128 participants with clinically manifested CHD (previous myocardial infarction or cor- onary revascularization) were excluded from the main analysis. The study protocol was approved by the local institutional review board of the University Hospital of Essen, and all participants gave written informed consent before the study. Exposure assessment. Exposure to SHS at the time of the baseline examination was assessed in a computer-aided personal interview: “Do you frequently stay in rooms where people smoke at work, at home, or at other places?” and “How many persons live and smoke in your home including yourself?” We constructed an exposure variable regarding exposure to SHS at any place (yes/no) combining information about the three possible locations of exposure and also evaluated SHS exposure according to location. Objective quantification of exposure time was not provided. Outcome assessment. Coronary athero- sclerosis was investigated through an assess- ment of the degree of CAC by electron-beam computed tomography (EBCT) (Greenland et al. 2007). The person who performed and interpreted the CAC results was blinded to participants’ characteristics, including SHS status. Noncontrast-enhanced EBCT was per- formed with a C-150 scanner (GE Imatron, South San Francisco, CA, USA) (Schmermund et al. 2006). The scanner was operated in the single-slice mode with an image acquisition time of 100 msec and a section thickness of 3 mm. Prospective electrocardiogram trig- gering was done at 80% of the R-R interval. Contiguous slices down to the apex of the heart were obtained. The CAC score was determined using the method of Agatston et al. (1990). An area of CAC was defined as at least four contiguous pixels with a computer tomography density ≥ 130 Hounsfield units. The total CAC score was computed compris- ing all calcified lesions in the epicardial coro- nary system. Analyses were performed using a Virtuoso workstation (Siemens Medical Solutions, Forchheim, Germany). Risk factor assessment. The baseline assess- ment included a self-administered question- naire, a computer-aided personal interview for personal risk factor assessment [family history of cardiovascular disease, history of hyperten- sion and diabetes, smoking history, medica- tions, socioeconomic status (SES)], laboratory tests, anthropometric measurements (weight, height), and a physical examination accord- ing to a standard protocol, including the stan- dardized measurement of brachial artery blood pressure. Current medications were coded according to the Anatomical Therapeutic Chemical Classification Index (World Health Organization Collaborating Centre for Drug Statistics Methodology 2005). Diabetes mel- litus was defined as a prior physician diagnosis of diabetes, current use of antidiabetic drugs, r a n d o m b l o o d g l u c o s e ≥ 1 1 m m o l / L (≥ 200 mg/dL), or having fasting blood glu- cose ≥ 7 mmol/L (≥ 126 mg/dL) at the time of baseline examination. We used informa- tion from self-reported medical history of such measurements. Information relevant to individual-level SES included formal education [categorized into four categories, with the high- est ≥ 18 years (equivalent to a university degree) and the lowest ≤ 10 years (equivalent to a basic school degree and no vocational training)] and employment status (full-time or part-time work of ≥ 15 hr/week, inactive or housewife, pen- sioner, and unemployed). Leisure time physical activity was assessed by questionnaire and con- verted into weekly metabolic equivalents, which were included as a continuous variable. Statistical analysis. Analyses were performed on the subgroup of never-smokers (n = 1,766) with available information on CAC, SHS expo- sure, age, sex, length of education, employment status, and other important cardiovascular risk factors [diabetes mellitus, body mass index (BMI), physical activity, and ratio of low- to high-density lipoprotein (LDL:HDL)]. We conducted unadjusted and multiple linear regression analysis with exposure to SHS at any place (yes, no) as the explanatory variable. For these analyses, CAC scores were trans- formed to normalize the distribution by using ln(CAC + 1) as the response variable. The rela- tive effect of SHS exposure is given as percent change in CAC + 1 associated with any expo- sure versus none. We used a directed acyclic graph, also known as causal diagram, to iden- tify confounders and factors that may represent SHS exposure and CAC among nonsmokers intermediate steps in the causal path (Glymour and Greenland 2008; Greenland et al. 1999; Shrier and Platt 2008). We concluded that age, sex, years of education, and employment were necessary covariates, which we used for adjust- ment in the main model. We also adjusted for other factors, including potential intermediates in extended models, such as cardiovascular risk factors diabetes mellitus, BMI, physical activ- ity, and LDL:HDL, as important predictors of CAC. Because the simultaneous adjustment for SES variables and cardiovascular risk fac- tors that are also related to SES can lead to an overadjustment, we conducted this analysis as an additional step. Because SHS exposure might exert its effect on subclinical atherosclerosis through an increase in blood pressure, we included systolic blood pressure and antihypertensive medication in a separate step. To identify the most important location of SHS exposure, we included exposure to SHS at home, at work, and at other places as separate indicator variables in one model. This analysis was repeated after limiting the study population to participants < 66 years of age. In addition, we created indicator variables representing increasing exposure to SHS (no exposure as reference, exposure only at home, and exposure at home plus exposure at work or other places). To visualize the age- and sex-specific difference between exposed and nonexposed subjects, we stratified the regres- sion analysis by exposure status (any SHS or no SHS) and plotted predicted CAC over age in both exposure groups. Separate graphs were generated for men and women, analogous Participants recall study n = 4,814 Never smoker n = 2,013 Available exposure and outcome data n = 1,904 No manifest coronary heart disease n = 1,766 Excluded n = 2,801 Smoking status: current smoker, n = 1,211; former smoker, n = 1,578; missing value, n = 12 Missing values: CAC, n = 68; SHS n = 1; other variables, n = 50 Excluded n = 109 Excluded n = 128 Manifest coronary artery disease, n = 128 Exposure to SHS n = 379 Home, n =169; at work, n = 213; other, n = 106 Figure 1. Definition of study population. No exposure to SHS n = 1,387 Environmental Health Perspectives • volume 119 | number 11 | November 2011 1557