Online Supplement: Methods



Online Supplement:

METHODS

Description of study participants and recruitment

We invited patients from the Massachusetts General Hospital (MGH) Internal Medicine Associates (IMA) primary care practice to participate. Patients with a validated diagnosis of diabetes (1) or cardiovascular disease (2) in the electronic health record (EHR) were excluded from the study. Using a validated algorithm (3), we identified metabolic syndrome risk factors using the EHR to insure that we recruited patients at actual low and high risk. For recruitment and informed consent, patients were told that the study was about “risk factors for future diabetes”, that they were invited by virtue of being IMA patients, not specifically because they were or were not at risk. The study was approved by the Partners Health Care System IRB.

After obtaining written informed consent, we performed standardized measurements. Weight and height were measured without shoes, in light street clothing. Waist circumference was measured at the top of the iliac crest; we used the average of two measurements. Blood pressure was measured sitting, after at least 5 minutes of rest; we used the average of two measurements. Venous blood was drawn for fasting glucose and insulin levels and a lipid profile (>8h of overnight fasting). Metabolic syndrome and its component criteria were diagnosed based on the updated NCEP-ATPIII criteria (4). The FHS diabetes risk score (5) was also calculated to estimate the risk of developing diabetes.

The diabetes risk perception questionnaire was self-administered, but study staff remained available to resolve language or comprehension issues. Of 435 potential eligible patients on the calling list, we contacted 230 by phone, 165 of whom agreed to meet with research staff, and 154 consented to participate. Of these, we excluded one patient for missing lab data, and three patients because of missing data in the questionnaire.

Description of the Study Questionnaire

We adapted the RPS-DD questionnaire to our population and needs. All the sections needed to calculate the Composite Score were included. The section General Attitudes included questions about Personal Control (4 questions), Worry (2 questions), and Optimistic Bias (2 questions) about getting diabetes. The section Your Attitudes about Health Risks listed 15 health problems and diseases, including Diabetes, asking to rank personal judgment from 1 (Almost No Risk) to 4 (High Risk). Also, this section asks if any of the listed diseases have been diagnosed in the patients themselves, or in family members. The Environmental Health Risks section listed 9 possible hazards and asked the patients to rank their judgment from 1 (Almost No Risk) to 4 (High Risk). The section Risks of Getting Diabetes for People in the General Public evaluates the knowledge of patients about known risk factors for diabetes (12 questions). We used the 4 questions evaluating “Dread” of diabetes (scale from 1 to 6) in the section General Attitude about Diabetes. In the section Treatment to Prevent Diabetes, patients had to give their opinion on a scale from 1 (Strongly Agree) to 4 (Strongly Disagree).

To address the issue of knowledge of metabolic syndrome as a risk factor for future diabetes, we supplemented the RPS-DD with three questions. We asked how much the patient had read or heard about diabetes, heart disease, or metabolic syndrome on a scale from 1 (not at all) to 4 (very much). We also added “Metabolic Syndrome” as one of the health problems listed in section Your Attitudes about Health Risks of the RPS-DD. Additionally, we included “Having the Metabolic Syndrome” to the list of risk factors for diabetes in the section Risks of Getting Diabetes for People in the General Public (evaluating knowledge).

To make sure that recent changes in health behaviors did not influence risk perception (according to the risk reappraisal hypothesis (6)), we asked participants if they had made any conscious changes in their lifestyles in the previous year (questions on a 1 to 4 scale). We also addressed the behavior motivation hypothesis (6) by asking patients if they intended to modify their diet, physical activity levels, or planned to lose weight in the coming year (questions on a scale from 1 to 4). Finally, we asked patients to rank their likelihood of adopting healthier lifestyle in the coming year (scale from 1 Very likely to 6 Not likely at all), and to re-rank their likelihood again after reading hypothetical situations in which their primary care physician would advise them to change their lifestyle on the basis of specific diabetes risk factors. The risk factors included in the hypothetical situations were based on 1) family history, 2) body weight and inactivity, 3) blood test results, 4) metabolic syndrome diagnosis, or 5) genetic testing.

Each sub-score and the Composite Risk Score were calculated as indicated by the scoring system of the RPS-DD. The scoring system for each section and the composite score are available on the Diabetes Research Center website of Albert Einstein College of Medicine (aecom.yu.edu/diabetes). The Cronbach ( were calculated for each sub-score and the Composite Risk Score (reported in supplementary Table 2). All the answers not included in the composite score based on a scale from 1 to 4 were dichotomized (1 and 2 vs 3 and 4) and expressed as proportions. The answers based on the Likert score from 1 to 6 are presented comparing “very likely” to the other categories; we conducted subsidiary analysis using a different split in the Likert score (1-2 vs 3-6 score) and using the 1 to 6 score as a continuous variable.

REFERENCES

1. Grant RW, Cagliero E, Sullivan CM, Dubey AK, Estey GA, Weil EM, Gesmundo J, Nathan DM, Singer DE, Chueh HC, Meigs JB: A controlled trial of population management: diabetes mellitus: putting evidence into practice (DM-PEP). Diabetes Care 27:2299-2305, 2004

2. DeFaria Yeh D, Freeman MW, Meigs JB, Grant RW: Risk factors for coronary artery disease in patients with elevated high-density lipoprotein cholesterol. American Journal of Cardiology 99:1-4, 2007

3. Hivert M-F, Grant RW, Shrader P, Meigs JB: Identifying Primary Care Patients at Risk for Future Diabetes and Cardiovascular Disease using Electronic Health Records. (submitted), 2009

4. Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, Gordon DJ, Krauss RM, Savage PJ, Smith SC, Jr., Spertus JA, Costa F, American Heart A, National Heart L, Blood I: Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation 112:2735-2752, 2005

5. Wilson PWF, Meigs JB, Sullivan L, Fox CS, Nathan DM, D'Agostino RB, Sr.: Prediction of incident diabetes mellitus in middle-aged adults: the Framingham Offspring Study. Archives of Internal Medicine 167:1068-1074, 2007

6. Brewer NT, Weinstein ND, Cuite CL, Herrington JE: Risk perceptions and their relation to risk behavior. Annals of Behavioral Medicine 27:125-130, 2004

Supplementary Table1: Characteristics of the patients, and comparisons between patients with Low vs High perceived risk for diabetes*

| |Low Perceived diabetes |High Perceived diabetes |p-value |

| |risk* |risk* | |

|Number |99 |51 | |

|Demographic Characteristics | | | |

|Age |56.4 (13.3) |55.2 (12.9) |0.60 |

|Sex (% female) |44.4 |68.6 |0.005 |

|Marital status (% married) |66.3 |58.8 |0.37 |

|Ethnic background (% white) |95.0 |96.1 |0.76 |

|Employment (% employed, full+part time) |66.3 |66.7 |0.97 |

|Education (% some college) |81.6 |78.4 |0.64 |

|Family history of Diabetes (%) |18.2 |67.6 | ................
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