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      Projecting the Future Diabetes Population Size and Related Costs for the U.S.

      research-article
      , MD, MPH 1 , , PHD 1 , , PHD 2 , , MA 3
      Diabetes Care
      American Diabetes Association

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          Abstract

          OBJECTIVE

          We developed a novel population-level model for projecting future direct spending on diabetes. The model can be used in the federal budget process to estimate the cost implications of alternative policies.

          RESEARCH DESIGN AND METHODS

          We constructed a Markov model simulating individuals' movement across different BMI categories, the incidence of diabetes and screening, and the natural history of diabetes and its complications over the next 25 years. Prevalence and incidence of obesity and diabetes and the direct spending on diabetes care and complications are projected. The study population is 24- to 85-year-old patients characterized by the Centers for Disease Control and Prevention's National Health and Nutrition Examination Survey and National Health Interview Survey.

          RESULTS

          Between 2009 and 2034, the number of people with diagnosed and undiagnosed diabetes will increase from 23.7 million to 44.1 million. The obesity distribution in the population without diabetes will remain stable over time with ∼65% of individuals of the population being overweight or obese. During the same period, annual diabetes-related spending is expected to increase from $113 billion to $336 billion (2007 dollars). For the Medicare-eligible population, the diabetes population is expected to rise from 8.2 million in 2009 to 14.6 million in 2034; associated spending is estimated to rise from $45 billion to $171 billion.

          CONCLUSIONS

          The diabetes population and the related costs are expected to at least double in the next 25 years. Without significant changes in public or private strategies, this population and cost growth are expected to add a significant strain to an overburdened health care system.

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          Most cited references12

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          The UKPDS risk engine: a model for the risk of coronary heart disease in Type II diabetes (UKPDS 56).

          A definitive model for predicting absolute risk of coronary heart disease (CHD) in male and female people with Type II diabetes is not yet available. This paper provides an equation for estimating the risk of new CHD events in people with Type II diabetes, based on data from 4540 U.K. Prospective Diabetes Study male and female patients. Unlike previously published risk equations, the model is diabetes-specific and incorporates glycaemia, systolic blood pressure and lipid levels as risk factors, in addition to age, sex, ethnic group, smoking status and time since diagnosis of diabetes. All variables included in the final model were statistically significant (P<0.001, except smoking for which P=0.0013) in likelihood ratio testing. This model provides the estimates of CHD risk required by current guidelines for the primary prevention of CHD in Type II diabetes.
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            Improvements in diabetes processes of care and intermediate outcomes: United States, 1988-2002.

            Progress of diabetes care is a subject of public health concern. To assess changes in quality of diabetes care in the United States by using standardized measures. National population-based, serial cross-sectional surveys. National Health and Nutrition Examination Survey (1988-1994 and 1999-2002) and the Behavioral Risk Factor Surveillance System (1995 and 2002). Survey participants 18 to 75 years of age who reported a diagnosis of diabetes. Glycemic control, blood pressure, low-density lipoprotein (LDL) cholesterol level, annual cholesterol level monitoring, and annual foot and dilated eye examination, as defined by the National Diabetes Quality Improvement Alliance measures. In the past decade, the proportion of persons with diabetes with poor glycemic control (hemoglobin A1c > 9%) showed a nonstatistically significant decrease of 3.9% (95% CI, -10.4% to 2.5%), while the proportion of persons with fair or good lipid control (LDL cholesterol level < 3.4 mmol/L [<130 mg/dL]) had a statistically significant increase of 21.9% (CI, 12.4% to 31.3%). Mean LDL cholesterol level decreased by 0.5 mmol/L (18.8 mg/dL). Although mean hemoglobin A1c did not change, the proportion of persons with hemoglobin A(1c) of 6% to 8% increased from 34.2% to 47.0%. The blood pressure distribution did not change. Annual lipid testing, dilated eye examination, and foot examination increased by 8.3% (CI, 4.0% to 12.7%), 4.5% (CI, 0.5% to 8.5%), and 3.8% (CI, -0.1% to 7.7%), respectively. The proportion of persons reporting annual influenza vaccination and aspirin use improved by 6.8 percentage points (CI, 2.9 percentage points to 10.7 percentage points) and 13.1 percentage points (CI, 5.4 percentage points to 20.7 percentage points), respectively. Data are self-reported, and the surveys do not have all National Diabetes Quality Improvement Alliance indicators. Diabetes processes of care and intermediate outcomes have improved nationally in the past decade. But 2 in 5 persons with diabetes still have poor LDL cholesterol control, 1 in 3 persons still has poor blood pressure control, and 1 in 5 persons still has poor glycemic control.
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              UKPDS 60: risk of stroke in type 2 diabetes estimated by the UK Prospective Diabetes Study risk engine.

              People with type 2 diabetes are at elevated risk of stroke compared with those without diabetes. Relative risks have been examined in earlier work, but there is no readily available method for predicting the absolute risk of stroke in a diabetic individual. We developed mathematical models to estimate the risk of a first stroke using data from 4549 newly diagnosed type 2 diabetic patients enrolled in the UK Prospective Diabetes Study. During 30 700 person-years of follow-up, 188 first strokes (52 fatal) occurred. Model fitting was carried out by maximum likelihood estimation using the Newton-Raphson method. Diagnostic plots were used to compare survival probabilities calculated by the model with those calculated using nonparametric methods. Variables included in the final model were duration of diabetes, age, sex, smoking, systolic blood pressure, total cholesterol to high-density lipoprotein cholesterol ratio and presence of atrial fibrillation. Not included in the model were body mass index, hemoglobin A1c, ethnicity, and ex-smoking status. The use of the model is illustrated with a hypothetical study power calculation. This model forecasts the absolute risk of a first stroke in people with type 2 diabetes using variables readily available in routine clinical practice.
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                Author and article information

                Journal
                Diabetes Care
                diacare
                dcare
                Diabetes Care
                Diabetes Care
                American Diabetes Association
                0149-5992
                1935-5548
                December 2009
                : 32
                : 12
                : 2225-2229
                Affiliations
                [1] 1Department of Medicine, University of Chicago, Chicago, Illinois;
                [2] 2National Opinion Research Center at the University of Chicago, Chicago, Illinois;
                [3] 3Civic Enterprises, Washington, DC.
                Author notes
                Corresponding author: Elbert S. Huang, ehuang@ 123456medicine.bsd.uchicago.edu .
                Article
                0459
                10.2337/dc09-0459
                2782981
                19940225
                d925486b-69fc-4e9e-9ea2-9cb766a399e0
                © 2009 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. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.

                History
                : 9 March 2009
                : 12 August 2009
                Categories
                Original Research
                Epidemiology/Health Services Research

                Endocrinology & Diabetes
                Endocrinology & Diabetes

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