Participants () were about half of African-American race and half white and were of predominantly moderate-to-low social class. Children’s ages ranged from 5 to 12 years at baseline, and 62% were male.
Table 1 Geometric means and standard deviations of serum cotinine and hair cotinine at baseline stratified by parent and environmental measures of SHS exposure and by housing, child and family characteristics, Cincinnati Asthma Prevention Study (2000–2003) (more ...)
The children spent on average 17 h at home per day, during which 1.3 h were in a room with someone smoking (range 0–14 h). Thirty-six percent lived with two or more smokers, 74% with a mother and 35% with a father who smoked, with a mean of 16 cigarettes smoked in and around the home per day. Children were exposed to SHS in vehicles and others’ homes (). Exposure in other places was infrequent: at baseline, two children had exposure during after-school care, five children had any SHS exposure in restaurants, and eight children had exposure in other public places. Consequently, exposure in these places was not considered for multivariable models.
Average values for household nicotine, serum cotinine, and hair cotinine were stable during the study period (). Spearman’s rank correlations between serum and hair cotinine values overall and by study visit were all 0.5. The intraclass correlation coefficient was 0.78 for serum cotinine and 0.57 for hair cotinine, indicating that cotinine measurements within the same child across time were more similar than measurements between children.
Geometric means and standard deviations of household nicotine, serum cotinine, and hair cotinine by study visit
Every group of determinants satisfied our final model inclusion criteria for both serum cotinine and hair cotinine (). For both biomarkers, the best predictive model included variables from the parent questionnaire, household nicotine, housing and ventilation observations, and child and social class characteristics. The bulk of variance was explained by the parent questionnaire, household nicotine concentration, and housing and ventilation characteristics. Once these more proximal determinants were included, child characteristics and social class factors met our model inclusion criteria but explained only small amounts of additional variability. The final predictive model for serum cotinine contained 15 factors explaining 61% of the variance and 11 factors for hair cotinine explaining 45% of the variance.
Figure 1 Predictive ability of increasingly complex models of determinants of serum cotinine and hair cotinine. R2 values were estimated from ordinary least squares linear regression using data from the 12-month visit of the Cincinnati Asthma Prevention Study (more ...)
Predictors that remained in the final model for both serum and hair cotinine () included hours spent in a room with smoking, number of cigarettes smoked, paternal smoking, household nicotine, home size, exposure in vehicles, African-American race, parental education, health insurance, and the HOME scale.
Multiplicative change and 95% confidence intervals for serum and hair cotinine by potential determinants, unadjusted and adjusted, from the Cincinnati Asthma Prevention Study (2000–2003)
African-American race was the strongest predictor of hair cotinine. This variable was associated with an almost fourfold increase both before and after adjusting for other determinants ().
The multiplicative change value for many variables was similar when included alone and after accounting for all other important factors, indicating little colinearity among these factors (). For example, parent report that the child was in a room, in which people smoked, for over 2 h compared with 0 h was associated with a 2.3-fold increase (95% confidence interval of 1.6, 3.3) in serum cotinine without accounting for other factors, and a 1.9-fold increase (1.4, 2.6) after accounting for variables in the final model. Similarly, multiplicative change values for the number of cigarettes smoked in the home, staff perception of smokiness, season, exposure in vehicles and others’ homes, and African-American race were all robust to adjustment for other factors.
In contrast, the predictive values of a few variables were attenuated after adjusting for other determinants, suggesting that these variables were serving as proxies of other predictors of cotinine (). For example, parental education less than high school compared with a college degree was associated with a 2.4-fold (1.2, 4.7) increase in serum cotinine, but after adjustment for other variables was associated a 20% decrease: 0.8 (0.5, 1.3). Other determinants that were less predictive after adjustment included home volume, air conditioning, and health insurance status.
The nicotine dosimeter added predictive ability on top of parent report for both serum and hair cotinine (). In side-by-side comparisons (), household nicotine alone performed markedly better than parent report alone in predicting serum cotinine, as indicated by a reduction in AIC of 91 units for household nicotine but only 37 units for parent report. The predictive ability of the environmental measure of household nicotine did not offer such substantial improvements for hair cotinine ().
Table 4 Strength of ability to explain variance in serum cotinine and hair cotinine for questionnaire and environmental measures of environmental tobacco smoke as indicated by reduction in Akaike Information Criteria (AIC), Cincinnati Asthma Prevention Study (more ...)
Individual parent-report variables associated with the largest reduction in AIC included number of cigarettes/day and maternal smoking (). Substantially better prediction was achieved by including multiple parent report questions together with an indication of home size.