Effect of Social Vulnerability on Efficacy of Bariatric Surgery Versus Medical and Lifestyle Intervention for Type 2 Diabetes: A

Effect of Social Vulnerability on Efficacy of Bariatric Surgery Versus Medical and Lifestyle Intervention for Type 2 Diabetes: Analysis of the ARMMS-T2D Consortium of Randomized Trials - PMC
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. Author manuscript; available in PMC: 2026 Mar 5.
Published in final edited form as:
Ann Intern Med. 2026 Jan 20;179(3):353–361. doi:
10.7326/ANNALS-24-01882
Effect of Social Vulnerability on Efficacy of Bariatric Surgery Versus Medical and Lifestyle Intervention for Type 2 Diabetes: Analysis of the ARMMS-T2D Consortium of Randomized Trials
Mary Elizabeth Patti
Mary Elizabeth Patti
MD
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
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Mary Elizabeth Patti
Bo Hu
Bo Hu
PhD
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
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Bo Hu
Sarah Kirschling
Sarah Kirschling
MS
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
Find articles by
Sarah Kirschling
Hanna J Wang
Hanna J Wang
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
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Hanna J Wang
Kathleen Foster
Kathleen Foster
BS, RN
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
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Kathleen Foster
Yael Sarig
Yael Sarig
BA
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
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Yael Sarig
Donald C Simonson
Donald C Simonson
MD, MPH, ScD
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
Find articles by
Donald C Simonson
Danielle Wolfs
Danielle Wolfs
MS
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
Find articles by
Danielle Wolfs
David Arterburn
David Arterburn
MD, MPH
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
Find articles by
David Arterburn
Matthew J O’Brien
Matthew J O’Brien
MD, MSc
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
Find articles by
Matthew J O’Brien
Ashley H Vernon
Ashley H Vernon
MD
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
Find articles by
Ashley H Vernon
John M Jakicic
John M Jakicic
PhD
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
Find articles by
John M Jakicic
Lori Laffel
Lori Laffel
MD, MPH
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
Find articles by
Lori Laffel
Sando Ojukwu
Sando Ojukwu
MD, MPH
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
Find articles by
Sando Ojukwu
Sangeeta R Kashyap
Sangeeta R Kashyap
MD
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
Find articles by
Sangeeta R Kashyap
Ali Aminian
Ali Aminian
MD
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
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Ali Aminian
Philip R Schauer
Philip R Schauer
MD
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
Find articles by
Philip R Schauer
David E Cummings
David E Cummings
MD
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
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David E Cummings
William F Gourash
William F Gourash
PhD, CRNP, RN
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
Find articles by
William F Gourash
Anita Courcoulas
Anita Courcoulas
MD, MPH
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
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Anita Courcoulas
John P Kirwan
John P Kirwan
PhD
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
Find articles by
John P Kirwan
Research and Clinic Division, Joslin Diabetes Center and Harvard Medical School, Boston, Massachusetts (M.E.P., H.J.W., K.F., Y.S., D.W., L.L., S.O.); Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (B.H., S.K.); Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts (D.C.S., A.H.V.); Kaiser Permanente Washington Health Research Institute, Seattle, Washington (D.A.); Division of General Internal Medicine and Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.J.O.); Department of Internal Medicine, Division of Physical Activity and Weight Management, University of Kansas Medical Center, Kansas City, Kansas (J.M.J.); Weill Cornell Medicine-New York Presbyterian, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York, New York (S.R.K.); Bariatric and Metabolic Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio (A.A.); Metamor Institute, Pennington Biomedical Research Center, Baton Rouge, Louisiana (P.R.S., J.P.K.); Department of Medicine, University of Washington, and VA Puget Sound Health Care System, Seattle, Washington (D.E.C.); and Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (W.F.G., A.C.).
Author Contributions:
Conception and design: M.E. Patti, K. Foster, D.C. Simonson, M.J. O’Brien, P.R. Schauer, J.P. Kirwan.
Analysis and interpretation of the data: M.E. Patti, B. Hu, S. Kirschling, H.J. Wang, Y. Sarig, D.C. Simonson, M.J. O’Brien, P.R. Schauer, D.E. Cummings, J.P. Kirwan.
Drafting of the article: M.E. Patti, H.J. Wang, D.C. Simonson, D. Arterburn, S.R. Kashyap, D.E. Cummings, J.P. Kirwan.
Critical revision for important intellectual content: M.E. Patti, H.J. Wang, D.C. Simonson, D. Arterburn, M.J. O’Brien, L. Laffel, S.R. Kashyap, A. Aminian, P.R. Schauer, D.E. Cummings, W.F. Gourash, A. Courcoulas, J.P. Kirwan.
Final approval of the article: M.E. Patti, B. Hu, S. Kirschling, H.J. Wang, K. Foster, Y. Sarig, D.C. Simonson, D. Wolfs, D. Arterburn, M.J. O’Brien, A.H. Vernon, J.M. Jakicic, L. Laffel, S. Ojukwu, S.R. Kashyap, A. Aminian, P.R. Schauer, D.E. Cummings, W.F. Gourash, A. Courcoulas, J.P. Kirwan.
Provision of study materials or patients: M.E. Patti, A.H. Vernon, S.R. Kashyap, A. Aminian, J.P. Kirwan.
Statistical expertise: B. Hu.
Obtaining of funding: M.E. Patti, D.C. Simonson, D. Arterburn, S.R. Kashyap, P.R. Schauer, D.E. Cummings, A. Courcoulas, J.P. Kirwan.
Administrative, technical, or logistic support: M.E. Patti, K. Foster, D. Wolfs, D. Arterburn, A.H. Vernon, S. Ojukwu, S.R. Kashyap, A. Aminian, J.P. Kirwan.
Collection and assembly of data: M.E. Patti, K. Foster, Y. Sarig, D.C. Simonson, D. Wolfs, S.R. Kashyap, A. Aminian, D.E. Cummings, W.F. Gourash, A. Courcoulas, J.P. Kirwan.
Author contributions are available at
Annals.org
Corresponding Author:
Mary Elizabeth Patti, MD, Research Division, Joslin Diabetes Center, 1 Joslin Place, Boston, MA 02215;
mary.elizabeth.patti@joslin.harvard.edu
Issue date 2026 Mar.
PMC Copyright notice
PMCID: PMC12958453  NIHMSID: NIHMS2147031  PMID:
41554124
The publisher's version of this article is available at
Ann Intern Med
Abstract
Background:
Social determinants of health (SDOH) can affect metabolic health.
Objective:
To determine the effect of social vulnerability on the comparative effectiveness of metabolic bariatric surgery or medical and lifestyle intervention on glycemia and weight outcomes in people with type 2 diabetes (T2D).
Design:
Analysis of the effect modification of baseline Area Deprivation Index (ADI; a metric of social vulnerability) on longitudinal outcomes between randomized treatment groups using linear mixed-effects models. (
ClinicalTrials.gov
NCT02328599
Setting:
4 U.S. academic centers.
Participants:
258 participants with T2D enrolled in 4 randomized controlled trials of surgical versus medical management and a longitudinal observational follow-up study.
Measurements:
ADI linked to ZIP code data at randomization; weight loss and hemoglobin A
1c
(HbA
1c
) level at the end of the active intervention period (7 to 12 years).
Results:
Baseline characteristics were well balanced between the surgical and medical therapy groups after adjustment for study site and stratification by high versus low ADI. Surgery was more effective than medical therapy in reducing HbA
1c
level among persons with high ADI (net difference, −1.29% [95% CI, −1.95% to −0.63%]) and those with low ADI (net difference, −0.95% [CI, −1.29% to −0.62%]). Surgery was also more effective than medical therapy at producing weight loss across ADIs, with respective net differences of −10.6% (CI, −15.2% to −5.9%) for high ADI and −13.3% (CI, −15.7% to −10.9%) for low ADI. The interaction between ADI and intervention group was not significant for either HbA1c (
= 0.37) or weight loss (
= 0.31).
Limitations:
Small sample size; parent trials were not designed to address effect modification by ADI.
Conclusion:
Surgery was superior to medical therapy for people with T2D regardless of social deprivation. This study did not detect statistically significant differences in the comparative advantage of surgery over medical therapy by ADI.
Primary Funding Source:
National Institutes of Health.
Social determinants of health (SDOH), defined by the World Health Organization as the nonmedical factors that influence health outcomes (
), are major contributors to the prevalence and severity of chronic disease (
). It has been estimated that 50% to 60% of health outcomes are related to social, environmental, and behavioral factors independent of genetics and medical care (
). These relationships are well established in type 2 diabetes (T2D) (
) and obesity (
). High social vulnerability is associated with higher prevalence of T2D, poor glycemic control (
), elevated body mass index (BMI), and obesity-associated comorbidities such as cardiovascular disease (
) and premature mortality (
10
). The intersection of SDOH with obesity may particularly affect people with both T2D and obesity (
11
14
).
Current approaches targeting glycemic control and weight loss in patients with T2D include medical and lifestyle management, which involves medications and lifestyle interventions, or metabolic bariatric surgery, such as sleeve gastrectomy (SG), Roux-en-Y gastric bypass (RYGB), or adjustable gastric banding (AGB) (
15
). Many studies have demonstrated the efficacy of surgery to achieve both metabolic control and weight loss (
16
21
), reduce diabetes-associated complications (
19
25
), and reduce overall mortality (
20
23
), with superior efficacy versus medical therapy seen in both randomized and observational studies.
Although adverse SDOH are recognized to contribute to health measures of both T2D and obesity, whether SDOH influence the long-term comparative efficacy of medical versus surgical therapeutic approaches for T2D is uncertain. Within a nonrandomized study or general clinical care, baseline differences in patients who choose surgery versus medical therapy may contribute to outcome differences. To test social vulnerability as an effect modifier within a randomized clinical trial setting, we analyzed data from the Alliance of Randomized Trials of Medicine vs Metabolic Surgery in Type 2 Diabetes (ARMMS-T2D) consortium (
19
). We recently reported that people randomly assigned to metabolic bariatric surgery had greater hemoglobin A
1c
(HbA
1c
) reductions, weight loss, and diabetes remission; lower use of antidiabetes medications; and reductions in several cardiovascular risk factors (
19
). Due to its framework of randomization, large sample size, and longitudinal follow-up, the ARMMS-T2D consortium provides a unique opportunity to study the independent influence of social vulnerability on the relative efficacy of surgery versus medical therapy on T2D outcomes. We hypothesized that patients with T2D who had high social vulnerability would have reduced response to diabetes and obesity-targeted therapy but would experience greater metabolic improvement after randomization to surgery. We tested these hypotheses by assessing the Area Deprivation Index (ADI), an address-based metric of neighborhood socioeconomic deprivation and social vulnerability, at baseline and the end of the study.
Methods
Written informed consent was obtained from participants at each center for the parent ARMMS-T2D trial, and the study was registered at
ClinicalTrials.gov
NCT02328599
). The Joslin Diabetes Center Committee on Human Studies approved this ancillary study. Electronically dated and signed informed consent was obtained from all participants before participation in the end-of-study survey.
ARMMS-T2D and Intervention Groups
ARMMS-T2D is a pooled longitudinal follow-up study of participants with T2D initially enrolled in 4 randomized clinical trials. Details of the study methods and results were published previously (
19
26
), and the study protocol is available at
Annals.org
. In brief, people with T2D were randomly assigned in 1 of the 4 parent trials (STAMPEDE [Cleveland, Ohio], SLIMM-T2D [Boston, Massachusetts], TRIABETES [Pittsburgh, Pennsylvania], or CROSSROADS [Seattle, Washington]) to undergo either medical and lifestyle management or 1 of 3 metabolic bariatric surgical procedures (RYGB, SG, or AGB) from 2007 to 2013. Participants self-identified their race and ethnicity based on fixed categories. Study eligibility criteria included diagnosis of T2D, BMI of 27 to 45 kg/m
, and age 18 to 65 years.
Randomization protocol and operation type options differed by site, as described previously (
27
) and summarized in
Supplement Table 1
(available at
Annals.org
). In brief, 1 site (CROSSROADS) randomly assigned participants in a 1:1 ratio to surgery (RYGB) versus medical management, whereas the other 3 sites (SLIMM-T2D, STAMPEDE, and TRIABETES) offered more than 1 surgical option. In SLIMM-T2D, participants chose their preferred surgical procedure (RYGB or AGB) and were then randomly assigned in a 1:1 allocation to that surgery versus medical therapy. The STAMPEDE trial randomly assigned participants in a 1:1:1 ratio to RYGB, SG, or medical therapy, and the TRIABETES trial assigned participants in a 1:1:1 ratio to RYGB, AGB, or medical therapy (
27
). This resulted in a larger number of participants in the ARMMS-T2D study who had been randomly assigned to surgery (
= 166) versus medical therapy (
= 96). Patients who underwent surgery had standard postoperative care, including guidance on diet and activity, at least monthly in the first year.
All medical and lifestyle interventions were based on the Diabetes Prevention Program (
28
) and Look AHEAD (
29
) interventions and included individualized nutrition counseling, instruction on exercise and self-monitoring of glucose, and behavioral education and counseling for at least 1 year after randomization (details are provided in
Supplement Table 1
). Although these interventions were intended to promote a healthy lifestyle and modest weight loss, specific pharmacologic therapy for weight loss was not part of the diabetes-focused medical intervention at the time of study initiation. After year 1, weight loss therapy could have been prescribed as part of usual care, and incretin-based agents were increasingly used for glycemic control with benefits for weight loss (37% of participants in the medical therapy groups and 27% in the surgical groups were receiving incretin-based therapy at the end of the study).
Participants who received their initially allocated intervention in one of the parent trials and provided consent for longitudinal follow-up were enrolled in the ARMMS-T2D study. Participants were followed for 7 to 12 years in annual visits (window from randomization date encompassing ±6 months) at each site, during which HbA
1c
, weight, diabetes medication use (including incretin-based therapy but not nonincretin weight loss medications), and complications were assessed (
19
27
). Observational follow-up within the ARMMS-T2D study was conducted through July 2022. Baseline HbA
1c
measurements were performed at each center, with standardization against a universal calibrator to reduce assay variability as per the National Glycohemoglobin Standardization Program. Thereafter, blood samples were analyzed using a central laboratory (Northwest Lipid Research Laboratories at the University of Washington until May 2020, and Advanced Research and Diagnostic Laboratory at the University of Minnesota thereafter). Wall-mounted stadiometers and calibrated scales were used for measurement of height and weight at each center.
An intention-to-treat analysis related to group assignment was performed. The primary outcome of the ARMMS-T2D trial was the between-group difference in the absolute change in HbA
1c
level and between-group differences in the relative change in BMI from baseline to 7 years, and up to 12 years for participants who reached that follow-up point before study closure. A study flow diagram is provided in
Figure 1
Figure 1.
Open in a new tab
Study flow diagram.
ADI = Area Deprivation Index; AGB = adjustable gastric banding; ARMMS-T2D = Alliance of Randomized Trials of Medicine vs Metabolic Surgery in Type 2 Diabetes; RYGB = Roux-en-Y gastric bypass; SG = sleeve gastrectomy.
* Three participants were successfully re-recruited.
Assessment of Social Vulnerability
To assess the impact of social vulnerability as an effect modifier for the comparative effectiveness of surgical versus medical weight loss interventions, we used addresses provided by participants before randomization and at completion of the ARMMS-T2D study to obtain a metric of social vulnerability based on geographic location and adjusted for year. Baseline addresses were collected during enrollment into the initial ARMMS-T2D clinical trials, and current addresses were extracted from surveys conducted at study completion.
Address information was processed using the Census Geocoder tool to obtain 12-digit Federal Information Processing Standards (FIPS) codes, which are directly linked to census blocks that uniquely identify geographic locations in the United States. Baseline addresses were geocoded to the 2010 FIPS as this is the oldest data benchmark available on the Census Geocoder tool; end-of-study addresses were geocoded to the most recent FIPS. The FIPS codes were then used to obtain values for the ADI, a defined measure of social vulnerability that is refined to the census block level and a composite of 17 variables based on the domains of education, income and employment, housing, and household characteristics derived from U.S. Census data (
30
). The ADI is a continuous variable that ranges from 1 to 100, with higher ADI indicating greater social vulnerability. ADI data were downloaded from the Neighborhood Atlas (
), a University of Wisconsin–Madison website that publishes ADI data sets. Baseline FIPS codes, using Census Geocoder 2010 benchmark data, were matched to the 2015 ADI (
31
), the oldest ADI database available (based on 2011–2015 American Community Survey [ACS] 5-year data). End-of-study FIPS data were derived from the most up-to-date Census Geocoder data at the time of geocoding and matched to the most current ADI data available (based on 2015–2019 ACS 5-year data [
32
]). Seven participants were excluded: 5 due to missing information on their baseline address in the Census Geocoder, 1 with a baseline address that was contained within group quarters (not assigned an ADI value due to large populations) (
33
), and 1 due to missing information about their primary address.
Outcome Measures
Our co–primary outcomes were glycemia, as measured by absolute change in HbA
1c
level, and weight loss, as measured by percentage change in BMI. These were measured at annual study visits at each consortium site using standardized protocols as described earlier and reported previously (
19
).
Statistical Analysis
Participant characteristics were summarized as appropriate descriptive statistics. The
test, the Wilcoxon rank-sum test, or the
test was used to compare characteristics between groups.
The ADI was considered as both a continuous variable and a dichotomized variable in separate analyses; for the dichotomized analysis, the third quartile (ADI >75) was used as a threshold for assignment to high ADI groups.
To test the comparative effectiveness of surgical versus medical intervention and its effect modification by ADI, linear mixed-effects models included intervention group, baseline ADI, and HbA
1c
level or BMI as covariates and an interaction term for intervention group and ADI category. For subject
and visit
= 1,…,12, the mixed-effects model for change in HbA
1c
level is expressed as
it
ADI
ADI
it
where Y
it
represents the absolute change in HbA
1c
level (HbA
1c
at visit
minus baseline HbA
1c
), G
represents the group (medical vs. surgical), ADI
represents ADI status (high vs. low), X
is a vector of baseline HbA
1c
and site, b
is a Gaussian random intercept at the subject level with mean 0, and e
it
is the residual that is independent of b
, and
are unknown parameters. The model for BMI change has the same format, with Y
it
being the percentage change in BMI and baseline HbA
1c
replaced by baseline BMI. Because the 4 trials began at different times, follow-up durations varied administratively. Missingness from shorter follow-up, death, or loss to follow-up was assumed to be at random (
34
35
).
Statistical significance was established at a 2-sided
value less than 0.05. All analyses were conducted using RStudio (Posit Software).
Role of the Funding Source
ARMMS-T2D is supported by the National Institutes of Health (U01 DK114156). The sponsor requested proposals for a randomized trial comparing surgery versus medical therapy for T2D but had no role in the design of the original trials. The National Institute of Diabetes and Digestive and Kidney Diseases was not involved in data collection but was involved in discussion of the planning of this ancillary study.
Results
Study Sample Characteristics
Of 262 eligible participants from the 4 parent trials, 258 were available for analysis of social vulnerability, as measured by ADI, at study entry (
Figure 1
). Demographic and metabolic information at study entry for this cohort (164 in the surgery group and 94 in the medical therapy group), stratified by baseline ADI and randomization group, is shown in
Table 1
Table 1.
Baseline Characteristics of Participants, Overall and Stratified by Randomization and ADI Group
Characteristic
Overall (
= 258)
ADI >75
ADI ≤75
Medical and Lifestyle Intervention (
= 16)
Metabolic Bariatric Surgery (
= 39)
Medical and Lifestyle Intervention (
= 76)
Metabolic Bariatric Surgery (
= 120)
Mean age (SD),
49.84 (8.35)
49.90 (8.11)
46.10 (9.25)
51.86 (6.58)
50.04 (8.63)
Female,
n (%)
176 (68)
14 (88)
33 (85)
44 (58)
81 (68)
Race,
n (%)
Black
80 (31)
9 (56)
23 (59)
25 (33)
20 (17)
Other
5 (1.9)
0 (0)
0 (0)
3 (3.9)
2 (1.7)
White
173 (67)
7 (44)
16 (41)
48 (63)
98 (82)
Mean BMI (SD),
kg/m
36.43 (3.51)
36.94 (3.19)
37.43 (3.38)
36.07 (3.51)
36.22 (3.61)
Mean weight (SD),
kg
104.26 (15.39)
103.07 (11.49)
102.75 (13.20)
106.30 (16.27)
103.35 (16.11)
Mean waist circumference (SD),
cm
114.55 (9.81)
114.71 (7.40)
115.59 (8.68)
113.67 (10.06)
114.65 (10.44)
Mean diabetes duration (SD),
8.45 (5.38)
8.00 (5.35)
7.92 (4.59)
8.95 (5.28)
8.45 (5.76)
Insulin dependence,
n (%)
116 (45)
7 (44)
20 (51)
27 (36)
61 (51)
Mean HbA
1c
level (SD),
8.51 (1.52)
8.36 (0.98)
9.08 (1.79)
8.14 (1.21)
8.56 (1.62)
Mean glucose level (SD),
mg/dL
165.39 (62.80)
154.94 (44.33)
178.95 (76.15)
154.84 (51.14)
167.54 (66.98)
Mean systolic blood pressure (SD),
mm Hg
132.64 (16.87)
132.88 (19.97)
138.23 (18.70)
129.20 (14.70)
133.12 (16.73)
Mean diastolic blood pressure (SD),
mm Hg
80.08 (9.88)
78.19 (10.32)
82.28 (11.48)
79.87 (9.68)
79.78 (9.60)
Mean total cholesterol level (SD),
mg/dL
177.32 (42.72)
177.94 (31.26)
195.85 (41.81)
171.44 (40.51)
174.70 (45.20)
Mean HDL cholesterol level (SD),
mg/dL
43.31 (12.23)
49.56 (13.80)
47.03 (11.44)
43.23 (12.85)
41.10 (10.91)
Mean LDL cholesterol level (SD),
mg/dL
99.17 (33.74)
97.38 (29.02)
117.03 (37.47)
96.24 (33.84)
95.26 (31.85)
Mean triglyceride level (SD),
mg/dL
180.71 (138.46)
155.13 (89.27)
161.74 (88.01)
162.16 (94.10)
200.45 (173.94)
Median albumin-creatinine ratio (IQR)
7.00 (4.00–21.75)
6.00 (4.00–12.00)
7.00 (4.00–17.00)
6.00 (3.00–16.00)
9.00 (4.00–23.50)
Mean ADI (SD)
47.27 (29.12)
87.75 (7.82)
89.33 (7.05)
31.00 (19.70)
38.51 (21.60)
Open in a new tab
ADI = Area Deprivation Index; BMI = body mass index; HbA
1c
= hemoglobin A
1c
; HDL = high-density lipoprotein; LDL = low-density lipoprotein.
To convert glucose values to millimoles per liter, multiply by 0.0555.
To convert cholesterol values to millimoles per liter, multiply by 0.0259.
To convert triglyceride values to millimoles per liter, multiply by 0.0113.
Seven patients were missing baseline ADI.
ADIs were higher in the surgery group at both baseline (
= 0.008) and the end of the study (
= 0.003), reflecting higher values at the Cleveland and Pittsburgh sites and the larger number of surgical participants from these sites due to the 2:1 treatment allocation in favor of surgery (2 surgical groups vs. 1 medical group) (
Supplement Figure
, available at
Annals.org
). Differences in ADI between surgery and medical therapy did not remain after adjustment for study site.
Stratification of the entire study population (both randomization groups) according to baseline ADI (>75 [high] vs. ≤75 [low]) (
Table 1
Supplement Table 2
, available at
Annals.org
) revealed that participants with high social vulnerability were younger; were more likely to be female; were more likely to be Black; and had higher BMI, HbA
1c
level, systolic blood pressure, and total, high-density lipoprotein, and low-density lipoprotein cholesterol levels. Baseline ADI was positively correlated with baseline HbA
1c
level (
= 0.20;
= 0.001) but not with BMI (
= 0.11;
= 0.080).
Baseline ADI and Effectiveness of Surgical vs. Medical and Lifestyle Intervention on Glycemic Outcomes
Table 2
and
Figure 2
top
) show the comparative effectiveness of surgery versus medical and lifestyle interventions, stratified by baseline ADI, on glycemic control over the 12 years of the study. Consistent with the primary results of the parent trials (
19
), reduction in HbA
1c
was greater for the surgical group than the medical group. Although the estimate of the surgical group’s net advantage was numerically higher among those with high versus low ADI, the CIs were wide and the interaction effect (the difference of the differences between surgery and medical therapy in the high and low ADI groups) was not statistically significant over the 12 years of the study (interaction: −0.34% [95% CI, −1.08% to 0.40%];
= 0.37). We note similar patterns at 1 year after the intervention (
Supplement Table 3
, available at
Annals.org
).
Table 2.
Longitudinal Relationship Between Baseline ADI Category and Absolute Change in HbA1c Level or Percentage Change in BMI
Variable
HbA
1c
Level
BMI
Absolute Change (95% CI), %
Value
Relative Change (95% CI), %
Value
Low ADI (≤75)
Medical and lifestyle intervention
−0.50 (−0.79 to −0.22)
<0.001
−8.6 (−10.6 to −6.7)
<0.001
Metabolic bariatric surgery
−1.46 (−1.70 to −1.21)
<0.001
−21.8 (−23.6 to −20.2)
<0.001
Difference (surgery – medical)
−0.95 (−1.29 to −0.62)
<0.001
− 13.3 (−15.7 to −10.9)
<0.001
High ADI (
75)
Medical and lifestyle intervention
0.06 (−0.53 to 0.65)
0.84
−7.8 (−12.0 to −3.7)
<0.001
Metabolic bariatric surgery
−1.23 (−1.63 to −0.83)
<0.001
− 18.4 (−21.3 to −15.5)
<0.001
Difference (surgery – medical)
−1.29 (−1.95 to −0.63)
<0.001
−10.6 (−15.2 to −5.9)
<0.001
Interaction (difference in high ADI group – difference in low ADI group)
−0.34 (−1.08 to 0.40)
0.37
2.7 (−2.5 to 7.9)
0.31
Open in a new tab
ADI = Area Deprivation Index; BMI = body mass index; HbA
1c
= hemoglobin A
1c
Covariates include site and baseline HbA
1c
level or BMI. Estimates from a linear mixed-effects model are presented. A negative estimate indicates a decrease in HbA
1c
level or BMI.
Figure 2.
Open in a new tab
Longitudinal absolute change in HbA
1c
level
(top
) and longitudinal percentage change in weight (
bottom
), stratified by ADI and randomization group.
Adjusted estimates from the linear mixed-effects models are shown along with 95% CIs. The numbers below the graphs indicate the number of participants in each group who were available for analysis at that time point. The brackets indicate comparative outcome differences between the medical and surgical groups for the high ADI group and the low ADI group; interaction differences were not significant. Results of statistical comparisons between groups are provided in
Table 2
. ADI = Area Deprivation Index; BMI = body mass index; HbA
1c
hemoglobin A
1c
; MED = medical and lifestyle intervention group; SURG = metabolic bariatric surgery group.
We similarly assessed outcomes using ADI as a continuous variable (
Supplement Table 4
, available at
Annals.org
). Higher ADI was associated with significantly less decrease in HbA
1c
in the medical and lifestyle intervention group (
= 0.038); differences between the surgical and medical groups, stratified by ADI, were not significant in a test for interaction (
= 0.192).
Rates of remission and insulin use, or the number of medication classes prescribed, differed significantly between the high and low ADI groups, with estimates numerically favoring participants with low ADI (
Supplement Table 5
, available at
Annals.org
). The interaction between ADI and treatment group for incretin use was statistically significant (
< 0.001), with lower probability of use of incretins in the high ADI medical group and higher probability in the high ADI surgical group.
Association With Weight Loss Outcomes
Stratification by both baseline ADI and randomization group (
Figure 2
bottom
]) showed greater weight loss in participants randomly assigned to surgery versus medical therapy in both the high and low vulnerability groups, although the interaction was not statistically significant. The difference in the percentage change in BMI between the surgical and medical groups was −10.6% (CI, −15.2% to −5.9%) in the high ADI group compared with −13.3% (CI, −15.7% to −10.9%) in the low ADI group over 12 years of follow-up. The difference in the differences (high ADI – low ADI) was 2.7% (CI, −2.5% to 7.9%;
= 0.31). The pattern was similar at 1 year (
Supplement Table 3
).
Likewise, assessment of baseline ADI as a continuous variable revealed that while higher ADI was significantly associated with less weight loss in the overall cohort, there was no significant interaction between group and ADI for weight loss outcomes (
Supplement Table 4
).
DISCUSSION
Using pooled results of 4 randomized controlled trials comparing metabolic bariatric surgery versus medical interventions in participants with moderate to severe obesity, we explored the influence of SDOH on the comparative efficacy of surgical versus medical therapy. We found that surgery was more effective than medical therapy for both glycemic and weight loss outcomes, regardless of participants’ social vulnerability as determined by ZIP code–linked ADI at study entry. Moreover, the relative comparative advantage of surgery over medical therapy did not definitively differ by ADI.
Metrics of social vulnerability have previously been shown to moderate the effect of nonsurgical interventions on weight loss and diabetes care and prevention. Within a cluster randomized trial, an intensive behavioral weight loss intervention yielded more weight loss than usual care, but patients with food insecurity had a 2.5-kg lower weight loss than patients with food security (
14
36
). Likewise, in a nonrandomized intervention designed to improve access to food resources for patients with T2D, those with poor glycemic control at baseline had greater improvement in HbA
1c
, but this improvement was not seen in those with food insecurity (
37
). In the diabetes-focused Diabetes Prevention Program, there was a lower magnitude of diabetes risk reduction with either lifestyle intervention or metformin in participants with lower educational attainment, with a statistically significant education-by-treatment interaction (
38
).
Prior investigations analyzing the relationship between SDOH and longitudinal outcomes of metabolic bariatric surgery in nonrandomized populations have yielded more mixed conclusions. A retrospective study using a sample of 13 275 patients who underwent gastric bypass from the Scandinavian Obesity Surgery Registry found that first-generation immigrants and patients residing in larger towns had lower weight loss than other groups, but associations with other factors, including income, education, and employment type, were weaker (
39
). In contrast, other studies have found no major effect of SDOH on surgical weight loss. There was no significant effect of insurance type (public Medicaid vs. non-Medicaid), ADI, or neighborhood urbanicity or walkability on weight loss in the University of Wisconsin bariatric surgery registry database (
40
41
). Similarly, food accessibility and security were not associated with surgical weight loss (
42
43
). These studies are limited in that weight loss associations were cross-sectional and were analyzed after a relatively short postoperative period, and the long-term effect on diabetes control was not assessed. Furthermore, the nonrandomized design could have introduced bias related to the effect of SDOH factors on patient selection and/or actual completion of surgical therapy (
44
).
Our randomized study allowed us to explore the influence of social deprivation on the comparative efficacy of surgical versus medical therapy. The comparative advantage of surgery over medical therapy was seen in populations with both high and low social deprivation over the long term. Notably, weight loss medications were not a component of medical therapy at study onset. Although incretin-based therapies for diabetes were implemented widely in both the surgical and medical groups during the course of the study as part of usual care, highly effective weight loss medications were not yet available to our participants during the early follow-up period of our study; thus, our findings related to the medical therapy group may not be generalizable to interventions where pharmacotherapy for weight loss was a core component.
Although our measure of social vulnerability did not clearly affect the comparative advantage of surgery over medical intervention, social vulnerability metrics were associated with less reduction in BMI over the course of the study (
Supplement Table 4
). These data are consistent with reduced weight loss in people with high social vulnerability in some observational studies and in the cluster randomized trial cited earlier (
14
36
). The potential role of food insecurity, lower health literacy, reduced medication access and adherence, and reduced physical activity as mediators of these relationships will need to be assessed in future studies (
11
45
47
).
Our study has both strengths and limitations. Our longitudinal analysis utilized baseline social vulnerability data from the randomized study population in the ARMMS-T2D clinical trial. A key strength of this approach is that analysis of baseline vulnerability on longitudinal outcomes within a randomized study minimizes potential bias of these variables on patient-specific choice of therapy. However, given that analysis of social deprivation was not a primary outcome of ARMMS-T2D, the power to detect differences in outcomes as a function of baseline vulnerability was limited. Moreover, the ARMMS-T2D study did not include specific weight loss pharmacotherapy (beyond nutrition and physical activity) as a core element of medical therapy. Our study population may not be fully representative of patients from historically disadvantaged backgrounds who may be less likely to volunteer for medical research. Enrollment was also restricted to patients residing in the Northeast, Midwest, and Pacific Northwest regions of the United States, which tend to be more affluent on average (
48
). Finally, we relied on ADI as a metric of neighborhood-level social deprivation but recognize that no single available metric adequately captures the complete effect of social vulnerability for an individual.
In summary, the long-term efficacy of metabolic bariatric surgery for glycemic control and weight loss was superior to medical and lifestyle intervention for people with T2D, regardless of social vulnerability at randomization. We did not detect statistically significant differences in the comparative advantage of surgery over medical therapy by ADI. However, associations were stronger for the medical treatment group, suggesting that social vulnerability may modify outcomes, particularly when the ongoing need for medical therapy for diabetes and obesity is greater.
Supplementary Material
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See also:
Web-Only
Supplemental material
Acknowledgment:
The authors thank all of the participants and staff who contributed to this research study.
Grant Support:
ARMMS-T2D was supported by cooperative agreement U01 DK114156 from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). Dr. Patti acknowledges support from the Diabetes Research Center at Joslin Diabetes Center (P30-DK036836). Dr. O’Brien acknowledges support from the Chicago Center for Diabetes Translation Research (P30-DK092949). Dr. Kirwan was supported by the Louisiana Clinical and Translational Science Center (U54-GM104940).
Footnotes
Disclosures:
Disclosure forms are available with the article online.
Data Sharing Statement:
Available with the article online.
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Supplementary Materials
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