Abstract
Secondhand smoke exposure is estimated to account for 3,000 cancer deaths per year. Although several countries and states in the United States have passed comprehensive smoke-free laws to protect all employees, a significant number of workers are still not protected. The purpose of this study was to determine the effects of passing a comprehensive smoking ban that included bars and restaurants on biomarkers of nicotine and carcinogen exposure. The urines of nonsmoking employees (n = 24) of bars and restaurants that allowed smoking before the smoke-free law were analyzed before and after the law was passed in Minnesota. The results showed significant reductions in both total cotinine and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (free plus glucuronidated) after the ban was instituted. These results provide further support for the importance of protecting employees working in all venues. Cancer Epidemiol Biomarkers Prev; 19(4); 1016–21. ©2010 AACR.
Introduction
Exposure to secondhand smoke (SHS) has been consistently identified as a public health hazard and cause of disease (1). The U.S. Environmental Protection Agency (EPA) classified SHS as a group A carcinogen (2) and the International Agency for Research on Cancer (IARC) also classified SHS as carcinogenic to humans (3). SHS exposure has been associated with the increased risks for lung cancer (1, 3), coronary heart disease (1), and possibly respiratory disease (1). The health risks of SHS are no longer in dispute, leading to a number of local ordinances and state legislative initiatives that have restricted smoking in public places. Due to these smoking bans, cotinine levels have decreased approximately 50% to 70% in nonsmokers as observed in state and national surveys (4, 5). Although causality cannot be inferred, a cross-sectional study has shown a dose-response relationship between exposure to SHS, as measured by cotinine, and extensiveness of clean indoor air acts in subject's county of residence (6). As of August 2009, 27 states had implemented smoke-free workplace policies that include restaurants and bars (7).
Even with an overall increase in restrictions in smoking in public places, a significant number of smoke-free workplace policies still do not include hospitality venues such as bars, restaurants, and casinos. Establishment owners have proposed exemptions to these laws claiming economic hardship if these venues were to become smoke free. Unfortunately, these exemptions have resulted in greater SHS exposure among some hospitality workers. For example, bartenders have a 2- to 4-fold increase in SHS exposure compared with table waiting staff (8). Siegel and Skeer (9) found that workers in these venues had three to four times greater excess risk of lung cancer mortality than those exposed to the “typical de manifestis” levels used to determine obligatory regulation of a hazardous worksite. Similarly, in the Boston pubs tested by Repace et al. (10), before a smoking ban, indoor air quality did not meet the Occupational Health and Safety Significant Standards for environmental exposure. According to the EPA Air Quality Index, levels of outdoor fine particulate matter at several of these pubs averaged in the “very unhealthy” category. These findings on SHS exposure indicate that hospitality workers may be at an increased health risk in the absence of comprehensive indoor air policies.
The enactment of comprehensive smoke-free workplace laws in some U.S. states as well as in other countries has provided an opportunity to examine the effect of these laws on tobacco toxicant exposure among workers in these venues. The results from these studies should allay the questions about positive health benefits from comprehensive bans. These studies show significant reductions in air levels of small particulate matter (11-18), particulate polycyclic aromatic hydrocarbons (10, 19), nicotine (20), and benzene (11) after enactment of smoking bans. Similarly, countries that have instituted nationwide laws prohibiting indoor smoking in public places showed significantly lower levels of small particulate matter in these venues than countries without such bans (21). Additionally, nonsmoking workers had a significant reduction in levels of cotinine, a metabolite of nicotine (4, 11-15, 20, 22-24), or nicotine levels in hair (25). To date, no study has examined employee exposure to both nicotine and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone, a potent tobacco-specific lung carcinogen found in tobacco smoke, before and after the implementation of a comprehensive ban. Such an opportunity occurred when Minnesota enacted a comprehensive statewide law prohibiting smoking in virtually all indoor workplaces, including bars and restaurants, beginning October 1, 2007.
Materials and Methods
The study was submitted to and approved by the University of Minnesota's Institutional Review Board: Committee on the Use of Human Subjects.
Eligible subjects were nonsmokers who worked in bars, restaurants, or bowling alleys where smoking was allowed before October 1, 2007 when the statewide smoke-free law took effect. Subjects were recruited through local tobacco control leaders. They were recruited from the following Minnesota communities: Thief River Falls, Duluth, St. Cloud, Red Wing, and Moorhead. Recruitment of subjects was done by local tobacco control leaders, who contacted nonsmoking bar, restaurant, and bowling alley employees who reported work exposure to tobacco smoke. The local recruiters informed the potential participant of the opportunity to participate in a study with the University of Minnesota and ClearWay MinnesotaSM (an independent, nonprofit organization funded by the state's 1998 tobacco settlement with the tobacco industry). They were told that this study would investigate the health effects of the upcoming statewide smoke-free law. Interested potential subjects were instructed to telephone the University of Minnesota's Tobacco Use Research Center, at which time they provided oral consent to be screened over the phone for study eligibility.
Potential participants who reported they were currently not using tobacco or nicotine products and had not used them for the last 6 mo, lived in a nonsmoking household, and were employed in a hospitality venue where they were exposed to SHS for shifts of 6 or more hours were informed of the study procedures. Interested subjects were mailed a packet that included a letter describing the study, a consent form, and a Demographics and Smoke Exposure Environment form with questions about typical work hours and extent of tobacco smoke exposure at work, in the home and when socializing. The questionnaire also included questions on their employment venues, size of smoking and nonsmoking sections, and their employer's policy on smoking. Subjects mailed the consent form and the Smoke Exposure questionnaire back to the Tobacco Use Research Center in a self-addressed, stamped envelope. Subjects received a urine cup in the packet for the sample collection that was to occur within the 2 wk before the law going into effect on October 1, 2007. A Sample Day Questionnaire was to be completed the morning the urine sample was collected. This questionnaire asked about the number of hours worked the day preceding the sample collection, occupancy at the hospitality venue, and the estimated percentage of patrons who smoked during the subjects' shift. Subjects were instructed to collect the urine sample from their first void in the morning, after they had completed at least a 6 h shift the day before. The urine samples and the Sample Day Questionnaire were returned to the local contact where the sample was frozen until shipment. The samples were sent to the University of Minnesota on ice in thermal coolers through overnight shipment.
Urine cups and the second Sample Day Questionnaire were mailed out to the subjects to obtain the post–October 1 sample. Samples were collected 4 to 8 wk after the law went into effect. The post–October 1 sample was also frozen and shipped by the local contact to the University of Minnesota. Subjects were compensated $100 for providing both urine samples.
Analysis was done by the University of Minnesota Transdisciplinary Tobacco Use Research Center Biomarkers Core laboratory. Samples were analyzed for creatinine and urinary metabolites of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) and its glucuronides (NNAL-Glucs), or total NNAL, as previously described (26). In addition, samples were analyzed for total cotinine (cotinine plus cotinine-N-glucuronide) as previously described (27). The biomarker values are presented as both unadjusted and adjusted for creatinine to correct for urine volume.
Summary statistics included number and percentage of subjects for categorical variables and the mean, SD, median, range, and 95% confidence intervals for continuous variables. For statistical analysis, total NNAL levels below the detection limit were given a value of 0.0025 pmol per milligram of creatinine, whereas those for total cotinine were assigned a value of 1.0 nanogram per milligram of creatinine, both of which are approximately half the detection limit. Due to a skewed distribution to high values, both total cotinine and total NNAL were transformed to the natural logarithmic scale. The difference of the log-transformed biomarkers before and after the smoking ban is reported as the corrected geometric mean and confidence interval using Cox's method (28). These mean values represent the estimated average ratio of the measurements before and after the ban. The differences in total NNAL and total cotinine levels before and after the smoking ban were evaluated with the two-sided Wilcoxon signed-rank test.
The Spearman correlation measured the association between total NNAL and total cotinine levels and exposure to SHS at work. P values of <0.05 were considered statistically significant. All analyses were done using SAS version 9.1 (SAS Institute, Inc.).
Results
Thirty-one subjects provided oral consent by telephone and 24 returned the written consent form, completed the additional questionnaires, and returned both urine samples. All subjects were Caucasian and 15 were female. They worked in a bar and grill (n = 7), bar (n = 5), restaurant (n = 6), bowling alley (n = 5), and one subject did not provide information on their hospitality workplace. They averaged 29.6 years of age (range, 18-58) and worked an average of 3.9 (SD, 1.4) shifts per week and 6.9 (SD, 1.3) hours per shift. The mean percent of the hospitality venues considered as a smoking section was 52.2% (SD, 35.5%; range, 10-100%). The mean number of hours spent in the smoking section before the ban was estimated to be about 7.2 (SD, 2.9; range, 1-15 hours). Nineteen subjects indicated that they were around smokers most or all of the time at work and four indicated exposure to SHS outside of work some of the time (n = 3) or very often (n = 1). None or very little exposure to SHS outside of the work environment was reported by 20 of the participants.
Table 1 shows the extent of SHS exposure at the workplace and outside the workplace just before the time of urine collection before and after the statewide smoke-free law went into effect.
SHS exposure before and after the smoking ban
Amount of SHS exposure . | Before smoking ban . | After smoking ban . |
---|---|---|
Duration of shift, h (mean ± SD) | 8.0 ± 2.1 (range, 6-15) | 7.7 ± 2.4 (range, 4-15) |
Time in smoking areas, h (mean ± SD) | 7.2 ± 2.9 (range, 1-15) | — |
Smoke exposure outside of work (no. of subjects) | 4 | 1 |
Smoke exposure outside of work, h (mean ± SD) | 1.9 ± 2.8 (range, 0-6)* | 0.25 |
Amount of SHS exposure . | Before smoking ban . | After smoking ban . |
---|---|---|
Duration of shift, h (mean ± SD) | 8.0 ± 2.1 (range, 6-15) | 7.7 ± 2.4 (range, 4-15) |
Time in smoking areas, h (mean ± SD) | 7.2 ± 2.9 (range, 1-15) | — |
Smoke exposure outside of work (no. of subjects) | 4 | 1 |
Smoke exposure outside of work, h (mean ± SD) | 1.9 ± 2.8 (range, 0-6)* | 0.25 |
*The extents of exposure were 15, 35 min, 1, and 6 h for the four individuals.
Table 2 shows the data for each subject. Although one subject (#14) had a seemingly high total cotinine level, the total NNAL level was consistent for an SHS-exposed nonsmoker; therefore, his data were retained in the analysis. One subject (#24) had total NNAL and total cotinine levels that were higher than would be expected for a nonsmoker. The data were analyzed with and without this data point, and because no differences were found in the analyses, the subject's data were retained.
Preban and postban urinary total cotinine and total NNAL levels in nonsmoking hospitality workers
ID . | When . | Total cotinine . | Total NNAL . | ||
---|---|---|---|---|---|
ng/mL* . | ng/mg creatinine† . | pmol/mL* . | pmol/mg creatinine† . | ||
1 | Preban | 26 | 11.4 | LOD | LOD |
Postban | 5 | 3.2 | LOD | LOD | |
2 | Preban | 39 | 23.9 | 0.168 | 0.103 |
Postban | 5 | 8.6 | 0.026 | 0.0448 | |
3 | Preban | 18 | 9.1 | 0.035 | 0.0179 |
Postban | 6 | 4.7 | LOD | LOD | |
4 | Preban | 12 | 21.4 | LOD | LOD |
Postban | 2 | 2.9 | 0.021 | 0.0304 | |
5 | Preban | 25 | 18.7 | 0.097 | 0.0726 |
Postban | 3 | 2.2 | LOD | LOD | |
6 | Preban | 26 | 10.1 | 0.049 | 0.0192 |
Postban | LOD | LOD | LOD | LOD | |
7 | Preban | 26 | 12.0 | 0.084 | 0.0387 |
Postban | 10 | 12.5 | 0.041 | 0.0516 | |
8 | Preban | 7 | 6.1 | 0.018 | 0.0157 |
Postban | LOD | LOD | LOD | LOD | |
9 | Preban | 42 | 25.9 | 0.127 | 0.0782 |
Postban | 7 | 3.9 | 0.019 | 0.0104 | |
10 | Preban | LOD | LOD | 0.008 | 0.0034 |
Postban | 3 | Not available | LOD | LOD | |
11 | Preban | 66 | 58.4 | 0.219 | 0.194 |
Postban | LOD | LOD | LOD | LOD | |
12 | Preban | 8 | 8.1 | 0.055 | 0.0553 |
Postban | 2 | 1.2 | LOD | LOD | |
13 | Preban | LOD | LOD | LOD | LOD |
Postban | 5 | 2.2 | LOD | LOD | |
14 | Preban | 390 | 500 | 0.069 | 0.0888 |
Postban | 9 | 20.0 | 0.022 | 0.0489 | |
15 | Preban | 18 | 14.3 | 0.104 | 0.0828 |
Postban | LOD | LOD | LOD | LOD | |
16 | Preban | 4 | 3.3 | LOD | LOD |
Postban | LOD | LOD | 0.017 | 0.0120 | |
17 | Preban | LOD | LOD | LOD | LOD |
Postban | LOD | LOD | LOD | LOD | |
18 | Preban | 6 | 5.1 | LOD | LOD |
Postban | LOD | LOD | LOD | LOD | |
19 | Preban | 3 | 5.5 | 0.050 | 0.0909 |
Postban | LOD | LOD | LOD | LOD | |
20 | Preban | 9 | 6.8 | 0.038 | 0.0288 |
Postban | LOD | LOD | LOD | LOD | |
21 | Preban | 5 | 6.9 | LOD | LOD |
Postban | 2 | 2.3 | LOD | LOD | |
22 | Preban | 7 | 5.3 | 0.092 | 0.0692 |
Postban | LOD | LOD | LOD | LOD | |
23 | Preban | 15 | 20.5 | LOD | LOD |
Postban | LOD | LOD | LOD | LOD | |
24 | Preban | 1,820 | 1,456 | 0.763 | 0.611 |
Postban | 651 | 455 | 0.509 | 0.356 |
ID . | When . | Total cotinine . | Total NNAL . | ||
---|---|---|---|---|---|
ng/mL* . | ng/mg creatinine† . | pmol/mL* . | pmol/mg creatinine† . | ||
1 | Preban | 26 | 11.4 | LOD | LOD |
Postban | 5 | 3.2 | LOD | LOD | |
2 | Preban | 39 | 23.9 | 0.168 | 0.103 |
Postban | 5 | 8.6 | 0.026 | 0.0448 | |
3 | Preban | 18 | 9.1 | 0.035 | 0.0179 |
Postban | 6 | 4.7 | LOD | LOD | |
4 | Preban | 12 | 21.4 | LOD | LOD |
Postban | 2 | 2.9 | 0.021 | 0.0304 | |
5 | Preban | 25 | 18.7 | 0.097 | 0.0726 |
Postban | 3 | 2.2 | LOD | LOD | |
6 | Preban | 26 | 10.1 | 0.049 | 0.0192 |
Postban | LOD | LOD | LOD | LOD | |
7 | Preban | 26 | 12.0 | 0.084 | 0.0387 |
Postban | 10 | 12.5 | 0.041 | 0.0516 | |
8 | Preban | 7 | 6.1 | 0.018 | 0.0157 |
Postban | LOD | LOD | LOD | LOD | |
9 | Preban | 42 | 25.9 | 0.127 | 0.0782 |
Postban | 7 | 3.9 | 0.019 | 0.0104 | |
10 | Preban | LOD | LOD | 0.008 | 0.0034 |
Postban | 3 | Not available | LOD | LOD | |
11 | Preban | 66 | 58.4 | 0.219 | 0.194 |
Postban | LOD | LOD | LOD | LOD | |
12 | Preban | 8 | 8.1 | 0.055 | 0.0553 |
Postban | 2 | 1.2 | LOD | LOD | |
13 | Preban | LOD | LOD | LOD | LOD |
Postban | 5 | 2.2 | LOD | LOD | |
14 | Preban | 390 | 500 | 0.069 | 0.0888 |
Postban | 9 | 20.0 | 0.022 | 0.0489 | |
15 | Preban | 18 | 14.3 | 0.104 | 0.0828 |
Postban | LOD | LOD | LOD | LOD | |
16 | Preban | 4 | 3.3 | LOD | LOD |
Postban | LOD | LOD | 0.017 | 0.0120 | |
17 | Preban | LOD | LOD | LOD | LOD |
Postban | LOD | LOD | LOD | LOD | |
18 | Preban | 6 | 5.1 | LOD | LOD |
Postban | LOD | LOD | LOD | LOD | |
19 | Preban | 3 | 5.5 | 0.050 | 0.0909 |
Postban | LOD | LOD | LOD | LOD | |
20 | Preban | 9 | 6.8 | 0.038 | 0.0288 |
Postban | LOD | LOD | LOD | LOD | |
21 | Preban | 5 | 6.9 | LOD | LOD |
Postban | 2 | 2.3 | LOD | LOD | |
22 | Preban | 7 | 5.3 | 0.092 | 0.0692 |
Postban | LOD | LOD | LOD | LOD | |
23 | Preban | 15 | 20.5 | LOD | LOD |
Postban | LOD | LOD | LOD | LOD | |
24 | Preban | 1,820 | 1,456 | 0.763 | 0.611 |
Postban | 651 | 455 | 0.509 | 0.356 |
*Unadjusted for creatinine.
†Adjusted for creatinine; total cotinine limit of detection (LOD), 1.0 ng per mg creatinine; total NNAL LOD, 0.0025 pmol per mg creatinine.
Nineteen of 24 workers (79%) showed at least a 50% reduction in total cotinine and 13 (54%) showed at least a 50% reduction in total NNAL. One subject had levels at the limit of detection for total cotinine before and after the ban; two subjects had levels that were at the limit of detection before the ban and slightly higher after the ban; and one subject had slightly higher levels after the ban when the value was adjusted for creatinine. For total NNAL, the respective numbers of subjects in these categories were 6, 2 and 1, respectively.
Table 3 shows the median percent decreases in total cotinine and total NNAL after the ban, geometric means for the before the ban/after the ban ratios of total NNAL and total cotinine, and the median differences in these biomarkers before and after the ban. Significant reductions were seen for all measures (P ≤ 0.001). Levels of total NNAL (pmol/mg creatine) were significantly correlated with number of hours worked in the smoking section (r = 0.43; P < 0.05), but total cotinine (ng/mg creatinine) was not (r = 0.20; P > 0.30).
Change in total cotinine and total NNAL from before to after the smoking ban (n = 24)
Biomarker . | Median percent decrease after the ban . | Geometric mean of before/after (95% CI) . | Median difference (before minus after) . | P (before minus after) . |
---|---|---|---|---|
Total cotinine ng/mL* | 83.3% | 12.3 (5.7-26.6) | 11.0 | <0.001 |
Total cotinine ng/mg creatinine† | 78.6% | 9.3 (5.1-16.9) | 6.9 | <0.001 |
Total NNAL pmol/mL* | 76.6% | 21.4 (6.2-73.7) | 0.039 | <0.001 |
Total NNAL pmol/mg creatinine† | 56.5% | 19.8 (5.4-72.8) | 0.018 | 0.001 |
Biomarker . | Median percent decrease after the ban . | Geometric mean of before/after (95% CI) . | Median difference (before minus after) . | P (before minus after) . |
---|---|---|---|---|
Total cotinine ng/mL* | 83.3% | 12.3 (5.7-26.6) | 11.0 | <0.001 |
Total cotinine ng/mg creatinine† | 78.6% | 9.3 (5.1-16.9) | 6.9 | <0.001 |
Total NNAL pmol/mL* | 76.6% | 21.4 (6.2-73.7) | 0.039 | <0.001 |
Total NNAL pmol/mg creatinine† | 56.5% | 19.8 (5.4-72.8) | 0.018 | 0.001 |
Abbreviation: CI, confidence interval.
*Unadjusted for creatinine.
†Adjusted for creatinine; total cotinine LOD, 1.0 ng per mg creatinine; total NNAL LOD, 0.0025 pmol per mg creatinine.
Discussion
The results of this study are consistent with others that we have conducted, examining SHS exposure levels in patrons and workers in restaurants and bars (29-31). In one of the prior studies, total NNAL and total cotinine were measured in workers at bars and restaurants that allowed smoking (30). Twenty-four hour urine collections were obtained during and after their work day and during a nonwork day. The results showed that for total cotinine the median difference was 7.5 ng/mL and the mean difference was 11.6 ng/mL on work days compared with nonwork days. The values were 0.025 and 0.033 pmol/mL, respectively, for total NNAL. In another study, total NNAL and cotinine levels of 32 nonsmoking workers in bars and restaurants that prohibited smoking were compared with 52 nonsmoking employees of bars and restaurants where smoking was allowed (31). The employees of restaurants and bars where smoking was permitted were significantly more likely to have detectable levels of urinary total NNAL as well as urinary total cotinine and to experience thrice greater increase in levels of total NNAL and 10 times greater increase in total cotinine levels compared with workers in similar venues that did not allow smoking.
It is notable that eight of the subjects in the current study did not have detectable levels of total NNAL before the ban. Five of these eight subjects were employees of two restaurants. The low levels of total NNAL may have been a function of the level of exposure on the day that they collected urine samples; perhaps they had higher exposure on other days. The 57% to 77% reductions in total NNAL levels is consistent with studies that have shown reductions in particulate matter or respirable suspended particles that range from 68% to 99%, with the majority of studies showing >80% reductions (10-17, 19, 32). The percent reduction in total NNAL exceeds the 30% coefficient of variation observed across repeated total NNAL measurements in smokers, according to our unpublished data, but no similar data are available for nonsmokers exposed to SHS.
Unlike total NNAL, the majority of subjects did have detectable levels of total cotinine in their urine before the ban. Prior studies using cotinine as an outcome measure showed a reduction in levels preban and postban that ranged from 43% to 95% with a mean reduction of ∼76% (4, 11-15, 20, 22-24, 33). These observations are in line with the ∼ 80% reduction observed in total cotinine in this study and these findings are consistent with the 83% and 98% reduction observed in air nicotine concentrations observed before and after bans (15, 20). Similar to total NNAL, the coefficient of variation observed across repeated total cotinine measurements in smokers is ∼30%, according to our unpublished data, but no data are available for nonsmokers exposed to SHS.
The levels of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone and nicotine exposure reported here are significantly less than found among smokers. However, in spite of these low exposure levels, SHS is believed to contribute to 3,000 lung cancer deaths and >35,000 coronary heart disease deaths per year in the United States (1) and can negatively affect the health outcomes of individuals who already have a disease (34).
With accumulating findings such as those observed in this study, there is increasingly less challenge to the concept that reducing tobacco smoke in hospitality venues will reduce employee exposure to tobacco toxicants and ultimately reduce health risk. Consistent with significant reductions in exposures, smoke-free bans have resulted in a rapid effect on reduction in hospital admissions for acute myocardial infarctions in the community (35-37) as well as decreased respiratory symptoms and increased pulmonary function in bartenders (13, 24, 38) or other hospitality workers (23) and improved systemic inflammatory markers (24). Not only do these laws provide health benefits to employees and patrons, smoke-free workplace bans provide benefits to other groups. Rates of smoking initiation after bans are reduced in adolescents (39). A review of 26 studies before and after smoking bans estimated that bans resulted in a reduction in the prevalence of smoking by 3.8%, reduction in the number of cigarettes per day by 3.1, and an estimated drop in U.S. consumption of 4.5% (40). In addition, smokers are more likely to make a quit attempt and be successful (41, 42). Studies also show minimal economic problems associated with bans (43).
A limitation of this study is that the subjects were self selected. They were recruited by local tobacco control leaders who support and in some cases work to advance comprehensive smoke-free workplace policies. It is possible that a participant may have altered his or her behavior to influence the study outcome. However, our results are consistent with other published studies on restaurant and bar workers showing decreased levels of cotinine and other tobacco related exposure biomarkers after smoking bans went into effect (11, 12, 20). Additional limitations included the lack of sensitivity in our analytic methods to adequately determine the concentrations of NNAL in all workers before the ban and only a single measurement point before and after the ban.
In summary, it is critical for states and communities to continue to support strict restrictions on smoking in workplaces to ensure that all employees, including those in the hospitality industry, are guaranteed a safe work environment, free of exposures to carcinogens and toxicants that enhance the risk of cancer, cardiovascular, and pulmonary disease.
Disclosure of Potential Conflicts of Interest
Dorothy Hatsukami is conducting a clinical trial supported by Nabi Biopharmaceuticals. The other authors disclosed no potential conflicts of interest.
Acknowledgments
Grant Support: ClearWay MinnesotaSM and NIH P50DA 013333.
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.