D F Williamson

Centers for Disease Control and Prevention, Атланта, Michigan, United States

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Publications (193)1909.92 Total impact

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    ABSTRACT: Although diabetes is one of the most costly and rapidly increasing serious chronic diseases worldwide, the optimal mix of strategies to reduce diabetes prevalence has not been determined. Using a dynamic model that incorporates national data on diabetes prevalence and incidence, migration, mortality rates, and intervention effectiveness, we project the effect of five hypothetical prevention policies on future US diabetes rates through 2030: 1) no diabetes prevention strategy; 2) a "high-risk" strategy, wherein adults with both impaired fasting glucose (IFG) (fasting plasma glucose of 100--124 mg/dl) and impaired glucose tolerance (IGT) (2-hour post-load glucose of 141--199 mg/dl) receive structured lifestyle intervention; 3) a "moderate-risk" strategy, wherein only adults with IFG are offered structured lifestyle intervention; 4) a "population-wide" strategy, in which the entire population is exposed to broad risk reduction policies; and 5) a "combined" strategy, involving both the moderate-risk and population-wide strategies. We assumed that the moderate- and high-risk strategies reduce the annual diabetes incidence rate in the targeted subpopulations by 12.5% through 2030 and that the population-wide approach would reduce the projected annual diabetes incidence rate by 2% in the entire US population. We project that by the year 2030, the combined strategy would prevent 4.6 million incident cases and 3.6 million prevalent cases, attenuating the increase in diabetes prevalence by 14%. The moderate-risk approach is projected to prevent 4.0 million incident cases, 3.1 million prevalent cases, attenuating the increase in prevalence by 12%. The high-risk and population approaches attenuate the projected prevalence increases by 5% and 3%, respectively. Even if the most effective strategy is implemented (the combined strategy), our projections indicate that the diabetes prevalence rate would increase by about 65% over the 23 years (i.e., from 12.9% in 2010 to 21.3% in 2030). While implementation of appropriate diabetes prevention strategies may slow the rate of increase of the prevalence of diabetes among US adults through 2030, the US diabetes prevalence rate is likely to increase dramatically over the next 20 years. Demand for health care services for people with diabetes complications and diabetes-related disability will continue to grow, and these services will need to be strengthened along with primary diabetes prevention efforts.
    Population Health Metrics 09/2013; 11(1):18. DOI:10.1186/1478-7954-11-18 · 2.11 Impact Factor
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    ABSTRACT: Background: Weight loss is recommended for overweight or obese patients with type 2 diabetes on the basis of short-term studies, but long-term effects on cardiovascular disease remain unknown. We examined whether an intensive lifestyle intervention for weight loss would decrease cardiovascular morbidity and mortality among such patients. Methods: In 16 study centers in the United States, we randomly assigned 5145 overweight or obese patients with type 2 diabetes to participate in an intensive lifestyle intervention that promoted weight loss through decreased caloric intake and increased physical activity (intervention group) or to receive diabetes support and education (control group). The primary outcome was a composite of death from cardiovascular causes, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for angina during a maximum follow-up of 13.5 years. Results: The trial was stopped early on the basis of a futility analysis when the median follow-up was 9.6 years. Weight loss was greater in the intervention group than in the control group throughout the study (8.6% vs. 0.7% at 1 year; 6.0% vs. 3.5% at study end). The intensive lifestyle intervention also produced greater reductions in glycated hemoglobin and greater initial improvements in fitness and all cardiovascular risk factors, except for low-density-lipoprotein cholesterol levels. The primary outcome occurred in 403 patients in the intervention group and in 418 in the control group (1.83 and 1.92 events per 100 person-years, respectively; hazard ratio in the intervention group, 0.95; 95% confidence interval, 0.83 to 1.09; P=0.51). Conclusions: An intensive lifestyle intervention focusing on weight loss did not reduce the rate of cardiovascular events in overweight or obese adults with type 2 diabetes. (Funded by the National Institutes of Health and others; Look AHEAD ClinicalTrials.gov number, NCT00017953.).
    New England Journal of Medicine 06/2013; 369(2). DOI:10.1056/NEJMoa1212914 · 55.87 Impact Factor
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    ABSTRACT: Although glycated hemoglobin (HbA1c) has been widely recommended for the diagnosis of diabetes, considerable ambiguity remains about how HbA1c should be used to identify people with prediabetes or other high-risk states for preventive interventions. The current paper provides a synthesis of the epidemiologic basis and the health and economic implications of using various HbA1c-based risk-stratification approaches for diabetes prevention. HbA1c predicts diabetes and related outcomes across a wide range of HbA1c values. However, the authors estimate that, among U.S. adults, the top 15% of the nondiabetic HBA1c distribution (HbA1c of 5.7%–6.4%) accounts for 47% of diabetes cases over 5 years, and the top 30% (5.5%–6.4%) accounts for about 70% of cases. Although this clustering of eventual cases at the high end of the HbA1c risk distribution means that intervention resources will be more efficient when applied to the upper end of the distribution, no obvious threshold exists to prioritize people for preventive interventions. Thus, the choice of optimal thresholds is a tradeoff, wherein selecting a lower HbA1c cut-point will lead to a higher rate of eligibility and health benefits for more people, and a higher HbA1c cut-point will lead to fewer cases of diabetes prevented but greater “economic efficiency” in terms of diabetes cases prevented per intervention participant. Selection of optimal HbA1c thresholds also may change with the evolving science, as better evidence on the biologic effectiveness of lower-intensity interventions and effects of lifestyle interventions on additional outcomes could pave the way for a more comprehensive, tiered approach to risk stratification.
    American journal of preventive medicine 11/2012; 44(4):S375–S380. DOI:10.1016/j.amepre.2012.12.012 · 4.53 Impact Factor
  • Mohammed K Ali · Justin B. Echouffo-Tcheugui · David F Williamson
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    ABSTRACT: We conducted a systematic review and meta-analysis of twenty-eight US-based studies applying the findings of the Diabetes Prevention Program, a clinical trial that tested the effects of a lifestyle intervention for people at high risk for diabetes, in real-world settings. The average weight change at twelve months after the intervention was a loss of about 4 percent from participants' baseline weight. Change in weight was similar regardless of whether the intervention was delivered by clinically trained professionals or lay educators. Additional analyses limited to seventeen studies with a nine-month or greater follow-up assessment showed similar weight change. With every additional lifestyle session attended, weight loss increased by 0.26 percentage point. We conclude that costs associated with diabetes prevention can be lowered without sacrificing effectiveness, using nonmedical personnel and motivating higher attendance at program sessions.
    Health Affairs 01/2012; 31(1):67-75. DOI:10.1377/hlthaff.2011.1009 · 4.97 Impact Factor
  • Ann Albright · David Williamson
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    ABSTRACT: Preventing type 2 diabetes is a public health challenge that cannot be met by the clinical care sector acting alone. It requires complimentary and shared public health and clinical approaches that together achieve more than each can accomplish unaided (Fig. 12.1). The clinical sector must be involved in assessing patients’ risk for type 2 diabetes, discussing risk status with patients and their support network, referring (or encouraging) high-risk patients to participate in proven, community-based structured lifestyle programs, and, where necessary, prescribing medications for those at risk for and treating those who go on to develop diabetes.
    Prevention of Type 2 Diabetes, 01/2012: pages 203-219; , ISBN: 978-1-4614-3313-2
  • David F Williamson
    JAMA The Journal of the American Medical Association 08/2011; 306(6):608; author reply 609-10. DOI:10.1001/jama.2011.1106 · 35.29 Impact Factor
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    ABSTRACT: This study aimed to test the "healthy immigrant" hypothesis and assess health heterogeneity among newly arrived working-age immigrants (18-64 years) from various regions of origin. Using the 5% sample of the 2000 U.S. Census (PUMS), we found that, compared with their native-born counterparts, immigrants from all regions of the world were less likely to report mental disability and physical disability. Immigrants from selected regions of origin were, however, more likely to report work disability. Significant heterogeneity in disabilities exists among immigrants: Those from Eastern Europe and Southeast Asia reported the highest risk of mental and physical disability, and those from East Asia reported the lowest risk of physical disability. Furthermore, Mexican immigrants reported the lowest risk of mental disability, and Canadian immigrants reported the lowest risk of work disability. Socioeconomic status and English proficiency partially explained these differences. The health advantage of immigrants decreased with longer U.S. residence.
    Population Research and Policy Review 06/2011; 30(3):399-418. DOI:10.1007/s11113-010-9194-x · 0.76 Impact Factor
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    Diabetes Care 02/2011; 34(2-2):e21. DOI:10.2337/dc10-2155 · 8.42 Impact Factor
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    Ronald T Ackermann · Yiling J Cheng · David F Williamson · Edward W Gregg
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    ABSTRACT: The American Diabetes Association (ADA) recently proposed the use of hemoglobin A1c as a practical and valid strategy to identify high-risk people for whom delivery of an intensive lifestyle intervention to prevent type 2 diabetes is likely to be cost effective. To estimate composite risks of developing diabetes and cardiovascular disease (CVD) for adults with different hemoglobin A1c test results and to compare those risks with those of adults who met the 2003 ADA definition for prediabetes. Cross-sectional data from the 2005-2006 National Health and Nutrition Examination Survey were analyzed in 2009. The method of Stern and colleagues was used to estimate the 7.5-year probability of type 2 diabetes, and the Framingham General CVD Risk Engine was used to estimate the 10-year probability of CVD for adults with different A1c results. Sample weights were used to account for sampling probability and to adjust for noncoverage and nonresponse. Among adults meeting the 2003 ADA definition for prediabetes, the probabilities for incident type 2 diabetes (over 7.5 years) and CVD (over 10 years) were 33.5% and 10.7%, respectively. Use of A1c alone, in the range of 5.5% to <6.5%, would identify a population with comparable risks for diabetes (32.4% [SE=1.2%]) and CVD (11.4% [SE=0.6%]). A slightly higher cutoff (≥5.7%) would identify adults with risks of 41.3% (SE=1.5%) for diabetes and 13.3% (SE=0.8%) for CVD-risks that are comparable to people enrolled in the Diabetes Prevention Program. A1c-based testing in clinical settings should be considered as a means to identify greater numbers of adults at high risk of developing type 2 diabetes and CVD.
    American journal of preventive medicine 01/2011; 40(1):11-7. DOI:10.1016/j.amepre.2010.09.022 · 4.53 Impact Factor
  • C. Huang · Z. Li · K. M. Venkat Narayan · D. F. Williamson · R. Martorell
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    ABSTRACT: The Chinese Famine of 1959–1961 caused up to 30 million deaths. It varied in intensity across China and affected rural areas disproportionately. Data from the China–U.S. Collaborative Project for Neural Tube Defect Prevention on 31, 449 women (born 1957–1963) and their offspring birth size were recorded in 1993–1996. We used a measure of famine intensity at county level based on the size of famine-born cohorts relative to cohorts preceding and following the famine in a difference-in-difference model that compared offspring birth size of pre-famine (1957–1958; exposed between 0.5 and 4.5 years), famine (1959–1961; prenatal and up to 2.5 years) and post-famine (1962; some exposed in early pregnancy) cohort groups to that of the unexposed 1963 cohort. The model corrected for age and cohort trends and estimated associations between maternal famine exposure and offspring birth size for the average level of famine intensity across counties, and included adjustment for clustering. In rural areas and in pre-famine and famine cohorts, exposure to famine was associated with larger weight (69 g; 95% CI 30, 108), length (0.3 cm; 95% CI −0.0, 0.5) and birth body mass index (0.1 kg/m2; 95% CI 0.0, 0.2). In urban areas, however, exposure to famine was not associated with offspring birth size. Our findings in rural areas suggest that severe and prolonged famine leads to larger newborn size in the offspring of mothers exposed to famine in utero and during the first few years of life; less severe famine in urban areas however, appeared to have no impact. The markedly increased mortality in rural areas may have resulted in the selection of hardier mothers with greater growth potential, which becomes expressed in their offspring.
    12/2010; 1(06). DOI:10.1017/S2040174410000504
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    ABSTRACT: In studies of weight and mortality, the construct of reverse causation has come to be used to imply that the exposure-outcome relation is biased by weight loss due to preexisting illness. Observed weight-mortality associations are sometimes thought to result from this bias. Evidence for the occurrence of such bias is weak and inconsistent, suggesting that either the analytical methods used have been inadequate or else illness-related weight loss is not an important source of bias. Deleting participants has been the most frequent approach to control possible bias. As implemented, this can lead to deletion of almost 90% of all deaths in a sample and to deletion of more overweight and obese participants than participants with normal or below normal weight. Because it has not been demonstrated that the procedures used to adjust for reverse causation increase validity or have large or systematic effects on relative risks, it is premature to consider reverse causation as an important cause of bias. Further research would be useful to elucidate the potential effects and importance of reverse causation or illness-related weight loss as a source of bias in the observed associations between weight and mortality in cohort studies.
    American journal of epidemiology 11/2010; 173(1):1-9. DOI:10.1093/aje/kwq341 · 5.23 Impact Factor
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    ABSTRACT: People with diabetes can suffer from diverse complications that seriously erode quality of life. Diabetes, costing the United States more than $174 billion per year in 2007, is expected to take an increasingly large financial toll in subsequent years. Accurate projections of diabetes burden are essential to policymakers planning for future health care needs and costs. Using data on prediabetes and diabetes prevalence in the United States, forecasted incidence, and current US Census projections of mortality and migration, the authors constructed a series of dynamic models employing systems of difference equations to project the future burden of diabetes among US adults. A three-state model partitions the US population into no diabetes, undiagnosed diabetes, and diagnosed diabetes. A four-state model divides the state of "no diabetes" into high-risk (prediabetes) and low-risk (normal glucose) states. A five-state model incorporates an intervention designed to prevent or delay diabetes in adults at high risk. The authors project that annual diagnosed diabetes incidence (new cases) will increase from about 8 cases per 1,000 in 2008 to about 15 in 2050. Assuming low incidence and relatively high diabetes mortality, total diabetes prevalence (diagnosed and undiagnosed cases) is projected to increase from 14% in 2010 to 21% of the US adult population by 2050. However, if recent increases in diabetes incidence continue and diabetes mortality is relatively low, prevalence will increase to 33% by 2050. A middle-ground scenario projects a prevalence of 25% to 28% by 2050. Intervention can reduce, but not eliminate, increases in diabetes prevalence. These projected increases are largely attributable to the aging of the US population, increasing numbers of members of higher-risk minority groups in the population, and people with diabetes living longer. Effective strategies will need to be undertaken to moderate the impact of these factors on national diabetes burden. Our analysis suggests that widespread implementation of reasonably effective preventive interventions focused on high-risk subgroups of the population can considerably reduce, but not eliminate, future increases in diabetes prevalence.
    Population Health Metrics 10/2010; 8(1):29. DOI:10.1186/1478-7954-8-29 · 2.11 Impact Factor
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    ABSTRACT: We examined ranges of A1C useful for identifying persons at high risk for diabetes prior to preventive intervention by conducting a systematic review. From 16 included studies, we found that annualized diabetes incidence ranged from 0.1% at A1C <5.0% to 54.1% at A1C >or=6.1%. Findings from 7 studies that examined incident diabetes across a broad range of A1C categories showed 1) risk of incident diabetes increased steeply with A1C across the range of 5.0 to 6.5%; 2) the A1C range of 6.0 to 6.5% was associated with a highly increased risk of incident diabetes, 25 to 50% incidence over 5 years; 3) the A1C range of 5.5 to 6.0% was associated with a moderately increased relative risk, 9 to 25% incidence over 5 years; and 4) the A1C range of 5.0 to 5.5% was associated with an increased incidence relative to those with A1C <5%, but the absolute incidence of diabetes was less than 9% over 5 years. Our systematic review demonstrated that A1C values between 5.5 and 6.5% were associated with a substantially increased risk for developing diabetes.
    Diabetes care 07/2010; 33(7):1665-73. DOI:10.2337/dc09-1939 · 8.42 Impact Factor
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    Katherine M Flegal · David F Williamson
    Obesity 06/2010; 18(6):1069; author reply 1069-70. DOI:10.1038/oby.2010.37 · 3.73 Impact Factor
  • David F Williamson
    The Journals of Gerontology Series A Biological Sciences and Medical Sciences 05/2010; 65(8):904; author reply 905. DOI:10.1093/gerona/glq075 · 5.42 Impact Factor
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    ABSTRACT: Diabetes can be prevented or delayed in high-risk adults through lifestyle modifications, including dietary changes, moderate-intensity exercise, and modest weight loss. However, the extent to which U.S. adults with prediabetes are making lifestyle changes consistent with reducing risk is unknown. This study aimed to study lifestyle changes consistent with reducing diabetes risk and factors associated with their adoption among adults with prediabetes. In 2009, data were analyzed from 1402 adults aged > or =20 years without diabetes who participated in the 2005-2006 National Health and Nutrition Examination Survey and had valid fasting plasma glucose and oral glucose tolerance tests. The extent to which adults with prediabetes report that in the past year they tried to control or lose weight, reduced the amount of fat or calories in their diet, or increased physical activity or exercise was estimated and factors associated with the adoption of these behaviors were examined. Almost 30% of the U.S. adult population had prediabetes in 2005-2006, but only 7.3% (95% CI=5.5%, 9.2%) were aware they had it. About half of adults with prediabetes reported performing diabetes risk reduction behaviors in the past year, but only about one third of adults with prediabetes had received healthcare provider advice about these behaviors in the past year. In multivariate analyses, provider advice, female gender, and being overweight or obese were positively associated with all three risk reduction behaviors. Adoption of risk reduction behaviors among U.S. adults with prediabetes is suboptimal. Efforts to improve awareness of prediabetes, increase promotion of healthy behaviors, and improve availability of evidence-based lifestyle programs are needed to slow the growth in new cases of diabetes.
    American journal of preventive medicine 04/2010; 38(4):403-9. DOI:10.1016/j.amepre.2009.12.029 · 4.53 Impact Factor
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    ABSTRACT: Estimates of obesity-associated deaths in the United States for 1991 were published by Allison et al (JAMA 1999;282:1530-8) and subsequently for 2000 by Mokdad et al (JAMA 2004;291:1238-45). Flegal et al (JAMA 2005;293:1861-7) then published lower estimates of obesity-associated deaths for 2000. All 3 studies incorporated data from the first National Health and Nutrition Examination Survey (NHANES I). The objective was to clarify the effects of methodologic differences between the 3 studies in estimates of obesity-associated deaths in the US population by using NHANES I hazard ratios. The earlier reports used imputed smoking data for much of the NHANES I sample rather than the available reported data and applied a method of calculating attributable fractions that did not adjust for the effects of age, sex, and smoking on mortality in the target US population and did not account for effect modification by age. The effects of these and other methodologic factors were examined. The NHANES I hazard ratios in the earlier reports were too low, probably because of the imputed smoking data. The low hazard ratios obscured the magnitude and direction of the bias arising from the incompletely adjusted attributable fraction method. When corrected hazard ratios were used, the incompletely adjusted attributable fraction method overestimated obesity-associated mortality in the target population by >100,000 deaths. Methodologic sources of bias in the reports by Allison et al and Mokdad et al include the assessment of smoking status in NHANES I and the method of calculating attributable fractions.
    American Journal of Clinical Nutrition 03/2010; 91(3):519-27. DOI:10.3945/ajcn.2009.28222 · 6.77 Impact Factor
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    K. M. Venkat Narayan · David F. Williamson
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    ABSTRACT: Although the idea of preventing type 2 diabetes has been articulated since the discovery of insulin, only in the past decade have clinical trials demonstrated that diabetes can be prevented or delayed. These trials found lifestyle intervention reduces diabetes incidence by over 50% and is more efficacious than metformin. Evidence from prevention trials comes from persons with “pre-diabetes” in which blood glucose levels are elevated but not yet in the diabetes range. In normoglycemic persons, lifestyle or drug intervention has little impact on diabetes incidence. Prevention programs are often conducted outside the clinical sector where participants’ glycemic status is usually unknown; these programs may include many normoglycemic participants, which greatly reduces cost-effectiveness. An economically sustainable system for diabetes prevention will require effective partnerships among the clinical sector, community-based lifestyle programs, and third-party payers to ensure that limited resources for diabetes prevention are focused on persons at high risk of diabetes.
    Journal of General Internal Medicine 02/2010; 25(2):154-157. DOI:10.1007/s11606-009-1148-9 · 3.45 Impact Factor
  • David F Williamson · K M Venkat Narayan
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    ABSTRACT: Allocating scarce resources for dysglycemia intervention requires identification of persons who will benefit. Identification has two steps: screening followed by diagnosis. Lowering a screening test's cut-off score identifies more persons with dysglycemia, but causes more normoglycemic persons to receive diagnostic testing. Raising a test's cut-off score reduces needless diagnostic testing, but increases the number falsely identified as not having dysglycemia. With limited budgets for intervention, raising a screening test's cut-off score may be appropriate. With ample budgets, lowering the test's cut-off score may be appropriate. Screening tests are most efficient in populations with high prevalence of dysglycemia.
    09/2009; 3(4):211-7. DOI:10.1016/j.pcd.2009.08.006
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    Mitchell H Gail · Barry Graubard · David F Williamson · Katherine M Flegal
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    ABSTRACT: No abstract is available for this article.
    Statistics in Medicine 04/2009; 28(8):1315-7. DOI:10.1002/sim.3473 · 1.83 Impact Factor

Publication Stats

24k Citations
1,909.92 Total Impact Points


  • 1987–2013
    • Centers for Disease Control and Prevention
      • • Division of Diabetes Translation
      • • National Center for Health Statistics
      • • National Center for Chronic Disease Prevention and Health Promotion
      Атланта, Michigan, United States
  • 1994–2012
    • Emory University
      • • Department of Global Health
      • • Centers for Disease Control and Prevention
      • • Department of Family and Preventive Medicine
      Atlanta, Georgia, United States
  • 2006
    • National Cancer Institute (USA)
      베서스다, Maryland, United States
    • NCI-Frederick
      Фредерик, Maryland, United States
  • 2005
    • University of California, Berkeley
      Berkeley, California, United States
  • 1999
    • Columbia University
      New York, New York, United States
    • St. Luke's Hospital
      Cedar Rapids, Iowa, United States
  • 1995
    • Georgia Health Sciences University
      Augusta, Georgia, United States
  • 1989
    • Zoo Atlanta
      Atlanta, Georgia, United States