1. Overlapping Cardiovascular Risk Factors in the United States Adult Diabetes Population: Data from the Study to Help Improve Early Evaluation and Management of Risk Factors Leading to Diabetes Walter Stewart, PhD, MPH, 1 Nathaniel Clark, MD, 2 Benjamin Ansell, MD, 3 Michael L. Reed, PhD, 4 Richard Chapman, PhD, 5 Susan Grandy, PhD, 6 for the SHIELD Study Group 1 Geisinger Medical Center, Danville, Pennsylvania; 2 American Diabetes Association, Alexandria, Virginia; 3 UCLA School of Medicine, Los Angeles, California; 4 Vedanta Research, Chapel Hill, North Carolina; 5 ValueMedics Research, Falls Church, Virginia; 6 AstraZeneca, Wilmington, Delaware Abstract Introduction Objectives Methods Results References Conclusions This research was supported by Background: Diabetes is an epidemic disease in the US and worldwide and associated with increased risk for cardiovascular disease (CVD). A study was done in the US to determine rates of co-occurrence of CVD/risk factors in adults with diabetes. Methods: The Study to Help Improve Early evaluation and management of risk factors Leading to Diabetes (SHIELD) is a 5-yr, national, longitudinal study of diabetes, CVD, and metabolic risks in US adults. In 2004, a 12-item screening questionnaire was sent to 200,000 households chosen as demographically representative of US adult population. Questionnaires were completed by head of household for up to 4 adult members (≥18 years). Data were obtained on BMI, based on self-measured height and weight, and self- reported diagnosis of diabetes, hypertension (HTN) and dyslipidemia. SHIELD self- reported CVD/risk factor prevalence estimates were compared with estimates from National Health and Nutrition Examination Survey (NHANES) 1999–2002, using both self- reported and laboratory values. Results: SHIELD yielded data on 211,097 adults from 127,420 households (63.7% response rate). Of the 8.2% with diabetes (N=17,375), 56.1% were obese (BMI ≥30.0), 59.5% reported HTN, and 57.1% dyslipidemia. Co-occurrence rates were: obesity and HTN, 34.0%; obesity and dyslipidemia, 31.2%; HTN and dyslipidemia, 39.7%. Almost one- fourth (23.3%) of respondents with diabetes also reported having all 3 CVD-related risk factors. Self-reported prevalence estimates from SHIELD were similar to NHANES estimates for diabetes (8.2% vs. 9.0%) and HTN within diabetes (59.5% vs. 57.5%). In SHIELD relative to NHANES, diabetes-specific prevalence of obesity was higher (56.1% vs. 51.0%), whereas prevalence of dyslipidemia was lower (57.1% vs. 77.3%). Conclusions: In SHIELD, individuals with diabetes reported CVD, metabolic risk factors, and combinations of these factors at alarming rates. The under-reporting of dyslipidemia in SHIELD relative to NHANES highlights the need for continued education to increase awareness and improve health outcomes. Annual results from SHIELD may provide greater insight into health burden and outcomes associated with co-occurrence of these conditions.  Diabetes is an epidemic disease in the US and worldwide. About 18.2 million Americans currently have diabetes, 1 with that number projected to increase to 29 million Americans by the year 2050. 2  The risk of CVD is increased 2- to 4-fold in people with diabetes and accounts for up to 80% of mortality in these patients. 3,4  Therefore, it is important to identify the rates of co-occurrence of diabetes and other risk factors for CVD, such as hypertension, dyslipidemia, and obesity.  In addition, while these conditions are important to control as distinct risk factors, the coexistence of several risk factors may have greater than additive effects. 5-7  SHIELD (the Study to Help Improve Early evaluation and management of risk factors Leading to Diabetes) is a large, ongoing longitudinal study in the US adult population.  This study is designed to provide the medical community with information on the unmet medical need and burden of illness in patients with or at risk for diabetes, including self-reported rates of comorbid conditions. SHIELD  SHIELD is a 5-year, national, longitudinal study of diabetes, CVD, and metabolic disease risks in US adults, with data collected annually.  As the first phase of the longitudinal SHIELD study, a screener questionnaire was developed by a panel of healthcare experts (the SHIELD Study Group) and mailed to a stratified random sample of 200,000 US households (part of the National Family Opinion [NFO] household panel) in 2004.  NFO maintains a survey panel of more than 600,000 households throughout the US, constructed to represent the US population in terms of geographic residence, age of head of household and household size and income.  The screener questionnaire consisted of 12 questions and was completed by the head of household, who answered for up to 4 adult (  18 years of age) household members.  Respondents were asked if they had ever been diagnosed as having each of several conditions, including diabetes, high BP, or cholesterol problems. (We expected that respondents to a self-administered questionnaire would be unlikely to recall their actual FPG, BP, or lipid levels.)  Respondents were also asked to provide their weight and height, which were used to calculate BMI.  SHIELD data on adults  18 years old (N=211,097) were analyzed to determine self-reported prevalence of diabetes, hypertension, dyslipidemia, and obesity, as well as their overlap. NHANES  Data from SHIELD were compared with similar data from the fourth round of the National Health and Nutrition Examination Survey (NHANES 1999–2002).  NHANES produces nationally representative data about the health and nutritional status of the US civilian noninstitutionalized population.  NHANES data have the added value of including self-reported risk factors as well as clinical evaluation and laboratory testing to confirm diagnoses and to identify undiagnosed risk factors.  Because the NHANES data include laboratory values along with diagnoses and treatments, they can be used with a weighting system to estimate actual national prevalence of various conditions.  NHANES data on adults ≥18 years old (N=4257) were analyzed to estimate the prevalence of diabetes, hypertension, dyslipidemia, and obesity, as well as their overlap, in the adult US population. Identifying conditions For SHIELD, conditions were identified in the following manner:  Self-report that a healthcare professional had diagnosed the condition (i.e., “conditions that you/other adult household members have ever been told you have by a doctor or nurse”) was used for:  Diabetes (type 1 and type 2, but not gestational)  Hypertension (“high blood pressure”)  Dyslipidemia (“problems with cholesterol” or specific components, e.g., “high total cholesterol”)  Obesity was defined as BMI ≥30.0 kg/m 2 and was calculated using self- reported height and weight..  SHIELD yielded data on 211,097 adults from 127,420 households (63.7% response rate).  8.2% of SHIELD respondents reported a diagnosis of diabetes (N=17,375).  Table 1 shows the percentage of diabetes patients with each CVD risk factor:  59.5% reported hypertension  57.1% reported dyslipidemia  56.1% were obese (BMI ≥30.0 kg/m 2 )  In SHIELD and NHANES, individuals with diabetes reported CVD, metabolic risk factors, and combinations of these factors at alarming rates, underscoring the need to identify and manage the individual’s overall cardiometabolic risk.  The estimated proportions of the diabetes population with each of these factors were similar in SHIELD and NHANES, except for dyslipidemia.  The lower proportion of dyslipidemia reported in SHIELD relative to NHANES highlights the need for continued education to increase awareness of this condition and improve health outcomes in the diabetes population.  This level of difference was even more striking given the definition of dyslipidemia used for NHANES data. Were a more aggressive definition of dyslipidemia employed, including LDL-C levels >100 mg/dL or >130 mg/dL, there would be an increase in the proportion of respondents with dyslipidemia, further widening the differences in prevalence between NHANES and SHIELD.  Annual results from the SHIELD longitudinal surveys will provide greater insight into the health outcomes and overall burden of illness associated with co-occurrence of these conditions. 1. Centers for Disease Control and Prevention. National diabetes fact sheet: general information and national estimates on diabetes in the United States, 2003. Rev ed. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, 2004. 2. Boyle JP, Honeycutt AA, Narayan KMV, et al. Projection of diabetes burden through 2050. Impact of changing demography and disease prevalence in the U.S. Diabetes Care 2001;24:1936–1940. 3. Centers for Disease Control and Prevention. National diabetes fact sheet: general information and national estimates on diabetes in the United States, 2005. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, 2005. 4. Geiss LS, Herman H, Smith PJ. Mortality in non-insulin-dependent diabetes. In: National Diabetes Data Group. Diabetes in America. 2 nd ed. Bethesda, MD: National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases. 1995:233–257. 5. Neaton JD, Wentworth D, for the Multiple Risk Factor Intervention Trial Research Group. Serum cholesterol, blood pressure, cigarette smoking, and death from coronary heart disease. Arch Intern Med 1992;152:56-64. 6. Thomas F, Bean K, Guize S, et al. Combined effects of systolic blood pressure and serum cholesterol on cardiovascular mortality in young (<55 years) men and women. Eur Heart J 2002;23:528–535. 7. Liao D, Mo J, Duan Y, et al. The joint effect of hypertension and elevated LDL-cholesterol on CHD is beyond additive. European Society of Cardiology Congress, Aug 28 – Sept 1, 2004, Munich, Germany. Abstract 1377. Accessible at www.escardio.org.www.escardio.org 8. Carroll MD, Lacher DA, Sorlie PD, et al. Trends in serum lipids and lipoproteins of adults, 1960–2002. JAMA 2005;294:1773–1781. BMI = body mass index; BP = blood pressure; CHD = coronary heart disease; FPG = fasting plasma glucose; HDL-C = high-density lipoprotein cholesterol; LDL-C = low-density lipoprotein cholesterol; NFO = National Family Opinion; NHANES = National Health and Nutrition Examination Survey; SHIELD = Study to Help Improve Early evaluation and management of risk factors Leading to Diabetes; TC = total cholesterol; TG = triglycerides Abbreviations Table 1. Overlapping CVD Risk Factors Present in SHIELD Respondents with a Diabetes Diagnosis SHIELD Compared with NHANES  Self-reported prevalence estimates from SHIELD were similar to NHANES estimates for diabetes (8.2% vs. 9.0%).  Diabetes-specific prevalences (Figure 1) were:  Somewhat higher in SHIELD relative to NHANES for hypertension (59.5% vs. 57.5%) and obesity (56.1% vs. 51.0%)  Substantially lower in SHIELD relative to NHANES for dyslipidemia (57.1% vs. 77.3%) Limitations  The households participating in the NFO panel had voluntarily elected to do so, leading to the possibility of bias due to self-selection.  Household panels also tend to under-represent the very wealthy and very poor segments of the population and do not include military or institutionalized individuals.  Differences in results from these studies could be due to factors other than or in addition to SHIELD being self-report only, such as the different sampling frames and time periods used for the surveys.  For example, there has been a trend toward lower levels of TC and LDL-C in US adults over time. 8 However, it is unlikely that the time period from the NHANES surveys (1999–2002) and the SHIELD survey (2004) was sufficient to account for the large differences observed here. Analyses  The weighted data from each study were used to calculate the self-reported, national prevalence of diabetes, as well as the co-occurrence of hypertension, dyslipidemia, and obesity in those with diabetes.  For SHIELD, the returned sample (N=211,097) was upweighted to match 2003 US census data on age, gender, and household size.  For NHANES, overall prevalence estimates (self-reported plus laboratory-test confirmed) were calculated using NHANES sampling weights based on age, income, and race/ethnicity to represent the US adult population.  Standard errors were estimated using SUDAAN® to account for both the complex sample design and the use of both interview and morning examination sample data in combination.  SHIELD self-reported CVD/risk factor prevalence estimates were then compared with estimates from NHANES 1999 – 2002 using both self-reported and laboratory values. For NHANES, the following definitions were used:  Diabetes includes both previously diagnosed and undiagnosed diabetes mellitus (type 1 or type 2). Diagnosed diabetes is based on self-report (i.e., answered yes to “ Has a doctor ever told you that you have diabetes? ” ). Undiagnosed diabetes is defined using the criterion of FPG >125 mg/dL.  Hypertension was defined as either having elevated BP (systolic pressure ≥140 mm Hg or diastolic pressure ≥90 mm Hg) or taking antihypertensive medication. (BP is reported as the average of measurements taken; 78% of participants had 3 BP readings.)  Dyslipidemia was defined as any of the following: TC ≥240 mg/dL, TG >200 mg/dL, LDL-C ≥160 mg/dL, and HDL-C <40 mg/dL. No consideration of coronary heart disease risk factors was included in the definition of dyslipidemia.  Obesity was defined as BMI ≥ 30.0 kg/m 2, calculated using clinically measured height and weight. Figure 1. Percentage of Diabetes Respondents with Comorbid CVD Risk Factors: SHIELD Compared with NHANES  To determine rates of co-occurrence of other CVD risk factors in US adults with diabetes, including rates of:  Hypertension  Dyslipidemia  Obesity  Combinations of these conditions  One-fourth (25.7%) of respondents with diabetes reported also having all 3 of these CVD-related risk factors.  Co-occurrence rates of the CVD risk factors in respondents with diabetes were (Table 1):  37.4% for obesity and hypertension  34.4% for obesity and dyslipidemia  39.7% for hypertension and dyslipidemia Presented at the 7 th Scientific Forum on Quality of Care and Outcomes Research in Cardiovascular Disease and Stroke Washington, DC May 7–9, 2006