BMC Public Health 2009, 9:100 http://www.biomedcentral.com/1471-2458/9/100 Our underlying idea was that it would be especially the 'worried well' who might use self-tests. The questionnaire was piloted among a small sample (n = 15) of the target population to assess its readability and comprehension, and to check for possible technical errors (online research). The questionnaire assessed the following variables (see additional file 1: Questionnaire on Self-tests). 1) Whether the person had ever used, had ever considered using, or intended to use a self-test for 25 specified condi- tions, with room provided to add any tests not listed. 2) Demographic factors: age, sex, weight, height, educa- tion, nationality and country of origin. 3) Lifestyle factors: smoking behaviour, physical activity, consumption of fruit and vegetables, dietary fat intake (in terms of types and amounts of fat), alcohol consumption, use of dietary supplements, use of homeopathic medicine and blood donorship. 4) Health status: chronic illness or disability and per- ceived health. Statistical analysis Basic descriptive statistics were used to describe the use of self-tests, type of self-tests and characteristics of the respondents. Chi-square test statistics were used to assess associations between characteristics of respondents and self-test use. A multiple logistic regression analysis was conducted to identify potential selection bias due to non- response (with response versus non-response as the dependent variable and age, sex and education as inde- pendent variables). Further multiple logistic regression analyses were conducted to assess the relationship between self-test use and the various variables. Since we found some significant interactions between sex and the other independent variables, and because there were sev- eral sex-specific tests, separate analyses were done for women and men. Differences were considered to be statis- tically significant if p < 0.05 (two-sided). Analyses were performed with SPSS (Version 13.0). Results Respondents Response to the survey was 63% (n = 7919). The mean age of the respondents was 36.7 years (SD = 13.7), with age ranging range from 12 to 94. There were more women (65%) than men (35%) among the respondents. Seven- teen percent of the respondents had a low level of educa- tion, 39% an intermediate level, and 44% a high level. Non-respondents were found to be younger and less edu- cated than respondents. Almost all respondents had been born in the Netherlands (96%) and had a Dutch passport (98%). More than a quarter (26%) indicated that they had a chronic illness or disability. More than a quarter (27%) perceived their health as moderate (23%) or poor (4%). Frequency of self-testing in general and for specific self- tests Sixty-three percent of the respondents (n = 5019) had ever, i.e. before the present study, heard of diagnostic self- tests. Twenty-eight percent (n = 2220) had ever consid- ered using a self-test and 16% (n = 1263) had used at least one self-test. The mean number of self-tests among self- testers was 2.1, and 9% had used more than four self-tests. The ten most frequently reported self-tests were tests for diabetes, cholesterol, allergies, urinary infection, HIV infection, anaemia, ovulation, Chlamydia, glandular fever and hepatitis. Relevant true home tests included those for diabetes, cholesterol, ovulation, menopause and female fertility, and kidney diseases (Table 1). Three quarters of these true home tests were bought from a chemist, phar- macy or supermarket. The remaining ones were ordered through the Internet, newspapers or magazines (see addi- tional file 1: Questionnaire on Self-tests, question 3b). Seventeen percent of those who had never used a self-test said they would probably or definitely use one in the future and 54% said they would perhaps do so. Seventy- eight percent of these respondents mentioned home tests as their preferred format. Differences between self-testers and non-testers Potential differences in variables between self-testers and non-testers were calculated separately for women and men. Both female and male self-testers, when compared with non-testers, were older (p < .001), had a higher BMI (p < .001), were eating more fruit (p < .01) and less fat (p < .001), were more likely to use dietary supplements (p < .001) and homeopathic medicine (p < .001), were more likely to be blood donors (women: p < .01; men: p < .05), were more likely to report having a chronic disease (p < .001), and perceived to be in poorer health (p < .001). In addition, female self-testers were eating more vegetables (p < .05), whereas male self-testers were less likely to be physically active (p < .05). Correlates of self-test use in general Multiple logistic regression analyses were conducted to assess the relationship between self-test use and the vari- ous variables, for women and men (Table 2). Both female and male self-testers, when compared with non-testers, had a higher BMI, were eating less fat (or less saturated fat), were more likely to use dietary supplements and homeopathic medicine, were more likely to report having a chronic disease, and perceived to be in poorer health. In Page 3 of 6 (page number not for citation purposes)