Jinan B. Saaddine

A diabetes report card for the United States: Quality of care in the 1990s

Context There are no recent national evaluations of diabetes care in the United States. Contribution Using data from two national surveys, this study documents a substantial gap between the recommended and actual care of diabetes in the United States between 1988 and 1995. Many participants had hemoglobin A1c levels greater than 9.5% (18.0%), poorly controlled blood pressure (34.3%), and elevated cholesterol levels (58.0%). Implications As a nation, the United States is falling short in caring for patients with diabetes. A periodic national report card may help us to gauge the success of future efforts to improve. The Editors Diabetes, a typical example of chronic disease, currently affects 16 million people in the United States, causes considerable morbidity and mortality, and costs the nation almost

Improvements in diabetes processes of care and intermediate outcomes: United States, 1988-2002.

100 billion per year (1, 2). Fortunately, several efficacious treatment strategies to prevent or delay diabetes complications have emerged during the past decade, including control of glycemia, lipids, and hypertension; early detection and treatment of diabetic retinopathy, nephropathy, and foot disease; therapy with aspirin and angiotensin-converting enzyme inhibitors; and influenza and pneumococcal vaccines (3-12). Many of these treatments are cost-effective (13-17). However, their implementation in the United States remains suboptimal and varied (18-22). There is considerable pressure on U.S. health care systems to improve this situation and to deliver high-quality care while controlling costs. Influential bodies, such as the Institute of Medicine, have recently emphasized the need for strategies to improve the current quality of all medical care in the United States (23). Federal agencies are also increasingly responding with initiatives to address quality of care (24, 25). One powerful quality initiative in the United States is the Diabetes Quality Improvement Project (DQIP), which is designed to influence the care of millions of U.S. patients with diabetes (26). The standard measures of quality of diabetes care proposed by DQIP were incorporated into the National Committee for Quality Assurance (NCQA) Health Plan Employer and Data Information Set. In contrast to guidelines or clinical goals for individual care, DQIP measures are designed to assess the performance of health care systems for a population, and they offer a wayto make comparisons across health care systems. Several public and private health care systems, including the Indian Health Service (27), the Veterans Administration, the U.S. Department of Defense, and numerous managed care organizations, have adopted these indicators. Currently, there is no national reference for assessing the quality of diabetes care using a standard set of measures. Such a reference could help health care systems using DQIP measures to compare their own performance against population norms rather than the norms of other health systems. This reference could be a benchmark for assessing population changes in quality of diabetes care after implementation of national quality improvement initiatives recommended by the Institute of Medicine and NCQA. Furthermore, the use of a standard set of measures to assess the quality of diabetes care at a national level can facilitate international comparison. For this report, we used U.S. national data to provide a reference and benchmark of the quality of diabetes care as measured by the DQIP indicators. Methods Surveys We used two federally funded, nationally representative population-based surveys, the Third U.S. National Health and Nutrition Examination Survey (NHANES III) (19881994) and the Behavioral Risk Factors Surveillance System (BRFSS) (1995). Data from these two surveys were analyzed separately. Some measures came exclusively from NHANES III, and others came from BRFSS. We included adults 18 to 75 years of age who reported receiving a previous diagnosis of diabetes from a physician. Women with gestational diabetes were excluded. The two survey groups were similar in demographic characteristics, household income, health insurance coverage, and prevalence of diabetes. In NHANES III compared with BRFSS, more persons did not have a high school education (41.5% vs. 27.1%) and fewer persons used insulin (30.9% vs. 39.8%) (Table 1). Table 1. Characteristics of Persons with Self-Reported Diabetes in the Third U.S. National Health and Nutrition Examination Survey (19881994) and the Behavioral Risk Factors Surveillance System1995 The methods for NHANES III are described elsewhere (28). Briefly, the NHANES III survey used a nationally representative sample of the civilian noninstitutionalized population obtained through a complex multistage cluster sampling design, with oversampling of non-Hispanic black persons, Mexican-American persons, and elderly persons. During a household interview, data were collected on sociodemographic characteristics and medical and family history. Within 4 weeks, this was followed by a clinical examination at a mobile examination center. The procedures for blood collection and processing have also been described elsewhere (29, 30). Low-density lipoprotein (LDL) cholesterol level was calculated by using the Friedwald equation for persons who fasted more than 8 hours (n = 302). Data from NHANES III were self-reported (demographic and clinical variables) or were obtained during clinical examination (hemoglobin A1c level, cholesterol level, triglyceride level, and blood pressure). The survey included 16 705 participants 18 to 75 years of age, 1026 of whom reported receiving a diagnosis of diabetes from a physician before the survey. The BRFSS is an annual random-digit telephone survey of state populationbased samples of the civilian noninstitutionalized population of adults ( 18 years of age) in each of the 50 states and the District of Columbia. Its purpose, methods, and data analyses have been described in detail elsewhere (31). A diabetes-specific BRFSS module was used to collect data on clinical characteristics and preventive care practices from respondents with diabetes. Data from BRFSS were self-reported (dilated eye examination, lipid test, foot examination, and demographic and clinical variables). The survey included 103 929 participants 18 to 75 years of age, 3059 of whom completed the diabetes module and reported receiving a diagnosis of diabetes from a physician. We used the 1995 BRFSS so that the time frame would correspond with NHANES III. Quality-of-Care Measures We assessed the quality of diabetes care using indicators from the DQIP measurement set for which data were available. The DQIP began under the sponsorship of a coalition that included the American Diabetes Association, the Foundation for Accountability, the Health Care Financing Administration, and NCQA. The American Academy of Physicians, the American College of Physicians, the Veterans Administration, and the Centers for Disease Control and Prevention later joined the coalition. A committee of experts in diabetes care was responsible for developing the DQIP measure set. The DQIP classified the proposed indicators into three categories: accountability indicators, quality improvement indicators, and indicators under field-testing. The accountability measures, which are well grounded in evidence, have received consensus support from the scientific and medical community and have been extensively field-tested in a variety of health care settings. These measures are used to compare health systems and plans or providers. The quality improvement measures are not considered appropriate for comparing systems and plans or providers but were recommended by the NCQA for assessing internal performance. Table 2 shows all of the analyzed quality indicators and their data sources. The DQIP measures are a combination of process and outcome measures. In this paper, we use DQIP terminology and DQIP accountability and quality improvement measures. Table 2. Diabetes Quality Improvement Project Indicators and Related Data Sources Statistical Analysis All analyses were conducted by using SAS software (SAS Institute, Inc., Cary, North Carolina) for data management and SUDAAN (Research Triangle Institute, Research Triangle Park, North Carolina) to account for the complex sampling scheme, the unequal probability of selection, the oversampling of certain demographic groups, and nonresponse factors (32, 33). Level of care was estimated by the percentage, with corresponding 95% CIs, of respondents who reported each preventive care practice. We estimated prevalence by groups of sex, age, ethnicity, education, health insurance, type of treatment, and duration of diabetes. Multiple logistic regression and computation of predictive margins were used to estimate the probability of receiving DQIP indicators when we controlled for all other independent variables. Predictive margins are a type of direct standardization in which the predicted values from the logistic regression models are averaged over the covariate distribution in the population (34). Predictive margins and their standard errors from logistic regression models are provided by the current version of SUDAAN (33). Taylor linearization is used in SUDAAN for calculating these standard errors. Odds ratios are usually used to display the result from logistic regression models. However, predictive margins are easier to interpret than odds ratios, and they do not require designating one of the groups as the referent group. Results Diabetes Quality Improvement Project Accountability and Quality Improvement Measures Among adults 18 to 75 years of age with diabetes, 28.8% had had hemoglobin A1c levels tested in the past year, and 18.0% had a hemoglobin A1c level greater than 9.5%. Biannual lipid testing was done in 85.3% of participants, but only 42.0% had an LDL cholesterol level less than 3.4 mmol/L (<130 mg/dL). Only 65.7% had blood pressure less than 140/90 mm Hg, 63.3% had an annual dilated eye examination, an

The Evolving Diabetes Burden in the United States

Context As the target of many quality improvement programs, positive change in diabetes care is a good marker for progress toward better health care. Content The authors analyzed measures of diabetes care from national population-based surveys that were conducted between 1988 and 2002. Improvements occurred in the proportion of patients with hemoglobin A1c between 6% and 8%, low-density lipoprotein (LDL) cholesterol levels less than 3.4 mmol/L (<130 mg/dL), annual influenza vaccination, and aspirin use. Blood pressure did not change. Substantial proportions of patients still had poor control of LDL cholesterol levels, glycemia, and blood pressure. Implications Despite some progress, population-based measurements show that care for many Americans with diabetes falls far short of targets. The Editors Diabetes currently affects 20.8 million people in the United States (1), and that number is projected to reach 39 million by the year 2050 (2). If current trends continue, 1 in 3 Americans will develop diabetes sometime in his or her lifetime, and those with diabetes will lose, on average, 10 to 15 life-years (3). In 2002, diabetes cost the nation an estimated

Impact of Recent Increase in Incidence on Future Diabetes Burden: U.S., 2005–2050

132 billion in direct and indirect costs (4). There is, however, a growing array of effective and cost-effective treatments to help prevent or delay diabetes complications and also diabetes itself (5-17). Diabetes care has been suboptimal and varied in the United States (18-21). The National Diabetes Quality Improvement Project, founded in 1997, developed a comprehensive set of measures of diabetes quality of care (22). These measures have been incorporated into the Health Plan Employer Data and Information Set, the American Diabetes Association Provider Recognition Program, the American Medical Association Diabetes Measures Group, the Veterans Administration performance monitoring program, and other activities. The Diabetes Quality Improvement Project partners now continue their work as a coalition of 13 influential private and public national organizations called the National Diabetes Quality Improvement Alliance. The Alliance develops, maintains, and promotes the use of an updated standardized measurement set (the Alliance measures) for quality of diabetes care (23). We previously established a national benchmark for diabetes quality of care in the United States for the years 1988 to 1995 by using the standard measurements recommended by the Diabetes Quality Improvement Project (18). On the basis of nationally representative data collected in 1999 to 2002, we report the changes in the quality of diabetes care from the 1990s to 2000s by using the standardized Alliance measures for both time periods. Methods Surveys We used data from 2 federally funded, nationally representative surveys: the National Health and Nutrition Examination Survey, 19881994 (NHANES III) and 19992002 (NHANES 19992002), and the Behavioral Risk Factor Surveillance System, 1995 (BRFSS 1995) and 2002 (BRFSS 2002). As previously explained (18), we used both BRFSS and NHANES to obtain data on all the process and intermediate outcome measures needed for the analysis. In our report, we refer to NHANES III and BRFSS 1995 as baseline surveys and NHANES 19992002 and BRFSS 2002 as recent surveys. We analyzed data from each survey separately. Table 1 presents the indicators used and their respective data source. Table 1. National Diabetes Quality Improvement Alliance and Additional Indicators of Diabetes Processes and Outcomes of Care National Health and Nutrition Examination Survey The NHANES consists of nationally representative samples of the U.S. civilian, noninstitutionalized population. Samples were obtained by using a stratified multistage probability design with planned oversampling of older and minority groups. Household interviews were conducted to ascertain sociodemographic characteristics and medical and family history. After the household interview, clinical examinations were conducted at a mobile examination center. Detailed descriptions of the design and data collection of each survey have been published elsewhere (24-27). Data from NHANES were self-reported (demographic characteristics and clinical variables) or were obtained during the clinical examination (hemoglobin A1c, cholesterol level, triglycerides level, and blood pressure level). Hemoglobin A1c measurements were standardized to the Diabetes Control and Complications Trial. Cholesterol levels were standardized by using the criteria established by the Centers for Disease Control and Prevention and the National Heart, Lung, and Blood Institute Lipid Standardization Program II. For persons who fasted for more than 8 hours and had triglyceride levels less than 4.5 mmol/L (<400 mg/dL), the Friedewald equation was applied to calculate low-density lipoprotein (LDL) cholesterol level. We log-transformed triglyceride levels because data were not normally distributed. We used the average of each persons blood pressure readings that were taken in the seated position during the clinical examination. Because we did not have data on annual testing for microalbuminuria, we assessed the absence of microalbuminuria, defined as albumin-to-creatinine ratio greater than 30 g/mg in spot urine collection (28). We analyzed the data for all indicators regardless of respective treatment status. Behavioral Risk Factor Surveillance System The BRFSS is an ongoing random-digit telephone survey of the noninstitutionalized U.S. adult population in each of the 50 states and the District of Columbia. Detailed descriptions of the design and data collection of the BRFSS have been published elsewhere (29). We used the diabetes-specific module that contains questions on clinical and preventive care practices to collect information from the participants with diabetes. Participants We included adults 18 to 75 years of age who reported a previous diagnosis of diabetes by a health care professional. We excluded women with gestational diabetes. We analyzed data from 1024 participants in NHANES III and 750 participants in NHANES 19992002 who selfreported a diagnosis of diabetes and who completed the clinical examination. We analyzed data from 3065 persons in BRFSS 1995 and 13078 persons in BRFSS 2002 who identified themselves as having diabetes. Participants reporting diabetes in all surveys were similar in age, sex, education, smoking, and insurance status at each point of time. Among participants of the recent surveys compared with those of the baseline surveys, the proportion of women and non-Hispanic white persons was lower and the proportion of participants with more than a high school education and an annual household income of

Achievement of Goals in U.S. Diabetes Care, 1999–2010

20000 or more was higher (Table 2). The proportion of people with diabetes who use insulin was also lower in the recent surveys but was statistically significant only in BRFSS 2002. Table 2. Characteristics of Participants 18 to 75 Years of Age with Self-Reported Diabetes in the National Health and Nutrition Examination Survey, 19881994 and 19992002, and Behavioral Risk Factors Surveillance System, 1995 and 2002 Performance Measurement Set We assessed the quality of diabetes care by using the Alliance measurement set (22) (Table 1). We used the Alliance measures of diabetes care wherever data were available, and we also examined additional measures that may be indicators of quality care in the future: pneumococcal vaccination, diabetes education, annual dental examination, and self-monitoring of blood glucose level. The BRFSS did not have a question about smoking counseling. We, therefore, used the proportion of smokers who tried to quit smoking. Questions about aspirin use were asked only every other year, so we used data from BRFSS 1996 for this variable. Statistical Analysis We conducted statistical analyses by using SAS for Windows software, version 7.0 (SAS Institute, Inc., Cary, North Carolina), for data management. We used SUDAAN software (Research Triangle Institute, Research Triangle Park, North Carolina) to obtain point estimates and SEs based on sampling weights to produce national estimates accounting for the complex survey design. We used Taylor series linearization for variance estimation. We computed the percentage of respondents who reported receipt of each measure. We examined the diabetes care measures by age, sex, race or ethnicity, education, insulin use, and health insurance status because our previous analysis had variations by these factors (18). However, insulin users were not asked to fast; hence, we did not examine LDL levels by insulin use. We used multiple logistic regression and predictive margins to estimate the probability of receiving or meeting the care measure after controlling for all known potential confounders. Predictive margins are a type of direct standardization, where the predicted values from the logistic regression models are averaged over the covariate distribution in the population (30). This statistic has several advantages over the odds ratio: It is not influenced if the outcome is not rare; a comparison group is not required; and it provides a measure of absolute difference rather than relative difference. We included an interaction term between time and each measure in the models to allow estimation of the probability for each period. To assess the difference in the percentage change between the 2 comparison groups, we tested the interaction term of each demographic characteristic and clinical variable (age, sex, race or ethnicity, education, insulin use, and health insurance status) with time. Role of the Funding Source No funding was received for this study. Results Half of the quality care measures that we analyzed improved between the baseline and recent surveys, and the only measure that worsened was the proportion of participants with hemoglobin A1c < 6%. We observed absolute increases for LDL levels less than 3.4 mmol/L (<130 mg/dL) (22 percentage points), annual lipid profil

Prevalence of Diabetic Retinopathy in the United States, 2005-2008

Diabetes was first described in ancient times with the cardinal symptoms of polyuria, polydipsia, and polyphagia (1). The use of uniform diagnostic criteria provided a means to reliably track the disease and unveiled a worldwide epidemic that emerged during the second half of the 20th century and is now extending into the 21st century (2-4). This report examines the evolution of the diabetes epidemic in the United States and the burden imposed by its complications. Classification of Diabetes Mellitus There are 3 major types of diabetes (5). Type 1 diabetes usually involves children and was previously called insulin-dependent diabetes mellitus or juvenile-onset diabetes. It develops when the bodys immune system destroys pancreatic cells, which make insulin. Type 1 diabetes accounts for 5% to 10% of all diagnosed cases of diabetes in the United States. Type 2 diabetes, previously called noninsulin-dependent diabetes mellitus or adult-onset diabetes, usually begins as insulin resistance, in which target tissues do not use insulin properly. It accounts for approximately 90% to 95% of all diagnosed cases of diabetes. Gestational diabetes is glucose intolerance diagnosed during pregnancy with return to a normal metabolic state after delivery. Other, lesser types of diabetes result from specific genetic conditions (such as maturity-onset diabetes of youth), surgery, drugs, malnutrition, infections, and other illnesses; these account for 1% to 5% of all diagnosed cases of diabetes (5). Diagnosis of Diabetes Uniform diagnostic criteria for diabetes were first recommended by the American Diabetes Association and the World Health Organization in 1979 and 1980 and were updated in the late 1990s (5, 6). Currently, when typical symptoms of diabetes are present (for example, polyuria, polydipsia, or unexplained weight loss), a casual (that is, at any time without regard to the last meal) plasma glucose level of 11.1 mmol/L (200 mg/dL) or greater confirms the diagnosis. In addition, the diagnosis can be made with a fasting plasma glucose level of 7.0 mmol/L (126 mg/dL) or greater or an oral glucose tolerance test with a 2-hour value of 11.0 mmol/L (200 mg/dL) or greater. A positive diagnostic test result should be followed by a repeated test on a different day to confirm the clinical diagnosis. In contrast, for epidemiologic studies, a single fasting plasma glucose or 2-hour oral glucose tolerance test measurement is used to estimate the prevalence of diabetes in a population. Tracking the Diabetes Epidemic Currently, 3 periodic national surveys track diabetes prevalence in the United States. The National Health Interview Survey and National Health and Nutrition Examination Survey (NHANES) use national population-based samples and query persons in face-to-face interviews about whether they have been told by their health care provider that they have diabetes. A third survey, the Behavioral Risk Factors Surveillance System, asks a similar question of state-based population samples during telephone interviews of residents. Unlike the other 2 surveys, NHANES includes a laboratory-based examination that measures glucose levels and identifies persons with undiagnosed diabetes. All 3 surveys provide national estimates of the prevalence of diagnosed diabetes. Only the Behavioral Risk Factors Surveillance System provides state-based estimates, and only NHANES provides estimates of undiagnosed diabetes. Prevalence In 2002, an estimated 6.3% of the U.S. population (about 18.2 million persons) had diabetes (7). Diabetes affects various sociodemographic groups unequally. According to data from the National Health Interview Survey, persons 65 years of age or older make up almost 40% of all persons with diagnosed diabetes, and the prevalence in this age group is more than 10 times that in persons younger than 45 years of age (8). Minority race and ethnic groups, including black persons, Hispanic persons, and Native Americans, are disproportionately affected; the prevalence of diagnosed diabetes is generally 2 to 4 times higher in these groups than in the majority population (Figure 1) (7, 8). Figure 1. Prevalence of diagnosed diabetes in people 20 years of age and older by age and race or ethnicity, United States, 2002. The longest running of the surveys, the National Health Interview Survey, found a 4- to 8-fold increase over the last half-century in the number of persons who received a diagnosis of diabetes (1.6 million in 1958 and 12.1 million in 2000) and the prevalence of diagnosed diabetes in the United States (0.9% in 1958 and 4.4% in 2000) (Figure 2) (8, 9). Increases occurred across all demographic categories, including sex, race or ethnicity, and age (8). Between 1990 and 2001, data from the Behavioral Risk Factors Surveillance System indicate that the largest relative increases in diagnosed diabetes occurred in persons 30 to 39 and 40 to 49 years of age (95% and 83%, respectively); increases in other age groups were 40% in persons 18 to 29 years of age, 49% in persons 50 to 59 years of age, 42% in persons 60 to 69 years of age, and 33% in persons 70 years of age or older (10, 11). Although the magnitude of the increase varied, the prevalence of diagnosed diabetes among adults increased in every state in the United States (Figure 3). Trends are also disturbing in children and adolescents, in whom type 2 diabetes is increasingly being recognized, but as yet less commonly than type 1 diabetes (12). Studies of estimates of the incidence of type 1 diabetes in the United States, which are limited by sparse data, do not find a consistent patternsome show an increase, some show a decrease, and some remain unchanged (13). Figure 2. Prevalence of diagnosed diabetes and the number of people with diagnosed diabetes in the United States, 1958 to 2000. Figure 3. Prevalence of diagnosed diabetes (including gestational diabetes) by state in the United States, 1990 to 2001. The NHANES found that diabetes is undiagnosed in approximately one third of all persons with diabetes and that this fraction has changed little over time (14). Many factors may have affected these uptrends in the prevalence of diabetes, including changes in diagnostic criteria, improved or enhanced detection, decreasing mortality, changes in demographic characteristics of the population (for example, aging), and growth in minority populations in whom the prevalence and incidence of diabetes are increasing. Diabetes Complications Morbidity Cardiovascular Disease Data on cardiovascular disease among the diabetic population are scant. However, in 2000, 37.2% of diabetic persons age 35 years and older reported receiving a diagnosis of a cardiovascular disease (8). Prevalence of ischemic heart disease among persons with diabetes was about 14 times the rate among those without diabetes in persons 18 to 44 years of age (2.7% vs. 0.2 %), 3 times as high in persons 45 to 64 years of age (14.3% vs. 4.7%), and almost twice as high in those 65 years of age or older (20% vs. 12%) (15). Other studies have shown that the absolute rates of cardiovascular disease in persons with diabetes are higher in men than in women (as in the general population), but the relative risk (comparing those with and without diabetes) is higher in women than in men (relative risk, 2 to 4 for women and 1.5 to 2.5 for men) (16, 17). Eye, Kidney, and Lower-Extremity Disease Visual impairment and blindness are major disabling complications of diabetes. Diabetic retinopathy, the leading cause of blindness (visual acuity 20/200) in persons age 20 to 64 years, accounts for 12% of all new cases of blindness and leads to 12 000 to 24 000 new cases each year in the United States (18). Considerable visual impairment (best corrected [for example, with glasses] visual acuity in either eye < 20/40) among persons with diabetes is much more common than blindness and is associated with reduced functional status. A national population-based survey based on self-reports found that 25% of all persons with diabetes had considerable visual impairment, approximately double the proportion among persons without diabetes (19). Impairment among persons with diabetes can have several causes. Some are specific to diabetes, such as macular edema and diabetic retinopathy, and others are not specific to diabetes but occur more commonly in diabetic than in nondiabetic persons. Examples of conditions not specific to diabetes are cataracts (32% vs. 20% in persons 65 to 74 years of age) and glaucoma (6.0% vs. 2.3% in persons 65 to 74 years of age) (20-23). In the United States in 2000, diabetic nephropathy accounted for more than 40% of new cases of end-stage renal disease (that is, kidney failure that requires dialysis or transplantation) (8). Persons with diabetes are the fastest-growing group of recipients of dialysis and transplantation (8). Several factors may account for the increase in incidence, including greater recognition of the etiologic role of diabetes, more use of treatments for end-stage renal disease, a true increase in the incidence of diabetes-related end-stage renal disease, or a combination of these factors. Lower-extremity disease, which includes peripheral neuropathy and peripheral arterial disease or both, results in elevated rates of lower-extremity amputations among persons with diabetes. An estimated 15% of persons with diabetes will have a diabetic foot ulcer during their lifetime (24); of these, 6% to 43% will ultimately undergo a lower-extremity amputation (25). Among persons with diabetes who have had an amputation, as many as 85% may have had a preceding foot ulcer (25). Currently, more than half of all nontraumatic lower-extremity amputations in the United States occur among people with diagnosed diabetes (8). An analysis of the 1999 to 2000 NHANES found that an estimated 8.1% of the diabetic population age 40 years or older have peripheral arterial disease (defined as an ankle to brachial artery blood pressure ra

Prevalence of Age-Related Macular Degeneration in the US Population

In an earlier study, we had forecasted 39 million with diagnosed diabetes in 2050 in the U.S. (1,2). However, since then, national diabetes incidence increased (3) and the relative risk of death among people with diabetes declined (4,5). These changes will impact future forecasts. Incorporating these changes, we now project 48.3 million people with diagnosed diabetes in the U.S. in 2050. We also present age-, sex-, and race/ethnicity-specific forecasts, with Bayesian CIs, of the number of people with diagnosed diabetes through 2050. We used a discrete-time (1-year intervals), incidence-based Markov model with three states (no diagnosed diabetes, diagnosed diabetes, and death) (1). In each cycle of the model, projections are developed for 808 population subgroups defined by age, sex, and race/ethnicity. We estimated the age-, sex-, and race/ethnicity-specific prevalence and incidence of diabetes from the U.S. National Health Interview Survey (6–9) and modeled data for 1984–2004 to improve the precision of 2004 estimates. Models were fit using Bayesian methods with improper flat priors applied to logistic regression. We assessed adequacy of model fit using posterior predictive P values (10). Estimated prevalence of diagnosed diabetes for 2000 and 2004 were 4.35 and 5.37%, respectively, and estimated incidence were 0.42 and 0.53% per year, respectively. The age-, sex-, and race/ethnicity-specific 2004 prevalence estimates were combined with U.S. population data for 2004 (11 …

Projection of Diabetic Retinopathy and Other Major Eye Diseases Among People With Diabetes Mellitus: United States, 2005-2050

BACKGROUND Tracking national progress in diabetes care may aid in the evaluation of past efforts and identify residual gaps in care. METHODS We analyzed data for adults with self-reported diabetes from the National Health and Nutrition Examination Survey and the Behavioral Risk Factor Surveillance System to examine risk-factor control, preventive practices, and risk scores for coronary heart disease over the 1999-2010 period. RESULTS From 1999 through 2010, the weighted proportion of survey participants who met recommended goals for diabetes care increased, by 7.9 percentage points (95% confidence interval [CI], 0.8 to 15.0) for glycemic control (glycated hemoglobin level <7.0%), 9.4 percentage points (95% CI, 3.0 to 15.8) for individualized glycemic targets, 11.7 percentage points (95% CI, 5.7 to 17.7) for blood pressure (target, <130/80 mm Hg), and 20.8 percentage points (95% CI, 11.6 to 30.0) for lipid levels (target level of low-density lipoprotein [LDL] cholesterol, <100 mg per deciliter [2.6 mmol per liter]). Tobacco use did not change significantly, but the 10-year probability of coronary heart disease decreased by 2.8 to 3.7 percentage points. However, 33.4 to 48.7% of persons with diabetes still did not meet the targets for glycemic control, blood pressure, or LDL cholesterol level. Only 14.3% met the targets for all three of these measures and for tobacco use. Adherence to the recommendations for annual eye and dental examinations was unchanged, but annual lipid-level measurement and foot examination increased by 5.5 percentage points (95% CI, 1.6 to 9.4) and 6.8 percentage points (95% CI, 4.8 to 8.8), respectively. Annual vaccination for influenza and receipt of pneumococcal vaccination for participants 65 years of age or older rose by 4.5 percentage points (95% CI, 0.8 to 8.2) and 6.9 percentage points (95% CI, 3.4 to 10.4), respectively, and daily glucose monitoring increased by 12.7 percentage points (95% CI, 10.3 to 15.1). CONCLUSIONS Although there were improvements in risk-factor control and adherence to preventive practices from 1999 to 2010, tobacco use remained high, and almost half of U.S. adults with diabetes did not meet the recommended goals for diabetes care.

Forecasting Age-Related Macular Degeneration Through the Year 2050 The Potential Impact of New Treatments

CONTEXT The prevalence of diabetes in the United States has increased. People with diabetes are at risk for diabetic retinopathy. No recent national population-based estimate of the prevalence and severity of diabetic retinopathy exists. OBJECTIVES To describe the prevalence and risk factors of diabetic retinopathy among US adults with diabetes aged 40 years and older. DESIGN, SETTING, AND PARTICIPANTS Analysis of a cross-sectional, nationally representative sample of the National Health and Nutrition Examination Survey 2005-2008 (N = 1006). Diabetes was defined as a self-report of a previous diagnosis of the disease (excluding gestational diabetes mellitus) or glycated hemoglobin A(1c) of 6.5% or greater. Two fundus photographs were taken of each eye with a digital nonmydriatic camera and were graded using the Airlie House classification scheme and the Early Treatment Diabetic Retinopathy Study severity scale. Prevalence estimates were weighted to represent the civilian, noninstitutionalized US population aged 40 years and older. MAIN OUTCOME MEASUREMENTS Diabetic retinopathy and vision-threatening diabetic retinopathy. RESULTS The estimated prevalence of diabetic retinopathy and vision-threatening diabetic retinopathy was 28.5% (95% confidence interval [CI], 24.9%-32.5%) and 4.4% (95% CI, 3.5%-5.7%) among US adults with diabetes, respectively. Diabetic retinopathy was slightly more prevalent among men than women with diabetes (31.6%; 95% CI, 26.8%-36.8%; vs 25.7%; 95% CI, 21.7%-30.1%; P = .04). Non-Hispanic black individuals had a higher crude prevalence than non-Hispanic white individuals of diabetic retinopathy (38.8%; 95% CI, 31.9%-46.1%; vs 26.4%; 95% CI, 21.4%-32.2%; P = .01) and vision-threatening diabetic retinopathy (9.3%; 95% CI, 5.9%-14.4%; vs 3.2%; 95% CI, 2.0%-5.1%; P = .01). Male sex was independently associated with the presence of diabetic retinopathy (odds ratio [OR], 2.07; 95% CI, 1.39-3.10), as well as higher hemoglobin A(1c) level (OR, 1.45; 95% CI, 1.20-1.75), longer duration of diabetes (OR, 1.06 per year duration; 95% CI, 1.03-1.10), insulin use (OR, 3.23; 95% CI, 1.99-5.26), and higher systolic blood pressure (OR, 1.03 per mm Hg; 95% CI, 1.02-1.03). CONCLUSION In a nationally representative sample of US adults with diabetes aged 40 years and older, the prevalence of diabetic retinopathy and vision-threatening diabetic retinopathy was high, especially among Non-Hispanic black individuals.

Association of A1C and Fasting Plasma Glucose Levels With Diabetic Retinopathy Prevalence in the U.S. Population: Implications for diabetes diagnostic thresholds

OBJECTIVE To examine the prevalence of age-related macular degeneration (AMD) in non-Hispanic white, non-Hispanic black, Mexican American, and other racial/ethnic groups. DESIGN A US nationally representative, population-based, cross-sectional study involving a total of 5553 persons aged 40 years and older from the 2005-2008 National Health and Nutrition Examination Survey. The main outcome measure was AMD determined by the grading of 45° digital images from both eyes using a standardized protocol. RESULTS In the civilian, noninstitutionalized, US population aged 40 years and older, the estimated prevalence of any AMD was 6.5% (95% confidence interval, 5.5-7.6) and the estimated prevalence of late AMD was 0.8% (95% confidence interval, 0.5-1.3). Non-Hispanic black persons aged 60 years and older had a statistically significantly lower prevalence of any AMD than non-Hispanic white persons aged 60 years and older (odds ratio = 0.37; 95% confidence interval, 0.21-0.67). CONCLUSIONS Overall, the prevalence of any AMD in the 2005-2008 National Health and Nutrition Examination Survey was 6.5%, which is lower than the 9.4% prevalence reported in the 1988-1994 Third National Health and Nutrition Examination Survey. While this finding might be explained in part by possible methodological differences, these estimates are consistent with a decreasing incidence of AMD and suggest important public health care implications.