, McDaniel K, Pak J, Reimers J, Shaw R, Swift M, Vargo P, Watson S, Manly J, Mayer-Davis E, Moran RR, Ganiats T, David K, Sarkin AJ, Groessl E, Katzir N, Chong H, Herman WH, Brändle M, Brown MB, Altshuler D, Billings LK, Chen L, Harden M, Knowler WC, Pollin TI, Shuldiner AR, Franks PW, Hivert MF. Association of Metformin With the Development of Age-Related Macular Degeneration. JAMA Ophthalmol 2023; 141:140-147. [PMID: 36547967 PMCID: PMC9936345 DOI: 10.1001/jamaophthalmol.2022.5567] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 10/29/2022] [Indexed: 12/24/2022]
Abstract
Importance Age-related macular degeneration (AMD) is a leading cause of blindness with no treatment available for early stages. Retrospective studies have shown an association between metformin and reduced risk of AMD. Objective To investigate the association between metformin use and age-related macular degeneration (AMD). Design, Setting, and Participants The Diabetes Prevention Program Outcomes Study is a cross-sectional follow-up phase of a large multicenter randomized clinical trial, Diabetes Prevention Program (1996-2001), to investigate the association of treatment with metformin or an intensive lifestyle modification vs placebo with preventing the onset of type 2 diabetes in a population at high risk for developing diabetes. Participants with retinal imaging at a follow-up visit 16 years posttrial (2017-2019) were included. Analysis took place between October 2019 and May 2022. Interventions Participants were randomly distributed between 3 interventional arms: lifestyle, metformin, and placebo. Main Outcomes and Measures Prevalence of AMD in the treatment arms. Results Of 1592 participants, 514 (32.3%) were in the lifestyle arm, 549 (34.5%) were in the metformin arm, and 529 (33.2%) were in the placebo arm. All 3 arms were balanced for baseline characteristics including age (mean [SD] age at randomization, 49 [9] years), sex (1128 [71%] male), race and ethnicity (784 [49%] White), smoking habits, body mass index, and education level. AMD was identified in 479 participants (30.1%); 229 (14.4%) had early AMD, 218 (13.7%) had intermediate AMD, and 32 (2.0%) had advanced AMD. There was no significant difference in the presence of AMD between the 3 groups: 152 (29.6%) in the lifestyle arm, 165 (30.2%) in the metformin arm, and 162 (30.7%) in the placebo arm. There was also no difference in the distribution of early, intermediate, and advanced AMD between the intervention groups. Mean duration of metformin use was similar for those with and without AMD (mean [SD], 8.0 [9.3] vs 8.5 [9.3] years; P = .69). In the multivariate models, history of smoking was associated with increased risks of AMD (odds ratio, 1.30; 95% CI, 1.05-1.61; P = .02). Conclusions and Relevance These data suggest neither metformin nor lifestyle changes initiated for diabetes prevention were associated with the risk of any AMD, with similar results for AMD severity. Duration of metformin use was also not associated with AMD. This analysis does not address the association of metformin with incidence or progression of AMD.
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Affiliation(s)
- Amitha Domalpally
- Wisconsin Reading Center, Department of Ophthalmology, University of Wisconsin School of Medicine and Public and Health, Madison
| | - Samuel A. Whittier
- Wisconsin Reading Center, Department of Ophthalmology, University of Wisconsin School of Medicine and Public and Health, Madison
| | - Qing Pan
- Department of Statistics, George Washington University, Washington, DC
| | - Dana M. Dabelea
- Department of Epidemiology, University of Colorado School of Public Health, Denver
| | - Christine H. Darwin
- Department of Medicine, Ronald Reagan UCLA Medical Center, Los Angeles, California
| | - William C. Knowler
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona
| | - Christine G. Lee
- Division of Diabetes, Endocrinology, and Metabolic Diseases, National Institutes of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland
| | - Jose A. Luchsinger
- Department of Medicine, Columbia University Medical Center, New York, New York
| | - Neil H. White
- Division of Endocrinology & Diabetes, Department of Pediatrics, Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Emily Y. Chew
- Division of Epidemiology and Clinical Applications–Clinical Trials Branch, National Eye Institute - National Institutes of Health, Bethesda, Maryland
| | | | | | | | | | | | - Amber Dragg
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Crystal Duncan
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Frank Greenway
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | - Erma Levy
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Monica Lockett
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Donna H. Ryan
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Lisa L. Smith
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | | | | | - Janet Tobian
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Bart Clark
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Kirsten Czech
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Wylie McNabb
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Jose F. Caro
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Kevin Furlong
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Jewel Mendoza
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Marsha Simmons
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Wendi Wildman
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Renee Liberoni
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Constance Pepe
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Ronald Prineas
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Anna Giannella
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Patricia Rowe
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | - Rajesh Garg
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Olga Lara
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Carmen Larreal
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Jadell Mendez
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Arlette Perry
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Patrice Saab
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Bertha Veciana
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Kathy Hattaway
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Juan Isaac
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Carlos Lorenzo
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Monica Salazar
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Tatiana Walker
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | | | | | | | | | - Brian Bucca
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - B. Ned Calonge
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Lynne Delve
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Martha Farago
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - James O. Hill
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Tonya Jenkins
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Dione Lenz
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Marsha Miller
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Thomas Nilan
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - David W. Price
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Helen Seagle
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Medha Munshi
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Kati Swift
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Ronald A. Arky
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | | | | | - Om P. Ganda
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Ashley Guidi
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Mathew Guido
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Lyn M. Kula
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Margaret Kocal
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Lori Lambert
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Sarah Ledbury
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | - Jocelyn Pan
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Ellen W. Seely
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Dana Schweizer
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Fannie Smith
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - James Warram
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Steven E. Kahn
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Basma Fattaleh
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | | | - Michelle Marr
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Anne Murillo
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Kayla O’Neal
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Dace Trence
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Lonnese Taylor
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - April Thomas
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Elaine C. Tsai
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Mary E. Murphy
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Laura Taylor
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Debra Clark
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Uzoma Ibebuogu
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Raed Imseis
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Helen Lambeth
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Hooman Oktaei
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Harriet Ricks
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Amy R. Sherman
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Clara M. Smith
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Avnisha Patel
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | | | | | | | - Michelle Cook
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Mimi M. Giles
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Deloris Heard
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Diane Larsen
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Anne Lowe
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Megan Lyman
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Samsam C. Penn
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Thomas Pitts
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Renee Reinhart
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Susan Roston
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Amisha Wallia
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Mary Larkin
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Kathy Abbott
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Ellen Anderson
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Laurie Bissett
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Kristy Bondi
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Jose C. Florez
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Elaine Grassa
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Lindsery Gurry
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Kali D’Anna
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Peter Lou
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Elyse Raymond
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Valerie Ripley
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Beverly Tseng
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | | | - Karen Vejvoda
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | | | | | | | - Javiva Horne
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Marycie Lamkin
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Diana Leos
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Rosa Ruiz
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Jean Smith
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Jane E. Lee
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Susan Hagamen
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Maria Baldo
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Sandra T. Foo
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Carmen Pal
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Kathy Parkes
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Mary Beth Pena
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Mary de Groot
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Susie M. Kelly
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Gina McAtee
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Paula Putenney
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | - Megan Fultz
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - John C. Guare
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Angela Hadden
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Kisha L Pinner
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Paris J. Roach
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Vanita Aroda
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Michelle Magee
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Sue Shapiro
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Natalie Andon
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | | | | | - Susan Cola
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Cindy Evans
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Peggy Gibbs
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Tracy Kellum
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Lilia Leon
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Milvia Lagarda
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Asha K. Nair
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Jean Park
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Gabriel Uwaifo
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Renee Wiggins
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Karol Watson
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Maria Budget
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Medhat Botrous
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Anthony Sosa
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Sameh Tadros
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Khan Akbar
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Kathy Ngo
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Amer Rassam
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Debra Waters
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Samia Das
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Tamara Stich
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Ana Santiago
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Edwin Fisher
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Emma Hurt
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Tracy Jones
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Michelle Kerr
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Lucy Ryder
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | - Emily Sullivan
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Caroline Abbas
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Adrienne Allen
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | - Janice Freel
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Alicia Greene
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Dawn Jiggetts
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Hope Joseph
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Kimberly Loman
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Henry Mosley
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - John Reusing
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Alafia Samuels
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Thomas Shields
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - LeeLana Thomas
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Evonne Utsey
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | | | | | - Penny Hyde
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Mark R. Burge
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Lisa Chai
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Ateka Fondino
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Ysela Gonzales
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Patricia Katz
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Carolyn King
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Jill Crandall
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Harry Shamoon
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Janet O. Brown
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Elsie Adorno
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Liane Cox
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Helena Duffy
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Samuel Engel
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Jennifer Lukin
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Stacey Kloiber
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Helen Martinez
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Dorothy Pompi
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Elissa Violino
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Joel Zonszein
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Trevor Orchard
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Rena R. Wing
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Susan Jeffries
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Gaye Koenning
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - M. Kaye Kramer
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Marie Smith
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Susan Barr
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Miriam Boraz
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Lisa Clifford
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Rebecca Culyba
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Ryan Gilligan
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Susan Harrier
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Louann Harris
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Andrea Kriska
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Monica Mullen
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Alicia Noel
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Amy Otto
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Linda Semler
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Tara Wilson
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - John S. Melish
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Mae K. Isonaga
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Ralph Beddow
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Lorna Dias
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Jillian Inouye
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Kathy Mikami
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Sharon K. Odom
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | | | - Mary A. Hoskin
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Carol A. Percy
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Alvera Enote
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Camille Natewa
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Kelly J. Acton
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Rosalyn Barber
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Shandiin Begay
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Evelyn C. Bird
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Brian C. Bucca
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Sherron Cook
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Jeff Curtis
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Tara Dacawyma
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Roberta Duncan
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Cyndy Edgerton
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Justin Glass
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Martia Glass
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Dorothy Gohdes
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Wendy Grant
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Ellie Horse
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Merry Jackson
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Priscilla Jay
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Karen Kavena
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - David Kessler
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Jason Kurland
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Cherie McCabe
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Sara Michaels
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Tina Morgan
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Steven Poirier
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Mike Reidy
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Debra Rowse
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Robert J. Roy
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Miranda Smart
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Darryl Tonemah
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Raymond Bain
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Sarah Fowler
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Tina Brenneman
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Solome Abebe
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Julie Bamdad
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Joel Bethepu
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Anna Bowers
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Nicole Butler
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | - Mary Foulkes
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Yuping Gao
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Robert Gooding
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | - Lori Haffner
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Steve Jones
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Tara L. Jones
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Richard Katz
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - John M. Lachin
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Yong Ma
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Pamela Mucik
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Robert Orlosky
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Susan Reamer
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - James Rochon
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Hanna Sherif
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | | | | | | | | | | | - John Albers
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - R. Eastman
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Judith Fradkin
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Christine Lee
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Edward Gregg
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Ping Zhang
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Dan O’Leary
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Gregory Evans
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Matthew Budoff
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Chris Dailing
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Ann Schwartz
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Caroline Navy
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Lisa Palermo
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | - Sharon Hall
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Yabing Li
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Margaret Mills
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Zhuming Zhang
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Julie Hu
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Susan Hensley
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Lisa Keasler
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Tonya Taylor
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Barbara Blodi
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Ronald Danis
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Matthew Davis
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Larry Hubbard*
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Ryan Endres**
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Dawn Myers**
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Nancy Barrett
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Wendy Benz
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Holly Cohn
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Ellie Corkery
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Kristi Dohm
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Vonnie Gama
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Anne Goulding
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Andy Ewen
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Kyle McDaniel
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Jeong Pak
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - James Reimers
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Ruth Shaw
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Maria Swift
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Pamela Vargo
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Sheila Watson
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Jennifer Manly
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | - Ted Ganiats
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Kristin David
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Erik Groessl
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Naomi Katzir
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Helen Chong
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | | | | | | | | | - Ling Chen
- for the Diabetes Prevention Program Research (DPPOS) Group
| | - Maegan Harden
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Toni I. Pollin
- for the Diabetes Prevention Program Research (DPPOS) Group
| | | | - Paul W. Franks
- for the Diabetes Prevention Program Research (DPPOS) Group
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2
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Doupis J, Horton ES. Utilizing the New Glucometrics: A Practical Guide to Ambulatory Glucose Profile Interpretation. Endocrinology 2022; 18:20-26. [PMID: 35949362 PMCID: PMC9354515 DOI: 10.17925/ee.2022.18.1.20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 05/03/2022] [Indexed: 11/24/2022]
Abstract
Traditional continuous glucose monitoring and flash glucose monitoring systems are proven to lower glycated haemoglobin levels, decrease the time and impact of hypoglycaemia or hyperglycaemia and, consequently, improve the quality of life for children and adults with type 1 diabetes mellitus (T1DM) and adults with type 2 diabetes mellitus (T2DM). These glucose-sensing devices can generate large amounts of glucose data that can be used to define a detailed glycaemic profile for each user, which can be compared with targets for glucose control set by an International Consensus Panel of diabetes experts. Targets have been agreed upon for adults, children and adolescents with T1DM and adults with T2DM; separate targets have been agreed upon for older adults with diabetes, who are at higher risk of hypoglycaemia, and women with pregestational T1DM during pregnancy. Along with the objective measures and targets identified by the International Consensus Panel, the dense glucose data delivered by traditional continuous glucose monitoring and flash glucose monitoring systems is used to generate an ambulatory glucose profile, which summarizes the data in a visually impactful format that can be used to identify patterns and trends in daily glucose control, including those that raise clinical concerns. In this article, we provide a practical guide on how to interpret these new glucometrics using a straightforward algorithm, and clear visual examples that demystify the process of reviewing the glycaemic health of people with T1DM or T2DM such that forward-looking goals for diabetes management can be agreed.
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Affiliation(s)
- John Doupis
- Department of Internal Medicine and Diabetes, Salamis Naval and Veterans Hospital, Salamis, Attiki, Greece
- Iatriko Paleou Falirou Medical Center, Diabetes Clinic, Athens, Greece
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3
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Lin PID, Cardenas A, Hauser R, Gold DR, Kleinman KP, Hivert MF, Calafat AM, Webster TF, Horton ES, Oken E. Temporal trends of concentrations of per- and polyfluoroalkyl substances among adults with overweight and obesity in the United States: Results from the Diabetes Prevention Program and NHANES. Environ Int 2021; 157:106789. [PMID: 34333293 PMCID: PMC8490287 DOI: 10.1016/j.envint.2021.106789] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 07/13/2021] [Accepted: 07/19/2021] [Indexed: 05/19/2023]
Abstract
BACKGROUND Understanding the temporal trends and change of concentrations of per- and polyfluoroalkyl substances (PFAS) is important to evaluate the health impact of PFAS at both the individual- and population-level, however, limited information is available for pre-diabetic adults in the U.S. OBJECTIVES Determine trends and rate of change of plasma PFAS concentrations in overweight or obese U.S. adults and evaluate variation by sex, race/ethnicity, and age. METHODS We described temporal trends of plasma PFAS concentrations using samples collected in 1996-1998, 1999-2001, and 2011-2012 from 957 pre-diabetic adults enrolled in the Diabetes Prevention Program (DPP) trial and Outcomes Study (DPPOS) and compared to serum concentrations from the National Health and Nutrition Examination Survey (NHANES 1999-2000, 2003-2016, adults with BMI ≥ 24 kg/m2). We examined associations between participants' characteristics and PFAS concentrations and estimated the rate of change using repeated measures in DPP/DPPOS assuming a first-order elimination model. RESULTS Longitudinal measures of PFAS concentrations in DPP/DPPOS individuals were comparable to NHANES cross-sectional populational means. Plasma concentrations of perfluorooctanesulfonic acid (PFOS), perfluorooctanoic acid, perfluorohexanesulfonic acid (PFHxS), N-ethyl-perfluorooctane sulfonamido acetic acid (EtFOSAA), and N-methylperfluorooctane sulfonamido acetic acid (MeFOSAA) started to decline after the year 2000 and concentrations of perfluorononanoic acid (PFNA) increased after 2000 and, for NHANES, decreased after 2012. We consistently observed higher PFOS, PFHxS and PFNA among male, compared to female, and higher PFOS and PFNA among Black, compared to white, participants. The estimated time for concentrations to decrease by half ranged from 3.39 years for EtFOSAA to 17.56 years for PFHxS. DISCUSSION We observed a downward temporal trend in plasma PFOS concentrations that was consistent with the timing for U.S. manufacturers' phaseout. Male and Black participants consistently showed higher PFOS and PFNA than female and white participants, likely due to differences in exposure patterns, metabolism or elimination kinetics.
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Affiliation(s)
- Pi-I D Lin
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health and Center for Computational Biology, University of California, Berkeley, Berkeley, CA, USA.
| | - Russ Hauser
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Diane R Gold
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
| | - Ken P Kleinman
- Department of Biostatistics, School of Public Health and Human Sciences, University of Massachusetts Amherst, Amherst, MA, USA
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA; Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA.
| | - Antonia M Calafat
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, USA.
| | - Thomas F Webster
- Department of Environmental Health, Boston University School of Public Health, Boston, MA, USA.
| | - Edward S Horton
- Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA.
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
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4
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Osorio-Yáñez C, Sanchez-Guerra M, Cardenas A, Lin PID, Hauser R, Gold DR, Kleinman KP, Hivert MF, Fleisch AF, Calafat AM, Webster TF, Horton ES, Oken E. Per- and polyfluoroalkyl substances and calcifications of the coronary and aortic arteries in adults with prediabetes: Results from the diabetes prevention program outcomes study. Environ Int 2021; 151:106446. [PMID: 33631604 PMCID: PMC8721596 DOI: 10.1016/j.envint.2021.106446] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 01/31/2021] [Accepted: 02/03/2021] [Indexed: 05/28/2023]
Abstract
BACKGROUND Per- and polyfluoroalkyl substances (PFAS) are endocrine disrupting chemicals that have been associated with cardiovascular risk factors including elevated body weight and hypercholesterolemia. Therefore, PFAS may contribute to the development of atherosclerosis and cardiovascular disease (CVD). However, no previous study has evaluated associations between PFAS exposure and arterial calcification. METHODS AND RESULTS This study used data from 666 prediabetic adults enrolled in the Diabetes Prevention Program trial who had six PFAS quantified in plasma at baseline and two years after randomization, as well as measurements of coronary artery calcium (CAC) and ascending (AsAC) and descending (DAC) thoracic aortic calcification 13-14 years after baseline. We performed multinomial regression to test associations between PFAS and CAC categorized according to Agatston score [low (<10), moderate (11-400) and severe (>400)]. We used logistic regression to assess associations between PFAS and presence of AsAC and DAC. We adjusted models for baseline sex, age, BMI, race/ethnicity, cigarette smoking, education, treatment assignment (placebo or lifestyle intervention), and statin use. PFAS concentrations were similar to national means; 53.9% of participants had CAC > 11, 7.7% had AsAC, and 42.6% had DAC. Each doubling of the mean sum of plasma concentrations of linear and branched isomers of perfluorooctane sulfonic acid (PFOS) was associated with 1.49-fold greater odds (95% CI: 1.01, 2.21) of severe versus low CAC. This association was driven mainly by the linear (n-PFOS) isomer [1.54 (95% CI: 1.05, 2.25) greater odds of severe versus low CAC]. Each doubling of mean plasma N-ethyl-perfluorooctane sulfonamido acetic acid concentration was associated with greater odds of CAC in a dose-dependent manner [OR = 1.26 (95% CI:1.08, 1.47) for moderate CAC and OR = 1.37 (95% CI:1.07, 1.74) for severe CAC, compared to low CAC)]. Mean plasma PFOS and n-PFOS were also associated with greater odds of AsAC [OR = 1.67 (95% CI:1.10, 2.54) and OR = 1.70 (95% CI:1.13, 2.56), respectively], but not DAC. Other PFAS were not associated with outcomes. CONCLUSIONS Prediabetic adults with higher plasma concentrations of select PFAS had higher risk of coronary and thoracic aorta calcification. PFAS exposure may be a risk factor for adverse cardiovascular health among high-risk populations.
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Affiliation(s)
- Citlalli Osorio-Yáñez
- Instituto de Investigaciones Biomédicas, Universidad Nacional Autonoma de Mexico, Ciudad de Mexico, Mexico.
| | - Marco Sanchez-Guerra
- Department of Developmental Neurobiology, National Institute of Perinatology, Mexico City, Mexico.
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, CA, USA
| | - Pi-I D Lin
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Russ Hauser
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Diane R Gold
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Ken P Kleinman
- Department of Biostatistics, School of Public Health and Human Sciences, University of Massachusetts Amherst, Amherst, MA, USA
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Abby F Fleisch
- Pediatric Endocrinology and Diabetes, Maine Medical Center, Portland, ME, USA; Center for Outcomes Research and Evaluation, Maine Medical Center Research Institute, Portland, ME, USA
| | - Antonia M Calafat
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Thomas F Webster
- Department of Environmental Health, Boston University School of Public Health, Boston, MA, USA
| | - Edward S Horton
- Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
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5
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Lin PID, Cardenas A, Hauser R, Gold DR, Kleinman KP, Hivert MF, Calafat AM, Webster TF, Horton ES, Oken E. Per- and polyfluoroalkyl substances and kidney function: Follow-up results from the Diabetes Prevention Program trial. Environ Int 2021; 148:106375. [PMID: 33482440 PMCID: PMC7929640 DOI: 10.1016/j.envint.2020.106375] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 12/28/2020] [Accepted: 12/29/2020] [Indexed: 05/04/2023]
Abstract
Per- and polyfluoroalkyl substances (PFAS) are ubiquitously detected in populations worldwide and may hinder kidney function. The objective of the study was to determine longitudinal associations of plasma PFAS concentrations with estimated glomerular filtration rate (eGFR) and evaluate whether a lifestyle intervention modify the associations. We studied 875 participants initially randomized to the lifestyle or placebo arms in the Diabetes Prevention Program (DPP, 1996-2002) trial and Outcomes Study (DPPOS, 2002-2014). We ran generalized linear mixed models accounting a priori covariates to evaluate the associations between baseline PFAS concentrations and repeated measures of eGFR, separately, for six PFAS (PFOS, PFOA, PFHxS, EtFOSAA, MeFOSAA, PFNA); then used quantile-based g-computation to evaluate the effects of the six PFAS chemicals as a mixture. The cohort was 64.9% female; 73.4% 40-64 years-old; 29.4% with hypertension; 50.5% randomized to lifestyle intervention and 49.5% to placebo and had similar plasma PFAS concentrations as the general U.S. population in 1999-2000. Most participants had normal kidney function (eGFR > 90 mL/min/1.73 m2) over the approximately 14 years of follow-up. We found that plasma PFAS concentrations during DPP were inversely associated with eGFR during DPPOS follow-up. Each quartile increase in baseline plasma concentration of the 6 PFAS as a mixture was associated with 2.26 mL/min/1.73 m2 lower eGFR (95% CI: -4.12, -0.39) at DPPOS Year 5, approximately 9 years since DPP randomization and PFAS measurements. The lifestyle intervention did not modify associations, but inverse associations were stronger among participants with hypertension at baseline. Among prediabetic adults, we found inverse associations between baseline plasma PFAS concentrations and measures of eGFR throughout 14 years of follow-up. The lifestyle intervention of diet, exercise and behavioral changes did not modify the associations, but persons with hypertension may have heightened susceptibility.
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Affiliation(s)
- Pi-I D Lin
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, CA, USA.
| | - Russ Hauser
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Diane R Gold
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
| | - Ken P Kleinman
- Department of Biostatistics, School of Public Health and Human Sciences, University of Massachusetts Amherst, Amherst, MA, USA
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA; Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA.
| | - Antonia M Calafat
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, USA.
| | - Thomas F Webster
- Department of Environmental Health, Boston University School of Public Health, Boston, MA, USA.
| | - Edward S Horton
- Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA.
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
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Kriska AM, Rockette-Wagner B, Edelstein SL, Bray GA, Delahanty LM, Hoskin MA, Horton ES, Venditti EM, Knowler WC. The Impact of Physical Activity on the Prevention of Type 2 Diabetes: Evidence and Lessons Learned From the Diabetes Prevention Program, a Long-Standing Clinical Trial Incorporating Subjective and Objective Activity Measures. Diabetes Care 2021; 44:43-49. [PMID: 33444158 PMCID: PMC7783946 DOI: 10.2337/dc20-1129] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 10/13/2020] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Across the Diabetes Prevention Program (DPP) follow-up, cumulative diabetes incidence remained lower in the lifestyle compared with the placebo and metformin randomized groups and could not be explained by weight. Collection of self-reported physical activity (PA) (yearly) with cross-sectional objective PA (in follow-up) allowed for examination of PA and its long-term impact on diabetes prevention. RESEARCH DESIGN AND METHODS Yearly self-reported PA and diabetes assessment and oral glucose tolerance test results (fasting glucose semiannually) were collected for 3,232 participants with one accelerometry assessment 11-13 years after randomization (n = 1,793). Mixed models determined PA differences across treatment groups. The association between PA and diabetes incidence was examined using Cox proportional hazards models. RESULTS There was a 6% decrease (Cox proportional hazard ratio 0.94 [95% CI 0.92, 0.96]; P < 0.001) in diabetes incidence per 6 MET-h/week increase in time-dependent PA for the entire cohort over an average of 12 years (controlled for age, sex, baseline PA, and weight). The effect of PA was greater (12% decrease) among participants less active at baseline (<7.5 MET-h/week) (n = 1,338) (0.88 [0.83, 0.93]; P < 0.0001), with stronger findings for lifestyle participants. Lifestyle had higher cumulative PA compared with metformin or placebo (P < 0.0001) and higher accelerometry total minutes per day measured during follow-up (P = 0.001 and 0.047). All associations remained significant with the addition of weight in the models. CONCLUSIONS PA was inversely related to incident diabetes in the entire cohort across the study, with cross-sectional accelerometry results supporting these findings. This highlights the importance of PA within lifestyle intervention efforts designed to prevent diabetes and urges health care providers to consider both PA and weight when counseling high-risk patients.
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Affiliation(s)
| | | | | | - George A Bray
- Pennington Biomedical Research Center, Baton Rouge, LA
| | | | - Mary A Hoskin
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ
| | | | | | - William C Knowler
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ
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7
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Zhang P, Atkinson KM, Bray GA, Chen H, Clark JM, Coday M, Dutton GR, Egan C, Espeland MA, Evans M, Foreyt JP, Greenway FL, Gregg EW, Hazuda HP, Hill JO, Horton ES, Hubbard VS, Huckfeldt PJ, Jackson SD, Jakicic JM, Jeffery RW, Johnson KC, Kahn SE, Killean T, Knowler WC, Korytkowski M, Lewis CE, Maruthur NM, Michaels S, Montez MG, Nathan DM, Patricio J, Peters A, Pi-Sunyer X, Pownall H, Redmon B, Rushing JT, Steinburg H, Wadden TA, Wing RR, Wyatt H, Yanovski SZ. Within-Trial Cost-Effectiveness of a Structured Lifestyle Intervention in Adults With Overweight/Obesity and Type 2 Diabetes: Results From the Action for Health in Diabetes (Look AHEAD) Study. Diabetes Care 2021; 44:67-74. [PMID: 33168654 PMCID: PMC7783933 DOI: 10.2337/dc20-0358] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 10/07/2020] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To assess the cost-effectiveness (CE) of an intensive lifestyle intervention (ILI) compared with standard diabetes support and education (DSE) in adults with overweight/obesity and type 2 diabetes, as implemented in the Action for Health in Diabetes study. RESEARCH DESIGN AND METHODS Data were from 4,827 participants during their first 9 years of study participation from 2001 to 2012. Information on Health Utilities Index Mark 2 (HUI-2) and HUI-3, Short-Form 6D (SF-6D), and Feeling Thermometer (FT), cost of delivering the interventions, and health expenditures was collected during the study. CE was measured by incremental CE ratios (ICERs) in costs per quality-adjusted life year (QALY). Future costs and QALYs were discounted at 3% annually. Costs were in 2012 U.S. dollars. RESULTS Over the 9 years studied, the mean cumulative intervention costs and mean cumulative health care expenditures were $11,275 and $64,453 per person for ILI and $887 and $68,174 for DSE. Thus, ILI cost $6,666 more per person than DSE. Additional QALYs gained by ILI were not statistically significant measured by the HUIs and were 0.07 and 0.15, respectively, measured by SF-6D and FT. The ICERs ranged from no health benefit with a higher cost based on HUIs to $96,458/QALY and $43,169/QALY, respectively, based on SF-6D and FT. CONCLUSIONS Whether ILI was cost-effective over the 9-year period is unclear because different health utility measures led to different conclusions.
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Affiliation(s)
- Ping Zhang
- Centers for Disease Control and Prevention, Atlanta, GA
| | - Karen M Atkinson
- VA Puget Sound Health Care System and University of Washington, Seattle, WA
| | - George A Bray
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA
| | - Haiying Chen
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Jeanne M Clark
- Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - Mace Coday
- Department of Preventive Medicine, The University of Tennessee Health Science Center, Memphis, TN
| | - Gareth R Dutton
- Division of Preventive Medicine, School of Medicine, The University of Alabama at Birmingham, Birmingham, AL
| | - Caitlin Egan
- Weight Control and Diabetes Research Center, The Miriam Hospital, Providence RI
| | - Mark A Espeland
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Mary Evans
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD
| | - John P Foreyt
- Department of Medicine, Baylor College of Medicine, Houston, TX
| | - Frank L Greenway
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA
| | - Edward W Gregg
- Department of Epidemiology and Biostatistics, Imperial College London, London, U.K
| | - Helen P Hazuda
- Department of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX
| | - James O Hill
- Department of Nutrition Sciences, The University of Alabama at Birmingham, Birmingham, AL
| | | | - Van S Hubbard
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD
| | - Peter J Huckfeldt
- Division of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis, MN
| | | | - John M Jakicic
- Department of Health and Physical Activity, University of Pittsburgh, Pittsburgh, PA
| | - Robert W Jeffery
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, University of Minnesota Medical School, Minneapolis, MN
| | - Karen C Johnson
- Department of Preventive Medicine, The University of Tennessee Health Science Center, Memphis, TN
| | - Steven E Kahn
- VA Puget Sound Health Care System and University of Washington, Seattle, WA
| | - Tina Killean
- National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ
| | - William C Knowler
- National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ
| | - Mary Korytkowski
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA
| | - Cora E Lewis
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | - Nisa M Maruthur
- Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD
| | | | - Maria G Montez
- Department of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX
| | - David M Nathan
- Diabetes Research Center, Massachusetts General Hospital, Boston, MA
| | - Jennifer Patricio
- Department of Medicine, St. Luke's-Roosevelt Hospital Center, Columbia University, New York, NY
| | - Anne Peters
- Houston Methodist Research Institute, Baylor College of Medicine, Houston, TX
| | - Xavier Pi-Sunyer
- Department of Medicine, St. Luke's-Roosevelt Hospital Center, Columbia University, New York, NY
| | - Henry Pownall
- Division of Endocrinology and Diabetes, Keck School of Medicine of the University of Southern California, Los Angeles, CA
| | - Bruce Redmon
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, University of Minnesota Medical School, Minneapolis, MN
| | - Julia T Rushing
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Helmut Steinburg
- Department of Preventive Medicine, The University of Tennessee Health Science Center, Memphis, TN
| | - Thomas A Wadden
- Center for Weight and Eating Disorders, University of Pennsylvania, Philadelphia, PA
| | - Rena R Wing
- Weight Control and Diabetes Research Center, The Miriam Hospital, Providence RI
| | - Holly Wyatt
- Department of Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
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Williams KJ, Horton ES, Siraj ES. Guenther Boden, MD (1935-2015): A Pioneer in Human Studies of Nutrition and Obesity-And the Mystery of Insulin Resistance for Handling Glucose. Diabetes Care 2020; 43:2910-2915. [PMID: 33218979 PMCID: PMC7770270 DOI: 10.2337/dci20-0041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
- Kevin Jon Williams
- Department of Physiology and Department of Medicine, Lewis Katz School of Medicine, Temple University, Philadelphia, PA .,Department of Molecular and Clinical Medicine, Sahlgrenska Academy, University of Gothenburg, Göteborg, Sweden
| | - Edward S Horton
- Harvard Medical School and Joslin Diabetes Center, Boston, MA
| | - Elias S Siraj
- Division of Endocrine and Metabolic Disorders and Strelitz Diabetes Center, Eastern Virginia Medical School, Norfolk, VA
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9
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Yeh HC, Bantle JP, Cassidy-Begay M, Blackburn G, Bray GA, Byers T, Clark JM, Coday M, Egan C, Espeland MA, Foreyt JP, Garcia K, Goldman V, Gregg EW, Hazuda HP, Hesson L, Hill JO, Horton ES, Jakicic JM, Jeffery RW, Johnson KC, Kahn SE, Knowler WC, Korytkowski M, Kure A, Lewis CE, Mantzoros C, Meacham M, Montez MG, Nathan DM, Pajewski N, Patricio J, Peters A, Xavier Pi-Sunyer F, Pownall H, Ryan DH, Safford M, Sedjo RL, Steinburg H, Vitolins M, Wadden TA, Wagenknecht LE, Wing RR, Wolff AC, Wyatt H, Yanovski SZ. Intensive Weight Loss Intervention and Cancer Risk in Adults with Type 2 Diabetes: Analysis of the Look AHEAD Randomized Clinical Trial. Obesity (Silver Spring) 2020; 28:1678-1686. [PMID: 32841523 PMCID: PMC8855671 DOI: 10.1002/oby.22936] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Revised: 05/18/2020] [Accepted: 05/19/2020] [Indexed: 12/30/2022]
Abstract
OBJECTIVE This study was designed to determine whether intensive lifestyle intervention (ILI) aimed at weight loss lowers cancer incidence and mortality. METHODS Data from the Look AHEAD trial were examined to investigate whether participants randomized to ILI designed for weight loss would have reduced overall cancer incidence, obesity-related cancer incidence, and cancer mortality, as compared with the diabetes support and education (DSE) comparison group. This analysis included 4,859 participants without a cancer diagnosis at baseline except for nonmelanoma skin cancer. RESULTS After a median follow-up of 11 years, 684 participants (332 in ILI and 352 in DSE) were diagnosed with cancer. The incidence rates of obesity-related cancers were 6.1 and 7.3 per 1,000 person-years in ILI and DSE, respectively, with a hazard ratio (HR) of 0.84 (95% CI: 0.68-1.04). There was no significant difference between the two groups in total cancer incidence (HR, 0.93; 95% CI: 0.80-1.08), incidence of nonobesity-related cancers (HR, 1.02; 95% CI: 0.83-1.27), or total cancer mortality (HR, 0.92; 95% CI: 0.68-1.25). CONCLUSIONS An ILI aimed at weight loss lowered incidence of obesity-related cancers by 16% in adults with overweight or obesity and type 2 diabetes. The study sample size likely lacked power to determine effect sizes of this magnitude and smaller.
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Affiliation(s)
- Hsin-Chieh Yeh
- Departments of Medicine, Epidemiology, and Oncology, Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland, USA
| | - John P Bantle
- Department of Medicine, University of Minnesota Medical School, Minneapolis, Minnesota, USA
| | - Maria Cassidy-Begay
- National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix Epidemiology and Clinical Research Branch, Phoenix, Arizona, USA
| | - George Blackburn
- Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - George A Bray
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, Louisiana, USA
| | - Tim Byers
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Jeanne M Clark
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Mace Coday
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Caitlin Egan
- Psychiatry and Human Behavior, The Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Mark A Espeland
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - John P Foreyt
- Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Katelyn Garcia
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Valerie Goldman
- Diabetes Clinical Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Edward W Gregg
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Helen P Hazuda
- Department of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Louise Hesson
- Center for Weight and Eating Disorders, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - James O Hill
- Department of Nutrition Sciences, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Edward S Horton
- Department of Medicine, Joslin Diabetes Center, Boston, Massachusetts, USA
| | - John M Jakicic
- Department of Health and Physical Activity, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Robert W Jeffery
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - Karen C Johnson
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Steven E Kahn
- Department of Medicine, VA Puget Sound Health Care System / University of Washington, Seattle, Washington, USA
| | - William C Knowler
- National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix Epidemiology and Clinical Research Branch, Phoenix, Arizona, USA
| | - Mary Korytkowski
- Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Anne Kure
- Department of Medicine, VA Puget Sound Health Care System / University of Washington, Seattle, Washington, USA
| | - Cora E Lewis
- Division of Preventive Medicine, School of Medicine, The University of Alabama at Birmingham, Birmingham, Alabama, USA
| | | | - Maria Meacham
- National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix Epidemiology and Clinical Research Branch, Phoenix, Arizona, USA
| | - Maria G Montez
- Department of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - David M Nathan
- Diabetes Clinical Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Nicholas Pajewski
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | | | - Anne Peters
- Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | | | - Henry Pownall
- Division of Cardiology, Baylor College of Medicine, Houston, Texas, USA
| | - Donna H Ryan
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, Louisiana, USA
| | - Monika Safford
- Department of Medicine, Weill Cornell Medical College of Cornell University, New York, New York, USA
| | - Rebecca L Sedjo
- Department of Community and Behavioral Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Helmut Steinburg
- Department of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Mara Vitolins
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Thomas A Wadden
- Center for Weight and Eating Disorders, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Rena R Wing
- Psychiatry and Human Behavior, The Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Antonio C Wolff
- Department of Oncology, The Johns Hopkins Sydney Kimmel Cancer Center, Baltimore, Maryland, USA
| | - Holly Wyatt
- Department of Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Susan Z Yanovski
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, USA
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10
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Chao AM, Wadden TA, Berkowitz RI, Blackburn G, Bolin P, Clark JM, Coday M, Curtis JM, Delahanty LM, Dutton GR, Evans M, Ewing LJ, Foreyt JP, Gay LJ, Gregg EW, Hazuda HP, Hill JO, Horton ES, Houston DK, Jakicic JM, Jeffery RW, Johnson KC, Kahn SE, Knowler WC, Kure A, Michalski KL, Montez MG, Neiberg RH, Patricio J, Peters A, Pi-Sunyer X, Pownall H, Reboussin D, Redmon B, Rejeski WJ, Steinburg H, Walker M, Williamson DA, Wing RR, Wyatt H, Yanovski SZ, Zhang P. Weight Change 2 Years After Termination of the Intensive Lifestyle Intervention in the Look AHEAD Study. Obesity (Silver Spring) 2020; 28:893-901. [PMID: 32320144 PMCID: PMC7437140 DOI: 10.1002/oby.22769] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Accepted: 02/03/2020] [Indexed: 01/07/2023]
Abstract
OBJECTIVE This study evaluated weight changes after cessation of the 10-year intensive lifestyle intervention (ILI) in the Look AHEAD (Action for Health in Diabetes) study. It was hypothesized that ILI participants would be more likely to gain weight during the 2-year observational period following termination of weight-loss-maintenance counseling than would participants in the diabetes support and education (DSE) control group. METHODS Look AHEAD was a randomized controlled trial that compared the effects of ILI and DSE on cardiovascular morbidity and mortality in participants with overweight/obesity and type 2 diabetes. Look AHEAD was converted to an observational study in September 2012. RESULTS Two years after the end of the intervention (EOI), ILI and DSE participants lost a mean (SE) of 1.2 (0.2) kg and 1.8 (0.2) kg, respectively (P = 0.003). In addition, 31% of ILI and 23.9% of DSE participants gained ≥ 2% (P < 0.001) of EOI weight, whereas 36.3% and 45.9% of the respective groups lost ≥ 2% of EOI weight (P = 0.001). Two years after the EOI, ILI participants reported greater use of weight-control behaviors than DSE participants. CONCLUSIONS Both groups lost weight during the 2-year follow-up period, but more ILI than DSE participants gained ≥ 2% of EOI weight. Further understanding is needed of factors that affected long-term weight change in both groups.
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Affiliation(s)
| | - Ariana M Chao
- Department of Biobehavioral Health Sciences, School of Nursing, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Thomas A Wadden
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Robert I Berkowitz
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - George Blackburn
- Division of Nutrition, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Paula Bolin
- Southwestern American Indian Center, National Institute of Diabetes and Digestive and Kidney Diseases and St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Jeanne M Clark
- Division of General Internal Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Mace Coday
- Departments of Preventive Medicine and Psychiatry, The University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Jeffrey M Curtis
- Southwestern American Indian Center, National Institute of Diabetes and Digestive and Kidney Diseases and St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Linda M Delahanty
- Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Gareth R Dutton
- Division of Preventive Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Mary Evans
- Division of Digestive Diseases and Nutrition, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland, USA
| | - Linda J Ewing
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - John P Foreyt
- Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Linda J Gay
- Department of Psychiatry, The Miriam Hospital, Brown Medical School, Providence, Rhode Island, USA
| | - Edward W Gregg
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Helen P Hazuda
- Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - James O Hill
- Anschutz Health and Wellness Center, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Edward S Horton
- Department of Integrative Physiology and Metabolism, Joslin Diabetes Center, Boston, Massachusetts, USA
| | - Denise K Houston
- Department of Internal Medicine - Geriatrics, Wake Forest University, Winston-Salem, North Carolina, USA
| | - John M Jakicic
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Robert W Jeffery
- Divisions of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - Karen C Johnson
- Departments of Preventive Medicine and Psychiatry, The University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Steven E Kahn
- Division of Metabolism, Endocrinology and Nutrition, US Department of Veterans Affairs Puget Sound Health Care System, University of Washington, Seattle, Washington, USA
| | - William C Knowler
- Southwestern American Indian Center, National Institute of Diabetes and Digestive and Kidney Diseases and St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Anne Kure
- Division of Metabolism, Endocrinology and Nutrition, US Department of Veterans Affairs Puget Sound Health Care System, University of Washington, Seattle, Washington, USA
| | - Katherine L Michalski
- Division of General Internal Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Maria G Montez
- Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Rebecca H Neiberg
- Department of Internal Medicine - Geriatrics, Wake Forest University, Winston-Salem, North Carolina, USA
| | - Jennifer Patricio
- Department of Medicine, St. Luke's Roosevelt Hospital Center, Columbia University, New York, New York, USA
| | - Anne Peters
- Division of Endocrinology, University of Southern California, Los Angeles, California, USA
| | - Xavier Pi-Sunyer
- Department of Medicine, St. Luke's Roosevelt Hospital Center, Columbia University, New York, New York, USA
| | - Henry Pownall
- Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - David Reboussin
- Department of Internal Medicine - Geriatrics, Wake Forest University, Winston-Salem, North Carolina, USA
| | - Bruce Redmon
- Divisions of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - W Jack Rejeski
- Department of Internal Medicine - Geriatrics, Wake Forest University, Winston-Salem, North Carolina, USA
| | - Helmut Steinburg
- Departments of Preventive Medicine and Psychiatry, The University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Martha Walker
- Division of Endocrinology, University of Southern California, Los Angeles, California, USA
| | | | - Rena R Wing
- Department of Psychiatry, The Miriam Hospital, Brown Medical School, Providence, Rhode Island, USA
| | - Holly Wyatt
- Anschutz Health and Wellness Center, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Susan Z Yanovski
- Division of Digestive Diseases and Nutrition, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland, USA
| | - Ping Zhang
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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11
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Lin PID, Cardenas A, Hauser R, Gold DR, Kleinman KP, Hivert MF, Calafat AM, Webster TF, Horton ES, Oken E. Per- and polyfluoroalkyl substances and blood pressure in pre-diabetic adults-cross-sectional and longitudinal analyses of the diabetes prevention program outcomes study. Environ Int 2020; 137:105573. [PMID: 32088543 PMCID: PMC7094005 DOI: 10.1016/j.envint.2020.105573] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 01/24/2020] [Accepted: 02/10/2020] [Indexed: 05/20/2023]
Abstract
The relationship of plasma concentration of per- and polyfluoroalkyl substances (PFAS) with blood pressure (BP) is uncertain. This study examined cross-sectional and prospective associations of PFAS with BP and hypertension. We quantified plasma PFAS concentrations from 957 participants enrolled in the lifestyle and placebo arms of the Diabetes Prevention Program (DPP), a randomized controlled trial with approximately 15 years of follow-up. We used multivariable linear and logistic regressions to test cross-sectional associations of six PFAS, including perfluorooctanesulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorohexane sulfonic acid (PFHxS), N-ethyl-perfluorooctane sulfonamido acetic acid (EtFOSAA), N-methyl-perfluorooctane sulfonamido acetic acid (MeFOSAA), and perfluorononanoic acid (PFNA), with BP and hypertension prevalence, respectively, at baseline. We used generalized linear mixed models to estimate longitudinal associations between baseline PFAS and the rate of BP changes, and Cox-Proportional hazard models to estimate risk of developing hypertension relative to baseline PFAS. Models were adjusted for baseline age, sex, race/ethnicity, treatment arm, educational attainment, income, marital status, smoking habit, alcohol drinking, and diet. We tested for effect modification by the treatment arm and sex, and accounted for multiple comparisons using the False-Discovery Rate (FDR). PFAS concentrations and hypertension prevalence within the study population (65.3% female, 57.7% White, 65.3% aged 40-59 years) were comparable to the general U.S. population. Cross-sectionally, we found small but statistically significant associations of baseline plasma concentrations of PFOA with systolic BP (β per doubling: 1.49 mmHg, 95% CI: 0.29, 2.70); and MeFOSAA with hypertension (RR = 1.09 per doubling, 95% CI: 1.01, 1.19). Estimates were not statistically significant after FDR adjustment. Longitudinally, we observed null associations in the placebo arm, but some inverse associations of baseline PFOS and MeFOSAA with systolic BP in the lifestyle arm, perhaps due to regression toward the mean. Baseline PFAS concentrations also were not prospectively associated with hypertension risk. Overall, there were modest and mostly null associations of plasma PFAS concentrations with BP and hypertension.
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Affiliation(s)
- Pi-I D Lin
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, CA, USA.
| | - Russ Hauser
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Diane R Gold
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
| | - Ken P Kleinman
- Department of Biostatistics, School of Public Health and Human Sciences, University of Massachusetts Amherst, Amherst, MA, USA
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA; Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA.
| | - Antonia M Calafat
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, USA.
| | - Thomas F Webster
- Department of Environmental Health, Boston University School of Public Health, Boston, MA, USA.
| | - Edward S Horton
- Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA.
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
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Lin PID, Cardenas A, Hauser R, Gold DR, Kleinman KP, Hivert MF, Fleisch AF, Calafat AM, Sanchez-Guerra M, Osorio-Yáñez C, Webster TF, Horton ES, Oken E. Dietary characteristics associated with plasma concentrations of per- and polyfluoroalkyl substances among adults with pre-diabetes: Cross-sectional results from the Diabetes Prevention Program Trial. Environ Int 2020; 137:105217. [PMID: 32086073 PMCID: PMC7517661 DOI: 10.1016/j.envint.2019.105217] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Revised: 09/04/2019] [Accepted: 09/23/2019] [Indexed: 05/20/2023]
Abstract
Diet is assumed to be the main source of exposure to per- and polyfluoroalkyl substances (PFAS) in non-occupationally exposed populations, but studies on the diet-PFAS relationship in the United States are scarce. We extracted multiple dietary variables, including daily intakes of food group, diet scores, and dietary patterns, from self-reported dietary data collected at baseline (1996-1999) from adults with pre-diabetes enrolled in the Diabetes Prevention Program, and used linear regression models to evaluate relationships of each dietary variable with plasma concentrations of six PFAS (perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorohexane sulfonic acid (PFHxS), 2-(N-ethyl-perfluorooctane sulfonamido) acetic acid (EtFOSAA), 2-(N-methyl-perfluorooctane sulfonamido) acetic acid (MeFOSAA), perfluorononanoic acid (PFNA) adjusting for covariates. Participants (N = 941, 65% female, 58% Caucasian, 68% married, 75% with higher education, 95% nonsmoker) had similar PFAS concentrations compared to the general U.S. population during 1999-2000. Using a single food group approach, fried fish, other fish/shellfish, meat and poultry had positive associations with most PFAS plasma concentrations. The strongest effect estimate detected was between fried fish and PFNA [13.6% (95% CI: 7.7, 19.9) increase in median concentration per SD increase]. Low-carbohydrate and high protein diet score had positive association with plasma PFHxS. Some food groups, mostly vegetables and fruits, and the Dietary Approaches to Stop Hypertension diet score had inverse associations with PFOS and MeFOSAA. A vegetable diet pattern was associated with lower plasma concentrations of MeFOSAA, while high-fat meat and low-fiber and high-fat grains diet patterns were associated with higher plasma concentrations of PFOS, PFHxS, MeFOSAA and PFNA. We summarized four major dietary characteristics associated with variations in PFAS plasma concentrations in this population. Specifically, consuming more meat/fish/shellfish (especially fried fish, and excluding Omega3-rich fish), low-fiber and high-fat bread/cereal/rice/pasta, and coffee/tea was associated with higher plasma concentrations while dietary patterns of vegetables, fruits and Omega-3 rich fish were associated with lower plasma concentrations of some PFAS.
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Affiliation(s)
- Pi-I D. Lin
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, CA
| | - Russ Hauser
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Diane R. Gold
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Ken P. Kleinman
- Department of Biostatistics, School of Public Health and Human Sciences, University of Massachusetts Amherst, Amherst, MA, USA
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Abby F. Fleisch
- Pediatric Endocrinology and Diabetes, Maine Medical Center, Portland, ME, USA
- Center for Outcomes Research and Evaluation, Maine Medical Center Research Institute, Portland, ME, USA
| | - Antonia M. Calafat
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Marco Sanchez-Guerra
- Department of Developmental Neurobiology, National Institute of Perinatology, Mexico City, Mexico
| | - Citlalli Osorio-Yáñez
- Instituto de Investigaciones Biomédicas, Universidad Nacional Autonoma de Mexico, Ciudad de Mexico, Mexico
| | - Thomas F. Webster
- Department of Environmental Health, Boston University School of Public Health, Boston, MA, USA
| | | | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Corresponding Author: Pi-I D. Lin, ScD, Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, 401 Park Drive, Suite 401, Boston, MA 02215, USA, Phone: (617) 867-4240; Fax: (617) 867-4845,
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13
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Lewis CE, Bantle JP, Bertoni AG, Blackburn G, Brancati FL, Bray GA, Cheskin LJ, Curtis JM, Egan C, Evans M, Foreyt JP, Ghazarian S, Gibbs BB, Glasser S, Gregg EW, Hazuda HP, Hesson L, Hill JO, Horton ES, Hubbard VS, Jakicic JM, Jeffery RW, Johnson KC, Kahn SE, Kitabchi AE, Kitzman D, Knowler WC, Lipkin E, Michaels S, Montez MG, Nathan DM, Nyenwe E, Patricio J, Peters A, Pi-Sunyer X, Pownall H, Reboussin D, Ryan DH, Wadden TA, Wagenknecht LE, Wyatt H, Wing RR, Yanovski SZ. History of Cardiovascular Disease, Intensive Lifestyle Intervention, and Cardiovascular Outcomes in the Look AHEAD Trial. Obesity (Silver Spring) 2020; 28:247-258. [PMID: 31898874 PMCID: PMC6980987 DOI: 10.1002/oby.22676] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Accepted: 09/11/2019] [Indexed: 01/08/2023]
Abstract
OBJECTIVE To examine the effects of an intensive lifestyle intervention (ILI) on cardiovascular disease (CVD), the Action for Health in Diabetes (Look AHEAD) trial randomized 5,145 participants with type 2 diabetes and overweight/obesity to a ILI or diabetes support and education. Although the primary outcome did not differ between the groups, there was suggestive evidence of heterogeneity for prespecified baseline CVD history subgroups (interaction P = 0.063). Event rates were higher in the ILI group among those with a CVD history (hazard ratio 1.13 [95% CI: 0.90-1.41]) and lower among those without CVD (hazard ratio 0.86 [95% CI: 0.72-1.02]). METHODS This study conducted post hoc analyses of the rates of the primary composite outcome and components, adjudicated cardiovascular death, nonfatal myocardial infarction (MI), stroke, and hospitalization for angina, as well as three secondary composite cardiovascular outcomes. RESULTS Interaction P values for the primary and two secondary composites were similar (0.060-0.064). Of components, the interaction was significant for nonfatal MI (P = 0.035). This interaction was not due to confounding by baseline variables, different intervention responses for weight loss and physical fitness, or hypoglycemic events. In those with a CVD history, statin use was high and similar by group. In those without a CVD history, low-density lipoprotein cholesterol levels were higher (P = 0.003) and statin use was lower (P ≤ 0.001) in the ILI group. CONCLUSIONS Intervention response heterogeneity was significant for nonfatal MI. Response heterogeneity may need consideration in a CVD-outcome trial design.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Jeffrey M. Curtis
- Southwestern American Indian Center, Phoenix, AZ; National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ; St. Joseph’s Hospital and Medical Center, Phoenix
| | - Caitlin Egan
- The Miriam Hospital, Brown Medical School; Providence, RI
| | - Mary Evans
- National Institute of Diabetes and Digestive and Kidney Diseases; Bethesda; MD
| | | | | | | | | | | | - Helen P. Hazuda
- University of Texas Health Science Center at San Antonio; San Antonio, TX
| | | | - James O. Hill
- University of Colorado Anschutz Medical Campus; Aurora, CO
| | | | - Van S. Hubbard
- National Institute of Diabetes and Digestive and Kidney Diseases; Bethesda; MD
| | | | | | | | - Steven E. Kahn
- VA Puget Sound Health Care System, University of Washington; Seattle, WA
| | | | | | - William C. Knowler
- Southwestern American Indian Center, Phoenix; National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ
| | - Edward Lipkin
- VA Puget Sound Health Care System, University of Washington; Seattle, WA
| | | | - Maria G. Montez
- University of Texas Health Science Center at San Antonio; San Antonio, TX
| | | | | | - Jennifer Patricio
- St. Luke’s Roosevelt Hospital Center, Columbia University; New York, NY
| | - Anne Peters
- University of Southern California; Los Angeles, CA
| | - Xavier Pi-Sunyer
- St. Luke’s Roosevelt Hospital Center, Columbia University; New York, NY
| | | | | | - Donna H. Ryan
- Pennington Biomedical Research Center; Baton Rouge, LA
| | | | | | - Holly Wyatt
- University of Colorado Anschutz Medical Campus; Aurora, CO
| | - Rena R. Wing
- The Miriam Hospital, Brown Medical School; Providence, RI
| | - Susan Z. Yanovski
- National Institute of Diabetes and Digestive and Kidney Diseases; Bethesda; MD
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14
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Jakicic JM, Horton ES, Curtis JM, Killean TM, Bray GA, Cheskin LJ, Johnson KC, Middelbeek RJW, Pi-Sunyer FX, Regensteiner JG, Ribisl PM, Wagenknecht L, Espeland MA. Abnormal Exercise Test or CVD History on Weight Loss or Fitness: the Look AHEAD Trial. Transl J Am Coll Sports Med 2020; 5:e000134. [PMID: 34017914 PMCID: PMC8130141 DOI: 10.1249/tjx.0000000000000134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
PURPOSE Obesity and type 2 diabetes are associated with an increased risk of cardiovascular disease (CVD) and the combination of weight loss and increased physical exercise are commonly recommended to reduce CVD. This study examined whether people with obesity and type 2 diabetes with an abnormal graded exercise tolerance test (GXT) or a history of CVD would have less success in achieving weight loss and improved fitness, compared to adults without these conditions. METHODS The Look AHEAD Study examined whether an intensive lifestyle intervention (ILI) compared with diabetes support and education (DSE) reduced cardiovascular events in adults with overweight/obesity and type 2 diabetes. Participants underwent a baseline maximal GXT and provided medical history data. Weight loss and fitness change were examined in 5011 participants over four years in those with or without an abnormal baseline GXT and/or history of CVD. RESULTS After four years, weight loss in both ILI and DSE were significantly greater in those without a prior history of CVD than in those with a CVD history (6.69% vs 5.98%, p=0.02, in ILI and 0.73 vs -.07% (weight gain), p=0.01, in DSE). Likewise, those without a prior history of CVD experienced greater improvements in fitness in both ILI and DSE relative to those with a history of CVD. Having an abnormal GXT at baseline did not affect weight loss or fitness. CONCLUSIONS A history of CVD at baseline modestly lessened weight loss and fitness changes at 4 years, whereas having any abnormality on the baseline GXT did not affect these outcomes. Thus, weight loss and improved fitness are achievable in adults with a history of CVD or ECG abnormalities.
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Affiliation(s)
| | | | - Jeffrey M. Curtis
- NIDDK, Phoenix, AZ
- St. Joseph’s Hospital and Medical Center, Phoenix, AZ
| | - Tina M. Killean
- NIDDK, Phoenix, AZ
- Northern Navajo Medical Center, Shiprock, NM
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15
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Houston DK, Neiberg RH, Miller ME, Hill JO, Jakicic JM, Johnson KC, Gregg EW, Hubbard VS, Pi-Sunyer X, Rejeski WJ, Wing RR, Bantle JP, Beale E, Berkowitz RI, Cassidy-Begay M, Clark JM, Coday M, Delahanty LM, Dutton G, Egan C, Foreyt JP, Greenway FL, Hazuda HP, Hergenroeder A, Horton ES, Jeffery RW, Kahn SE, Kure A, Knowler WC, Lewis CE, Martin CK, Michaels S, Montez MG, Nathan DM, Patricio J, Peters A, Pownall H, Regensteiner J, Steinburg H, Wadden TA, White K, Yanovski SZ, Zhang P, Kritchevsky SB. Physical Function Following a Long-Term Lifestyle Intervention Among Middle Aged and Older Adults With Type 2 Diabetes: The Look AHEAD Study. J Gerontol A Biol Sci Med Sci 2019; 73:1552-1559. [PMID: 29053861 DOI: 10.1093/gerona/glx204] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2017] [Indexed: 01/26/2023] Open
Abstract
Background Lifestyle interventions have been shown to improve physical function over the short term; however, whether these benefits are sustainable is unknown. The long-term effects of an intensive lifestyle intervention (ILI) on physical function were assessed using a randomized post-test design in the Look AHEAD trial. Methods Overweight and obese (body mass index ≥ 25 kg/m2) middle-aged and older adults (aged 45-76 years at enrollment) with type 2 diabetes enrolled in Look AHEAD, a trial evaluating an ILI designed to achieve weight loss through caloric restriction and increased physical activity compared to diabetes support and education (DSE), underwent standardized assessments of performance-based physical function including a 4- and 400-m walk, lower extremity physical performance (expanded Short Physical Performance Battery, SPPBexp), and grip strength approximately 11 years postrandomization and 1.5 years after the intervention was stopped (n = 3,783). Results Individuals randomized to ILI had lower odds of slow gait speed (<0.8 m/s) compared to those randomized to DSE (adjusted OR [95% CI]: 0.84 [0.71 to 0.99]). Individuals randomized to ILI also had faster gait speed over 4- and 400-m (adjusted mean difference [95% CI]: 0.019 [0.007 to 0.031] m/s, p = .002, and 0.023 [0.012 to 0.034] m/sec, p < .0001, respectively) and higher SPPBexp scores (0.037 [0.011 to 0.063], p = .005) compared to those randomized to DSE. The intervention effect was slightly larger for SPPBexp scores among older versus younger participants (0.081 [0.038 to 0.124] vs 0.013 [-0.021 to 0.047], p = .01). Conclusions An intensive lifestyle intervention has modest but significant long-term benefits on physical function in overweight and obese middle-aged and older adults with type 2 diabetes. ClinicalTrials.gov Identifier NCT00017953.
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Affiliation(s)
| | | | | | - James O Hill
- University of Colorado Denver School of Medicine, Aurora
| | | | | | | | - Van S Hubbard
- National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland
| | | | | | - Rena R Wing
- Brown University and Miriam Hospital, Providence, Rhode Island
| | | | - Elizabeth Beale
- Keck School of Medicine of University of Southern California, Los Angeles
| | | | | | | | - Mace Coday
- University of Tennessee Health Science Center, Memphis
| | | | - Gareth Dutton
- University of Alabama at Birmingham School of Medicine
| | - Caitlin Egan
- Weight Control and Diabetes Research Center, Providence, Rhode Island
| | | | | | - Helen P Hazuda
- University of Texas Health Science Center at San Antonio
| | | | - Edward S Horton
- Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts
| | | | | | | | - William C Knowler
- National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona
| | - Cora E Lewis
- University of Alabama at Birmingham School of Medicine
| | - Corby K Martin
- Pennington Biomedical Research Center, Baton Rouge, Louisiana
| | | | - Maria G Montez
- University of Texas Health Science Center at San Antonio
| | | | | | - Anne Peters
- Keck School of Medicine of University of Southern California, Los Angeles
| | | | | | | | - Thomas A Wadden
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Karen White
- Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Susan Z Yanovski
- National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland
| | - Ping Zhang
- Centers for Disease Control, Atlanta, Georgia
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16
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Srinivasan S, Jablonski KA, Knowler WC, Dagogo-Jack S, E. Kahn S, Boyko EJ, Bray GA, Horton ES, Hivert MF, Goldberg R, Chen L, Mercader J, Harden M, Florez JC. A Polygenic Lipodystrophy Genetic Risk Score Characterizes Risk Independent of BMI in the Diabetes Prevention Program. J Endocr Soc 2019; 3:1663-1677. [PMID: 31428720 PMCID: PMC6694040 DOI: 10.1210/js.2019-00069] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Accepted: 06/18/2019] [Indexed: 01/24/2023] Open
Abstract
CONTEXT There is substantial heterogeneity in insulin sensitivity, and genetics may suggest possible mechanisms by which common variants influence this trait. OBJECTIVES We aimed to evaluate an 11-variant polygenic lipodystrophy genetic risk score (GRS) for association with anthropometric, glycemic and metabolic traits in the Diabetes Prevention Program (DPP). In secondary analyses, we tested the association of the GRS with cardiovascular risk factors in the DPP. DESIGN In 2713 DPP participants, we evaluated a validated GRS of 11 common variants associated with fasting insulin-based measures of insulin sensitivity discovered through genome-wide association studies that cluster with a metabolic profile of lipodystrophy, conferring high metabolic risk despite low body mass index (BMI). RESULTS At baseline, a higher polygenic lipodystrophy GRS was associated with lower weight, BMI, and waist circumference measurements, but with worse insulin sensitivity index (ISI) values. Despite starting at a lower weight and BMI, a higher GRS was associated with less weight and BMI reduction at one year and less improvement in ISI after adjusting for baseline values but was not associated with diabetes incidence. A higher GRS was also associated with more atherogenic low-density lipoprotein peak-particle-density at baseline but was not associated with coronary artery calcium scores in the Diabetes Prevention Program Outcomes Study. CONCLUSIONS In the DPP, a higher polygenic lipodystrophy GRS for insulin resistance with lower BMI was associated with diminished improvement in insulin sensitivity and potential higher cardiovascular disease risk. This GRS helps characterize insulin resistance in a cohort of individuals at high risk for diabetes, independent of adiposity.
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Affiliation(s)
- Shylaja Srinivasan
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, University of California at San Francisco, San Francisco, California
| | - Kathleen A Jablonski
- Department of Epidemiology and Biostatistics, Milken Institute School of Public Health, George Washington University, Washington, DC
| | - William C Knowler
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona
| | - Samuel Dagogo-Jack
- Division of Endocrinology, Diabetes and Metabolism, University of Tennessee Health Science Center, Memphis, Tennessee
| | - Steven E. Kahn
- Division of Metabolism, Endocrinology and Nutrition, Department of Medicine, VA Puget Sound Health Care System and University of Washington, Seattle, Washington
| | - Edward J Boyko
- Division of General Internal Medicine, University of Washington, Seattle, Washington
| | - George A Bray
- Division of Clinical Obesity and Metabolism, Pennington Biomedical Research Center, Baton Rouge, Louisiana
| | | | - Marie-France Hivert
- Diabetes Research Center, Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, Massachusetts
| | - Ronald Goldberg
- Diabetes Research Institute, University of Miami Health System, Miami, Florida
| | - Ling Chen
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard & Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Josep Mercader
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard & Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Maegan Harden
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard & Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Jose C Florez
- Diabetes Research Center, Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard & Massachusetts Institute of Technology, Cambridge, Massachusetts
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17
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Cardenas A, Hivert MF, Gold DR, Hauser R, Kleinman KP, Lin PID, Fleisch AF, Calafat AM, Ye X, Webster TF, Horton ES, Oken E. Associations of Perfluoroalkyl and Polyfluoroalkyl Substances With Incident Diabetes and Microvascular Disease. Diabetes Care 2019; 42:1824-1832. [PMID: 31296647 PMCID: PMC6702604 DOI: 10.2337/dc18-2254] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Accepted: 06/22/2019] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Perfluoroalkyl and polyfluoroalkyl substances (PFASs) are suspected endocrine disruptors widely detected across populations. We examine the extent to which PFASs are associated with diabetes incidence and microvascular disease. Secondarily, we tested whether a lifestyle intervention modifies associations and decreases concentrations. RESEARCH DESIGN AND METHODS We analyzed data from a prospective cohort of 957 participants from the Diabetes Prevention Program (DPP) trial and Diabetes Prevention Program Outcomes Study (DPPOS). At baseline, participants were randomized to an intensive lifestyle intervention of diet, physical activity, and behavior modification or a placebo medication. We quantified plasma concentrations of six PFASs at baseline and 2 years after randomization. Participants were monitored for ∼15 years, repeatedly tested for diabetes, and evaluated for microvascular disease at the end of the follow-up. RESULTS A doubling in baseline branched perfluorooctanoic acid concentration was associated with a 14% increase in diabetes risk for the placebo (hazard ratio [HR] 1.14, 95% CI 1.04, 1.25) but not in the lifestyle intervention group (HR 1.01, 95% CI 0.92, 1.11, P interaction = 0.11). Mean change in plasma baseline branched perfluorooctanoic acid concentration was greater for the placebo (0.96 ng/mL; 95% CI 0.71, 1.22) compared with the lifestyle intervention group (0.31 ng/mL; 95% CI 0.14, 0.48) 2 years after randomization. Each doubling in N-ethyl-perfluorooctane sulfonamido acetic acid was associated with 17% greater odds of prevalent microvascular disease (OR 1.17, 95% CI 1.05, 1.31), and a similar association was observed for perfluorodimethylhexane sulfonic acid (OR 1.18, 95% CI 1.04, 1.35), regardless of treatment. CONCLUSIONS Some plasma PFASs were associated with diabetes and microvascular disease. Our results suggest that exercise and diet may attenuate the diabetogenic association of PFASs.
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Affiliation(s)
- Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, CA
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA
| | - Diane R Gold
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA
| | - Russ Hauser
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Ken P Kleinman
- Department of Biostatistics and Epidemiology, University of Massachusetts-Amherst School of Public Health and Health Sciences, Amherst, MA
| | - Pi-I D Lin
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA
| | - Abby F Fleisch
- Division of Pediatric Endocrinology and Diabetes, Maine Medical Center, Portland, ME
- Center for Outcomes Research and Evaluation, Maine Medical Center Research Institute, Portland, ME
| | - Antonia M Calafat
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
| | - Xiaoyun Ye
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
| | - Thomas F Webster
- Department of Environmental Health, Boston University School of Public Health, Boston, MA
| | | | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA
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18
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Lin PID, Cardenas A, Hauser R, Gold DR, Kleinman KP, Hivert MF, Fleisch AF, Calafat AM, Webster TF, Horton ES, Oken E. Per- and polyfluoroalkyl substances and blood lipid levels in pre-diabetic adults-longitudinal analysis of the diabetes prevention program outcomes study. Environ Int 2019; 129:343-353. [PMID: 31150976 PMCID: PMC6570418 DOI: 10.1016/j.envint.2019.05.027] [Citation(s) in RCA: 68] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 05/06/2019] [Accepted: 05/10/2019] [Indexed: 05/20/2023]
Abstract
Exposure to per- and polyfluoroalkyl substances (PFASs) may interfere with lipid regulation. However, most previous studies were cross-sectional with the risk of reverse causation, suggesting a need for long-term prospective studies. We examined the relationship of baseline plasma PFAS concentrations with repeated measures of blood lipids. We included 888 prediabetic adults from the Diabetes Prevention Program (DPP) and DPP Outcomes Study, who had measurements of 6 plasma PFAS concentrations at baseline (1996-1999) and repeated measures of blood lipids over 15 years of follow-up, and were initially randomized to placebo or a lifestyle intervention. We used linear regression to examine cross-sectional associations of PFAS concentrations and lipid levels at baseline, and evaluated prospective risks of hypercholesterolemia and hypertriglyceridemia using Cox proportional hazard models, and tested for effect modification by study arm. Participants (65.9% female, 57.0% White, 65.9% aged 40-59 years) had comparable PFAS concentrations [e.g., median (IQR) perfluorooctanoic acid (PFOA) 4.9 ng/mL (3.2)] with the general U.S. population in 1999-2000. We observed higher total cholesterol at baseline per doubling of PFOA (β: 6.1 mg/dL, 95% CI: 3.1, 9.04), perfluorohexane sulfonic acid (PFHxS, β: 2.2 mg/dL, 95% CI: 0.2, 4.3), and perfluorononanoic acid (PFNA, β: 2.9 mg/dL, 95% CI: 0.7, 5.0). Prospectively, baseline concentrations of several PFASs, including PFOA, PFOS, PFHxS and PFNA, predicted higher risks of incident hypercholesterolemia and hypertriglyceridemia, but only in the placebo group and not the lifestyle intervention group. For example, participants in the placebo group with PFOA concentration > median (4.9 ng/mL) were almost twice as likely (HR: 1.90, 95% CI: 1.25, 2.88) to develop hypertriglyceridemia compared to those ≤median. Findings suggest adverse effects of some PFASs on lipid profiles in prediabetic adults. However, the detrimental effect was attenuated with a lifestyle intervention.
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Affiliation(s)
- Pi-I D Lin
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
| | - Russ Hauser
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Diane R Gold
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Ken P Kleinman
- Department of Biostatistics, School of Public Health and Human Sciences, University of Massachusetts Amherst, Amherst, MA, USA
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA; Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Abby F Fleisch
- Pediatric Endocrinology and Diabetes, Maine Medical Center, Portland, ME, USA; Center for Outcomes Research and Evaluation, Maine Medical Center Research Institute, Portland, ME, USA
| | - Antonia M Calafat
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Thomas F Webster
- Department of Environmental Health, Boston University School of Public Health, Boston, MA, USA
| | - Edward S Horton
- Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
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Rosenzweig JL, Bakris GL, Berglund LF, Hivert MF, Horton ES, Kalyani RR, Murad MH, Vergès BL. Primary Prevention of ASCVD and T2DM in Patients at Metabolic Risk: An Endocrine Society* Clinical Practice Guideline. J Clin Endocrinol Metab 2019; 104:3939-3985. [PMID: 31365087 DOI: 10.1210/jc.2019-01338] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Accepted: 06/13/2019] [Indexed: 12/16/2022]
Abstract
OBJECTIVE To develop clinical practice guidelines for the primary prevention of atherosclerotic cardiovascular disease (ASCVD) and type 2 diabetes mellitus (T2DM) in individuals at metabolic risk for developing these conditions. CONCLUSIONS Health care providers should incorporate regular screening and identification of individuals at metabolic risk (at higher risk for ASCVD and T2DM) with measurement of blood pressure, waist circumference, fasting lipid profile, and blood glucose. Individuals identified at metabolic risk should undergo 10-year global risk assessment for ASCVD or coronary heart disease to determine targets of therapy for reduction of apolipoprotein B-containing lipoproteins. Hypertension should be treated to targets outlined in this guideline. Individuals with prediabetes should be tested at least annually for progression to diabetes and referred to intensive diet and physical activity behavioral counseling programs. For the primary prevention of ASCVD and T2DM, the Writing Committee recommends lifestyle management be the first priority. Behavioral programs should include a heart-healthy dietary pattern and sodium restriction, as well as an active lifestyle with daily walking, limited sedentary time, and a structured program of physical activity, if appropriate. Individuals with excess weight should aim for loss of ≥5% of initial body weight in the first year. Behavior changes should be supported by a comprehensive program led by trained interventionists and reinforced by primary care providers. Pharmacological and medical therapy can be used in addition to lifestyle modification when recommended goals are not achieved.
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Affiliation(s)
| | | | | | - Marie-France Hivert
- Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, Massachusetts
| | | | - Rita R Kalyani
- Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - M Hassan Murad
- Evidence-Based Practice Center, Mayo Clinic, Rochester, Minnesota
| | - Bruno L Vergès
- Centre Hospitalier Universitaire Dijon Bourgogne, Dijon, France
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Hazuda HP, Gaussoin SA, Wing RR, Yanovski SZ, Johnson KC, Coday M, Wadden TA, Horton ES, Van Dorsten B, Knowler WC. Long-term Association of Depression Symptoms and Antidepressant Medication Use With Incident Cardiovascular Events in the Look AHEAD (Action for Health in Diabetes) Clinical Trial of Weight Loss in Type 2 Diabetes. Diabetes Care 2019; 42:910-918. [PMID: 30833373 PMCID: PMC6489104 DOI: 10.2337/dc18-0575] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2018] [Accepted: 02/07/2019] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To examine whether depression symptoms or antidepressant medication (ADM) use predicts the probability of cardiovascular events in overweight/obese individuals with type 2 diabetes. RESEARCH DESIGN AND METHODS Preplanned analyses of depression and incident cardiovascular disease (CVD) were performed in the Look AHEAD (Action for Health in Diabetes) weight loss trial after a median follow-up of 9.6 years. Depression symptoms, assessed with the Beck Depression Inventory (BDI), were analyzed both as a continuous and dichotomized variable (BDI score <10 or ≥10). ADM use was coded from participants' prescription medications. Four composite CVD outcomes were defined in the study protocol. Sex-stratified Cox proportional hazards models were adjusted for a range of baseline covariates. RESULTS Depression symptoms were only significantly associated with a composite secondary outcome comprising CVD death, nonfatal myocardial infarction, nonfatal stroke, hospitalized angina, congestive heart failure, peripheral vascular disease, coronary artery bypass graft, and carotid endarterectomy. Significant sex interactions were observed for BDI score and BDI score ≥10. BDI score was significantly associated with higher probability of this composite outcome in men but was not associated with the outcome in women. BDI score ≥10 was positively associated with this composite outcome in men but was negatively associated in women. Exploratory analysis identified a significant BDI ≥10 × ADM use interaction for this composite outcome that differed in men versus women. Men with both BDI score ≥10 and ADM use compared with those with neither had 60% higher probability of the outcome, whereas women with both compared with those with neither had 50% lower probability. CONCLUSIONS Sex differences in the association of depression symptoms and ADM use with incident CVD warrant further investigation.
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Affiliation(s)
- Helen P Hazuda
- The University of Texas Health Science Center at San Antonio, San Antonio, TX
| | | | - Rena R Wing
- The Miriam Hospital/Brown Medical School, Providence, RI
| | - Susan Z Yanovski
- National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD
| | | | - Mace Coday
- The University of Tennessee, Memphis, TN
| | | | | | | | - William C Knowler
- National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD
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Cardenas A, Hauser R, Gold DR, Kleinman KP, Hivert MF, Fleisch AF, Lin PID, Calafat AM, Webster TF, Horton ES, Oken E. Association of Perfluoroalkyl and Polyfluoroalkyl Substances With Adiposity. JAMA Netw Open 2018; 1:e181493. [PMID: 30646133 PMCID: PMC6324277 DOI: 10.1001/jamanetworkopen.2018.1493] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
IMPORTANCE Perfluoroalkyl and polyfluoroalkyl substances (PFASs) are ubiquitous synthetic chemicals that are suspected endocrine disruptors. OBJECTIVES To determine the extent to which PFASs are associated with increases in weight and body size and evaluate whether a lifestyle intervention modifies this association. DESIGN, SETTING, AND PARTICIPANTS This prospective cohort study included 957 individuals who participated in the Diabetes Prevention Program trial, conducted from July 1996 to May 2001, and the Diabetes Prevention Program Outcomes Study, conducted from September 2002 to January 2014. Statistical analysis was conducted from September 1, 2017, to May 25, 2018. INTERVENTIONS AND EXPOSURES The initial lifestyle intervention consisted of training in diet, physical activity, and behavior modification, with the major goals of achieving 7% weight loss with subsequent maintenance and a minimum of 150 minutes per week of physical activity. Participants randomized to placebo received standard information about diet and exercise. A total of 6 plasma PFASs were quantified at baseline and 2 years after randomization, means were calculated from baseline and year 2 concentrations, and means were summed to assess total PFAS burden. MAIN OUTCOMES AND MEASURES Weight, waist circumference, and hip girth were measured at baseline and at scheduled visits. RESULTS Of the 957 participants, 625 (65.3%) were women and 731 participants (76.4%) were between 40 and 64 years of age; 481 participants were randomized to the lifestyle intervention and 476 participants were randomized to the placebo arm. The PFAS concentrations were not different by treatment arm and were similar to concentrations reported for the US population in 1999-2000. The association of PFAS and weight change differed by treatment. Each doubling in total PFAS concentration was associated with an increase of 1.80 kg (95% CI, 0.43-3.17 kg; P = .01) from baseline to 9 years after randomization for the placebo group but not the lifestyle intervention group (-0.59 kg; 95% CI, -1.80 to 0.62 kg; P = .34). Similarly, each doubling in PFAS was associated with a 1.03-cm increase in hip girth in the Diabetes Prevention Program trial for the placebo group (95% CI, 0.18-1.88 cm; P = .02) but not the lifestyle intervention group (-0.09 cm; 95% CI, -0.82 to 0.63 cm; P = .80). No associations were observed for changes in mean waist circumference. CONCLUSIONS AND RELEVANCE Among adults at high risk for diabetes, higher plasma PFAS concentration was associated with increases in weight and hip girth over time, but a lifestyle intervention attenuated these associations. Diet and exercise may mitigate the obesogenic effects of environmental chemicals. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT00004992 and NCT00038727.
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Affiliation(s)
- Andres Cardenas
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, Massachusetts
| | - Russ Hauser
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Diane R. Gold
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Ken P. Kleinman
- Department of Biostatistics and Epidemiology, University of Massachusetts–Amherst School of Public Health and Health Sciences, Amherst
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, Massachusetts
- Diabetes Unit, Massachusetts General Hospital, Boston
| | - Abby F. Fleisch
- Division of Pediatric Endocrinology and Diabetes, Maine Medical Center, Portland
- Center for Outcomes Research and Evaluation, Maine Medical Center Research Institute, Portland
| | - Pi-I D. Lin
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, Massachusetts
| | - Antonia M. Calafat
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Thomas F. Webster
- Department of Environmental Health, Boston University School of Public Health, Boston, Massachusetts
| | - Edward S. Horton
- Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, Massachusetts
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Carmichael OT, Neiberg RH, Dutton G, Hayden KM, Horton ES, Pi-Sunyer X, Johnson KC, Rapp SR, Spira AP, Espeland MA. O4‐06‐06: ASSOCIATIONS BETWEEN TEN‐YEAR CHANGE IN DIABETES MARKERS AND COGNITIVE PERFORMANCE IN TYPE 2 DIABETES. Alzheimers Dement 2018. [DOI: 10.1016/j.jalz.2018.06.2944] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Affiliation(s)
| | | | - Gareth Dutton
- UAB Nutrition Obesity Research CenterBirminghamALUSA
| | | | | | | | | | | | - Adam P. Spira
- Johns Hopkins Bloomberg School of Public HealthBaltimoreMDUSA
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Brinkley TE, Anderson A, Soliman EZ, Bertoni AG, Greenway F, Knowler WC, Glasser SP, Horton ES, Espeland MA. Long-Term Effects of an Intensive Lifestyle Intervention on Electrocardiographic Criteria for Left Ventricular Hypertrophy: The Look AHEAD Trial. Am J Hypertens 2018; 31:541-548. [PMID: 29324968 DOI: 10.1093/ajh/hpy004] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Accepted: 01/08/2018] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Left ventricular hypertrophy assessed by electrocardiography (ECG-LVH) is a marker of subclinical cardiac damage and a strong predictor of cardiovascular disease (CVD) events. The prevalence of ECG-LVH is increased in obesity and type 2 diabetes; however, there are no data on the long-term effects of weight loss on ECG-LVH. The purpose of this study was to determine whether an intensive lifestyle intervention (ILI) reduces ECG-LVH in overweight and obese adults with type 2 diabetes. METHODS Data from 4,790 Look AHEAD participants (mean age: 58.8 ± 6.8 years, 63.2% White) who were randomized to a 10-year ILI (n = 2,406) or diabetes support and education (DSE, n = 2,384) were included. ECG-LVH defined by Cornell voltage criteria was assessed every 2 years. Longitudinal logistic regression analysis with generalized estimation equations and linear mixed models were used to compare the prevalence of ECG-LVH and changes in absolute Cornell voltage over time between intervention groups, with tests of interactions by sex, race/ethnicity, and baseline CVD status. RESULTS The prevalence of ECG-LVH at baseline was 5.2% in the DSE group and 5.0% in the ILI group (P = 0.74). Over a median 9.5 years of follow-up, prevalent ECG-LVH increased similarly in both groups (odds ratio: 1.02, 95% confidence interval: 0.83-1.25; group × time interaction, P = 0.49). Increases in Cornell voltage during follow-up were also similar between intervention groups (group × time interaction, P = 0.57). Intervention effects were generally similar between subgroups of interest. CONCLUSIONS The Look AHEAD long-term lifestyle intervention does not significantly lower ECG-LVH in overweight and obese adults with type 2 diabetes. CLINICAL TRIALS REGISTRATION Trial Number NCT00017953 (ClinicalTrials.gov).
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Affiliation(s)
- Tina E Brinkley
- Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Andrea Anderson
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Elsayed Z Soliman
- Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Alain G Bertoni
- Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Frank Greenway
- Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, Louisiana, USA
| | - William C Knowler
- Diabetes Epidemiology and Clinical Research Section, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona, USA
| | - Stephen P Glasser
- Division of Preventive Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Edward S Horton
- Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Mark A Espeland
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
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Espeland MA, Carmichael O, Hayden K, Neiberg RH, Newman AB, Keller JN, Wadden TA, Rapp SR, Hill JO, Horton ES, Johnson KC, Wagenknecht L, Wing RR. Long-term Impact of Weight Loss Intervention on Changes in Cognitive Function: Exploratory Analyses from the Action for Health in Diabetes Randomized Controlled Clinical Trial. J Gerontol A Biol Sci Med Sci 2018; 73:484-491. [PMID: 28958022 PMCID: PMC5861893 DOI: 10.1093/gerona/glx165] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Accepted: 08/23/2017] [Indexed: 11/13/2022] Open
Abstract
Background Diabetes adversely impacts cognition. Lifestyle change can improve diabetes control and potentially improve cognition. We examined whether weight loss through reduced caloric intake and increased physical activity was associated with slower cognitive aging in older adults with type 2 diabetes mellitus. Methods The Look AHEAD randomized controlled clinical trial delivered 10 years of intensive lifestyle intervention (ILI) that yielded long-term weight losses. During 5 years spanning the end of intervention and postintervention follow-up, repeated cognitive assessments were obtained in 1,091 individuals who had been assigned to ILI or a control condition of diabetes support and education (DSE). We compared the means and slopes of scores on cognitive testing over these repeated assessments. Results Compared with DSE, assignment to ILI was associated with a -0.082 SD deficit in mean global cognitive function across repeated assessments (p = .010). However, overweight (body mass index [BMI] < 30 kg/m2) ILI participants had 0.099 (95% confidence interval [CI]: -0.006, 0.259) better mean global cognitive function compared with overweight DSE participants, while obese (BMI ≥ 30 kg/m2) ILI participants had -0.117 (-0.185, -0.049) SD worse mean composite cognitive function scores (interaction p = .014) compared to obese DSE participants. For both overweight and obese participants, cognitive decline was marginally (-0.014 SD/y overall) steeper for ILI participants (p = .068), with 95% CI for differences in slopes excluding 0 for measures of attention and memory. Conclusions The behavioral weight loss intervention was associated with small relative deficits in cognitive function among individuals who were obese and marginally greater cognitive decline overall compared to control. ClinicalTrials.gov Identifier: NCT00017953.
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Affiliation(s)
- Mark A Espeland
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Owen Carmichael
- Brain and Metabolism Imaging in Chronic Disease Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA
| | - Kathleen Hayden
- Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, NC
| | - Rebecca H Neiberg
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Anne B Newman
- Healthy Aging Research Program, University of Pittsburgh, PA
| | - Jeffery N Keller
- Institute for Dementia Research and Prevention, Pennington Biomedical Research Center, Baton Rouge, LA
| | - Thomas A Wadden
- Center for Weight and Eating Disorders, University of Pennsylvania, Philadelphia
| | - Stephen R Rapp
- Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, NC
| | - James O Hill
- Center for Human Nutrition, University of Colorado Anschutz Medical Campus, Denver
| | | | - Karen C Johnson
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis
| | - Lynne Wagenknecht
- Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, NC
| | - Rena R Wing
- Weight Control and Diabetes Research Center, Miriam Hospital, Providence, RI
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Fried PJ, Schilberg L, Brem AK, Saxena S, Wong B, Cypess AM, Horton ES, Pascual-Leone A. Humans with Type-2 Diabetes Show Abnormal Long-Term Potentiation-Like Cortical Plasticity Associated with Verbal Learning Deficits. J Alzheimers Dis 2018; 55:89-100. [PMID: 27636847 DOI: 10.3233/jad-160505] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
BACKGROUND Type-2 diabetes mellitus (T2DM) accelerates cognitive aging and increases risk of Alzheimer's disease. Rodent models of T2DM show altered synaptic plasticity associated with reduced learning and memory. Humans with T2DM also show cognitive deficits, including reduced learning and memory, but the relationship of these impairments to the efficacy of neuroplastic mechanisms has never been assessed. OBJECTIVE Our primary objective was to compare mechanisms of cortical plasticity in humans with and without T2DM. Our secondary objective was to relate plasticity measures to standard measures of cognition. METHODS A prospective cross-sectional cohort study was conducted on 21 adults with T2DM and 15 demographically-similar non-diabetic controls. Long-term potentiation-like plasticity was assessed in primary motor cortex by comparing the amplitude of motor evoked potentials (MEPs) from single-pulse transcranial magnetic stimulation before and after intermittent theta-burst stimulation (iTBS). Plasticity measures were compared between groups and related to neuropsychological scores. RESULTS In T2DM, iTBS-induced modulation of MEPs was significantly less than controls, even after controlling for potential confounds. Furthermore, in T2DM, modulation of MEPs 10-min post-iTBS was significantly correlated with Rey Auditory Verbal Learning Task (RAVLT) performance. CONCLUSION Humans with T2DM show abnormal cortico-motor plasticity that is correlated with reduced verbal learning. Since iTBS after-effects and the RAVLT are both NMDA receptor-dependent measures, their relationship in T2DM may reflect brain-wide alterations in the efficacy of NMDA receptors. These findings offer novel mechanistic insights into the brain consequences of T2DM and provide a reliable means to monitor brain health and evaluate the efficacy of clinical interventions.
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Affiliation(s)
- Peter J Fried
- Berenson-Allen Center for Noninvasive Brain Stimulation, Division of Interventional Cognitive Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Lukas Schilberg
- Berenson-Allen Center for Noninvasive Brain Stimulation, Division of Interventional Cognitive Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.,Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Anna-Katharine Brem
- Berenson-Allen Center for Noninvasive Brain Stimulation, Division of Interventional Cognitive Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.,Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Sadhvi Saxena
- Berenson-Allen Center for Noninvasive Brain Stimulation, Division of Interventional Cognitive Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.,Department of Psychiatry and Behavioral Sciences, Johns Hopkins Medical School, Baltimore, MD, USA
| | - Bonnie Wong
- Berenson-Allen Center for Noninvasive Brain Stimulation, Division of Interventional Cognitive Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.,Frontotemporal Dementia Unit, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Aaron M Cypess
- Diabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, MD, USA.,Research Division, Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA
| | - Edward S Horton
- Research Division, Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA
| | - Alvaro Pascual-Leone
- Berenson-Allen Center for Noninvasive Brain Stimulation, Division of Interventional Cognitive Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
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Sylvetsky AC, Edelstein SL, Walford G, Boyko EJ, Horton ES, Ibebuogu UN, Knowler WC, Montez MG, Temprosa M, Hoskin M, Rother KI, Delahanty LM. A High-Carbohydrate, High-Fiber, Low-Fat Diet Results in Weight Loss among Adults at High Risk of Type 2 Diabetes. J Nutr 2017; 147:2060-2066. [PMID: 28954840 PMCID: PMC5657137 DOI: 10.3945/jn.117.252395] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Revised: 05/12/2017] [Accepted: 08/31/2017] [Indexed: 01/17/2023] Open
Abstract
Background: Weight loss is a key factor in reducing diabetes risk. The Diabetes Prevention Program (DPP) is a completed clinical trial that randomly assigned individuals at high risk of diabetes to a placebo (PLBO), metformin (MET), or intensive lifestyle intervention (ILS) group, which included physical activity (PA) and reduced dietary fat intake.Objective: We aimed to evaluate the associations between diet and weight at baseline and to identify specific dietary factors that predicted weight loss among DPP participants.Methods: Diet was assessed by a food frequency questionnaire. The associations between intakes of macronutrients and various food groups and body weight among DPP participants at baseline were assessed by linear regression, adjusted for race/ethnicity, age, sex, calorie intake, and PA. Models that predicted weight loss at year 1 were adjusted for baseline weight, change in calorie intake, and change in PA and stratified by treatment allocation (MET, ILS, and PLBO). All results are presented as estimates ± SEs.Results: A total of 3234 participants were enrolled in the DPP; 2924 had completed dietary data (67.5% women; mean age: 50.6 ± 10.7 y). Adjusted for calorie intake, baseline weight was negatively associated with carbohydrate intake (-1.14 ± 0.18 kg body weight/100 kcal carbohydrate, P < 0.0001) and, specifically, dietary fiber (-1.26 ± 0.28 kg/5 g fiber, P < 0.0001). Baseline weight was positively associated with total fat (1.25 ± 0.21 kg/100 kcal, P < 0.0001), saturated fat (1.96 ± 0.46 kg/100 kcal, P < 0.0001), and protein (0.21 ± 0.05 kg/100 kcal, P < 0.0001). For all groups, weight loss after 1 y was associated with increases in carbohydrate intake, specifically dietary fiber, and decreases in total fat and saturated fat intake.Conclusions: Higher carbohydrate consumption among DPP participants, specifically high-fiber carbohydrates, and lower total and saturated fat intake best predicted weight loss when adjusted for changes in calorie intake. Our results support the benefits of a high-carbohydrate, high-fiber, low-fat diet in the context of overall calorie reduction leading to weight loss, which may prevent diabetes in high-risk individuals. This trial was registered at clinicaltrials.gov as NCT00004992.
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Affiliation(s)
- Allison C Sylvetsky
- Department of Exercise and Nutrition Sciences,,Sumner M. Redstone Global Center for Prevention and Wellness,,Section on Pediatric Diabetes and Metabolism, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, MD
| | - Sharon L Edelstein
- Biostatistics Center, and,Department of Epidemiology and Biostatistics Milken Institute School of Public Health, George Washington University, Washington, DC
| | - Geoffrey Walford
- Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Edward J Boyko
- General Medicine Service, VA Puget Sound, Seattle, WA;,Department of Medicine, University of Washington, Seattle, WA
| | | | - Uzoma N Ibebuogu
- Department of Medicine, University of Tennessee Health Sciences Center, Memphis, TN
| | - William C Knowler
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Phoenix, AZ; and
| | - Maria G Montez
- Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX
| | - Marinella Temprosa
- Biostatistics Center, and,Department of Epidemiology and Biostatistics Milken Institute School of Public Health, George Washington University, Washington, DC
| | - Mary Hoskin
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Phoenix, AZ; and
| | - Kristina I Rother
- Section on Pediatric Diabetes and Metabolism, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, MD
| | - Linda M Delahanty
- Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA
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Johnson KC, Lewis CE, Womack C, Garcia KR, Wagenknecht L, Pownall HJ, Horton ES, Pi-Sunyer X, Gregg EW, Schwartz AV. The Effect of Intentional Weight Loss on Fracture Risk in Persons With Diabetes: Results From the Look AHEAD Randomized Clinical Trial. J Bone Miner Res 2017; 32:2278-2287. [PMID: 28678345 PMCID: PMC5685890 DOI: 10.1002/jbmr.3214] [Citation(s) in RCA: 51] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2017] [Revised: 06/29/2017] [Accepted: 07/03/2017] [Indexed: 12/24/2022]
Abstract
Intentional weight loss is an important treatment option for overweight persons with type 2 diabetes mellitus (DM), but the effects on long-term fracture risk are not known. The purpose of this Look AHEAD analysis was to evaluate whether long-term intentional weight loss would increase fracture risk in overweight or obese persons with DM. Look AHEAD is a multicenter, randomized clinical trial. Recruitment began in August 2001 and follow-up continued for a median of 11.3 years at 16 academic centers. A total of 5145 persons aged 45 to 76 years with DM were randomized to either an intensive lifestyle intervention (ILI) with reduced calorie consumption and increased physical activity designed to achieve and maintain ≥7% weight loss or to diabetes support and education intervention (DSE). Incident fractures were ascertained every 6 months by self-report and confirmed with central adjudication of medical records. The baseline mean age of participants was 59 years, 60% were women, 63% were white, and the mean BMI was 36 kg/m2 . Weight loss over the intervention period (median 9.6 years) was 6.0% in ILI and 3.5% in DSE. A total of 731 participants had a confirmed incident fracture (358 in DSE versus 373 in ILI). There were no statistically significant differences in incident total or hip fracture rates between the ILI and DSE groups. However, compared to the DSE group, the ILI group had a statistically significant 39% increased risk of a frailty fracture (HR 1.39; 95% CI, 1.02 to 1.89). An intensive lifestyle intervention resulting in long-term weight loss in overweight/obese adults with DM was not associated with an overall increased risk of incident fracture but may be associated with an increased risk of frailty fracture. When intentional weight loss is planned, consideration of bone preservation and fracture prevention is warranted. © 2017 American Society for Bone and Mineral Research.
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Affiliation(s)
| | - Karen C. Johnson
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN
| | - Cora E. Lewis
- University of Alabama at Birmingham, Birmingham, ALA
| | - Catherine Womack
- Department of Preventive Medicine and Medicine, University of Tennessee Health Science Center, Memphis, TN
| | - Katelyn R. Garcia
- Wake Forest School of Medicine, Wake Forest University, Winston-Salem, NC
| | - Lynne Wagenknecht
- Wake Forest School of Medicine, Wake Forest University, Winston-Salem, NC
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Cardenas A, Gold DR, Hauser R, Kleinman KP, Hivert MF, Calafat AM, Ye X, Webster TF, Horton ES, Oken E. Plasma Concentrations of Per- and Polyfluoroalkyl Substances at Baseline and Associations with Glycemic Indicators and Diabetes Incidence among High-Risk Adults in the Diabetes Prevention Program Trial. Environ Health Perspect 2017; 125:107001. [PMID: 28974480 PMCID: PMC5933403 DOI: 10.1289/ehp1612] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2017] [Revised: 08/03/2017] [Accepted: 08/04/2017] [Indexed: 05/20/2023]
Abstract
BACKGROUND Several per- and polyfluoroalkyl substances (PFAS) are ubiquitous anthropogenic pollutants almost universally detected in humans. Experimental evidence indicates that PFAS alter glucose metabolism and insulin secretion. However, epidemiological studies have yielded inconsistent results. OBJECTIVE We sought to examine associations between plasma PFAS concentrations, glycemic indicators, and diabetes incidence among high-risk adults. METHODS Within the Diabetes Prevention Program (DPP), a trial for the prevention of type 2 diabetes among high-risk individuals, we quantified baseline plasma concentrations of nine PFAS among 957 participants randomized to a lifestyle intervention or placebo. We evaluated adjusted associations for plasma PFAS concentrations with diabetes incidence and key glycemic indicators measured at baseline and annually over up to 4.6 y. RESULTS Plasma PFAS concentrations were similar to those reported in the U.S. population in 1999-2000. At baseline, in cross-sectional analysis, a doubling in plasma perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) concentrations was associated with higher homeostatic model assessment of insulin resistance (HOMA-IR) [βPFOS=0.39; 95% confidence interval (CI): 0.13, 0.66; βPFOA=0.64; 95% CI: 0.34, 0.94], β-cell function (HOMA-β) (βPFOS=9.62; 95% CI: 1.55, 17.70; βPFOA=15.93; 95% CI: 6.78, 25.08), fasting proinsulin (βPFOS=1.37 pM; 95% CI: 0.50, 2.25; βPFOA=1.71 pM; 95% CI: 0.72, 2.71), and glycated hemoglobin (HbA1c) (βPFOS=0.03%; 95% CI: 0.002, 0.07; βPFOA=0.04%; 95% CI: 0.001, 0.07). There was no strong evidence of associations between plasma PFAS concentrations and diabetes incidence or prospective changes in glycemic indicators during the follow-up period. CONCLUSIONS At baseline, several PFAS were cross-sectionally associated with small differences in markers of insulin secretion and β-cell function. However, there was limited evidence suggesting that PFAS concentrations are associated with diabetes incidence or changes in glycemic indicators during the follow-up period. https://doi.org/10.1289/EHP1612.
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Affiliation(s)
- Andres Cardenas
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim HealthCare Institute , Boston, Massachusetts, USA
| | - Diane R Gold
- Channing Laboratory, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Russ Hauser
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Ken P Kleinman
- Department of Biostatistics, School of Public Health and Human Sciences, University of Massachusetts Amherst , Amherst, Massachusetts, USA
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim HealthCare Institute , Boston, Massachusetts, USA
- Diabetes Unit , Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Antonia M Calafat
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention , Atlanta, Georgia, USA
| | - Xiaoyun Ye
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention , Atlanta, Georgia, USA
| | - Thomas F Webster
- Department of Environmental Health, Boston University School of Public Health , Boston, Massachusetts, USA
| | - Edward S Horton
- Joslin Diabetes Center, Harvard Medical School , Boston, Massachusetts, USA
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim HealthCare Institute , Boston, Massachusetts, USA
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Matarazzo M, Giardina MG, Guardasole V, Davalli AM, Horton ES, Weir GC, Saccà L, Napoli R. Islet Transplantation under the Kidney Capsule Corrects the Defects in Glycogen Metabolism in Both Liver and Muscle of Streptozocin-Diabetic Rats. Cell Transplant 2017. [DOI: 10.3727/096020198389834] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
Insulin-deficient rats are characterized by multiple defects in the pathway of glycogen synthesis and breakdown in both liver and skeletal muscle. The aim of this study was to clarify whether islet transplantation under the kidney capsule, which is associated with delivery of insulin into the peripheral circulation, is able to normalize glycogen metabolism in liver and muscle of streptozotocin-diabetic rats. Three groups of male Lewis rats were studied under fasting condition: controls, untreated diabetics, and islet transplanted diabetics. Glycogen content, glucose-6-phosphate concentration, and glycogen synthase activity were measured in both liver and skeletal muscle. Untreated diabetic rats were characterized by an increase in glycogen content of 178% and a reduction of glucose-6-phosphate level of 50%. Both glycogen and glucose-6-phosphate contents were restored to normal in transplanted diabetic rats. Active glycogen synthase (0.35 ± 0.1 nmol/min/mg) and activity ratio (0.22 ± 0.04) were significantly impaired compared with controls (0.99 ± 0.2 nmol/min/mg and 0.43 ± 0.06, respectively) and were normalized by islet transplantation. In the skeletal muscle, glycogen content was similar in the three groups of animals, whereas muscle glucose-6-phosphate level was reduced by 28% and glycogen synthase was in a less active state in the untreated diabetic rats. Both the glucose-6-phosphate concentration and the kinetic profile of glycogen synthase were normalized by islet transplantation. In conclusion, islet transplantation under the kidney capsule corrects the diabetes-induced abnormalities in glycogen and glucose-6-phosphate content and glycogen synthase activity in both liver and skeletal muscle.
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Affiliation(s)
- Margherita Matarazzo
- Department of Internal Medicine and Cardiovascular Sciences, University Federico II School of Medicine, Napoli, Italy
| | - Maria Grazia Giardina
- Department of Internal Medicine and Cardiovascular Sciences, University Federico II School of Medicine, Napoli, Italy
| | - Vincenzo Guardasole
- Department of Internal Medicine and Cardiovascular Sciences, University Federico II School of Medicine, Napoli, Italy
| | - Alberto M. Davalli
- Scientific Institute S. Raffaele, Milano, Italy
- Joslin Diabetes Center, Harvard Medical School, Boston, MA
| | | | - Gordon C. Weir
- Joslin Diabetes Center, Harvard Medical School, Boston, MA
| | - Luigi Saccà
- Department of Internal Medicine and Cardiovascular Sciences, University Federico II School of Medicine, Napoli, Italy
| | - Raffaele Napoli
- Department of Internal Medicine and Cardiovascular Sciences, University Federico II School of Medicine, Napoli, Italy
- Joslin Diabetes Center, Harvard Medical School, Boston, MA
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Goldberg RB, Aroda VR, Bluemke DA, Barrett-Connor E, Budoff M, Crandall JP, Dabelea D, Horton ES, Mather KJ, Orchard TJ, Schade D, Watson K, Temprosa M. Effect of Long-Term Metformin and Lifestyle in the Diabetes Prevention Program and Its Outcome Study on Coronary Artery Calcium. Circulation 2017; 136:52-64. [PMID: 28476766 PMCID: PMC5526695 DOI: 10.1161/circulationaha.116.025483] [Citation(s) in RCA: 83] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2016] [Accepted: 04/18/2017] [Indexed: 02/06/2023]
Abstract
BACKGROUND Despite the reduced incidence of coronary heart disease with intensive risk factor management, people with diabetes mellitus and prediabetes remain at increased coronary heart disease risk. Diabetes prevention interventions may be needed to reduce coronary heart disease risk. This approach was examined in the DPP (Diabetes Prevention Program) and the DPPOS (Diabetes Prevention Program Outcome Study), a long-term intervention study in 3234 subjects with prediabetes (mean±SD age, 64±10 years) that showed reduced diabetes risk with lifestyle and metformin compared with placebo over 3.2 years. METHODS The DPPOS offered periodic group lifestyle sessions to all participants and continued metformin in the originally randomized metformin group. Subclinical atherosclerosis was assessed in 2029 participants with coronary artery calcium (CAC) measurements after an average of 14 years of follow-up. The CAC scores were analyzed continuously as CAC severity and categorically as CAC presence (CAC score >0) and reported separately in men and women. RESULTS There were no CAC differences between lifestyle and placebo intervention groups in either sex. CAC severity and presence were significantly lower among men in the metformin versus the placebo group (age-adjusted mean CAC severity, 39.5 versus 66.9 Agatston units, P=0.04; CAC presence, 75% versus 84%, P=0.02), but no metformin effect was seen in women. In multivariate analysis, the metformin effect in men was not influenced by demographic, anthropometric, or metabolic factors; by the development of diabetes mellitus; or by use/nonuse of statin therapy. CONCLUSIONS Metformin may protect against coronary atherosclerosis in prediabetes and early diabetes mellitus among men. CLINICAL TRIAL REGISTRATION URL: http://www.clinicaltrials.gov. Unique identifier: NCT00038727.
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Affiliation(s)
- Ronald B Goldberg
- From Diabetes Research Institute, University of Miami Miller School of Medicine, FL (R.B.G.); MedStar Health Research Institute, Washington, DC (V.R.A.); National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Washington, DC (D.A.B.); University of California, San Diego (E.B.-C.); Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles (M.B.); Albert Einstein College of Medicine, New York, NY (J.P.C.); University of Colorado Denver (D.D.); Joslin Diabetes Center, Boston, MA (E.S.H.); Indiana University School of Medicine, Indianapolis (K.J.M.); University of Pittsburgh Medical Center, PA (T.J.O.); University of New Mexico School of Medicine, Albuquerque (D.S.); University of California Los Angeles School of Medicine (K.W.); and George Washington University Biostatistics Center, Department of Epidemiology and Biostatistics, Rockville, MD (M.T.).
| | - Vanita R Aroda
- From Diabetes Research Institute, University of Miami Miller School of Medicine, FL (R.B.G.); MedStar Health Research Institute, Washington, DC (V.R.A.); National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Washington, DC (D.A.B.); University of California, San Diego (E.B.-C.); Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles (M.B.); Albert Einstein College of Medicine, New York, NY (J.P.C.); University of Colorado Denver (D.D.); Joslin Diabetes Center, Boston, MA (E.S.H.); Indiana University School of Medicine, Indianapolis (K.J.M.); University of Pittsburgh Medical Center, PA (T.J.O.); University of New Mexico School of Medicine, Albuquerque (D.S.); University of California Los Angeles School of Medicine (K.W.); and George Washington University Biostatistics Center, Department of Epidemiology and Biostatistics, Rockville, MD (M.T.)
| | - David A Bluemke
- From Diabetes Research Institute, University of Miami Miller School of Medicine, FL (R.B.G.); MedStar Health Research Institute, Washington, DC (V.R.A.); National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Washington, DC (D.A.B.); University of California, San Diego (E.B.-C.); Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles (M.B.); Albert Einstein College of Medicine, New York, NY (J.P.C.); University of Colorado Denver (D.D.); Joslin Diabetes Center, Boston, MA (E.S.H.); Indiana University School of Medicine, Indianapolis (K.J.M.); University of Pittsburgh Medical Center, PA (T.J.O.); University of New Mexico School of Medicine, Albuquerque (D.S.); University of California Los Angeles School of Medicine (K.W.); and George Washington University Biostatistics Center, Department of Epidemiology and Biostatistics, Rockville, MD (M.T.)
| | - Elizabeth Barrett-Connor
- From Diabetes Research Institute, University of Miami Miller School of Medicine, FL (R.B.G.); MedStar Health Research Institute, Washington, DC (V.R.A.); National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Washington, DC (D.A.B.); University of California, San Diego (E.B.-C.); Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles (M.B.); Albert Einstein College of Medicine, New York, NY (J.P.C.); University of Colorado Denver (D.D.); Joslin Diabetes Center, Boston, MA (E.S.H.); Indiana University School of Medicine, Indianapolis (K.J.M.); University of Pittsburgh Medical Center, PA (T.J.O.); University of New Mexico School of Medicine, Albuquerque (D.S.); University of California Los Angeles School of Medicine (K.W.); and George Washington University Biostatistics Center, Department of Epidemiology and Biostatistics, Rockville, MD (M.T.)
| | - Matthew Budoff
- From Diabetes Research Institute, University of Miami Miller School of Medicine, FL (R.B.G.); MedStar Health Research Institute, Washington, DC (V.R.A.); National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Washington, DC (D.A.B.); University of California, San Diego (E.B.-C.); Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles (M.B.); Albert Einstein College of Medicine, New York, NY (J.P.C.); University of Colorado Denver (D.D.); Joslin Diabetes Center, Boston, MA (E.S.H.); Indiana University School of Medicine, Indianapolis (K.J.M.); University of Pittsburgh Medical Center, PA (T.J.O.); University of New Mexico School of Medicine, Albuquerque (D.S.); University of California Los Angeles School of Medicine (K.W.); and George Washington University Biostatistics Center, Department of Epidemiology and Biostatistics, Rockville, MD (M.T.)
| | - Jill P Crandall
- From Diabetes Research Institute, University of Miami Miller School of Medicine, FL (R.B.G.); MedStar Health Research Institute, Washington, DC (V.R.A.); National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Washington, DC (D.A.B.); University of California, San Diego (E.B.-C.); Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles (M.B.); Albert Einstein College of Medicine, New York, NY (J.P.C.); University of Colorado Denver (D.D.); Joslin Diabetes Center, Boston, MA (E.S.H.); Indiana University School of Medicine, Indianapolis (K.J.M.); University of Pittsburgh Medical Center, PA (T.J.O.); University of New Mexico School of Medicine, Albuquerque (D.S.); University of California Los Angeles School of Medicine (K.W.); and George Washington University Biostatistics Center, Department of Epidemiology and Biostatistics, Rockville, MD (M.T.)
| | - Dana Dabelea
- From Diabetes Research Institute, University of Miami Miller School of Medicine, FL (R.B.G.); MedStar Health Research Institute, Washington, DC (V.R.A.); National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Washington, DC (D.A.B.); University of California, San Diego (E.B.-C.); Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles (M.B.); Albert Einstein College of Medicine, New York, NY (J.P.C.); University of Colorado Denver (D.D.); Joslin Diabetes Center, Boston, MA (E.S.H.); Indiana University School of Medicine, Indianapolis (K.J.M.); University of Pittsburgh Medical Center, PA (T.J.O.); University of New Mexico School of Medicine, Albuquerque (D.S.); University of California Los Angeles School of Medicine (K.W.); and George Washington University Biostatistics Center, Department of Epidemiology and Biostatistics, Rockville, MD (M.T.)
| | - Edward S Horton
- From Diabetes Research Institute, University of Miami Miller School of Medicine, FL (R.B.G.); MedStar Health Research Institute, Washington, DC (V.R.A.); National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Washington, DC (D.A.B.); University of California, San Diego (E.B.-C.); Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles (M.B.); Albert Einstein College of Medicine, New York, NY (J.P.C.); University of Colorado Denver (D.D.); Joslin Diabetes Center, Boston, MA (E.S.H.); Indiana University School of Medicine, Indianapolis (K.J.M.); University of Pittsburgh Medical Center, PA (T.J.O.); University of New Mexico School of Medicine, Albuquerque (D.S.); University of California Los Angeles School of Medicine (K.W.); and George Washington University Biostatistics Center, Department of Epidemiology and Biostatistics, Rockville, MD (M.T.)
| | - Kieren J Mather
- From Diabetes Research Institute, University of Miami Miller School of Medicine, FL (R.B.G.); MedStar Health Research Institute, Washington, DC (V.R.A.); National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Washington, DC (D.A.B.); University of California, San Diego (E.B.-C.); Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles (M.B.); Albert Einstein College of Medicine, New York, NY (J.P.C.); University of Colorado Denver (D.D.); Joslin Diabetes Center, Boston, MA (E.S.H.); Indiana University School of Medicine, Indianapolis (K.J.M.); University of Pittsburgh Medical Center, PA (T.J.O.); University of New Mexico School of Medicine, Albuquerque (D.S.); University of California Los Angeles School of Medicine (K.W.); and George Washington University Biostatistics Center, Department of Epidemiology and Biostatistics, Rockville, MD (M.T.)
| | - Trevor J Orchard
- From Diabetes Research Institute, University of Miami Miller School of Medicine, FL (R.B.G.); MedStar Health Research Institute, Washington, DC (V.R.A.); National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Washington, DC (D.A.B.); University of California, San Diego (E.B.-C.); Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles (M.B.); Albert Einstein College of Medicine, New York, NY (J.P.C.); University of Colorado Denver (D.D.); Joslin Diabetes Center, Boston, MA (E.S.H.); Indiana University School of Medicine, Indianapolis (K.J.M.); University of Pittsburgh Medical Center, PA (T.J.O.); University of New Mexico School of Medicine, Albuquerque (D.S.); University of California Los Angeles School of Medicine (K.W.); and George Washington University Biostatistics Center, Department of Epidemiology and Biostatistics, Rockville, MD (M.T.)
| | - David Schade
- From Diabetes Research Institute, University of Miami Miller School of Medicine, FL (R.B.G.); MedStar Health Research Institute, Washington, DC (V.R.A.); National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Washington, DC (D.A.B.); University of California, San Diego (E.B.-C.); Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles (M.B.); Albert Einstein College of Medicine, New York, NY (J.P.C.); University of Colorado Denver (D.D.); Joslin Diabetes Center, Boston, MA (E.S.H.); Indiana University School of Medicine, Indianapolis (K.J.M.); University of Pittsburgh Medical Center, PA (T.J.O.); University of New Mexico School of Medicine, Albuquerque (D.S.); University of California Los Angeles School of Medicine (K.W.); and George Washington University Biostatistics Center, Department of Epidemiology and Biostatistics, Rockville, MD (M.T.)
| | - Karol Watson
- From Diabetes Research Institute, University of Miami Miller School of Medicine, FL (R.B.G.); MedStar Health Research Institute, Washington, DC (V.R.A.); National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Washington, DC (D.A.B.); University of California, San Diego (E.B.-C.); Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles (M.B.); Albert Einstein College of Medicine, New York, NY (J.P.C.); University of Colorado Denver (D.D.); Joslin Diabetes Center, Boston, MA (E.S.H.); Indiana University School of Medicine, Indianapolis (K.J.M.); University of Pittsburgh Medical Center, PA (T.J.O.); University of New Mexico School of Medicine, Albuquerque (D.S.); University of California Los Angeles School of Medicine (K.W.); and George Washington University Biostatistics Center, Department of Epidemiology and Biostatistics, Rockville, MD (M.T.)
| | - Marinella Temprosa
- From Diabetes Research Institute, University of Miami Miller School of Medicine, FL (R.B.G.); MedStar Health Research Institute, Washington, DC (V.R.A.); National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Washington, DC (D.A.B.); University of California, San Diego (E.B.-C.); Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles (M.B.); Albert Einstein College of Medicine, New York, NY (J.P.C.); University of Colorado Denver (D.D.); Joslin Diabetes Center, Boston, MA (E.S.H.); Indiana University School of Medicine, Indianapolis (K.J.M.); University of Pittsburgh Medical Center, PA (T.J.O.); University of New Mexico School of Medicine, Albuquerque (D.S.); University of California Los Angeles School of Medicine (K.W.); and George Washington University Biostatistics Center, Department of Epidemiology and Biostatistics, Rockville, MD (M.T.)
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Espeland MA, Luchsinger JA, Baker LD, Neiberg R, Kahn SE, Arnold SE, Wing RR, Blackburn GL, Bray G, Evans M, Hazuda HP, Jeffery RW, Wilson VM, Clark JM, Coday M, Demos-McDermott K, Foreyt JP, Greenway F, Hill JO, Horton ES, Jakicic JM, Johnson KC, Knowler WC, Lewis CE, Nathan DM, Peters A, Pi-Sunyer X, Pownall H, Wadden TA, Rapp SR. Effect of a long-term intensive lifestyle intervention on prevalence of cognitive impairment. Neurology 2017; 88:2026-2035. [PMID: 28446656 DOI: 10.1212/wnl.0000000000003955] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2016] [Accepted: 02/21/2017] [Indexed: 01/07/2023] Open
Abstract
OBJECTIVE To assess whether an average of 10 years of lifestyle intervention designed to reduce weight and increase physical activity lowers the prevalence of cognitive impairment among adults at increased risk due to type 2 diabetes and obesity or overweight. METHODS Central adjudication of mild cognitive impairment and probable dementia was based on standardized cognitive test battery scores administered to 3,802 individuals who had been randomly assigned, with equal probability, to either the lifestyle intervention or the diabetes support and education control. When scores fell below a prespecified threshold, functional information was obtained through proxy interview. RESULTS Compared with control, the intensive lifestyle intervention induced and maintained marked differences in weight loss and self-reported physical activity throughout follow-up. At an average (range) of 11.4 (9.5-13.5) years after enrollment, when participants' mean age was 69.6 (54.9-87.2) years, the prevalence of mild cognitive impairment and probable dementia was 6.4% and 1.8%, respectively, in the intervention group, compared with 6.6% and 1.8%, respectively, in the control group (p = 0.93). The lack of an intervention effect on the prevalence of cognitive impairment was consistent among individuals grouped by cardiovascular disease history, diabetes duration, sex, and APOE ε4 allele status (all p ≥ 0.50). However, there was evidence (p = 0.03) that the intervention effect ranged from benefit to harm across participants ordered from lowest to highest baseline BMI. CONCLUSIONS Ten years of behavioral weight loss intervention did not result in an overall difference in the prevalence of cognitive impairment among overweight or obese adults with type 2 diabetes. CLINICALTRIALSGOV IDENTIFIER NCT00017953 (Action for Health in Diabetes). LEVEL OF EVIDENCE This study provides Class II evidence that for overweight adults with type 2 diabetes, a lifestyle intervention designed to reduce weight and increase physical activity does not lower the risk of cognitive impairment.
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Affiliation(s)
| | | | - Laura D Baker
- Author affiliations are provided at the end of the article
| | | | - Steven E Kahn
- Author affiliations are provided at the end of the article
| | | | - Rena R Wing
- Author affiliations are provided at the end of the article
| | | | - George Bray
- Author affiliations are provided at the end of the article
| | - Mary Evans
- Author affiliations are provided at the end of the article
| | - Helen P Hazuda
- Author affiliations are provided at the end of the article
| | | | | | - Jeanne M Clark
- Author affiliations are provided at the end of the article
| | - Mace Coday
- Author affiliations are provided at the end of the article
| | | | - John P Foreyt
- Author affiliations are provided at the end of the article
| | - Frank Greenway
- Author affiliations are provided at the end of the article
| | - James O Hill
- Author affiliations are provided at the end of the article
| | | | - John M Jakicic
- Author affiliations are provided at the end of the article
| | | | | | - Cora E Lewis
- Author affiliations are provided at the end of the article
| | - David M Nathan
- Author affiliations are provided at the end of the article
| | - Anne Peters
- Author affiliations are provided at the end of the article
| | | | - Henry Pownall
- Author affiliations are provided at the end of the article
| | | | - Stephen R Rapp
- Author affiliations are provided at the end of the article
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32
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Colberg SR, Sigal RJ, Yardley JE, Riddell MC, Dunstan DW, Dempsey PC, Horton ES, Castorino K, Tate DF. Physical Activity/Exercise and Diabetes: A Position Statement of the American Diabetes Association. Diabetes Care 2016; 39:2065-2079. [PMID: 27926890 PMCID: PMC6908414 DOI: 10.2337/dc16-1728] [Citation(s) in RCA: 1312] [Impact Index Per Article: 164.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Sheri R Colberg
- Department of Human Movement Sciences, Old Dominion University, Norfolk, VA
| | - Ronald J Sigal
- Departments of Medicine, Cardiac Sciences, and Community Health Sciences, Faculties of Medicine and Kinesiology, University of Calgary, Calgary, Alberta, Canada
| | - Jane E Yardley
- Department of Social Sciences, Augustana Campus, University of Alberta, Camrose, Alberta, Canada
| | - Michael C Riddell
- School of Kinesiology and Health Science, York University, Toronto, Ontario, Canada
| | - David W Dunstan
- Baker IDI Heart & Diabetes Institute, Melbourne, Victoria, Australia
| | - Paddy C Dempsey
- Baker IDI Heart & Diabetes Institute, Melbourne, Victoria, Australia
| | - Edward S Horton
- Harvard Medical School and Joslin Diabetes Center, Boston, MA
| | | | - Deborah F Tate
- Department of Health Behavior, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC
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Varga TV, Winters AH, Jablonski KA, Horton ES, Khare-Ranade P, Knowler WC, Marcovina SM, Renström F, Watson KE, Goldberg R, Florez JC, Pollin TI, Franks PW. Comprehensive Analysis of Established Dyslipidemia-Associated Loci in the Diabetes Prevention Program. ACTA ACUST UNITED AC 2016; 9:495-503. [PMID: 27784733 DOI: 10.1161/circgenetics.116.001457] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2016] [Accepted: 10/03/2016] [Indexed: 01/19/2023]
Abstract
BACKGROUND We assessed whether 234 established dyslipidemia-associated loci modify the effects of metformin treatment and lifestyle intervention (versus placebo control) on lipid and lipid subfraction levels in the Diabetes Prevention Program randomized controlled trial. METHODS AND RESULTS We tested gene treatment interactions in relation to baseline-adjusted follow-up blood lipid concentrations (high-density lipoprotein [HDL] and low-density lipoprotein-cholesterol, total cholesterol, and triglycerides) and lipoprotein subfraction particle concentrations and size in 2993 participants with pre-diabetes. Of the previously reported single-nucleotide polymorphism associations, 32.5% replicated at P<0.05 with baseline lipid traits. Trait-specific genetic risk scores were robustly associated (3×10-4>P>1.1×10-16) with their respective baseline traits for all but 2 traits. Lifestyle modified the effect of the genetic risk score for large HDL particle numbers, such that each risk allele of the genetic risk scores was associated with lower concentrations of large HDL particles at follow-up in the lifestyle arm (β=-0.11 µmol/L per genetic risk scores risk allele; 95% confidence interval, -0.188 to -0.033; P=5×10-3; Pinteraction=1×10-3 for lifestyle versus placebo), but not in the metformin or placebo arms (P>0.05). In the lifestyle arm, participants with high genetic risk had more favorable or similar trait levels at 1-year compared with participants at lower genetic risk at baseline for 17 of the 20 traits. CONCLUSIONS Improvements in large HDL particle concentrations conferred by lifestyle may be diminished by genetic factors. Lifestyle intervention, however, was successful in offsetting unfavorable genetic loading for most lipid traits. CLINICAL TRIAL REGISTRATION URL: https://www.clinicaltrials.gov. Unique Identifier: NCT00004992.
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Affiliation(s)
- Tibor V Varga
- Dept of Clinical Sciences, Genetic & Molecular Epidemiology Unit, Lund Univ, Malmö, Sweden
| | - Alexandra H Winters
- Division of Endocrinology, Diabetes & Nutrition, Dept of Medicine & Program in Genetics & Genomic Medicine, Univ of Maryland School of Medicine, Baltimore
| | | | - Edward S Horton
- Dept of Medicine, Harvard Medical School.,Joslin Diabetes Center, Boston, MA
| | | | - William C Knowler
- Diabetes Epidemiology & Clinical Research Section, NIDDK, Phoenix, AZ
| | - Santica M Marcovina
- Northwest Lipid Metabolism & Diabetes Research Laboratories, Univ of Washington, Seattle, WA
| | - Frida Renström
- Dept of Clinical Sciences, Genetic & Molecular Epidemiology Unit, Lund Univ, Malmö, Sweden.,Dept of Biobank Research, Umeå Univ, Umeå, Sweden
| | | | - Ronald Goldberg
- Lipid Disorders Clinic, Division of Endocrinology, Diabetes & Metabolism, Leonard M. Miller School of Medicine, Univ of Miami, Miami, FL.,The Diabetes Research Institute, Leonard M. Miller School of Medicine, Univ of Miami, Miami, FL
| | - José C Florez
- Dept of Medicine, Harvard Medical School.,Program in Medical & Population Genetics, Broad Institute of Harvard & MIT, Cambridge.,Center for Human Genetic Research, Diabetes Unit, MGH.,Diabetes Research Center, Diabetes Unit, MGH
| | - Toni I Pollin
- Division of Endocrinology, Diabetes & Nutrition, Dept of Medicine & Program in Genetics & Genomic Medicine, Univ of Maryland School of Medicine, Baltimore
| | - Paul W Franks
- Dept of Clinical Sciences, Genetic & Molecular Epidemiology Unit, Lund Univ, Malmö, Sweden.,Dept of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA.,Dept of Public Health & Clinical Medicine, Umeå Univ, Umeå, Sweden
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Kim C, Barrett-Connor E, Aroda VR, Mather KJ, Christophi CA, Horton ES, Pi-Sunyer X, Bray GA, Labrie F, Golden SH. Testosterone and depressive symptoms among men in the Diabetes Prevention Program. Psychoneuroendocrinology 2016; 72:63-71. [PMID: 27371769 PMCID: PMC5070975 DOI: 10.1016/j.psyneuen.2016.06.009] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2016] [Revised: 06/12/2016] [Accepted: 06/13/2016] [Indexed: 01/09/2023]
Abstract
OBJECTIVE We examined associations between intensive lifestyle intervention (ILS) and changes in testosterone and associations with mood among middle-aged men. DESIGN Secondary analysis of men (n=886) participating in the Diabetes Prevention Program which randomized glucose-intolerant, overweight men to ILS, metformin, or placebo between 1996 and 1999. MAIN OUTCOME MEASURES Changes in testosterone between baseline and 1-year follow-up asnd associations of these changes with mood measures (Beck Depression Inventory [BDI-II], Beck Anxiety Inventory [BAI]). RESULTS Median baseline testosterone was 10.98nmol/l and 44% (n=385) had testosterone<10.41nmol/l or 300ng/dl. Testosterone increases were greater among men randomized to ILS vs. metformin vs. placebo (1.15nmol/l vs. -0.12nmol/l vs. -0.27nmol/l, p<0.001). The association between changes in testosterone and mood differed by study arm (p<0.001 for interaction); there were no significant associations between changes in testosterone and mood changes among men in the ILS or placebo arms. Among men in the metformin arm, increases in testosterone were significantly associated with decreases in BDI-II (improved depressive symptoms) (β-coefficient -0.2336, p=0.0002) indicating a 0.23 decrease in BDI-II for every 1nmol/l increase in testosterone and decreases in BAI (improved anxiety symptoms) (β-coefficient -0.2147, p=0.0014). Similar patterns were observed for bioavailable testosterone. CONCLUSIONS Among overweight middle-aged men with glucose-intolerance, ILS increased endogenous testosterone slightly but without significant improvements in mood. Metformin did not increase testosterone, but among metformin users, testosterone increases were associated with improvements in mood. Thus, interventions that increase endogenous testosterone may not also improve mood.
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Affiliation(s)
- Catherine Kim
- University of Michigan, Ann Arbor, MI, United States.
| | | | - Vanita R Aroda
- MedStar Health Research Institute, Hyattsville, MD, United States
| | | | | | | | | | - George A Bray
- Louisiana State University, Baton Rouge, LA, United States
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Peng C, Luttmann-Gibson H, Zanobetti A, Cohen A, De Souza C, Coull BA, Horton ES, Schwartz J, Koutrakis P, Gold DR. AIR POLLUTION INFLUENCES ON EXHALED NITRIC OXIDE AMONG PEOPLE WITH TYPE II DIABETES. Air Qual Atmos Health 2016; 9:265-273. [PMID: 27213020 PMCID: PMC4871616 DOI: 10.1007/s11869-015-0336-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
OBJECTIVE In a population with type 2 diabetes mellitus (T2DM), we examined associations of short-term air pollutant exposures with pulmonary inflammation, measured as fraction of exhaled pulmonary nitric oxide (FeNO). METHODS Sixty-nine Boston Metropolitan residents with T2DM completed up to 5 bi-weekly visits with 321 offline FeNO measurements. We measured ambient concentrations of particle mass, number and components at our stationary central site. Ambient concentrations of gaseous air pollutants were obtained from state monitors. We used linear models with fixed effects for participants, adjusting for 24-hour mean temperature, 24-hour mean water vapor pressure, season, and scrubbed room NO the day of the visit, to estimate associations between FeNO and interquartile range increases in exposure. RESULTS Interquartile increases in the 6-hour averages of black carbon (BC) (0.5 μg/m3) and particle number (PN) (1,000 particles/cm3) were associated with increases in FeNO of 3.84% (95% CI 0.60% to 7.18%) and 9.86 % (95% CI 3.59% to 16.52%), respectively. We also found significant associations of increases in FeNO with increases in 24-hour moving averages of BC, PN and nitrogen oxides (NOx). CONCLUSION Recent studies have focused on FeNO as a marker for eosinophilic pulmonary inflammation in asthmatic populations. This study adds support to the relevance of FeNO as a marker for pulmonary inflammation in diabetic populations, whose underlying chronic inflammatory status is likely to be related to innate immunity and proinflammatory adipokines.
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Affiliation(s)
- Cheng Peng
- Department of Environmental Health, Harvard University School of Public Health, Boston, MA
| | - Heike Luttmann-Gibson
- Department of Environmental Health, Harvard University School of Public Health, Boston, MA
| | - Antonella Zanobetti
- Department of Environmental Health, Harvard University School of Public Health, Boston, MA
| | | | - Celine De Souza
- Department of Environmental Health, Harvard University School of Public Health, Boston, MA
| | - Brent A. Coull
- Department of Biostatistics, Harvard School of Public Health, Boston, MA
| | | | - Joel Schwartz
- Department of Environmental Health, Harvard University School of Public Health, Boston, MA
- Channing Laboratory, Harvard Medical School, Boston, MA
| | - Petros Koutrakis
- Department of Environmental Health, Harvard University School of Public Health, Boston, MA
| | - Diane R. Gold
- Department of Environmental Health, Harvard University School of Public Health, Boston, MA
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
- Channing Laboratory, Harvard Medical School, Boston, MA
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36
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Hivert MF, Christophi CA, Franks PW, Jablonski KA, Ehrmann DA, Kahn SE, Horton ES, Pollin TI, Mather KJ, Perreault L, Barrett-Connor E, Knowler WC, Florez JC. Lifestyle and Metformin Ameliorate Insulin Sensitivity Independently of the Genetic Burden of Established Insulin Resistance Variants in Diabetes Prevention Program Participants. Diabetes 2016; 65:520-6. [PMID: 26525880 PMCID: PMC4747453 DOI: 10.2337/db15-0950] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2015] [Accepted: 10/27/2015] [Indexed: 12/15/2022]
Abstract
Large genome-wide association studies of glycemic traits have identified genetics variants that are associated with insulin resistance (IR) in the general population. It is unknown whether people with genetic enrichment for these IR variants respond differently to interventions that aim to improve insulin sensitivity. We built a genetic risk score (GRS) based on 17 established IR variants and effect sizes (weighted IR-GRS) in 2,713 participants of the Diabetes Prevention Program (DPP) with genetic consent. We tested associations between the weighted IR-GRS and insulin sensitivity index (ISI) at baseline in all participants, and with change in ISI over 1 year of follow-up in the DPP intervention (metformin and lifestyle) and control (placebo) arms. All models were adjusted for age, sex, ethnicity, and waist circumference at baseline (plus baseline ISI for 1-year ISI change models). A higher IR-GRS was associated with lower baseline ISI (β = -0.754 [SE = 0.229] log-ISI per unit, P = 0.001 in fully adjusted models). There was no differential effect of treatment for the association between the IR-GRS on the change in ISI; higher IR-GRS was associated with an attenuation in ISI improvement over 1 year (β = -0.520 [SE = 0.233], P = 0.03 in fully adjusted models; all treatment arms). Lifestyle intervention and metformin treatment improved the ISI, regardless of the genetic burden of IR variants.
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Affiliation(s)
- Marie-France Hivert
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA Diabetes Research Center (Diabetes Unit), Department of Medicine, Massachusetts General Hospital, Boston, MA Department of Medicine, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | | | - Paul W Franks
- Genetic & Molecular Epidemiology Unit, Lund University Diabetes Center, Department of Clinical Sciences, Lund University, Malmö, Sweden Department of Nutrition, Harvard School of Public Health, Boston, MA Department of Public Health and Clinical Medicine, Division of Medicine, Umeå University, Umeå, Sweden
| | | | - David A Ehrmann
- Department of Medicine, The University of Chicago School of Medicine, Chicago, IL
| | - Steven E Kahn
- Division of Metabolism, Endocrinology & Nutrition, VA Puget Sound Health Care System and University of Washington, Seattle, WA
| | - Edward S Horton
- Section on Clinical, Behavioral & Outcomes Research, Joslin Diabetes Center, Boston, MA Department of Medicine, Harvard Medical School, Boston, MA
| | - Toni I Pollin
- Departments of Medicine and Epidemiology & Public Health, University of Maryland School of Medicine, Baltimore, MD Program in Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Kieren J Mather
- Division of Endocrinology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
| | - Leigh Perreault
- Department of Medicine, Division of Endocrinology, Metabolism and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Elizabeth Barrett-Connor
- Division of Epidemiology, Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA
| | - William C Knowler
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ
| | - Jose C Florez
- Diabetes Research Center (Diabetes Unit), Department of Medicine, Massachusetts General Hospital, Boston, MA Department of Medicine, Harvard Medical School, Boston, MA Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
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Munshi MN, Segal AR, Slyne C, Samur AA, Brooks KM, Horton ES. Shortfalls of the use of HbA1C-derived eAG in older adults with diabetes. Diabetes Res Clin Pract 2015; 110:60-65. [PMID: 26272739 DOI: 10.1016/j.diabres.2015.07.012] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2015] [Revised: 06/18/2015] [Accepted: 07/27/2015] [Indexed: 12/26/2022]
Abstract
AIMS The hemoglobin HbA1C (HbA1C) value, translated into estimated average glucose concentration (eAG), is commonly used to assess glycaemic control and manage treatment regimens in people with diabetes. However, the relationships among HbA1C-derived eAG, and mean glucose concentration derived from continuous glucose monitoring (CGM) in different populations have not been well studied. We examined this relationship in older people with diabetes and compared the results to those currently used in clinical practice. METHODS Data from three studies evaluating CGM in older adults (≥70 years of age), with stable glycaemic control were analyzed retrospectively. Mean glucose and mean amplitude of glucose excursion (MAGE) were calculated from CGM data and correlated with HbA1C and HbA1C-derived eAG using the ADAG study formula. RESULTS HbA1C and CGM data were analyzed from 90 patients with mean age 76±5 years, HbA1C 7.9±1.2% (63±13 mmol/mol) and 77% with Type 2 diabetes. The HbA1C and HbA1C-derived eAG correlated significantly with CGM-measured mean glucose (r(2)=0.30, p<0.0001) and MAGE (r(2)=0.16, p=0.00013) in this population and all its subgroups, but the slopes of the relationship between HbA1C and eAG or CGM-measured mean glucose were significantly different. CONCLUSIONS HbA1C-derived eAG values may not accurately reflect CGM-measured mean glucose or MAGE in older adults with diabetes. Wide glucose excursions should be considered and HbA1C should be interpreted cautiously when making treatment changes based on HbA1C.
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Affiliation(s)
- M N Munshi
- Joslin Diabetes Center, United States; Beth Israel Deaconess Medical Center, United States; Harvard Medical School, United States.
| | - A R Segal
- Joslin Diabetes Center, United States; MCPHS University, United States
| | - C Slyne
- Joslin Diabetes Center, United States
| | | | - K M Brooks
- Tufts University School of Medicine, United States
| | - E S Horton
- Joslin Diabetes Center, United States; Harvard Medical School, United States
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Handelsman Y, Bloomgarden ZT, Grunberger G, Umpierrez G, Zimmerman RS, Bailey TS, Blonde L, Bray GA, Cohen AJ, Dagogo-Jack S, Davidson JA, Einhorn D, Ganda OP, Garber AJ, Garvey WT, Henry RR, Hirsch IB, Horton ES, Hurley DL, Jellinger PS, Jovanovič L, Lebovitz HE, LeRoith D, Levy P, McGill JB, Mechanick JI, Mestman JH, Moghissi ES, Orzeck EA, Pessah-Pollack R, Rosenblit PD, Vinik AI, Wyne K, Zangeneh F. American association of clinical endocrinologists and american college of endocrinology - clinical practice guidelines for developing a diabetes mellitus comprehensive care plan - 2015. Endocr Pract 2015; 21 Suppl 1:1-87. [PMID: 25869408 PMCID: PMC4959114 DOI: 10.4158/ep15672.gl] [Citation(s) in RCA: 262] [Impact Index Per Article: 29.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Yehuda Handelsman
- Medical Director & Principal Investigator, Metabolic Institute of America, American College of Endocrinology, Tarzana, California
| | | | - George Grunberger
- Grunberger Diabetes Institute, Internal Medicine and Molecular Medicine & Genetics, Wayne State University School of Medicine, Bloomfield Hills, Michigan
| | - Guillermo Umpierrez
- Endocrinology Section, Grady Health System, Emory University School of Medicine, Atlanta, Georgia
| | | | | | - Lawrence Blonde
- Ochsner Diabetes Clinical Research Unit, Department of Endocrinology, Diabetes and Metabolism, Ochsner Medical Center, New Orleans, Louisiana
| | - George A Bray
- Pennington Center, Louisiana State University, Baton Rouge, Louisiana
| | - A Jay Cohen
- The Endocrine Clinic, P.C., Memphis, Tennessee
| | - Samuel Dagogo-Jack
- Division of Endocrinology, Diabetes and Metabolism, University of Tennessee Health Science Center, Memphis, Tennessee
| | - Jaime A Davidson
- Division of Endocrinology, Touchstone Diabetes Center, Southwestern Medical Center, The University of Texas, Dallas, Texas
| | - Daniel Einhorn
- American College of Endocrinology, American Association of Clinical Endocrinologists, La Jolla, California
| | - Om P Ganda
- Lipid Clinic, Joslin Diabetes Center, Associate Clinical Professor of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Alan J Garber
- Department of Medicine, Biochemistry, and Molecular Biology, and Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas
| | - W Timothy Garvey
- Department of Nutrition Sciences, UAB Diabetes Research Center, University of Alabama at Birmingham, Mountain Brook, Alabama
| | - Robert R Henry
- UCSD, Section of Diabetes, Endocrinology & Metabolism, VA San Diego Healthcare System, San Diego, California
| | - Irl B Hirsch
- University of Washington School of Medicine, Seattle, Washington
| | - Edward S Horton
- Joslin Diabetes Center, Harvard Medical School, Brookline, Massachusetts
| | | | | | - Lois Jovanovič
- Biomolecular Science and Engineering and Chemical Engineering, University of California Santa Barbara, Santa Barbara, California
| | - Harold E Lebovitz
- State University of New York Health Science Center at Brooklyn, Staten Island, New York
| | - Derek LeRoith
- Division of Endocrinology, Diabetes and Bone Diseases, Mount Sinai School of Medicine, New York, New York
| | - Philip Levy
- Banner Good Samaritan Multispecialty Group, University of Arizona College of Medicine, Phoenix, Arizona
| | - Janet B McGill
- Division of Endocrinology, Metabolism & Lipid Research, Washington University, St. Louis, Missouri
| | - Jeffrey I Mechanick
- Metabolic Support, Division of Endocrinology, Diabetes, and Bone Disease, Icahn School of Medicine at Mount Sinai, New York, New York
| | | | - Etie S Moghissi
- University of California Los Angeles, Marina Del Ray, California
| | | | | | - Paul D Rosenblit
- Medicine, Division of Endocrinology, Diabetes, Metabolism, University California Irvine School of Medicine, Irvine, California
| | - Aaron I Vinik
- Medicine/Pathology/Neurobiology, Research & Neuroendocrine Unit, Eastern Virginia Medical Center, The Strelitz Diabetes Center, Norfolk, Virginia
| | - Kathleen Wyne
- Weill Cornell Medical College, Houston Methodist Hospital, Houston, Texas
| | - Farhad Zangeneh
- Endocrine, Diabetes & Osteoporosis Clinic, Sterling, Virginia
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Handelsman Y, Bloomgarden ZT, Grunberger G, Umpierrez G, Zimmerman RS, Bailey TS, Blonde L, Bray GA, Cohen AJ, Dagogo-Jack S, Davidson JA, Einhorn D, Ganda OP, Garber AJ, Garvey WT, Henry RR, Hirsch IB, Horton ES, Hurley DL, Jellinger PS, Jovanovič L, Lebovitz HE, LeRoith D, Levy P, McGill JB, Mechanick JI, Mestman JH, Moghissi ES, Orzeck EA, Pessah-Pollack R, Rosenblit PD, Vinik AI, Wyne K, Zangeneh F. AMERICAN ASSOCIATION OF CLINICAL ENDOCRINOLOGISTS AND AMERICAN COLLEGE OF ENDOCRINOLOGY--CLINICAL PRACTICE GUIDELINES FOR DEVELOPING A DIABETES MELLITUS COMPREHENSIVE CARE PLAN--2015--EXECUTIVE SUMMARY. Endocr Pract 2015; 21:413-437. [PMID: 27408942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
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Espeland MA, Glick HA, Bertoni A, Brancati FL, Bray GA, Clark JM, Curtis JM, Egan C, Evans M, Foreyt JP, Ghazarian S, Gregg EW, Hazuda HP, Hill JO, Hire D, Horton ES, Hubbard VS, Jakicic JM, Jeffery RW, Johnson KC, Kahn SE, Killean T, Kitabchi AE, Knowler WC, Kriska A, Lewis CE, Miller M, Montez MG, Murillo A, Nathan DM, Nyenwe E, Patricio J, Peters AL, Pi-Sunyer X, Pownall H, Redmon JB, Rushing J, Ryan DH, Safford M, Tsai AG, Wadden TA, Wing RR, Yanovski SZ, Zhang P. Impact of an intensive lifestyle intervention on use and cost of medical services among overweight and obese adults with type 2 diabetes: the action for health in diabetes. Diabetes Care 2014; 37:2548-56. [PMID: 25147253 PMCID: PMC4140155 DOI: 10.2337/dc14-0093] [Citation(s) in RCA: 128] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2014] [Accepted: 03/06/2014] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To assess the relative impact of an intensive lifestyle intervention (ILI) on use and costs of health care within the Look AHEAD trial. RESEARCH DESIGN AND METHODS A total of 5,121 overweight or obese adults with type 2 diabetes were randomly assigned to an ILI that promoted weight loss or to a comparison condition of diabetes support and education (DSE). Use and costs of health-care services were recorded across an average of 10 years. RESULTS ILI led to reductions in annual hospitalizations (11%, P = 0.004), hospital days (15%, P = 0.01), and number of medications (6%, P < 0.001), resulting in cost savings for hospitalization (10%, P = 0.04) and medication (7%, P < 0.001). ILI produced a mean relative per-person 10-year cost savings of $5,280 (95% CI 3,385-7,175); however, these were not evident among individuals with a history of cardiovascular disease. CONCLUSIONS Compared with DSE over 10 years, ILI participants had fewer hospitalizations, fewer medications, and lower health-care costs.
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Affiliation(s)
- Mark A Espeland
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Henry A Glick
- Weight and Eating Disorder Program, University of Pennsylvania, Philadelphia, PA
| | - Alain Bertoni
- Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, NC
| | | | - George A Bray
- Pennington Biomedical Research Center, Baton Rouge, LA
| | | | - Jeffrey M Curtis
- Southwest American Indian Center, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ Southwest American Indian Center, National Institute of Diabetes and Digestive and Kidney Diseases, Shiprock, NM
| | - Caitlin Egan
- Weight Control and Diabetes Research Center, Brown Medical School/The Miriam Hospital, Providence, RI
| | - Mary Evans
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD
| | - John P Foreyt
- Department of Medicine, Baylor College of Medicine, Houston, TX
| | | | | | - Helen P Hazuda
- University of Texas Health Science Center at San Antonio, San Antonio, TX
| | - James O Hill
- Anschutz Health and Wellness Center, University of Colorado Health Sciences Center, Aurora, CO
| | - Don Hire
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Edward S Horton
- Department of Clinical Epidemiology, Joslin Diabetes Center, Boston, MA
| | - Van S Hubbard
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD
| | - John M Jakicic
- Diabetes Unit, Department of Health and Physical Activity, University of Pittsburgh, Pittsburgh, PA
| | - Robert W Jeffery
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN
| | - Karen C Johnson
- Department of Preventive Medicine, University of Tennessee Health Sciences Center, Memphis, TN
| | - Steven E Kahn
- Department of Medicine, University of Washington, Seattle, WA
| | - Tina Killean
- Southwest American Indian Center, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ Southwest American Indian Center, National Institute of Diabetes and Digestive and Kidney Diseases, Shiprock, NM
| | - Abbas E Kitabchi
- Department of Preventive Medicine, University of Tennessee Health Sciences Center, Memphis, TN
| | - William C Knowler
- Southwest American Indian Center, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ Southwest American Indian Center, National Institute of Diabetes and Digestive and Kidney Diseases, Shiprock, NM
| | - Andrea Kriska
- Diabetes Unit, Department of Health and Physical Activity, University of Pittsburgh, Pittsburgh, PA
| | - Cora E Lewis
- Preventive Medicine, University of Alabama at Birmingham, Birmingham, AL
| | - Marsha Miller
- Anschutz Health and Wellness Center, University of Colorado Health Sciences Center, Aurora, CO
| | - Maria G Montez
- University of Texas Health Science Center at San Antonio, San Antonio, TX
| | - Anne Murillo
- Department of Medicine, University of Washington, Seattle, WA
| | | | - Ebenezer Nyenwe
- Department of Preventive Medicine, University of Tennessee Health Sciences Center, Memphis, TN
| | - Jennifer Patricio
- Division of and Department of Medicine, St. Luke's-Roosevelt Hospital, New York, NY
| | | | - Xavier Pi-Sunyer
- Division of and Department of Medicine, St. Luke's-Roosevelt Hospital, New York, NY
| | - Henry Pownall
- Department of Medicine, Baylor College of Medicine, Houston, TX
| | - J Bruce Redmon
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN
| | - Julia Rushing
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Donna H Ryan
- Pennington Biomedical Research Center, Baton Rouge, LA
| | - Monika Safford
- Preventive Medicine, University of Alabama at Birmingham, Birmingham, AL
| | - Adam G Tsai
- Division of Internal Medicine, University of Colorado Health Sciences Center, Aurora, CO
| | - Thomas A Wadden
- Weight and Eating Disorder Program, University of Pennsylvania, Philadelphia, PA
| | - Rena R Wing
- Weight Control and Diabetes Research Center, Brown Medical School/The Miriam Hospital, Providence, RI
| | - Susan Z Yanovski
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD
| | - Ping Zhang
- Centers for Disease Control and Prevention, Atlanta, GA
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Rubin RR, Wadden TA, Bahnson JL, Blackburn GL, Brancati FL, Bray GA, Coday M, Crow SJ, Curtis JM, Dutton G, Egan C, Evans M, Ewing L, Faulconbridge L, Foreyt J, Gaussoin SA, Gregg EW, Hazuda HP, Hill JO, Horton ES, Hubbard VS, Jakicic JM, Jeffery RW, Johnson KC, Kahn SE, Knowler WC, Lang W, Lewis CE, Montez MG, Murillo A, Nathan DM, Patricio J, Peters A, Pi-Sunyer X, Pownall H, Rejeski WJ, Rosenthal RH, Ruelas V, Toledo K, Van Dorsten B, Vitolins M, Williamson D, Wing RR, Yanovski SZ, Zhang P. Impact of intensive lifestyle intervention on depression and health-related quality of life in type 2 diabetes: the Look AHEAD Trial. Diabetes Care 2014; 37:1544-53. [PMID: 24855155 PMCID: PMC4030096 DOI: 10.2337/dc13-1928] [Citation(s) in RCA: 146] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE We examined the effects of an intensive lifestyle intervention (ILI), compared with a diabetes support and education (DSE) control intervention, on long-term changes in depression symptoms, antidepressant medication (ADM) use, and health-related quality of life (HRQoL) in overweight/obese individuals with type 2 diabetes. RESEARCH DESIGN AND METHODS Look AHEAD was a multisite randomized controlled trial of 5,145 overweight/obese participants assigned to ILI (designed to produce weight loss) or DSE and followed for a median of 9.6 years. The Beck Depression Inventory (BDI) was administered at baseline, annually at years 1-4, and again at year 8. Mean BDI scores and incidence of BDI scores ≥10, indicative of likely mild or greater depression, were examined. Annually through year 10, participants reported their ADM use and completed the Medical Outcomes Study Short Form 36 (SF-36) questionnaire, which yields physical component summary (PCS) and mental component summary (MCS) scores. RESULTS ILI significantly reduced the incidence of mild or greater depression symptoms (BDI scores ≥10) compared with DSE (hazard ratio [HR] = 0.85; 95% CI 0.75-0.97; P = 0.0145). Although SF-36 PCS scores worsened over time in both groups, ILI participants reported better physical function than DSE throughout the first 8 years (all P values <0.01). There were no significant differences between treatment arms in the proportion of participants who used ADMs or in SF-36 MCS scores. CONCLUSIONS ILI for overweight/obese patients with type 2 diabetes may reduce the risk of developing clinically significant symptoms of depression and preserve physical HRQoL. These findings should be considered when evaluating the potential benefits of ILIs.
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Franks PW, Christophi CA, Jablonski KA, Billings LK, Delahanty LM, Horton ES, Knowler WC, Florez JC. Common variation at PPARGC1A/B and change in body composition and metabolic traits following preventive interventions: the Diabetes Prevention Program. Diabetologia 2014; 57:485-90. [PMID: 24317794 PMCID: PMC4154629 DOI: 10.1007/s00125-013-3133-4] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2013] [Accepted: 11/19/2013] [Indexed: 12/21/2022]
Abstract
AIMS/HYPOTHESIS PPARGC1A and PPARGCB encode transcriptional coactivators that regulate numerous metabolic processes. We tested associations and treatment (i.e. metformin or lifestyle modification) interactions with metabolic traits in the Diabetes Prevention Program, a randomised controlled trial in persons at high risk of type 2 diabetes. METHODS We used Tagger software to select 75 PPARGCA1 and 94 PPARGC1B tag single-nucleotide polymorphisms (SNPs) for analysis. These SNPs were tested for associations with relevant cardiometabolic quantitative traits using generalised linear models. Aggregate genetic effects were tested using the sequence kernel association test. RESULTS In aggregate, PPARGC1A variation was strongly associated with baseline triacylglycerol concentrations (p = 2.9 × 10(-30)), BMI (p = 2.0 × 10(-5)) and visceral adiposity (p = 1.9 × 10(-4)), as well as with changes in triacylglycerol concentrations (p = 1.7 × 10(-5)) and BMI (p = 9.9 × 10(-5)) from baseline to 1 year. PPARGC1B variation was only associated with baseline subcutaneous adiposity (p = 0.01). In individual SNP analyses, Gly482Ser (rs8192678, PPARGC1A) was associated with accumulation of subcutaneous adiposity and worsening insulin resistance at 1 year (both p < 0.05), while rs2970852 (PPARGC1A) modified the effects of metformin on triacylglycerol levels (p(interaction) = 0.04). CONCLUSIONS/INTERPRETATION These findings provide several novel and other confirmatory insights into the role of PPARGC1A variation with respect to diabetes-related metabolic traits. TRIAL REGISTRATION ClinicalTrials.gov NCT00004992.
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Affiliation(s)
- Paul W Franks
- Department of Clinical Science, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden,
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Zanobetti A, Luttmann-Gibson H, Horton ES, Cohen A, Coull BA, Hoffmann B, Schwartz JD, Mittleman MA, Li Y, Stone PH, de Souza C, Lamparello B, Koutrakis P, Gold DR. Brachial artery responses to ambient pollution, temperature, and humidity in people with type 2 diabetes: a repeated-measures study. Environ Health Perspect 2014; 122:242-8. [PMID: 24398072 PMCID: PMC3948021 DOI: 10.1289/ehp.1206136] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2012] [Accepted: 01/03/2014] [Indexed: 05/06/2023]
Abstract
BACKGROUND Extreme weather and air pollution are associated with increased cardiovascular risk in people with diabetes. OBJECTIVES In a population with diabetes, we conducted a novel assessment of vascular brachial artery responses both to ambient pollution and to weather (temperature and water vapor pressure, a measure of humidity). METHODS Sixty-four 49- to 85-year-old Boston residents with type 2 diabetes completed up to five study visits (279 repeated measures). Brachial artery diameter (BAD) was measured by ultrasound before and after brachial artery occlusion [i.e., flow-mediated dilation (FMD)] and before and after nitroglycerin-mediated dilation (NMD). Ambient concentrations of fine particulate mass (PM2.5), black carbon (BC), organic carbon (OC), elemental carbon, particle number, and sulfate were measured at our monitoring site; ambient concentrations of carbon monoxide, nitrogen dioxide, and ozone were obtained from state monitors. Particle exposure in the home and during each trip to the clinic (home/trip exposure) was measured continuously and as a 5-day integrated sample. We used linear models with fixed effects for participants, adjusting for date, season, temperature, and water vapor pressure on the day of each visit, to estimate associations between our outcomes and interquartile range increases in exposure. RESULTS Baseline BAD was negatively associated with particle pollution, including home/trip-integrated BC (-0.02 mm; 95% CI: -0.04, -0.003, for a 0.28 μg/m3 increase in BC), OC (-0.08 mm; 95% CI: -0.14, -0.03, for a 1.61 μg/m3 increase) as well as PM2.5, 5-day average ambient PM2.5, and BC. BAD was positively associated with ambient temperature and water vapor pressure. However, exposures were not consistently associated with FMD or NMD. CONCLUSION Brachial artery diameter, a predictor of cardiovascular risk, decreased in association with particle pollution and increased in association with ambient temperature in our study population of adults with type 2 diabetes. CITATION Zanobetti A, Luttmann-Gibson H, Horton ES, Cohen A, Coull BA, Hoffmann B, Schwartz JD, Mittleman MA, Li Y, Stone PH, de Souza C, Lamparello B, Koutrakis P, Gold DR. 2014. Brachial artery responses to ambient pollution, temperature, and humidity in people with type 2 diabetes: a repeated-measures study. Environ Health Perspect 122:242-248; http://dx.doi.org/10.1289/ehp.1206136.
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Affiliation(s)
- Antonella Zanobetti
- Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA
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Shen L, Shah BR, Reyes EM, Thomas L, Wojdyla D, Diem P, Leiter LA, Charbonnel B, Mareev V, Horton ES, Haffner SM, Soska V, Holman R, Bethel MA, Schaper F, Sun JL, McMurray JJV, Califf RM, Krum H. Role of diuretics, β blockers, and statins in increasing the risk of diabetes in patients with impaired glucose tolerance: reanalysis of data from the NAVIGATOR study. BMJ 2013; 347:f6745. [PMID: 24322398 PMCID: PMC3898638 DOI: 10.1136/bmj.f6745] [Citation(s) in RCA: 65] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
OBJECTIVE To examine the degree to which use of β blockers, statins, and diuretics in patients with impaired glucose tolerance and other cardiovascular risk factors is associated with new onset diabetes. DESIGN Reanalysis of data from the Nateglinide and Valsartan in Impaired Glucose Tolerance Outcomes Research (NAVIGATOR) trial. SETTING NAVIGATOR trial. PARTICIPANTS Patients who at baseline (enrolment) were treatment naïve to β blockers (n=5640), diuretics (n=6346), statins (n=6146), and calcium channel blockers (n=6294). Use of calcium channel blocker was used as a metabolically neutral control. MAIN OUTCOME MEASURES Development of new onset diabetes diagnosed by standard plasma glucose level in all participants and confirmed with glucose tolerance testing within 12 weeks after the increased glucose value was recorded. The relation between each treatment and new onset diabetes was evaluated using marginal structural models for causal inference, to account for time dependent confounding in treatment assignment. RESULTS During the median five years of follow-up, β blockers were started in 915 (16.2%) patients, diuretics in 1316 (20.7%), statins in 1353 (22.0%), and calcium channel blockers in 1171 (18.6%). After adjusting for baseline characteristics and time varying confounders, diuretics and statins were both associated with an increased risk of new onset diabetes (hazard ratio 1.23, 95% confidence interval 1.06 to 1.44, and 1.32, 1.14 to 1.48, respectively), whereas β blockers and calcium channel blockers were not associated with new onset diabetes (1.10, 0.92 to 1.31, and 0.95, 0.79 to 1.13, respectively). CONCLUSIONS Among people with impaired glucose tolerance and other cardiovascular risk factors and with serial glucose measurements, diuretics and statins were associated with an increased risk of new onset diabetes, whereas the effect of β blockers was non-significant. TRIAL REGISTRATION ClinicalTrials.gov NCT00097786.
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Affiliation(s)
- Lan Shen
- Duke Clinical Research Institute, Durham, NC, USA
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Mendivil CO, Robles-Osorio L, Horton ES, Hamdy O, Caballero AE. Young Hispanics at risk of type 2 diabetes display endothelial activation, subclinical inflammation and alterations of coagulation and fibrinolysis. Diabetol Metab Syndr 2013; 5:37. [PMID: 23870459 PMCID: PMC3733973 DOI: 10.1186/1758-5996-5-37] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2013] [Accepted: 07/16/2013] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Hispanics have a high rate of diabetes that exposes them to an increased risk of cardiovascular disease. We hypothesized that many of the pathophysiological mechanisms that cause atherosclerotic disease may be present in young Hispanics who do not have clinical diabetes but are at increased risk of developing it. METHODS We studied 36 young Hispanic adults without diabetes (ages 18-40). Seventeen participants were at increased risk of developing type 2 diabetes given by overweight and a family history of diabetes on one or both parents (at risk group). Nineteen participants with normal body-mass index and no parental history of diabetes constituted the control group. We measured and compared plasma markers of endothelial dysfunction, disturbed coagulation and fibrinolysis, subclinical inflammation and adipose tissue dysfunction in the at risk and control groups. RESULTS Participants at risk of diabetes were more insulin-resistant according to different indicators, and had significantly higher levels of soluble intercellular adhesion molecule-1 (sICAM-1), tissue plasminogen activator (tPA), inhibitor of plasminogen activator-1 (PAi-1), high sensitivity C-reactive protein and free fatty acids, signaling the presence of multiple proatherogenic alterations despite the absence of overt diabetes. Levels of the prothrombotic molecule PAi-1 were most elevated in participants who were not only at risk of diabetes by the study definition, but also abdominally obese. CONCLUSIONS Young adult Hispanics at risk of type 2 diabetes but without overt disease already bear considerably high levels of markers reflecting processes that lead to the development of atherosclerotic cardiovascular disease.
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Affiliation(s)
| | - Ludivina Robles-Osorio
- Joslin Diabetes Center, Clinical Research Center, Harvard Medical School, Boston, MA 02115, USA
| | - Edward S Horton
- Joslin Diabetes Center, Clinical Research Center, Harvard Medical School, Boston, MA 02115, USA
| | - Osama Hamdy
- Joslin Diabetes Center, Clinical Research Center, Harvard Medical School, Boston, MA 02115, USA
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Wing RR, Bolin P, Brancati FL, Bray GA, Clark JM, Coday M, Crow RS, Curtis JM, Egan CM, Espeland MA, Evans M, Foreyt JP, Ghazarian S, Gregg EW, Harrison B, Hazuda HP, Hill JO, Horton ES, Hubbard VS, Jakicic JM, Jeffery RW, Johnson KC, Kahn SE, Kitabchi AE, Knowler WC, Lewis CE, Maschak-Carey BJ, Montez MG, Murillo A, Nathan DM, Patricio J, Peters A, Pi-Sunyer X, Pownall H, Reboussin D, Regensteiner JG, Rickman AD, Ryan DH, Safford M, Wadden TA, Wagenknecht LE, West DS, Williamson DF, Yanovski SZ. Cardiovascular effects of intensive lifestyle intervention in type 2 diabetes. N Engl J Med 2013; 369:145-54. [PMID: 23796131 PMCID: PMC3791615 DOI: 10.1056/nejmoa1212914] [Citation(s) in RCA: 1758] [Impact Index Per Article: 159.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
BACKGROUND Weight loss is recommended for overweight or obese patients with type 2 diabetes on the basis of short-term studies, but long-term effects on cardiovascular disease remain unknown. We examined whether an intensive lifestyle intervention for weight loss would decrease cardiovascular morbidity and mortality among such patients. METHODS In 16 study centers in the United States, we randomly assigned 5145 overweight or obese patients with type 2 diabetes to participate in an intensive lifestyle intervention that promoted weight loss through decreased caloric intake and increased physical activity (intervention group) or to receive diabetes support and education (control group). The primary outcome was a composite of death from cardiovascular causes, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for angina during a maximum follow-up of 13.5 years. RESULTS The trial was stopped early on the basis of a futility analysis when the median follow-up was 9.6 years. Weight loss was greater in the intervention group than in the control group throughout the study (8.6% vs. 0.7% at 1 year; 6.0% vs. 3.5% at study end). The intensive lifestyle intervention also produced greater reductions in glycated hemoglobin and greater initial improvements in fitness and all cardiovascular risk factors, except for low-density-lipoprotein cholesterol levels. The primary outcome occurred in 403 patients in the intervention group and in 418 in the control group (1.83 and 1.92 events per 100 person-years, respectively; hazard ratio in the intervention group, 0.95; 95% confidence interval, 0.83 to 1.09; P=0.51). CONCLUSIONS An intensive lifestyle intervention focusing on weight loss did not reduce the rate of cardiovascular events in overweight or obese adults with type 2 diabetes. (Funded by the National Institutes of Health and others; Look AHEAD ClinicalTrials.gov number, NCT00017953.).
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Wing RR, Bolin P, Brancati FL, Bray GA, Clark JM, Coday M, Crow RS, Curtis JM, Egan CM, Espeland MA, Evans M, Foreyt JP, Ghazarian S, Gregg EW, Harrison B, Hazuda HP, Hill JO, Horton ES, Hubbard VS, Jakicic JM, Jeffery RW, Johnson KC, Kahn SE, Kitabchi AE, Knowler WC, Lewis CE, Maschak-Carey BJ, Montez MG, Murillo A, Nathan DM, Patricio J, Peters A, Pi-Sunyer X, Pownall H, Reboussin D, Regensteiner JG, Rickman AD, Ryan DH, Safford M, Wadden TA, Wagenknecht LE, West DS, Williamson DF, Yanovski SZ. Cardiovascular effects of intensive lifestyle intervention in type 2 diabetes. N Engl J Med 2013. [PMID: 23796131 DOI: 10.1056/nejm] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND Weight loss is recommended for overweight or obese patients with type 2 diabetes on the basis of short-term studies, but long-term effects on cardiovascular disease remain unknown. We examined whether an intensive lifestyle intervention for weight loss would decrease cardiovascular morbidity and mortality among such patients. METHODS In 16 study centers in the United States, we randomly assigned 5145 overweight or obese patients with type 2 diabetes to participate in an intensive lifestyle intervention that promoted weight loss through decreased caloric intake and increased physical activity (intervention group) or to receive diabetes support and education (control group). The primary outcome was a composite of death from cardiovascular causes, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for angina during a maximum follow-up of 13.5 years. RESULTS The trial was stopped early on the basis of a futility analysis when the median follow-up was 9.6 years. Weight loss was greater in the intervention group than in the control group throughout the study (8.6% vs. 0.7% at 1 year; 6.0% vs. 3.5% at study end). The intensive lifestyle intervention also produced greater reductions in glycated hemoglobin and greater initial improvements in fitness and all cardiovascular risk factors, except for low-density-lipoprotein cholesterol levels. The primary outcome occurred in 403 patients in the intervention group and in 418 in the control group (1.83 and 1.92 events per 100 person-years, respectively; hazard ratio in the intervention group, 0.95; 95% confidence interval, 0.83 to 1.09; P=0.51). CONCLUSIONS An intensive lifestyle intervention focusing on weight loss did not reduce the rate of cardiovascular events in overweight or obese adults with type 2 diabetes. (Funded by the National Institutes of Health and others; Look AHEAD ClinicalTrials.gov number, NCT00017953.).
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Espeland MA, Rejeski WJ, West DS, Bray GA, Clark JM, Peters AL, Chen H, Johnson KC, Horton ES, Hazuda HP. Intensive weight loss intervention in older individuals: results from the Action for Health in Diabetes Type 2 diabetes mellitus trial. J Am Geriatr Soc 2013; 61:912-922. [PMID: 23668423 DOI: 10.1111/jgs.12271] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
OBJECTIVES To compare the effects of 4 years of intensive lifestyle intervention on weight, fitness, and cardiovascular disease risk factors in older and younger individuals. DESIGN Randomized controlled clinical trial. SETTING Sixteen U.S. clinical sites. PARTICIPANTS Individuals with type 2 diabetes mellitus: 1,053 aged 65 to 76 and 4,092 aged 45 to 64. INTERVENTIONS An intensive behavioral intervention designed to promote and maintain weight loss through caloric restriction and increased physical activity was compared with diabetes mellitus support and education. MEASUREMENTS Standardized assessments of weight, fitness (based on graded exercise testing), and cardiovascular disease risk factors. RESULTS Over 4 years, older individuals had greater intervention-related mean weight losses (6.2%) than younger participants (5.1%; interaction P = .006) and comparable relative mean increases in fitness (0.56 vs 0.53 metabolic equivalents; interaction P = .72). These benefits were seen consistently across subgroups of older adults formed according to many demographic and health factors. Of a panel of age-related health conditions, only self-reported worsening vision was associated with poorer intervention-related weight loss in older individuals. The intensive lifestyle intervention produced mean increases in high-density lipoprotein cholesterol (2.03 mg/dL; P < .001) and decreases in glycated hemoglobin (0.21%; P < .001) and waist circumference (3.52 cm; P < .001) over 4 years that were at least as large in older as in younger individuals. CONCLUSION Intensive lifestyle intervention targeting weight loss and increased physical activity is effective in overweight and obese older individuals to produce sustained weight loss and improvements in fitness and cardiovascular risk factors.
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Affiliation(s)
- Mark A Espeland
- Department of Biostatistical Sciences, School of Medicine, Wake Forest University, Winston-Salem, North Carolina 27157, USA.
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Herzlinger S, Horton ES. Extraglycemic effects of glp-1-based therapeutics: addressing metabolic and cardiovascular risks associated with type 2 diabetes. Diabetes Res Clin Pract 2013; 100:1-10. [PMID: 23332049 DOI: 10.1016/j.diabres.2012.11.009] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2012] [Accepted: 11/14/2012] [Indexed: 12/25/2022]
Abstract
CONTEXT To examine whether widespread tissue expression of the glucagon-like peptide (GLP)-1 receptor supports the possibility of differential effects of GLP-1-based therapeutics on cardiac function, blood pressure, food intake, gastric emptying, and other regulatory activities. GLP-1 receptor agonists (RAs) have demonstrated pleiotropic effects on overweight/obesity, hypertension, dyslipidemia, and cardiovascular (CV) disease. Food-regulatory effects have been demonstrated in preclinical and clinical trials, including reduced gastric motility and food intake leading to body weight reductions. Native GLP-1 and GLP-1 RAs have demonstrated cardioprotective effects in preclinical models. EVIDENCE ACQUISITION Using PubMed, we performed a search of the recent literature on GLP-1 and GLP-1 RAs. EVIDENCE SYNTHESIS Preliminary clinical data indicate native GLP-1 has beneficial effects on endothelial cell function and vascular inflammation. Native GLP-1 and GLP-1 RAs have demonstrated renoprotective and antihypertensive effects, and reductions in lipid parameters. The GLP-1 RA liraglutide has also demonstrated positive effects on such markers of endothelial dysfunction as tumor necrosis factor-α and plasminogen activator inhibitor-1. CONCLUSION Preliminary data suggest GLP-1 RAs could benefit type 2 diabetes patients at risk for CV comorbidities. Additional studies are needed to confirm the extraglycemic and extrapancreatic effects and determine whether outcomes will translate into beneficial effects for patient care.
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Affiliation(s)
- Susan Herzlinger
- Joslin Diabetes Center, Harvard Medical School, Boston, MA 02215, United States
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Dobs AS, Goldstein BJ, Aschner P, Horton ES, Umpierrez GE, Duran L, Hill JS, Chen Y, Golm GT, Langdon RB, Williams-Herman DE, Kaufman KD, Amatruda JM, Ferreira JCA. Efficacy and safety of sitagliptin added to ongoing metformin and rosiglitazone combination therapy in a randomized placebo-controlled 54-week trial in patients with type 2 diabetes. J Diabetes 2013; 5:68-79. [PMID: 22742523 DOI: 10.1111/j.1753-0407.2012.00223.x] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND New therapeutic approaches are needed to improve glycemic control in patients with type 2 diabetes (T2D), a progressive disorder that often requires combination therapy. The present study assessed the efficacy and safety of sitagliptin as add-on therapy to metformin and rosiglitazone in patients with T2D. METHODS The present study was a randomized double-blind placebo-controlled parallel-group 54-week study conducted at 41 sites across North and South America, Europe, and Asia in 278 patients with HbA1c ranging from ≥7.5% to ≤11.0% despite ongoing combination therapy with metformin (≥1500 mg/day) and rosiglitazone (≥4 mg/day). Patients were randomized (2:1) to receive sitagliptin 100 mg or placebo once daily. The main outcome measure was change from baseline in HbA1c at Week 18. RESULTS Mean baseline HbA1c was 8.8%. The mean placebo-adjusted change from baseline in HbA1c with sitagliptin treatment was -0.7% (P < 0.001) at Week 18 and -0.8% (P < 0.001) at Week 54. There were also significant (P < 0.001) reductions in 2-h post-meal glucose and fasting plasma glucose compared with placebo at Weeks 18 and 54. Significantly higher proportions of sitagliptin- than placebo-treated patients had HbA1c<7.0% at Weeks 18 (22% vs 9%; P = 0.003) and 54 (26% vs 14%; P = 0.015). Changes in body weight and the rates of adverse events overall, hypoglycemia, and gastrointestinal adverse events were similar in the sitagliptin and placebo groups during the 54-week study. CONCLUSIONS In patients with T2D, the addition of sitagliptin for 54 weeks to ongoing therapy with metformin and rosiglitazone improved glycemic control and was generally well tolerated compared with placebo.
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Affiliation(s)
- Adrian S Dobs
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
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