BMC Public Health 2007, 7:277 http://www.biomedcentral.com/1471-2458/7/277 as the individual who is the panel member for the NFO panel and typically was the adult female of the household. Due to the self-administration approach, the head of household was able to consult with other adult family members and personal health records to report whether they or any adult member had been told by their doctor or nurse that they had any of the conditions. Risk factors (RFs) associated with diabetes mellitus In addition to self-reported DM, the screening question- naire included the following items: age, family history, adiposity (as measured by body mass index [BMI]) and presence of potential DM-related predictors such as abdominal obesity, hypertension, dyslipidemia, and car- diovascular disease (CVD) events. The SHIELD data were analyzed and compared with overall prevalence estimates from NHANES 1999–2002 data (which used both self- reported and laboratory values). The following factors were hypothesized to be associated with a diagnosis of DM: (1) abdominal obesity (waist circumference), (2) over- weight/obesity (BMI, calculated from self-reported height and weight), (3) cholesterol problems (reported diagnosis of cholesterol problems of any type), (4) hypertension (reported diagnosis of high blood pressure), and (5) his- tory of CVD ("heart disease/myocardial infarction, narrow or blocked arteries, stroke, coronary artery bypass graft surgery/angioplasty/stents/surgery to clear arteries"). Respondents were provided with a measuring tape and while standing were asked to hold the tape measure loosely around their waist at the level of their navel ("belly button") to determine waist circumference. These CVD parameters were confirmed using logistic regression analyses on the SHIELD screening data, which indicated that each RF had independent and similar pre- dictive power for diagnosis of DM. Specific thresholds for waist circumference and BMI were determined as described below in "Data Analysis." Sampling for baseline survey Once the screening questionnaire was returned, baseline (BL) follow-up disease impact questionnaires were mailed in September and October of 2004 to a represent- ative stratified random sample of individuals based upon several subgroups of interest, which included: (1) type 1 DM (defined as reported type 1 diagnosis made at age ≤21 years plus insulin use), (2) type 2 DM (defined as reported type 2 diagnosis made at age >21 years), and (3) individ- uals without DM but with 0, 1, 2, 3, 4, or 5 RFs. Less than 12% of baseline survey respondents were from the same household and the correlation between responses for individuals from the same household was minimal (r < 0.03) and not statistically significant. After the BL ques- tionnaires were returned, a subgroup of 600 responses was created from the total response pool to represent a general population sample for comparison with the DM and RF groups. This "population-based" control group sampled returns from the type 1 and type 2 DM groups and each RF level in proportions to reflect the overall prev- alence of that stratum in the general population. This group was constructed by stratified random sampling (without replacement) of 600 individuals from within the disease and RF groups in proportion to their rates of occurrence in the population (as estimated from the screening study). Baseline (BL) questionnaire The BL questionnaire consisted of 64 detailed questions regarding comorbidities, symptoms, and family history; medical testing; health-related quality of life, depression and health-related disruptions of normal activities; diet, exercise and other health-related behaviors; healthcare insurance coverage and resource use; and impact of health problems on work productivity. The BL questionnaire also included several validated sur- vey instruments including: (1) the 12-item Short Form Health Survey [11] (SF-12v2;) and the European Quality of Life (EuroQoL) EQ-5D instrument [12-15] to assess quality of life; (2) Sheehan Disability Scale [16] to assess the level of disruption felt in work, social life, and family/ home life due to health problems; (3) 9-item Patient Health Questionnaire (PHQ-9) [17] to assess depression; and (4) the Work Productivity and Activity Impairment Questionnaire: General Health, version 2.0 (WPAI-GH) to assess work productivity and performance of other reg- ular activities [18]. In addition, the questionnaire included some, but not all, questions from the following instruments: the Diet and Health Knowledge Survey (DHKS), the Press-Ganey Satis- faction Questionnaire, and the International Physical Activity Questionnaire (IPAQ), which was developed to assess health-related aspects of physical activity and sed- entary behaviors [19]. Data analysis Estimated national prevalence of DM and each RF was cal- culated using SHIELD and NHANES data. Logistic regres- sion analyses of the SHIELD screening data with diagnosis of type 2 DM as the dependent variable and sociodemo- graphic characteristics and RFs as explanatory variables were used to identify those factors associated with being diagnosed with type 2 DM. In addition, specific thresh- olds for waist circumference and BMI were determined separately for men and women, using the area under receiver operating characteristic (ROC) curves to quantify sensitivity and specificity. The waist circumference or BMI value that maximized the area under the ROC curve was chosen as the threshold (point that maximized the Page 3 of 9 (page number not for citation purposes)