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Griauzde DH, Turner CD, Othman A, Oshman L, Gabison J, Arizaca-Dileo PK, Walford E, Henderson J, Beckius D, Lee JM, Carter EW, Dallas C, Herrera-Theut K, Richardson CR, Kullgren JT, Piatt G, Heisler M, Kraftson A. A Primary Care-Based Weight Navigation Program. JAMA Netw Open 2024; 7:e2412192. [PMID: 38771575 PMCID: PMC11109771 DOI: 10.1001/jamanetworkopen.2024.12192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 03/18/2024] [Indexed: 05/22/2024] Open
Abstract
Importance Evidence-based weight management treatments (WMTs) are underused; strategies are needed to increase WMT use and patients' weight loss. Objective To evaluate the association of a primary care-based weight navigation program (WNP) with WMT use and weight loss. Design, Setting, and Participants This cohort study comprised a retrospective evaluation of a quality improvement program conducted from October 1, 2020, to September 30, 2021. Data analysis was performed from August 2, 2022, to March 7, 2024. Adults with obesity and 1 or more weight-related condition from intervention and control sites in a large academic health system in the Midwestern US were propensity matched on sociodemographic and clinical factors. Exposure WNP, in which American Board of Obesity Medicine-certified primary care physicians offered weight-focused visits and guided patients' selection of preference-sensitive WMTs. Main Outcomes and Measures Primary outcomes were feasibility measures, including rates of referral to and engagement in the WNP. Secondary outcomes were mean weight loss, percentage of patients achieving 5% or more and 10% or more weight loss, referral to WMTs, and number of antiobesity medication prescriptions at 12 months. Results Of 264 patients, 181 (68.6%) were female and mean (SD) age was 49.5 (13.0) years; there were no significant differences in demographic characteristics between WNP patients (n = 132) and matched controls (n = 132). Of 1159 WNP-eligible patients, 219 (18.9%) were referred to the WNP and 132 (11.4%) completed a visit. In a difference-in-differences analysis, WNP patients lost 4.9 kg more than matched controls (95% CI, 2.11-7.76; P < .001), had 4.4% greater weight loss (95% CI, 2.2%-6.4%; P < .001), and were more likely to achieve 5% or more weight loss (odds ratio [OR], 2.90; 95% CI, 1.54-5.58); average marginal effects, 21.2%; 95% CI, 8.8%-33.6%) and 10% or more weight loss (OR, 7.19; 95% CI, 2.55-25.9; average marginal effects, 17.4%; 95% CI, 8.7%-26.2%). Patients in the WNP group were referred at higher rates to WMTs, including bariatric surgery (18.9% vs 9.1%; P = .02), a low-calorie meal replacement program (16.7% vs 3.8%; P < .001), and a Mediterranean-style diet and activity program (10.6% vs 1.5%; P = .002). There were no between-group differences in antiobesity medication prescribing. Conclusions and Relevance The findings of this cohort study suggest that WNP is feasible and associated with greater WMT use and weight loss than matched controls. The WNP warrants evaluation in a large-scale trial.
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Affiliation(s)
- Dina H. Griauzde
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan
- University of Michigan Institute for Healthcare Policy and Innovation, Ann Arbor
| | - Cassie D. Turner
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan
- Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor
| | - Amal Othman
- Department of Family Medicine, University of Michigan Medical School, Ann Arbor
| | - Lauren Oshman
- University of Michigan Institute for Healthcare Policy and Innovation, Ann Arbor
- Department of Family Medicine, University of Michigan Medical School, Ann Arbor
| | - Jonathan Gabison
- Department of Family Medicine, University of Michigan Medical School, Ann Arbor
| | | | - Eric Walford
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
| | - James Henderson
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- University of Michigan Institute for Healthcare Policy and Innovation, Ann Arbor
| | - Deena Beckius
- University of Michigan Elizabeth Weiser Caswell Diabetes Institute, Ann Arbor
| | - Joyce M. Lee
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan
- Department of Pediatrics, University of Michigan Medical School, Ann Arbor
| | - Eli W. Carter
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
| | - Chris Dallas
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- University of Michigan Elizabeth Weiser Caswell Diabetes Institute, Ann Arbor
| | - Kathyrn Herrera-Theut
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- Department of Pediatrics, University of Michigan Medical School, Ann Arbor
| | - Caroline R. Richardson
- Department of Family Medicine, The Warren Alpert Medical School of Brown University and Care New England, Providence, Rhode Island
| | - Jeffrey T. Kullgren
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan
- University of Michigan Institute for Healthcare Policy and Innovation, Ann Arbor
- Department of Health Management and Policy, University of Michigan School of Public Health, Ann Arbor
| | - Gretchen Piatt
- Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor
- Department of Health Behavior and Health Education, University of Michigan School of Public Health, Ann Arbor
| | - Michele Heisler
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan
- University of Michigan Institute for Healthcare Policy and Innovation, Ann Arbor
| | - Andrew Kraftson
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
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Chakkalakal RJ, Galaviz KI, Thirunavukkarasu S, Shah MK, Narayan KMV. Test and Treat for Prediabetes: A Review of the Health Effects of Prediabetes and the Role of Screening and Prevention. Annu Rev Public Health 2024; 45:151-167. [PMID: 38109519 DOI: 10.1146/annurev-publhealth-060222-023417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2023]
Abstract
The term prediabetes describes blood glucose levels above the normal range but below the threshold to diagnose type 2 diabetes. Several population health initiatives encourage a test and treat approach for prediabetes. In this approach, screening and identification of individuals with prediabetes should be followed by prompt referral to structured lifestyle modification programs or pharmacologic interventions that have been shown to prevent or delay the progression to type 2 diabetes in clinical trials. Here we provide a critical review of evidence for this test and treat approach by examining health outcomes associated with prediabetes and the availability and effectiveness of lifestyle modification approaches that target prediabetes. We also describe current limitations to the reach and uptake of evidence-based treatment options for prediabetes. Finally, we highlight lessons learned from identifying and labeling other preconditions to consider challenges and opportunities that may arise with increasing awareness of prediabetes as part of routine preventive care.
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Affiliation(s)
- Rosette J Chakkalakal
- Department of Medicine, Emory University School of Medicine, Emory University, Atlanta, Georgia, USA;
- Department of Family and Preventive Medicine, Emory University School of Medicine, Emory University, Atlanta, Georgia, USA
- Emory Global Diabetes Research Center, Woodruff Health Sciences Center, Emory University, Atlanta, Georgia, USA
| | - Karla I Galaviz
- Indiana University School of Public Health-Bloomington, Indiana University, Bloomington, Indiana, USA
| | - Sathish Thirunavukkarasu
- Department of Family and Preventive Medicine, Emory University School of Medicine, Emory University, Atlanta, Georgia, USA
- Emory Global Diabetes Research Center, Woodruff Health Sciences Center, Emory University, Atlanta, Georgia, USA
| | - Megha K Shah
- Department of Family and Preventive Medicine, Emory University School of Medicine, Emory University, Atlanta, Georgia, USA
- Emory Global Diabetes Research Center, Woodruff Health Sciences Center, Emory University, Atlanta, Georgia, USA
| | - K M Venkat Narayan
- Emory Global Diabetes Research Center, Woodruff Health Sciences Center, Emory University, Atlanta, Georgia, USA
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
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3
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Gore R, Engelberg RS, Johnson D, Jebb O, Schwartz MD, Islam N. Integrating Community Health Workers' Dual Clinic-Community Role in Safety-Net Primary Care: Implementation Lessons from a Pragmatic Diabetes-Prevention Trial. J Gen Intern Med 2024; 39:774-781. [PMID: 37973708 PMCID: PMC11043246 DOI: 10.1007/s11606-023-08512-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Accepted: 10/24/2023] [Indexed: 11/19/2023]
Abstract
BACKGROUND Over a third of US adults carry a diagnosis of prediabetes, 70% of whom may progress to type 2 diabetes mellitus ("diabetes"). Community health workers (CHWs) can help patients undertake healthy behavior to prevent diabetes. However, there is limited guidance to integrate CHWs in primary care, specifically to address CHWs' dual clinic-based and community-oriented role. OBJECTIVE Using evidence from CHWs' adaptations of a diabetes-prevention intervention in safety-net hospitals in New York City, we examine the nature, intent, and possible consequences of CHWs' actions on program fidelity. We propose strategies for integrating CHWs in primary care. DESIGN Case study drawing on the Model for Adaptation Design and Impact (MADI) to analyze CHWs' actions during implementation of CHORD (Community Health Outreach to Reduce Diabetes), a cluster-randomized pragmatic trial (2017-2022) at Manhattan VA and Bellevue Hospital. PARTICIPANTS CHWs and clinicians in the CHORD study, with a focus in this analysis on CHWs. APPROACH Semi-structured interviews and focus group discussion with CHWs (n=4); semi-structured interviews with clinicians (n=17). Interpretivist approach to explain CHWs' adaptations using a mix of inductive and deductive analysis. KEY RESULTS CHWs' adaptations extended the intervention in three ways: by extending social assistance, healthcare access, and operational tasks. The adaptations were intended to improve fit, reach, and retention, but likely had ripple effects on implementation outcomes. CHWs' focus on patients' complex social needs could divert them from judiciously managing their caseload. CONCLUSIONS CHWs' community knowledge can support patient engagement, but overextension of social assistance may detract from protocolized health-coaching goals. CHW programs in primary care should explicitly delineate CHWs' non-health support to patients, include multiprofessional teams or partnerships with community-based organizations, establish formal communication between CHWs and clinicians, and institute mechanisms to review and iterate CHWs' work to resolve challenges in their community-oriented role.
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Affiliation(s)
- Radhika Gore
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA.
| | - Rachel S Engelberg
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA
| | - Danielle Johnson
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA
- Bellevue Hospital Center, New York, NY, USA
| | - Olivia Jebb
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA
- Bellevue Hospital Center, New York, NY, USA
| | - Mark D Schwartz
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA
- VA NY Harbor Health Care System, New York, NY, USA
| | - Nadia Islam
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA
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Schlechter CR, Del Fiol G, Jones DR, Orleans B, Gibson B, Nahum-Shani I, Maxfield E, Locke A, Cornia R, Bradshaw R, Wirth J, Jaggers SJ, Lam CY, Wetter DW. Increasing the reach of evidence-based interventions for weight management and diabetes prevention among Medicaid patients: study protocol for a pilot Sequential Multiple Assignment Randomised Trial. BMJ Open 2023; 13:e075157. [PMID: 38011967 PMCID: PMC10685946 DOI: 10.1136/bmjopen-2023-075157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 10/16/2023] [Indexed: 11/29/2023] Open
Abstract
INTRODUCTION Over 40% of US adults meet criteria for obesity, a major risk factor for chronic disease. Obesity disproportionately impacts populations that have been historically marginalised (eg, low socioeconomic status, rural, some racial/ethnic minority groups). Evidence-based interventions (EBIs) for weight management exist but reach less than 3% of eligible individuals. The aims of this pilot randomised controlled trial are to evaluate feasibility and acceptability of dissemination strategies designed to increase reach of EBIs for weight management. METHODS AND ANALYSIS This study is a two-phase, Sequential Multiple Assignment Randomized Trial, conducted with 200 Medicaid patients. In phase 1, patients will be individually randomised to single text message (TM1) or multiple text messages (TM+). Phase 2 is based on treatment response. Patients who enrol in the EBI within 12 weeks of exposure to phase 1 (ie, responders) receive no further interventions. Patients in TM1 who do not enrol in the EBI within 12 weeks of exposure (ie, TM1 non-responders) will be randomised to either TM1-Continued (ie, no further TM) or TM1 & MAPS (ie, no further TM, up to 2 Motivation And Problem Solving (MAPS) navigation calls) over the next 12 weeks. Patients in TM+ who do not enrol in the EBI (ie, TM+ non-responders) will be randomised to either TM+Continued (ie, monthly text messages) or TM+ & MAPS (ie, monthly text messages, plus up to 2 MAPS calls) over the next 12 weeks. Descriptive statistics will be used to characterise feasibility (eg, proportion of patients eligible, contacted and enrolled in the trial) and acceptability (eg, participant opt-out, participant engagement with dissemination strategies, EBI reach (ie, the proportion of participants who enrol in EBI), adherence, effectiveness). ETHICS AND DISSEMINATION Study protocol was approved by the University of Utah Institutional Review Board (#00139694). Results will be disseminated through study partners and peer-reviewed publications. TRIAL REGISTRATION NUMBER clinicaltrials.gov; NCT05666323.
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Affiliation(s)
- Chelsey R Schlechter
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA
- Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USA
| | - Guilherme Del Fiol
- Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA
| | - Dusti R Jones
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA
- Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USA
| | - Brian Orleans
- Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USA
| | - Bryan Gibson
- Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA
| | - Inbal Nahum-Shani
- Institute for Social Research, University of Michigan, Ann Arbor, Michigan, USA
| | - Ellen Maxfield
- Osher Center for Integrative Health, University of Utah, Salt Lake City, Utah, USA
- Department of Family & Preventive Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Amy Locke
- Osher Center for Integrative Health, University of Utah, Salt Lake City, Utah, USA
- Department of Family & Preventive Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Ryan Cornia
- Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA
| | - Richard Bradshaw
- Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA
| | - Jennifer Wirth
- Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USA
| | - Shanna J Jaggers
- Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USA
| | - Cho Y Lam
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA
- Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USA
| | - David W Wetter
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA
- Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USA
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5
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Rahim NE, Flood D, Marcus ME, Theilmann M, Aung TN, Agoudavi K, Aryal KK, Bahendeka S, Bicaba B, Bovet P, Diallo AO, Farzadfar F, Guwatudde D, Houehanou C, Houinato D, Hwalla N, Jorgensen J, Kagaruki GB, Mayige M, Wong-McClure R, Larijani B, Saeedi Moghaddam S, Mwalim O, Mwangi KJ, Sarkar S, Sibai AM, Sturua L, Wesseh C, Geldsetzer P, Atun R, Vollmer S, Bärnighausen T, Davies J, Ali MK, Seiglie JA, Manne-Goehler J. Diabetes risk and provision of diabetes prevention activities in 44 low-income and middle-income countries: a cross-sectional analysis of nationally representative, individual-level survey data. Lancet Glob Health 2023; 11:e1576-e1586. [PMID: 37734801 PMCID: PMC10560068 DOI: 10.1016/s2214-109x(23)00348-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 06/27/2023] [Accepted: 07/12/2023] [Indexed: 09/23/2023]
Abstract
BACKGROUND The global burden of diabetes is rising rapidly, yet there is little evidence on individual-level diabetes prevention activities undertaken by health systems in low-income and middle-income countries (LMICs). Here we describe the population at high risk of developing diabetes, estimate diabetes prevention activities, and explore sociodemographic variation in these activities across LMICs. METHODS We performed a pooled, cross-sectional analysis of individual-level data from nationally representative, population-based surveys conducted in 44 LMICs between October, 2009, and May, 2019. Our sample included all participants older than 25 years who did not have diabetes and were not pregnant. We defined the population at high risk of diabetes on the basis of either the presence of impaired fasting glucose (or prediabetes in countries with a haemoglobin A1c available) or overweight or obesity, consistent with the WHO Package of Essential Noncommunicable Disease Guidelines for type 2 diabetes management. We estimated the proportion of survey participants that were at high risk of developing diabetes based on this definition. We also estimated the proportion of the population at high risk that reported each of four fundamental diabetes prevention activities: physical activity counselling, weight loss counselling, dietary counselling, and blood glucose screening, overall and stratified by World Bank income group. Finally, we used multivariable Poisson regression models to evaluate associations between sociodemographic characteristics and these activities. FINDINGS The final pooled sample included 145 739 adults (86 269 [59·2%] of whom were female and 59 468 [40·4%] of whom were male) across 44 LMICs, of whom 59 308 (40·6% [95% CI 38·5-42·8]) were considered at high risk of diabetes (20·6% [19·8-21·5] in low-income countries, 38·0% [37·2-38·9] in lower-middle-income countries, and 57·5% [54·3-60·6] in upper-middle-income countries). Overall, the reach of diabetes prevention activities was low at 40·0% (38·6-41·4) for physical activity counselling, 37·1% (35·9-38·4) for weight loss counselling, 42·7% (41·6-43·7) for dietary counselling, and 37·1% (34·7-39·6) for blood glucose screening. Diabetes prevention varied widely by national-level wealth: 68·1% (64·6-71·4) of people at high risk of diabetes in low-income countries reported none of these activities, whereas 49·0% (47·4-50·7) at high risk in upper-middle-income countries reported at least three activities. Educational attainment was associated with diabetes prevention, with estimated increases in the predicted probability of receipt ranging between 6·5 (3·6-9·4) percentage points for dietary fruit and vegetable counselling and 21·3 (19·5-23·2) percentage points for blood glucose screening, among people with some secondary schooling compared with people with no formal education. INTERPRETATION A large proportion of individuals across LMICs are at high risk of diabetes but less than half reported receiving fundamental prevention activities overall, with the lowest receipt of these activities among people in low-income countries and with no formal education. These findings offer foundational evidence to inform future global targets for diabetes prevention and to strengthen policies and programmes to prevent continued increases in diabetes worldwide. FUNDING Harvard T H Chan School of Public Health McLennan Fund: Dean's Challenge Grant Program and the EU's Research and Innovation programme Horizon 2020.
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Affiliation(s)
- Nicholas Errol Rahim
- Medical Practice Evaluation Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - David Flood
- Department of Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Maja E Marcus
- Division of Infectious Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michaela Theilmann
- Heidelberg Institute of Global Health, Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg, Germany; Behavioral Science for Disease Prevention and Health Care, Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany
| | - Taing N Aung
- Medical Practice Evaluation Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Krishna Kumar Aryal
- Bergen Centre for Ethics and Priority Setting, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | - Silver Bahendeka
- Diabetes and Endocrinology, Saint Francis Hospital Nsambya, Kampala, Uganda
| | - Brice Bicaba
- National Institute of Public Health, Ouagadougou, Burkina Faso
| | - Pascal Bovet
- University Center for General Medicine and Public Health (Unisanté), Lausanne, Switzerland; Ministry of Health, Victoria, Seychelles
| | - Alpha Oumar Diallo
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Farshad Farzadfar
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - David Guwatudde
- Department of Epidemiology and Biostatistics, School of Public Health, Makerere University, Kampala, Uganda
| | - Corine Houehanou
- Laboratory of Epidemiology of Chronic and Neurological Diseases, Faculty of Health Sciences, University of Abomey-Calavi, Cotonou, Benin
| | - Dismand Houinato
- Laboratory of Epidemiology of Chronic and Neurological Diseases, Faculty of Health Sciences, University of Abomey-Calavi, Cotonou, Benin
| | - Nahla Hwalla
- Faculty of Agricultural and Food Sciences, American University of Beirut, Beirut, Lebanon
| | - Jutta Jorgensen
- Institute of Global Health, Department of Public Health and Epidemiology, Copenhagen University, Copenhagen, Denmark
| | | | - Mary Mayige
- National Institute for Medical Research, Dar es Salaam, Tanzania
| | | | - Bagher Larijani
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Sahar Saeedi Moghaddam
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran; Kiel Institute for the World Economy, Kiel, Germany
| | | | - Kibachio Joseph Mwangi
- Division of Non-Communicable Diseases, Ministry of Health, Nairobi, Kenya; World Health Organization Country Office, Pretoria, South Africa
| | - Sudipa Sarkar
- Division of Endocrinology, Diabetes, and Metabolism, John Hopkins University, Baltimore, MD, USA
| | - Abla M Sibai
- Department of Epidemiology and Population Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
| | - Lela Sturua
- Non-Communicable Disease Department, National Center for Disease Control and Public Health, Tbilisi, Georgia
| | | | - Pascal Geldsetzer
- Division of Primary Care and Population Health, Department of Medicine, Stanford University, Stanford, CA, USA; Chan Zuckerberg Biohub-San Francisco, San Francisco, CA, USA
| | - Rifat Atun
- Department of Global Health and Population, Harvard T H Chan School of Public Health, Harvard University, Boston, MA, USA; Department of Global Health and Social Medicine, Harvard Medical School, Harvard University, Boston, MA, USA
| | - Sebastian Vollmer
- Department of Economics and Centre for Modern Indian Studies, University of Göttingen, Göttingen, Germany
| | - Till Bärnighausen
- Heidelberg Institute of Global Health, Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg, Germany; Department of Global Health and Social Medicine, Harvard Medical School, Harvard University, Boston, MA, USA; Africa Health Research Institute, Somkhele, South Africa
| | - Justine Davies
- MRC/Wits Rural Public Health and Health Transitions Research Unit, School of Public Health, University of Witwatersrand, Johannesburg, South Africa; Institute of Applied Health Research, University of Birmingham, Birmingham, UK; Centre for Global Surgery, Department of Global Health, Stellenbosch University, Cape Town, South Africa
| | - Mohammed K Ali
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA; Department of Family and Prevention Medicine, School of Medicine, Emory University, Atlanta, GA, USA
| | - Jacqueline A Seiglie
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Jennifer Manne-Goehler
- Medical Practice Evaluation Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Division of Infectious Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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Hu J, Fang M, Pike JR, Lutsey PL, Sharrett AR, Wagenknecht LE, Hughes TM, Seegmiller JC, Gottesman RF, Mosley TH, Coresh J, Selvin E. Prediabetes, intervening diabetes and subsequent risk of dementia: the Atherosclerosis Risk in Communities (ARIC) study. Diabetologia 2023; 66:1442-1449. [PMID: 37221246 PMCID: PMC10467356 DOI: 10.1007/s00125-023-05930-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 02/28/2023] [Indexed: 05/25/2023]
Abstract
AIMS/HYPOTHESIS The aim of this work was to evaluate whether the association of prediabetes with dementia is explained by the intervening onset of diabetes. METHODS Among participants of the Atherosclerosis Risk in Communities (ARIC) study we defined baseline prediabetes as HbA1c 39-46 mmol/mol (5.7-6.4%) and subsequent incident diabetes as a self-reported physician diagnosis or use of diabetes medication. Incident dementia was ascertained via active surveillance and adjudicated. We quantified the association of prediabetes with dementia risk before and after accounting for the subsequent development of diabetes among ARIC participants without diabetes at baseline (1990-1992; participants aged 46-70 years). We also evaluated whether age at diabetes diagnosis modified the risk of dementia. RESULTS Among 11,656 participants without diabetes at baseline, 2330 (20.0%) had prediabetes. Before accounting for incident diabetes, prediabetes was significantly associated with the risk of dementia (HR 1.12 [95% CI 1.01, 1.24]). After accounting for incident diabetes, the association was attenuated and non-significant (HR 1.05 [95% CI 0.94, 1.16]). Earlier age of onset of diabetes had the strongest association with dementia: HR 2.92 (95% CI 2.06, 4.14) for onset before 60 years; HR 1.73 (95% CI 1.47, 2.04) for onset at 60-69 years; and HR 1.23 (95% CI 1.08, 1.40) for onset at 70-79 years. CONCLUSIONS/INTERPRETATION Prediabetes is associated with dementia risk but this risk is explained by the subsequent development of diabetes. Earlier age of onset of diabetes substantially increases dementia risk. Preventing or delaying progression of prediabetes to diabetes will reduce dementia burden.
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Affiliation(s)
- Jiaqi Hu
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
| | - Michael Fang
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
| | - James R Pike
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Pamela L Lutsey
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - A Richey Sharrett
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
| | - Lynne E Wagenknecht
- Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Timothy M Hughes
- Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Jesse C Seegmiller
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Rebecca F Gottesman
- Stroke Branch, National Institute of Neurological Disorders and Stroke, Baltimore, MD, USA
| | - Thomas H Mosley
- The MIND Center, University of Mississippi School of Medicine, Jackson, MS, USA
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA.
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA.
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Boltri JM, Tracer H, Strogatz D, Idzik S, Schumacher P, Fukagawa N, Leake E, Powell C, Shell D, Wu S, Herman WH. The National Clinical Care Commission Report to Congress: Leveraging Federal Policies and Programs to Prevent Diabetes in People With Prediabetes. Diabetes Care 2023; 46:e39-e50. [PMID: 36701590 PMCID: PMC9887613 DOI: 10.2337/dc22-0620] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 11/03/2022] [Indexed: 01/27/2023]
Abstract
Individuals with an elevated fasting glucose level, elevated glucose level after glucose challenge, or elevated hemoglobin A1c level below the diagnostic threshold for diabetes (collectively termed prediabetes) are at increased risk for type 2 diabetes. More than one-third of U.S. adults have prediabetes but fewer than one in five are aware of the diagnosis. Rigorous scientific research has demonstrated the efficacy of both intensive lifestyle interventions and metformin in delaying or preventing progression from prediabetes to type 2 diabetes. The National Clinical Care Commission (NCCC) was a federal advisory committee charged with evaluating and making recommendations to improve federal programs related to the prevention of diabetes and its complications. In this article, we describe the recommendations of an NCCC subcommittee that focused primarily on prevention of type 2 diabetes in people with prediabetes. These recommendations aim to improve current federal diabetes prevention activities by 1) increasing awareness of and diagnosis of prediabetes on a population basis; 2) increasing the availability of, referral to, and insurance coverage for the National Diabetes Prevention Program and the Medicare Diabetes Prevention Program; 3) facilitating Food and Drug Administration review and approval of metformin for diabetes prevention; and 4) supporting research to enhance the effectiveness of diabetes prevention. Cognizant of the burden of type 1 diabetes, the recommendations also highlight the importance of research to advance our understanding of the etiology of and opportunities for prevention of type 1 diabetes.
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Affiliation(s)
| | - Howard Tracer
- Agency for Healthcare Research and Quality, Department of Health and Human Services, Rockville, MD
| | | | - Shannon Idzik
- School of Nursing, University of Maryland, Baltimore, MD
| | - Pat Schumacher
- Centers for Disease Control and Prevention, Department of Health and Human Services, Atlanta, GA
| | | | - Ellen Leake
- Juvenile Diabetes Research Foundation, Jackson, MS
| | - Clydette Powell
- School of Medicine and Health Services, George Washington University, Washington, DC
| | | | - Samuel Wu
- U.S. Office of Minority Health, Rockville, MD
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