Kuhrs et al. BMC Public Health 2012, 12:190 http://www.biomedcentral.com/1471-2458/12/190 risks via the odds ratio (OR), a conditional logistic regression procedure was performed [26]. First, univari- ate analysis was conducted to examine individual risk factors. For the multivariate logistic regression model, the following potential risk factors were considered: high body mass index (BMI > 27.0 kg/m2), high alcohol consumption (> 0.76 L per month [27]), smoking (ever vs. never smoking), sports (intensive sports activities vs. no activities), consumption of fruits and vegetables (daily or several times a week vs. less consumption), consumption of sweets, salt intake, burden of work (heavy physical work), education, medical history (dia- betes mellitus, hypertension, elevated cholesterol levels, drug treatment of high blood pressure), diseases of the parents (diabetes mellitus, hypertension, CVD and cancer). For some of the above-mentioned potential risk fac- tors, missing values occurred in both the case and in the control group. Therefore the multiple imputation method was used [28]. Multiple imputation improves parameter estimates, standard errors, and test statistics when reconciling missing data. For information on BMI 9% of the data were missing. For the variables “blood pressure”, “cholesterol levels” and the illnesses of par- ents, the answer “I do not know” was given by 5, 26 and 37 (father) or 20% (mother) of respondents, respectively. These variables were also processed using multiple imputation. For the determination of a final multivariate model, backward selection was conducted. To compare the pre- valence of CVD risk factors in the Aussiedler with that of the German population, we used data from other large studies and surveys [29-36]. Results For 103 of the 440 relatives of the potential cases, a contact telephone number was available. Among those, 58 interviews were performed (response rate including dropouts excluding cancelled due to illness, death or wrong contact data 73%). The remaining cases were contacted by mail only, through available addresses of relatives. Of those, 40 interviews were performed. The total number of cases for analysis is therefore 58 + 40 = 98. Calculation of an overall response rate is difficult since not all relatives of the cases may have received the letter or had a physical condition that allowed a response. Only few answered the letter, this indicates that they did not want to participate. Assuming half of all without telephone could have answered, we obtain an overall response estimate of (58 + 40)/(103 + 337/2) = 36.1%. From the cohort, 680 potential controls were selected. Likewise, response rate of controls with telephone num- bers was 77%, and the overall response rate under the Page 4 of 9 same assumptions of potential response as for cases was 41%. The total number of interviewed controls for ana- lysis is 250. Descriptive analysis Descriptive analysis of the study population is given in Table 1. The participants of the study (N = 348) are predominantly male (Ncase_male = 70 (71.4%), Ncase_female = 28 (28.6%), Ncontrol_male = 183 (73.2%), Ncontrol_female = 67 (27.0%), Table 2). Median year of birth of cases and controls was 1935. Median age of death for cases is 65 years with a range from 31 to 88 years. At the time of the interview, the average age of the control group was 75 years (range 44-97 years). Education in cases and controls both in women and men is approximately equal. The majority of participants (Ncase_male = 49%, Ncase_female = 39%, Ncontrol_male = 52%, Ncontrol_female = 39%) were blue-collar workers or farmers, and the dif- ference between cases and controls and women and men is relatively low. Housewives are 18% of the female case group and 10% of the female control group. The distribution of relevant variables is given in Table 2. Both in women and in men, there are more ever smo- kers in the cases than in controls. Whereas about 80% Table 1 Descriptive analysis of the study population cases N = 98 controls N = 250 28 (28.6%) 67 (27.0%) 70 (71.4%) 183 (73.2%) 7 (7.1%) 21 (8.4%) 31 (32.0%) 71 (28.4%) 33 (34.0%) 89 (36.0%) 12 (12.2%) 29 (12.0%) 11 (11.2%) 29 (12.0%) 4 (4.1%) 11 (4.4%) 83 (84.7%) 209 (83.6%) 10 (10.2%) 24 (9.6%) 17 (6.8%) 5 (5.1%) 20 (20.4%) 17 (17.3%) 35 (35.7%) 26 (26.5%) 49 (48.9%) 19 (19.4%) 12 (12.2%) 98 (100%) Gender Year of birth 1910-1919 Year of migration Year of death 1992-1995 f m 1920-1929 1930-1939 1940-1949 1950-1959 1960-1969 1990-1995 1996-1999 2000-2001 1996-1999 2000-2003 2004-2006 Cause of death I20-I25 Ischaemic heart diseases I30-I52 Other forms of heart 19 (19.4%) disease I60-I69 Cerebrovascular diseases other I00-I99 total