Kehl et al. BMC Public Health 2010, 10:424 http://www.biomedcentral.com/1471-2458/10/424 seven days, parents were also asked if their infant spend time (in the daytime or in the evening) in rooms in which smoking occurs, and if yes, how many minutes. Nicotine exposure was assessed for seven consecutive days by nicotine metabolite monitoring (mainly cotinine) from daily urine samples from each child and parent. Parents’ urine was collected in a vacuum blood collection tube (Vacutainer®). If infants were toilet- trained, urine was collected in a vacuum blood collec- tion tube or was absorbed with a cotton roll. Among infants who were not toilet-trained, the cotton roll was placed into the diaper to collect infants’ urine. If wet, it was returned to the hygienic vial (Salivette®, Sarstedt, Nümbrecht, Germany). Urine samples were stored at -20°C until analysis. Samples were analyzed for quantita- tive determinations of cotinine and other principal metabolites of nicotine on an Immulite 2500 analyzer via a solid-phase competitive chemiluminescent immu- noassay (reagents and analyzer from Siemens Healthcare Diagnostics, Frankfurt, Germany). The reportable range was between 10 and 500 ng/ml, and the detection limit for cotinine was 10 ng/ml. Analytical sensitivity is 5 ng/ml. Urine creatinine measurements were performed photome- trically on a Dimension RxL (Siemens Healthcare Diagnostics, Frankfurt, Germany). To adjust for dilution of the urine, CCR were calculated [12]. CCR was expressed as μg of cotinine per mmol of creatinine. Data analysis Cotinine values greater than or equal to 500 ng/ml were used to distinguish tobacco smokers from non-smokers or from passive smokers only. To interpret the cotinine values of passive smokers the following categories of exposure were used: low exposure (10 to14 ng/ml), moderate exposure (15 to 40 ng/ml), and heavy expo- sure (more than 40 ng/ml) [17]. Because the average of the multiple measurements should provide the best available estimation of ETS exposure [15], the median and the mean with standard deviation of cotinine and CCR for each infant over the study period was calculated. The intra-individual means and standard deviations were then averaged across all infants. Because the reportable range of the analyzer was 10 to 500 ng/ml, cotinine values less than 10 ng/ml were assumed to be 10 ng/ml for the calculation of descriptive statistics. All seven urine samples were obtained from 25 of the participating infants. For one infant, none of the seven urine samples could be ana- lyzed due to insufficient urine. Among all urine samples collected (191 out of 196), 13.1% could not be analyzed for cotinine and CCR due to insufficient urine. Generalized estimating equation (GEE) was used to determine how the self-reported smoking behavior of adults is related with childrens’ urinary CCR over time. Page 3 of 8 The strength of the relation between the childrens’ daily urinary CCR and the ETS exposure variables can best be determined by using GEE analysis [18]. Accurate inferences can only be determined by taking into account the within-participant correlation between repeated measurements [18]. Cotinine values of less than 10 ng/ml were set to zero before the CCRs were calculated. As the CCRs were not normally distributed, a logarithmic e-transformation was performed. The longitudinal design involved seven repeated measure- ments of infants’ urinary CCR log e. Within-infant corre- lation of these values was expected. Predictor variables included smoking outside the home (compared to inside the home), one or two smokers at home, cpd smoked in the presence of the infant at home, on the balcony, in the car or outside home, and time infants spend (in the daytime or in the evening) in rooms in which smoking occurs. Due to potential multicollinearity - the fact that independent variables should not be interrelated - each predictor variable was first entered separately into a GEE analysis. These predictor variables were adjusted for study days, one through seven, for the assessment of the within-participant correlation between repeated measurements. The significant predictor variable was again entered into a GEE analysis that was adjusted for study day, infants’ age (in months) and infants’ sex. Finally, the explained variance of the models was calcu- lated as follows: 1-(scale parameter2/standard deviation of the outcome variable2) [19]. Pearson correlation coef- ficients of CCR log e over the seven-day study period were calculated. The coefficients were required to assess the variability of CCR log e over the seven-day study per- iod, respectively, over the weekdays, including all infants. Furthermore, an intra-class coefficient (Two- Way Mixed Model, Type Absolute Agreement, Single Measures ICC) was calculated over the study period. Analyses were performed using Stata 9. Results Demographic and smoking characteristics of the adult respondents are provided in Table 1. There was no sig- nificant relation between the age of the mother and the infants’ mean cotinine value, τ = .23, p = .11. There was no significant effect of mothers’ school education on infants’ mean cotinine levels, F (2, 24) = 2.52, p = .10, ω = .10, although a small effect was observed. Addition- ally there was no significant effect of household income, F (2, 24) = 1.08, p = .36, ω = .01, and employment sta- tus of the mother, F (3, 23) = .58, p = .64, ω = -.05, on infants’ mean cotinine levels. Daily smokers’ cotinine concentrations during the study period of seven days were 500.0 or more ng/ml. The mean cotinine concentration among former and never smokers was 40.0 ng/ml (SD = 36.6).