Significant differences in concentrations of nicotine in residential dust were observed for all self-reported smoking categories. Pearson correlation coefficients for covariates of interest are shown in Table 15. The group of smoking variables was highly correlated as was the group of parental demographic variables, whereas the two groups of variables were negatively correlated with each other. Other variables correlated with residential-dust nicotine were age of residence, breastfeeding duration, size of sampling area , and vacuum use frequency.Tables 16 and 17 show the results of the principal components analysis for the two groups of highly correlated variables, i.e., self-reported smoking and parental demographics. Three meaningful factors were chosen to represent the 15 self-reported smoking variables and 2 factors were chosen to represent the 5 parental demographic variables. A variable was said to load on a given component if the factor loading was 0.40 or greater . Using this criterion, 12 variables describing parental smoking were found to load on the first smoking component, which was subsequently labeled the parental smoking component. Similarly, the 4 father’s smoking variables loaded on the second smoking component and 3 variables, describing other household smoking, loaded on the third component . Combined, the smoking-related principal components accounted for 65% of the total variance of all smoking variables. The demographic variable group, shown in Table 17 was described by a parental socioeconomic status component, which was loaded by parental education and income, and a parental age component,curing drying which was loaded by the mother’s age and father’s age. Combined, the summary demographic principal components accounted for 80% of the total variance explained by all demographic variables.
Several determinants of concentrations of nicotine in residential dust were identified . Notably, two principal components summarizing self-reported smoking variables were highly significant predictors of residential-dust nicotine in the final models . These principal components represented self-reported smoking for time periods of months and years before dust collection. Based on the regression model results, nicotine concentrations in residential dust seem to reflect cumulative smoking habits of residents over periods of up to several years rather than simply the current smoking pattern in the home. To verify the hypothesis that levels of nicotine in residential-dust samples reflect past smoking habits, it was useful to examine NCCLS households that reported changes in their smoking status between the initial interview and dust collection. Of the households that reported no smoking in the month before dust collection, 90 households had previously reported some smoking at the initial interview. Nicotine concentrations in residential-dust samples from these 90 households did, indeed, remain elevated . This finding suggests that nicotine may contaminant homes long after cigarette smoking has ceased, a phenomenon referred to as “third hand smoke”. In fact, investigators have reported that children living in apartments that were formerly occupied by smokers had elevated levels of residential-dust nicotine and urinary cotinine . Additionally, of the NCCLS households that reported some smoking at the time of dust collection, 5 reported no smoking at the initial interview. These 5 households had lower concentration of nicotine in residential dust than households that consistently reported smoking . Both of these findings support the conjecture that current concentrations of nicotine in residential dust may be particularly good measures of cumulative household smoking habits. Furthermore, these findings suggests that, in studies that aim to estimate prenatal or postnatal cigarette smoking exposures retrospectively, concentration of nicotine in residential dust could be a more useful surrogate than short-term exposure markers such as concentrations of nicotine in air or of cotinine in urine. After considering self-reported smoking, the age of the residence was a significant predictor of concentrations of nicotine in residential dust. Since concentrations of nicotine in residential dust increase with the age of the residence,nicotine evidently accumulates in household carpets. Thus, nicotine concentrations in residential dust likely reflect cumulative smoking habits in a household. Two measures of parental demographics, namely, the parental SES component and the parental age component, remained significant predictors of the concentrations of nicotine in residential dust, after accounting for self-reported smoking.
Table 19 illustrates that, in general, after adjusting for self-reported smoking, concentrations of nicotine in residential dust decreased with increasing parental SES and age. Interestingly, when considering the 211 households that reported no smoking at any time, the households with below median income had significantly higher concentration of nicotine in their residential dust than the households with above median income . Thus, even when no smoking was reported, low-income households had elevated concentrations of nicotine in their residential dust compared to high-income households. There are several possible explanations for the discrepancy in levels of nicotine in residential dust from self-reported non-smoking households: low-SES residences may be physically different from high-SES residences, due to unmeasured differences in ventilation, carpet types, light, moisture or microbial action; low-SES parents may be more likely to be exposed to passive cigarette smoke, and may convey nicotine into their homes on their skin or clothing; low-SES households may be more likely to have residual nicotine in residential dust from previous residents; low-SES households may use more smokeless tobacco products or; low-SES households may have under reported their smoking habits. If differential self-reporting by SES or age is present, then an objective measure of exposure to household smoking, such as concentrations of nicotine in residential dust, would be advantageous. Three other variables were significant predictors of nicotine concentrations in residential dust after adjusting for self-reported smoking and parental demographics, residence is apartment, residence is townhouse, and size of sampling area. Since apartments and townhouses generally have less square footage than single family homes, the positive regression coefficient for the variables residence is apartment and residence is townhouse are consistent with the observation of Hein et al. who found that residential-dust nicotine concentrations increased with decreasing square footage of the residence. The negative regression coefficient for the variable size of sampling area in the final model with HVS3-sampled homes indicates that, as the size of carpet sampled increased, the concentration of nicotine measured in residential dust decreased.
This relationship could be a limitation of the HVS3 sampling method and it suggests that this variable should be measured and adjusted for in models of residential-dust nicotine concentrations using HVS3 sampling. Still,drying curing including size of sampling area in the regression model had little effect on the other parameters. Given that the ultimate purpose of the NCCLS is to compare leukemia cases and controls, the effect of case-control status on measured nicotine concentration was examined. Interestingly, case-control status was not a significant predictor of nicotine concentrations and there was no indication that case parents were reporting their smoking differently than controls . This finding suggests that there was little differential misclassification of exposures in case and control households in the previous analysis of self-reported cigarette smoking in the NCCLS population . The concentrations of nicotine measured in dust from smoking and non-smoking NCCLS residences were lower than those previously reported . Specifically, the median concentrations of nicotine for self-reported non-smoking NCCLS homes was 0.3 µg/g, substantially lower than median levels reported for non-smoking homes in previous studies . As discussed in Chapter 1, lower levels of background nicotine contamination might be explained by the low prevalence of smoking in California. Alternatively, these differences may partly reflect differences in analytical methodology. Despite the lower levels of nicotine measured in the NCCLS, the nicotine concentrations in residential-dust samples were correlated with concurrently self-reported household cigarette consumption . Although concentrations of nicotine in residential dust are specific indicators of cigarette smoke contamination, the use of dust to assess children’s exposure to secondhand cigarette smoke has limitations. First, it must be assumed that children are in the home when smoking occurs. This is a reasonable expectation given the young age of the children in the NCCLS . Secondly, it must be assumed that nicotine in residential dust originated from cigarettes smoked in the home. However, a previous study found that nicotine levels in residential dust were elevated in homes where parents reported only smoking outdoors compared to homes where parents reported no smoking . Thus, parents that are exposed to cigarette smoke may convey nicotine into carpets, via their skin, clothing, or shoes without exposing their children to secondhand cigarette smoke.Future studies should consider using a long-term biomarker of exposure to cigarette smoke, such as hair nicotine, to investigate the relationship between concentrations of nicotine in residential dust and the corresponding biological dose of nicotine in children. Since parents may have tracked nicotine into their homes after smoking outside, the results of the residential-dust nicotine models may have been somewhat obscured. Specifically, the variable describing household cigarette consumption during the month before dust collection was specific to in-home smoking and it was a relatively weak predictor of nicotine concentrations in dust.
In contrast, the highly significant parental and father smoking components were based on general smoking habits . It is possible that the variable describing household cigarette consumption during the month before dust collection was a relatively weak predictor of nicotine levels, because outdoor smoking was excluded. In summary, results reported in this chapter confirmed previous findings that concentrations of nicotine in residential dust were significantly associated with self reported household smoking. Chapter 3 also presents evidence that residual smoke contamination , could persist in homes long after cigarette smoking ceased. Finally, these results suggest that concentrations of nicotine in residential dust can be used as long-term surrogates for exposures to cigarette smoke in the home. Polycyclic aromatic hydrocarbons are formed as products of incomplete combustion and there are a variety of indoor PAH sources including cigarette smoke, wood-burning fireplaces, gas appliances, and charred foods, as well as outdoor sources, including vehicle exhaust and coal-tar-based pavement sealants . Occupational exposures to PAHs have been associated with increased risks of lung, skin, and bladder cancers . Likewise, increased levels of PAH-DNA adducts have been associated with lung cancer in the general population. Moreover, in-utero PAH exposures, as measured by maternal personal air monitoring during pregnancy, have been associated with IQ deficits , cognitive developmental delays , decreased gestational size , and respiratory effects . Surrogates of PAH exposure have been measured in several environmental and biological media, including air , residential dust , urine , and blood . Because chemicals can accumulate in carpets , concentrations of PAH in residential dust may be long-term predictors of indoor PAH exposures. Moreover, because inadvertent dust ingestion could be responsible for as much as 42% of non-dietary PAH exposure in young children , levels of PAHs in residential dust may be particularly relevant to the uptake of PAHs in children. Although measurements of chemicals in residential dust are specific measures of indoor exposures, such data have rarely been collected in epidemiologic investigations. Rather, epidemiologists have classified potential exposures to chemicals based on selfreported information and/or ambient levels of chemicals measured at outdoor monitoring sites. Since self-reports and estimated outdoor air levels may not be good surrogates for indoor exposures, it is important to know the extent to which these indirect measures predict residential levels of environmental agents. Chapter 4 evaluates the predictive value of self-reported and geographic data in estimating measured levels of 9 PAHs in residential-dust samples. A global-positioning-system device was used to determine the latitude and longitude coordinates for each residence. Subsequently, three surrogates for outdoor PAH concentrations: traffic density, modeled predictions of outdoor PAH concentrations, and urban or rural location were considered. Traffic density was estimated as described previously . Briefly, a 500-m radius was drawn around each residence and traffic density was defined as the sum of the annual average daily traffic count from 2000, multiplied by the length of the road for all roads within the buffer, divided by the buffer’s area . The estimates of outdoor PAH concentrations were taken from the EPA’s 2002 National-Scale Air Toxics Assessment . The outdoor PAH concentrations were estimated at a census-tract resolution using an air dispersion model and National Emissions Inventory data, which includes major stationary sources , area sources , and mobile sources .