William H Herman

University of Michigan, Ann Arbor, Michigan, United States

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Publications (320)2119.18 Total impact

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    William H. Herman ·

    12/2015; 1(1). DOI:10.1186/s40842-015-0009-1
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    ABSTRACT: We sought to identify factors associated with participant retention in a 2-year, physician-lead, multidisciplinary, clinical weight management program that employs meal replacements to produce weight loss and intensive behavioral interventions and financial incentives for weight loss maintenance. We studied 270 participants enrolled in 2010 and 2011. Sociodemographic factors, health insurance, distance traveled, body mass index, comorbidities, health-related quality-of-life, and depression were explored as potential predictors of retention. Mean age was 49 ± 8 years and BMI was 41 ± 5 kg/m(2). Retention was excellent at 3 months (90%) and 6 months (83%). Attrition was greatest after participants were transitioned to regular foodstuffs and fell to 67% at 12 months and 51% at 2 years. Weight decreased by 15 ± 12 kg and BMI decreased by 5.1 ± 4.0 kg/m(2) in 2-year completers. Older age, lower baseline BMI, and financial incentives for program participation were independently associated with retention. Fewer depressive symptoms at baseline were associated with retention. This multidisciplinary, clinical, weight management program demonstrated high retention and excellent outcomes. Older age at baseline, less extreme obesity, and financial incentives were associated with program retention.
    12/2015; 2(1). DOI:10.1186/s40608-015-0041-9

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    ABSTRACT: Two distinct patterns of sweet taste liking have been described: one showing a peak liking response in the mid-range of sucrose concentrations and the other showing a monotonic liking response at progressively higher sucrose concentrations. Classification of these patterns has been somewhat arbitrary. In this report, we analyzed patterns of sweet taste liking in a pilot study with 26 adults including 14 women and 12 men, 32.6 ± 14.5 years of age with body mass index 26.4 ± 5.1 kg/m² (mean ± SD). Sweet taste liking was measured for 10 levels of sucrose solutions (0.035 M to 1.346 M). Participants rated their liking of each solution using a visual analog scale with 0 indicating strongly disliking and 100 strongly liking. The cluster analysis demonstrated two distinct groups: 13 liked relatively low sucrose concentrations and liked high sucrose concentrations less, and 13 liked high sucrose concentrations greatly. If we use the 0.598 M sucrose solution alone and a cutoff liking score of 50, we can distinguish the two clusters with high sensitivity (100%) and specificity (100%). If validated in additional studies, this simple tool may help us to better understand eating behaviors and the impact of sweet taste liking on nutrition-related disorders.
    Nutrients 09/2015; 7(9):7298-7311. DOI:10.3390/nu7095336 · 3.27 Impact Factor
  • William H Herman · Amy E Rothberg ·

    JAMA The Journal of the American Medical Association 09/2015; 314(10):1005-1007. DOI:10.1001/jama.2015.10030 · 35.29 Impact Factor
  • William H Herman ·

    Diabetes care 09/2015; 38(9):e143. DOI:10.2337/dc15-1234 · 8.42 Impact Factor
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    Wen Ye · Michael Brandle · Morton B Brown · William H Herman ·
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    ABSTRACT: The aim of this study was to develop and validate a computer simulation model for coronary heart disease (CHD) in type 2 diabetes mellitus (T2DM) that reflects current medical and surgical treatments. We modified the structure of the CHD submodel in the Michigan Model for Diabetes to allow for revascularization procedures before and after first myocardial infarction, for repeat myocardial infarctions and repeat revascularization procedures, and for congestive heart failure. Transition probabilities that reflect the direct effects of medical and surgical therapies on outcomes were derived from the literature and calibrated to recently published population-based epidemiologic studies and randomized controlled clinical trials. Monte Carlo techniques were used to implement a discrete-state and discrete-time multistate microsimulation model. Performance of the model was assessed using internal and external validation. Simple regression analysis (simulated outcome=b0+b1×published outcome) was used to evaluate the validation results. For the 21 outcomes in the six studies used for internal validation, R(2) was 0.99, and the slope of the regression line was 0.98. For the 16 outcomes in the five studies used for external validation, R(2) was 0.81, and the slope was 0.84. Our new computer simulation model predicted the progression of CHD in patients with T2DM and will be incorporated into the Michigan Model for Diabetes to assess the cost-effectiveness of alternative strategies to prevent and treat T2DM.
    Diabetes Technology &amp Therapeutics 07/2015; 17(10). DOI:10.1089/dia.2014.0304 · 2.11 Impact Factor
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    ABSTRACT: To determine if individualized education before Ramadan results in a safer fast for people with type 2 diabetes. Patients with type 2 diabetes who received care from participating clinics in Egypt, Iran, Jordan and Saudi Arabia and intended to fast during Ramadan 2014 were prospectively studied. Twelve clinics participated. Individualized education addressed meal planning, physical activity, blood glucose monitoring and acute metabolic complications and when deemed necessary, provided an individualized diabetes treatment plan. 774 people met study criteria, 515 received individualized education and 259 received usual care. Those who received individualized education were more likely to modify their diabetes treatment plan during Ramadan (97% vs 88%, p<0.0001), to perform self-monitoring of blood glucose at least twice daily during Ramadan (70% vs 51%, p<0.0001), and to have improved knowledge about hypoglycemic signs and symptoms (p=0.0007). Those who received individualized education also reduced their body mass index (-1.1±2.4 kg/m(2) vs -0.2±1.7 kg/m(2), p<0.0001) and glycated haemoglobin (-0.7±1.1% vs -0.1±1.3%, p<0.0001) during Ramadan compared those who received usual care. There were more mild (77% vs 67%, p=0.0031) and moderate (38% vs 19%, p<0.0001) hypoglycemic events reported by participants who received individualized education than those who received usual care, but fewer reported severe hypoglycemic events during Ramadan (23% vs 34%, p=0.0017). This individualized education and diabetes treatment program helped patients with type 2 diabetes lose weight, improve glycemic control and achieve a safer fast during Ramadan.
    06/2015; 3(1-1). DOI:10.1136/bmjdrc-2015-000111
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    ABSTRACT: To estimate the benefits of screening and early treatment of type 2 diabetes compared with no screening and late treatment using a simulation model with data from the ADDITION-Europe study. We used the Michigan Model, a validated computer simulation model, and data from the ADDITION-Europe study to estimate the absolute risk of cardiovascular outcomes and the relative risk reduction associated with screening and intensive treatment, screening and routine treatment, and no screening with a 3- or 6-year delay in the diagnosis and routine treatment of diabetes and cardiovascular risk factors. When the computer simulation model was programmed with the baseline demographic and clinical characteristics of the ADDITION-Europe population, it accurately predicted the empiric results of the trial. The simulated absolute risk reduction and relative risk reduction were substantially greater at 5 years with screening, early diagnosis, and routine treatment compared with scenarios in which there was a 3-year (3.3% absolute risk reduction [ARR], 29% relative risk reduction [RRR]) or a 6-year (4.9% ARR, 38% RRR) delay in diagnosis and routine treatment of diabetes and cardiovascular risk factors. Major benefits are likely to accrue from the early diagnosis and treatment of glycemia and cardiovascular risk factors in type 2 diabetes. The intensity of glucose, blood pressure, and cholesterol treatment after diagnosis is less important than the time of its initiation. Screening for type 2 diabetes to reduce the lead time between diabetes onset and clinical diagnosis and to allow for prompt multifactorial treatment is warranted. © 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.
    Diabetes care 05/2015; 38(8). DOI:10.2337/dc14-2459 · 8.42 Impact Factor
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    ABSTRACT: After the Diabetes Control and Complications Trial (DCCT), the Epidemiology of Diabetes Interventions and Complications (EDIC) study continued to demonstrate persistent benefit of prior intensive therapy on neuropathy, retinopathy, and nephropathy in type 1 diabetes mellitus (DM)., The relationship between control of glycemia and gastric emptying (GE) is unclear. We assessed GE with a (13)C-spirulina breath test and symptoms in 78 participants with type 1 diabetes at year 20 of EDIC. The relationship between delayed GE and HbA1c, complications of DM, and gastrointestinal symptoms were evaluated. GE was normal (37 participants, 50%), delayed (35 participants, 47%), or rapid (2 participants, 3%). The latest mean HbA1c was 7.7%. In univariate analyses, delayed GE was associated with greater DCCT baseline HbA1c and duration of DM prior to DCCT (P ≤ 0.04), greater mean HbA1c over an average of 27 years of follow up (during DCCT-EDIC, P = 0.01), lower R-R variability during deep breathing (P=0.03) and severe nephropathy (P=0.05) and a greater composite upper gastrointestinal symptom score (P<0.05). In multivariate models, retinopathy was the only complication of DM associated with delayed GE. Separately, DCCT baseline HbA1c (OR 1.6, 95% CI 1.1-2.3) and duration of DM (OR 1.2, 95%CI 1.01-1.3) prior to DCCT entry and mean HbA1c during DCCT-EDIC (OR 2.2, 95%CI 1.04-4.5) were independently associated with delayed GE. In the DCCT/EDIC study, delayed GE was remarkably common and associated with gastrointestinal symptoms and with measures of early and long-term hyperglycemia. ClinicalTrials.gov numbers NCT00360815 and NCT00360893. Copyright © 2015 AGA Institute. Published by Elsevier Inc. All rights reserved.
    Gastroenterology 05/2015; 149(2). DOI:10.1053/j.gastro.2015.05.007 · 16.72 Impact Factor
  • Keiko Asao · Laura N. McEwen · Joyce M. Lee · William H. Herman ·
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    ABSTRACT: To estimate and evaluate the sensitivity and specificity of providers' diagnosis codes and medication lists to identify outpatient visits by patients with diabetes. We used data from the 2006 to 2010 National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey. We assessed the sensitivity and specificity of providers' diagnoses and medication lists to identify patients with diabetes, using the checkbox for diabetes as the gold standard. We then examined differences in sensitivity by patients' characteristics using multivariate logistic regression models. The checkbox identified 12,647 outpatient visits by adults with diabetes among the 70,352 visits used for this analysis. The sensitivity and specificity of providers' diagnoses or listed diabetes medications were 72.3% (95% CI: 70.8% to 73.8%) and 99.2% (99.1% to 99.4%), respectively. Diabetic patients ≥75years of age, women, non-Hispanics, and those with private insurance or Medicare were more likely to be missed by providers' diagnoses and medication lists. Diabetic patients who had more diagnosis codes and medications recorded, had glucose or hemoglobin A1c measured, or made office- rather than hospital-outpatient visits were less likely to be missed. Providers' diagnosis codes and medication lists fail to identify approximately one quarter of outpatient visits by patients with diabetes. Copyright © 2015. Published by Elsevier Inc.
    Journal of diabetes and its complications 04/2015; DOI:10.1016/j.jdiacomp.2015.03.019 · 3.01 Impact Factor

  • Gastroenterology 04/2015; 148(4):S-143-S-144. DOI:10.1016/S0016-5085(15)30490-X · 16.72 Impact Factor

  • Gastroenterology 04/2015; 148(4):S-64. DOI:10.1016/S0016-5085(15)30224-9 · 16.72 Impact Factor
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    William H Herman · William T Cefalu ·

    Diabetes care 03/2015; 38(5). DOI:10.2337/dc15-0348 · 8.42 Impact Factor
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    ABSTRACT: Context: Gestational diabetes (GDM) confers a high risk of type 2 diabetes. In the Diabetes Prevention Program (DPP), intensive lifestyle (ILS) and metformin prevented or delayed diabetes in women with a history of GDM. Objective: The objective of the study was to evaluate the impact of ILS and metformin intervention over 10 years in women with and without a history of GDM in the DPP/Diabetes Prevention Program Outcomes Study. Design: This was a randomized controlled clinical trial with an observational follow-up. Setting: The study was conducted at 27 clinical centers. Participants: Three hundred fifty women with a history of GDM and 1416 women with previous live births but no history of GDM participated in the study. The participants had an elevated body mass index and fasting glucose and impaired glucose tolerance at study entry. Interventions: Interventions included placebo, ILS, or metformin. Outcomes Measure: Outcomes measure was diabetes mellitus. Results: Over 10 years, women with a history of GDM assigned to placebo had a 48% higher risk of developing diabetes compared with women without a history of GDM. In women with a history of GDM, ILS and metformin reduced progression to diabetes compared with placebo by 35% and 40%, respectively. Among women without a history of GDM, ILS reduced the progression to diabetes by 30%, and metformin did not reduce the progression to diabetes. Conclusions: Women with a history of GDM are at an increased risk of developing diabetes. In women with a history of GDM in the DPP/Diabetes Prevention Program Outcomes Study, both lifestyle and metformin were highly effective in reducing progression to diabetes during a 10-year follow-up period. Among women without a history of GDM, lifestyle but not metformin reduced progression to diabetes.
    Journal of Clinical Endocrinology &amp Metabolism 02/2015; 100(4):jc20143761. DOI:10.1210/jc.2014-3761 · 6.21 Impact Factor
  • William H Herman · George W Taylor · Jed J Jacobson · Ray Burke · Morton B Brown ·
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    ABSTRACT: Most Americans see dentists at least once a year. Chair-side screening and referral may improve diagnosis of prediabetes and diabetes. In this study, we developed a multivariate model to screen for dysglycemia (prediabetes and diabetes defined as HbA1c ≥5.7 percent) using information readily available to dentists and assessed the prevalence of dysglycemia in general dental practices. We recruited 1,033 adults ≥30 years of age without histories of diabetes from 13 general dental practices. A sample of 181 participants selected on the basis of random capillary glucose levels and periodontal status underwent definitive diagnostic testing with hemoglobin A1c. Logistic models were fit to identify risk factors for dysglycemia, and sample weights were applied to estimate the prevalence of dysglycemia in the population ≥30 years of age. Individuals at high risk for dysglycemia could be identified using a questionnaire that assessed sex, history of hypertension, history of dyslipidemia, history of lost teeth, and either self-reported body mass index ≥35 kg/m(2) (severe obesity) or random capillary glucose ≥110 mg/dl. We estimate that 30 percent of patients ≥30 years of age seen in these general dental practices had dysglycemia. There is a substantial burden of dysglycemia in patients seen in general dental practices. Simple chair-side screening for dysglycemia that includes or does not include fingerstick random capillary glucose testing can be used to rapidly identify high-risk patients. Further studies are needed to demonstrate the acceptability, feasibility, effectiveness, and cost-effectiveness of chair-side screening. © 2015 American Association of Public Health Dentistry.
    Journal of Public Health Dentistry 02/2015; 75(3). DOI:10.1111/jphd.12082 · 1.65 Impact Factor
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    ABSTRACT: Adults with diabetes typically take multiple medications for hyperglycemia, diabetes-associated conditions, and other comorbidities. Medication adherence is associated with improved outcomes, including reduced health care costs, hospitalization, and mortality. We conducted a retrospective analysis of a large pharmacy claims database to examine patient, medication, and prescriber factors associated with adherence to antidiabetic medications. We extracted data on a cohort of >200,000 patients who were treated for diabetes with noninsulin medications in the second half of 2010 and had continuous prescription benefits eligibility through 2011. Adherence was defined as a medication possession ratio ≥0.8. We used a modified adherence measure that accounted for switching therapies. Logistic regression analysis was performed to determine factors independently associated with adherence. Sixty-nine percent of patients were adherent. Adherence was independently associated with older age, male sex, higher education, higher income, use of mail order versus retail pharmacies, primary care versus nonendocrinology specialist prescribers, higher daily total pill burden, and lower out-of-pocket costs. Patients who were new to diabetes therapy were significantly less likely to be adherent. Several demographic, clinical, and potentially modifiable system-level factors were associated with adherence to antidiabetic medications. Patients typically perceived to be healthy (those who are younger, new to diabetes, and on few other medications) may be at risk for nonadherence. For all patients, efforts to reduce out-of-pocket costs and encourage use of mail order pharmacies may result in higher adherence. © 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.
    Diabetes Care 01/2015; 38(4). DOI:10.2337/dc14-2098 · 8.42 Impact Factor
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    ABSTRACT: Type 1 diabetes has been associated with an elevated relative risk (RR) of mortality compared to the general population. To review published studies on the RR of mortality of Type 1 diabetes patients compared to the general population, we conducted a meta-analysis and examined the temporal changes in the RR of mortality over time. Systematic review of studies reporting RR of mortality for Type 1 diabetes compared to the general population. We conducted meta-analyses using a DerSimonian and Laird random effects model to obtain the average effect and the distribution of RR estimates. Sub-group meta-analyses and multivariate meta-regression analysis was performed to examine heterogeneity. Summary RR with 95% CIs was calculated using a random-effects model. 26 studies with a total of 88 subpopulations were included in the meta-analysis and overall RR of mortality was 3.82 (95% CI 3.41, 3.4.29) compared to the general population. Observations using data prior to 1971 had a much larger estimated RR (5.80 (95% CI 4.20, 8.01)) when compared to: data between; 1971 and 1980 (5.06 (95% CI 3.44, 7.45)); 1981-90 (3.59 (95% CI 3.15, 4.09)); and those after 1990 (3.11 (95% CI 2.47, 3.91)); suggesting mortality of Type 1 diabetes patients when compared to the general population have been improving over time. Similarly, females (4.54 (95% CI 3.79-5.45)) had a larger RR estimate when compared to males (3.25 (95% CI 2.82-3.73) and the meta-regression found evidence for temporal trends and sex (p<0.01) accounting for heterogeneity between studies. Type 1 diabetes patients' mortality has declined at a faster rate than the general population. However, the largest relative improvements have occurred prior to 1990. Emphasis on intensive blood glucose control alongside blood pressure control and statin therapy may translate into further reductions in mortality in coming years.
    PLoS ONE 11/2014; 9(11):e113635. DOI:10.1371/journal.pone.0113635 · 3.23 Impact Factor
  • Keiko Asao · Laura N. McEwen · Jesse C. Crosson · Beth Waitzfelder · William H. Herman ·
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    ABSTRACT: Objective To describe patient and provider characteristics associated with outpatient revisit frequency and to examine the associations between the revisit frequency and the processes and intermediate outcomes of diabetes care. Research Design and Methods We analyzed data from Translating Research Into Action for Diabetes (TRIAD), a prospective, multicenter, observational study of diabetes care in managed care. Results Our analysis included 6,040 eligible adult participants with type 2 diabetes (42.6% ≥ 65 years of age, 54.1% female) whose primary care providers were the main provider of the participants’ diabetes care. The median (interquartile range) revisit frequency was 4.0 (3.7, 6.0) visits per year. Being female, having lower education, lower income, more complex diabetes treatment, cardiovascular disease, higher Charlson comorbidity index, and impaired mobility were associated with higher revisit frequency. The proportion of participants who had annual assessments of HbA1c and LDL-cholesterol, foot examinations, advised or documented aspirin use, and influenza immunizations were higher for those with higher revisit frequency. The proportion of participants who met HbA1c (< 9.5%) and LDL-cholesterol (< 130 mg/dL) treatment goals was higher for those with a higher revisit frequency. The predicted probabilities of achieving more aggressive goals, HbA1c < 8.5%, LDL-cholesterol < 100 mg/dL, and blood pressure < 130/85 or even < 140/90 mmHg were not associated with higher revisit frequency. Conclusions Revisit frequency was highly variable and was associated with both sociodemographic characteristics and disease severity. A higher revisit frequency was associated with better processes of diabetes care, but the association with intermediate outcomes was less clear.
    Journal of Diabetes and its Complications 11/2014; 28(6). DOI:10.1016/j.jdiacomp.2014.06.006 · 3.01 Impact Factor

Publication Stats

17k Citations
2,119.18 Total Impact Points


  • 1991-2015
    • University of Michigan
      • • Medical School
      • • Department of Internal Medicine
      • • Division of Metabolism, Endocrinology & Diabetes
      • • School of Public Health
      Ann Arbor, Michigan, United States
  • 2012-2013
    • Baker IDI Heart and Diabetes Institute
      • Clinical Diabetes and Epidemiology Research Group
      Melbourne, Victoria, Australia
  • 1994-2013
    • Centers for Disease Control and Prevention
      • Division of Diabetes Translation
      Atlanta, MI, United States
    • University of Chicago
      Chicago, Illinois, United States
  • 1990-2013
    • Concordia University–Ann Arbor
      Ann Arbor, Michigan, United States
  • 2006-2012
    • University of California, San Francisco
      • Department of Obstetrics, Gynecology and Reproductive Sciences
      San Francisco, CA, United States
    • Indiana University Bloomington
      Bloomington, Indiana, United States
    • University of Florida
      • Department of Medicine
      Gainesville, FL, United States
  • 2003-2011
    • Wayne State University
      • Department of Pharmacy Practice
      Detroit, MI, United States
    • University of Toronto
      Toronto, Ontario, Canada
    • George Washington University
      Washington, Washington, D.C., United States
    • Brigham and Women's Hospital
      Boston, Massachusetts, United States
  • 2009
    • Kaiser Permanente
      Oakland, California, United States
  • 2003-2009
    • University of California, Los Angeles
      • Department of Emergency Medicine
      Los Ángeles, California, United States
  • 2008
    • RTI International
      Durham, North Carolina, United States
  • 2007
    • California State University, Los Angeles
      Los Ángeles, California, United States
  • 2003-2007
    • Indiana University-Purdue University Indianapolis
      Indianapolis, Indiana, United States
  • 2005
    • University of Wisconsin–Madison
      Madison, Wisconsin, United States
  • 2003-2004
    • University of California, San Diego
      • Division of Endocrinology & Metabolism
      San Diego, California, United States
  • 2000
    • Hillsdale College
      Hillsdale, New Jersey, United States
  • 1999
    • University of Kuopio
      Kuopio, Northern Savo, Finland
  • 1997
    • Massachusetts Department of Public Health
      Boston, Massachusetts, United States